An ensemble framework for farmland quality evaluation based on machine learning and physical models.

Farmland quality (FQ) evaluation is crucial to curb agricultural land's "non-grain" behavior and promote ecological nitrogen trade-off in North China. However, a promising approach to obtain the verified spatial distribution of nitrogen emissions remains to be developed, making it difficult to achieve the precise FQ estimation. Facing this issue, we present a Machine Learning (ML) - Nitrogen Export Verification (NEV) ensemble framework for the precise evaluation of FQ, taking the Beijing-Tianjin-Hebei 200 km traffic zone (zone) as the case. This was done by employing physical models for the precisely spatial estimation of Nitrogen Export (NE) values and then using ML methods to compute the spatial distribution of FQ using the Farmland Quality Evaluation System (FQES) indicators. We found: (1) the ML - NEV framework showed promising results, as the relative error of the NEV method was lower than 5.25 %, and the Determination coefficient of the ML method in FQ evaluation was higher than 0.84; (2) the FQ results within the zone were mainly good-quality areas (~47.25 % and primarily concentrated in the southwest-northeast regions) with improvement significance, with Fractal Dimension, NE values, and unbalanced Irrigation or Drainage Capabilities serving as the primary driving factors. Our results would be helpful in offering decision support for improving FQ based on refined grids, benefiting to Agribusiness Revitalization Plans (i.e., safeguarding grain yield, activating agribusiness development, Etc.) in developing countries.

An integrative evaluation of circadian gene TIMELESS as a pan-cancer immunological and predictive biomarker.

BACKGROUND: The gene TIMELESS, which is involved in the circadian clock and the cell cycle, has recently been linked to various human cancers. Nevertheless, the association between TIMELESS expression and the prognosis of individuals afflicted with pan-cancer remains largely unknown. OBJECTIVES: The present study aims to exhaustively scrutinize the expression patterns, functional attributes, prognostic implications, and immunological contributions of TIMELESS across diverse types of human cancer. METHODS: The expression of TIMELESS in normal and malignant tissues was examined, as well as their clinicopathologic and survival data. The characteristics of genetic alteration and molecular subtypes of cancers were also investigated. In addition, the relationship of TIMELESS with immune infiltration, tumor mutation burden (TMB), microsatellite instability (MSI), and drug sensitivity was illustrated. Immunohistochemistry (IHC) was used to validate the expression of TIMELESS in clinical patients with several types of cancer. RESULTS: In contrast to the matching normal controls, most tumor types were found to often overexpress TIMELESS. Abnormal expression of TIMELESS was significantly related to more advanced tumor stage and poorer prognosis of breast cancer, as well as infiltrating immune cells such as cancer-associated fibroblast infiltration in various tumors. Multiple cancer types exhibited abnormal expression of TIMELESS, which was also highly correlated with MSI and TMB. More crucially, TIMELESS showed promise in predicting the effectiveness of immunotherapy and medication sensitivity in cancer therapy. Moreover, cell cycle, DNA replication, circadian rhythm, and mismatch repair were involved in the functional mechanisms of TIMELESS on carcinogenesis. Furthermore, immunohistochemical results manifested that the TIMELESS expression was abnormal in some cancers. CONCLUSIONS: This study provides new insights into the link between the circadian gene TIMELESS and the development of various malignant tumors. The findings suggest that TIMELESS could be a prospective prognostic and immunological biomarker for pan-cancer.

Pan-cancer analysis identifies RNF43 as a prognostic, therapeutic and immunological biomarker.

