Frequency of diminished ovarian reserve in women with multiple sclerosis in Chile: An exploratory study.

INTRODUCTION: Multiple Sclerosis (MS) is a chronic disease affecting around 2.8 million people worldwide. Two-thirds are women, and the mean age at diagnosis is about 30 years old. Social trends are moving towards older age at first pregnancy, both in women with and without MS. OBJECTIVES: To determine the frequency of diminished ovarian reserve (DOR) through anti-Mullerian Hormone (AMH) measurement in women with MS at fertile age and Healthy Females (HF) in Chile. METHODS: Case-control, multicentric, cross-sectional study including relapsing-remitting people with MS (pwMS) between 18 and 40 years and sex and age-matched HF. We obtained a blood sample to determine AMH levels. We defined DOR as AMH <1.5 ng/mL and very-low AMH levels as <0.5 ng/mL. Also, we performed questions regarding reproductive decision-making. RESULTS: We included 79 sex and age-matched HF and 92 pwMS, median age 32(19-40) years, median disease duration 6 (1-17)years, median EDSS 1.0 (0-6), 95% were receiving disease-modifying therapy (DMT), 70% high-efficacy DMT and 37% with a treatment that contraindicates pregnancy. DOR was observed in 24% (n = 22) of the pwMS, compared to 14% (n = 11) of the HF (p = 0.09), while very-low AMH levels were observed in 7.6% (n = 7) of pwMS and none of the HF (p = 0.0166). We observed an inverse correlation between age and AMH levels. Age was the only significant risk factor for low AMH levels in pwMS (OR 1.14 95%CI(1.00-1-31), p = 0.04), including smoking, body mass index (BMI), hormonal contraception, autoimmune comorbidity, high/low-moderate efficacy DMT, and active disease as covariables. We did not find statistically significant differences in age at diagnosis, BMI, disease duration, EDSS, autoimmune comorbidity, use of hormonal contraception, or percentage of active disease between MS women with normal vs DOR. Over 70% of pwMS desired to become pregnant in the future, while 60% considered that the diagnosis of MS was a limitation for pregnancy planning. CONCLUSIONS: No differences in DOR, measured by levels of AMH, were observed between pwMS MS and HF in Chile. As expected, AMH levels were correlated only with ageing. This information may be evaluated early during the disease course to help patients and neurologists with fertility counselling and family planning considerations regarding DMT use.

PLANTdataHUB: a collaborative platform for continuous FAIR data sharing in plant research.

In modern reproducible, hypothesis-driven plant research, scientists are increasingly relying on research data management (RDM) services and infrastructures to streamline the processes of collecting, processing, sharing, and archiving research data. FAIR (i.e., findable, accessible, interoperable, and reusable) research data play a pivotal role in enabling the integration of interdisciplinary knowledge and facilitating the comparison and synthesis of a wide range of analytical findings. The PLANTdataHUB offers a solution that realizes RDM of scientific (meta)data as evolving collections of files in a directory - yielding FAIR digital objects called ARCs - with tools that enable scientists to plan, communicate, collaborate, publish, and reuse data on the same platform while gaining continuous quality control insights. The centralized platform is scalable from personal use to global communities and provides advanced federation capabilities for institutions that prefer to host their own satellite instances. This approach borrows many concepts from software development and adapts them to fit the challenges of the field of modern plant science undergoing digital transformation. The PLANTdataHUB supports researchers in each stage of a scientific project with adaptable continuous quality control insights, from the early planning phase to data publication. The central live instance of PLANTdataHUB is accessible at (https://git.nfdi4plants.org), and it will continue to evolve as a community-driven and dynamic resource that serves the needs of contemporary plant science.

Competition co-immunoprecipitation reveals the interactors of the chloroplast CPN60 chaperonin machinery.

The functionality of all metabolic processes in chloroplasts depends on a balanced integration of nuclear- and chloroplast-encoded polypeptides into the plastid's proteome. The chloroplast chaperonin machinery is an essential player in chloroplast protein folding under ambient and stressful conditions, with a more intricate structure and subunit composition compared to the orthologous GroEL/ES chaperonin of Escherichia coli. However, its exact role in chloroplasts remains obscure, mainly because of very limited knowledge about the interactors. We employed the competition immunoprecipitation method for the identification of the chaperonin's interactors in Chlamydomonas reinhardtii. Co-immunoprecipitation of the target complex in the presence of increasing amounts of isotope-labelled competitor epitope and subsequent mass spectrometry analysis specifically allowed to distinguish true interactors from unspecifically co-precipitated proteins. Besides known substrates such as RbcL and the expected complex partners, we revealed numerous new interactors with high confidence. Proteins that qualify as putative substrate proteins differ from bulk chloroplast proteins by a higher content of beta-sheets, lower alpha-helical conformation and increased aggregation propensity. Immunoprecipitations targeted against a subunit of the co-chaperonin lid revealed the ClpP protease as a specific partner complex, pointing to a close collaboration of these machineries to maintain protein homeostasis in the chloroplast.

Software Training in HEP.

