AnnoSpat annotates cell types and quantifies cellular arrangements from spatial proteomics.

Cellular composition and anatomical organization influence normal and aberrant organ functions. Emerging spatial single-cell proteomic assays such as Image Mass Cytometry (IMC) and Co-Detection by Indexing (CODEX) have facilitated the study of cellular composition and organization by enabling high-throughput measurement of cells and their localization directly in intact tissues. However, annotation of cell types and quantification of their relative localization in tissues remain challenging. To address these unmet needs for atlas-scale datasets like Human Pancreas Analysis Program (HPAP), we develop AnnoSpat (Annotator and Spatial Pattern Finder) that uses neural network and point process algorithms to automatically identify cell types and quantify cell-cell proximity relationships. Our study of data from IMC and CODEX shows the higher performance of AnnoSpat in rapid and accurate annotation of cell types compared to alternative approaches. Moreover, the application of AnnoSpat to type 1 diabetic, non-diabetic autoantibody-positive, and non-diabetic organ donor cohorts recapitulates known islet pathobiology and shows differential dynamics of pancreatic polypeptide (PP) cell abundance and CD8+ T cells infiltration in islets during type 1 diabetes progression.

Immunopathogenesis of multiple sclerosis: molecular and cellular mechanisms and new immunotherapeutic approaches.

Background: Multiple sclerosis (MS) is a central nervous system (CNS) demyelinating autoimmune disease with increasing global prevalence. It predominantly affects females, especially those of European descent. The interplay between environmental factors and genetic predisposition plays a crucial role in MS etiopathogenesis.Methods: We searched recent relevant literature on reputable databases, which include, PubMed, Embase, Web of Science, Scopus, and ScienceDirect using the following keywords: multiple sclerosis, pathogenesis, autoimmunity, demyelination, therapy, and immunotherapy.Results: Various animal models have been employed to investigate the MS etiopathogenesis and therapeutics. Autoreactive T cells within the CNS recruit myeloid cells through chemokine expression, leading to the secretion of inflammatory cytokines driving the MS pathogenesis, resulting in demyelination, gliosis, and axonal loss. Key players include T cell lymphocytes (CD4+ and CD8+), B cells, and neutrophils. Signaling dysregulation in inflammatory pathways and the immunogenetic basis of MS are essential considerations for any successful therapy to MS. Data indicates that B cells and neutrophils also have significant roles in MS, despite the common belief that T cells are essential. High neutrophil-to-lymphocyte ratios correlate with MS severity, indicating their contribution to disease progression. Dysregulated signaling pathways further exacerbate MS progression.Conclusion: MS remains incurable, but disease-modifying therapies, monoclonal antibodies, and immunomodulatory drugs offer hope for patients. Research on the immunogenetics and immunoregulatory functions of gut microbiota is continuing to provide light on possible treatment avenues. Understanding the complex interplay between genetic predisposition, environmental factors, and immune dysregulation is critical for developing effective treatments for MS.

A practical guide to cross-cultural and multi-sited data collection in the biological and behavioural sciences.

Researchers in the biological and behavioural sciences are increasingly conducting collaborative, multi-sited projects to address how phenomena vary across ecologies. These types of projects, however, pose additional workflow challenges beyond those typically encountered in single-sited projects. Through specific attention to cross-cultural research projects, we highlight four key aspects of multi-sited projects that must be considered during the design phase to ensure success: (1) project and team management; (2) protocol and instrument development; (3) data management and documentation; and (4) equitable and collaborative practices. Our recommendations are supported by examples from our experiences collaborating on the Evolutionary Demography of Religion project, a mixed-methods project collecting data across five countries in collaboration with research partners in each host country. To existing discourse, we contribute new recommendations around team and project management, introduce practical recommendations for exploring the validity of instruments through qualitative techniques during piloting, highlight the importance of good documentation at all steps of the project, and demonstrate how data management workflows can be strengthened through open science practices. While this project was rooted in cross-cultural human behavioural ecology and evolutionary anthropology, lessons learned from this project are applicable to multi-sited research across the biological and behavioural sciences.

Women's subsistence strategies predict fertility across cultures, but context matters.

