Room­Temperature Antisymmetric Magnetoresistance in van der Waals Ferromagnet Fe3GaTe2 Nanosheets.

Van der Waals (vdW) ferromagnetic materials have emerged as a promising platform for the development of 2D spintronic devices. However, studies to date are restricted to vdW ferromagnetic materials with low Curie temperature (Tc) and small magnetic anisotropy. Here, a chemical vapor transport method is developed to synthesize a high-quality room-temperature ferromagnet, Fe3GaTe2 (c-Fe3GaTe2), which boasts a high Tc = 356 K and large perpendicular magnetic anisotropy. Due to the planar symmetry breaking, an unconventional room-temperature antisymmetric magnetoresistance (MR) is first observed in c-Fe3GaTe2 devices with step features, manifesting as three distinctive states of high, intermediate, and low resistance with the sweeping magnetic field. Moreover, the modulation of the antisymmetric MR is demonstrated by controlling the height of the surface steps. This work provides new routes to achieve magnetic random storage and logic devices by utilizing the room-temperature thickness-controlled antisymmetric MR and further design room-temperature 2D spintronic devices based on the vdW ferromagnet c-Fe3GaTe2.

Identification of the shared hub gene signatures and molecular mechanisms between HIV-1 and pulmonary arterial hypertension.

The close link between HIV-1 infection and the occurrence of pulmonary arterial hypertension (PAH). However, the underlying molecular mechanisms of their interrelation remain unclear. The microarray data of HIV-1 and PAH were downloaded from GEO database. We utilized WGCNA to identify shared genes between HIV-1 and PAH, followed by conducting GO and pathway enrichment analyses. Subsequently, differentially genes analysis was performed using external validation datasets to further filter hub genes. Immunoinfiltration analysis was performed using CIBERSORT. Finally, hub gene expression was validated using scRNA-seq data. We identified 109 shared genes through WGCNA, primarily enriched in type I interferon (IFN) pathways. By taking the intersection of WGCNA important module genes and DEGs, ISG15 and IFI27 were identified as pivotal hub genes. Immunoinfiltration analysis and scRNA-seq results indicated the significant role of monocytes in the shared molecular mechanisms of HIV-1 and PAH. In summary, our study illustrated the possible mechanism of PAH secondary to HIV-1 and showed that the heightened IFN response in HIV-1 might be a crucial susceptibility factor for PAH, with monocytes being pivotal cells involved in the type I IFN response pathway. This provides potential new insights for further investigating the molecular mechanisms connecting HIV-1 and PAH.

Human microbiota dysbiosis after SARS-CoV-2 infection have the potential to predict disease prognosis.

BACKGROUND: The studies on SARS-CoV-2 and human microbiota have yielded inconsistent results regarding microbiota α-diversity and key microbiota. To address these issues and explore the predictive ability of human microbiota for the prognosis of SARS-CoV-2 infection, we conducted a reanalysis of existing studies. METHODS: We reviewed the existing studies on SARS-CoV-2 and human microbiota in the Pubmed and Bioproject databases (from inception through October 29, 2021) and extracted the available raw 16S rRNA sequencing data of human microbiota. Firstly, we used meta-analysis and bioinformatics methods to reanalyze the raw data and evaluate the impact of SARS-CoV-2 on human microbial α-diversity. Secondly, machine learning (ML) was employed to assess the ability of microbiota to predict the prognosis of SARS-CoV-2 infection. Finally, we aimed to identify the key microbiota associated with SARS-CoV-2 infection. RESULTS: A total of 20 studies related to SARS-CoV-2 and human microbiota were included, involving gut (n = 9), respiratory (n = 11), oral (n = 3), and skin (n = 1) microbiota. Meta-analysis showed that in gut studies, when limiting factors were studies ruled out the effect of antibiotics, cross-sectional and case-control studies, Chinese studies, American studies, and Illumina MiSeq sequencing studies, SARS-CoV-2 infection was associated with down-regulation of microbiota α-diversity (P < 0.05). In respiratory studies, SARS-CoV-2 infection was associated with down-regulation of α-diversity when the limiting factor was V4 sequencing region (P < 0.05). Additionally, the α-diversity of skin microbiota was down-regulated at multiple time points following SARS-CoV-2 infection (P < 0.05). However, no significant difference in oral microbiota α-diversity was observed after SARS-CoV-2 infection. ML models based on baseline respiratory (oropharynx) microbiota profiles exhibited the ability to predict outcomes (survival and death, Random Forest, AUC = 0.847, Sensitivity = 0.833, Specificity = 0.750) after SARS-CoV-2 infection. The shared differential Prevotella and Streptococcus in the gut, respiratory tract, and oral cavity was associated with the severity and recovery of SARS-CoV-2 infection. CONCLUSIONS: SARS-CoV-2 infection was related to the down-regulation of α-diversity in the human gut and respiratory microbiota. The respiratory microbiota had the potential to predict the prognosis of individuals infected with SARS-CoV-2. Prevotella and Streptococcus might be key microbiota in SARS-CoV-2 infection.

