Progress in small-molecule inhibitors targeting PD-L1.

PD-L1 is a transmembrane protein overexpressed by tumor cells. It binds to PD-1 on the surface of T-cells, suppresses T-cell activity and hinders the immune response against cancer. Clinically, several monoclonal antibodies targeting PD-1/PD-L1 have achieved significant success in cancer immunotherapy. Nevertheless, their disadvantages, such as unchecked immune responses, high cost and long half-life, stimulated pharmacologists to develop small-molecule inhibitors targeting PD-1/PD-L1. After a batch of excellent inhibitors with a biphenyl core structure were firstly reported by BMS, more and more researchers focused on small-molecule inhibitors targeting PD-L1 rather than PD-1. Numerous small-molecule inhibitors were extensively designed and synthesized in the past few years. In this paper, the structural characteristics of PD-L1 and complexes of PD-L1 with its inhibitors are elaborated and small molecule inhibitors developed in the last decade are summarized as well. This paper aims to provide insights into further designing and synthesis of small molecule inhibitors targeting PD-L1.

Comparative analysis of models in predicting the effects of SNPs on TF-DNA binding using large-scale in vitro and in vivo data.

Non-coding variants associated with complex traits can alter the motifs of transcription factor (TF)-deoxyribonucleic acid binding. Although many computational models have been developed to predict the effects of non-coding variants on TF binding, their predictive power lacks systematic evaluation. Here we have evaluated 14 different models built on position weight matrices (PWMs), support vector machines, ordinary least squares and deep neural networks (DNNs), using large-scale in vitro (i.e. SNP-SELEX) and in vivo (i.e. allele-specific binding, ASB) TF binding data. Our results show that the accuracy of each model in predicting SNP effects in vitro significantly exceeds that achieved in vivo. For in vitro variant impact prediction, kmer/gkm-based machine learning methods (deltaSVM_HT-SELEX, QBiC-Pred) trained on in vitro datasets exhibit the best performance. For in vivo ASB variant prediction, DNN-based multitask models (DeepSEA, Sei, Enformer) trained on the ChIP-seq dataset exhibit relatively superior performance. Among the PWM-based methods, tRap demonstrates better performance in both in vitro and in vivo evaluations. In addition, we find that TF classes such as basic leucine zipper factors could be predicted more accurately, whereas those such as C2H2 zinc finger factors are predicted less accurately, aligning with the evolutionary conservation of these TF classes. We also underscore the significance of non-sequence factors such as cis-regulatory element type, TF expression, interactions and post-translational modifications in influencing the in vivo predictive performance of TFs. Our research provides valuable insights into selecting prioritization methods for non-coding variants and further optimizing such models.

Platinum-based neoadjuvant chemotherapy upregulates STING/IFN pathway expression and promotes TILs infiltration in NSCLC.

Objectives: To evaluate the effects of platinum-based neoadjuvant chemotherapy (NACT) on the STING/IFN pathway and tumor-infiltrating lymphocytes (TILs) in non-small cell lung cancer (NSCLC), as well as clinicopathological factors affecting patient survival. Materials and methods: A total of 68 patients aged 34-77 years with NSCLC who received neoadjuvant chemotherapy and surgical treatment from March 2012 to February 2019 were reviewed, and the clinical pathological data and paired tissue specimens before and after NACT were collected. Immunohistochemistry and immunofluorescence were used to detect the protein levels of STING, PD-L1 and IFN-ß, and the infiltration density of CD3+ TILs and CD8+TILs. The correlation between the expression of STING, PD-L1, IFN-ß and the infiltration density of CD3+ TILs and CD8+ TILs as well as the clinicopathological characteristics before and after NACT was analyzed. The relationship between the related indexes, clinicopathological features and prognosis was also discussed. Results: NACT increased the expression of STING, IFN-ß and PD-L1 in tumor cells, and the infiltration of CD3+ and CD8+ TILs. In addition, ypTNM stage, ypN stage, changes in CD3+ TILs and in PD-L1 were associated with DFS (disease-free survival). CD3+ TILs changes and ypN stage were associated with OS (overall survival). Notably, ypN stage and CD3+ TILs changes were independent prognostic factors for DFS and OS. Conclusion: NACT stimulates STING/IFN-ß pathway, promotes infiltration of CD3+ and CD8+ TILs, triggers innate and adaptive immunity, and also upregulates PD-L1, which complemented the rationale for neoadjuvant chemotherapy in combination with immunotherapy. In addition, DFS was longer in patients with ypTNM I, ypN0-1, and elevated CD3+TILs after NACT. Patients with ypN0 and elevated CD3+ TILs after NACT had better OS benefits.

