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Mechanoluminescence from Amorphous Organic Luminogens

Sleep quality of college students in Fujian and its influencing factors: A cross-sectional study

Aim This study aims to investigate college students’ sleep quality, explore the factors influencing it, and provide data support for further studies. Methods College students in Fujian Province were chosen as the study sample using snowball sampling. Data was gathered from the participants through the utilization of a self-designed personal questionnaire, the Pittsburgh Sleep Quality Index(PSQI) scale, and the Mobile Phone Addiction Index (MPAI) scale. Binary logistic regression is utilized to assess the sleep quality of college students and identify risk factors. Results A total of 971 participants were included in this study. The mean total PSQI score was 4.52 ± 3.17. There were 310 students with poor sleep quality and the detection rate was 32.0%. The multivariate logistic regression analysis showed that smoking (OR(Odds ratio):1.832(1.076,3.118)), electronic product addiction(OR:2.861(1.928,4.246)), personal history of acute illness(OR:2.328(1.671,3.244)) were identified as independent risk factors.In turn, education (OR:0.594(0.456,0,772)) and parents without sleep problems (OR:0.533(0.361,0.787)) were protective factors. Conclusion College students in Fujian have some sleep problems. We should pay attention to the relationship between smoking, electronic product addiction, personal history of acute illness and sleep quality. Health policymakers should consider these factors to improve college students’ sleep quality.

Efficacy analysis and prognostic factors of first-line chemotherapy combined with immunotherapy in extensive-stage small cell lung cancer: a real-world study

Deep reinforcement learning for decision making of autonomous vehicle in non-lane-based traffic environments

Existing research on decision-making of autonomous vehicles (AVs) has mainly focused on normal road sections, with limited exploration of decision-making in complex traffic environments without lane markings. Taking toll plaza diverging area as an example, this study proposes a lateral motion strategy for AVs based on deep reinforcement learning (DRL) algorithms. First, a microscopic simulation platform is developed to simulate the realistic diverging trajectories of human-driven vehicles (HVs), providing AVs with a high-fidelity training environment. Next, a DRL-based self-efficient lateral motion strategy for AVs is proposed, with state and reward functions tailored to the environmental features of the diverging area. Simulation results indicate that the strategy can significantly reduce the diverging time of single vehicles. In addition, considering the long-term coexistence of AVs and HVs, the study further explores how the varying penetration of AVs with self-efficient strategy impacts traffic flow in the diverging area. Findings reveal that a moderate increase in AV penetration can improve overall traffic efficiency and safety. But an excessive penetration of AVs with self-efficient strategy leads to intense competition for limited road resources, further deteriorating operational conditions in the diverging area.

Robust and secure image steganography with recurrent neural network and fuzzy logic integration

Perceptual judgments are resistant to the advisor’s perceived level of trustworthiness: A deep fake approach

As we navigate our environment, we frequently make spontaneous judgments about other’s characteristics. Trustworthiness is a particularly important trait, often judged instantly and used to guide decisions, especially in uncertain situations. Although the impact of trustworthiness on social behaviour is well-documented, its influence on more fundamental cognitive processes, such as perceptual decision-making, remains unclear. The present study aims to fill this gap. In the first experiment (N =  100), we validated a new trustworthiness manipulation by applying deep fake technology to create animated versions of perceptually trustworthy, untrustworthy, and neutral static computer-generated faces. In the second experiment (N =  199), the deep fake procedure was applied to a new set of trustworthy and untrustworthy faces that served as advisors during a perceptual decision-making task. Here participants had to indicate the direction of dots that were either moving coherently to the left or the right (i.e., random dot motion task). Contrary to our predictions, participants did not align more with the advice of trustworthy advisors than that of untrustworthy advisors. While participants made faster decisions and reported greater confidence when aligning with the advice, these effects were not influenced by the advisor’s perceived trustworthiness. We integrate our findings within theoretical frameworks of advice taking, domain specificity of facial trustworthiness, and task requirements.

