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Abstract Advances in single-cell transcriptomics provide an unprecedented opportunity to explore complex biological processes. However, computational methods for analyzing single-cell transcriptomics still have room for improvement especially in dimension reduction, cell clustering, and cell–cell communication inference. Herein, we propose a versatile method, named DcjComm, for comprehensive analysis of single-cell transcriptomics. DcjComm detects functional modules to explore expression patterns and performs dimension reduction and clustering to discover cellular identities by the non-negative matrix factorization-based joint learning model. DcjComm then infers cell–cell communication by integrating ligand-receptor pairs, transcription factors, and target genes. DcjComm demonstrates superior performance compared to state-of-the-art methods.

Abstract The inference of cell–cell communication (CCC) is crucial for a better understanding of complex cellular dynamics and regulatory mechanisms in biological systems. However, accurately inferring spatial CCCs at single-cell resolution remains a significant challenge. To address this issue, we present a versatile method, called DeepTalk, to infer spatial CCC at single-cell resolution by integrating single-cell RNA sequencing (scRNA-seq) data and spatial transcriptomics (ST) data. DeepTalk utilizes graph attention network (GAT) to integrate scRNA-seq and ST data, which enables accurate cell-type identification for single-cell ST data and deconvolution for spot-based ST data. Then, DeepTalk can capture the connections among cells at multiple levels using subgraph-based GAT, and further achieve spatially resolved CCC inference at single-cell resolution. DeepTalk achieves excellent performance in discovering meaningful spatial CCCs on multiple cross-platform datasets, which demonstrates its superior ability to dissect cellular behavior within intricate biological processes.

Seafloor landing research is crucial for underwater robots tasked with long-term fixed-point observation missions, particularly those requiring prolonged operations on the seabed. Developing safe and stable landing technology is essential for the success of these missions. This paper introduces a novel underwater robot by establishing its dynamic model and using the arbitrary Lagrangian–Eulerian (ALE) method to conduct a comprehensive study of its deep-sea landing process. Prior to detailed parameter analysis, the ALE algorithm’s effectiveness and accuracy were validated through experimental data and simulation results from previous studies. This study examines the penetration depth and force conditions during the landing process by varying factors such as seabed soil properties, landing velocity, and the robot’s mass. Findings indicate that seabed soil properties significantly influence penetration depth and pressure, with variations in soil density and strength affecting the robot’s landing behavior. In contrast, the robot’s mass has a relatively minor effect, suggesting that the choice of structural materials has limited impact on penetration depth and pressure during landing. Additionally, landing velocity was found to significantly affect penetration depth and pressure; higher velocities result in greater penetration depths and pressures. This highlights the importance of controlling landing velocity to minimize impact forces and protect the robot. The results of this study provide theoretical support and data for developing deep-sea landing technology for novel underwater robots and inform the selection of structural materials, ensuring the successful execution of long-term fixed-point observation missions in deep-sea environments.

Circulating tumor cells (CTCs) that undergo epithelial-to-mesenchymal transition (EMT) can provide valuable information regarding metastasis and potential therapies. However, current studies on the EMT overlook alternative splicing. Here, we used single-cell full-length transcriptome data and mRNA sequencing of CTCs to identify stage-specific alternative splicing of partial EMT and mesenchymal states during pancreatic cancer metastasis. We classified definitive tumor and normal epithelial cells via genetic aberrations and demonstrated dynamic changes in the epithelial-mesenchymal continuum in both epithelial cancer cells and CTCs. We provide the landscape of alternative splicing in CTCs at different stages of EMT, uncovering cell-type-specific splicing patterns and splicing events in cell surface proteins suitable for therapies. We show that MBNL1 governs cell fate through alternative splicing independently of changes in gene expression and affects the splicing pattern during EMT. We found a high frequency of events that contained multiple premature termination codons and were enriched with C and G nucleotides in close proximity, which influence the likelihood of stop codon readthrough and expand the range of potential therapeutic targets. Our study provides insights into the EMT transcriptome’s dynamic changes and identifies potential diagnostic and therapeutic targets in pancreatic cancer.

Ethnopharmacological relevance: Murrayae Folium et Cacumen (MFC) is a plant considered to be a traditional Chinese medicine with culinary value as well. The dry leaves and twigs of Murraya paniculata and M. exotica are used to treat stomach aches, rheumatism, toothaches, swelling, and insect and snake bites. They are also used to prepare spicy chicken dishes.Aim of the review: This review comprehensively summarizes the available information on the botanical characterization, phytochemistry, pharmacological activities, pharmacodynamics, pharmacokinetics, and toxicity of MFC.Methods: Relevant scientific literature up to August 2023 was included in the study. Chinese and English studies on MFC were collected from databases, including PubMed, Elsevier, Web of Science, Springer, Science Direct, Wiley, ACS, and CNKI (Chinese). Doctoral and Master’s dissertations were also included.Results: In total, 720 compounds have been identified and reported in the literature, including flavonoids, coumarins, alkaloids, sterols, phenylpropenols, organic acids, spirocyclopentenones, and volatile oils. Flavonoids and coumarins are the two most important bioactive compounds responsible for these pharmacological activities. MFC has anti-inflammatory, anti-bacterial, anti-microbial, anti-diabetic, anti-tumor, anti-oxidant, anti-depressant, potential anti-Alzheimer’s disease, chondroprotective, and analgesic properties. The pharmacological effects include interrupting the STAT3/NF-κB/COX-2 and EGFR signaling pathways, downregulating EpCAM expression, inhibiting NF-κB and ERK signals, inhibiting the EP/cAMP/PKA signaling pathway and miR-29a/Wnt/β-catenin signaling activity, and upregulating Foxo3a expression.Conclusion: This review demonstrates that the chemical constituents, pharmacological activities, pharmacodynamics, pharmacokinetics, and toxicity of MFC support its use in traditional Chinese botanical medicines. MFC contains a wide range of chemical compounds. Flavonoids and coumarins promote strong pharmacological activity and, are low-toxicity natural phytomedicines that are widely used in medicine, food, ornamentation, and cosmetics, making MFC a promising compound for development and use in the treatment of several medical conditions.