Alectinib continuation beyond progression in ALK-positive non-small cell lung cancer with alectinib-refractory.

Background: Alectinib, a next-generation anaplastic lymphoma kinase tyrosine kinase inhibitor (ALK-TKI), has demonstrated noteworthy efficacy in the treatment of non-small cell lung cancer (NSCLC). Unfortunately, 53.3% of untreated patients receiving first-line treatment with alectinib developed resistance to alectinib. However, despite the widespread use of alectinib, studies on the efficacy and safety of continuing alectinib with other necessary therapies after progression of alectinib and possible population of benefit are still limited. Methods: This retrospective cohort study included fifteen patients with ALK-positive NSCLC from nine institutions in China who experienced disease progression after first- or second-line treatment and continued to receive alectinib treatment between 2019 and 2022. This study aimed to evaluate the median progression-free survival (mPFS), objective response rate (ORR), median overall survival (mOS), and adverse events (AEs) of continuing alectinib combined with other therapies after the emergence of drug resistance. Results: Among fifteen patients eligible for this study, all patients started continuing treatment with alectinib after oligoprogression or central nervous system (CNS) progression. The mPFS for the whole cohort receiving continuing alectinib with other necessary therapies was 8 months [95% confidence interval (CI): 4 to not applicable (NA)], with an ORR of 46.7%. The mOS was not reached. During continuing alectinib treatment, only one patient experienced grade 2 elevation of aspartate aminotransferase (AST) and serum glutamic-oxaloacetic transaminase (SGOT). Conclusions: The continuation of alectinib treatment combined with other necessary therapies demonstrates favorable response and safety in patients with ALK-positive NSCLC who experienced oligoprogression or CNS progression following alectinib in first- or second-line therapy. Instead of immediately switching to another ALK-TKI, continuing alectinib combined with other necessary therapies may offer greater survival benefits to the patients.

One-Pot Conversion of Polyester and Carbonate into Formate without External H2.

The coconversion of two kinds of waste materials, plastics and CO2, into a single value-added product is an innovative and challenging endeavor that simultaneously achieves the upcycling of plastic waste and reduces CO2 emissions. Herein, we report a one-pot, two-step catalytic process for transforming polyesters, such as poly(glycolic acid), carbonate, and water, into sodium formate with a high yield of 79%, using a commercial Pd/C catalyst. This process involves the aqueous-phase reforming of polyester with water at 250-270 °C and the hydrogenation of NaHCO3 at 150 °C, utilizing H2 generated during the reforming process. Notably, no external H2 or other reactive reagents are required. This strategy can be applied for the coconversion of poly(ethylene terephthalate) (PET), poly(butylene-adipate-co-terephthalate) (PBAT), and commercial biodegradable plastic bags with Na2CO3 obtained from CO2 capture via a NaOH solution, opening up a new path for "turning trash into treasure".

Studying financial development with low-carbon architecture development and green technological innovation: sustaining SDG-9.

In order to accomplish Sustainable Growth Goal 9, this research analyzes in detail how green technological innovation, low-carbon architectural improvement, and more significant financial growth all work together to reach the goal. This research meticulously integrates secondary data from reputable sources to examine the relationship between economic growth, technological innovation in the built environment, and environmental sustainability from 1994 to 2019. For economic insights, the World Bank's World Development Indicators is a go-to resource, while Yale University's Environmental Performance Index (EPI) is a go-to for environmental metrics. Our research is based on this synthesis of multi-dimensional data, which enables an in-depth investigation of the interplay between financial development, sustainable architecture, and technical progress toward SDG-9. This research employs quantitative and qualitative methodologies to shed light on the intricate interaction between these elements, making it useful for policymakers, scholars, and stakeholders dedicated to directing sustainable development paths.

