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Demographic, social and health system factors associated with maternal mortality in Pakistan: A nested case-control study

Background Pakistan has experienced a significant reduction in maternal mortality with a decline of 33 percent between 2006 and 2019. However, the country still grapples with a high number (186 per 100,000 live births) of maternal deaths each year. This study aims to identify socio-demographic and health system related factors associated with maternal mortality. Methods Using the nested case-control design, we conducted an in-depth analysis of Pakistan Maternal Mortality Survey (PMMS) 2019. We identified 147 maternal deaths occurring within three years prior to the PMMS 2019 as “cases” and 724 women who gave birth and were alive during the same period as “controls”. Socio-demographic characteristics of cases and controls were compared, and multivariate regression was employed to investigate the predictors of maternal mortality in Pakistan. Results Cases and controls were similar on access to antenatal care (ANC) and ANC provider but differed on age, education, number of pregnancies, type of delivery, tetanus toxoid vaccination during last pregnancy, and contraceptive usage. A higher proportion of cases had deliveries by skilled birth attendants (83% compared to 63% among controls) while home deliveries were more common among controls (32% compared to 25% among cases). Odds of maternal death were lowest among women aged 20–29 years (odds ratio–OR: 0.5; 95% CI 0.23–1.07) and those with secondary or higher education (OR: 0.35; 95% CI 0.17–0.74). Surprisingly, deliveries attended by skilled birth attendants were associated with higher odds of maternal death (OR: 4.07; 95% CI 2.19–7.57) compared to those who were not. Conclusion This study identifies secondary or higher maternal education, having had tetanus injection during the last pregnancy, ever-used contraception or being in the age group of 20–29 years were factors associated with lower risk of maternal mortality. Conversely, skilled birth attendance increases the risk of maternal death in Pakistan. Further investigation is needed into the determinants of high maternal mortality.

Effects of maximum dose on local control after stereotactic body radiotherapy for oligometastatic tumors of colorectal cancer

This study aimed to identify radiotherapy dosimetric parameters related to local failure (LF)-free survival (LFFS) in patients with lung and liver oligometastases from colorectal cancer treated with stereotactic body radiotherapy (SBRT). We analyzed 75 oligometastatic lesions in 55 patients treated with SBRT between January 2014 and December 2021. There was no constraint or intentional increase in maximum dose. LF was defined as the progression of the treated lesion until the last follow-up or death. The dose distributions were recalculated using Monte Carlo-based algorithms. The significance of the planning target volume (PTV) biologically effective dose (BED) 10s (D2, D95, D98, Dmean) in LFFS was evaluated using Cox regression, considering sex, age, primary cancer, tumor site, oligometastatic status, multiplicity, and either tumor size or one of the volume parameters. LF occurred in 23.4% of the lesions. Lesions showing LF received significantly lower PTV D2 (146 ± 21 vs. 164 ± 23, p = 0.006). Multivariate analysis revealed that PTV D2 (< 159 Gy10 vs. ≥ 159 Gy10) was the sole dosimetric parameter associated with LFFS. Tumors equal to or larger than the median size/volume yet receiving < 159 Gy10 of PTV D2 showed the lowest LFFS following stratification by median PTV D2 combined with tumor size or volume parameters. The maximum dose (PTV D2) was significantly associated with LFFS after SBRT for lung and liver oligometastases from colorectal cancer. Increasing the maximum dose may be beneficial for managing larger tumors.

