Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

General anesthesia, pivotal for surgical procedures, requires precise depth monitoring to mitigate risks ranging from intraoperative awareness to postoperative cognitive impairments. Traditional assessment methods, relying on physiological indicators or behavioral responses, fall short of accurately capturing the nuanced states of unconsciousness. This study introduces a machine learning-based approach to decode anesthesia depth, leveraging EEG data across different anesthesia states induced by propofol and esketamine in rats. Our findings demonstrate the model's robust predictive accuracy, underscored by a novel intra-subject dataset partitioning and a 5-fold cross-validation method. The research diverges from conventional monitoring by utilizing anesthetic infusion rates as objective indicators of anesthesia states, highlighting distinct EEG patterns and enhancing prediction accuracy. Moreover, the model's ability to generalize across individuals suggests its potential for broad clinical application, distinguishing between anesthetic agents and their depths. Despite relying on rat EEG data, which poses questions about real-world applicability, our approach marks a significant advance in anesthesia monitoring.
Animals ; Machine Learning ; Electroencephalography/methods* ; Ketamine/administration & dosage* ; Rats ; Male ; Propofol/administration & dosage* ; Rats, Sprague-Dawley ; Anesthesia, General/methods* ; Brain/physiology* ; Intraoperative Neurophysiological Monitoring/methods*

Myeloproliferative neoplasms(MPN)are a group of malignant myeloid tumors caused by hematopoietic stem cell proliferation.The discovery of gene mutations has elucidated the pathogenesis of MPN and provided molecular diagnostic criteria for MPN.Recent studies have shown that there are cytokine disorders in MPN patients,and the changes in the microenvironment caused by these cytokine disorders may have great significance for the pathophysiology and pathogenesis of MPN,which may lead to corresponding clinical symptoms and different prognosis in patients.In this review,the latest research progress on the role and status of cytokines in MPN will be summarized.

Objective To understand the infectious pathogen characteristics and drug sensitivity of hospitalized patients in the respiratory intensive care unit (RICU) of Renmin Hospital of Wuhan University. Methods Bacterial culture samples sent to the RICU of our hospital from January 2020 to December 2022 were retrospectively analyzed. The bacterial types were identified by Bruker mass spectrometer, and the Phoenix 100 was used for drug sensitivity analysis. The antimicrobial susceptibility was analyzed by WHONET 5.6 software. Results A total of 1 157 strains of bacteria were isolated, including 878 strains of Gram-negative bacteria (75.89%) and 279 strains of Gram-positive bacteria (24.11%). The top five with the highest detection rate were Acinetobacter baumannii (25.50%), Pseudomonas aeruginosa (18.76%), Klebsiella pneumoniae (13.83%), Staphylococcus aureus (6.57%) and Escherichia coli (5.70%). Among them, Acinetobacter baumannii was extremely drug-resistant, only showing relatively high sensitivity to colistin, minocycline, and tigecycline. Staphylococcus aureus accounted for the highest proportion of Gram-positive bacteria (6.57%), with methicillin-resistant Staphylococcus (MRSA) showing a continuous increase. Conclusion In the past three years, Gram-negative bacteria have been the main pathogenic bacteria detected in the respiratory intensive care unit of our hospital. The main bacteria are Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae, which have a high resistance rate to various antibiotics. Therefore, clinical monitoring of resistant strains in RICU should be strengthened to facilitate rational use of antibiotics and improve antibacterial effect.

The purpose of this study was to enrich the genomic information and provide a basis for further development and utilization of Polygonatum kingianum. The fresh rhizome of P. kingianum was used as the experimental material, and the full-length transcriptome was sequenced by PacBio Sequel platform. The final measured polymerase reads were 1 120 485, with a total of 77.73 GB of data. In NR database, 41 864 homologous sequence alignments were aligned to 5 species; 40 506 were annotated in the KOG database and classified into 26 categories based on their functionality; 69 060 GO annotated 32 functional groups divided into 3 categories: cellular components, molecular functions, and biological processes; 45 779 annotations were added to 145 metabolic pathways in the KEGG database. Among them, there are 127 identified transcripts related to polysaccharide synthesis in the glycolysis/gluconeogenesis metabolic pathway, 144 in the starch and sucrose metabolic pathway, 85 in the amino acid sugar and nucleotide sugar metabolic pathway, and 69 in the fructose and mannose metabolic pathway. In addition, 1 781 transcription factors were detected, distributed in 37 transcription factor families; 180 293 SSR loci were detected, among which single base repeats accounted for the most, accounting for 30.48% of all base repeats, and at least five base repeats, accounting for only 0.14% of single base repeats. The results of this study provide important data supporting for enriching the genomic information of P. kingianum and exploring its effective biosynthetic pathway.

Objective:To investigated the safety and efficacy of donor-derived CD19+ or sequential CD19+ CD22+ chimeric antigen receptor T-cell (CAR-T) therapy in patients with B-cell acute lymphoblastic leukemia (B-ALL) after allogeneic hematopoietic stem cell transplantation (allo-HSCT).Methods:The data of 22 patients with B-ALL who relapsed after allo-HSCT and who underwent donor-derived CAR-T therapy at the Zhujiang Hospital of Southern Medical University and the 920th Hospital of Joint Logistics Support Force of the People’s Liberation Army of China from September 2015 to December 2022 were retrospectively analyzed. The primary endpoint was overall survival (OS), and the secondary endpoints were event-free survival (EFS), complete remission (CR) rate, and Grade 3-4 adverse events.Results:A total of 81.82% ( n=18) of the 22 patients achieved minimal residual disease-negative CR after CAR-T infusion. The median follow-up time was 1037 (95% CI 546–1509) days, and the median OS and EFS were 287 (95% CI 132-441) days and 212 (95% CI 120-303) days, respectively. The 6-month OS and EFS rates were 67.90% (95% CI 48.30%-84.50%) and 58.70% (95% CI 37.92%-79.48%), respectively, and the 1-year OS and EFS rates were 41.10% (95% CI 19.15%-63.05%) and 34.30% (95% CI 13.92%-54.68%), respectively. Grade 1-2 cytokine release syndrome occurred in 36.36% ( n=8) of the patients, and grade 3-4 occurred in 13.64% of the patients ( n=3). Grade 2 and 4 graft-versus-host disease occurred in two patients. Conclusion:Donor-derived CAR-T therapy is safe and effective in patients with relapsed B-ALL after allo-HSCT.

