Improving PTM Site Prediction by Coupling of Multi-Granularity Structure and Multi-Scale Sequence Representation

Protein post-translational modification (PTM) site prediction is a fundamental task in bioinformatics. Several computational methods have been developed to predict PTM sites. However, existing methods ignore the structure information and merely utilize protein sequences. Furthermore, designing a more fine-grained structure representation learning method is urgently needed as PTM is a biological event that occurs at the atom granularity. In this paper, we propose a PTM site prediction method by Coupling of Multi-Granularity structure and Multi-Scale sequence representation, PTM-CMGMS for brevity. Specifically, multigranularity structure-aware representation learning is designed to learn neighborhood structure representations at the amino acid, atom, and whole protein granularity from AlphaFold predicted structures, followed by utilizing contrastive learning to optimize the structure representations.Additionally, multi-scale sequence representation learning is used to extract context sequence information, and motif generated by aligning all context sequences of PTM sites assists the prediction. Extensive experiments on three datasets show that PTM-CMGMS outperforms the state-of-the-art methods

The Top-level Institutional Design on the Perfection & Expansion of VAT Reform Pilot

The VAT Pilot Reform has deepened the tax reform and adjustment, and also brought significant reform to the tax law system, tax institution and the whole economic, societal, and political institutions. In fact, a lot of unpredicted problems arose during the process of VAT Reform. For example, the doubt of legitimacy and constitutionality in this reform, the implementation of structural tax cuts in enterprises, the revenue allocation between central and local government, the principle of tax fairness and the reliance interests relationship between both sides as prime examples. Consequently, we must understand that only by improving tax legislation and specific institution design on structural tax cuts and enhancing the supporting measures of VAT Reform under the guidance of Constitution and Law can we really achieve the VAT Reform purposes. Key words: VAT pilot reform; Structural tax cuts; Top-level institutional desig

Chronic Alcohol Causes Alteration of Lipidome Profiling in Brain

Much efforts have been tried to clarify the molecular mechanism of alcohol-induced brain damage from the perspective of genome and protein; however, the effect of chronic alcohol exposure on global lipid profiling of brain is unclear. In the present study, by using Q-TOF/MS-based lipidomics approach, we investigated the comprehensive lipidome profiling of brain from the rats orally administrated with alcohol daily, continuously for one year. Through systematically analysis of all lipids in prefrontal cortex (PFC) and striatum region, we found that long-term alcohol exposure profoundly modified brain lipidome profiling. Notably, three kinds of lipid classes, glycerophospholipid (GP), glycerolipid (GL) and fatty acyls (FA), were significantly increased in these two brain regions. Interestingly, most of the modified lipids were involved in synthetic pathways of endoplasmic reticulum (ER), which may result in ER stress-related metabolic disruption. Moreover, alcohol-modified lipid species displayed long length of carbon chain with high degree of unsaturation. Taken together, our results firstly present that chronic alcohol exposure markedly modifies brain lipidomic profiling, which may activate ER stress and eventually result in neurotoxicity. These findings provide a new insight into the mechanism of alcohol-related brain damage.Peer reviewe

INTEnsive care bundle with blood pressure reduction in acute cerebral hemorrhage trial (INTERACT3): Study protocol for a pragmatic stepped-wedge cluster-randomized controlled trial