The influence of workload on muscle fatigue, tissue properties, and postural stability in older and younger workers

Demographic aging and extended working lives have prompted interest in the physiological changes that occur with age, particularly in the lumbar spine. Age-related declines in muscle quality and intervertebral disc alterations may reduce muscular endurance, strength, and postural stability, potentially increasing the risk of musculoskeletal injuries in older workers. As experienced workers play an important role in addressing labor shortages, understanding the impact of age-related physiological changes on the biomechanical properties of the lumbar spine is key to ensure safe and sustainable employment for aging individuals. This study aimed to compare the impact of daily work-related physical efforts on lumbar muscular endurance and fatigue, spine tissue properties, and postural stability between older and younger workers. A total of 40 participants, 20 in Group 1 (young workers: ≤50 years; mean age: 28.89 ± 7.23) and 20 in Group 2 (older workers: >50 years; mean age: 59.40 ± 5.29) were recruited. Measurements taken at the beginning and end of the workday included lumbar muscle endurance, maximal voluntary contraction, disc height and postural stability. Age groups were compared using repeated measures ANOVA across the two measurement times. No significant interaction between age and time of day was observed, indicating that, for similar workload, both age groups experienced similar changes. Despite age-related effects on maximal force production and postural stability, incorporating weight as a covariate revealed that these differences were partially explained by the weight discrepancy between older and younger workers. The study suggests that age may not be the primary determinant of the impact of a workday on older workers.

How the nursing work environment moderates the relationship between clinical judgment and person-centered care among intensive care unit nurses

Background Person-centered care focuses on individualized care that respects patients’ values, preferences, and autonomy. To enhance the quality of critical care nursing, institutions need to identify the factors influencing ICU nurses’ ability to provide person-centered care. This study explored the relationship between clinical judgment ability and person-centered care among intensive care unit (ICU) nurses, emphasizing how the ICU nursing work environment moderates this relation. Methods A cross-sectional survey was conducted between September 4 and September 18, 2023, with 192 ICU nurses recruited from four general hospitals with a convenience sample (valid response rate = 97.4%). Participants completed online self-report structured questionnaires. The collected data were analyzed using hierarchical multiple regression and PROCESS macro Model 1, with a 95% bias-corrected bootstrap confidence interval to verify moderating effects. Results Clinical judgment ability (β = .24, p < .001) and ICU nursing work environment (β = .50 p < .001) were found to be significant predictors of person-centered care. These two predictors explained the 47.0% of person-centered care in the final hierarchical regression model. Additionally, Clinical judgment (B = 0.28, p < .001, Boot. 95%CI = 0.13~0.42) and the ICU nursing work environment (B = 0.41, p < .001, Boot. 95%CI = 0.30~0.52) positively affected person-centered care, and the interaction term of clinical judgment and ICU nursing work environment (B = 0.16, p = .026, Boot. 95%CI = 0.02~0.30) also positively affected person-centered care. The moderating effect was particularly significant when the ICU nursing work environment score was 2.90 points (below 14.6%, above 85.4%) or higher on a scale of 1–5 and As the ICU nursing work environment score increased, the positive moderating effect also increased. Conclusions The ICU nurses’ clinical judgment ability positively affected person-centered care, and the nursing work environment moderated the relationship between clinical judgment ability and person-centered care. Therefore, strategies for enhancing person-centered care among ICU nurses should focus on developing educational programs to improve clinical judgment ability and implementing comprehensive efforts to effectively improve and manage the nursing work environment.

Factors associated with contracting border malaria: A systematic and meta-analysis