Goal-directed fluid therapy using stroke volume variation on length of stay and postoperative gastrointestinal function after major abdominal surgery-a randomized controlled trial.

BACKGROUND AND OBJECTIVE: The effectiveness of goal-directed fluid therapy (GDFT) in promoting postoperative recovery remains unclear, the aim of this study was to evaluate the effect of GDFT on length of hospital stay and postoperative recovery of GI function in patients undergoing major abdominal oncologic surgery. METHODS: In this randomized, double- blinded, controlled trial, adult patients scheduled for elective major abdominal surgery with general anesthesia, were randomly divided into the GDFT protocol (group G) or conventional fluid therapy group (group C). Patients in group C underwent conventional fluid therapy based on mean arterial pressure (MAP) and central venous pressure (CVP) whereas those in group G received GDFT protocol associated with the SVV less than 12% and the cardiac index (CI) was controlled at a minimum of 2.5 L/min/m2. The primary outcomes were the length of hospital stay and postoperative GI function. RESULTS: One hundred patients completed the study protocol. The length of hospital stay was significantly shorter in group G compared with group C [9.0 ± 5.8 days versus 12.0 ± 4.6 days, P = 0.001]. Postoperative gastrointestinal dysfunction (POGD) occurred in two of 50 patients (4%) in group G and 16 of 50 patients (32%) in the control group (P < 0.001). GDFT significantly also shorten time to first flatus by 11 h (P = 0.009) and time to first tolerate oral diet by 2 days (P < 0.001). CONCLUSIONS: Guided by SVV and CI, the application of GDFT has the potential to expedite postoperative recovery of GI function and reduce hospitalization duration after major abdominal surgery. TRIAL REGISTRATION: This study was registered on www. CLINICALTRIALS: gov on 07/05/2019 with registration number: NCT03940144.

Role and mechanisms of SGLT-2 inhibitors in the treatment of diabetic kidney disease.

Diabetic kidney disease (DKD) is a chronic inflammatory condition that affects approximately 20-40% of individuals with diabetes. Sodium-glucose co-transporter 2 (SGLT-2) inhibitors, emerging as novel hypoglycemic agents, have demonstrated significant cardiorenal protective effects in patients with DKD. Initially, it was believed that the efficacy of SGLT-2 inhibitors declined as the estimated glomerular filtration rate (eGFR) decreased, which led to their preferential use in DKD patients at G1-G3 stages. However, recent findings from the DAPA-CKD and EMPA-KIDNEY studies have revealed equally beneficial cardiorenal effects of SGLT-2 inhibitors in individuals at stage G4 DKD, although the underlying mechanism behind this phenomenon remains unclear. In this comprehensive analysis, we provide a systematic review of the mechanisms and functioning of SGLT-2 inhibitors, potential renal protection mechanisms, and the therapeutic efficacy and safety of SGLT-2 inhibitors in kidney diseases, with a particular focus on stage G4 DKD. Gaining a deeper understanding of the renal protective effect of SGLT-2 inhibitors and their underlying mechanisms is highly significance for the successful utilization of these inhibitors in the treatment of diverse kidney disorders.

Near Infrared Light-Triggered Photocatalytic Decaging for Remote-Controlled Spatiotemporal Activation in Living Mice.

Spatiotemporal manipulation of biological processes in living animals using noninvasive, remote-controlled stimuli is a captivating but challenging endeavor. Herein, we present the development of a biocompatible photocatalytic technology termed CAT-NIR, which uses external near infrared light (NIR, 740 nm) to trigger decaging reactions in living mice. The Os(II) terpyridine complex was identified as an efficient NIR photocatalyst for promoting deboronative hydroxylation reactions via superoxide generation in the presence of NIR light, resulting in the deprotection of phenol groups and the release of bioactive molecules under living conditions. The validation of the CAT-NIR system was demonstrated through the NIR-triggered rescue of fluorophores, prodrugs as well as biomolecules ranging from amino acids, peptides to proteins. Furthermore, by combining genetic code expansion and computer-aided screening, CAT-NIR could regulate affibody binding to the cell surface receptor HER2, providing a selective cell tagging technology through external NIR light. In particular, the tissue-penetrating ability of NIR light allowed for facile prodrug activation in living mice, enabling noninvasive, remote-controlled rescue of drug molecules. Given its broad adaptability, this CAT-NIR system may open new opportunities for manipulating the functions of bioactive molecules in living animals using external NIR light with spatiotemporal resolution.

