Objective:This study aims to analyze the performance of five automatic cell type annotation methods in single cell RNA sequencing (scRNA-seq) data.Methods:Simulated data were generated using the Splatter package in R language, taking into account two data characteristics: the number of cells and the number of genes. The actual data came from the GSE10245 scRNA seq dataset of non-small cell lung cancer in Gene Expression Omnibus (GEO) database, the data had been pre-processed and batch effects had been eliminated. The automatic cell type recognition (ACTINN) of neural networks, the single-cell type annotation method based on deep learning (scDeepSort), the reference batch transcriptome annotation scRNA seq R-package (SingleR), the cross platform and cross species scRNA seq data classifier (SingleCellNet), and the cross scRNA seq dataset projection (scMap-cell) were implemented using the Tensorflow library in Python. The performance evaluation indicators for cell type annotation included accuracy (ACC), F1-score, and Matthews correlation coefficient (MCC). Each method was validated using ten fold cross validation, and the average value was taken after 50 repeated runs for performance comparison between methods. The Dunnett's t-test in the DescTools package of R language was used for multiple comparisons between ACTINN and other four methods. Results:Under 12 different scenarios (3 levels of cell numbers × 4 levels of gene numbers), simulated data analysis showed that compared with scDeepSort, SingleR, SingleCellNet, and scMap-cell, the percentage increase in ACC value of ACTINN ranged from 3.31% to 14.59%, 1.38% to 13.03%, 12.98% to 25.25%, and 20.72% to 29.62%, respectively; the range of F1 score improvement percentages were 2.75% - 22.74%, 2.46% - 23.68%, 5.07% - 27.47%, and 10.27% - 31.47%, respectively; the percentage increase ranges for MCC values were 3.42% - 9.75%, 2.26% - 7.61%, 5.41% - 11.11%, and 8.27% - 15.22%, respectively. Actual data analysis showed that the ACC value of ACTINN was 81.0%, which was increased by 2.1%, 5.2%, 7.9%, and 8.9% compared with the above four methods, respectively; the F1-score value was 80.5%, which was increased by 2.3%, 5.9%, 2.4%, and 6.0%, respectively; the MCC value was 83.3%, which was increased by 0.9%, 2.5%, 3.4%, and 11.2%, respectively. The results of Dunnett's t-test showed that the difference was not statistically significant in ACC values between scDeepSort and ACTINN ( P = 0.821), in F1-score values between scDeepSort and ACTINN ( P = 0.498), and in MCC values between scDeepSort, SingleCellNet and ACTINN ( P = 0.904, 0.134). However, the differences were statistically significant in other multiple comparisons ( P < 0.05). Conclusions:ACTINN and scDeepSort have good performance in cell type annotation, with ACTINN showing outstanding performance and SingleR showing robust performance, while SingleCellNet and scMap-cell have relatively limited performance. This suggests that self-attention mechanism algorithm based on Transformer framework is expected to promote further development of automatic cell annotation methods.

