Prediction of lysine HMGylation sites using multiple feature extraction and fuzzy support vector machine.

Protein 3-hydroxyl-3-methylglutarylation (HMGylation) is newly discovered lysine acylation modification in mitochondrion. The accurate identification of HMGylation sites is the premise and key to further explore the molecular mechanisms of HMGylation. In this study, a novel bioinformatics tool named HMGPred is developed to predict HMGylation sites. Multiple effective features, including amino acid composition, amino acid factors, binary encoding, and the composition of k-spaced amino acid pairs, are integrated to encode HMGylation sites. And F-score feature ranking with incremental feature selection was used to eliminate redundant features. Moreover, a fuzzy support vector machine algorithm is used to effectively reduce the influence of noise problem by assigning different samples to different fuzzy membership degrees. As illustrated by 10-fold cross-validation, HMGPred achieves a satisfactory performance with an area under receiver operating characteristic curve of 0.9110. Feature analysis indicates that some k-spaced amino acid pair features, such as 'KxxxT' and 'DxxxE', play a critical role in the prediction of HMGylation sites. The results of prediction and analysis might be helpful for investigating the mechanisms of HMGylation. For the convenience of experimental researchers, HMGPred is implemented as a web server at http://123.206.31.171/HMGPred/.

Effectiveness of a breastfeeding promotion intervention model based on Society ecosystems Theory for maternal women: a study protocol of randomized controlled trial.

BACKGROUND: Breastfeeding is recognized internationally as the most scientific and effective way to feed infants and young children. According to the World Health Organization in 2022, the exclusive breastfeeding rate within 6 months is 34.1% in China, which is still far from the goal of "more than 60% exclusive breastfeeding rate of infants within 6 months" by 2030 required by China's State Council. It is necessary to promote breastfeeding and provide maternal breastfeeding guidance to increase exclusive breastfeeding. Factors influencing breastfeeding can be explained by the society ecosystems theory, distributed in macro, mezzo and micro systems. The interventions focused on breastfeeding promotion are mainly carried out in the health systems and services, home and family environment, community environment, work environment, policy environment or a combination of these facilities. But there is sparse research on integrating resources in the macro, mezzo and micro systems of maternal breastfeeding processes to promote breastfeeding behavior. A randomized controlled trial will test the effect of a breastfeeding promotion intervention model based on the society ecosystems theory versus usual prenatal and postnatal care on maternal and infant health and the exclusive breastfeeding rate at 6 months. METHODS/DESIGN: The study is a single-blind, parallel design, randomized controlled trial with an intervention group (n = 109) and a control group (n = 109) that compares the effect of a breastfeeding promotion intervention model based on the society ecosystems theory with usual prenatal and postnatal care. The intervention covers macro- (policy, culture), mezzo- (family-hospital-community) and micro- (biological, psychological and social) systems of the maternal breastfeeding process. Infant feeding patterns, neonatal morbidity and physical and mental health of antenatal and postpartum women will be collected at baseline (28 to 35 weeks of gestation), 1-, 4-, and 6-month postpartum. DISCUSSION: This is a multifaceted, multifactorial, and multi-environmental breastfeeding promotion strategy to help mothers and their families learn breastfeeding knowledge and skills. The study provides a new modality for adding breastfeeding interventions to prenatal and postnatal care for healthcare providers in the hospital and the community. TRIAL REGISTRATION: Chinese Clinical Trial Registry at www.chictr.org.cn , ChiCTR2300075795.

Maternal education and support during breastfeeding can increase maternal breastfeeding self-efficacy, promote breastfeeding behaviors, and improve maternal and infant health outcomes. The interventions focused on breastfeeding promotion are mainly carried out in the health systems and services, home and family environment, community environment, work environment, policy environment or a combination of any of these facilities. But there is sparse research on integrating in multifaceted, multifactorial, and multi-environmental resources of maternal breastfeeding processes to help pregnant women and their families learn breastfeeding knowledge and skills. The current study optimizes the existing breastfeeding promotion intervention program and construct a breastfeeding promotion intervention program to correct the public's perception of breastfeeding, increase breastfeeding self-efficacy and improve breastfeeding behavior, thus increasing the breastfeeding duration and improving maternal and infant outcomes. The program includes presenting breastfeeding-related policies and support facilities; prenatal educational sessions combined with theories and skills on breastfeeding, development of lactation, infants feeding and cares for maternal families; postnatal hands-on instruction and WeChat group peer support from hospital; home visits, group counseling and experience sharing from community and one-on-one personalized counseling throughout the intervention. The present study will be conducted to evaluate the effect of breastfeeding promotion intervention including prenatal and postnatal care on the breastfeeding duration, breastfeeding attitudes, knowledge, and self-efficacy, maternal and infant health.

