Preventive, safety and control measures against Avian Influenza A(H5N1) in occupationally exposed groups: A scoping review

Introduction

During the outbreak of avian influenza, A (H5N1) (IA) in wild and domestic birds recorded in January 2023, the epidemiological alert has been extended due to its potential contagion to humans, particularly in those exposed occupational groups.

Objective

to identify the primary occupational risk groups, as well as the preventive, safety, and control measures against IA intended or implemented in these positions.

Material and methods

A systematic search was conducted in Pubmed, Scopus, Web of science, Scielo and literature databases. Scientific articles, normative documents, and technical reports identifying vulnerable occupational groups and preventive measures against IA were included. Two authors conducted a full-text review, extracting information independently, and findings were summarized narratively.

Results

A total of 5518 documents were identified, and 30 reports were included. 20% of the reports were published in 2023, 13/30 were affiliated to a university institution. Occupationally exposed groups were identified both directly and indirectly. 63.3% of reports identified breeders, poultry farmers and sellers as the most concerning occupational group, while 60% identified biosecurity practices (use of PPE, handwashing) as the primary measure against IA, followed by strategies such as education (training and capacity-building).

Conclusion

Occupational groups of interest were identified, primarily those involved in sales, commerce, and the handling of bird waste with potential exposure to IA. Furthermore, the maintenance of biosecurity measures, cleaning-disinfection practices, and educational strategies in workplace settings are recommended.

A systematic discussion and comparison of the construction methods of synthetic microbial community

Synthetic microbial community has widely concerned in the fields of agriculture, food and environment over the past few years. However, there is little consensus on the method to synthetic microbial community from construction to functional verification. Here, we review the concept, characteristics, history and applications of synthetic microbial community, summarizing several methods for synthetic microbial community construction, such as isolation culture, core microbiome mining, automated design, and gene editing. In addition, we also systematically summarized the design concepts, technological thresholds, and applicable scenarios of various construction methods, and highlighted their advantages and limitations. Ultimately, this review provides four efficient, detailed, easy-to-understand and -follow steps for synthetic microbial community construction, with major implications for agricultural practices, food production, and environmental governance.

Integrated methodology for gas content assessment and prediction in shallow muddy lake sediments: acoustic mapping and correlation analysis

This paper provides a step-by-step description of integrated methodology for quantification and prediction of gas (methane, CH4) content dynamics in shallow aquatic sediments under changing spatial and temporal conditions. Presence of gas bubbles even in small concentrations significantly affects sediment compressibility, which in turn decreases sound speed in sediment. Our integrated methodology consists of two basic steps. In the first step, free gas content is evaluated by acoustic applications based on the sound speed inferred from the reflection coefficient from gassy bottom. The experimental bottom reflections are registered and compared to the simulated ones, using a geoacoustic inversion technique. The best match between the model and the experiment provides sediment sound speed estimate, which is converted into free gas content using a basic relation. In the second step, a multivariate linear regression is fitted for gas content and closed form expression of gas content dependence on the following predictors, which change spatially and temporally over the aquatic ecosystem, is obtained: 1) water depth, 2) short-leaving CH4 production rate peaks fueled by punctuated organic matter deposition; and 3) CH4 bubble dissolution rates.•Gas content and sound speed in the sediment are estimated via the geoacoustic inversion technique by matching the experimentally recorded and simulated bottom reflections•Only single source and receiver are required for the acoustic methodology•A multivariate linear regression is fitted for gas content to indicate its dependence on various predictors that change spatially and temporally over the lake.

MiR-200b-3p elevates 5-FU sensitivity in cholangiocarcinoma cells via autophagy inhibition by targeting KLF4

Cholangiocarcinoma is one of the most lethal human cancers, and chemotherapy failure is a major cause of recurrence and poor prognosis. We previously demonstrated that miR-200 family members are downregulated in clinical samples of cholangiocarcinoma and inhibit cholangiocarcinoma tumorigenesis and metastasis. However, the role of differentially expressed miR-200b-3p in 5-fluorouracil chemosensitivity remains unclear. Here, we examined how miR-200b-3p modulates 5-fluorouracil chemosensitivity in cholangiocarcinoma. We observed that miR-200b-3p was associated with 5-fluorouracil sensitivity in cholangiocarcinoma and increased 5-fluorouracil-induced mitochondrial apoptosis in cholangiocarcinoma cells. Mechanistically, miR-200b-3p suppressed autophagy in cholangiocarcinoma cells to mediate 5-fluorouracil sensitivity. Further, we identified KLF4 as an essential target of miR-200b-3p in cholangiocarcinoma. Notably, the miR-200b-3p/KLF4/autophagy pathway augmented the chemosensitivity of cholangiocarcinoma cells to 5-fluorouracil. Our findings underscore the key role of miR-200b-3p in chemosensitivity to 5-fluorouracil and highlight the miR-200b-3p/KLF4/autophagy axis as a potential therapeutic target for cholangiocarcinoma.