Predicting pulmonary tuberculosis incidence in China using Baidu search index: an ARIMAX model approach.

BACKGROUND: Existing researches have established a correlation between internet search data and the epidemics of numerous infectious diseases. This study aims to develop a prediction model to explore the relationship between the Pulmonary Tuberculosis (PTB) epidemic trend in China and the Baidu search index. METHODS: Collect the number of new cases of PTB in China from January 2011 to August 2022. Use Spearman rank correlation and interaction analysis to identify Baidu keywords related to PTB and construct a PTB comprehensive search index. Evaluate the predictive performance of autoregressive integrated moving average (ARIMA) and ARIMA with explanatory variable (ARIMAX) models for the number of PTB cases. RESULTS: Incidence of PTB had shown a fluctuating downward trend. The Spearman rank correlation coefficient between the PTB comprehensive search index and its incidence was 0.834 (P < 0.001). The ARIMA model had an AIC value of 2804.41, and the MAPE value was 13.19%. The ARIMAX model incorporating the Baidu index demonstrated an AIC value of 2761.58 and a MAPE value of 5.33%. CONCLUSIONS: The ARIMAX model is superior to ARIMA in terms of fitting and predicting accuracy. Additionally, the use of Baidu Index has proven to be effective in predicting cases of PTB.

Early Warning and Prediction of Scarlet Fever in China Using the Baidu Search Index and Autoregressive Integrated Moving Average With Explanatory Variable (ARIMAX) Model: Time Series Analysis.

BACKGROUND: Internet-derived data and the autoregressive integrated moving average (ARIMA) and ARIMA with explanatory variable (ARIMAX) models are extensively used for infectious disease surveillance. However, the effectiveness of the Baidu search index (BSI) in predicting the incidence of scarlet fever remains uncertain. OBJECTIVE: Our objective was to investigate whether a low-cost BSI monitoring system could potentially function as a valuable complement to traditional scarlet fever surveillance in China. METHODS: ARIMA and ARIMAX models were developed to predict the incidence of scarlet fever in China using data from the National Health Commission of the People's Republic of China between January 2011 and August 2022. The procedures included establishing a keyword database, keyword selection and filtering through Spearman rank correlation and cross-correlation analyses, construction of the scarlet fever comprehensive search index (CSI), modeling with the training sets, predicting with the testing sets, and comparing the prediction performances. RESULTS: The average monthly incidence of scarlet fever was 4462.17 (SD 3011.75) cases, and annual incidence exhibited an upward trend until 2019. The keyword database contained 52 keywords, but only 6 highly relevant ones were selected for modeling. A high Spearman rank correlation was observed between the scarlet fever reported cases and the scarlet fever CSI (rs=0.881). We developed the ARIMA(4,0,0)(0,1,2)(12) model, and the ARIMA(4,0,0)(0,1,2)(12) + CSI (Lag=0) and ARIMAX(1,0,2)(2,0,0)(12) models were combined with the BSI. The 3 models had a good fit and passed the residuals Ljung-Box test. The ARIMA(4,0,0)(0,1,2)(12), ARIMA(4,0,0)(0,1,2)(12) + CSI (Lag=0), and ARIMAX(1,0,2)(2,0,0)(12) models demonstrated favorable predictive capabilities, with mean absolute errors of 1692.16 (95% CI 584.88-2799.44), 1067.89 (95% CI 402.02-1733.76), and 639.75 (95% CI 188.12-1091.38), respectively; root mean squared errors of 2036.92 (95% CI 929.64-3144.20), 1224.92 (95% CI 559.04-1890.79), and 830.80 (95% CI 379.17-1282.43), respectively; and mean absolute percentage errors of 4.33% (95% CI 0.54%-8.13%), 3.36% (95% CI -0.24% to 6.96%), and 2.16% (95% CI -0.69% to 5.00%), respectively. The ARIMAX models outperformed the ARIMA models and had better prediction performances with smaller values. CONCLUSIONS: This study demonstrated that the BSI can be used for the early warning and prediction of scarlet fever, serving as a valuable supplement to traditional surveillance systems.