Vector resistance, human population movement, and cross-border malaria continue to pose a threat to the attainment of malaria elimination goals. Border malaria is prominent in border regions characterised by poor access to health services, remoteness, and vector abundance. Human socio-economic behaviour, vectoral behaviour, access and use of protective methods, age, sex, and occupation have been identified in non-border regions as key predictors for malaria. We conducted a systematic and meta-analysis review to characterise and establish pooled effect sizes of the factors associated with the occurrence of border malaria. An exhaustive search was done in EBSCOHost (Medline Full Text), Health Source, Google Scholar, Regional Office for Africa Library, African Index Medicus, and PubMed databases. A total of 847 articles were identified from the search and after screening for quality and eligibility, twelve (12) articles were included in the review. Pooled odds ratios, inverse variance statistic (I2), Luis Furuya-Kanamori (LFK) index, and forest plot were computed. Findings from this study suggest night outdoor activities (POR 2.87 95% CI, 1.17 7,01), engaging in forestry activities (POR 2.76 95% CI, 2.08 3.67), working in mines (POR 197 95% CI, 175 22171), access to poor housing structure (POR 3.42 95% CI, 2.14 5.46), and cross-border movement (POR 50.86 95% CI, 12.88 200.85) none use of insecticide-treated nets (POR 5.09 95% CI, 2.44 10.63) were all significantly associated with contracting malaria within border regions. The use of insecticide-treated nets (ITN) (POR 0.61 95% CI, 0.50 0.76) and indoor residual spraying (IRS) (POR 0.61 95% CI, 0.47 0.79) were protective. Risk factors for border malaria are comparable to non-border malaria. Effective border malaria control requires an integrated and targeted approach that addresses socio-economic, environmental, and behavioural drivers. Established vector control interventions remain protective and should be sustained to mitigate the border malaria burden effectively. Novel strategies should be developed to address the unique challenge of cross-border human population movement underpinned by robust regional, bilateral, and multi-sectoral collaborative initiatives.

Factors influencing fans’ spectating experience and configuration effects in CBA league

The low satisfaction of fans’ spectator experience, the weak willingness to continue to watch games have become the realistic barriers limiting the sustained and favorable development of Chinese Basketball Association league (CBA League). Using Structural Equation Modeling (SEM) and Fuzzy-set Qualitative Comparative Analysis (fsQCA), this study clarifies the complex causal relationship behind the phenomenon of fans’ spectator experience, explore the linkage mechanism between different influencing factors of spectator experience. Also constructs a variety of grouping paths to enhance the fans’ spectator experience in the CBA League. The results shows that Sense, Feel, Think, Act, Relate and Spectator Service all positively affect the satisfaction of the live Spectator experience in the CBA League. Among six influencing factors, none of them is the necessary condition for high satisfaction of Fans’ Spectator Experience. In this way, the characteristics of multi-factors and different paths of the live Spectator experience were verified. Influential factors were coupled to form six grouping paths for high satisfaction of the fans’ spectator experience, which were categorized into two types of configurations by combining the grouping characteristics: 1) Led by spectator service, feel and act experience co-driven, 2) Spectator service and think experience co-driven. The findings provide theoretical guidance for enhancing fan experience and meeting the practical needs of cultivating loyal CBA fan groups while expanding the league’s influence.

Perceived racial discrimination, resilience, and oral health behaviours of adolescents with immigrant backgrounds

Introduction Unmet oral health needs remain a significant issue among immigrant adolescents, often exacerbated by experiences of racial discrimination. This study aimed to examine the associations between perceived discrimination and oral health behaviours in adolescents with immigrant backgrounds and explore the potential moderating role of resilience on this association. Methods Ethical approval for this cross-sectional study was obtained from the University of Alberta Research Ethics Board. Participants were 12 to 18-year-old adolescents from immigrant backgrounds. Participants were recruited through nine community organizations using a snowball sampling technique. After obtaining active parental consent and assent from the adolescent, the participants completed a questionnaire covering demographics, oral health behaviours, and perceived racial discrimination and resilience. Perceived racial discrimination and resilience were measured using validated scales. Descriptive statistics summarized variables. Logistic regression assessed associations, controlling for confounding factors. Resilience’s moderating impact was analyzed via the interaction model of regression analysis. Results In this cross-sectional study of 316 participants, average age of 15.3 (SD = 1.9) years, and a median age of 15 years (Inter Quartile Range-12-18), 76% reported discrimination experiences. Adjusted analysis showed that an increase of one unit in the total discrimination distress score was associated with 51% less likelihood of categorizing self-rated oral health as good (OR = 0.49, 95% CI: 0.29–0.81). The odds of brushing teeth more than twice a day, as opposed to once a day, decreased by 58% with one unit increase in the total discrimination distress score (OR = 0.42, 95% CI: 0.25–0.71). The odds of visiting the dentist for an urgent procedure instead of a regular check-up were 2.3 times higher with a unit increase in the total discrimination distress score (OR = 2.3: 95% CI:1.3–4.0) Resilience did not moderate the observed association. Conclusion Perceived racial discrimination was associated with the pattern for dental attendance, tooth brushing frequency, and self-rated oral health. Resilience did not moderate the observed association.

