Tag: statistics

Menopause. 2026 May 12. doi: 10.1097/GME.0000000000002788. Online ahead of print.

ABSTRACT

OBJECTIVE: To explore any association between risk-reducing bilateral salpingooophorectomy (RRSO) and bone mineral density (BMD) and fracture risk among women with a germline likely pathogenic or pathogenic variant in genes causing hereditary breast and ovarian cancer.

METHODS: Longitudinal prospective observational study. Clinical, biochemical, and BMD assessments were performed at study entry (V0) and after 18 months (V1). Four groups were compared: RRSO (RRSO in premenopause without hormone therapy [HT]), RRSO+HT (RRSO followed by HT), MEN (natural menopause with/without RRSO), and FERT (regular menstrual cycles not undergoing RRSO).

RESULTS: One hundred four women were enrolled (52 BRCA1 germline likely pathogenic or pathogenic variant, 49 BRCA2, 3 other genes): 30 RRSO, 10 RRSO+HT, 29 MEN, 35 FERT. The V0 evaluation was performed at 2.85 ± 2.03 years from RRSO. At V0, no difference in lumbar spine (LS) and femoral neck BMD was detected comparing RRSO to RRSO+HT, MEN, and FERT. At V1 RRSO was associated with higher femoral neck BMD than MEN (P = 0.016), together with worse LS BMD than FERT (P = 0.045). The temporal decline of LS BMD in RRSO was more pronounced than MEN (P = 0.019). Calculated risk of fracture (Fracture Risk Assessment Tool [FRAX]) at V0 was lower in RRSO than MEN (P < 0.001), similar to RRSO+HT and FERT; at V1, FRAX was higher in RRSO than FERT (P = 0.014).

CONCLUSIONS: RRSO was associated with greater and prolonged bone health decline in women ovariectomized at premenopausal age, not receiving HT. This high-risk population deserves long-term BMD monitoring, and HT mitigating effect might be considered.

PMID:42118531 | DOI:10.1097/GME.0000000000002788

Anal Sci. 2026 May 12. doi: 10.1007/s44211-026-00902-4. Online ahead of print.

ABSTRACT

A portable microfluidic titration system using a smartphone camera was developed as a detector for onsite quantitative analysis. Two types of cross-shaped microfluidic devices with different channel geometries were designed and evaluated to improve the visual detectability of the equivalence point under limited spatial resolution. An expanding-channel device was found to promote molecular diffusion downstream, resulting in enhanced visibility of the equivalence point compared to a constant-width device. Using the optimized device, a strong acid-strong base system was subjected to acid-base titration using bromothymol blue as the indicator. The color images captured by the smartphone camera were analyzed by extracting the red channel intensity profiles and used to determine the distance corresponding to the equivalence point. A linear relationship was obtained between the measured distance and hydrochloric acid concentration in the range of 25-150 mM. The applicability of the proposed system was demonstrated by analyzing a real hot-spring water sample. The determined acid concentration was in good agreement with that obtained by conventional volumetric titration, with no statistically significant difference at the 95% confidence level. These results indicate that the proposed portable microfluidic titration system enables reliable quantitative analysis without the use of microscopes or specialized optical instruments, highlighting its potential for onsite analytical applications.

PMID:42118521 | DOI:10.1007/s44211-026-00902-4

Phys Eng Sci Med. 2026 May 12. doi: 10.1007/s13246-026-01739-x. Online ahead of print.

ABSTRACT

The early diagnosis of Parkinson’s disease (PD) using SPECT imaging continues to be challenging due to the subtle dopaminergic deficits present in the early stages of the disease. This study proposes a novel hybrid approach combining conventional and deep learning features to improve PD classification, and applies it to reclassify scans without evidence of dopaminergic deficit (SWEDD) cases. We used SPECT images from early PD patients and healthy controls (HC) and extracted SBR metrics, morphometric, and deep learning features. Our multi-stage feature selection pipeline employed near-zero variance filtering, ANOVA F-test analysis, correlation-based feature elimination, and Random Forest importance scoring. We evaluated multiple machine learning algorithms and selected Linear Discriminant Analysis as the optimal classifier, then applied this model to reclassify 79 SWEDD cases. Feature selection reduced 79 significant features to 15 optimal features: 1 SBR metric (6.7%), 7 morphometric (46.7%), and 7 deep features (46.7%). The hybrid Linear Discriminant model achieved the best performance, outperforming individual feature approaches with 97.40% test accuracy, 96.25% sensitivity, 98.65% specificity, and 99.59% AUC. Statistical analysis revealed morphometric features had the highest mean importance (0.0699 ± 0.0539), followed by deep (0.0400 ± 0.0570) and SBR features (0.0206 ± 0.019). SWEDD reclassification identified 5 cases (6.3%) with imaging patterns consistent with early PD, while 74 cases (93.7%) maintained HC characteristics. This study presents a proof-of-concept demonstration of the effectiveness of integrating conventional measures with deep learning techniques for improving the early diagnosis of PD, while offering new insights into SWEDD case reclassification.

