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Objective: The PCSPHs were prepared by enzymatic hydrolysis of Procambarus clarkii shells, and their hypoglycemic and lipid-lowering activities in vitro were evaluated and peptide sequence were analyzed. Methods: Different crayfish shell proteolysates were prepared by hydrolysis of pepsin, alcalase protease, trypsin, flavor protease and papain, and their in vitro hypoglycemic and lipid-lowering activities were evaluated and peptide sequences were determined. The peptides sequence of Procambarus clarkii shells was identified by LC-MS/MS. Taking the crystal structure of the nuclear receptor PPARγ ligand binding region as the target, Autodock vina was used to simulate molecular docking to obtain crayfish shell peptides with potential hypoglycemic/lipid-lowering activities. Results: The PEP-PCSPHs had significant inhibitory effects on α-amylase and α-glucosidase activity, with IC50 values of （5.42±0.05） mg/mL and （7.11±1.01） mg/mL, respectively. The TRY-PCSPHs had the strongest inhibitory effect on pancreatic lipase activity, with an IC50 of （4.71±1.12） mg/mL, and exhibited the best in vitro binding effects on sodium glycinocholate. In addition, 3 391 peptide sequences were identified in pepsin hydrolysates and 2 086 peptide sequences were identified in trypsin hydrolysates, and multiple hypoglycemic/lipid-lowering crayfish shell active peptides that could bind to PPARγ were screened through online website prediction and molecular docking. Conclusion: The shrimp shell peptides prepared by enzymatic hydrolysis of crayfish shells have potential hypoglycemic and lipid-lowering activities, which may play a role in improving glucose and lipid metabolism disorders.

Objective: Explore the protective effect of Procambarus clarkii shell bioactive peptides （PCSBP） on oxidative stress injury in the organism. Methods: This study using alkaline protease hydrolysis method to prepare bioactive peptides and measured their antioxidant activity in vitro. Subsequently, the protective effects of PCSBP on oxidative stress injury in zebrafish under fasting stress was analyzed. Results: The PCSBP showed potential antioxidant capacity in vitro, with scavenging rates of DPPH radicals and hydroxyl radicals at （46.35±1.32）% and （75.22±2.18）%. The final body weight, body length and muscle amino acid content of zebrafish were decreased under fasting stress, but the growth performance and muscle amino acid content of Zebrafish were effectively improved after taking PCSBP. The muscle tissue structure showed that the myofiber gap widened and ruptured in zebrafish after fasting. The myofiber were arranged neatly, with complete morphology and structure after PCSBP ingestion, and no obvious rupture was observed. In terms of anti-oxidative stress, PCSBP significantly enhanced the activities of superoxide dismutase （SOD）, catalase （CAT）, glutathione peroxidase （GSH-PX）, and glutathione （GSH） content in zebrafish muscle, and also decreased the production of malondialdehyde （MDA） and protein carbonyl （PC）, which were oxidative damage indexes. Further analysis revealed that PCSBP significantly up-regulated the expression of antioxidant signaling molecule nrf2 mRNA, down-regulated keap1 expression, and increased the transcriptional expression of downstream antioxidant enzyme genes, which effectively ameliorated the oxidative stress damage in muscle of zebrafish. Conclusion: Bioactive peptides derived from crayfish shell has a protective effect on oxidative stress injury in zebrafish and can be used as a potential antioxidant.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Most genes associated with neurodevelopmental disorders (NDDs) were identified with an excess of de novo mutations (DNMs) but the significance in case-control mutation burden analysis is unestablished. Here, we sequence 63 genes in 16,294 NDD cases and an additional 62 genes in 6,211 NDD cases. By combining these with published data, we assess a total of 125 genes in over 16,000 NDD cases and compare the mutation burden to nonpsychiatric controls from ExAC. We identify 48 genes (25 newly reported) showing significant burden of ultra-rare (MAF

