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Abstract There are few analyses comparing complete nephrectomy with resection of the renal parenchyma only (CN) or radical nephrectomy that includes simultaneous resection of the parenchyma, affected perirenal fascia, perirenal fat, and ureter (RN) relative to partial nephrectomy (PN) for patients with nonmetastatic (M0) renal cell carcinoma (RCC) in terms of overall survival (OS). This study aimed to evaluate the effect of different nephrectomy on the OS of M0 RCC and to identify the main beneficiaries of different nephrectomy. The data was collected from the Surveillance, Epidemiology and End Results (SEER) database. Kaplan–Meier plots, and multivariable Cox regression models were used. Propensity score matching (PSM) was performed to reduce the effect of selection bias. A prognostic model for M0 RCC patients after nephrectomy was established using the deep learning framework. Stage I M0 RCC patients who received PN did not have a better prognosis than none surgery in terms of CSS and OS after PSM. Stage I M0 RCC patients who received PN did not have a better prognosis than CN in terms of CSS but had in terms of OS after PSM. Stage I M0 RCC patients who received PN had a better prognosis in terms of CSS and OS after PSM. The test set AUC values for 1/3/5/7/9 year survival prediction of the surgical decision model were 0.844, 0.812, 0.794, 0.79, 0.813. For OS and CSS in M0 RCC patients, PN was superior to CN and RN regardless of grade. But for grade I, PN and none surgery did not show significant differences. In order to further categorize surgical patients and make more precise decisions regarding their treatment, a surgical decision-making model has been established.

Abstract The extracellular matrix (ECM) is a complex, dynamic network of multiple macromolecules that serve as a crucial structural and physical scaffold for neighboring cells. In the tumor microenvironment (TME), ECM proteins play a significant role in mediating cellular communication between cancer-associated fibroblasts (CAFs) and tumor-associated macrophages (TAMs). Revealing the ECM modification of the TME necessitates the intricate signaling cascades that transpire among diverse cell populations and ECM proteins. The advent of single-cell sequencing has enabled the identification and refinement of specific cellular subpopulations, which has substantially enhanced our comprehension of the intricate milieu and given us a high-resolution perspective on the diversity of ECM proteins. However, it is essential to integrate single-cell data and establish a coherent framework. In this regard, we present a comprehensive review of the relationships among ECM, TAMs, and CAFs. This encompasses insights into the ECM proteins released by TAMs and CAFs, signaling integration in the TAM-ECM-CAF axis, and the potential applications and limitations of targeted therapies for CAFs. This review serves as a reliable resource for focused therapeutic strategies while highlighting the crucial role of ECM proteins as intermediates in the TME.

Abstract Background In hepatocellular carcinoma (HCC) treatment, first-line targeted therapy in combination with immune checkpoint inhibitors (ICIs) has improved patient prognosis, but the 5-year survival rate is far from satisfactory. Studies have shown that the extracellular matrix (ECM) is an essential part of the tumour microenvironment (TME) and participates in the progression of malignant tumours. ECM remodelling can enhance matrix stiffness in cirrhosis patients, induce an immunosuppressive microenvironment network, and affect the efficacy of targeted therapies and ICIs for treating HCC. However, the exact mechanism is still unclear. Methods We downloaded data from public databases, selected differentially expressed ECM proteins associated with matrix stiffness, constructed and validated a prognostic model of HCC using Lasso Cox regression, and investigated the roles and mechanism of one of the ECM proteins, dynein light chain LC8-type 1 (DYNLL1), in HCC proliferation, migration, and apoptosis via in vitro experiments. Results In this study, the risk score of the matrix stiffness-related ECM protein model effectively predicted the prognosis of HCC patients. The high- and low-risk subgroups of the model also showed differences in immune cells, immune functions, and drug sensitivity. DYNLL1 promoted HCC cell progression and migration and inhibited HCC cell apoptosis through the Wnt/β-catenin pathway in vitro. Conclusion The expression of matrix stiffness-related ECM proteins could be an independent predictor of HCC prognosis. DYNLL1, an oncogenic gene in HCC, has the potential to be a new target for HCC treatment.

Objective For precise and minimally invasive treatment of ossification of the posterior longitudinal ligament of the cervical spine, the lifting segment is minimized, anterior controllable antedisplacement and fusion (ACAF) was refined and improved. In addition, the development of appropriate surgical procedures for the ossification of each segment was rarely reported. Therefore, this study aimed to compare the efficacy and safety of hybrid anterior controlled antedisplacement fusion (Hybrid ACAF) with laminoplasty for multilevel ossification of the posterior longitudinal ligament (OPLL). Methods Between May 2018 and May 2021, 70 patients with multilevel OPLL were divided into a hybrid ACAF group and a laminoplasty group according to surgical methods. All patients were followed up for at least 1 year. Japanese Orthopaedic Association (JOA) score and recovery rate (JOARR), (VAS, NDI) score and C2–C7 Cobb angle, the sagittal vertical axis of the neck (SVA), and complications (cerebrospinal fluid leakage, C5 paralysis, etc.) were compared between the two groups by t test or non‐parametric test. Results The operation time of hybrid ACAF was longer. C5 paralysis and axial pain were more common in the laminoplasty group, while dysphagia and hoarseness were more common in the hybrid ACAF group. At the last follow‐up, the hybrid ACAF group had better recovery and maintenance of cervical lordosis and sagittal plane balance and a higher JOA score and recovery rate than the laminoplasty group. Conclusions Hybrid ACAF can reduce the number of vertebral bodies and expand the decompression range, which is safe, effective, and tailored to local conditions. Compared with laminoplasty, hybrid ACAF is a precise alternative for patients with OPLL.

Abstract Objective To create a deep‐learning automatic segmentation model for esophageal cancer (EC), metastatic lymph nodes (MLNs) and their adjacent structures using the UperNet Swin network and computed tomography angiography (CTA) images and to improve the effectiveness and precision of EC automatic segmentation and TN stage diagnosis. Methods Attention U‐Net, UperNet Swin, UNet++ and UNet were used to train the EC segmentation model to automatically segment the EC, esophagus, pericardium, aorta and MLN from CTA images of 182 patients with postoperative pathologically proven EC. The Dice similarity coefficient (DSC), sensitivity, and positive predictive value (PPV) were used to assess their segmentation effectiveness. The volume of EC was calculated using the segmentation results, and the outcomes and times of automatic and human segmentation were compared. All statistical analyses were completed using SPSS 25.0 software. Results Among the four EC autosegmentation models, the UperNet Swin had the best autosegmentation results with a DSC of 0.7820 and the highest values of EC sensitivity and PPV. The esophagus, pericardium, aorta and MLN had DSCs of 0.7298, 0.9664, 0.9496 and 0.5091. The DSCs of the UperNet Swin were 0.6164, 0.7842, 0.8190, and 0.7259 for T1‐4 EC. The volume of EC and its adjacent structures between the ground truth and UperNet Swin model were not significantly different. Conclusions The UperNet Swin showed excellent efficiency in autosegmentation and volume measurement of EC, MLN and its adjacent structures in different T stage, which can help to T and N stage diagnose EC and will save clinicians time and energy.

