Kawtar Ghiatt

Ahmad Diab

Kiyoka Kinugawa

Ning Jiang

Sofiane Boudaoud

Evaluation of Age and Sex Effects on Force Complexity and Fluctuation during isometric elbow flexion

Keywords: aging, force, steadiness, complexity, muscle, elbow flexion

This study attempts to examine the impact of age and gender on fluctuations in force output during voluntary muscle contractions and how this impacts task performance. More precisely, the study investigates how these fluctuations vary during an elbow flexion task at sub-maximal forces. Interestingly, the study found that elderly women exhibit lower steadiness, meaning they exhibit a diminished capacity to maintain a steady force output and lower complexity than young adults when dealing with high levels of contraction. This suggests that women may have a diminished ability to maintain a steady and adaptable force output during the elbow flexion task, which could affect their performance. However, the findings from this study show that the existence of notable differences in force fluctuations among diverse age groups was limited to specific levels of contraction. Thus, it can be deduced that various factors, apart from age alone, might contribute to the observed decrease in force fluctuations in this study. Additionally, there are differences in behavior between women and men.

I. INTRODUCTION

Age-related changes in motor units significantly impact both strength and force control, resulting in a reduction to generate accurate levels of force [START_REF] Hepple | Innervation and neuromuscular control in aging skeletal muscle[END_REF]. Age-related changes involve various aspects related to motor units and motor neuron function such as a loss of motor units,alterations in discharge rates, motor unit remodeling, or variations in the common synaptic input to motor neurons.. [START_REF] Hepple | Innervation and neuromuscular control in aging skeletal muscle[END_REF], [START_REF] Piasecki | Age-dependent motor unit remodeling in human limb muscles[END_REF]. [START_REF] Hepple | Innervation and neuromuscular control in aging skeletal muscle[END_REF], [START_REF] Piasecki | Age-dependent motor unit remodeling in human limb muscles[END_REF]. These changes provoke a decline in their maximal force, which refers to their strength, and a decline in their ability to control their movements and perform tasks with precision, which is known as force control and task performance [START_REF] Pethick | Aging and skeletal muscle force control: Current perspectives and future directions[END_REF], [START_REF] Laidlaw | Steadiness is reduced and motor unit discharge is more variable in old adults[END_REF]. However, Some studies suggest, that as individuals begin to age, the initial stages of decline in functional capacity appear to be more connected to difficulties in controlling force rather than a decrease in the ability to generate maximum force. [START_REF] Enoka | Force steadiness: from motor units to voluntary actions[END_REF]. Studies have shown that there are disparities in both the magnitude of force variations and force complexity between older and younger adults [START_REF] Morrison | Aging, neuromuscular decline, and the change in physiological and behavioral complexity of upper-limb movement dynamics[END_REF] [7] [START_REF] Hong | Coupling and irregularity in the aging motor system: tremor and movement[END_REF]. These changes contribute to the decline in older adults' capacity to engage in activities of daily living (ADLs) such as maintaining balance, moving about, and handling objects [START_REF] Oomen | Effects of age on force steadiness: a literature review and meta-analysis[END_REF]. In addition to agerelated changes in force control, sex differences in strength and force fluctuations have also been studied. Typically, men exhibit greater strength than women, which may contribute to differences in force control between genders [START_REF] Pethick | Aging and skeletal muscle force control: Current perspectives and future directions[END_REF].

Indeed, this study aimed to examine whether agerelated changes in force fluctuations also extend to changes in the temporal structure or complexity of force signals during isometric elbow flexion and whether sex differences play a role in these changes. In particular, we quantified force fluctuations and complexity at 20%, 40%, and 60% of maximal voluntary contraction (MVC) in both young, middle-aged, and older men and women. This study is innovative as it explores potential disparities of the variations in stability and complexity of force signals among men and women, across three different age groups (Young, Middle-aged, and Elderly).

II. MATERIAL AND METHODS

A. Cohort description

The INSEAD Institutional Review Board has approved the study, and the data collection has been done at the INSEAD-Sorbonne University Behavioural Lab (protocol ID 2022-55) to assess age-related changes in muscle during elbow flexion. The cohort was built following specific inclusion criteria such as age, sex, physical activity (IPAQ), and healthy status.

B. Force recording

A hand-made ergometer with a torque sensor (Model TFF350) was used to measure the elbow flexion of each participant. The participants were placed on a chair, and their upper arm was supported by the ergometer. Both shoulder and elbow were flexed at a 90°angle, with their wrist resting against a bar. They were instructed to perform isometric elbow flexion (Figure 1). The signals acquired from the torque sensor were amplified and displayed on a biofeedback screen, which provided the subjects with real-time information about their force production. The force values were digitized at a high sampling frequency of 2 kHz to allow precise complexity and deviation assessment. Simultaneously, HD-sEMG signals were also recorded but not exploited in this study.

C. Experimental protocol

In the experiment, each participant was asked to perform three MVCs. The reference MVC was established as the highest of the three measurements, with a 5-minute interval between each measurement. After the MVC measurement, the subjects were given a 10-minute rest period. Subsequently, the participants performed nine voluntary contractions, each lasting 15 seconds, at varying levels: three at 40% of their maximum capacity, three at 60%, and three at 20%. Even with the same order, no skill acquisition was observed among subjects. They were asked to maintain the asked torque level with fluctuations of no more than ± 5% with visual biofeedback display.

D. Data analysis

A low-pass Butterworth filter of 4th order was applied with a cutoff frequency of 10 Hz [START_REF] Thompson | Influence of signal filtering and sample rate on isometric torque-time parameters using a traditional isokinetic dynamometer[END_REF]. This helped to eliminate high-frequency noise and artifacts that could potentially interfere with the analysis of the force signals. The resulting filtered signal is then suitable for further processing and analysis.

