Dr Bernadette Montanari

Shifting Priorities or Perpetuating the Cycle: The Excluded Rural Women of the Green Moroccan Plan

Introduction

Worldwide, women play a major role in producing and securing food, managing natural resources, and earning an income either formally or informally in natural resource and agricultural activities (FAO 2011;Masaiganah 2012;[START_REF] Ogato | Gender Roles in Crop Production and Management Practices: A Case Study of Three Rural Communities in Ambo District, Ethiopia[END_REF][START_REF] Olumakaiye | Women's Empowerment for Household Food Security: The Place of Education[END_REF]. As such, even the first goal of the Millennium Development Goals called for the recognition of women (Rao 2012, 84-86). However, they have been largely undermined for their contribution in socio-economic development. Women produce between 60 to 80 percent of the world food crops; a representation of 43 percent of the overall agricultural labor force (Rao 2012, 84). In addition, besides their contribution for the provision of food security at the household level, they are often fully involved in agricultural activities that contribute to the communities in which they live. In Morocco, this accounts for 79 percent of the rural labor force, a rate which can exceed 90 percent in mountainous areas (Euromed 2006;IFAD 2014).

The country has made substantial progress in the domains of education, mortality, health and sanitation. However, certain aspects of the social development agenda remain insufficient; poverty is still a major issue in some parts of the country. Nineteen percent of the population still lives at the margin of the national poverty line ($1.25 as set up by the World Bank in 2010) and two thirds of these are in rural areas. Another 25 percent of the population lives under the poverty line, in both urban and rural environments. Two and a half million rural children are illiterate, particularly girls, and 83 percent of the total population in rural environments is still illiterate. Furthermore, 74 percent of girls aged below fifteen have left school to find work in agricultural activities with no contract or social status and three women out of four are not remunerated. In contrast, 63 percent of women in the urban area start working at the age of 20, and only five percent of women have unremunerated work [START_REF] Belarbi | Egalité économique entre hommes et femmes?[END_REF]. To address these issues, the government allocates 55 percent of the national budget for social programs.

Green Moroccan Plan

The government's latest attempt to address the issues of poverty, climate change, food security, natural resource conservation and the general challenge of rural women's employment and social integration is the Green Moroccan Plan-GMP (2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019)(2020). The GMP is expected to promote growth in the country over the next 10 to 15 years. It aims to end the current economic duality predominant in agriculture, a division between a modern agro-exporting model and subsistence farming of millions of rural families (Duporte 2014, 13). Its main objectives are to increase the share of agriculture in the Gross Domestic Product (GDP) from 6.35 to 9 billion Euros, to create 1.5 million additional jobs, to fight against poverty and to increase by two to three times the income for four million peasants, and to raise export figures from 0.72 to 4 Mds Dh (ADS 2014;GMP 2016).

Based on two 'pillars' of reforms, the first pillar seeks to accelerate development towards a modern and competitive export-oriented agriculture, relying on projects of high added value in agro-industries, and private investment. The Moroccan government anticipates accomplishing 962 projects by 2020 and to benefit 560,000 farmers with an investment of 75 billion dirhams (US $7 billion). Pillar II is rural development through sustainable natural resources, agriculture of the poor, women's employment towards gender equality and socio-economic development in the most-isolated parts of the country. It foresees the creation of 545 social projects transiting from traditional subsistence agriculture to a more intensive form of agricultural production to benefit 860,000 farmers [START_REF] Duporte | La mise en oeuvre d'une agriculture solidaire au Maroc: Entre impératif écologique et viabilité économique. L'exemple des projets de reconversion de la sole céréalière en arboriculture fruitière à destination des petits agriculteurs dans la province de Taza[END_REF]Laatar 2014) with an allocated budget of 20 billion Dirhams (approx. US $2 billion).

A series of actions and measures are specifically targeting women, seeking their participation in bodies and committees making decisions related to project activities, encouraging them to state specific goals towards their participation, capacity building and empowerment through income-generating activities, economic improvement via access to and control of productive assets and an increase of household wealth. The government's plan is to strengthen and ensure that women's decision-making powers are accounted for at the household and community level, that they are represented and participating in the decision-making organs of local bodies. It further seeks to alleviate the workload and to achieve a fair balance of the workload between women and men. Last but not least, the government wants to ensure that the arrangements of projects (composition of, ToR for hiring staff and implementing partners) reflect particular attention to gender equity and empowerment aspects. It stipulates that all efforts will be deployed to reach women with an adequate number of qualified staff to dispense awareness training and all the stages of implementation of a given project (Laatar 2014). To implement this, the government has deployed an important array of reforms within the Ministry of Agriculture and the Chambers of Agriculture and the creation of structures for social proximity services to implement the two pillars of the GMP [START_REF] Akesbi | Une nouvelle stratégie pour l'agriculture marocaine: Le 'Plan Maroc Vert[END_REF]). These include several local, regional and provincial structures responsible for the implementation of the agricultural policy programs and additional committees at the provincial, regional and local levels to reach the rural populations.

Results and Implications

Geographical Isolation

Several obstacles impede the participation of women in Pillar II initiatives of the GMP in the most isolated villages. The geographical distance and isolation stand as major obstacles for the local populations to be able to benefit from a full exposure of the initiatives of the GMP Pillar II. Because the rural villages are located away from the main axis and the infrastructures are poor, access is difficult. While the local people are used to commutes with donkeys, or carts hauled by mules, visiting the villages is unpractical unless travelling with a vehicle off the ground (type 4x4), a standard car being too low for the broken dust tracks which branch off from the main national road. Therefore, the creation of cooperatives is more likely to occur in locations that are close to the main geographical infrastructures and the urban centers.

Lack of Consultation with the Women

The government has set up an intricate network of sub-sections, local committees and rural animation teams to reach the local populations. Although the committees at the commune level (elected officials of municipalities, presidents of communes, associative network and decentralized technical services) are the closest geographically, the information about the initiatives is not delivered at the community level. The rural animation teams have specific tasks to engage the populations in participatory processes. They have a major role to play in consulting, informing, triggering initiatives at the village level, enrolling the local populations and encouraging the validation of projects. However, no actions or initiatives are undertaken in most villages. Unlike the government's prescription to encourage autonomy, decision making and participation of women, there is a lack of consultation and a participatory process that would otherwise permit establishing a close collaboration with the women and with the local population. Taking into account the complexity of social factors encountered at the village level (illiteracy, poverty, community social norms, frequent community conflicts, mistrust), the creation of cooperatives and income generating activities implies persistent and recurring visits to the villages supported by advisory services and to establish a trust relationship with the women and the local population.

Unrealistic Expectations

The rural women are eager to participate in and work on projects to improve their livelihood and provide better education for their children. However, given the complexity of the administrative and financial processes, the creation of cooperatives is problematic. The ability to benefit from financial support for the initiatives and opportunities offered by the initiatives of the GMP Pillar II requires not only the ability to read and understand the information and the funding mechanisms, but also to be able to fill application forms and the associated administrative duties. Given that the women in the villages are illiterate, they do not have the educational capacity to proceed with the required administrative tasks.

In addition, it is expected that the women are able to financially contribute 30 percent of the overall cost of a project, or a 20 percent contribution (from a personal source, personal savings, acquaintance or family support) and a 10 percent of the total cost in cash for the creation of a cooperative (INDH 2015). To request this type of financial contribution from a poor population is unrealistic given that people subsist on a low economy and cannot access microcredit facilities that usually imply repaying high interest rates. Another unrealistic requirement for the creation of a cooperative is the gathering of likeminded people for an administrative bureau. This is a difficult task given that unresolved conflicts are common within villages; the people who manage to create a cooperative have some level of education and typically enroll family members to facilitate the creation.

