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GV effects of diabetes mellitus on clinical outcomes of patients with acute heart failure: A systematic review and meta-analysis

Diabetes mellitus (DM) is identified as a potential modifier of clinical outcomes in acute heart failure (AHF), yet its prognostic impact is not fully determined. This systematic review and meta-analysis aimed to assess the prognostic impact of DM on survival outcomes in AHF patients by synthesizing evidence from 26 studies involving 326,928 subjects collected from Cochrane Library, PubMed, Web of Science, and Embase databases up to 1 June 2024. Both prospective/retrospective cohort and case-control studies published since 2000 were included, with outcomes evaluated through multivariate, univariate, and binary analyses using the Newcastle-Ottawa Scale for quality assessment. Multivariate analysis indicated that DM significantly increased the risk of all-cause mortality in AHF patients (cohort studies: HR = 1.21, 95%CI (1.13, 1.29), OR=1.15, 95%CI (1.05, 1.26); case-control studies: HR = 1.39, 95%CI (1.26, 1.53), OR=1.43, 95%CI (1.10, 1.84)]. Univariate analysis confirmed this finding in case-control studies [HR = 1.30, 95%CI (1.01, 1.67)], but not in cohort studies. In both cohort [RR = 1.27, 95%CI (1.12, 1.43)] and case-control [OR=1.21, 95%CI (1.08, 1.35)] studies, DM increased the risk of all-cause mortality. AHF patients with DM had a higher risk of cardiovascular mortality [cohort studies: HR = 1.85, 95%CI (1.46, 2.33); case-control: OR=1.70, 95%CI (1.17, 2.47)]. While multivariate analysis showed no association between DM and in-hospital mortality, case-control studies indicated an increased risk [OR=1.21, 95%CI (1.03, 1.42)]. DM also increased the risk of readmission [cohort studies: HR = 1.32, 95%CI (1.14, 1.53); case-control studies: HR = 1.44, 95%CI (1.23, 1.69); binary data: OR=1.19, 95%CI (1.07, 1.31)].This updated meta-analysis demonstrates that DM imposes significant adverse effects on all-cause mortality, cardiovascular-related mortality, and readmission risk in AHF patients. However, no significant connection was found between diabetes and survival outcomes with respect to the co-endpoint of death or readmission and the endpoint of in-hospital mortality. These findings underscore the necessity for implementing targeted diabetes management within AHF care protocols to enhance clinical outcomes, an essential consideration for future practice.

Ubiquitination by HRD1 is essential for TLR3 trafficking and its innate immune signaling

Dynamic stability analysis of a fractional calculus-based colon cancer model with therapeutic interventions

Abstract Colon cancer is a high-risk malignant tumor worldwide. To address the limited efficacy and overlapping toxicity of current chemoimmunotherapy, this study establishes a fractional-order colon cancer model with a core architecture capturing the probiotics- $$\hbox {CD4}^{+}$$ T cells-tumor cells axis. The primary theoretical contributions include: rigorous proof of solution existence and uniqueness through fixed-point theory. Analytical derivation of equilibrium stability conditions using the Routh-Hurwitz criterion. Numerical simulations systematically quantify how the fractional parameter $$\alpha$$ governs system dynamics and memory effects, while identifying critical drug dosage thresholds for tumor clearance. These findings provide a mathematical foundation for optimizing probiotic-based combination therapies.

Online propagation of emotions: A study of resharing dynamics on social media following celebrity suicides

