The immune factors have complex causal regulation effects on kidney stone disease: a mendelian randomization study.

PURPOSE: Previous studies have reported the potential impact of immune cells on kidney stone disease (KSD), but definitive causal relationships have yet to be established. The purpose of this paper is to elucidate the potential causal association between immune cells and KSD by Mendelian randomization (MR) analysis. METHODS: In our study, a thorough two-sample Mendelian randomization (MR) analysis was performed by us to determine the potential causal relationship between immune cell traits and kidney stone disease. We included a total of four immune traits (median fluorescence intensity (MFI), relative cellular (RC), absolute cellular (AC), and morphological parameters (MP)), which are publicly available data. GWAS summary data related to KSD (9713 cases and 366,693 controls) were obtained from the FinnGen consortium. The primary MR analysis method was Inverse variance weighted. Cochran's Q test, MR Egger, and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) were used to assess the stability of the results. RESULTS: After FDR correction, the CD8 on HLA DR + CD8br (OR = 0.95, 95% CI = 0.93-0.98, p-value = 7.20 × 10- 4, q-value = 0.088) was determined to be distinctly associated with KSD, and we also found other 25 suggestive associations between immune cells and KSD, of which 13 associations were suggested as protective factors and 12 associations were suggested as risk factors. There was no horizontal pleiotropy or significant heterogeneity in our MR analysis, as determined by the p-value results of our Cochrane Q-test, MR Egger's intercept test, and MR-PRESSO, which were all > 0.05. CONCLUSIONS: Our study has explored the potential causal connection between immune cells and KSD by Mendelian randomization analysis, thus providing some insights for future clinical studies.

Inflammatory cytokines and their potential role in kidney stone disease: a Mendelian randomization study.

PURPOSE: Previous studies have reported a complex relationship between inflammatory cytokines and kidney stone disease (KSD). The purpose of this paper is to investigate the potential causal impact of inflammatory cytokines on KSD by Mendelian randomization (MR) analysis. METHODS: In our study, a thorough two-sample Mendelian randomization (MR) analysis was performed by us to determine the potential causal relationship between inflammatory cytokines and kidney stone disease. Utilizing GWAS summary data of inflammatory cytokines and KSD, we performed the first two-sample MR analysis. Genetic variants in GWASs related to inflammatory cytokines were employed as instrumental variables (IVs). The data on cytokines were derived from 14,824 participants and analyzed by utilizing the Olink Target-96 Inflammation Panel. GWAS summary data related to KSD (9713 cases and 366,693 controls) were obtained from the FinnGen consortium. The primary MR analysis method was Inverse variance weighted. Reverse MR analysis, Cochran's Q test, MR Egger, and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) were used to assess the stability of the results. RESULTS: 91 cytokines were enrolled in the MR analysis after strict quality control of IV. The IVW analysis revealed 2 cytokines as risk factors for KSD: Cystatin D (OR 1.06, 95% CI 1.01-1.11), Fibroblast growth factor 5 (OR 1.06, 95% CI 1.00-1.12), suggesting they are positively associated with the occurrence of kidney stones. We also found 3 protective associations between cytokines and KSD: Artemin (OR 0.86, 95% CI 0.78-0.96), T-cell surface glycoprotein CD6 isoform (OR 0.92, 95% CI 0.88-0.98), STAM-binding protein (OR 0.83, 95% CI 0.69-0.99). There was no horizontal pleiotropy or significant heterogeneity in our MR analysis, as determined by the p-value results of our MR Egger's intercept test, Cochrane Q-test, and MR-PRESSO, which were all > 0.05. CONCLUSIONS: Our study explored a variety of inflammatory cytokines related to KSD through MR analysis, which validated several previous findings and provided some new potential biomarkers for KSD. However, the findings require further investigation to validate their exact functions in the pathogenesis and evolution of KSD.

Artificial intelligence significantly facilitates development in the mental health of college students: a bibliometric analysis.

