Deep neural network models for cell type prediction based on single-cell Hi-C data.

BACKGROUND: Cell type prediction is crucial to cell type identification of genomics, cancer diagnosis and drug development, and it can solve the time-consuming and difficult problem of cell classification in biological experiments. Therefore, a computational method is urgently needed to classify and predict cell types using single-cell Hi-C data. In previous studies, there is a lack of convenient and accurate method to predict cell types based on single-cell Hi-C data. Deep neural networks can form complex representations of single-cell Hi-C data and make it possible to handle the multidimensional and sparse biological datasets. RESULTS: We compare the performance of SCANN with existing methods and analyze the model by using five different evaluation metrics. When using only ML1 and ML3 datasets, the ARI and NMI values of SCANN increase by 14% and 11% over those of scHiCluster respectively. However, when using all six libraries of data, the ARI and NMI values of SCANN increase by 63% and 88% over those of scHiCluster respectively. These findings show that SCANN is highly accurate in predicting the type of independent cell samples using single-cell Hi-C data. CONCLUSIONS: SCANN enhances the training speed and requires fewer resources for predicting cell types. In addition, when the number of cells in different cell types was extremely unbalanced, SCANN has higher stability and flexibility in solving cell classification and cell type prediction using the single-cell Hi-C data. This predication method can assist biologists to study the differences in the chromosome structure of cells between different cell types.

[Retracted] SOX2 knockdown inhibits the migration and invasion of basal cell carcinoma cells by targeting the SRPK1­mediated PI3K/AKT signaling pathway.

[This retracts the article DOI: 10.3892/ol.2018.9810.].

NPI-DCGNN: An Accurate Tool for Identifying ncRNA-Protein Interactions Using a Dual-Channel Graph Neural Network.

Noncoding RNA (NcRNA)-protein interactions (NPIs) play fundamentally important roles in carrying out cellular activities. Although various predictors based on molecular features and graphs have been published to boost the identification of NPIs, most of them often ignore the information between known NPIs or exhibit insufficient learning ability from graphs, posing a significant challenge in effectively identifying NPIs. To develop a more reliable and accurate predictor for NPIs, in this article, we propose NPI-DCGNN, an end-to-end NPI predictor based on a dual-channel graph neural network (DCGNN). NPI-DCGNN initially treats the known NPIs as an ncRNA-protein bipartite graph. Subsequently, for each ncRNA-protein pair, NPI-DCGNN extracts two local subgraphs centered around the ncRNA and protein, respectively, from the bipartite graph. After that, it utilizes a dual-channel graph representation learning layer based on GNN to generate high-level feature representations for the ncRNA-protein pair. Finally, it employs a fully connected network and output layer to predict whether an interaction exists between the pair of ncRNA and protein. Experimental results on four experimentally validated datasets demonstrate that NPI-DCGNN outperforms several state-of-the-art NPI predictors. Our case studies on the NPInter database further demonstrate the prediction power of NPI-DCGNN in predicting NPIs. With the availability of the source codes (https://github.com/zhangxin11111/NPI-DCGNN), we anticipate that NPI-DCGNN could facilitate the studies of ncRNA interactome by providing highly reliable NPI candidates for further experimental validation.

Dynamic optical coherence elastography for skin burn assessment: A preliminary study on mice model.

Skin burns that include tissue coagulation necrosis imply variations in stiffness. Dynamic phase-sensitive optical coherence elastography (OCE) is used to evaluate the stiffness of burned skin nondestructively in this paper. The homemade dynamic OCE was initially verified through tissue-mimicking phantom experiments regarding Rayleigh wave speed. After being burned with a series of temperatures and durations, the corresponding structure and stiffness variations of mice skin were demonstrated by histological images, optical coherence tomography B-scans, and OCE elastic wave speed maps. The results clearly displayed the variation in elastic properties and stiffness of the scab edge extending in the lateral direction. Statistical analysis revealed that murine skin burned at temperatures exceeding 100°C typically exhibited greater stiffness than skin burned at temperatures below 100°C. The dynamic OCE technique shows potential application for incorporating elasticity properties as a biomechanical extension module to diagnose skin burn injuries.

DeepOCR: A multi-species deep-learning framework for accurate identification of open chromatin regions in livestock.

