High-Performance Bifunctional Electrocatalysts for Flexible and Rechargeable Zn-Air Batteries: Recent Advances.

Flexible rechargeable Zn-air batteries (FZABs) exhibit high energy density, ultra-thin, lightweight, green, and safe features, and are considered as one of the ideal power sources for flexible wearable electronics. However, the slow and high overpotential oxygen reaction at the air cathode has become one of the key factors restricting the development of FZABs. The improvement of activity and stability of bifunctional catalysts has become a top priority. At the same time, FZABs should maintain the battery performance under different bending and twisting conditions, and the design of the overall structure of FZABs is also important. Based on the understanding of the three typical configurations and working principles of FZABs, this work highlights two common strategies for applying bifunctional catalysts to FZABs: 1) powder-based flexible air cathode and 2) flexible self-supported air cathode. It summarizes the recent advances in bifunctional oxygen electrocatalysts and explores the various types of catalyst structures as well as the related mechanistic understanding. Based on the latest catalyst research advances, this paper introduces and discusses various structure modulation strategies and expects to guide the synthesis and preparation of efficient bifunctional catalysts. Finally, the current status and challenges of bifunctional catalyst research in FZABs are summarized.

Coronal deformity in ankylosing spondylitis with concomitant thoracolumbar kyphosis: patterns, manifestations and surgical strategies.

PURPOSE: To evaluate different patterns of coronal deformity secondary to ankylosing spondylitis (AS), to propose relevant treatment strategies, and to assess efficacy of asymmetrical pedicle subtraction osteotomy (APSO). METHODS: Coronal deformity was defined as coronal Cobb angle over 20º or coronal balance distance (CBD) more than 3 cm. 65 consecutive AS patients with concomitant coronal and sagittal deformity who underwent PSO were included. The average follow-up time was 40.4 months. Radiographic evaluation included coronal Cobb angle and CBD. Furthermore, sagittal parameters were used to assess magnitude and maintenance of kyphosis correction. RESULTS: Based on curve characteristics, coronal deformity caused by AS included four different radiologic patterns: Pattern I: lumbar scoliosis; Pattern II: C-shaped thoracolumbar curve; Pattern III: trunk shift without major curve; Pattern IV: proximal thoracic scoliosis. APSO was performed for patients in Pattern I to III while conventional PSO was applied for patients in Pattern IV. Significant improvement in all the sagittal parameters were noted in 65 patients without obvious correction loss at the last follow-up. Besides, significant and sustained correction of coronal mal-alignment was identified in 59 APSO-treated patients. Rod fracture occurred in four cases and revision surgery was performed for one case. CONCLUSION: According to radiologic manifestations, coronal deformity caused by AS could be categorized into four patterns. APSO proved to be a feasible and effective procedure for correction of Pattern I to III patients. Coronal deformity pattern, apex location, sagittal profile of lumbar spine and preoperative hip function should be considered for osteotomy level selection in APSO.

Free-hand technique of C7 pedicle screw insertion using a simply defined entry point without fluoroscopic guidance for cervical spondylotic myelopathy patients with C3 to C6 instrumented by lateral mass screws: a retrospective cohort study.

BACKGROUND: Nowadays, both lateral mass screw (LMS) and pedicle screw were effective instrumentation for posterior stabilization of cervical spine. This study aims to evaluate the feasibility of a new free-hand technique of C7 pedicle screw insertion without fluoroscopic guidance for cervical spondylotic myelopathy (CSM) patients with C3 to C6 instrumented by lateral mass screws. METHODS: A total of 53 CSM patients underwent lateral mass screws instrumentation at C3 to C6 levels and pedicle screw instrumentation at C7 level were included. The preoperative 3-dimenional computed tomography (CT) reconstruction images of cervical spine were used to determine 2 different C7 pedicle screw trajectories. Trajectory A passed through the axis of the C7 pedicle while trajectory B selected the midpoint of the base of C7 superior facet as the entry point. All these 53 patients had the C7 pedicle screw inserted through trajectory B by free-hand without fluoroscopic guidance and the postoperative CT images were obtained to evaluate the accuracy of C7 pedicle screw insertion. RESULTS: Trajectory B had smaller transverse angle, smaller screw length, and smaller screw width but both similar sagittal angle and similar pedicle height when compared with trajectory A. A total of 106 pedicle screws were inserted at C7 through trajectory B and only 8 screws were displaced with the accuracy of screw placement as high as 92.5%. CONCLUSION: In CSM patients with C3 to C6 instrumented by LMS, using trajectory B for C7 pedicle screw insertion is easy to both identify the entry point and facilitate the rod insertion.

