Browse Articles

Minimizing Urban Carbon Emissions and Heat Island Intensity: A theoretical study

Cities exhibit both beneficial and detrimental characteristics, many of which stem from agglomeration effects and are, to a first approximation, influenced by population size. However, urban density also plays a critical role. For example, cities with similar population sizes but higher densities tend to emit less carbon, while simultaneously exhibiting a more pronounced urban heat island (UHI) effect. This trade-off highlights the need for a balanced approach that simultaneously minimizes both carbon emissions and the urban heat island (UHI) effect. To address this challenge, we examine how both carbon emissions and UHI intensity are influenced by the population size and spatial extent of the cities. As objective function we define the some of both quantities where city population and area are variables. Considering the scaling relation between area and population as constraint, we derive a theoretical expression leading to an optimal city size. To validate our approach, we analyze carbon emissions data from cities in Germany and consider UHI parameters from the literature. We find that, in the specific case of German cities, achieving an optimal city size that simultaneously minimizes both carbon emissions and UHI intensity is not physically feasible. From a methodological perspective, only the UHI intensity parameters, together with the exponent of the relationship between population and area, determine whether an optimum exists or not. We argue that instead, the scaling relation between population and area itself should be understood as an optimum.

Forecasting and analysing global average temperature trends based on LSTM and ARIMA models

Previous studies have demonstrated a significant correlation between global average temperature change trends and greenhouse gases, and employed various prediction models. However, the potential of the combination of the LSTM and ARIMA models for temperature forecasting has not been fully explored, especially in terms of enhancing prediction accuracy. Based on the hypothesis that COVID-19 has affected the global average temperature, this study utilizes global average temperature data from 1880 to 2022. We combine the LSTM model, which excels at capturing long-term dependencies, with the ARIMA model, known for its effectiveness in handling linear time series data, to predict the global mean temperature. This combination compensated for the limitations of individual models, providing a more accurate and comprehensive temperature forecast. Our findings reveal that the early trend of global temperature rise is significant, yet the implementation delay leads to severe issues. Moreover, COVID-19 has indirectly reduced greenhouse gas emissions, slowing global warming. Additionally, we find that the correlation between longitude and mean temperature is weak, while the correlation between latitude and temperature is strongly negative. This study offers valuable insights and provides a reliable prediction method for ecological environment governance and the formulation of economic construction policies.

An integrated blockchain and IPFS-based solution for secure and efficient source code repository hosting using middleman approach

Centralized version control systems (VCS) are vital for software development but pose risks of data loss and ownership disputes. While blockchain offers a decentralized alternative, existing solutions are often hindered by high latency, compromising the real-time collaboration essential for modern workflows. This study introduces a novel hybrid architecture combining the security of the Ethereum blockchain and the InterPlanetary File System (IPFS) with two key contributions: 1) Shamir’s Secret Sharing (SSS) to create a trust-minimized model for key distribution, and 2) an authoritative-first, optimistic-fallback retrieval protocol utilizing a temporary middleware to decouple the user experience from blockchain confirmation delays. We implemented a full prototype and conducted a comprehensive performance evaluation on the public Sepolia testnet. Our results demonstrate that this architecture not only provides a secure, auditable, and resilient platform for source code hosting but also achieves highly competitive user-perceived performance. Our user-perceived push time reduces submission latency by up to 49% compared to a standard git push for common repository sizes, proving that a well-designed decentralized VCS can balance the core tenets of security and decentralization with the practical need for speed and efficiency.