In the study, the analysis was specifically focused on the plateau phase of the constant-force trial, which lasted for 8-10 seconds for all target forces. To avoid any adaptability effects, the first 5 seconds of the signal were excluded, and only the following 10 seconds were analyzed. The exclusion of the initial 5 seconds helped to focus on a more stable and representative part of the signal, thus improving the accuracy and reliability of the results.

Moreover, the study observed no significant differences in fluctuations among the three trials. As a result, to minimize bias and ensure reliability, the values from the three trials were averaged to obtain a more robust and accurate estimate of steadiness values.

In the context of sustaining a constant force during a submaximal isometric contraction, the applied force is not constant, but, it fluctuates around a mean value. The method used to determine this steadiness of force during a muscle contraction is to calculate the coefficient of variation (CV) of force. This involves measuring the amplitude variability of the force produced during a constant-force contraction and expressing it as a percentage of the mean force [START_REF] Enoka | Force steadiness: from motor units to voluntary actions[END_REF]. To calculate the CV, the standard deviation of the force is divided by the mean force and then multiplied by 100%. A lower CV indicates greater steadiness of force production, while a higher CV indicates lower steadiness of force production [START_REF] Pethick | Aging and skeletal muscle force control: Current perspectives and future directions[END_REF].

Muscle force complexity can be defined as the variability and unpredictability of the forces produced by muscle contractions over time. Approximate entropy (ApE) is a used metric to evaluate the regularity of time series data such as muscle force [START_REF] Pincus | Approximate entropy as a measure of system complexity[END_REF]. ApE quantifies the likelihood that a given pattern of force fluctuations will repeat itself over time. Lower values of ApE indicate greater regularity and higher values indicate greater complexity [START_REF] Pincus | Approximate entropy as a measure of system complexity[END_REF]. ApE quantifies the negative natural logarithm of the conditional probability that a template is repeated during a time series. The ApE formula :

ApE(m, r, N ) = - 1 N -m N -m i=1 log A i B i
Denoted as ApE(m, r, N), operates by analyzing sequences of m data points to determine the logarithmic likelihood of these sequences resembling other sequences within the dataset. Matching templates, which maintain their similarity within a defined tolerance 'r', are identified and quantified. The count of matches to the 'i-th' template, which has a length of 'm' data points, is denoted as 'Bi'. Following this, the algorithm proceeds to count the instances where these matches persist even when considering the 'm ± i-th' data point. This count is represented as 'Ai' for the 'i-th' template. In the context of sequence comparison, sequences are deemed similar only if the difference between them exceeds the specified noise threshold r [START_REF] Pincus | Approximate entropy as a measure of system complexity[END_REF]. Indeed, ApE was computed for each one-second epoch for all signals using this method by fixing m=2 and r = 0.25.

E. Statistical analysis

The force measurement between gender groups was compared using Welch's t-test. The force measurements between different age groups were compared using an analysis of variance (ANOVA) with age group as a between-subjects factor. Pairwise comparisons between the age groups were conducted using Tukey's honest significance test to establish if there were significant differences in force measurements between any of the groups.

The statistical analysis was performed using the Matlab software (Version: 9.13.0 (R2022b)) in this study. A significance level of 0.05 was used for all statistical tests, and the results are presented as the mean ± standard deviation (SD) in the text. The figures' values are displayed as the mean ± standard error of the mean (SEM) to provide a clearer representation of the data. The SEM is equal to the ratio of the standard deviation to the root of the sample size.

III. RESULTS

A. Maximum voluntary contraction

Table II presents the mean and standard deviation of torque for each age group and gender.

In terms of the MVC of the elbow flexors among the men group, no significant differences were observed (P > 0.05). However, for women, the ANOVA test revealed significant differences between the age groups. To further investigate these differences, pairwise comparisons were conducted. It was found that the MVC was significantly greater in younger women compared to elderly women (p = 0.0068).However, there were no significant differences in MVC between young and middle-aged women (p = 0.051), as well as between middle-aged women and elderly women (p = 0.34). The results indicate that the MVC values were significantly lower in women compared to men (P > 0.05) for the middle-aged group and (P > 0.01) for the young and elderly groups (Table II).

B. Coefficient of variation

Figure 2 displays the coefficient of variation (CV) and standard error of the mean at different levels of MVC for each age group and gender.

Age Differences

The force steadiness was significantly greater (P < 0.05) in the elderly age group at 40% MVC than young men and middle-aged group for men and 60% for women group. The CV of young women (2.65 ± 1.47) was significantly greater (P < 0.05) than middle-aged women (1.52 ± 0.78) and (1.12 ± 0.83) in Elderly women (Figure 2). For men, a similar observation was made, but the difference did not have statistical significance. with a P -value of less than 0.5.

Sex Differences

The coefficient of variation (CV) values reflect the variability in force steadiness. Significant differences between sexes are observed at different force levels. Specifically, at 40% and 60% of maximal voluntary contraction (MVC), the CV is significantly higher in women compared to men (P < 0.01). On the other hand, at 20% MVC, men exhibit a significantly higher CV compared to women (P < 0.01). This indicates that there are distinct sex differences in force steadiness, with women generally displaying greater variability at higher force levels and men exhibiting higher variability at lower force levels.

C. Approximate entropy

Age Differences

Although a decrease in complexity was observed with age in the men's group at 20% and 40% MVC, the difference in approximate entropy was not statistically significant. This suggests that factors other than age may contribute to the decline of complexity in force movements during elbow flexion for men at those specific levels of MVC.

