Tag: nevin manimala

J Cancer Surviv. 2026 Jun 8. doi: 10.1007/s11764-026-02054-w. Online ahead of print.

ABSTRACT

PURPOSE: Prospective evidence on the role of pre-chemotherapy psychosocial factors in symptom burden across the first chemotherapy cycle remains limited among patients with cancer. This prospective multicenter observational cohort study aimed to comprehensively evaluate clinical and pre-chemotherapy psychosocial predictors of chemotherapy-induced nausea and vomiting (CINV) across the entire first chemotherapy cycle.

METHODS: Chemotherapy-naive adult cancer patients scheduled to receive their first cycle of highly or moderately emetogenic chemotherapy (HEC or MEC) were enrolled. Pre-chemotherapy psychosocial variables were assessed using the Distress Thermometer (DT), selected Mini-Mental Adjustment to Cancer (Mini-MAC) subscales, and an investigator-developed behavioral/cognitive risk factor questionnaire. CINV was assessed through a 21-day patient diary after chemotherapy. Correlation and multicollinearity diagnostics were performed to assess relationships among psychosocial variables. Univariable and multivariable logistic regression analyses were applied to identify factors associated with CINV across the acute, delayed, and beyond-risk phases. Moderation analyses examined whether clinical variables modified psychosocial effects. A sensitivity analysis restricted to patients receiving guideline-adherent prophylaxis assessed psychosocial associations with CINV using reduced models adjusted for established CINV risk factors.

RESULTS: Among 1168 patients screened, 1031 chemotherapy-naive individuals were eligible and included in the final analysis. Acute-phase CINV occurred in 72.8% of patients, while delayed-phase CINV was reported by 73.0%. Notably, 25.6% of patients experienced CINV beyond the risk phase, predominantly nausea (25.5%) rather than vomiting (3.8%). Patients who developed CINV had higher levels of pre-treatment psychological distress and maladaptive coping, including helplessness/hopelessness and anxious preoccupation (all P < 0.001). In univariable analyses, clinical factors, including HEC, advanced disease stage, and non-adherence to guideline-recommended prophylaxis, as well as patient-related and psychosocial factors, were associated with CINV. After adjustment, motion sickness history, short sleep duration, and clinically significant distress remained independently associated with CINV across multiple phases. In the beyond-risk phase, multiple psychosocial and behavioral factors, including vomiting expectancy, perceived nausea susceptibility, motion sickness history, short sleep duration, clinically significant distress, helplessness/hopelessness, and anxious preoccupation, remained independently associated with CINV, whereas most clinical determinants lost statistical significance, except chemotherapy emetogenicity. Moderation analyses indicated that these psychosocial associations were not significantly modified by chemotherapy emetogenicity or antiemetic guideline adherence. In sensitivity analyses restricted to patients receiving guideline-adherent prophylaxis, Mini-MAC/H, Mini-MAC/AP, and short sleep duration remained associated with overall CINV.

CONCLUSIONS: Pre-chemotherapy psychosocial and behavioral susceptibility factors were independently associated with CINV throughout the first chemotherapy cycle, with particularly persistent associations beyond the conventional risk window. These findings support integrating routine pre-chemotherapy psychosocial screening into standard antiemetic and survivorship-oriented supportive care.

IMPLICATIONS FOR CANCER SURVIVORS: Incorporating psychosocial risk assessment before chemotherapy may help identify patients vulnerable to persistent CINV and inform individualized supportive care across the survivorship continuum.

PMID:42258111 | DOI:10.1007/s11764-026-02054-w

Phys Eng Sci Med. 2026 Jun 8. doi: 10.1007/s13246-026-01750-2. Online ahead of print.