BackgroundThe identification of compound-protein interactions (CPIs) is crucial for drug discovery and understanding mechanisms of action. Accurate CPI prediction can elucidate drug-target-disease interactions, aiding in the discovery of candidate compounds and effective synergistic drugs, particularly from traditional Chinese medicine (TCM). Existing in silico methods face challenges in prediction accuracy and generalization due to compound and target diversity and the lack of largescale interaction datasets and negative datasets for model learning.MethodsTo address these issues, we developed a computational model for CPI prediction by integrating the constructed large-scale bioactivity benchmark dataset with a deep learning (DL) algorithm. To verify the accuracy of our CPI model, we applied it to predict the targets of compounds in TCM. An herb pair of Astragalus membranaceus and Hedyotis diffusaas was used as a model, and the active compounds in this herb pair were collected from various public databases and the literature. The complete targets of these active compounds were predicted by the CPI model, resulting in an expanded target dataset. This dataset was next used for the prediction of synergistic antitumor compound combinations. The predicted multi-compound combinations were subsequently examined through in vitro cellular experiments.ResultsOur CPI model demonstrated superior performance over other machine learning models, achieving an area under the Receiver Operating Characteristic curve (AUROC) of 0.98, an area under the precision-recall curve (AUPR) of 0.98, and an accuracy (ACC) of 93.31% on the test set. The model’s generalization capability and applicability were further confirmed using external databases. Utilizing this model, we predicted the targets of compounds in the herb pair of Astragalus membranaceus and Hedyotis diffusaas, yielding an expanded target dataset. Then, we integrated this expanded target dataset to predict effective drug combinations using our drug synergy prediction model DeepMDS. Experimental assay on breast cancer cell line MDA-MB-231 proved the efficacy of the best predicted multi-compound combinations: Combination I (Epicatechin, Ursolic acid, Quercetin, Aesculetin and Astragaloside IV) exhibited a half-maximal inhibitory concentration (IC50) value of 19.41 μM, and a combination index (CI) value of 0.682; and Combination II (Epicatechin, Ursolic acid, Quercetin, Vanillic acid and Astragaloside IV) displayed a IC50 value of 23.83 μM and a CI value of 0.805. These results validated the ability of our model to make accurate predictions for novel CPI data outside the training dataset and evaluated the reliability of the predictions, showing good applicability potential in drug discovery and in the elucidation of the bioactive compounds in TCM.ConclusionOur CPI prediction model can serve as a useful tool for accurately identifying potential CPI for a wide range of proteins, and is expected to facilitate drug research, repurposing and support the understanding of TCM.

Radiation therapy for cancer treatment brings about a series of radiation injuries to normal tissues. In recent years, the discovery of copper-regulated cell death, cuproptosis, a novel form of programmed cell death, has attracted widespread attention and exploration in various biological functions and pathological mechanisms of copper metabolism and cuproptosis. Understanding its role in the process of radiation injury may open up new avenues and directions for exploration in radiation biology and radiation oncology, thereby improving tumor response and mitigating adverse reactions to radiotherapy. This review provides an overview of copper metabolism, the characteristics of cuproptosis, and their potential regulatory mechanisms in radiation injury.

Abstract BackgroundRecently, the growing demand for pediatric sedation services outside the operating room has imposed a heavy burden on pediatric centers in China. There is an urgent need to develop a novel system for improved sedation services. ObjectiveThis study aimed to develop and implement a computerized system, the Pediatric Sedation Assessment and Management System (PSAMS), to streamline pediatric sedation services at a major children’s hospital in Southwest China. MethodsPSAMS was designed to reflect the actual workflow of pediatric sedation. It consists of 3 main components: server-hosted software; client applications on tablets and computers; and specialized devices like gun-type scanners, desktop label printers, and pulse oximeters. With the participation of a multidisciplinary team, PSAMS was developed and refined during its application in the sedation process. This study analyzed data from the first 2 years after the system’s deployment. Implementation (Results)From January 2020 to December 2021, a total of 127,325 sedations were performed on 85,281 patients using the PSAMS database. Besides basic variables imported from Hospital Information Systems (HIS), the PSAMS database currently contains 33 additional variables that capture comprehensive information from presedation assessment to postprocedural recovery. The recorded data from PSAMS indicates a one-time sedation success rate of 97.1% (50,752/52,282) in 2020 and 97.5% (73,184/75,043) in 2021. The observed adverse events rate was 3.5% (95% CI 3.4%‐3.7%) in 2020 and 2.8% (95% CI 2.7%-2.9%) in 2021. ConclusionsPSAMS streamlined the entire sedation workflow, reduced the burden of data collection, and laid a foundation for future cooperation of multiple pediatric health care centers.

Abstract. Instruction:. Growing pains are the most common cause of musculoskeletal pain in children, affecting both children's and caregivers' well-being. The lack of definitive diagnostic criteria complicates diagnosis and treatment. Objectives:. This study aims to outline the clinical features and identify factors associated with the frequency and intensity of growing pains in children in Chongqing, China. Methods:. A cross-sectional study was conducted in a children's hospital using its Internet hospital follow-up platform. Children initially diagnosed with growing pains between July and September 2022 were enrolled. Sociodemographics, pain locations, duration, frequency, intensity, and potentially related factors were collected. Results:. Eight hundred sixty-three children were enrolled (average age: 8.19 ± 3.24 years; 455 boys [52.72%]). Pain frequency was reported as quarterly (62.11%), monthly (24.80%), biweekly (1.74%), weekly (10.08%), and daily (1.27%). The prevalence of mild, moderate, and severe pain was 26.65%, 55.74%, and 17.61%, respectively. The knee was the most common pain location (63.85%), mostly encountered between 4 pm and 5 pm (20.51%). Multivariate analysis revealed that pain frequency negatively correlated with vitamin supplementation during pregnancy, positively correlated with underweight, bad temper, increased exercise, and cold lower extremities. Pain intensity positively correlated with irritability, increased exercise, and pain sensitivity but negatively correlated with age and vitamin supplementation during lactation. Conclusion:. Growing pains typically occur on a quarterly basis, predominantly affecting the knees during 4 pm to 5 pm. Factors in sociodemographics, maternal aspect, temperament, and exercise levels can influence pain frequency and intensity. Clinicians should consider these aspects when developing comprehensive strategies for pain management.

Abstract Plant‐derived exosomes (PEs) possess an array of therapeutic properties, including antitumor, antiviral, and anti‐inflammatory capabilities. They are also implicated in defensive responses to pathogenic attacks. Spinal cord injuries (SCIs) regeneration represents a global medical challenge, with appropriate research concentration on three pivotal domains: neural regeneration promotion, inflammation inhibition, and innovation and application of regenerative scaffolds. Unfortunately, the utilization of PE in SCI therapy remains unexplored. Herein, we isolated PE from the traditional Chinese medicinal herb, Lycium barbarum L. and discovered their inflammatory inhibition and neuronal differentiation promotion capabilities. Compared with exosomes derived from ectomesenchymal stem cells (EMSCs), PE demonstrated a substantial enhancement in neural differentiation. We encapsulated isoliquiritigenin (ISL)‐loaded plant‐derived exosomes (ISL@PE) from L. barbarum L. within a 3D‐printed bionic scaffold. The intricate construct modulated the inflammatory response following SCI, facilitating the restoration of damaged axons and culminating in ameliorated neurological function. This pioneering investigation proposes a novel potential route for insoluble drug delivery via plant exosomes, as well as SCI repair. The institutional animal care and use committee number is UJS‐IACUC‐2020121602.

Abstract Purpose The aim of this study was to diminish radiation exposure in interventional radiology (IR) imaging while maintaining image quality. This was achieved by decreasing the acquisition frame rate and employing a deep neural network to interpolate the reduced frames. Methods This retrospective study involved the analysis of 1634 IR sequences from 167 pediatric patients (March 2014 to January 2022). The dataset underwent a random split into training and validation subsets (at a 9:1 ratio) for model training and evaluation. Our approach proficiently synthesized absent frames in simulated low-frame-rate sequences by excluding intermediate frames from the validation subset. Accuracy assessments encompassed both objective experiments and subjective evaluations conducted by nine radiologists. Results The deep learning model adeptly interpolated the eliminated frames within IR sequences, demonstrating encouraging peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) results. The average PSNR values for angiographic, subtraction, and fluoroscopic modes were 44.94 dB, 34.84 dB, and 33.82 dB, respectively, while the corresponding SSIM values were 0.9840, 0.9194, and 0.7752. Subjective experiments conducted with experienced interventional radiologists revealed minimal discernible differences between interpolated and authentic sequences. Conclusion Our method, which interpolates low-frame-rate IR sequences, has shown the capability to produce high-quality IR images. Additionally, the model exhibits potential for reducing the frame rate during IR image acquisition, consequently mitigating radiation exposure. Critical relevance statement This study presents a critical advancement in clinical radiology by demonstrating the effectiveness of a deep neural network in reducing radiation exposure during pediatric interventional radiology while maintaining image quality, offering a potential solution to enhance patient safety. Key points • Reducing radiation: cutting IR image to reduce radiation. • Accurate frame interpolation: our model effectively interpolates missing frames. • High visual quality in terms of PSNR and SSIM, making IR procedures safer without sacrificing quality. Graphical Abstract

