Associations of polycyclic aromatic hydrocarbons exposure with serum uric acid and hyperuricemia in US adults: The role of systemic inflammation.

The associations of polycyclic aromatic hydrocarbon (PAH) exposure with serum uric acid (SUA) or hyperuricemia have been rarely assessed. We aimed to investigate the relationships between urinary PAH metabolites and SUA or hyperuricemia among US adults and to explore the mediating role of systemic inflammation in the associations. A total of 10,307 US adults were conducted to assess the associations of seven urinary hydroxy­PAH with SUA and hyperuricemia and evaluate the role of C-reactive protein (CRP), a biomarker of systemic inflammation, in such associations. Results showed that each 1-unit increase in ln-transformed 2-hydroxynaphthalene (2-OHNa), 1-hydroxyphenanthrene (1-OHPh), 2&3-hydroxyphenanthrene (2&3-OHPh) and total hydroxyphenanthrene (ΣOHPh) was associated with a 1.68 (95% confidence interval (CI): 0.19 to 3.17), 2.46 (0.78 to 4.13), 3.34 (1.59 to 5.09), and 2.99 (1.23 to 4.75) µmol/L increase in SUA, and a 8% (odds ratio (OR): 1.08, 1.02 to 1.15), 9% (OR: 1.09, 1.02 to 1.18), 13% (OR: 1.13, 1.05 to 1.22), and 12% (OR: 1.12, 95% CI: 1.03, 1.21) increase in hyperuricemia, respectively. Co-exposure of seven PAHs was positively associated with SUA and hyperuricemia, with 2&3-OHPh showing the highest weight (components weights: 0.83 and 0.78, respectively). The CRP mediated 11.47% and 10.44% of the associations of ΣOHPh and 2&3-OHPh with SUA and mediated 8.60% and 8.62% in associations of ΣOHPh and 2&3-OHPh with hyperuricemia, respectively. In conclusion, internal levels of PAH metabolites were associated with elevated SUA levels and the increased risk of hyperuricemia among US adults, and CRP played a mediating role in the associations.

Population Pharmacokinetic Model of Intravenous Immunoglobulin in Patients Treated for Various Immune System Disorders.

PURPOSE: Intravenous immunoglobulin (IVIG) is used to treat various immune system disorders, but the factors influencing its disposition are not well understood. This study aimed to estimate the population pharmacokinetic parameters of IVIG and to investigate the effect of genetic polymorphism of the FCGRT gene encoding the neonatal Fc receptor (FcRn) and clinical variability on the pharmacokinetic properties of IVIG in patients with immune system disorders. METHODS: Patients were recruited from 4 hospitals in Malaysia. Clinical data were recorded, and blood samples were taken for pharmacokinetic and genetic studies. Population pharmacokinetic parameters were estimated by nonlinear mixed-effects modeling in Monolix. Age, weight, baseline immunoglobulin G concentration, ethnicity, sex, genotype, disease type, and comorbidity were investigated as potential covariates. Models were evaluated using the difference in objective function value, goodness-of-fit plots, visual predictive checks, and bootstrap analysis. FINDINGS: A total of 292 blood samples were analyzed from 79 patients. The IVIG concentrations were best described by a 2-compartment model with linear elimination. Weight was found to be an important covariate for volume of distribution in the central compartment (Vc), volume of distribution in the peripheral compartment (Vp), and clearance in the central compartment, whereas disease type was found to be an important covariate for Vp. Goodness-of-fit plots indicated that the model fit the data adequately. Genetic polymorphism of the FCGRT gene encoding the neonatal Fc receptor did not affect the pharmacokinetic properties of IVIG. IMPLICATIONS: This study supports the use of dosage based on weight as per current practice. The study findings highlight that Vp is significantly influenced by the type of disease being treated with IVIG. This relationship suggests that different disease types, particularly inflammatory and autoimmune conditions, may alter tissue permeability and fluid distribution due to varying degrees of inflammation. Increased inflammation can lead to enhanced permeability and retention of IVIG in peripheral tissues, reflecting higher Vp values.