Survival of dental implants in irradiated head and neck cancer patients compared to non-irradiated patients: An umbrella review

Background: There is an increasing demand for oral rehabilitation in patients undergoing irradiation for head and neck cancer treatment. Although radiotherapy appears to adversely affect implanted oral rehabilitation, the evidence provided by previous systematic reviews in the field remains controversial. Thus, this umbrella review aimed to evaluate the survival of dental implants installed before and/or after radiotherapy in patients with head and neck cancer compared to those not irradiated. Methods: A comprehensive search of electronic databases was performed in the PubMed, Cochrane Library, Embase, Web of Science, and Google Scholar databases, including manual searches, from inception to February, 2024, with no language or date restrictions. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines were followed. Survival percentage of dental implants was the primary outcome. A Measurement Tool to Assess systematic Reviews (AMSTAR) 2 was used as a critical appraisal tool for the included studies. The protocol for this review has been registered with PROSPERO (CRD42023406059). Results: Of the 1,811 articles screened, 11 articles that evaluated 73,674 implants were included. Quantitative analyses showed 2,674 failures out of 14,471 implants installed in irradiated bone and 1,825 failures out of 34,092 implants in non-irradiated bone. The survival rate was 81.52% for irradiated implants and 94.64% for non-irradiated implants. A significant difference in survival in favor of implants in non-irradiated bone is supported by 11 meta-analyses. The included systematic reviews showed critically low methodological quality. Conclusions: Although the included studies had low methodological quality, the findings indicate a higher failure rate of implants in irradiated patients. Further well-designed clinical studies are warranted.

A scoping review of innovations that promote interprofessional collaboration (IPC) in primary care for older adults living with age-related chronic disease in rural areas

Background and objectives An aging population and associated multi-morbid chronic diseases (CDs) require comprehensive health care across multiple disciplines. Literature suggests interprofessional collaboration (IPC) in primary care is effective for CD models of care. However, IPC requires innovative implementation, particularly in rural and remote areas where access to health care services and providers is often limited. Our main objective was to identify and synthesize the available research evidence on innovations that promote IPC in primary care for older rural adults with CD, identify gaps in the literature, and provide recommendations for future research. Methods Comprehensive and systematic searches were conducted across four scientific databases for peer-reviewed, original research published in English since 1990, resulting in 9,343 records. Following elimination of duplicates, screening, and evaluation, 38 studies were included for synthesis. All studies were described and illustrated by frequency distribution, and findings were grouped thematically. Results Most innovations involved case management and focused on diabetes (n = 15), dementia (n = 12), and hypertension (n = 10). Rural challenges were more prevalent than benefits and mainly involved limited services and resources, while strengths were mainly related to close-knit connections and familiarity with one another. Three main themes regarding benefits of the innovations were: 1) enhanced availability/accessibility, 2) earlier detection/management/support, and 3) improved care. Subthemes included: 2a) education/support, 2b) CD or risk factor outcomes, 3a) care continuity, and 3b) care coordination. Five main gaps in the literature included few studies with age-related CDs other than diabetes, dementia, and hypertension; conducted outside of United States and Canada; randomized controlled trial (RCT) and longitudinal studies; that involved virtual or technology-assisted innovations; and that considered sex and gender in the analysis. Conclusions Several main areas were highlighted including rural strengths and challenges that impacted the innovations, key innovation benefits, and gaps in the literature. Recommendations for future research were made.

Smartphone use on the toilet and the risk of hemorrhoids

Smartphones are ubiquitous in daily life, with many people now using them while sitting on the toilet. Despite anecdotal evidence that length of time spent on the toilet is a risk factor for hemorrhoids, a multivariate analysis of smartphone use has not been performed. This study examines the correlation between smartphone use on the toilet and prevalence of hemorrhoids. A cross-sectional study was conducted among adult patients undergoing screening colonoscopy at Beth Israel Deaconess Medical Center. Participants completed survey questions regarding their smartphone habits while using the toilet, Rome IV questionnaires, and additional behaviors including straining, fiber intake and levels of physical activity. Presence of hemorrhoids were evaluated endoscopically and independently rated by two blinded endoscopists. Categorical variables were analyzed using chi-square tests and linear variables with regression analysis. A total of 125 adult participants completed the survey and 43% had hemorrhoids visualized on colonoscopy. Participants who used smartphones on the toilet were younger than non-users (mean ages 55.4 vs. 62.1, p = 0.001). Of all respondents, 66% used smartphones while on the toilet. Participants who used smartphones on the toilet spent significantly more time there than those who did not, with 37.3% of smartphone users spending more than five minutes per visit on the toilet, compared to 7.1% of non-smartphone users (p = 0.006). Furthermore, in a multivariate logistic regression, smartphone use on the toilet was associated with a 46% increased risk of hemorrhoids (p = 0.044) after adjusting for age, sex, BMI, exercise activity, straining and fiber intake. The most common activity performed while on the toilet was reading “news” (54.3%), followed by “social media” (44.4%). The study suggests that prolonged engagement with smartphones while using the toilet may be associated with an increased prevalence of hemorrhoids.

