Search Results (34)

Background/Objectives: Hypertension is a growing public health concern in Saudi Arabia, driven by rapid socioeconomic changes. This study investigated the interplay between habitual, behavioral, and dietary risk factors associated with hypertension among Saudi adults. Methods: A cross-sectional survey was conducted among 3312 Saudi adults using multistage stratified random sampling. The data were collected via validated questionnaires assessing sociodemographic, anthropometric indicators, lifestyle behaviors, dietary patterns, and medical history. Hypertension status was determined through self-reported diagnosis. Bivariate analyses and multiple logistic regression identified independent predictors (p < 0.05). Results: Hypertension prevalence was 13% (mean age: 34 ± 15 years; 50% male). The strongest predictors were age (OR = 1.08/year; 95% CI: 1.07–1.10; p < 0.001), increased body mass index (OR = 1.03; 95% CI: 1.01–1.06; p = 0.011), smoking (OR = 1.55; 95% CI: 1.04–2.29; p = 0.030), and family history of hypertension (OR = 7.71; 95% CI: 5.61–10.75; p < 0.001). Participants with diabetes mellitus had 89% higher odds of hypertension (OR = 1.89; 95% CI: 1.42–2.51; p < 0.001), and those with dyslipidemia had more than double the odds (OR = 2.45; 95% CI: 1.38–4.22; p = 0.002). Protective factors included higher income (≥15,000 SAR; OR = 0.54; 95% CI: 0.36–0.81; p = 0.003) and regular whole grain consumption (OR = 0.60; 95% CI: 0.46–0.77; p < 0.001). Conclusions: Hypertension risk in Saudi adults is shaped by age, obesity, smoking, comorbid metabolic conditions (diabetes and dyslipidemia), and genetic pre-disposition. In contrast, higher income and whole grain intake may offer protection. These findings underscore the need for comprehensive prevention strategies that address both lifestyle and cardiometabolic comorbidities, in alignment with Saudi Vision 2030 health priorities. Full article

Many dogs suffer from pruritus, which is commonly caused by atopic dermatitis and associated with skin inflammation. The immune system and inflammatory response, and in particular the gut–skin axis, are central to the pathogenesis of atopic dermatitis. Managing atopic dermatitis involves complex, iterative treatment plans; early strategies supporting gut–skin health are needed to prevent elevated itching from progressing toward a disease condition requiring drug therapy. This double-blind, placebo-controlled, randomized trial evaluated the ability of a novel, indole-rich canine immune health postbiotic (CIHP) to reduce itching and promote a healthy gut microbiome in dogs with subclinical, but elevated itching behavior. Thirty dogs were stratified into two groups based on baseline scratching frequency, receiving either CIHP or placebo as a powder topper for 28 days. Canine itching was evaluated through accelerometer-based tracking and the Pruritus Visual Analog Scale (PVAS) score on Days 0, 7, 14, 21, and 28. Skin and coat health was assessed on Days 0, 14, and 28, and the gut microbiome was sequenced from fecal samples on Days 0 and 28. CIHP reduced scratching by 20% relative to the baseline (p = 0.032) and PVAS score by 27% compared to the placebo (p = 0.02). CIHP improved skin and coat quality compared to the placebo at Day 14 (p = 0.01) and increased Shannon diversity by 4.6% (p = 0.043), shifting gut microbiome composition. These findings validate this postbiotic’s ability to reduce itching in dogs with subclinical, but elevated itching behavior, provide evidence of promoting a healthy gut–skin axis, and suggest potential as an early intervention in the context of pruritic conditions, as well as for broader immune-related benefits. Full article

Chronic coronary syndrome (CCS) and atrial fibrillation (AF) are prevalent cardiovascular conditions between whom there is a dual relationship, with significant morbidity and mortality. Recent studies have highlighted the roles of galectin-3 and pentraxin-3 as potential biomarkers in coronary atherosclerosis, yet their specific interactions and implications in patients with CCS and AF remain underexplored. This proof-of-concept study aimed to evaluate the levels of galectin-3 and pentraxin-3 in a cohort of patients with CCS and AF. A total of 131 patients diagnosed with CCS or/and AF were stratified based on coronary stenosis severity (significant, S-CCS and nonsignificant, N-CCS coronary lesions) and arrhythmia burden. Blood samples were collected to measure serum levels of galectin-3 and pentraxin-3 using enzyme-linked immunosorbent assay (ELISA) techniques. Clinical data, including demographic information, comorbidities, medication use, and biological markers of systemic inflammation, were recorded. The galectin-3 value was more than double in patients with S-CCS compared with those with N-CCS (17.39 ± 4.459 ng/mL versus 7.49 ± 2.732 ng/mL, p < 0.001). Atrial fibrillation was not associated with statistically significant variations in galectin-3 values, neither overall nor separately in the group of S-CCS or N-CCS. However, pentraxin-3 values were similar in S-CCS compared with those with N-CCS (2839.18 ± 1521.639 pg/mL versus 2564.07 ± 1299.055 pg/mL, p = 0.417). These values were lower in patients with sinus rhythm, with a mean of 2469.91 ± 1253.782 pg/mL, and steadily increased in those with paroxysmal, persistent, and permanent AF, for whom they reached a mean of 3162.87 ± 1893.068 pg/mL. Elevated levels of galectin-3 appear to correlate with coronary stenosis severity and may inform future strategies for risk stratification, patients’ selection for invasive coronarography or therapeutic targeting in CCS. Full article