Estimating the prevalence of chronic kidney disease in the older population using health screening data in Japan.

BACKGROUND: In aging societies, the prevalence of chronic kidney disease (CKD) is expected to increase but may be underestimated because many asymptomatic patients remain undiagnosed. This study aimed to estimate the CKD prevalence among the general older population in Japan. METHODS: This cross-sectional study used health screening data from the Japan Health Insurance Association collected between April 2014 and March 2023. Data from older people aged 65-90 years who underwent renal function screening for estimated glomerular filtration rate (eGFR) and urine protein tests were analyzed. CKD was defined as eGFR < 60 mL/min/1.73 m2 or proteinuria ≥ 1 + . Inverse probability weighting was used to account for the selection bias. The variables used for weighting were age, sex, insurance status, and the number of previous screenings. RESULTS: Among 2.98 million older individuals, 588,809 (19.7%) had undergone screening (median [IQR] age, 69.9 [67.9-76.2] years, 337,862 women [57.4%]). Regarding the weighted CKD prevalence, 25.3% of the individuals aged 65-90 years had CKD; 11.8% of those aged 65-75 years and 34.6% of those aged 75 years and over showed an increase in prevalence with age. Among the patients with CKD, over half exhibited mild renal dysfunction without proteinuria. Hypertension and diabetes were common comorbidities in older patients with CKD. CONCLUSIONS: This cross-sectional study revealed that the weighted prevalence of CKD in the older population aged 65-90 years was high (one in four individuals), indicating that it increases with age. Further studies are required to examine the clinical significance of these findings.

Risk and benefits of expanded donor screening: A viewpoint from Germany.

This review describes the risks and benefits of expanding screening for transmissible pathogens in deceased organ donors. The focus is on the experience and procedure in Germany to make a decision on how to proceed with a possible donor. Three issues are of interest in how screening policies impact the process with the aim of mitigating unexpected transmission risks: (1) Should we add universal or targeted nucleic acid testing to serological tests for common blood-borne viruses (BBVs; HIV, HBV, and HCV)? (2) Which tests should be added for screening in a geographically restricted region beyond testing for these BBVs? (3) Being faced with changes (e.g., climate and population) in the own geographically restricted region, what strategies are needed before implementing new tests, and which considerations apply for proper indication to do this? Testing may only be effective when during donor characterization the appropriate conclusions are drawn from the existing findings and screening tests are initiated. This statement overlaps the need to implement universal screening for a pathogen or targeted screening based on the risk that the donor has acquired the transmissible pathogen or is not as possible to identify by current methods of clinical judgment and/or specific tests.

Seascape effects on the nursery function of macroalgal habitats.

Understanding how seascape configuration influences nursery function is important for spatial management and conservation of essential habitats. Here, we examine how local habitat, seascape, and environmental factors influence demographic metrics of juvenile Lethrinus punctulatus and assess spatial variation in macroalgae nursery function. We quantified abundance, biomass, and productivity of juvenile L. punctulatus over three years and estimated size-at-age and condition from collected fish. Abundance, biomass, productivity, and size-at-age exhibited significant spatial variation, although each pattern was best explained by different factors. Lethrinus punctulatus were most abundant in macroalgae-rich seascapes, whereas biomass and productivity peaked where macroalgal cover and water temperatures were high. Conversely, fish exhibited the greatest average daily growth at sites near coral reefs. Processes contributing to spatial variation in size-at-age occur prior to fish reaching ∼5 cm in length and may be due to differences in resource availability, size at settlement, or size-selective mortality. Our findings suggest habitat and resource availability constrain L. punctulatus abundance and productivity, while size-at-age is influenced by size-selective mortality and prey quality. Thus, while seascape configuration can affect nursery function, the degree of influence will depend on the processes involved, emphasising the value of considering multiple metrics when identifying nurseries.

Projected changes in heatwaves over Central and South America using high-resolution regional climate simulations.