Objective: This study aims to investigate the therapeutic effects and underlying mechanisms of Xuanfei Baidu Decoction (XFBD) in a mouse model of dampness-heat toxin pneumonia. By exploring how XFBD exerts its effects, we seek to deepen our understanding of its role in treating pulmonary diseases and to address the current knowledge gap regarding its mechanisms of action, thereby supporting its clinical application. Methods: Ultra-high-performance liquid chromatography and high-resolution mass spectrometry (HRMS) were employed to analyze the chemical constituents of XFBD. The protective effects of XFBD were evaluated using a dampness-heat toxin-induced mouse model, established through dampness-heat exposure and HCoV-229E infection. XFBD was administered orally, followed by assessments including lung index measurement, micro-CT imaging, viral load quantification, cytokine analysis, and histological evaluation via hematoxylin-eosin staining. Proteomics and single-cell transcriptomic analyses were conducted to explore the potential mechanisms underlying XFBD’s pharmacological effects. A cellular model of HCoV-229E infection was developed to investigate changes in the cAMP/PKA signaling pathway. Molecular docking and surface plasmon resonance (SPR) experiments confirmed the strong binding affinity between key XFBD components and PKA. Finally, PKA activators and inhibitors were applied in vitro to validate these mechanistic findings. Results: In vivo studies demonstrated that XFBD significantly reduced the lung index, improved the structural integrity of lung and tongue tissues, and decreased levels of proinflammatory mediators, including IL-6, IL-8, and TNF-α. Proteomic and single-cell transcriptomic analyses showed that the differentially expressed proteins after XFBD treatment were primarily associated with inflammatory responses and immune regulation. The cAMP/PKA signaling pathway was identified as a key mechanism underlying these therapeutic effects. Notably, Western blot, ELISA, molecular docking, and SPR analyses confirmed that XFBD elevated cAMP levels and p-PKA expression, thereby activating the cAMP/PKA signaling pathway in vitro. Conclusion: This study demonstrated that XFBD significantly alleviates symptoms in mice with dampness-heat toxin pneumonia. Its therapeutic effects are mediated, at least in part, through activation of the cAMP/PKA signaling pathway. These findings provide compelling evidence that XFBD is an effective herbal remedy against HCoV-229E infection.

Objective:This study aims to analyze the performance of five automatic cell type annotation methods in single cell RNA sequencing (scRNA-seq) data.Methods:Simulated data were generated using the Splatter package in R language, taking into account two data characteristics: the number of cells and the number of genes. The actual data came from the GSE10245 scRNA seq dataset of non-small cell lung cancer in Gene Expression Omnibus (GEO) database, the data had been pre-processed and batch effects had been eliminated. The automatic cell type recognition (ACTINN) of neural networks, the single-cell type annotation method based on deep learning (scDeepSort), the reference batch transcriptome annotation scRNA seq R-package (SingleR), the cross platform and cross species scRNA seq data classifier (SingleCellNet), and the cross scRNA seq dataset projection (scMap-cell) were implemented using the Tensorflow library in Python. The performance evaluation indicators for cell type annotation included accuracy (ACC), F1-score, and Matthews correlation coefficient (MCC). Each method was validated using ten fold cross validation, and the average value was taken after 50 repeated runs for performance comparison between methods. The Dunnett's t-test in the DescTools package of R language was used for multiple comparisons between ACTINN and other four methods. Results:Under 12 different scenarios (3 levels of cell numbers × 4 levels of gene numbers), simulated data analysis showed that compared with scDeepSort, SingleR, SingleCellNet, and scMap-cell, the percentage increase in ACC value of ACTINN ranged from 3.31% to 14.59%, 1.38% to 13.03%, 12.98% to 25.25%, and 20.72% to 29.62%, respectively; the range of F1 score improvement percentages were 2.75% - 22.74%, 2.46% - 23.68%, 5.07% - 27.47%, and 10.27% - 31.47%, respectively; the percentage increase ranges for MCC values were 3.42% - 9.75%, 2.26% - 7.61%, 5.41% - 11.11%, and 8.27% - 15.22%, respectively. Actual data analysis showed that the ACC value of ACTINN was 81.0%, which was increased by 2.1%, 5.2%, 7.9%, and 8.9% compared with the above four methods, respectively; the F1-score value was 80.5%, which was increased by 2.3%, 5.9%, 2.4%, and 6.0%, respectively; the MCC value was 83.3%, which was increased by 0.9%, 2.5%, 3.4%, and 11.2%, respectively. The results of Dunnett's t-test showed that the difference was not statistically significant in ACC values between scDeepSort and ACTINN ( P = 0.821), in F1-score values between scDeepSort and ACTINN ( P = 0.498), and in MCC values between scDeepSort, SingleCellNet and ACTINN ( P = 0.904, 0.134). However, the differences were statistically significant in other multiple comparisons ( P < 0.05). Conclusions:ACTINN and scDeepSort have good performance in cell type annotation, with ACTINN showing outstanding performance and SingleR showing robust performance, while SingleCellNet and scMap-cell have relatively limited performance. This suggests that self-attention mechanism algorithm based on Transformer framework is expected to promote further development of automatic cell annotation methods.