Correction: Perceived barriers to physical activity and their predictors among adults in the Central Region in Saudi Arabia: Gender differences and cultural aspects

Assessing the burden of severe nausea and vomiting of pregnancy or hyperemesis gravidarum and the associated use and experiences of medication treatments: An Australian consumer survey

Background There is little data on contemporary patterns of antiemetic use or women’s experiences when using such agents in the treatment of severe nausea and vomiting of pregnancy (NVP) or hyperemesis gravidarum (HG). Methods Online, national survey of Australian women who were currently or had previously experienced severe NVP or HG, distributed through the HG consumer group, Hyperemesis Australia between July and September 2020. Results There were a total of 289 respondents with a mean age of 33 years, of which 38% were currently pregnant. More than 50% of respondents reported “major impacts” of the condition on areas such as social life, ability to undertake daily chores, ability to eat or drink, effects on work, taking care of pre-existing children and sleep. This resulted in 62% of respondents reporting ‘often’ or ‘always’ experiencing feelings of depression or anxiety as a result of their HG symptoms, with 54% reporting considering terminating their pregnancy, and 90% having considered having no more children. The most commonly used anti-emetic was ondansetron (91%), followed by pyridoxine (62%), doxylamine (62%), and metoclopramide (61%). Nearly all (95%) women who reported using ondansetron commenced it within the first trimester, with 55% reporting use as a first-line therapy. Most women reported one or more side effects to anti-emetics such as headache, constipation, sedation or impaired cognition, with 31% stopping metoclopramide because of side effects, compared with 14% for ondansetron and 10% for doxylamine. Ondansetron, doxylamine and corticosteroids had the greatest perceived effectiveness, with more than 50% rating them as “effective” or “very effective”. Half (50%) reported use of acid suppressive therapy, with 51% reporting using complementary or alternative therapies in addition to conventional treatments. Conclusions The study findings demonstrate large variability in antiemetic use and outcomes, highlighting the need for individualised care and treatment approaches during pregnancy.

Validity of the German version of the Stay Independent Questionnaire applied by telephone interview: A diagnostic accuracy study