Tumor-infiltrating T cells are essential players in tumor immunotherapy. Great progress has been achieved in the investigation of T cell heterogeneity. However, little is well known about the shared characteristics of tumor-infiltrating T cells across cancers. In this study, we conduct a pan-cancer analysis of 349,799 T cells across 15 cancers. The results show that the same T cell types had similar expression patterns regulated by specific transcription factor (TF) regulons across cancers. Multiple T cell type transition paths were consistent in cancers. We found that TF regulons associated with CD8+ T cells transitioned to terminally differentiated effector memory (Temra) or exhausted (Tex) states were associated with patient clinical classification. We also observed universal activated cell-cell interaction pathways of tumor-infiltrating T cells in all cancers, some of which specifically mediated crosstalk in certain cell types. Moreover, consistent characteristics of TCRs in the aspect of variable and joining region genes were found across cancers. Overall, our study reveals common features of tumor-infiltrating T cells in different cancers and suggests future avenues for rational, targeted immunotherapies.

Abstract Background Given their potent antioxidation properties, carotenoids play a role in delaying and preventing dementia and mild cognitive impairment (MCI). However, observational studies have found inconsistent results regarding the associations between blood carotenoid levels and the risk of dementia and MCI. We conducted this systematic review and meta-analysis to investigate the relationship between blood carotenoid levels and the risk of dementia and MCI. Methods A systematic search was performed in the Web of Science, PubMed, Embase, and Cochrane Library electronic databases to retrieve relevant English articles published from their inception until February 23, 2023. Study quality was assessed by the Newcastle-Ottawa scale. Standardized mean differences (SMDs) and 95% confidence intervals (CIs) were pooled using random-effect meta-analyses. Ultimately, 23 studies (n = 6610) involving 1422 patients with dementia, 435 patients with MCI, and 4753 controls were included. Results Our meta-analysis showed that patients with dementia had lower blood lycopene (SMD: -0.521; 95%CI: -0.741, -0.301), α-carotene (SMD: -0.489; 95%CI: -0.697, -0.281), β-carotene (SMD: -0.476; 95%CI: -0.784, -0.168), lutein (SMD: -0.516; 95%CI: -0.753, -0.279), zeaxanthin (SMD: -0.571; 95%CI: -0.910, -0.232) and β-cryptoxanthin (SMD: -0.617; 95%CI: -0.953, -0.281) than the controls. Our results indicated that blood carotenoid levels were significantly lower in patients with dementia than in controls, despite high heterogeneity across the studies. Owing to insufficient data, we did not observe a similar and stable relationship between blood carotenoid levels and MCI. Conclusions Our meta-analysis indicated that lower blood carotenoid levels may be a risk factor for dementia and MCI.

BackgroundFibroblast activation protein (FAP) is a cell-surface serine protease that has both dipeptidyl peptidase as well as endopeptidase activities and could cleave substrates at post-proline bond. Previous findings showed that FAP was hard to be detected in normal tissues but significantly up-regulated in remodeling sites like fibrosis, atherosclerosis, arthritis and embryonic tissues. Though increasing evidence has demonstrated the importance of FAP in cancer progression, no multifactorial analysis has been developed to investigate its function in gastrointestinal cancers until now.MethodsBy comprehensive use of datasets from The Cancer Genome Atlas (TCGA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), scTIME Portal and Human Protein Atlas (HPA), we evaluated the carcinogenesis potential of FAP in gastrointestinal cancers, analyzing the correlation between FAP and poor outcomes, immunology in liver, colon, pancreas as well as stomach cancers. Then liver cancer was selected as example to experimentally validate the pro-tumor and immune regulative role of FAP in gastrointestinal cancers.ResultsFAP was abundantly expressed in gastrointestinal cancers, such as LIHC, COAD, PAAD and STAD. Functional analysis indicated that the highly-expressed FAP in these cancers could affect extracellular matrix organization process and interacted with genes like COL1A1, COL1A2, COL3A1 and POSTN. In addition, it was also observed that FAP was positively correlated to M2 macrophages infiltration across these cancers. To verify these findings in vitro, we used LIHC as example and over-expressed FAP in human hepatic stellate LX2 cells, a main cell type that produce FAP in tumor tissues, and then investigate its role on LIHC cells as well as macrophages. Results showed that the medium from FAP-over-expressed LX2 cells could significantly promote the motility of MHCC97H and SK-Hep1 LIHC cells, increase the invasion of THP-1 macrophages and induce them into pro-tumor M2 phenotype.ConclusionIn summary, we employed bioinformatic tools and experiments to perform a comprehensive analysis about FAP. Up-regulation of FAP in gastrointestinal cancers was primarily expressed in fibroblasts and contributes to tumor cells motility, macrophages infiltration and M2 polarization, revealing the multifactorial role of FAP in gastrointestinal cancers progression.

Abstract Painting is the largest energy consumption unit in ship repair enterprises, with annual electrical energy costs amounting to millions of dollars. The energy-saving model of painting business based on artificial intelligence, Internet of Vehicles (IoV) and big data technologies has become a current research hot spot. This paper takes a cargo ship of Youlian Shipyard as an example to improve the quality of special coating construction, reduce cost and increase efficiency. In the process of special coating construction, a comprehensive analysis of equipment usage in different compartments is carried out, and a compartment energy consumption analysis model based on combined weighting and Gray Fuzzy Comprehensive Evaluation is proposed. The model uses factors such as energy consumption, hours, and number of devices as evaluation indicators. Based on the fuzzy comprehensive evaluation, the gray correlation coefficients and comprehensive weights were weighted to obtain the final comprehensive evaluation results of each planning scheme, and then compare them to determine the optimal scheme. The results show that the grey fuzzy comprehensive evaluation model with combined weighting has better results than other models, and the evaluation results are scientific and reasonable. It has certain application value in multi-objective scheme optimization.