The role of gut microbiota in the occurrence and progression of non-alcoholic fatty liver disease.

Background: Non-alcoholic fatty liver disease (NAFLD) is the most prevalent cause of chronic liver disease worldwide, and gut microbes are associated with the development and progression of NAFLD. Despite numerous studies exploring the changes in gut microbes associated with NAFLD, there was no consistent pattern of changes. Method: We retrieved studies on the human fecal microbiota sequenced by 16S rRNA gene amplification associated with NAFLD from the NCBI database up to April 2023, and re-analyzed them using bioinformatic methods. Results: We finally screened 12 relevant studies related to NAFLD, which included a total of 1,189 study subjects (NAFLD, n = 654; healthy control, n = 398; obesity, n = 137). Our results revealed a significant decrease in gut microbial diversity with the occurrence and progression of NAFLD (SMD = -0.32; 95% CI -0.42 to -0.21; p < 0.001). Alpha diversity and the increased abundance of several crucial genera, including Desulfovibrio, Negativibacillus, and Prevotella, can serve as an indication of their predictive risk ability for the occurrence and progression of NAFLD (all AUC > 0.7). The occurrence and progression of NAFLD are significantly associated with higher levels of LPS biosynthesis, tryptophan metabolism, glutathione metabolism, and lipid metabolism. Conclusion: This study elucidated gut microbes relevance to disease development and identified potential risk-associated microbes and functional pathways associated with NAFLD occurrence and progression.

An intelligent prediagnosis system for disease prediction and examination recommendation based on electronic medical record and a medical-semantic-aware convolution neural network (MSCNN) for pediatric chronic cough.

Background: Due to the phenotypic similarities among different pediatric respiratory diseases with chronic cough, primary doctors often misdiagnose and the misuse of examinations is prevalent. In the pre-diagnosis stage, the patients' chief complaints and other information in the electronic medical record (EMR) provide a powerful reference for respiratory experts to make preliminary disease judgment and examination plan. In this paper, we proposed an intelligent prediagnosis system to predict disease diagnosis and recommend examinations based on EMR text. Methods: We examined the clinical notes of 178,293 children with chronic cough symptoms from retrospective EMR data. The dataset is split into 7:3 for training and testing. From the testing set, we also extract 5% of samples for validation. We proposed a medical-semantic-aware convolution neural network (MSCNN) framework that can accomplish two downstream tasks from the same medical language model through transfer learning. First, a medical language model based on the word2vec algorithm was built to generate embeddings for the text data. Then, text convolutional neural network (TextCNN) was used to build models for disease prediction and examination recommendation. Results: We implemented 5 algorithms for disease prediction. In the disease prediction task, our algorithm outperformed the baseline methods on all metrics, with a top-1 accuracy (AC) of 0.68 and a top-3 AC of 0.923 on the testing set. By adding data enhancement, the top-3 AC reached 0.926. In the examination recommendation task, the overall AC on the testing set was 0.93 and the macro average (MA) F1-score was 0.88. The average area under the curve (AUC) on the training set was 0.97 while on the testing set it was 0.86. Conclusions: We constructed an intelligent prediagnosis system with an MSCNN framework that can predict diseases and make examination recommendations based on EMR data. Our approach achieved good results on a retrospective clinical dataset and thus has great potential for the application of automated diagnosis assist in clinical practice during pre-diagnosis stage, which will provide help for primary level doctors or doctors in basic-level hospitals. Due to the generality of the proposed framework, it can be straight forwardly extended to prediagnosis for other diseases.

