OsMKK1 is a novel element that positively regulates the Xa21-mediated resistance response to Xanthomonas oryzae pv. oryzae in rice.

KEY MESSAGE: OsMKK1, a MAPK gene, positively regulates rice Xa21-mediated resistance response and also plays roles in normal growth and development process of rice. The mitogen-activated protein kinase (MAPK) cascade was highly conserved among eukaryotes, which played crucial roles in plant responses to pathogen infection. Bacterial blight is the most devastating bacterial disease. Xa21 confers broad-spectrum resistance to Xanthomonas oryzae pv. Oryzae (Xoo). This study identified that the transcription level of OsMKK1 was up-regulated in resistant response against Xoo, thus overexpression (OsMKK1-OX) and RNA interference (OsMKK1-RNAi) transgenic rice lines under the background of Xa21 was constructed. Compared with recipient control plants 4021, the OsMKK1-OX lines significantly enhanced disease resistance to Xoo, on the contrary, the resistance of OsMKK1-RNAi lines was weakened, demonstrated that OsMKK1 played a positive role in Xa21-mediated disease resistance pathway. A number of pathogenesis-related proteins, including PR1A, PR2 and PR10A showed enhanced expression in OsMKK1-OX lines, supported that these PR genes may be regulated by OsMKK1 to participate in the defense responses. In addition, the agronomic traits of OsMKK1 transgenic plants were affected. Overall, these results revealed the role of OsMKK1 in Xa21-mediated resistance against Xoo and in the normal growth and development process in rice.

AMPFinder: A computational model to identify antimicrobial peptides and their functions based on sequence-derived information.

Antimicrobial peptides (AMPs) called host defense peptides have existed among all classes of life with 5-100 amino acids generally and can kill mycobacteria, envelop viruses, bacteria, fungi, cancerous cells and so on. Owing to the non-drug resistance of AMP, it has been a wonderful agent to find novel therapies. Therefore, it is urgent to identify AMPs and predict their function in a high-throughput way. In this paper, we propose a cascaded computational model to identify AMPs and their functional type based on sequence-derived and life language embedding, called AMPFinder. Compared with other state-of-the-art methods, AMPFinder obtains higher performance both on AMP identification and AMP function prediction. AMPFinder shows better performance with improvement of F1-score (1.45%-6.13%), MCC (2.92%-12.86%) and AUC (5.13%-8.56%) and AP (9.20%-21.07%) on an independent test dataset. And AMPFinder achieve lower bias of R2 on a public dataset by 10-fold cross-validation with an improvement of (18.82%-19.46%). The comparison with other state-of-the-art methods shows that AMP can accurately identify AMP and its function types. The datasets, source code and user-friendly application are available at https://github.com/abcair/AMPFinder.

Postoperative alterations of sagittal cervical alignment and risk factors for cervical kyphosis in 124 Lenke 1 adolescent idiopathic scoliosis patients.

BACKGROUND: This study aims to analyze postoperative changes of cervical sagittal curvature and to identify independent risk factors for cervical kyphosis in Lenke type 1 adolescent idiopathic scoliosis (AIS) patients. METHODS: A total of 124 AIS patients who received all-pedicle-screw instrumentation were enrolled. All patients were followed up for at least 2 years. The following parameters were measured preoperatively, immediately after the operation, and at the last follow-up: pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS), lumbar lordosis (LL), thoracic kyphosis (TK), global thoracic kyphosis (GTK), proximal thoracic kyphosis (PrTK), T1-slope, cervical lordosis (CL), McGregor slope (McGS), sagittal vertical axis (SVA), C2-7 SVA (cSVA), and main thoracic angle (MTA). Statistical analysis was performed to evaluate postoperative alterations of and correlations between the parameters and to identify risk factors for cervical kyphosis. Statistical significance was set at P < 0.05. RESULTS: After the operation, PrTK and T1-slope significantly increased (3.01 ± 11.46, 3.8 ± 10.76, respectively), cervical lordosis improved with an insignificant increase (- 2.11 ± 13.47, P = 0.154), and MTA, SS, and LL decreased significantly (- 33.68 ± 15.35, - 2.98 ± 8.41, 2.82 ± 9.92, respectively). Intergroup comparison and logistic regression revealed that preoperative CK > 2.35° and immediate postoperative GTK < 27.15° were independent risk factors for final cervical kyphosis, and △T1-slope < 4.8° for a kyphotic trend. CONCLUSIONS: Postoperative restoration of thoracic kyphosis, especially proximal thoracic kyphosis, and T1-slope play a central role in cervical sagittal compensation. Preoperative CK, postoperative small GTK, and insufficient △T1-slope are all independent risk factors for cervical decompensation.

