Nevin Manimala

Eur Radiol Exp. 2026 Jul 1;10(1):104. doi: 10.1186/s41747-026-00759-2.

ABSTRACT

OBJECTIVE: To determine the optimal low-keV level using deep learning image reconstruction (DLIR) that maximizes lesion detectability, and to assess the potential for iodinated contrast media (ICM) reduction based on detectability improvements across varying patient body habitus.

MATERIALS AND METHODS: An abdominal phantom was scanned using a standard thoraco-abdomino-pelvic dual-energy computed tomography (DECT) protocol during the portal venous phase, with three rings inserted simulating different body habitus. Virtual monoenergetic images (VMI) were reconstructed from 40 to 70 keV in 10 keV increments using adaptive statistical iterative reconstruction-V (ASIR-V) 50% and high-strength DLIR (DLIR-H). Contrast enhancement was quantified, spatial resolution was evaluated with the task-based transfer function, and noise characteristics were analyzed using the noise power spectrum. Low-contrast lesion detectability (5-10 mm) was assessed using an anthropomorphic model observer.

RESULTS: Compared to ASIR-V, DLIR-H provided equivalent contrast, reduced image noise, and improved spatial resolution. All lesion sizes with DLIR-H were technically detectable under all conditions. The reconstruction at 40 keV demonstrated the highest detectability of hypovascular lesions under all conditions. However, a decrease in detectability was observed in the large phantom relative to the small and medium phantoms, resulting in a reduced theoretical potential for iodine dose reduction. The theoretical potential for iodine dose reduction using 40 keV with DLIR-H is at least 31.3% based on the phantom-based model.

CONCLUSION: Under phantom conditions, 40 keV with DLIR-H shows superior detectability of hypovascular lesions under all conditions, suggesting the theoretical possibility of reducing iodine load by up to 31.3%, based on modeled detectability performance.

RELEVANCE STATEMENT: Based on a phantom-derived model, the combination of 40-keV VMI reconstruction with DLIR-H suggests the potential for more than 30% ICM reduction in oncologic body CT, a finding that warrants confirmation in clinical studies.

KEY POINTS: Based on a phantom-derived model 40 keV VMI with DLIR-H achieved the highest detectability of hypovascular liver lesions. This approach enabled a 31.3% ICM volume reduction. Larger body habitus limits ICM volume reduction optimization margins.

PMID:42384360 | DOI:10.1186/s41747-026-00759-2

Mol Cell Biochem. 2026 Jul 1. doi: 10.1007/s11010-026-05621-y. Online ahead of print.

ABSTRACT

Quantitative polymerase chain reaction (qPCR) is an indispensable tool in clinical biochemistry laboratories for gene expression and copy number variation (CNV) analyses. However, the interpretation of qPCR data including normalization, rigorous statistical testing, and professional visualization typically requires advanced bioinformatics expertise. This study aimed to develop a user-friendly, web-based platform that integrates robust statistical frameworks and quality control modules for streamlined and standardized qPCR data evaluation. GeneQuantify is freely accessible at https://GeneQuantify.streamlit.app/ and its source code is openly available at https://github.com/burhanettiny/GeneQuantify (GPL-3.0 license). GeneQuantify, a web-based application developed using Python and Streamlit, allows for the input of target and reference gene Cq values via manual entry or direct import from spreadsheet software or standardized RDML/RDES file formats. The platform automatically calculates ΔCq, ΔΔCq, and relative expression levels using the 2^{^(-ΔΔCq)} method. Integrated features include multi-reference gene normalization (geNorm), automated outlier detection (Grubbs’ test or Interquartile Range), and amplification efficiency correction (Pfaffl model). ΔCt values are subjected to normality (Shapiro-Wilk) and variance homogeneity (Levene’s) testing to ensure statistical validity. The platform features an automated statistical decision pipeline (Shapiro-Wilk → Levene → t/Welch/Mann-Whitney/ANOVA/Kruskal-Wallis) with Bonferroni and Benjamini-Hochberg FDR corrections. A six-language interface (Turkish, English, German, French, Spanish, and Arabic) ensures international accessibility. Platform accuracy was validated against manual Excel-based calculations across seven predefined test scenarios, yielding consistent results in all cases. GeneQuantify provides a highly accessible, integrated qPCR analysis environment that consolidates automated calculations, quality control, statistical decision-making, and visualization. By aligning with MIQE guidelines and offering RQ-based automated statistical selection, the platform enhances reproducibility, transparency, and workflow efficiency in molecular research, clinical biochemistry, and educational settings.