Evaluation of miRNA-146a, miRNA-34a, and pro-inflammatory cytokines as a potential early indicators for type 1 diabetes mellitus

Background

Type I diabetes mellitus (T1DM) is one of the most common chronic autoimmune diseases worldwide. miRNAs are a class of small non-coding RNA molecules that have been linked to immune system functions, β-cell metabolism, proliferation, and death, all of which contribute to pathogenesis of TIDM. Dysregulated miRNAs have been identified in Egyptian TIDM patients.

Aim

Several miRNAs were profiled in Egyptian TIDM patients to determine whether they can be used as molecular biomarkers for T1DM. The relationship between the investigated miRNAs and pro-inflammatory cytokines (TNF-α and IL-6) has also been evaluated in the development of TIDM, in addition to the creation of a proposed model for TIDM prediction.

Patients & methods

Case-control study included 177 Egyptian patients with confirmed type I diabetes mellitus and 177 healthy individuals. MiRNA-34 and miRNA-146 were detected in serum samples using real-time PCR, whereas TNF-α and IL-6 levels were assessed using ELIZA.

Results

Patients with TIDM showed a significant decrease in the expression of miRNA-146, with a cut-off value ≤ 3.3, 48 % specificity, and 92.1 % sensitivity, whereas miRNA-34 had the highest sensitivity (95.5 %) and specificity (97.2 %) for differentiating diabetic patients from controls. Furthermore, other diagnostic proinflammatory markers showed lower sensitivity and specificity.

Conclusion

Serum levels of miRNA-34a, miRNA-146, IL-6, and TNF-α provide new insights into T1DM pathogenesis and could be used for screening and diagnosis purposes. They can be also a potential therapeutic target, as well as allowing for more strategies to improve T1DM disease outcomes.

Sustained descemetocele management with Prosthetic Replacement of the Ocular Surface Ecosystem (PROSE) treatment

Purpose

To report a case of a 67-year-old male who was successfully managed over a 7-year period for descemetocele secondary to ocular graft versus host disease (oGVHD) using Prosthetic Replacement of the Ocular Surface Ecosystem (PROSE) treatment.

Observations

We previously reported on a patient managed with a PROSE device for severe dry eyes secondary to oGVHD, who subsequently developed a central corneal descemetocele. The patient was deemed a poor surgical candidate due to limbal stem cell deficiency secondary to oGVHD. Therefore, we elected to closely monitor the descemetocele as the patient continued PROSE therapy. The patient's descemetocele has been managed successfully without perforation throughout a 7-year follow-up period with corrected distance visual acuity remaining stable at 20/50 in the affected eye.

Conclusions and importance

Descemetoceles are an uncommon complication of ocular graft versus host disease. This is the longest published report of a corneal descemetocele managed with PROSE. Our report suggests that in appropriate patients who are at high-risk for post-surgical complications, PROSE in conjunction with other medical management should be considered as an alternative to corneal transplantation.

A roadmap towards safe and sustainable by design nanotechnology: Implementation for nano-silver-based antimicrobial textile coatings production by ASINA project

This report demonstrates a case study within the ASINA project, aimed at instantiating a roadmap with quantitative metrics for Safe(r) and (more) Sustainable by Design (SSbD) options. We begin with a description of ASINA's methodology across the product lifecycle, outlining the quantitative elements within: Physical-Chemical Features (PCFs), Key Decision Factors (KDFs), and Key Performance Indicators (KPIs). Subsequently, we delve in a proposed decision support tool for implementing the SSbD objectives across various dimensions-functionality, cost, environment, and human health safety-within a broader European context. We then provide an overview of the technical processes involved, including design rationales, experimental procedures, and tools/models developed within ASINA in delivering nano-silver-based antimicrobial textile coatings. The result is pragmatic, actionable metrics intended to be estimated and assessed in future SSbD applications and to be adopted in a common SSbD roadmap aligned with the EU's Green Deal objectives. The methodological approach is transparently and thoroughly described to inform similar projects through the integration of KPIs into SSbD and foster data-driven decision-making. Specific results and project data are beyond this work's scope, which is to demonstrate the ASINA roadmap and thus foster SSbD-oriented innovation in nanotechnology.