Nucleus basalis of Meynert (NbM), one of the earliest targets of Alzheimer's disease (AD), may act as a seed for pathological spreading to its connected regions. However, the underlying basis of regional vulnerability to NbM dysconnectivity remains unclear. NbM functional dysconnectivity was assessed using resting-state fMRI data of health controls and mild cognitive impairment (MCI) patients from the Alzheimer's disease Neuroimaging Initiative (ADNI2/GO phase). Transcriptional correlates of NbM dysconnectivity was explored by leveraging public intrinsic and differential post-mortem brain-wide gene expression datasets from Allen Human Brain Atlas (AHBA) and Mount Sinai Brain Bank (MSBB). By constructing an individual-level tissue-specific gene set risk score (TGRS), we evaluated the contribution of NbM dysconnectivity-correlated gene sets to change rate of cerebral spinal fluid (CSF) biomarkers during preclinical stage of AD, as well as to MCI onset age. An independent cohort of health controls and MCI patients from ADNI3 was used to validate our main findings. Between-group comparison revealed significant connectivity reduction between the right NbM and right middle temporal gyrus in MCI. This regional vulnerability to NbM dysconnectivity correlated with intrinsic expression of genes enriched in protein and immune functions, as well as with differential expression of genes enriched in cholinergic receptors, immune, vascular and energy metabolism functions. TGRS of these NbM dysconnectivity-correlated gene sets are associated with longitudinal amyloid-beta change at preclinical stages of AD, and contributed to MCI onset age independent of traditional AD risks. Our findings revealed the transcriptional vulnerability to NbM dysconnectivity and their crucial role in explaining preclinical amyloid-beta change and MCI onset age, which offer new insights into the early AD pathology and encourage more investigation and clinical trials targeting NbM.

Abstract Background Small interfering RNA (siRNA) has emerged as a kind of promising therapeutic agents for cancer therapy. However, the off-target effect and degradation are the main challenges for siRNAs delivery. Herein, an enzyme-free DNA amplification strategy initiated by a specific endogenous microRNA has been developed for in situ generation of siRNAs with enhanced gene therapy effect on cervical carcinoma. Methods This strategy contains three DNA hairpins (H1, H2/PS and H3) which can be triggered by microRNA-21 (miR-21) for self-assembly of DNA nanowheels (DNWs). Notably, this system is consistent with the operation of a DNA logic circuitry containing cascaded “AND” gates with feedback mechanism. Accordingly, a versatile biosensing and bioimaging platform is fabricated for sensitive and specific analysis of miR-21 in HeLa cells via fluorescence resonance energy transfer (FRET). Meanwhile, since the vascular endothelial growth factor (VEGF) antisense and sense sequences are encoded in hairpin reactants, the performance of this DNA circuit leads to in situ assembly of VEGF siRNAs in DNWs, which can be specifically recognized and cleaved by Dicer for gene therapy of cervical carcinoma. Results The proposed isothermal amplification approach exhibits high sensitivity for miR-21 with a detection limit of 0.25 pM and indicates excellent specificity to discriminate target miR-21 from the single-base mismatched sequence. Furthermore, this strategy achieves accurate and sensitive imaging analysis of the expression and distribution of miR-21 in different living cells. To note, compared to naked siRNAs alone, in situ siRNA generation shows a significantly enhanced gene silencing and anti-tumor effect due to the high reaction efficiency of DNA circuit and improved delivery stability of siRNAs. Conclusions The endogenous miRNA-activated DNA circuit provides an exciting opportunity to construct a general nanoplatform for precise cancer diagnosis and efficient gene therapy, which has an important significance in clinical translation. Graphic abstract

Objective Using the Comprehensive Score for Financial Toxicity (COST) tool to measure financial toxicity (FT) among nasopharyngeal cancer (NPC) patients in western China and investigate the association between FT and psychological distress.MethodsWe conducted a cross-sectional study of survivors with NPC in a tertiary oncology hospital in China. FT was assessed using the COST (Chinese version), a validated instrument widely used both at home and abroad. The NCCN Distress Thermometer (DT) was used to measure psychological distress. A multivariate logistic regression model was built to determine factors associated with FT, and the Pearson correlation was used to assess the correlation between COST and DT scores.ResultsOf 210 patients included in this study, the mean FT score was 16.3 (median: 22.5, SD: 9.7), and the prevalence of FT was 66.2% (mild FT: 37.1%, moderate FT: 50.5%, severe FT: 2.4%). Suggested by the logistic regression model, 5 variables were associated with increased FT: unemployed, no commercial insurance, receiving lower annual income, advanced cancer, and receiving targeted therapy. The Pearson correlation showed a significantly moderate correlation between financial toxicity and psychological distress (r= -0.587, P < 0.001).ConclusionPatients with nasopharyngeal carcinoma (NPC) in western China demonstrated higher self-reported financial toxicity (FT) associated with factors including unemployed, no commercial insurance, receiving lower annual income, advanced cancer, and receiving targeted therapy. These predictors will help clinicians identify potential patients with FT in advance and conduct effective psychological interventions.

The Sry-related HMG-box (Sox) family is a group of transcriptional regulators that play a critical role in many important developmental processes in both vertebrates and invertebrates. In aquatic animals, the function of Sox genes on sexual development has attracted particular attention. The present study reported on the molecular characterization of a Sox member (PtSoxE) in the swimming crab, Portunus trituberculatus, and tissue distribution analysis showed it was male-specific. Since the highest expression of PtSoxE was found in the androgenic gland (AG), its relation to the insulin-like androgenic gland hormone (IAG) was further investigated. The PtSoxE siRNA caused a significant decrease in IAG expression in both AG and testis, whereas PtSoxE expression could be induced by treating with AG homogenate and rIAG. The result suggested a transcriptional interaction between PtSoxE and IAG. In addition, PtSoxE expression showed a closely positive correlation with several reported spermatogenesis-related genes, suggesting its involvement in the testicular development of P. trituberculatus.

Abstract Given the chronic inflammatory nature of Parkinson’s disease (PD), T cell immunity may be important for disease onset. Here, we performed single-cell transcriptome and TCR sequencing, and conducted integrative analyses to decode composition, function and lineage relationship of T cells in the blood and cerebrospinal fluid of PD. Combined expression and TCR-based lineage tracking, we discovered a large population of CD8+ T cells showing continuous progression from central memory to terminal effector T cells in PD patients. Additionally, we identified a group of cytotoxic CD4+ T cells (CD4 CTLs) remarkably expanded in PD patients, which derived from Th1 cells by TCR-based fate decision. Finally, we screened putative TCR–antigen pairs that existed in both blood and cerebrospinal fluid of PD patients to provide potential evidence for peripheral T cells to participate in neuronal degeneration. Our study provides valuable insights and rich resources for understanding the adaptive immune response in PD.