Background Mobility limitations are among the most common functional problems in older people. Repeated falls can lead to injuries and fractures, trigger or intensify concerns of falling, and contribute to subsequent functional decline and loss of independence. Various questionnaires have been developed, both nationally and internationally, to identify older people at increased risk of falling. Data for evaluation against standard tests from the geriatric mobility assessment are scarce. Methods In a German project evaluating home emergency call systems, the Stay Independent Questionnaire (SIQ) from the American prevention program STEADI (Stopping Elderly Accidents, Deaths, and Injuries) was used for the identification of community-dwelling seniors aged 70 and older at risk of falling. The original questionnaire was translated by professional translators using the typical forward and backward translation process, and a final version was established after discussion involving a bilingual scientist. The diagnostic performance of the questionnaire (diagnostic test) was tested against the mobility assessment Short Physical Performance Battery (SPPB, gold standard). To describe the test performance, typical statistical measures are used, i.e., sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios, each with the corresponding 95% confidence interval (95% CI). Results Data from a total of 190 participants (143 women, 75.3%; average age 80.5 years ± 5.5 years standard deviation) were included in the analysis. According to existing comorbidities and functional abilities, between 30% and 40% suffered of advanced comorbidity and/or functional impairment. The questionnaire identified 148 individuals (77.9%) as at risk of falling. According to SPPB, 81 participants had an objectively measurable impairment of standing and walking balance. The test performance measures for SIQ as a diagnostic test are: sensitivity 95.1% 95% CI [88.0%; 98.1%], specificity 34.9% [26.6%; 44.2%], positive and negative predictive value 52.0% [44.0%; 59.9%] and 90.5% [77.9%; 96.2%], respectively, and positive and negative likelihood ratio 1.46 [1.26; 1.69] and 0.14 [0.05; 0.38]. In receiver-operating characteristic (ROC) analysis, the unadjusted area under the curve for SIQ was 65.0% [57.3%; 72.7%], after adjustment for sex and age 71.0% [63.8%; 78.2%]. Conclusions The German version of the Stay Independent Questionnaire is capable of identifying community-dwelling seniors aged 70 and older without impairment in standing and walking balance. The high sensitivity of the test allows excluding test-negative individuals from further investigation. A limitation of the questionnaire is the high proportion of false positives, resulting from the low specificity of the test. Scientific evaluation will show to what extent the use of the questionnaire may improve the identification and medical care of community-dwelling seniors at risk of falling in terms of fall prevention.

Virtual Reality in Awake brain Surgery (VIRAS) stage I: Proof of concept and tolerance validation during scheduled orthopedic surgery

Introduction The VIRAS (Virtual Reality in Awake Surgery) project is a two-stage, adaptive study. Its goal is to demonstrate the tolerance of the virtual reality (VR) headset for performing cognitive neuro-monitoring during awake brain surgery. Awake surgery involves operating on patients who remain conscious during the procedure and is most commonly employed in interventions such as tumor resections and epilepsy treatments. This approach allows surgeons to monitor and preserve critical brain functions by engaging the patient in real-time assessments of motor, sensory, and cognitive capabilities. The use of immersive distractions such as VR can help reduce anxiety and discomfort during awake craniotomy. We present the results of the first stage of the study, conducted in patients undergoing scheduled orthopedic surgery under regional anesthesia, aimed at validating the tolerance and safety of using the VR headset in the operating room. Materials and methods Eligibility required a minimum predicted surgery duration of one hour. All participants received standardized training in the use of VR headset the day before surgery. Investigators supervised intraoperative neurofunctional testing delivered through the VR system. Tolerance and safety were evaluated using VAS scores, the Simulator Sickness Questionnaire (SSQ), and the State-Trait Anxiety Inventory (STAI). Acceptability was assessed among healthcare providers. The primary outcome was defined as successful maintenance of the VR headset and completion of neurofunctional testing for at least one hour. Data analysis employed the Sequential Probability Ratio Test (SPRT) with predefined thresholds (P₀ = 0.6, P₁ = 0.8; Nmin = 10, Nmax = 50). Result The first 10 patients completed the procedure successfully, meeting the primary endpoint and leading to early study termination per SPRT design. The VR headset was well tolerated in all cases, with no adverse events reported. Median VAS tolerance scores were high (training: 9.0; intraoperative: 10.0). SSQ scores indicated minimal cybersickness. All participants completed neurofunctional tests during surgery and expressed willingness to reuse the device. Acceptance among healthcare providers was excellent (median VAS: 10). Conclusion The initial phase of the VIRAS study demonstrated excellent overall tolerance of the VR headset by both participants and the healthcare professionals involved in orthopedic surgery.