Objective: College students are currently grappling with severe mental health challenges, and research on artificial intelligence (AI) related to college students mental health, as a crucial catalyst for promoting psychological well-being, is rapidly advancing. Employing bibliometric methods, this study aim to analyze and discuss the research on AI in college student mental health. Methods: Publications pertaining to AI and college student mental health were retrieved from the Web of Science core database. The distribution of publications were analyzed to gage the predominant productivity. Data on countries, authors, journal, and keywords were analyzed using VOSViewer, exploring collaboration patterns, disciplinary composition, research hotspots and trends. Results: Spanning 2003 to 2023, the study encompassed 1722 publications, revealing notable insights: (1) a gradual rise in annual publications, reaching its zenith in 2022; (2) Journal of Affective Disorders and Psychiatry Research emerged were the most productive and influential sources in this field, with significant contributions from China, the United States, and their affiliated higher education institutions; (3) the primary mental health issues were depression and anxiety, with machine learning and AI having the widest range of applications; (4) an imperative for enhanced international and interdisciplinary collaboration; (5) research hotspots exploring factors influencing college student mental health and AI applications. Conclusion: This study provides a succinct yet comprehensive overview of this field, facilitating a nuanced understanding of prospective applications of AI in college student mental health. Professionals can leverage this research to discern the advantages, risks, and potential impacts of AI in this critical field.

Research trends of exercise therapy of college students in depression from 2002 to 2022: a bibliometric analysis.

Background: Depression is a serious psychological disorder that college students are experiencing. College students' depression problems, which can be caused by various factors, have been easily ignored and untreated. In recent years, exercise, as a low-cost and easily accessible method for treating depression, has attracted widespread attention. The purpose of this study is to use bibliometrics to explore the hotspots and trends in the field of exercise therapy of college students in depression from 2002 to 2022. Methods: We retrieved relevant literature from the Web of Science (WoS), PubMed, and Scopus databases, and generated a ranking table to describe the core productivity in the field. We used VOSViewer software to generate network maps of authors, countries, co-cited journals, and co-occurring keywords to help us better understand the scientific collaboration patterns, potential disciplinary foundations, as well as research hotspots and trends in this field. Results: From 2002 to 2022, a total of 1,397 articles related to exercise therapy of college students in depression were selected. The key findings of this study are as follows: (1) the number of publications has gradually increased, especially after 2019; (2) United States and its affiliated higher education institutions have made significant contributions to the development of this field; (3) there are multiple research groups in this field, but their connections are relatively limited; (4) the field is relatively interdisciplinary, primarily a convergence of behavioral science, public health, and psychology; (5) based on co-occurring keyword analysis, six main themes were summarized: health-promoting factors, body image, negative behaviors, increased stress, depression coping strategies, and diet. Conclusion: Our study illustrates the research hotspots and trends for the research of exercise therapy of college students in depression, presents some challenges and new insights, and provides valuable information for further research.

Deciphering the pharmacological mechanisms of Rostellularia procumbens (L) Nees. Extract alleviates adriamycin-induced nephropathy in vivo and in vitro.

BACKGROUND: Rostellularia procumbens (L) Nees. is an effective traditional Chinese herbal medicine for the treatment of patients with chronic glomerulonephritis (CGN) in the clinic. However, the underlying molecular mechanisms need further elucidation. PURPOSE: This study aims to investigate the renoprotective mechanisms of n-butanol extract from Rostellularia procumbens (L) Nees. (J-NE) in vivo and in vitro. METHODS: The components of J-NE were analyzed by UPLC-MS/MS. In vivo, the nephropathy model was induced in mice by tail vein injection with adriamycin (10 mg·kg-1), and mice were treated with vehicle or J-NE or benazepril by daily gavage. In vitro, MPC5 cells exposed to adriamycin (0.3 µg/ml) were treated with J-NE. The effects of J-NE inhibit podocyte apoptosis and protect against adriamycin-induced nephropathy were determined by Network pharmacology, RNA-seq, qPCR, ELISA, immunoblotting, flow cytometry, and TUNEL assay, according to the experimental protocols. RESULT: The results showed that treatment significantly improved ADR-induced renal pathological changes, and the therapeutic mechanism of J-NE was related to the inhibition of podocyte apoptosis. Further molecular mechanism studies found that J-NE inhibited inflammation, increase the proteins expression levels of Nephrin and Podocin, reduce TRPC6 and Desmin expression levels and calcium ion levels in podocytes, and decrease the proteins expression levels of PI3K, p-PI3K, Akt and p-Akt to attenuated apoptosis. Furthermore, 38 compounds of J-NE were identified. CONCLUSION: J-NE exerted the renoprotective effects by inhibiting podocyte apoptosis, which provides effective evidence for the treatment of J-NE targeting renal injury in CGN.