ABSTRACT

The complex dose delivery mechanisms of TomoTherapy (TOMO) demand rigorous patient-specific quality assurance (PSQA). This study systematically evaluates the relationship between ArcCHECK measurements and GPU-accelerated Monte Carlo (GPU-MC) calculations for nasopharyngeal carcinoma (NPC) TOMO plans across multiple gamma criteria, aiming to delineate their respective strengths and inform an optimized verification strategy. A retrospective analysis was conducted on 317 TOMO plans for NPC, each optimized using the Accuray Precision Treatment Planning System. Patient-specific dose verification was performed using ArcCHECK measurements and independent MC calculations implemented through PlanQA. Gamma passing rates (GPRs) were evaluated under nine different conditions, including both same-criterion and cross-criterion comparisons. To assess differences, agreement, and correlations between methods, statistical analyses were conducted using the Wilcoxon signed-rank test, Bland-Altman analysis, and Spearman correlation. Under identical Gamma criteria, there was no statistically significant difference in GPR between ArcCHECK and MC. However, cross-criterion comparisons revealed marked discrepancies, highlighting the criterion-dependent nature of GPR outcomes. Lenient standards typically exhibit good consistency and relatively minor deviations. Furthermore, the correlations among all combinations of these standards can be considered negligible. The comparable performance of GPU-MC and ArcCHECK under conventional criteria (3%/3 mm, 3%/2 mm) validates ArcCHECK’s established role in verifying delivery fidelity. Crucially, under the stringent 2%/2 mm criterion where ArcCHECK passing rates decline, MC provides critical diagnostic power to differentiate between discrepancies originating from the dose calculation algorithm and those arising from the physical delivery process. For TOMO PSQA, GPU-MC and ArcCHECK are complementary. An integrated approach leveraging both methods is therefore recommended.

PMID:42258104 | DOI:10.1007/s13246-026-01750-2

Carbon Balance Manag. 2026 Jun 8. doi: 10.1186/s13021-026-00464-y. Online ahead of print.

ABSTRACT

BACKGROUND: Carbon stocks and stock changes in harvested wood products (HWPs) are an important part of land sector greenhouse gas (GHG) estimation and reporting. HWPs broadly categorized as products in-use (e.g., solid wood and paper products) and in solid waste disposal sites (SWDS; e.g., landfills), store carbon transferred from harvested trees. In the United States (US), estimates of carbon in HWPs have historically been reported in the US GHG Inventory and included in submissions to the United Nations Framework Convention on Climate Change. These data have been obtained from national and international statistics on production and consumption of forest products and incorporated into a compilation system to estimate carbon in products in-use and in SWDS. In contrast, estimates of carbon in forest ecosystems have been obtained from nationwide forest inventory (NFI) data collected and maintained by the US Forest Service, Forest Inventory and Analysis (FIA) program. Here we describe a case study for the northern Lake States region of the US (Michigan, Minnesota, Wisconsin) where harvest data from the FIA program were integrated into HWP compilation systems. This advance improves consistency and continuity with forest ecosystem from NFI plots with estimates of HWPs.

RESULTS: Over the 1900-2024 time period, total estimated net accumulation (i.e., balance of additions from transfers of harvested wood from forest ecosystems and losses from decay of wood harvested in the past) of carbon stored in products in-use was 277.0 ± 17.5 Million Metric Tons (MMT) Carbon (C) and in SWDS was 155.2 ± 9.8 MMT C. We estimate that HWPs from the region represent a carbon sink of 4.9 ± 0.1 MMT C in 2024. These estimates include HWPs produced in the region and exported domestically or internationally, as well as any HWPs produced and retained in the region, but not imports.

CONCLUSIONS: The proposed methodology enables disaggregation with coarse national and state-level FIA data, and allows for integration of more specific, entity-level data to improve precision and reduce uncertainty in HWPs estimates in the US and improves consistency and continuity with forest ecosystem estimates across spatial and temporal scales.

PMID:42258097 | DOI:10.1186/s13021-026-00464-y

J Patient Rep Outcomes. 2026 Jun 8. doi: 10.1186/s41687-026-01094-1. Online ahead of print.

ABSTRACT

BACKGROUND: Endoscopic retrograde cholangiopancreatography (ERCP) is often performed under conscious sedation, which may increase pain and dissatisfaction. Mental health conditions may influence patient-reported experience measures (PREMs), including tolerability. This study explores the association between pre-existing anxiety and/or depression and ERCP tolerability using the validated Patient-Reported Scale for Tolerability of Endoscopic Procedure (PRO-STEP) to address this.

METHODOLOGY: We performed a retrospective analysis of prospectively maintained data from an international observational cohort of adult patients undergoing ERCP. Pre-existing anxiety/depression were identified prior to the index procedure and the PRO-STEP questionnaire was used to evaluate peri- and post-procedure outcomes. Univariable and multivariable logistic regressions examined the associations between pre-operative anxiety/depression and peri- and post-operative tolerability and patient-reported health outcomes.