Abstract Backgroud Cancer stemness is associated with metastases in kidney renal clear cell carcinoma (KIRC) and negatively correlates with immune infiltrates. Recent stemness evaluation methods based on the absolute expression have been proposed to reveal the relationship between stemness and cancer. However, we found that existing methods do not perform well in assessing the stemness of KIRC patients, and they overlooked the impact of alternative splicing. Alternative splicing not only progresses during the differentiation of stem cells, but also changes during the acquisition of the stemness features of cancer stem cells. There is an urgent need for a new method to predict KIRC-specific stemness more accurately, so as to provide help in selecting treatment options. Methods The corresponding RNA-Seq data were obtained from the The Cancer Genome Atlas (TCGA) data portal. We also downloaded stem cell RNA sequence data from the Progenitor Cell Biology Consortium (PCBC) Synapse Portal. Independent validation sets with large sample size and common clinic pathological characteristics were obtained from the Gene Expression Omnibus (GEO) database. we constructed a KIRC-specific stemness prediction model using an algorithm called one-class logistic regression based on the expression and alternative splicing data to predict stemness indices of KIRC patients, and the model was externally validated. We identify stemness-associated alternative splicing events (SASEs) by analyzing different alternative splicing event between high- and low- stemness groups. Univariate Cox and multivariable logistic regression analysisw as carried out to detect the prognosis-related SASEs respectively. The area under curve (AUC) of receiver operating characteristic (ROC) was performed to evaluate the predictive values of our model. Results Here, we constructed a KIRC-specific stemness prediction model with an AUC of 0.968,and to provide a user-friendly interface of our model for KIRC stemness analysis, we have developed KIRC Stemness Calculator and Visualization (KSCV), hosted on the Shiny server, can most easily be accessed via web browser and the url https://jiang-lab.shinyapps.io/kscv/ . When applied to 605 KIRC patients, our stemness indices had a higher correlation with the gender, smoking history and metastasis of the patients than the previous stemness indices, and revealed intratumor heterogeneity at the stemness level. We identified 77 novel SASEs by dividing patients into high- and low- stemness groups with significantly different outcome and they had significant correlations with expression of 17 experimentally validated splicing factors. Both univariate and multivariate survival analysis demonstrated that SASEs closely correlated with the overall survival of patients. Conclusions Basing on the stemness indices, we found that not only immune infiltration but also alternative splicing events showed significant different at the stemness level. More importantly, we highlight the critical role of these differential alternative splicing events in poor prognosis, and we believe in the potential for their further translation into targets for immunotherapy.

Clinical practice shows that when single-target drugs treat multi-factor diseases such as tumors, cardiovascular system and endocrine system diseases, it is often difficult to achieve good therapeutic effects, and even serious adverse reactions may occur. Multi-target drugs can simultaneously regulate multiple links of disease, improve efficacy, reduce adverse reactions, and improve drug resistance. They are ideal drugs for treating complex diseases, and therefore have become the main direction of drug development. At present, some multi-target drugs have been successfully used in many major diseases. Entrectinib is an oral small molecule inhibitor that targets TRK, ROS1, and ALK. It is used to treat locally advanced or metastatic solid tumors with NTRK1/2/3, ROS1 and ALK gene fusion mutations. It can pass through the blood-brain barrier and is the only TRK inhibitor clinically proven to be effective against primary and metastatic brain diseases. In 2019, entrectinib was approved by the FDA to treat adult patients with ROS1-positive metastatic non-small cell lung cancer. Case reports showed that continuous administration of entrectinib was effective and tolerable. In this review, we give a brief introduction to TKK, ROS1 and ALK, and on this basis, we give a detailed and comprehensive introduction to the mechanism of action, pharmacokinetics, pharmacodynamics, clinical efficacy, tolerability and drug interactions of entrectinib.

Abstract Background This study aimed to translate the English version of the supportive care needs scale of head and neck cancer patients (SCNS-HNC) questionnaire into Mandarin and to test the reliability and validity of the SCNS-SF34 and SCNS-HNC module in head and neck cancer patients. Methods The Mandarin version of the Supportive Care Needs Survey Short-Form (SCNS-SF34) and SCNS-HNC scales were used to assess 206 patients with head and neck cancer in Chengdu, China. Among them, 51 patients were re-tested 2 or 3 days after the first survey. The internal consistency of the scale was evaluated by Cronbach’s alpha coefficient, the retest reliability of the scale was evaluated by retest correlation coefficient r, the structural validity of the scale was evaluated by exploratory factor analysis, and the ceiling and floor effects of the scale were evaluated. Results The Mandarin version of the SCNS-HNC had Cronbach’s alpha coefficients greater than 0.700 (0.737 ≤ 0.962) for all of the domains. Except for the psychological demand dimension (r = 0.674) of the SCNS-SF34 scale, the retest reliability of the other domains was greater than 0.8. Three common factors were extracted by exploratory factor analysis, and the cumulative variance contribution rate was 64.39%. Conclusions The Mandarin version of the SCNS-SF34 and SCNS-HNC demonstrated satisfactory reliability and validity and is able to measure the supportive care needs of Chinese patients with head and neck cancer. Trial registration ChiCTR, ChiCTR1900026635 . Registered 16 October 2019- Retrospectively registered.

After the outbreak of COVID-19, medical institutions in China and even around the world are facing unprecedented challenges. In order to minimize the adverse impact of this unexpected epidemic on patients who need radiotherapy, the expert group of our radiotherapy center immediately formulated comprehensive emergency plans and prevention and control measures, partitioned the work area, launched online staff training, and optimized the radiotherapy process after the outbreak, which provided a strong guarantee for the safe and orderly operation of our radiotherapy center and kept the infection rate to an extremely low level. We hope our experience could provide reference and suggestions for other medical institutions.

Abstract Background With the rapid development of high-throughput sequencing technologies, many datasets on the same biological subject are generated. A meta-analysis is an approach that combines results from different studies on the same topic. The random-effects model in a meta-analysis enables the modeling of differences between studies by incorporating the between-study variance. Results This paper proposes a moments estimator of the between-study variance that represents the across-study variation. A new random-effects method (DSLD2), which involves two-step estimation starting with the DSL estimate and the Dg2 $D_{g}^{2}$ in the second step, is presented. The DSLD2 method is compared with 6 other meta-analysis methods based on effect sizes across 8 aspects under three hypothesis settings. The results show that DSLD2 is a suitable method for identifying differentially expressed genes under the first hypothesis. The DSLD2 method is also applied to Alzheimer’s microarray datasets. The differentially expressed genes detected by the DSLD2 method are significantly enriched in neurological diseases. Conclusions The results from both simulationes and an application show that DSLD2 is a suitable method for detecting differentially expressed genes under the first hypothesis.