PPSNO: A Feature-Rich SNO Sites Predictor by Stacking Ensemble Strategy from Protein Sequence-Derived Information.

The protein S-nitrosylation (SNO) is a significant post-translational modification that affects the stability, activity, cellular localization, and function of proteins. Therefore, highly accurate prediction of SNO sites aids in grasping biological function mechanisms. In this document, we have constructed a predictor, named PPSNO, forecasting protein SNO sites using stacked integrated learning. PPSNO integrates multiple machine learning techniques into an ensemble model, enhancing its predictive accuracy. First, we established benchmark datasets by collecting SNO sites from various sources, including literature, databases, and other predictors. Second, various techniques for feature extraction are applied to derive characteristics from protein sequences, which are subsequently amalgamated into the PPSNO predictor for training. Five-fold cross-validation experiments show that PPSNO outperformed existing predictors, such as PSNO, PreSNO, pCysMod, DeepNitro, RecSNO, and Mul-SNO. The PPSNO predictor achieved an impressive accuracy of 92.8%, an area under the curve (AUC) of 96.1%, a Matthews correlation coefficient (MCC) of 81.3%, an F1-score of 85.6%, an SN of 79.3%, an SP of 97.7%, and an average precision (AP) of 92.2%. We also employed ROC curves, PR curves, and radar plots to show the superior performance of PPSNO. Our study shows that fused protein sequence features and two-layer stacked ensemble models can improve the accuracy of predicting SNO sites, which can aid in comprehending cellular processes and disease mechanisms. The codes and data are available at https://github.com/serendipity-wly/PPSNO .

4mCBERT: A computing tool for the identification of DNA N4-methylcytosine sites by sequence- and chemical-derived information based on ensemble learning strategies.

N4-methylcytosine (4mC) is an important DNA chemical modification pattern which is a new methylation modification discovered in recent years and plays critical roles in gene expression regulation, defense against invading genetic elements, genomic imprinting, and so on. Identifying 4mC site from DNA sequence segment contributes to discovering more novel modification patterns. In this paper, we present a model called 4mCBERT that encodes DNA sequence segments by sequence characteristics including one-hot, electron-ion interaction pseudopotential, nucleotide chemical property, word2vec and chemical information containing physicochemical properties (PCP), chemical bidirectional encoder representations from transformers (chemical BERT) and employs ensemble learning framework to develop a prediction model. PCP and chemical BERT features are firstly constructed and applied to predict 4mC sites and show positive contributions to identifying 4mC. For the Matthew's Correlation Coefficient, 4mCBERT significantly outperformed other state-of-the-art models on six independent benchmark datasets including A. thaliana, C. elegans, D. melanogaster, E. coli, G. Pickering, and G. subterraneous by 4.32 % to 24.39 %, 2.52 % to 31.65 %, 2 % to 16.49 %, 6.63 % to 35.15, 8.59 % to 61.85 %, and 8.45 % to 34.45 %. Moreover, 4mCBERT is designed to allow users to predict 4mC sites and retrain 4mC prediction models. In brief, 4mCBERT shows higher performance on six benchmark datasets by incorporating sequence- and chemical-driven information and is available at http://cczubio.top/4mCBERT and https://github.com/abcair/4mCBERT.

DeepDRP: Prediction of intrinsically disordered regions based on integrated view deep learning architecture from transformer-enhanced and protein information.

Intrinsic disorder in proteins, a widely distributed phenomenon in nature, is related to many crucial biological processes and various diseases. Traditional determination methods tend to be costly and labor-intensive, therefore it is desirable to seek an accurate identification method of intrinsically disordered proteins (IDPs). In this paper, we proposed a novel Deep learning model for Intrinsically Disordered Regions in Proteins named DeepDRP. DeepDRP employed an innovative TimeDistributed strategy and Bi-LSTM architecture to predict IDPs and is driven by integrated view features of PSSM, Energy-based encoding, AAindex, and transformer-enhanced embeddings including DR-BERT, OntoProtein, Prot-T5, and ESM-2. The comparison of different feature combinations indicates that the transformer-enhanced features contribute far more than traditional features to predict IDPs and ESM-2 accounts for a larger contribution in the pre-trained fusion vectors. The ablation test verified that the TimeDistributed strategy surely increased the model performance and is an efficient approach to the IDP prediction. Compared with eight state-of-the-art methods on the DISORDER723, S1, and DisProt832 datasets, the Matthews correlation coefficient of DeepDRP significantly outperformed competing methods by 4.90 % to 36.20 %, 11.80 % to 26.33 %, and 4.82 % to 13.55 %. In brief, DeepDRP is a reliable model for IDP prediction and is freely available at https://github.com/ZX-COLA/DeepDRP.