Research trend of epigenetics and depression: adolescents' research needs to strengthen.

Objective: With its high prevalence, depression's pathogenesis remains unclear. Recent attention has turned to the interplay between depression and epigenetic modifications. However, quantitative bibliometric analyses are lacking. This study aims to visually analyze depression epigenetics trends, utilizing bibliometric tools, while comprehensively reviewing its epigenetic mechanisms. Methods: Utilizing the Web of Science core dataset, we collected depression and epigenetics-related studies. Employing VOSViewer software, we visualized data on authors, countries, journals, and keywords. A ranking table highlighted field leaders. Results: Analysis encompassed 3,469 depression epigenetics studies published from January 2002 to June 2023. Key findings include: (1) Gradual publication growth, peaking in 2021; (2) The United States and its research institutions leading contributions; (3) Need for enhanced collaborations, spanning international and interdisciplinary efforts; (4) Keyword clustering revealed five main themes-early-life stress, microRNA, genetics, DNA methylation, and histone acetylation-highlighting research hotspots; (5) Limited focus on adolescent depression epigenetics, warranting increased attention. Conclusion: Taken together, this study revealed trends and hotspots in depression epigenetics research, underscoring global collaboration, interdisciplinary fusion, and multi-omics data's importance. It discussed in detail the potential of epigenetic mechanisms in depression diagnosis and treatment, advocating increased focus on adolescent research in this field. Insights aid researchers in shaping their investigative paths toward understanding depression's epigenetic mechanisms and antidepressant interventions.

Circular_0086414 induces SPARC like 1 (SPARCL1) production to inhibit esophageal cancer cell proliferation, invasion and glycolysis and induce cell apoptosis by sponging miR-1290.

Circular RNA (circRNA) plays an important role in cancer progression. Here, we investigated the function of circ_0086414 in the malignant progression of esophageal cancer (EC). RNA expression of circ_0086414, microRNA-1290 (miR-1290), and SPARC like 1 (SPARCL1) was detected by quantitative real-time polymerase chain reaction. The protein levels of N-cadherin, E-cadherin, and SPARCL1 were checked by Western blotting analysis. Cell proliferation was investigated by 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), 5-Ethynyl-29-deoxyuridine (EdU), and cell colony formation assays. Cell invasion and apoptosis were analyzed by transwell invasion assay and flow cytometry analysis, respectively. Glycolysis was evaluated by analyzing glucose consumption and lactate production. In an xenograft mouse model, the effect of circ_0086414 on tumor tumorigenesis was investigated. The interactions among circ_0086414, miR-1290, and SPARCL1 were identified by dual-luciferase reporter and RNA pull-down assays. Results showed that circ_0086414 and SPARCL1 expression were significantly downregulated, while miR-1290 was upregulated in EC tissues and cells. EC patients with low circ_0086414 expression had a poor prognosis. Increasing circ_0086414 expression led to decreased EC cell proliferation, invasion and glycolysis and increased cell apoptosis, accompanied by a decrease of N-cadherin expression and an increase of E-cadherin expression. Also, the enforced expression of circ_0086414 delayed tumor tumorigenesis. Besides, circ_0086414 acted as a miR-1290 sponge and regulated EC cell processes by binding to the miRNA. MiR-1290 also participated in EC malignant progression through SPARCL1. Further, circ_0086414 stimulated SPARCL1 production by negatively regulating miR-1290. Thus, circ_0086414 inhibited EC cell malignancy through the miR-1290/SPARCL1 pathway, providing a reliable target for the therapy of EC.

The Sequence of Chemotherapy and Toripalimab Might Influence the Efficacy of Neoadjuvant Chemoimmunotherapy in Locally Advanced Esophageal Squamous Cell Cancer-A Phase II Study.