Effects of marine-derived and plant-derived omega-3 polyunsaturated fatty acids on erythrocyte fatty acid composition in type 2 diabetic patients.

BACKGROUND: Dietary fatty acids intake affects the composition of erythrocyte fatty acids, which is strongly correlated with glycolipid metabolism disorders. This study aimed at investigating the different effects of marine-derived and plant-derived omega-3 polyunsaturated fatty acid (n-3 PUFA) on the fatty acids of erythrocytes and glycolipid metabolism in patients with type 2 diabetes mellitus (T2DM). METHODS: The randomized double-blinded trial that was performed on 180 T2DM patients. The participants were randomly assigned to three groups for the six-month intervention. The participants were randomly assigned to three groups for the six-month intervention. The fish oil (FO) group was administered with FO at a dose of 3 g/day containing eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), the perilla oil (PO) group was administered with PO at a dose of 3 g/day containing α-linolenic (ALA), the linseed and fish oil (LFO) group was administered with mixed linseed and fish oil at a dose of 3 g/day containing EPA, DHA and ALA. Demographic information were collected and anthropometric indices, glucose and lipid metabolism indexes, erythrocyte fatty acid composition were measured. Statistical analyses were performed using two-way ANOVA. RESULTS: A total of 150 patients finished the trial, with 52 of them in the FO group, 50 in the PO group and 48 in the LFO group. There were significant effects of time × treatment interaction on fast blood glucose (FBG), insulin, HOMA-IR and C-peptide, TC and triglyceride (TG) levels (P < 0.001). Glucose and C-peptide in PO and LFO groups decreased significantly and serum TG in FO group significantly decreased (P < 0.001) after the intervention. Erythrocyte C22: 5 n-6, ALA, DPA, n-6/n-3 PUFA, AA/EPA levels in the PO group were significantly higher than FO and LFO groups, while EPA, total n-3 PUFA and Omega-3 index were significantly higher in the FO and LFO groups compared to PO group. CONCLUSION: Supplementation with perilla oil decreased FBG while fish oil supplementation decreased the TG level. Marine-based and plant-based n-3 PUFAs exhibit different effects on fatty acid compositions of erythrocytes and regulated glycolipid metabolism. TRIAL REGISTRATION: This trial was recorded under Chinese Clinical Trial Registry Center (NO: ChiCTR-IOR-16008435 ) on May 28 2016.

Engineering Hierarchical Co@N-Doped Carbon Nanotubes/α-Ni(OH)2 Heterostructures on Carbon Cloth Enabling High-Performance Aqueous Nickel-Zinc Batteries.

Searching for high-performance Ni-based cathodes plays an important role in developing better aqueous nickel-zinc (Ni-Zn) batteries. For this purpose, herein, we demonstrate the design and synthesis of ultrathin α-Ni(OH)2 nanosheets branched onto metal-organic frameworks (MOFs)-derived 3D cross-linked N-doped carbon nanotubes encapsulated with tiny Co nanoparticles (denoted as Co@NCNTs/α-Ni(OH)2), which are directly supported on a flexible carbon cloth (CC). An aqueous Ni-Zn battery employing the hierarchical CC/Co@NCNTs/α-Ni(OH)2 as the binder-free cathode and a commercial Zn plate as the anode is fabricated, which displays an ultrahigh capacity (316 mAh g-1) and energy density (540.4 Wh kg-1) at 1 A g-1 as well as excellent rate capability (238 mAh g-1 at 10 A g-1) and superior cycling performance (about 84% capacity retention after 2000 cycles at 10 A g-1). The impressive electrochemical performance might benefit from the rich active sites, rapid electron transfer, cushy electrolyte access, rapid ion transport, and robust structural stability. In addition, the quasi-solid-state CC/Co@NCNTs/α-Ni(OH)2//Zn batteries are also successfully assembled with polymer electrolyte, indicating the great potential for portable and wearable electronics. This work might provide important guidance for constructing carbon-based hybrid materials directly supported on conductive substrates as high-performance electrodes for energy-related devices.