Heatwaves (HWs) pose a severe threat to human and ecological systems. Here we assess the projected changes in heatwaves over Latin America using bias corrected high-resolution regional climate simulations under two Representative Concentration Pathway scenarios (RCPs). Heatwaves are projected to be more frequent, long-lasting, and intense in the mid-century under both RCP2.6 and RCP8.5 scenarios, with severe increases under the RCP8.5 scenario. Even under the low emissions scenario of RCP2.6, the frequency of heatwaves doubles over most of the region. A three- to tenfold rise in population exposure to heatwave days is projected over Central and South America, with climate change playing a dominant role in driving these changes. Results show that following the low emission pathway would reduce 57% and 50% of heatwave exposure for Central and South American regions respectively, highlighting the need to control anthropogenic emissions and implement sustainable practices.

Project Vayoraksha: Implementation of novel mHealth technology for healthcare delivery during COVID-19 in geriatric population of Kerala.

Background & objectives mHealth technologies, with their potential in improving public health, have recently gained considerable interest in India, offering an opportunity to deliver tailored and low cost interventions to the selected populations, especially in resource-poor settings. Project Vayoraksha aimed at developing and pilot testing mHealth technology-assisted strategies (Vayoraksha mobile application and field Vayoraksha network) to improve healthcare delivery and reverse quarantine at the field level among the geriatric population. Methods This field operational research study was implemented in Pathanamthitta, Kerala, from October 2020 to July 2021. The Vayoraksha mobile phone application for the geriatric users and a web interface used by healthcare workers involved in the field Vayoraksha network was developed with multisectoral expertise. Vayoraksha had facilities for symptom surveillance, teleconsultation and assessment of needs and included a community-based system to monitor and meet their needs that can help in reverse quarantine of the geriatric population. Results The project was implemented using the field Vayoraksha campaign involving frontline health workers and community volunteers. A baseline survey of 4782 geriatric population in the study area was conducted in Phase I, and 2383 (49.8%) had access to a smartphone facility to use Vayoraksha. Of these, 1257 (52.7%) were covered under the 'field Vayoraksha campaign' using intersectoral coordination and community participation. A total of 750 (59.6%) geriatric individuals downloaded the application of whom, 452 (60.3%) used the services of Vayoraksha. Needs were registered by 56 (12.3%) individuals of which 46 (82.1%) were medical needs related to the management of chronic diseases. More than 70 per cent of the needs were met through the Vayoraksha field network under the local primary health centre. More than 80 per cent of the geriatric individuals reported symptoms related to COVID-19 during the intervention period. Compliance with quarantine was observed in 77.7 per cent of the geriatric populations. Among those who used Vayoraksha, 26 (5.7%) availed tele-counselling services, and 3 (0.6%) used teleconsultation facilities. It was observed that Vayoraksha users had a higher proportion of the geriatric population who were young, educated, having chronic morbidity and living with family. Regular symptom surveillance was done within this group; only 12 (2.6%) of them tested positive for COVID-19 during this study. Interpretation & conclusions Results of this pilot study are promising, with 60 per cent of the geriatric population downloading and using Vayoraksha within a short time. Technology-assisted interventions can supplement the existing system for improved healthcare delivery among the vulnerable groups and have good potential for scale-up in the near future in developing countries.

Implementation research on registering cancer cases in primary health centres of Puducherry through community health workers.

