Browse Articles

After boom

Retraction: Transcultural validation of the “revised sport motivation scale” (SMS‐II) in Arabic language: Exploratory study on motivation in sport for a sample of Tunisian Athletes

Trapping Anions within Stacks of Tetra-Urea Macrocycles

Nurses’ knowledge and its determinants in surgical site infection prevention: A comprehensive systematic review and meta-analysis

Objective The objective of this systematic review and meta-analysis is to assess and synthesize the global evidence on the level of nurses’ knowledge and its determinants regarding the prevention of surgical site infections. Methods This systematic review and meta-analysis were conducted following strict methodological guidelines to ensure accuracy and reliability. Adhering to the 2020 PRISMA checklist, a systematic review and meta-analysis sought to establish the pooled proportion of nurse’s knowledge and its determinants regarding surgical site infection prevention globally. MeSH terms and keywords were included in the search. Data extraction, quality assessment, and analysis followed established protocols. Heterogeneity and publication bias was assessed using STATA version 17.0. Results A total of seventeen observational studies, with sample sizes ranging from 30 to 515 participants, were included in the final analysis in a global context. In this systematic review and meta-analysis, the pooled proportion of nurses with good knowledge of surgical site infection prevention is 62% (95% CI: 50–74%) when assessed using a dichotomous scale. However, when knowledge is measured using a three-point Likert scale, the pooled proportion of those with good knowledge drops to 46% (95% CI: 21–72%), with an additional 27% (95% CI: 16–38%) demonstrating fair or moderate knowledge. Conclusion and recommendation This systematic review and meta-analysis is the first to synthesize data on nurses’ knowledge of surgical site infection (SSI) prevention. The findings reveal poor knowledge levels, highlighting the need for targeted educational interventions globally. While the pooled odds ratio is not statistically significant, training, longer service years, and higher education improve SSI prevention knowledge by enhancing critical thinking, boosting confidence, and fostering adherence to evidence-based practices. Future research should focus on identifying factors influencing nurses’ knowledge, particularly through longitudinal and interventional studies. Policymakers should incorporate international guidelines such as those recommended by the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC) into nursing curricula, supported by robust assessment tools and educator training, to improve knowledge transfer and implementation of best practices.

Arsenic efflux and bioremediation potential of Klebsiella oxytoca via the arsB gene

Arsenic-resistant Klebsiella oxytoca strain AT-02 was isolated from the ground water of the Multan region of Pakistan. The strain displayed high arsenite and arsenate resistance as minimal inhibitory concentration (MIC) was 600ppm and 10,000ppm respectively. The high tolerance of the isolated strain towards arsenate can be postulated due to significant increase in biofilm in response to arsenate. The bacterial strain exposed to 1/2 and 3/4 MIC showed a significant 10 and 12 folds increase in expression of the arsenite efflux gene arsB. Sequential and structural comparison of the arsB gene showed the presence of conserved arsenic binding residues. Arsenic remediation by AT-02 biomass was 50% after 0.5 hours of incubation and 66% in 2 hours. the increase in remediation efficiency with the increase in incubation time indicates its biosorption potential. the arsenic sensitive strain NK11 showed only 4–5% arsenic remediation. Fourier transform infrared spectroscopy (FTIR) analysis confirmed interaction of arsenate and arsenite with functional groups (aromatic amino acid residues) on the cell surface leading to characteristic peak shifts. Thus, the isolated AT-02 has the potential to remediate both arsenite and arsenate from contaminated environmental sites.

Accuracy of latest large language models in answering multiple choice questions in dentistry: A comparative study

Objectives This study aims to evaluate the performance of the latest large language models (LLMs) in answering dental multiple choice questions (MCQs), including both text-based and image-based questions. Material and methods A total of 1490 MCQs from two board review books for the United States National Board Dental Examination were selected. This study evaluated six of the latest LLMs as of August 2024, including ChatGPT 4.0 omni (OpenAI), Gemini Advanced 1.5 Pro (Google), Copilot Pro with GPT-4 Turbo (Microsoft), Claude 3.5 Sonnet (Anthropic), Mistral Large 2 (Mistral AI), and Llama 3.1 405b (Meta). χ2 tests were performed to determine whether there were significant differences in the percentages of correct answers among LLMs for both the total sample and each discipline (p < 0.05). Results Significant differences were observed in the percentage of accurate answers among the six LLMs across text-based questions, image-based questions, and the total sample (p<0.001). For the total sample, Copilot (85.5%), Claude (84.0%), and ChatGPT (83.8%) demonstrated the highest accuracy, followed by Mistral (78.3%) and Gemini (77.1%), with Llama (72.4%) exhibiting the lowest. Conclusions Newer versions of LLMs demonstrate superior performance in answering dental MCQs compared to earlier versions. Copilot, Claude, and ChatGPT achieved high accuracy on text-based questions and low accuracy on image-based questions. LLMs capable of handling image-based questions demonstrated superior performance compared to LLMs limited to text-based questions. Clinical relevance Dental clinicians and students should prioritize the most up-to-date LLMs when supporting their learning, clinical practice, and research.