PtpA protein from Mycobacterium avium subsp. paratuberculosis as a potential marker of rheumatoid arthritis in humans

Studies have noted the connection between Mycobacterium avium subspecies paratuberculosis (MAP) and autoimmunity. MAP is an intracellular pathogen that infects and multiplies in macrophages. To overcome the hostile environment elicited by the macrophage, MAP secretes a battery of virulence factors to neutralize the toxic effects of the macrophage. One of the virulence factors is the Protein Tyrosine Phosphatase A (PtpA), a protein secreted by MAP that interferes in the phago-lysosome fusion, rendering the pathogen unnoticed in the cytoplasm of the macrophage. This study aimed to assess the presence of PtpA antibodies in the sera of Mexican individuals with rheumatoid arthritis (RA) and investigate its possible use as a biomarker for disease activity. We compared RA patients (n = 100) to control subjects (CS) (n = 100) by assessing specific immune responses to PtpA (the antigen) by an indirect ELISA method. Results showed a significant difference in PtpA levels between RA and CS, with RA patients having a median OD of 0.4645 compared to 0.1372 in CS. Antibodies against PtpA were present in 95% of RA patients and 16% of CS (AUC = 0.9163, p = 0.0001). Male control subjects showed higher PtpA reactivity than female CS. The Disease Activity Score (DAS-28) analysis showed that individuals with moderate to high disease activity had lower levels of PtpA reactivity. The results suggest a potential connection between RA and MAP infection.

Clonal phylogenies inferred from bulk, single cell, and spatial transcriptomic analysis of epithelial cancers

Epithelial cancers are typically heterogeneous with primary prostate cancer being a typical example of histological and genomic variation. Prior studies of primary prostate cancer tumour genetics revealed extensive inter and intra-patient genomic tumour heterogeneity. Recent advances in machine learning have enabled the inference of ground-truth genomic single-nucleotide and copy number variant status from transcript data. While these inferred SNV and CNV states can be used to resolve clonal phylogenies, however, it is still unknown how faithfully transcript-based tumour phylogenies reconstruct ground truth DNA-based tumour phylogenies. We sought to study the accuracy of inferred-transcript to recapitulate DNA-based tumour phylogenies. We first performed in-silico comparisons of inferred and directly resolved SNV and CNV status, from single cancer cells, from three different cell lines. We found that inferred SNV phylogenies accurately recapitulate DNA phylogenies (entanglement = 0.097). We observed similar results in iCNV and CNV based phylogenies (entanglement = 0.11). Analysis of published prostate cancer DNA phylogenies and inferred CNV, SNV and transcript based phylogenies demonstrated phylogenetic concordance. Finally, a comparison of pseudo-bulked spatial transcriptomic data to adjacent sections with WGS data also demonstrated recapitulation of ground truth (entanglement = 0.35). These results suggest that transcript-based inferred phylogenies recapitulate conventional genomic phylogenies. Further work will need to be done to increase accuracy, genomic, and spatial resolution.