DHHC5 facilitates oligodendrocyte development by palmitoylating and activating STAT3.

Myelin sheath is an important structure to maintain functions of the nerves in central nervous system. Protein palmitoylation has been established as a sorting determinant for the transport of myelin-forming proteins to the myelin membrane, however, its function in the regulation of oligodendrocyte development remains unknown. Here, we show that an Asp-His-His-Cys (DHHC) motif-containing palmitoyl acyltransferases, DHHC5, is involved in the control of oligodendrocyte development. Loss of Zdhhc5 in oligodendrocytes inhibits myelination and remyelination by reducing total myelinating oligodendrocyte population. STAT3 is the primary substrate for DHHC5 palmitoylation in oligodendrocytes. Zdhhc5 ablation reduces STAT3 palmitoylation and suppresses STAT3 phosphorylation and activation. As a result, the transcription of the myelin-related and anti-apoptosis genes is inhibited, leading to suppressed oligodendrocyte development and myelination. Our findings demonstrate a key role DHHC5 in controlling myelinogenesis.

The effect of haptoglobin genotype on the association of asymmetric dimethylarginine and DDAH 1 polymorphism with diabetic macroangiopathy.

BACKGROUND: Dimethylarginine dimethylaminohydrolase (DDAH) 1 maintains the bioavailability of nitric oxide by degrading asymmetric dimethylarginine (ADMA). Here, we aimed to investigate the effect of haptoglobin (Hp) genotype on the association of ADMA and DDAH 1 polymorphism with diabetic macroangiopathy. METHODS: In stage 1, 90 Chinese participants with type 2 diabetes were enrolled to measure a panel of targeted metabolites, including ADMA, using tandem mass spectrometry (BIOCRATES AbsoluteIDQ™ p180 kit). In stage 2, an independent cohort of 2965 Chinese patients with type 2 diabetes was recruited to analyze the effect of Hp genotype on the association between DDAH 1 rs233109 and diabetic macroangiopathy. Hp genotypes were detected using a validated assay based on the TaqMan method. DDAH 1 rs233109 was genotyped by matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy using the MassARRAY platform. RESULTS: In stage 1, serum ADMA levels correlated with common Hp genotypes (ß ± SE = - 0.049 ± 0.023, P = 0.035), but not with diabetic macroangiopathy (P = 0.316). In stage 2, the distribution of DDAH 1 rs233109 genotype frequencies was 15% (CC), 47% (TC), and 38% (TT), which was in Hardy-Weinberg equilibrium (P = 0.948). A significant Hp genotype by rs 233109 genotype interaction effect on diabetic macroangiopathy was found (P = 0.017). After adjusting for confounders, patients homozygous for rs233109 CC were more likely to develop diabetic macroangiopathy than those carrying TT homozygotes in the Hp 2-2 subgroup [odds ratio = 1.750 (95% confidence interval, 1.101-2.783), P = 0.018]. CONCLUSION: Hp genotype affects the association between DDAH 1 rs233109 and diabetic macroangiopathy in Chinese patients with type 2 diabetes.

Prediction of lysine formylation sites using the composition of k-spaced amino acid pairs via Chou's 5-steps rule and general pseudo components.

Lysine formylation is a newly discovered post-translational modification in histones, which plays a crucial role in epigenetics of chromatin function and DNA binding. In this study, a novel bioinformatics tool named CKSAAP_FormSite is proposed to predict lysine formylation sites. An effective feature extraction method, the composition of k-spaced amino acid pairs, is employed to encode formylation sites. Moreover, a biased support vector machine algorithm is proposed to solve the class imbalance problem in the prediction of formylation sites. As illustrated by 10-fold cross-validation, CKSAAP_FormSite achieves an satisfactory performance with an AUC of 0.8234. Therefore, CKSAAP_FormSite can be a useful bioinformatics tool for the prediction of formylation sites. Feature analysis shows that some amino acid pairs, such as 'KA', 'SxxxxK' and 'SxxxA' around formylation sites may play an important role in the prediction. The results of analysis and prediction could offer useful information for elucidating the molecular mechanisms of formylation.

