APOE ε4-associated downregulation of the IL-7/IL-7R pathway in effector memory T cells: Implications for Alzheimer's disease.

INTRODUCTION: The apolipoprotein E (APOE) ε4 allele exerts a significant influence on peripheral inflammation and neuroinflammation, yet the underlying mechanisms remain elusive. METHODS: The present study enrolled 54 patients diagnosed with late-onset Alzheimer's disease (AD; including 28 APOE ε4 carriers and 26 non-carriers). Plasma inflammatory cytokine concentration was assessed, alongside bulk RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) analysis of peripheral blood mononuclear cells (PBMCs). RESULTS: Plasma tumor necrosis factor α, interferon γ, and interleukin (IL)-33 levels increased in the APOE ε4 carriers but IL-7 expression notably decreased. A negative correlation was observed between plasma IL-7 level and the hippocampal atrophy degree. Additionally, the expression of IL-7R and CD28 also decreased in PBMCs of APOE ε4 carriers. ScRNA-seq data results indicated that the changes were mainly related to the CD4+ Tem (effector memory) and CD8+ Tem T cells. DISCUSSION: These findings shed light on the role of the downregulated IL-7/IL-7R pathway associated with the APOE ε4 allele in modulating neuroinflammation and hippocampal atrophy. HIGHLIGHTS: The apolipoprotein E (APOE) ε4 allele decreases plasma interleukin (IL)-7 and aggravates hippocampal atrophy in Alzheimer's disease. Plasma IL-7 level is negatively associated with the degree of hippocampal atrophy. The expression of IL-7R signaling decreased in peripheral blood mononuclear cells of APOE ε4 carriers Dysregulation of the IL-7/IL-7R signal pathways enriches T cells.

Recurrence in isolated distal DVT after anticoagulation: a systematic review and meta-analysis of axial and muscular venous thrombosis.

OBJECTIVE: To identify recurrent venous thromboembolism (VTE) after discontinuation of anticoagulation in patients with isolated distal deep vein thrombosis based on its anatomic localization (axial or muscular veins). METHODS: Data were sourced from PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov databases in the time period up to October 2023. The study followed PRISMA guidelines using a registered protocol (CRD42023443029). Studies reporting recurrent VTE in patients with axial or muscular DVT were included in the analysis. RESULTS: Five studies with a total of 1,403 participants were evaluated. The results showed a pooled odds ratio of 1.12 (95% confidence interval 0.77-1.63) between axial and muscular DVT. Heterogeneity was low (I2 = 0%, p = 0.91) and there was no significant difference in the rate of recurrent VTE between axial and muscular DVT in each subgroup. CONCLUSIONS: Muscular and axial DVT showed comparable recurrent VTE rates after anticoagulation. However, uncertainties regarding the possibility of recurrence affecting the popliteal vein or resulting in pulmonary embolism following muscular DVT anticoagulation persisted. Randomized trials in patients with isolated distal DVT are still needed to clarify its prognosis for different anatomical thrombus locations.

Using large language model (LLM) to identify high-burden informal caregivers in long-term care.

BACKGROUND: The rising global elderly population increases the demand for caregiving, yet traditional methods may not fully assess the challenges faced by vital informal caregivers. OBJECTIVE: To investigate the efficacy of Large Language Model (LLM) in detecting overburdened informal caregivers, benchmarking against rule-based and machine learning methods. METHODS: 1,791 eligible informal caregivers from Southern Taiwan and utilized their textual case summary reports for the LLM. We also employed structured questionnaire results for machine learning models. Furthermore, we leveraged the visualization of the LLM's attention mechanisms to enhance our understanding of the model's interpretative capabilities. RESULTS: The LLM achieved an Area Under the Receiver Operating Characteristic (AUROC) curve of 0.84 and an Area Under the Precision-Recall Curve (AUPRC) of 0.70, marking an 8% and 14% improvement over traditional methods. The visualization of the attention mechanism accurately reflected the evaluations of human experts, concentrating on descriptions of high-burden descriptions and the relationships between caregivers and recipients. CONCLUSION: This research demonstrates the notable capability of LLM to accurately identify high-burden caregivers in Long-term Care (LTC) settings. Compared to traditional approaches, LLM offers an opportunity for the future of LTC research and policymaking.