Research on hydrodynamic performance of S-type turbine based on linear wave

The hydrodynamic performance of a Savonius type turbine (S-type turbine) in wave field is studied. The method of combining numerical simulation with physical experiment is adopted.Based on linear wave theory and turbulence model, Star CCM+numerical simulation software is used for digital modeling, and overlapping grid technology is used for grid modeling. Dynamic Fluid Body Interaction (DFBI) model is called to control the movement of S-type turbine, and second-order time discretization is adopted to establish a two-dimensional wave field model and conduct numerical simulation. At the same time, the physical test system of S-type turbine was developed for physical experiment verification, and the rotating performance of S-type turbine under different wave heights and pe-riods was measured, and the results of numerical simulation and physical experiment were com-prehensively evaluated. The results show that in wave field, the inverted S-shape arrangement of horizontal axis is better than the positive S-shape arrangement of horizontal axis and the vertical axis arrangement, and the captured energy is more than 3 times. At the same time, the fluctuating rotation speed of S-type turbine in wave field needs to be close to the wave frequency to capture more wave energy, which has guiding significance for practical engineering.

Association between age-related hearing loss and depression: A systematic review and meta-analysis

Introduction This meta-analysis examined the relationship between age-related hearing loss (ARHL) and depression in older adults, and further explored whether this relationship is moderated by age and gender. Methods We searched in 4 English databases: PubMed, Embase, Web of Science, and Cochrane Library. Ultimately, we identified 9 studies, involving 3 cohort studies and 6 cross-sectional studies. We used Hedges’ g as the effect size, and all pooled analyses were performed using random-effects models. Results ARHL patients had higher depressive symptom scores than non-ARHL older adults (g = 0.52). When divided into subgroups based on study type, a large effect size was demonstrated in the cross-sectional study group (g = 0.68) and was not statistically different in the cohort study group (g = 0.06). Meta-regression results showed that the effect size of depression in older adults with ARHL was significantly associated with the percentage of females (t = 5.97, p = 0.000) and not significantly associated with age (t = 0.94, p = 0.364). Conclusions Patients with ARHL are more likely to be depressed than older adults with normal hearing, and this relationship is influenced by the gender of the patients.

Genetic diversity and population structure studies of West African sweetpotato [Ipomoea batatas (L.) Lam] collection using DArTseq

Background Sweetpotato is a vegetatively propagated crop cultivated worldwide, predominantly in developing countries, valued for its adaptability, short growth cycle, and high productivity per unit land area. In most sub-Saharan African (SSA) countries, it is widely grown by smallholder farmers. Niger, Nigeria, and Benin have a huge diversity of sweetpotato accessions whose potential has not fully been explored to date. Diversity Arrays Technology (DArTseq), a Genotyping by Sequencing (GBS) method, has been developed and enables genotyping with high-density single nucleotide polymorphisms (SNPs) in different crop species. The aim of this study was to assess the genetic diversity and population structure of the West African sweetpotato collection using Diversity Arrays Technology through Genotyping by Sequencing (GBS). Results 29,523 Diversity Arrays Technology (DArTseq) single nucleotide polymorphism markers were used to genotype 271 sweetpotato accessions. Genetic diversity analysis revealed an average polymorphic information content (PIC) value of 0.39, a minor allele frequency of 0.26, and an observed heterozygosity of 10%. The highest value of polymorphic information content (PIC) (0.41) was observed in chromosomes 4, while the highest proportion of heterozygous (He) (0.18) was observed in chromosomes 11. Molecular diversity revealed high values of polymorphic sites (Ps), theta (θ), and nucleotide diversity (π) with 0.973, 0.158, and 0.086, respectively, which indicated high genetic variation. The pairs of genetic distances revealed a range from 0.08 to 0.47 with an overall average of 0.34. Population structure analysis divided the 271 accessions into four populations (population 1 was characterised by a mixture of accessions from all countries; population 2, mostly comprised of Nigerian breeding lines; population 3 contained exclusively landraces from Benin; and population 4 was composed by only landraces from West African countries) at K = 4, and analysis of molecular variance (AMOVA) based on PhiPT values showed that most of the variation was explained when accessions were categorized based on population structure at K = 4 (25.25%) and based on cluster analysis (19.43%). Genetic distance showed that group 4 (which constituted by landraces of Niger and Benin) was genetically distant (0.428) from groups 2 (formed by 75% of breeding lines of Nigeria), while group 1 was the closest (0.182) to group 2. Conclusions This study employed 7,591 DArTseq-based SNP markers, revealing extensive polymorphism and variation within and between populations. Variability among countries of origin (11.42%) exceeded that based on biological status (9.13%) and storage root flesh colour (7.90%), emphasizing the impact of migration on genetic diversity. Population structure analysis using principal component analysis (PCA), Neighbor-Joining (NJ) tree, and STRUCTURE at K = 4 grouped 271 accessions into distinct clusters, irrespective of their geographic origins, indicating widespread genetic exchange. Group 4, dominated by landraces (95%), showed significant genetic differentiation (Nei’s Gst = 0.428) from Group 2, mainly comprising breeding lines, suggesting their potential as heterotic groups for breeding initiatives like HEBS or ABS.