Furthermore, beside the unrealistic requirements that are expected from people, one of the conditions to benefit from institutional funding is the proceeding of diagnostics to identify local resources and local needs. The women have in-depth knowledge of the local resources and especially the local needs; however, to expect them to proceed to diagnostics as required by the authorities is illusory. Given women's tasks to maintain daily subsistence (women's average schedule is from 6am to 10pm), their schedule does not allow time for anything else and making diagnoses is the last preoccupation on people's minds.

Conclusion

The Pillar II initiatives hold the potential to benefit all within the rural world. However, it requires a new approach that is culturally sensitive and that encompasses women's aspirations and needs, integrating local inherent factors, socio-economic conditions and community dynamics. This requires a shift in priorities: first, re-designing policies to engage women in an entrepreneurial "mind set" and increasing confidence for the integration of markets; second, employing experienced technicians who dedicate time, energy at the local level and who bring technical support to the initiatives; third, enforcing of accountability to higher level of authorities for technicians working at the ground level.


Verónica Muñoz Ramírez

Virgilio Kmetzsch

Florence Forbes

Michel Dojat

Deep learning models to study the early stages of Parkinson's disease

Keywords: Brain, Anomaly detection, Autoencoder, Diffusion Imaging, MRI

Current physio-pathological data suggest that Parkinson's Disease (PD) symptoms are related to important alterations in subcortical brain structures. However, structural changes in these small regions remain difficult to detect for neuroradiologists, in particular, at the early stages of the disease (de novo PD patients). The absence of a reliable ground truth at the voxel level prevents the application of traditional supervised deep learning techniques. In this work, we consider instead an anomaly detection approach and show that autoencoders (AE) could provide an efficient anomaly scoring to discriminate de novo PD patients using quantitative Magnetic Resonance Imaging (MRI) data.

INTRODUCTION

Today, there is a pressing need for objective and reliable biomarkers that allow the detection of Parkinson's Disease (PD) from its early stages. MRI has played a vital role in the characterization of multiple neurological diseases like Multiple Sclerosis and brain cancer [START_REF] Tofts | Quantitative MRI of the brain[END_REF]. However, structural MR images appear to be insufficient to detect the subtle changes caused by PD, especially in the sub-cortical structures of the brain [START_REF] Ramirez | No structural differences are revealed by vbm in de novo parkinsonian patients[END_REF]. This motivates the study of PD through quantitative MRI techniques such as DTI (Diffusion Tensor Imaging) that measures the displacement of water molecules in the brain. Indeed, DTI has been useful in the study of Alzheimer's disease [START_REF] Tofts | Quantitative MRI of the brain[END_REF], making it very attractive for the study of PD.

In this work, we propose to implement an anomaly detection framework to uncover alterations in the diffusion MR images of newly diagnosed (i.e. de novo) patients.

While there exists numerous techniques for anomaly detection [START_REF] Pimentel | Review: A review of novelty detection[END_REF], deep learning models have achieved remarkable results in recent brain lesion classification challenges such as BRATS, BrainLes and ISLES at MICCAI conferences (see for instance [START_REF]MICCAI 2018 Proceedings[END_REF]). Nonetheless, these deep learning approaches for anomaly detection are often supervised, meaning that the networks are trained with representatives of both healthy and diseased voxels so as to learn their characteristics. Seeing that the only information available for PD MR scans is an indication of the global presence or absence of the disease, we designed a semi-supervised framework employing three different types of fully convolutional auto-encoders.

More specifically, we trained the auto-encoders to reconstruct healthy diffusion MR scans with a healthy training dataset. Since the network is learned only from healthy subjects, there is no guarantee that it provides good reconstructions outside this population. We therefore compared the scan reconstruction errors of a healthy test data set with those of a pathological data set to identify unusual patterns in the sub-cortical structures of de novo PD patients.

We follow the work of [START_REF] Baur | Deep autoencoding models for unsupervised anomaly segmentation in brain mr images[END_REF], which demonstrated the advantages of employing full MR slices as input for the network architectures instead of down sampling and patch division that result in important loss of spatial information.

INPUT DATA

We pooled our data from the PPMI (Parkinson Progression Markers Initiative) database. The PPMI is a longitudinal study that follows de novo PD patients of 35 centers for five years. The database is openly available for researchers and contains, among other clinical test results, structural and diffusion MR images. To eliminate any additional sources of bias, we only selected scans acquired with the same acquisition parameters, notably magnetic field and scanner manufacturer. As a result, we pooled 129 de novo patients (age: 62 ± 9; sex: 48 F, 80 M) and 57 healthy controls (age: 61 ± 10; sex: 23 F, 34 M).

From this data, two features were extracted: mean diffusivity (MD), accounting for the overall water displacement, and fractional anisotropy (FA), an indication of diffusion orientation. Values of FA and MD were normalized into the range [0, 1]. Each volume was composed of 116 × 116 × 72 voxels. Forty coronal slices (116 × 72) were extracted from the center of the brain encompassing the sub-cortical structures under study.

To avoid data leakage, the control dataset was divided into a training dataset (42 MR volumes) and a testing dataset (15 MR volumes). Special care was taken to maintain similar age and sex profiles in both datasets. In order to choose the best network architecture and tune the corresponding hyperparameters, all models were trained and assessed with 7-fold cross-validation, with 36 MR volumes used for training and 6 MR volumes for validation in each fold. Once the final models were defined, they were retrained with the full control training set (1680 slices) and evaluated with the PD dataset (5160 slices) and the healthy control test set (600 slices).

ARCHITECTURE DESIGN

Three autoencoder-based models were developed and evaluated: a spatial autoencoder (sAE), a spatial variational autoencoder (sVAE) and a dense variational autoencoder (dVAE).

As seen in Figure 1-A, all autoencoders come with two parts, an encoder f φ and a decoder g θ . The encoder maps the input images x to a lower dimensional latent representation z, then the decoder maps the latent vector z to the reconstructed output images x ∈ R H×W ×C :

z = f φ (x) x = g θ (z) (1)
We extended the work of [START_REF] Baur | Deep autoencoding models for unsupervised anomaly segmentation in brain mr images[END_REF] by using multiple quantitative MRI measures simultaneously as input. Thus, every input can be expressed as x ∈ R H×W ×C , where H is the height, W the width and C the number of channels (FA and MD).

Depending on the network architecture, the latent code may be a simple vector (z ∈ R d ) or a third-order tensor (z ∈ R h×w×c ). The former is referred as a dense bottleneck and the latter as a spatial bottleneck.

All models were implemented using Python 3.6.8, Py-Torch 1.0.1, CUDA 10.0.130 and trained on a NVIDIA GeForce RTX 2080 Ti GPU with batches of 32 images. After each convolutional layer, batch normalization [START_REF] Ioffe | Batch normalization: Accelerating deep network training by reducing internal covariate shift[END_REF] was applied for its regularization properties. The nonlinear activation function in each layer was the rectified linear unit (ReLU), except for the last layer where a sigmoid was employed in order to have output pixels normalized between [0, 1]. The loss functions were optimized using Adam [START_REF] Kingma | Adam: A Method for Stochastic Optimization[END_REF], a popular optimization algorithm for training deep neural networks.

Spatial autoencoder (sAE)

The spatial autoencoder model is fully convolutional, 4 convolutional layers go from input to bottleneck and 4 transposed convolutional layers from bottleneck to output. As depicted in Figure 1-B, the output of the encoder network is directly the latent vector z and loss function is simply the reconstruction error:

L = x -x 1 (2)
This model was trained for 160 epochs, with a learning rate of 10 -3 . 5 × 5 kernels were convolved using padding of 1 pixel and a stride of (2, 2), and there were no pooling layers.

Spatial variational autoencoder (sVAE)

Our spatial variational autoencoder model is shown in Figure 1-C. Similar to sAE, the model is fully convolutional, however, the encoder generated the parameters of the approximate posterior of the latent variable given the input, constrained to follow a multivariate normal distribution. A sampling operation was needed to obtain an actual value for z.

