Association of body roundness index with abdominal aortic calcification among middle aged and elderly population: findings from NHANES

AimWe aim to investigate the association between body roundness index (BRI) and abdominal aortic calcification (AAC) among middle aged and elderly US residents.MethodsThis cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) 2013–2014 cycle, including 3,079 middle-aged and elderly participants aged 40 and above. AAC scores for these participants were assessed using dual-energy x-ray absorptiometry (DXA). BRI was calculated from participants’ height and waist circumference, with all measurements conducted by trained surveyors using standardized methods. The relationship between BRI and AAC was analyzed using weighted multivariate logistic regression, adjusting for confounding variable. Additionally, restricted cubic splines (RCS) analysis was also employed.ResultsWe found that those with AAC were significantly older and had a higher prevalence of smoking and chronic kidney disease (CKD) prevalence compared to those without AAC. Using weighted multivariable logistic regression, we determined that an increase of one unit in BRI was associated with a 22% higher risk of AAC. Additionally, higher BRI quartiles (Q2, Q3, Q4) showed significantly increased risks of AAC compared to the lowest quartile. Visualization using RCS indicated a gradual increase in AAC risk with higher BRI, which plateaued beyond a BRI of 7.2. This relationship was significant across different age and gender group.ConclusionThere is a positive association between abdominal obesity (as measured by BRI) and AAC in the middle-aged and elderly population. This suggests the impact of abdominal obesity on vascular health and that this factor should be considered in public health strategies

Repeat expansion scanning of the NOTCH2NLC gene in patients with multiple system atrophy

© 2020 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals, Inc on behalf of American Neurological Association. Objective: Trinucleotide GGC repeat expansion in the 5’UTR of the NOTCH2NLC gene has been recognized as the pathogenesis of neuronal intranuclear inclusion disease (NIID). Previous studies have described that some NIID patients showed clinical and pathological similarities with multiple system atrophy (MSA). This study aimed to address the possibility that GGC repeat expansion in NOTCH2NLC might be associated with some cases diagnosed as MSA. Methods: A total of 189 patients with probable or possible MSA were recruited to screen for GGC repeat expansion in NOTCH2NLC by repeat-primed PCR (RP-PCR). In addition, long-read sequencing (LRS) was performed for all patients with RP-PCR-positive expansion, five patients with RP-PCR-negative expansion, and five controls on the Nanopore platform. Skin biopsies were performed on two patients with GGC expansion. Results: Five of 189 patients (2.6%) were found to have GGC expansion in NOTCH2NLC. LRS results identified that the five patients had GGC expansion between 101 and 266, but five patients with RP-PCR-negative expansion and five controls had GGC expansion between 8 and 29. Besides the typical symptoms and signs of MSA, patients with GGC expansion might have longer disease duration, severe urinary retention, and prominent cognitive impairment. In the skin samples from the patients with GGC expansion, typical p62-postive but alpha-synuclein-negative intranuclear inclusions were found in fibroblasts, adipocyte and ductal epithelial cells of sweat glands. Conclusion: Trinucleotide GGC repeat expansion in NOTCH2NLC could be observed in patients with clinically diagnosed MSA. Adult-onset NIID should be considered as a differential diagnosis of MSA

Gene Prioritization of Resistant Rice Gene against<i>Xanthomas oryzae pv. oryzae</i>by Using Text Mining Technologies

To effectively assess the possibility of the unknown rice protein resistant toXanthomonas oryzae pv. oryzae, a hybrid strategy is proposed to enhance gene prioritization by combining text mining technologies with a sequence-based approach. The text mining technique of term frequency inverse document frequency is used to measure the importance of distinguished terms which reflect biomedical activity in rice before candidate genes are screened and vital terms are produced. Afterwards, a built-in classifier under the chaos games representation algorithm is used to sieve the best possible candidate gene. Our experiment results show that the combination of these two methods achieves enhanced gene prioritization.</jats:p

Gene prioritization of resistant rice gene against Xanthomas oryzae pv. oryzae by using text mining technologies

