NFMCLDA: Predicting miRNA-based lncRNA-disease associations by network fusion and matrix completion.

In recent years, emerging evidence has revealed a strong association between dysregulations of long non-coding RNAs (lncRNAs) and sophisticated human diseases. Biological experiments are adequate to identify such associations, but they are costly and time-consuming. Therefore, developing high-quality computational methods is a challenging and urgent task in the field of bioinformatics. This paper proposes a new lncRNA-disease association inference approach NFMCLDA (Network Fusion and Matrix Completion lncRNA-Disease Association), which can effectively integrate multi-source association data. In this approach, miRNA information is used as the transition path, and an unbalanced random walk method on three-layer heterogeneous network is adopted in the preprocessing. Therefore, more effective information between networks can be mined and the sparsity problem of the association matrix can be solved. Finally, the matrix completion method accurately predicts associations. The results show that NFMCLDA can provide more accurate lncRNA-disease associations than state-of-the-art methods. The areas under the receiver operating characteristic curves are 0.9648 and 0.9713, respectively, through the cross-validation of 5-fold and 10-fold. Data from published case studies on four diseases - lung cancer, osteosarcoma, cervical cancer, and colon cancer - have confirmed the reliable predictive potential of NFMCLDA model.

FASN Inhibition Decreases MHC-I Degradation and Synergizes with PD-L1 Checkpoint Blockade in Hepatocellular Carcinoma.

Immune checkpoint inhibitors (ICI) transformed the treatment landscape of hepatocellular carcinoma (HCC). Unfortunately, patients with attenuated MHC-I expression remain refractory to ICIs, and druggable targets for upregulating MHC-I are limited. Here, we found that genetic or pharmacologic inhibition of fatty acid synthase (FASN) increased MHC-I levels in HCC cells, promoting antigen presentation and stimulating antigen-specific CD8+ T-cell cytotoxicity. Mechanistically, FASN inhibition reduced palmitoylation of MHC-I that led to its lysosomal degradation. The palmitoyltransferase DHHC3 directly bound MHC-I and negatively regulated MHC-I protein levels. In an orthotopic HCC mouse model, Fasn deficiency enhanced MHC-I levels and promoted cancer cell killing by tumor-infiltrating CD8+ T cells. Moreover, the combination of two different FASN inhibitors, orlistat and TVB-2640, with anti-PD-L1 antibody robustly suppressed tumor growth in vivo. Multiplex IHC of human HCC samples and bioinformatic analysis of The Cancer Genome Atlas data further illustrated that lower expression of FASN was correlated with a higher percentage of cytotoxic CD8+ T cells. The identification of FASN as a negative regulator of MHC-I provides the rationale for combining FASN inhibitors and immunotherapy for treating HCC. SIGNIFICANCE: Inhibition of FASN increases MHC-I protein levels by suppressing its palmitoylation and lysosomal degradation, which stimulates immune activity against hepatocellular carcinoma and enhances the efficacy of immune checkpoint inhibition.

Prognosis prediction and risk stratification of breast cancer patients based on a mitochondria-related gene signature.

As the malignancy with the highest global incidence, breast cancer represents a significant threat to women's health. Recent advances have shed light on the importance of mitochondrial function in cancer, particularly in metabolic reprogramming within tumors. Recognizing this, we developed a novel risk signature based on mitochondrial-related genes to improve prognosis prediction and risk stratification in breast cancer patients. In this study, transcriptome data and clinical features of breast cancer samples were extracted from two sources: the TCGA, serving as the training set, and the METABRIC, used as the independent validation set. We developed the signature using LASSO-Cox regression and assessed its prognostic efficacy via ROC curves. Furthermore, the signature was integrated with clinical features to create a Nomogram model, whose accuracy was validated through clinical calibration curves and decision curve analysis. To further elucidate prognostic variations between high and low-risk groups, we conducted functional enrichment and immune infiltration analyses. Additionally, the study encompassed a comparison of mutation landscapes and drug sensitivity, providing a comprehensive understanding of the differing characteristics in these groups. Conclusively, we established a risk signature comprising 8 mitochondrial-related genes-ACSL1, ALDH2, MTHFD2, MRPL13, TP53AIP1, SLC1A1, ME3, and BCL2A1. This signature was identified as an independent risk predictor for breast cancer patient survival, exhibiting a significant high hazard ratio (HR = 3.028, 95%CI 2.038-4.499, P < 0.001). Patients in the low-risk group showed a more favorable prognosis, with enhanced immune infiltration, distinct mutation landscapes, and greater sensitivity to anti-tumor drugs. In contrast, the high-risk group exhibited an adverse trend in these aspects. This risk signature represents a novel and effective prognostic indicator, suggesting valuable insights for patient stratification in breast cancer.

