The Chinese Pharmacopoeia is the legal technical standard which should be followed during the research, production, use, and administration of drugs. At present, the new edition of the Chinese Pharmacopoeia is planned to be promulgated and implemented. This article summarizes and analyzes the main characteristics and the content of updates and amendments of the Chinese Pharmacopoeia 2025 Edition(Volume Ⅰ), to provide a reference for the correct understanding and accurate implementation the new edition of the pharmacopoeia.

A 20-year-old male patient presented to the Department of Dermatology of Peking Union Medical College Hospital with complaints of an 8-year history of facial scarring, swelling of the lower limbs, and a 4-year history of scalp thickening. Physical examination showed thickening furrowing wrinkling of the skin on the face and behind the ears, ciliary body hirsutism, blepharoptosis, and cutis verticis gyrate. Both lower limbs were swollen, especially the knees and ankles. The skin of the palms and soles of the feet was keratinized and thickened. Laboratory examination using bone and joint X-ray showed periostosis of the proximal middle phalanges and metacarpals of both hands, distal ulna and radius, tibia and fibula, distal femurs, and metatarsals.Genetic testing revealed two variants in SLCO2A1, c.1658T > A and c.96+4A > C.Through multidisciplinary consultation, we confirmed the diagnosis of pachydermoperiostosis.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Nucleotide-binding oligomerization domain (NOD)-like receptor protein 3 (NLRP3) is a cytosolic pattern recognition receptor that recognizes multiple pathogen-associated molecular patterns and damage-associated molecular patterns. It is a cytoplasmic immune factor that responds to cellular stress signals, and it is usually activated after infection or inflammation, forming an NLRP3 inflammasome to protect the body. Aberrant NLRP3 inflammasome activation is reportedly associated with some inflammatory diseases and metabolic diseases. Recently, there have been mounting indications that NLRP3 inflammasomes play an important role in liver injuries caused by a variety of diseases, specifically hepatic ischemia/reperfusion injury, hepatitis, and liver failure. Herein, we summarize new research pertaining to NLRP3 inflammasomes in hepatic injury, hepatitis, and liver failure. The review addresses the potential mechanisms of action of the NLRP3 inflammasome, and its regulation in these liver diseases.
Humans ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Inflammasomes/physiology* ; Animals ; Liver Diseases/metabolism* ; Liver/metabolism* ; Reperfusion Injury/metabolism*

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

PURPOSE: The rate of complications among patients undergoing surgery has increased due to infection with SARS-CoV-2 and other variants of concern. However, Omicron has shown decreased pathogenicity, raising questions about the risk of postoperative complications among patients who are infected with this variant. This study aimed to investigate complications and related factors among patients with recent Omicron infection prior to undergoing orthopedic surgery. METHODS: A historical control study was conducted. Data were collected from all patients who underwent surgery during 2 distinct periods: (1) between Dec 12, 2022 and Jan 31, 2023 (COVID-19 positive group), (2) between Dec 12, 2021 and Jan 31, 2022 (COVID-19 negative control group). The patients were at least 18 years old. Patients who received conservative treatment after admission or had high-risk diseases or special circumstances (use of anticoagulants before surgery) were excluded from the study. The study outcomes were the total complication rate and related factors. Binary logistic regression analysis was used to identify related factors, and odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the impact of COVID-19 infection on complications. RESULTS: In the analysis, a total of 847 patients who underwent surgery were included, with 275 of these patients testing positive for COVID-19 and 572 testing negative. The COVID-19-positive group had a significantly higher rate of total complications (11.27%) than the control group (4.90%, p < 0.001). After adjusting for relevant factors, the OR was 3.08 (95% CI: 1.45-6.53). Patients who were diagnosed with COVID-19 at 3-4 weeks (OR = 0.20 (95% CI: 0.06-0.59), p = 0.005), 5-6 weeks (OR = 0.16 (95% CI: 0.04-0.59), p = 0.010), or ≥7 weeks (OR = 0.26 (95% CI: 0.06-1.02), p = 0.069) prior to surgery had a lower risk of complications than those who were diagnosed at 0-2 weeks prior to surgery. Seven factors (age, indications for surgery, time of operation, time of COVID-19 diagnosis prior to surgery, C-reactive protein levels, alanine transaminase levels, and aspartate aminotransferase levels) were found to be associated with complications; thus, these factors were used to create a nomogram. CONCLUSION Omicron continues to be a significant factor in the incidence of postoperative complications among patients undergoing orthopedic surgery. By identifying the factors associated with these complications, we can determine the optimal surgical timing, provide more accurate prognostic information, and offer appropriate consultation for orthopedic surgery patients who have been infected with Omicron.
Humans ; COVID-19/complications* ; Male ; Female ; Middle Aged ; Postoperative Complications/epidemiology* ; SARS-CoV-2 ; Orthopedic Procedures/adverse effects* ; Aged ; Nomograms ; Adult ; Retrospective Studies ; Risk Factors