Research progress in the application of catalytic infrared technology in fruit and vegetable processing.

Fruit and vegetable processing can effectively maintain the quality and safety of fruit and vegetable-based products while extending the shelf life of products and saving transportation costs. Infrared (IR) technology has been widely used in many operating units of fruit and vegetable processing because of its versatility of uniform heating, high heat transfer efficiency, and minimized damage to fruit and vegetable tissues. Catalytic IR (CIR), compared to traditional electric IR, is powered by natural gas or liquefied gas, which can improve thermal efficiency while significantly saving energy. However, there is no comprehensive overview discussing and summarizing the utilization and application of the CIR technology in fruit and vegetable processing. Therefore, this review aims to highlight recent advances in the application of CIR technology in fruit and vegetable processing. Specifically, a comprehensive discussion of the physicochemical properties and underlying mechanisms of CIR is provided, and its applications as a single method or in combination with other technologies in fruit and vegetable processes, such as blanching, peeling, microbial population reduction, and drying, are also presented. Besides, the currently used laboratory and pilot-scale equipment of CIR has also been summarized.

Preoperative assessment of peripheral vascular invasion of pancreatic ductal adenocarcinoma based on high-resolution MRI.

OBJECTIVES: Preoperative imaging of vascular invasion is important for surgical resection of pancreatic ductal adenocarcinoma (PDAC). However, whether MRI and CT share the same evaluation criteria remains unclear. This study aimed to compare the diagnostic accuracy of high-resolution MRI (HR-MRI), conventional MRI (non-HR-MRI) and CT for PDAC vascular invasion. METHODS: Pathologically proven PDAC with preoperative HR-MRI (79 cases, 58 with CT) and non-HR-MRI (77 cases, 59 with CT) were retrospectively collected. Vascular invasion was confirmed surgically or pathologically. The degree of tumour-vascular contact, vessel narrowing and contour irregularity were reviewed respectively. Diagnostic criteria 1 (C1) was the presence of all three characteristics, and criteria 2 (C2) was the presence of any one of them. The diagnostic efficacies of different examination methods and criteria were evaluated and compared. RESULTS: HR-MRI showed satisfactory performance in assessing vascular invasion (AUC: 0.87-0.92), especially better sensitivity (0.79-0.86 vs. 0.40-0.79) than that with non-HR-MRI and CT. HR-MRI was superior to non-HR-MRI. C2 was superior to C1 on CT evaluation (0.85 vs. 0.79, P = 0.03). C1 was superior to C2 in the venous assessment using HR-MRI (0.90 vs. 0.87, P = 0.04) and in the arterial assessment using non-HR-MRI (0.69 vs. 0.68, P = 0.04). The combination of C1-assessed HR-MRI and C2-assessed CT was significantly better than that of CT alone (0.96 vs. 0.86, P = 0.04). CONCLUSIONS: HR-MRI more accurately assessed PDAC vascular invasion than conventional MRI and may contribute to operative decision-making. C1 was more applicable to MRI scans, and C2 to CT scans. The combination of C1-assessed HR-MRI and C2-assessed CT outperformed CT alone and showed the best efficacy in preoperative examination of PDAC.