Vebreltinib for Advanced Non-Small Cell Lung Cancer Harboring c-Met Exon 14 Skipping Mutation: A Multicenter, Single-Arm, Phase II KUNPENG Study.

PURPOSE: The KUNPENG study aimed to evaluate the efficacy and safety of vebreltinib (also known as bozitinib, APL-101, PLB-1001, and CBT-101), a potent and highly selective inhibitor of c-mesenchymal-epithelial transition (MET), in patients with locally advanced or metastatic non-small cell lung cancer (NSCLC) harboring c-Met alterations. METHODS: This multicenter, multicohort, open-label, single-arm, phase II trial enrolled patients with c-Met dysregulated, locally advanced or metastatic NSCLC from January 2020 to August 2022 across 17 centers. Cohort 1 included patients with MET exon 14 skipping (METex14)-mutant NSCLC who had not previously received MET inhibitors. Participants were administered vebreltinib at a dosage of 200 mg twice a day in 28-day cycles. The primary end point was the objective response rate (ORR), and the key secondary end point was the duration of response (DoR), both evaluated by a blinded independent review committee according to the RECIST version 1.1. RESULTS: As of August 9, 2022, 52 patients had been enrolled in cohort 1, of whom 35 (67.3%) were treatment-naïve. The ORR reached 75% (95% CI, 61.1 to 86). Among treatment-naïve patients, the ORR was 77.1% (95% CI, 59.9 to 89.6), and in previously treated patients, it was 70.6% (95% CI, 44.0 to 89.7). The disease control rate was 96.2%, with a median DoR of 15.9 months, a median progression-free survival of 14.1 months, and a median overall survival of 20.7 months. The most common treatment-related adverse events were peripheral edema (82.7%), QT prolongation (30.8%), and elevated serum creatinine (28.8%). CONCLUSION: Vebreltinib has shown promising efficacy and a favorable safety profile in patients with METex14-mutant NSCLC.

Digital ischemic necrosis in a patient with systematic lupus erythematosus patient after severe acute respiratory syndrome coronavirus 2 infection: a case report.

BACKGROUND: Patients with coronavirus disease 2019 have a high incidence of thrombosis that decreases after recovery. When coronavirus disease 2019 is accompanied by diseases prone to thrombosis, risk of post-infection thrombotic events may increase. CASE PRESENTATION: We report a case of digital ischemic gangrene in a 24-year-old Chinese female with systemic lupus erythematosus after recovery from coronavirus disease 2019. The pathogenesis was related to clinical characteristics of systemic lupus erythematosus, hypercoagulability caused by coronavirus disease 2019, and second-hit due to viral infection. CONCLUSION: Patients with autoimmune diseases should remain alert to autoimmune system disorders induced by severe acute respiratory syndrome coronavirus 2 and other viruses. Treatment for these patients should be strictly standardized, and appropriate anticoagulation methods should be selected to prevent thrombosis.

Validation of a pulmonary embolism risk assessment model in gynecological inpatients : Clinical trial: A single-center, retrospective study.

OBJECTIVE: To compare the predictive efficacy of the PADUA and Caprini models for pulmonary embolism (PE) in gynecological inpatients, analyze the risk factors for PE, and validate whether both models can effectively predict mortality rates. METHODS: A total of 355 gynecological inpatients who underwent computed tomography pulmonary angiography (CTPA) were included in the retrospective analysis. The comparative assessment of the predictive capabilities for PE between the PADUA and Caprini was carried out using receiver operating characteristic (ROC) curves. Logistic regression analysis was used to identify risk factors associated with PE. Additionally, Kaplan-Meier survival analysis plots were generated to validate the predictive efficacy for mortality rates. RESULTS: Among 355 patients, the PADUA and Caprini demonstrated the area under the curve (AUC) values of 0.757 and 0.756, respectively. There was no statistically significant difference in the AUC between the two models (P = 0.9542). Multivariate logistic analysis revealed immobility (P < 0.001), history of venous thromboembolism (VTE) (P = 0.002), thrombophilia (P < 0.001), hormonal treatment (P = 0.022), and obesity (P = 0.019) as independent risk factors for PE. Kaplan-Meier survival analysis demonstrated the reliable predictive efficacy of both the Caprini (P = 0.00051) and PADUA (P = 0.00031) for mortality. ROC for the three- and six-month follow-ups suggested that the Caprini model exhibited superior predictive efficacy for mortality. CONCLUSIONS: The PADUA model can serve as a simple and effective tool for stratifying high-risk gynecological inpatients before undergoing CTPA. The Caprini model demonstrated superior predictive efficacy for mortality rates.