PMID:42118513 | DOI:10.1007/s13246-026-01739-x

Saudi Dent J. 2026 May 12;38(5):65. doi: 10.1007/s44445-026-00178-4.

ABSTRACT

Periodontal wound dressings have advanced from passive protectants to bioactive agents. This study compared the efficacy of Blue®m gel and a hyaluronic acid (HA) gel in promoting wound healing and controlling postoperative pain after functional crown lengthening surgery. A prospective, randomized, patient and outcome assessor-blinded study was conducted on 40 systemically healthy patients (aged 20-60 years) requiring crown lengthening of posterior teeth. Participants were divided into two groups: Blue®m gel (Group A) and custom-formulated HA gel (Group B). Both gels were applied to the surgical site immediately after suturing and then three times daily for 1 week. Wound healing was assessed at 1, 2, and 3 weeks using the Early Wound Healing Index (EHS, including CSR for closure, CSH for hemostasis and CSI for inflammation) and the Landry Wound Healing Index. Postoperative pain was evaluated via a Numeric Pain Rating Scale (NPRS) on Days 1, 2, and 3. Outcome comparisons between groups were performed with Chi-square tests for categorical healing indices and Mann-Whitney test for ordinal data. Both interventions yielded excellent clinical outcomes with comparable healing patterns. By Week 1, 100% of sites in both groups had complete incision closure (merged margins). Approximately 20% of patients in each group showed slight fibrin presence and mild redness at Week 1, which resolved entirely by Week 2. Consequently, EHS scores were high in both groups (most cases scoring 9-10 at Week 1 and 10 by Week 2) with no significant intergroup difference (p > 0.05). The Landry index reflected progressive improvement from predominantly red tissue at Week 1 to fully pink, healthy tissue by Week 3 in both groups (p > 0.05). Postoperative pain was mild and diminished rapidly: On Day 1, pain scores ranged from 0 to 4 in Group A and 1 to 2 in Group B, dropping significantly by Day 3 with no difference between the two groups (p > 0.05). No adverse effects were observed with either gel. Blue®m gel and HA gel demonstrated favorable clinical outcomes in soft tissue wound healing and early postoperative pain control, with no statistically significant differences observed between groups. Both agents can be safely recommended as effective periodontal dressings in this context, with the choice between them potentially guided by practical considerations such as cost and availability.

PMID:42118509 | DOI:10.1007/s44445-026-00178-4

Drug Saf. 2026 May 12. doi: 10.1007/s40264-026-01677-3. Online ahead of print.

ABSTRACT

Spontaneous reporting databases play a central role in pharmacovigilance for monitoring the safety of drugs and vaccines. Conventional statistical signal detection has relied primarily on disproportionality analyses based on reporting frequencies, whereas information on the timing of adverse event onset has not been fully exploited. Time to onset (TTO), defined as the interval between the initiation of drug administration and the occurrence of an adverse event, provides complementary information that captures temporal patterns of event manifestation beyond simple occurrence counts. This review summarizes the definition, calculation, characteristics, and limitations of TTO analyses in spontaneous reporting databases and provides an overview of statistical signal detection methods incorporating TTO information. In particular, nonparametric distribution-comparison approaches, such as the Kolmogorov-Smirnov and Anderson-Darling tests, are well suited to spontaneous reporting data, in which the underlying population and exposure size are unknown. These methods enable the detection of abnormalities in the temporal structure of adverse event onset that may not be identifiable through frequency-based analyses alone. Furthermore, disproportionality analysis and TTO-based approaches are not competing methods but complementary strategies that capture different dimensions of safety signals-reporting frequency and temporal patterns-and their combined use may improve both sensitivity and interpretability of signal detection. The review also discusses survival analysis-based methods and Weibull modeling for TTO data, outlining their theoretical background and applications while emphasizing their inherent limitations when applied to spontaneous reporting systems. Because of reporting bias, incomplete time information, and the absence of non-event cases, such methods should not be used to estimate population-level risks or to infer causality. In conclusion, TTO analyses using spontaneous reporting databases should be positioned as exploratory tools for characterizing onset patterns, generating hypotheses, and informing the design of subsequent epidemiological and safety studies, rather than as a direct basis for clinical or regulatory decision making.