OBJECTIVE: To investigate the genetic causal relationship of leukocyte telomere length (LTL) with prostatitis, orchitis and epididymitis by two-sample Mendelian randomization (MR). METHODS: Using LTL as the exposure factor and prostatitis, orchitis and epididymitis as outcome factors, we mined the Database of Genome-Wide Association Studies (GWAS). Then, we analyzed the causal relationship of LTL with prostatitis, orchitis and epididymitis by Mendelian randomization using inverse variance weighting (IVW) as the main method and weighted median and MR-Egger regression as auxiliary methods, determined the horizontal multiplicity by MR-Egger intercept test, and conducted sensitivity analysis using the leaving-one-out method. RESULTS: A total of 121 related single nucleotide polymorphisms (SNPs) were identified in this study. IVW showed LTL to be a risk factor for prostatitis (OR = 1.383, 95% CI: 1.044－1.832, P = 0.024), and for orchitis and epididymitis as well (OR = 1.770, 95% CI: 1.275－2.456, P = 0.000 6). CONCLUSION Genetic evidence from Mendelian randomized analysis indicates that shortening of LTL reduces the risk of prostatitis, orchitis and epididymitis.
Humans ; Male ; Mendelian Randomization Analysis ; Epididymitis/genetics* ; Prostatitis/genetics* ; Polymorphism, Single Nucleotide ; Leukocytes ; Orchitis/genetics* ; Genome-Wide Association Study ; Telomere ; Risk Factors

OBJECTIVE: To evaluate the impact of sutureless approach to the dorsal venous complex (DVC) combined with robotic-assisted laparoscopic prostatectomy on sexual function of patients with prostatic cancer. METHODS: This study included 114 prostate cancer patients who underwent robot-assisted laparoscopic radical prostatectomy at our hospital from January 2021 to January 2024. The patients were randomly divided into a control group (n=57) and an observation group (n=57). The control group received conventional "figure-of-eight" suture ligation of the dorsal venous complex (DVC), while the observation group underwent direct DVC transection using monopolar electrocautery scissors after increasing pneumoperitoneum pressure.Surgical duration, intraoperative blood loss, positive surgical margin rates, and positive apical margin rates were recorded. The continence rates and rates of morning erections at 1, 3 and 6 months after the operation were compared between groups. Sexual function was assessed pre-operatively and at 6 months post-operation by using the IIEF-5 and PEDT. RESULTS: The operative time in the observation group was significantly longer than that in the control group (［115.71 ± 19.42］ min vs ［103.42 ± 12.78］ min， P<0.05). While no significant differences were observed in intraoperative blood loss, positive surgical margin rate, or positive apical margin rate between the two groups (P>0.05). At 3 and 6 months after the operation, the observation group exhibited higher urinary continence rates and morning erection recovery rates compared to the control group （P<0.05). Furthermore, at 6 months postoperatively, the observation group demonstrated significantly higher IIEF-5 scores and lower PEDT scores than those of control group(P<0.05). CONCLUSION The use of a sutureless DVC technique in robotic-assisted laparoscopic radical prostatectomy protects the post-operative sexual function in patients.
Humans ; Male ; Prostatectomy/methods* ; Laparoscopy/methods* ; Prostatic Neoplasms/surgery* ; Robotic Surgical Procedures/methods* ; Middle Aged ; Operative Time ; Aged

