Predicting potential microbe-disease associations based on dual branch graph convolutional network.

Studying the association between microbes and diseases not only aids in the prevention and diagnosis of diseases, but also provides crucial theoretical support for new drug development and personalized treatment. Due to the time-consuming and costly nature of laboratory-based biological tests to confirm the relationship between microbes and diseases, there is an urgent need for innovative computational frameworks to anticipate new associations between microbes and diseases. Here, we propose a novel computational approach based on a dual branch graph convolutional network (GCN) module, abbreviated as DBGCNMDA, for identifying microbe-disease associations. First, DBGCNMDA calculates the similarity matrix of diseases and microbes by integrating functional similarity and Gaussian association spectrum kernel (GAPK) similarity. Then, semantic information from different biological networks is extracted by two GCN modules from different perspectives. Finally, the scores of microbe-disease associations are predicted based on the extracted features. The main innovation of this method lies in the use of two types of information for microbe/disease similarity assessment. Additionally, we extend the disease nodes to address the issue of insufficient features due to low data dimensionality. We optimize the connectivity between the homogeneous entities using random walk with restart (RWR), and then use the optimized similarity matrix as the initial feature matrix. In terms of network understanding, we design a dual branch GCN module, namely GlobalGCN and LocalGCN, to fine-tune node representations by introducing side information, including homologous neighbour nodes. We evaluate the accuracy of the DBGCNMDA model using five-fold cross-validation (5-fold-CV) technique. The results show that the area under the receiver operating characteristic curve (AUC) and area under the precision versus recall curve (AUPR) of the DBGCNMDA model in the 5-fold-CV are 0.9559 and 0.9630, respectively. The results from the case studies using published experimental data confirm a significant number of predicted associations, indicating that DBGCNMDA is an effective tool for predicting potential microbe-disease associations.

Metabolism score and machine learning models for the prediction of esophageal squamous cell carcinoma progression.

The incomplete prediction of prognosis in esophageal squamous cell carcinoma (ESCC) patients is attributed to various therapeutic interventions and complex prognostic factors. Consequently, there is a pressing demand for enhanced predictive biomarkers that can facilitate clinical management and treatment decisions. This study recruited 491 ESCC patients who underwent surgical treatment at Huashan Hospital, Fudan University. We incorporated 14 blood metabolic indicators and identified independent prognostic indicators for overall survival through univariate and multivariate analyses. Subsequently, a metabolism score formula was established based on the biochemical markers. We constructed a nomogram and machine learning models utilizing the metabolism score and clinically significant prognostic features, followed by an evaluation of their predictive accuracy and performance. We identified alkaline phosphatase, free fatty acids, homocysteine, lactate dehydrogenase, and triglycerides as independent prognostic indicators for ESCC. Subsequently, based on these five indicators, we established a metabolism score that serves as an independent prognostic factor in ESCC patients. By utilizing this metabolism score in conjunction with clinical features, a nomogram can precisely predict the prognosis of ESCC patients, achieving an area under the curve (AUC) of 0.89. The random forest (RF) model showed superior predictive ability (AUC = 0.90, accuracy = 86%, Matthews correlation coefficient = 0.55). Finally, we used an RF model with optimal performance to establish an online predictive tool. The metabolism score developed in this study serves as an independent prognostic indicator for ESCC patients.

Pre-pubertal sublingual immunotherapy is more effective than immunotherapy during puberty in allergic rhinitis and asthma.

BACKGROUND: To evaluate the clinical efficacy of sublingual-specific immunotherapy (SLIT) and pulmonary function in children with allergic rhinitis and asthma before and after puberty. METHODS: This retrospective analysis included 136 patients aged 4-18 years with allergic asthma and rhinitis who received two years of SLIT treatment. Patients were divided into two groups based on age: the prepubertal group (4-10 years old) and the pubertal group (11-18 years old). After half a year, one year, and two years of SLIT, the total nasal symptom score (TNSS), total rhinitis medication score (TRMS), daytime asthma symptom score (DASS), nighttime asthma symptom score (NASS), total asthma medication score (TAMS), asthma control test (ACT), and peak expiratory flow rate (PEF%) were evaluated and compared with the baseline before treatment. RESULTS: In both groups, TNSS, TRMS, DASS, NASS, TAMS, ACT, and PEF% improved significantly after half a year, one year, and two years of SLIT treatment. After half a year of treatment, prepubertal patients showed better therapy for TNSS, DASS, NASS, and TAMS compared to the pubertal group. The TAMS of the pubertal group was higher than that of the prepubertal group after one year of treatment. Finally, the PEF% showed better therapy compared to the pubertal group. CONCLUSION: SLIT treatment with Dermatophagoides farinae drops can effectively control the symptoms of rhinitis and asthma in children with allergic rhinitis and asthma before and after puberty, reduce the use of symptomatic drugs, significantly improve the pulmonary function of patients, and have better effects on asthma in prepubertal children than in adolescents.