BACKGROUND: RING finger protein 43 (RNF43), an E3 ubiquitin ligase, is a homologous gene mutated in several cancers. However, the pan-cancer panoramic picture of RNF43 and its predictive value for tumor immune phenotypes and immunotherapeutic efficacy are still largely unclear. Our study aims to clarify the functions of RNF43 in predicting the prognosis, immune signature, and immunotherapeutic efficacy in pan-cancer. METHODS: By using RNA-seq, mutation, and clinical data from the TCGA database, the expression levels and prognostic significance of RNF43 in pan-cancer were analyzed. The genetic alteration characteristics of RNF43 were displayed by the cBioPortal database. Gene Set Enrichment Analysis (GSEA) was performed to investigate the potential biological functions and signaling pathways modulated by RNF43 in cancers. The relationship of RNF43 expression with immune cell infiltration, and immune modulators expression was interpreted by the ESTIMATE algorithm, CIBERSORT algorithm, and TISIDB database. The correlations between RNF43, microsatellite instability (MSI), and tumor mutation burden (TMB) were also investigated. Furthermore, the predictive value of RNF43 for immunotherapeutic efficacy and drug sensitivity was further illustrated. Besides, immunohistochemistry (IHC) was employed to validate the expression of the RNF43 in different cancer types by our clinical cohorts, including patients with lung cancer, sarcoma, breast cancer, and kidney renal clear cell carcinoma. RESULTS: The results demonstrated that RNF43 was abnormally expressed in multiple cancers, and RNF43 is a critical prognosis-related factor in several cancers. RNF43 was frequently mutated in several cancers with a high frequency of 4%, and truncating mutation was the most frequent RNF43 mutation type. RNF43 expression was linked to the abundance of several immune cell types, including CD8+ T cells, B cells, and macrophages within the tumor immune microenvironment. Furthermore, RNF43 expression was significantly correlated with the efficacy of anti-PD-1/PD-L1 treatment, and it could predict the sensitivity of various anti-cancer drugs. Finally, IHC explored and validated the different expression levels of RNF43 in different cancers by our clinical samples. CONCLUSION: Our results first present the expression pattern and the mutation signature of RNF43, highlighting that RNF43 is an important prognostic biomarker in pan-cancer. Furthermore, RNF43 seems to be a critical modulator in the tumor immune microenvironment and can function as a promising biomarker for predicting the immunotherapeutic efficacy of anti-PD-1/PD-L1 treatment, and drug sensitivity in cancer treatment.

Exploring effective ways to increase reliable positive samples for machine learning-based urban waterlogging susceptibility assessments.

Machine learning (ML)-based urban waterlogging susceptibility studies suffer from class imbalance, as fewer positive samples are generally available than potential negative samples. Few studies have considered optimizing the results by improving the quality of training samples. To address this issue, we explored effective approaches to reliably increase the numbers of positive samples for such studies. The Synthetic Minority Over-Sampling Technique (SMOTE) and Optimized Seed Spread Algorithm (OSSA), representative of oversampling (synthesizing new samples based on the feature space) and physical (simulating potential inundated area based on the mechanisms of water flow) approaches, respectively, were employed to increase the number of positive samples. Waterlogging in Shenzhen was selected as a case study using eight selected spatial variables. An elaborate experiment was conducted to compare the quality of added samples based on the classifiers' performance and accuracy of waterlogging susceptibility maps (WSMs). The results indicated that (1) the performance of classifiers generated with SMOTE was worse than the original samples, while the use of OSSA improved the trained classifiers, and (2) the accuracy of WSMs was not improved with SMOTE but increased markedly with OSSA. These results may be driven by the diversity of information and features of the added samples. This study indicates the use of SMOTE fails to synthesize reliable samples when applied to waterlogging analysis in Shenzhen, whereas an effective solution for generating reliable positive samples is to use OSSA that simulates the potential submerged regions based on the mechanisms of disaster occurrence and spread.

Ferroptosis-related gene HIC1 in the prediction of the prognosis and immunotherapeutic efficacy with immunological activity.