Understanding and alleviating informal caregiver burden through the development and validation of a caregiver strain index-based model in Taiwan.

BACKGROUND: Quantifying the informal caregiver burden is important for understanding the risk factors associated with caregiver overload and for evaluating the effectiveness of services provided in Long-term Care (LTC). OBJECTIVE: This study aimed to develop and validate a Caregiver Strain Index (CSI)-based score for quantifying the informal caregiver burden, while the original dataset did not fully cover evaluation items commonly included in international assessments. Subsequently, we utilized the CSI-based score to pinpoint key caregiver burden risk factors, examine the initial timing of LTC services adoption, and assess the impact of LTC services on reducing caregiver burden. METHODS: The study analyzed over 28,000 LTC cases in Southern Taiwan from August 2019 to December 2022. Through multiple regression analysis, we identified significant risk factors associated with caregiver burden and examined changes in this burden after utilizing various services. Survival analysis was employed to explore the relationship between adopting the first LTC services and varying levels of caregiver burden. RESULTS: We identified 126 significant risk factors for caregiver burden. The most critical factors included caregiving for other disabled family members or children under the age of three (ß = 0.74, p < 0.001), the employment status of the caregiver (ß = 0.30-0.53, p < 0.001), the frailty of the care recipient (ß = 0.28-0.31, p < 0.001), and the behavioral symptoms of dementia in care recipients (ß = 0.28-2.60, p < 0.05). Generally, caregivers facing higher burdens sought LTC services earlier, and providing home care services alleviated the caregiver's burden. CONCLUSION: This comprehensive study suggests policy refinements to recognize high-risk caregivers better early and provide timely support to improve the overall well-being of both informal caregivers and care recipients.

A ResNet mini architecture for brain age prediction.

The brain presents age-related structural and functional changes in the human life, with different extends between subjects and groups. Brain age prediction can be used to evaluate the development and aging of human brain, as well as providing valuable information for neurodevelopment and disease diagnosis. Many contributions have been made for this purpose, resorting to different machine learning methods. To solve this task and reduce memory resource consumption, we develop a mini architecture of only 10 layers by modifying the deep residual neural network (ResNet), named ResNet mini architecture. To support the ResNet mini architecture in brain age prediction, the brain age dataset (OpenNeuro #ds000228) that consists of 155 study participants (three classes) and the Alzheimer MRI preprocessed dataset that consists of 6400 images (four classes) are employed. We compared the performance of the ResNet mini architecture with other popular networks using the two considered datasets. Experimental results show that the proposed architecture exhibits generality and robustness with high accuracy and less parameter number.

Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores.

We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model's performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1 to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8 to 5.1% (SBP) and 4.7 to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs. In summary, non-linear ML models improves BP prediction in models incorporating diverse populations.

NLRP3 inflammasome-mediated premature immunosenescence drives diabetic vascular aging dependent on the induction of perivascular adipose tissue dysfunction.

AIMS: The vascular aging process accelerated by type 2 diabetes mellitus (T2DM) is responsible for the elevated risk of associated cardiovascular diseases (CVDs). Metabolic disorder-induced immune senescence has been implicated in multi-organ/tissue damage. Herein, we sought to determine the role of immunosenescence in diabetic vascular aging and to investigate the underlying mechanisms. METHODS AND RESULTS: Aging hallmarks of the immune system appear prior to the vasculature in streptozotocin (STZ)/high-fat diet (HFD)-induced T2DM mice or db/db mice. Transplantation of aged splenocytes or diabetic splenocytes into young mice triggered vascular senescence and injury compared to normal control splenocyte transfer. RNA-seq profile and validation in immune tissues revealed that the Toll-like receptor 4 (TLR4)- Nuclear factor-kappa B (NF-κB) -NLRP3 axis might be the mediator of diabetic premature immunosenescence. The absence of Nlrp3 attenuated immune senescence and vascular aging during T2DM. Importantly, senescent immune cells, particularly T cells, provoked perivascular adipose tissue (PVAT) dysfunction and alternations in its secretome, which in turn impair vascular biology. In addition, senescent immune cells may uniquely affect vasoconstriction via influencing PVAT. Lastly, rapamycin alleviated diabetic immune senescence and vascular aging, which may be partly due to NLRP3 signaling inhibition. CONCLUSION: These results indicated that NLRP3 inflammasome-mediated immunosenescence precedes and drives diabetic vascular aging. The contribution of senescent immune cells to vascular aging is a combined effect of their direct effects and induction of PVAT dysfunction, the latter of which can uniquely affect vasoconstriction. We further demonstrated that infiltration of senescent T cells in PVAT was increased and associated with PVAT secretome alterations. Our findings suggest that blocking the NLRP3 pathway may prevent early immunosenescence and thus mitigate diabetic vascular aging and damage, and targeting senescent T cells or PVAT might also be the potential therapeutic approach.