Emotional contagion on social media, particularly following shocking and tragic events, often unfolds through widespread resharing, amplifying affective responses that are typically intense and negative. This study focuses on the context of celebrity suicides, which have the potential to trigger emotional contagion and lead to adverse behavioral outcomes, such as copycat suicides. Using an exhaustive Twitter dataset covering four celebrity suicides, we theorize the propagation of emotional content through a valence-arousal framework, distinguishing emotions based on affective valence (positive or negative) and physiological arousal (high or low). We analyze how distinct emotions embedded in tweets propagate through retweet cascades, treating each tweet and its retweets as a single cascade. Propagation is measured across four cascade dimensions: size, lifetime, speed, and burstiness. Emotions are extracted from over a million tweets and retweets using a BERT-based language model and are used as predictors in regression analyses of the propagation metrics. Our results show that emotional messages propagate in distinct ways after tragic events. Disgust emerges as the most contagious emotion, spreading quickly, widely, and with longevity, while fear, despite its arousal, spreads weakly. Anger and surprise generate fast but short-lived cascades marked by high burstiness. Joy, though less frequent, endures longer than neutral and negative content, reflecting resilience but with lower burstiness. These findings advance research on online emotional propagation by demonstrating that discrete emotions differ significantly even within the same valence–arousal characteristic. They also offer insights for public health strategies to mitigate risks linked to emotional amplification in digital environments.

Evolution of chromosomes and nuclear architectures of amniotes

Increased integration and synergy in EEG- and fNIRS-based data in migraine patients after a three-month treatment with galcanezumab: relations with long-term clinical outcome

Dog ownership enhances anchored personal relationships and sense of community: A comparison with incidental interactions and friendships

Dogs are known to be catalysts for human-human relationships. However, there is insufficient quantitative research that directly compares dog owners’ human-human relationships with those of non-owners. This study focused on whether dog owners are more likely to have human-human relationships and engage in social interactions within their neighborhoods. A previous model considered incidental interactions—which occur spontaneously between passersby in public settings—and friendships, as human-human relationships fostered by dog ownership. This study also considered anchored personal relationships, which are the types of relationships that dog owners would typically cultivate within their neighborhoods. Anchored personal relationships are relationships highly embedded within a social context and exist solely in a shared time, place, and activity. This study examined the associations between dog ownership and incidental interactions, friendships, and anchored personal relationships. We also examined the potential mediating effects of these relationships on the association between dog ownership and a sense of community. Analyzed data included 377 participants from a social survey conducted in a suburb of the Tokyo metropolitan area. We used generalized structural equation modeling to examine indirect effects. The findings revealed a positive correlation between dog ownership and having anchored personal relationships, as well as between dog ownership and having incidental interactions. However, after controlling for demographics, dog ownership did not increase the likelihood of having friends in one’s neighborhood. All types of relationships were positively correlated with a stronger sense of community. However, only anchored personal relationships mediated the effect of dog ownership on sense of community. These findings support the proposition that anchored personal relationships should be considered alongside incidental interactions and friendships when studying human-human relationships fostered by dog ownership. Furthermore, exploratory analyses revealed that ownership of cats and other pets were not correlated with the relationships or a stronger sense of community.

Flash droughts threaten global managed forests

Genomic surveillance of HBV and HDV reveals genotype-specific risk of liver disease in central Vietnam

Abstract Hepatitis B virus (HBV) genotype distribution, resistance mutations, and hepatitis delta virus (HDV) co-infection play critical roles in disease progression and treatment outcomes yet remain understudied in central Vietnam. This study aimed to understand their characteristics and association with clinical outcomes. Serum from 376 HBV-infected patients in Hue, Vietnam (June 2023-June 2024) was analysed. HBV-DNA and HDV-RNA were extracted and amplified by nested PCR, followed by Sanger sequencing. HBV viral load was quantified using real-time PCR. HBV and HDV genotypes were determined through phylogenetic analysis, and HBV resistance mutation identified using geno2pheno [hbv]. HBV genotype B was predominant (95%), followed by genotypes C (5%) and D (0.3%). Infection with genotype C was significantly associated with an increased risk of hepatocellular carcinoma (OR = 6.05, 95% CI: 1.6–22.5; p  = 0.007). Classical drug resistance mutations were rare (1.3%), while non-classical mutations were observed in 33% of sequences, especially V207M in genotype B. HDV co-infection was identified in two patients (0.5%), both infected with HDV genotype 1 and associated with elevated liver enzymes and liver disease progression. In conclusion, HBV genotype C emerged as a key predictor of hepatocellular carcinoma risk in Central Vietnam, highlighting the need of genotype-based monitoring. Low antiviral resistance and HDV co-infection likely reflect effective vaccination and treatment in the region. Routine HDV screening and resistance surveillance are recommended.

