FAM83B promotes cell proliferation via regulating the expression of CDK4/CDK6/CCND1 complex in laryngeal squamous cell carcinoma.

FAM83B, as one of the FAM83 family members, has been closely involved in cell transformation, and a growing number of scholars have been studied its role in tumours over the years. Whereas the effect and potential mechanism of FAM83B in laryngeal squamous cell carcinoma (LSCC) have not been investigated. In this research, we discovered that the expression quantity of FAM83B was remarkably higher in LSCC tissues (79.65 ± 35.98) than in matched adjacent tissues (59.34 ± 32.59) by tissue microarrays and immunohistochemistry. Furthermore, expression of FAM83B was knocked down in HEP-2 and TU177 cell lines via lentivirus, and in the course of intracorporal and extracorporeal experiments, FAM83B knockdown showed the inhibition of tumour growth, migration, and invasion ability. Moreover, cell cycle assay showed that FAM83B knockdown leads to an apparent accumulation of cells in the G1 phase, indicating that FAM83B knockdown can inhibit cell proliferation. Meanwhile, western blotting (WB) demonstrated that FAM83B knockdown led to a significant reduction in CDK4/CDK6/CCND1 protein expression, which may have decelerated cell cycle progression. Collectively, this study demonstrates that FAM83B serves as an oncogene in LSCC, promoting cell proliferation by controlling the protein expression of CDK4, CDK6, and CCND1, thus inducing a transference of the G1 stage to S stage in cell-cycle of LSCC cells. These results provide an academic foundation for elucidating the mechanism of LSCC occurrence and evolution and for developing treatment strategies for LSCC.

DeepLION2: deep multi-instance contrastive learning framework enhancing the prediction of cancer-associated T cell receptors by attention strategy on motifs.

Introduction: T cell receptor (TCR) repertoires provide valuable insights into complex human diseases, including cancers. Recent advancements in immune sequencing technology have significantly improved our understanding of TCR repertoire. Some computational methods have been devised to identify cancer-associated TCRs and enable cancer detection using TCR sequencing data. However, the existing methods are often limited by their inadequate consideration of the correlations among TCRs within a repertoire, hindering the identification of crucial TCRs. Additionally, the sparsity of cancer-associated TCR distribution presents a challenge in accurate prediction. Methods: To address these issues, we presented DeepLION2, an innovative deep multi-instance contrastive learning framework specifically designed to enhance cancer-associated TCR prediction. DeepLION2 leveraged content-based sparse self-attention, focusing on the top k related TCRs for each TCR, to effectively model inter-TCR correlations. Furthermore, it adopted a contrastive learning strategy for bootstrapping parameter updates of the attention matrix, preventing the model from fixating on non-cancer-associated TCRs. Results: Extensive experimentation on diverse patient cohorts, encompassing over ten cancer types, demonstrated that DeepLION2 significantly outperformed current state-of-the-art methods in terms of accuracy, sensitivity, specificity, Matthews correlation coefficient, and area under the curve (AUC). Notably, DeepLION2 achieved impressive AUC values of 0.933, 0.880, and 0.763 on thyroid, lung, and gastrointestinal cancer cohorts, respectively. Furthermore, it effectively identified cancer-associated TCRs along with their key motifs, highlighting the amino acids that play a crucial role in TCR-peptide binding. Conclusion: These compelling results underscore DeepLION2's potential for enhancing cancer detection and facilitating personalized cancer immunotherapy. DeepLION2 is publicly available on GitHub, at https://github.com/Bioinformatics7181/DeepLION2, for academic use only.

Decreased NMIIA heavy chain phosphorylation at S1943 promotes mitoxantrone resistance by upregulating BCRP and N-cadherin expression in breast cancer cells.

Mitoxantrone (MX) is an effective treatment for breast cancer; however, high efflux of MX that is accomplished by breast cancer resistance protein (BCRP) leads to acquired multidrug resistance (MDR), reducing MX's therapeutic efficacy in breast cancer. Non-muscle myosin IIA (NMIIA) and its heavy phosphorylation at S1943 have been revealed to play key roles in tumor metastasis and progression, including in breast cancer; however, their molecular function in BCRP-mediated MDR in breast cancer remains unknown. In this study, we revealed that the expression of NMIIA heavy chain phosphorylation at S1943 was downregulated in BCRP-overexpressing breast cancer MCF-7/MX cells, and stable expression of NMIIA-S1943A mutant increased BCRP expression and promoted the resistance of MCF-7/MX cells to MX. Meanwhile, NMIIA S1943 phosphorylation induced by epidermal growth factor (EGF) was accompanied by the downregulation of BCRP in MCF-7/MX cells. Furthermore, stable expression of NMIIA-S1943A in MCF-7/MX cells resulted in upregulation of N-cadherin and the accumulation of ß-catenin on the cell surface, which inhibited the nucleus translocation of ß-catenin and Wnt/ß-catenin-based proliferative signaling. EGF stimulation of MCF-7/MX cells showed the downregulation of N-cadherin and ß-catenin. Our results suggest that decreased NMIIA heavy phosphorylation at S1943 increases BCRP expression and promotes MX resistance in breast cancer cells via upregulating N-cadherin expression.