Evaluation of Hypoxia in Hepatocellular Carcinoma Using Quantitative MRI: Significances, Challenges, and Advances.

This review aimed to perform a scoping review of promising MRI methods in assessing tumor hypoxia in hepatocellular carcinoma (HCC). The hypoxic microenvironment and upregulated hypoxic metabolism in HCC are determining factors of poor prognosis, increased metastatic potential, and resistance to chemotherapy and radiotherapy. Assessing hypoxia in HCC is essential for personalized therapy and predicting prognoses. Oxygen electrodes, protein markers, optical imaging, and positron emission tomography can evaluate tumor hypoxia. These methods lack clinical applicability because of invasiveness, tissue depth, and radiation exposure. MRI methods, including blood oxygenation level-dependent, dynamic contrast-enhanced MRI, diffusion-weighted imaging, MRI spectroscopy, chemical exchange saturation transfer MRI, and multinuclear MRI, are promising noninvasive methods that evaluate the hypoxic microenvironment by observing biochemical processes in vivo, which may inform on therapeutic options. This review summarizes the recent challenges and advances in MRI techniques for assessing hypoxia in HCC and highlights the potential of MRI methods for examining the hypoxic microenvironment via specific metabolic substrates and pathways. Although the utilization of MRI methods for evaluating hypoxia in patients with HCC is increasing, rigorous validation is needed in order to translate these MRI methods into clinical use. Due to the limited sensitivity and specificity of current quantitative MRI methods, their acquisition and analysis protocols require further improvement. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 4.

Research progress on extraction of active components from apple processing waste.

Apple waste (APW) is the residual product after apple processing, including apple peel, apple core, apple seed, and other components. A large quantity of APW produced is abandoned annually, leading to serious resource waste and environmental pollution. APW is rich in natural active compounds, such as pectin, polyphenols, fatty acids, and dietary fiber, which has a good use value. This paper reviewed the current research on recovering active components from APW. The traditional extraction methods (acid, alkali, physical, enzyme, etc.) and the novel extraction methods (SWE, UAE, MAE, RFAE, etc.) for the recovery of pectin, polyphenols, apple seed oil, apple seed protein, and dietary fiber from APW were systematically summarized. The basic principles, advantages, and disadvantages of different extraction methods were introduced. The requirements of different extraction methods on extraction conditions and the effects of different extraction methods on the yield, quality, and functional activity of extracted products were analyzed. The challenges and future study direction of APW extraction have prospected. This paper aims to provide a reference for other researchers interested in APW extraction, improve the utilization rate of APW and extend the value chain of the apple industry.

Interaction among biofilter microbiome, fecal metabolome and water quality and regulation of sewage discharge in the recirculating aquaculture system of Apostichopus japonicus.

With the aggravation of environmental pollution caused by traditional culture of Apostichopus japonicus, the concept of A. japonicus recirculating aquaculture system (RAS) came into being. To plan the sewage discharge time reasonably, we explored the temporal variation of water quality, biofilter microbe and fecal metabolome in RAS and relevant mechanism. The results showed that monitored water quality in RAS were within the safe living range of A. japonicus. Proteobacteria and Desulfobacterota were dominant bacteria in biofilter. The RDA results and correlation heatmap showed that NH4-N and NO2-N significantly affected the microbial community composition. The expression pattern of fecal metabolites changed with the passage of time after feeding. And ROC curve analysis and VIP bar chart showed that there were inter group biomarkers with predictive performance, which could help to remind timely sewage discharge. Topological analysis of KEGG pathway enrichment showed that metabolic pathways such as alanine, aspartate and glutamate metabolism changed significantly after feeding (P < 0.01). Additionally, the correlation analysis results showed that biofilter microbe and fecal metabolites were related to water quality (P < 0.05). Combined with the above research results, this study concluded that the RAS could discharge sewage 25-30 h after feeding. These findings were of direct significance to the management of RAS environment and the protection of A. japonicus healthy growth.