Abstract Background Hand, foot, and mouth disease (HFMD) is a common infectious disease that poses a serious threat to children all over the world. However, the current prediction models for HFMD still require improvement in accuracy. In this study, we proposed a hybrid model based on autoregressive integrated moving average (ARIMA), ensemble empirical mode decomposition (EEMD) and long short-term memory (LSTM) to predict the trend of HFMD. Methods The data used in this study was sourced from the National Clinical Research Center for Child Health and Disorders, Chongqing, China. The daily reported incidence of HFMD from 1 January 2015 to 27 July 2023 was collected to develop an ARIMA-EEMD-LSTM hybrid model. ARIMA, LSTM, ARIMA-LSTM and EEMD-LSTM models were developed to compare with the proposed hybrid model. Root mean square error (RMSE), mean absolute error (MAE) and coefficient of determination (R2) were adopted to evaluate the performances of the prediction models. Results Overall, ARIMA-EEMD-LSTM model achieved the most accurate prediction for HFMD, with RMSE, MAPE and R2 of 4.37, 2.94 and 0.996, respectively. Performing EEMD on the residual sequence yields 11 intrinsic mode functions. EEMD-LSTM model is the second best, with RMSE, MAPE and R2 of 6.20, 3.98 and 0.996. Conclusion Results showed the advantage of ARIMA-EEMD-LSTM model over the ARIMA model, the LSTM model, the ARIMA-LSTM model and the EEMD-LSTM model. For the prevention and control of epidemics, the proposed hybrid model may provide a more powerful help. Compared with other three models, the two integrated with EEMD method showed significant improvement in predictive capability, offering novel insights for modeling of disease time series.

Background: A COVID-19 outbreak in the rural areas of Shijiazhuang City was attributed to the complex interactions among vaccination, host, and non-pharmaceutical interventions (NPIs). Herein, we investigated the epidemiological characteristics of all reported symptomatic cases by picking Shijiazhuang City, Hebei Province in Northern China as research objective. In addition, we established an age-group mathematical model to perform the optimal fitting and to investigate the dynamical profiles under three scenarios. Methods: All reported symptomatic cases of Shijiazhuang epidemic (January 2-February 3, 2021) were investigated in our study. The cases were classified by gender, age group and location, the distributions were analyzed by epidemiological characteristics. Furthermore, the reported data from Health Commission of Hebei Province was also analyzed by using an age-group mathematical model by two phases and three scenarios. Results: Shijiazhuang epidemic caused by SARS-CoV-2 wild strain was recorded with the peak 84 cases out of 868 reported symptomatic cases on January 11, 2021, which was implemented with strong NPIs by local government and referred as baseline situation in this study. The research results showed that R0 under baseline situation ranged from 4.47 to 7.72, and Rt of Gaocheng Distinct took 3.72 with 95% confidence interval from 3.23 to 4.35 on January 9, the declining tendencies of Rt under baseline situation were kept till February 3, the value of Rt reached below 1 on January 19 and remained low value up to February 3 for Gaocheng District and Shijiazhuang City during Shijiazhuang epidemic. This indicated Shijiazhuang epidemic was under control on January 19. However, if the strong NPIs were kept, but remote isolation operated on January 11 was not implemented as of February 9, then the scale of Shijiazhuang epidemic reached 9,482 cases from age group who were 60 years old and over out of 31,017 symptomatic cases. The investigation also revealed that Shijiazhuang epidemic reached 132,648 symptomatic cases for age group who were 60 years old and over (short for G2) under risk-based strategies (Scenario A), 58,048 symptomatic cases for G2 under late quarantine strategies (Scenario B) and 207,124 symptomatic cases for G2 under late quarantine double risk strategies (Scenario C), and that the corresponding transmission tendencies of Rt for three scenarios were consistently controlled on Jan 29, 2021. Compared with baseline situation, the dates for controlling Rt below 1 under three scenarios were delayed 10 days. Conclusions: Shijiazhuang epidemic was the first COVID-19 outbreak in the rural areas in Hebei Province of Northern China. The targeted interventions adopted in early 2021 were effective to halt the transmission due to the implementation of a strict and village-wide closure. However we found that age group profile and NPIs played critical rules to successfully contain Shijiazhuang epidemic, which should be considered by public health policies in rural areas of mainland China during the dynamic zero-COVID policy.

This study selected two sweet potato varieties as research subjects and conducted a field experiment using a two-factor design with two potassium (K) levels (K0 and K1) and five nitrogen (N) levels (N0–N4). The physiological changes in sweet potato leaves under different N and K treatments were measured, and nutrients such as the soluble sugar, protein, and starch content of sweet potato roots were analyzed. The results indicate that the activity of glutamine synthetase (GS) and the soluble protein content in sweet potato leaves increase first and then decrease with increasing N application, while K application can significantly increase the activity of GS and the soluble protein content. The N metabolic capacity of leaves is strongest when the fertilizer ratio is K1N2. The SPAD value of sweet potato leaves increases with increasing N application. The net photosynthetic rate, stomatal conductance, and intercellular CO2 concentration first increase and then decrease with increasing N application. K fertilizer has a significant effect on these parameters. As the N application rate increases, the starch and protein content in the tubers increase, while the soluble sugar content decreases. However, the number of tubers per plant, fresh weight of the tubers, and dry weight of the tubers increase initially and then decrease, while the vine length continuously increases. The application of K fertilizer can significantly increase the number of tubers per plant and stem thickness of sweet potato. In conclusion, the appropriate N–K combined application can promote N metabolism, enhance the photosynthetic capacity of sweet potato, increase yield, and improve quality.

Abstract Asthma control in children is often challenging. This retrospective cohort study aimed to investigate the potential contribution of small airway function in predicting asthma control within a 2‐ to 3‐month period following the initial diagnosis in preschool children with asthma. A total of 219 preschool children diagnosed with asthma were enrolled, and their follow‐up was conducted by pediatric pulmonary physicians. Clinical history and lung function results were collected for analysis. To identify risk factors associated with poor asthma control, a multivariable regression model was employed. Sixty‐nine of the patients (31.5%) exhibited poor asthma control. Poor adherence to therapy (14.5% vs. 6.0%, p = 0.038) and the presence of severe airway hyperresponsiveness (AHR) (20.6% vs. 1.6%, p

BackgroundTumor lysis syndrome (TLS) often occurs early after induction chemotherapy for acute lymphoblastic leukemia (ALL) and can rapidly progress. This study aimed to construct a machine learning model to predict the risk of TLS using clinical indicators at the time of ALL diagnosis.MethodsThis observational cohort study was conducted at the National Clinical Research Center for Child Health and Disease. Data were collected from pediatric ALL patients diagnosed between December 2008 and December 2021. Four machine learning models were constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) to select key clinical indicators for model construction.ResultsThe study included 2,243 pediatric ALL patients, and the occurrence of TLS was 8.87%. A total of 33 indicators with missing values ≤30% were collected, and 12 risk factors were selected through LASSO regression analysis. The CatBoost model with the best performance after feature screening was selected to predict the TLS of ALL patients. The CatBoost model had an AUC of 0.832 and an accuracy of 0.758. The risk factors most associated with TLS were the absence of potassium, phosphorus, aspartate transaminase (AST), white blood cell count (WBC), and urea levels.ConclusionWe developed the first TLS prediction model for pediatric ALL to assist clinicians in risk stratification at diagnosis and in developing personalized treatment protocols. This study is registered on the China Clinical Trials Registry platform (ChiCTR2200060616).Clinical trial registrationhttps://www.chictr.org.cn/, identifier ChiCTR2200060616.