Traditional Thai massage steps development in acute ischemic stroke patients

Stroke results in many survivors experiencing limb dysfunction and functional disability. Early rehabilitation has shown promise in improving recovery. Traditional Thai Massage (TTM) is noted for potential benefits in aiding stroke recovery. Chaophya Abhaibhubejhr Hospital in Thailand has integrated TTM in treating various diseases and has developed a specialized TTM protocol for acute stroke patients. We develop 23 unique Traditional Thai Massage Steps based on Chaophya Abhaibhubejhr Hospital Experience and assess the feasibility and safety of combining TTM steps with physical therapy (PT) in treating acute ischemic stroke compared to PT alone. 33 stroke patients were randomized into two groups: intervention (TTM + PT) and control (PT alone). The outcomes were improvements in daily living, quality of life, and acute stroke severity by using a modified Rankin Scale (mRS) score, Barthel index of activities of daily living (BI), National Institutes of Health Stroke Scale (NIHSS), and the Stroke Specific Quality Of Life scale (SS-QOL). Both groups significantly improved outcomes over the 20-day study. However, there were no significant differences between the two groups in these measures. Both groups also reported no adverse effects from the treatments.•The 23 unique Traditional Thai Massage Steps for acute ischemic stroke based on Chaophya Abhaibhubejhr Hospital Experience are developed.•TTM protocols for acute ischemic stroke are practical and approved by well-trained Traditional Thai Medicine Practitioners.•Although TTM protocols do not show additional benefits to conventional PT at day 20 after treatment, their combinations for patients with acute ischemic stroke appear safe and feasible.

Structure-based protein and small molecule generation using EGNN and diffusion models: A comprehensive review

Recent breakthroughs in deep learning have revolutionized protein sequence and structure prediction. These advancements are built on decades of protein design efforts, and are overcoming traditional time and cost limitations. Diffusion models, at the forefront of these innovations, significantly enhance design efficiency by automating knowledge acquisition. In the field of de novo protein design, the goal is to create entirely novel proteins with predetermined structures. Given the arbitrary positions of proteins in 3-D space, graph representations and their properties are widely used in protein generation studies. A critical requirement in protein modelling is maintaining spatial relationships under transformations (rotations, translations, and reflections). This property, known as equivariance, ensures that predicted protein characteristics adapt seamlessly to changes in orientation or position. Equivariant graph neural networks offer a solution to this challenge. By incorporating equivariant graph neural networks to learn the score of the probability density function in diffusion models, one can generate proteins with robust 3-D structural representations. This review examines the latest deep learning advancements, specifically focusing on frameworks that combine diffusion models with equivariant graph neural networks for protein generation.

Integration of single-nucleus and exosome RNA sequencing dissected inter-cellular communication and biomarkers in pancreatic ductal adenocarcinoma

Background

Mounting evidence underscores the importance of cell communication within the tumor microenvironment, which is pivotal in tumor proliferation, invasion, and metastasis. Exosomes play a crucial role in cell-to-cell communication. Although single-cell RNA sequencing (scRNA-seq) provides insights into individual cell transcriptional characteristics, it falls short of comprehensively capturing exosome-mediated intercellular communication.

Method

We analyzed Pancreatic Ductal Adenocarcinoma (PDAC) tissues, separating supernatant and precipitate for exosome purification and single-cell nucleus suspension. We then constructed Single-nucleus RNA sequencing (snRNA-seq) and small RNA-seq libraries from these components. Our bioinformatic analysis integrated these sequences with ligand-receptor analysis and public miRNA data to map the cell communication network.

Results

We established intercellular communication networks using bioinformatic analysis to track exosome miRNA effects and ligand-receptor pairs. Significantly, hsa-miR-1293 emerged as a prognostic biomarker for pancreatic cancer, linked to immune evasion, increased myeloid-derived suppressor cells, and poorer prognosis. Targeting this miRNA may enhance anti-tumor immunity and improve outcomes.

Conclusion

Our study offers a novel approach to constructing intercellular communication networks using snRNA-seq and exosome-small RNA sequencing. By integrating miRNA tracing with ligand-receptor analysis, we illuminate the complex interactions in the pancreatic cancer microenvironment, highlighting the pivotal role of miRNAs and identifying potential biomarkers and therapeutic targets.