Metabolic dysfunction-associated steatohepatitis is the leading indication for adult liver transplantation in Saudi Arabia

Background Liver transplantation (LT) represents the life-saving treatment for advanced liver disease. We aim to investigate LT indication trends and outcomes in Saudi Arabia, following the evolution of effective therapies for hepatitis C virus (HCV) and the rising fatty liver disease prevalence. Methods We retrospectively analyzed data from adult patients who underwent LT from 2011 to 2023 at a tertiary referral center in Saudi Arabia. We assessed demographics, LT indication trends, Model for End-stage Liver Disease (MELD) scores, donor type, and survival outcomes. Results A total of 1,419 patients were included. The median age was 56.9 years, with 37.4% female. Living donor LT (LDLT) represented 79.8% of all transplants, and 22.0% of recipients had hepatocellular carcinoma (HCC). Metabolic dysfunction-associated steatohepatitis (MASH) was the predominant indication for LT (33.2%), followed by HCV (18.0%) and hepatitis B virus (HBV) (17.1%). Overall survival rates at 1-, 2-, 3-, 5-, and 10-years post-transplantation were 87.9%, 85.0%, 82.4%, 77.7%, and 71.3%, respectively. Hazard ratios (HR) for mortality were lower in patients with HBV compared to MASH (HR: 0.44, 95% CI: 0.28–0.69, p < 0.001), and higher in patients aged ≥65 years (HR: 1.37, 95% CI: 1.02–1.84, p = 0.036), those with diabetes (HR: 1.33, 95% CI: 1.03–1.73, p = 0.029), and those with increased MELD score (HR: 1.02, 95% CI: 1.00–1.04, p = 0.022). LDLT was associated with reduced mortality risk (HR: 0.68, 95% CI: 0.51–0.92, p = 0.013). Conclusions MASH represents the leading indication for LT in this large cohort, necessitating preventive strategies and early detection efforts.

Large-scale stochastic simulation of open quantum systems

Abstract Understanding interactions between quantum systems and their environments is crucial for developing stable quantum technologies and accurate physical models. Yet, simulating open quantum systems with non-unitary dynamics remains computationally demanding. We introduce the tensor jump method (TJM), a scalable and embarrassingly parallel algorithm for stochastically simulating large-scale open quantum systems governed by Lindbladians. The TJM extends the Monte Carlo wave function (MCWF) approach to matrix product states, employs a dynamic time-dependent variational principle (TDVP) to minimize evolution errors, and introduces a sampling MPS to reduce timestep dependence. This method scales efficiently, ensuring convergence to Lindbladian dynamics independent of system size, as demonstrated both rigorously and numerically. We showcase its utility by simulating XXX Heisenberg models with up to a thousand spins on a consumer-grade CPU. The TJM represents a significant advance in open quantum system simulation, enabling exploration of dissipative many-body dynamics and the design of more stable quantum hardware.

Isolation and characterization of two novel phages with lytic activity against multidrug-resistant Acinetobacter baumannii strains: potential for phage therapy

Abstract The emergence of multidrug-resistant Acinetobacter baumannii (MDR-AB) has raised concerns regarding the lack of effective treatment options, prompting interest in phage therapy. In this study, two phages, designated vB_MZM_2AB-P and vB_MZM_4AB-P, were isolated and characterized for their lytic activity against MDR-AB strains. vB_MZM_2AB-P demonstrated considerable stability, retaining activity at 70 °C and pH 11.00, with over 37.10% survival rate after three months of storage. It displayed a 10-min latent period and a burst size of 39.72 PFU/cell. vB_MZM_4AB-P was stable at 50 °C and pH 7.00, but lost activity after three months of storage. Its latent period was also 10 min, with a burst size as high as 746.70 PFU/cell. Transmission electron microscopy revealed that phage vB_MZM_2AB-P has an icosahedral head with a diameter of 55.00 nm and a non-contractile tail that is 121.00 nm long, while phage vB_MZM_4AB-P has an icosahedral head with a diameter of 75.36 nm and a non-contractile tail that is 19.44 nm long. Genomic analysis showed that vB_MZM_2AB-P (43,664 bp) shared 94.18% and 92.80% similarity with phages DMU1 and SH-Ab15497, respectively, while vB_MZM_4AB-P (42,975 bp) shared 73.82% similarity with phage vB_AbaP_Acibel007. Phylogenetic analysis indicated that vB_MZM_2AB-P may represent a new genus within the order Caudoviricetes, and vB_MZM_4AB-P a new species within the genus Daemvirus . No antibiotic resistance or virulence genes were detected. These findings demonstrate that vB_MZM_2AB-P and vB_MZM_4AB-P are novel phages with distinct genomic features and favorable lytic activity against MDR-AB strains, highlighting their value for expanding phage diversity and for future fundamental research.