An independent evaluation in a CRC patient cohort of microbiome 16S rRNA sequence analysis methods: OTU clustering, DADA2, and Deblur.

16S rRNA is the universal gene of microbes, and it is often used as a target gene to obtain profiles of microbial communities via next-generation sequencing (NGS) technology. Traditionally, sequences are clustered into operational taxonomic units (OTUs) at a 97% threshold based on the taxonomic standard using 16S rRNA, and methods for the reduction of sequencing errors are bypassed, which may lead to false classification units. Several denoising algorithms have been published to solve this problem, such as DADA2 and Deblur, which can correct sequencing errors at single-nucleotide resolution by generating amplicon sequence variants (ASVs). As high-resolution ASVs are becoming more popular than OTUs and only one analysis method is usually selected in a particular study, there is a need for a thorough comparison of OTU clustering and denoising pipelines. In this study, three of the most widely used 16S rRNA methods (two denoising algorithms, DADA2 and Deblur, along with de novo OTU clustering) were thoroughly compared using 16S rRNA amplification sequencing data generated from 358 clinical stool samples from the Colorectal Cancer (CRC) Screening Cohort. Our findings indicated that all approaches led to similar taxonomic profiles (with P > 0.05 in PERMNAOVA and P <0.001 in the Mantel test), although the number of ASVs/OTUs and the alpha-diversity indices varied considerably. Despite considerable differences in disease-related markers identified, disease-related analysis showed that all methods could result in similar conclusions. Fusobacterium, Streptococcus, Peptostreptococcus, Parvimonas, Gemella, and Haemophilus were identified by all three methods as enriched in the CRC group, while Roseburia, Faecalibacterium, Butyricicoccus, and Blautia were identified by all three methods as enriched in the healthy group. In addition, disease-diagnostic models generated using machine learning algorithms based on the data from these different methods all achieved good diagnostic efficiency (AUC: 0.87-0.89), with the model based on DADA2 producing the highest AUC (0.8944 and 0.8907 in the training set and test set, respectively). However, there was no significant difference in performance between the models (P >0.05). In conclusion, this study demonstrates that DADA2, Deblur, and de novo OTU clustering display similar power levels in taxa assignment and can produce similar conclusions in the case of the CRC cohort.

miR-31 ameliorates type 2 diabetic vascular damage through up-regulation of hypoxia-inducible factor-1α/vascular endothelial growth factor-A.

AIMS: microRNA may be a new therapeutic direction for diabetes. As a typical tumor marker, miR-31 is involved in a variety of metabolic diseases, but the specific role is still unclear. This study aimed to investigate the effect of miR-31 on type 2 diabetes mellitus and its accompanying vascular injury, as well as on the effects of hypoxia-inducible factor-1α inhibitor (HIF1AN), hypoxia-inducible factor (HIF)-1α, and vascular endothelial growth factor (VEGF)-A expression in vitro and in vivo. MATERIALS AND METHODS: In vitro, a model of high-fat and high-glucose-induced human aortic endothelial cell (HAEC) injury was established to simulate diabetes mellitus (DM). Cell functions were compared between the control group, the DM damage group, and the group transfected with miR-31 after DM damage. In vivo, overexpressing miR-31 FVB mice and FVB mice were divided into the control and induced type 2 diabetes mellitus groups. Type 2 diabetes mellitus models were induced by a high-fat diet combined with streptozotocin. The lipid metabolism levels, viscera, and vascular damage were compared between the control and type 2 diabetes mellitus groups. RESULTS: In vitro, miR-31 improved the proliferation ability of damaged cells by targeting HIF1AN and up-regulating the expression of HIF-1α and VEGF-A. In vivo, miR-31 ameliorated the development of type 2 diabetes mellitus, disturbance of glucose and lipid metabolism, and damage to some organs. Meanwhile, miR-31 had a protective effect on vascular damage complicated by type 2 diabetes mellitus by increasing the levels of HIF-1α and VEGF-A. CONCLUSION: Our experiments show that miR-31 can delay the progression of type 2 diabetes mellitus and ameliorate diabetic vascular injury.