Background: Hereditary colorectal cancer syndromes, including familial adenomatous polyposis (FAP), Lynch syndrome (LS), and Peutz–Jeghers syndrome (PJS), are associated with an increased risk of small bowel cancer (SBC). Due to the low incidence and non-specific presentation of SBC, effective surveillance strategies are essential for early detection and management. This review aims to evaluate and compare current endoscopic techniques for small bowel surveillance in these patients. Methods: A comprehensive review was conducted using peer-reviewed studies sourced from PubMed. Various endoscopic modalities, including capsule endoscopy (CE), device-assisted enteroscopy (DAE), and intraoperative enteroscopy (IOE), were assessed for their diagnostic yield, safety, and clinical utility. Surveillance recommendations of the different syndromes were also examined. Results: CE offers high sensitivity but lacks histological sampling capability. DAE, including double-balloon enteroscopy (DBE) and single-balloon enteroscopy (SBE), enables direct visualization, biopsy, and therapeutic interventions, albeit with greater procedural complexity. In FAP, duodenal surveillance follows the Spigelman classification to stratify cancer risk, while jejunal and ileal polyps remain less studied. LS patients have an increased SBC risk, warranting tailored endoscopic approaches. In PJS, surveillance aims to mitigate intussusception risks and allow early malignancy detection. Conclusions: Optimized surveillance strategies in hereditary colorectal cancer syndromes require a multimodal approach, integrating advanced endoscopic techniques with genetic risk stratification. Centralized care in tertiary centers improves outcomes by ensuring standardized surveillance protocols and enhancing early cancer detection. Artificial intelligence (AI) applied to CE and DAE is shaping promising prospects for the future surveillance of small bowel polyps by enhancing diagnostic accuracy and reducing the duration of the diagnostic process. Further research should investigate AI-assisted imaging and molecular biomarkers to optimize screening strategies. Full article

Sampling survey data can sometimes contain outlier observations. When the mean estimator becomes skewed due to the presence of extreme values in the sample, results can be biased. The tendency to remove outliers from sample data is common. However, performing such removal can reduce the accuracy of conventional estimating techniques, particularly with regard to the mean square error (MSE). In order to increase population mean estimation accuracy while taking extreme values into consideration, this study presents an enhanced class of estimators. The method uses extreme values from an auxiliary variable as a source of information rather than eliminating these outliers. Using a first-order approximation, the properties of the suggested class of estimators are investigated within the context of a stratified two-phase sampling framework. A simulation research is conducted to examine the practical performance of these estimators in order to validate the theoretical conclusions. To further demonstrate the superiority of the suggested class of estimators for dealing with extreme values, an analysis of three different datasets demonstrates that they consistently provide higher percent relative efficiency (PRE) when compared to existing estimators. Full article

When direct survey are about sensitive characteristics such as addiction to drugs, alcoholism, proneness to tax invasion and sexual violence, nonresponse bias and response bias become serious problems because people oftentimes do not wish to give true information. In this study, when the population is composed of strata such as gender, region, age group, we consider the simple model and crossed model by applying stratified random sampling which can estimate not only the domain population proportion but also the whole population proportion for two sensitive attributes such as drug use and sexual violence in the same time. In addition, when the size of each population stratum is unknown in stratified random sampling, we propose the simple model and crossed model by using stratified double sampling method. In each proposed survey design, the sample allocation of each stratum is dealt with in consideration of proportional allocation and optimal one. We compare the efficiency between the simple model and the crossed model according to the proposed stratified random sampling design. Full article