Data-driven prediction of future purchase behavior in cross-border e-commerce using sequence modeling with PSO-tuned LSTM

With the rapid advancement of cross-border e-commerce, accurately predicting user purchase behavior has emerged as a critical challenge for enhancing platform operational efficiency and user experience. This study proposes a hybrid deep learning framework for predicting user purchase behavior in cross-border e-commerce. The model integrates Long Short-Term Memory (LSTM) networks with Variational Mode Decomposition (VMD) to forecast future user actions. The proposed methodology begins by applying VMD to preprocess raw behavioral time-series data, decomposing it into multiple intrinsic mode functions (IMFs) to mitigate noise and extract multi-frequency features, thereby enhancing data quality. The refined components are subsequently fed into an LSTM network to model long-term temporal dependencies and generate precise purchase predictions. Furthermore, Particle Swarm Optimization (PSO) is employed to automate the hyperparameter tuning of the LSTM model, effectively mitigating overfitting and improving generalization. Experimental evaluations demonstrate that the VMD-PSO-LSTM hybrid model achieves superior prediction accuracy and robustness compared to conventional approaches. The results underscore the efficacy of integrating signal decomposition, deep learning, and evolutionary optimization as a viable solution for behavioral prediction in cross-border e-commerce contexts.

Vasopressin-to-oxytocin receptor crosstalk in the preoptic area underlying parental behaviors in male mice

Heterogeneous collaboration patterns and radical innovation performance—a data-driven analysis from specialized, refined, differentiated, and innovative enterprises

A scoping review of the role of the arts in enhancing data literacy

With the growing use of personal and public data in everyday life, data literacy is increasing in importance. There is a significant body of research indicating the role of artistic practice in the regulation of our response to information and experience, particularly as these relate to experiences of trust and social bonding. However, there is a gap in the literature concerning a review of current publications investigating the use of artistic practices to enhance data literacy. The aim of this study was to conduct a scoping review to identify and map the extent of evidence available on this topic. Specifically, the review aims to contribute to a better understanding of which artistic practices and art forms were being used, the profile of population groups and settings, and the rationale provided for using the arts. Our review utilized Arksey and O’Malley’s methodological framework. The review includes an updated search, conducted in April 2025, to provide a comprehensive overview of recent studies. Following abstract and full text screening, a total of 51 publications were deemed eligible for review. The findings indicate the use of a broad spectrum of artistic practices, with visual arts and storytelling being the most prevalent. Most of the research to date has been conducted within educational settings. The arts were identified as key tools in enhancing accessibility, engagement and critical thinking when engaging with data. Limits in the value of harnessing artistic practices for data literacy were noted, including the sometimes competing demands of artistic freedom and scientific exactitude. Further research is needed to more fully understand the importance of cultural context in how the arts are deployed in the dynamic and rapidly changing world of data.