Training lasted for 200 epochs using a learning rate of 0.3 × 10 -3 . A 5 × 5 kernel was chosen as filter, along with a padding of 1 and stride of [START_REF] Ramirez | No structural differences are revealed by vbm in de novo parkinsonian patients[END_REF][START_REF] Ramirez | No structural differences are revealed by vbm in de novo parkinsonian patients[END_REF]. No pooling layers were used. The loss function was computed as follows:

L = λ x -x 1 + (1 -λ) -1 2 J j=1 (1 + log((σ j ) 2 ) -(µ j ) 2 -(σ j ) 2 )
(3) where µ and σ denote the mean and the variance of the approximate posterior, J is the number of dimensions of the latent space and λ controls the proportions between the two terms. The first term is the reconstruction error and the second term is the Kullback-Leibler (KL) divergence between the approximate posterior and the prior of the latent variable, for the Gaussian case [START_REF] Kingma | Auto-encoding variational bayes[END_REF]. To favor good reconstructions over a Gaussian-like distribution of the latent variables, we put more weight (90%) in the reconstruction term and less weight (10%) in the KL divergence term.

Dense variational autoencoder (dVAE)

The main difference of the dense variational autoencoder when compared to the sVAE is its dense bottleneck. Encoder and decoder also have fully connected layers in addition to the convolutional layers, as shown in Figure 1-D.

For regularization purposes, the dropout [START_REF] Srivastava | Dropout: A simple way to prevent neural networks from overfitting[END_REF] technique was used to turn off 30% of the units in fully-connected layers during training. This model was trained for 100 epochs with a learning rate of 0.3 × 10 -3 . There were no pooling layers. Kernels for all convolutional layers were 5 × 5, and convolutions were performed with a padding of 1 and stride of (2, 2). The dVAE shared the same loss function as the sVAE and we kept the same 90/10 proportion between the reconstruction term and the KL divergence term.

PD ANOMALY DETECTION

A reference model is learned from healthy MR images using the autoencoder-based models presented in Section 3. During the training process the model parameters are tuned so as to minimize a loss function that favors good reconstructions. Since the network was solely trained on healthy subjects, we hypothesized that the MR scans of the PD population would have greater reconstruction errors in some regions. The idea is therefore to use the reconstruction error as an anomaly score.

The voxel-wise reconstruction errors in one image can be computed as |x i -xi |. Seeing that our decoders output two images ( FA, MD), we defined the joint reconstruction error of every voxel as:

(FA i -F A i ) 2 + (MD i -MD i ) 2 (4)
We identified four sources of reconstruction errors : 1) noise in the input data, 2) loss of information due to dimension reduction in the latent space, 3) variability of healthy controls not captured by the model and 4) finally real anomalies caused by PD. Because we were only interested in the latter, the best way to evaluate and compare the models is by measuring their ability to discriminate between controls and PD patients, based on the intensity and localization of the reconstruction errors.

To help evaluate the localization of anomalies, we employed the MNI PD25 atlas [START_REF] Xiao | Multi-contrast unbiased MRI atlas of a Parkinson's disease population[END_REF], specifically designed for PD patient exploration. It contains 8 regions: substantia nigra (SN), red nucleus (RN), subthalamic nucleus (STN), globus pallidus interna and externa (GPi, GPe), thalamus, putamen and caudate nucleus. In addition, we considered the superior colliculus (SC) and the inferior colliculus (IC), where we recently found functional deficits [START_REF] Bellot | First steps of visual processing are altered in de novo Parkinson's disease patients[END_REF].

Regarding comparisons of reconstruction error intensities, we investigated extreme reconstruction errors with the idea that PD patients should exhibit very abnormal voxels in larger quantities. Accordingly, we considered an extreme quantile (eg. the 95% quantile) of the distribution of errors in the control population as possible threshold value to decide whether or not a given voxel was considered as abnormal. For each control or PD subject, we counted the number of extreme abnormalities detected in every structure. The idea being to classify a subject as PD or healthy when this number was above a certain value. The critical choice of this value was investigated using a ROC curve of sensitivity and specificity to account for class imbalance. We chose the AUC as our principal indicator of discrimination performance.

RESULTS: RECONSTRUCTION ASSESSMENT

We used the reconstruction errors of every structure in every subject to classify patients from controls as explained in Section 4. Amongst the three models tested, we noticed that dVAE detected the biggest reconstruction errors, as an example the mean reconstruction error of the control's subcortical structures is of 0.075, 0.086 and 0.106 for the sAE, sVAE and dVAE respectively. However, the absence of ground truth at a voxel level prevented us from determining which model was the most accurate relative to PD abnormalities.

The number of voxels over the 95% quantile abnormality threshold were generally superior in a patient than in a healthy control. We employed the ROC curve as a performance measurement for our classification problem, we were able to measure the AUC to have an indication on the ability of the model to distinguish between patients and healthy controls. The structures with the highest AUC were the Substantia Nigra, the Red Nucleus, the Thalamus and the combination of all subcortical structures as seen in Table 1. This was in accordance with the literature. The total white matter present in the reconstructed slices obtained even better results with an AUC of 0.83, 0.80 and 0.74 for the sAE, sVAE and dVAE respectively. When assessing the reconstructions of FA and MD separately, FA obtained the highest ROC AUC for the caudates and the putamen, whereas for the white matter and the red nucleus MD was better. The substantia nigra and the ensemble of all subcortical structures benefited from the joint measures of FA and MD.

DISCUSSION AND CONCLUSION

Although preliminary, these results offer compelling evidence that deep learning-based models are useful to identify subtle anomalies in de novo PD patients, even when trained with a moderate number of images and only two parametric maps as input. The good discriminative performances of the sub-cortical structures are in accordance to our physiopathological knowledge of PD. The dopaminergic neuron deficit in Substantia Nigra is known as critical in the development of PD. What is more, the absence of motor symptoms in the pre-clinical stages of PD may be the result of compensation mechanisms involving the structures in the motor coordination pathways of the brain such as the Thalamus and the Red Nucleus [START_REF] Philippens | Involvement of the Red Nucleus in the Compensation of Parkinsonism may Explain why Primates can develop Stable Parkinson 's Disease[END_REF].

We have shown that no structural changes, including in the White Matter (WM), can be robustly observed from T1weighted images to automatically distinguish between controls and de novo PD patients [START_REF] Ramirez | No structural differences are revealed by vbm in de novo parkinsonian patients[END_REF]. To explain the good performances of autoencoders based on white matter voxels, we may hypothesize that 1) diffusion parameters (FA an MD) are more informative than grey levels from T1-weighted imaging, or that 2) they dispose of more voxels, compared to subcortical structures, to build a model that captures the variability of healthy controls.

Undeniably, experiments on a larger cohort are necessary to confirm our results. The control group available for our experiments contained only 57 MRI volumes, with gender and age imbalance. Although we were able to discriminate between healthy controls and individuals affected by PD with good performances, we cannot rule out that other possible causes of variability in brain properties, such as age and gender, and other hidden parameters, might have influenced our classification performance.

Similar anomaly detection frameworks could be of interest for studying other neurological disorders where small lesions are suspected and difficult to localize for a human observer. In future work, it could be beneficial to include other quantitative MR measures, such as perfusion and relaxation times, to encode a more complete picture of the pathophysiology of the disease.

Fig. 1 .

 1 Fig. 1. A) The general architecture of the implemented autoencoders with an unspecified bottleneck; B) sAE spatial bottleneck; C) sVAE spatial bottleneck and D) fourth convolutional layer of the dVAE along with its fully connected layers and dense bottleneck. µ and σ describe the approximate posterior of the latent variable, z is obtained by a sampling operation.

Table 1 .