Astrocytes in intracerebral hemorrhage: impact and therapeutic objectives.

Intracerebral hemorrhage (ICH) manifests precipitously and profoundly impairs the neurological function in patients who are affected. The etiology of subsequent injury post-ICH is multifaceted, characterized by the intricate interplay of various factors, rendering therapeutic interventions challenging. Astrocytes, a distinct class of glial cells, interact with neurons and microglia, and are implicated in a series of pathophysiological alterations following ICH. A comprehensive examination of the functions and mechanisms associated with astrocytic proteins may shed light on the role of astrocytes in ICH pathology and proffer innovative therapeutic avenues for ICH management.

Cell mechanics regulate the migration and invasion of hepatocellular carcinoma cells via JNK signaling.

Hepatocellular carcinoma (HCC) cells, especially those with metastatic competence, show reduced stiffness compared to the non-malignant counterparts. However, it is still unclear whether and how the mechanics of HCC cells influence their migration and invasion. This study reports that HCC cells with enhanced motility show reduced mechanical stiffness and cytoskeleton, suggesting the inverse correlation between cellular stiffness and motility. Through pharmacologic and genetic approaches, inhibiting actomyosin activity reduces HCC cellular stiffness but promotes their migration and invasion, while activating it increases cell stiffness but impairs cell motility. Actomyosin regulates cell motility through the influence on cellular stiffness. Mechanistically, weakening/strengthening cells inhibits/promotes c-Jun N terminal kinase (JNK) phosphorylation, activation/inhibition of which rescues the effects of cell mechanics on their migration and invasion. Further, HCC cancer stem cells (CSCs) exhibit higher motility but lower stiffness than control cells. Increasing CSC stiffness weakens migration and invasion through the activation of JNK signaling. In conclusion, our findings unveil a new regulatory role of actomyosin-mediated cellular mechanics in tumor cell motility and present new evidence to support that tumor cell softening may be one driving force for HCC metastasis. STATEMENT OF SIGNIFICANCE: Tumor cells progressively become softened during metastasis and low cell stiffness is associated with high metastatic potential. However, it remains unclear whether tumor cell softening is a by-product of or a driving force for tumor progression. This work reports that the stiffness of hepatocellular carcinoma cells is linked to their migration and invasion. Importantly, tumor cell softening promotes migration and invasion, while cell stiffening impairs the mobility. Weakening/strengthening cells inhibits/promotes JNK phosphorylation, activation/inhibition of which rescues the effects of cell mechanics on their migration and invasion ability. Further, stiffening liver cancer stem cells attenuates their motility through activating JNK signaling. In summary, our study uncovers a previously unappreciated role of tumor cell mechanics in migration and invasion and implicates the therapeutic potential of cell mechanics in the mechanotargeting of metastasis.

Comparison of IMD and ICG videoangiography in combined bypass surgery: a single-center study.