Background: Hypermethylated in Cancer 1 (HIC1) was originally confirmed as a tumor suppressor and has been found to be hypermethylated in human cancers. Although growing evidence has supported the critical roles of HIC1 in cancer initiation and development, its roles in tumor immune microenvironment and immunotherapy are still unclear, and no comprehensive pan-cancer analysis of HIC1 has been conducted. Methods: HIC1 expression in pan-cancer, and differential HIC1 expression between tumor and normal samples were investigated. Immunohistochemistry (IHC) was employed to validate HIC1 expression in different cancers by our clinical cohorts, including lung cancer, sarcoma (SARC), breast cancer, and kidney renal clear cell carcinoma (KIRC). The prognostic value of HIC1 was illustrated by Kaplan-Meier curves and univariate Cox analysis, followed by the genetic alteration analysis of HIC1 in pan-cancer. Gene Set Enrichment Analysis (GSEA) was conducted to illustrate the signaling pathways and biological functions of HIC1. The correlations between HIC1 and tumor mutation burden (TMB), microsatellite instability (MSI), and the immunotherapy efficacy of PD-1/PD-L1 inhibitors were analyzed by Spearman correlation analysis. Drug sensitivity analysis of HIC1 was performed by extracting data from the CellMiner™ database. Results: HIC1 expression was abnormally expressed in most cancers, and remarkable associations between HIC1 expression and prognostic outcomes of patients in pan-cancer were detected. HIC1 was significantly correlated with T cells, macrophages, and mast cell infiltration in different cancers. Moreover, GSEA revealed that HIC1 was significantly involved in immune-related biological functions and signaling pathways. There was a close relationship of HIC1 with TMB and MSI in different cancers. Furthermore, the most exciting finding was that HIC1 expression was significantly correlated with the response to PD-1/PD-L1 inhibitors in cancer treatment. We also found that HIC1 was significantly correlated with the sensitivity of several anti-cancer drugs, such as axitinib, batracylin, and nelarabine. Finally, our clinical cohorts further validated the expression pattern of HIC1 in cancers. Conclusions: Our investigation provided an integrative understanding of the clinicopathological significance and functional roles of HIC1 in pan-cancer. Our findings suggested that HIC1 can function as a potential biomarker for predicting the prognosis, immunotherapy efficacy, and drug sensitivity with immunological activity in cancers.

ATF3 Modulates the Proliferation, Migration, and Apoptosis of Synovial Fibroblasts after Arthroscopy by Promoting RGS1 Transcription.

BACKGROUND: Osteoarthritis (OA) is a degenerative joint disease involving both cartilage and synovium. Activating transcription factor 3 (ATF3) and regulator of G protein signaling 1 (RGS1) have been reported to be up-regulated in OA. However, little is known regarding the relationship between these two genes and the mechanism of this relationship in OA development. Therefore, the present study explores the mechanism of ATF3-mediated RGS1 in the proliferation, migration, and apoptosis of synovial fibroblasts. METHODS: After the OA cell model was constructed with TGF-ß1 induction, human fibroblast-like synoviocytes (HFLSs) were transfected with ATF3 shRNA or RGS1 shRNA alone or co-transfected with ATF3 shRNA and pcDNA3.1-RGS1. Then, proliferation, migration, apoptosis, and the expression of ATF3, RGS1, α-SMA, BCL-2, caspase3, and cleaved-caspase3 were measured. Meanwhile, the potential relationship between ATF3 and RGS1 was predicted and validated. RESULTS AND DISCUSSION: Analysis of the GSE185059 dataset suggested that RGS1 was up-regulated in OA synovial fluid exosomes. Moreover, ATF3 and RGS1 were both highly expressed in TGF-ß1-induced HFLSs. Transfection of ATF3 shRNA or RGS1 shRNA significantly reduced proliferation and migration and promoted apoptosis of TGF- ß1-induced HFLSs. Mechanistically, ATF3 bound to the RGS1 promoter and elevated RGS1 expression. Silencing ATF3 repressed proliferation and migration and enhanced apoptosis of TGF-ß1-induced HFLSs by down-regulating RGS1. CONCLUSION: ATF3 binds to the RGS1 promoter and enhances RGS1 expression to accelerate cell proliferation and block cell apoptosis in TGF-ß1-induced synovial fibroblasts.

Investigation of the clinicopathological and prognostic role of circMTO1 in multiple cancers.

OBJECTIVE: To observe the prognostic value of circular RNA mitochondrial tRNA translation optimization 1 (circMTO1) in human tumors. METHODS: We searched multiple databases for related reports published before November 01, 2021. The OR/HR and 95% CI were extracted to explore the correlation between circMTO1 expression and clinicopathological features in various cancers. The stability of the results from meta-analysis was estimated via sensitivity analysis. We adopted Begg's funnel plots and Egger's test to appraise the potential bias of publication. Subgroup analysis for overall survival (OS) were also performed. RESULTS: 11 studies containing 1383 patients and 4 articles including 536 patients were enrolled. We found that low expression status of circMTO1 was significantly related to big tumor size (OR=2.11, 95% CI: 1.26-3.56, P<0.05), poor differentiation tumors (OR=2.09, 95% CI: 1.46-2.98, P<0.05), OS (HR=2.02, 95% CI: 1.63-2.50, P<0.05), disease-free survival (DFS) (HR=1.83, 95% CI: 1.27-2.56, P<0.05) of cancers. Subgroup analysis indicated that low expression status of circMTO1 was correlated with OS, regardless of analysis method, cut-off value, case number and NOS score. CONCLUSIONS: The low expression of circMTO1 may predict big tumor size, poor differentiation and worse outcome of cancer, presenting that circMTO1 may be a useful biomarker for prognosis of tumors.