A conceptual model of the nurse's role as primary palliative care provider in goals of care communication

Objective

Nurses have opportunities to engage in goals of care conversations that can promote palliative care communication. The purpose of this study was to describe nurses' experiences in goals of care communication as summarized in the literature and to present a conceptual model of communication pathways for nurses.

Methods

An integrative review of the literature (2016-2022) addressing nurses' experiences in goals of care communication was conducted using PubMed, CINAHL, and PsychInfo databases. A total of 92 articles were retrieved. A total of 12 articles were included for this review after applying the inclusion and exclusion criteria.

Results

Of the 12 articles, the majority were qualitative studies (n = 8). Qualitative analysis of findings from all articles revealed three dominant themes: nurses' ambiguous role responsibilities, goals of care as end-of-life communication, and the need for nurse communication training.

Conclusion

This article suggests an innovative conceptual model for advancing nurse communication about goals of care to facilitate primary palliative care.

Innovation

The framework characterizes two communication pathways for Advanced Practice Nurses who direct goals of care discussions and Registered Nurses who support goals of care communication. The model informs future communication training aimed at supporting primary palliative care.

The bidirectional association between diabetes and periodontitis, from basic to clinical

The prevalence and severity of periodontitis are increased and advanced in diabetes. Severe periodontitis elicits adverse effects on diabetes by impairing insulin actions due to systemic microinflammation. Recent studies unveil the emerging findings and molecular basis of the bidirectional relationship between periodontitis and diabetes. In addition to conventional mechanisms such as hyperglycemia, hyperlipidemia, and chronic inflammation, deficient insulin action may play a pathogenic role in the progression of periodontitis under diabetes. Epidemiologically, from the viewpoint of the adverse effect of periodontitis on diabetes, recent studies have suggested that Asians including Japanese and Asian Americans with diabetes and mild obesity (BMI <25 kg/m2) should pay more attention to their increased risk for cardiovascular diseases. In this review, we summarize recent findings on the effect of diabetes on periodontitis from the viewpoint of abnormalities in metabolism and insulin resistance with novel mechanisms, and the influence of periodontitis on diabetes mainly focused on micro-inflammation related to mature adipose tissue and discuss future perspectives about novel approaches to interrupt the adverse interrelationship.

Enhancing Mass spectrometry-based tumor immunopeptide identification: machine learning filter leveraging HLA binding affinity, aliphatic index and retention time deviation

Accurately identifying neoantigens is crucial for developing effective cancer vaccines and improving tumor immunotherapy. Mass spectrometry-based immunopeptidomics has emerged as a promising approach to identifying human leukocyte antigen (HLA) peptides presented on the surface of cancer cells, but false-positive identifications remain a significant challenge. In this study, liquid chromatography-tandem mass spectrometry-based proteomics and next-generation sequencing were utilized to identify HLA-presenting neoantigenic peptides resulting from non-synonymous single nucleotide variations in tumor tissues from 18 patients with renal cell carcinoma or pancreatic cancer. Machine learning was utilized to evaluate Mascot identifications through the prediction of MS/MS spectral consistency, and four descriptors for each candidate sequence: the max Mascot ion score, predicted HLA binding affinity, aliphatic index and retention time deviation, were selected as important features in filtering out identifications with inadequate fragmentation consistency. This suggests that incorporating rescoring filters based on peptide physicochemical characteristics could enhance the identification rate of MS-based immunopeptidomics compared to the traditional Mascot approach predominantly used for proteomics, indicating the potential for optimizing neoantigen identification pipelines as well as clinical applications.

Are circadian rhythms in disarray in patients with chronic critical illness?

Aim

The aim of our study is to assess circadian rhythms in patients with chronic critical illness due to severe brain injury in intensive care unit by establishing the relation between melatonin and cortisol secretion, considering astronomical time and the sleep-wake cycle in chronic critical illness.

Materials and methods

The study included 54 adult patients with chronic critical illness who resided in the intensive care unit for at least 30 days. The level of consciousness was determined using the CRS-R scale. We did the continuous electroencephalographic (EEG) monitoring with polygraphic leads for 24 h. Also, we determined the serum levels of cortisol and melatonin using the tandem mass spectrometry method with ultra-performance liquid chromatography.

Results

90.74 % of patients had one acrophase in melatonin secretion curve, which suggests the preservation of the rhythmic secretion of melatonin. These acrophases of the melatonin rhythm occurred during the night time in 91.8 % of patients. Most of the patients (69.3 %) slept during the period from 2:00 to 4:00 a.m. The evening levels of cortisol and melatonin had an inverse relation (rs=0.61, p<0.05), i.e., a decrease in the level of cortisol secretion accompanies an increase in melatonin.