Strange flashes from ancient galaxy deepen mystery of fast radio bursts

Effects of intrathecal administration of sodium nitroprusside and nicardipine on cerebral pial microcirculation, cortical tissue oxygenation, and electrocortical activity in the early post-resuscitation period in a porcine cardiac arrest model

Recent studies suggested intrathecal vasodilator administration as a therapy to mitigate post-ischemic cerebral hypoperfusion following cardiac arrest. We examined the effects of two commonly used intrathecal vasodilators, sodium nitroprusside (SNP) and nicardipine, on cerebral pial microcirculation, cortical tissue oxygen tension (PctO2), and electrocortical activity in the early post-resuscitation period using a porcine model of cardiac arrest. Thirty pigs were resuscitated after 14 min of untreated cardiac arrest. At 30 min after resuscitation from cardiac arrest, 30 pigs randomly received 4 mg of SNP, 4 mg of nicardipine, or saline placebo via subdural intracranial catheters and were observed for 5 h. Group effect and group-time interaction were assessed using linear mixed-effects models. The mean arterial pressure was lower in the nicardipine group (coefficient [95% confidence interval {CI}], -15.824 [-24.082 to -7.566]) and higher in the SNP group (coefficient [95%CI], 11.232 [2.974–19.490]) compared to the saline group. The percentage of pial arteriole diameter relative to the pre-arrest baseline value (coefficient [95% CI], 48.970 [13.884–84.057]), microvascular flow index (coefficient [95% CI], 0.296 [0.071–0.521]), and PctO2 (coefficient [95% CI], 26.926 [12.404–41.449]) were higher in the SNP group but not in the nicardipine group compared to the saline group. Amplitude-integrated electroencephalography amplitude recovery was faster in the SNP group (coefficient [95% CI], 1.149 [0.468–1.829]) but not in the nicardipine group compared to the saline group. In conclusion, intrathecal SNP but not nicardipine was effective in treating post-ischemic cerebral hypoperfusion after cardiac arrest.

Effects of cold-water immersion on health and wellbeing: A systematic review and meta-analysis

Background Cold-water immersion (CWI) has gained popularity as a health and wellbeing intervention among the general population. Objective This systematic review and meta-analysis aimed to evaluate the psychological, cognitive, and physiological effects of CWI in healthy adults. Methods Electronic databases were searched for randomized trials involving healthy adults aged ≥ 18 years undergoing acute or long-term CWI exposure via cold shower, ice bath, or plunge with water temperature ≤15°C for at least 30 seconds. Outcomes of interest were sleep, stress, fatigue, energy, skin health, immunity, inflammation, mental wellbeing, depression, anxiety, mood, concentration, and alertness or focus. Meta-analyses were conducted using RevMan software (version 5.4), applying random effects models to calculate standardized mean differences (SMD) between pre- and post-CWI exposure outcomes. Risk of bias was assessed using the PEDro scale. Results Eleven studies were included, comprising 3177 total participants and a mean PEDro score of 6.4 (n = 7 moderate quality, n = 4 high quality). CWI interventions were performed in baths (n = 10) or showers (n = 1) at temperatures ranging from 7°C to 15°C and durations ranging from 30 seconds to 2 hours. The meta-analysis revealed significant increases in inflammation immediately (SMD: 1.03, [95% CI: 0.37, 1.68], p <  0.01) and 1 hour post CWI (SMD: 1.26, [95% CI: 0.59, 1.94], p <  0.01), indicating an acute inflammatory response. A significant reduction in stress was observed 12 hours post-CWI (SMD: –1.00, [95% CI: –1.40, –0.61], p <  0.01), however, no significant effects on stress were detected immediately (SMD: –0.09 [95% CI: –0.45, 0.63], p >  0.05), 1 hour (SMD: –0.29 [95% CI: –0.66, 0.08], p >  0.05), 24 hours (SMD: –0.06 [95% CI: –0.50, 0.38], p >  0.05), or 48 hours (SMD: 0.09 [95% CI: –0.28, 0.46], p >  0.05) post-exposure. While meta-analysis showed no significant effects on immune function immediately (SMD: –0.16 [95% CI: –0.82, 0.51], p >  0.05) or 1 hour (SMD: –0.18 [95% CI: –1.09, 0.74], p >  0.05) post-CWI, narrative synthesis suggested longer-term benefits, including a 29% reduction in sickness absence among participants who took cold showers. Improvements were also observed in sleep quality and quality of life, but not mood. Conclusions This systematic review suggests that CWI delivers time-dependent effects on inflammation, stress, immunity, sleep quality, and quality of life, offering potential practical applications for health practitioners considering CWI for stress management and wellbeing support. However, the current evidence base is constrained by few RCTs, small sample sizes, and a lack of diversity in study populations. Future high-quality RCTs are needed to examine the long-term effects of CWI, its impact on diverse health outcomes, and optimal CWI protocols. PROSPERO (ID: CRD42024500591)