Low dose aspirin associated with greater bone mineral density in older adults.

The use of low-dose aspirin in older adults is increasing as is the prevalence of osteoporosis. Aspirin has been shown in numerous studies to affect bone metabolism. However, there is no clear link between low-dose aspirin use and bone mineral density (BMD). This study examined differences in bone mineral density between low-dose aspirin users and non-aspirin users in adults aged 50-80 years. We conducted a cross-sectional study of 15,560 participants who participated in the National Health and Nutrition Examination Survey (NHANES) 2017-March 2020. We used a multivariate logistic regression model to evaluate the relationship between low-dose aspirin and femoral neck BMD, femoral total BMD, intertrochanteric BMD, and the first lumbar vertebra BMD (L1 BMD) in patients aged 50 to 80 years. A total of 1208 (Group 1: femoral neck BMD, total femur BMD, and intertrochanter BMD) and 1228 (Group 2: L1 BMD) adults were included in this study. In both group 1 and group 2, BMD was higher in the low-dose aspirin group than in the non-aspirin group (Total femur BMD ß = 0.019, 95% CI 0.004-0.034; Femoral neck BMD ß = 0.017, 95% CI 0.002-0.032; Intertrochanter BMD ß = 0.025, 95% CI 0.007-0.043; L1 BMD ß = 0.026, 95% CI 0.006-0.046). In subgroup analyses stratified by gender, this positive association existed in both gender after adjusting for confounders. On subgroup analyses stratified by age, this positive association existed in three different age groups after adjusting for confounders. To test whether the effect of low-dose aspirin on BMD was affected by gender and age, the interaction P value was greater than 0.05. These findings from a human study looking into the relationship between low-dose aspirin use and BMD suggest that regular low-dose aspirin may be associated with a higher BMD. The association between low-dose aspirin and BMD did not differ by age group or gender.

Pan-cancer analysis of CREB3L1 as biomarker in the prediction of prognosis and immunotherapeutic efficacy.

Background: CAMP response element binding protein 3-like 1 (CREB3L1) has been indicated as a critical biomarker and can modulate multifaced behaviors of tumor cells in diverse cancers. However, a systematic assessment of CREB3L1 in pan-cancer is of absence, and the predictive value of CREB3L1 in cancer prognosis, the tumor immune microenvironment and the efficacy of immunotherapy remains unexplored. Methods: CREB3L1 expression in 33 different cancer types was investigated using RNAseq data from The Cancer Genome Atlas (TCGA) database. The characteristics of CREB3L1 alternations were illustrated in cBioPortal database. The prognostic and clinicopathological value of CREB3L1 was analyzed through clinical data downloaded from the TCGA database. The potential role of CREB3L1 in the tumor immune microenvironment was illustrated by utilizing CIBERSORT and ESTIMATE algorithms, and TISIDB online database. The associations between CREB3L1 expression and tumor mutation burden (TMB), and microsatellite instability (MSI) were assessed by spearman's rank correlation coefficient. Furthermore, Gene Set Enrichment Analysis (GSEA) was conducted to explore the potential biological functions and downstream pathways of CREB3L1 in different human cancers. The correlations of CREB3L1 expression with PD-1/PD-L1 inhibitors efficacy and drug sensitivity were also investigated. Results: The expression of CREB3L1 was abnormally high or low in several different cancer types, and was also strictly associated with the prognosis of cancer patients. CREB3L1 expression levels have a strong relationship with infiltrating immune cells, including regulatory T cells, CD8+ T cells, macrophages, B naïve cells, dendritic cells and mast cells. CREB3L1 expression was also correlated with the expression of multiple immune-related biomolecules, TMB, and MSI in several cancers. Moreover, CREB3L1 had promising applications in predicting the immunotherapeutic benefits and drug sensitivity in cancer management. Conclusions: Our results highlight the value of CREB3L1 as a predictive biomarker for the prognosis and immunotherapy efficacy in multiple cancers, and CREB3L1 seems to play key roles in the tumor immune microenvironment, suggesting the role of CREB3L1 as a promising biomarker for predicting the prognosis and immune-related signatures in diverse cancers.