The experience of self-advocacy among cancer patients: A qualitative meta-synthesis

Background During cancer treatment, patients are faced with major changes in physical function, psychological challenges and decline in quality of life. Self-advocacy is a key tool for patients to cope with the challenges of treatment. By fostering self-advocacy, patients can effectively self-manage, enhancing their overall quality of life and treatment outcomes. Besides, a significant majority of cancer patients encounter barriers when attempting to articulate their healthcare needs and engage in treatment decision-making processes. It’s important to identify obstacles in the process of self-advocacy. The aim of this meta-synthesis was to describe the patients’ experience of self-advocacy, and identify the facilitators and barriers of self-advocacy for cancer patients. Methods The review used the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidelines guided reporting, and appraised the quality of each eligible study using the Critical Appraisal Skills Programme (CASP) checklist. A prospective review protocol was registered in the International Prospective Register of Systematic Reviews(no: CRD42023493926). A qualitative meta-synthesis was performed by searching eight electronic databases, including PubMed, Web of Science, Embase, Ovid MEDLINE, CINAHL, CNKI, Wanfang and SinoMed for studies meeting pre-defined eligibility criteria, from inception to November, 2023. Two reviewers independently undertook screening and review of articles, using the CASP checklist for evaluating qualitative research. The data were synthesised using Thomas and Harden’s method of thematic and content analysis. Results A total of 7 papers were included, and 24 research findings were distilled and integrated into three themes: benefits; challenges; external environmental support; and seven sub-themes: Gain confidence; improve self-management ability; Interaction and share; lack of awareness; obstacles; health system support and social support. Conclusions Cancer patients have different levels of self-advocacy ability, which is the result of the interaction between personal consciousness and family and social environment. Factors influencing self-initiative include patient gender, personality characteristics, support from friends and family, and support from the medical system. Therefore, medical staff should pay more attention to cancer patients with weak awareness of self-advocacy and poor enthusiasm and can use patient friend exchange meetings and entertainment interventions to improve patients ‘level of self-advocacy. Future interventions should comprehensively consider the characteristics of cancer patients themselves and their external environment, and engage in multidisciplinary team cooperation.

Inferential procedures for random effects in generalized linear mixed models

We study three commonly applied measures of uncertainty for random effects prediction in generalized linear mixed models (GLMMs), namely the unconditional and conditional mean squared errors of prediction (UMSEP and CMSEP, respectively), and the unconditional variance of the prediction gap used by the popular R package for glmmTMB. We demonstrate that, although the three theoretical measures differ in how they quantify uncertainty, the resulting estimators all turn out to be very similar in form. We derive asymptotic results regarding the consistency of the three measures of uncertainty, and in doing so resolve a contradiction between theoretical and empirical results for the glmmTMB variance estimator by re-interpreting it conditionally on a finite subset of the random effects. Our results have important implications for predictive inference in GLMMs, particularly around the legitimacy and implications of coupling these measures with a normality assumption to construct prediction intervals for the random effects.

‘Big leap’ for Parkinson’s treatment: symptoms improve in stem-cell trials

Drivers of rodent community structure in an Urban National Park, Kenya

Nairobi National Park (NNP) is among Kenya’s most vulnerable ecosystems, experiencing significant pressure from urbanization. Rodents, which are sensitive to environmental changes, are considered bioindicators of ecosystem health, and their population dynamics can be used to assess ecosystem pressures such as urbanization. This study assessed the rodent community structure in NNP to understand the effects of various urban pressures by examining the relationships between rodent diversity, richness, and abundance with vegetation types and metrics, seasonality, and habitat disturbances. The capture-mark-release method was used to trap rodents from 15 sites in Nairobi National Park’s savannah, forest, and riverine vegetation types during the dry and wet seasons. The diversity, species richness and abundance were determined from the trappings. From 56 rodents trapped, five species were identified namely: Lemniscomys striatus, Hylomyscus sp, Rattus rattus, Mus mus and Otomys tropicalis. Rodent diversity at NNP was low (Simpson=0.7130; Shannon Weiner=1.40; Brillouin index=1.27) while Pielou’s species evenness, was moderate=0.44 indicating near equity in species distribution. Univariate Generalised linear models showed that rodent abundance was influenced by season, vegetation type, and vegetation metrics. The multivariate model indicated that rodents were more abundant in the wet season compared to the dry season, and that abundance was also positively associated with increased tree and shrub densities. Rodent species richness was positively associated with higher tree density, while vegetation types influenced rodent species diversity. Rodent abundance was influenced by vegetation type, vegetation metrics (density and cover), and season. Human disturbance had no effect in both models. It was observed that the diverse anthropogenic activities occurring in NNP, do not significantly influence rodent abundance compared to the measured biotic and abiotic factors. This first rodent survey in this Park provides preliminary data for continued monitoring of this ecosystem.