Pulse pressure is associated with decline in physical function in older adults.

OBJECTIVES: This study examined the associations between pulse pressure, hypertension, and the decline in physical function in a prospective framework. STUDY DESIGN: The Healthy Aging Longitudinal Study tracked a group of Taiwanese adults aged 55 or more over an average of 6.19 years to assess pulse pressure and decline in physical function, including in handgrip strength, gait speed, and 6-min walking distance, at baseline (2009-2013) and in the second phase of assessments (2013-2020). MAIN OUTCOME MEASURES: Pulse pressure was calculated as the difference between systolic and diastolic blood pressure values. Weakness, slowness, and low endurance were defined as decreases of ≥0.23 m/s (one standard deviation) in gait speed, ≥5.08 kg in handgrip strength, and ≥ 57.73 m in a 6-min walk, as determined from baseline to the second phase of assessment. Linear and logistic regressions were employed to evaluate the associations between pulse pressure, hypertension, and decline in physical function. RESULTS: Baseline pulse pressure was associated with future handgrip strength (beta = -0.017, p = 0.0362), gait speed (beta = -0.001, p < 0.0001), and 6-min walking distance (beta = -0.470, p < 0001). In multivariable models, only handgrip strength (beta = -0.016, p = 0.0135) and walking speed (beta = -0.001, p = 0.0042) remained significantly associated with future pulse pressure. Older adults with high systolic blood pressure (≥140 mmHg) and elevated pulse pressure (≥60 mmHg) exhibited a significantly increased risk of weakness (odds ratio: 1.30, 95 % confidence interval: 1.08-1.58), slowness (1.29, 1.04-1.59), and diminished endurance (1.25, 1.04-1.50) compared with the reference group, who exhibited systolic blood pressure of <140 mmHg and pulse pressure of <60 mmHg. CONCLUSIONS: Among older adults, pulse pressure is associated with a decline in physical function, especially in terms of strength and locomotion.

Electroreductive Remote Benzylic C(sp3)-H Arylation of Aliphatic Ethers Using Cyanoarenes for the Synthesis of α-(Hetero)aryl Ethers.

An iodoarene-driven electroreductive remote C(sp3)-H arylation of unsymmetrical 1-(o-iodoaryl)alkyl ethers with cyanoarenes for the site selective synthesis of α-(hetero)aryl ethers is developed. With the introduction of cyanoarenes as both aryl sources and electron transfer mediators, this method includes an iodoarene-driven strategy to enable the regiocontrollable formation of two new bonds, one C(sp2)-H bond, and one C(sp2)-C(sp3) bond, in a single reaction step through the sequence of halogen atom transfer (XAT), hydrogen atom transfer (HAT), radical-radical coupling, and decyanation.

Physical Grinding of Prefabricated Co3O4 and MCM-22 Zeolite for Fischer-Tropsch Synthesis: Impact of Pretreatment Procedure on the Dispersion and Catalytic Performance.