Clinical and radiological outcomes of combined modular prothesis and cortical strut for revision proximal femur in giant cell tumor of bone patients.

BACKGROUND: Femoral bone deficiency is a challenging problem in revision proximal femoral replacement. The purpose of this study is to evaluate the clinical and radiological outcomes of revision proximal femoral replacement as a salvage treatment for severe bone loss after oncologic proximal replacement surgery in patient with benign giant cell tumor of bone. METHODS: 16 patients (6 men and 10 women) were included in this retrospective study, with a mean age of 46.6 year at the time of revision surgery. All patients underwent revision proximal femoral replacement with the use of modular prosthesis and cortical strut allografts. The modified Harris Hip Score, Short Form 36, and musculoskeletal Tumor Society Score were used for patient evaluation. Regular follow-up was performed to evaluate the recurrence and metastases rate, limb function, and long-term complications of patients. RESULTS: The average follow-up was 46.3 months (range, 26-75 months), during which there was no local recurrence and metastases of patient. At the latest follow-up, the mean modified Harris Hip Score was 70.6 points, which was significantly improved compared with that of preoperative (p < 0.05). The final follow-up results of Short Form 36, Musculoskeletal Tumor Society Score, and limb-length discrepancy were also significantly improved compared to that of preoperative (p < 0.05). At the latest follow-up, the implanted femoral stems were all stable and all cortical strut allografts were also incorporated to their own bone. CONCLUSION: Using modular prosthesis and cortical strut allografts in revision, proximal femur replacement is an acceptable procedure for relatively young patient with severe proximal femoral bone loss after oncologic surgery with benign giant cell tumor of bone. More attentions should be paid to reduce the risk of complications in these complex reconstructions.

Integrative analysis of expression, prognostic significance and immune infiltration of RFC family genes in human sarcoma.

OBJECTIVE: To reveal the expression and prognostic value of replication factor C family genes (RFCs) in patients with sarcoma. RESULTS: The results showed that the mRNA expression levels of RFC2, RFC3, RFC4, and RFC5 were increased in sarcoma tissues. In addition, Cancer Cell Line Encyclopedia (CCLE) dataset analysis indicated that RFC1, RFC2, RFC3, RFC4, and RFC5 were elevated expressed in sarcoma cell lines. Moreover, Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan-Meier Plotter showed that highly expressed RFC2-5 were associated with poor overall survival (OS) or relapse-free survival (RFS) in sarcoma patients. The results of the Tumor Immune Estimation Resource (TIMER) database indicated that the expression of RFCs was negatively correlated with the infiltration of CD4+ T cells and macrophages. CONCLUSIONS: There were significant differences in the expression of RFCs between normal tissue and sarcoma tissue, and RFC2, RFC3, RFC4, and RFC5 might be promising prognostic biomarkers for sarcoma. METHODS: The expression of RFCs was analyzed using the ONCOMINE dataset and GEPIA dataset. CCLE dataset was used to assess the expression of RFCs in the cancer cell line. The prognostic value of RFCs was evaluated by GEPIA and Kaplan-Meier analysis. Furthermore, the association between RFCs and their co-expressed genes were explored via ONCOMINE and GEPIA datasets. We used the TIMER dataset to analyze the immune cell infiltration of RFCs in sarcoma.

Construction of a Novel Signature and Prediction of the Immune Landscape in Soft Tissue Sarcomas Based on N6-Methylandenosine-Related LncRNAs.