LncCat: An ORF attention model to identify LncRNA based on ensemble learning strategy and fused sequence information.

Background: Long non-coding RNA (lncRNA) is one of the most essential forms of transcripts, playing crucial regulatory roles in the development of cancers and diseases without protein-coding ability. It was assumed that short ORFs (sORFs) in lncRNA were weak to translate proteins. However, recent research has shown that sORFs can encode peptides, which increases the difficulty to identify lncRNA. Therefore, identifying lncRNAs with sORFs facilitates finding novel regulatory factors. Results: In this paper, we propose LncCat for identifying lncRNA based on category boosting (CatBoost) and ORF-attention features. LncCat combines five types of features to encode transcript sequences and employs CatBoost to build a prediction model. In addition, the visualization comparison reveals that the ORF-attention features between lncRNAs and protein-coding transcripts are significantly distinct. The comparison results show that LncCat outperforms competing methods on several benchmark datasets. For Matthew's Correlation Coefficient (MCC), LncCat achieves 0.9503, 0.9219, 0.8591, 0.8672, and 0.9047 on the human, mouse, zebrafish, wheat, and chicken datasets, with improvements ranging from 1.90% to 7.82%, 1.49-17.63%, 6.11-21.50%, 3.02-51.64% and 5.35-26.90%, respectively. Moreover, LncCat dramatically improves the MCC by at least 11.90%, 12.96% and 42.61% on sORF test datasets of human, mouse, and zebrafish, respectively. Conclusions: Experiments indicate that LncCat performs better both on long ORF and sORF datasets, and ORF-attention features show positive effects on predicting lncRNA. In brief, LncCat is a reliable method for identifying lncRNA. Additionally, a user-friendly web server is developed for academics at http://cczubio.top/lnccat.

Clinical Application of the Roussouly Classification in the Sagittal Balance Reconstruction of 101 Adolescent Idiopathic Scoliosis Patients.

PURPOSE: Although Roussouly classification has been widely used in spinal surgery, it was mainly applied to degenerative scoliosis patients and correlational studies concerning adolescent idiopathic scoliosis (AIS) are still insufficient. This retrospective study explored the clinical application of Roussouly classification in surgeries and prognosis prediction for AIS. METHODS: This clinical research selected 101 AIS patients who received surgeries between August 2005 and November 2019. Whole spine standing radiographs were obtained for each patient preoperatively, postoperatively, and at the last follow-up (>24 months). All patients were classified into "theoretical types" and "current types." Patients were further divided into mismatch or match groups based on the consistency of their current type and theoretical type. The main parameters include: proximal junctional angle (PJA), pelvic incidence (PI), sacral slope (SS), pelvic tilt (PT), fixed thoracic kyphosis (TK), global TK, fixed lumbar lordosis (LL), global LL, thoracic tilt, proximal thoracic alignment (PTA), lumbar tilt, spino-sacral angle (SSA), and spinal tilt (ST). RESULTS: A total of 47.5% of AIS patients were subject to a preoperative mismatch of Roussouly classification. There was a significant difference in PI-LL between the preoperative mismatch and match groups (p = 0.008). There was a significant difference in the rate of PI-LL deformity between the match and mismatch groups with a preoperative mismatch (p = 0.037). A significant difference in thoracic tilt was observed between the postoperative mismatch and match groups (p = 0.019). The preoperative mismatch group has a higher risk of postoperative PI-LL malformation than match group (OR = 2.303, 95% CI: 1.026, 5.165). When mismatch occurred postoperatively, there were significant differences between groups in the rate of pelvic deformity (p = 0.002) and PI-LL deformity (p = 0.025) at the last follow-up. Compared with the postoperative match group, mismatch group had an increased risk of pelvic deformity (OR = 5.029, 95% CI: 1.618, 15.629) and PJK deformity (OR = 3.017, 95% CI: 1.709, 11.375) at the last follow-up. Short Form-36 and Scoliosis Research Society 22 score of the match group was significantly higher than that of the mismatch group at the last follow-up. CONCLUSION: The Roussouly classification mismatch before or after operation leads to increased risks of PI-LL deformity and pelvis deformity postoperatively or at the follow-up, which seriously worsens the clinical symptoms and prognosis of patients. Therefore, recovering to the theoretical type in Roussouly classification may effectively improve patients' prognosis.