 1 AUC values obtained in different structures when counting the number of voxels above the 95% percentile to discriminate between patients and controls

		sAE sVAE dVAE
	Red Nucleus	0.75	0.76	0.65
	Substantia Nigra	0.74	0.73	0.72
	Sub-thalamic Nucleus	0.59	0.64	0.53
	Caudates	0.70	0.64	0.61
	Putamen	0.72	0.74	0.63
	Globus Pallidus ext.	0.65	0.69	0.69
	Globus Pallidus int.	0.69	0.69	0.71
	Thalamus	0.71	0.73	0.72
	Superior Colliculus	0.51	0.59	0.54
	Inferior Colliculus	0.54	0.56	0.49
	All subcortical structures 0.76	0.77	0.73
	White Matter	0.83	0.80	0.74


Jordan M Rabus

Shanshan Guan

Lauren M Schultz

Maha T Abutokaikah

Philippe Maître

Benjamin J Bythell

Protonated α-GalNAc-Glycopeptide Dissociation Chemistry

We recently provided mass spectrometric, H/D labeling, and computational evidence of pyranose to furanose N-Acetylated ion isomerization reactions occurring prior to glycosidic bond cleavage in both O-and N-linked glycosylated amino acid model systems (Phys. Chem. Chem. Phys., 2021, 23, 23256-23266). These reactions occurred irrespective of glycosidic linkage stereochemistry (α/β) and N-Acetylated hexose structure (GlcNAc/GalNAc). In the present article we test the generality of the preceding findings by examining Threonyl α-GalNAc glycosylated peptides. We utilize computational chemistry to compare the various dissociation and isomerization pathways accessible with collisional activation. We then interrogate the structure(s) of the resulting charged glycan and peptide fragments with infrared "action" spectroscopy. Isomerization of the original pyranose, protonated glycopeptide, [AT(GalNAc)A+H] + , is predicted to be facile compared to direct dissociation, as is glycosidic bond cleavage of the newly formed furanose form. i.e., furanose oxazolinium ion structures are predicted to predominate. IR action spectra for the m/z 204, C8H14N1O5 + , glycan fragment population support this prediction. The IR action spectra of the complementary m/z 262, peptide fragment are assigned as a mixture of the lowest energy structures of [ATA+H] + consistent with the literature. If general, the change to a furanose m/z 204 product ion structure fundamentally alters the ion population available for MS 3 dissociation and glycopeptide sequence identification.

Peptide and protein glycosylation is widespread in biological systems. Glycosylation is involved in the pathogenesis of diseases, with variations of glycan at each particular site thought to provide further biomarkers of disease [START_REF] Bones | Ultra Performance Liquid Chromatographic Profiling of Serum N-Glycans for Fast and Efficient Identification of Cancer Associated Alterations in Glycosylation[END_REF][START_REF] Saldova | Ovarian Cancer Is Associated with Changes in Glycosylation in Both Acute-Phase Proteins and IgG[END_REF][START_REF] Miyoshi | Fucosylated Haptoglobin Is a Novel Marker for Pancreatic Cancer: Detailed Analyses of Oligosaccharide Structures[END_REF][START_REF] Okuyama | Fucosylated Haptoglobin Is a Novel Marker for Pancreatic Cancer: A Detailed Analysis of the Oligosaccharide Structure and a Possible Mechanism for Fucosylation[END_REF][START_REF] Dube | Glycans in Cancer and Inflammation -Potential for Therapeutics and Diagnostics[END_REF][START_REF] Rachagani | Current Status of Mucins in the Diagnosis and Therapy of Cancer[END_REF][START_REF] Cazet | Consequences of the Expression of Sialylated Antigens in Breast Cancer[END_REF][START_REF] Tian | Characterization of Disease-Associated N -Linked Glycoproteins[END_REF][START_REF] Chernykh | Towards Structure-Focused Glycoproteomics[END_REF] and immune response. [START_REF] Gornik | Changes of Serum Glycans during Sepsis and Acute Pancreatitis[END_REF][START_REF] Sperandio | Glycosylation in Immune Cell Trafficking[END_REF] The spike, envelope, and membrane structural proteins of SARS-CoV-2 and other coronaviruses are glycosylated, affecting their attachment to host, entry, replication, and infection. [START_REF] Shajahan | Glycosylation of SARS-CoV-2: Structural and Functional Insights[END_REF][START_REF] Arnaud | Adding the Missing Sugars to Coronavirus Protein Structures[END_REF] These also affect the viruses ability to mask the proteins from the body's immune system. [START_REF] Arnaud | Adding the Missing Sugars to Coronavirus Protein Structures[END_REF] Consequently accurate profiling of sitespecific glycan modifications has great importance. [START_REF] Darula | Analysis of Mammalian O-Glycopeptides -We Have Made a Good Start, but There Is a Long Way to Go[END_REF][START_REF] You | Recent Advances in Methods for the Analysis of Protein O-Glycosylation at Proteome Level[END_REF][START_REF] Ohtsubo | Glycosylation in Cellular Mechanisms of Health and Disease[END_REF][START_REF] Reily | Glycosylation in Health and Disease[END_REF] Despite numerous studies/approaches involving these analytes' there are still many challenges to glycoprotein sequencing. [START_REF] Chernykh | Towards Structure-Focused Glycoproteomics[END_REF][START_REF] Darula | Analysis of Mammalian O-Glycopeptides -We Have Made a Good Start, but There Is a Long Way to Go[END_REF] Current large-scale sequencing and identification of glycopeptides is contingent on algorithms almost wholly reliant on m/z differences between the fragment ion series. [START_REF] Peltoniemi | De Novo Glycan Structure Search with the CID MS/MS Spectra of Native N-Glycopeptides[END_REF][START_REF] Ozohanics | A New Software Tool to Elucidate Glycopeptide Composition[END_REF][START_REF] Goldberg | Automated N-Glycopeptide Identification Using a Combination of Single-and Tandem-MS[END_REF] Thus our ability to differentiate a hexose (Hex) from a N-Acetylated-hexose (HexNAc) residue or fragment, far outstrips our ability to determine which Hex or HexNAc was present. [START_REF] Chernykh | Towards Structure-Focused Glycoproteomics[END_REF][START_REF] Darula | Analysis of Mammalian O-Glycopeptides -We Have Made a Good Start, but There Is a Long Way to Go[END_REF] A greater understanding of the dissociation chemistry of these analytes is one way to improve the accuracy of structural assignments and subsequent confidence in claims based on these assignments. [START_REF] Chernykh | Towards Structure-Focused Glycoproteomics[END_REF][START_REF] Bythell | Cationized Carbohydrate Gas-Phase Fragmentation Chemistry[END_REF][START_REF] Guan | Evidence of Gas-Phase Pyranose-to-Furanose Isomerization in Protonated Peptidoglycans[END_REF] We recently investigated the dissociation chemistry of single-residue glycopeptide model systems for the core structures of N-linked glycosylation, mucin-type glycosylation, and O-GlcNAcylation. [START_REF] Guan | Evidence of Gas-Phase Pyranose-to-Furanose Isomerization in Protonated Peptidoglycans[END_REF] O-linked glycosylation is more varied than N-linked glycosylation due to the lack of either core glycan structures and the lack of consensus peptide sequences to ease identification of potential sites of glycosylation. [START_REF] Zhu | Carbohydrates on Proteins: Site-Specific Glycosylation Analysis by Mass Spectrometry[END_REF] However, O-linked glycosylation to an alpha N-Acetyl galactose, α-GalNAc [START_REF] Reily | Glycosylation in Health and Disease[END_REF][START_REF] Jensen | Mucin-Type O-Glycosylation -Putting the Pieces Together[END_REF][START_REF] Alley | Structural Glycomic Analyses at High Sensitivity: A Decade of Progress[END_REF] , residue is the most common residue and linkage type combination in humans and is also the subject of the present manuscript. Dissociation of these analytes produces GalNAc reporter ions at m/z 204 (Scheme 1). 23 Recently we provided mass spectral, isotopic (H/D) labelling, and computational evidence indicating that the dissociation chemistry of glycosylated amino acid model systems was more complex than had previously been believed. [START_REF] Guan | Evidence of Gas-Phase Pyranose-to-Furanose Isomerization in Protonated Peptidoglycans[END_REF] Earlier labelling and tandem mass spectrometric work had proposed mechanisms for these dissociation processes. [START_REF] Yu | Distinctive MS/MS Fragmentation Pathways of Glycopeptide-Generated Oxonium Ions Provide Evidence of the Glycan Structure[END_REF] In contrast, further, extensive [START_REF] Arnaud | Adding the Missing Sugars to Coronavirus Protein Structures[END_REF] C and [START_REF] You | Recent Advances in Methods for the Analysis of Protein O-Glycosylation at Proteome Level[END_REF] N labelling and ion-mobility data from Mookherjee et al. [START_REF] Mookherjee | Dissection of Fragmentation Pathways in Protonated N -Acetylhexosamines[END_REF] on bare N-Acetylated hexose model systems was not consis-tent with these early mechanistic proposals. [START_REF] Yu | Distinctive MS/MS Fragmentation Pathways of Glycopeptide-Generated Oxonium Ions Provide Evidence of the Glycan Structure[END_REF] i.e., HexNAc ions not attached to a peptide/amino acid. Our findings [START_REF] Guan | Evidence of Gas-Phase Pyranose-to-Furanose Isomerization in Protonated Peptidoglycans[END_REF] were more consistent with the Mookherjee et al.. [START_REF] Mookherjee | Dissection of Fragmentation Pathways in Protonated N -Acetylhexosamines[END_REF] We found evidence for pyranose to furanose isomerization prior to glycosidic bond cleavage. i.e., that furanose oxazolinium B1 ions are the predominant m/z 204 ion structure within the gas-phase populations (Scheme 1b). The newly released carbons 5 and 6 in the furanose structures are then available for secondary fragmentation to form the m/z 126 peak (loss of C2H4O2 and H2O) utilized to differentiate HexNAc-linked peptides based on MS 3 abundances. [START_REF] Guan | Evidence of Gas-Phase Pyranose-to-Furanose Isomerization in Protonated Peptidoglycans[END_REF][START_REF] Halim | Assignment of Saccharide Identities through Analysis of Oxonium Ion Fragmentation Profiles in LC-MS/MS of Glycopeptides[END_REF][START_REF] Yu | Distinctive MS/MS Fragmentation Pathways of Glycopeptide-Generated Oxonium Ions Provide Evidence of the Glycan Structure[END_REF][START_REF] Ashwood | Discrimination of Isomers of Released N-and O-Glycans Using Diagnostic Product Ions in Negative Ion PGC-LC-ESI-MS/MS[END_REF] METHODS SECTION Chemicals. HPLC grade Acetonitrile, HPLC grade water, and the formic acid were purchased from Sigma Aldrich (St. Louis, MO). Glycopeptides were custom synthesized by Karebay Biochemical, South Brunswick Township, New Jersey. All samples were used as received.