[Effect of deep needling "Tianshu" (ST25) on colonic motility in rats with slow transit constipation].

OBJECTIVE: To observe the effect of acupuncture of "Tianshu"(ST25) at different depths on colonic transportation function, expressions of colonic substance P (SP) and interstitial cells of Cajal (ICC) in rats with slow transit constipation (STC), so as to explore its mechanisms underlying improvement of STC．. METHODS: Fifty male Wistar rats were selected and randomly divided into control，STC model，conventional acupuncture，deep needling group 1 and deep needling group 2 groups，with 10 rats in each group．The STC model was established by gavage of 1 mg/mL compound diphenoxylate suspension (10 mg/kg), once every other day for 21 days, and rats of the control group were given the same dose of distilled water by gavage．EA (2 Hz, 2 mA) was applied to "Tianshu"(ST25), with the acupuncture needle inserted to a depth of 3 mm for rats of the conventional acupuncture group, 4.5 mm for those of deep needling group 1, and 10 mm for those of the deep needling group 2. The acupuncture needle was twirled for 1 min, then retained for 15 min each time, once a day for 15 consecutive days．Following modeling, rats of the 4 groups and the control group received gavage of active carbon 2 mL (100 g/L) for observing the excretion time of the first black stool grain to assess the intestinal transit function. The colonic myoelectric activities (frequency and amplitude) were recorded by using BIOPAC multichannel physiograph. The immunoactivity of SP and c-kit (a transmembrane protein kinase for identification of ICC) of colonic musculature was detected by immunohistochemistry. RESULTS: Compared with the control group，the time of excretion of the first black stool grain, and the amplitude of colonic electromyogram (EMG) were significantly increased (P<0.01), while the frequency of EMG, expressions of SP and c-kit (ICC) were significantly decreased in the model group (P<0.01). In contrast to the model group, both deep needling group 1 and 2 had a decrease in the time of excretion of the first black stool grain, and amplitude of intestinal EMG, and an increase of frequency of intestinal EMG, and immunoactivity of SP and c-kit (P<0.01). The effect of deep needling 2 is superior to that of deep needling 1 in reducing the time of excretion of the first black stool grain (P<0.05), lowering the amplitude of EMG of the gut smooth muscle (P<0.05) and in increasing the frequency of EMG (P<0.05) and the expressions of SP and c-kit (P<0.05). No significant changes were found in the levels of frequency and amplitude of EMG, and expressions of SP and c-kit after routine needling in comparison with the model group (P>0.05), except the excretion time of the first black stool grain (P<0.05). CONCLUSION: Deep needling at ST25 at depth of 4.5 mm and 10 mm，especially at depth of 10 mm，has a significant effect in promoting gut motility to ameliorate constipation in rats with STC, which may be related to its function in up-regulating the expressions of SP and ICC activity.

Metformin Alleviates Sepsis-Associated Myocardial Injury by Enhancing AMP-Activated Protein Kinase/Mammalian Target of Rapamycin Signaling Pathway-Mediated Autophagy.

ABSTRACT: Sepsis-associated myocardial injury is one of the main causes of death in intensive care units, and current clinical treatments have not been satisfactory. Therefore, finding an effective intervention is an urgent requirement. Metformin, an anti-type 2 diabetes drug, has been reported to be an autophagic activator agent that confers protection in some diseases. However, it is unclear whether it can provide defense against sepsis-associated myocardial injury. In this study, we investigated the cardioprotective effects of metformin pretreatment against lipopolysaccharide (LPS)-induced myocardial injury in C57BL/6J mice or H9c2 cells and the possible underlying mechanisms. Metformin was administered at a dose of 100 mg/kg for a week before LPS intraperitoneal injection. Twenty-four hours after LPS intervention, echocardiographic evaluation, reactive oxygen species measurement, Hoechst staining, western blotting, hematoxylin and eosin staining, and enzyme-linked immunosorbent assay were performed. Inhibitors of autophagy and AMP-activated protein kinase (AMPK) were used to further clarify the mechanisms involved. Metformin pretreatment effectively attenuated cardiac dysfunction, reduced the levels of myocardial enzymes, and alleviated cardiac hydroncus in LPS-treated mice. In addition, metformin restored the LPS-disrupted antioxidant defense and activated LPS-reduced autophagy by modulating the AMPK/mammalian target of rapamycin (AMPK/mTOR) pathway both in vivo and in vitro. The antioxidant effects of metformin on cardiomyocytes were abolished by the autophagy inhibitor 3-methyladenine (3-MA). Treatment with compound C, an AMPK inhibitor, reversed the metformin-induced autophagy in LPS-treated H9c2 cells. In conclusion, metformin pretreatment alleviates LPS-induced myocardial injury by activating AMPK/mTOR pathway-mediated autophagy.