Background: There is no standard neoadjuvant therapy for locally advanced esophageal cancer in China. The role of neoadjuvant chemotherapy plus immunotherapy for locally advanced esophageal cancer is still being explored. Methods: This open-label, randomized phase II study was conducted at a single center between July 2019 and September 2020; 30 patients with locally advanced esophageal squamous cell carcinoma (ESCC) (T3, T4, or lymph-node positive) were enrolled. Patients were randomized according to the enrollment order at a 1:1 ratio to receive chemotherapy on day 1 and toripalimab on day 3 (experimental group) or chemotherapy and toripalimab on day 1 (control group). The chemotherapeutic regimen was paclitaxel and cisplatin. Surgery was performed 4 to 6 weeks after the second cycle of chemoimmunotherapy. The primary endpoint was pathological complete response (pCR) rate, and the secondary endpoint was safety and disease-free survival. Results: Thirty patients completed at least one cycle of chemoimmunotherapy; 11 in the experimental group and 13 in the control group received surgery. R0 resection was performed in all these 24 patients. Four patients (36%) in the experimental group and one (7%) in the control group achieved pCR. The experimental group showed a statistically non-significant higher pCR rate (p = 0.079). PD-L1 combined positive score (CPS) examination was performed in 14 patients; one in the control group had a PD-L1 CPS of 10, and pCR was achieved; the remaining 13 all had ≤1, and 11 of the 13 patients received surgery in which two (in the experimental group) achieved pCR. Two patients endured ≥grade 3 adverse events, and one suffered from grade 3 immune-related enteritis after one cycle of chemoimmunotherapy and dropped off the study. Another patient died from severe pulmonary infection and troponin elevation after surgery. Conclusions: Although the primary endpoint was not met, the initial results of this study showed that delaying toripalimab to day 3 in chemoimmunotherapy might achieve a higher pCR rate than that on the same day, and further large-sample clinical trials are needed to verify this. Clinical Trial Registration: ClinicalTrials.gov, identifier NCT03985670.

CircRNA CircZMYM4 inhibits the growth and metastasis of lung adenocarcinoma via the miR-587/ODAM pathway.

Circular RNAs (circRNAs) are known to regulate tumorigenesis. In this study, circRNAs microarray was used to analyze the circRNA expression in lung adenocarcinoma (LUAD) tissues, and CircRNA zinc finger MYM-type containing 4(circZMYM4) was selected for further analysis. In this study, we detected circZMYM4 expression in LUAD specimens and cell lines using RT-PCR. The expression of circZMYM4 was further verified in the GEO datasets and TCGA datasets. Gain-of-function and loss-of-function experiments were used to analyze the effects of circZMYM4 on LUAD in vivo and in vitro. The relationship between miR-587 and circZMYM4 or ODAM was predicted by bioinformatics tools and confirmed using dual-luciferase reporter assays and RNA-pull down. We found that circZMYM4 was distinctly down-regulated in LUAD tissues and cell lines. Functional assays revealed that circZMYM4 overexpression suppressed LUAD cell proliferation, metastasis and suppressed apoptosis, while miR-587 overexpression could weaken these effects. Importantly, circZMYM4 upregulated ODAM expression via sponging miR-587 to suppress LUAD progression. ODAM knockdown could reverse the repressive effect of circZMYM4 overexpression on cell proliferation, migration and invasion abilities. Overall, circZMYM4 regulates the miR-587/ODAM axis to suppress LUAD progression, which may become a potential biomarker and therapeutic target.

A phase III study on neoadjuvant chemotherapy versus neoadjuvant toripalimab plus chemotherapy for locally advanced esophageal squamous cell carcinoma: Henan Cancer Hospital Thoracic Oncology Group 1909 (HCHTOG1909).

BACKGROUND: Neoadjuvant chemotherapy (NAC) and neoadjuvant chemoradiotherapy (NACR) are the standard treatments for esophageal squamous cell carcinoma (ESCC). However, the 5-year overall survival (OS) rate is still far from satisfactory. In recent years, immune checkpoint inhibitors (ICIs) have shown promising results in the treatment of ESCC. More than 20 phase II clinical trials have been launched to explore combinations of ICIs in the neoadjuvant setting for ESCC. Based on our phase II clinical trial, a two-arm phase III trial was launched in Henan Cancer Hospital. ICIs combined with NAC may usher in a new era and may benefit locally advanced, resectable ESCC patients. METHODS: A two-arm phase III trial was launched in April 2020 in Henan Cancer Hospital. Patient recruitment will be completed within 18 months. The primary endpoint is event-free survival (EFS). The secondary endpoints include pathologic complete response (pCR), disease-free survival (DFS) rate, overall response rate (ORR), R0 resection rate, major pathologic response (MPR), adverse events (AEs), complication rate and quality of life (QOL). A biobank of pretreatment, resected tumor tissue and paired blood samples will be built for translational research in the future. DISCUSSION: This RCT directly compares NAC with neoadjuvant toripalimab plus chemotherapy in terms of EFS for locally advanced ESCC. The results may usher in a new era of resectable ESCC treatment. TRIAL REGISTRATION: NCT04280822 (https://www.clinicaltrials.gov/ct2/show/NCT04280822). Registered title: "A Phase III, Randomized Controlled Study of Neo-adjuvant Toripalimab (JS001) in Combination with Chemotherapy versus Neo-adjuvant Chemotherapy for Resectable Esophageal Squamous Cell Carcinoma". Version 1.0/Nov. 21, 2019.