Antibacterial activity of closantel against methicillin-resistant Staphylococcus aureus and itsbiofilm. / æ°¯æ°°ç¢˜æŸ³èƒºå¯¹è€ç”²æ°§è¥¿æž—é‡‘é»„è‰²è‘¡è„çƒèŒåŠå ¶ç”Ÿç‰©è†œçš„æŠ—èŒæ´»æ€§.

OBJECTIVES: The antimicrobial resistance of Staphylococcus aureus (S. aureus) has become a challenge in the treatment of infectious diseases. It is of great clinical value to discovery effective antimicrobial agents against multi-drug resistant S. aureus and its biofilms. This study aims to explore the antibacterial activity of the antiparasitic drug closantel against methicillin-resistant S. aureus and its biofilms through drug repurposing. METHODS: The sensitivity of S. aureus to closantel was assessed using microbroth dilution and disk diffusion methods. The bacteriostatic and bactericidal activities of closantel were determined by time-kill curves and colony count. Scanning electron microscopy combined with SYTOX Green and DiSC3(5) fluorescence probes were used to study the bactericidal mechanism of closantel. The influence of resistance was assessed by continuous exposure to sub-inhibitory concentrations of closantel. The anti-biofilm activity was evaluated using 96-well plates and crystal violet staining, and cytotoxicity was measured using the CCK-8 assay. RESULTS: The minimal inhibitory concentration (MIC) of closantel for both methicillin-sensitive and methicillin-resistant S. aureus ranged from 0.125 to 1.000 µg/mL. Disk diffusion tests showed that 80 µg of closantel created an inhibition zone, which increased in diameter with higher drug amounts. Sub-inhibitory concentrations (0.031 µg/mL) of closantel significantly inhibited S. aureus proliferation, reducing bacterial turbidity from 0.26±0.00 to 0.11±0.01 (t=16.06, P<0.001), with stronger inhibition at higher concentrations. Closantel at 0.25×MIC inhibited S. aureus proliferation for 12 hours, while 1×MIC inhibited it for over 24 hours, with the number of viable bacteria decreasing as the drug concentration increased. Mechanistic studies indicated that closantel effectively disrupted the integrity of S. aureus cell membranes, significantly increasing SYTOX Green and DiSC3(5) fluorescence intensity. Even after 25 days of continuous exposure to sub-inhibitory concentrations of closantel, no resistance developed. Closantel at 0.0625 µg/mL significantly inhibited biofilm formation, reducing it from 1.29±0.16 to 0.62±0.04 (t=11.62, P<0.001), showing a clear dose-dependent effect. Closantel at 2 µg/mL also significantly eradicated established biofilms, reducing biofilm mass from 1.62±0.34 to 0.51±0.39 (t=4.84, P<0.01). Additionally, closantel exhibited extremely low cytotoxicity, with half-maximal lethal concentrations for HepG2 liver cancer cells and normal LO2 liver cells both exceeding 64 µg/mL. CONCLUSIONS: Closantel exhibits strong antibacterial activity against S. aureus and its biofilm with low cytotoxicity against human cells, making it a promising candidate for new therapeutic strategies against S. aureus-related infections.

ESRRG-PKM2 axis reprograms metabolism to suppress esophageal squamous carcinoma progression and enhance anti-PD-1 therapy efficacy.