The Therapeutic Potential of CDK4/6 Inhibitors, Novel Cancer Drugs, in Kidney Diseases.

Inflammation is a crucial pathological feature in cancers and kidney diseases, playing a significant role in disease progression. Cyclin-dependent kinases CDK4 and CDK6 not only contribute to cell cycle progression but also participate in cell metabolism, immunogenicity and anti-tumor immune responses. Recently, CDK4/6 inhibitors have gained approval for investigational treatment of breast cancer and various other tumors. Kidney diseases and cancers commonly exhibit characteristic pathological features, such as the involvement of inflammatory cells and persistent chronic inflammation. Remarkably, CDK4/6 inhibitors have demonstrated impressive efficacy in treating non-cancerous conditions, including certain kidney diseases. Current studies have identified the renoprotective effect of CDK4/6 inhibitors, presenting a novel idea and potential direction for treating kidney diseases in the future. In this review, we briefly reviewed the cell cycle in mammals and the role of CDK4/6 in regulating it. We then provided an introduction to CDK4/6 inhibitors and their use in cancer treatment. Additionally, we emphasized the importance of these inhibitors in the treatment of kidney diseases. Collectively, growing evidence demonstrates that targeting CDK4 and CDK6 through CDK4/6 inhibitors might have therapeutic benefits in various cancers and kidney diseases and should be further explored in the future.

Establishment of a risk classifier to predict the in-hospital death risk of nosocomial fungal infections in cancer patients.

BACKGROUND: Patients with malignancy are at a higher risk of developing nosocomial infections. However, limited studies investigated the clinical features and prognostic factors of nosocomial infections due to fungi in cancer patients. Herein, this study aims to investigate the clinical characteristics of in-hospital fungal infections and develop a nomogram to predict the risk of in-hospital death during fungal infection of hospitalized cancer patients. METHODS: This retrospective observational study enrolled cancer patients who experienced in-hospital fungal infections between September 2013 and September 2021. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of in-hospital mortality. Variables demonstrating significant statistical differences in the multivariate analysis were utilized to construct a nomogram for personalized prediction of in-hospital death risk associated with nosocomial fungal infections. The predictive performance of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis. RESULTS: A total of 216 participants were included in the study, of which 57 experienced in-hospital death. C.albicans was identified as the most prevalent fungal species (68.0%). Respiratory infection accounted for the highest proportion of fungal infections (59.0%), followed by intra-abdominal infection (8.8%). The multivariate regression analysis revealed that Eastern Cooperative Oncology Group Performance Status (ECOG-PS) 3-4 (odds ratio [OR] = 6.08, 95% confidence interval [CI]: 2.04-18.12), pulmonary metastases (OR = 2.76, 95%CI: 1.11-6.85), thrombocytopenia (OR = 2.58, 95%CI: 1.21-5.47), hypoalbuminemia (OR = 2.44, 95%CI: 1.22-4.90), and mechanical ventilation (OR = 2.64, 95%CI: 1.03-6.73) were independent risk factors of in-hospital death. A nomogram based on the identified risk factors was developed to predict the individual probability of in-hospital mortality. The nomogram demonstrated satisfactory performance in terms of classification ability (area under the curve [AUC]: 0.759), calibration ability, and net clinical benefit. CONCLUSIONS: Fungi-related nosocomial infections are prevalent among cancer patients and are associated with poor prognosis. The constructed nomogram provides an invaluable tool for oncologists, enabling them to make timely and informed clinical decisions that offer substantial net clinical benefit to patients.

Construction and Evaluation of Clinical Prediction Model for Immunotherapy-related Adverse Events and Clinical Benefit in Cancer Patients Receiving Immune Checkpoint Inhibitors Based on Serum Cytokine Levels.