ObjectiveTo evaluate the effectiveness of Lutongning granules in the treatment of trigeminal neuralgia in animal models and study its mechanism of action， so as to provide laboratory data support for the clinical application of Lutongning granules and precise treatment. MethodMale SD rats were randomly divided into normal group， model group， carbamazepine group （0.06 g·kg^-1·d^-1）， high-dose Lutongning group （2.70 g·kg^-1·d^-1）， and low-dose Lutongning group （1.35 g·kg^-1·d^-1） according to the stratified basic mechanical pain thresholds， with 10 rats in each group. A trigeminal neuralgia model of rats was prepared by injecting 30% talc suspension into the infraorbital foramen area of the rat. The drug groups were administered 10 mL·kg^-1 of drugs by gavage after 2 h of modeling. The normal group and the model group were administered distilled water by gavage under the same conditions once a day for 10 consecutive days. Von Frey brushes were used to determine the mechanical pain threshold of rats. A fully automated blood and body fluid analyzer was employed to detect the blood routine of rats. Hematoxylin and eosin （HE） staining was utilized to detect the pathological changes in the trigeminal ganglion and medulla oblongata tissue. Transmission electron microscopy was used to scan the ultrastructure of the medulla oblongata tissue. Enzyme-linked immunosorbent assay （ELISA） was used to detect the levels of inflammatory factors interleukin （IL）-1， IL-6， IL-8， tumor necrosis factor （TNF）-α， neuropeptide substance P， and β-endorphins （β-EP） in the serum of rats， and Western blot was used to detect the protein expression levels of IL-1β， purinergic receptor P2X7 （P2X7R）， and phosphorylated p38 mitogen-activated protein kinase （p-p38 MAPK）. ResultCompared with that in the normal group， the pain threshold of rats in the model group was significantly lower （P<0.01）. The absolute value of neutrophils （NEUT#） and the percentage of neutrophils （NEUT） were significantly improved， and the percentage of lymphocytes （LYMPH） was significantly reduced （P<0.01）. The serum levels of IL-1， IL-6， IL-8， and TNF-α were significantly increased （P<0.01）. SP content in brain tissue was significantly increased， and β-EP content was significantly decreased （P<0.01）. The relative protein expression of IL-1β， P2X7R， and p-p38 MAPK was significantly increased （P<0.05）. HE staining and transmission electron microscopy results of medulla oblongata tissue revealed neuronal degeneration， mild proliferation of microglial cells， reduction in the number of myelinated nerves， and obvious demyelination. The trigeminal nerve fibers of rats were disarranged， and some nerve fibers showed vacuolization. Axons were swollen， and Schwann cells proliferated. Demyelination was observed. Compared with the model group， each administration group significantly increased the pain threshold of rats （P<0.05， P<0.01）， reduced NEUT# and NEUT， and elevated LYMPH （P<0.05， P<0.01）. The administration group significantly decreased the levels of IL-1， IL-6， IL-8， and TNF-α in serum and SP in brain tissue （P<0.01） and increased the level of β-EP （P<0.01）. They significantly down-regulated the protein expression of IL-1β， P2X7R， and p-p38 MAPK（P<0.05， P<0.01） and significantly ameliorated the pathological changes in medulla oblongata tissue and trigeminal nerves of rats. ConclusionLutongning Granules had significant therapeutic effects on trigeminal neuralgia induced by injection of talc into the infraorbital foramen of model rats， and the mechanism may be related to amelioration of P2X7R-mediated neuroinflammation and inhibition of demyelination of myelinated nerves.

Based on the International Federation of Nursing Anesthetists (IFNA) education and training base, our hospital has built a training base for anesthesia specialized nurses in Nanjing from the following aspects: the application for training base of anesthesia specialized nurses, the qualification and examination of students' and teachers' qualification, the settings of training curriculum, the examination contents and methods, and the evaluation of post-training effect. This article summarizes the construction experience of this base, therefore, providing support and standard for the training of anesthesia specialized nurses.