Tandem Mass Spectrometry. An electrospray ionization (ESI) Bruker MaXis plus quadrupole time-of-flight mass spectrometer (Bruker, Billerica, MA) was utilized for the initial MS and MS/MS experiments. Nitrogen was used as both nebulizing and drying gas in the ESI source. MS/MS spectra were obtained by quadrupole isolation of the precursor ion (E.g., [AT(GalNAc)A+H] + , m/z 465.1±4) followed by collision-induced-dissociation (CID) with nitrogen in the hexapole collision cell. Product ion dispersion was achieved by the time-of-flight mass analyzer. Data were collected as a function of collision energy (averages of 120 spectra presented). Ionization was by electrospray with the samples infused into the instrument in ~1 µM acetonitrile/water/formic acid (50/50/0.1) solutions at a flow rate of 3 µl min -1 .

IRMPD Spectroscopy. Spectra were collected at the Centre Laser Infrarouge d'Orsay [START_REF] Prazeres | Two-Colour Operation of a Free-Electron Laser and Applications in the Mid-Infrared[END_REF][START_REF] Lemaire | Gas Phase Infrared Spectroscopy of Selectively Prepared Ions[END_REF] in the X-H (X=N, O) stretching region (3200-3700 cm -1 ) provided by an optical parametric oscillator/amplifier (OPO/OPA from LaserVision) laser system [START_REF] Bakker | Gas-Phase Structure of a π-Allyl-Palladium Complex: Efficient Infrared Spectroscopy in a 7 T Fourier Transform Mass Spectrometer[END_REF][START_REF] Bakker | Tautomerism of Uracil Probed via Infrared Spectroscopy of Singly Hydrated Protonated Uracil[END_REF] light source. An Innolas Spitlight 600 non-seeded Nd:YAG (1064 nm, 550 mJ/pulse, bandwidth ~1 cm -1 ) laser running at 25 Hz and delivering pulses of 4-6 ns duration pumps this system. Typical output energy of the OPO/OPA was 12-13 mJ/pulse at 3600 cm -1 with a 3-4 cm -1 (FWHM) bandwidth.

Experimental spectroscopic work was carried out in a Bruker Apex IV Qe, a 7 Tesla Fourier transform-ion cyclotron resonance (FT-ICR) tandem mass spectrometer (Bruker, Bremen, Germany) [START_REF] Bakker | Gas-Phase Structure of a π-Allyl-Palladium Complex: Efficient Infrared Spectroscopy in a 7 T Fourier Transform Mass Spectrometer[END_REF] . Precursor ions were pulseextracted into the ICR cell where they were irradiated with IR light. With the OPO/OPA tuned on a vibrational transition of the mass-selected ion a significant boost in signalto-noise is achieved by irradiating the ions for a few ms with a CO2 laser pulse [10 Watt continuous wave (CW), BFi OPTiLAS, France] following each OPO/OPA pulse with a delay of ~1 μs. The total irradiation period was 1 s. This combination has been used previously. [START_REF] Yeh | Vibrational Spectroscopy of the Hydrated Hydronium Cluster Ions H3O+⋅(H2O)n (N=1, 2, 3)[END_REF][35][36][START_REF] Peiris | Infrared Multiple Photon Dissociation Spectra of Gaseous Ions[END_REF][START_REF] Lagutschenkov | Structure and Infrared Spectrum of the Ag+-Phenol Ionic Complex †[END_REF] The abundances of the precursors and their corresponding photo fragments were recorded at each IR wavenumber, which was scanned stepwise. IR action spectra were derived by plotting the IRMPD efficiency against the photon energy. A Savitzky-Galoy [START_REF] Savitzky | Smoothing and Differentiation of Data by Simplified Least Squares Procedures[END_REF] filter, with a rolling window length of 5 and a quadratic polynomial fit was used to smooth the raw datapoints.

IR action spectra were collected for the m/z 204.087 (C8H14N1O5 + ), produced from [AT(GalNAc)A+H] + , [PT(GalNAc)P+H] + , and [RVT(GalNAc)AG+2H] 2+ . i.e., the glycan fragment. The IR action spectrum of the m/z 262.143 [ATA+H] + , [AT(GalNAc)A+H-C8H14N1O5] + peptide fragment was also collected. These ions were formed by low-energy collisional activation and thermalization with Ar (∼10 -3 mbar) in the linear hexapole. For the m/z 204.087 ions the IRMPD fragments followed were m/z 186.076, 168.066, 144.066, and 126.055. For [ATA+H] + , the fragments followed were m/z 244.129 and 173.092.