Immune checkpoint inhibitors (ICIs) have revolutionized the therapeutic landscape of cancer therapy. This study aimed to develop novel risk classifiers to predict the risk of immune-related adverse events (irAEs) and the probability of clinical benefits. Patients with cancer who received ICIs from the First Affiliated Hospital of Xi 'an Jiaotong University from November 2020 to October 2022 were recruited and followed up. Logistic regression analyses were performed to identify independent predictive factors for irAEs and clinical response. Two nomograms were developed to predict the irAEs and clinical responses of these individuals, with a receiver operating characteristic curve to assess their predictive ability. Decision curve analysis was performed to estimate the clinical utility of the nomogram. This study included 583 patients with cancer. Among them, 111 (19.0%) developed irAEs. Duration of treatment (DOT)>3 cycles, hepatic-metastases, IL2>2.225 pg/mL, and IL8>7.39 pg/mL were correlated with higher irAEs risk. A total of 347 patients were included in the final efficacy analysis, with an overall clinical benefit rate of 39.7%. DOT>3 cycles, nonhepatic-metastases, and irAEs and IL8>7.39 pg/mL were independent predictive factors of clinical benefit. Ultimately, 2 nomograms were successfully established to predict the probability of irAEs and their clinical benefits. Ultimately, 2 nomograms were successfully established to predict the probability of irAEs and clinical benefits. The receiver operating characteristic curves yielded acceptable nomogram performance. Calibration curves and decision curve analysis supported the hypothesis that nomograms could provide more significant net clinical benefits to these patients. Specific baseline plasma cytokines were closely correlated with irAEs and clinical responses in these individuals.

Monocular camera and laser based semantic mapping system with temporal-spatial data association for indoor mobile robots.

In the future, the goal of service robots is to operate in human-centric indoor environments, requiring close cooperation with humans. In order to enable the robot to perform various interactive tasks, it is necessary for robots to perceive and understand environments from a human perspective. Semantic map is an augmented representation of the environment, containing both geometric information and high-level qualitative features. It can help the robot to comprehensively understand the environment and bridge the gap in human-robot interaction. In this paper, we propose a unified semantic mapping system for indoor mobile robots. This system utilizes the techniques of scene classification and object detection to construct semantic representations of indoor environments by fusing the data of a camera and a laser. In order to improve the accuracy of semantic mapping, the temporal-spatial correlation of semantics is leveraged to realize data association of semantic maps. Also, the proposed semantic mapping system is scalable and portable, which can be applied to different indoor scenarios. The proposed system was evaluated with collected datasets captured in indoor environments. Extensive experimental results indicate that the proposed semantic mapping system exhibits great performance in the robustness and accuracy of semantic mapping.

A study of the use of virtual reality headsets in Chinese adolescents with intellectual disability.

Background: Virtual reality technologies (VRTs) present many characteristics that can facilitate learning, especially in individuals with intellectual disabilities (ID). The VRT head-mounted display (HMD) has recently shown significant technological improvement. This study aims to prove the suitability of the newer commercially available VRT HMDs used in interventions for adolescents with ID in China. To this end, we explored the acceptance, immersion, and negative effects for adolescents with ID in a series of virtual environments. Methods: Forty-nine adolescents with ID (33 boys and 16 girls, IQ < 70), aged 11 to 21, from three special schools participated in this study. Questionnaires, observations, and interviews were used to investigate their views while using a VR HMD. Results: Our analysis found that most participants narrated a pleasant experience using HMD and a series of VR experiences and experienced a high level of immersion accompanied by low negative effects. In addition, our study found that the gender variable was independent of the acceptance of HMDs and the immersion experience. Conclusions: Overall, this study suggests that the HMD is accepted by most Chinese adolescents with ID; thus, its application has great potential in China.

A novel risk classifier to predict the in-hospital death risk of nosocomial infections in elderly cancer patients.