BACKGROUND: Superficial temporal artery-middle cerebral artery (STA-MCA) bypass combined with an encephaloduromyosynangiosis (EDMS) had gained significant role in treating chronic cerebral ischemia. Invasiveness and costs of intraoperative digital subtraction angiography (DSA) limited its application in operations. OBJECTIVE: To find the reliable parameters for determining bypass patency with intraoperative micro-Doppler (IMD) sonography and compare the diagnostic accuracy of indocyanine green (ICG) videoangiography with IMD in combined bypass. METHOD: One hundred fifty bypass procedures were included and divided into patent and non-patent groups according to postoperative computed tomography angiography (CTA) within 72 h. The surgical process was divided into four phases in the following order: preparation phase (phase 1), anastomosis phase (phase 2), the temporalis muscle closure phase (phase 3), and the bone flap closure phase (phase 4). The IMD parameters were compared between patent and non-patent groups, and then compared with the patency on CTA by statistical analyses. IMD with CTA, ICG videoangiography with CTA, IMD with ICG videoangiography were performed to assess bypass patency. The agreement between methods was evaluated using kappa statistics. RESULTS: No significant differences of baseline characteristics were found between patent and non-patent group. Parameters in the STA were different between patent and non-patent groups in phases 2, 3, and 4. In patent group, Vm was apparently higher and PI was lower in phases 2, 3, and 4 compared with phase 1 (P < .001). In non-patent group, no differences of Vm and PI were found within inter-group. The best cutoff value of IMD in the STA to distinguish patent from non-patent bypasses was Vm in phase 4 > 17.5 cm/s (sensitivity 94.2%, specificity 100%). In addition, the agreement for accessing bypass patency was moderate between ICG videoangiography and CTA (kappa = 0.67), IMD and ICG videoangiography (kappa = 0.73), and good between IMD and CTA (kappa = 0.86). CONCLUSION: ICG videoangiography could directly display morphology changes of bypass. IMD could be used for providing half-quantitative parameters to assess bypass patency. Vm in phase 4 > 17.5 cm/s suggesting the patency of bypass on CTA would be good. Also, compared with ICG videoangiography, IMD had more accuracy.

Scavenger Receptor Class B Type I Deficiency Induces Iron Overload and Ferroptosis in Renal Tubular Epithelial Cells via Hypoxia-Inducible Factor-1α/Transferrin Receptor 1 Signaling Pathway.

Aims: Scavenger receptor class B type I (SRBI) promotes cell cholesterol efflux and the clearance of plasma cholesterol. Thus, SRBI deficiency causes abnormal cholesterol metabolism and hyperlipidemia. Studies have suggested that ferroptosis is involved in lipotoxicity; however, whether SRBI deficiency could induce ferroptosis remains to be investigated. Results: We knocked down or knocked out SRBI in renal HK-2 cells and C57BL/6 mice to determine the expression levels of ferroptosis-related regulators. Our results demonstrated that SRBI deficiency upregulates transferrin receptor 1 (TFR1) expression and downregulates ferroportin expression, which induces iron overload and subsequent ferroptosis in renal tubular epithelial cells. TFR1 is known to be regulated by hypoxia-inducible factor-1α (HIF-1α). Next, we investigated whether SRBI deletion affected HIF-1α. SRBI deletion upregulated the mRNA and protein expression of HIF-1α, and promoted its translocation to the nucleus. To determine whether HIF-1α plays a key role in SRBI-deficiency-induced ferroptosis, we used HIF-1α inhibitor and siHIF-1α in HK-2 cells, and found that downregulation of HIF-1α prevented SRBI-silencing-induced TFR1 upregulation and iron overload, and eventually reduced ferroptosis. The underlying mechanism of HIF-1α activation was explored next, and the results showed that SRBI knockout or knockdown may upregulate the expression of HIF-1α, and promote HIF-1α translocation from the cytoplasm into the nucleus via the PKC-ß/NF-κB signaling pathway. Innovation and Conclusion: Our study showed, for the first time, that SRBI deficiency induces iron overload and subsequent ferroptosis via the HIF-1α/TFR1 pathway.

The Crosstalk Between Immune Cells After Intracerebral Hemorrhage.