Correction: Developing climate-resilient rice varieties (BRRI dhan97 and BRRI dhan99) suitable for salt-stress environments in Bangladesh

Optimal tactics in community pension model for defined benefit pension plans

Against the backdrop of an aging population, community pension initiatives are gaining traction, permeating societal landscapes. This study delves into the equilibrium strategy within the context of a defined benefit pension plan, employing a differential game framework with a community pension model. Hence, the model entails the company’s controls over investment rates in funds, juxtaposed with employees’ inclination towards a greater proportion of community pension allocation in said funds. To tackle this issue, a stochastic differential game model for pensions under a community pension scheme is formulated. Leveraging the Hamilton-Jacobi-Bellman equation, we derive the Markov Perfect Nash Equilibrium solution and optimal portfolio. Through numerical simulations, we analyze the impact of varying risk aversion levels across different parameter values on equilibrium ratios, thereby offering insights into managerial risk tolerance.

MARCHF8-mediated ubiquitination via TGFBI regulates NF-κB dependent inflammatory responses and ECM degradation in intervertebral disc degeneration

Aim To explore the role of the hub gene Transforming Growth Factor Beta Induced (TGFBI) in Intervertebral disc degeneration (IDD) pathogenesis and its regulatory relationship with Membrane Associated Ring-CH-Type Finger 8 (MARCHF8). Background IDD is a prevalent musculoskeletal disorder leading to spinal pathology. Despite its ubiquity and impact, effective therapeutic strategies remain to be explored. Objective Identify key modules associated with IDD and understand the impact of TGFBI on nucleus pulposus (NP) cell behavior, extracellular matrix (ECM)-related proteins, and the Nuclear Factor kappa-light-chain-enhancer of Activated B cells (NF-κB) signaling pathway. Methods The GSE146904 dataset underwent Weighted Gene Co-Expression Network Analysis (WGCNA) for key module identification and Differentially Expressed Genes (DEGs) screening. Intersection analysis, network analysis, and co-expression identified TGFBI as a hub gene. In vitro experiments delved into the interplay between TGFBI and MARCHF8 and their effects on NP cells. Results WGCNA linked the MEturquoise module with IDD samples, revealing 145 shared genes among DEGs. In vitro findings indicated that MARCHF8 determines TGFBI expression. TGFBI boosts apoptosis and ECM breakdown in Lipopolysaccharide-stimulated (LPS-stimulated) NP cells. Altering TGFBI levels modulated these effects and the NF-κB signaling pathway, influencing inflammatory cytokine concentrations. Moreover, MARCHF8 ubiquitination controlled TGFBI expression. Conclusion TGFBI, modulated by MARCHF8, significantly influences IDD progression by affecting NP cell apoptosis, ECM degradation, and inflammation through the NF-κB signaling pathway.