A wealth of experimental evidence has suggested that open chromatin regions (OCRs) are involved in many critical biological activities, such as DNA replication, enhancer activity, and gene transcription. Accurately identifying OCRs in livestock species can provide critical insights into the distribution and characteristics of OCRs for disease treatment in livestock, thereby improving animal welfare. However, most current machine-learning methods for OCR prediction were originally designed for a limited number of model organisms, such as humans and some model organisms, and thus their performance on non-model organisms, specifically livestock, is often unsatisfactory. To bridge this gap, we propose DeepOCR, a lightweight depth-separable residual network model for predicting OCRs in livestock, including chicken, cattle, and sheep. DeepOCR integrates a single convolution layer and two improved residue structure blocks to extract and learn important features from the input DNA sequences. A fully connected layer was also employed to further process the extracted features and improve the robustness of the entire network. Our benchmarking experiments demonstrated superior prediction performance of DeepOCR compared to state-of-the-art approaches on testing datasets of the three species. The source code of DeepOCR is freely available for academic purposes at https://github.com/jasonzhao371/DeepOCR/. We anticipate DeepOCR servers as a practical and reliable computational tool for OCR-related studies in livestock species.

Vitamin D effects on Chlamydia trachomatis infection: a case-control and experimental study.

Introduction: Vitamin D deficiency is the most common nutritional deficiency worldwide. Chronic vitamin D deficiency causes immune system dysfunction, which increases susceptibility to pathogens such as bacteria, especially intracellular parasites, and viruses. Chlamydia trachomatis (C. t) is an obligate intracellular parasitic bacterium that causes a variety of sequelae. We speculated that vitamin D might be associated with C. t infection. This study aimed to address this gap in knowledge by investigating the relationship between vitamin D and C. t infection using both in vitro and in vivo models. Methods and results: The addition of calcitriol to McCoy cell culture in vitro delayed and reduced the quantity and volume of inclusions compared to the control group. Macrophages of peritoneally lavaged mice co-cultured with McCoy decreased the infection rate and delayed the appearance of inclusions. In mice models of vitamin D deficiency, mice in the VD-group exhibited more severe genital tract inflammation and a longer duration of infection after inoculation with C. t in the genital tract. Supplementing these mice with vitamin D3 during treatment enhanced the therapeutic effect of antibiotics. We also conducted a case-control study involving 174 C. t-positive patients (95 males and 79 females) and 380 healthy volunteers (211 males and 169 females) aged 20-49 from January 2016 to March 15, 2017. Serum 25-(OH)D concentration was measured by assessing morning fasting blood samples of healthy volunteers and C. t-positive patients 1 day before antibiotic treatment and the next day after one course of treatment. The patients were followed up for 1 month and evaluated for recovery. The results showed that vitamin D deficiency was a risk factor for C. t infection and treatment failure. Conclusion: In summary, findings from experimental and clinical studies indicate a close association between vitamin D levels and C. t infection and treatment outcomes. Given the affordability and safety of vitamin D, both healthy individuals and patients should focus on vitamin D intake. Vitamin D supplementation could enhance treatment success and should be used as an adjunctive therapy alongside antibiotic therapy for C. t infections, pending confirmation in larger, prospective, randomized controlled trials.

Identification of cell surface markers for acute myeloid leukemia prognosis based on multi-model analysis.

Given the extremely high inter-patient heterogeneity of acute myeloid leukemia (AML), the identification of biomarkers for prognostic assessment and therapeutic guidance is critical. Cell surface markers (CSMs) have been shown to play an important role in AML leukemogenesis and progression. In the current study, we evaluated the prognostic potential of all human CSMs in 130 AML patients from The Cancer Genome Atlas (TCGA) based on differential gene expression analysis and univariable Cox proportional hazards regression analysis. By using multi-model analysis, including Adaptive LASSO regression, LASSO regression, and Elastic Net, we constructed a 9-CSMs prognostic model for risk stratification of the AML patients. The predictive value of the 9-CSMs risk score was further validated at the transcriptome and proteome levels. Multivariable Cox regression analysis showed that the risk score was an independent prognostic factor for the AML patients. The AML patients with high 9-CSMs risk scores had a shorter overall and event-free survival time than those with low scores. Notably, single-cell RNA-sequencing analysis indicated that patients with high 9-CSMs risk scores exhibited chemotherapy resistance. Furthermore, PI3K inhibitors were identified as potential treatments for these high-risk patients. In conclusion, we constructed a 9-CSMs prognostic model that served as an independent prognostic factor for the survival of AML patients and held the potential for guiding drug therapy.