Background & objectives Hospital-based cancer registry does not represent the true burden of cancer in the community. Initiating a Primary Health Centre (PHC)-based cancer registry may better estimate population-level data for cancer cases in an area. This study aimed to set up a system for facilitating a PHC-based cancer registry and to assess the registration status of cancer cases in various PHCs of Puducherry. The facilitating and limiting factors while setting up this registry were also assessed. Methods A quasi-experimental study with an embedded mixed-method design was conducted in 31 PHCs/Community Health Centres (CHCs) from March 2021 to November 2022. The interventions were implemented in all PHCs/CHCs of Puducherry with the involvement of the State Non-Communicable Diseases (NCD) cell. The line list of cancer cases from the Jawaharlal Institute of Postgraduate Medical Education & Research (JIPMER) Hospital-based cancer registry was shared with all PHCs/CHCs. Sensitization sessions for all Community Health Workers (CHWs) were conducted, and feedback on cancer registration status was given to the State NCD cell. Focus group discussion (FGD)/Key informant interview (KII) was undertaken to understand strengths, challenges, and suggestions. The logic model was used to understand the various indicators while setting up this PHC-based cancer registry. Results Over a one-year intervention period, 1270 cancer cases were registered at Puducherry's PHCs/CHCs, 1203 (88%) from the shared list and 67(5%) from other facilities. However, only 53 per cent of the expected living cases were captured in the various PHCs. Major limitations for registration were the COVID-19 pandemic, stigma, inadequate manpower, infrastructure issues, and privacy concerns during screening. Interpretation & conclusions It was feasible to set up a PHC-based cancer registry in all PHCs of Puducherry. However, registration of cancer cases was suboptimal, as population-based screening of cancer cases, as recommended in the National Programme for Prevention & Control of Non-Communicable Diseases (NP-NCD) programme, was weak due to the COVID-19 pandemic. Once this is strengthened, the PHC-based cancer registry will better represent the population.

Shift in Demographic Involvement and Clinical Characteristics of COVID-19 From Wild-Type SARS-CoV-2 to the Delta Variant in the Indian Population: In Silico Analysis.

BACKGROUND: The Delta variant (B.1.617.2) was considered the most dangerous SARS-CoV-2 strain; however, in-depth studies on its impact based on demographic and clinical characteristics of COVID-19 are scarce. OBJECTIVE: We aimed to investigate the shift in demographic and clinical characteristics of the COVID-19 pandemic with the emergence of the SARS-CoV-2 Delta variant compared with the wild-type (WT) strain (B.1). METHODS: A cross-sectional study of COVID-19 cases in the Indian population caused by the WT strain (B.1) and Delta variant of SARS-CoV-2 was performed. The viral genomic sequence metadata containing demographic, vaccination, and patient status details (N=9500, NDelta=6238, NWT=3262) were statistically analyzed. RESULTS: With the Delta variant, in comparison with the WT strain, a higher proportion of young individuals (<20 years) were infected (0-9 years: Delta: 281/6238, 4.5% vs B.1: 75/3262, 2.3%; 10-19 years: Delta: 562/6238, 9% vs B.1: 229/3262, 7%; P<.001). The proportion of women contracting infection increased (Delta: 2557/6238, 41% vs B.1: 1174/3262, 36%; P<.001). However, it decreased for men (Delta: 3681/6238, 59% vs B.1: 2088/3262, 64%; P<.001). An increased proportion of the young population developed symptomatic illness and were hospitalized (Delta: 27/262, 10.3% vs B.1: 5/130, 3.8%; P=.02). Moreover, an increased proportion of the women (albeit not men) from the young (Delta: 37/262, 14.1% vs B.1: 4/130, 3.1%; P<.001) and adult (Delta: 197/262, 75.2% vs B.1: 72/130, 55.4%; P<.001) groups developed symptomatic illness and were hospitalized. The mean age of men and women who contracted infection (Delta: men=37.9, SD 17.2 years; women=36.6, SD 17.6 years; P<.001; B.1: men=39.6, SD 16.9 years; women=40.1, SD 17.4 years; P<.001) as well as developing symptoms or being hospitalized (Delta: men=39.6, SD 17.4 years; women=35.6, SD 16.9 years, P<.001; B.1: men=47, SD 18 years; women=49.5, SD 20.9 years, P<.001) were considerably lower with the Delta variant than the B.1 strain. The total mortality was about 1.8 times higher with the Delta variant than with the WT strain. With the Delta variant, compared with B.1, mortality decreased for men (Delta: 58/85, 68% vs B.1: 15/20, 75%; P<.001); in contrast, it increased for women (Delta: 27/85, 32% vs B.1: 5/20, 25%; P<.001). The odds of death increased with age, irrespective of sex (odds ratio 3.034, 95% CI 1.7-5.2, P<.001). Frequent postvaccination infections (24/6238) occurred with the Delta variant following complete doses. CONCLUSIONS: The increased involvement of young people and women, the lower mean age for illness, higher mortality, and frequent postvaccination infections were significant epidemiological concerns with the Delta variant.