Hierarchical Nanoreactor with Multiple Adsorption and Catalytic Sites for Robust Lithium-Sulfur Batteries.

Developing high-performance cathode host materials is fundamental to solve the low utilization of sulfur, the sluggish redox kinetics, and the lithium polysulfide (LiPS) shuttle effect in lithium-sulfur batteries (LSBs). Here, a multifunctional Ag/VN@Co/NCNT nanocomposite with multiple adsorption and catalytic sites within hierarchical nanoreactors is reported as a robust sulfur host for LSB cathodes. In this hierarchical nanoreactor, heterostructured Ag/VN nanorods serve as a highly conductive backbone structure and provide internal catalytic and adsorption sites for LiPS conversion. Interconnected nitrogen-doped carbon nanotubes (NCNTs), in situ grown from the Ag/VN surface, greatly improve the overall specific surface area for sulfur dispersion and accommodate volume changes in the reaction process. Owing to their high LiPS adsorption ability, outer Co nanoparticles at the top of the NCNTs catch escaped LiPS, thus effectively suppressing the shuttle effect and enhancing kinetics. Benefiting from the multiple adsorption and catalytic sites of the developed hierarchical nanoreactors, Ag/VN@Co/NCNTs@S cathodes display outstanding electrochemical performances, including a superior rate performance of 609.7 mAh g-1 at 4 C and a good stability with a capacity decay of 0.018% per cycle after 2000 cycles at 2 C. These properties demonstrate the exceptional potential of Ag/VN@Co/NCNTs@S nanocomposites and approach LSBs closer to their real-world application.

Synthesis and antitumor evaluation of (aryl)methyl-amine derivatives of dehydroabietic acid-based B ring-fused-thiazole as potential PI3K/AKT/mTOR signaling pathway inhibitors.

In an attempt to search for new natural product-based antitumor agents, a series of novel (aryl)methyl-amine derivatives of dehydroabietic acid-based B ring-fused-thiazole were designed and synthesized. The primary bioassay showed that compounds 5r and 5s presented certain inhibitory activity against cancer cells, weak cytotoxic activity against normal cells, and inhibitory activity against PI3K/AKT/mTOR signaling pathway. The binding modes and the binding site interactions between the active compounds and the target proteins were predicted preliminarily by the molecular docking method.

A comparative study of the effects of palm olein, cocoa butter and extra virgin olive oil on lipid profile, including low-density lipoprotein subfractions in young healthy Chinese people.

The aim of this study is to investigate the effects of palm olein (POL), cocoa butter (CB) and extra virgin olive oil (EVOO) on the lipid profile and low-density lipoprotein subfractions in a young, healthy Chinese population. After screening, 72 subjects were randomly assigned to three groups, and an 18-week randomized crossover trial was conducted. The first phase was a 2-week run-in period, followed by three phases of the 4-week experimental periods with a 2-week washout period between experimental periods. Three groups of subjects alternately consumed a Chinese diet enriched with the different test oils. The various indices of subjects were collected before and after each experimental period. Sixty-seven subjects completed the study, and there were no significant differences in conventional indices amongst the three groups at the beginning of the three experimental periods (p > .05). Each test oil accounted for approximately 40% of total fat intake and approximately 11.3% of the total energy supply. After controlling for dietary interventions, only the serum triglyceride level of the POL-Diet was significantly lower than that of the EVOO-Diet (p = .034), and most indices did not significantly differ amongst the three test oil diets (p > .05). POL, CB and EVOO have almost identical effects on serum lipids.