To effectively assess the possibility of the unknown rice protein resistant to Xanthomonas oryzae pv. oryzae, a hybrid strategy is proposed to enhance gene prioritization by combining text mining technologies with a sequence-based approach. The text mining technique of term frequency inverse document frequency is used to measure the importance of distinguished terms which reflect biomedical activity in rice before candidate genes are screened and vital terms are produced. Afterwards, a built-in classifier under the chaos games representation algorithm is used to sieve the best possible candidate gene. Our experiment results show that the combination of these two methods achieves enhanced gene prioritization

Variants in MME are associated with autosomal-recessive distal hereditary motor neuropathy

© 2019 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals, Inc on behalf of American Neurological Association. Objective: To identify a new genetic cause in patients segregating distal hereditary motor neuropathy (dHMN) with an autosomal recessive pattern. Methods: Whole-exome sequencing was conducted in two siblings and was combined with segregation analysis. Additionally, 83 unrelated dHMN patients with unknown genetic cause were screened. RNA analysis was performed using blood lymphocytes and HEK293 cells transfected with mutant plasmids. Immunohistochemistry and Western blot analysis was applied to the nerve tissue. The enzymatic activities of mutant proteins were measured in the cultured cells to verify the pathogenicity of variants. Results: The clinical features of the patients showed late-onset phenotype of distal motor neuropathy without sensory involvement. We identified that compound heterozygous variants of c.1342C\u27T and c.2071_2072delGCinsTT in the membrane metalloendopeptidase (MME) gene co-segregated with the phenotype in a dHMN family. In an additional group of 83 patients with dHMN, compound heterozygous variants of c.1416+2T\u27C and c.2027C\u27T in MME were identified in one patient. The splice site variant c.1416+2T\u27C results in skipping of exon 13. The stop variant c.1342C\u27T induces mRNA degradation via nonsense-mediated mRNA decay. Transcript levels of MME in the lymphocytes showed no significant differences between the patients and controls. We also identified that MME variants were associated with mild decrease in protein expression in the sural nerve and significant impairments of enzymatic activity. Interpretation: Variants in the MME gene were associated with not only a Charcot-Marie-Tooth neuropathy phenotype but also with an autosomal-recessive dHMN phenotype. Loss of function may play a role in the pathogenesis of dHMN

Simvastatin nanoparticles attenuated intestinal ischemia/reperfusion injury by downregulating BMP4/COX-2 pathway in rats

The purpose of the research was to explore the therapeutic action of simvastatin-loaded poly(ethylene glycol)-b-poly(gamma-benzyl l-glutamate) (PEG-b-PBLG(50)) on intestinal ischemia/reperfusion injury (II/RI) through downregulating bone morphogenetic protein 4 (BMP4)/cyclooxygenase-2 (COX-2) pathway as compared to free simvastatin (Sim). Sprague Dawley rats were preconditioned with 20 mg/kg Sim or simvastatin/PEG-b-PBLG(50) (Sim/P) compounds, and then subjected to 45 min of ischemia and 1 h of reperfusion. The blood and small intestines were collected, serum levels of interleukin-4 (IL-4), interleukin-6 (IL-6), interleukin-10 (IL-10), tumor necrosis factor-α, and nitric oxide (NO) were checked, and the dry/wet intestine ratios, superoxide dismutase activity, myeloperoxidase content, reactive oxygen species, endothelial nitric oxide synthase, protein 47 kDa phagocyte oxidase (p47phox), BMP4, COX-2, and p38 mitogen-activated protein kinase (p38MAPK) expressions were measured in intestinal tissues. Both Sim and Sim/P pretreatment reduced intestinal oxidative damnification, restricted inflammatory harm, and downregulated the BMP4 and COX-2 expressions as compared to II/RI groups, while Sim/P remarkably improved this effect

Advancements in acne detection: application of the CenterNet network in smart dermatology

IntroductionAcne detection is critical in dermatology, focusing on quality control of acne imagery, precise segmentation, and grading. Traditional research has been limited, typically concentrating on singular aspects of acne detection.MethodsWe propose a multi-task acne detection method, employing a CenterNet-based training paradigm to develop an advanced detection system. This system collects acne images via smartphones and features multi-task capabilities for detecting image quality and identifying various acne types. It differentiates between noninflammatory acne, papules, pustules, nodules, and provides detailed delineation for cysts and post-acne scars.ResultsThe implementation of this multi-task learning-based framework in clinical diagnostics demonstrated an 83% accuracy in lesion categorization, surpassing ResNet18 models by 12%. Furthermore, it achieved a 76% precision in lesion stratification, outperforming dermatologists by 16%.DiscussionOur framework represents a advancement in acne detection, offering a comprehensive tool for classification, localization, counting, and precise segmentation. It not only enhances the accuracy of remote acne lesion identification by doctors but also clarifies grading logic and criteria, facilitating easier grading judgments