While it is commonly assumed that farmers have higher, and foragers lower, fertility compared to populations practicing other forms of subsistence, robust supportive evidence is lacking. We tested whether subsistence activities-incorporating market integration-are associated with fertility in 10,250 women from 27 small-scale societies and found considerable variation in fertility. This variation did not align with group-level subsistence typologies. Societies labeled as "farmers" did not have higher fertility than others, while "foragers" did not have lower fertility. However, at the individual level, we found strong evidence that fertility was positively associated with farming and moderate evidence of a negative relationship between foraging and fertility. Markers of market integration were strongly negatively correlated with fertility. Despite strong cross-cultural evidence, these relationships were not consistent in all populations, highlighting the importance of the socioecological context, which likely influences the diverse mechanisms driving the relationship between fertility and subsistence.

Secretome-based acellular therapy of bone marrow-derived mesenchymal stem cells in degenerative and immunological disorders: A narrative review.

The bone marrow (BM) plays a pivotal role in homeostasis by supporting hematopoiesis and immune cells' activation, maturation, interaction, and deployment. "BMSC-derived secretome" refers to the complete repertoire of secreted molecules, including nucleic acids, chemokines, growth factors, cytokines, and lipids from BM-derived mesenchymal stem cells (BMSCs). BMSC-derived secretomes are the current molecular platform for acellular therapy. Secretomes are highly manipulable and can be synthesised in vast quantities using commercially accessible cell lines in the laboratory. Secretomes are less likely to elicit an immunological response because they contain fewer surface proteins. Moreover, the delivery of BMSC-derived secretomes has been shown in numerous studies to be an effective, cell-free therapy method for alleviating the symptoms of inflammatory and degenerative diseases. As a result, secretome delivery from BMSCs has the same therapeutic effects as BMSCs transplantation but may have fewer adverse effects. Additionally, BMSCs' secretome has therapeutic promise for organoids and parabiosis studies. This review focuses on recent advances in secretome-based cell-free therapy, including its manipulation, isolation, characterisation, and delivery systems. The diverse bioactive molecules of secretomes that successfully treat inflammatory and degenerative diseases of the musculoskeletal, cardiovascular, nervous, respiratory, reproductive, gastrointestinal, and anti-ageing systems were also examined in this review. However, secretome-based therapy has some unfavourable side effects that may restrict its uses. Some of the adverse effects of this modal therapy were briefly mentioned in this review.

Preeclampsia and eclampsia-specific maternal mortality in Bangladesh: Levels, trends, timing, and care-seeking practices.

Background: Despite improvements in many health indicators, maternal mortality has plateaued in Bangladesh. Achieving the global target of reductions in maternal mortality and the associated Sustainable Development Goals will not be possible without actions to prevent deaths due to preeclampsia/eclampsia. Here we examined the levels, trends, specific causes, timing, place, and care-seeking behaviours of women who died due to these two causes. Methods: We used nationally representative Bangladesh Maternal Mortality and Health Care Surveys (BMMSs) conducted in 2001, 2010, and 2016 to examine levels and trends of deaths due to preeclampsia/eclampsia. We based the analysis of specific causes, timing, and place of preeclampsia/eclampsia deaths, and care seeking before the deaths on 41 such deaths captured in the 2016 survey. We also used BMMS 2016 survey verbal autopsy (VA) questionnaire to highlight stories that put faces to the numbers. Results: The preeclampsia/eclampsia-specific mortality ratio decreased from 77 per 100 000 live births in the 2001 BMMS to 40 per 100 000 live births in the 2010 BMMS, yet halted in the 2016 BMMS at 46 per 100 000 live births. Although preeclampsia/eclampsia accounted for around one-fifth of all maternal deaths in the 2010 BMMS, in the 2016 BMMS, the percentage contribution reached the 2001 BMMS level of 24%. An analysis of the VA questionnaire's open section showed that almost all such death cases left their homes to seek care; however, most had to visit more than one facility before they died, indicating an unprepared health system. Conclusions: A cluster of preeclampsia/eclampsia-specific mortality observed during the first trimester, during delivery, and within 48 hours of birth indicates a need for preconception health check-ups and strengthened facility readiness. Awareness of maternal complications, proper care seeking, and healthy reproductive practices, like family planning to space and limit pregnancy through client-supportive counselling, may be beneficial. Improving regular and emergency maternal services readiness is also essential.