Improved eutrophication model with flow velocity-influence function and application for algal bloom control in a reservoir in East China.

Improving hydrodynamic conditions is considered an effective method for facilitating the eutrophication management. However, the effect of hydrodynamic conditions on algal growth has rarely been quantified. In this work, a eutrophication model was developed and flow velocity was introduced into the algae growth kinetic formula to simulate the dynamics of algae growth in a drinking water source reservoir in East China. Based on the previous research and model calibration, the flow velocity-influence function f(v) and its parameters were determined. Accordingly, the optimal flow velocity for the dominant algae growth and critical flow velocity for algal growth inhibition were presented to be 0.055 m/s and 0.200 m/s for the study reservoir. Modeled results considering f(v) agreed with better with observations and reproduced the algal overgrowth process more accurately. The spatial-temporal differences in chlorophyll a (Chl a) concentration distribution during the algal proliferation period were analyzed on the basis of simulation results, which corroborated the significant influence of flow velocity on algal growth. The established model was applied to investigate the effect of improvement in hydrodynamic conditions on algal bloom control in the reservoir, and the scenario simulation of the additional sluice was conducted. Results showed that the additional sluice operation inhibited algal overgrowth effectively, resulting in an average decrease of 24.8%, 3.3%, 43.0%, and 37.5% in modeled Chl a concentration upstream north, upstream south, midstream and downstream, respectively. The established model might serve as a practical tool for eutrophication management in the study reservoir and other water bodies with similar hydrological characteristics and geographical features.

Utility of Quantitative Metrics From Dual-Layer Spectral-Detector CT for Differentiation of Pancreatic Neuroendocrine Tumor and Neuroendocrine Carcinoma.

BACKGROUND. The 2019 WHO classification of digestive system tumors separates neuroendocrine neoplasms (NENs) into neuroendocrine tumors (NETs) and neuroendocrine carcinomas (NECs), which are considered to represent pathologically distinct entities warranting different management approaches. Dual-layer spectral-detector CT (DLCT) may aid their differentiation through specific material decomposition. OBJECTIVE. The purpose of this study was to assess the utility of quantitative metrics derived from DLCT for the differentiation of pancreatic NET and NEC. METHODS. This retrospective study included 104 patients (mean age, 51 ± 13 [SD] years; 52 women, 52 men) with pathologically confirmed NEN (89 NET, including 22 grade 1, 48 grade 2, and 19 grade 3; 15 NEC) who underwent multiphase DLCT within 15 days before biopsy or resection. Two radiologists independently placed ROIs to record tumor attenuation, iodine concentration (IC), and effective atomic number (Zeff) across phases and assessed qualitative features (composition, homogeneity, margins, calcifications, main pancreatic duct dilatation, vascular invasion, lymphadenopathy). Interobserver agreement was assessed. Mean and median values of both readers' measurements were obtained for quantitative measures; consensus was reached for qualitative features. NET and NEC were compared using multivariable regression analysis and ROC analysis. RESULTS. Interobserver agreement, expressed as intraclass correlation coefficients, ranged from 0.869 to 0.992 for quantitative metrics and, expressed as kappa coefficients, ranged from 0.723 to 0.816 for qualitative features. In multivariable analysis of qualitative and quantitative features, significant independent predictors of NEC (p < .05) were IC in the portal venous phase (median, 1.3 mg/mL for NEC vs 2.7 mg/mL for NET), Zeff in the portal venous phase (median, 8.1 vs 8.6), and attenuation in the portal venous phase (median, 78.2 vs 113.5 HU). AUC for predicting NEC was 0.897 for IC, 0.884 for Zeff, 0.921 for combination of IC and Zeff, and 0.855 for attenuation. Predicted probability based on a combination of IC and Zeff achieved sensitivity of 93.33% and specificity of 80.90% for predicting NEC. Significant independent predictors (p < .05) for differentiating grade 3 NET and NEC were IC (median, 2.0 vs 1.3 mg/mL; AUC = 0.789) and attenuation (mean, 90.3 vs 78.2 HU; AUC = 0.647), both measured in the portal venous phase. CONCLUSION. Incorporation of DLCT metrics improves differentiation of NET and NEC compared with conventional CT attenuation and qualitative features. CLINICAL IMPACT. DLCT may help select patients with pancreatic NENs for platinum-based chemotherapies.