[Correlation of serum low density lipoprotein subfractions with routine lipid profile and physical indices in medical students from a university in 2016].

OBJECTIVE: To investigate the correlation among the serum low density lipoprotein subfractions, lipoprotein a and other routine indices. METHODS: Medical students who didn 't experience cardiovascular events were recruited at a university in Nanjing City, their physical indicators were measured( including height, weight, waist circumference and hip circumference) and fasting blood was collected to detect the seven items of serum lipid. Lipoprint system was used to detect low density lipoprotein subfractions, the correlation among the indices was analyzed ultimately. RESULTS: A total of 84 students( 40 male and 44 female) at the age of 20-29 were enrolled in the study. Levels of body mass index, waist-to-hip ratio, very low density lipoprotein, small dense low density lipoprotein in male were significantly higher than those in female, while levels ofhigh density lipoprotein, apolipoprotein A1, intermediate density lipoprotein and mean low density lipoprotein size in male were significantly lower than those in female( P < 0. 05). In this population, the abnormal rate of lipoprotein a reached 27. 4% and was only significantly positively correlated with high density lipoprotein( r = 0. 265, P = 0. 015), and the mean low density lipoprotein size was significantly negatively correlated with waist-to-hip ratio, triglyceride and small dense low density lipoprotein etc. ( P < 0. 05). CONCLUSION: Male medical students have more risk factors of angiocardiopathy than young women, and the abnormal rate of serum lipoprotein a in medical students is higher.

Effects of a liquid high-fat meal on postprandial lipid metabolism in type 2 diabetic patients with abdominal obesity.

BACKGROUND: Postprandial lipemia and lipoprotein lipase (LPL) activity play crucial roles in the pathogenesis of accelerated atherosclerosis. This study aimed to evaluate the postprandial lipid metabolism after the ingestion of a liquid high-fat meal in type 2 diabetic patients with abdominal obesity, and determine if the PvuII polymorphisms of LPL influence their postprandial lipid responses. METHODS: Serum glucose, insulin, triglycerides (TG), total cholesterol (TC) and high density lipoprotein cholesterol (HDL-C) were measured in fasting and postprandial state at 0.5, 1, 2, 4, 6 and 8 h after a liquid high-fat meal in 51 type 2 diabetic patients with abdominal obesity, 31 type 2 diabetic patients without abdominal obesity and 39 controls. Their PvuII polymorphisms of LPL were tested in fasting. RESULTS: Type 2 diabetic patients with abdominal obesity had significantly higher postprandial areas under the curve (AUC) of glucose [least square mean difference (LSMD) = 30.763, 95% confidence interval (CI) = 23.071-38.455, F = 37.346, P < 0.05] and TC (LSMD = 3.995, 95% CI = 1.043-6.947, F = 3.681, P < 0.05) than controls. Postprandial AUCs for insulin, homeostasis model assessment-insulin resistance (HOMA-IR) and TG were higher (LSMD = 86.987, 95% CI = 37.421-136.553, F = 16.739, P < 0.05; LSMD = 37.456, 95% CI = 16.312-58.600, F = 27.012, P < 0.05; LSMD = 4.684, 95% CI = 2.662-6.705, F = 26.158, P < 0.05), whereas HDL-C AUC was lower (LSMD = -1.652, 95% CI = -2.685 - -0.620, F = 8.190, P < 0.05) in type 2 diabetic subjects with abdominal obesity than those without abdominal obesity. In type 2 diabetic patients with abdominal obesity, postprandial TG AUC was lower in P-/- than in P+/- (LSMD = -4.393, 95% CI = -9.278 - -0.491, F = 4.476, P < 0.05) and P+/+ (LSMD = -7.180, 95% CI = -12.319 - -2.014, F = 4.476, P < 0.05) phenotypes. Postprandial AUCs for glucose, insulin, HOMA-IR, TC and HDL-C were not different according to PvuII phenotypes. CONCLUSIONS: Abdominal obesity exacerbates the postprandial lipid responses in type 2 diabetic patients, which partly explains the excess atherogenic risk in these patients. In addition, the presence of P+ allele could contribute to a greater postprandial TG increase in type 2 diabetic patients with abdominal obesity. TRIAL REGISTRATION: ChiCTR-IOR-16008435. Registered 8 May 2016.