Reproductive inequality in humans and other mammals.

To address claims of human exceptionalism, we determine where humans fit within the greater mammalian distribution of reproductive inequality. We show that humans exhibit lower reproductive skew (i.e., inequality in the number of surviving offspring) among males and smaller sex differences in reproductive skew than most other mammals, while nevertheless falling within the mammalian range. Additionally, female reproductive skew is higher in polygynous human populations than in polygynous nonhumans mammals on average. This patterning of skew can be attributed in part to the prevalence of monogamy in humans compared to the predominance of polygyny in nonhuman mammals, to the limited degree of polygyny in the human societies that practice it, and to the importance of unequally held rival resources to women's fitness. The muted reproductive inequality observed in humans appears to be linked to several unusual characteristics of our species-including high levels of cooperation among males, high dependence on unequally held rival resources, complementarities between maternal and paternal investment, as well as social and legal institutions that enforce monogamous norms.

Levels, trends, causes, place and time of, care-seeking for, and barriers in preventing indirect maternal deaths in Bangladesh: An analysis of national-level household surveys.

Background: Eclampsia, haemorrhage, and other direct causes are the primary burden of maternal mortality in Bangladesh, often reducing attention given to indirect maternal deaths (IMDs). However, Sustainable Development Goals may not be achieved without actions to prevent IMDs. We examined the levels, trends, specific causes, timing, place, and care-seeking, and explored the barriers to IMD prevention. Methods: We used three nationally representative surveys conducted in 2001, 2010, and 2016 to examine levels and trends in IMDs. The analysis of specific causes, timing, and place of IMDs, and care-seeking before the deaths was based on 37 IMDs captured in the 2016 survey. Finally, we used thematic content analysis of the open history from the 2016 survey verbal autopsy (VA) questionnaire to explore barriers to IMD prevention. Results: After increasing from 51 deaths per 100 000 live births in 2001 to 71 in 2010, the indirect maternal mortality ratio (IMMR) dropped to 38 deaths per 100 000 live births in 2016. In 2016, the indirect causes shared one-fifth of the maternal deaths in Bangladesh. Stroke, cancer, heart disease, and asthma accounted for 80% of the IMDs. IMDs were concentrated in the first trimester of pregnancy (27%) and day 8-42 after delivery (32%). Public health facilities were the main places for care-seeking (48%) and death (49%). Thirty-four (92%) women who died from IMDs sought care from a health facility at least once during their terminal illness. However, most women experienced at least one of the "three delays" of health care. Other barriers were financial insolvency, care-seeking from unqualified providers, lack of health counselling, and the tendency of health facilities to avoid responsibilities. Conclusions: IMMR remained unchanged at a high level during the last two decades. The high concentration of IMDs in pregnancy and the large share due to chronic health conditions indicate the need for preconception health check-ups. Awareness of maternal complications, proper care-seeking, and healthy reproductive practices may benefit. Improving regular and emergency maternal service readiness is essential.

Economic impacts and nutritional outcomes of the 2017 floods in Bangladeshi Shodagor fishing families.

OBJECTIVES: As climate change continues to increase the frequency and severity of flooding in Bangladesh and globally, it becomes increasingly critical to understand the pathways through which flooding influences health outcomes, particularly in lower-income and subsistence-based communities. We aim to assess economic pathways that link flooding to nutritional outcomes among Shodagor fishing families in Bangladesh. METHODS: We examine longitudinal economic data on kilograms of fish caught, the income earned from those fish, and household food expenditures (as a proxy for dietary intake) from before, during, and after severe flooding in August-September of 2017 to enumerate the impacts of flooding on Shodagor economics and nutrition. We also analyze seasonally collected anthropometric data to model the effects of flooding and household food expenditures on child growth rates and changes to adult body size. RESULTS: While Shodagor fishing income declined during the 2017 flooding, food expenditures simultaneously spiked with market inflation, and rice became the predominant expenditure only during and immediately following the flood. Our nutritional models show that children and adults lost more body mass in households that spent more money on rice during the flood. Shodagor children lost an average of 0.36 BMI-for-age z-scores and adults lost an average of 0.32 BMI units during the flooded 2017 rainy season, and these metrics continued to decline across subsequent seasons and did not recover by the end of the study period in 2019. CONCLUSIONS: These results show major flood-induced economic impacts that contributed to loss of child and adult body mass among Shodagor fishing families in Bangladesh. More frequent and severe flooding will exacerbate these nutritional insults, and more work is needed to effectively stabilize household nutrition throughout natural disasters and economic hardship.