Influenza-Like Illness in Lesotho From July 2020 to July 2021: Population-Based Participatory Surveillance Results.

Background: Participatory surveillance involves at-risk populations reporting their symptoms using technology. In Lesotho, a landlocked country of 2 million people in Southern Africa, laboratory and case-based COVID-19 surveillance systems were complemented by a participatory surveillance system called "LeCellPHIA" (Lesotho Cell Phone Population-Based HIV Impact Assessment Survey). Objective: This report describes the person, place, and time characteristics of influenza-like illness (ILI) in Lesotho from July 15, 2020, to July 15, 2021, and reports the risk ratio of ILI by key demographic variables. Methods: LeCellPHIA employed interviewers to call participants weekly to inquire about ILI. The average weekly incidence rate for the year-long period was created using a Quasi-Poisson model, which accounted for overdispersion. To identify factors associated with an increased risk of ILI, we conducted a weekly data analysis by fitting a multilevel Poisson regression model, which accounted for 3 levels of clustering. Results: The overall response rate for the year of data collection was 75%, which resulted in 122,985 weekly reports from 1776 participants. ILI trends from LeCellPHIA mirrored COVID-19 testing data trends, with an epidemic peak in mid to late January 2021. Overall, any ILI symptoms (eg, fever, dry cough, and shortness of breath) were reported at an average weekly rate of 879 per 100,000 (95% CI 782-988) persons at risk. Compared to persons in the youngest age group (15-19 years), all older age groups had an elevated risk of ILI, with the highest risk of ILI in the oldest age group (≥60 years; risk ratio 2.6, 95% CI 1.7-3.8). Weekly data were shared in near real time with the National COVID-19 Secretariat and other stakeholders to monitor ILI trends, identify and respond to increases in reports of ILI, and inform policies and practices designed to reduce COVID-19 transmission in Lesotho. Conclusions: LeCellPHIA, an innovative and cost-effective system, could be replicated in countries where cell phone ownership is high but internet use is not yet high enough for a web- or app-based surveilance system.

The Population Typology of Conspiracy Beliefs About Sars-Cov-2 Origin in Russia Based on Predictive Modelling of COMET-G Study Data: Incoherent Attitude Indicator as a Predisposing Factor for Developing Mental Disturbances.

BACKGROUND: We examined the prevalence and spread of conspiracy beliefs about the origins of the COVID-19 pandemic among representatives of the Russian population. Our study aimed to identify belief clusters and develop predictive models to understand the factors that influence conspiracy beliefs, particularly in the context of how they might evolve in response to socio-political events and cause mental disturbances, thus in relation to specific pathways of the infodemic and psychodemic waves that spread among vulnerable population groups. METHODS: Data respondents to the international COMET-G study living in Russia during pandemic period (n=7,777) were analyzed using descriptive statistics, K-means clustering, and various machine learning models, including gradient boosting. We identified distinct populations depending on predominant beliefs about COVID-19 pandemic origins, and applied game theory (Shapely additive explanations) to determine the most influential variables in predicting cluster membership. RESULTS: Four distinct belief clusters emerged, which we designate as Naturalists, Conspiracists, COVID-Sceptics, and the Incoherent Attitude groups. The Incoherent Attitude cluster constituted 20.8% of the sample, and was particularly associated with mental health signs such as sleep disturbances and the use of psychotropic medications. Internet use and mental health-related factors, as well as the respondents' education level, were key predictors of mental disturbances with mediating effects of the conspiracy views across all clusters. Conspiracy beliefs about COVID-19 origin were highly fluid/variable, often being shaped by external sociopolitical factors rather than objective health data. CONCLUSIONS: The cluster with Incoherent Attitude regarding COVID-pandemic origins, which had an association with psychoticism, showed a greater predisposition for mental health problems, than did the Conspiracist, Naturalist and Sceptic clusters. We suppose that underlying psychoticism bears a relation to their sleep problems and resorting to use of psychotropic medications. These results emphasizes the global health need for implementing target-focused and selective strategies that address public misinformation and promote the adoption of critical thinking skills to mitigate the impact of conspiracy theories, considering the factors of education level and pre-existing mental disorders.