Immune system plays important roles in the pathogenesis of Parkinson’s disease (PD). However, the role of B cells in this complex disease are still not fully understood. B cells produce antibodies but can also regulate immune responses. In order to decode the relative contribution of peripheral B cell subtypes to the etiology of PD, we performed single cell RNA and BCR sequencing for 10,466 B cells from 8 PD patients and 6 age-matched healthy controls. We observed significant increased memory B cells and significant decreased naïve B cells in PD patients compared to healthy controls. Notably, we also discovered increased IgG and IgA isotypes and more frequent class switch recombination events in PD patients. Moreover, we identified preferential V and J gene segments of B cell receptors in PD patients as the evidence of convergent selection in PD. Finally, we found a marked clonal expanded memory B cell population in PD patients, up-regulating both MHC II genes (HLA-DRB5, HLA-DQA2 and HLA-DPB1) and transcription factor activator protein 1 (AP-1), suggesting that the antigen presentation capacity of B cells was enhanced and B cells were activated in PD patients. Overall, this study conducted a comprehensive analysis of peripheral B cell characteristics of PD patients, which provided novel insights into the humoral immune response in the pathogenesis of PD.

BackgroundGenes spanning long chromosomal domains are coordinately regulated in human genome, which contribute to global gene dysregulation and carcinogenesis in cancer. It has been noticed that epigenetic modification and chromatin architecture may participate in the regulation process. However, the regulation patterns and functional elements of long-range gene regulation are unclear.MethodsBased on the clinical transcriptome data from different tumor sets, a novel expressional correlation analysis pipeline was performed to classify the co-regulated regions and subsets of intercorrelated regions. The GLAM2 program was used to predict conserved DNA elements that enriched in regions. Two conserved elements were selected to delete in Ishikawa and HeLa cells by CRISPR-Cas9. SAHA treatment and HDAC knockdown were used to change the histone acetylation status. Using qPCR, MTT, and scratch healing assay, we evaluate the effect on gene expression and cancer cell phenotype. By DNA pull-down and ChIP, the element-binding proteins were testified. 3C and 3D-FISH were performed to depict the alteration in chromatin architecture.ResultsIn multiple cancer genomes, we classified subsets of coordinately regulated regions (sub-CRRs) that possibly shared the same regulatory mechanisms and exhibited similar expression patterns. A new conserved DNA element (CRE30) was enriched in sub-CRRs and associated with cancer patient survival. CRE30 could restrict gene regulation in sub-CRRs and affect cancer cell phenotypes. DNA pull-down showed that multiple proteins including CTCF were recruited on the CRE30 locus, and ChIP assay confirmed the CTCF-binding signals. Subsequent results uncovered that as an essential element, CRE30 maintained chromatin loops and mediated a compact chromatin architecture. Moreover, we found that blocking global histone deacetylation induced chromatin loop disruption and CTCF dropping in the region containing CRE30, linked to promoted gene regulation. Additionally, similar effects were observed with CRE30 deletion in another locus of chromosome 8.ConclusionsOur research clarified a new functional element that recruits CTCF and collaborates with histone deacetylation to maintain high-order chromatin organizations, linking to long-range gene regulation in cancer genomes. The findings highlight a close relationship among conserved DNA element, epigenetic modification, and chromatin architecture in long-range gene regulation process.

Abstract Background The association between BIN1 rs744373 variant and Alzheimer’s disease (AD) had been identified by genome-wide association studies (GWASs) as well as candidate gene studies in Caucasian populations. But in East Asian populations, both positive and negative results had been identified by association studies. Considering the smaller sample sizes of the studies in East Asian, we believe that the results did not have enough statistical power. Results We conducted a meta-analysis with 71,168 samples (22,395 AD cases and 48,773 controls, from 37 studies of 19 articles). Based on the additive model, we observed significant genetic heterogeneities in pooled populations as well as Caucasians and East Asians. We identified a significant association between rs744373 polymorphism with AD in pooled populations (P = 5 × 10− 07, odds ratio (OR) = 1.12, and 95% confidence interval (CI) 1.07–1.17) and in Caucasian populations (P = 3.38 × 10− 08, OR = 1.16, 95% CI 1.10–1.22). But in the East Asian populations, the association was not identified (P = 0.393, OR = 1.057, and 95% CI 0.95–1.15). Besides, the regression analysis suggested no significant publication bias. The results for sensitivity analysis as well as meta-analysis under the dominant model and recessive model remained consistent, which demonstrated the reliability of our finding. Conclusions The large-scale meta-analysis highlighted the significant association between rs744373 polymorphism and AD risk in Caucasian populations but not in the East Asian populations.

Although our knowledge of human diseases has increased dramatically, the molecular basis, phenotypic traits, and therapeutic targets of most diseases still remain unclear. An increasing number of studies have observed that similar diseases often are caused by similar molecules, can be diagnosed by similar markers or phenotypes, or can be cured by similar drugs. Thus, the identification of diseases similar to known ones has attracted considerable attention worldwide. To this end, the associations between diseases at the molecular, phenotypic, and taxonomic levels were used to measure the pairwise similarity in diseases. The corresponding performance assessment strategies for these methods involving the terms “category-based,” “simulated-patient-based,” and “benchmark-data-based” were thus further emphasized. Then, frequently used methods were evaluated using a benchmark-data-based strategy. To facilitate the assessment of disease similarity scores, researchers have designed dozens of tools that implement these methods for calculating disease similarity. Currently, disease similarity has been advantageous in predicting noncoding RNA (ncRNA) function and therapeutic drugs for diseases. In this article, we review disease similarity methods, evaluation strategies, tools, and their applications in the biomedical community. We further evaluate the performance of these methods and discuss the current limitations and future trends for calculating disease similarity. Keywords: disease similarity, phenotypic traits, molecular basis, ncRNA function, therapeutic drugs