RESULTS: Among 3,714 participants, 13% had anxiety and/or depression. The mean age of participants in the control group was 62.3 ± 17.4 years, and 49.9% were female, while in the group with depression and/or anxiety, the mean age was 60.0 ± 16.4 years and 68.3% were female (p < 0.001). Common bile duct stones were the most common indications for ERCP in both groups (41.6% of controls and 42.4% of the depression/anxiety group, p = 0.10). Patients in the depression/anxiety group reported higher rates of opioid use (23.4% vs. 13.8%, p < 0.001), cannabis use (22.8% vs. 10.5%, p < 0.001), and heavy alcohol consumption (5.0% vs. 3.6%, p < 0.001). There were no statistically significant differences between groups in terms of disposition, comorbidities, or procedural parameters. Underlying anxiety and/or depression was significantly associated with increased intra-procedural awareness score > 3 (odds ratio, OR, 1.55, 95% CI 1.23-1.95) and discomfort score > 6 (OR 1.73, 95% CI 1.23-2.43) and with post-procedural scores > 3 for abdominal pain (OR 1.44, 95% CI 1.08-1.93), nausea (OR 2.03, 95% CI 1.43-2.89), and distension (OR 2.12, 95% CI 1.29-3.50).

CONCLUSIONS: Patients with pre-existing anxiety and/or depression reported significantly worse tolerability of ERCP under conscious sedation. Although further research is needed in this area, staff in gastrointestinal endoscopy units should consider strategies aimed at improving tolerability and, consequently, satisfaction among vulnerable populations.

PMID:42258080 | DOI:10.1186/s41687-026-01094-1

Clin Rheumatol. 2026 Jun 8. doi: 10.1007/s10067-026-08213-9. Online ahead of print.

ABSTRACT

BACKGROUND: Humans are concurrently exposed to a variety of environmental endocrine-disrupting chemicals (EDCs), which include such widespread substances like urinary perchlorates, nitrates, thiocyanates, and serum per- and polyfluoroalkyl substances (PFAS). The vast majority of the previous studies were devoted to individual chemicals or certain groups of chemicals, but the impact of co-exposure to mixtures of EDCs was also not thoroughly studied. The objective of this study is to identify the relationship between these EDC mixtures and prevalence of rheumatoid arthritis (RA) based on NHANES database.

METHODS: We used three types of regression models with individual chemical effects, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) in 2005-2012 to analyze results of individuals aged ≥ 20 years. Age and gender subgroup analyses were also done.

RESULTS: A total of 4219 patients were analyzed, and 215 (5.10%) of them had RA. Multivariate logistic regression demonstrated that there was a significant relationship between thiocyanate (as a continuous variable) and the prevalence of RA. The upper quartile of perchlorate, nitrate as well as thiocyanate and MPAH showed correlation with elevated prevalence of RA. The effects of specific chemicals were stronger among the older subjects and females. WQS and BKMR models showed a positive association between co-exposure to these chemicals and RA, with thiocyanate as the primary contributor. These associations were especially strong in young adults and females.

CONCLUSION: This study provides the first evidence that co-exposure to a mixture of EDCs is positively correlated with RA, with a stronger effect in young adults and females. Thiocyanate is identified as a key contributor. Limiting exposure to EDCs may be beneficial for potentially reducing RA risk. Key Points • We assessed the association between a mixture of ten chemicals and the risk of incidence of RA. • The co-exposure of chemical mixtures were positively associated with RA by WQS and BKMR models. • Thiocyanate was the key contributor in these mixtures. • The associations were more pronounced among young adults and females.

PMID:42258069 | DOI:10.1007/s10067-026-08213-9

Saudi Dent J. 2026 Jun 8;38(6):82. doi: 10.1007/s44445-026-00191-7.

ABSTRACT

PURPOSE: To examine the associations between oral microbiome diversity and genus composition with the Zhejiang University Index (ZJU Index) and clinical biomarkers.

METHODS: We included 2,490 eligible participants from the U.S. National Health and Nutrition Examination Survey (NHANES). Oral microbiome diversity was assessed using alpha and beta diversity, and genus-level analyses were based on abundance transformed using the centered log-ratio (CLR) method to account for compositionality. Weighted logistic regression models were used to assess the corresponding associations. Beta diversity disparities were evaluated through Principal Coordinate Analysis (PCoA) and Permutational Multivariate Analysis of Variance (PERMANOVA).