Copper-Catalyzed Enantioselective 1,2-Allylation of Azadienes with Allylboronates.

Catalytic asymmetric 1,2-allylation of aurone-derived azadienes is very difficult to achieve due to the driving force for aromatization and the greater steric hindrance of 1,2-addition compared with 1,4-addition. By taking advantage of the ability of nitrogen ligated metal complexes, we successfully demonstrated the first example of copper-catalyzed 1,2-allylation of azadienes with allylboronates for the highly enantioselective synthesis of homoallylic amines. Meanwhile, the enantioenriched 1,4-addition products could also be obtained through a subsequent 3,3-sigmatropic rearrangement of the 1,2-addition products. Extensive DFT calculations were carried out to elucidate the origins of high regioselectivity (1,2- vs 1,4-) and enantioselectivity.

CTISL: a dynamic stacking multi-class classification approach for identifying cell types from single-cell RNA-seq data.

MOTIVATION: Effective identification of cell types is of critical importance in single-cell RNA-sequencing (scRNA-seq) data analysis. To date, many supervised machine learning-based predictors have been implemented to identify cell types from scRNA-seq datasets. Despite the technical advances of these state-of-the-art tools, most existing predictors were single classifiers, of which the performances can still be significantly improved. It is therefore highly desirable to employ the ensemble learning strategy to develop more accurate computational models for robust and comprehensive identification of cell types on scRNA-seq datasets. RESULTS: We propose a two-layer stacking model, termed CTISL (Cell Type Identification by Stacking ensemble Learning), which integrates multiple classifiers to identify cell types. In the first layer, given a reference scRNA-seq dataset with known cell types, CTISL dynamically combines multiple cell-type-specific classifiers (i.e. support-vector machine and logistic regression) as the base learners to deliver the outcomes for the input of a meta-classifier in the second layer. We conducted a total of 24 benchmarking experiments on 17 human and mouse scRNA-seq datasets to evaluate and compare the prediction performance of CTISL and other state-of-the-art predictors. The experiment results demonstrate that CTISL achieves superior or competitive performance compared to these state-of-the-art approaches. We anticipate that CTISL can serve as a useful and reliable tool for cost-effective identification of cell types from scRNA-seq datasets. AVAILABILITY AND IMPLEMENTATION: The webserver and source code are freely available at http://bigdata.biocie.cn/CTISLweb/home and https://zenodo.org/records/10568906, respectively.

Copper-Catalyzed Asymmetric Allylation of N-Aryl Aldimines.

The copper-catalyzed enantioselective allylation reaction of N-aryl aldimines has been developed using a combination of Cu(OAc)2 and SPINOL-based phosphonamidite. This protocol significantly broadens the substrate scope, such that imines bearing various ortho-substituents on the N-aryl were converted smoothly into homoallylic amines in up to 99% yield and 98% ee. Taking advantage of the diversity of the N-aryl motif, three kinds of N-heterocyclic compounds were constructed, respectively, from the corresponding homoallylic amines in merely one step.

Nickel-Catalyzed Three-Component Alkylarylation of Alkenyl N-Heteroarenes.

A nickel-catalyzed three-component alkylarylation of alkenyl N-heteroarenes with α-bromocarboxylates and aryl boronic acids is reported. The protocol provides a new method to access a variety of N-heteroarene substituted diarylalkanes in moderate to good yields. It features mild reaction conditions, cheap nickel catalyst, readily available substrates, and broad substrate scope.

Efficacy and Safety of Spesolimab in Patients with Generalized Pustular Psoriasis: A Subgroup Analysis of Chinese Patients in the Effisayil 1 Trial.

