The chemical constituents in dried roots of Atractylodes macrocephala were investigated in this study. Through utilizing normal-phase silica gel and ODS column chromatography, TLC, and semi-preparative HPLC, 4 new sesquiterpenoids were purified from the ethyl acetate extract of A. macrocephala. By various spectroscopic techniques, such as 1D and 2D NMR, HR-ESI-MS, IR, UV, and CD, their structures were identified as atractylmacron A (1), 9β-hydroxyasterolide (2), atractylenolide H (3), atractylenolide J (4). Compound 1 possesses a rare 6/7 bicyclic skeleton.

To investigate the association between neutrophil to lymphocyte ratio (NLR) andestimated glomerular filtration rate (eGFR) in patients with diabetes using large-scale data.

RNA-binding proteins (RBPs) are ubiquitous components within cells, fulfilling essential functions in a myriad of biological processes. These proteins interact with RNA molecules to regulate gene expression at various levels, including transcription, splicing, transport, localization, translation, and degradation. Understanding the intricate network of RBP-RNA interactions is crucial for deciphering the complex regulatory mechanisms that govern cellular function and organismal development. Ultravidet (UV) cross-linking and immunoprecipitation (CLIP) stands out as a powerful approach designed to map the precise locations where RBPs bind to RNA. By using UV light to create covalent bonds between proteins and RNA, followed by immunoprecipitation to isolate the protein-RNA complexes, researchers can identify the direct targets of specific RBPs. The advent of high-throughput sequencing technologies has revolutionized CLIP, enabling the identification of not only the types but also the exact sequences of RNA bound by RBPs on a genome-wide scale. The evolution of CLIP has led to the development of specialized variants, each with unique features that address specific challenges and expand the scope of what can be studied. High-throughput sequencing CLIP (HITS-CLIP) was one of the first advancements, significantly increasing the throughput and resolution of RNA-protein interaction mapping. Photoactivatable-ribonucleoside-enhanced CLIP (PAR-CLIP) introduced the use of photoactivatable ribonucleosides to enhance cross-linking efficiency and specificity, reducing background noise and improving the detection of low-abundance RNA-protein interactions. Individual-nucleotide resolution CLIP (iCLIP) further refined the technique, achieving unprecedented precision by resolving individual nucleotides involved in RBP binding, which is particularly valuable for studying the fine details of RNA structure and function. Despite the remarkable progress, there remains room for improvement in CLIP technology. Researchers continue to seek methods to increase sensitivity, reduce technical variability, and improve the reproducibility of results. Advances in sample preparation, data analysis algorithms, and computational tools are critical for addressing these challenges. Moreover, the application of CLIP to more diverse biological systems, including non-model organisms and clinical samples, requires the development of tailored protocols and the optimization of existing ones. Looking forward, the field of RNA biology is poised to benefit greatly from ongoing innovations in CLIP technology. The exploration of non-canonical RNA-protein interactions, such as those involving long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), promises to reveal new layers of cellular regulation and may lead to the discovery of novel therapeutic targets. Furthermore, integrating CLIP data with other omics approaches, such as proteomics and metabolomics, will provide a more comprehensive understanding of the dynamic interplay between RNA and its binding partners within the cell. In conclusion, the continuous refinement and expansion of CLIP techniques have not only deepened our knowledge of RNA biology but have also opened up new avenues for investigating the molecular underpinnings of health and disease. As the technology matures, it is expected to play an increasingly pivotal role in both basic and applied research, contributing to the advancement of medical science and biotechnology.

Lianggesan was first recorded in Taiping Huimin Heji Jufang， which was composed of Rhei Radix et Rhizoma， Natrii Sulfas， Gardeniae Fructus， Forsythiae Fructus， Scutellariae Radix， Glycyrrhizae Radix et Rhizoma（GRR）， Menthae Haplocalycis Herba， Lophatheri Herba and Mel. It was clinically applied to treat fire-heat syndrome in the upper and middle Jiao， and the curative effect was positive. In this study， the bibliometric method was used to conduct a detailed textual research on the formula name， medicinal composition， dosage evolution， origin and processing， functional indications and other aspects of Lianggesan. Research revealed that Lianggesan has six other names， such as Lianqiao Yinzi， Lianqiao Jiedusan， Jufang Lianggesan， Jiegu Lianggesan， Hejian Lianggesan and Qingji Lianggesan. Based on the edition of Taiping Huimin Heji Jufang， an analysis of the evolution of its formula composition revealed that the missing Chinese medicines were predominantly bamboo leaves and honey， while the added Chinese medicines were primarily supplements introduced to address changes in disease manifestations. After textual research， the dosage for one dose of Lianggesan from Taiping Huimin Heji Jufang was as follows：826 g of Rhei Radix et Rhizoma， 826 g of Natrii Sulfas， 826 g of GRR， 413 g of Gardeniae Fructus， 413 g of Menthae Haplocalycis Herba， 413 g of Scutellariae Radix， and 1652 g of Forsythiae Fructus. Decocting method was as following：Grinding the Chinese medicines into coarse powder（2-4 mm）， taking 8.16 g per dose， adding 300 mL of water， along with 2 g of Lophatheri Herba and 5 g of Mel， and decocting to 140 mL. The residue was removed and taken warmly 30 min after meals. It was recommended to take it three times daily until improvement was achieved. The origins of the 9 Chinese medicines were consistent with the 2020 edition of Pharmacopoeia of the People's Republic of China. Except for GRR， which required single frying（stir-frying）， the remaining medicines were all raw products. The description of the function of this formula in ancient books was summarized as purging fire and promoting bowel movements， clearing heat from the upper body and purging the lower body， and the main syndromes included facial redness， tongue swelling， red eyes， etc. In modern applications， the formula is primarily used for respiratory and digestive system diseases， including acute lung injury， chronic obstructive pulmonary disease， herpetic angina and aphthous stomatitis， covering 142 types of diseases. In summary， this paper can provide a basis for further research and development of Lianggesan through the literature review and key information combing.