BACKGROUND: Glycolysis under normoxic conditions, known as the Warburg effect, confers a selective advantage for the survival and proliferation of many tumors. In this study, we investigated the role of estrogen-related receptor gamma (ESRRG) in metabolic reprogramming in esophageal squamous cell carcinoma (ESCC). METHODS: Bioinformatics analysis indicated that ESRRG expression was decreased in ESCC tissue and associated with poor clinical outcomes. We also examined the effects of altered ESRRG expression on the proliferation and metabolic reprogramming of ESCC cells. We explored the impact of ESRRG on Pyruvate kinase M2 (PKM2) expression and malignant behavior in ESCC. RESULTS: Our study revealed the inhibitory effects of ESRRG on the growth, tumorigenesis, and glycolysis activity of ESCC cells, which were mediated by the downregulation of PKM2 expression. We further demonstrated that ESRRG directly interacts with the PKM2 promoter to inhibit its activity in ESCC. Notably, the ESRRG-specific agonist, DY131, inhibited ESCC cell proliferation and glycolysis activity by modulating genes in the glycolysis pathway. Moreover, we verified that DY131 exhibits enhanced activity as an immune checkpoint inhibitor, considering the significance of the ESRRG-PKM2 axis in the lactate regulation of ESCC cells. CONCLUSION: Our findings provide novel insights into the role of ESRRG-PKM2 signaling in regulating ESCC cell metabolism and immune checkpoint regulation. Additionally, we suggest that DY131 holds promise as a promising therapeutic agent for ESCC treatment.

Renal tubular epithelial cell necroptosis promotes tubulointerstitial fibrosis in patients with chronic kidney disease.

Renal fibrosis, a common pathological manifestation of virtually all types of chronic kidney disease (CKD), ultimately predisposes patients to end-stage renal disease. However, there is no effective therapy for renal fibrosis. Our earlier studies proved that RIP3-mediated necroptosis might be an important mode of renal tubular cell death in rats with chronic renal injury. Under transmission electron microscopy (TEM), we found morphological changes in the necrosis of human renal tissue, and the percentage of necrotic cells increased significantly in patients with stages 2 and 3a CKD. Immunofluorescence analyses showed that the percentages of TUNEL+ /RIP3+ double-positive and TUNEL+ /MLKL+ double-positive tubular epithelial cells in renal tubules of patients with stages 2 and 3a CKD were significantly increased compared to those in control patients without renal disease. Immunohistochemistry analyses of renal biopsy specimens from patients with CKD revealed RIP3, MLKL, and p-MLKL upregulation in patients with stages 2 and 3a CKD, suggesting that necroptosis of renal tubular epithelial cells in CKD patients occurs, and the peak of necroptosis was in stages 2 and 3a CKD. We showed that profibrotic factor proteins (TGF-ß1, Smad2 and Smad3) and fibroblast activation markers (α-SMA and Vimentin) were specifically upregulated in stage 2 and 3a CKD patients. In addition, Pearson correlation analysis showed that the percentage of necroptotic renal tubular epithelial cells was positively correlated with TGF-ß1 and collagen-I. We also showed that RIP1/3 or MLKL inhibitors decreased the expression of RIP3, MLKL, TGF-ß1, and Smad3 in HK-2 cells treated with TNF-α. FGF-2, α-SMA, Vimentin and FN were overexpressed in the hRIFs cultured with the supernatant of necroptotic HK-2 cells, whereas necroptosis blockers (Nec-1s, GSK'872 and NSA) and TGF-ß1/Smad3 pathway antagonists (LY364947 and SIS3) reduced FGF-2, α-SMA, Vimentin and FN levels. Collectively, necroptosis of renal tubular epithelial cells in CKD patients occurs, and the peak of necroptosis was in stages 2 and 3a CKD. Renal tubular epithelial cell necroptosis mediates renal tubulointerstitial fibrosis in patients with chronic kidney disease, which is related to the TGF-ß1/Smad3 signaling pathway.

The characteristics and clinical relevance of tumor fusion burden in non-EBV (+) gastric cancer with MSS.