Isolation and In Silico Prediction of Potential Drug-like Compounds with a New Dimeric Prenylated Quinolone Alkaloid from Zanthoxylum rhetsa (Roxb.) Root Extracts Targeted against SARS-CoV-2 (Mpro).

A new dimeric prenylated quinolone alkaloid, named 2,11-didemethoxy-vepridimerine A, was isolated from the root bark of Zanthoxylum rhetsa, together with twelve known compounds. The structure of the new compound was elucidated on the basis of spectroscopic investigations (NMR and Mass). The interaction of the isolated compounds with the main protease of SARS-CoV-2 (Mpro) was evaluated using molecular docking followed by MD simulations. The result suggests that 2,11-didemethoxy-vepridimerine A, the new compound, has the highest negative binding affinity against the Mpro with a free energy of binding of -8.5 Kcal/mol, indicating interaction with the Mpro. This interaction was further validated by 100 ns MD simulation. This implies that the isolated new compound, which can be employed as a lead compound for an Mpro-targeting drug discovery program, may be able to block the action of Mpro.

Interleukin-6 cytokine: An overview of the immune regulation, immune dysregulation, and therapeutic approach.

Several studies have shown that interleukin 6 (IL-6) is a multifunctional cytokine with both pro-inflammatory and anti-inflammatory activity, depending on the immune response context. Macrophages are among several cells that secrete IL-6, which they express upon activation by antigens, subsequently inducing fever and production of acute-phase proteins from the liver. Moreover, IL-6 induces the final maturation of B cells into memory B cells and plasma cells as well as an adaptive role for short-term energy allocation. Activation of IL-6 receptors results in the intracellular activation of the JAK/STAT pathway with resultant production of inflammatory cytokines. Several mechanisms-controlled IL-6 expression, but aberrant production was shown to be crucial in the pathogenesis of many diseases, which include autoimmune and chronic inflammatory diseases. IL-6 in combination with transforming growth factor ß (TGF-ß) induced differentiation of naïve T cells to Th17 cells, which is the cornerstone in autoimmune diseases. Recently, IL-6 secretion was shown to form the backbone of hypercytokinemia seen in the Coronavirus disease 2019 (COVID-19)-associated hyperinflammation and multiorgan failure. There are two classes of approved IL-6 inhibitors: anti-IL-6 receptor monoclonal antibodies (e.g., tocilizumab) and anti-IL-6 monoclonal antibodies (i.e., siltuximab). These drugs have been evaluated in patients with rheumatoid arthritis, juvenile idiopathic arthritis, cytokine release syndrome, and COVID-19 who have systemic inflammation. JAK/STAT pathway blockers were also successfully used in dampening IL-6 signal transduction. A better understanding of different mechanisms that modulate IL-6 expression will provide the much-needed solution with excellent safety and efficacy profiles for the treatment of autoimmune and inflammatory diseases in which IL-6 derives their pathogenesis.

Deep neural network for detecting arbitrary precision peptide features through attention based segmentation.

A promising technique of discovering disease biomarkers is to measure the relative protein abundance in multiple biofluid samples through liquid chromatography with tandem mass spectrometry (LC-MS/MS) based quantitative proteomics. The key step involves peptide feature detection in the LC-MS map, along with its charge and intensity. Existing heuristic algorithms suffer from inaccurate parameters and human errors. As a solution, we propose PointIso, the first point cloud based arbitrary-precision deep learning network to address this problem. It consists of attention based scanning step for segmenting the multi-isotopic pattern of 3D peptide features along with the charge, and a sequence classification step for grouping those isotopes into potential peptide features. PointIso achieves 98% detection of high-quality MS/MS identified peptide features in a benchmark dataset. Next, the model is adapted for handling the additional 'ion mobility' dimension and achieves 4% higher detection than existing algorithms on the human proteome dataset. Besides contributing to the proteomics study, our novel segmentation technique should serve the general object detection domain as well.