Abstract Background The use of regorafenib in the treatment of hepatocellular carcinoma (HCC) is widespread. Albumin-Bilirubin (ALBI) has been shown to be a potential prognostic marker for regorafenib treatment, but its prognostic value remains controversial. Therefore, we conducted a meta-analysis to investigate the value of the baseline ALBI grade in predicting the efficacy and survival outcomes of HCC patients after regorafenib treatment. Methods PubMed, Embase, Cochrane library, Web of Science, CNKI, Wan Fang Data, and Vip Database were searched from January 2010 to October 2022. Studies treating HCC patients with regorafenib and with ALBI as a categorical variable, overall survival (OS) and progression-free survival (PFS) as outcome indicators were included. After applying Newcastle–Ottawa Scale (NOS) to evaluate the quality of the included studies, Review Manager 5.4 was used to statistically analyze. Chi-square Q test and I2 statistics were used to detect heterogeneity. Funnel plot asymmetry, Egger’s and Begg’s test were used to evaluate publication bias. Results A total of 12 studies, comprising 1,918 patients, were included in the meta-analysis. The included studies were all evaluated as high quality. Compared to the high-grade baseline ALBI group, patients in the low-grade group had a longer survival time after receiving regorafenib and also more suitable for regorafenib treatment [odds ratio (OR) = 6.50, 95% confidence interval (CI): 2.22–18.96, P

Abstract Background There is limited longitudinal evidence on the hypertensive effects of long-term exposure to ambient O3. We investigated the association between long-term O3 exposure at workplace and incident hypertension, diastolic blood pressure (DBP), systolic blood pressure (SBP), pulse pressure (PP), and mean arterial pressure (MAP) in general working adults. Methods We conducted a cohort study by recruiting over 30,000 medical examination attendees through multistage stratified cluster sampling. Participants completed a standard questionnaire and comprehensive medical examination. Three-year ambient O3 concentrations at each employed participant’s workplace were estimated using a two-stage machine learning model. Mixed-effects Cox proportional hazards models and linear mixed-effects models were used to examine the effect of O3 concentrations on incident hypertension and blood pressure parameters, respectively. Generalized additive mixed models were used to explore non-linear concentration-response relationships. Results A total of 16,630 hypertension-free working participants at baseline finished the follow-up. The mean (SD) O3 exposure was 45.26 (2.70) ppb. The cumulative incidence of hypertension was 7.11 (95% CI: 6.76, 7.47) per 100 person-years. Long-term O3 exposure was independently, positively and non-linearly associated with incident hypertension (Hazard ratios (95% CI) for Q2, Q3, and Q4 were 1.77 (1.34, 2.36), 2.06 (1.42, 3.00) and 3.43 (2.46, 4.79), respectively, as compared with the first quartile (Q1)), DBP (β (95% CI) was 0.65 (0.01, 1.30) for Q2, as compared to Q1), SBP (β (95% CI) was 2.88 (2.00, 3.77), 2.49 (1.36, 3.61) and 2.61 (1.64, 3.58) for Q2, Q3, and Q4, respectively), PP (β (95% CI) was 2.12 (1.36, 2.87), 2.03 (1.18, 2.87) and 2.14 (1.38, 2.90) for Q2, Q3, and Q4, respectively), and MAP (β (95% CI) was 1.39 (0.76, 2.02), 1.04 (0.24, 1.84) and 1.12 (0.43, 1.82) for Q2, Q3, and Q4, respectively). The associations were robust across sex, age, BMI, and when considering PM2.5 and NO2. Conclusions To our knowledge, this is the first cohort study in the general population that demonstrates the non-linear hypertensive effects of long-term O3 exposure. The findings are particularly relevant for policymakers and researchers involved in ambient pollution and public health, supporting the integration of reduction of ambient O3 into public health interventions.

Abstract Hepatocellular carcinoma (HCC) is one of the deadliest malignancies worldwide, with late detection, ineffective treatment and poor overall survival. Immunotherapy, including immune checkpoint inhibitor (ICI) therapy, holds great potential for treatment of HCC. Although some patients respond well to ICIs, many fail to obtain a significant benefit. It is therefore of great interest to find appropriate markers to stratify patient responses to immunotherapy and to explore suitable targets for modulating the TME and immune cell infiltration. ATP6V1F encodes a constituent of vacuolar ATPase (V-ATPase). V-ATPase-mediated acidification of organelles is required for intracellular processes such as zymogen activation, receptor-mediated endocytosis, protein sorting and synaptic vesicle proton gradient generation. In this study, we confirmed for the first time that ATP6V1F is overexpressed in HCC and related to poor prognosis in these patients. We identified that overexpression of ATP6V1F is associated with infiltration of some immune cells and expression of several immune checkpoints. Furthermore, we explored the possible mechanisms of action of ATP6V1F. Finally, we conducted in vitro experiments, including wound healing, Transwell invasion, and apoptosis assays, to verify that ATP6V1F promotes development of HCC by promoting migration and invasion and inhibiting apoptosis of HCC cells. Our findings will contribute to providing precise immunotherapy to patients with HCC.

Abstract Background Small airways are the major sites of inflammation and airway remodeling in all severities of asthma patients. However, whether small airway function parameters could reflect the airway dysfunction feature in preschool asthmatic children remain unclear. We aim to investigate the role of small airway function parameters in evaluating airway dysfunction, airflow limitation and airway hyperresponsiveness (AHR). Methods Eight hundred and fifty-one preschool children diagnosed with asthma were enrolled retrospectively to investigate the characteristics of small airway function parameters. Curve estimation analysis was applied to clarify the correlation between small and large airway dysfunction. Spearman’s correlation and receiver-operating characteristic (ROC) curves were employed to evaluate the relationship between small airway dysfunction (SAD) and AHR. Results The prevalence of SAD was 19.5% (166 of 851) in this cross-sectional cohort study. Small airway function parameters (FEF25-75%, FEF50%, FEF75%) showed strong correlations with FEV1% (r = 0.670, 0.658, 0.609, p

Abstract Background Polygalacturonase (PG), a crucial enzyme involved in pectin degradation, is associated with various plants’ developmental and physiological processes such as seed germination, fruit ripening, fruit softening and plant organ abscission. However, the members of PG gene family in sweetpotato (Ipomoea batatas) have not been extensively identified. Results In this study, there were 103 PG genes identified in sweetpotato genome, which were phylogenetically clustered into divergent six clades. The gene structure characteristics of each clade were basically conserved. Subsequently, we renamed these PGs according to their locations of the chromosomes. The investigation of collinearity between the PGs in sweetpotato and other four species, contained Arabidopsis thaliana, Solanum lycopersicum, Malus domestica and Ziziphus jujuba, revealed important clues about the potential evolution of the PG family in sweetpotato. Gene duplication analysis showed that IbPGs with collinearity relationships were all derived from segmental duplications, and these genes were under purifying selection. In addition, each promoter region of IbPG proteins contained cis-acting elements related to plant growth and development processes, environmental stress responses and hormone responses. Furthermore, the 103 IbPGs were differentially expressed in various tissues (leaf, stem, proximal end, distal end, root body, root stalk, initiative storage root and fibrous root) and under different abiotic stresses (salt, drought, cold, SA, MeJa and ABA treatment). IbPG038 and IbPG039 were down-regulated with salt, SA and MeJa treatment. According to the further investigation, we found that IbPG006, IbPG034 and IbPG099 had different patterns under the drought and salt stress in fibrous root of sweetpotato, which provided insights into functional differences among these genes. Conclusion A total of 103 IbPGs were identified and classified into six clades from sweetpotato genome. The results of RNA-Seq and qRT-PCR suggested that IbPG006, IbPG034 and IbPG099 might play a significant role in tissue specificity as well as drought and salt stress responses, which showed valuable information for further functional characterization and application of the IbPGs.

Abstract With the advance of artificial intelligence technology, large language models such as ChatGPT are drawing substantial interest in the healthcare field. A growing body of research has evaluated ChatGPT's performance in various medical departments, yet its potential in pediatrics remains under‐studied. In this study, we presented ChatGPT with a total of 4160 clinical consultation questions in both English and Chinese, covering 104 pediatric conditions, and repeated each question independently 10 times to assess the accuracy of its responses in pediatric disease treatment recommendations. ChatGPT achieved an overall accuracy of 82.2% (95% CI: 81.0%–83.4%), with superior performance in addressing common diseases (84.4%, 95% CI: 83.2%–85.7%), offering general treatment advice (83.5%, 95% CI: 81.9%–85.1%), and responding in English (93.0%, 95% CI: 91.9%–94.1%). However, it was prone to errors in disease definitions, medications, and surgical treatment. In conclusion, while ChatGPT shows promise in pediatric treatment recommendations with notable accuracy, cautious optimism is warranted regarding the potential application of large language models in enhancing patient care.