Phages have seriously affected the biochemical systems of the world, and not only are phages related to our health, but medical treatments for many cancers and skin infections are related to phages; therefore, this paper sought to identify phage proteins. In this paper, a Pseudo-188D model was established. The digital features of the phage were extracted by PseudoKNC, an appropriate vector was selected by the AdaBoost tool, and features were extracted by 188D. Then, the extracted digital features were combined together, and finally, the viral proteins of the phage were predicted by a stochastic gradient descent algorithm. Our model effect reached 93.4853%. To verify the stability of our model, we randomly selected 80% of the downloaded data to train the model and used the remaining 20% of the data to verify the robustness of our model.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing an outbreak of coronavirus disease 2019 (COVID-19), has been undergoing various mutations. The analysis of the structural and energetic effects of mutations on protein-protein interactions between the receptor binding domain (RBD) of SARS-CoV-2 and angiotensin converting enzyme 2 (ACE2) or neutralizing monoclonal antibodies will be beneficial for epidemic surveillance, diagnosis, and optimization of neutralizing agents. According to the molecular dynamics simulation, a key mutation N439K in the SARS-CoV-2 RBD region created a new salt bridge with Glu329 of hACE2, which resulted in greater electrostatic complementarity, and created a weak salt bridge with Asp442 of RBD. Furthermore, the N439K-mutated RBD bound hACE2 with a higher affinity than wild-type, which may lead to more infectious. In addition, the N439K-mutated RBD was markedly resistant to the SARS-CoV-2 neutralizing antibody REGN10987, which may lead to the failure of neutralization. The results show consistent with the previous experimental conclusion and clarify the structural mechanism under affinity changes. Our methods will offer guidance on the assessment of the infection efficiency and antigenicity effect of continuing mutations in SARS-CoV-2.

Abstract Background During procedures for conducting multiple sequence alignment, that is so essential to use the substitution score of pairwise alignment. To compute adaptive scores for alignment, researchers usually use Hidden Markov Model or probabilistic consistency methods such as partition function. Recent studies show that optimizing the parameters for hidden Markov model, as well as integrating hidden Markov model with partition function can raise the accuracy of alignment. The combination of partition function and optimized HMM, which could further improve the alignment’s accuracy, however, was ignored by these researches. Results A novel algorithm for MSA called ProbPFP is presented in this paper. It intergrate optimized HMM by particle swarm with partition function. The algorithm of PSO was applied to optimize HMM’s parameters. After that, the posterior probability obtained by the HMM was combined with the one obtained by partition function, and thus to calculate an integrated substitution score for alignment. In order to evaluate the effectiveness of ProbPFP, we compared it with 13 outstanding or classic MSA methods. The results demonstrate that the alignments obtained by ProbPFP got the maximum mean TC scores and mean SP scores on these two benchmark datasets: SABmark and OXBench, and it got the second highest mean TC scores and mean SP scores on the benchmark dataset BAliBASE. ProbPFP is also compared with 4 other outstanding methods, by reconstructing the phylogenetic trees for six protein families extracted from the database TreeFam, based on the alignments obtained by these 5 methods. The result indicates that the reference trees are closer to the phylogenetic trees reconstructed from the alignments obtained by ProbPFP than the other methods. Conclusions We propose a new multiple sequence alignment method combining optimized HMM and partition function in this paper. The performance validates this method could make a great improvement of the alignment’s accuracy.

Revealing the future spatial-temporal patterns of heatwave impacts on crops due to global climate change is of great scientific significance for climate change-related agricultural hazards prevention. However, the prediction of future wheat heatwave considering the planting distribution, growth period of wheat, as well as heatwave frequencies, days, and intensities remain poorly understood. In this paper, using predicted meteorological data of the Representative Concentration Pathway 8.5 (RCP8.5) scenario from 2011 to 2099 as well as a set of indicators that include heatwave days, frequencies and effective accumulative high temperatures, a comprehensive evaluation was performed to characterize the spatial-temporal variability of the heatwave hazard impacts on wheat in northern China under extreme climate scenarios. The results indicate that heatwaves across the Huang-Huai-Hai Plain, Xinjiang, western Gansu and the agro-pastoral ecotone are most frequent in the long-term. Heatwaves show significant increasing trends with regard to future occurrence frequency, days and intensities. The heatwave hazard on the Huang-Huai-Hai Plain, Northeast China, and the agro-pastoral ecotone shows a rapid growth trend, and there is a clear transition from relatively low heatwave hazard to a higher hazard. We argue that the continuous increase in heatwaves may pose a great threat to wheat production in northern China.

Abstract Background Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the top two common neurodegenerative diseases in elderly. Recent studies found the α-synuclein have a key role in AD. Although many clinical and pathological features between AD and PD are shared, the genetic association between them remains unclear, especially whether α-synuclein in PD genetically alters AD risk. Results We did not obtain any significant result (OR = 0.918, 95% CI: 0.782–1.076, P = 0.291) in MR analysis between PD and AD risk. In MR between α-synuclein in PD with AD risk, we only extracted rs356182 as the IV through a strict screening process. The result indicated a significant association based on IVW method (OR = 0.638, 95% CI: 0.485–0.838, P = 1.20E-03). In order to examine the robustness of the IVW method, we used other three complementary analytical methods and also obtained consistent results. Conclusion The overall PD genetic risk factors did not predict AD risk, but the α-synuclein susceptibility genetic variants in PD reduce the AD risk. We believe that our findings may help to understand the association between them, which may be useful for future genetic studies for both diseases.

The insulin-like androgenic gland hormone (IAG) is mainly produced in the androgenic gland (AG) of the male crustaceans and is a crucial regulator in male sexual differentiation. In the current study, the full-length cDNA of IAG in the swimming crab, Portunus trituberculatus (Pt-IAG), was cloned and characterized. Similar to other reported IAGs, the deduced amino acid sequence of Pt-IAG consists of signal peptide, B chain, C peptide, and A chain, containing six conserved cysteines that form two interchain disulfide bonds and one intra-B chain disulfide bond. Tissue distribution analysis suggested that the Pt-IAG cDNA was highly expressed in the AG and was slightly expressed in several other tissues. A short-term silencing of PtIAG with double-stranded RNA was found to reduce the transcript levels of insulin receptor (Pt-IR) and insulin-like growth factor-binding protein (Pt-IGFBP), suggesting the Pt-IAG might perform its biological function through the insulin family-based signaling system. Bilateral eyestalk ablation (ESA) induced the expression of Pt-IAG in the AG at 4 and 7 days after surgery, while the transcript levels of Pt-IR in the AG and testis and Pt-IGFBP in the muscle, testis, and thoracalia ganglia were significantly decreased from 1 day after surgery. The results suggested that the Pt-IR and Pt-IGFBP might also be the targets of eyestalk neuropeptides and responded to the ESA independent of IAG regulation.