BACKGROUND: Next-generation sequencing (NGS) is maturely applied for gene fusion detection. Although tumor fusion burden (TFB) has been identified as an immune marker for cancer, the relationship between these fusions and the immunogenicity and molecular characteristics of gastric cancer (GC) patients remains unclear. GCs have different clinical significance depending on their subtypes, and thus, this study aimed to investigate the characteristics and clinical relevance of TFB in non-Epstein-Barr-virus-positive (EBV+) GC with microsatellite stability (MSS). METHODS: A total of 319 GC patients from The Cancer Genome Atlas stomach adenocarcinoma (TCGA-STAD) and a cohort of 45-case from ENA (PRJEB25780) were included. The cohort characteristics and distribution of TFB among the patients were analyzed. Additionally, the correlations of TFB with mutation characteristics, pathway differences, relative abundance of immune cells, and prognosis were examined in the TCGA-STAD cohort of MSS and non-EBV (+) patients. RESULTS: We observed that in the MSS and non-EBV (+) cohort, the TFB-low group exhibited significantly lower gene mutation frequency, gene copy number, loss of heterozygosity score, and tumor mutation burden than in the TFB-high group. Additionally, the TFB-low group exhibited a higher abundance of immune cells. Furthermore, the immune gene signatures were significantly upregulated in the TFB-low group, 2-year disease-specific survival was markedly increased in the TFB-low group compared with to the TFB-high group. The rates of TFB-low cases were significantly higher TFB-than high cases in durable clinical benefit (DCB) and response groups with pembrolizumab treatment. Low TFB may serve as a predictor of GC prognosis, and the TFB-low group exhibits higher immunogenicity. CONCLUSION: In conclusion, this study reveals that the TFB-based classification of GC patient may be instructive for individualized immunotherapy regimens.

An Exploratory Study of Medical Journal's Twitter Use: Metadata, Networks, and Content Analyses.

BACKGROUND: An increasing number of medical journals are using social media to promote themselves and communicate with their readers. However, little is known about how medical journals use Twitter and what their social media management strategies are. OBJECTIVE: This study aimed to understand how medical journals use Twitter from a global standpoint. We conducted a broad, in-depth analysis of all the available Twitter accounts of medical journals indexed by major indexing services, with a particular focus on their social networks and content. METHODS: The Twitter profiles and metadata of medical journals were analyzed along with the social networks on their Twitter accounts. RESULTS: The results showed that overall, publishers used different strategies regarding Twitter adoption, Twitter use patterns, and their subsequent decisions. The following specific findings were noted: journals with Twitter accounts had a significantly higher number of publications and a greater impact than their counterparts; subscription journals had a slightly higher Twitter adoption rate (2%) than open access journals; journals with higher impact had more followers; and prestigious journals rarely followed other lesser-known journals on social media. In addition, an in-depth analysis of 2000 randomly selected tweets from 4 prestigious journals revealed that The Lancet had dedicated considerable effort to communicating with people about health information and fulfilling its social responsibility by organizing committees and activities to engage with a broad range of health-related issues; The New England Journal of Medicine and the Journal of the American Medical Association focused on promoting research articles and attempting to maximize the visibility of their research articles; and the British Medical Journal provided copious amounts of health information and discussed various health-related social problems to increase social awareness of the field of medicine. CONCLUSIONS: Our study used various perspectives to investigate how medical journals use Twitter and explored the Twitter management strategies of 4 of the most prestigious journals. Our study provides a detailed understanding of medical journals' use of Twitter from various perspectives and can help publishers, journals, and researchers to better use Twitter for their respective purposes.

Ixazomib Induces Apoptosis and Suppresses Proliferation in Esophageal Squamous Cell Carcinoma through Activation of the c-Myc/NOXA Pathway.