Theoretical Methods. Similar to prior systems [START_REF] Guan | Evidence of Gas-Phase Pyranose-to-Furanose Isomerization in Protonated Peptidoglycans[END_REF][START_REF] Abutokaikah | Fragmentation Pathways of Lithiated Hexose Monosaccharides[END_REF][START_REF] Bythell | Sequence Ion Structures and Dissociation Chemistry of Deprotonated Sucrose Anions[END_REF][START_REF] Rabus | Sodium-Cationized Carbohydrate Gas-Phase Fragmentation Chemistry: Influence of Glycosidic Linkage Position[END_REF][START_REF] Rabus | Deprotonated Carbohydrate Anion Fragmentation Chemistry: Structural Evidence from Tandem Mass Spectrometry, Infra-Red Spectroscopy, and Theory[END_REF][START_REF] Rabus | Unravelling the Structures of Sodiated β-Cyclodextrin and Its Frag-ments[END_REF] we performed quantum chemical calculations to model the potential energy surfaces of [AT(GalNAc)A+H] + , [ATA+H] + , [GalNAc-H2O+H] + , ATA, and (GalNAc-H2O). Initial candidate structures were systematically generated via the tool Fafoom [START_REF] Supady | adrianasupady/fafoom[END_REF][START_REF] Marianski | Assessing the Accuracy of Across-the-Scale Methods for Predicting Carbohydrate Conformational Energies for the Examples of Glucose and α-Maltose[END_REF][START_REF] Supady | First-Principles Molecular Structure Search with a Genetic Algorithm[END_REF][48] , a genetic algorithm with the generated structures initially optimized using the MMFF94 Force Field 49- 53 . Geometry optimizations of the resulting candidate conformations were performed with the Gaussian 09 software package 54 at four increasing levels of theory: HF/3-21g, B3LYP/6-31G(d), B3LYP/6-31+G(d,p), [START_REF] Lee | Development of the Colle-Salvetti Correlation Energy Formula into a Functional of the Electron Density[END_REF][START_REF] Stephens | Ab Initio Calculation of Vibrational Absorption and Circular Dichroism Spectra Using Density Functional Force Fields[END_REF][START_REF] Becke | Density-functional Thermochemistry. III. The Role of Exact Exchange[END_REF] and M06-2X/6-31+G(d,p) [START_REF] Zhao | Exchange-Correlation Functional with Broad Accuracy for Metallic and Nonmetallic Compounds, Kinetics, and Noncovalent Interactions[END_REF][START_REF] Zhao | The M06 Suite of Density Functionals for Main Group Thermochemistry, Thermochemical Kinetics, Noncovalent Interactions, Excited States, and Transition Elements: Two New Functionals and Systematic Testing of Four M06-Class Functionals and 12 Other Functionals[END_REF] . Degenerate structures were removed after each level and the remaining structures were utilized as the starting points of the subsequent calculation set. Supplemental manual manipulation and adjustment of the lowest energy structures followed by re-optimizations were also undertaken to ensure that other important conformers had not been missed.

Calculations of reaction pathways including transition structures, product ions and neutrals were performed at the B3LYP/6-31G(d), B3LYP/6-31+G(d,p), and M06-2X/6-31+G(d,p) levels of theory. Multiple transition structures (TSs) were systematically generated and calculated from multiple precursor ion structures for each potential fragmentation pathway. All minima and TSs were tested by vibrational analysis (all real frequencies or 1 imaginary frequency, respectively). The potential energy surface generated combines the zero-point energy correction (ZPE) to the electronic energy (Eel,0K) for improved accuracy (ΔEel+ZPE,0K). The related, standard enthalpy (ΔH298K), Gibbs free energy (ΔG298K), and entropy (ΔS298K) corrections to 298 K were also determined. The reaction pathway through each TS was tested with intrinsic reaction coordinate calculations (GS2 keyword) with up to 10 steps in each direction. The terminating points of these calculations (one on product-side, one on reactant-side) were then optimized further to determine which minima were connected to each TS. Targeted single point calculations utilizing the B3LYP, M06-2X, and ωB97XD 54,60 models with 6-311+G(2d,2p) basis sets to assess the extent of energetic variability followed.

B3LYP/6-311+G(2d,p) vibrational frequencies from optimized structures at the same level of theory were utilized for comparisons with the experimental IRMPD spectra. A 20 cm -1 full width at half maximum Gaussian line shape and a scaling factor of 0.960 was utilized for the vibrational frequencies for comparison to the experimental spectra. Facile cleavage of the glycosidic bond to produce substantial peaks at m/z 204 is consistent with the literature. [START_REF] Bones | Ultra Performance Liquid Chromatographic Profiling of Serum N-Glycans for Fast and Efficient Identification of Cancer Associated Alterations in Glycosylation[END_REF][START_REF] Dube | Glycans in Cancer and Inflammation -Potential for Therapeutics and Diagnostics[END_REF][START_REF] Darula | Analysis of Mammalian O-Glycopeptides -We Have Made a Good Start, but There Is a Long Way to Go[END_REF][START_REF] Yu | Distinctive MS/MS Fragmentation Pathways of Glycopeptide-Generated Oxonium Ions Provide Evidence of the Glycan Structure[END_REF][START_REF] Ashwood | Discrimination of Isomers of Released N-and O-Glycans Using Diagnostic Product Ions in Negative Ion PGC-LC-ESI-MS/MS[END_REF][START_REF] Mariño | A Systematic Approach to Protein Glycosylation Analysis: A Path through the Maze[END_REF] At increased collision energies consecutive losses from these ions become increasingly prevalent (m/z 186, 138, 126). [AT(GalNAc)A+H] + Minima. The lowest energy conformer of [AT(GalNAc)A+H] + (Figure 2, Table S1) is predicted to have a highly folded structure [START_REF] Mookherjee | Thermodynamics and Reaction Mechanisms of Decomposition of the Simplest Protonated Tripeptide, Triglycine: A Guided Ion Beam and Computational Study[END_REF] offering excellent charge solvation through hydrogen bonding side-chain Nacetyl and C-terminal carbonyl oxygens to the protonated N-terminus. These beneficial interactions result in a skew hexose ring which in turn has an additional hydrogen bonding network between the hydroxyls. Other low energy structures (Figure S1, Table S1) are predicted to be a mix-ture of highly folded (II) and more extended, so entropically favorable conformations (III, IV). fragments are complementary resulting from cleavage of the glycosidic bond. Consistent with the wider understanding of peptide dissociation chemistry, the key difference is which fragment keeps the ionizing proton. [START_REF] Wysocki | Mobile and localized protons: a framework for understanding pep-tide dissociation[END_REF][START_REF] Tsaprailis | Influence of Secondary Structure on the Fragmentation of Protonated Peptides[END_REF][START_REF] Paizs | Fragmentation pathways of protonated peptides[END_REF] For the [AT(GalNAc)A+H] + ions, the lowest energy mechanism involves isomerization [START_REF] Guan | Evidence of Gas-Phase Pyranose-to-Furanose Isomerization in Protonated Peptidoglycans[END_REF][START_REF] Abutokaikah | Leaving Group Effects in a Series of Electrosprayed CcHhN1 Anthracene Derivatives[END_REF] prior to glycosidic bond dissociation (Scheme 2). This pathway begins with mobilization of the ionizing proton to the carbonyl oxygen of the N-terminal alanine. The reactive configuration positions the pyranose ring oxygen solvating the ionizing proton (V, Figure S2, Table S1). Transfer of the proton to the ring oxygen and concerted nucleophilic attack into carbon 1 of the GalNAc residue in a SN2-like transition structure (TS_V_VI, ΔH298K (ΔG298K) = 113 (113) kJ mol -1 (M06-2X/6-31+G(d,p)), Table S1, Figure 3) forms an oxazoliniumderivative that allows free rotation of carbons 3 to 6. Once the hydroxyl group of carbon 4 is appropriately positioned a second SN2-like transition structure may occur (TS_VII_VIII, 131 (116) kJ mol -1 , Figure 3, Table S1) to produce a furanose GalNAc residue and protonation back at the carbonyl oxygen of the N-terminal alanine. Further proton transfers and rotations enable population of the furanose glycosidic bond cleavage reactive configuration (IX, Table S1, Figure S2). This elongated structure positions the ionizing proton close to the glycosidic oxygen while simultaneously bridged between the threonyl carbonyl oxygen and the carbonyl oxygen of the GalNAc residue. Proton transfer weakens the glycosidic bond, [START_REF] Bythell | Cationized Carbohydrate Gas-Phase Fragmentation Chemistry[END_REF][START_REF] Guan | Evidence of Gas-Phase Pyranose-to-Furanose Isomerization in Protonated Peptidoglycans[END_REF] enabling cleavage with concerted oxazolinium ion formation through nucleophilic attack by the carbonyl oxygen of GalNAc into carbon 1 of the GalNAc residue (TS_IX_X, 132 (111) kJ mol -1 , Table S1, Figure 3, Figure S2). The resulting proton bound dimer of ATA and the furanose oxazolinium ion, X, then either dissociates directly to yield the m/z 204 ion and neutral ATA or transfers a proton to ATA prior to dissociation, thereby generating m/z 262, [ATA+H] + . For all these reactions the peptide provides key charge solvation to lower the barriers substantially. [START_REF] Guan | Evidence of Gas-Phase Pyranose-to-Furanose Isomerization in Protonated Peptidoglycans[END_REF] Without this solvation this complicated dissociation mechanism would not be feasible. The conceptually simpler direct mechanism [START_REF] Halim | Assignment of Saccharide Identities through Analysis of Oxonium Ion Fragmentation Profiles in LC-MS/MS of Glycopeptides[END_REF][START_REF] Yu | Distinctive MS/MS Fragmentation Pathways of Glycopeptide-Generated Oxonium Ions Provide Evidence of the Glycan Structure[END_REF][START_REF] Ashwood | Discrimination of Isomers of Released N-and O-Glycans Using Diagnostic Product Ions in Negative Ion PGC-LC-ESI-MS/MS[END_REF] of dissociation (Scheme S1) is again [START_REF] Guan | Evidence of Gas-Phase Pyranose-to-Furanose Isomerization in Protonated Peptidoglycans[END_REF] predicted to be more energetically demanding (TS_XI_XII, 143 (130) kJ mol -1 , Table S1, Figure S3). The mechanism begins with mobilization of a proton from the global minimum, N-terminally protonated structure to the glycosidic oxygen via the carbonyl oxygen of the GalNAc residue enabling concerted glycosidic bond cleavage and nucleophilic attack into carbon 1 to form a pyranose GalNAc oxazolinium ion. A summary of the 2 pathways and their relative energetics is provided in Figure S4.