Background: N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) are critically involved in cancer development. However, the roles and clinical significance of m6A-related lncRNAs in soft tissue sarcomas (STS) are inconclusive, thereby warranting further investigations. Methods: Transcriptome profiling data were extracted from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx). Consensus clustering was employed to divide patients into clusters and Kaplan-Meier analysis was used to explore the prognostic differences between the subgroups. Gene set enrichment analysis (GSEA) was conducted to identify the biological processes and signaling pathways associated with m6A-Related lncRNAs. Finally, patients were randomly divided into training and validation cohorts, and least absolute shrinkage and selection operator (LASSO) Cox regression was conducted to establish the m6A-related lncRNA-based risk signature. Results: A total of 259 STS patients from TCGA-SARC dataset were enrolled in our study. Thirteen m6A-Related lncRNAs were identified to be closely related to the prognosis of STS patients. Patients were divided into two clusters, and patients in cluster 2 had a better overall survival (OS) than those in cluster 1. Patients in different clusters also showed differences in immune scores, infiltrating immune cells, and immune checkpoint expression. Patients were further classified into high-risk and low-risk subgroups according to risk scores, and high-risk patients were found to have a worse prognosis. The receiver operating characteristic (ROC) curve indicated that the risk signature displayed excellent performance at predicting the prognosis of patients with STS. Further, the risk signature was remarkably connected with the immune microenvironment and chemosensitivity in STS. Conclusion: Our study demonstrated that m6A-related lncRNAs were significantly associated with prognosis and tumor immune microenvironment and could function as independent prognosis-specific predictors in STS, thereby providing novel insights into the roles of m6A-related lncRNAs in STS.

Prognostic and clinicopathological value of circPVT1 in human cancers: A meta-analysis.

BACKGROUND: Circular RNA PVT1 (circPVT1) is significantly upregulated in various human cancers and is related to poor clinical outcome of cancer patients. However, the prognostic and clinicopathological value of circPVT1 in diverse human cancers remains controversial and inconclusive. AIM: The objective of our study is to evaluate the prognostic and clinicopathological role of circPVT1 for cancer patients. METHODS AND RESULTS: PubMed, Embase, Web of Science, and Cochrane Library were searched for eligible studies by October 1, 2020. The correlation between circPVT1 expression, and overall survival (OS) and clinical parameters was assessed by pooled hazard ratios (HRs) and odds ratios (ORs) with 95% confidence intervals (CIs). Subgroup analyses, heterogeneity, and publication bias were conducted to further enhance reliability. Twelve studies (1282 patients) were selected for this meta-analysis, including 11 on prognosis and 10 on clinicopathological parameters. Elevated expression of circPVT1 was associated with a worse OS in cancer patients (HR, 2.009; 95% CI, 1.667-2.408, 1.892; P < .001). For clinicopathological value, upregulation of circPVT1 was closely related to poor clinical parameters lymph node metastasis (OR = 2.019; 95% CI, 1.026-3.976; P = .042; I2  = 77.5%; PH  = 0.000), late clinical stage (OR = 3.594; 95% CI, 1.828-7.065; P < .001; I2  = 71.7%; PH  = 0.001), distant metastasis (OR = 4.598; 95% CI, 1.411-14.988; P = .011; I2  = 78.1%; PH  = 0.001), and chemoresistant (OR = 6.400; 95% CI, 2.107-19.441; P = .001; I2  = 49.6%; PH  = 0.159). CONCLUSION: High expression of circPVT1 is correlated with unfavorable prognosis of cancer patients, indicating that circPVT1 can function as a potential prognostic biomarker in human cancer.

An Optimized Weighted Naïve Bayes Method for Flood Risk Assessment.

Floods occur frequently and cause considerable damage to local environments. Effectively assessing the flood risk contributes to reducing loss caused by such disasters. In this study, the weighted naïve Bayes (WNB) method was selected to evaluate flood risk, and the entropy weight method was employed to compute the weights. A sampling and verifying model was employed to generate the most accurate conditional probability table (MACPT) to calculate the probability of flooding. When using the framework integrating WNB with the sampling and verifying model, previous studies could not obtain a WNB-based MACPT and the WNB classification accuracy, for lacking WNB functions that could be called directly. Facing this issue, in this study we developed WNB functions with the MATLAB platform to directly integrate with the sampling and verifying model to generate a WNB-based MACPT, contributing to the greater interpretability and extensibility of the model. Shantou and Jieyang cities in China were selected as the study area. The results demonstrate that: (1) a WNB-based MACPT can reflect the real spatial distribution of flood risk and (2) the WNB outperform the NB when integrated with the sampling and verifying model. The resulting gridded estimation reveal a detailed spatial pattern of flood risk, which can serve as a realistic reference for decision making related to floods. Furthermore, the proposed method uses less data, which would be helpful in developing countries where long-term intensive hydrologic monitoring is limited.