T Cells Expanded from PD-1+ Peripheral Blood Lymphocytes Share More Clones with Paired Tumor-Infiltrating Lymphocytes.

Both tumor-infiltrating lymphocytes (TIL) and PD-1+ peripheral blood lymphocytes (PBL) are enriched for tumor-reactive clones recognizing known and unknown tumor antigens. However, the relationship between the T-cell receptor-ß (TCRß) repertoires of the TILs and T cells expanded from paired PD-1+ PBLs, and whether T cells expanded from PD-1+ PBLs can be used to treat patients with cancer as TIL substitutes remain unclear. Here, we established a highly efficient protocol to prepare polyclonal T cells from PD-1+ PBLs. A functional T-cell assay and tetramer staining revealed that cells from PD-1+ PBLs were relatively enriched for tumor-reactive T cells. Furthermore, deep TCRß sequencing data revealed that an average of 11.29% (1.32%-29.06%; P = 0.015; n = 8) tumor-resident clonotypes were found in T cells expanded from paired PD-1+ PBLs, and the mean accumulated frequency of TIL clones found in T cells expanded from PD-1+ PBLs was 35.11% (7.23%-78.02%; P = 0.017; n = 8). Moreover, treatment of four patients, who failed multiline therapy and developed acquired resistance to anti-PD-1, with autologous T cells expanded from PD-1+ PBLs combined with anti-PD-1 antibody elicited objective responses from three of them. These results indicate that T cells expanded from PD-1+ PBLs share more clones with paired TILs and could be used to treat patients with cancer as TIL substitutes. SIGNIFICANCE: This study harnesses the tumor reactivity of PD-1+ PBLs, developing a method to expand T cells from these clones as a potential therapeutic strategy and TIL substitute in patients with cancer.See related commentary by Ladle, p. 1940.

Location Property of Convolutional Neural Networks for Image Classification.

When doing image classification, the core task of convolutional neural network (CNN)-based methods is to learn better feature representation. Our analysis has shown that a better feature representation in the layer before softmax operation (BSM-layer) means a better feature embedding location that has a larger distance to the separating hyperplane. By defining this property "Location Property" of CNN, the core task of CNN-based methods can be regarded as to find out the optimal feature embedding location in the BSM-layer. In order to achieve this, in this work, we first propose two feature embedding directions, principal embedding direction (PE-direction) and secondary embedding direction (SE-direction). And then, we further propose a loss-based optimization framework, location property loss (LP-loss), which can make feature representation move in the PE-direction and the SE-direction simultaneously during the training phase. LP-loss consists of two parts, LPPE and LPSE, where LPPE focuses on PE-direction, and LPSE focuses on SE-direction. Any loss function focusing on these two embedding directions can be chosen as LPPE and LPSE. Based on the analysis that softmax, L-softmax, and AM softmax can make the feature representation move in PE-direction to a different extent, any of them can be chosen as LPPE. Since there is no existing works can fulfill the purpose of LPSE, a novel loss, secondary optimal feature plane loss (S-OFP loss), is developed. S-OFP loss is designed to make feature representations belonging to the same category embed onto their corresponding S-OFP. It is proved that S-OFP loss is the optimal feature plane in the SE-direction. Experiments are done with shallow, moderate, and deep models on four benchmark data sets, including the MNIST, SVHN, CIFAR-10, and CIFAR-100, and results demonstrate that CNN models can obtain remarkable performance improvements with LPsoftmax, S-OFP and LPAM softmax, S-OFP, which verify the effectiveness of location property.