INTRODUCTION: Generalized pustular psoriasis (GPP) is a rare and potentially life-threatening skin disease. The global Effisayil 1 study investigated the efficacy and safety of spesolimab, a humanized monoclonal antibody targeting the IL-36 receptor, in patients experiencing GPP flare. This analysis aimed to explore the efficacy and safety of spesolimab in the Chinese subgroup of Effisayil 1. METHODS: Effisayil 1 was a multicenter, randomized, double-blind, placebo-controlled phase II study. Eligible patients with a GPP flare were randomly assigned (2:1) to receive a single intravenous dose of spesolimab (900 mg) or placebo on day 1. On day 8, patients who had persistent symptoms that met a predefined criterion could receive open-label spesolimab. After day 8, patients with recurrent flares following clinical response could receive rescue treatment with open-label spesolimab. The primary end point was a Generalized Pustular Psoriasis Physician Global Assessment (GPPGA) pustulation sub-score of 0 at week 1. The key secondary end point was a GPPGA total score of 0 or 1 at week 1. RESULTS: Eleven Chinese patients were randomized, with five patients receiving spesolimab and six receiving placebo. At week 1, 60.0% (3/5) of patients in the spesolimab group and 16.7% (1/6) of patients in the placebo group achieved a GPPGA pustulation sub-score of 0 (risk difference 43.3%; 95% CI -22.6, 86.2); 60.0% and 16.7% of patients in the spesolimab and placebo group, respectively, achieved a GPPGA total score 0 or 1 (risk difference 43.3%; 95% CI -22.6, 86.2). Overall, four patients in each group of the spesolimab and the placebo groups reported at least one adverse event (AE) by week 1, with two and three reporting drug-related AEs, respectively. One patient reported a serious AE that was not considered to be drug related. No death occurred during the study period. CONCLUSION: In the Chinese subgroup of the Effisayil 1 study, more patients receiving spesolimab experienced lesion clearance than those on placebo at week 1, with an acceptable safety profile that was consistent with the global study population. TRIAL REGISTRATION: NCT03782792.

Single-cell transcriptome analysis indicates fatty acid metabolism-mediated metastasis and immunosuppression in male breast cancer.

Male breast cancer (MBC) is a rare but aggressive malignancy with cellular and immunological characteristics that remain unclear. Here, we perform transcriptomic analysis for 111,038 single cells from tumor tissues of six MBC and thirteen female breast cancer (FBC) patients. We find that that MBC has significantly lower infiltration of T cells relative to FBC. Metastasis-related programs are more active in cancer cells from MBC. The activated fatty acid metabolism involved with FASN is related to cancer cell metastasis and low immune infiltration of MBC. T cells in MBC show activation of p38 MAPK and lipid oxidation pathways, indicating a dysfunctional state. In contrast, T cells in FBC exhibit higher expression of cytotoxic markers and immune activation pathways mediated by immune-modulatory cytokines. Moreover, we identify the inhibitory interactions between cancer cells and T cells in MBC. Our study provides important information for understanding the tumor immunology and metabolism of MBC.

Synthesis of Cyclopenta[b]indoles via Sc(III)-Catalyzed Annulation of Vinyl Diazoacetates with Indole-Derived Unsaturated Imines.

A Lewis acid Sc(OTf)3-catalyzed annulation reaction of vinyl diazoacetates with in situ formed α,ß-unsaturated imines for the preparation of indole-fused tricyclic rings has been reported. This strategy involves a sequential addition/rebound addition process of vinyl diazoacetates and an in situ dedinitrogenation. This annulation protocol features low-cost catalysts, mild reaction conditions, and facilely prepared substrates.

Cyclization of Vinyl Diazo Compounds with Benzofuran-Derived Azadienes Enabled by NaBArF4.

An unprecedented cycloaddition of vinyl diazo compounds with benzofuran-derived azadienes catalyzed by rarely independently used NaBArF4 has been established. Benzofuran-fused hydropyridines were constructed with excellent yields and high diastereoselectivity via a Na+-catalyzed inverse-electron-demand aza-Diels-Alder reaction. Notably, this transformation also features good compatibility with a one-pot protocol to deliver the spiro[benzofuran-cyclopentene] skeleton, as well as perfect atom economy and simple reaction conditions.

MSINGB: A Novel Computational Method Based on NGBoost for Identifying Microsatellite Instability Status from Tumor Mutation Annotation Data.