Background: Elderly cancer patients are more predisposed to developing nosocomial infections during anti-neoplastic treatment, and are associated with a bleaker prognosis. This study aimed to develop a novel risk classifier to predict the in-hospital death risk of nosocomial infections in this population. Methods: Retrospective clinical data were collected from a National Cancer Regional Center in Northwest China. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm was utilized to filter the optimal variables for model development and avoid model overfitting. Logistic regression analysis was performed to identify the independent predictors of the in-hospital death risk. A nomogram was then developed to predict the in-hospital death risk of each participant. The performance of the nomogram was evaluated using receiver operating characteristics (ROC) curve, calibration curve, and decision curve analysis (DCA). Results: A total of 569 elderly cancer patients were included in this study, and the estimated in-hospital mortality rate was 13.9%. The results of multivariate logistic regression analysis showed that ECOG-PS (odds ratio [OR]: 4.41, 95% confidence interval [CI]: 1.95-9.99), surgery type (OR: 0.18, 95%CI: 0.04-0.85), septic shock (OR: 5.92, 95%CI: 2.43-14.44), length of antibiotics treatment (OR: 0.21, 95%CI: 0.09-0.50), and prognostic nutritional index (PNI) (OR: 0.14, 95%CI: 0.06-0.33) were independent predictors of the in-hospital death risk of nosocomial infections in elderly cancer patients. A nomogram was then constructed to achieve personalized in-hospital death risk prediction. ROC curves yield excellent discrimination ability in the training (area under the curve [AUC]=0.882) and validation (AUC=0.825) cohorts. Additionally, the nomogram showed good calibration ability and net clinical benefit in both cohorts. Conclusion: Nosocomial infections are a common and potentially fatal complication in elderly cancer patients. Clinical characteristics and infection types can vary among different age groups. The risk classifier developed in this study could accurately predict the in-hospital death risk for these patients, providing an important tool for personalized risk assessment and clinical decision-making.

Guanxinping ameliorates atherosclerosis via MAPK/NF-κB signaling pathway in ApoE-/- mice.

BACKGROUND: Atherosclerosis (AS), one of the leading causes of deaths and disabilities, is a kind of vascular disease of lipid disorders and chronic inflammation. Guanxinping (GXP) has been administrated in the treatment of AS for nearly 20 years with satisfying clinical response. This study aimed to explore its underlying mechanisms of anti-atherosclerotic effect in AS. METHODS: Male ApoE-/- mice were randomized into five groups and fed with either standard diet (control group, CON) or high-fat diet (HFD) for 12 weeks. HFD mice were further divided randomly and either fed continually with HFD as a model group, or atorvastatin (ATO), or low-dose GXP (LGXP), or high-dose GXP (HGXP). After 12 weeks, the body weight, serum triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-c), and low-density lipoprotein cholesterol (LDL-c) were detected. Moreover, serum inflammation cytokines including tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and interleukin-1ß (IL-1ß) concentrations were measured. The structure of aortic tissues was examined by hematoxylin-eosin staining. The mRNA expression of TNF-α, IL-6, and IL-1ß were assessed by qPCR. The protein expressions of ICAM-1, VCAM-1, MCP-1, IL-6, IL-1ß, p38MAPK, ERK1/2, JNK, IκB-α, and NF-κBp65 in the aorta were also detected. RESULTS: GXP treatment reduced serum TG, TC, and LDL-c levels in ApoE-/- mice. Moreover, GXP reduced lipid accumulation in the aorta of ApoE-/- mice, induced by HFD. Furthermore, GXP ameliorated the aorta morphological damage and reduced the serum TNF-α, IL-6, and IL-1ß levels. GXP also attenuated the protein expression of ICAM-1, VCAM-1, MCP-1, IL-6, IL-1ß, p38MAPK, ERK1/2, JNK, and NF-κBp65, whereas it increased the IκBα level in aortic tissues of ApoE-/- mice. CONCLUSIONS: Our results show that GXP could ameliorate atherosclerosis, which is mediated by inhibition of the MAPK/NF-κB signaling pathway in ApoE-/- mice. This study provides evidence that GXP might be a promising drug for the treatment of AS.

Exposure level of neonicotinoid pesticides and their metabolites in pregnant women in the suburb of Shanghai / 中华预防医学杂志