Objective:To compare the efficacy of the horizontal plate plus raft screws above the acetabulum and fixation with screws only for acetabular fractures combined with dome impaction in the aged patients.Methods:A retrospective cohort study was conducted to analyze the clinical data of 20 aged patients with acetabular fractures combined with dome impaction, who were admitted to Tianjin hospital between May 2013 and January 2023, including 5 males and 15 females, aged 61-84 years [(72.2±7.3)years]. According to Letournel and Judet classification, 13 patients had anterior column fracture, 5 anterior column fracture combined with posterior transverse fracture and 2 two-column fracture. All the patients underwent open reduction and internal fixation through an anterior approach. Of them, 11 patients were treated with the fixation with the horizonal plate plus raft screws above the acetabulum (plate plus raft screw group) and 9 with the screws only (screw only group). The operative time, intraoperative blood loss, and intraoperative fluoroscopy times were compared between the two groups. The quality of fracture reduction was evaluated with the Matta′s radiographic criteria at 3 days after surgery and the function of the hip joint was assessed with Merle D′Aubigné and Postel scoring system at 3 months after surgery and at the last follow-up as well as the excellent and good rate at te last follow-up. The occurrence of postoperative complications was observed.Results:All the patients were followed up for 6-18 months [(13.1±3.1)months]. There were no significant differences in the operative time, intraoperative blood loss or intraoperative fluoroscopy times between the two groups ( P>0.05). According to the Matta′s radiographic criteria at 3 days after surgery, patients with anatomical reduction and satisfactory reduction accounted 6 and 5 in the plate plus raft screw group, compared to 5 and 4 respectively in the screw only group ( P>0.05). The values of Merle D′Aubigné and Postel score at 3 months after surgery and at the last follow-up were (14.0±2.4)points and (15.8±2.2)points in the plate plus raft screw group, which were higher than those in the screw only group [(11.0±2.6)points and (13.0±3.1)points] ( P<0.01). The values of Merle D′Aubigné and Postel score at the last follow-up of both groups were further enhanced from those at 3 months after surgery ( P<0.01). At the last follow-up, 3 patients were rated excellent, 6 good, 1 fair and 1 poor in the plate plus raft screw group, with an excellent and good rate of 81.8%, while in the screw only group, 3 were rated good, 2 fair and 4 poor, with an excellent and good rate of 33.3% ( P<0.05). One patient in the plate plus raft screw group and 5 in the screw only group had displacement of the dome impaction fragment combined with traumatic arthritis after surgery ( P<0.05). Conclusion:For acetabular fractures combined with dome impaction in the aged patients, the horizontal plate plus raft screw above the acetabulum can effectively improve the function restoration of the hip joint and reduce the occurrence of the displacement of the dome impaction fragment and traumatic arthritis after surgery compared to the fixation with screws only.

Objective To establish a predictive model for spinal canal labor analgesia-related in-trapartum fever and validate its predictive efficacy.Methods A total of 2 276 parturients who received labor analgesia from January to December 2021 were selected as the training set,aged≥18 years,BMI 18.5-40.0 kg/m2,ASA physical status Ⅰ or Ⅱ.The patients were divided into fever group and non-fever group according to the occurrence of intrapartum fever(body temperature≥38.0 ℃).The independent risk factors of intrapartum fever were screened by multivariate logistic regression,and the predictive model was established.A total of 568 parturients who received labor analgesia in the same hospital from January to March 2022 were selected as the verification.The inclusion criteria were the same as the training set,and the model was externally verified by R language.Results There were 197 parturients(8.7％)in the train-ing set and 46 parturients(8.1％)in the validation set experienced intrapartum fever.The multivariate lo-gistic regression analysis showed that primiparity,a high neutrophil count,anemia,and a heavier estimated fetal weight were risk factors of intrapartum fever,while a large body surface area and large cervical dilata-tion degree before labor analgesia were protective factors against intrapartum fever.According to the predic-tors,the predictive model for spinal canal labor analgesia-related maternal fever was established.The area under the receiver operating characteristic(ROC)curve(AUC)was 0.698(95％CI 0.660-0.732),the sensitivity and specificity was 83.2％and 47.9％,respectively.Using R language for the external validation,the AUC of the predictive model was 0.703(95％CI 0.634-0.772),the sensibility and specificity was 65.2％and 71.3％,respectively.The results showed that the prediction model for spinal canal labor analgesia-related intrapartum fever is effective.Conclusion Primiparity,a high neutrophil count,anemia,and a heavier estimated fetal weight were risk factors of intrapartum fever,while a large body surface area and large cervical dilatation degree before labor analgesia were protective factors.The predictive model established based on these indicators can effectively predict the occurrence of intrapartum fever before labor analgesia.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.