The in vitro digestion fates of diacylglycerol under different intestinal conditions:a potential lipid source for lipid indigestion patients

The in vitro digestion models mimicking the gastrointestinal(GI)tract of general population and lipid indigestion patients(with lower levels of bile salts or pancreatic lipase)were selected to investigate whether diacylglycerols(DAGs)are potential good lipid sources for these patients.Linseed oil-based DAG(LD)and linseed oil(LT)were selected.LD-based emulsion((83.74±1.23)%)had higher lipolysis degree than LT-based emulsion((74.47±1.16)%)when monitoring the GI tract of normal population as previously reported.Indigestion conditions seriously decreased the digestive degree of LT-based emulsion((40.23±2.48)%-(66.50±3.70)%)while showed less influence on LD-based emulsion((64.18±2.41)%-(81.85±3.45)%).As opposed to LT-based emulsion,LD-based emulsion exhibited preference for releasing unsaturated fatty acids(especially oleic acid andα-linolenic acid)due to their different glycerolipid compositions.LD-based emulsion showed potential for providing lipids and nutrients(including essential fatty acids)for lipid indigestion patients.

Shared diagnostic genes and potential mechanisms between COVID-19 and sepsis revealed by bioinformatics analysis

The coronavirus disease 2019(COVID-19)pandemic,triggered by the novel coronavirus severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),has ravaged the globe,resulting in a staggering loss of life and wreaking havoc on the worldwide economy.[1,2]Sepsis is a cascade of abnormal responses provoked by infection,leading to a critical deterioration in organ function that poses a life-threatening risk.[3]However,it is unclear from published reports whether COVID-19 and sepsis are commonly aff ected by molecular factors.Therefore,we performed a bioinformatics analysis to uncover shared diagnostic genes and potential mechanisms between COVID-19 and sepsis.

MEM-TET: Improved Triplet Network for Intrusion Detection System

With the advancement of network communication technology,network traffic shows explosive growth.Consequently,network attacks occur frequently.Network intrusion detection systems are still the primary means of detecting attacks.However,two challenges continue to stymie the development of a viable network intrusion detection system:imbalanced training data and new undiscovered attacks.Therefore,this study proposes a unique deep learning-based intrusion detection method.We use two independent in-memory autoencoders trained on regular network traffic and attacks to capture the dynamic relationship between traffic features in the presence of unbalanced training data.Then the original data is fed into the triplet network by forming a triplet with the data reconstructed from the two encoders to train.Finally,the distance relationship between the triples determines whether the traffic is an attack.In addition,to improve the accuracy of detecting unknown attacks,this research proposes an improved triplet loss function that is used to pull the distances of the same class closer while pushing the distances belonging to different classes farther in the learned feature space.The proposed approach’s effectiveness,stability,and significance are evaluated against advanced models on the Android Adware and General Malware Dataset(AAGM17),Knowledge Discovery and Data Mining Cup 1999(KDDCUP99),Canadian Institute for Cybersecurity Group’s Intrusion Detection Evaluation Dataset(CICIDS2017),UNSW-NB15,Network Security Lab-Knowledge Discovery and Data Mining(NSL-KDD)datasets.The achieved results confirmed the superiority of the proposed method for the task of network intrusion detection.

Cinnamon free phenolic extract regulates glucose absorption in intestinal cells by inhibiting glucose transporters

Cinnamon is a traditional herbal medicine that is a valuable source of bioactive phenolic compounds.In this study,we determined the effects of cinnamon free phenolic extract(CFPE)on glucose transport in Caco-2 cells and its possible mechanisms of action.First,the contents of phenolic compounds and flavonoids in bark were compared among four cinnamon cultivars.The‘Taiwan’cultivar had the highest contents of these compounds,and the CFPE was prepared from it.A Caco-2 monolayer was established,and the effect of CFPE on glucose transport across the monolayer was determined.The results showed that CFPE(at 150-300μg/mL)suppressed glucose transport across the monolayer in a dose-dependent manner.Procyanidin C1,procyanidin B2,procyanidin B1,procyanidin B3,procyanidin A2,and(􀀀)-epicatechin derivatives in CFPE may have contributed to its suppressive effect.Treatment with CFPE decreased the transcript levels of SGK1 encoding serum and glucocorticoid-inducible kinase and PLC/PKC encoding phospholipase C/protein kinase C,which are involved in the signaling pathway associated with glucose transport;and the transcript levels of SGLT1 encoding sodium/glucose cotransporter 1 and GLUT2 encoding glucose transporter 2,the key glucose transporters in this pathway.These findings suggest that CFPE inhibits glucose transport via its effects on the signaling pathway and glucose transporters involved in glucose absorption in intestinal cells.Thus,CFPE has potential applications in preventing postprandial hyperglycemia.