Preoperative Prediction of Pancreatic Neuroendocrine Neoplasms Grading Based on Enhanced Computed Tomography Imaging: Validation of Deep Learning with a Convolutional Neural Network.

INTRODUCTION: The pathological grading of pancreatic neuroendocrine neoplasms (pNENs) is an independent predictor of survival and indicator for treatment. Deep learning (DL) with a convolutional neural network (CNN) may improve the preoperative prediction of pNEN grading. METHODS: Ninety-three pNEN patients with preoperative contrast-enhanced computed tomography (CECT) from Hospital I were retrospectively enrolled. A CNN-based DL algorithm was applied to the CECT images to obtain 3 models (arterial, venous, and arterial/venous models), the performances of which were evaluated via an eightfold cross-validation technique. The CECT images of the optimal phase were used for comparing the DL and traditional machine learning (TML) models in predicting the pathological grading of pNENs. The performance of radiologists by using qualitative and quantitative computed tomography findings was also evaluated. The best DL model from the eightfold cross-validation was evaluated on an independent testing set of 19 patients from Hospital II who were scanned on a different scanner. The Kaplan-Meier (KM) analysis was employed for survival analysis. RESULTS: The area under the curve (AUC; 0.81) of arterial phase in validation set was significantly higher than those of venous (AUC 0.57, p = 0.03) and arterial/venous phase (AUC 0.70, p = 0.03) in predicting the pathological grading of pNENs. Compared with the TML models, the DL model gave a higher (although insignificantly) AUC. The highest OR was achieved for the p ratio <0.9, the AUC and accuracy for diagnosing G3 pNENs were 0.80 and 79.1% respectively. The DL algorithm achieved an AUC of 0.82 and an accuracy of 88.1% for the independent testing set. The KM analysis showed a statistical significant difference between the predicted G1/2 and G3 groups in the progression-free survival (p = 0.001) and overall survival (p < 0.001). CONCLUSION: The CNN-based DL method showed a relatively robust performance in predicting pathological grading of pNENs from CECT images.

Imaging biomarkers for well and moderate hepatocellular carcinoma: preoperative magnetic resonance image and histopathological correlation.

BACKGROUND: Our aim of the study is to investigate the feasibility of preoperative prediction for hepatocellular carcinoma (HCC) histological grading using gadoxetic acid-enhanced magnetic resonance imaging (MRI). METHODS: This study included one hundred and fifty-six patients with solitary HCC. Preoperative gadoxetic acid-enhanced MRI findings were retrospectively analyzed. MRI qualitative features such as tumor size, margin, capsule status, signal homogeneity, intratumoral vessels, peritumoral enhancement during mid-arterial phase, peritumoral hypointensity during the hepatobiliary phase (HBP) were investigated. Apparent diffusion coefficients (ADCs), T1 reduction ratio of pre- and post-contrast enhanced images of the tumors were calculated. HCC histological grading in surgical specimens were confirmed by Edmonson's criteria. Correlations between these MRI features and HCC histological grading were analyzed using multivariate logistic regression. The receiver operating characteristic (ROC) curve was used to assess the predictive efficacy of the model. RESULTS: Univariate analysis showed that maximum tumor diameter (p = 0.004), tumor margin (p = 0.006), intratumoral vessels (p = 0.001) and peritumoral hypointensity during HBP (p = 0.000), were significantly correlated with HCC histological grading. There was no relationship between capsule, tumor signal, venous thrombosis, peritumoral enhancement during mid-arterial phase, ADC value, T1 reduction ratio, and HCC histological grading. Multivariate logistic regression analysis demonstrated that the maximum tumor diameter (p = 0.012, odds ratio = 1.002, 95% confidence interval: 1.007-1.046)) was an independent risk factor for high grade HCC. CONCLUSIONS: Greater tumor size, a more irregular margin, presence of intratumoral vessels, and peritumoral hypointensity during HBP were indicators for high grade HCC. The maximum tumor diameter was an independent risk factor for high grade HCC.

