Categories
Nevin Manimala Statistics

Environmental impact of food consumption: determinants of carbon and water footprints in an Italian population

Eur J Public Health. 2026 Mar 14;36(2):ckag054. doi: 10.1093/eurpub/ckag054.

ABSTRACT

Understanding the environmental impact of food consumption is essential for addressing climate change and water scarcity. This study investigates the carbon and water footprints (WFs) of dietary habits in Italy, identifying sociodemographic and dietary determinants influencing these impacts. We conducted a cross-sectional analysis using data from the nationally representative Italian National Food Consumption Survey (INRAN-SCAI) 2005-06, which included 2831 participants. Daily food intake was multiplied by environmental coefficients from the SU-EATABLE LIFE database to estimate carbon (kg CO2 eq) and water (l) footprints. We used multiple regression models to assess associations between environmental indicators and individual characteristics, including age, sex, education, body mass index, geographical area, and adherence to the Mediterranean diet (MD). The mean daily carbon footprint (CF) was 3.53 kg CO2 eq, and the mean WF was 3331 l. Animal-based food groups were the main contributors to both footprints, particularly meat, which accounted for 6.87% of the total CF and 27.54% of the total WF, and dairy products, contributing 20.0% to CF and 21.3% to WF. Higher adherence to the MD was associated with lower carbon (9.84 vs 11.01 kg CO2 eq) and WFs (9356.0 vs 10 348.3 l). Multiple analysis showed this association remained significant for both carbon (β = -0.239) and WFs (β = -206.4), independent of energy intake. Animal-based foods and specific sociodemographic factors substantially influence the environmental impact of diet. Promoting Mediterranean-style, plant-based diet through targeted policies for specific populations could enhance environmental sustainability.

PMID:41915858 | DOI:10.1093/eurpub/ckag054

Categories
Nevin Manimala Statistics

Enhancing Data-Driven Decision-Making in HIV Care With Viral Load and Early Infant Diagnosis Data Dashboards in Côte d’Ivoire: Qualitative Study

JMIR Hum Factors. 2026 Mar 31;13:e76550. doi: 10.2196/76550.

ABSTRACT

BACKGROUND: Data dashboards are popular tools for supporting routine monitoring and decision-making in public health. Two dashboards were developed in Côte d’Ivoire to visualize laboratory data on HIV viral load (VL) and early infant diagnosis (EID) testing.

OBJECTIVE: This study assessed the attitudes and experiences regarding data-driven decision-making and the VL and EID dashboards among existing and potential dashboard users in Côte d’Ivoire.

METHODS: We conducted a qualitative study including 2 focus group discussions (FGDs) and 12 in-depth interviews (IDIs). The conceptual framework for the use of health data in decision-making guided the FGDs, and the Consolidated Framework for Implementation Research informed the IDIs. We used deductive and inductive approaches to analyze the interview data.

RESULTS: The 26 participants were from 17 organizations; 11 (42.3%) were female. The participants reported a supportive data culture that valued data-driven decision-making and external pressure from the United States President’s Emergency Plan for AIDS Relief (PEPFAR) that motivated data use. The dashboards were considered useful for monitoring performances and making decisions for service delivery and laboratory operations. Existing users used the dashboards regularly. Potential users expressed interest in the speed and ability to track progress. The participants considered the dashboards simple and straightforward compared to other analytical tools but suggested updating the dashboards more frequently and visualizing more data.

CONCLUSIONS: The study highlighted the importance of supportive data culture and the potential of dashboards to promote data use. However, challenges such as limited access to the internet and equipment for potential users need to be addressed.

PMID:41915845 | DOI:10.2196/76550

Categories
Nevin Manimala Statistics

Robot-assisted versus traditional core decompression combined with human umbilical cord-derived mesenchymal stem cell transplantation for osteonecrosis of the femoral head: A retrospective cohort study

J Int Med Res. 2026 Mar;54(3):3000605261436561. doi: 10.1177/03000605261436561. Epub 2026 Mar 31.

ABSTRACT

ObjectiveTo compare the efficacy of robot-assisted versus traditional core decompression combined with human umbilical cord-derived mesenchymal stem cell transplantation for osteonecrosis of the femoral head.MethodsA total of thirty-eight patients were divided into two groups according to the surgical technique. The observation group (20 patients, 28 hips) underwent robot-assisted core decompression, while the control group (18 patients, 22 hips) underwent traditional decompression. Both groups underwent human umbilical cord-derived mesenchymal stem cell implantation. Relevant parameters were compared between the groups.ResultsAt the final follow-up, the observation group showed lower visual analog scale scores and necrotic volume as well as higher Harris hip scores and femoral head survival rates than the control group; however, these differences were not statistically significant. The observation group required significantly fewer intraoperative fluoroscopies, experienced less intraoperative blood loss, and had a shorter operation time than the control group (all p < 0.01).ConclusionOur findings suggests that the robotic-assisted technique demonstrates comparable clinical and radiological outcomes as the traditional technique in the treatment of osteonecrosis of the femoral head. However, it may offer significant advantages in terms of surgical precision.