A phase II, single-centre trial of neoadjuvant toripalimab plus chemotherapy in locally advanced esophageal squamous cell carcinoma.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) remains a challenging malignancy with poor prognosis and limited therapeutic methods. However, recent clinical trials of immune checkpoint inhibitors (ICIs) have shown promising results in the treatment of lethal malignancies. The second-line treatment of late-stage ESCC was approved based on the results of KEYNOTE-180, KEYNOTE-181 and ATTRACTION-1, ATTRACTION-3. Combining ICIs with chemotherapy in neoadjuvant therapy may benefit patients with locally advanced, resectable ESCC. METHODS: A two-arm phase II trial was launched in July 2019 in Henan Cancer Hospital. The primary outcome measure will be completed within 21 months. The pathological complete response (pCR) rate is the primary endpoint, and the secondary endpoints include overall survival (OS), disease-free survival (DFS), the toxicities of the neoadjuvant toripalimab plus chemotherapy, the relationship between combined positivity score (CPS) of specimen and the treatment response, the relationship between lymphocyte infiltration and the treatment response, the progression-free survival (PFS) rate, and adverse events (AEs). It was assumed that the pCR rate of this trial might be 25%. Therefore, the 30 enrolled patients could reject the hypothesis at 75% (α=0.1). DISCUSSION: The study will determine the safety and efficacy of neoadjuvant immunochemotherapy for ESCC and provide enough evidence for phase III clinical trials. TRIAL REGISTRATION: Clinical Trials.gov, NCT03985670, Registered: October 24, 2019, https://register.clinicaltrials.gov/prs/app/action/SelectProtocol?sid=S0008Z9D&selectaction=Edit&uid=U0002MIY&ts=2&cx=-i71o4q. Registry name: "Teripalimab Plus Chemotherapy in Local Advanced Esophageal Cancer".

An improved clear cell renal cell carcinoma stage prediction model based on gene sets.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma and accounts for cancer-related deaths. Survival rates are very low when the tumor is discovered in the late-stage. Thus, developing an efficient strategy to stratify patients by the stage of the cancer and inner mechanisms that drive the development and progression of cancers is critical in early prevention and treatment. RESULTS: In this study, we developed new strategies to extract important gene features and trained machine learning-based classifiers to predict stages of ccRCC samples. The novelty of our approach is that (i) We improved the feature preprocessing procedure by binning and coding, and increased the stability of data and robustness of the classification model. (ii) We proposed a joint gene selection algorithm by combining the Fast-Correlation-Based Filter (FCBF) search with the information value, the linear correlation coefficient, and variance inflation factor, and removed irrelevant/redundant features. Then the logistic regression-based feature selection method was used to determine influencing factors. (iii) Classification models were developed using machine learning algorithms. This method is evaluated on RNA expression value of clear cell renal cell carcinoma derived from The Cancer Genome Atlas (TCGA). The results showed that the result on the testing set (accuracy of 81.15% and AUC 0.86) outperformed state-of-the-art models (accuracy of 72.64% and AUC 0.81) and a gene set FJL-set was developed, which contained 23 genes, far less than 64. Furthermore, a gene function analysis was used to explore molecular mechanisms that might affect cancer development. CONCLUSIONS: The results suggested that our model can extract more prognostic information, and is worthy of further investigation and validation in order to understand the progression mechanism.

Developing prognostic gene panel of survival time in lung adenocarcinoma patients using machine learning.

BACKGROUND: Transcriptome data generates massive amounts of information that can be used for characterization and prognosis of patient outcomes for many diseases. The goal of our research is to predict the survival time of lung adenocarcinoma patients and improve the accuracy of classifying the long-survival cohort and short-survival cohort. METHODS: We filtered prognostic features related with survival time of lung adenocarcinoma patients by the method of Relief and predicted whether survival time of the patient is >3 years or not-using eight machine learning algorithms (Support Vector Machines, Random Forests, Logistic Regression, Naïve Bayes, Linear Regression, Support Vector Regression (kernel Poly), Support Vector Regression (kernel Linear), and Ridge Regression). Then the best-performed algorithm was chosen to build a predictive model of survival time of lung adenocarcinoma patients. Further, another dataset was used to verify the stability and suitability of this model. We explored the underlying mechanisms of RNA expression changes with the corresponding DNA mutations and DNA methylation patterns in the 22 selected genetic features. RESULTS: The best machine learning algorithm was Naïve Bayes (accuracy=75%, AUC =0.81) using the top 22 genetic features, and this algorithm had the stable and great performance on another dataset as well. The coupled mutation number of the long-survival group (>6 years) was less than the short-survival group (<1 year) in 22 genes (P=0.031). CONCLUSIONS: The expression of gene panel can predict the survival time of lung adenocarcinoma patients using Naïve Bayes. These 22 genes do affect the survival time of lung adenocarcinoma.

microRNA-301b-3p downregulation underlies a novel inhibitory role of long non-coding RNA MBNL1-AS1 in non-small cell lung cancer.