Background/Objectives: The incidence of colorectal cancer (CRC) is rising, and Western diets high in red and processed meats may be contributing. It is important to identify dietary nutrients that increase CRC risk and perhaps interventions that may modulate such risk. The relationship between dietary choline intake and CRC is still unclear. We hypothesize that high dietary choline intake is associated with greater CRC risk, and B vitamin supplementation may modify this risk. Methods: In this case-control study, we collected demographic and dietary data using the validated National Cancer Institute CRC Risk Assessment Tool and Dietary Health Questionnaire III and analyzed colonoscopy outcomes. Logistic regression and stratified analyses were performed to calculate adjusted odds ratios and evaluate for effect modification. Results: Of 52 total patients, 21 had a normal colonoscopy result, and 31 were found to either have benign polyps or CRC. The average dietary choline intake was 207 mg/day in the normal group and 297 mg/day in the abnormal outcome group. A doubling in dietary choline intake was significantly associated with increased odds of polyps or CRC (OR 25.32, 95% CI 1.95–327.94). When stratified by vitamin B levels, the effect modification was difficult to confidently quantify due to the limited sample size. Conclusions: Our findings suggest that higher dietary choline intake may be associated with an increased risk of CRC and its precursors, such as polyps. Although the potential modifying role of B vitamins was inconclusive, this study underscores the need for larger-scale research to further explore these associations and to assess the potential of dietary interventions in reducing CRC risk. Full article

Blockchain technology has impacted various sectors and is transforming them through its decentralized, immutable, transparent, smart contracts (automatically executing digital agreements) and traceable attributes. Due to the adoption of blockchain technology in versatile applications, millions of transactions take place globally. These transactions are no exception to adversarial attacks which include data tampering, double spending, data corruption, Sybil attacks, eclipse attacks, DDoS attacks, P2P network partitioning, delay attacks, selfish mining, bribery, fake transactions, fake wallets or phishing, false advertising, malicious smart contracts, and initial coin offering scams. These adversarial attacks result in operational, financial, and reputational losses. Although numerous studies have proposed different blockchain anomaly detection mechanisms, challenges persist. These include detecting anomalies in just a single layer instead of multiple layers, targeting a single anomaly instead of multiple, not encountering adversarial machine learning attacks (for example, poisoning, evasion, and model extraction attacks), and inadequate handling of complex transactional data. The proposed AHEAD model solves the above problems by providing the following: (i) data aggregation transformation to detect transactional and user anomalies at the data and network layers of the blockchain, respectively, (ii) a Three-Layer Hierarchical Ensemble Learning Model (HELM) incorporating stratified random sampling to add resilience against adversarial attacks, and (iii) an advanced preprocessing technique with hybrid feature selection to handle complex transactional data. The performance analysis of the proposed AHEAD model shows that it achieves higher anti-adversarial resistance and detects multiple anomalies at the data and network layers. A comparison of the proposed AHEAD model with other state-of-the-art models shows that it achieves 98.85% accuracy against anomaly detection on data and network layers targeting transaction and user anomalies, along with 95.97% accuracy against adversarial machine learning attacks, which surpassed other models. Full article

Persistent human papillomavirus (HPV) infection is recognized as a major risk factor for cervical cancer. Women with persistent HPV and negative cytology are at greater risk of CIN2+ than women with negative infection. The diagnosis becomes more complicated when the woman has a type 3 transformation zone at colposcopy. The aim of this study was to determine the prevalence of CIN2+ in women with persistent HPV, negative cytology and TZ3; how to stratify the risk of CIN2+; and what the best diagnostic strategy is, given TZ3. Methods: In a multicenter retrospective cohort study, we enrolled women with negative cytology and TZ3 among the 213 women referred for colposcopy for persistent HPV. The average age of the women was 53 years; in particular, 83% were postmenopausal women. In the presence of a TZ3, the entire transformation zone cannot be explored, making colposcopy and targeted biopsy useless and inadequate, with great risks of underdiagnosis or missed diagnosis. Women with TZ3 underwent diagnostic LEEP to ensure correct diagnoses. Results: The study highlighted 19% (16/84) of CIN2+ lesions, a higher frequency of non-HPV 16/18 genotypes (76.2%), and 50% of CIN2+ lesions being due to non-HPV 16/18 genotypes. Furthermore, more than half of the women (80.9%) had normal histopathological results in the LEEP sample. Conclusion. Women with viral persistence, negative cytology, and TZ3 have a 19% risk of CIN2+; genotyping helps stratify risk, but extensive genotyping is necessary instead of partial genotyping (16/18), referring to a population of women over 50 years old in which the prevalence of genotypes 16,18 decreases and the prevalence of other genotypes increases; diagnostic LEEP is excessive (only 16 cases of CIN2+ out of 48 cases treated), even though 83% of women had viral clearance after LEEP; p16/Ki67 double staining could be a potential risk marker, which would only highlight women at risk of CIN2+ to undergo LEEP. To individualize the diagnostic workup and treatment and minimize the risk of under diagnosis and overtreatment, future studies should explore the use of extended genotyping and new biomarkers for individual risk stratification. Full article