Microsatellite instability (MSI), a vital mutator phenotype caused by DNA mismatch repair deficiency, is frequently observed in several tumors. MSI is recognized as a critical molecular biomarker for diagnosis, prognosis, and therapeutic selection in several cancers. Identifying MSI status for current gold standard methods based on experimental analysis is laborious, time-consuming, and costly. Although several computational methods based on machine learning have been proposed to identify MSI status, we need to further understand which machine learning model would favor identification for MSI and which feature subset is strongly related to MSI. On this basis, more effective machine learning-based methods can be developed to improve the performance of MSI status identification. In this work, we present MSINGB, an NGBoost-based method for identifying MSI status from tumor somatic mutation annotation data. MSINGB first evaluates the prediction performance of 11 popular machine learning algorithms and 9 deep learning models to identify MSI. Among 20 models, NGBoost, a novel natural gradient boosting method, achieves the overall best performance. MSINGB then introduces two feature selection strategies to find the compact feature subset, which is strongly related to MSI, and employs the SHAP approach to interpreting how selected features impact the model prediction. MSINGB achieves a better prediction performance on both the tenfold cross-validation test and independent test compared with state-of-the-art methods.

Efficacy and Safety of AbobotulinumtoxinA for the Treatment of Glabellar Lines in Chinese Patients: A Pivotal, Phase 3, Randomized, Double-Blind and Open-Label Phase Study.

BACKGROUND: Various botulinumtoxinA formulations are approved for glabellar lines treatment worldwide, including abobotulinumtoxinA (Dysport®). OBJECTIVES: Assess abobotulinumtoxinA superiority versus placebo and non-inferiority versus active comparator (onabotulinumtoxinA; Botox®), for the treatment of Chinese patients with moderate/severe glabellar lines. METHODS: Phase 3, randomized study (NCT02450526) comprising a double-blind (cycle 1) phase and an open-label (cycles 2-5) phase. Patients received abobotulinumtoxinA 50 units or matching placebo (5:1), active comparator (onabotulinumtoxinA 20 units) or matching placebo (5:1). In cycles 2-5, eligible patients were retreated with abobotulinumtoxinA only. Responders had glabellar lines of none/mild severity. PRIMARY ENDPOINT: responder rates at cycle 1, day 29 at maximum frown with abobotulinumtoxinA versus placebo (for superiority; by investigator's live assessment [ILA] and subject's self-assessment [SSA]), and versus active comparator (for non-inferiority; by ILA). Treatment-emergent adverse events were recorded. RESULTS: Overall, 520 patients were randomized. Superiority and non-inferiority, respectively, were demonstrated for abobotulinumtoxinA versus placebo (ILA, SSA; both p < 0.0001) and abobotulinumtoxinA versus active comparator. AbobotulinumtoxinA efficacy was maintained over open-label cycles; median time to onset of efficacy was 2.0 days. After 6 months, 17% of patients treated with abobotulinumtoxinA remained responders. AbobotulinumtoxinA was well-tolerated. Safety results were in line with the known profile of abobotulinumtoxinA; adverse events rate decreased with repeated treatment. CONCLUSIONS: After a single injection, abobotulinumtoxinA demonstrated superiority versus placebo and non-inferiority versus onabotulinumtoxinA for the treatment of moderate-to-severe glabellar lines in Chinese patients. Multiple injections of abobotulinumtoxinA demonstrated efficacy and safety in the treatment of glabellar lines in Chinese patients. LEVEL OF EVIDENCE I: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Botulinum toxin injections can be used to smooth frown lines that appear between the eyebrows (known as glabellar lines) in patients who have moderate or severe frown lines. This study looked at how injections of a botulinum toxin (abobotulinumtoxinA [aboBoNT-A]) could help with smoothing frown lines in patients from China compared with an injection of another botulinum toxin called onabotulinumtoxinA (onaBoNT-A) or placebo (saltwater, no treatment). The study included 520 patients from China, 18­65 years old, who had moderate or severe frown lines. All patients received a first injection of either aboBoNT-A, onaBoNT-A, or saltwater, and were studied for 12 weeks. After the first injection, patients could receive up to four more injections of aboBoNT-A, given at 12-week intervals, if their frown lines became moderate or severe again. Most patients (92%) had not previously received any botulinum toxin injections. The results showed that single and repeat injections of aboBoNT-A helped to smooth moderate and severe frown lines. The researchers found that after a single injection, aboBoNT-A was superior to no treatment and was similar to onaBoNT-A. Patients recorded a response to aboBoNT-A after 2 days and the response lasted for 6 months in 17% of patients. The effect on frown lines was maintained after repeat injections and aboBoNT-A was well tolerated by patients. These results suggest that aboBoNT-A is a suitable treatment for smoothing frown lines in patients from China with moderate to severe frown lines.