RESULTS: Alpha diversity metrics were positively correlated with the ZJU Index in males aged 30-44 years (Faith’s Phylogenetic Diversity: unadjusted: β = 0.05, 95% CI: 0.006 to 0.094, p = 0.033; Model 1: β = 0.058, 95% CI: 0.011 to 0.104, p = 0.026; Model 2: β = 0.076, 95% CI: 0.032 to 0.120, p = 0.005; Model 3: β = 0.081, 95% CI: 0.035 to 0.128, p = 0.008) and in females aged 60-69 years (Observed ASVs: β = 1.242, 95% CI: 0.345 to 2.139, p = 0.042; Faith’s Phylogenetic Diversity: β = 0.097, 95% CI: 0.025 to 0.168, p = 0.045). Significant differences in beta diversity metrics were observed among ZJU Index-defined subgroups (p < 0.05), confirmed with age- and sex-stratified analyses. Genera including Bulleidia, Senegalimassilia, Fretibacterium, and Hungatella exhibited significant associations with the ZJU Index and with clinical biomarkers (triglycerides, low-density lipoproteins (LDL), high-density lipoproteins (HDL), insulin, and testosterone).

CONCLUSIONS: Higher oral microbiome alpha diversity was associated with higher ZJU Index in certain populations. Beta diversity demonstrated that ZJU Index-defined subgroups differed in oral microbial composition. Specific genera were identified to be significantly associated with the ZJU Index and clinical biomarkers.

PMID:42258061 | DOI:10.1007/s44445-026-00191-7

Clin Exp Nephrol. 2026 Jun 8. doi: 10.1007/s10157-026-02895-w. Online ahead of print.

ABSTRACT

BACKGROUND: Cyclophosphamide (CTX) combined with glucocorticoids and rituximab (RTX) are widely used for idiopathic membranous nephropathy (IMN), but clinical data comparing them in newly diagnosed patients with impaired renal function (eGFR < 60 mL/min/1.73 m²) remain scarce. This study aimed to compare their efficacy, safety, and effects on renal function in this specific population.

METHODS: A retrospective study was conducted at the First Affiliated Hospital of Wannan Medical University from November 2019 to July 2024, including 113 newly diagnosed IMN patients (55 in the CTX group, 58 in the RTX group) diagnosed by renal biopsy or positive PLA2R antibodies. All patients were treatment-naive and followed for ≥ 6 months.

RESULTS: At 6 months, composite remission rates were 69.09% in the CTX group and 62.07% in the RTX group (P > 0.05). At 12 months, the RTX group showed a numerically higher composite remission rate (83.87% vs. 70.83% in CTX group) without statistical significance (P = 0.186). By 18 months, both groups reached 73.68% composite remission (P = 1.000). In the subgroup with eGFR < 60 mL/min/1.73 m², RTX significantly improved renal function at 6 months (P = 0.008), while CTX showed no significant improvement (P = 0.113); however, no intergroup difference in eGFR was observed (P = 0.793). The CTX group had a higher incidence of non-serious adverse events, including leukopenia and mild infections (P < 0.05). HypoIgGemia was documented in 5 patients (8.62%) in the RTX group, all mild and asymptomatic.

CONCLUSION: RTX shows comparable efficacy and better safety relative to CTX in this cohort, and may be a preferred option for newly diagnosed untreated IMN, especially in those with early renal impairment. RTX demonstrated comparable efficacy to CTX in newly diagnosed IMN but with superior safety. Notably, RTX showed greater short-term (6-month) renal function improvement in patients with early renal impairment, though long-term effects need further verification in larger-sample prospective studies.

PMID:42258058 | DOI:10.1007/s10157-026-02895-w

Trop Anim Health Prod. 2026 Jun 8;58(5):321. doi: 10.1007/s11250-026-05117-3.