Risk Assessment Suicidality Scale (RASS)-Based On-Line Calculator Targeting Early Prevention of Suicides in General Population: from COMET-G Study Results Towards Integration of the Screening Tool into Routine Clinical Practice.

BACKGROUND: Suicide is a major global health concern, particularly among young people. This study evaluates an online suicide risk calculator based on the Risk Assessment of Suicidality Scale (RASS), which is designed to enhance accessibility and early detection of suicide risk. METHODS: The study involved 444 participants who completed the RASS via an online calculator. Results were compared with data from the COMET-G study's Russian sample (n=7572). Descriptive statistics, correlation analysis, and two-way ANOVA were used to analyze the data. RESULTS: The mean age of participants was 22.71 years (SD=7.94). The mean total RASS standardized score was 837.7 (SD=297.8). There was a significant negative correlation between age and RASS scores (r=-0.463, p<0.0001). The online calculator sample showed significantly higher RASS scores compared to the COMET-G sample, with 71% of online users scoring above the 90th percentile of the COMET-G sample. CONCLUSION: Our study demonstrated the advantage of the on-line suicidality risk calculator based on the RASS scale as a sensitive tool in detecting suicidal behaviours and measuring the severity of suicidality risks, offering a capability for broad reach and immediate assessment during clinical conversation between doctor and patient. Moreover, the RASS on-line psychometric instrument, when being freely distributed among the general population over internet sources, enabled to attract vulnerable groups of respondents with significantly higher suicidality risks. Future research should focus on integrating such tools into comprehensive suicide prevention programs and developing appropriate follow-up monitoring strategies for high risk-cases.

Excess mortality and suicide risk in treatment-seeking individuals with schizotypal disorder: A population-based study using Swedish national registers.

This study investigates the excess mortality, both all-cause and due to suicide, among individuals with schizotypal disorder (SD) compared to the general population. Using individual-level data from the Swedish National Patient Register and the Cause of Death Register, we analyzed mortality in 998 patients diagnosed with SD from 2006 to 2017. Our primary outcomes were all-cause mortality and suicide mortality, with baseline variables including sex, age, and psychiatric comorbidities. Results indicated significantly elevated mortality rates for both all-cause mortality (Standardized Mortality Ratio (SMR) 5.2) and suicide (SMR 23.4). Substance use disorders, personality disorders, and ADHD were identified as significant predictors of increased all-cause mortality. Notably, having a personality disorder in conjunction with schizotypal disorder resulted in a markedly increased risk of suicide. The study underscores the urgent need for targeted interventions and improved diagnostic precision to reduce premature mortality in this vulnerable population. Additionally, the relatively low prevalence of SD diagnoses in Sweden highlights a potential underdiagnosis or misclassification issue. These findings have critical implications for clinical practice and public health efforts, emphasizing the necessity for comprehensive care strategies and suicide prevention interventions to improve outcomes for individuals with schizotypal disorder.

Large-scale selection of highly informative microhaplotypes for ancestry inference and population specific informativeness.

Microhaplotypes (MHs) describe physically close genetic markers that are inherited together and are gaining prominence due to their efficiency in forensic, clinical, and population studies. They excel in kinship analysis, DNA mixture detection, and ancestry inference, offering advantages in precision over individual SNPs and STRs. In this study, a pipeline was developed to efficiently select highly informative MHs from large-scale genomic datasets. Over 120,000 MHs were identified from almost a million markers, which allow this non-independent information to be efficiently used for inference. The MHs were compared to SNPs in terms of their informativeness and performance of their subsets in ancestry inference and all the results consistently favored MHs. A method for ranking markers by specific population informativeness was also introduced, which showed improvement in the accuracy of Native American ancestry estimation, overcoming the challenges of its underrepresentation in datasets. In conclusion, this study presents a comprehensive way for selecting highly informative MHs for accurate ancestry inference. The proposed approach and the subsets selected by specific population informativeness offer valuable tools for improving ancestry inference accuracy, particularly for admixed populations as demonstrated for a Brazilian dataset.