Sex Differences

At 40% and 60'% MVC, Figure 3 shows that men exhibited higher approximate entropy compared to women in all age groups. However, at 20% MVC, the differences in approximate entropy between men and women were not statistically significant. These results indicate that the sex differences in complexity during elbow flexion, as indicated by approximate entropy, may be influenced by the level of muscle contraction. In agreement with the literature, this study found that women had a lower maximal voluntary contraction (MVC) of elbow flexors compared to men, indicating a sex discrepancy. The study also noted that at 40% and 60% MVC, men exhibited greater steadiness and lower variability than women did. This finding may be explained by the difference in maximal torque between men and women, a higher MVC than women, which can cause more force stability and less force variation in muscle activation levels during these levels of contraction [12] [3].

However, concerning age differences, the MVC of elbow flexors only differed significantly between younger and older women. Furthermore, there were only significant differences in force steadiness at 40% for men and 60% for women. Although it has not been found a statistically significant decrease in signal complexity in older men during voluntary muscle contractions at 20% and 40% of MVC. The observed trend towards decreased complexity, especially at 60 % of MVC, may suggest a decline in adaptability and control of force output. Several studies have also consistently reported a lack of significant differences in force steadiness among the muscles responsible for elbow flexion [START_REF] Oomen | Effects of age on force steadiness: a literature review and meta-analysis[END_REF]. However, the complexity, for all the studied contraction levels, seems to be higher for men than women.Future research should focus on tasks involving fine motor skills and consider lifestyle factors like physical activity level and occupation, which can affect muscle force variability and contribute to agerelated changes in force control [START_REF] Pethick | Aging and skeletal muscle force control: Current perspectives and future directions[END_REF]. The impact of age on force control may vary across different muscle groups, with some showing significant changes while others may not [START_REF] Morrison | Aging, neuromuscular decline, and the change in physiological and behavioral complexity of upper-limb movement dynamics[END_REF] [7] [START_REF] Oomen | Effects of age on force steadiness: a literature review and meta-analysis[END_REF].

Moreover, it is important to acknowledge sex disparities in age-related changes, with women potentially experiencing different or greater declines in force control for elbow flexor muscles due to factors such as reduced engagement in activities that utilize specific muscle groups [START_REF] Guo | Sex disparities in age-related neuromuscular decline: unveiling female susceptibility from early to late elderly[END_REF] [START_REF] Lizu | Effect of the biceps brachii tendon on elbow flexor force steadiness in men and women[END_REF]. Recent research has demonstrated a sex-specific degradation of the neuromuscular system, with women being more susceptible to such degradation, largely influenced by hormonal differences [START_REF] Guo | Sex disparities in age-related neuromuscular decline: unveiling female susceptibility from early to late elderly[END_REF].

V. CONCLUSION

This study attempted to examine the impact of age on force steadiness and complexity during elbow flexion at various levels of contraction (ranging from 20% to 60% of maximal voluntary contraction). The results revealed that women show lower force steadiness and increased complexity compared to men. Regarding age differences, significant variations were observed only for specific levels of contractions. This study confirms the importance of considering factors such as sex disparities, the specific muscle group involved, and the level of contraction when examining force fluctuations and complexity. However, further studies with larger cohorts are needed to confirm the obtained results.

Fig. 1 .

 1 Fig. 1. A.Participant performing an elbow flexion exercise using the ergometer B.64 electrodes grid placed on the BB muscle C. Force signal output D.HD-sEMG signals output

Figure 3

 3 Figure 3 displays the approximate entropy and standard deviation for each age group and sex at different levels of MVC.

Fig. 2 .

 2 Fig. 2. Mean ± SEM of coefficient of variation for each age group

Fig. 3 .

 3 Fig. 3. Mean ± SEM of approximate entropy for each age group

Table I

 I

	YW (Young Women), MM (Middle-Aged Men), MW
	(Middle-Aged Women), EM (Elderly Men), and EW
	(Elderly Women).
	presents the participant characteristics, in-
	cluding the age (years) and BMI (kg/m²), for each
	age group and gender. The abbreviations used for
	the age groups are as follows: YM (Young Men),

TABLE II MEAN

 II AND STANDARD DEVIATION OF TORQUE FOR EACH PARTICIPANT WHERE "N.S." DENOTES "NON-SIGNIFICANT" (NULL HYPOTHESIS REJECTED), "*" DENOTES A P-VALUE OF 0.05;'* *' DENOTES A P-VALUE OF 0.01, AND A P-VALUE OF 0.001

	Age group Torque (Nm)
	YW	37.5 ± 9.2**
	MW	34.9 ± 7.3
	OW	25.3 ± 6.7
	YM	61.5 ± 15.3
	MM	51.9 ± 10.6
	OM	50 ± 9.7

ACKNOWLEDGMENT

This work was carried out and funded in the framework of the Labex MS2T. We would also like to acknowledge the support from the INSEAD-Sorbonne Université Behavioural Lab in helping to conduct this study.This work is carried out within the framework of the International Research Project IRP ADONIS, "Approaches of Diagnostics and Intelligent Control of Systems" (2020-2024), funded by the CNRS and Université de Technologie de Compiègne in France, and, the Lebanese University in Lebanon.