In this paper, the concepts of p-harmonic mappings and log-p-harmonic mappings in the unit disk have been introduced and studied by many researchers. We proved the normality of the p-harmonic mappings and log-p-harmonic mappings, which extend the related results of harmonic mappings of earlier authors.

Clear-cell renal cell carcinoma (ccRCC) is the most common and lethal subtype of kidney cancer. VHL and PBRM1 are the top two significantly mutated genes in ccRCC specimens, while the genetic mechanism of the VHL/PBRM1-negative ccRCC remains to be elucidated. Here we carried out a comprehensive analysis of single-cell genomic copy number variations (CNVs) in VHL/PBRM1-negative ccRCC. Genomic CNVs were identified at the single-cell level, and the tumor cells showed widespread amplification and deletion across the whole genome. Functional enrichment analysis indicated that the amplified genes are significantly enriched in cancer-related signaling transduction pathways. Besides, receptor protein tyrosine kinase (RTK) genes also showed widespread copy number variations in cancer cells. Our studies indicated that the genomic CNVs in RTK genes and downstream signaling transduction pathways may be involved in VHL/PBRM1-negative ccRCC pathogenesis and progression, and highlighted the role of the comprehensive investigation of genomic CNVs at the single-cell level in both clarifying pathogenic mechanism and identifying potential therapeutic targets in cancers.

Although genome sequencing has become increasingly popular, the simulation of individual genomes is still important. This is because sequencing a large number of individual genomes is costly and genome data with extreme and boundary conditions, such as fatal genetic defects, are difficult to obtain. Privacy and legal barriers also prevent many applications of real data. Large sequencing projects in recent years have provided a deeper understanding of the human genome. However, there is a lack of tools to leverage known data to simulate personal genomes as real as possible. Here, we designed and developed PGsim, a comprehensive and highly customizable individual genome simulator, that fully uses existing knowledge, such as variant allele frequencies in global or world main populations, mutation probability differences between protein-coding regions and non-coding regions, transition/transversion (Ti/Tv) ratios, Indel incidence, Indel length distribution, structural variation sites, and pathogenic mutation sites. Users can flexibly control the proportion and quantity of known variants, common variants, novel variants in both coding and non-coding regions, and special variants through detailed parameter settings. To ensure that the simulated personal genome has sufficient randomness, PGsim makes the generated variants more real and reliable in terms of variant distribution, proportion, and population characteristics. PGsim is able to employ a huge volume database as background data to simulate personal genomes and does not require SQL database support. Users can easily change the variant databases used as needed. As a Perl script, there is no obstacle to running PGsim on any version of the MAC OS or Linux systems, and no libraries, packages, interpreters, compilers, or other dependencies need to be installed in advance. The PGsim tool is publicly available at https://github.com/lrjuan/PGsim.

Abstract Background The Human Phenotype Ontology (HPO) is one of the most popular bioinformatics resources. Recently, HPO-based phenotype semantic similarity has been effectively applied to model patient phenotype data. However, the existing tools are revised based on the Gene Ontology (GO)-based term similarity. The design of the models are not optimized for the unique features of HPO. In addition, existing tools only allow HPO terms as input and only provide pure text-based outputs. Results We present PhenoSimWeb, a web application that allows researchers to measure HPO-based phenotype semantic similarities using four approaches borrowed from GO-based similarity measurements. Besides, we provide a approach considering the unique properties of HPO. And, PhenoSimWeb allows text that describes phenotypes as input, since clinical phenotype data is always in text. PhenoSimWeb also provides a graphic visualization interface to visualize the resulting phenotype network. Conclusions PhenoSimWeb is an easy-to-use and functional online application. Researchers can use it to calculate phenotype similarity conveniently, predict phenotype associated genes or diseases, and visualize the network of phenotype interactions. PhenoSimWeb is available at http://120.77.47.2:8080.

Abstract Background Large scale association studies have found a significant association between type 2 diabetes mellitus (T2DM) and transcription factor 7-like 2 (TCF7L2) polymorphism rs7903146. However, the quality of data varies greatly, as the studies report inconsistent results in different populations. Hence, we perform this meta-analysis to give a more convincing result. Methods The articles, published from January 1st, 2000 to April 1st, 2017, were identified by searching in PubMed and Google Scholar. A total of 56628 participants (34232 cases and 22396 controls) were included in the meta-analysis. A total of 28 studies were divided into 4 subgroups: Caucasian (10 studies), East Asian (5 studies), South Asian (5 studies) and Others (8 studies). All the data analyses were analyzed by the R package meta. Results The significant association was observed by using the dominant model (OR = 1.41, CI = 1.36 - 1.47, p

Abstract Background Similar diseases are always caused by similar molecular origins, such as diasease-related protein-coding genes (PCGs). And the molecular associations reflect their similarity. Therefore, current methods for calculating disease similarity often utilized functional interactions of PCGs. Besides, the existing methods have neglected a fact that genes could also be associated in the gene functional network (GFN) based on intermediate nodes. Methods Here we presented a novel method, InfDisSim, to deduce the similarity of diseases. InfDisSim utilized the whole network based on random walk with damping to model the information flow. A benchmark set of similar disease pairs was employed to evaluate the performance of InfDisSim. Results The region beneath the receiver operating characteristic curve (AUC) was calculated to assess the performance. As a result, InfDisSim reaches a high AUC (0.9786) which indicates a very good performance. Furthermore, after calculating the disease similarity by the InfDisSim, we reconfirmed that similar diseases tend to have common therapeutic drugs (Pearson correlation γ2 = 0.1315, p = 2.2e-16). Finally, the disease similarity computed by infDisSim was employed to construct a miRNA similarity network (MSN) and lncRNA similarity network (LSN), which were further exploited to predict potential associations of lncRNA-disease pairs and miRNA-disease pairs, respectively. High AUC (0.9893, 0.9007) based on leave-one-out cross validation shows that the LSN and MSN is very appropriate for predicting novel disease-related lncRNAs and miRNAs, respectively. Conclusions The high AUC based on benchmark data indicates the method performs well. The method is valuable in the prediction of disease-related lncRNAs and miRNAs.