PMID:42384344 | DOI:10.1007/s11010-026-05621-y

Ann Biomed Eng. 2026 Jul 1. doi: 10.1007/s10439-026-04267-7. Online ahead of print.

ABSTRACT

Post-stroke dysphagia (PSD) affects approximately 42% of acute stroke patients, increasing hospitalization costs and length of stay. Early identification improves outcomes, yet many patients-especially in low-resource settings-lack access to gold-standard evaluations. This scoping review explores the integration of artificial intelligence (AI) and data science-defined as the interdisciplinary use of computational methods, statistical modeling, and machine learning to extract clinically meaningful patterns from biomedical data-in PSD screening and assessment. We synthesize evidence from bedside screening instruments, acoustic voice analyses, and emerging AI-driven models for dysphagia and aspiration risk stratification, critically appraising limitations related to small datasets, overfitting risk, and the need for external validation. Traditional tools like the water swallow test show high sensitivity but varying specificity; recent studies support augmenting these with voice-based biomarkers such as post-swallow wet voice, jitter, and shimmer. While wet voice as a standalone marker has limited sensitivity (8-29%), its high specificity (75-94%) within multimodal approaches justifies continued investigation. AI models trained on acoustic parameters have demonstrated strong performance in detecting penetration-aspiration events, while mobile and voice-based platforms may expand diagnostic reach, pending further validation. We also review optimal screening timing, emphasizing assessment within 24 h of stroke onset with repeated evaluations for high-risk patients. Future directions advocate multimodal, patient-centered approaches combining wearable biosensors, cloud-based analytics, and culturally adapted algorithms, while addressing implementation challenges including infrastructure requirements, digital literacy, workflow integration, and ethical considerations. The convergence of clinical expertise and computational technologies presents a promising path to equitable, scalable, and precise dysphagia care.

PMID:42384315 | DOI:10.1007/s10439-026-04267-7

Int Microbiol. 2026 Jul 1. doi: 10.1007/s10123-026-00857-6. Online ahead of print.

ABSTRACT

BACKGROUND: Free-living amoebae (FLA), such as Acanthamoeba, are protozoan parasites that take advantage of opportunities with a widespread distribution in various environmental sources, such as a wide range of water sources. The amoeba can accidentally infect individuals and cause a variety of diseases, including amoebic encephalitis and keratitis, in both immunocompetent and immune-deficient individuals. The amoeba can act as reservoirs and carriers for pathogenic microorganisms, increasing the risk of pathogenicity in humans. The objective of this research was to identify the genotypes, besides in addition to the species of the FLA, in water sources in Qazvin province using high-resolution melting analysis (HRM).

METHODS: A total of 44 DNA isolates from FLA, including samples from swimming pools irrigation canals, and drinking water, were analyzed for the 18SrDNA gene using HRM. The data was evaluated using Chi-square test and Fisher’s exact tests.

RESULTS: The Molecular analysis revealed that 79.5% of the isolates were of the T3 genotype, 6.9% were of the T4 genotype of Acanthamoeba, and 13.6% were identified as Protoacantamoeba bohemica species. The statistical analysis exhibited a significant difference among the contamination and water source.

CONCLUSION: As water sources directly related to the public health, this study recommends paying close attention to treating water sources and utilizing new and accurate molecular methods to identify the potential pathogenic amoeba.

PMID:42384305 | DOI:10.1007/s10123-026-00857-6

Arch Osteoporos. 2026 Jul 1;21(1):98. doi: 10.1007/s11657-026-01730-9.

ABSTRACT

We examined the association of COVID time periods and equity-related variables with pharmacotherapy in a large jurisdiction fracture liaison service (FLS). We did not observe a significant association between COVID time periods and medication prescription after adjusting for all covariates. This highlights another potential success of the FLS model.

PURPOSE: Our objective was to examine the impact of COVID on bone-active medication prescription in a fracture liaison service (FLS), after adjusting for fracture risk status and equity-related variables.

METHODS: We conducted a logistic regression analysis with medication prescription (prescription by a bone health specialist or primary care provider) as the outcome. The model included covariates COVID time periods (T1: “pre-COVID” (n = 2796); T2: “during COVID” (n = 1575); T3: “COVID recovery” (n = 2208)), fracture risk status (high risk/not high risk) and equity-related variables (sex, age, marital status, living arrangement, education status, geographic location, and presence of comorbidities). Goodness of fit was assessed with the area under the receiver operating characteristic curve (AUC) and the Hosmer and Lemeshow test.