Functions and mechanisms of circular RNAs in regulating stem cell differentiation.

Stem cells are a class of undifferentiated cells with great self-renewal and differentiation capabilities that can differentiate into mature cells in specific tissue types. Stem cell differentiation plays critical roles in body homoeostasis, injury repair and tissue generation. The important functions of stem cell differentiation have resulted in numerous studies focusing on the complex molecular mechanisms and various signalling pathways controlling stem cell differentiation. Circular RNAs (circRNAs) are a novel class of noncoding RNAs with a covalently closed structure present in eukaryotes. Numerous studies have highlighted important biological functions of circRNAs, and they play multiple regulatory roles in various physiological and pathological processes. Importantly, multiple lines of evidence have shown the abnormal expression of numerous circRNAs during stem cell differentiation, and some play a role in regulating stem cell differentiation, highlighting the role of circRNAs as novel biomarkers of stem cell differentiation and novel targets for stem cell-based therapy. In this review, we systematically summarize and discuss recent advances in our understanding of the roles and underlying mechanisms of circRNAs in modulating stem cell differentiation, thus providing guidance for future studies to investigate stem cell differentiation and stem cell-based therapy.Abbreviations: CircRNAs: circular RNAs; ESCs: embryonic stem cells; ADSCs: adipose-derived mesenchymal stem cells; ecircRNAs: exonic circRNAs; EIciRNAs: exon-intron circRNAs; eiRNAs: circular intronic RNAs; tricRNAs: tRNA intronic circRNAs; pol II: polymerase II; snRNP: small nuclear ribonucleoprotein; m6A: N6-methyladenosine; AGO2: Argonaute 2; RBPs: RNA-binding proteins; MBNL: muscleblind-like protein 1; MSCs: mesenchymal stem cells; hiPSCs: human induced pluripotent stem cells; hiPSC-CMs: hiPSC-derived cardiomyocytes; hBMSCs: human bone marrow mesenchymal stem cells; hADSCs: human adipose-derived mesenchymal stem cells; hDPSCs: human dental pulp stem cells; RNA-seq: high-throughput RNA sequencing; HSCs: haematopoietic stem cells; NSCs: neural stem cells; EpSCs: epidermal stem cells; hESCs: human embryonic stem cells; mESCs: murine embryonic stem cells; MNs: motor neurons; SSUP: small subunit processome; BMSCs: bone marrow-derived mesenchymal stem cells; OGN: osteoglycin; GIOP: glucocorticoid­induced osteoporosis; CDR1as: cerebellar degeneration-related protein 1 transcript; SONFH: steroid-induced osteogenesis of the femoral head; rBMSCs: rat bone marrow-derived mesenchymal stem cells; QUE: quercetin; AcvR1b: activin A receptor type 1B; BSP: bone sialoprotein; mADSCs: mouse ADSCs; PTBP1: polypyrimidine tract-binding protein; ER: endoplasmic reticulum; hUCMSCs: MSCs derived from human umbilical cord; MSMSCs: maxillary sinus membrane stem cells; SCAPs: stem cells from the apical papilla; MyoD: myogenic differentiation protein 1; MSTN: myostatin; MEF2C: myocyte enhancer factor 2C; BCLAF1: BCL2-associated transcription factor 1; EpSCs: epidermal stem cells; ISCs: intestinal stem cells; NSCs: neural stem cells; Lgr5+ ISCs: crypt base columnar cells; ILCs: innate lymphoid cells.

Flood susceptibility mapping by integrating frequency ratio and index of entropy with multilayer perceptron and classification and regression tree.

Episodes of frequent flooding continue to increase, often causing serious damage and tools to identify areas affected by such disasters have become indispensable in today's society. Using the latest techniques can make very accurate flood predictions. In this study, we introduce four effective methods to evaluate the flood susceptibility of Poyang County, in China, by integrating two independent models of frequency ratio and index of entropy with multilayer perceptron and classification and regression tree models. The flood locations of the study area were identified through the flood inventory process, and 12 flood conditioning factors were used in the training and validation processes. According to the results of the linear support vector machine, elevation, slope angle, and soil have the highest predictive ability. The experimental results of the four hybrid models demonstrate that between 20% and 50% of the study area has high and very high flood susceptibility. The multilayer perceptron-probability density hybrid model is the most effective among the six comparative methods.