Esophageal squamous cell carcinoma (ESCC) is one of the major subtypes of esophageal cancer. More than half of the patients with ESCC in the world are in China, and the 5-year survival rate is less than 10%. As a new oral proteasome inhibitor, ixazomib has shown strong therapeutic effect in many solid tumors. In this study, we aimed to investigate the effects of ixazomib on the proliferation inhibition and apoptosis of ESCC cells. We used four human ESCC cell lines, cell viability assay, cell cycle and apoptosis assay, reverse-transcription polymerase chain reaction (RT-PCR), Western blot, immunohistochemistry, and ESCC xenografts model to clarify the roles of the therapeutic effect and mechanism of ixazomib in ESCC. Ixazomib significantly inhibited the proliferation and induced apoptosis in ESCC cells. RT-PCR results showed that the expressions of endoplasmic reticulum stress-related gene phorbol-12-myristate-13-acetate-induced protein 1 (NOXA) and MYC proto-oncogene (c-Myc) significantly increase after treatment with ixazomib in ESCC cells. When we knocked down the NOXA and c-Myc by small interfering RNA, the therapeutic effect of ixazomib markedly decreased, which confirmed that c-Myc/NOXA pathway played a key role in the treatment of ESCC with ixazomib. In vivo, the xenograft ESCC model mice were given 10 mg/kg of ixazomib every other day for 30 days. The results showed that the tumor size in the treatment group was significantly smaller than the control group. These results suggested that ixazomib is known to suppress proliferation and induce apoptosis in ESCC cell lines, and this effect was likely mediated by increased activation of the c-Myc/NOXA signaling pathways. SIGNIFICANCE STATEMENT: Esophageal squamous cell carcinoma (ESCC) is the common worldwide malignant tumor, but conventional chemotherapeutics suffer from a number of limitations. In this study, the results suggested that ixazomib suppresses proliferation and induces apoptosis in ESCC cell lines. Therefore, ixazomib may be a potential new strategy for ESCC therapy.

Network embedding in biomedical data science.

Owning to the rapid development of computer technologies, an increasing number of relational data have been emerging in modern biomedical research. Many network-based learning methods have been proposed to perform analysis on such data, which provide people a deep understanding of topology and knowledge behind the biomedical networks and benefit a lot of applications for human healthcare. However, most network-based methods suffer from high computational and space cost. There remain challenges on handling high dimensionality and sparsity of the biomedical networks. The latest advances in network embedding technologies provide new effective paradigms to solve the network analysis problem. It converts network into a low-dimensional space while maximally preserves structural properties. In this way, downstream tasks such as link prediction and node classification can be done by traditional machine learning methods. In this survey, we conduct a comprehensive review of the literature on applying network embedding to advance the biomedical domain. We first briefly introduce the widely used network embedding models. After that, we carefully discuss how the network embedding approaches were performed on biomedical networks as well as how they accelerated the downstream tasks in biomedical science. Finally, we discuss challenges the existing network embedding applications in biomedical domains are faced with and suggest several promising future directions for a better improvement in human healthcare.

Endoscopic Cyanoacrylate Injection Versus Balloon-Occluded Retrograde Transvenous Obliteration for Prevention of Gastric Variceal Bleeding: A Randomized Controlled Trial.

BACKGROUND AND AIMS: The optimal treatment for gastric varices (GVs) is a topic that remains open for study. This study compared the efficacy and safety of endoscopic cyanoacrylate injection and balloon-occluded retrograde transvenous obliteration (BRTO) to prevent rebleeding in patients with cirrhosis and GVs after primary hemostasis. APPROACH AND RESULTS: Patients with cirrhosis and history of bleeding from gastroesophageal varices type 2 or isolated gastric varices type 1 were randomized to cyanoacrylate injection (n = 32) or BRTO treatment (n = 32). Primary outcomes were gastric variceal rebleeding or all-cause rebleeding. Patient characteristics were well balanced between two groups. Mean follow-up time was 27.1 ± 12.0 months in a cyanoacrylate injection group and 27.6 ± 14.3 months in a BRTO group. Probability of gastric variceal rebleeding was higher in the cyanoacrylate injection group than in the BRTO group (P = 0.024). Probability of remaining free of all-cause rebleeding at 1 and 2 years for cyanoacrylate injection versus BRTO was 77% versus 96.3% and 65.2% versus 92.6% (P = 0.004). Survival rates, frequency of complications, and worsening of esophageal varices were similar in both groups. BRTO resulted in fewer hospitalizations, inpatient stays, and lower medical costs. CONCLUSIONS: BRTO is more effective than cyanoacrylate injection in preventing rebleeding from GVs, with similar frequencies of complications and mortalities.