Jonathan Corren

MD Andrew Menzies-Gow

Johan Bimmel

Anthony Mcguinness

Gun Almqvist

Karin Bowen

Janet M Griffiths

Sandhia Ponnarambil

Arnaud Bourdin

Elliot Israel

Gene Colice

Christopher E Brightling

MD Michael E Wechsler

Tezepelumab for the treatment of severe asthma: a plain language summary of the PATHWAY and NAVIGATOR studies

Keywords: Antibody therapeutics, Clinical immunology, Cytokines and cell signaling

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Tezepelumab is a type of biologic treatment called an antibody. Biologics are treatments that target certain cells or proteins in the body and often in the immune system -the body's natural defence system against infections and diseases -to reduce patients' disease. It works by blocking a key first step in the body's chain reaction leading to inflammation in the airways of people with severe asthma.

The clinical studies were done to learn if tezepelumab can be used to treat people with severe, uncontrolled asthma and to find out about its safety. In both studies, tezepelumab was compared to placebo. A placebo is a dummy treatment that looked like tezepelumab but did not have any medicine in it.

What were the main conclusions reported by the researchers?:

In both studies, tezepelumab reduced the number of severe asthma attacks that the participants had per year compared with placebo. It also increased the volume of air that the participants could breathe out in 1 second compared with placebo.

Tezepelumab was well-tolerated, and a similar number of participants had health issues in the tezepelumab and placebo treatment groups.

The most common health issues that the participants had during the PATHWAY study were: Worsening of asthma, common cold, headache, and inflammation of the airways. The most common health issues that the participants had during the NAVIGATOR study were:

Common cold, infection of the sinuses, throat and airways, headache, worsening of asthma, and inflammation of the airways.

What are the key takeaways?:

The results showed that participants who had monthly doses of tezepelumab had fewer severe asthma attacks and better lung function than those who had placebo. In both studies, the health issues that the participants had were similar between the tezepelumab and placebo treatment groups.

Overall, the studies showed that tezepelumab worked in a broad population of people with severe asthma and that the study participants had an acceptable level of health issues during the studies. These results led to the approval of tezepelumab for people with severe asthma aged 12 and above in the USA, EU and other countries.

Clinical Trial Registration:

PATHWAY study: NCT02054130; NAVIGATOR study: NCT03347279 (ClinicalTrials.gov).

Who sponsored these studies and this summary?

The PATHWAY study was sponsored by MedImmune, a member of the AstraZeneca group, and Amgen Inc. The NAVIGATOR study was sponsored by AstraZeneca and Amgen Inc. This summary of the study results was sponsored by AstraZeneca UK.

What is severe, uncontrolled asthma?

What is severe, uncontrolled asthma?

Asthma is a long-term condition caused by ongoing inflammation of the airways. The main symptoms are difficulty breathing, coughing, wheezing and shortness of breath. These symptoms can be present every day and can also cause severe asthma attacks, called exacerbations. These symptoms can prevent a person from taking part in their normal daily activities and can also lead to emergency treatment or admission to hospital.

Although asthma cannot be cured, treatments are available to reduce, or control, the symptoms. Most people only have mild symptoms, but up to 1 in 10 people (10%) with asthma have a severe form of the disease. Many people with severe asthma continue to have symptoms despite getting treatment with high doses of inhaled therapies. When this happens, the condition is called severe, uncontrolled asthma.

Why are the inner surfaces of the airways important for asthma?

The specialized layer of cells that forms the surface of the airways in the lung is called the epithelium. This airway's epithelium is the body's first line of defense against harmful particles in the air. These can include air pollution, cigarette smoke, allergens (e.g. pollen) and disease-causing germs, including viruses, bacteria and fungi.

For this reason, the epithelium drives the immune response, which is the response of the body's natural defense system, against these particles in the air. It is also involved in the development of asthma.

What role does the molecule TSLP play in asthma?

Thymic stromal lymphopoietin, also called TSLP, is a molecule that is produced by the airway epithelium and other cells in the body in response to harmful particles in the air. It is one of the key early signals in the body's chain reaction that results in the inflammation that causes asthma.

In asthma, too much TSLP is released from the epithelium. TSLP then activates a large number of pathways that cause inflammation, including those in the airway muscles. As a result, the airways become inflamed, swell and narrow, and produce extra mucus, which is the thick, sticky fluid that lines the airways. This leads to the symptoms of asthma and increases the risk of asthma attacks. TSLP has been shown to play an important role in the ongoing inflammation of the airways in people with asthma.

What is tezepelumab?

Tezepelumab is a type of asthma treatment called a biologic treatment, also known as a monoclonal antibody. Tezepelumab works by preventing TSLP from activating the body's chain reactions that cause inflammation in the airways. In this way, tezepelumab targets the very start of the multiple chain reactions that cause inflammation. This can help to decrease inflammation more widely than blocking targets further along these individual pathways.

Tezepelumab is given as an injection under the skin, also known as a subcutaneous injection, once every 4 weeks. It is a medicine that can be prescribed by a doctor for people with severe asthma who are 12 years of age and older. Tezepelumab is usually given in addition to other asthma medicines, such as inhalers, as an add-on treatment.

Why were these studies needed?

Severe, uncontrolled asthma greatly contributes to the health and financial burden of asthma worldwide. Asthma has many different disease traits. Although biologic treatments are available, they do not work for all people with severe, uncontrolled asthma, depending on their disease traits. So, researchers were looking for other biologic treatments that work for more people with severe, uncontrolled asthma.

Who took part in the studies?

The PATHWAY study included 550 participants with asthma who got study treatment from 12 countries worldwide. These included: Bulgaria, the Czech Republic, Hungary, Israel, Japan, Latvia, Lithuania, Serbia, Slovakia, South Africa, Ukraine and the USA.