Machine learning-based risk prediction of acute kidney disease and hospital mortality in older patients

IntroductionAcute kidney injury (AKI) is a prevalent complication in older people, elevating the risks of acute kidney disease (AKD) and mortality. AKD reflects the adverse events developing after AKI. We aimed to develop and validate machine learning models for predicting the occurrence of AKD, AKI and mortality in older patients.MethodsWe retrospectively reviewed the medical records of older patients (aged 65 years and above). To explore the trajectory of kidney dysfunction, patients were categorized into four groups: no kidney disease, AKI recovery, AKD without AKI, or AKD with AKI. We developed eight machine learning models to predict AKD, AKI, and mortality. The best-performing model was identified based on the area under the receiver operating characteristic curve (AUC) and interpreted using the Shapley additive explanations (SHAP) method.ResultsA total of 22,005 patients were finally included in our study. Among them, 4,434 patients (20.15%) developed AKD, 4,000 (18.18%) occurred AKI, and 866 (3.94%) patients deceased. Light gradient boosting machine (LGBM) outperformed in predicting AKD, AKI, and mortality, and the final lite models with 15 features had AUC values of 0.760, 0.767, and 0.927, respectively. The SHAP method revealed that AKI stage, albumin, lactate dehydrogenase, aspirin and coronary heart disease were the top 5 predictors of AKD. An online prediction website for AKD and mortality was developed based on the final models.DiscussionThe LGBM models provide a valuable tool for early prediction of AKD, AKI, and mortality in older patients, facilitating timely interventions. This study highlights the potential of machine learning in improving older adult care, with the developed online tool offering practical utility for healthcare professionals. Further research should aim at external validation and integration of these models into clinical practice

TNF-α-1031T/C gene polymorphism as a predictor of malnutrition in patients with gastric cancer

IntroductionMalnutrition is a complex clinical syndrome, the exact mechanism of which is yet not fully understood. Studies have found that malnutrition is associated with anorexia and inadequate intake, tumor depletion, leptin, tumor-induced metabolic abnormalities in the body, and catabolic factors produced by the tumor in the circulation and cytokines produced by the host immune system. Among these, single nucleotide polymorphisms (SNPs) are present in the gene encoding the pro-inflammatory cytokine TNF-α.AimThe objective of this study was to investigate TNF-α -1,031 T/C gene polymorphism as an unfavorable predictor of malnutrition in patients with gastric cancer.MethodsThe study group consisted of 220 gastric cancer patients treated at Affiliated Jinhua Hospital, Zhejiang University School of Medicine. Malnutrition was mainly assessed by the Global Consensus on Malnutrition Diagnostic Criteria (GLIM). DNA was extracted from peripheral leukocytes of whole blood samples using an animal DNA extraction kit. DNA was amplified using a 1.1× T3 Super PCR mixture and genotyped using SNP1 software.ResultsThere are three major genetic polymorphisms in TNF-α. Among the 220 patients with gastric cancer, there were 7 patients with the CC genotype, 61 with the CT genotype and 152 with the TT genotype. Compared to patients with the TT genotype, patients with the C allele had an approximately 2.5-fold higher risk of developing malnutrition (p = 0.003; OR = 0.406). On the basis of multivariate analysis, patients with the CC genotype had an approximately 20.1-fold higher risk of developing malnutrition (p = 0.013; OR = 20.114), while those with the CT genotype had an almost 3.7-fold higher risk of malnutrition (p = 0.002; OR = 3.218).ConclusionSNP (−1,031 T/C) of the TNF-α may be a useful marker in the assessment of the risk of nutritional deficiencies in gastric cancer patients. Patients with gastric cancer carrying the C allele should be supported by early nutritional intervention, but more research is still needed to explore confirmation