Cornus officinalis vinegar reduces body weight and attenuates hepatic steatosis in mouse model of nonalcoholic fatty liver disease

This study aimed to determine the main bioactive components of Cornus officinalis vinegar (COV) and assess the effects of COV on the body weight (BW) and hepatic steatosis in a nonalcoholic fatty liver disease (NAFLD) mouse model. Seven-week-old KM female mice were divided into five treatment groups: (1) Normal control (NC) group, (2) high fat diet (HFD) group, (3) low concentration treatment group (3.5% COV), (4) medium concentration treatment group (5.0% COV), and (5) high concentration treatment group (6.5% COV). Mice in the NC group were fed with a normal chow diet, and those in the other four groups were fed with a HFD known for causing obesity for 10 weeks. Then, mice in the three COV treatment groups were orally administered with COV once a day for 6 weeks. Results showed that the contents of loganin and morroniside in COV reached 16.82 and 51.17 µg/ml, respectively, and COV also contained multiple organic acids. COV significantly reduced BW, abdominal fat weight, liver weight, and the levels of glucose, triglyceride, and low-density lipoprotein cholesterol of serum and increased the levels of high-density lipoprotein cholesterol of serum (p < 0.05). COV also improved the liver function and anti-oxidant activity of liver (p < 0.05). COV treatments increased the interleukin-10 expression and reduced the tumor necrosis factor-α expression in the liver tissue of NAFLD mice (p < 0.05). Histopathological observation revealed that COV suppressed hepatic lipid accumulation and steatosis. The results suggest that COV may contribute to the alleviation of NAFLD and obesity.     

Glycaemic response of pseudocereal-based gluten-free food products: a review

Rapid digestion and absorption of carbohydrates have become a health issue (high glycaemic index, GI), which can be a matter of greater concern when consumed in large quantities. Depending upon the influence of carbohydrates on the blood sugar levels, GI classifies carbohydrates (on a scale of 100) as low (<55), medium (55–70) and high (>70) GI foods. Among the pseudocereals, chia seed possesses relatively lower GI (28.53), as compared to buckwheat (52.35), amaranth (47.65) and quinoa (61.50). Consumers now prefer foods with a high GI over the ones with low GI to prevent various metabolic alterations. Celiac disease is a lifelong disorder prevalent worldwide and can only be controlled by following a strict lifelong gluten-free diet. Therefore, pseudocereals could be a potential alternate for low GI food and developing gluten-free food products, including bread, cookies, noodles and pasta. This review synthesises the recently published literatures on pseudocereals as a lowering GI and healthy food option. This review also gives insights into developing pseudocereals as a potential and novel ingredient for gluten-free food applications and the latest research conducted worldwide.     

Deep Learning Based Process Analytics Model for Predicting Type 2 Diabetes Mellitus

Process analytics is one of the popular research domains that advanced in the recent years. Process analytics encompasses identification, monitoring, and improvement of the processes through knowledge extraction from historical data. The evolution of Artificial Intelligence (AI)-enabled Electronic Health Records (EHRs) revolutionized the medical practice. Type 2 Diabetes Mellitus (T2DM) is a syndrome characterized by the lack of insulin secretion. If not diagnosed and managed at early stages, it may produce severe outcomes and at times, death too. Chronic Kidney Disease (CKD) and Coronary Heart Disease (CHD) are the most common, long-term and life-threatening diseases caused by T2DM. Therefore, it becomes inevitable to predict the risks of CKD and CHD in T2DM patients. The current research article presents automated Deep Learning (DL)-based Deep Neural Network (DNN) with Adagrad Optimization Algorithm i.e., DNN-AGOA model to predict CKD and CHD risks in T2DM patients. The paper proposes a risk prediction model for T2DM patients who may develop CKD or CHD. This model helps in alarming both T2DM patients and clinicians in advance. At first, the proposed DNN-AGOA model performs data preprocessing to improve the quality of data and make it compatible for further processing. Besides, a Deep Neural Network (DNN) is employed for feature extraction, after which sigmoid function is used for classification. Further, Adagrad optimizer is applied to improve the performance of DNN model. For experimental validation, benchmark medical datasets were used and the results were validated under several dimensions. The proposed model achieved a maximum precision of 93.99%, recall of 94.63%, specificity of 73.34%, accuracy of 92.58%, and F-score of 94.22%. The results attained through experimentation established that the proposed DNN-AGOA model has good prediction capability over other methods.     