Gut microbiota dynamics interacting with gastrointestinal evacuation of Apostichopus japonicus: novel insights into promising strategies for environmental improvement.

As an important input of environmental micropollutants into aquaculture environment, feed is now considered to be a critical factor in shaping gastrointestinal evacuation characteristics of animals. We analyzed the gastrointestinal evacuation characteristics and gut bacteria of Apostichopus japonicus within 30 h after feeding in recirculating aquaculture system (RAS) and explored the evacuation mechanism interacting by bacteria. The Gauss model was the most precise gastrointestinal evacuation curve, and 80% of gastrointestinal evacuation time was 27.81 h after feeding. Linear discriminant analysis effect size analysis revealed that gut microbial abundance associated significantly with time (P < 0.05), and 42 biomarkers that could predict gastrointestinal evacuation were totally detected, such as Lutibacter and Vibrio. Biomarkers at 25 h after feeding were related to harmful bacteria. A dynamic response between gastrointestinal content ratio and gut microbial abundance was detected. Taken together, we could discharge sewage about 25 h after feeding and carry out the next round of feeding activities.

Hyaluronan degradation by HYAL2 is essential for odontoblastic differentiation and migration of mouse dental papilla cells.

The coordination between odontoblastic differentiation and directed cell migration of mesenchymal progenitors is necessary for regular dentin formation. The synthesis and degradation of hyaluronan (HA) in the extracellular matrix create a permissive niche that directly regulates cell behaviors. However, the role and mechanisms of HA degradation in dentin formation remain unknown. In this work, we present that HA digestion promotes odontoblastic differentiation and cell migration of mouse dental papilla cells (mDPCs). Hyaluronidase 2 (HYAL2) is responsible for promoting odontoblastic differentiation through degrading HA, while hyaluronidase 1 (HYAL1) exhibits negligible effect. Silencing Hyal2 generates an extracellular environment rich in HA, which attenuates F-actin and filopodium formation and in turn inhibits cell migration of mDPCs. In addition, activating PI3K/Akt signaling significantly rescues the effects of HA accumulation on cytodifferentiation. Taken together, the results confirm the contribution of HYAL2 to HA degradation in dentinogenesis and uncover the mechanism of the HYAL2-mediated HA degradation in regulating the odontoblastic differentiation and migration of mDPCs.

Current and future trends of acupuncture as an adjuvant therapy in cancer: A bibliometric and visual analysis.

BACKGROUND: Acupuncture, as one of the representatives of complementary therapies, is often used as an adjunctive therapy in the treatment of cancer and related complications with beneficial results. METHODS: We selected the Web of Science Core Collection (WOSCC) database as the data source and searched to obtain relevant literatures on the application of acupuncture in cancer treatment. The relevant literature was analyzed using CiteSpace (version 6.1.R6) and VOSviewer (version 1.6.20). RESULTS: A total of 592 publications were included, with an overall upward trend in the number of publications. There were 135 countries or institutions involved, with China as the most published country. There were 1888 related institutions, and Memorial Sloan Kettering Cancer Center was the institution with the most publications. A total of 3067 authors were involved, and there were obvious collaborations between authors. There were 190 related journals, and J Clin Oncol was the most cited journal. The most frequently occurring keywords were breast cancer and management, but also other related topics such as quality of life, chemotherapy, and complementary. CONCLUSION: Acupuncture is gaining increasing attention as an adjunctive therapy in cancer treatment programs. Currently, relevant research focuses on acupuncture to alleviate cancer-induced comorbid symptoms, such as pain and insomnia. Future research is gradually shifting toward spiritual care, Colorectal Cancer Surgery, and systematic review.