The prediction system EpiSIX was used to study the COVID-19 epidemic in mainland China between November 2022 and January 2023, based on reported data from December 9, 2022, to January 30, 2023, released by The Chinese Center for Disease Control and Prevention on February 1, 2023. Three kinds of reported data were used for model fitting: the daily numbers of positive nucleic acid tests and deaths, and the daily number of hospital beds taken by COVID-19 patients. It was estimated that the overall infection rate was 87.54% and the overall case fatality rate was 0.078%–0.116% (median 0.100%). Assuming that a new COVID-19 epidemic outbreak would start in March or April of 2023, induced by a slightly more infectious mutant strain, we predicted a possible large rebound between September and October 2023, with a peak demand of between 800,000 and 900,000 inpatient beds. If no such new outbreak was induced by other variants, then the current COVID-19 epidemic course in mainland China would remain under control until the end of 2023. However, it is suggested that the necessary medical resources be prepared to manage possible COVID-19 epidemic emergencies in the near future, especially for the period between September and October 2023.

Background: Hemophagocytic Lymphohistiocytosis (HLH) is a rare and life-threatening disease in children, with a high early mortality rate. This study aimed to construct machine learning model to predict the risk of early death using clinical indicators at the time of HLH diagnosis. Methods: This observational cohort study was conducted at the National Clinical Research Center for Child Health and Disease. Data was collected from pediatric HLH patients diagnosed by the HLH-2004 protocol between January 2006 and December 2022. Six machine learning models were constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) to select key clinical indicators for model construction. Results: The study included 587 pediatric HLH patients, and the early mortality rate was 28.45 %. The logistic and XGBoost model with the best performance after feature screening were selected to predict early death of HLH patients. The logistic model had an AUC of 0.915 and an accuracy of 0.863, while the XGBoost model had an AUC of 0.889 and an accuracy of 0.829. The risk factors most associated with early death were the absence of immunochemotherapy, decreased TC levels, increased BUN and total bilirubin, and prolonged TT. We developed an online calculator tool for predicting the probability of early death in children with HLH. Conclusions: We developed the first web-based early mortality prediction tool for pediatric HLH to assist clinicians in risk stratification at diagnosis and in developing personalized treatment protocols. This study is registered on the China Clinical Trials Registry platform (ChiCTR2200061315).

The World Health Organization (WHO) declared monkeypox as a public health emergency of international concern (PHEIC) on July 23, 2022, their highest level of alert. This raised concerns about the management of the global monkeypox outbreak, as well as the scientific analysis and accurate prediction of the future course of the epidemic. This study used EpiSIX (an analysis and prediction system for epidemics based on a general SEIR model) to analyze the monkeypox epidemic and to forecast the major tendencies based on data from the USA CDC (https://www.cdc.gov) and the WHO (https://www.who.int/health-topics/monkeypox). The global outbreak of monkeypox started in the UK on May 2, 2022, which marked the beginning of an epidemic wave. As of October 28, 2022, the cumulative number of reported cases worldwide was 77,115, with 36 deaths. EpiSIX simulations predict that the global monkeypox epidemic will enter a low epidemic status on March 1, 2023 with the cumulative number of confirmed cases ranging from 85,000 to 124,000, and the total number of deaths ranging from 60 to 87. Our analysis revealed that the basic reproduction number (R0) of monkeypox virus (MPXV) is near to 3.1 and the percentage of asymptomatic individuals is 13.1 %–14.5 %, both of which are similar to the data for SARS. The vaccination efficiency against susceptibility (VEs) of individuals who have had monkeypox is ∼ 79 %, and the vaccination efficiency against infectiousness (VEi) of individuals who have had monkeypox is ∼ 76 %–82 %. The mean incubation period for monkeypox is 8 days. In total, 94.7 % of infected individuals develop symptoms within 20 days and recover within 2 weeks after the confirmation of symptoms. Simulation results using EpiSIX showed that ring vaccination was remarkably effective against monkeypox. Our findings confirmed that a 20-day isolation for close contacts is necessary.

Objective To evaluate the clinical value of diabetes mellitus for diagnosis and postoperative prognosis in patients with cervical spondylotic myelopathy undergoing anterior decompression and fusion. Methods A total of 84 Patients (50 males and 34 females) who underwent anterior decompression and fusion were reviewed in this single‐center retrospective study. The patients were divided into two groups (44 patients in the diabetes mellitus group and 40 in the non‐diabetic group). Clinical manifestations were evaluated, including characteristics baseline, clinical tests, MRI information, clinical scores, and complications. The predictive effect of diabetes mellitus on clinical scores were assessed via the receiver operating characteristic curve. The correlation between the severity of diabetes mellitus and neurological function recovery was estimated using the Pearson correlation coefficient. Results Patients with diabetes mellitus exhibited a higher ratio of hyperintensity of the spinal cord (P 0.05). Conclusion This present study revealed that the neurological impairment caused by diabetes mellitus in patients undergoing anterior decompression and fusion does not only affect postoperative functional recovery but also interferes with the preoperative clinical manifestations, especially the sensory function in the upper and lower limbs.

Scientific and reasonable application of potassium fertilizer is an important agronomic measure to achieve high yield and high quality of sweetpotato, and it is of great significance to determine the appropriate amount of potassium fertilizer in the field. For this we constructing a model of the critical K dilution curve (CKDC) of sweetpotato under different N levels to determine crop nutritional statuses. In this study, a 3-year field experiment was conducted in Zhejiang Province in China, using two nitrogen levels (N0: 0 kg ha−1 and N1: 120 kg ha−1) and five K fertilization rates (K0: 0, K1: 75, K2: 150, K3: 225, K4: 300 kg ha−1) for two sweetpotato cultivars of ‘Shang 19’ and ‘Yan 25’. Plant dry matter first increased and then decreased and the K concentration increased continuously with an increase in K application rate. The required amount of K fertilizer to achieve maximum sweetpotato yield under high N conditions was greater than that under low nitrogen conditions. A new CKDC based on dry matter and K concentration was created to assess K nutrition in sweetpotato. At two N levels, CKDC was expressed by the negative power function equation, aboveground: Kc(N0)=5.30W-0.463, R2 = 0.79, and Kc(N1)=4.23W-0.298, R2 = 0.78, under-ground: Kc(N0)=1.38W-0.125, R2 = 0.81, and Kc(N1)=1.32W-0.132, R2 = 0.72;whole-plant: Kc(N0)=4.31W-0.421, R2 = 0.80; Kc(N1)=3.89W-0.415, R2 = 0.79. There is no significantly different for CKDC of whole-plant and underground between N0 and N1 levels, while there is significantly different for CKDC of aboveground between N0 and N1 levels. N fertilizer can strengthen the dilution effect of K concentration, and its effect on the aboveground is greater than that on the underground and whole-plant. Then, potassium nutrition indexes were constructed to identify K nutrition status and could be used as a reliable indicator for K nutrition diagnosis of sweetpotato. The results provide a theoretical basis to improve K fertilization management and sustainability of sweetpotato.

The quality of fresh-cut produce, particularly sweet potatoes, is crucial for their value. Licorice extract is an optional additive in fresh-cut sweet potatoes. This study examined the impact of three licorice extracts (licorice acid, LA; licorice flavonoids, LF; and licorice polysaccharides, LP) on the quality of fresh-cut sweet potato slices (FCSPSs) for one week of storage. After one week of storage, the extracts showed varying effects on FCSPSs. LA and LF treatments reduced the area proportion of browning (APB), while LP treatments increased APB and decreased L* values. Antioxidant experiments revealed that LP treatments increased PPO and POD activity while reducing SOD activity. The concentrations of the three licorice extracts showed a strong negative correlation with SOD activity. In conclusion, LP harmed the appearance and antioxidant qualities of FCSPSs. LA and LF may be suitable additive components for FCSPSs, and 30 mg/mL LA and LF treatments were found to maintain the appearance and texture quality of FCSPSs during storage. Therefore, careful consideration should be given when using LP as a food additive for FCSPSs.