Computational Identification of Lysine Glutarylation Sites Using Positive-Unlabeled Learning.

BACKGROUND: As a new type of protein acylation modification, lysine glutarylation has been found to play a crucial role in metabolic processes and mitochondrial functions. To further explore the biological mechanisms and functions of glutarylation, it is significant to predict the potential glutarylation sites. In the existing glutarylation site predictors, experimentally verified glutarylation sites are treated as positive samples and non-verified lysine sites as the negative samples to train predictors. However, the non-verified lysine sites may contain some glutarylation sites which have not been experimentally identified yet. METHODS: In this study, experimentally verified glutarylation sites are treated as the positive samples, whereas the remaining non-verified lysine sites are treated as unlabeled samples. A bioinformatics tool named PUL-GLU was developed to identify glutarylation sites using a positive-unlabeled learning algorithm. RESULTS: Experimental results show that PUL-GLU significantly outperforms the current glutarylation site predictors. Therefore, PUL-GLU can be a powerful tool for accurate identification of protein glutarylation sites. CONCLUSION: A user-friendly web-server for PUL-GLU is available at http://bioinform.cn/pul_glu/.

Association between serum haptoglobin and carotid arterial functions: usefulness of a targeted metabolomics approach.

BACKGROUND: Serum haptoglobin (Hp) has been closely associated with cardio-cerebrovascular diseases. We investigated a metabolic profile associated with circulating Hp and carotid arterial functions via a targeted metabolomics approach to provide insight into potential mechanisms. METHODS: A total of 240 participants, including 120 patients with type 2 diabetes mellitus (T2DM) and 120 non-diabetes mellitus (non-DM) subjects were recruited in this study. Targeted metabolic profiles of serum metabolites were determined using an AbsoluteIDQ™ p180 Kit (BIOCRATES Life Sciences AG, Innsbruck, Austria). Ultrasound of the bilateral common carotid artery was used to measure intima-media thickness and inter-adventitial diameter. Serum Hp levels were tested by enzyme-linked immunosorbent assay. RESULTS: Serum Hp levels in T2DM patients and non-DM subjects were 103.40 (72.46, 131.99) mg/dL and 100.20 (53.99, 140.66) mg/dL, respectively. Significant differences of 19 metabolites and 17 metabolites were found among serum Hp tertiles in T2DM patients and non-DM subjects, respectively (P < 0.05). Of these, phosphatidylcholine acyl-alkyl C32:2 (PC ae C32:2) was the common metabolite observed in two populations, which was associated with the serum Hp groups and lipid traits (P < 0.05). Furthermore, the metabolite ratios of two acidic amino acids, including aspartate to PC ae C32:2 (Asp/PC ae C32:2) and glutamate to PC ae C32:2 (Glu/PC ae C32:2) were correlated with serum Hp, carotid arterial functions and other biochemical index in both populations significantly (P < 0.05). CONCLUSIONS: Targeted metabolomics analyses might provide a new insight into the potential mechanisms underlying the association between serum Hp and carotid arterial functions.

Identify Lysine Neddylation Sites Using Bi-profile Bayes Feature Extraction via the Chou's 5-steps Rule and General Pseudo Components.

INTRODUCTION: Neddylation is a highly dynamic and reversible post-translational modification. The abnormality of neddylation has previously been shown to be closely related to some human diseases. The detection of neddylation sites is essential for elucidating the regulation mechanisms of protein neddylation. OBJECTIVE: As the detection of the lysine neddylation sites by the traditional experimental method is often expensive and time-consuming, it is imperative to design computational methods to identify neddylation sites. METHODS: In this study, a bioinformatics tool named NeddPred is developed to identify underlying protein neddylation sites. A bi-profile bayes feature extraction is used to encode neddylation sites and a fuzzy support vector machine model is utilized to overcome the problem of noise and class imbalance in the prediction. RESULTS: Matthew's correlation coefficient of NeddPred achieved 0.7082 and an area under the receiver operating characteristic curve of 0.9769. Independent tests show that NeddPred significantly outperforms existing lysine neddylation sites predictor NeddyPreddy. CONCLUSION: Therefore, NeddPred can be a complement to the existing tools for the prediction of neddylation sites. A user-friendly webserver for NeddPred is accessible at 123.206.31.171/NeddPred/.