The inflammatory mechanism of intracerebral hemorrhage (ICH) has been widely studied, and it is believed that the regulation of this mechanism is of great significance to the prognosis. In the early stage of the acute phase of ICH, the release of a large number of inflammatory factors around the hematoma can recruit more inflammatory cells to infiltrate the area, further release inflammatory factors, cause an inflammatory cascade reaction, aggravate the volume of cerebral hematoma and edema and further destroy the blood-brain barrier (BBB), according to this, the crosstalk between cells may be of great significance in secondary brain injury (SBI). Because most of the cells recruited are inflammatory immune cells, this paper mainly discusses the cells based on the inflammatory mechanism to discuss their functions after ICH, we found that among the main cells inherent in the brain, glial cells account for the majority, of which microglia are the most widely studied and it can interact with a variety of cells, which is reflected in the literature researches on its pathogenesis and treatment. We believe that exploring multi-mechanism and multi-cell regulated drugs may be the future development trend, and the existing research, the comparison and unification of modeling methods, and the observation of long-term efficacy may be the first problem that researchers need to solve.

[Meta-analysis of obesity on the outcome of rotator cuff repair].

OBJECTIVE: To systematically evaluate obesity on the outcome of rotator cuff repair. METHODS: Literatures on the relationship between obesity and outcomes after rotator cuff repair were searched from PubMed, Embase, Cochrane Library, Web of Science, China biology medicine(CBM), CNKI, Wanfang and VIP databases from building database to August 1, 2022, and were screened independently by two authors according to inclusion and exclusion criteria. Endnote X9 and Excel 2019 were used for literature extraction, management and data entry, and Newcastle-Ottawa Scale (NOS) was used to evaluate quality of the included literatures. STATA 16.0 and RevMan 5.4 softwares were used to evaluate postoperative retear rate, reoperation rate, complication rate, American Shoulder and Elbow Surgeons (ASES) score, visual analogue scale (VAS), operative time and external rotation angle of shoulder joint pain were analyzed. RESULTS: Totally 13 literatures were included, including 6 retrospective studies, 5 case-control studies, 1 prospective cohort study, and 1 abstract of a study for which the full text was not available, with 85 503 patients (31 973 in obese group and 53 530 in non-obese group). Meta-analysis showed there were statistical differences between two groups in retear rate [OR=2.58, 95%CI(1.23, 5.41), P=0.01], reoperation rate[OR=1.31, 95%CI(1.21, 1.42), P<0.00], complication rate [OR=1.57, 95%CI(1.31, 1.87), P=0.00], ASES score[MD=-3.59, 95%CI(-5.45, -1.74), P=0.00], and VAS[MD=0.24, 95%CI(0.00, 0.49), P=0.05]. While there were no differences between two groups in operative time[MD=6.03, 95%CI(-7.63, 19.69), P=0.39], external rotation angle of shoulder joint[MD=-1.79, 95%CI(-5.30, 1.71), P=0.32]. CONCLUSION: Obesity is associated with higher rates of retear, resurgery, complications, poorer shoulder function and pain after rotator cuff repair.

Sublethal effects of imidacloprid on the fitness of two species of wheat aphids, Schizaphis graminum (R.) and Rhopalosiphum padi (L.).

Imidacloprid is a neonicotinoid insecticide that efficiently controls piercing-sucking mouthparts pests. However, the impact of low lethal concentration of imidacloprid on key demographic parameters of wheat aphids, Schizaphis graminum (R.) and Rhopalosiphum padi (L.) has been scarcely studied. In this study, we used the age stage, two-sex life table approach to investigate the sublethal effects of imidacloprid on the biological traits of S. graminum and R. padi. Bioassays showed that imidacloprid possesses high toxicity to adult S. graminum and R. padi, with LC50 of 3.59 and 13.78 mg L-1 following 24 h exposure. A low lethal concentration of imidacloprid (LC25) significantly decreased adult longevity and total longevity of progeny generation aphids (F1) of S. graminum. Nevertheless, imidacloprid (LC25) had no significant effects on the fecundity and longevity of directly exposed parental parental S. graminum and R. padi (F0). Our results showed that the low lethal concentration of imidacloprid affected the demographic parameters that ultimately impact on the population of S. graminum. This study provides detailed information about the overall effects of imidacloprid on S. graminum and R. padi that might help to manage these two key pests.

scGAMNN: Graph Antoencoder-Based Single-Cell RNA Sequencing Data Integration Algorithm Using Mutual Nearest Neighbors.