Heat treatment is a widely applied technique in the preservation of fruits and vegetables, effectively addressing issues such as disease management, rot prevention, and browning. In this study, we investigated the impact of heat treatment at 35 °C for 24 h on the quality characteristics and disease resistance of two sweet potato varieties, P32/P (Ipomoea batatas (L.) Lam. cv ‘Pushu13’) and Xinxiang (Ipomoea batatas (L.) Lam. cv ‘Xinxiang’). The growth in vitro and reproduction of Rhizopus stolonifer were significantly inhibited at 35 °C. However, it resumed when returned to suitable growth conditions. The heat treatment (at 35 °C for 24 h) was found to mitigate nutrient loss during storage while enhancing the structural characteristics and free radical scavenging capacity of sweet potato. Additionally, it led to increased enzyme activities for APX, PPO, and POD, alongside decreased activities for Cx and PG, thereby enhancing the disease resistance of sweet potato against soft rot. As a result, the heat treatment provided a theoretical basis for the prevention of sweet potato soft rot and had guiding significance for improving the resistance against sweet potato soft rot.

To discuss the possibility of the non-destructive prediction of the total colonies of Porphyra yezoensis，this research explored a non-destructive method that using near infrared spectral imaging to predict the total colonies of Porphyra yezoensis. Porphyra yezoensis samples were measured the total colonies first, and then collected the original spectral information and total colonies of samples. Standard normal variable transformation (SNV), multiple scattering correction (MSC) and second order derivative were used to preprocess spectral data. After selecting the best pretreatment method in this study, the prediction models of total number of bacteria were established based on spectral information including mixed logistic regression (MLR), support vector regression (SVR), artificial neuro network (ANN) and convolutional neural networks (CNN). The results of the investigation showed that the second derivative method combined with standard normal variable transformation was the relative best pretreatment method. And the relative best prediction model was the CNN model which was based on the full-wave band, which the r value was 0.940. According to these results, the convolutional neural networks (CNN) could be used to predict the total number of colonies of Porphyra yezoensis.

The mechanism of cold-activated TRPM8 channel activation remains unclear. Here, authors have determined structures of mouse TRPM8 in apo or ligand-bound states, providing insights into the activation of TRPM8 structures in different states.

Abstract Tubulin alpha-1c chain (TUBA1C), a subtype of α-tubulin, has been shown to be involved in cell proliferation and cell cycle progression in several cancers and to influence cancer development and prognosis. However, a pancancer analysis of TUBA1C to reveal its immunological and prognostic roles has not been performed. In this study, we first downloaded raw data on TUBA1C expression in cancers from The Cancer Genome Atlas (TCGA) database and multiple other databases and analysed these data with R software to investigate the prognostic and immunological value of TUBA1C in cancers. Immunohistochemical analysis was performed in gliomas to further validate our findings. Overall, TUBA1C was overexpressed in most cancers, and overexpression of TUBA1C was linked to poor prognosis and higher tumour grade in patients. In addition, TUBA1C expression was associated with tumour mutation burden (TMB), microsatellite instability (MSI), the tumour microenvironment (TME) and the infiltration of immune cells. TUBA1C was also coexpressed with most immune-related genes and influenced immune-related pathways. Immunohistochemical analysis showed that TUBA1C expression was highest in glioblastoma (GBM) tissues, second highest in low-grade glioma (LGG) tissues and lowest in normal tissues. Our study indicated that TUBA1C might be a biomarker for predicting the immune status and prognosis of cancers, offering new ideas for cancer treatment.

Browning is one of the main phenomena limiting the production of fresh-cut sweetpotatoes. This study investigated the anti-browning effect of citrus peel extracts and the key components and modes of action associated with browning in fresh-cut sweetpotatoes. Five different concentrations of citrus peel extract (1, 1.5, 2, 2.5 and 3 g/L) were selected to ensure storage quality; and the physical and chemical properties of fresh-cut sweetpotato slices were analysed. A concentration of 2 g/L of citrus peel extract significantly inhibited the browning of fresh-cut sweetpotatoes. The results showed that the browning index and textural characteristics of fresh-cut sweetpotatoes improved significantly after treatment with citrus peel extract; all the citrus peel extract solutions inhibited browning to some extent compared to the control. In addition; LC-IMS-QTOFMS analysis revealed a total of 1366 components in citrus peel extract; the evaluation of citrus peel extract monomeric components that prevent browning in fresh-cut sweetpotato indicated that the components with better anti-browning effects were citrulloside, hesperidin, sage secondary glycosides, isorhamnetin and quercetin. The molecular docking results suggest that citrullosides play a key role in the browning of fresh-cut sweetpotatoes. In this study, the optimum amount of citrus peel extract concentration was found to be 2 g/L.

BackgroundHemophagocytic lymphohistiocytosis (HLH) is a rapidly progressive and potentially life-threatening disorder. Identifying risk factors and timely adjustment of the given treatment regimens is critical to reducing the early mortality in HLH patients. Hypocholesterolemia has been reported to be associated with poor prognosis in a variety of critical illnesses. However, serum cholesterol is rarely studied in HLH patients, and its prognostic value is unclear.MethodsWe conducted a retrospective cohort study in National Clinical Research Center for Child Health and Disorders (Chongqing), identifying pediatric HLH patients (including genetically confirmed pHLH and not genetically confirmed pHLH) diagnosed with the HLH-2004 protocol and treated with immunochemotherapy between January 2008 and December 2020. The patients' blood lipid levels at initial diagnosis of HLH, including triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), were reviewed based on electronic medical records. Both Cox and logistic regression models were used to estimate the effects of blood lipid indicators on early death (within 30 days after diagnosis).ResultsA total of 353 patients were enrolled in the study, with a median age at diagnosis of 45 months. The observed 30-day mortality rate was 19.05% (64/336, 17 were lost to follow-up) and Kaplan-Meier-estimated 3-year survival rate was 61.67% (95% CI, 56.27%–67.59%). DNA-targeted sequencing of HLH-related genes was performed in 173 (49.0%, 173/353) patients (not all patients with suspected pHLH underwent genetic testing), and 29 patients were diagnosed with genetically confirmed pHLH. Lipid panel was performed in 349 patients: 91.98% (321/349) had TG ≥ 1.80 mmol/L, 62.75%(219/349) had TG ≥ 3.00 mmol/L, 92.84% (324/349) had HDL-C ≤ 1.04 mmol/L, 58.74% (205/349) had LDL-C ≤ 1.30 mmol/L and 24.64% (86/349) had TC ≤ 3.11 mmol/L. TC ≤ 3.11 mmol/L and BUN ≥ 7.14 mmol/L were the independent risk factors for 30-day mortality [HR(95%CI): 2.85(1.46, 5.57) and 2.90(1.48, 5.68), respectively]. The presence of one of these risk factors increased the 30-day mortality rate by 6-fold [HR = 6.24, 95%CI: (3.18, 12.22)] and the presence of two risk factors by nearly 10-fold [HR = 9.98, 95%CI: (4.23, 23.56)] compared with the patients with no risk factors.ConclusionSevere derangement of lipoproteins is common in children with HLH, and decreased TC is an independent risk factor for early death. Hypocholesterolemia should be included as a biomarker during the diagnosis and management of HLH patients.

Abstract Background Anti‐silencing function 1 (ASF1) is a conserved histone H3–H4 chaperone protein. ASF1B, a paralog of ASF1, acts by promoting cell proliferation and influencing cell cycle progression. Although there is some evidence demonstrating that ASF1B plays a key role in the development, progression, and prognosis of certain cancers, there are no pan‐cancer analyses of ASF1B. Methods We used a range of bioinformatics approaches to investigate the predictive role of ASF1B, including its correlation with prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), tumor microenvironment (TME), and immune cell infiltration, in diverse cancer types. Results We found that ASF1B was highly expressed in 22 cancers and was negatively correlated with the prognosis of multiple major cancer types. Furthermore, ASF1B expression was correlated with TMB in 21 cancers and with MSI in 7 cancers. We found that ASF1B was coexpressed with genes encoding immune activators, immune suppressors, major histocompatibility complexes, chemokines, and chemokine receptors. We further found that the role of ASF1B in the infiltration of different types of immune cells varied across tumor types. ASF1B may potentially affect several key immune‐related pathways, such as those involved in antigen processing and presentation, natural killer cell‐mediated cytotoxicity, and autoimmune thyroid disease. Conclusions Our findings show that ASF1B may serve as a prognostic marker and potential immunotherapeutic target for several malignancies due to its role in tumorigenesis and immune infiltration.