Mutational landscape of DNA damage response deficiency-related genes and its association with immune biomarkers in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) has limited effective treatment strategies. DNA damage response (DDR) genes are of therapeutic interest in multiple cancer types. This study aimed to depict the landscape of DDR mutations in ESCC and evaluate the association between DDR mutations and known immunotherapy biomarkers. We recruited 250 Chinese patients with ESCC and performed next-generation sequencing. A total of 107 patients underwent a PD-L1 examination. Among the 250 patients, 73 (29.2%) harbored at least one DDR gene mutation and were defined as DDR-mut. Among the six functional DDR pathways, homologous recombination (HR) accounted for 12.4% (31/250). DDR-mut patients were significantly associated with higher tumor mutational burden than those in the DDR-wt group (p=7.4e-07). Patients with PDL1-H accounted for 21.2% (36/107) of the patients. PDL1-H was more prevalent in DDR-mut than DDR-wt, although the p-value did not reach a significant level (40.5% vs. 30%, p=0.29). Further analysis revealed that BRCA1, one of the most frequently mutated genes in the HR pathway, was significantly associated with PDL1-H (p=0.01). Our data revealed a subset of patients with ESCC harbored DDR gene mutations. Patients with these DDR gene mutations are significantly associated with immune biomarkers, implying the potential feasibility of combining DDR agents with immunotherapy in patients with DDR deficiency.

Managing thrombosis of arteriovenous fistula accompanied by aneurysm and single outflow of elbow perforating vein: a case report.

BACKGROUND: We report a case of a patient who suffered thrombosis of a radial artery-cephalic vein fistula accompanied by aneurysm and a single outflow path of the elbow perforating vein. We performed open surgery combined with Fogarty balloon catheter embolectomy, anastomotic reconstruction and forearm median vein transposition. CASE PRESENTATION: The patient presented with an arteriovenous fistula (AVF) after haemodialysis 5 years ago. In the process of dialysis, the fistula vein was punctured, resulting in aneurysm, high pressure and difficult haemostasis after needle extraction. AVF occlusion was observed on April 12, 2022. We performed a combined open surgery. First, a Fogarty balloon catheter was used to remove the thrombus, and the anastomosis was then reconstructed to restore AVF fistula patency. Finally, forearm median vein transposition was used to establish dual outflow. Postoperative haemodialysis was possible. There are various methods for removing the thrombus in AVF. Here, we report a case in which we performed open surgery combined with Fogarty balloon catheter embolectomy, anastomotic reconstruction and forearm median vein transposition to ensure fistula patency. CONCLUSION: We removed a complete reverse 'Z'-shaped thrombus of the elbow perforating vein in a haemodialysis fistula. This report provides an effective strategy to manage a high-pressure fistula with single outflow of the elbow perforating vein.

Understanding the Research Landscape of Deep Learning in Biomedical Science: Scientometric Analysis.

BACKGROUND: Advances in biomedical research using deep learning techniques have generated a large volume of related literature. However, there is a lack of scientometric studies that provide a bird's-eye view of them. This absence has led to a partial and fragmented understanding of the field and its progress. OBJECTIVE: This study aimed to gain a quantitative and qualitative understanding of the scientific domain by analyzing diverse bibliographic entities that represent the research landscape from multiple perspectives and levels of granularity. METHODS: We searched and retrieved 978 deep learning studies in biomedicine from the PubMed database. A scientometric analysis was performed by analyzing the metadata, content of influential works, and cited references. RESULTS: In the process, we identified the current leading fields, major research topics and techniques, knowledge diffusion, and research collaboration. There was a predominant focus on applying deep learning, especially convolutional neural networks, to radiology and medical imaging, whereas a few studies focused on protein or genome analysis. Radiology and medical imaging also appeared to be the most significant knowledge sources and an important field in knowledge diffusion, followed by computer science and electrical engineering. A coauthorship analysis revealed various collaborations among engineering-oriented and biomedicine-oriented clusters of disciplines. CONCLUSIONS: This study investigated the landscape of deep learning research in biomedicine and confirmed its interdisciplinary nature. Although it has been successful, we believe that there is a need for diverse applications in certain areas to further boost the contributions of deep learning in addressing biomedical research problems. We expect the results of this study to help researchers and communities better align their present and future work.

PDL1-positive exosomes suppress antitumor immunity by inducing tumor-specific CD8+ T cell exhaustion during metastasis.