BACKGROUND: Non-small cell lung cancer (NSCLC) is the second most prevalent cause of cancer-related fatality. Long non-coding RNAs (lncRNAs) have been observed to exercise functions in NSCLC. Here, the current study aimed to explore the potential mechanism of lncRNA MBNL1-AS1 in NSCLC. METHODS: Microarray analysis was performed to screen the differentially expressed lncRNA associated with NSCLC and its potential mechanism. The lncRNA MBNL1-AS1 expression was quantified in 56 paired NSCLC and adjacent normal tissue samples. In an attempt to outline the function of lncRNA MBNL1-AS1 in NSCLC and to identify the interaction among lncRNA MBNL1-AS1, microRNA-301b-3p (miR-301b-3p) and TGFBR2, ectopic expression, depletion, and reporter assay experiments were conducted to detect CSC proliferation, migration, invasion, drug resistance, and sphere formation in NSCLC. RESULTS: Initially, the intersection among lncRNA MBNL1-AS1, miR-301b-3p, and TGFBR2 was observed in NSCLC. While a poor expression of lncRNA MBNL1-AS1 and TGFBR2, along with a high expression of miR-301b-3p was observed in NSCLC tissues. A demonstration of lncRNA MBNL1-AS1 restoration significantly decreased CSC proliferation, migration, invasion, drug resistance, and sphere formation in NSCLC. LncRNA MBNL1-AS1 functioned as a sponge of miR-301b-3p, which inverted the inhibitory role of lncRNA MBNL1-AS1 in CSC proliferation, migration, invasion, drug resistance, and sphere formation in NSCLC. LncRNA MBNL1-AS1 positively regulated TGFBR2 which was a target gene of miR-301b-3p. At last, upregulated lncRNA MBNL1-AS1 or depleted miR-301b-3p suppressed the xenograft tumor formation in vivo. CONCLUSION: Collectively, the present study suggests an inhibitory role of lncRNA MBNL1-AS1 in CSC drug resistance of NSCLC by upregulating miR-301b-3p-targeted TGFBR2.

Practical value of identifying circulating tumor cells to evaluate esophageal squamous cell carcinoma staging and treatment efficacy.

BACKGROUND: This study was conducted to investigate the correlation between clinicopathological features and post-therapeutic response in esophageal squamous cell carcinoma (ESCC) patients. Peripheral blood circulating tumor cells (CTCs) expressing epithelial-mesenchymal transition markers were identified. METHODS: Peripheral blood samples were collected from 71 patients with newly diagnosed ESCC and 40 healthy volunteers. CTCs were isolated using CanPatrol CTC enrichment technology. RNA-fluorescent in situ hybridization was used to phenotype the CTCs on the basis of epithelial and/or mesenchymal markers. RESULTS: The median mesenchymal CTC counts in 71 patients were: 0 in 19 stage I patients, 2 in 31 stage II, and 3 in 21 stage III/IV. The overall diagnostic performance of total CTCs to correctly identify ESCC patients was 0.991. We observed a correlation between increases in tumor size or advanced stage and an increased number of mesenchymal CTCs (P < 0.05). Thirty-nine patients were administered two cycles of neoadjuvant chemotherapy and their therapeutic response was evaluated: 2 complete response, 20 partial response, 13 stable disease, and 4 progressive disease. After treatment, the positive rate of mesenchymal CTCs was 70.6% in the progressive and stable disease group versus 36.4% in the complete and partial response group (P = 0.05). CONCLUSION: The results showed that mesenchymal CTC count is related to ESCC clinical stage and the efficacy of neoadjuvant chemotherapy.

[Clinical Study on the Prognosis of Patients with Thymoma with Myasthenia Gravis].