Object: Perimenopause depression disorder (PDD) is a very common problem in clinical practice and is characterized by depression and autonomic nervous symptoms, including hot flashes, palpitation, and night sweating. In addition, the comorbidity of menopause depression has long been an integral component of the estradiol (E2) shortage. Previous studies have suggested that the mechanisms underlying this comorbidity involved overlap of endocrine and cerebellar networks. Emerging evidence has shown that the endocrine–brain–gut–microbiota axis plays a key role in the regulation of affective disorders. Yangyin-ningshen formula (YYNS) is a traditional Chinese decoction tailored by Yijintang for menopausal depression intervention. Thus, we hypothesized that the YYNS may be involved in the menopause depression alleviation through the endocrine–brain–gut–microbiota axis. Methods: To verify this, we constructed a bilateral ovariectomy (OVX) mouse model to simulate menopausal-related depression. Subsequently, behavioral tests including the open field test (OFT) and the forced swimming test (FST) were conducted to examine the depression state post-OVX. With YYNS or E2 intervention, enzyme-linked immunosorbent assay (ELISA) was used to determine the serum sex hormones level. 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MS) were used to analyze the microbiome of the colon samples collected from mice in the sham surgery group (CSH), the OVX model group (CMD), the OVX with E2 hormone intervention group (CHM), and the OVX with YYNS intervention group (CYYNS). One week after OVX, CMD, CHM, and CYYNS showed depression in OFT, FST. Three weeks post-OVX, CHM and CYYNS showed a notable relief of depression; CMD shaped the OTUs shrinkage; and OTUs were raised in the sham, CHM, and CYYNS group. The CMD group showed that the abundance of Actinobiota decreased but that of Bacteriodia increased. The relative abundance of the genus varied in each group. Moreover, functional correlation of changes in sex hormone and gut microbes between different groups showed that the PRL level was negatively correlated with Odoribacter. T level was positively correlated with Lachnospiraceae NK4A136 group and Odoribacter abundance (p < 0.05). Conclusion: Our results not only offer novel insights into the sex hormones and depression with OVX mice but also build an important basis for E2 or YYNS therapeutic efficacy on PDD, which provide for future research on this etiology through the endocrine–brain–gut–microbiota network. [ABSTRACT FROM AUTHOR]

Several epidemiological studies have investigated the association between sugar intake, the levels of systolic blood pressure (SBP) and diastolic blood pressure (DBP) and the risk of hypertension, but findings have been inconsistent. We carried out a systematic review and meta-analysis of observational studies to examine the associations between sugar intake, hypertension risk, and BP levels. Articles published up to February 2, 2021 were sourced through PubMed, EMBASE and Web of Science. Pooled relative risks (RRs) and 95% confidence intervals (CIs) were estimated using a fixed- or random-effects model. Restricted cubic splines were used to evaluate dose-response associations. Overall, 35 studies were included in the present meta-analysis (23 for hypertension and 12 for BP). Sugar-sweetened beverages (SSBs) and artificially sweetened beverages (ASBs) were positively associated with hypertension risk: 1.26 (95% CI, 1.15–1.37) and 1.10 (1.07–1.13) per 250-g/day increment, respectively. For SBP, only SSBs were significant with a pooled β value of 0.24 mmHg (95% CI, 0.12–0.36) per 250 g increase. Fructose, sucrose, and added sugar, however, were shown to be associated with elevated DBP with 0.83 mmHg (0.07–1.59), 1.10 mmHg (0.12–2.08), and 5.15 mmHg (0.09–10.21), respectively. Current evidence supports the harmful effects of sugar intake for hypertension and BP level, especially SSBs, ASBs, and total sugar intake. [ABSTRACT FROM AUTHOR]

Early blight and ladybug beetle infestation are important factors threatening potato yields. The current research on disease classification using the spectral differences between the healthy and disease-stressed leaves of plants has achieved good progress in a variety of crops, but less research has been conducted on early blight in potato. This paper proposes a CARS-SPA-GA feature selection method. First, the raw spectral data of potato leaves in the visible/near-infrared light region were preprocessed. Then, the feature wavelengths were selected via competitive adaptive reweighted sampling (CARS) and the successive projection algorithm (SPA), respectively. Then, the two sets of wavelengths were reorganized and duplicates were removed, and secondary feature selection was conducted with genetic algorithm (GA). Finally, the feature wavelengths were fed into different classifiers and the parameters were optimized using a real-coded genetic algorithm (RCGA). The experimental results show that the feature wavelengths selected by the CARS-SPA-GA method accounted only for 9% of the full band, and the classification accuracy of the RCGA-optimized support vector machine (SVM) classification model reached 98.366%. These results show that it is feasible to classify early blight and ladybug beetle infestation in potato using visible/near-infrared spectral data, and the CARS-SPA-GA method can substantially improve the accuracy and detection efficiency of potato pest and disease classification. [ABSTRACT FROM AUTHOR]