Efficacy and safety of tai chi exercise on bone health: An umbrella review.

PURPOSE: To critically evaluate systematic reviews (SRs) of the Tai Chi (TC) exercise on bone health and provide more recently available evidence. METHODS: SRs with or without meta-analysis (MA) of TC on bone health were comprehensively searched in eight electronic databases (PubMed, EMBASE, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang Database, Chinese Biomedical Literature Database, and Chinese Scientific Journals Database) and in the international prospective register of systematic reviews of (PROSPERO) from initiation to March 2023. Descriptive analyses of SRs were performed, and reporting and methodological quality of the included SRs were evaluated using the updated version of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist and A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR-2). The certainty of the synthesized evidence was assessed with the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach. RESULTS: Eighteen SRs, 15 with MAs, were included. Forty-nine RCTs and 16 NRSIs with 3956 and 1157 participants, respectively, were included in these SRs. The reporting quality of the included SRs ranged from high to low, but most received critically low AMSTAR-2 scores. Efficacy of TC on nine bone health biomarkers has been explored, covering bone mineral density (BMD) and serum biomarkers. The results showed that compare to non-intervention, perimenopausal and postmenopausal participants who practiced TC may benefit in BMD of the lumbar spine [MD = 0.04, 95% CI (0.02, 0.07)], and femoral neck [MD = 0.04, 95% CI (0.02, 0.06)], but not BMD of the femoral proximal trochanter [MD = 0.02, 95% CI (0.00, 0.03)], ward's triangle [MD = 0.02, 95% CI (-0.01, 0.04)], and femoral shaft [SMD = 0.16, 95% CI (-0.11, 0.44)]. Elders practicing TC may benefit in BMD of the femoral neck [SMD = 0.28, 95% CI (0.10, 0.45)], femoral proximal trochanter [SMD = 0.39, 95% CI (0.05, 0.73)], and ward's triangle [SMD = 0.21, 95% CI (0.05,0.37)], but may not in BMD of lumbar spine [SMD = 0.03, 95% CI (-0.22, 0.27)]. CONCLUSION: We have low certainty that for perimenopausal and postmenopausal women, compare to those with no exercise, TC could improve BMD of the lumbar spine, femoral neck. We also have low certainty that in elder population, TC practitioners may benefit in BMD of femoral neck, and Ward's triangle. REGISTRATION: PROSPERO (CRD42020173543).

What makes TMB an ambivalent biomarker for immunotherapy? A subtle mismatch between the sample-based design of variant callers and real clinical cohort.

Tumor mutation burden (TMB) is a widely recognized biomarker for predicting the efficacy of immunotherapy. However, its use still remains highly controversial. In this study, we examine the underlying causes of this controversy based on clinical needs. By tracing the source of the TMB errors and analyzing the design philosophy behind variant callers, we identify the conflict between the incompleteness of biostatistics rules and the variety of clinical samples as the critical issue that renders TMB an ambivalent biomarker. A series of experiments were conducted to illustrate the challenges of mutation detection in clinical practice. Additionally, we also discuss potential strategies for overcoming these conflict issues to enable the application of TMB in guiding decision-making in real clinical settings.

OCRFinder: a noise-tolerance machine learning method for accurately estimating open chromatin regions.