Conclusions

We concluded from our study that the rhythmic secretion of melatonin and cortisol is preserved in patients with chronic critical illness that resulted from severe brain injury. No statistically significant discrepancy between melatonin and cortisol secretion, day-and-night time and the sleep-wake cycle are found. We may focus our future work on finding more reliable methods to stabilize the preservation of circadian rhythms to protect vital organ functions.

Privacy-preserving federated machine learning on FAIR health data: A real-world application

Objective

This paper introduces a privacy-preserving federated machine learning (ML) architecture built upon Findable, Accessible, Interoperable, and Reusable (FAIR) health data. It aims to devise an architecture for executing classification algorithms in a federated manner, enabling collaborative model-building among health data owners without sharing their datasets.

Materials and methods

Utilizing an agent-based architecture, a privacy-preserving federated ML algorithm was developed to create a global predictive model from various local models. This involved formally defining the algorithm in two steps: data preparation and federated model training on FAIR health data and constructing the architecture with multiple components facilitating algorithm execution. The solution was validated by five healthcare organizations using their specific health datasets.

Results

Five organizations transformed their datasets into Health Level 7 Fast Healthcare Interoperability Resources via a common FAIRification workflow and software set, thereby generating FAIR datasets. Each organization deployed a Federated ML Agent within its secure network, connected to a cloud-based Federated ML Manager. System testing was conducted on a use case aiming to predict 30-day readmission risk for chronic obstructive pulmonary disease patients and the federated model achieved an accuracy rate of 87%.

Discussion

The paper demonstrated a practical application of privacy-preserving federated ML among five distinct healthcare entities, highlighting the value of FAIR health data in machine learning when utilized in a federated manner that ensures privacy protection without sharing data.

Conclusion

This solution effectively leverages FAIR datasets from multiple healthcare organizations for federated ML while safeguarding sensitive health datasets, meeting legislative privacy and security requirements.

Cyclodextrins: Establishing building blocks for AI-driven drug design by determining affinity constants in silico

Cyclodextrins (CDs) are cyclic carbohydrate polymers that hold significant promise for drug delivery and industrial applications. Their effectiveness depends on their ability to encapsulate target molecules with strong affinity and specificity, but quantifying affinities in these systems accurately is challenging for a variety of reasons. Computational methods represent an exceptional complement to in vitro assays because they can be employed for existing and hypothetical molecules, providing high resolution structures in addition to a mechanistic, dynamic, kinetic, and thermodynamic characterization. Here, we employ potential of mean force (PMF) calculations obtained from guided metadynamics simulations to characterize the 1:1 inclusion complexes between four different modified βCDs, with different type, number, and location of substitutions, and two sterol molecules (cholesterol and 7-ketocholesterol). Our methods, validated for reproducibility through four independent repeated simulations per system and different post processing techniques, offer new insights into the formation and stability of CD-sterol inclusion complexes. A systematic distinct orientation preference where the sterol tail projects from the CD's larger face and significant impacts of CD substitutions on binding are observed. Notably, sampling only the CD cavity's wide face during simulations yielded comparable binding energies to full-cavity sampling, but in less time and with reduced statistical uncertainty, suggesting a more efficient approach. Bridging computational methods with complex molecular interactions, our research enables predictive CD designs for diverse applications. Moreover, the high reproducibility, sensitivity, and cost-effectiveness of the studied methods pave the way for extensive studies of massive CD-ligand combinations, enabling AI algorithm training and automated molecular design.

Level of self-efficacy among skill-based allied health students in the University of Santo Tomas-Enriched Virtual Mode of learning: A cross-sectional study

Background

Self-efficacy expresses a learner's perception of how well they can do in the online academic setting. Although students' academic successes can be measured by online learning self-efficacy, there is a scarcity of evidence targeted toward allied health students.

Objective

The primary aim of this study is to determine the level of online self-efficacy among students from skill-based allied health programs. The secondary aim is to correlate online self-efficacy with age, sex, year level, and program of the students.

Methods

This cross-sectional analytic study utilized the Online Learning Self-Efficacy Scale (OLSE) to determine students' level of self-efficacy via a survey conducted with students who underwent the Enriched Virtual Mode of learning. Descriptive statistics was used to characterize the study participants, describe the level of self-efficacy, and compare the subscales of OLSE. Inferential statistics using Spearman's rho was performed to determine the correlation.