To improve the mess-specific activity of Co supported on zeolite catalysts in Fischer-Tropsch (FT) synthesis, the Co-MCM-22 catalyst was prepared by simply grinding the MCM-22 with nanosized Co3O4 prefabricated by the thermal decomposition of the Co(II)-glycine complex. It is found that this novel strategy is effective for improving the mess-specific activity of Co catalysts in FT synthesis compared to the impregnation method. Moreover, the ion exchange and calcination sequence of MCM-22 has a significant influence on the dispersion, particle size distribution, and reduction degree of Co. The Co-MCM-22 prepared by the physical grinding of prefabricated Co3O4 and H+-type MCM-22 without a further calcination process exhibits a moderate interaction between Co3O4 and MCM-22, which results in the higher reduction degree, higher dispersion, and higher mess-specific activity of Co. Thus, the newly developed method is more controllable and promising for the synthesis of metal-supported catalysts.

Inflammation-related molecular signatures involved in the anticancer activities of brigatinib as well as the prognosis of EML4-ALK lung adenocarcinoma patient.

Although ALK tyrosine kinase inhibitors (ALK-TKIs) have shown remarkable benefits in EML4-ALK positive NSCLC patients compared to conventional chemotherapy, the optimal sequence of ALK-TKIs treatment remains unclear due to the emergence of primary and acquired resistance and the lack of potential prognostic biomarkers. In this study, we systematically explored the validity of sequential ALK inhibitors (alectinib, lorlatinib, crizotinib, ceritinib and brigatinib) for a heavy-treated patient with EML4-ALK fusion via developing an in vitro and in vivo drug testing system based on patient-derived models. Based on the patient-derived models and clinical responses of the patient, we found that crizotinib might inhibit proliferation of EML4-ALK positive tumors resistant to alectinib and lorlatinib. In addition, NSCLC patients harboring the G1269A mutation, which was identified in alectinib, lorlatinib and crizotinib-resistant NSCLC, showed responsiveness to brigatinib and ceritinib. Transcriptomic analysis revealed that brigatinib suppressed the activation of multiple inflammatory signaling pathways, potentially contributing to its anti-tumor activity. Moreover, we constructed a prognostic model based on the expression of IL6, CXCL1, and CXCL5, providing novel perspectives for predicting prognosis in EML4-ALK positive NSCLC patients. In summary, our results delineate clinical responses of sequential ALK-TKIs treatments and provide insights into the mechanisms underlying the superior effects of brigatinib in patients harboring ALKG1269A mutation and resistant towards alectinib, lorlatinib and crizotinib. The molecular signatures model based on the combination of IL6, CXCL1 and CXCL5 has the potential to predict prognosis of EML4-ALK positive NSCLC patients.

[Genetic analysis of a case with Al Kaissi syndrome and a literature review].

OBJECTIVE: To explore the genetic etiology of a child with delayed growth and development and carry out a literature review. METHODS: A child suspected for Al Kaissi syndrome at the First Affiliated Hospital of Zhengzhou University on March 6, 2021 was selected as the study subject. Following extraction of genomic DNA, the child was subjected to copy number variation sequencing (CNV-seq) and whole exome sequencing (WES), and candidate variants were verified by PCR-agarose gel electrophoresis and quantitative real-time PCR (qPCR). Prenatal diagnosis was conducted on chorionic villi sample upon subsequent pregnancy. RESULTS: The child, a 6-year-and-4-month-old boy, has dysmorphic features including low-set protruding ears and triangular face, delayed language and intellectual development, and ventricular septal defect. CNV-seq result has found no obvious abnormality, whilst WES revealed homozygous deletion of exons 1 and 2 of the CDK10 gene, which was confirmed by PCR-agarose gel electrophoresis and qPCR. Both of his parents were heterozygous carriers. Prenatal diagnosis using chorionic villi samples suggested that the fetus also carried the heterozygous deletion. CONCLUSION: The clinical features of Al Kaissi syndrome in this child can probably be attributed to the homozygous deletion of exons 1 and 2 of the CDK10 gene.

Changes of neurofilament light chain in patients with alcohol dependence following withdrawal and the genetic effect from ALDH2 Polymorphism.