RESULTS: Fracture risk status was the primary driver of treatment with high-risk patients 7.8 times more likely to receive a medication prescription compared to patients who were not high risk, after adjusting for all covariates (OR = 7.80 [95% CI 6.91, 8.79]). COVID time period was not statistically significant. Female patients, those married or in a common-law relationship, living alone, or residing in urban areas were more likely to be prescribed medication. The model had good prediction power and fit the data well (AUC: 0.77; Hosmer-Lemeshow test p-value: 0.83).

CONCLUSION: Among patients reached by the FLS, COVID time period was not significantly associated with medication prescription, although program reach decreased at T2 and T3. Fracture risk status, sex, marital status, living arrangement, and geographic location were significantly associated with medication prescription.

PMID:42384300 | DOI:10.1007/s11657-026-01730-9

Saudi Dent J. 2026 Jul 1;38(7):93. doi: 10.1007/s44445-026-00202-7.

ABSTRACT

Gingival recession is a highly prevalent mucogingival condition that can significantly compromise oral health and esthetics. Patients commonly suffer from dentinal hypersensitivity, root caries, poor esthetics, discomfort during brushing, and in severe cases tooth mobility or tooth loss, ultimately affecting their quality of life. To compare the effectiveness of Platelet Rich Fibrin (PRF) and Amnio-Chorion Membrane (ACM) with Coronally Advanced Flap (CAF) to manage the case of isolated gingival recession defects (GRD). The study is a split-mouth randomised trial that included 13 patients (n = 26) with bilateral Miller Class 1 or 2 maxilla anterior and premolar recession of the gingiva. The randomizing of locations was also done to 13 sites in each group of either Group I (CAF+ PRF, n = 13) or Group II (CAF +ACM, n = 13). At 6 months follow-up, plaque Index (PI), Gingival Index (GI), Probing pocket depth (PPD), gingival recession depth (GRD), Clinical attachment level (CAL), Keratinized gingiva width (WKG), Percentage of root coverage, and root coverage Esthetic score (RES) were measured. All data were analyzed in the SPSS v21.0 software; paired t-tests and unpaired t-tests were used for comparing the intragroup and intergroup respectively. The level of statistical significance was defined as p < 0.05. At 6 months, statistically significant improvements in PRF and CAM in all clinical parameters was seen. Root coverage of Group I was 78.84 ± 19.13 and Group II was 74.99 ± 15.59. Intergroup comparisons showed no statistically significance in clinical outcome, RES or root coverage percentage (p > 0.05). PRF and ACM had both positive outcomes on gingival thickness, WKG, and CAL. PRF or ACM resulted in significant improvement in clinical periodontal parameters, root coverage, and esthetic outcomes, with no statistically significant difference between the two groups.

PMID:42384299 | DOI:10.1007/s44445-026-00202-7

Food Sci Anim Resour. 2026 Jul 1;46(1):81. doi: 10.1007/s44463-026-00082-9.

ABSTRACT

This study aimed to optimize the conditions for obtaining an ethanol extract from Micromeria fruticosa (M. fruticosa) and to determine the antioxidant activity and phenolic compound content of the resulting extract. Subsequently, the use of the optimized extract in beef patties was evaluated, and the effects of the cooking process on the physicochemical properties of the product were examined. In this context, the highest efficiency was obtained in terms of total phenolic contents (TPC), as well as DPPH (2,2-diphenyl-1-picrylhydrazyl) and ferric reducing antioxidant power (FRAP) values, during the ethanol extraction of the plant. The optimum extraction conditions were determined to be 12 g of sample, 20 min, and 75% ultrasonic power. Under these conditions, the TPC of the extract was found to be 37.128 mg GAE/g dry weight, the DPPH value was 42.865, and the FRAP value was 254.776 mg TE/g dry weight. In the second phase of the study, the optimized extract was used at different concentrations (0%, 0.5%, 1.0%, and 1.5%) to produce beef patties, which were then analyzed for pH, moisture content, TBARS (thiobarbituric acid-reactive substances), and cooking yield. The use of the extract did not cause a statistically significant difference in the moisture content and TBARS values of the samples (p > 0.05). However, it was determined that the pH values of the samples containing 0% and 0.5% extract were lower than those containing 1.0% and 1.5% extract (p < 0.01). In addition, it was observed that the use of the extract had a positive effect on cooking yield, and that cooking yield increased with increasing extract concentration. As a result of the study, it was concluded that M. fruticosa holds promising potential as a natural additive in meat and meat products, offering a functional ingredient that can contribute to the development of value-added, health-oriented food products.