Results

A total of 117 respondents with a mean age ± SD of 20.59 ± 0.11 years old, predominantly female (71%) were included in the study. The students from allied health programs had an online self-efficacy overall mean score of 3.83 (SD = 0 . 05 ; range 2.64-5.00) with the use of technology subscales weighted the highest mean score (4.24). Females have a higher average OLSE score (M = 3 . 92 , SD = 0 . 05 ) compared to males. Significant correlation was found between OLSE scores to sex (r = 0 . 260 , p = 0 . 005 ) and year level (r =- 0 . 199 , p = 0 . 031 ) while nonsignificant correlation was found between OLSE scores to the program (r =- 0 . 048 , p = 0 . 604 ) and age (r =- 0 . 123 , p = 0 . 185 ).

Conclusion

Students of allied health programs generally have a very good level of online self-efficacy. This study assists educators in developing proactive strategies and approaches to promote students' self-confidence across all domains and encourage them to adopt a dynamic remote learning-based approach. Educational institutions should use this opportunity to assess how well they have implemented remote learning to ensure educational continuity, especially in times of crisis.

Human umbilical cord mesenchymal stem cells protect MC3T3-E1 osteoblasts from dexamethasone-induced apoptosis via induction of the Nrf2-ARE signaling pathway

Objective

To investigate the protective effect human umbilical cord mesenchymal stem cells (hUC-MSCs) have on Dexamethasone (Dex)-induced apoptosis in osteogenesis via the Nrf2-ARE signaling pathway.

Methods

Glucocorticoid-induced osteonecrosis of the femoral head (GC-ONFH) was developed in rats through the administration of lipopolysaccharide and methylprednisolone. The incidence of femoral head necrosis, cavity notch, apoptosis of osteoblasts, and bone density were observed by HE staining, TUNEL staining, and Micro-CT. HUC-MSCs were co-cultured with mouse pre-osteoblast MC3T3-E1. The survival rate of osteoblasts was determined by CCK8, and apoptosis and ROS levels of osteoblasts were determined by flow cytometer. The viability of antioxidant enzymes SOD, GSH-Px, and CAT was analyzed by biochemistry. Nrf2 expression levels and those of its downstream proteins and apoptosis-related proteins were analyzed by Western blotting.

Results

In rats, hUC-MSCs can reduce the rates of empty bone lacuna and osteoblast apoptosis that are induced by glucocorticoids (GCs), while reducing the incidence of GC-ONFH. hUC-MSCs can significantly improve the survival rate and antioxidant SOD, GSH-Px, and CAT activity of MC3T3-E1 cells caused by Dex, and inhibit apoptosis and oxidative stress levels. In addition, hUC-MSCs can up-regulate the expression of osteoblast antioxidant protein Nrf2 and its downstream protein HO-1, NQO-1, GCLC, GCLM, and apoptosis-related protein bcl-2, while also down-regulating the expression of apoptosis-related protein bax, cleaved caspase-3, cleaved caspase-9, and cytochrome C in MC3T3-E1 cells. hUC-MSCs improve the ability of MC3T3-E1 cells to mineralize to osteogenesis. However, the promoting effects of hUC-MSCs were abolished following the blocking of the Nrf2-ARE signaling pathway for osteoblasts.

Conclusion

The results reveal that hUC-MSCs can reduce Dex-induced apoptosis in osteoblasts via the Nrf2-ARE signaling pathway.

A generative benchmark for evaluating the performance of fluorescent cell image segmentation

Fluorescent cell imaging technology is fundamental in life science research, offering a rich source of image data crucial for understanding cell spatial positioning, differentiation, and decision-making mechanisms. As the volume of this data expands, precise image analysis becomes increasingly critical. Cell segmentation, a key analysis step, significantly influences quantitative analysis outcomes. However, selecting the most effective segmentation method is challenging, hindered by existing evaluation methods' inaccuracies, lack of graded evaluation, and narrow assessment scope. Addressing this, we developed a novel framework with two modules: StyleGAN2-based contour generation and Pix2PixHD-based image rendering, producing diverse, graded-density cell images. Using this dataset, we evaluated three leading cell segmentation methods: DeepCell, CellProfiler, and CellPose. Our comprehensive comparison revealed CellProfiler's superior accuracy in segmenting cytoplasm and nuclei. Our framework diversifies cell image data generation and systematically addresses evaluation challenges in cell segmentation technologies, establishing a solid foundation for advancing research and applications in cell image analysis.