Objective:To investigate the association between blood lead concentrations and cognition impairment among Chinese older adults aged 65 or over.Method:Data was collected in 9 longevity areas from Heathy Aging and Biomarkers Cohort Study between 2017 and 2018. This study included 1 684 elderly aged 65 years and older. Information about demographic characteristics, socioeconomic factors, health status and cognitive function score of respondents were collected by questionnaire survey and physical examination. Venous blood of the subjects was collected to detect the blood lead concentration. Subjects were stratified into four groups ( Q 1- Q 4) by quartile of blood lead concentration. Multivariate logistic regression model was used to analyze the association between blood lead concentration and cognitive impairment. The linear or non-linear association between blood lead concentration and cognitive impairment were described by restrictive cubic splines (RCS). Results:Among the 1 684 respondents, 843 (50.1%) were female and 191 (11.3%) suffered from cognition impairment. After adjusting for confounding factors, the OR value and 95% CI of cognition impairment was 1.05 (1.01-1.10) for every 10 μg/L increase in blood lead concentration in elderly; Compared with the elderly in Q 1, the elderly with higher blood lead concentration had an increased risk of cognitive impairment. The OR value and 95% CIof Q2, Q3 and Q4 groups were 1.19 (0.69-2.05), 1.45 (0.84-2.51) and 1.92 (1.13-3.27), respectively. Conclusion:Higher blood lead concentration is associated with cognitive impairment among the elderly aged 65 years and older in 9 longevity areas in China.

Objective:To investigate the association between blood lead concentrations and cognition impairment among Chinese older adults aged 65 or over.Method:Data was collected in 9 longevity areas from Heathy Aging and Biomarkers Cohort Study between 2017 and 2018. This study included 1 684 elderly aged 65 years and older. Information about demographic characteristics, socioeconomic factors, health status and cognitive function score of respondents were collected by questionnaire survey and physical examination. Venous blood of the subjects was collected to detect the blood lead concentration. Subjects were stratified into four groups ( Q 1- Q 4) by quartile of blood lead concentration. Multivariate logistic regression model was used to analyze the association between blood lead concentration and cognitive impairment. The linear or non-linear association between blood lead concentration and cognitive impairment were described by restrictive cubic splines (RCS). Results:Among the 1 684 respondents, 843 (50.1%) were female and 191 (11.3%) suffered from cognition impairment. After adjusting for confounding factors, the OR value and 95% CI of cognition impairment was 1.05 (1.01-1.10) for every 10 μg/L increase in blood lead concentration in elderly; Compared with the elderly in Q 1, the elderly with higher blood lead concentration had an increased risk of cognitive impairment. The OR value and 95% CIof Q2, Q3 and Q4 groups were 1.19 (0.69-2.05), 1.45 (0.84-2.51) and 1.92 (1.13-3.27), respectively. Conclusion:Higher blood lead concentration is associated with cognitive impairment among the elderly aged 65 years and older in 9 longevity areas in China.