The long-term sustainability of the high-energy physics (HEP) research software ecosystem is essential to the field. With new facilities and upgrades coming online throughout the 2020s, this will only become increasingly important. Meeting the sustainability challenge requires a workforce with a combination of HEP domain knowledge and advanced software skills. The required software skills fall into three broad groups. The first is fundamental and generic software engineering (e.g., Unix, version control, C++, and continuous integration). The second is knowledge of domain-specific HEP packages and practices (e.g., the ROOT data format and analysis framework). The third is more advanced knowledge involving specialized techniques, including parallel programming, machine learning and data science tools, and techniques to maintain software projects at all scales. This paper discusses the collective software training program in HEP led by the HEP Software Foundation (HSF) and the Institute for Research and Innovation in Software in HEP (IRIS-HEP). The program equips participants with an array of software skills that serve as ingredients for the solution of HEP computing challenges. Beyond serving the community by ensuring that members are able to pursue research goals, the program serves individuals by providing intellectual capital and transferable skills important to careers in the realm of software and computing, inside or outside HEP.

Scalable Declarative HEP Analysis Workflows for Containerised Compute Clouds.

We describe a novel approach for experimental High-Energy Physics (HEP) data analyses that is centred around the declarative rather than imperative paradigm when describing analysis computational tasks. The analysis process can be structured in the form of a Directed Acyclic Graph (DAG), where each graph vertex represents a unit of computation with its inputs and outputs, and the graph edges describe the interconnection of various computational steps. We have developed REANA, a platform for reproducible data analyses, that supports several such DAG workflow specifications. The REANA platform parses the analysis workflow and dispatches its computational steps to various supported computing backends (Kubernetes, HTCondor, Slurm). The focus on declarative rather than imperative programming enables researchers to concentrate on the problem domain at hand without having to think about implementation details such as scalable job orchestration. The declarative programming approach is further exemplified by a multi-level job cascading paradigm that was implemented in the Yadage workflow specification language. We present two recent LHC particle physics analyses, ATLAS searches for dark matter and CMS jet energy correction pipelines, where the declarative approach was successfully applied. We argue that the declarative approach to data analyses, combined with recent advancements in container technology, facilitates the portability of computational data analyses to various compute backends, enhancing the reproducibility and the knowledge preservation behind particle physics data analyses.

Identification of small RNAs during cold acclimation in Arabidopsis thaliana.

BACKGROUND: Cold stress causes dynamic changes in gene expression that are partially caused by small non-coding RNAs since they regulate protein coding transcripts and act in epigenetic gene silencing pathways. Thus, a detailed analysis of transcriptional changes of small RNAs (sRNAs) belonging to all known sRNA classes such as microRNAs (miRNA) and small interfering RNA (siRNAs) in response to cold contributes to an understanding of cold-related transcriptome changes. RESULT: We subjected A. thaliana plants to cold acclimation conditions (4 °C) and analyzed the sRNA transcriptomes after 3 h, 6 h and 2 d. We found 93 cold responsive differentially expressed miRNAs and only 14 of these were previously shown to be cold responsive. We performed miRNA target prediction for all differentially expressed miRNAs and a GO analysis revealed the overrepresentation of miRNA-targeted transcripts that code for proteins acting in transcriptional regulation. We also identified a large number of differentially expressed cis- and trans-nat-siRNAs, as well as sRNAs that are derived from long non-coding RNAs. By combining the results of sRNA and mRNA profiling with miRNA target predictions and publicly available information on transcription factors, we reconstructed a cold-specific, miRNA and transcription factor dependent gene regulatory network. We verified the validity of links in the network by testing its ability to predict target gene expression under cold acclimation. CONCLUSION: In A. thaliana, miRNAs and sRNAs derived from cis- and trans-NAT gene pairs and sRNAs derived from lncRNAs play an important role in regulating gene expression in cold acclimation conditions. This study provides a fundamental database to deepen our knowledge and understanding of regulatory networks in cold acclimation.

Effects of population- and seed bank size fluctuations on neutral evolution and efficacy of natural selection.

Population genetics models typically consider a fixed population size and a unique selection coefficient. However, population dynamics inherently generate fluctuations in numbers of individuals and selection acts on various components of the individuals' fitness. In plant species with seed banks, the size of both the above- and below-ground compartments induce fluctuations depending on seed production and the state of the seed bank. We investigate if this fluctuation has consequences on (1) the rate of genetic drift, and (2) the efficacy of selection. We consider four variants of two-allele Moran-type models defined by combinations of presence and absence of fluctuations in the population size in above-ground and seed bank compartments. Time scale analysis and dimension reduction methods allow us to reduce the corresponding Fokker-Planck equations to one-dimensional diffusion approximations of a Moran model. We first show that if the fluctuations of above-ground population size classically affect the rate of genetic drift, fluctuations of below-ground population size reduce the diversity storage effect of the seed bank. Second, we consider that selection can act on four different components of the plant fitness: plant or seed death rate, seed production or seed germination. Our striking result is that the efficacy of selection for seed death rate or germination rate is reduced by fluctuations in the seed bank size, whereas selection occurring on plant death rate or seed production is not affected. We derive the expected site-frequency spectrum reflecting this heterogeneity in selection efficacy between genes underpinning different plant fitness components. Our results highlight the importance to consider the effect of ecological noise to predict the impact of seed banks on neutral and selective evolution.