The epidermis coordinates multi-scale symmetry breaking in chiral root growth

Measuring the impact of built environment factors on station-level contributions to link-level crowding using a novel crowding contribution index

Abstract Metro crowding undermines passenger comfort, operational efficiency and network reliability. While prior research has examined station-level and system-wide crowding, little attention has been given to quantifying how individual stations contribute to link-level overcrowding. This study addresses this gap by introducing the Crowding Contribution Index (CCI), a metric that quantifies the extent to which destination stations drive overcapacity flows on preceding links. The CCI is computed via a structured framework integrating Automated Fare Collection (AFC) and GTFS link-network data. Applied to over 80 million trips across 237 Delhi Metro stations, 142 200 hourly CCI values reveal that 46.35% of station-hours exceed capacity, with highest contributions clustered in specific stations. A Type II Tobit model assesses built-environment (BE) variables, showing that POI and intersection densities increase contributions, while POI entropy reduces them, underscoring land-use diversity’s role. Random Forest and XGBoost models corroborate these findings, ranking BE variables as the strongest CCI predictors. These insights emphasise the need for integrated land-use and transport strategies. The CCI framework offers operators a scalable tool for real-time service adjustments, such as targeted short-turns and dynamic fleet deployment, and guides planners toward sustainable, integrated land-use planning, making it especially valuable for rapidly urbanising, data-constrained cities.

Investigation on the knowledge-attitude-practice of medical students in controlling emerging infectious diseases: A case study of COVID-19

Objective Investigate the Knowledge-Attitude-Practice (KAP) of students from Medical College towards emerging infectious diseases, and assess their impact, can provide a scientific basis and practical guidance for enhancing medico’s prevention and control capabilities. Methods A total of 2,395 participants from various grades and majors at Medical University were randomly selected using a stratified cluster sampling method. This cross-sectional study was conducted between April 25 and May 31, 2020, using a self-administered questionnaire developed on the Wenjuanxing platform to assess COVID-19-related knowledge, attitudes, and practices (KAP) among medical students. Results A total of 2,245 participants (aged 16–28 years) were included in the study, coming from five medical disciplines: Clinical Medicine, Preventive Medicine, Nursing, Clinical Pharmacy, Health Inspection and Quarantine. The average scores for the COVID-19 epidemiological knowledge and the control measures for the epidemic were 4.92 ± 1.03 and 4.50 ± 0.78, respectively. Among them, the scores of epidemiological knowledge exhibited significant differences in sex, nation, type of dwelling place, major, grade, annual per capita household income, and age. The scores of preventive knowledge significantly differed by sex, major, grade, physical condition, and age. Further, behavioral data indicated that 96.0% of the students thought the pandemic had severely affected their daily life, while >90% maintained consistent mask usage and >80% insisted on health-protective practices. Practice scores finally varied significantly by sex, family structure, and ethnicity. Conclusions Altogether, medical students possess certain basic knowledge in controlling emerging infectious diseases, but some still generally suffer from insufficient cognitive depth and anxiety. Colleges can systematically enhance students’ rational cognitive level which include offering specialized courses as well as promoting cutting-edge research achievements, and through standardized operations stabilize their psychological states.

MCARE enhances SERCA1 activity in fast-twitch muscle to maintain calcium handling and muscle integrity

Abstract The release of Ca 2+ from the sarcoplasmic reticulum into the cytoplasm, followed by its reuptake by sarco/endoplasmic reticulum Ca 2+ ATPase (SERCA), is critical for the muscle contraction-relaxation cycle. In this study, we identify a small transmembrane protein, predominantly expressed in fast-twitch muscles, which regulates SERCA1 activity. This protein, termed muscle-enriched Ca 2+ regulator (MCARE), enhances SERCA1 function by competitively inhibiting myoregulin, a muscle-specific micropeptide that otherwise suppresses SERCA1 activity. By facilitating more efficient Ca 2+ clearance from the cytoplasm, MCARE accelerates muscle relaxation. Mcare -deficient mice exhibit symptoms resembling muscular dystrophy, including progressive muscle wasting in fast-twitch muscles, reduced muscle strength, and increased susceptibility to exercise-induced muscle damage. Notably, these mice also present with distinctive rippling muscle contractions. Our findings establish MCARE as a key regulator of SERCA1 activity, essential for maintaining Ca 2+ homeostasis and the functional integrity of fast-twitch muscle fibers.