The NAVIGATOR study included 1059 participants with asthma who got study treatment from 18 countries worldwide. These included: Argentina, Australia, Brazil, Canada, France, Germany, Israel, Japan, Russia, Saudi Arabia, South Africa, South Korea, Taiwan, UK, USA and Vietnam.

Participants who took part in the studies:

• Were 18-75 years of age (PATHWAY study) or 12-80 years of age (NAVIGATOR study)

• Had a diagnosis of asthma • Had been treated with mediumor high-dose inhaled asthma medications, also known as steroid inhalers or inhaled corticosteroids, and at least one other asthma medication before the start of the studies • Had at least 2 severe asthma attacks in the 12 months before the studies started (or 1 admission to hospital because of a severe asthma attack in the PATHWAY study)

The figure below shows some of the characteristics of the participants before they started the studies. They are the averages of each characteristic across all the participants in the treatment group. It is important that the characteristics are similar for the participants in both treatment groups at the start of the study so that the 2 treatment groups can be directly compared at the end of the study. The figure shows the characteristics of all those participants, whose results are included in this summary.

What happened in these studies?

Phase: In the phase 2 clinical study, the researchers wanted to find out if tezepelumab worked in a small number of participants with severe, uncontrolled asthma. In the phase 3 clinical study, the researchers wanted to find out if tezepelumab worked in a large number of participants with severe, uncontrolled asthma. In both types of study, the researchers also wanted to find out if the participants had any health issues during the study.

Randomized:

The participants were assigned to the study treatment by chance to get either tezepelumab or placebo. This helped to make sure that the groups were chosen fairly. Researchers do this so that comparing the results of each treatment is as accurate as possible.

Placebo: The placebo looked like tezepelumab but did not have any medicine in it. Researchers used placebo to help to make sure that any of the effects they saw in the participants who were given tezepelumab were actually caused by tezepelumab.

Double-blind:

This means that none of the participants, researchers, study doctors or other study staff knew what treatment each participant was given. Some studies are done this way because knowing what treatment the participants are given can affect the results of the study. When the study ended, the company that sponsored the clinical studies found out which treatments the participants were given so that they could create The PATHWAY and NAVIGATOR studies were done to learn if tezepelumab works for people with severe, uncontrolled asthma and how safe it is.

The PATHWAY study was a phase 2, randomized, double-blind clinical study that compared 3 separate doses of tezepelumab (low, medium and high) with the placebo, over a period of 1 year to find out which dose worked best.

• The low dose of tezepelumab was 70 milligrams (mg) every 4 weeks • The medium dose of tezepelumab was 210 mg every 4 weeks • The high dose of tezepelumab was 280 mg every 2 weeks This summary will only show the results of the medium dose of tezepelumab. This was the dose that was also used in the NAVIGATOR study and that is now approved for the treatment of severe asthma. The PATHWAY study started in December 2012 and ended in March 2017.

The NAVIGATOR study was a phase 3, randomized, double-blind clinical study that compared tezepelumab (210 mg every 4 weeks) with placebo, over a period of 1 year. It started in November 2017 and ended in September 2020.

Both studies looked at a broad population of people with severe asthma and many different disease traits. This was done because the effects of some asthma treatments can differ based on whether patients have specific disease traits. The broad population included people with and without allergies as well as people with and without high numbers of eosinophils in their blood. Eosinophils are white blood cells that are linked to some types of asthma.

During the studies, the participants continued to take their usual asthma medications in addition to tezepelumab or placebo.

The main questions that the researchers wanted to answer in these studies are below.

Did tezepelumab reduce the number of severe asthma attacks that the participants had per year compared with placebo?

Did tezepelumab increase the volume of air that the participants could breathe out in 1 second compared with placebo?

What were the most common health issues

The following chart shows the treatment groups in the individual studies.

What were the overall results of these studies?

Did tezepelumab reduce the number of severe asthma attacks that the participants had per year compared with the placebo?

Yes. In both studies, tezepelumab reduced the number of severe asthma attacks that the participants had per year compared with placebo. These reductions were seen for participants with or without allergies and with or without high numbers of eosinophils in their blood.

To answer this question, the researchers:

• Recorded the total number of severe asthma attacks, also called exacerbations, that each participant had during the studies • Calculated the average number of severe asthma attacks that all participants had per year in each study • Compared the average number of severe asthma attacks for the participants who had tezepelumab with the average number of severe asthma attacks for participants who had placebo within each study These results are shown in the figure below.

Did tezepelumab increase the volume of air that the participants could breathe out in 1 second compared with the placebo?

Yes. Tezepelumab increased the volume of air that the participants could breathe out in 1 second compared with the placebo. This effect was seen as early as 2-4 weeks after the participants started treatment.

To answer this question, the researchers:

• Measured the volume of air that the participants in the PATHWAY and NAVIGATOR studies could breathe out in 1 second

• Measured this after the participants were given study treatment for 1 year and compared it with the measurements at the beginning of the studies • Compared the average measurements for the participants who had tezepelumab with the average measurements for those who had the placebo For this measurement, the participants had to breathe forcefully into the mouthpiece of a machine called a spirometer. Given the inflammation of their airways, people with asthma can usually force a smaller volume of air out of their lungs than people without asthma. If people are able to force out more air from their lungs, it means that their asthma has likely improved.

For both studies, the information is shown for those participants who had available results and not for the total number of participants.

What were the most common health issues?

The main aim of the PATHWAY and NAVIGATOR studies was to find out how well tezepelumab worked for people with severe asthma, but the studies also looked at its safety.

The researchers kept track of all the health issues that the participants had during the studies. Any health issues that happen during studies are called adverse events. Adverse events may or may not be caused by the treatments in the studies. A lot of research is needed to know whether an adverse event is caused by a treatment.