BACKGROUND: Thymoma is frequently associated with myasthenia gravis (MG). However, whether MG is a factor for the outcome of patients with thymoma following complete thymectomy remains unknown. The aim of this study is to investigate the effect of thymoma with MG prognostic factors. METHODS: A retrospective analysis of The Chinese Alliance for Research in Thymomas (ChART) database within 1992-2012 complete cases 875 cases, 20 years follow-up data analysis thymic tumor tissue type credits and MG, Masaoka staging and prognosis, postoperative adjuvant therapy and relationship with the prognosis of surgical removal of the way. RESULTS: Thymic tumor tissue type credit has correlation with MG, difference was statistically significant (χ²=24.908, P<0.001). MG: incidence of B2 type (58/178, 32.58%) > B3 type (65/239, 27.20%) > B1 (27/132, 20.45%) > AB (43/267, 16.10%) > type A, 10.17% (6/59), Masaoka stage has no correlation with MG (χ²=0.365, P=1.365). Survival analysis showed that the WHO classification, Masaoka stage associated with prognosis (P<0.05), and whether the merger MG (χ²=0.113, P=0.736), postoperative adjuvant radiotherapy (χ²=0.380, P=0.538) has nothing to do with the prognosis, postoperative adjuvant chemotherapy is associated with poor prognosis (χ²=14.417, P<0.001). Whether has nothing to do with the prognosis of the thymus resection (χ²=1.548, P=1.548), whether the whole correlated with the curative effect of thymus excision with MG (χ²=24.695, P<0.001). CONCLUSIONS: Thymoma patients with MG and extended thymectomy have no correlation with prognosis. Extended thymectomy can improve the effect of MG patients.

Joint Transmit Power Allocation and Splitting for SWIPT Aided OFDM-IDMA in Wireless Sensor Networks.

In this paper, we propose to combine Orthogonal Frequency Division Multiplexing-Interleave Division Multiple Access (OFDM-IDMA) with Simultaneous Wireless Information and Power Transfer (SWIPT), resulting in SWIPT aided OFDM-IDMA scheme for power-limited sensor networks. In the proposed system, the Receive Node (RN) applies Power Splitting (PS) to coordinate the Energy Harvesting (EH) and Information Decoding (ID) process, where the harvested energy is utilized to guarantee the iterative Multi-User Detection (MUD) of IDMA to work under sufficient number of iterations. Our objective is to minimize the total transmit power of Source Node (SN), while satisfying the requirements of both minimum harvested energy and Bit Error Rate (BER) performance from individual receive nodes. We formulate such a problem as a joint power allocation and splitting one, where the iteration number of MUD is also taken into consideration as the key parameter to affect both EH and ID constraints. To solve it, a sub-optimal algorithm is proposed to determine the power profile, PS ratio and iteration number of MUD in an iterative manner. Simulation results verify that the proposed algorithm can provide significant performance improvement.

[Diagnostic Value of Folate Receptor-positive Circulating Tumor Cell in Lung Cancer: A Pilot Study].

BACKGROUND: The aim of this study is to determine the efficacy and feasibility of a novel folate receptor (FR)-based circulating tumor cell (CTC) detection method in the diagnosis of lung cancer. CTCs were collected from 3 mL of blood based on negative enrichment by immunomagnetic beads and then labeled by a conjugate of a tumor-specific ligand folate and an oligonucleotide. METHODS: After washing off redundant conjugates, the bound conjugates were removed and analyzed by quantitative polymerase chain reaction. RESULTS: The CTC levels of 97 patients with lung cancer were significantly higher than that of the controls (18 patients with benign lung diseases; P<0.001). With a threshold of 8.7 Folate units, the method showed a sensitivity of 82.5% and a specificity of 72.2% in the diagnosis of lung cancer, especially a sensitivity of 86.8% in stage I disease. Compared with the existing clinical biomarkers such as neuron-specific enolase (NSE), carcinoembryonic antigen (CEA), and CYFRA21-1, the method showed the highest diagnostic efficiency in lung cancer (area under the curve, 0.859; 95%CI: 0.779-0.939) and stage I lung cancer (area under the curve, 0.912; 95%CI: 0.829-0.994). For future work, the CTC levels of 5 lung cancer patients higher than 8.7 Folate units/3 mL in their postoperation. CONCLUSIONS: FR-positive CTCs were feasible diagnostic biomarkers in patients with lung cancer, as well as in early-stage tumors.