PMID:42118500 | DOI:10.1007/s40264-026-01677-3

Discov Nano. 2026 May 12;21(1):185. doi: 10.1186/s11671-026-04610-w.

ABSTRACT

In industries like chemical processing, energy systems, metallurgy, filtration, and electronics cooling, activation energy in magneto-nanofluid flow with variant viscosity is essential for regulating reaction rates, maximizing heat and mass transfer, enhancing energy efficiency, and guaranteeing safe operation. This work is important because it advances our knowledge of heat and mass transmission in magnetized nanofluid flows, where the fluid viscosity varies nonlinearly with temperature or other physical parameters. The study’s primary goal is to create a numerical model capable of precisely analyzing the intricate relationship between magnetic forces, nonlinear viscosity, porous media, and nanoparticle transport. To get the perfect predictions, the governing model employed the efficacy of artificial neural networks with Levenberg Marquardt structure back propagation (ANN-LMSB), which is designed to investigate energy activation with exponential viscosity variant with temperature on magneto-hydrodynamic nanofluid flow past porous plate (MHD-NFPP). To articulate mathematical modeling, the Reynolds exponential model is used. By employing the model of Darcy-Brinkman-Forchheimer, the momentum equation is additionally formulated. Thermophoresis force and Brownian diffusion have been inspected by implementing Buongiorno model. Along with magnetic body force, mass conservation, nanoparticle concentration, momentum, and energy equations are expressed. Initially, the flow of fluid is denoted by the scheme of PDEs, which are transformed into the structure of ODEs. By employing Adams numerical method, a data set for suggested ANN-LMSB is produced for diverse scenarios by alteration of stretching parameter, the Hartmann number, the thermal and concentration Grashof numbers, the thermophoresis, the Brownian motion, Prandtl number, the chemical reaction constant, Schmidt number, and relative temperature parametric number. By training, testing, and validation procedures of ANN-LMSB, estimated solution of distinct cases is verified, and for the perfection of the suggested model, the comparison for verification is carried out. Afterwards, execution of suggested ANN-LMSB was validated by regression evaluation, mean square error, and histogram studies. Correctness level in range from 10^-9 to 10^-11 approves distinction of suggested methodology established on the closeness of the recommended and reference results.

PMID:42118499 | DOI:10.1186/s11671-026-04610-w

Psicol Reflex Crit. 2026 May 12. doi: 10.1186/s41155-026-00391-4. Online ahead of print.

ABSTRACT

BACKGROUND: The lack of development assessment instruments aimed at children with disabilities in the early years of life means that standardized items are used for accommodation.

OBJECTIVE: This study aimed to describe accommodations implemented in the administration of the Bayley Scales of Infant Development (BSID-III) cognitive scale and analyze their association with the cognitive performance of children affected by Congenital Zika Syndrome.

METHODS: A total of 125 children were assessed at 12 months using BSID-III. Twelve types of accommodation strategies were adopted and organized according to participants’ main disability conditions, such as sensory, motor, auditory, and general accommodations.

RESULTS: This study identified that 59.2% of participants used some accommodation. “Lighting” (sensory accommodation) included the use of lighting during the test, and “not timing” includes disabling time tracking for tasks that involve time management. They were the most used accommodations, in addition to having presented a statistically significant association (p < = 0.05) with several items assessed by the instrument. A strong, statistically significant negative correlation (ρ = -0.73; p < 0.001) was found between the number of accommodations used and the cognitive performance score obtained by children. This indicates that the greater the use of accommodations, the lower the level of cognitive performance. It is understood that the more severe the congenital syndrome, the more accommodations are required during the assessment.

CONCLUSION: These findings are consistent with the guidelines provided in the accommodation procedures, which aim to offer opportunities for adequate assessment of children and allow for an explanation of their actual level of development, without any compensation. Assessment using accommodation provides more reliable data on children’s developmental strengths and weaknesses and has the potential to guide effective intervention programs. Such explanation favors a perspective of equity in the provision of care to children with disabilities.

PMID:42118492 | DOI:10.1186/s41155-026-00391-4

Environ Sci Pollut Res Int. 2026 May 12. doi: 10.1007/s11356-026-37813-w. Online ahead of print.

ABSTRACT

The cement industry is a typical high-carbon and overcapacity sector. In the context of global climate change, identifying productivity loss driven by resource misallocation is essential for controlling CO₂ emissions in the cement industry. We incorporate energy and CO₂ emissions into the Hsieh and Klenow (2009) model (HK model), reconstruct the analytical framework through which resource misallocation affects productivity, and empirically evaluate the resulting productivity loss in Hunan Province’s cement industry from 2016 to 2019. The results show that eliminating resource misallocation increases industry productivity by 22.14%, with CO₂ price distortion accounting for 12% of the productivity loss. The study also shows that in the cement industry, economically developed regions have lower resource use efficiency than less developed regions; large enterprises have higher efficiency than small enterprises; older enterprises perform better than newer ones; and state-owned enterprises have higher efficiency than non-state-owned enterprises.