Identification and application of a novel patulin degrading enzyme from Cyberlindnera fabianii.

Patulin (PAT) is a mycotoxin commonly found in fruits and vegetables, prompting the need for effective removal and detoxification methods, which have garnered significant research attention in recent years. Among these methods, the utilization of microbial-derived enzymes stands out due to their mild operating conditions, specificity in targeted functional groups, and the production of non-toxic by-products, making it a preferred degradation approach. In this study, a novel PAT-degrading enzyme derived from Cyberlindnera fabianii (Cyfa-SDR) was identified, demonstrating its highest catalytic activity at pH 7.0 and 80 °C against PAT. This temperature tolerance level represents the highest reported for PAT-degrading enzymes to date. The enzyme was further characterized as a short-chain dehydrogenase through analysis of its amino acid composition, conserved GXXXGXG motif, and dependency on NADPH. Moreover, the study evaluated the efficiency of PAT degradation by Cyfa-SDR at varying substrate and enzyme concentrations, surpassing the performance of other PAT-degrading enzymes, thus highlighting its substantial potential for the biological control of PAT. In conclusion, the enzymatic treatment using the PAT-degrading enzyme Cyfa-SDR presents a viable and promising solution for enhancing the quality and safety of fruit juice.

Nrf-2/ROS/NF-κB pathway is modulated by cynarin in human mesenchymal stem cells in vitro from ankylosing spondylitis.

Ankylosing spondylitis (AS) is an immune chronic inflammatory disease, resulting in back pain, stiffness, and thoracolumbar kyphotic deformity. Based on the reported anti-inflammatory and antioxidant capacities of cynarin (Cyn), this study explored its protective role and molecular mechanisms in mesenchymal stem cells (MSCs) from AS. The target pathways and genes were verified using Western blotting, quantitative real-time polymerase chain reaction, and immunofluorescent staining, while molecular docking analysis was conducted. In AS-MSCs, we found that the expression levels of p-NF-κB, IL-6, IL-1ß, and TNF-α were higher and IκB-α, Nrf-2, and HO-1 were lower compared with healthy control (HC)-MSCs. With molecular docking analysis, the biding affinities between Cyn and Keap1-Nrf-2 and p65-IκB-α were predicted. The mRNA and protein expression of p-NF-κB, IL-6, IL-1ß, and TNF-α and the reactive oxygen species (ROS) generation were downregulated following Cyn administration. Meanwhile, the expression level of IκB-α, Nrf-2, and HO-1 were significantly increased after Cyn pretreatment. The results suggested that the protective mechanisms of Cyn in AS-MSCs were based on enhancing the antioxidation and suppression of excessive inflammatory responses via Nrf-2/ROS/NF-κB axis. Our findings demonstrate that Cyn is a potential candidate for alleviating inflammation in AS.

The Influence of Radiographic Parameter on the S2 Alar-Iliac Screw Virtual Trajectory in Degenerative Lumbar Scoliosis Patients: A Computed Tomography Study.