PMID:41915812 | DOI:10.1177/03000605261436561

Categories
Nevin Manimala Statistics

The Effect of School-Based Bullying Prevention Program on Adolescents’ Traditional Bullying and Cyberbullying Victimization, Dispositions and Future Expectations: A Randomized Controlled Study

Clin Child Psychol Psychiatry. 2026 Mar 31:13591045251396371. doi: 10.1177/13591045251396371. Online ahead of print.

ABSTRACT

BackgroundTraditional bullying and cyberbullying have many negative physical and psychological consequences on adolescents.AimIn this study, the effects of a school-based bullying prevention program on adolescents’ traditional bullying and cyberbullying victimization, tendencies and future expectations were examined.MethodThis research is a randomized controlled experimental study with a pretest-posttest design. The data of the study were collected adolescents studying a school in the Southeastern Anatolia Region of Turkey between September and October 2024. The study was completed with a total of 169 adolescents. The adolescents in the intervention group were included in the school-based bullying prevention program.ResultsAdolescents who were included in the school-based bullying prevention program had statistically significantly lower mean scores of physical victimization and bullying, verbal victimization and bullying, and relational victimization and bullying, and higher mean scores of future expectations total scale than adolescents who were not included in the program in the measurements made one month after the program.ConclusionsSchool-based bullying prevention program is effective in reducing traditional bullying and victimization of adolescents and increasing their future expectations. It is thought that school-based interventions to improve adolescents’ future expectations will contribute to reducing bullying and victimization rates of adolescents.

PMID:41915809 | DOI:10.1177/13591045251396371

Categories
Nevin Manimala Statistics

Occupational Exposure to Resorcinol and Thyroid-Disrupting Effects: Protocol for an Exploratory Field Study in French Hairdressers

JMIR Res Protoc. 2026 Mar 31;15:e65833. doi: 10.2196/65833.

ABSTRACT

BACKGROUND: All around the world, the hairdressing sector constitutes a major occupational group, including about 90% women, most of whom are of reproductive age. Hairdressers are continuously exposed to numerous chemicals used in hair products, including endocrine-disrupting compounds such as resorcinol, parabens, phthalates, and UV filters. Few biomonitoring studies have explored occupational exposure to endocrine disruptors in hairdressers, and no data were found on their impact on the thyroid hormone system. Resorcinol is an oxidative hair dye with thyroid-disrupting properties that decrease thyroid hormone synthesis and could alter neurodevelopmental functions during fetal and perinatal stages in case of maternal exposure.

OBJECTIVE: This study aims to assess the occupational exposure to resorcinol in French hairdressers and analyze the relationship with biological thyroid parameters, taking into account the occupational exposure to other potential thyroid disruptors (parabens and UV filters like benzophenone and cinnamates).

METHODS: An exposed-unexposed cross-sectional study is proposed involving female hairdressers aged 18 to 45 years (working in hair salons) compared to occupationally unexposed controls (employed in office activities), who are recruited within 14 French occupational health centers. The hairdressers are followed during a 5-day working week to assess exposure data at both the individual level and the salon level. Urinary samples for the measurement of thyroid disruptors (resorcinol, parabens, metabolites of ethylhexyl methoxycinnamate, and benzophenone-3) are collected at 6 time points (before the day 1 shift, before and after the day 3 and day 4 shifts, and before the day 5 shift). Daily work tasks and use of hair products are self-reported within the workplace, and a complete inventory of hair products within the salon is carried out. Thyroid disruption effects are assessed by measuring blood thyroid parameters: triiodothyronine, thyroxine, thyroid-stimulating hormone, thyroglobulin, thyroperoxidase, and thyroglobulin antibodies. To assess nonoccupational exposure to thyroid disruptors and other confounding factors, information on sociodemographic data, place of residence, food and tobacco consumption, personal use of care products, professional career, and medical history is collected through questionnaires. Regarding statistical analysis, urinary samples from hairdressers and controls will be compared, and adjusted multivariable models will be used to analyze health outcomes.

RESULTS: The study duration extends from 2022 to 2027. As of December 2025, 9 occupational health centers have enrolled 66 hairdressers (employed in 54 hair salons) and 30 occupationally unexposed participants.

CONCLUSIONS: The results will represent the first data on occupational exposure to resorcinol in France and its relationship with thyroid hormones in hairdressers. Following a multidisciplinary approach that includes biomonitoring, epidemiology, and exposure data collection at both the hairdressers and salon levels, this study enables an in-depth assessment of exposure to the thyroid disruptors in the workplace. Together with the inventory of hair products, these results may enhance the tools for chemical risk assessment and prevention in hair salons.