某福利院一起肠炎沙门菌食源性疾病的调查分析

目的 对某福利院一起肠炎沙门菌食源性疾病进行调查和溯源,为研究相关食源性疾病提供参考。方法采用流行病学、食品卫生学和脉冲场凝胶电泳(PFGE)同源性分析等方法,分析本次食源性疾病事件。结果 确认本次事件中病例23名,患病率5.65%(23/407)；现场采集病例肛拭子15份和厨房工作人员肛拭子3份、留样菜品3份、水果2份以及冰棒1份,其中从11份病例肛拭子中检出肠炎沙门菌,PFGE结果显示11株肠炎沙门菌的DNA条带图谱相似性为96.4%,聚类分析为同一型,结合流行病学调查,初步判断菌株来自同一克隆系。结论 综合流行病学、食品卫生学和实验室检测结果,确定为一起肠炎沙门菌引起的食源性疾病,福利院应加强对特殊人群的饮食安全管理,制定相应的食源性疾病突发事件应急处理预案,防止此类事故再发生。     

A Systematic Review and Meta-Analysis of Pharmacogenetic Studies in Patients with Chronic Kidney Disease

Chronic kidney disease (CKD) is an important global public health problem due to its high prevalence and morbidity. Although the treatment of nephrology patients has changed considerably, ineffectiveness and side effects of medications represent a major issue. In an effort to elucidate the contribution of genetic variants located in several genes in the response to treatment of patients with CKD, we performed a systematic review and meta-analysis of all available pharmacogenetics studies. The association between genotype distribution and response to medication was examined using the dominant, recessive, and additive inheritance models. Subgroup analysis based on ethnicity was also performed. In total, 29 studies were included in the meta-analysis, which examined the association of 11 genes (16 polymorphisms) with the response to treatment regarding CKD. Among the 29 studies, 18 studies included patients with renal transplantation, 8 involved patients with nephrotic syndrome, and 3 studies included patients with lupus nephritis. The present meta-analysis provides strong evidence for the contribution of variants harbored in the ABCB1, IL-10, ITPA, MIF, and TNF genes that creates some genetic predisposition that reduces effectiveness or is associated with adverse events of medications used in CKD.     

Molecular Characteristics of Amyloid Precursor Protein (APP) and Its Effects in Cancer

Amyloid precursor protein (APP) is a type 1 transmembrane glycoprotein, and its homologs amyloid precursor-like protein 1 (APLP1) and amyloid precursor-like protein 2 (APLP2) are highly conserved in mammals. APP and APLP are known to be intimately involved in the pathogenesis and progression of Alzheimer’s disease and to play important roles in neuronal homeostasis and development and neural transmission. APP and APLP are also expressed in non-neuronal tissues and are overexpressed in cancer cells. Furthermore, research indicates they are involved in several cancers. In this review, we examine the biological characteristics of APP-related family members and their roles in cancer.     

Upregulated Expression of Activation-Induced Cytidine Deaminase in Ocular Adnexal Marginal Zone Lymphoma with IgG4-Positive Cells