PMID:42384298 | DOI:10.1007/s44463-026-00082-9

Cancer Causes Control. 2026 Jul 1;37(7):117. doi: 10.1007/s10552-026-02209-1.

ABSTRACT

PURPOSE: Racial and ethnic differences in oral cavity cancer (OCC) stage at diagnosis are substantial, but the reasons remain unclear. We assessed insurance status and social neighborhood factors as potential pathways.

METHODS: Using the Texas Cancer Registry, we identified adults diagnosed with OCC between 2010 and 2020. We examined the crude and multivariable associations of race and ethnicity, insurance status, and social neighborhood factors with stage at diagnosis. We investigated the mediating effects of insurance status and neighborhood-level social factors on racial and ethnic differences in stage at diagnosis using four-way decomposition with modified Poisson regression and robust standard errors.

RESULTS: Among the 6,488 patients, 49.6% were diagnosed at a late stage. Compared to non-Hispanic White patients, non-Hispanic Black, Hispanic, and non-Hispanic Asian Americans, Native Hawaiians, and Pacific Islanders had 51% (Prevalence Ratio [PR]: 1.51; 95% confidence interval [95% CI]: 1.40, 1.63), 29% (PR: 1.29; 95% CI 1.22-1.37), and 17% (PR: 1.17; 95% CI 1.05-1.32) higher risks of being diagnosed at a late stage, respectively. For non-Hispanic Black patients, being uninsured, living in a vulnerable neighborhood, and living in a deprived neighborhood explained roughly 20%, 31%, and 15% of the disparity in late stage diagnosis, respectively. These pathways accounted for similar proportions of the disparity in stage at diagnosis among Hispanic patients.

CONCLUSIONS: Insurance status and neighborhood-level social factors may partially account for the differences in OCC stage at diagnosis between racial and ethnic groups. Identifying these pathways may help clarify and reduce these disparities.

PMID:42384290 | DOI:10.1007/s10552-026-02209-1

Indian J Pediatr. 2026 Jul 1. doi: 10.1007/s12098-026-06239-0. Online ahead of print.

ABSTRACT

OBJECTIVES: To present an overview of the practice of prenatal diagnosis and genomics in India.

METHODS: This manuscript was compiled through review of published literature, survey of peers and professional experience of authors.

RESULTS: The field of prenatal diagnosis in India had its beginnings in the 1980s with advent of ultrasound machines and invasive procedures. The high prevalence of birth defects and genetic diseases in the population had been recognized by pediatricians and clinical geneticists as early as the 1950-60s. Various factors, like epidemiological transition with increasing contribution of genetic diseases and birth defects towards adverse health statistics, enhanced awareness of health care providers and policy makers, availability of trained manpower and rapid advancements in the field of genomics have all led to expansion of the field of prenatal diagnosis and genomics in the country since these early times. Medical termination of pregnancy has been legally allowed since 1971 and culturally acceptable to the majority. In the last four decades, advances in prenatal diagnosis have given women the option to make decisions about termination of pregnancy by earlier detection of fetal structural and genetic abnormalities.

CONCLUSIONS: This study reviews the historical journey of the field in India and the current status. It also discusses the challenges faced by the country and the measures being undertaken to address the same.

PMID:42384265 | DOI:10.1007/s12098-026-06239-0

Eur J Orthop Surg Traumatol. 2026 Jul 1;36(1):267. doi: 10.1007/s00590-026-04832-9.

ABSTRACT

PURPOSE: To evaluate surgical outcomes in cervical spondylotic myelopathy (CSM) with intramedullary signal changes (IMSCs) and assess the impact of preoperative severity on recovery.

METHODS: This retrospective study included 312 patients undergoing cervical decompression. Neurological status was assessed using the mJOA score preoperatively and at 6-12 months. A subset of 43 patients was analyzed separately for inferential statistics using chi-square testing.

RESULTS: Severe CSM was present in 54.2% and moderate in 45.8%. Overall improvement occurred in 53.2%, with a mean mJOA increase of 2.9 points. In the subset, mean mJOA improved from 10.25 (SD 1.80) to 13.16 (SD 2.43). A significant association was found between preoperative severity and outcome (p < 0.05).

CONCLUSION: Surgical decompression leads to meaningful neurological improvement, with outcomes influenced by preoperative severity.

PMID:42384242 | DOI:10.1007/s00590-026-04832-9