Neurofilament light chain (NFL), as a measure of neuroaxonal injury, has recently gained attention in alcohol dependence (AD). Aldehyde dehydrogenase 2 (ALDH2) is the major enzyme which metabolizes the alcohol breakdown product acetaldehyde. An ALDH2 single nucleotide polymorphism (rs671) is associated with less ALDH2 enzyme activity and increased neurotoxicity. We examined the blood NFL levels in 147 patients with AD and 114 healthy controls using enzyme-linked immunosorbent assay and genotyped rs671. We also followed NFL level, alcohol craving and psychological symptoms in patients with AD after 1 and 2 weeks of detoxification. We found the baseline NFL level was significantly higher in patients with AD than in controls (mean ± SD: 264.2 ± 261.8 vs. 72.1 ± 35.6 pg/mL, p < 0.001). The receiver operating characteristic curve revealed that NFL concentration could discriminate patients with AD from controls (area under the curve: 0.85; p < 0.001). The NFL levels were significantly reduced following 1 and 2 weeks of detoxification, with the extent of reduction correlated with the improvement of craving, depression, and anxiety (p < 0.001). Carriers with the rs671 GA genotype, which is associated with less ALDH2 activity, had higher NLF levels either at baseline or after detoxification compared with GG carriers. In conclusion, plasma NFL level was increased in patients with AD and reduced after early abstinence. Reduction in NFL level corroborated well with the improvement of clinical symptoms. The ALDH2 rs671 polymorphism may play a role in modulating the extent of neuroaxonal injury and its recovery.

A randomized controlled trial of standard vs customized graduated elastic compression stockings in patients with chronic venous disease.

OBJECTIVE: This study aimed to compare the efficacy of customized graduated elastic compression stockings (c-GECSs) based on lower leg parameter models with standard GECSs (s-GECSs) in patients with chronic venous disease (CVD). METHODS: In this randomized, single-blind, controlled trial, 79 patients with stage C2 or C3 CVD were assigned to one of two groups: c-GECSs or s-GECSs. The primary outcome was change to Venous Insufficiency Epidemiological and Economic Study Quality of Life (VEINES-QOL) scores at months 1, 3, and 6 as compared with baseline. Secondary outcomes included compliance with wearing ECSs, interface pressure at the smallest circumference of the ankle (point B) and the largest circumference of the calf (point C), and calf volume (CV). RESULTS: There were 13 pairs of s-GECS and 2 pairs of c-GECS that showed pressure values higher than the standard at either point B or C. The c-GECSs were significantly superior to s-GECSs in terms of score improvement at all three time points (month 1, 8.47 [95% confidence interval (CI), 7.47-9.45] vs 5.89 [95% CI, 5.00-6.78]; month 3, 9.60 [95% CI, 8.47-10.72] vs 6.72 [95% CI, 5.62-7.83]; month 6, 7.09 [95% CI, 5.93-8.24] vs 3.92 [95% CI, 2.67-5.18]; P < .0001). Besides, at month 1, the mean daily use time of the c-GECS and s-GECS groups was 10.7 and 9.5 hours, respectively (P < .05). Correlation analysis indicated a negative relationship between local high pressure and daily duration in the s-GECS group (rpb = -0.388; n = 38; P < .05). Variances in pressure were greater in the s-GECSs group. The c-GECSs showed advantage in maintaining pressure. Both c-GECSs and s-GECSs effectively reduced CV (mL), with no significant differences between groups (month 1, 90.0 [95% CI, 71.4-108.5] vs 85.0 [95% CI, 65.6-104.2]; month 3, 93.8 [95% CI, 69.7-117.8] vs 85.9 [95% CI, 65.5-106.2]; month 6, 70.8 [95% CI, 46.5-95.2]) vs 60.8 [95% CI, 44.1-77.5]). CONCLUSIONS: The c-GECSs based on individual leg parameter models significantly improved VEINES-QOL scores and provided stable and enduring pressure as compared with s-GECSs for patients with stage C2 or C3 CVD. Although both c-GECSs and s-GECSs effectively reduced CV, the superior fit and comfort of c-GECSs improved patient compliance. Hence, c-GECSs are a viable alternative for patients who have difficulty tolerating s-GECSs.

Evaluating polygenic risk scores for predicting cardiometabolic traits and disease risks in the Taiwan Biobank.