Open chromatin regions are the genomic regions associated with basic cellular physiological activities, while chromatin accessibility is reported to affect gene expressions and functions. A basic computational problem is to efficiently estimate open chromatin regions, which could facilitate both genomic and epigenetic studies. Currently, ATAC-seq and cfDNA-seq (plasma cell-free DNA sequencing) are two popular strategies to detect OCRs. As cfDNA-seq can obtain more biomarkers in one round of sequencing, it is considered more effective and convenient. However, in processing cfDNA-seq data, due to the dynamically variable chromatin accessibility, it is quite difficult to obtain the training data with pure OCRs or non-OCRs, and leads to a noise problem for either feature-based approaches or learning-based approaches. In this paper, we propose a learning-based OCR estimation approach with a noise-tolerance design. The proposed approach, named OCRFinder, incorporates the ideas of ensemble learning framework and semi-supervised strategy to avoid potential overfitting of noisy labels, which are the false positives on OCRs and non-OCRs. Compared to different noise control strategies and state-of-the-art approaches, OCRFinder achieved higher accuracies and sensitivities in the experiments. In addition, OCRFinder also has an excellent performance in ATAC-seq or DNase-seq comparison experiments.

Acute and Subacute Toxicity Evaluation of Erythrocyte Membrane-Coated Boron Nitride Nanoparticles.

Boron nitride nanoparticles have been reported for boron drug delivery. However, its toxicity has not been systematically elucidated. It is necessary to clarify their potential toxicity profile after administration for clinical application. Here, we prepared erythrocyte membrane-coated boron nitride nanoparticles (BN@RBCM). We expect to use them for boron neutron capture therapy (BNCT) in tumors. In this study, we evaluated the acute toxicity and subacute toxicity of BN@RBCM of about 100 nm and determined the half-lethal dose (LD50) of the particles for mice. The results showed that the LD50 of BN@RBCM was 258.94 mg/kg. No remarkable pathological changes by microscopic observation were observed in the treated animals throughout the study period. These results indicate that BN@RBCM has low toxicity and good biocompatibility, which have great potential for biomedical applications.

[Adding acupoint identification into the textbook Meridians and Acupoints: preliminary assumption].

To deepen the understanding of the acupoint indications, clarify the targeting of acupoints, and provide a basis for the composition of acupuncture prescriptions, it is suggested to add acupoint identification into the textbook Meridians and Acupoints, and a preliminary assumption that relevant acupoints can be identified by taking the indications, locations, and meridians as the key points is proposed. In this paper, acupoints for treating stomach disease, acupoints of eye region, and five-shu points of lung meridian are taken as examples, combined with ancient literature and modern scientific research achievements, the main indications of acupoint is identified, which is of great significance to the discipline's development, talent training, and achievement transformation.

State-level metabolic comorbidity prevalence and control among adults age 50-plus with diabetes: estimates from electronic health records and survey data in five states.

BACKGROUND: Although treatment and control of diabetes can prevent complications and reduce morbidity, few data sources exist at the state level for surveillance of diabetes comorbidities and control. Surveys and electronic health records (EHRs) offer different strengths and weaknesses for surveillance of diabetes and major metabolic comorbidities. Data from self-report surveys suffer from cognitive and recall biases, and generally cannot be used for surveillance of undiagnosed cases. EHR data are becoming more readily available, but pose particular challenges for population estimation since patients are not randomly selected, not everyone has the relevant biomarker measurements, and those included tend to cluster geographically. METHODS: We analyzed data from the National Health and Nutritional Examination Survey, the Health and Retirement Study, and EHR data from the DARTNet Institute to create state-level adjusted estimates of the prevalence and control of diabetes, and the prevalence and control of hypertension and high cholesterol in the diabetes population, age 50 and over for five states: Alabama, California, Florida, Louisiana, and Massachusetts. RESULTS: The estimates from the two surveys generally aligned well. The EHR data were consistent with the surveys for many measures, but yielded consistently lower estimates of undiagnosed diabetes prevalence, and identified somewhat fewer comorbidities in most states. CONCLUSIONS: Despite these limitations, EHRs may be a promising source for diabetes surveillance and assessment of control as the datasets are large and created during the routine delivery of health care. TRIAL REGISTRATION: Not applicable.

Clinicopathological differences of high Fusobacterium nucleatum levels in colorectal cancer: A review and meta-analysis.