Cancer related knowledge, attitude, and practice among community health care providers and health assistants in rural Bangladesh.

BACKGROUND: Cancer remains one of the primary causes of death in Bangladesh. The success of cancer control in rural areas depends on the ability of the health care system and workforce to identify and manage cases properly at early stages. Community Health Workers (CHW) can play a vital role in this process. The present study aims to assess cancer related Knowledge, Attitude, and Practice (KAP) among 2 categories of CHWs - Community Health Care Providers (CHCP) and Health Assistants (HA) in rural Bangladesh. METHODS: A descriptive cross-sectional study was conducted using a self-administered questionnaire from July 2019 to June 2020. Multi-stage sampling technique was used to determine the sample. One Upazilla Health Complex (UHC) from each of the eight administrative divisions of Bangladesh were randomly chosen as study sites, from which 325 CHCPs and HAs were in the final sample. Multivariate logistic regression models were developed to determine the association between KAP scores and demographic variables. RESULTS: Our study shows that a modest number of respondents scored above average in the knowledge (54.15%), attitude (58.15%), and practice (65.54%) sections. Majority CHCPs (90.91%) and HAs (96.06%) did not receive govt. training on cancer. Only 20.71% HAs and 25.2% CHCPs knew about the availability of cancer treatment options in Bangladesh. Uncertainty about the availability of relevant treatments or vaccinations at public facilities was also high. Having cancer in the family, income, duration of employment and workplace locations were important predictors of cancer related KAP scores. CONCLUSION: Healthcare workforce's knowledge gap and unfavorable attitude towards cancer may result in poor delivery of care at the rural level. For many people in rural areas, CHCPs and HAs are the first point of contact with the healthcare system and thus effective cancer control strategies must consider them as key stakeholders. Targeted training programs must be adopted to address the cancer related KAP gaps among CHCPs and HAs.

DeepIso: A Deep Learning Model for Peptide Feature Detection from LC-MS map.

Liquid chromatography with tandem mass spectrometry (LC-MS/MS) based quantitative proteomics provides the relative different protein abundance in healthy and disease-afflicted patients, which offers the information for molecular interactions, signaling pathways, and biomarker identification to serve the drug discovery and clinical research. Typical analysis workflow begins with the peptide feature detection and intensity calculation from LC-MS map. We are the first to propose a deep learning based model, DeepIso, that combines recent advances in Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) to detect peptide features of different charge states, as well as, estimate their intensity. Existing tools are designed with limited engineered features and domain-specific parameters, which are hardly updated despite a huge amount of new coming proteomic data. On the other hand, DeepIso consisting of two separate deep learning based modules, learns multiple levels of representation of high dimensional data itself through many layers of neurons, and adaptable to newly acquired data. The peptide feature list reported by our model matches with 97.43% of high quality MS/MS identifications in a benchmark dataset, which is higher than the matching produced by several widely used tools. Our results demonstrate that novel deep learning tools are desirable to advance the state-of-the-art in protein identification and quantification.

Application of consensus string matching in the diagnosis of allelic heterogeneity involving transposition mutation.

In this paper, an algorithm is proposed that detects the existence of a common ancestor gene sequence for non-overlapping transposition metric given two input DNA sequences. We consider two cases: fixed length transposition and all length transposition. For the first one, the algorithm has the time complexity of O(n3), where n is the length of input sequences. In case of all length transposition, theoretical worst case time complexity of the algorithm is proven to be O(n4). However, practically the worst case and the average case time complexity for all length transposition are found to be O(n3) and O(n2) respectively. This work is motivated by the purpose of diagnosing unknown genetic disease that shows allelic heterogeneity, a case where a normal gene mutates in different orders resulting in two different gene sequences causing two different genetic diseases. The algorithm can be useful as well in the study of breed-related hereditary to determine the genetic spread of a defective gene in the population.