Daily briefing: Chaos erupts in US science as Trump’s team declares freeze on federal grants

Methanol-Enhanced Low-Cell-Voltage Hydrogen Generation at Industrial-Grade Current Density by Triadic Active Sites of Pt₁–Pd<i>_n</i>–(Ni,Co)(OH)_<i>x</i>

Measurement of population agglomeration, dynamic change characteristics, and motivations in metropolitan agglomerations—A case study of the Xi’an metropolitan area

This article compares the population agglomeration characteristics of the Xi’an metropolitan area in western China with those of metropolitan areas in other regions officially approved by the Chinese government. The kernel density estimation method and Markov chain model were used to conduct the study. The results revealed that from 2010 to 2020, the population agglomeration level of the Xi’an metropolitan area showed a trend of first increasing and then decreasing. The absolute gap in the population agglomeration level between cities within the metropolitan area gradually narrowed, and the polarization phenomenon of population agglomeration was not obvious. Compared with metropolitan agglomerations such as Nanjing, Wuhan, Fuzhou, Changsha-Zhuzhou-Xiangtan, Chongqing, and Chengdu, the Xi’an metropolitan agglomeration had a lower population agglomeration level, with a significant gap. Moreover, there was an obvious “club convergence” phenomenon in the population agglomeration levels of different urban agglomerations. The probability of the population agglomeration level remaining stable was at least 53.85%, indicating that there was a “Matthew effect” in which the rich become richer and the poor become poorer. Through the convergence models of α and β, the analysis suggested that there was no significant α convergence between the population agglomeration level of the Xi’an metropolitan agglomeration and that of other metropolitan agglomerations. Instead, there was a significant β divergence, indicating that the gap between the Xi’an metropolitan agglomeration’s population agglomeration level and that of other metropolitan agglomerations is gradually widening. An integrated theoretical framework of population agglomeration was constructed from three dimensions: producers, consumers, and social people. An empirical analysis was conducted on the causes of population agglomeration in the Xi’an metropolitan area and other metropolitan areas. The multiple regression results showed that the income level, public consumption expenditure level, education level, comfortable living environment, and educational level were important factors leading to differences in population agglomeration. The geographic detector results showed that factors in the consumer dimension were the main reasons for population agglomeration in metropolitan areas.

Evidence that engineered muscle could patch up failing hearts

Relationships between multivitamins, blood biochemistry markers, and BMC and BMD based on RF: A cross-sectional and population-based study of NHANES, 2017–2018

Background Previous studies have separately suggested a possible association between the vitamin exposure, blood biochemical indicators, and bone density. Our study aimed to investigate the relationship between vitamin exposure serum concentrations, blood biochemical indicator serum concentrations, and BMC and BMD using the NHANES 2017–2018 nutrient survey data. This population-based cross-sectional study aimed to explore these associations. Methods In this study, we measured vitamin serum concentrations, serum ion serum concentrations, and serum biochemical indicators in adults participating in the NHANES . Skeletal status was assessed by evaluating BMC and BMD in the whole body. Given the inclusion of multiple variables and diverse data types, we used the RF to fit a multivariable model to estimate the associations between vitamin serum concentrations, blood biochemical indicator serum concentrations, and skeletal status. Results Under the dimension reduction and comparison selection of RF model, we identified ALP , CPK , and creatinine serum concentrations as the most important factors associated with BMC and BMD in multiple skeletal sites, and the gender, age, height, weight, and body mass index which were found to be related to BMC and BMD in different skeletal sites. Vitamin D and blood calcium serum concentrations were not the important factors associated with BMC and BMD and the three blood biochemical indexes were more important than the vitamin level for BMC and BMD . Conclusion The effect of vitamin serum concentrations and blood calcium serum concentrations on human bone density was not significant. ALP , CPK and creatinine serum concentrations body development indicators were identified as the most important factors related to bone status. The RF model can be used to comprehensively evaluate the effects of vitamin content and blood biochemistry serum concentrations in adults on BMC and BMD.