PMID:41915798 | DOI:10.2196/65833

Categories
Nevin Manimala Statistics

Analysis of interactions between posaconazole/voriconazole and venetoclax

Antimicrob Agents Chemother. 2026 Mar 31:e0110125. doi: 10.1128/aac.01101-25. Online ahead of print.

ABSTRACT

Venetoclax (VEN), a selective BCL-2 inhibitor predominantly metabolized by CYP3A4, is a cornerstone therapeutic for myeloid neoplasms (MNs). Patients with myeloid malignancies are at elevated risk of invasive fungal infections (IFIs), and triazole antifungal drugs, such as posaconazole (PCZ) and voriconazole (VCZ), are commonly used for prophylaxis or treatment. These agents are potent CYP3A4 inhibitors and will exhibit significant potential for pharmacokinetic drug-drug interactions with VEN. Although studies on their interaction are limited, such combinations are frequently used in clinical practice, making further research highly significant. This study aimed to investigate the changes in blood concentration and the safety of VEN when combined with triazole antifungal drugs (PCZ and VCZ). Patients with MN treated with VEN from April 2023 to April 2025 were enrolled and allocated to the VEN monotherapy group and the VEN plus triazole antifungal drug group. We collected baseline demographic characteristics and monitored adverse events. Steady-state plasma concentrations of VEN were quantified using the liquid chromatography-mass spectrometry methodology. Statistical analyses, including comparative assessments of plasma concentrations and adverse event rates, were performed using IBM SPSS Statistics 26. A total of 54 patients were enrolled in the study. Following VEN dose reduction to 100 mg, plasma concentrations in the VEN + PCZ/VCZ group remained significantly elevated compared to the VEN group (P < 0.001). However, the magnitude of this elevation did not differ significantly between the VEN + PCZ group and the VEN + VCZ group (P = 0.176). In addition, there was no linear correlation between VEN concentration and PCZ/VCZ concentration. Safety analysis revealed no statistically significant differences between the two groups in the incidence of grade ≥3 hematological adverse events (P = 0.214) or severe (grade ≥3) gastrointestinal adverse events (P = 0.671). VEN combined with PCZ or VCZ resulted in significantly higher VEN exposure without a corresponding increase in severe hematological or gastrointestinal toxicity. This strategy effectively mitigates IFI risk without compromising the safety profile of VEN therapy.

PMID:41915767 | DOI:10.1128/aac.01101-25

Categories
Nevin Manimala Statistics

Graph statistics theory of individualized quantitative genetics under haplotype-resolved genome assembly

Proc Natl Acad Sci U S A. 2026 Apr 7;123(14):e2600004123. doi: 10.1073/pnas.2600004123. Epub 2026 Mar 31.

ABSTRACT

Quantitative genetics is essential for genetic dissection of complex traits, yet the existing theory fails to illustrate a comprehensive landscape of genetic control mechanisms driving phenotypic variation and evolution. Here, we develop a statistical approach to assemble all genome loci into omnigenic interactome networks from diplotyped sequencing data. Such networks can not only capture dominance, epistasis, and pleiotropy and leverage these genetic concepts as bidirectional, signed, and weighted interactions among alleles and nonalleles, but also establish a framework for dissecting the genetic architecture of any single individual. While traditional approaches can only estimate coarse-grained genetic parameters at the population level, our approach can portray a fine-grained picture involving how each allele acts and interacts with every other allele for a single individual, thus facilitating its genome editing and genome engineering. By analyzing transcriptomic data of two diplotyped cultivars of a woody plant, our approach can interpret the genetic mechanisms underlying this species’ cold resistance and interorgan communication. Our network-centric approach, generalized as a graph statistics theory, builds the foundation of individualized quantitative genetics, a theory that can make genetics even more transformational to precision breeding or precision medicine.

PMID:41915744 | DOI:10.1073/pnas.2600004123

Categories
Nevin Manimala Statistics

Non-ergodicity in ecology and evolution

Proc Natl Acad Sci U S A. 2026 Apr 7;123(14):e2522964123. doi: 10.1073/pnas.2522964123. Epub 2026 Mar 31.

ABSTRACT

Stochasticity plays an important role in all biological systems. The standard way to deal with stochasticity involves averaging over an ensemble of independent realizations. However, such mean statistics need not accurately reflect the typical outcomes in any finite sample unless the system satisfies the property of ergodicity, which guarantees that each trajectory will over time experience the same statistics as the entire ensemble. Here, we argue that, in contrast, non-ergodicity might instead be the rule rather than exception in real biological systems and investigate its implications for eco-evolutionary dynamics through three case-studies. First, we show how demographic stochasticity leads to ergodicity breaking where the asymptotic growth rate carries a signature of the initial condition. This motivates us to define a mutant establishment threshold, which quantifies a critical population size above which the typical mutant population starts to grow. Second, we consider environmental stochasticity and demonstrate that eco-evolutionary feedback can lead to non-ergodic dynamics, which has the important consequence that the fitness of a genotype cannot be simply averaged over the environments. Finally, we show how in a metapopulation structure the evolutionary dynamics within a typical subpopulation can deviate from the ensemble dynamics in the entire metapopulation, which is sufficient to explain the evolution and persistence of cooperation despite a fitness cost.