Objective: To systematically evaluate the significance of Fusobacterium nucleatum (Fn) levels the clinicopathological impacts of cancer. Methods: Literature from Pubmed, Embase, and Web of Science was retrieved to collect all English literatures on the correlation between Fn and cancer, and the quality of literatures collected was assessed based on the Newcastle-Ottawa Quality Assessment Scale. The heterogeneity and sensitivity were detected by Stata 14.0 software, and the correlation between Fn and cancer clinicopathological as the effect variables was assessed according to the odds ratio (OR) and 95% confidence interval (CI). The forest plot was drawn. Results: A total of 19 articles meeting the inclusion criteria were selected. The incidence of Fn prevalence varied considerably (range: 6.1 to 83.3%) and was greater than 10% in 13 of 19 studies. Compared with those with no/low Fn levels, the high levels of Fn was positively associated with vascular invasion, nerve invasion, depth of invasion, and distant metastasis [vascular invasion: OR = 1.66, 95%CI(1.07, 2.57), I 2 = 21.9%, fixed effect model; nerve invasion: OR = 1.36, 95%CI(1.00, 1.84), I 2 = 43.1%, fixed effect model; infiltration depth: OR = 1.94, 95%CI(1.20, 3.15), I 2 = 67.2%, random effect model; distant metastasis: OR = 1.80, 95%CI(1.23, 2.64), I 2 = 3.4%, fixed effect model]. Patients with MLH1 methylation always present a higher Fn levels than those without methylation [OR = 2.53, 95%CI(1.42, 4.53), P = 0.01, I 2 = 57.5%, random effect model]. Further, Fn was associatedwith the molecular characteristics of cancers [MSI-H Vs. MSS/MSI-low: OR = 2.92, 95%CI(1.61, 5.32), P = 0.01, I 2 = 63.2%, random effect model; High Vs. Low/Negative CIMP: OR = 2.23, 95%CI(1.64, 3.03), P = 0.01, I 2 = 64.2%, random effect model; KRAS mutation Vs. wild-type: OR = 1.24, 95%CI(1.04, 1.48), P = 0.02, I 2 = 27.0%, fixed effect model; Present Vs. Abscent BRAF mutations: OR = 1.88, 95%CI(1.44, 2.45), P = 0.01, I 2 = 24.2%, fixed effect model]. The cancer patients with high levels of Fn often have worse RFS than those with no/low Fn levels[OR = 1.14, 95%CI(0.61, 1.68), P = 0.01, I 2 = 80.7%, random effect model]. Conclusion: This review and meta-analysis showed that Fn could be used to predict unfavorable prognosis and function as potential prognostic biomarkers in colorectal cancer (CRC). Our data may have implications for targeting Fn to develop strategies for cancer prevention and treatment.

[Visual analysis of the acupoint prescription characteristics of acupuncture and moxibustion in treatment of rheumatoid arthritis].

Using the complex network technology, the characteristics of the core acupoint prescriptions and the application of acupuncture-moxibustion techniques were analyzed in treatment of rheumatoid arthritis (RA) so as to provide the evidences for acupoint selection and therapeutic methods for RA treated with acupuncture and moxibustion. The articles of acupuncture and moxibustion for treatment of RA in recent 20 years were collated and imported, and the database of the acupoint prescriptions was developed. Using Cytoscape 3.9.2 software, the acupoints in the prescriptions were visualized for the common occurrence network analysis. The association rule analysis was performed with IBM SPSS Modeler 18.0 software and the complex network analysis was by Gephi 0.9.2 software. A total of 798 articles were screened, in which, 3 258 prescriptions were extracted with 253 acupoints involved. The analysis of acupoint selection was conducted in terms of syndrome/pattern differentiation, acupoint locations and main acupoints, and therapeutic methods. The results showed that the most common TCM syndromes of RA included painful bi syndrome, wandering bi syndrome, fixed bi syndrome and bi syndrome due to wind, damp and heat. Regarding the core combination of acupoints, painful bi syndrome: Guanyuan (CV 4) and Shenshu (BL 23); fixed bi syndrome: Yinlingquan (SP 9), Sanyinjiao (SP 6), Zusanli (ST 36), Pishu (BL 20) and Fenglong (ST 40); wandering bi syndrome: Fengchi (GB 20), Geshu (BL 17), Fengmen (BL 12), Xuehai (SP 10) and Waiguan (TE 5); bi syndrome due to wind, damp and heat: Dazhui (GV 14), Quchi (LI 11) and Hegu (LI 4). Regarding the acupoint locations, the acupoints located in the upper limbs, lower limbs and spinal region were generally selected. Quchi (LI 11) was one of the main acupoints in prescriptions with the highest use frequency. Zusanli (ST 36) and Shenshu (BL 23) presented the highest co-occurrence intensity, while Zusanli (ST 36) and Quchi (LI 11) indicated the highest correlation. The treatment of acupuncture-moxibustion for RA is generally complied with the principle as "the synthesis of main acupoints, supplementary acupoints in local affected area and those based on syndrome differentiation". Warm needling and the combination of acupuncture and herbal medication are the most common therapeutic methods for RA.