Antarctic ice shelf kept its cool during the last interglacial period

Correction: Towards an affect intensity regulation hypothesis: Systematic review and meta-analyses of the relationship between affective states and alcohol consumption

Anxiety among cancer patients: A cross-sectional study at The University of Gondar comprehensive specialized hospital

Introduction Anxiety is a prevalent psychological issue among cancer patients, significantly affecting their quality of life and potentially influencing treatment outcomes. This study aims to investigate the prevalence and associated factors of anxiety among cancer patients at the University of Gondar Comprehensive Specialized Hospital in Northwest Ethiopia. Methods A cross-sectional study design was used, involving 384 cancer patients, selected by systematic random sampling technique, from the oncology ward. Data were collected using the Generalized Anxiety Disorder 7-item (GAD-7) scale and the Oslo Social Support Scale (OSS-3). Descriptive and inferential statistics, including bi-variable and multi-variable logistic regression analyses, were employed to analyze the data. Results The prevalence of anxiety was 88.3%, with 34.4% of patients experiencing severe anxiety, 29.2% moderate anxiety, and 24.7% mild anxiety. Significant predictors of anxiety included participants age&gt;= 61years (AOR =  2.99, 95% CI =  1.31–6.79), participants age 30-60 years (AOR =  4.13, 95% CI =  1.53–11.07), female sex (AOR =  2.04, 95% CI =  1.02–4.07), advanced cancer stage (AOR =  3.08, 95% CI =  1.11–8.53), and ongoing treatment (AOR =  2.40, 95% CI =  1.14–5.10). Conclusion The study found a high prevalence of anxiety among cancer patients, compared to the previous studies, highlighting the need for integrated psycho-oncology services. Specific interventions are necessary for high-risk groups, including older patients, females, and those with advanced-stage cancer.

Large exciton binding energy in a bulk van der Waals magnet from quasi-1D electronic localization

Heterogeneity analysis provides evidence for a genetically homogeneous subtype of bipolar-disorder

Background Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. One way to assess this heterogeneity is to look for patterns in the subphenotype data. Because of the variability in how phenotypic data was collected by the various BD studies over the years, homogenizing this subphenotypic data is a challenging task, and so is replication. An alternative methodology, taken here, is to set aside the intricacies of subphenotype and allow the genetic data itself to determine which subjects define a homogeneous genetic subgroup (termed ‘bicluster’ below). Results In this paper, we leverage recent advances in heterogeneity analysis to look for genetically-driven subgroups (i.e., biclusters) within the broad phenotype of Bipolar Disorder. We first apply this covariate-corrected biclustering algorithm to a cohort of 2524 BD cases and 4106 controls from the Bipolar Disease Research Network (BDRN) within the Psychiatric Genomics Consortium (PGC). We find evidence of genetic heterogeneity delineating a statistically significant bicluster comprising a subset of BD cases which exhibits a disease-specific pattern of differential-expression across a subset of SNPs. This disease-specific genetic pattern (i.e., ‘genetic subgroup’) replicates across the remaining data-sets collected by the PGC containing 5781/8289, 3581/7591, and 6825/9752 cases/controls, respectively. This genetic subgroup (discovered without using any BD subtype information) was more prevalent in Bipolar type-I than in Bipolar type-II. Conclusions Our methodology has successfully identified a replicable homogeneous genetic subgroup of bipolar disorder. This subgroup may represent a collection of correlated genetic risk-factors for BDI. By investigating the subgroup’s bicluster-informed polygenic-risk-scoring (PRS), we find that the disease-specific pattern highlighted by the bicluster can be leveraged to eliminate noise from our GWAS analyses and improve risk prediction. This improvement is particularly notable when using only a relatively small subset of the available SNPs, implying improved SNP replication. Though our primary focus is only the analysis of disease-related signal, we also identify replicable control-related heterogeneity.

Strength and durability of indirect protection against SARS-CoV-2 infection through vaccine and infection-acquired immunity

Abstract Early investigation revealed a reduced risk of SARS-CoV-2 infection among social contacts of COVID-19 vaccinated individuals, referred to as indirect protection. However, indirect protection from SARS-CoV-2 infection-acquired immunity and its comparative strength and durability to vaccine-derived indirect protection in the current epidemiologic context of high levels of vaccination, prior infection, and novel variants are not well characterized. Here, we show that both vaccine-derived and infection-acquired immunity independently yield indirect protection to close social contacts with key differences in their strength and waning. Analyzing anonymized SARS-CoV-2 surveillance data from 9,625 residents in California state prisons from December 2021 to December 2022, we find that vaccine-derived indirect protection against Omicron SARS-CoV-2 infection is strongest within three months of COVID-19 vaccination [30% (95% confidence interval: 20–38%)] with subsequent modest protection. Infection-acquired immunity provides 38% (24–50%) indirect protection for 6 months after SARS-CoV-2 infection, with moderate indirect protection persisting for over one year. Variant-targeted vaccines (bivalent formulation including Omicron subvariants BA.4/BA.5) confer strong indirect protection for at least three months [40% (3–63%)]. These results demonstrate that both vaccine-derived and infection-acquired immunity can reduce SARS-CoV-2 transmission which is important for understanding long-term transmission dynamics and can guide public health intervention, especially in high-risk environments such as prisons.