Abstract Background The development of single-cell RNA sequencing has enabled profound discoveries in biology, ranging from the dissection of the composition of complex tissues to the identification of novel cell types and dynamics in some specialized cellular environments. However, the large-scale generation of single-cell RNA-seq (scRNA-seq) data collected at multiple time points remains a challenge to effective measurement gene expression patterns in transcriptome analysis. Results We present an algorithm based on the Dynamic Time Warping score (DTWscore) combined with time-series data, that enables the detection of gene expression changes across scRNA-seq samples and recovery of potential cell types from complex mixtures of multiple cell types. Conclusions The DTWscore successfully classify cells of different types with the most highly variable genes from time-series scRNA-seq data. The study was confined to methods that are implemented and available within the R framework. Sample datasets and R packages are available at https://github.com/xiaoxiaoxier/DTWscore .

Alzheimer’s disease (AD) is a common neurodegenerative disease. APOE is the strong genetic risk factor of AD. The existing genome-wide association studies have identified many single nucleotide polymorphisms (SNPs) with minor effects on AD risk and the polygenic risk score (PRS) is presented to combine the effect of these SNPs. On the other hand, the volumes of various brain regions in AD patients have significant changes compared to that in normal individuals. Ch4 brain region containing at least 90% cholinergic neurons is the most extensive and conspicuous in the basal forebrain. Here, we investigated the relationship between the combined effect of AD-associated SNPs and Ch4 volume using the PRS approach. Our results showed that Ch4 volume in AD patients is significantly different from that in normal control subjects (p-value < 2.2 × 10−16). AD PRS, is not associated with the Ch4 volume in AD patients, excluding the APOE region (p-value = 0.264) and including the APOE region (p-value = 0.213). However, AD best-fit PRS, excluding the APOE region, is associated with Ch4 volume in normal control subjects (p-value = 0.015). AD PRS based on 8070 SNPs could explain 3.35% variance of Ch4 volume. In addition, the p-value of AD PRS model in normal control subjects, including the APOE region, is 0.006. AD PRS based on 8079 SNPs could explain 4.23% variance of Ch4 volume. In conclusion, PRS based on AD-associated SNPs is significantly related to Ch4 volume in normal subjects but not in patients.

Gene set analysis is commonly used in functional enrichment and molecular pathway analyses. Most of the present methods are based on the competitive testing methods which assume each gene is independent of the others. However, the false discovery rates of competitive methods are amplified when they are applied to datasets with high inter-gene correlations. The self-contained testing methods could solve this problem, but there are other restrictions on data characteristics. Therefore, a statistically rigorous testing method applicable to different datasets with various complex characteristics is needed to obtain unbiased and comparable results. We propose a self-contained and competitive incorporated analysis (SCIA) to alleviate the bias caused by the limited application scope of existing gene set analysis methods. This is accomplished through a novel permutation strategy using a priori biological networks to selectively permute gene labels with different probabilities. In simulation studies, SCIA was compared with four representative analysis methods (GSEA, CAMERA, ROAST, and NES), and produced the best performance in both false discovery rate and sensitivity under most conditions with different parameter settings. Further, the KEGG pathway analysis on two real datasets of lung cancer showed that the results found by SCIA in both of the two datasets are much more than that of GSEA and most of them could be supported by literature. Overall, SCIA promisingly offers researchers more reliable and comparable results with different datasets.

We derive exact solutions to the Vakhnenko-Parkes equation by means of the complex method, and then we illustrate our main results by some computer simulations. We can apply the idea of this study to related nonlinear differential equation.

A bulk micromachined inertial measurement unit (MIMU) is presented in this paper. Three single-axis accelerometers and three single-axis gyroscopes were simultaneously fabricated on a silicon wafer using a bulk micromachining process; the wafer is smaller than one square centimeter. In particular, a global area optimization method based on the relationship between the sensitivity and layout area was proposed to determine the layout configuration of the six sensors. The scale factors of the X/Y-axis accelerometer and Z-axis accelerometer are about 213.3 mV/g and 226.9 mV/g, respectively. The scale factors of the X/Y-axis gyroscope and Z-axis gyroscope are about 2.2 mV/o/s and 10.8 mV/o/s, respectively. The bias stability of the X/Y-axis gyroscope and the Z-axis gyroscope are about 2135 deg/h and 80 deg/h, respectively. Finally, the resolutions of X/Y-axis accelerometers, Z-axis accelerometers, X/Y-axis gyroscopes, and Z-axis gyroscopes are 0.0012 g/ √Hz, 0.0011 g/ √Hz, 0.314 °/s/ √Hz, and 0.008 °/s/ √Hz, respectively.

Topological entropy is one of the most difficult entropies to be used to analyze the DNA sequences, due to the finite sample and high-dimensionality problems. In order to overcome these problems, a generalized topological entropy is introduced. The relationship between the topological entropy and the generalized topological entropy is compared, which shows the topological entropy is a special case of the generalized entropy. As an application the generalized topological entropy in introns, exons and promoter regions was computed, respectively. The results indicate that the entropy of introns is higher than that of exons, and the entropy of the exons is higher than that of the promoter regions for each chromosome, which suggest that DNA sequence of the promoter regions is more regular than the exons and introns.

Salvia miltiorrhiza is one of the most popular traditional medicinal herbs in Asian nations. Its dried root contains a number of tanshinones, protocatechuic aldehyde, salvianolic acid B and rosmarinic, and is used for the treatment of various diseases. The finding of microRNAs (miRNAs) and their target genes will help understand their biological role on the biosynthesis of tanshinones in S. miltiorrhiza. In the present study, a total of 452 known miRNAs corresponding to 589 precursor miRNAs (pre-miRNAs), and 40 novel miRNAs corresponding to 24 pre-miRNAs were identified in different tissues of S. miltiorrhiza by high-throughput sequencing, respectively. Among them, 62 miRNAs express only in root, 95 miRNAs express only in stem, 19 miRNAs express only in leaf, and 71 miRNAs express only in flower, respectively. By the degradome analysis, 69 targets potentially cleaved by 25 miRNAs were identified. Among them, acetyl-CoA C-acetyltransferase was cleaved by miR5072, and involved in the biosynthesis of tanshinones. This study provided valuable information for understanding the tissue-specific expression patterns of miRNAs in S. miltiorrhiza, and offered a foundation for future studies of the miRNA-mediated biosynthesis of tanshinones.