Prevalence of Hepatitis C viral infection in Ghana: A systematic review and meta-analysis protocol

Background Hepatitis C virus (HCV) infection remains a major public health concern for many countries. A recent survey report in Ghana revealed a national HCV prevalence rate of 4.6% in a population of 35 million but with notably higher regional variations ranging from 8.6 to 14.4%. Considering that Ghana is targeting micro-elimination of HCV as part of the STOP Hepatitis C project, it is prudent to estimate the current epidemiological burden of hepatitis C for evidence-based policymaking, public health research, and program direction. An initial search of the literature showed a previous review that spanned from 1995 to 2015. The gap of almost 10 years may not reflect the current burden of hepatitis C in Ghana, hence this review. A systematic literature search will be performed in the major electronic databases and search engines including PubMed, Embase, Web of Science, CINAHL, and African Journals Online (AJOL). There will be a search for articles reporting on the prevalence of hepatitis C in Ghana from 2016 to 2024 in these databases. The protocol is registered with PROSPERO (CRD42024592505).

Multi-omics profiles of chronic low back pain and fibromyalgia—Study protocol

Background Chronic low back pain (CLBP) and fibromyalgia (FM) are leading causes of suffering, disability, and social costs. Current pharmacological treatments do not target molecular mechanisms driving CLBP and FM, and no validated biomarkers are available, hampering the development of effective therapeutics. Omics research has the potential to substantially advance our ability to develop mechanism-specific therapeutics by identifying pathways involved in the pathophysiology of CLBP and FM, and facilitate the development of diagnostic, predictive, and prognostic biomarkers. We will conduct a blood and urine multi-omics study in comprehensively phenotyped and clinically characterized patients with CLBP and FM. Our aims are to identify molecular pathways potentially involved in the pathophysiology of CLBP and FM that would shift the focus of research to the development of target-specific therapeutics, and identify candidate diagnostic, predictive, and prognostic biomarkers. Methods We are conducting a prospective cohort study of adults ≥18 years of age with CLBP (n=100) and FM (n=100), and pain-free controls (n=200). Phenotyping measures include demographics, medication use, pain-related clinical characteristics, physical function, neuropathic components (quantitative sensory tests and DN4 questionnaire), pain facilitation (temporal summation), and psychosocial function as moderator. Blood and urine samples are collected to analyze metabolomics, lipidomics and proteomics. We will integrate the overall omics data to identify common mechanisms and pathways, and associate multi-omics profiles to pain-related clinical characteristics, physical function, indicators of neuropathic pain, and pain facilitation, with psychosocial variables as moderators. Discussion Our study addresses the need for a better understanding of the molecular mechanisms underlying chronic low back pain and fibromyalgia. Using a multi-omics approach, we hope to identify converging evidence for potential targets of future therapeutic developments, as well as promising candidate biomarkers for further investigation by biomarker validation studies. We believe that accurate patient phenotyping will be essential for the discovery process, as both conditions are characterized by high heterogeneity and complexity, likely rendering molecular mechanisms phenotype specific.

Unlocking the diversity of wild and domesticated rice

Social subordination is associated with better cognitive performance and higher theta coherence of the mPFC-vHPC circuit in male rats

Social dominance hierarchy is considered an influential factor on cognitive performance. The spatial working memory (SWM) is inversely related to dominance status after the formation of social hierarchy. However, their neural underpinings are poorly understood. The medial prefrontal cortex (mPFC) and ventral hippocampus (vHPC) play pivotal roles in social hierarchy and SWM. To investigate the associations between social hierarchy and SWM and their neural circuit (mPFC-vHPC), we used twenty one natal male Wistar rats after weaning (3 rats per cage, 7 cages in total). In the 9th postnatal week, the tube test was started to determine the relative social rank in each cage (dominant, middle-ranked, subordinate). One month after living in the hierarchy, we implanted electrodes in mPFC and vHPC. One week following recovery, the SWM test was performed using T-maze with two difficulty levels (30s and 5min delays between trials) while recording the local field potentials. The percentage of correct responses showed no significant difference among three different social groups. However, subordinates demonstrated significantly lower latency in reaching the goal arm, while middle-ranked rats exhibited the longest latency in 30s delay. Electrophysiological data revealed significantly higher theta correlation and coherence of the mPFC-vHPC circuit in subordinates. Although theta rhythm synchronization was reduced in all social ranks by increasing task difficulty, the subordinates maintained better task performance and less reduction of theta coherence. These findings underscore the association between social hierarchy and working memory performance within the mPFC-vHPC circuit, highlighting the influence of social rank on implicated circuit.