The use of machine learning algorithms in healthcare can amplify social injustices and health inequities. While the exacerbation of biases can occur and be compounded during problem selection, data collection, and outcome definition, this research pertains to the generalizability impediments that occur during the development and post-deployment of machine learning classification algorithms. Using the Framingham coronary heart disease data as a case study, we show how to effectively select a probability cutoff to convert a regression model for a dichotomous variable into a classifier. We then compare the sampling distribution of the predictive performance of eight machine learning classification algorithms under four stratified training/testing scenarios to test their generalizability and their potential to perpetuate biases. We show that both extreme gradient boosting and support vector machine are flawed when trained on an unbalanced dataset. We then show that the double discriminant scoring of type 1 and 2 is the most generalizable with respect to the true positive and negative rates, respectively, as it consistently outperforms the other classification algorithms, regardless of the training/testing scenario. Finally, we introduce a methodology to extract an optimal variable hierarchy for a classification algorithm and illustrate it on the overall, male and female Framingham coronary heart disease data. Full article

Synbiotics modulate the gut microbiome and contribute to the prevention of liver diseases such as metabolic-dysfunction-associated fatty liver disease (MAFLD). This study aimed to evaluate the effect of a randomized, placebo-controlled, double-blinded seven-week intervention trial on the liver metabolism in 117 metabolically healthy male participants. Anthropometric data, blood parameters, and stool samples were analyzed using linear mixed models. After seven weeks of intervention, there was a significant reduction in alanine aminotransferase (ALT) in the synbiotic group compared to the placebo group (−14.92%, CI: −26.60–−3.23%, p = 0.013). A stratified analysis according to body fat percentage revealed a significant decrease in ALT (−20.70%, CI: −40.88–−0.53%, p = 0.045) in participants with an elevated body fat percentage. Further, a significant change in microbiome composition (1.16, CI: 0.06–2.25, p = 0.039) in this group was found, while the microbial composition remained stable upon intervention in the group with physiological body fat. The 7-week synbiotic intervention reduced ALT levels, especially in participants with an elevated body fat percentage, possibly due to modulation of the gut microbiome. Synbiotic intake may be helpful in delaying the progression of MAFLD and could be used in addition to the recommended lifestyle modification therapy. Full article

The evaluation of surface quality after milling still represents a challenge due to the stratified structure of wood. In this paper, the surface quality of beech wood obtained by profile milling was analyzed differentiating between tool marks, fuzzy grain, and accidental surface gaps overlapped onto the deep anatomical cavities. The samples were milled at two rotation speeds, 3308 rpm (n₁) and 6594 rpm (n₂), and two feed speeds of 6.53 m/min (v_f1) and 23.74 m/min (v_f2). After the samples were cut, approximately 600 m of beech wood were further processed before measuring the surface quality again. The surface waviness measured by Wa increased more than double when the feed speed increased from v_f1 to v_f2. Rk increased with the feed speed (with the feed per tooth, f_z, for a constant n, respectively) for n₂ by a significant 57%. An increase in the rotation speed from n₁ to n₂ has reduced Rk, but the effect was not significant. The processing quality, Rk, measured at different depths did not differ statistically, in spite of the local differences in the cutting speed. The moment of measuring the surface roughness, such as immediately after sharpening or after a working period, influenced the surface quality. After the tool processed 600 m of beech material, the surface quality improved by 30%. The statistical analysis showed that the most important factor affecting the surface quality was the feed speed (implicitly f_z, for constant n and number of cutters). Full article