Consumption of a liquid high-fat meal increases triglycerides but decreases high-density lipoprotein cholesterol in abdominally obese subjects with high postprandial insulin resistance.

Abdominal obesity is associated with an increased risk of insulin resistance, which may be a potential contributor to dyslipidemia. However, the relationship between postprandial insulin resistance and lipid metabolism in abdominally obese subjects remains unknown. We hypothesized that postprandial dyslipidemia would be exaggerated in abdominally obese subjects with high postprandial insulin resistance. To test this hypothesis, serum glucose, insulin, triglycerides, total cholesterol, high-density lipoprotein cholesterol, and apolipoprotein B were measured at baseline and postprandial state at 0.5, 1, 2, 4, 6, and 8 hours after a liquid high-fat meal in non-abdominally obese controls (n=44) and abdominally obese subjects with low (AO-LPIR, n=40), middle (n=40), and high postprandial insulin resistance (AO-HPIR, n=40) based on the tertiles ratio of the insulin to glucose areas under the curve (AUC). Their serum adipokines were tested at baseline only. Fasting serum leptin was higher (P<.05) in AO-HPIR than that in AO-LPIR and controls. Postprandial triglycerides AUC was higher (P<.05), whereas high-density lipoprotein cholesterol AUC was lower (P<.05), in AO-HPIR than those in AO-LPIR and controls. Postprandial AUCs for total cholesterol and apolipoprotein B were similar in abdominally obese subjects with different degrees of postprandial insulin resistance and controls. The present study indicated that the higher degree of postprandial insulin resistance, the more adverse lipid profiles in abdominally obese subjects, which provides insight into opportunity for screening in health.

Methylenetetrahydrofolate reductase gene polymorphisms association with the risk of diffuse large B cell lymphoma: a meta-analysis.

To date, case-control studies on the association between methylenetetrahydrofolate reductase (MTHFR) and diffuse large B cell lymphoma (DLBCL) have provided either controversial or inconclusive results. To clarify the effect of MTHFR on the risk of diffuse large B cell lymphoma, a meta-analysis of all case-control observational studies was performed. The fixed effects and random effects model showed that the C677T polymorphism was associated with a risk of DLBCL among East Asian populations, and A1298C polymorphism was not associated with a risk of DLBCL among Caucasian and East Asian populations. Our pooled data suggest evidence for a major role of MTHFR C677T polymorphism in the carcinogenesis of DLBCL among East Asian populations.

Nuclear survivin expression is associated with a poor prognosis in Caucasian non-small cell lung cancer patients.

BACKGROUND: The role of the nuclear protein survivin in non-small cell lung cancer (NSCLC) remains controversial. To clarify the association of survivin with survival in NSCLC, we performed a meta-analysis of the literature with meta-analysis. METHODS: Trials were selected for further analysis if they provided an independent assessment of nuclear survivin in NSCLC and reported the survival data in the context of survivin status. A total of 7 trials, which comprised 823 patients, were included in the meta-analysis. Sensitivity analyses were conducted using the patient's disease stage, IHC cutoff value, and ethnicity. RESULTS: The combined hazard ratio (HR) of 1.54 [95% CI, 0.79-3.02; test for heterogeneity p<0.001] suggests that high nuclear survivin expression has no impact on patient survival. However, when the studies were restricted to Caucasian patients, high levels of nuclear survivin expression were correlated with reduced survival (HR 2.38, 95% CI=1.60-3.52; p=0.189 for heterogeneity). In addition, the heterogeneity disappeared when the analysis was restricted to Caucasians. CONCLUSION: Nuclear survivin expression is associated with poor prognosis for Caucasian NSCLC patients.