Carbon emissions accounting and uncertainty analysis in campus settings: A case study of a university in Sichuan, China

Within the context of advancing global sustainable development goals, universities are recognized as leaders in energy conservation and emissions reduction within the education sector. Universities should actively engage in the accounting and analysis of carbon emissions. This study uses Sichuan University Jinjiang College(Hereafter referred to as J University) in Sichuan, China, as a case study, where the campus’s carbon emissions for the year 2023 were calculated using the Emission Factor Method and the Delphi Method. The uncertainty associated with these emissions was further explored using Monte Carlo simulation. The results indicate that the net carbon emissions of J University amounted to 44,584.33 tons of CO2 equivalent (tCO2e), with per capita emissions of 1.89 tCO2e. The primary sources of campus carbon emissions, in descending order, include electricity (18879.94tCO2e), natural gas (8647.25tCO2e), business travel (5224.55tCO2e), campus commuting (3852.33tCO2e), food (3444.67tCO2e), and thermal energy (2566.63tCO2e). Among these sources, the carbon emissions from electricity, natural gas, and thermal energy were closely correlated with seasonal and regional factors. The uncertainties related to commuting and business travel had the most significant impact on the overall carbon emissions accounting for the campus. The study presents a framework for campus carbon emission accounting, providing a concrete case study for future researchers in this field. In particular, an in-depth exploration of statistical uncertainties is conducted, offering a scientific basis for the accurate calculation of carbon emissions in future studies.

Engineering the green algae Chlamydomonas incerta for recombinant protein production

Chlamydomonas incerta, a genetically close relative of the model green alga Chlamydomonas reinhardtii, shows significant potential as a host for recombinant protein expression. Because of the close genetic relationship between C. incerta and C. reinhardtii, this species offers an additional reference point for advancing our understanding of photosynthetic organisms, and also provides a potential new candidate for biotechnological applications. This study investigates C. incerta’s capacity to express three recombinant proteins: the fluorescent protein mCherry, the hemicellulose-degrading enzyme xylanase, and the plastic-degrading enzyme PHL7. We have also examined the capacity to target protein expression to various cellular compartments in this alga, including the cytosol, secretory pathway, cytoplasmic membrane, and cell wall. When compared directly with C. reinhardtii, C. incerta exhibited a distinct but notable capacity for recombinant protein production. Cellular transformation with a vector encoding mCherry revealed that C. incerta produced approximately 3.5 times higher fluorescence levels and a 3.7-fold increase in immunoblot intensity compared to C. reinhardtii. For xylanase expression and secretion, both C. incerta and C. reinhardtii showed similar secretion capacities and enzymatic activities, with comparable xylan degradation rates, highlighting the industrial applicability of xylanase expression in microalgae. Finally, C. incerta showed comparable PHL7 activity levels to C. reinhardtii, as demonstrated by the in vitro degradation of a polyester polyurethane suspension, Impranil® DLN. Finally, we also explored the potential of cellular fusion for the generation of genetic hybrids between C. incerta and C. reinhardtii as a means to enhance phenotypic diversity and augment genetic variation. We were able to generate genetic fusion that could exchange both the recombinant protein genes, as well as associated selectable marker genes into recombinant offspring. These findings emphasize C. incerta’s potential as a robust platform for recombinant protein production, and as a powerful tool for gaining a better understanding of microalgal biology.

Do ban-the-box policies increase the hiring of applicants with criminal records?