ABSTRACT

This study aimed to evaluate the impact of two probiotic-based dietary formulations, Amnil^®, containing Bacillus subtilis and Bacillus licheniformis, and M-Mobilize^®, composed of yeast extract, Bacillus subtilis, Lactobacillus plantarum, and Pediococcus acidilactici, as well as their potential combined effect when administered sequentially (Amnil^® from day 1 to 30, followed by M-Mobilize^® from day 31 to 60), on growth performance, bone health, and meat quality in Muscovy ducks. In total, 120 male Muscovy ducklings (one day old) were randomly allocated to four dietary groups: a control group (G-C) receiving no probiotics; (G-A), provided with Amnil^® at 0.4 kg/ton; (G-M), receiving M-Mobilize^® at 0.5 kg/ton; and (G-A-M), given Amnil^® (0.4 kg/ton) during days 1-30 and M-Mobilize^® (0.5 kg/ton) during days 31-60. The (G-A) group had improved body weight at 14 and 60 days, water-holding capacity % (WHC%), and cooking loss (CL) of thigh muscle (P < 0.05) compared to G-C. Furthermore, the G-A-M probiotic program increased tibial phosphorus concentration and thigh muscle weight (P < 0.05) compared to the control group (G-C). All probiotic-treated groups had increased tibial calcium concentrations and medial and lateral wall thickness but decrease gait score (2) (P < 0.05) compared to the control group. The G-M birds had increased tibial length, thigh muscle color, and sensory parameters (P < 0.05) compared to the control group. The G-A and G-M birds had an increased diameter of the tibial medullary canal and their ability to walk, but decreased tibiotarsal index (P < 0.05) compared to the control birds. There were no statistical treatment effects on the latency to lie test, foot pad dermatitis, hock burn, or thigh muscle pH (P > 0.05). The use of probiotics as dietary supplements may offer an effective nutritional strategy to improve productivity, welfare, and meat quality in Muscovy ducks.

PMID:42258054 | DOI:10.1007/s11250-026-05117-3

Behav Res Methods. 2026 Jun 8;58(7):189. doi: 10.3758/s13428-026-03053-6.

ABSTRACT

When modeling psychological processes and relationships, intrinsically nonlinear models often enhance researchers’ ability to draw useful theoretical and substantive conclusions. In addition, psychological theories frequently suggest that such processes and relationships are moderated; therefore, it is often important to test for, probe, and plot moderation. However, extant methods for assessing and visualizing moderation are largely restricted to linear models. Therefore, the goal of this paper is to develop novel analytical and software tools that enable researchers to specify and examine moderated parameters within intrinsically nonlinear models. First, methods for testing, plotting, and probing moderation are expanded in novel ways for use in nonlinear models; specifically, we present conceptual and mathematical extensions of the Johnson-Neyman (JN) technique. The JN technique is currently used to probe moderation of simple slopes within the linear modeling framework; our extensions enable its application to any moderated parameter of an intrinsically nonlinear model. Additionally, we introduce a Shiny application called CurveBuilder, which unifies the process of choosing, specifying, fitting, and visualizing intrinsically nonlinear models that may include moderated parameters and/or random effects. The application provides a code-free environment for users to complete all steps of the analysis process, including uploading data, visually choosing start values, specifying models, plotting results, and probing moderation with the extended JN technique. CurveBuilder examples are reviewed, and opportunities for future work in this area are discussed.

PMID:42258021 | DOI:10.3758/s13428-026-03053-6

J Comput Aided Mol Des. 2026 Jun 8;40(1):143. doi: 10.1007/s10822-026-00854-x.

ABSTRACT

Aqueous solubility is an important property for assessing the druggability and ecotoxicological effects of molecules. Successful drug candidates should have optimal aqueous solubility to improve bioavailability to target tissues. To effectively screen molecules in a short period of time, reliable predictive models are highly useful. In the present study, we conducted a round-robin exercise using a large, curated dataset of over 6000 compounds to predict aqueous solubility quantitatively. The six participating groups used an array of Machine Learning and Deep Learning algorithms to develop models with strong robustness and external predictive performance. All the models underwent rigorous Leave-One-Out and tenfold cross-validation. The diversity of training sets and descriptor types used by different groups paved the way for exploring the mechanistic basis for the efficient identification of contributing features. The best-performing model was selected using the statistical Sum of Ranking Differences (SRD) approach, considering the performances on training, cross-validation, and test, as well as the performance difference between the training and test sets. Additionally, a curated, true external set was screened by the six different models. Here, the best-performing model was selected using a consensus ranking strategy based on Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and [Formula: see text]. In both approaches, i.e., the inherent model performance in terms of training, test, and cross-validation statistics, and the ability of the model to efficiently predict true external data, the Stacking Ensemble of Deep q-RASPR models emerged as the winner. This model showed comparable predictive performance to the previously reported model, which apparently lacked a proper data curation workflow and contained a significant number of duplicates and mixtures in its dataset, which can inflate model statistics. The insights from the different feature contributions from the different groups identified the useful structural and physicochemical aspects, which can help synthetic chemists to optimize molecules.

PMID:42258020 | DOI:10.1007/s10822-026-00854-x