It is critical to correctly assemble high-dimensional single-cell RNA sequencing (scRNA-seq) datasets and downscale them for downstream analysis. However, given the complex relationships between cells, it remains a challenge to simultaneously eliminate batch effects between datasets and maintain the topology between cells within each dataset. Here, we propose scGAMNN, a deep learning model based on graph autoencoder, to simultaneously achieve batch correction and topology-preserving dimensionality reduction. The low-dimensional integrated data obtained by scGAMNN can be used for visualization, clustering and trajectory inference.By comparing it with the other five methods, multiple tasks show that scGAMNN consistently has comparable data integration performance in clustering and trajectory conservation.

Seasonal differences of feeding ecology of Uroteuthis edulis in the East China Sea based on fatty acid and stable isotope.

Uroteuthis edulis, an important fishery target species, plays an important role in the food web of the East China Sea. We collected U. edulis samples in the East China Sea from September 2020 to January 2021 to examine their feeding differences in autumn and winter based on fatty acid and stable isotope analyses. The results showed that the content of polyunsaturated fatty acids (PUFA) was the highest, followed by saturated fatty acids (SFA), and the lowest content of monounsaturated fatty acids (MUFA) in autumn and winter. Results of the similarity ana-lysis showed significant differences in PUFA and MUFA contents but no differences in SFA contents between autumn and winter. Results of non-metric multidimensional scale analysis showed that C18:1n9 could be used as signature fatty acids in autumn samples and C22:6n3 as characteristic fatty acids in winter samples. There was significant difference of δ15N between autumn and winter, but no difference of δ13C. The total area (TA), range of δ15N (NR), standard ellipse area (SEA) and the corrected version of the standard ellipse area (SEAC) in autumn were all smaller than those in winter, but range of δ13C (CR) was on the contrary. Results of the Spearman rank correlation test showed that there were differences between fatty acid content and stable isotope ratio of U. edulis and the dorsal mantle length in autumn and winter. Our results could provide basic data for understanding material and energy flow of the East China Sea food web, which is conducive to the sustainable development and utilization of U. edulis.

An Overview of the Mechanisms Involved in Neuralgia.

Neuralgia is a frequently occurring condition that causes chronic pain and burdens both patients and their families. Earlier research indicated that anti-inflammatory treatment, which was primarily utilized to address conditions like neuralgia, resulted in positive outcomes. However, recent years have witnessed the emergence of various novel mechanisms associated with pain-related disorders. This review provides a concise overview of the inflammatory mechanisms involved in neuralgia. It also examines recent advancements in research, exploring the influence of ion channels and synaptic proteins on neuralgia and its complications. Additionally, the interactions between these mechanisms are discussed with the aim of suggesting innovative therapeutic approaches and research directions for the management of neuralgia.

Predicting pathological response to neoadjuvant or conversion chemoimmunotherapy in stage IB-III non-small cell lung cancer patients using radiomic features.

BACKGROUND: To develop a radiomics model based on chest computed tomography (CT) for the prediction of a pathological complete response (pCR) after neoadjuvant or conversion chemoimmunotherapy (CIT) in patients with non-small cell lung cancer (NSCLC). METHODS: Patients with stage IB-III NSCLC who received neoadjuvant or conversion CIT between September 2019 and July 2021 at Hunan Cancer Hospital, Xiangya Hospital, and Union Hospital were retrospectively collected. The least absolute shrinkage and selection operator (LASSO) were used to screen features. Then, model 1 (five radiomics features before CIT), model 2 (four radiomics features after CIT and before surgery) and model 3 were constructed for the prediction of pCR. Model 3 included all nine features of model 1 and 2 and was later named the neoadjuvant chemoimmunotherapy-related pathological response prediction model (NACIP). RESULTS: This study included 110 patients: 77 in the training set and 33 in the validation set. Thirty-nine (35.5%) patients achieved a pCR. Model 1 showed area under the curve (AUC) = 0.65, 64% accuracy, 71% specificity, and 50% sensitivity, while model 2 displayed AUC = 0.81, 73% accuracy, 62% specificity, and 92% sensitivity. In comparison, NACIP yielded a good predictive value, with an AUC of 0.85, 81% accuracy, 81% specificity, and 83% sensitivity in the validation set. CONCLUSION: NACIP may be a potential model for the early prediction of pCR in patients with NSCLC treated with neoadjuvant/conversion CIT.