The predicted reaction energetics are consistent for both the M06-2X and B3LYP models with 6-31+G(d,p) basis sets although the magnitude of the predicted barriers differs. To assess the effect of chemical model as a function of basis set, we utilized the larger 6-311+G(2d,2p) basis set and the ωB97XD functional too. All 3 models consistently predict the furanose-forming mechanism be most likely (Table S2). Like the Kuo group, [START_REF] Chiu | Improved Agreement between Experimental and Computational Results for Collision-Induced Dissociation Mass Spectrometry of Cation-Tagged Hexoses[END_REF] we find that the newer models which contain dispersion terms and larger proportions of exact exchange produce larger barriers for gasphase glycan reactions. [START_REF] Bythell | Cationized Carbohydrate Gas-Phase Fragmentation Chemistry[END_REF][START_REF] Guan | Evidence of Gas-Phase Pyranose-to-Furanose Isomerization in Protonated Peptidoglycans[END_REF][START_REF] Bythell | Sequence Ion Structures and Dissociation Chemistry of Deprotonated Sucrose Anions[END_REF] Here, the key reactions are SN2-like which is a known weakness of the B3LYP model which systematically underestimates SN2 reaction barriers. [START_REF] Laerdahl | Gas phase nucleophilic substitution[END_REF][START_REF] Bythell | Formation of a 1 Ions Directly from Oxazolone b 2 Ions: An Energy-Resolved and Computational Study[END_REF][START_REF] Gritsenko | Comparison of the Accurate Kohn-Sham Solution with the Generalized Gradient Approximations (GGAs) for the SN2 Reaction F-+ CH3F -> FCH3 + F-: A Qualitative Rule To Predict Success or Failure of GGAs[END_REF][START_REF] Bleiholder | Competing Gas-Phase Fragmentation Pathways of Asparagine-, Glutamine-, and Lysine-Containing Protonated Dipeptides[END_REF] IR Action Spectra of dissociation products: m/z 204. Figure 4 shows our experimental IR action spectroscopy data for the m/z 204 population compared to theoretical spectra of the six lowest energy furanose oxazolinium ion structures predicted within 20 kJ mol -1 (Figure S5). All theoretical spectra have at least one intense band predicted at ~3460 cm -1 corresponding to the NH stretch, and higher energy bands predicted in the 3640-3680 cm -1 region corresponding to free OH stretches. H-bonding pattern strongly affects which OH stretch this corresponds to. i.e., all three hydroxyl stretches are predicted as the highest energy band for at least one structure in Figure 4 (Table S3). No individual structure's theoretical spectrum explains all experimental features. Population of several low energy structures is more plausible. In particular, one low energy structure (panel d, ~3525 cm -1 , C5-OH hydrogen bonded to C6-OH, Table S3) predicts a substantial band assignable to the experimental feature ~3510-3550 cm -1 ; conversely, the experimentally lower signal-to-noise band at ~3580 cm -1 is only predicted for one low energy structure (panel g, C5-OH hydrogen bonded to the free C6-OH, Table S3). What about the typically invoked [START_REF] Halim | Assignment of Saccharide Identities through Analysis of Oxonium Ion Fragmentation Profiles in LC-MS/MS of Glycopeptides[END_REF][START_REF] Yu | Distinctive MS/MS Fragmentation Pathways of Glycopeptide-Generated Oxonium Ions Provide Evidence of the Glycan Structure[END_REF][START_REF] Ashwood | Discrimination of Isomers of Released N-and O-Glycans Using Diagnostic Product Ions in Negative Ion PGC-LC-ESI-MS/MS[END_REF] pyranose oxazolinium ion structures?

Calculated IR spectra of the lowest energy pyranose oxazolinium ion structures (Figure S6) are compared to the experimental spectrum in Figure S7. Both experimental and theoretical spectra show a substantial band at ~3460 cm -1 again corresponding to the NH stretch. However, no pyranose oxazolinium structure has a predicted band which could explain the intense experimental at ~3510-3550 cm -1 . The much less intense experimental feature at 3575-3600 cm -1 is potentially consistent with an intense band predicted for the lowest energy pyranose oxazolinium ion structure (Figure S7, panel f). Although we cannot rule out a population of the pyranose oxazolinium ion structures based on these data, these structures are insufficient to explain all experimental features. Additionally, data from the m/z 204 peaks produced from 2 other protonated glycopeptides, [PT(GalNAc)P+H] + and [RVT(GalNAc)AG+2H] 2+ collected on a subsequent days produced similar, but noisier spectra (Figure S8) to those in Figure 4. While these spectra are lower signal-tonoise, the consistency in band position supports a similar distribution of m/z 204 ion gas-phase ion populations despite changes in peptide sequence and charge state. i.e., indirect support for current MS [START_REF] Miyoshi | Fucosylated Haptoglobin Is a Novel Marker for Pancreatic Cancer: Detailed Analyses of Oligosaccharide Structures[END_REF] -based approaches to residue identification. [START_REF] Halim | Assignment of Saccharide Identities through Analysis of Oxonium Ion Fragmentation Profiles in LC-MS/MS of Glycopeptides[END_REF][START_REF] Yu | Distinctive MS/MS Fragmentation Pathways of Glycopeptide-Generated Oxonium Ions Provide Evidence of the Glycan Structure[END_REF] IR Action Spectra of dissociation products: m/z 262. Figure S9 shows our experimental IR action spectroscopy data for the m/z 262 population compared to the 6 lowest energy theoretical IR action spectra of [ATA+H] + . These are O-protonated structures of similar energy (range <10 kJ mol -1 , Figure S10) and band position making definitively excluding structures difficult. The enthalpically lowest energy structure (Figure S9, panel f, Figure S10) is insufficient to explain the higher energy bands in the spectrum as it lacks a band predicted at ~3665 cm -1 . This is consistent with the greater entropic favorability of these structures (Figure S10).