Plastispheres as reservoirs of antimicrobial resistance: Insights from metagenomic analyses across aquatic environments

Evidence suggests that plastic particles from various environments can accumulate harmful microorganisms and carry bacteria with antimicrobial resistance genes (ARGs). The so-called “plastisphere” might facilitate the spread of pathogens and antimicrobial resistance across environments, posing risks to human and animal health. This study aimed to analyze the diversity and abundance of ARGs found in plastispheres from various aquatic environments, identify clinically relevant pathogenic species, and ascertain bacterial hosts carrying ARGs. We present data from 36 metagenomes collected from plastispheres in different environments (freshwater, raw wastewater, and treated wastewater). The diversity and abundance of ARGs in the resistome of the plastispheres were analyzed through metagenomic methods. A total of 537 high-quality metagenomic-assembled genomes (MAGs) were constructed to identify clinically relevant pathogens and to link the detected ARGs to their bacterial hosts. The results show that the environment has the greatest influence on the abundance and diversity of ARGs in the plastispheres resistome, with the wastewater plastisphere containing a resistome with the highest diversity of ARGs. Resistance to beta-lactams, aminoglycosides, and tetracyclines were the most abundant resistance mechanisms detected in the different plastispheres. The construction of MAGs identified potential pathogens and environmental bacteria that confer resistance to one or several drug classes, with beta-lactams being the most pervasive form of AMR detected. This work enhances our understanding of the plastisphere’s role in antimicrobial resistance dissemination and its ecological and public health risks.

Metagenomic profiling of the insect-specific virome in non-urban mosquitoes (Culicidae: Culicinae) from Colombia’s Northern inter-Andean valleys

Hematophagous mosquitoes are major vectors of diverse pathogens and serve as bioindicators in tropical ecosystems, yet their virome in non-urban Neotropical regions remains poorly characterized. We analyzed the virome of 147 mosquitoes from two natural ecosystems in Colombia using a hybrid viral identification approach, combining high-confidence and less stringent methods. Most high-confidence viral contigs remained unclassified or unknown, as expected for metagenomic surveys in novel ecosystems. However, members for the Magrovirales and Ortervirales, and other six orders were detected at lower abundance. Using a complementary, less stringent approach, we identified 168 viral species from 68 genera and 22 families across four mosquito tribes (Aedini, Culicini, Orthopodomyiini, Sabethini), with dominance of Metaviridae, Retroviridae, Iridoviridae, and Poxviridae, though many sequences could not be taxonomically assigned. Insect-specific viruses predominated, while no medically relevant arboviruses were detected. Both methods consistently identified Trichoplusia ni TED virus, Cladosporium fulvum T-1 virus, Lymphocystis disease viruses, and Oryctes rhinoceros nudivirus among the most abundant and frequently detected taxa across samples. Alpha diversity indices revealed the highest virome diversity in Sabethini, followed by Orthopodmyiini, and substantially lower richness and diversity in Aedini and Culicini. These results provide a baseline for virome characterization in sylvatic mosquitoes from Colombia and highlight the need for further research on the ecological roles of the mosquito virome in pathogen transmission and microbiome evolution.

The antiadipogenic effect of the pentacyclic triterpenoid isoarborinol is mediated by LKB1-AMPK activation

Obesity and overweight are two highly prevalent conditions worldwide, which can lead to death or produce chronic and degenerative diseases. The search for alternative therapies to control these morbidities can involve the study of metabolites obtained from plants. Particularly, pentacyclic triterpenes produce an antiadipogenic effect by affecting the expression of master regulators of adipogenesis and their signaling pathways, including LKB1-AMPK pathway. In this work, we evaluated the effect of the pentacyclic triterpene isoarborinol on adipogenesis in 3T3-L1 cells. This molecule inhibits differentiation and decreases lipid accumulation during cell differentiation in a dose-dependent manner, deregulates the expression of C/EBPβ, C/EBPδ, C/EBPα, PPARγ and SREBP-1C, causes an increase in the phosphorylation of LKB1 and AMPK, as well as a down regulation of the lipogenic factors ACC1, FAS and FABP4. These findings show that the antiadipogenic effect of isoarborinol is associated with the activation of LKB1-AMPK, leading to changes in the expression of master regulators of adipogenesis and lipogenic factors.