Predicting potential microbe-disease associations based on multi-source features and deep learning.

Studies have confirmed that the occurrence of many complex diseases in the human body is closely related to the microbial community, and microbes can affect tumorigenesis and metastasis by regulating the tumor microenvironment. However, there are still large gaps in the clinical observation of the microbiota in disease. Although biological experiments are accurate in identifying disease-associated microbes, they are also time-consuming and expensive. The computational models for effective identification of diseases related microbes can shorten this process, and reduce capital and time costs. Based on this, in the paper, a model named DSAE_RF is presented to predict latent microbe-disease associations by combining multi-source features and deep learning. DSAE_RF calculates four similarities between microbes and diseases, which are then used as feature vectors for the disease-microbe pairs. Later, reliable negative samples are screened by k-means clustering, and a deep sparse autoencoder neural network is further used to extract effective features of the disease-microbe pairs. In this foundation, a random forest classifier is presented to predict the associations between microbes and diseases. To assess the performance of the model in this paper, 10-fold cross-validation is implemented on the same dataset. As a result, the AUC and AUPR of the model are 0.9448 and 0.9431, respectively. Furthermore, we also conduct a variety of experiments, including comparison of negative sample selection methods, comparison with different models and classifiers, Kolmogorov-Smirnov test and t-test, ablation experiments, robustness analysis, and case studies on Covid-19 and colorectal cancer. The results fully demonstrate the reliability and availability of our model.

Chronic pulmonary mucormycosis caused by rhizopus microsporus mimics lung carcinoma in an immunocompetent adult: A case report.

BACKGROUND: Pulmonary mucormycosis is a rare but life-threatening invasive fungal infection that mostly affects immunocompromised patients. This disease usually develops acutely and progresses rapidly, often leading to a poor clinical prognosis. Chronic pulmonary mucormycosis is highly unusual in immunocompetent patients. CASE SUMMARY: A 43-year-old man, who was a house improvement worker with a long history of occupational dust exposure, presented with an irritating cough that had lasted for two months. The patient was previously in good health, without dysglycemia or any known immunodeficiencies. Chest computed tomography revealed a mass in the left lower lobe, measuring approximately 6 cm in diameter, which was suspected to be primary lung carcinoma complicated with obstructive pneumonia. Thoracoscopic-assisted left lower lobectomy was performed, and metagenomic next-generation sequencing detection, along with special pathological staining of surgical specimens, suggested Rhizopus microsporus infection. Postoperatively, the patient's respiratory symptoms were relieved, and no signs of recurrence were found during the six-month follow-up. CONCLUSION: This article reports a rare case of chronic pulmonary mucormycosis caused by Rhizopus microsporus in a middle-aged male without dysglycemia or immunodeficiency. The patient's surgical outcome was excellent, reaffirming that surgery remains the cornerstone of pulmonary mucormycosis treatment.

Association between post-stroke smoking and stroke recurrence in first-ever ischemic stroke survivors: based on a 10-year prospective cohort.