What do the results of these studies mean for the patient community?

"As a long term sufferer of severe asthma, my history goes back to the 1980s/1990s, when I believe my asthma was probably at its height. I spent a large proportion of this era in hospital and in the intensive therapy unit. Unfortunately for me, oral corticosteroids were overused and biologic treatments were not yet readily available, if at all. If they were available, they were never offered as an option to me! At the present moment of my life, I am still a severe asthmatic, although not as bad as before, and biologic treatments, now well advanced, have been very difficult for me to access. The reason was, as has always been explained to me by my fabulous severe asthma team, that my eosinophil marker levels have never been raised enough to qualify me for any biologic treatment.

As has been well explained in this PLSP, the PATHWAY and NAVIGATOR studies have provided me with plenty of valuable insights and knowledge. Both studies have strived to present a clear and concise overview of the outcomes. All new treatments are accompanied by positive and negative aspects. Rightly so, this has to be highlighted, including the side effects. The PATHWAY and NAVIGATOR studies have provided not just myself, but I firmly believe will provide my long-suffering family as well, with a reassuring array of knowledge."

-A. McGuinness
Tezepelumab has been approved in several countries as an add-on treatment for people with severe asthma whose asthma is not well controlled with their current medications. The symptoms, attacks and inflammation are not the same for everyone with severe asthma. As tezepelumab works on a key first step in the body's chain reaction leading to inflammation, it is not limited to a particular type of asthma and is available for a broad population of people with severe asthma. This includes people who do not qualify for other biologic treatments because the number of eosinophils in their blood is low, meaning that they may not respond well to the treatments.

  The result is shown as the average change of this measurement after 1 year of study treatment. If this change is a positive number, it means that the volume of air that the participants could breathe out in 1 second increased over time after the start of study treatment. If the change is a negative number, it means that the volume of air that the participants could breathe out in 1 second decreased over time after the start of study treatment. The results are shown in the figure below.

Acknowledgements

AstraZeneca and Amgen Inc. would like to thank the clinical study participants and their family members and carers. They would also like to thank the investigators and staff at the study centers who cared for the participants in the clinical studies.

Financial & competing interests disclosure

Jonathan Corren, MD, has received grants and personal fees from AstraZeneca, Genentech and Vectura, and has received grants from Optinose, Sanofi and Teva Pharmaceuticals. Andrew Menzies-Gow, MD, Gun Almqvist, MSc, Karin Bowen, MSc, Janet M Griffiths, PhD, and Sandhia Ponnarambil, MD, are employees of AstraZeneca and may own stocks or stock options in AstraZeneca. Andrew Menzies-Gow, MD, has attended advisory board meetings for AstraZeneca, GlaxoSmithKline, Novartis, Regeneron Pharmaceuticals, Sanofi and Teva Pharmaceuticals; has received speaker fees from AstraZeneca, Novartis, Sanofi and Teva Pharmaceuticals; has participated in research with AstraZeneca, for which his institution has been remunerated; has attended international conferences with Teva Pharmaceuticals; and has consultancy agreements with AstraZeneca and Sanofi. Arnaud Bourdin, MD, has received grants from AstraZeneca, Boehringer Ingelheim, Cephalon/Teva Pharmaceuticals, GlaxoSmithKline, Novartis and Sanofi-Regeneron Pharmaceuticals; has provided consultancy for Actelion, AstraZeneca, Boehringer Ingelheim, Chiesi, GlaxoSmithKline, MedinCell, Merck, Novartis, Roche and Sanofi-Regeneron Pharmaceuticals; and has acted as an investigator or co-investigator for trials sponsored by Actelion, AstraZeneca, Boehringer Ingelheim, Chiesi, Galapagos, GlaxoSmithKline, Merck, Novartis, Roche, Sanofi-Regeneron Pharmaceuticals and Vertex. Elliot Israel, MD, has served as a consultant to and received personal fees from 4D Pharma, AB Science, Amgen, AstraZeneca, Avillion, Biometry, Cowen, Equillium, Genentech, GlaxoSmithKline, Merck, Novartis, Pneuma Respiratory, PPS Health, Regeneron Pharmaceuticals, Sanofi, Sienna Biopharmaceuticals and Teva Pharmaceuticals; has received non-financial support from Circassia, Teva Pharmaceuticals and Vorso Corp; and has received clinical research grants from AstraZeneca, Avillion, Genentech, Gossamer Bio, Novartis and Sanofi. Gene Colice, MD, was an employee of AstraZeneca at the time of the study. Christopher E Brightling, MD, FMedSci, is an asthma doctor in the UK and has received grants and consultancy fees from 4D Pharma, AstraZeneca, Chiesi, Genentech, GlaxoSmithKline, Mologic, Novartis, Regeneron Pharmaceuticals, Roche

Where can I find more information?

The original article 'Tezepelumab in adults with uncontrolled asthma' was published in The New England Journal of Medicine in 2017 (Corren J et al. N. Engl. J. Med. 377, 936-946 [2017]). You can read the full article for free at: https://www.nejm.org/doi/pdf/10.1056/NEJMoa1704064?articleTools=true

The original article 'Tezepelumab in adults and adolescents with severe, uncontrolled asthma' was published in The New England Journal of Medicine in 2021 (Menzies-Gow A et al. N. Engl. J. Med. 384, 1800-1809 [2021]). You can read the full article for free at: https://www.nejm.org/doi/pdf/10.1056/NEJMoa2034975?articleTools=true

An adverse event is considered to be serious when it is life-threatening, causes lasting problems or requires hospital care.