Identification of immune-related biomarkers associated with allergic rhinitis and development of a sample diagnostic model

This study was designed to identify immune-related biomarkers associated with allergic rhinitis (AR) and construct a robust a diagnostic model. Two datasets (GSE5010 and GSE50223) were downloaded from the NCBI GEO database, containing 38 and 84 blood CD4 + T cell samples, respectively. To eliminate batch effects, the surrogate variable analysis (sva) R package (version 3.38.0) was employed, enabling the integration of data for subsequent analysis. Immune cell infiltration profiles were assessed using the Gene Set Variation Analysis (GSVA) R package (version 1.36.3). A gene co-expression network was constructed via the Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm to identify disease-related modules. Differentially expressed genes (DEGs) were identified using the linear models for microarray data (limma) R package (version 3.34.7), followed by functional enrichment analysis using DAVID. Protein-protein interaction (PPI) networks were constructed based on the STRING database to highlight key genes. A diagnostic model was subsequently developed utilizing the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm and Support Vector Machine (SVM) method, with its discriminative capacity assessed via Receiver Operating Characteristic (ROC) curves. A total of twenty-eight immune cell types were analyzed, revealing significant differences in eight types between the AR and control groups. Through WGCNA, three disease-related modules comprising 4278 candidate genes were identified. Differential expression analysis identified 326 significant DEGs, of which 257 overlapped with WGCNA-selected genes. These genes exhibited significant enrichment in immune-related pathways, including “cytokine-cytokine receptor interaction” and “chemokine signaling pathway.” Gene Set Enrichment Analysis (GSEA) further uncovered 12 KEGG pathways significantly associated with disease risk scores. Drug screening identified 24 small molecule drugs related to key genes. A diagnostic model incorporating five genes (RFC4, LYN, IL3, TNFRSF1B, and RBBP7) was constructed, demonstrating diagnostic efficiencies of 0.843 and 0.739 in the training and validation sets, respectively. An AR mouse model was successfully established, and the expression levels of relevant genes were validated through RT-qPCR experiments. The five-gene diagnostic model established in this study exhibits strong predictive ability in distinguishing AR patients from healthy controls, with potential clinical applications in diagnosing AR and advancing novel diagnostic and therapeutic strategies.

Hidden community interlayer spillover detection in financial multilayer networks: Generalization of hierarchical clustering to multilayer networks

Interdependent networks structurally influence each other so that the source network imposes hidden community structures into the target network. We propose a mathematical model so that when introducing an interlayer similarity function we generalize hierarchical clustering approaches for multilayer networks. The proposed methodology shows how a “source” network influences the “target” network via structural spillovers that are hidden and are not detectable by conventional community detection methods. The methodology reveals evidence that hidden interlayer interactions consequently generate hidden links on the target network. These hidden links construct hidden community structures on the target network (imposed from the source network) that are distinct from the community structures of the solo target network (without the presence of the source network). This model applies to systems with hidden interlayer interactions, such as, e.g., covert criminal groups, inter-platform social network interactions, scientific research groups, and financial markets. Financial markets are well known for complicated endogenous and exogenous, but often hidden, not to say the least, asymmetric layer interactions. We implement our model on multilayer financial networks: in particular, we find that trading value logarithmic changes (source) impose hidden community structures on the price return network (target). The main finding is that adding another relevant layer, such as the trading value layer, adds more information to systemic behaviors throughout the price return network. Dismissing it may yield less systemic information and underestimation of systemic risk because the footprint of some structures on the target network originated from another layer and is not detectable by singling out the target layer. As an empirical application, we exploit the methodology to define another perspective on portfolio diversification.