Background: Early intensive blood pressure (BP) lowering remains the most promising treatment for acute intracerebral hemorrhage (ICH), despite discordant results between clinical trials and potential variation in the treatment effects by approach to control BP. As the third in a series of clinical trials on this topic, the INTEnsive care bundle with blood pressure Reduction in Acute Cerebral hemorrhage Trial (INTERACT3) aims to determine the effectiveness of a goal-directed care bundle protocol of early physiological control (intensive BP lowering, glycemic control, and pyrexia treatment) and reversal of anticoagulation, in acute ICH.Methods: INTERACT3 is a pragmatic, international, multicenter, stepped-wedge (4 phases/3 steps), cluster-randomized controlled trial to determine the effectiveness of a multifaceted care package in adult (age ≥ 18 years) patients (target 8360) with acute ICH (\u3c 6 h of onset) recruited from 110 hospitals (average of 19 consecutive patients per phase) in low- and middle-income countries. After a control phase, each hospital implements the intervention (intensive BP lowering, target systolic \u3c 140 mmHg; glucose control, target 6.1-7.8 mmol/L and 7.8-10.0 mmol/L in those without and with diabetes mellitus, respectively; anti-pyrexia treatment to target body temperature ≤ 37.5 °C; and reversal of anticoagulation, target international normalized ratio \u3c 1.5 within 1 h). Information will be obtained on demographic and baseline clinical characteristics, in-hospital management, and 7-day outcomes. Central trained blinded assessors will conduct telephone interviews to assess physical function and health-related quality of life at 6 months. The primary outcome is the modified Rankin scale (mRS) at 6 months analyzed using ordinal logistic regression. The sample size of 8360 subjects provides 90% power (α = 0.05) to detect a 5.6% absolute improvement (shift) in the primary outcome of the intervention versus control standard care, with various assumptions.Discussion: As the largest clinical trial in acute ICH, INTERACT3 is on schedule to provide an assessment of the effectiveness of a widely applicable goal-directed care bundle for a serious condition in which a clearly proven treatment has yet to be established.Trial registration: ClinicalTrials.gov NCT03209258. Registered on 1 July 2017. Chinese Trial Registry ChiCTR-IOC-17011787. Registered on 28 June 2017

Mitigation mechanism of zinc oxide nanoparticles on cadmium toxicity in tomato

Cadmium (Cd) pollution seriously reduces the yield and quality of vegetables. Reducing Cd accumulation in vegetables is of great significance for improving food safety and sustainable agricultural development. Here, using tomato as the material, we analyzed the effect of foliar spraying with zinc oxide nanoparticles (ZnO NPs) on Cd accumulation and tolerance in tomato seedlings. Foliar spraying with ZnO NPs improved Cd tolerance by increasing photosynthesis efficiency and antioxidative capacity, while it reduced Cd accumulation by 40.2% in roots and 34.5% in leaves but increased Zn content by 33.9% in roots and 78.6% in leaves. Foliar spraying with ZnO NPs also increased the contents of copper (Cu) and manganese (Mn) in the leaves of Cd-treated tomato seedlings. Subsequent metabonomic analysis showed that ZnO NPs exposure alleviated the fluctuation of metabolic profiling in response to Cd toxicity, and it had a more prominent effect in leaves than in roots. Correlation analysis revealed that several differentially accumulated metabolites were positively or negatively correlated with the growth parameters and physiol-biochemical indexes. We also found that flavonoids and alkaloid metabolites may play an important role in ZnO NP-alleviated Cd toxicity in tomato seedlings. Taken together, the results of this study indicated that foliar spraying with ZnO NPs effectively reduced Cd accumulation in tomato seedlings; moreover, it also reduced oxidative damage, improved the absorption of trace elements, and reduced the metabolic fluctuation caused by Cd toxicity, thus alleviating Cd-induced growth inhibition in tomato seedlings. This study will enable us to better understand how ZnO NPs regulate plant growth and development and provide new insights into the use of ZnO NPs for improving growth and reducing Cd accumulation in vegetables

Who is the main caregiver of the mother during the doing-the-month : is there an association with postpartum depression?

Background: To examine the relationship between the main caregiver during the “doing-the-month” (a traditional Chinese practice which a mother is confined at home for 1 month after giving birth) and the risk of postpartum depression (PPD) in postnatal women. Methods: Participants were postnatal women stayed in hospital and women who attended the hospital for postpartum examination, at 14–60 days after delivery from November 1, 2013 to December 30, 2013. Postpartum depression status was assessed using the Edinburgh Postnatal Depression Scale. Univariate and multivariable logistic regressions were used to identify the associations between the main caregiver during “doing-the-month” and the risk of PPD in postnatal women. Results: One thousand three hundred twenty-five postnatal women with a mean (SD) age of 28 (4.58) years were included in the analyses. The median score (IQR) of PPD was 6.0 (2, 10) and the prevalence of PPD was 27%. Of these postnatal women, 44.5% were cared by their mother-in-law in the first month after delivery, 36.3% cared by own mother, 11.1% by “yuesao” or “maternity matron” and 8.1% by other relatives. No association was found between the main caregivers and the risk of PPD after multiple adjustments. Conclusions: Although no association between the main caregivers and the risk of PPD during doing-the-month was identified, considering the increasing prevalence of PPD in Chinese women, and the contradictions between traditional culture and latest scientific evidence for some of the doing-the-month practices, public health interventions aim to increase the awareness of PPD among caregivers and family members are warranted