Genetic Profiling of Non-Small Cell Lung Cancer in Moroccan Patients by Targeted Next-Generation Sequencing.

OBJECTIVES: We retrospectively analyzed the next-generation sequencing (NGS) results from diagnosed NSCLC patients to identify and compare genomic alterations of NSCLC between Moroccan patients and the Cancer Genome Atlas (TCGA). We also aimed to investigate the distribution and frequency of concurrent genomic alterations. METHODS: From December 2022 to December 2023, a retrospective study of 76 formalin-fixed paraffin-embedded (FFPE) samples have been profiled using the Oncomine™ Precision Assay on the Ion Torrent™ Genexus™ Integrated Sequencer across the panel of 50 key genes that are applicable for the selection of targeted therapy. RESULTS: Seventy of the 76 FFPE sequenced samples carried at least one genetic alteration in the tested genes. The study identified 234 genetic alterations in 18 genes. Targetable genetic alterations in EGFR, KRAS, MET, BRAF, ALK, RET and ROS1 were identified in 84.3% of tumors. EGFR and KRAS mutations were frequently reported, occurring in 24.3% and 22.9% of cases, respectively. The untargetable genetic alterations were found in 74.3% of the specimens in FGFR3, TP53, ERBB2, PIK3CA, CDKN2A, PDL1, FGFR1, PTEN, CHEK2 and ERBB3. There were additional uncommon/rare mutations in EGFR, BRAF, RET and ROS1. Comparing the prevalence of selected mutated genes in the NSCLC patients from the TCGA database identified substantial differences in EGFR (24.3%, vs14.97%), KRAS (22.9%, vs 25.99%), and TP53 (34.3%, vs 50.94%). ALK, ROS1, and RET gene rearrangements were detected in 4.3% of the 70 tumors tested. The ALK/RET/MET/ROS1/EML4 fusions were detected in 11.4% of samples. Co-alterations occurred in 67.1% of specimens. Co-occurring driver gene mutations were observed in 44.3%. TP53 mutations co-occurred driver gene mutations in 30% of tumors. Three cases (4.3%) harbored concurrent FGFR3, TP53, and PIK3CA alterations. CONCLUSION: Our results regarding the proportion of samples with actionable mutations demonstrate the value of NGS testing for NSCLC patients in a real-world clinical diagnostic setting.

Genetic influences, lifestyle and psychosocial aspects in relation to metabolically healthy obesity and conversion to a metabolically unhealthy state.

AIMS: About 10%-30% of individuals with obesity are metabolically healthy, but the specific characteristics of the metabolically healthy obesity (MHO) phenotype remain unclear. We aimed to examine how physical activity, education, depressive symptoms and genetic predisposition to obesity differ between individuals with MHO and those with metabolically unhealthy obesity (MUO), and whether these factors predict stability in MHO or conversion to a metabolically unhealthy state. MATERIALS AND METHODS: We retrieved data on 9809 individuals with obesity from the Health and Retirement Study collected between 2006 and 2016. We compared how physical activity, education, depressive symptoms and a polygenic score for higher body mass index (BMI) (PGSBMI) differed cross-sectionally between MHO and MUO using logistic regression. We then examined if the same factors predict conversion to a metabolically unhealthy state over 4 years in individuals with MHO. RESULTS: Individuals with MHO had higher physical activity (odds ratio [OR] = 0.81), higher education (OR = 0.83) and lower depressive symptoms (OR = 1.14) compared to those with MUO but did not differ in the PGSBMI. The associations were slightly attenuated in mutually adjusted models. None of the factors were associated with conversion from MHO to a metabolically unhealthy state. However, a higher PGSBMI indicated 24% lower risk of conversion to a metabolically unhealthy state (p = 0.07). CONCLUSIONS: Physical activity, education and depressive symptoms differed between MHO and MUO, even when mutually adjusted for, but did not predict conversion from a metabolically healthy to unhealthy state. Although not statistically significant, the results indicated that those with genetically predicted high BMI are more likely to maintain MHO and not convert to a metabolically unhealthy state.