Rational: Circulating tumor cells (CTCs) appear to be a promising tool for predicting the clinical outcome and monitoring the response to treatment in patients with solid tumors. The current study assessed the clinical relevance of monitoring CTCs in patients with metastatic castration resistant prostate cancer (mCRPC) treated with cabazitaxel. Patients and Methods: Patients with histologically confirmed mCRPC who were previously treated with a docetaxel-containing regimen and experienced disease progression were enrolled in this multicenter prospective study. CTC counts were enumerated using the CellSearch system at baseline (before cabazitaxel initiation), after one cabazitaxel cycle (post 1st cycle) and at disease progression (PD). Patients were stratified into predetermined CTC-positive and CTC-negative groups. The phenotypic characterization was performed using double immunofluorescence staining with anti-CKs and anti-Ki67, anti-M30 or anti-vimentin antibodies. Results: The median PFS and OS were 4.0 (range, 1.0–17.9) and 14.5 (range, 1.2–33.9) months, respectively. At baseline, 48 out of 57 (84.2%) patients had ≥1 CTCs/7.5 mL of peripheral blood (PB) and 37 (64.9%) had ≥5 CTCs/7.5 mL of PB. After one treatment cycle, 30 (75%) out of the 40 patients with available measurements had ≥1 detectable CTC/7.5 mL of PB and 24 (60%) ≥ 5CTCs/7.5 mL of PB; 12.5% of the patients with detectable CTCs at the baseline sample had no detectable CTCs after one treatment cycle. The detection of ≥5CTCs/7.5 mL of PB at baseline and post-cycle 1 was associated with shorter PFS and OS (p = 0.002), whereas a positive CTC status post-cycle 1 strongly correlated with poorer OS irrespective of the CTC cut-off used. Multivariate analysis revealed that the detection of non-apoptotic (CK⁺/M30⁻) CTCs at baseline is an independent predictor of shorter OS (p = 0.005). Conclusions: In patients with mCRPC treated with cabazitaxel, CTC counts both at baseline and after the first cycle retain their prognostic significance, implying that liquid biopsy monitoring might serve as a valuable tool for predicting treatment efficacy and survival outcomes. Full article

Calibration methods enhance estimates by modifying the initial design weights, for which supplementary information is exploited. This paper first proposes a generalized class of minimum-covariance-determinant (MCD)-based calibration estimators and then presents a novel class of MCD-based calibrated estimators under a stratified median-ranked-set-sampling (MRSS) design. Further, we also present a double MRSS version of generalized and novel classes of estimators. To assess and compare the performance of the generalized and novel classes of estimators, both real and artificial datasets are utilized. In the presented practical scenarios and real-world applications, we utilize information from a dataset comprising 800 individuals in Turkey from 2014. These data include body mass index (BMI) as the primary variable of interest and age values as auxiliary variables. The BMI results shows that the proposed estimators $({\overline{y}}_{P{M}_I}=581.1897,{\overline{y}}_{Pa{M}_I}=544.8397)$ have minimum and $({\overline{y}}_{P{M}_{II}}=669.1822,{\overline{y}}_{Pa{M}_{II}}=648.2363)$ have maximum PREs in the case of single and double MRSS for odd sample sizes. Similarly, $({\overline{y}}_{P{M}_I}=860.0099,{\overline{y}}_{Pa{M}_I}=844.7803)$ have minimum and $({\overline{y}}_{P{M}_{II}}=974.5859,{\overline{y}}_{Pa{M}_{II}}=953.7233)$ have maximum PREs in the case of single and double MRSS for even sample sizes. Additionally, we conduct a simulation study using a symmetric dataset. Full article

Few observational studies investigated the relationship between single food groups and disease activity in rheumatoid arthritis (RA). Within a recent Italian cross-sectional study (365 patients, median age: 58.46 years, 78.63% females), we focused on two food groups, olive oil and nuts, representing vegetable sources of fatty acids. Disease activity was measured with Disease Activity Score on 28 joints based on C-reactive protein (DAS28-CRP) and the Simplified Disease Activity Index (SDAI). Robust linear and logistic regression models included tertile-based consumption categories of each food group and several confounders. Stratified analyses were performed by disease severity or duration. Higher consumption of both food groups exerted a favorable effect on disease activity, significant only for olive oil (Beta: −0.33, p-value: 0.03) in the linear regression on the overall sample. This favorable effect was stronger in the more severe or long-standing forms of RA (p-value for heterogeneity <0.05, especially for disease severity). Significant ORs were as low as ~0.30 for both food groups, strata (i.e., more severe and long-standing RA), and disease activity measures. Mean DAS28-CRP significantly decreased by ~0.70 for olive oil and ~0.55 for nuts in the two strata; mean SDAI significantly decreased by 3.30 or more for olive oil in the two strata. Globally, the beta coefficients doubled, and the ORs halved (in absolute values) for both food groups, reaching significance in 12 of the 16 available models fitted to the more severe or long-standing RA strata. More compromised forms of RA may benefit from increasing consumption of olive oil, olives, and nuts. Full article