Mendelian randomization analysis to assess a causal effect of haptoglobin on macroangiopathy in Chinese type 2 diabetes patients.

BACKGROUND: Haptoglobin (Hp) functions as an antioxidant by binding with haemoglobin. We investigated whether serum Hp has a causal effect on macroangiopathy via Mendelian randomization (MR) analysis with common variants of the Hp gene in Chinese patients with type 2 diabetes. METHODS: A total of 5687 type 2 diabetes patients were recruited and genotyped for the Hp gene. Clinical features and vascular imaging tests were applied to diagnose macroangiopathy. The association between common Hp genotypes and macroangiopathy was analyzed in the whole population. Serum Hp levels were measured by enzyme-linked immunosorbent assay in a subset of 935 patients. We individually analyzed the correlations among Hp levels, Hp genotypes and macroangiopathy. Further, 8-hydroxy-2'-deoxyguanosine (8-OHdG), an oxidative marker of DNA damage, was examined to evaluate the levels of oxidative stress. RESULTS: Common Hp genotypes were correlated with macroangiopathy (OR = 1.140 [95% CI 1.005-1.293], P = 0.0410 for the Hp 1 allele). Serum Hp levels were associated with both common Hp genotypes (P = 3.55 × 10-31) and macroangiopathy (OR = 2.123 [95% CI 1.098-4.102], P = 0.0252) in the subset of 935 patients. In the MR analysis, the directional trends of the observed and predicted relationships between common Hp genotypes and macroangiopathy were the same (OR 1.357 and 1.130, respectively). Furthermore, common Hp genotypes and Hp levels were associated with serum 8-OHdG levels (P = 0.0001 and 0.0084, respectively). CONCLUSIONS: Our study provides evidence for a causal relationship between serum Hp levels and macroangiopathy in Chinese type 2 diabetes patients by MR analysis.

Predicting lysine lipoylation sites using bi-profile bayes feature extraction and fuzzy support vector machine algorithm.

Lipoylation is a highly conserved post-translational modification which has been found to be involved in many biological processes and closely associated with various metabolic diseases. The accurate identification of lipoylation sites is necessary to elucidate the underlying molecular mechanisms of lipoylation. As the traditional experimental methods are time consuming and expensive, it is desired to develop computational methods to predict lipoylation sites. In this study, a novel predictor named LipoPred is proposed to predict lysine lipoylation sites. On the one hand, an effective feature extraction method, bi-profile bayes encoding, is employed to encode lipoylation sites. On the other hand, a fuzzy support vector machine algorithm is proposed to solve the class imbalance and noise problem in the prediction of lipoylation sites. As illustrated by 10-fold cross-validation, LipoPred achieves an excellent performance with a Matthew's correlation coefficient of 0.9930. Therefore, LipoPred can be a useful bioinformatics tool for the prediction of lipoylation sites. Feature analysis shows that some residues around lipoylation sites may play an important role in the prediction. The results of analysis and prediction could offer useful information for elucidating the molecular mechanisms of lipoylation. A user-friendly web-server for LipoPred is established at 123.206.31.171/LipoPred/.

Prediction of S-sulfenylation sites using mRMR feature selection and fuzzy support vector machine algorithm.

Cysteine S-sulfenylation is an important protein post-translational modification, which plays a crucial role in transcriptional regulation, cell signaling, and protein functions. To better elucidate the molecular mechanism of S-sulfenylation, it is important to identify S-sulfenylated substrates and their corresponding S-sulfenylation sites accurately. In this study, a novel bioinformatics tool named Sulf_FSVM is proposed to predict S-sulfenylation sites by using multiple feature extraction and fuzzy support vector machine algorithm. On the one hand, amino acid factors, binary encoding, and the composition of k-spaced amino acid pairs features are incorporated to encode S-sulfenylation sites. And the maximum relevance minimum redundancy method are adopted to remove the redundant features. On the other hand, a fuzzy support vector machine algorithm is used to handle the class imbalance and noise problem in S-sulfenylation sites training dataset. As illustrated by 10-fold cross-validation, the performance of Sulf_FSVM achieves a satisfactory performance with a Sensitivity of 73.26%, a Specificity of 70.78%, an Accuracy of 71.07% and a Matthew's correlation coefficient of 0.2971. Independent tests also show that Sulf_FSVM significantly outperforms existing S-sulfenylation sites predictors. Therefore, Sulf_FSVM can be a useful tool for accurate prediction of protein S-sulfenylation sites.