Health literacy & Chagas disease knowledge: A cross-sectional study in Southern Loja Province, Ecuador

Objective

Health literacy is associated with many patient outcomes. This study sought to determine the association between a person's level of health literacy and their knowledge about Chagas disease.

Methods

A cross-sectional survey was conducted with people living in two counties in rural Loja Province, Ecuador who attended a mobile health clinic. The communities in which the study was conducted are at high risk of Chagas disease and have limited access to both health care and educational resources. The Spanish version of Short Assessment for Health Literacy measured health literacy. The Chagas Disease Knowledge questionnaire measured knowledge of Chagas disease. T-tests and correlational analysis were used to assess associations.

Results

Overall 85 people participated in this study. A majority of the respondents were female (64.1%), and a plurality were married (40.7%) and had education less than secondary (40.7%). The average age of the sample was 44.31 ± 18.85. Health literacy levels and Chagas disease knowledge in the communities were low. About half of people had inadequate health literacy. No association between health literacy and Chagas knowledge was found.

Conclusion

Health literacy levels and Chagas disease knowledge were not found to be correlated. Explanations for the lack of association may include common causes of inadequate investment in Chagas disease education as well as neglect of health systems in rural Ecuador. Efforts to improve both health literacy and Chagas disease knowledge in poorer, rural areas of Ecuador are needed.

Innovation

This is the first study to assess relationships between health literacy and knowledge of Chagas disease in an uninfected population. For novel conditions, relationships between health literacy and disease knowledge should be investigated before communication campaigns are adapted.

Atlas 2022 of African health Statistics: Key results towards achieving the health-related SDGs targets

Introduction

The Atlas 2022 of African Health Statistics is a comprehensive tool that gives an overview of the health ecosystem in the African region. As such, it tracks progress towards globally agreed objectives, such as Sustainable Development Goals (SDGs), assesses the capacity of African countries to achieve them, and helps policymakers identify gaps and areas requiring substantial reinforcement.

Methods

We analyzed health-related SDGs' key indicators in the Atlas 2022 of African Health Statistics. This platform is a nexus for consistent and comparable data sources across countries. A review of studies addressing the evolution of health-related SDG indicators in Africa was also considered for discussion and recommendations.

Results

Hunger and different forms of malnutrition remain prevalent in the Region. Maternal and neonatal mortality is still high compared to other regions, with increasing incidences of non-communicable diseases and poor mechanisms to address mental health issues. Many inequalities are noted in violence against women, access to health services, or access to water and basic sanitation, which is exacerbated in rural areas. Regarding achieving the SDGs, the trend of most indicators shows they will be challenging to perform at the Regional level. However, a few countries are on track to achieve some goals. These results clearly show that countries have different experiences and, therefore, different progress in achieving sustainable development goals. The delays experienced by many countries in terms of development in other sectors, such as climate and the environment, poverty reduction and economic growth, equity and justice, etc., will make it even more difficult to achieve the health-related SDGs. Achieving these goals should, therefore, be seen as a transdisciplinary and inclusive process.

Conclusion

Beyond the COVID-19 pandemic that has recently challenged health systems worldwide, the African Region is also dealing with several threats, jeopardizing its progress toward achieving the SDGs by 2030. Given the Region's particular context, a readjustment of the regional targets and/or deadlines would be advisable to ensure they are achievable.

The LysR family transcriptional regulator ORF-L16 regulates spinosad biosynthesis in Saccharopolyspora spinosa

Spinosad, a potent broad-spectrum bioinsecticide produced by Saccharopolyspora spinosa, has significant market potential. Despite its effectiveness, the regulatory mechanisms of spinosad biosynthesis remain unclear. Our investigation identified the crucial role of the LysR family transcriptional regulator ORF-L16, located upstream of spinosad biosynthetic genes, in spinosad biosynthesis. Through reverse transcription PCR (RT-PCR) and 5'-rapid amplification of cDNA ends (5'-Race), we unveiled that the spinosad biosynthetic gene cluster (BGC) contains six transcription units and seven promoters. Electrophoretic mobility shift assays (EMSAs) demonstrated that ORF-L16 bound to seven promoters within the spinosad BGC, indicating its involvement in regulating spinosad biosynthesis. Notably, deletion of ORF-L16 led to a drastic reduction in spinosad production from 1818.73 mg/L to 1.69 mg/L, accompanied by decreased transcription levels of spinosad biosynthetic genes, confirming its positive regulatory function. Additionally, isothermal titration calorimetry (ITC) and EMSA confirmed that spinosyn A, the main product of the spinosad BGC, served as an effector of ORF-L16. Specifically, it decreased the binding affinity between ORF-L16 and spinosad BGC promoters, thus exerting negative feedback regulation on spinosad biosynthesis. This research enhances our comprehension of spinosad biosynthesis regulation and lays the groundwork for future investigations on transcriptional regulators in S. spinosa.