The fast growth of the Internet has made network security problems more noticeable, so intrusion detection systems (IDSs) have become a crucial tool for maintaining network security. IDSs guarantee the normal operation of the network by tracking network traffic and spotting possible assaults, thereby safeguarding data security. However, traditional intrusion detection methods encounter several issues such as low detection efficiency and prolonged detection time when dealing with massive and high-dimensional data. Therefore, feature selection (FS) is particularly important in IDSs. By selecting the most representative features, it can not only improve the detection accuracy but also significantly reduce the computational complexity and attack detection time. This work proposes a new FS approach, BPSO-SA, that is based on the Binary Particle Swarm Optimization (BPSO) and Simulated Annealing (SA) algorithms. It combines these with the Gray Wolf Optimization (GWO) algorithm to optimize the LightGBM model, thereby building a new type of reflective Distributed Denial of Service (DDoS) attack detection model. The BPSO-SA algorithm enhances the global search capability of Particle Swarm Optimization (PSO) using the SA mechanism and effectively screens out the optimal feature subset; the GWO algorithm optimizes the hyperparameters of LightGBM by simulating the group hunting behavior of gray wolves to enhance the detection performance of the model. While showing great resilience and generalizing power, the experimental results show that the proposed reflective DDoS attack detection model surpasses conventional methods in terms of detection accuracy, precision, recall, F1-score, and prediction time. [ABSTRACT FROM AUTHOR]

Brain voltage plays a crucial role in indicating internal functions or diseases, and optical voltage imaging has gained intensive attention in recent years. Despite encouraging progress, current implementations encounter limitations pertaining to penetration depth, field of view (FOV), and photostability of indicators. To mitigate these challenges, a robust voltage‐sensitive dye (VSD)‐based whole‐field photoacoustic brain detection (WF‐PABD) platform is proposed, enabling direct evaluation of voltage dynamics across the whole brain, forming as PA‐VSD. WF‐PABD is equipped with a 512‐element ring‐array ultrasound detector capable of 360‐degree scanning, providing a large FOV (≈5 cm), high spatial resolution (≈110 µm), and rapid imaging acquisition. The proposed VSD remained ≈75% photostability after 30 min laser exposure, much greater than most calcium sensors. The optical voltage‐response mechanisms are validated and the capability of PA‐VSD to directly screen seizures is established. It is demonstrated that investigating connectivity among different brain regions allows to identify the precise location of active epileptic foci as well as the electrical conduction pathways and their directionality through fast temporal visualization. In summary, this study not only addresses the need for non‐invasive, high‐resolution, long‐term, and direct monitoring of brain voltage but also empowers exciting venues for PA applications in neuroscience. [ABSTRACT FROM AUTHOR]

With the increasing popularity of Android smartphones, malware targeting the Android platform is showing explosive growth. Currently, mainstream detection methods use static analysis methods to extract features of the software and apply machine learning algorithms for detection. However, static analysis methods can be less effective when faced with Android malware that employs sophisticated obfuscation techniques such as altering code structure. In order to effectively detect Android malware and improve the detection accuracy, this paper proposes a dynamic detection model for Android malware based on the combination of an Improved Zebra Optimization Algorithm (IZOA) and Light Gradient Boosting Machine (LightGBM) model, called IZOA-LightGBM. By introducing elite opposition-based learning and firefly perturbation strategies, IZOA enhances the convergence speed and search capability of the traditional zebra optimization algorithm. Then, the IZOA is employed to optimize the LightGBM model hyperparameters for the dynamic detection of Android malware multi-classification. The results from experiments indicate that the overall accuracy of the proposed IZOA-LightGBM model on the CICMalDroid-2020, CCCS-CIC-AndMal-2020, and CIC-AAGM-2017 datasets is 99.75%, 98.86%, and 97.95%, respectively, which are higher than the other comparative models. [ABSTRACT FROM AUTHOR]