In 2021, a total of 151 pregnant women were selected from the suburb of Shanghai. A questionnaire survey was conducted to obtain data about maternal age, gestational week, total annual household income, education level and passive smoking among pregnant women and one spot urine was collected. The concentrations of eight neonicotinoid pesticides and four metabolites in urine were measured by ultra-high performance liquid chromatography-tandem quadrupole time-of-flight mass spectrometry. The differences in detection frequencies and concentrations of neonicotinoid pesticides and their metabolites among pregnant women with different characteristics were compared, and the influencing factors of the detection of neonicotinoid pesticides in urine were analyzed. The results showed that at least one neonicotinoid pesticide was detected in 93.4% (141 samples) of urine samples. The detection frequencies of N-desmethyl-acetamiprid, clothianidin, thiamethoxam, and N-desmethyl-clothianidin were high, about 78.1% (118 samples), 75.5% (114 samples), 68.9% (104 samples), and 44.4% (67 samples), respectively. The median concentration of the sum of all neonicotinoid pesticides was 2.66 μg/g. N-desmethyl-acetamiprid had the highest detection concentration with a median concentration of 1.04 μg/g. A lower urinary detection frequency of imidacloprid and its metabolites was seen in pregnant women aged 30-44 years [OR (95%CI): 0.23 (0.07-0.77)]. A higher detection frequency of clothianidin and its metabolites was seen in pregnant women with per capita annual household income≥100 000 yuan [OR (95%CI): 6.15 (1.56-24.28)]. There was widespread exposure to neonicotinoid pesticides and their metabolites in pregnant women from the suburb of Shanghai, which might pose potential health risks to pregnant women, and maternal age and household income were potential influencing factors of the exposure to neonicotinoid pesticides.

A novel risk classifier for predicting the overall survival of patients with thymic epithelial tumors based on the eighth edition of the TNM staging system: A population-based study.

Objective: Thymic epithelial tumors (TETs) are rare tumors that originated from thymic epithelial cells, with limited studies investigating their prognostic factors. This study aimed to investigate the prognostic factors of TETs and develop a new risk classifier to predict their overall survival (OS). Methods: This retrospective study consisted of 1224 TETs patients registered in the Surveillance, Epidemiology, and End Results (SEER) database, and 75 patients from the First Affiliated Hospital of Xi'an Jiaotong University. The univariate and multivariate Cox regression analyses were adopted to select the best prognostic variables. A nomogram was developed to predict the OS of these patients. The discriminative and calibrated abilities of the nomogram were assessed using the receiver operating characteristics curve (ROC) and calibration curve. Decision curve analysis (DCA), net reclassification index (NRI), and integrated discrimination improvement (IDI) were adopted to assess its net clinical benefit and reclassification ability. Results: The multivariate analysis revealed that age, sex, histologic type, TNM staging, tumor grade, surgery, radiation, and tumor size were independent prognostic factors of TETs, and a nomogram was developed to predict the OS of these patients based on these variables. The time-dependent ROC curves displayed that the nomogram yielded excellent performance in predicting the 12-, 36- and 60-month OS of these patients. Calibration curves presented satisfying consistencies between the actual and predicted OS. DCA illustrated that the nomogram will bring significant net clinical benefits to these patients compared to the classic TNM staging system. The estimated NRI and IDI showed that the nomogram could significantly increase the predictive ability of 12-, 36- and 60-month OS compared to the classic TNM staging system. Consistent findings were discovered in the internal and external validation cohorts. Conclusion: The constructed nomogram is a reliable risk classifier to achieve personalized survival probability prediction of TETs, and could bring significant net clinical benefits to these patients.

FDRdb: a manually curated database of fibrotic disease-associated RNAome and high-throughput datasets.

Fibrosis is a common and serious disease that exists as a complicated impairment in many organs and triggers a complex cascade of responses. The deregulation of Ribonucleic Acids (RNAs) plays important roles in a variety of organ fibrosis cases. However, for fibrotic diseases, there is still a lack of an integrated platform with up-to-date information on RNA deregulation and high-throughput data. The Fibrotic Disease-associated RNAome database (FDRdb) (http://www.medsysbio.org/FDRdb) is a manually curated database of fibrotic disease-associated RNAome information and high-throughput datasets. This initial release (i) contains 1947 associations between 912 RNAs and 92 fibrotic diseases in eight species; (ii) collects information on 764 datasets of fibrotic diseases; (iii) provides a user-friendly web interface that allows users to browse, search and download the RNAome information on fibrotic diseases and high-throughput datasets and (iv) provides tools to analyze the expression profiles of fibrotic diseases, including differential expression analysis and pathway enrichment. The FDRdb is a valuable resource for researchers to explore the mechanisms of RNA dysregulation in organ fibrosis. Database URL: http://www.medsysbio.org/FDRdb.