PMID:42118488 | DOI:10.1007/s11356-026-37813-w

Mol Divers. 2026 May 12. doi: 10.1007/s11030-026-11584-5. Online ahead of print.

ABSTRACT

Bisphenol A (BPA), an environmental endocrine disruptor, is implicated in hepatocellular carcinoma (HCC), but its molecular mechanisms are unclear. This study employed an integrative computational framework to identify potential BPA-related molecular targets in HCC, assess their statistical clinical value, and generate hypotheses regarding their roles within the tumor microenvironment. BPA and HCC targets were retrieved from public databases and intersected with differentially expressed genes in HCC, identifying fifteen overlapping genes statistically enriched in cell cycle regulation, p53 signaling, and viral carcinogenesis. Six hub genes (MKI67, CCNA2, EZH2, CCNB1, CDK1, BIRC5) were significantly upregulated in HCC with high internal cross-validated diagnostic accuracy (AUC > 0.96), although these estimates may be susceptible to overfitting and require external validation. Molecular docking and dynamics simulations predicted stable BPA binding to six proteins (Ki67, Cyclin A2, EZH2, Cyclin B1, CDK1, Survivin), with van der Waals forces calculated as the primary driving energy contribution by MM-PBSA. The two-gene (CCNB1/EZH2) risk model showed statistical associations with patient survival, validated internally and externally, although its generalizability remains limited. Mendelian randomization provided genetic evidence consistent with a potential risk-associated role for CCNB1 and a protective-associated role for EZH2. Single-cell analysis localized high CCNB1 and EZH2 expression to malignant and proliferative T-cells, correlating with specific immune infiltration patterns and checkpoint expression. In conclusion, these computational findings suggest a statistical and structural association between BPA exposure and HCC-related core cell-cycle regulators (e.g., CCNB1/EZH2). The data generate the hypothesis that CCNB1 and EZH2 may serve as prognostic biomarkers and potential contributors to HCC biology, possibly through coordinated effects on cell cycle dysregulation and immune microenvironment remodeling, though direct evidence of in vivo molecular targeting by BPA or causal pathway activation is not established by this study. These findings provide novel insights into BPA’s putative role in hepatocarcinogenesis and offer clues for future experimental validation regarding risk assessment and therapeutic strategies.

PMID:42118483 | DOI:10.1007/s11030-026-11584-5

Clin Transl Oncol. 2026 May 12. doi: 10.1007/s12094-026-04359-9. Online ahead of print.

ABSTRACT

PURPOSE: Gastric cancer (GC) remains a major global health burden, with poor survival rates. HER2 is a key biomarker for targeted therapy, but discordance between primary tumors and metastases may impact treatment decisions. This meta-analysis evaluated the prevalence and clinical relevance of HER2 status differences between primary gastric cancers and metastatic lesions.

METHODS: A systematic search of PubMed, Embase, and Cochrane was conducted for studies assessing HER2 status in matched primary and metastatic gastric cancer samples. Pooled proportions and 95% confidence intervals (CIs) were calculated using random-effects models. Subgroup analyses by metastatic site were performed. Statistical analyses were conducted using R software, version 4.2.3.

RESULTS: This meta-analysis included 3,515 patients across 20 studies. The pooled proportion of HER2-positive expression in primary gastric tumors was 13% (95% CI: 12-15%; I² = 68.7%), while HER2-negative tumors accounted for 74% (95% CI: 72%-76%; I² = 94.9%). In metastatic sites, the overall pooled proportion of HER2-positive lesions was 18% (95% CI: 16%-20%; I² = 77.3%), with notable variation across anatomical locations: 38% in lung metastases, 31% in liver metastases, 19% in lymph nodes, and 7% in peritoneum. Conversely, HER2-negative metastases accounted for 82% overall (95% CI: 80%-84%; I² = 78.2%), with proportions of 93% in peritoneum, 81% lymph nodes, 69% in liver metastases, and 62% in lung.

CONCLUSIONS: Significant heterogeneity in HER2 expression between primary and metastatic gastric cancer underscores the need for reassessment of HER2 status in metastatic sites. Relying solely on primary tumor samples may lead to underestimation of HER2 positivity and suboptimal therapeutic decisions. Incorporating site-specific HER2 testing into clinical practice may enhance patient selection for HER2-targeted therapies and improve treatment outcomes.

PMID:42118480 | DOI:10.1007/s12094-026-04359-9