Simple Summary: When faced with starvation, fish can consume energy reserves and adaptively modify the metabolic responses of main energy substrates for fundamental activity. Carbohydrates and lipids are mobilized preferentially in most fish under starvation. However, the mobilization of endogenous energy in starving fish varies with the species, tissue, and fasting duration. Liver tissue is the primary tissue for energy reserves in multiple fish, particularly lipid-associated components. Therefore, this study was conducted to investigate the phenotypic changes in physiological, metabolic, histological, and molecular characteristics of glucose and lipid metabolism in the liver of Synechogobius hasta experiencing different starvation periods. Hepatic glycogen and triglycerides were concurrently mobilized in S. hasta during starvation, which was accompanied by consistent changes in liver intermediary metabolism enzyme activities and an increase in liver antioxidant capacity to some extent. S. hasta livers exhibited evident vacuolations, larger intercellular spaces, and other microstructural abnormalities from the third day of starvation. Additionally, fasting not only transcriptionally attenuated glucose and lipid anabolism, but also enhanced the catabolic pathway and fatty acid transport in S. hasta liver. These findings may provide preliminary data for further assessing the energy strategy to cope with starvation and the underlying mechanism in S. hasta and other fish species. In this study, the influence of fasting on hepatic glucose and lipid metabolism was explored by examining biochemical, antioxidative, and morphological indicators and transcriptional expression in the liver of javelin goby (Synechogobius hasta) after 0, 3, 7, or 14 days of starvation. Marked reductions in hepatic glycogen and triglycerides occurred from the seventh day of starvation until the end of the trial (p < 0.05). However, no alterations in hepatic cholesterol or protein were detected throughout the entire experiment (p > 0.05). During fasting, the activities of pyruvate kinase, lactate dehydrogenase, and glycogen phosphorylase a all rose firstly and then fell (p < 0.05). The activities of hepatic fatty acid synthase and acetyl-CoA carboxylase were minimized to their lowest levels at the end of food deprivation (p < 0.05), while lipase was elevated after 7–14 days of fasting (p < 0.05). Catalase, glutathione, and the total antioxidative capacity were increased and maintained their higher values in the later stage of fasting (p < 0.05), whereas malondialdehyde was not significantly changed (p > 0.05). Hepatic vein congestion, remarkable cytoplasmic vacuoles, and irregular cell shape were present in S. hasta which endured 3–7 days of fasting and were less pronounced when food shortage was prolonged. In terms of genes associated with glucose and lipid metabolism, the hepatic phosphofructokinase gene was constantly up-regulated during fasting (p < 0.05). However, the mRNA levels of glycogen synthase and glucose-6-phosphatase were obviously lower when the food scarcity extended to 7 days or more (p < 0.05). Fatty acid synthase, stearoyl-CoA desaturase 1, and peroxisome proliferator-activated receptor γ were substantially down-regulated in S. hasta livers after 7–14 days of food deprivation (p < 0.05). However, genes involved in lipolysis and fatty acid transport were transcriptionally enhanced to varying extents and peaked at the end of fasting (p < 0.05). Overall, starvation lasting 7 days or more could concurrently mobilize hepatic carbohydrates and fat as energy resources and diminished their hepatic accumulation by suppressing biosynthesis and enhancing catabolism and transport, ultimately metabolically and structurally perturbing the liver in S. hasta. This work presents preliminary data on the dynamic characteristics of hepatic glucose and lipid metabolism in S. hasta in response to starvation, which may shed light on the sophisticated mechanisms of energetic homeostasis in fish facing nutrient unavailability and may benefit the utilization/conservation of S. hasta. [ABSTRACT FROM AUTHOR]

In this study, the necessity of radiotherapy (RT) for hormone receptor-negative older breast cancer patients after breast-conserving surgery (BCS) was investigated. The data of hormone receptor-negative invasive breast cancer patients who underwent BCS were extracted from the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015. All patients were separated into two groups, namely, the RT group and the no radiotherapy (No RT) group. The 3- and 5-year overall survival (OS) and cancer-specific survival (CSS) rates were compared between the No RT and RT groups after propensity score matching (PSM). The nomograms for predicting the survival of patients were constructed from variables identified by univariate or multivariate Cox regression analysis. A total of 2504 patients were enrolled in the training cohort, and 630 patients were included in the validation cohort. After PSM, 738 patients were enrolled in the No RT group and RT group. We noted that RT can improve survival in hormone receptor-negative older breast cancer patients who undergo BCS. Based on the results of multivariate Cox analysis, age, race, tumour grade, receipt of RT and chemotherapy, pathological T stage, N status, M status and HER2 status were linked to OS and CSS for these patients, and nomograms for predicting OS and CSS were constructed and validated. Moreover, RT improved OS and CSS in hormone receptor-negative older breast cancer patients who underwent BCS. In addition, the proposed nomograms more accurately predicted OS and CSS for hormone receptor-negative older breast cancer patients after BCS. [ABSTRACT FROM AUTHOR]