Disturbance of the human gut microbiota in patients with Myotonic Dystrophy type 1

Myotonic dystrophy type 1 (DM1) is a rare autosomal dominant genetic disorder. Although DM1 is primarily characterized by progressive muscular weakness, it exhibits many multisystemic manifestations, such as cognitive deficits, cardiac conduction abnormalities, and cataracts, as well as endocrine and reproductive issues. Additionally, the gastrointestinal (GI) tract is frequently affected, encompassing the entire digestive tract. However, the underlying causes of these GI symptoms remain uncertain, whether it is biomechanical problems of the intestine, involvement of bacterial communities, or both. The primary objective of this study is to investigate the structural changes in the gut microbiome of DM1 patients. To achieve this purpose, 35 patients with DM1 were recruited from the DM-Scope registry of the neuromuscular clinic in the Saguenay-Lac-St-Jean region of the province of Québec, Canada. Stool samples from these 35 patients, including 15 paired samples with family members living with them as controls, were collected. Subsequently, these samples were sequenced by 16S MiSeq and were analyzed with DADA2 to generate taxonomic signatures. Our analysis revealed that the DM1 status correlated with changes in gut bacterial community. Notably, there were differences in the relative abundance of Bacteroidota, Euryarchaeota, Fusobacteriota, and Cyanobacteria Phyla compared to healthy controls. However, no significant shift in gut microbiome community structure was observed between DM1 phenotypes. These findings provide valuable insights into how the gut bacterial community, in conjunction with biomechanical factors, could potentially influence the gastrointestinal tract of DM1 patients.

The optimal metric for viral genome space

Understanding the structural similarity between genomes is pivotal in classification and phylogenetic analysis. As the number of known genomes rockets, alignment-free methods have gained considerable attention. Among these methods, the natural vector method stands out as it represents sequences as vectors using statistical moments, enabling effective clustering based on families in biological taxonomy. However, determining an optimal metric that combines different elements in natural vectors remains challenging due to the absence of a rigorous theoretical framework for weighting different k-mers and orders. In this study, we address this challenge by transforming the determination of optimal weights into an optimization problem and resolving it through gradient-based techniques. Our experimental results underscore the substantial improvement in classification accuracy achieved by employing these optimal weights, reaching an impressive 92.73% on the testing set, surpassing other alignment-free methods. On one hand, our method offers an outstanding metric for virus classification, and on the other hand, it provides valuable insights into feature integration within alignment-free methods.

Agreement and disagreement in pediatric functional neurological symptom disorders: Comparing patient reported outcome measures (PROMs) and clinician assessments

Youth with functional neurological symptom disorder (FNSD) often perceive themselves as having limited capabilities, which may not align with clinical evaluations. This study assessed the disparities between clinician evaluations and patient-reported outcome measures (PROMs) regarding pain, motor function, and learning difficulties in youth with FNSD. Sixty-two youths with FNSD participated in this study, all of whom reported experiencing pain, motor problems, and/or learning difficulties. Clinicians also assessed these domains, resulting in a two-by-two categorization matrix: (1) agreement: child and clinician report "problems"; (2) agreement: child and clinician report "no problems"; (3) disagreement: child reports "problems" while the clinician does not; and (4) disagreement: clinician reports "problems" while the child does not. Agreement/disagreement differences were analyzed. No significant differences in prevalence were observed between the evaluators regarding pain (clinician-85%, child-88%), motor (clinician-98%, child-95%), or learning problems (clinician-69%, child-61%). More than 80% of the children and clinicians report pain and motor disorders. Instances in which children and clinicians reported learning problems (40.3%) exceeded cases in which both reported no problems (9.6%) or only the child reported problems (20.9%). Overall, the agreement between pain and motor function assessments was high (>90%), whereas that concerning learning difficulties was moderate (49.9%). Disagreement in pain/motor assessments was minimal (<5%), whereas for learning difficulties, disagreement rates were high (>20%). In conclusion, a significant concordance exists between PROMs and clinician assessments of pain and motor problems. However, the higher frequency of disagreements regarding learning difficulties emphasizes the importance of incorporating patient and clinician evaluations in pediatric FNSD treatment.