Type 2 diabetes (T2D) and hypertension are common comorbidities and, along with hyperlipidemia, serve as risk factors for cardiovascular diseases. This study aimed to evaluate the predictive value of polygenic risk scores (PRSs) on cardiometabolic traits related to T2D, hypertension, and hyperlipidemia and the incidence of these three diseases in Taiwan Biobank samples. Using publicly available, large-scale genome-wide association studies summary statistics, we constructed cross-ethnic PRSs for T2D, hypertension, body mass index, and nine quantitative traits typically used to define the three diseases. A composite PRS (cPRS) for each of the nine traits was constructed by aggregating the significant PRSs of its genetically correlated traits. The associations of each of the nine traits at baseline as well as the change of trait values during a 3- to 6-year follow-up period with its cPRS were evaluated. The predictive performances of cPRSs in predicting future incidences of T2D, hypertension, and hyperlipidemia were assessed. The cPRSs had significant associations with baseline and changes of trait values in 3-6 years and explained a higher proportion of variance for all traits than individual PRSs. Furthermore, models incorporating disease-related cPRSs, along with clinical features and relevant trait measurements achieved area under the curve values of 87.8%, 83.7%, and 75.9% for predicting future T2D, hypertension, and hyperlipidemia in 3-6 years, respectively.

Nomogram for predicting pulmonary embolism in gynecologic inpatients with isolated distal deep venous thrombosis.

OBJECTIVE: To investigate the incidence of isolated distal deep venous thrombosis (IDDVT) concurrent with pulmonary embolism (PE) in gynecologic inpatients, analyze the risk factors for IDDVT with PE, and establish a nomogram model for IDDVT patients with PE. METHODS: A total of 260 patients were diagnosed with IDDVT between December 2017 and November 2020. The incidence of PE in these patients was determined using computed tomography pulmonary angiography. Logistic regression analysis was used to identify the related risk factors. On this basis, nomogram risk prediction models were established. RESULTS: Among 260 patients with IDDVT, 106 (40.8%) had concurrent PE, of whom 74 (28.5%) experienced silent PE. Univariate logistic analysis demonstrated statistical significance for body mass index (BMI; P = 0.044), glucocorticoid therapy (P = 0.009), hypertension (P < 0.001), and diabetes (P < 0.001). Multivariate logistic analysis revealed that these were independent risk factors for IDDVT with PE that retained statistical significance. A nomogram based on these factors was constructed to predict PE in patients with IDDVT. Its receiver operating characteristic (ROC) showed an area under the curve of 0.710 (95% confidence interval 0.642-0.779), with prediction sensitivity of 64.2% and prediction specificity of 76.6%. CONCLUSIONS: In the present study, a high prevalence of PE was found in gynecologic inpatients with IDDVT. Glucocorticoid therapy, hypertension, diabetes, and BMI were independent risk factors for IDDVT patients with PE. Taking these risk factors into account, a nomogram risk prediction model was developed to help facilitate early detection of concurrent PE.

Classifying Alzheimer's disease and normal subjects using machine learning techniques and genetic-environmental features.

BACKGROUND: Alzheimer's disease (AD) is complicated by multiple environmental and polygenetic factors. The accuracy of artificial neural networks (ANNs) incorporating the common factors for identifying AD has not been evaluated. METHODS: A total of 184 probable AD patients and 3773 healthy individuals aged 65 and over were enrolled. AD-related genes (51 SNPs) and 8 environmental factors were selected as features for multilayer ANN modeling. Random Forest (RF) and Support Vector Machine with RBF kernel (SVM) were also employed for comparison. Model results were verified using traditional statistics. RESULTS: The ANN achieved high accuracy (0.98), sensitivity (0.95), and specificity (0.96) in the intrinsic test for AD classification. Excluding age and genetic data still yielded favorable results (accuracy: 0.97, sensitivity: 0.94, specificity: 0.96). The assigned weights to ANN features highlighted the importance of mental evaluation, years of education, and specific genetic variations (CASS4 rs7274581, PICALM rs3851179, and TOMM40 rs2075650) for AD classification. Receiver operating characteristic analysis revealed AUC values of 0.99 (intrinsic test), 0.60 (TWB-GWA), and 0.72 (CG-WGS), with slightly lower AUC values (0.96, 0.80, 0.52) when excluding age in ANN. The performance of the ANN model in AD classification was comparable to RF, SVM (linear kernel), and SVM (RBF kernel). CONCLUSIONS: The ANN model demonstrated good sensitivity, specificity, and accuracy in AD classification. The top-weighted SNPs for AD prediction were CASS4 rs7274581, PICALM rs3851179, and TOMM40 rs2075650. The ANN model performed similarly to RF and SVM, indicating its capability to handle the complexity of AD as a disease entity.