A novel optimized repeatedly random undersampling for selecting negative samples: A case study in an SVM-based forest fire susceptibility assessment.

The negative sample selection method is a key issue in studies of using machine learning approaches to spatially assess natural hazards. Recently, a Repeatedly Random Undersampling (RRU) was proposed to address the randomness problem faced in Single Random Sampling. However, the RRU cannot guarantee that the generated classifier has the best classification performance during the repeatedly random sampling process. To address this weakness, in this study we proposed an optimized RRU, which follows the idea of RRU, and then changing its rule to find a best classifier. Then, the selected classifier, the actual most accurate classifier (MAC), was employed to compute the probability of hazard occurrence. Support Vector Machine (SVM) was selected as the analysis method, and Genetic Algorithm was employed to compute the parameters of SVM. Forest fire susceptibility was assessed in Huichang County in China due to its forest values and frequent fire events. The results indicated that compared with the RRU, the optimized RRU can find out an actual MAC which has the best classification performance among possible MACs; also, the fire susceptibility map generated by the actual MAC comforts to objective facts. The generated fire susceptibility map can provide useful decision supports for local government to reduce forest fire risks. Moreover, the proposed sampling method, the optimized RRU, presented an enhanced approach for selecting negative samples, which makes the results of forest fire susceptibility assessment more reliable and accurate.

Total knee arthroplasty in a patient with ipsilateral hip ankylosis: A case report.

RATIONALE: There is a large number of people that have knee degeneration in China. Total knee arthroplasty is one of the most effective methods of treatment in the later stages of the disease. However, there are challenges when performing total knee arthroplasty on patients with ipsilateral hip akylosis. So far, there are few reports on postoperative curative effect of total knee arthroplasty for these patients. This case report records how to perform total knee arthroplasty in a patient with ipsilateral hip ankylosis. PATIENT CONCERNS: Due to ankylosing spondylitis, the flexion of the patient's hips are restricted in 10°, which leads to a limited ipsilateral knee flexion to 30° when she is in the supine position. DIAGNOSES: Right knee osteoarthritis; right hip ankylosis. INTERVENTIONS: We modified the traditional surgical position to allow easy exposure of the knee during surgery. After total knee arthroplasty, the patient was included in a planned training program, and was followed for 6 months. OUTCOMES: The patient walked well without ambulation aid and achieved satisfactory knee joint function. LESSONS: Conversion of a fused hip to a total hip arthroplasty does improve the quality of life of patients, but, given the high incidence of complications and more financial burden to the patient, we modified traditional surgical position of the patient to provide ideal surgical exposure of the knee. We hope that this case can be used as a reference for clinicians to deal with similar situations.

A spatial assessment of urban waterlogging risk based on a Weighted Naïve Bayes classifier.

Urban waterlogging occurs frequently and often causes considerable damage that seriously affects the natural environment, human life, and the social economy. The spatial evaluation of urban waterlogging risk represents an essential analytic step that can be used to prevent urban waterlogging and minimize related losses. The Weighted Naïve Bayes (WNB) classifier is a powerful method for knowledge discovery and probability inference under conditions of uncertainty; a WNB classifier can be applied to estimate the likelihood of hazards. Six spatial factors were considered to be added to the WNB, which may improve the efficiency in predicting urban waterlogging risk during analysis. As such, a spatial framework integrating WNB with GIS was developed to assess the risk of urban waterlogging using the primary urban area of Guangzhou in China as an example. The results show that 1) the rationality of six spatial factors was determined according to the Conditional Probability Tables and weights; 2) the Most Accurate Sampling Table has objectivity; and 3) the areas with a high likelihood of waterlogging risk were mainly located in the southwestern part of the study area. The northeastern zones are relatively free of waterlogging risk. The results reveal a more accurate spatial pattern of urban waterlogging risk that can be used to identify risk "hot spots". The resulting gridded estimates provide a realistic reference for decision making related to urban waterlogging.