How many participants had adverse events?

How many participants had serious adverse events? What were the most common adverse events?

The figure below shows the adverse events that happened in at least 5% of the participants in any treatment group. There were other adverse events, but they happened in fewer participants.

What do the results of these studies mean overall?

The results of the PATHWAY and NAVIGATOR studies showed that the participants who had monthly doses of tezepelumab for 1 year had fewer severe asthma attacks and better lung function than the participants who had placebo. In both studies, the adverse events that the participants had were similar between the tezepelumab and placebo treatment groups.

Overall, the studies showed that tezepelumab worked in a broad population of people with severe asthma. It was well tolerated and had an acceptable safety profile after treatment for 1 year. These results led to the approval of tezepelumab for people with severe asthma who are Additional information on the PATHWAY and NAVIGATOR studies is available at: ClinicalTrials.gov (www.clinicaltrials.gov)type the NCT numbers below into the search bar.

• For the PATHWAY study: NCT02054130

• For the NAVIGATOR study: NCT03347279

EU clinical trials register (http://www.clinicaltrialsregister.eu/ctr-search/search)type the EudraCT number below into the search bar.

• For the NAVIGATOR study: 2017-003078-15


G J Molina-Cuberos

S Cardnell

O Witasse

A J García-Collado

S Toledo- Redondo

G Déprez

F Montmessin

and the EU H2020 project UPWARDS Electrical Properties of the Dust-Loaded Ionosphere of Mars

Introduction:

The electrical properties of the lower part of the Martian atmosphere and on the ground have a high importance for any surface mission and their deep understanding and knowledge are crucial to prepare future manned missions. The electrical conductivity and ground charge conditions, together the low atmospheric dynamics rule all the atmospheric electricity phenomena, such as large scale electric current, electric discharges and Schumann resonances.

Below 70 km, the main ionization sources are galactic cosmic rays and, during daytime, photoionization of aerosols due to solar UV radiation [1]. Several ionospheric models have been developed for both day and night conditions. The results predict that both positive and negative cluster ions are the most abundant near ground [2,3], which is similar to the terrestrial case. However, the presence of suspended dust can produce significant effects on the ion and electron densities [4]. In fact, the amount of dust can vary considerably and, therefore, it has an important effect.

The Model: The Martian ionosphere is modelled here by solving the continuity equations of positive ions, negative ions, electrons and charged aerosols [1]. Both positive ions and electrons are primary produced by cosmic rays and lost by ion-electron recombination and by attachment to aerosols. Therefore, aerosol particles can be positive or negative charged. Negative ions are produced by electron capture by oxygen (in the form of O, O 2 and O 3 ) and lost by ion-ion recombination and attachment to aerosols. During the daytime, aerosols can be charged also by photoionization (mainly UV radiation). Here we have followed the procedure described in Michael et al. [4] to calculate it. In the lower atmosphere of Mars transport phenomena can be neglected because the transport time is several orders of magnitude greater than the chemical lifetime [5]. The photoelectron production rate from aerosols was calculated by considering the attenuation of the solar flux through the atmosphere due to absorption and scattering of aerosols [1]. The attachment coefficient of electrons and ions to aerols was calculated using [6].

Results and Discussion: Figure 1 shows the cation, anion and electrons densities from 0 to 70 km for both low and high dust conditions. The model can be applied to different scenarios, and was tested for both day and nighttime conditions. We have made use of the Mars Climate Database (MCD) to obtain the meteorological variables corresponding to the expecting landing site of the ExoMars 2016 Schiaparelly module [7].

For the high dust scenario, the density of positive charges (cations) is not equals to that of negative charges (anions plus electrons), which means that same of the charge is accumulated on aerosols. The sign of the aerosol carge depends on the solar UV radiation. During nighttime, there are no photoelectrons emitted from aerosols and the attachment of electrons to aerosols is more effective than the attachment of positive ions because of the larger mobility of electrons. Therefore, aerosols tend to became negatively charged. During daytime, photoemission process outweighs electrons attachment and produces a net positive charge on the aerosols.

The daytime results obtained for the low dust scenario are similar to the ones obtained for aerosols-free models [3]. However, as the amount of dust increases, the density of electrons also increases, specially near the surface.

The total electric conductivity, as well as its positive and negative polar components are shown in Figure 2. The atmospheric conductivity varies in the 10 -13 -10 -7 S/m range, depending on the altitude, dust scenario and local time.

Once the atmospheric conductivity profile is modeled, it is possible to calculate the Schumann resonances, which are the standing waves oscillating in the electromagnetic cavity formed by the lower ionosphere and the conducting surface of the planet. Toledo-Redondo et al. [8] found that the first resonance should be in the range between 9 Hz and 16 Hz, depending on the dust scenario and the local time position of the source and the observer, owing to the strong day-night asymmetry of the cavity. Their simulation also shows that the daytime conductivity profile does not allow the development of Schuman resonances at all, while the conductivity of the nightside, which is two orders of magnitude lower, does.

Figure 1 :

 1 Figure 1: Cation (green lines), anion (blue lines) and electron (red lines) number densities for low and high dust scenarios during both day (solid lines) and nighttime (dashed lines) conditions [1].

Figure 2 .

 2 Figure 2. Polar and total electrical conductivity for different dust scenarios during day and nighttime conditions [1].

Workshop organized by ESA-ESAC & IAA-CSIC, with the support of the ESAC Faculty and the EU H2020 project UPWARDS

Acknowledgements: This work was supported by the Spanish Government (Project TEC2014-55463-C3-1-P) and by the European Commission (ERDF). O. Witasse and S. Cardnell acknowledge the ESA Young Graduate Trainee program.