Metastasis is the main cause of death in individuals with cancer. Immune checkpoint blockade (ICB) can potentially reverse CD8+ cytotoxic T lymphocytes (CTLs) dysfunction, leading to significant remission in multiple cancers. However, the mechanism underlying the development of CTL exhaustion during metastatic progression remains unclear. Here, we established an experimental pulmonary metastasis model with melanoma cells and discovered a critical role for melanoma-released exosomes in metastasis. Using genetic knockdown of nSMase2 and Rab27a, 2 key enzymes for exosome secretion, we showed that high levels of effector-like tumor-specific CD8+ T cells with transitory exhaustion, instead of terminal exhaustion, were observed in mice without exosomes; these cells showed limited inhibitory receptors and strong proliferation and cytotoxicity. Mechanistically, the immunosuppression of exosomes depends on exogenous PD-L1, which can be largely rescued by pretreatment with antibody blockade. Notably, we also found that exosomal PD-L1 acts as a promising predictive biomarker for ICB therapies during metastasis. Together, our findings suggest that exosomal PD-L1 may be a potential immunotherapy target, suggesting a new curative therapy for tumor metastasis.

Drug knowledge bases and their applications in biomedical informatics research.

Recent advances in biomedical research have generated a large volume of drug-related data. To effectively handle this flood of data, many initiatives have been taken to help researchers make good use of them. As the results of these initiatives, many drug knowledge bases have been constructed. They range from simple ones with specific focuses to comprehensive ones that contain information on almost every aspect of a drug. These curated drug knowledge bases have made significant contributions to the development of efficient and effective health information technologies for better health-care service delivery. Understanding and comparing existing drug knowledge bases and how they are applied in various biomedical studies will help us recognize the state of the art and design better knowledge bases in the future. In addition, researchers can get insights on novel applications of the drug knowledge bases through a review of successful use cases. In this study, we provide a review of existing popular drug knowledge bases and their applications in drug-related studies. We discuss challenges in constructing and using drug knowledge bases as well as future research directions toward a better ecosystem of drug knowledge bases.

MiR-467b alleviates lipopolysaccharide-induced inflammation through targeting STAT1 in chondrogenic ATDC5 cells.

Osteoarthritis (OA) is one of the most common degenerative joint diseases worldwide. Chondrocytes are activated in OA patients, accompanied by excessive chondrogenic proliferation and production of inflammatory cytokines. MiR-467b is implicated in the regulation of artherosclerosis and pro-inflammatory cytokine secretion. However, the precise role of miR-467b in OA remains unclear. In the present study, we induced inflammation in chondrogenic ATDC5 cells using lipopolysaccharide (LPS). LPS treatment significantly elevated the production of interleukin-6 (IL-6), IL-1ß and tumour necrosis factor-α (TNF-α) in ATDC5 cells, accompanied by decreased miR-467 level. Then, we over-expressed miR-467b using its specific mimics in ATDC5 cells, and LPS-induced inflammation was significantly inhibited as evidenced by decreased IL-6, IL-1ß and TNF-α levels. MiR-467b agomir also alleviated inflammation in rat knee osteoarthritis (KOA) model. In addition, we validated that signal transducer and activator of transcription 1 (STAT1) was a downstream target of miR-467b. LPS treatment significantly increased the STAT1 expression while miR-467b mimic transfection partially reversed this effect. Moreover, STAT1 knockout reversed the increased contents of IL-6, IL-1ß and TNF-α. Furthermore, miR-467b over-expression significantly decreased the production of IL-6, IL-1ß and TNF-α induced by LPS treatment, which was partially reversed by further STAT1 over-expression. In summary, our findings demonstrated that miR-467b alleviated LPS-induced inflammation through targeting STAT1, and this miR-467b/STAT1 regulation axis may provide a new therapeutic target for OA clinical management.

Homozygous mutations in SPEF2 induce multiple morphological abnormalities of the sperm flagella and male infertility.