BACKGROUND: Whether smoking is a risk factor for ischemic stroke (IS) recurrence in IS survivors is still uncovered, and evidences are sparse. Meanwhile, an add-on effect of clopidogrel was observed in myocardial infarction patients who smoked, but whether the paradox exists in IS patients is still unsolved. The objectives of this study are to explore the association between smoking behavior after index stroke and IS recurrence and to explore whether the paradox exists. METHODS: A prospective cohort of first-ever IS patients was conducted between 2010 and 2019. The prognosis and smoking features of enrolled patients were obtained via telephone follow-up every 3 months. Fine-gray model with interaction terms was applied to measure the relationships between stroke recurrence and smoking behaviors after index stroke and to explore the add-on effect of clopidogrel in smoking patients. RESULTS: There were 171 (24.26%) recurrences and 129 (18.30%) deaths during follow-up in 705 enrolled IS patients. One hundred forty-six (20.71%) patients smoked after index stroke. The hazard ratios (HRs) and 95% confidence intervals (CIs) of interaction terms between antiplatelet drug and follow-up smoking (smoking status and daily smoking amount) were 1.092 (95% CI: 0.524, 2.276) and 0.985 (95% CI: 0.941, 1.031), respectively. A significantly higher risk of recurrence was observed in patients with a higher daily smoking amount during follow-up (per cigarette), with HR being 1.027 (95% CI: 1.003, 1.052). CONCLUSIONS: Smoking could elevate the risk of IS recurrence, and IS survivor should be advised to quit or smoke less. Add-on effect of clopidogrel may not exist in smoking strokers taking clopidogrel.

[Research progress of optical motion capture technology in shoulder biomechanics].

The shoulder joint is the most flexible joint in the body with the largest range of motion, and the movement pattern is more complex. Accurate capture of three-dimensional motion data of the shoulder joint is crucial for biomechanical evaluation. Optical motion capture systems offer a non-invasive and radiation-free method to capture shoulder joint motion data during complex movements, enabling further biomechanical analysis of the shoulder joint. This review provides a comprehensive overview of optical motion capture technology in the context of shoulder joint movement, including measurement principles, data processing methods to reduce artifacts from skin and soft tissues, factors influencing measurement results, and applications in shoulder joint disorders.

Molecular characterization of nineteen cytokine receptor family B (CRFB) members, CRFB1, CRFB2, CRFB4-17, with three CRFB9 and two CRFB14 in a cyprinid fish, the blunt snout bream Megalobrama amblycephala.

The class II cytokine receptor family members are receptors of class 2 helical cytokines in mammals, and are named cytokine receptor family B (CRFB) in fish. In zebrafish, sixteen members, including CRFB1, CRFB2 and CRFB4-17 were reported. With the availability of genome sequence, a total of nineteen CRFBs was identified in the blunt snout bream (Megalobrama amblycephala), including CRFB1, CRFB2, CRFB4-17 with the presence of three CRFB9 isoforms, and two CRFB14 isoforms. These CRFB molecules contain well conserved features, such as fibronectin type III (FNIII) domain, transmembrane and intracellular domains as other class II cytokine receptors, and are phylogenetically grouped into thirteen clades with their homologues from other species of fish. The CRFB genes were constitutively expressed in organs/tissues examined in the fish. The finding of more CRFB members in the bream may provide clues to understand possible receptor-ligand interaction and their diversity from an evolutionary point of view.

P-CSN: single-cell RNA sequencing data analysis by partial cell-specific network.

Although many single-cell computational methods proposed use gene expression as input, recent studies show that replacing 'unstable' gene expression with 'stable' gene-gene associations can greatly improve the performance of downstream analysis. To obtain accurate gene-gene associations, conditional cell-specific network method (c-CSN) filters out the indirect associations of cell-specific network method (CSN) based on the conditional independence of statistics. However, when there are strong connections in networks, the c-CSN suffers from false negative problem in network construction. To overcome this problem, a new partial cell-specific network method (p-CSN) based on the partial independence of statistics is proposed in this paper, which eliminates the singularity of the c-CSN by implicitly including direct associations among estimated variables. Based on the p-CSN, single-cell network entropy (scNEntropy) is further proposed to quantify cell state. The superiorities of our method are verified on several datasets. (i) Compared with traditional gene regulatory network construction methods, the p-CSN constructs partial cell-specific networks, namely, one cell to one network. (ii) When there are strong connections in networks, the p-CSN reduces the false negative probability of the c-CSN. (iii) The input of more accurate gene-gene associations further optimizes the performance of downstream analyses. (iv) The scNEntropy effectively quantifies cell state and reconstructs cell pseudo-time.