A common glycan structure on immunoglobulin G for enhancement of effector functions.

Antibodies have been developed as therapeutic agents for the treatment of cancer, infection, and inflammation. In addition to binding activity toward the target, antibodies also exhibit effector-mediated activities through the interaction of the Fc glycan and the Fc receptors on immune cells. To identify the optimal glycan structures for individual antibodies with desired activity, we have developed an effective method to modify the Fc-glycan structures to a homogeneous glycoform. In this study, it was found that the biantennary N-glycan structure with two terminal alpha-2,6-linked sialic acids is a common and optimized structure for the enhancement of antibody-dependent cell-mediated cytotoxicity, complement-dependent cytotoxicity, and antiinflammatory activities.

Impaired pancreatic beta cell compensatory function is the main cause of type 2 diabetes in individuals with high genetic risk: a 9 year prospective cohort study in the Chinese population.

AIMS/HYPOTHESIS: We aimed to evaluate the combined effects of type 2 diabetes risk variants on predicting deterioration of blood glucose and progression of beta cell function and insulin sensitivity in a 9 year prospective cohort from the Chinese population. METHODS: We constructed a weighted genetic risk score (GRS) model based on 40 variants associated with type 2 diabetes validated in an established cross-sectional Chinese population (n = 6,822). The weighted scores were categorised into tertiles to assess the predictive capacity for incidence of type 2 diabetes and impaired glucose regulation (IGR), as well as for changes in Stumvoll first- and second-phase insulin secretion indices and Gutt's insulin sensitivity index (ISI) in a community-based 9 year prospective cohort (n = 2,495), including 2,192 individuals with normal glucose tolerance and 303 with IGR at baseline, through logistic, Cox and multiple linear regression tests. RESULTS: Weighted GRS predicted the incidence of type 2 diabetes and IGR in logistic regression (OR 1.236, 95% CI 1.100, 1.389, p = 0.0004) as well as in the Cox model (HR 1.129, 95% CI 1.026, 1.242, p = 0.0128) after adjusting for age, sex, BMI, smoking and alcohol status at baseline. Moreover, we observed that weighted GRS was able to predict deterioration in beta cell function (ß = -0.0480, p = 9.66 × 10(-5) and ß = -0.0303, p = 3.32 × 10(-5) for first- and second-phase insulin secretion, respectively), but not insulin sensitivity (p = 0.3815), during the 9 year follow-up period. CONCLUSIONS/INTERPRETATION: The weighted GRS predicted blood glucose deterioration arising from change in beta cell function in the Chinese population. Individuals in the intermediate- or high-weighted GRS group exhibited progressive deterioration of beta cell function.

Cell-permeable probe for identification and imaging of sialidases.

Alkyne-hinged 3-fluorosialyl fluoride (DFSA) containing an alkyne group was shown to be a mechanism-based target-specific irreversible inhibitor of sialidases. The ester-protected analog DFSA (PDFSA) is a membrane-permeable precursor of DFSA designed to be used in living cells, and it was shown to form covalent adducts with virus, bacteria, and human sialidases. The fluorosialyl-enzyme adduct can be ligated with an azide-annexed biotin via click reaction and detected by the streptavidin-specific reporting signals. Liquid chromatography-mass spectrometry/mass spectrometry analysis on the tryptic peptide fragments indicates that the 3-fluorosialyl moiety modifies tyrosine residues of the sialidases. DFSA was used to demonstrate influenza infection and the diagnosis of the viral susceptibility to the anti-influenza drug oseltamivir acid, whereas PDFSA was used for in situ imaging of the changes of sialidase activity in live cells.