Redefining player roles in professional women’s basketball: From traditional positions to functional profiles

The analysis of box-score performance indicators has traditionally been used to classify player roles in women’s basketball based on the five conventional positions: point guard, shooting guard, small forward, power forward, and center. However, this framework may not reflect the current tactical and functional demands of the game. The aim of this study was to identify and redefine functional player roles in professional women’s basketball using performance data derived from actual competition. A total of 36,204 individual player records from 3,894 games in the Spanish Liga Femenina Endesa (2012–2022) were analyzed. Game-related statistics were normalized by effective playing time and scaled to a 40-minute format. One-way ANOVA revealed significant differences across traditional positions, but also indicated considerable functional overlap. Unsupervised learning techniques, including k-means and Gaussian mixture models, were applied to identify underlying performance-based player profiles. The analysis yielded nine stable and interpretable functional roles, offering a more nuanced classification than the traditional five-position model. These roles capture offensive, defensive, and hybrid specializations, providing coaches and analysts with a practical framework for tactical planning, scouting, and individualized player development. The findings support a shift toward data-driven classification systems that better reflect the functional realities of modern elite women’s basketball.

How loneliness relates to health, wellbeing, quality of life, and healthcare resource utilisation and costs across multiple age groups in the UK

Increasing evidence of its detrimental impact has brought loneliness to the forefront of public health in recent years. Loneliness has been recognised as a cross-cutting theme for Healthy Ageing by the World Health Organisation and there is increasing need to better understand its wide-ranging health, wellbeing, and economic impacts across the wider population. This study utilises data from wave 13(2021–2023) of the Understanding Society UK Household Longitudinal Study to evaluate health and economic outcomes associated to loneliness (UCLA 3-item scale). Outcomes include the General Health Questionnaire, Short Form Health Survey, Short Warwick-Edinburgh Mental Well-being Scale, and costed GP, outpatient, and inpatient visits. Generalised Linear Modelling is applied to adjust for demographic characteristics, and subgroup analysis is conducted to consider costs in different age groups. Complete data provided observations for 23,071 respondents. Average marginal effects found loneliness is associated to higher mental distress, lower positive mental wellbeing, poorer physical and mental functioning, and higher healthcare service use. Overall, there is approximately a £900 cost difference in healthcare use between lonely and non-lonely respondents. Cost difference increases with age, and for more severe loneliness forms a U-shape with the greatest costs in younger and older adults. Additionally, difference in mean is only statistically significant across all models for 16- to 24-year-olds, suggesting importance in targeting young adult healthcare resource use. This is the first study to consider age-based analysis of health-related costs of loneliness in the UK. It also adds to the literature by considering validated wellbeing and health-related outcomes in a large UK based population. Findings motivate tackling young adult loneliness to support their health, wellbeing, quality of life, and potential overuse of healthcare services. This study also supports the pressing need for greater economic evaluation of loneliness and loneliness interventions.

Effect of planned preoperative oral care implemented at least 2 weeks before surgery on postoperative infections: A single-center retrospective observational study

This study aimed to investigate whether initiating oral care more than 2 weeks before surgery could prevent postoperative infections, particularly pneumonia. This retrospective observational study analyzed 1,806 patients who underwent surgery at the Ehime University Hospital between April 2019 and March 2023. The patients were divided into two groups: those receiving structured oral care at least 2 weeks before surgery (n = 257) and those receiving late or no oral care (n = 1,549). Propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were used to minimize selection bias. Nevertheless, residual confounding factors, especially confounding by indication, may remain, because as patients who received early oral care may differ systematically from those who did not. The primary outcome measure was the incidence of postoperative pneumonia. After PSM and IPTW analyses, the early oral care group showed significantly lower rates of postoperative pneumonia than the control group (risk difference: −3.56%, 95% confidence interval [CI]: −4.89% to −2.23%, p = 0.0004 in the matched analysis; −3.68%, 95% CI: −4.61% to −2.75%, p < 0.001 in the IPTW analysis). IPTW analysis demonstrated shorter hospital stays in the early oral care than in the control group (mean difference: −2.65 days, 95% CI: −4.75 to −0.55, p = 0.013). Implementing structured oral care at least 2 weeks before surgery reduced postoperative pneumonia and shortened hospital stays across various surgical procedures, suggesting its value as a preventive strategy for improving surgical outcomes.