Conclusions. Our combined tandem mass spectrometric, computational, and spectroscopic analyses provide evidence indicating that protonated α-GalNAc glycosylated peptides can produce furanose oxazolinium ion, m/z 204, C8H14N1O5 + , structures. Multiple levels of theory support isomerization prior to glycosidic bond dissociation to produce this ion. In principle, these reactions should be general for glycopeptides as the primary function of the peptide is to facilitate dissociation by providing charge solvation. However, multiple, low energy structures are necessary to explain the IR action spectrum. Concomitantly, we are unable to entirely rule out simultaneous production of at least some pyranose oxazolinium ion population due a combination of similar predicted bands and reaction barriers not being drastically different.

Future work will involve testing the generality of these findings for a wider range of glycan linkage types, glycan and peptide compositions, and at differing photon energies.

ASSOCIATED CONTENT Supporting Information

Supplementary Tables summarizing relative energetics, Figures, minima, and transition structure figures, coupled with additional discussion of the dissociation energetics are provided in the supporting PDF file. The Supporting Information is available free of charge on the ACS Publications website.

Scheme 1 .

 1 Scheme 1. Simplified formation of m/z 204 α-GalNAc oxazolinium reporter ion structures from protonated glycopeptides (R = peptide): (a) Direct, pyranose B1 ion; 26-29 (b) Indirect, furanose B1 ion 22 .

  Description of Reactions. Roman numerals are utilized to label calculated structures (consistent with other ACS journals) in the text. Transition structures are labelled in a similar manner as: TS_reactant_product. For example: TS_I_II would be the TS structure linking reactant structure I to product structure II. RESULTS AND DISCUSSION Tandem Mass Spectrometry. For [AT(GalNAc)A+H] + our electrospray-quadrupole time-of-flight tandem mass spectra show abundant peaks at m/z 204 and 262 (Figure 1). These peaks are complementary from a single cleavage of the glycosidic bond: m/z 204 is [GalNAc-H2O+H] + , C8H14N1O5 + , and m/z 262 is protonated alanylthreonylalanine, [ATA+H] + , C10H20N3O5 + .

Figure 1 .

 1 Figure 1. Electrospray-quadrupole time-of-flight MS/MS data: (a) Example spectrum of [AT(GalNAc)A+H]⁺, m/z 465.1±4, at 12 eV laboratory frame collision energy. (b) Breakdown graph summarizing the [AT(GalNAc)A+H]⁺ MS/MS spectra as a function of laboratory frame collision energy.

Figure 2 .

 2 Figure 2. Global minimum precursor ion structure, I, of [AT(GalNAc)A+H]⁺.Glycosidic Bond Cleavage. The m/z 204, C8H14N1O5 + , [GalNAc-H2O+H] + and m/z 262, C10H20N3O5 + , [ATA+H] + fragments are complementary resulting from cleavage of the glycosidic bond. Consistent with the wider understanding of peptide dissociation chemistry, the key difference is which fragment keeps the ionizing proton.[START_REF] Wysocki | Mobile and localized protons: a framework for understanding pep-tide dissociation[END_REF][START_REF] Tsaprailis | Influence of Secondary Structure on the Fragmentation of Protonated Peptides[END_REF][START_REF] Paizs | Fragmentation pathways of protonated peptides[END_REF] For the [AT(GalNAc)A+H] + ions, the lowest energy mechanism involves isomerization[START_REF] Guan | Evidence of Gas-Phase Pyranose-to-Furanose Isomerization in Protonated Peptidoglycans[END_REF][START_REF] Abutokaikah | Leaving Group Effects in a Series of Electrosprayed CcHhN1 Anthracene Derivatives[END_REF] prior to glycosidic bond dissociation (Scheme 2). This pathway begins with mobilization of the ionizing proton to the carbonyl oxygen of the N-terminal alanine. The reactive configuration positions the pyranose ring oxygen solvating the ionizing proton (V, FigureS2, TableS1). Transfer of the proton to the ring oxygen and concerted nucleophilic attack into carbon 1 of the GalNAc residue in a SN2-like transition structure (TS_V_VI, ΔH298K (ΔG298K) = 113 (113) kJ mol -1 (M06-2X/6-31+G(d,p)), TableS1, Figure3) forms an oxazoliniumderivative that allows free rotation of carbons 3 to 6. Once the hydroxyl group of carbon 4 is appropriately positioned a second SN2-like transition structure may occur (TS_VII_VIII, 131 (116) kJ mol -1 , Figure3, TableS1) to produce a furanose GalNAc residue and protonation back at the carbonyl oxygen of the N-terminal alanine. Further proton transfers and rotations enable population of the furanose glycosidic bond cleavage reactive configuration (IX, TableS1, FigureS2). This elongated structure positions the ionizing proton close to the glycosidic oxygen while simultaneously bridged between the threonyl carbonyl oxygen and the carbonyl oxygen of the GalNAc residue. Proton transfer weakens the glycosidic bond,[START_REF] Bythell | Cationized Carbohydrate Gas-Phase Fragmentation Chemistry[END_REF][START_REF] Guan | Evidence of Gas-Phase Pyranose-to-Furanose Isomerization in Protonated Peptidoglycans[END_REF] enabling cleavage with concerted oxazolinium ion formation through nucleophilic attack by the carbonyl oxygen of GalNAc into carbon 1 of the GalNAc residue (TS_IX_X, 132 (111) kJ mol -1 , TableS1, Figure3, FigureS2). The resulting proton bound dimer of ATA and the furanose oxazolinium ion, X, then either dissociates directly to yield the m/z 204 ion and neutral ATA or transfers a proton to ATA prior to dissociation, thereby generating m/z 262, [ATA+H] + . For all these reactions the peptide provides key charge solvation to lower the barriers substantially.[START_REF] Guan | Evidence of Gas-Phase Pyranose-to-Furanose Isomerization in Protonated Peptidoglycans[END_REF] Without this

Scheme 2 .

 2 Scheme 2. The predicted lowest energy pathways to glycosidic bond dissociation m/z 204 α-GalNAc

Figure 3 .

 3 Figure 3. Transition structures enabling furanose, GalNAc oxazolinium ion, m/z 204 formation: (a) pyranose ring-opening; (b) SN2-like formation of furanose GalNAc; (c) Proton transfer and glycosidic bond cleavage. Dotted green lines indicate bond breakage/formation.

Figure 4 .

 4 Figure 4. IR action spectra of the m/z 204 population (a) compared to the six lowest energy furanose GalNAc oxazolinium ion structures (b-g).

ACKNOWLEDGMENT This work was supported by the National Science Foundation under CHE-1948611, a University of Missouri-St. Louis Research Award, and start-up funds from Ohio University. Calculations were performed at Ohio Supercomputer Center (http://osc.edu/ark:/19495/f5s1ph73) and at the Missouri University of Science and Technology, Rolla, MO with support from the NSF (ACI-1919789). The research leading to this result has been supported by the project CALIPSOplus under the Grant Agreement 730872 from the EU Framework Program for Research and Innovation HORIZON 2020. The authors are grateful to E. Loire, J. M. Ortega, F. Gobert, and N. Jestin for technical support.

AUTHOR INFORMATION

Corresponding Author *Benjamin Bythell, bythell@ohio.edu

Author Contributions

Δ JMR and SG contributed equally to this manuscript. JMR, SG, and BJB performed the calculations. MTA and SG collected and initially analyzed the tandem mass spectral data. JMR, BJB, and PM collected the spectroscopic data. All authors analyzed data. Figures and Schemes were made by LMS, JMR, and BJB. The manuscript was written through contributions of all authors.