pyAKI—An open source solution to automated acute kidney injury classification

Objective Acute kidney injury (AKI) is a frequent complication in critically ill patients, affecting up to 50% of patients in the intensive care units. The lack of standardized and open-source tools for applying the Kidney Disease Improving Global Outcomes (KDIGO) criteria to time series, requires researchers to implement classification algorithms of their own which is resource intensive and might impact study quality by introducing different interpretations of edge cases. This project introduces pyAKI, an open-source pipeline addressing this gap by providing a comprehensive solution for consistent KDIGO criteria implementation. Materials and methods The pyAKI pipeline was developed and validated using a subset of the Medical Information Mart for Intensive Care (MIMIC)-IV database, a commonly used database in critical care research. We constructed a standardized data model in order to ensure reproducibility. PyAKI implements the Kidney Disease: Improving Global Outcomes (KDIGO) guideline on AKI diagnosis. After implementation of the diagnostic algorithm, using both serum creatinine and urinary output data, pyAKI was tested on a subset of patients and diagnostic accuracy was compared in a comparative analysis against annotations by physicians. Results Validation against expert annotations demonstrated pyAKI’s robust performance in implementing KDIGO criteria. Comparative analysis revealed its ability to surpass the quality of human labels with an accuracy of 1.0 in all categories. Discussion The pyAKI pipeline is the first open-source solution for implementing KDIGO criteria in time series data. It provides a standardized data model and a comprehensive solution for consistent AKI classification in research applications for clinicians and data scientists working with AKI data. The pipeline’s high accuracy make it a valuable tool for clinical research and decision support systems. Conclusion This work introduces pyAKI as an open-source solution for implementing the KDIGO criteria for AKI diagnosis using time series data with high accuracy and performance.

CD206+ Trem2+ macrophage accumulation in the murine knee joint after injury is associated with protection against post-traumatic osteoarthritis in MRL/MpJ mice

Post-traumatic osteoarthritis (PTOA) is a painful joint disease characterized by the degradation of bone, cartilage, and other connective tissues in the joint. PTOA is initiated by trauma to joint-stabilizing tissues, such as the anterior cruciate ligament, medial meniscus, or by intra-articular fractures. In humans, ~50% of joint injuries progress to PTOA, while the rest spontaneously resolve. To better understand molecular programs contributing to PTOA development or resolution, we examined injury-induced fluctuations in immune cell populations and transcriptional shifts by single-cell RNA sequencing of synovial joints in PTOA-susceptible C57BL/6J (B6) and PTOA-resistant MRL/MpJ (MRL) mice. We identified significant differences in monocyte and macrophage subpopulations between MRL and B6 joints. A potent myeloid-driven anti-inflammatory response was observed in MRL injured joints that significantly contrasted the pro-inflammatory signaling seen in B6 joints. Multiple CD206+ macrophage populations classically described as M2 were found enriched in MRL injured joints. These CD206+ macrophages also robustly expressed Trem2, a receptor involved in inflammation and myeloid cell activation. These data suggest that the PTOA resistant MRL mouse strain displays an enhanced capacity of clearing debris and apoptotic cells induced by inflammation after injury due to an increase in activated M2 macrophages within the synovial tissue and joint space.