Abstract Background Neovasculogenesis is characteristic of herniated lumbar discs, in which extruded nucleus pulposus is prone to heme iron-induced cytotoxicity (increased oxidative stress causing ferroptosis). However, recent analyses of neovascularization are very complicated, and the mechanism of action is rarely reported. Methods Matrix-assisted laser desorption/ionization–time-of-flight mass spectrometry (MALDI-TOF MS) was performed to analyze human herniated and nonherniated nucleus pulposus. Then, the clinical relevance of the MALDI-TOF MS results and Pfirrmann classification of the degenerative nucleus pulposus were analyzed. To explore the mechanism, the heme-induced ferroptosis effect was evaluated at both the tissue and cell levels using high-resolution MALDI-TOF MS and molecular biology methods. Results The spectra revealed that hemoglobin (Hb) and heme signals were greatly increased, thus serving as predictors of vasculogenesis in herniated nucleus pulposus. The clinical relevance analysis demonstrated that the intensity of Hb and heme peaks was closely related to the Pfirrmann classification of degenerative nucleus pulposus. Mechanistically, increased heme catabolism and downregulation of glutathione peroxidase 4 (GPX4) levels were detected in herniated nucleus pulposus, reflecting iron-dependent cell death or ferroptosis. Iron levels was also increased in herniated nucleus pulposus compared with that in nonherniated nucleus pulposus. Furthermore, accuracy mass measurements confirmed that the levels of ferroptosis-related metabolites, such as glutathione, arachidonic acid (AA), sphinganine, polyunsaturated fatty acid (PUFA), and tricarboxylic acid (TCA) cycle metabolites, were significantly different between herniated and nonherniated tissues, indicating that the interior of the herniated tissues is a pro-oxidant environment. Moreover, heme-induced ferroptosis was verified in human nucleus pulposus cells (HNPCs), and the underlying mechanism might be associated with the Notch pathway. Conclusions Neovascularization in herniated nucleus pulposus may expose tissues to high levels of heme, which can induce cytotoxicity and ferroptosis within tissues and accelerate the progressive degeneration of herniated nucleus pulposus. This study is beneficial for understanding the pathological mechanism of herniated nucleus pulposus and facilitating the development of nonoperative interventions for treating lumbar disc herniation (LDH).

ObjectivePrimary warm-antibody autoimmune hemolytic anemia (w-AIHA) is prone to recurrence in children. In this study, we aimed to identify risk indicators for the early recurrence of primary w-AIHA and construct an effective recurrence risk assessment model.MethodsThis was a retrospective cohort study. The clinical data of patients hospitalized with primary w-AIHA in the Department of Hematology and Oncology, Children's Hospital of Chongqing Medical University, between 1 January 2018 and 30 September 2021, were collected at the initial diagnosis. Univariate and multivariate logistic regression analyses were used to determine risk indicators for the early recurrence of primary w-AIHA in children, and ROC curve and Kaplan–Meier survival analyses were used for verification. Finally, a risk assessment model for early recurrence in children with primary w-AIHA was constructed using Cox regression and visualized using a nomogram. The model was also verified internally and externally.ResultsThis study included 62 children with primary w-AIHA. Of which, 18 experienced recurrence 1 year after the initial diagnosis. The univariate and multivariate logistic regression analyses showed that type O blood and the reticulocyte count (Ret) were risk indicators for the early recurrence of pediatric primary w-AIHA (P = 0.009, 0.047, respectively). The mean corpuscular hemoglobin concentration (MCHC) is a protective factor (P = 0.040). According to the ROC curve and Kaplan–Meier survival analyses, children with primary w-AIHA whose blood type was O or had an MCHC of

Early life is a “critical window” for gut microbiota development, antibiotic use during this period exerts a profound effect on gut microbial dysbiosis and asthma. In clinical practice, antibiotics are usually used in patients with bacterial infections, we previously showed that neonatal S. pneumoniae pneumonia promoted adult-onset asthma in mice model, while it remains unclear whether neonatal S. pneumoniae infection have long-term effects on gut microbiota. Neonatal BALB/c mice were inoculated with 5*106 CFU D39 to establish non-lethal S. pneumoniae pneumonia model. At 2, 3, 8 weeks of age, feces in the cecum were prepared for 16S rRNA sequencing, lungs were collected for histopathologic and lung function analysis. S. pneumoniae-infected neonatal mice exhibited histopathologic lesions in their lungs and increased airway hyperresponsiveness, obvious alterations in alpha and beta diversities in the entire gut microbiota, and changes of the community structure during the breastfeeding period, infancy, and adulthood. Furthermore, gut microbial composition was modified after neonatal S. pneumoniae infection, with a decreased relative abundance of Lactobacillus in the breastfeeding period and infancy; in adulthood, the relative abundance of Allobaculum diminished while that of Proteobacteria was augmented. Neonatal S. pneumoniae infection induced a long-term alteration in microbial community composition.

Background: The impacts of long-term high exposure to PM2.5 in workplace on glucose metabolism in asymptomatic working adults (AWAs) have rarely been explored. Objectives: To assess the relationship between long-term exposure to workplace PM2.5 and glucose metabolism in asymptomatic general working adults in heavily polluted regions. Methods: We used the baseline data of the asymptomatic working participants from the Beijing-Tianjin-Hebei Medical Examination Cohort, which recruited adults undergoing medical examinations. A machine learning-based spatial–temporal model was used to estimate daily average PM2.5 concentrations in the participants’ workplaces. We assessed the association of long-term PM2.5 concentrations (three years prior to the interview) and fasting plasma glucose (FPG) using generalized linear mixed-effects models (GLMM) with inclusion of potential confounders. Stratified analyses by sex, age, BMI and smoking status, and two pollutant models were further performed. Results: A total of 37,619 individuals were interviewed and 28,865 were included in the analyses. The mean FPG was 5.20 (0.96) mmol/L, and the estimated three-year average concentration of PM2.5 exposure was 69.51 (6.92) μg/m3. We detected a significant association of long-term exposure to workplace PM2.5 and FPG, a 10 µg/m3 increase in the long-term workplace PM2.5 exposure was associated with 0.075 (95%CI: 0.050–0.100) mmol/L elevated FPG and 25% (OR = 1.25, 95%CI: 1.05–1.50) elevated odds of abnormal fasting glucose metabolism with control of the potential confounding. The detected association between workplace PM2.5 and FPG metabolism remained significant in males, individuals aged > 44 years, overweight and/or obese people, both smokers and non-smokers, and when NO2, SO2, O3, and CO were included in the model. Conclusions: Long-term exposure to workplace PM2.5 was associated with elevated FPG and/or odds of abnormal glucose metabolism among AWAs. Male, middle-aged, overweight and/or obese AWAs were more susceptible to workplace PM2.5 regardless of smoking status.

Parkinson's disease (PD) is the most common motor-associated neurodegenerative disease. Although the pathogenesis of PD is still wrapped in the mist, accumulating evidence indicates that mitochondrial dysfunction contributes to the onset and progression of PD. We previously reported that the lysosomal protease asparagine endopeptidase (AEP) cleaves α-synuclein in the brains of PD patients. The major product, α-synuclein 1–103, significantly promotes PD-like histological changes and motor dysfunction. However, the underlying molecular mechanisms remain unknown. Here we show that α-synuclein 1–103 fragment interacts with mitochondria and induces morphological and functional abnormalities of mitochondria. Furthermore, we investigated the protective effects of 7,8-dihydroxyflavone (7,8-DHF) on mitochondrial dysfunction induced by α-synuclein 1–103 fragment. We found that 7,8-DHF ameliorated α-synuclein 1–103-induced mitochondrial impairment and motor dysfunction. These results indicate that 7,8-DHF represents a novel oral bioactive therapeutic agent for treating PD.