TMBcat: A multi-endpoint p-value criterion on different discrepancy metrics for superiorly inferring tumor mutation burden thresholds.

Tumor mutation burden (TMB) is a widely recognized stratification biomarker for predicting the efficacy of immunotherapy; however, the number and universal definition of the categorizing thresholds remain debatable due to the multifaceted nature of efficacy and the imprecision of TMB measurements. We proposed a minimal joint p-value criterion from the perspective of differentiating the comprehensive therapeutic advantages, termed TMBcat, optimized TMB categorization across distinct cancer cohorts and surpassed known benchmarks. The statistical framework applies to multidimensional endpoints and is fault-tolerant to TMB measurement errors. To explore the association between TMB and various immunotherapy outcomes, we performed a retrospective analysis on 78 patients with non-small cell lung cancer and 64 patients with nasopharyngeal carcinomas who underwent anti-PD-(L)1 therapy. The stratification results of TMBcat confirmed that the relationship between TMB and immunotherapy is non-linear, i.e., treatment gains do not inherently increase with higher TMB, and the pattern varies across carcinomas. Thus, multiple TMB classification thresholds could distinguish patient prognosis flexibly. These findings were further validated in an assembled cohort of 943 patients obtained from 11 published studies. In conclusion, our work presents a general criterion and an accessible software package; together, they enable optimal TMB subgrouping. Our study has the potential to yield innovative insights into therapeutic selection and treatment strategies for patients.

[Analysis on clinical application characteristics of acupuncture and moxibustion in the treatment of Meniere's disease based on topology model by complex network].

OBJECTIVE: To analyze the application characteristics of acupuncture and moxibustion in clinical treatment of Meniere's disease by using complex network technology, so as to provide evidence for selecting acupoints, needling and moxibustion methods and treatment ideas. METHODS: Articles both in English and Chinese published from the inception of databases of CNKI, Wanfang VIP, Chinese biomedical literature database (SinoMed), PubMed, Embase, EBSCO (Academic Search Pre-mier), Web of Science and Ovid to April of 2021 were retrieved by using key words "acupuncture" or "moxibustion" or "acupuncture and moxibustion" and "Meniere disease" or "Meniere's syndrome" or "Ménières vertigo" or "otogenic vertigo" or "auditory vertigo", followed by screening the literature according to the inclusion and exclusion criteria and establishing a database of clinical li-terature about acupuncture treatment of Meniere's Disease with software Epidata 3.1. Then, the descriptive analysis was conducted first, followed by association rule analysis using SPSS Modeler 18.0, and complex network analysis using Gephi 0.9.2 software. RESULTS: A total of 232 articles were included, containing 152 acupoints [97 body acupoints as Baihui (GV20), Fengchi (GB20), Neiguan (PC6), etc., 28 otopoints as Ershenmen (MA-TF1), Shen (MA-SC), etc., 20 scalp points as Yunting Area, 7 extra-points as Sishencong (EX-HN1), Taiyang (EX-HN5), etc.] which were used to be a total frequency of 1 569. Descriptive analysis showed that the main meridians were the Governor Vessel, Stomach Meridian of Foot Yangming, Trienergizer Meridian of Hand Shaoyang, and Gallbladder Meridian of Foot Shaoyang. Acupuncture was the most commonly used therapy for Meniere's disease. The association analysis showed that the most relevant combination of acupoints was GV20 and GB20, GV20 and PC6, reflecting the principles of local acupoint selection and combination of local and distant acupoints. Finally, "K-core Analytic Hierarchy Process" and "Community Analysis" revealed that 3 core acupoint groups were most frequently used in clinical treatment of Meniere's disease, including 1) auricular acupoints, as MA-TF1, MA-SC, Neier(MA-L), Zhen(MA-AT) and Pizhixia(MA-AT1), 2) acupoints of the 14 meridians and extra-points, as Tinggong(SI19), Yifeng(TE17), GB20, 3) acupoints of the Shaoyang meri-dians of hand and foot, as Shuaigu (GB8), Tinghui (GB2), Zhongzhu (TE3), Ermen (TE21), etc. CONCLUSION: The principle of acupoint selection is mainly based on the combination of acupoints along the meridians and local areas, while paying attention to the coordination among the auricular points, scalp acupoints and extra-points, which may provide a reference for the clinical treatment and scientific research on acupuncture treatment of Meniere's disease.

HRD-MILN: Accurately estimate tumor homologous recombination deficiency status from targeted panel sequencing data.