Objective To understand the current situation of protective mask wearing behavior of health care workers(HCWs),analyze the influencing factors for the failure to wear medical protective masks in a standard manner,and provide basis for the improvement of mask-wearing related training.Methods From June 2022 to March 2023,staff in a tertiary first-class hospital were selected as the research object.Real-time quantitative fitness testing using aerosol condensation particle counting method was applied to test 5 commonly used medical protective masks available in the market.Fitness factor changes of the testing instrument and assistance from professional per-sonnel were needed to comprehensively estimate the wearing condition of medical protective masks.Participants were surveyed through a self-made general information questionnaire.Heads and faces of participants were scanned by three-dimensional(3D)laser scanning technology,and scanned images were imported into Geomagic Studio 2013 software to measure head and face dimensions.Results A total of 222 HCWs were investigated,991 real-time tests and 208 times of 3D scanning were conducted.221(22.30％)tests showed failure of participants in wearing masks in a standard manner.The non-standard wearing rates of 5 types of medical protective masks were 30.56％,25.62％,25.87％,23.15％,and 7.35％,respectively.The non-standard mask-wearing rates showed statistically significant difference between groups categorized in terms of medical protective masks with different shapes,partici-pants'occupation,time of last training for wearing medical protective masks,and participants'experience in pre-vention and control of respiratory infectious disease(all P＜0.05).There were no statistically significant differences in non-standard mask-wearing rate between groups with different brands and sizes of medical protective masks,as well as gender and department of participants,etc.(all P＞0.05).The body mass index(BMI)was significantly different among participants who wear foldable medical protective masks in the standard and non-standard manner(both P＜0.05).Conclusion Wearing medical protective masks by HCWs in a non-standard manner is influenced by multiple factors.It is recommended to conduct real-time testing before formal quantitative fitness testing,so as to save time and improve testing efficiency.When conducting training on wearing medical protective masks in the fu-ture,targeted training should be provided based on mask shape and focus on logistics personnel,interns,individuals with high BMI,those who have never received training on wearing medical protective masks,and those who have never participated in the prevention and treatment of respiratory infectious diseases.

Objective:To estimate tissue/organ doses and effective dose to operators in the overexposure incident during an interventional procedure using Monte Carlo method.Methods:The phantoms were constructed for both the operators and the patient based on the adult mesh-type reference computational phantoms (MRCPs) recommended by the International Commission on Radiological Protection (ICRP) Publication 145 and phantom deformation technology. Models of exposure scenario were constructed based on the on-site equipment and the irradiation conditions. The Monte Carlod simulation method was used to evaluate the absorbed dose to critical tissues and organs, such as the operator′s eye lens and thyroid, as well as the effective dose.Results:In the particular exposure conditions, the maximum absorbed doses in the primary organs of the two operators were in the left eye lens, with doses of 1.216 and 0.223 mGy, respectively. The thyroid absorbed doses were 0.074 and 0.019 mGy, while the effective doses to the two operators were 0.088 and 0.021 mSv, respectively. The reduction rates of effective dose for the two operators when wearing lead aprons and lead thyroid collars were 67.16% and 78.79%, respectively.Conclusions:The combination of Monte Carlo method and MRCPs can be used to restore a specific irradiation scenario to a high degree and to estimate the physical dose of to the irradiated persons.

Liver size is regulated by circadian clock and exhibits a diurnal rhythm. Pregnane X receptor (PXR) and peroxisome proliferator-activated receptor α (PPARα), members of nuclear receptor superfamily, are important regulators of liver size. We previously demonstrated that mPXR agonist pregnenolone 16α-carbonitrile (PCN) and mPPARα agonist pirinixic acid (WY-14643) promoted liver enlargement and liver regeneration after partial hepatectomy. However, whether PXR or PPARα activation-induced liver enlargement exhibits diurnal rhythm with normal liver diurnal oscillations remains unclear. The aim of this study was to investigate the diurnal rhythm of PXR or PPARα activation-induced liver enlargement. Male C57BL/6 mice were intraperitoneally injected with corn oil, PCN or WY-14643 for three days, and liver samples were weighed and collected at various time points for analysis. The animal experiment protocol was reviewed and approved by Institutional Animal Care and Use Committee of Sun Yat-sen University (approval No. SYSU-IACUC-2023-001613, SYSU-IACUC-2023-001783). The results showed that PXR or PPARα activation at various time points significantly induced liver enlargement, and liver size maintained normal diurnal oscillations during PXR or PPARα activation-induced hepatomegaly, without significant effects on the expression of core clock genes. This study reveals PXR or PPARα activation-induced liver enlargement exhibits diurnal rhythm with normal liver diurnal oscillations, and provides novel data for nuclear receptor-induced liver enlargement and liver diurnal rhythm.