BackgroundThe development of a new strategy to overcome chemoresistance to hepatocellular carcinoma (HCC) treatment is a long-standing issue. We have previously found that upregulated SETD3 levels are closely correlated with HCC. This study aims to explore the mechanism underlying how upregulation of SETD3 promotes liver carcinogenesis.MethodsRNA-Sequencing analysis was used to explore the correlation of SETD3 with regulatory targets. In vitro assays including cell proliferation and migration were performed to study the oncogenic roles of SETD3 and PLK1. Western blotting, immunohistochemical staining, and blood biochemical assays were performed to examine protein expression or pathological index in tumor tissues and mice liver tissues. Luciferase reporter system and chromatin immunoprecipitation assays were used to explore the mechanism.ResultsWe revealed that SETD3 regulates gene expression in subgroups, including cell division, cell proliferation, and cell cycle, in hepatocellular tumor cells. We found that SETD3 upregulation is associated with elevated PLK1 level in both hepatic tumor cells and clinical liver tissues. We further showed that overexpression of SETD3 promoted tumor cell proliferation and migration, whereas inhibition of PLK1 activity attenuated these phenotypes caused by SETD3. By taking advantage of the Sleep Beauty transposase system, we confirmed that upregulated mouse Setd3 promoted hepatic carcinogenesis in situ, but knockdown of mouse Plk1 mitigated Setd3-promoted tumorigenesis in mice. Mechanistically, we showed that SETD3 could be recruited to the promoter of PLK1 gene to facilitate PLK1 transcription.ConclusionsOur data demonstrate that elevated SETD3 may promote HCC by enhancing PLK1 expression, which suggests that SETD3 may act as a potential drug target combined with PLK1 inhibition to treat HCC.

Rheumatoid arthritis (RA) occurs in about 5 per 1,000 people and can lead to severe joint damage and disability. However, the knowledge of pathogenesis and treatment for RA remains limited. Here, we found that histone demethylase inhibitor GSK-J4 relieved collagen induced arthritis (CIA) symptom in experimental mice model, and the underlying mechanism is related to epigenetic transcriptional regulation in macrophages. The role of epigenetic regulation has been introduced in the process of macrophage polarization and the pathogenesis of inflammatory diseases. As a repressive epigenetic marker, tri-methylation of lysine 27 on histone H3 (H3K27me3) was shown to be important for transcriptional gene expression regulation. Here, we comprehensively analyzed H3K27me3 binding promoter and corresponding genes function by RNA sequencing in two differentially polarized macrophage populations. The results revealed that H3K27me3 binds on the promoter regions of multiple critical cytokine genes and suppressed their transcription, such as IL6, specifically in M-CSF derived macrophages but not GM-CSF derived counterparts. Our results may provide a new approach for the treatment of inflammatory and autoimmune disorders.

Naringenin, a citrus flavonoid that possessed various biological activities, had emerged as a potential therapeutic agent for the management of a variety of diseases, but naringenin derivatives’ application in cancer therapy and underlying mechanisms of action were not fully understood. Our recent work had shown that 4′,7-Di-O-methylnaringenin (DMNG) exerted its anti-colon cancer activity and the underlying mechanisms of action. We reported that DMNG could activate p53 signal pathway, dependent of p53 wild type status. We observed that DMNG decreased the survival of HCT-116 cells by induction of apoptosis and G2/M phase arrest. We further demonstrated that, in a dose- and time-dependent manner, DMNG effectively downregulated the MDM2 protein expression at protein translation level. Hence, our study unearthed that DMNG was a potential therapeutic and anti-metastatic agent for human colon cancer through down-regulating MDM2 and activating p53 pathway.

The raw eating quality of sweet potato is complex. As consumers start paying more attention to the raw eating quality of tuberous roots in sweet potato, the evaluation of the raw eating quality of sweet potato is becoming an important issue. Therefore, we measured 16 quality indicators in 81 varieties of sweet potato. It was found that these 16 quality traits had different coefficients of variation (C.V.). Among them, the C.V. of fructose, glucose, and adhesiveness were the largest: 87.95%, 87.43% and 55.09%, respectively. The cluster analysis method was used to define six categories of the different tuberous roots of sweet potato. Group I, III, and IV had a stronger hardness and higher starch and cellulose content. Groups II, V, and VI were softer, with a high moisture and soluble sugar content. The principal component analysis method was used to comprehensively evaluate 16 quality indicators of 81 sweet potato varieties. It was found that Futian1, Taishu14, and Nanshu022 are good varieties in terms of raw eating quality. These varieties have low hardness, high adhesiveness in texture, high soluble sugar content, and low starch and cellulose. Future research should focus on improving the raw eating quality of sweet potato by reducing hardness, starch, and cellulose, while increasing adhesiveness, soluble sugar, and moisture content.

Intervertebral disc degeneration (IDD) has been generally accepted as the major cause of low back pain (LBP), which imposes massive clinical and socioeconomic burdens. Previous studies have demonstrated that oxidative stress and inflammation-induced senescence and apoptosis of nucleus pulposus cells (NPCs) are the main cellular processes that cause IDD. Arginase II (ARG2), an enzyme involved in a variety of pathological processes, including cellular senescence, apoptosis, oxidative stress, and inflammation, has been shown to promote degeneration in several degenerative diseases, including osteoarticular diseases. Based on previous studies, we hypothesized that ARG2 deficiency might be conducive to the treatment of IDD by inhibiting the dyshomeostasis of the extracellular matrix (ECM), and the oxidative stress and inflammatory response-induced senescence and apoptosis via NF-κB. In this study, we found that ARG2 deficiency inhibited senescence and apoptosis of NPCs, and degeneration of the ECM induced by oxidative stress and the inflammatory response. Similar results were found with the selective NF-κB pathway inhibitor JSH-23. In contrast, overexpression of ARG2 had the opposite effect. Taken together, our results suggest that ARG2 deficiency prevents IDD via NF-κB, and may therefore, be a potential therapeutic strategy for IDD.

Myeloid differentiation factor 88 (MyD88) is a hub protein in the Toll-like receptor signaling pathway, which acts as a master switch for numerous inflammatory diseases, including acute lung injury (ALI). Although this protein is considered as a crucial therapeutic target, there are currently no clinically approved MyD88-targeting drugs. Based on previous literature, here we report the discovery via computer-aided drug design (CADD) of a small molecule, M20, which functions as a novel MyD88 inhibitor to efficiently relieve lipopolysaccharide-induced inflammation both in vitro and in vivo. Computational chemistry, surface plasmon resonance detection (SPR) and biological experiments demonstrated that M20 forms an important interaction with the MyD88-Toll/interleukin-1 receptor domain and thereby inhibits the protein dimerization. Taken together, this study found a MyD88 inhibitor, M20, with a novel skeleton, which provides a crucial understanding in the development and modification of MyD88 inhibitors. Meanwhile, the favorable bioactivity of the hit compound is also conducive to the treatment of acute lung injury or other more inflammatory diseases.

MAX dimerization protein 3 (MXD3), a transcriptional regulator of the MXD3 superfamily, is a part of the MYC–MAX–MXD network. However, its role in tumors has been reported in several cancers, such as B-cell acute lymphoblastic leukemia, medulloblastoma, neuroblastoma, and glioblastoma. Based on TCGA and GEO data, our first pancancer study of MXD3 confirmed the high expression of MXD3 in cancer tissues. Our results revealed that patients suffering from cancers with higher MXD3 expression had poor OS, DSS, DFI, and PFI. We further explored the methylation status of the MXD3 gene body and gene promoter in cancer. Patients with a higher MXD3 gene body have better OS, while the prognosis of patients with a high MXD3 promoter is more complex. We also verified the differential expression of three clinical phenotypes of MXD3: age, sex, and tumor stage, in a variety of tumors, suggesting a correlation between MXD3 and clinical characteristics. We explored the negative relationship between MXD3 and TMB and MSI in most types of cancer, indicating the poor prognosis of patients with high MXD3 expression. We further investigated the relationship between MXD3 and immune infiltrating cells and identified the relationship between MXD3 and immune genes, immunosuppressive genes, and antigen-presenting genes. All of the above findings established a solid relationship between MXD3 and the immune environment and immune cells. These results demonstrated that MXD3 might also be a potential immune factor. We also found a higher expression of MXD3 and promoter according to the increasing glioma WHO grade or histologic types. Glioma patients with high MXD3 or MXD3 promoter expression had poor survival. Finally, we used IHC to verify the higher expression of MXD3 in glioma samples compared to normal samples. Our study shows that MXD3, as a poor prognostic factor, plays a significant role in many cancers, especially glioma. Although more clinical evidence for MXD3 as a clinical therapeutic target and an immunotherapy site is needed, MXD3 can play an important guiding role in multiple clinical treatments, including immunotherapy and demethylation therapy.