Roupsard Olivier

Cournac Laurent

Orange Didier, Do Fredéric Jourdan Christophe

Faye Waly

Gaglo Espoir

Gabriela Demarchi

Sow Sidy

Agbohessou Yélognissè

Orange Didier

"Faidherbia-Flux": a collaborative observatory for Ecosystem Services and GHG in a semi-arid agro-silvo-pastoral system (Senegal)

come   L'archive ouverte pluridisciplinaire

"Faidherbia-Flux": a collaborative observatory for Ecosystem Services and GHG in a semi-arid agro-silvo-pastoral system (Senegal) Roupsard Olivier 1,2 , Cournac Laurent 1 , Jourdan Christophe 1,2 ,Orange Didier 1 , Do Fredéric 1 , Faye Waly 3 , Gaglo Espoir 3,2 , DeMarchi, Gabriela 2 , Sow Sidy 3,2 , Agbohessou Yélognissè 3,2 , Diatta Seydou 3,2 , Diouf Khalisse 3,2 , Ly Atoumane 3,2 , Tall Laure 3,2 , Clermont-Dauphin Cathy 1,2 , Sanou Josias 15 , Koala Jonas 15 , Audebert Alain 4,5 , Ndour Adama 4,5 , Faye Emile 6,3 , Taugourdeau Simon 7,3 , Sanogo Diaminatou 3 , Sall Saïdou 8 , Sokhna Sarr Mame 3 , Duthoit Maxime 1 Rocheteau Alain 1 , Arnal Didier 1,9 , Bouvery Fredéric 9 , Kergoat Laurent 10 , Timouk Franck 10 , Grippa Manuela 10 , Gangneron Fabrice 10 , Badiane Ndour Yacine 3 , Chapuis-Lardy Lydie 1,2 , Josiane Seghieri 1 , Masse Dominique 1 , Fleury Laurence 11 , Delaunay Valérie 11 , Montes Nicolas 11, Vezy Rémi 12 , Le Maire Guerric 1 , Rajot Jean-Louis 13 ; Pierre Caroline 13 , Vallée Martin 14 , Leroy Nicolas 14 , Chotte Jean-Luc 1 1Eco&Sols, Univ Montpellier, CIRAD, INRA, IRD, Montpellier; 2 LMI IESOL; 3 ISRA; 4 UMR AGAP; 5 CERAAS; 6 UR Hortsys; 7 UMR SELMET; 8 UGB; 9 INRA; 10 UMR GET; 11 LPED; 12 UMR AMAP, 13 iEES; 14 IPGB; 15 INERA Contact: olivier.roupsard@cirad.fr

(1) AGRAF/Faidherbia-Flux website: http://agraf.msem.univ-montp2.fr/Senegal.html Observatoire Population-Santé-Environnement de Niakhar: https://lped.info/wikiObsSN/?PresNiakhar Rationale: The ecosystem services provided by agro-silvo-pastoral systems are complex to assess or model, owing to high spatial and temporal heterogeneities. In 2018, we set up a new long-term observatory , open to collaboration, for the monitoring and modelling of ecosystem services, GHG, hydrology and deep SOC in a semi-arid agro-silvo-pastoral system (Niakhar, Sénégal). The system is dominated by the multipurpose and reverse phenology tree Faidherbia albida (Fa). Crops are mainly millet and peanut (annual rotation). Transhumant livestock contributes to manure (see Dry Season picture below), SOM and soil fertility and is fed by the tree fodder pruned at that time. The positive effect of Faidherbia on crop yield is under scrutiny (see Wet Season picture below, trees are defoliated). 3m) and (iii) peanut (3m) and monitored energy, CO 2 balance and evapotranspiration for one full year. The ecosystem displayed low but significant CO 2 and H 2 O fluxes during the dry season, owing to Faidherbia in leaf (Fig. 1). When rains resumed, the soil bursted a large amount of CO 2 . Just after the growth of millet, CO 2 uptake by photosynthesis increased dramatically, then stabilized before harvest. However, this was compensated by large ecosystem respiration. The annual ecosystem CO 2 balance was a slight C uptake. Millet yield was about 3 times higher below Fa than in full sun (Fig. 2). We noted higher soil humidity and SOC close to the Fa trunks.

We scanned the 1.24 ha millet plot with VHR drone flights in visible, multispectral and thermal IR bands at 5 dates. Drone images confirm higher yield below or close to Fa trees, with at least 30m of influence (semivariogram). A simple model based on NDVI allowed to draw a plot yield map (g m -2 ) and to estimate the plot yield within 15% of the actual plot harvest (Fig. 3) Deep roots & Hydraulic Redistributions: Six deep (8m) pits were dug down to the water table and equipped with automatic scanners and minirhizotrons to monitor the tree and crop root growth, according to soil depth and distance to trees. In parallel, 5 Fa trees (in a range of sizes) were equipped with 57 TTD sap flow systems in the trunk (azimuthal and radial sampling), the tap and lateral roots and 20 pairs of thermocouples for direction and zero flow assessment. The goal is to study hydraulic distributions, from the soil water table to the superficial layers and assess if trees uplift deep water and nutrients for the crops. In Fig. 4, nocturnal sap flows were not nil in the tap roots.

  Eddy Covariance for CO 2 , H 2 O and energy balances: Early 2018, we set up 3 eddy-covariance towers above (i) the whole mosaic ecosystem (20m), (ii) millet (

  collected 12 subplots of 15 millet holes each, distributed either below the crown of Faidherbia, at 2.5 x crown radius, or at 5 x crown radius.

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