Uncovering NK cell sabotage in gut diseases via single cell transcriptomics

The identification of immune environments and cellular interactions in the colon microenvironment is essential for understanding the mechanisms of chronic inflammatory disease. Despite occurring in the same organ, there is a significant gap in understanding the pathophysiology of ulcerative colitis (UC) and colorectal cancer (CRC). Our study aims to address the distinct immunopathological response of UC and CRC. Using single-cell RNA sequencing datasets, we analyzed the profiles of immune cells in colorectal tissues obtained from healthy donors, UC patients, and CRC patients. The colon tissues from patients and healthy participants were visualized by immunostaining followed by laser confocal microscopy for select targets. Natural killer (NK) cells from UC patients on medication showed reduced cytotoxicity compared to those from healthy individuals. Nonetheless, a UC-specific pathway called the BAG6-NCR3 axis led to higher levels of inflammatory cytokines and increased the cytotoxicity of NCR3+ NK cells, thereby contributing to the persistence of colitis. In the context of colorectal cancer (CRC), both NK cells and CD8+ T cells exhibited significant changes in cytotoxicity and exhaustion. The GALECTIN-9 (LGALS9)-HAVCR2 axis was identified as one of the CRC-specific pathways. Within this pathway, NK cells solely communicated with myeloid cells under CRC conditions. HAVCR2+ NK cells from CRC patients suppressed NK cell-mediated cytotoxicity, indicating a reduction in immune surveillance. Overall, we elucidated the comprehensive UC and CRC immune microenvironments and NK cell-mediated immune responses. Our findings can aid in selecting therapeutic targets that increase the efficacy of immunotherapy.

Backbone extraction through statistical edge filtering: A comparative study

The backbone extraction process is pivotal in expediting analysis and enhancing visualization in network applications. This study systematically compares seven influential statistical hypothesis-testing backbone edge filtering methods (Disparity Filter (DF), Polya Urn Filter (PF), Marginal Likelihood Filter (MLF), Noise Corrected (NC), Enhanced Configuration Model Filter (ECM), Global Statistical Significance Filter (GloSS), and Locally Adaptive Network Sparsification Filter (LANS)) across diverse networks. A similarity analysis reveals that backbones extracted with the ECM and DF filters exhibit minimal overlap with backbones derived from their alternatives. Interestingly, ordering the other methods from GloSS to NC, PF, LANS, and MLF, we observe that each method’s output encapsulates the backbone of the previous one. Correlation analysis between edge features (weight, degree, betweenness) and the test significance level reveals that the DF and LANS filters favor high-weighted edges while ECM assigns them lower significance to edges with high degrees. Furthermore, the results suggest a limited influence of the edge betweenness on the filtering process. The backbones global properties analysis (edge fraction, node fraction, weight fraction, weight entropy, reachability, number of components, and transitivity) identifies three typical behavior types for each property. Notably, the LANS filter preserves all nodes and weight entropy. In contrast, DF, PF, ECM, and GloSS significantly reduce network size. The MLF, NC, and ECM filters preserve network connectivity and weight entropy. Distribution analysis highlights the PU filter’s ability to capture the original weight distribution. NC filter closely exhibits a similar capability. NC and MLF filters excel for degree distribution. These insights offer valuable guidance for selecting appropriate backbone extraction methods based on specific properties.

Risk assessment and prevention in airport security assurance by integrating LSTM algorithm

The risk assessment and prevention in traditional airport safety assurance usually rely on human experience for analysis, and there are problems such as heavy manual workload, excessive subjectivity, and significant limitations. This article proposed a risk assessment and prevention mechanism for airport security assurance that integrated LSTM algorithm. It analyzed the causes of malfunctioning flights by collecting airport flight safety log datasets. This article extracted features related to risk assessment, such as weather factors, airport facility inspections, and security check results, and conducted qualitative and quantitative analysis on these features to generate a datable risk warning weight table. This article used these data to establish an LSTM model, which trained LSTM to identify potential risks and provide early warning by learning patterns and trends in historical data. It then handed over the new data to the trained LSTM model for risk assessment and prediction, grading and warning of risks. It monitored the airport security situation in real-time based on the results and quickly notified airport security personnel to handle it. The outcome indicates that the standard error of the LSTM algorithm model training is less than 0.18, and the decision coefficients were all greater than 0.9. The predicted data was highly consistent with the actual data. It can be summarized that the algorithmic model has good accuracy and robustness. The LSTM algorithm can play a role in providing early warning, assisting decision-making, optimizing resources, and enhancing real-time monitoring in airport security assurance. It can effectively improve the safety and prevention capabilities of airports, and reduce the losses caused by potential risks.