Risk Factors and Three Radiological Predictor Models for the Progression of Proximal Junctional Kyphosis in Adult Degenerative Scoliosis Following Posterior Corrective Surgery: 113 Cases With 2-years Minimum Follow-Up.

STUDY DESIGN: Retrospective cohort study. OBJECTIVE: To identify risk factors and predictive models for proximal junctional kyphosis (PJK) in a long-term follow-up of patients with adult degenerative scoliosis (ADS) following posterior corrective surgeries. MATERIALS AND METHODS: A consecutive 113 ADS patients undergoing posterior corrective surgery between January 2008 and April 2019 with minimum 2-year follow-up were included. All patients underwent preoperative, postoperative, and final follow-up by X-ray imaging. Multivariate logistic analysis was performed on various risk factors and radiological predictor models. RESULTS: PJK was identified radiographically in 46.9% of patients. Potential risk factors for PJK included postoperative thoracic kyphosis (TK) (P < .05), final follow-up Pelvic Tilt (PT) (P < .05), PT changes at final follow-up (P < .05), age over 55 years old at the surgery (P < .05), theoretical thoracic kyphosis-actual thoracic kyphosis mismatch (TK mismatch) (P < .05) and theoretical lumbar lordosis-acutal lumbar lordosis mismatch (LL mismatch) (P < .05). As for the predictive models, PJK was predictive by the following indicators: preoperative global sagittal alignment ≥45° (Model 1), postoperative pelvic incidence-lumbar lordosis mismatch (PI-LL)≤10° and postoperative PI-LL overcorrection (Model 2), and TK+LL≥0° (Model 3) (P < .05). Postoperative TK mismatch (OR = 1.064) was independent as risk factors for PJK, with the cut-off values respectively set at -28.56° to predict occurrence of PJK. CONCLUSION: The risk of radiographic PJK increases with an age over 55 years old and higher postoperative TK. In addition, postoperative TK mismatch is an independent risk factor for developing PJK. All three predictive models could effectively indicate the occurrence of PJK.

Physical therapy and orthopaedic equipment-induced reduction in the biomechanical risk factors related to knee osteoarthritis: a systematic review and Bayesian network meta-analysis of randomised controlled trials.

OBJECTIVE: Are physical therapy or orthopaedic equipment efficacious in reducing the biomechanical risk factors in people with tibiofemoral osteoarthritis (OA)? Is there a better therapeutic intervention than others to improve these outcomes? DESIGN: Systematic review with network meta-analysis (NMA) of randomised trials. DATA SOURCES: PubMed, Web of Science, Cochrane Library, Embase and MEDLINE were searched through January 2021. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: We included randomised controlled trials exploring the benefits of using physical therapy or orthopaedic equipment in reducing the biomechanical risk factors which included knee adduction moment (KAM) and knee adduction angular impulse (KAAI) in individuals with tibiofemoral OA. DATA EXTRACTION AND SYNTHESIS: Two authors extracted data independently and assessed risk of bias. We conducted an NMA to compare multiple interventions, including both direct and indirect evidences. Heterogeneity was assessed (sensitivity analysis) and quantified (I2 statistic). Grading of Recommendations Assessment, Development and Evaluation assessed the certainty of the evidence. RESULTS: Eighteen randomised controlled trials, including 944 participants, met the inclusion criteria, of which 14 trials could be included in the NMA. Based on the collective probability of being the overall best therapy for reducing the first peak KAM, lateral wedge insoles (LWI) plus knee brace was closely followed by gait retraining, and knee brace only. Although no significant difference was observed among the eight interventions, variable-stiffness shoes and neuromuscular exercise exhibited an increase in the first peak KAM compared with the control condition group. And based on the collective probability of being the overall best therapy for reducing KAAI, gait retraining was followed by LWI only, and lower limb exercise. CONCLUSION: The results of our study support the use of LWI plus knee brace for reducing the first peak KAM. Gait retraining did not rank highest but it influenced both KAM and KAAI and therefore it was the most recommended therapy for reducing the biomechanical risk factors.

Rice MPK17 Plays a Negative Role in the Xa21-Mediated Resistance Against Xanthomonas oryzae pv. oryzae.