OBJECTIVE: To compare the differences of plasma valine level between autistic and healthy children, and to explore the relationship between plasma valine level and developmental quotient in children with autism. METHODS: In this study, a total of 29 autistic children and 30 typically developing children of the same age range were recruited as the autistic group and the control group. The childhood autism rating scale (CARS) was used to assess autistic core symptoms and severity in the autistic children. Children's developmental quotient was evaluated by Gesell developmental schedules (GDS), and plasma valine level was measured by high performance liquid chromatography-tandem mass spectrometry. The correlation between plasma valine level and developmental quotient scores in the autistic group was analyzed. RESULTS: The plasma level of valine in the autism group was significantly lower than in the control group (P < 0.05). Children in the autism group got significantly lower scores in the adaption, gross motor, fine motor, language function and personal/social function subscales in GDS than in the control group (P < 0.000 1). Plasma valine level in the autism group showed significant positive correlations with scores of the fine motor (r=0.441, P < 0.05) and personal/social function (r=0.437, P < 0.05) subscales in GDS, but showed no significant correlations with scores of the adaption, gross motor and language function subscales in GDS (P>0.05). According to the criteria of CARS, children in the autism group were subdivided into the mild to moderate subgroup and the severe subgroup based on the severity of the autistic symptoms. Compared with children in the mild to moderate subgroup, children in the severe subgroup got significantly lower scores in the adaption, fine motor, language function and personal/social function subscales in GDS (P < 0.05), while there was no significant difference between the two subgroups in gross motor scores and plasma valine level (P>0.05). CONCLUSION The level of valine in plasma of autistic children is relatively lower, and there is a certain relationship between plasma valine level and the fine movement and personal/social function among children with autism.
Humans ; Autistic Disorder/physiopathology* ; Child ; Male ; Female ; Valine/blood* ; Child Development ; Child, Preschool ; Case-Control Studies

BACKGROUND: Blood glucose and serum albumin have been associated with cardiovascular disease prognosis, but the impact of admission-blood-glucose-to-albumin ratio (AAR) on adverse outcomes in critical ill coronary artery disease (CAD) patients was not investigated. METHODS: Patients diagnosed with CAD were non-consecutively selected from the MIMIC-IV database and categorized into quartiles based on their AAR. The primary outcome was 1-year mortality, and secondary endpoints were in-hospital mortality, acute kidney injury (AKI), and renal replacement therapy (RRT). A restricted cubic splines model and Cox proportional hazard models assessed the association between AAR and adverse outcomes in CAD patients. Kaplan-Meier survival analysis determined differences in endpoints across subgroups. RESULTS: A total of 8360 patients were included. There were 726 patients (8.7%) died in the hospital and 1944 patients (23%) died at 1 year. The incidence of AKI and RRT was 63% and 4.3%, respectively. High AAR was markedly associated with in-hospital mortality (HR = 1.587, P = 0.003), 1-year mortality (HR = 1.502, P < 0.001), AKI incidence (HR = 1.579, P < 0.001), and RRT (HR = 1.640, P < 0.016) in CAD patients in the completely adjusted Cox proportional hazard model. Kaplan-Meier survival analysis noted substantial differences in all endpoints based on AAR quartiles. Stratified analysis and interaction test demonstrated stable correlations between AAR and outcomes. CONCLUSIONS The results highlight that AAR may be a potential indicator for assessing in-hospital mortality, 1-year mortality, and adverse renal prognosis in critical CAD patients.