Advances in the Application of Machine Learning to Microbial Structure and Quality Control of Traditional Fermented Foods

The unique flavor properties and rich nutrients of traditional fermented food are closely related to its complex and variable microbial structure, which also makes it difficult to control the quality of final fermented product. In order to explore the changes of microbial structure and sensory property and nutritional property in the process of food fermentation and the internal relationship between them, the data analysis process is a key step. Therefore, it is necessary to establish a fast and accurate data analysis method for quality control of fermented food. Machine learning has the advantages of high-dimensional simplification rate, large data throughput and high prediction accuracy, showing great application potential in the field of quality control of fermented food. Hence, machine learning has become one of the research hotspots. This paper reviews the application of machine learning in the quality control of fermented food. On the basis of an overview of common models of machine learning, this paper systematically summarizes the application of machine learning in the prediction of microbial structure evolution, flavor compound composition analysis and customization of personalized consumption in the process of food fermentation. The problems and developmental trends in the application of machine learning to quality control of traditional fermented food are summarized and prospected. Although the application of machine learning in fermented food is still confined by the problems such as insufficient general applicability of the model, limited quality indicators, and limited personalized consumption scenario, etc., with the iterative update of the technical model, the adaptation for multi-factors and whole process, and the application expansion in the background of personalized consumption, machine learning will show a greater value for practical application in the field of fermented food. The purpose of this study is to provide guidance for the further application of machine learning in the standardized and controllable production of traditional fermented food

ALS-Associated E478G Mutation in Human OPTN (Optineurin) Promotes Inflammation and Induces Neuronal Cell Death

Amyotrophic Lateral Sclerosis (ALS) is a group of neurodegenerative disorders that featured with the death of motor neurons, which leads to loss of voluntary control on muscles. The etiologies vary among different subtypes of ALS, and no effective management or medication could be provided to the patients, with the underlying mechanisms incompletely understood yet. Mutations in human Optn (Optineurin), particularly E478G, have been found in many ALS patients. In this work, we report that NF-κB activity was increased in Optn knockout (Optn−/−) MEF (mouse embryonic fibroblast) cells expressing OPTN of different ALS-associated mutants especially E478G. Inflammation was significantly activated in mice infected with lenti-virus that allowed overexpression of OPTNE478G mutation in the motor cortex, with marked increase in the secretion of pro-inflammatory cytokines as well as neuronal cell death. Our work with both cell and animal models strongly suggested that anti-inflammation treatment could represent a powerful strategy to intervene into disease progression in ALS patients who possess the distinctive mutations in OPTN gene

Short-chain fatty acids in breast milk and their relationship with the infant gut microbiota

IntroductionThe short-chain fatty acids (SCFAs) contained in breast milk play a key role in infant growth, affecting metabolism and enhancing intestinal immunity by regulating inflammation.MethodsIn order to examine the associations between the microbiota and SCFA levels in breast milk, and explore the roles of SCFAs in regulating the infant gut microbiota, we enrolled 50 paired mothers and infants and collected both breast milk and infant fecal samples. Breast milk SCFA contents were determined by UPLC-MS, and whole genome shotgun sequencing was applied to determine the microbial composition of breast milk and infant feces. The SCFA levels in breast milk were grouped into tertiles as high, medium, or low, and the differences of intestinal microbiota and KEGG pathways were compared among groups.ResultsThe results demonstrated that breast milk butyric acid (C4) is significantly associated with Clostridium leptum richness in breastmilk. Additionally, the specific Bifidobacterium may have an interactive symbiosis with the main species of C4-producing bacteria in human milk. Women with a low breast milk C4 tertile are associated with a high abundance of Salmonella and Salmonella enterica in their infants' feces. KEGG pathway analysis further showed that the content of C4 in breast milk is significantly correlated with the infants' metabolic pathways of lysine and arginine biosynthesis.DiscussionThis study suggests that interactive symbiosis of the microbiota exists in breast milk. Certain breast milk microbes could be beneficial by producing C4 and further influence the abundance of certain gut microbes in infants, playing an important role in early immune and metabolic development