Rice bacterial blight, caused by Xanthomonas oryzae pv. oryzae (Xoo), is one of the most serious diseases affecting rice production worldwide. Xa21 was the first disease resistance gene cloned in rice, which encodes a receptor kinase and confers broad resistance against Xoo stains. Dozens of components in the Xa21-mediated pathway have been identified in the past decades, however, the involvement of mitogen-activated protein kinase (MAPK) genes in the pathway has not been well described. To identify MAPK involved in Xa21-mediated resistance, the level of MAPK proteins was profiled using Western blot analysis. The abundance of OsMPK17 (MPK17) was found decreased during the rice-Xoo interaction in the background of Xa21. To investigate the function of MPK17, MPK17-RNAi and over-expression (OX) transgenic lines were generated. The RNAi lines showed an enhanced resistance, while OX lines had impaired resistance against Xoo, indicating that MPK17 plays negative role in Xa21-mediated resistance. Furthermore, the abundance of transcription factor WRKY62 and pathogenesis-related proteins PR1A were changed in the MPK17 transgenic lines when inoculated with Xoo. We also observed that the MPK17-RNAi and -OX rice plants showed altered agronomic traits, indicating that MPK17 also plays roles in the growth and development. On the basis of the current study and published results, we propose a "Xa21-MPK17-WRKY62-PR1A" signaling that functions in the Xa21-mediated disease resistance pathway. The identification of MPK17 advances our understanding of the mechanism underlying Xa21-mediated immunity, specifically in the mid- and late-stages.

Association study of single nucleotide polymorphism in tryptophan hydroxylase 1 gene with adolescent idiopathic scoliosis: A meta-analysis.

BACKGROUND: Adolescent idiopathic scoliosis is a common spinal deformity among children and adolescents worldwide with its etiology uncertain. Over a decade, a single nucleotide polymorphism rs10488682 in tryptophan hydroxylase 1 (TPH1) gene has been investigated in several association studies. We perform this study to summarize the current evidence of TPH1 rs10488682 polymorphisms and adolescent idiopathic scoliosis (AIS). METHODS: Six databases were systematically searched: PubMed, Embase, Cochrane Library, Web of Science, Chinese Biomedical Literature, and Wanfang database. Eligible case-control studies related to TPH1 and AIS were selected. Reference lists of them were reviewed for more available studies. Two authors independently screened and evaluated the literature and extracted data. The odds ratios and 95% confidence intervals were derived in association tests. Subgroup analysis was conducted by ethnicity. Sensitivity analysis was performed to examine the stability of the overall results. RESULTS: A total of 1006 cases and 1557 controls in 3 independent studies were included for meta-analysis. Statistical significance was discovered in heterozygote model (AT vs AA: OR = 1.741, 95%Cl = 1.100-2.753, P = .018 < .05, I2 = 0%), recessive model (AA vs AT + TT: OR = 0.640, 95%Cl = 0.414-0.990, P = .045 < .05, I2 = 0%) and over-dominant model (AT vs AA + TT: OR = 1.366, 95%Cl = 1.115-1.673, P = .003 < .05, I2 = 84.7%) in overall populations. Similar associations were also found in the Caucasian population. No significant associations were found in other genotypic comparisons and allelic comparisons. CONCLUSIONS: Statistically significant correlations were discovered between the TPH1 rs10488682 polymorphisms and AIS. Heterozygous AT genotype seems to be risky with an over-dominant effect. Ethnicity appears to modify the disease association. REGISTRATION: Not applicable.

A Premature Rise of Luteinizing Hormone Is Associated With a Reduced Cumulative Live Birth Rate in Patients ≥37 Years Old Undergoing GnRH Antagonist In Vitro Fertilization Cycles.

This is a retrospective cohort study included 1021 patients underwent a flexible GnRH antagonist IVF protocol from January 2017 to December 2017 to explore the effect of a premature rise in luteinizing hormone (LH) level on the cumulative live birth rate. All patients included received the first ovarian stimulation and finished a follow-up for 3 years. A premature rise in LH was defined as an LH level >10 IU/L or >50% rise from baseline during ovarian stimulation. The cumulative live birth rate was calculated as the number of women who achieved a live birth divided by the total number of women who had either delivered a baby or had used up all their embryos received from the first stimulated cycle. In the advanced patients (≥37 years), the cumulative live birth rate was reduced in patients with a premature rise of LH (ß: 0.20; 95% CI: 0.05-0.88; p=0.03), compared to patients (≥37 years) without the premature LH rise. The incidence of premature LH rise is associated with decreased rates of cumulative live birth rate in patients of advanced age (≥37 years) and aggravated the reduced potential of embryos produced by the advanced age, not the number of embryos.