Immunoglobulin G4-related disease (IgG4-RD) is a systemic disorder characterized by tissue fibrosis and intense lymphoplasmacytic infiltration, causing progressive organ dysfunction. Activation-induced cytidine deaminase (AID), a deaminase normally expressed in activated B-cells in germinal centers, edits ribonucleotides to induce somatic hypermutation and class switching of immunoglobulin. While AID expression is strictly controlled under physiological conditions, chronic inflammation has been noted to induce its upregulation to propel oncogenesis. We examined AID expression in IgG4-related ophthalmic disease (IgG4-ROD; n = 16), marginal zone lymphoma with IgG4-positive cells (IgG4+ MZL; n = 11), and marginal zone lymphoma without IgG4-positive cells (IgG4- MZL; n = 12) of ocular adnexa using immunohistochemical staining. Immunohistochemistry revealed significantly higher AID-intensity index in IgG4-ROD and IgG4+ MZL than IgG4- MZL (p < 0.001 and = 0.001, respectively). The present results suggest that IgG4-RD has several specific causes of AID up-regulation in addition to inflammation, and AID may be a driver of oncogenesis in IgG4-ROD to IgG4+ MZL.     

A Cumulative Effect of Food and Viruses to Trigger Celiac Disease (CD): A Commentary on the Recent Literature

Celiac disease (CD) is a type of inflammatory chronic disease caused by nutrients such as gliadin that induce a TC (T cell)-mediated response in a partially known genetical background in an environment predisposed to inflammation, including viruses and food. Various experimental and clinical observations suggest that multiple agents such as viruses and bacteria have some common, inflammatory pathways predisposing individuals to chronic inflammatory diseases including celiac disease (CD). More recently, a Western diet and lifestyle have been linked to tissue inflammation and increase in chronic inflammatory diseases. In CD, the gliadin protein itself has been shown to be able to induce inflammation. A cooperation between viruses and gliadin is present in vitro and in vivo with common mechanisms to induce inflammation. Nutrients could have also a protective effect on CD, and in fact the anti-inflammatory Mediterranean diet has a protective effect on the development of CD in children. The possible impact of these observations on clinical practice is discussed.     

TiO2/MXene-Assisted LDI-MS for Urine Metabolic Profiling in Urinary Disease

Cancer remains an intractable medical problem. Rapid diagnosis and identification of cancer are critical to differentiate it from nonmalignant diseases. High-throughput biofluid metabolic analysis has potential for cancer diagnosis. Nevertheless, the present metabolite analysis method does not meet the demand for high-throughput screening of diseases. Herein, a high-throughput, cost-effective, and noninvasive urine metabolic profiling method based on TiO₂/MXene-assisted laser desorption/ionization mass spectrometry (LDI-MS) is presented for the efficient screening of bladder cancer (BC) and nonmalignant urinary disease. Combined with machine learning, TiO₂/MXene-assisted LDI-MS enables high diagnostic accuracy (96.8%) for the classification of patient groups (including 47 BC and 46 ureteral calculus (UC) patients) from healthy controls (113 cases). In addition, BC patients can also be identified from noncancerous UC individuals with an accuracy of 88.3% in the independent test cohort. Furthermore, metabolite variations between BC and UC individuals are investigated based on relative quantification, and related pathways are also discussed. These results suggest that this method, based on urine metabolic patterns, provides a potential tool for rapidly distinguishing urinary diseases and it may pave the way for precision medicine.     

The Role of microRNAs in Development of Colitis-Associated Colorectal Cancer

Colorectal cancer (CRC) is the third most deadly cancer worldwide, and inflammatory bowel disease (IBD) is one of the critical factors in CRC carcinogenesis. IBD is responsible for an unphysiological and sustained chronic inflammation environment favoring the transformation. MicroRNAs (miRNAs) belong to a class of highly conserved short single-stranded segments (18–25 nucleotides) non-coding RNA and have been extensively discussed in both CRC and IBD. However, the role of miRNAs in the development of colitis-associated CRC (CAC) is less clear. The aim of this review is to summarize the major upregulated (miR-18a, miR-19a, miR-21, miR-31, miR-155 and miR-214) and downregulated (miR-124, miR-193a-3p and miR-139-5p) miRNAs in CAC, and their roles in genes’ expression modulation in chronic colonic-inflammation-induced carcinogenesis, including programmed cell-death pathways. These miRNAs dysregulation could be applied for early CAC diagnosis, to predict therapy efficacy and for precision treatment.