PMID:41915738 | DOI:10.1073/pnas.2522964123

Categories
Nevin Manimala Statistics

Network-constrained Random Lasso for biologically interpretable gene network inference across unequal sample sizes

PLoS One. 2026 Mar 31;21(3):e0344198. doi: 10.1371/journal.pone.0344198. eCollection 2026.

ABSTRACT

Gene regulatory network inference is a key approach for elucidating molecular mechanisms underlying complex diseases, but accurately inferring them from high-dimensional data, especially when sample sizes are imbalanced, remains a significant challenge. Although the L1-type regularization methods have been used for gene network inference, the existing methods often fail under conditions involving high dimensionality, noise, and unequal sample sizes across phenotypes. To overcome these limitations, this study developed netRL, a novel computational framework that integrates the Random Lasso with prior network biological knowledge. The proposed method leveraged a bootstrap-based strategy to stabilize the selection of key regulatory genes and incorporates network-informed penalization using centrality measures (i.e., hubness and betweenness centrality). This study also introduced a statistical strategy using a hypergeometric test to assess the significance of the inferred edges, thereby enhancing the reliability of the network. Through extensive simulation studies, this study demonstrated that netRL outperforms conventional methods in both network estimation and gene selection. Applying netRL to whole-blood RNA-seq profiles from the Japan COVID-19 Task Force, this study successfully identified distinct phenotype-specific molecular interplays between asymptomatic and critical cases despite pronounced sample imbalance. The findings reveal that asymptomatic networks were dense and enriched for ribosomal proteins, whereas critical networks were sparse, centralized, and characterized by hub genes such as NFKBIA, B2M, CXCL8, and FOS. Pathway enrichment further revealed phenotype-specific biological processes, highlighting molecular signatures of disease progression. The results of this study suggest that enhancing the activity of asymptomatic condition-specific markers (e.g., ribosomal proteins) may provide important insights into the molecular mechanisms underlying COVID-19 severity. Collectively, these results demonstrate that netRL enables biologically interpretable and statistically robust network inference, offering new insights into the molecular basis of COVID-19 severity and broader applications in systems biology.

PMID:41915715 | DOI:10.1371/journal.pone.0344198

Categories
Nevin Manimala Statistics

Feasibility and acceptability of task sharing collection of HIV viral load dried blood spot samples with community lay cadres: A cross-sectional diagnostic validation study in Zimbabwe

PLOS Glob Public Health. 2026 Mar 31;6(3):e0006180. doi: 10.1371/journal.pgph.0006180. eCollection 2026.

ABSTRACT

Viral load (VL) testing is a critical tool for clinical management of HIV, yet healthcare worker (HCW) shortages remain a key barrier to VL sample collection. This study assessed the feasibility and acceptability of VL dried blood spot (DBS) sample collection by community lay cadres (CLCs) compared to collection by trained HCWs. We implemented a cross-sectional diagnostic validation study across 10 purposefully selected public health facilities in Zimbabwe over six weeks in March-April 2024. Two DBS samples were collected from 374 participants: a reference sample collected by a HCW and a validation sample collected by a CLC. A subset of 173 CLC collections were observed using a checklist, and surveys were conducted with participating clients and CLCs. Diagnostic comparability was assessed using the proportion of matched pairs with agreement on viral load suppression status and Gwet’s AC1 statistic, while survey and observation data were analyzed using descriptive statistics. No samples were rejected by the laboratory, but two samples (one collected by a HCW and one by a CLC) were classified as invalid. Of the 372 paired tests analyzed, 96.0% (95%CI 93.2-97.7%) had concordant results, and the Gwet’s AC1 was 0.9564, indicating almost perfect agreement. All critical checklist items were done properly in 90.2% (95%CI 85.7-94.7%) of observed CLC collections. All CLCs reported confidence in performing DBS sample collection (89% very confident; 11% somewhat confident), and 94% of clients indicated willingness to have samples collected by a CLC in the future. These findings suggest that task-sharing VL DBS sample collection with CLCs is a feasible strategy, supported by strong diagnostic comparability, high CLC competency, and client acceptability. Policymakers should consider formalizing task shifting of VL sample collection within facilities. Further evidence on the feasibility of community-based DBS collection is needed.

PMID:41915714 | DOI:10.1371/journal.pgph.0006180