Homologous recombination deficiency (HRD) is a critical feature guiding drug and treatment selection, mainly for ovarian and breast cancers. As it cannot be directly observed, HRD status is estimated on a small set of genomic instability features from sequencing data. The existing methods often perform poorly when handling targeted panel sequencing data; however, the targeted panel is the most popular sequencing strategy in clinical practices. Thus, we proposed HRD-MILN to overcome the computational challenges from targeted panel sequencing. HRD-MILN incorporated a multi-instance learning framework to discover as many loss of heterozygosity (LOH) associated with HRD status to cluster as possible. Then the HRD score is obtained based on the association between the LOHs and the cluster in the sample to be estimated, and finally, the HRD status is estimated based on the score. In comparison experiments on targeted panel sequencing data, the Precision of HRD-MILN could achieve 87%, significantly improved from 63% reported by the existing methods, where the highest margin of improvement reached 14%. It also presented advantages on whole exome sequencing data. Based on our best knowledge, HRD-MILN is the first practical tool for estimating HRD status from targeted panel sequencing data and could benefit clinical applications.

PEcnv: accurate and efficient detection of copy number variations of various lengths.

Copy number variation (CNV) is a class of key biomarkers in many complex traits and diseases. Detecting CNV from sequencing data is a substantial bioinformatics problem and a standard requirement in clinical practice. Although many proposed CNV detection approaches exist, the core statistical model at their foundation is weakened by two critical computational issues: (i) identifying the optimal setting on the sliding window and (ii) correcting for bias and noise. We designed a statistical process model to overcome these limitations by calculating regional read depths via an exponentially weighted moving average strategy. A one-run detection of CNVs of various lengths is then achieved by a dynamic sliding window, whose size is self-adopted according to the weighted averages. We also designed a novel bias/noise reduction model, accompanied by the moving average, which can handle complicated patterns and extend training data. This model, called PEcnv, accurately detects CNVs ranging from kb-scale to chromosome-arm level. The model performance was validated with simulation samples and real samples. Comparative analysis showed that PEcnv outperforms current popular approaches. Notably, PEcnv provided considerable advantages in detecting small CNVs (1 kb-1 Mb) in panel sequencing data. Thus, PEcnv fills the gap left by existing methods focusing on large CNVs. PEcnv may have broad applications in clinical testing where panel sequencing is the dominant strategy. Availability and implementation: Source code is freely available at https://github.com/Sherwin-xjtu/PEcnv.

AttnTAP: A Dual-input Framework Incorporating the Attention Mechanism for Accurately Predicting TCR-peptide Binding.

T-cell receptors (TCRs) are formed by random recombination of genomic precursor elements, some of which mediate the recognition of cancer-associated antigens. Due to the complicated process of T-cell immune response and limited biological empirical evidence, the practical strategy for identifying TCRs and their recognized peptides is the computational prediction from population and/or individual TCR repertoires. In recent years, several machine/deep learning-based approaches have been proposed for TCR-peptide binding prediction. However, the predictive performances of these methods can be further improved by overcoming several significant flaws in neural network design. The interrelationship between amino acids in TCRs is critical for TCR antigen recognition, which was not properly considered by the existing methods. They also did not pay more attention to the amino acids that play a significant role in antigen-binding specificity. Moreover, complex networks tended to increase the risk of overfitting and computational costs. In this study, we developed a dual-input deep learning framework, named AttnTAP, to improve the TCR-peptide binding prediction. It used the bi-directional long short-term memory model for robust feature extraction of TCR sequences, which considered the interrelationships between amino acids and their precursors and postcursors. We also introduced the attention mechanism to give amino acids different weights and pay more attention to the contributing ones. In addition, we used the multilayer perceptron model instead of complex networks to extract peptide features to reduce overfitting and computational costs. AttnTAP achieved high areas under the curves (AUCs) in TCR-peptide binding prediction on both balanced and unbalanced datasets (higher than 0.838 on McPAS-TCR and 0.908 on VDJdb). Furthermore, it had the highest average AUCs in TPP-I and TPP-II tasks compared with the other five popular models (TPP-I: 0.84 on McPAS-TCR and 0.894 on VDJdb; TPP-II: 0.837 on McPAS-TCR and 0.893 on VDJdb). In conclusion, AttnTAP is a reasonable and practical framework for predicting TCR-peptide binding, which can accelerate identifying neoantigens and activated T cells for immunotherapy to meet urgent clinical needs.