Social determinants of health in lesbian, gay, bisexual, transgender, queer, and other sexual and gender minority (LGBTQ+) older adults: Impact of socioeconomic disadvantage on inpatient hospitalizations

Introduction Little is known about the impact of socioeconomic disadvantage on lesbian, gay, bisexual, transgender, queer, and other sexual and gender minority (LGBTQ+) older adults (≥50 years). The aim of this study is to determine whether the distribution of LGBTQ+ inpatient hospitalizations are related to structural socioeconomic factors. Methods A secondary analysis of retrospective electronic health record data for LGBTQ+ older adults hospitalized from 2018 to 2022 was conducted at one large health system. The average county area deprivation index where the patient resided was calculated. Results The analysis included 2270 LGBTQ+ older adult inpatient hospitalizations, with 1508 (66.4%) from low socioeconomic disadvantage, 595 (26.3%) from moderate socioeconomic disadvantage; and 17 (7.4%) from high socioeconomic disadvantage counties (p < .0001). LGBTQ+ older adults who resided in moderate and high socioeconomic disadvantaged counties had a significant proportion of patients identifying as asexual (a posteriori contrasts, p < .05) compared to the low socioeconomic disadvantaged group. Those from moderate socioeconomic disadvantaged counties had a significantly higher proportion of patients identifying as bisexual (a posteriori contrasts, p < .05) compared to the high socioeconomic disadvantaged group. Discussion This analysis highlights socioeconomic disadvantage of LGBTQ+ older adults who utilized one large health system. More work needs to be done to understand use of the hospital system by LGBTQ+ older adults in moderate to high socioeconomic disadvantaged areas.

Cheminformatics-based screening and evaluation of phytochemicals as CDK2 inhibitors in colorectal cancer therapy

Colorectal cancer (CRC) poses a significant global health issue. It ranks as the third most common type of cancer and the second leading cause of cancer-related deaths. Among the molecular factors driving its progression, cyclin-dependent kinase 2 (CDK2) plays a key role. CDK2 is a protein kinase essential for regulating the cell cycle, and its dysregulation is implicated in the development of various cancers, notably CRC. Fruquintinib is an already available drug against CRC. However, this study is being performed in search of better drug-like compounds. Some studies have shown that phytochemicals are less toxic and have fewer adverse effects than commercially available medications. With the vision of detecting CDK2 inhibitors, phytochemicals with anticancer activity can be used as alternatives to develop the drug candidate. Cheminformatics-based analysis is used for this purpose. This approach includes molecular docking, adsorption, distribution, metabolism, excretion/toxicity (ADME/T), post-docking molecular mechanism generalized born surface area (MM-GBSA), structural activity relationship (SAR), frontier molecular orbital (FMO), and molecular dynamics (MD) simulations. Molecular docking was employed to determine the binding strength of 4433 phytochemicals with anti-cancer properties sourced from the IMPPAT database. The top five candidates, CIDs-135438111, 6474893, 44257567, 10469828, and 353825, were selected based on their docking scores. Later, three lead compounds, CIDs-6474893, 10469828, and 135438111, were finalized depending on their favorable ADME/T profiles. All three selected pharmaceuticals demonstrated excellent post-dock MM-GBSA scores and HOMO-LUMO energy gaps, which served as confirmation of their efficacy and safety. The SAR analysis also revealed anti-mutagenic, antineoplastic, and apoptosis-inducing properties of the compounds. Finally, the rigidity of the protein-ligand complex structures was verified by MD simulations. Overall, the study suggests these three phytochemicals exhibit stronger binding and better pharmacological profiles than the control (fruquintinib), offering a promising direction for CRC treatment development.