Impacts of age and BMI on vancomycin model choice in a Bayesian software: Lessons from a very large multi-site retrospective study.

BACKGROUND: Model-informed precision dosing (MIPD) optimizes drug doses based on pharmacokinetic (PK) model predictions, necessitating careful selection of models tailored to patient characteristics. This study evaluates the predictive performance of various vancomycin PK models across diverse age and BMI categories, drawing insights from a large multi-site database. METHODS: Adults receiving vancomycin intravenous therapy at United States health systems between January 1, 2022, and December 31, 2023, were included. Patient demographics, vancomycin administration records, and therapeutic drug monitoring levels (TDMs) were collected from the InsightRX database. Age and body mass index (BMI)-based subgroups were formed to assess model performance, with predictions made iteratively. The optimal model for each age-BMI subgroup was chosen based on predefined criteria: models were filtered for mean percentage error (MPE) ≤ 20% and normalized root mean squared error (RMSE) < 8 mg/L, and then the most accurate among them was selected. RESULTS: A total of 384,876 treatment courses across 155 US health systems were analyzed, contributing 841,604 TDMs. Eleven models were compared, showing varying accuracy across age-BMI categories (41%-73%), with higher accuracy observed once TDMs were available for Bayesian estimates of individual PK parameters. Models performed more poorly in younger adults compared to older adults, and the optimal model differed depending on age-BMI categories and prediction methods. Notably, in the a priori period, the Colin model performed best in adults aged 18-64 years across most BMI categories; the Goti/Tong model performed best in the older, non-obese adults; and the Hughes model performed best in many of the obese categories. CONCLUSION: Our study identifies specific vancomycin PK models that demonstrate superior predictions across age-BMI categories in MIPD applications. Our findings underscore the importance of tailored model selection for vancomycin management, especially highlighting the need for improved models in younger adult patients. Further research into the clinical implications of model performance is warranted to enhance patient care outcomes.

EVE-X: Software to Identify Novel Viral Insertions in Wild-Caught Arthropod Hosts From Next-Generation Short Read Data.

Eukaryotic genomes harbour sequences derived from non-retroviral RNA viruses, known as endogenous viral elements (EVEs) or non-retroviral integrated RNA virus sequences (NIRVS). These sequences represent a record of past infections and have been implicated in host anti-viral response. We have created a program to identify viral sequences integrated in a host genome. It begins with a specimen BAM file and outputs candidate NIRVS, along with putative host insertion sites and overlapping genomic features of the host genome in XML and visual formats, with minimal intermediary intervention. We ran through this software short-read data derived from the genomes of 222 wild-caught A. aegypti mosquitoes, from a dozen geographical regions, and located putative NIRVS from seven virus families. This program is as accurate as currently available software for NIRVS detection, and represents a significant improvement in adaptability and user-friendliness. Furthermore, the flexibility of this pipeline allows the user to search for sequence integrations across the genome of any organism, as long as a query sequence database and a reference genome is provided. Potential extended applications include identification of integrated transgenic sequences used for research or vector control strategies.

Evolutionary Adaptation in Heterogeneous and Changing Environments.

Organisms that are adapting to long term environmental change almost always deal with mul- tiple environments and trade-offs that affect their optimal phenotypic strategy. Here we combine the idea of repeated variation or heterogeneity, like seasonal shifts, with long-term directional dy- namics. Using the framework of fitness sets, we determine the dynamics of the optimal phenotype in two competing environments encountered with different frequencies, one of which changes with time. When such an optimal strategy is selected for in simulations of evolving populations, we observe rich behavior that is qualitatively different from and more complex than adaptation to long-term change in a single environment. The probability of survival and the critical rate of environmental change above which populations go extinct depend crucially on the relative fre- quency of the two environments and the strength and asymmetry of their selection pressures. We identify a critical frequency for the stationary environment, above which populations can escape the pressure to constantly evolve by adapting to the stationary optimum. In the neighborhood of this critical frequency, we also find the counter-intuitive possibility of a lower bound on the rate of environmental change, below which populations go extinct, and above which a process of evolutionary rescue is possible.