OBJECTIVE: S2 alar-iliac (S2AI) screw had been widely used in the pelvic fusion for degenerative lumbar scoliosis (DLS) patients. However, whether S2AI screw trajectory was influenced by sagittal profile in DLS patients had not been comprehensively investigated. The objective of this study was to evaluate the associations between the optimal S2 alar-iliac (S2AI) screw trajectory and sagittal spinopelvic parameters in DLS patients. METHODS: Computed tomography (CT) scans of pelvis were performed in 47 DLS patients for three-dimensional reconstruction of S2AI screw trajectory from September 2019 to November 2021. Five S2AI screw trajectory parameters were measured in CT reconstruction images, including: 1) angle in the transverse plane (Tsv angle); 2) angle in the sagittal plane (Sag angle); 3) maximal screw length; 4) screw width; and 5) skin distance. The lumbar Cobb angle, lumbar apical vertebral translation (AVT); global kyphosis (GK); thoracic kyphosis (TK); lumbar lordosis (LL); sagittal vertical axis (SVA); sacral slope (SS); pelvic tilt (PT); and pelvic incidence (PI) were measured in standing X-ray films of the whole spine and pelvis. RESULTS: Both Tsv angle and Sag angle had significant positive associations with SS (p < 0.05) but negative associations with both PT (p < 0.05) and LL (p < 0.05) in all cases. Patients with SS less than 15° had both smaller Tsv angle and Sag angle than those with SS equal to or more than 15° (p < 0.05). The decreased LL would lead to the backward rotation of the pelvis, resulting in a more cephalic and less divergent trajectory of S2AI screw in DLS patients. CONCLUSIONS: For DLS patients with lumbar kyphosis, spine surgeons should avoid both excessive Tsv and Sag angles for S2AI screw insertion, especially when using free-hand technique.

Prediction of g-C3N4-based photocatalysts in tetracycline degradation based on machine learning.

Investigating the effects of g-C3N4-based photocatalysts on experimental parameters during tetracycline (TC) degradation can be helpful in discovering the optimal parameter combinations to improve the degradation efficiencies in general. Machine learning methods can avoid the problems of high cost, time-consuming and possible instrumental errors in experimental methods, which have been proven to be an effective alternative for evaluating the entire experimental process. Eight typical machine learning models were explored for their effectiveness in predicting the TC degradation efficiencies of g-C3N4 based photocatalysts. XGBoost (XGB) was the most reliable model with R2, RMSE and MAE values of 0.985, 4.167 and 2.900, respectively. In addition, XGB's feature importance and SHAP method were used to rank the importance of features to provide interpretability to the results. This study provided a new idea for developing g-C3N4-based photocatalysts for TC degradation and intelligent algorithms for predicting the photocatalytic activity of g-C3N4-based photocatalysts.

Predicting One-year Recurrence of HCC based on Gadoxetic Acid-enhanced MRI by Machine Learning Models.

OBJECTIVE: Accurate prediction of recurrence risk after resction in patients with Hepatocellular Carcinoma (HCC) may help to individualize therapy strategies. This study aimed to develop machine learning models based on preoperative clinical factors and multiparameter Magnetic Resonance Imaging (MRI) characteristics to predict the 1-year recurrence after HCC resection. METHODS: Eighty-two patients with single HCC who underwent surgery were retrospectively analyzed. All patients underwent preoperative gadoxetic acidenhanced MRI examination. Preoperative clinical factors and MRI characteristics were collected for feature selection. Least Absolute Shrinkage and Selection Operator (LASSO) was applied to select the optimal features for predicting postoperative 1-year recurrence of HCC. Four machine learning algorithms, Multilayer Perception (MLP), random forest, support vector machine, and k-nearest neighbor, were used to construct the predictive models based on the selected features. A Receiver Operating Characteristic (ROC) curve was used to assess the performance of each model. RESULTS: Among the enrolled patients, 32 patients experienced recurrences within one year, while 50 did not. Tumor size, peritumoral hypointensity, decreasing ratio of liver parenchyma T1 value (ΔT1), and α-fetoprotein (AFP) levels were selected by using LASSO to develop the machine learning models. The area under the curve (AUC) of each model exceeded 0.72. Among the models, the MLP model showed the best performance with an AUC, accuracy, sensitivity, and specificity of 0.813, 0.742, 0.570, and 0.853, respectively. CONCLUSION: Machine learning models can accurately predict postoperative 1-year recurrence in patients with HCC, which may help to provide individualized treatment.