BACKGROUND: Male infertility due to multiple morphological abnormalities of the sperm flagella (MMAF) is a genetically heterogeneous disorder. Previous studies revealed several MMAF-associated genes, which account for approximately 60% of human MMAF cases. The pathogenic mechanisms of MMAF remain to be illuminated. METHODS AND RESULTS: We conducted genetic analyses using whole-exome sequencing in 50 Han Chinese probands with MMAF. Two homozygous stop-gain variants (c.910C>T (p.Arg304*) and c.3400delA (p.Ile1134Serfs*13)) of the SPEF2 (sperm flagellar 2) gene were identified in two unrelated consanguineous families. Consistently, an Iranian subject from another cohort also carried a homozygous SPEF2 stop-gain variant (c.3240delT (p.Phe1080Leufs*2)). All these variants affected the long SPEF2 transcripts that are expressed in the testis and encode the IFT20 (intraflagellar transport 20) binding domain, important for sperm tail development. Notably, previous animal studies reported spontaneous mutations of SPEF2 causing sperm tail defects in bulls and pigs. Our further functional studies using immunofluorescence assays showed the absence or a remarkably reduced staining of SPEF2 and of the MMAF-associated CFAP69 protein in the spermatozoa from SPEF2-affected subjects. CONCLUSIONS: We identified SPEF2 as a novel gene for human MMAF across the populations. Functional analyses suggested that the deficiency of SPEF2 in the mutated subjects could alter the localisation of other axonemal proteins.

Ghrelin Affects Gastric Cancer Progression by Activating AMPK Signaling Pathway.

As the endogenous ligand for the GH secretagogue receptor (GHSR), Ghrelin is aberrant expressed in multiple malignant carcinoma, and involved in regulating a number of progression of cancer, especially in metastasis and proliferation. However, the precise role of Ghrelin in tumorigenesis of gastric cancer (GC) is still poorly understood. In this study, we extensively investigated the roles and mechanisms of Ghrelin in human gastric cancer. Ghrelin levels in cancer tissues and cell lines were analyzed by immunohistochemistry, qRT-PCR, and Western blot. Functional studies were performed after Ghrelin overexpressed or knockdown in AGS cell line. Cell proliferation was evaluated in by MTT and clone formation assays. The wound healing and Transwell system were used to assess the cell migration and invasive ability of GC cells. Cell apoptosis was detected by flow cytometry, and metabolic assays were performed to reveal the function of Warburg effect in the process. Ghrelin was lowly expressed in gastric cancer tissues and cell lines. Overexpression of Ghrelin inhibited gastric cancer cell proliferation, migration, invasion, and promoted apoptosis by activating the AMPK pathway, while D-[lys3]-GHRP-6 (a GHSR agonist) treatment relieved the effect, promoting tumorigenesis. Ghrelin knockdown increased the glucose uptake and lactic acid release, suggesting that Ghrelin elicited an anti-Warburg effect via AMPK pathway to inhibit gastric tumorigenesis. Ghrelin inhibits cell proliferation, migration, and invasion by eliciting an anti-Warburg effect via AMPK signaling pathway in gastric cancer cells.

POLE2 knockdown reduce tumorigenesis in esophageal squamous cells.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is one of the most frequent malignant tumors originated from digestive system around the world and the treatment was limited by the unclear mechanism. DNA polymerase epsilon 2, accessory subunit (POLE2) is involved in DNA replication, repair, and cell cycle control, whose association with ESCC is still not clear. METHODS: In this study, the expression level of POLE2 in ESCC tissues was detected by IHC. The POLE2 knockdown cell line was constructed, identified by qPCR and western blot and used for detecting cellular functions and constructing xenotransplantation mice model. MTT Assay, colony formation assay, flow cytometry, wound-healing assay and Transwell assay were used to detected cell proliferation, apoptosis and migration. RESULTS: We firstly identified that the expression of POLE2 was overexpressed in ESCC. Moreover, the high expression of POLE2 can predict the tumor deterioration and poor prognosis of ESCC patients. Additionally, downregulation of POLE2 was involved in ESCC progression by promoting proliferation, migration, and inhibiting apoptosis in vitro. In vivo studies proved that POLE2 was positively correlated with ESCC tumor formation, which was consistent with the results in vitro. We also illuminated that POLE2 knockdown upregulated pro-apoptotic proteins (Bax, Caspase3, CD40L, FasL, IGFBP-5 and P21) and downregulated anti-apoptotic proteins (CLAP-2, IGF-I and sTNF-R2). In addition, POLE2 was involved in ESCC via targeting PI3K/Akt, Cyclin D1 signaling pathway. CONCLUSIONS: Therefore, POLE2 was proved to be involved in the development of ESCC, which may be a potential therapeutic target and bring new breakthroughs in the treatment of ESCC.