Many United States jurisdictions have enacted Ban-the-Box (BTB) laws that are intended to improve the employment prospects of individuals with criminal records. The best-known feature of BTB statutes is a “screening ban:” employers cannot inquire about a criminal record until they have made a conditional offer of employment. Many BTB statutes contain a less well-known “use prohibition:” employers cannot withdraw a conditional offer based on a criminal record unless that record is sufficiently related to fulfillment of potential job duties. In this paper we provide the first evidence of the association of BTB policies with variation in the progression of candidates through hiring phases after the screening process. We use unique applicant-level data obtained from an employer before and after it voluntarily implemented a BTB policy. We find that the enactment of the BTB policy has little or no association with the rate at which individuals with criminal records survive the candidate assessment process and receive conditional employment offers. Indeed, our findings suggest a modest indication of a negative association between the implementation of BTB policies and the hiring of individuals with prior convictions for specific offenses. The observed pattern could be explained if, after losing access to criminal history, employers increase their reliance on hiring criteria that are correlated to criminal history. We also find that the rate at which individuals with a criminal record survive a final background check does not change after the implementation of the joint BTB policies. We find weak evidence that implementation of the two BTB policies is associated with worse outcomes for individuals with records of more serious offenses.

Within dead branches

Ferroptosis regulation by traditional chinese medicine for ischemic stroke intervention based on network pharmacology and data mining

Objective The aim of this study is to use network pharmacology and data mining to explore the role of traditional Chinese medicine (TCM) in ischemic stroke (IS) intervention by ferroptosis regulation. The results will provide reference for related research on ferroptosis in IS. Methods The ferroptosis-related targets were obtained from the GeneCards, GeneCLiP3, and FerrDdb databases, while the IS targets were sourced from the GeneCards and DisGeNET databases. Venny was used to identify IS targets associated with ferroptosis. A protein-protein interaction (PPI) analysis was then conducted, and machine learning screening was used to validate these potential targets. The potential targets that met specific criteria and their related compounds allowed us to select TCMs. A mechanistic analysis of the potential targets was conducted using the DAVID database. PPI network diagrams, target-compound network diagrams, and target-compound-TCM network diagrams were then constructed. Finally, molecular docking technology was used to verify the binding activities of the TCM compounds and core components with the identified targets. In addition, the properties, flavors, meridian tropism, and therapeutic effects of the candidate TCMs were analyzed and statistically evaluated. Results A total of 706 targets associated with ferroptosis in IS were obtained, and 14 potential ferroptosis targets in IS were obtained using machine learning. Furthermore, 413 compounds and 301 TCMs were screened, and the binding activities of the targets to the TCM compounds and the core prescriptions were stable. The candidate TCMs primarily exhibited cold, warm, bitter taste, pungent taste, liver meridian, heat-cleaning medicinal, and tonify deficiency properties. Conclusions This study investigated ferroptosis regulation for IS intervention using TCM. We began by investigating the targets of IS and ferroptosis, and we also analyzed the relevant mechanism of ferroptosis in IS. The results of this study provide reference for related research on ferroptosis in IS.

Post-Discharge non-invasive ventilation for hypercapnic respiratory failure: Outcomes in a Rural Cohort

Rationale Patients with acute-on-chronic hypercapnic respiratory failure suffer from recurrent readmissions due to acute exacerbations. These patients carry higher readmission and mortality rates compared to the general population. Objectives We aimed to delineate the outcomes of patients discharged on non-invasive ventilation. Methods A cross-sectional study was conducted. One hundred nine patients with acute-on-chronic hypercapnic respiratory failure were evaluated and qualified for non-invasive ventilation at discharge. Adherence data was collected post-discharge and the following outcomes were evaluated: 12-month mortality, 6-month hospital readmission, and emergency department visits in patients who were adherent with non-invasive ventilation therapy versus non-adherent and controls. Measurements and main results Of the 95 patients discharged on non-invasive ventilation, 25 patients (26%) were found to be adherent to post-discharge home non-invasive ventilation. The adherent group had significantly lower 12-month mortality (p=0.022). Survival benefit persisted on multivariate analysis with the Cox regression model adjusting for comorbidities and demographics (HR = 0.05, p=0.04). The study also observed reduced emergency department visits in the non-invasive ventilation-adherent group compared to the non-adherent (3% vs 17%) [p=0.049] and controls (3% vs 25%) [p=0.024]. Conclusions Hypercapnic respiratory failure patients discharged home with non-invasive ventilation in the adherent group had significantly lower mortality and emergency department visits. Apart from mask intolerance, low health literacy and transfer to skilled nursing facilities were identified as major reasons for non-adherence.