Common variants in or near ZNRF1, COLEC12, SCYL1BP1 and API5 are associated with diabetic retinopathy in Chinese patients with type 2 diabetes.

AIMS/HYPOTHESIS: Three recent genome-wide association studies (GWAS) identified several single-nucleotide polymorphisms (SNPs) with modest effects on diabetic retinopathy in Mexican-American and white patients with diabetes. This study aimed to evaluate the effects of these variants on diabetic retinopathy in Chinese patients with type 2 diabetes. METHODS: A total of 1,972 patients with type 2 diabetes were recruited to this study, including 819 patients with diabetic retinopathy and 1,153 patients with diabetes of ≥5 years duration but without retinopathy. Forty SNPs associated with diabetic retinopathy in three GWAS were genotyped. Fundus photography was performed to diagnose and classify diabetic retinopathy. RESULTS: rs17684886 in ZNRF1 and rs599019 near COLEC12 were associated with diabetic retinopathy (OR 0.812, p = 0.0039 and OR 0.835, p = 0.0116, respectively) and with the severity of diabetic retinopathy (p = 0.0365 and p = 0.0252, respectively, for trend analysis). Sub-analysis in patients with diabetic retinopathy revealed that rs6427247 near SCYL1BP1 (also known as GORAB) and rs899036 near API5 were associated with severe diabetic retinopathy (OR 1.368, p = 0.0333 and OR 0.340, p = 0.0005, respectively). The associations between rs6427247 and rs899036 and severe diabetic retinopathy became more evident after a meta-analysis of published GWAS data (OR 1.577, p = 2.01 × 10(-4) for rs6427247; OR 0.330, p = 5.84 × 10(-7) for rs899036). CONCLUSIONS/INTERPRETATION: We determined that rs17684886 and rs599019 are associated with diabetic retinopathy and that rs6427247 and rs899036 are associated with severe diabetic retinopathy in Chinese patients with type 2 diabetes.

The transcriptional repression activity of STAF65γ is facilitated by promoter tethering and nuclear import of class IIa histone deacetylases.

Aberrant expression levels of transcriptional regulators result in alterations in transcriptional control. STAF65γ is a structural subunit of the GCN5 transcriptional co-activator complex. Reports showed that STAF65γ is highly expressed in several human cancer cells, but the consequences of this aberrant expression pattern remain elusive. Here, we show that the STAF65γ protein is highly expressed in lung adenocarcinoma patients and high levels of STAF65γ correlate with poor prognosis. High levels of STAF65γ cause repression of the c-Myc oncogene through physical association with transcription factor YY1 and co-repressors HDACs. Physical interactions between STAF65γ and class IIa HDACs facilitate nuclear enrichment and regulate the assembly of HDAC complexes. Moreover, SUMOylation of STAF65γ is necessary for maintaining the co-repressor complex containing YY1 and class IIa HDACs at the promoter. Our findings reveal a distinct role of STAF65γ in nuclear import, transcriptional repression, and cell cycle regulation at high levels of expression, which is associated with poor clinical outcomes of lung adenocarcinoma.

C-reactive protein genetic variant is associated with diabetic retinopathy in Chinese patients with type 2 diabetes.

BACKGROUND: Diabetic retinopathy (DR) is an important microvascular complication of diabetes with a high concordance rate in patients with diabetes. Inflammation is supposed to participate in the development of DR. This study aimed to investigate whether genetic variants of CRP are associated with DR. METHODS: A total of 1,018 patients with type 2 diabetes were recruited in this study. Of these patients, 618 were diagnosed with DR, 400 were patients with diabetes for over 10 years but without DR, considered as cases and controls for DR, respectively. Four tagging SNPs (rs2808629, rs3093077, rs1130864 and rs2808634) within CRP region were genotyped for all the participants. Fundus photography was performed for diagnosis and classification for DR. RESULTS: rs2808629 was significantly associated with increased susceptibility to DR (odds ratio 1.296, 95% CI 1.076-1.561, P = 0.006, empirical P = 0.029, for G allele). This association remained significant after adjustment for confounding factors (odds ratio 1.261, 95% CI 1.022-1.555, P = 0.030). CONCLUSIONS: In this study, we found CRP rs2808629 was associated with DR in the Chinese patients with type 2 diabetes.