OBJECTIVE：To systematically evaluate the effects of CYP1A2 gene polymorphisms on blood concentrations of antipsychotic drugs （haloperidol，clozapine，olanzapine），and to provide evidence-based reference for the clinical drug use . METHODS：Retrieved from Cochrane Library ，PubMed，Embase，CBM，CNKI and Wanfang data ，during the inception to Nov. 2019，cross-sectional study was conducted to investigate the effects of CYP1A2 gene polymorphisms on blood concentrations of antipsychotic drugs （haloperidol，clozapine，olanzapine）were collected. After screening the literature ，extracting the data and quality evaluation with Q-Genie tool ，Meta-analysis was performed by using Rev Man 5.3 software. RESULTS ：A total of 11 cross-sectional studies were included ，with a total of 914 patients. Of these ，haloperidol was used in 2 studies，clozapine was used in 5 studies，and olanzapine was used in 4 studies. Meta-analysis showed that there was no statistically significant difference in the blood concentration of haloperidol between CYP1A2（－2964G＞A）G/G type and G/A+A/A type [SMD ＝－0.22，95％CI（－0.66， 0.23），P＝0.35]. The blood concentration of clozapine in CYP1A2（－163C＞A）A/C type was significantly lower than C/C type [SMD ＝0.31，95％CI（0.01，0.62），P＝0.04]；there was no statistical significance in blood concentration of clozapine between A/A type and C/C type [SMD ＝0.09，95％CI（－0.21，0.40），P＝0.56]，between A/A type and A/C type [SMD ＝－0.22，95％CI（－0.55， 0.10），P＝0.18]，between CYP1A2（－2467delT）delT/delT type and T/T type [SMD ＝－0.11，95％CI（－0.75，0.52），P＝0.72]， between delT/T type and T/T type [SMD ＝0.01，95％CI（－0.33，0.34），P＝0.97]，between delT/delT type and delT/T type [SMD ＝ －0.15，95％CI（－0.80，0.05），P＝0.66]. The blood concentration of olanzapine in CYP1A2（－163C＞A）A/A type was signifi- cantly lower than A/C type [SMD ＝－0.31，95％CI（－0.55， － 0.08），P＝0.009]；there was no statistically significant difference in the blood concentration of olanzapine between A/A liukefeng-num.1@163.com type and C/C type [SMD ＝－0.20，95％CI（－0.61，0.21），P＝ 0.34]，between A/C type and C/C type [SMD ＝0.06，95％CI E-mail：hnmuzj@163.com （－0.35，0.47），P＝0.77]，between CYP1A2（－2467delT）delT/T type and T/T type [SMD ＝0.28，95％CI（－0.15，0.71），P＝0.20]. CONCLUSIONS：CYP1A2（－163C＞A）A/C type is related to the reduction of clozapine blood concentration ，and A/A type is related to the reduction of olanzapine blood concentration. CYP1A2 （－163C＞A）gene polymorphism is significance for guiding individualized medication of schizophrenia patients.

Objective: To study the segment of liver according to the large amount of three-dimensional(3D) reconstructive images of normal human livers and the vascular system, and to recognize the basic functional liver unit based on the anatomic features of the intrahepatic portal veins. Methods: The enhanced CT primitive DICOM files of 1 260 normal human livers from different age groups who treated from October 2013 to February 2017 provided by 16 hospitals were analyzed using the computer-aided surgery system.The 3D liver and liver vascular system were reconstructed, and the digital liver 3D model was established.The vascular morphology, anatomical features, and anatomical distributions of intrahepatic portal veins were statistically analyzed. Results: The digital liver model obtained from the 3D reconstruction of CAS displayed clear intrahepatic portal vein vessels of level four.Perform a digital liver segments study based on the analysis of level four vascular distribution areas.As the less anatomical variation of left hepatic portal vein, the liver was classified into four types of liver segmentation mainly based on right hepatic portal vein.Type A was similar to Couinaud or Cho′s segmentation, containing 8 segments(537 cases, 42.62%). Type B contained 9 segments as there are three ramifications of right-anterior portal vein(464 cases, 36.82%). The main difference for Type C was the variation of right-posterior portal vein which was sector shape(102 cases, 8.10%). Type D contained the cases with special portal vein variations, which needs three-dimensional simulation to design individualized liver resection plan(157 cases, 12.46%). These results showed that there was no significant difference in liver segmental typing between genders(χ²=2.179, P=0.536) and did not reveal any significant difference in liver segmental typing among the different age groups(χ²=0.357, P=0.949). Conclusions The 3D digital liver model can demonstrate the true 3D anatomical structures, and its spatial vascular variations.The observation of anatomic features, distribution areas of intrahepatic portal veins and individualized liver segmentation achieved via digital medical 3D visualization technology is of great value for understand the complexity of liver anatomy and to guide the precise hepatectomy.

Objective To investigate and analysis the actuality and demands of scientific researchers in state clinical research facility of TCM, in order to provide evidences for policy making. Methods All the trainees taken part in the meeting for the training of clinical research method were assigned to answer the self-designed questionnaire. Results Of all these people, 47.58 percent people had senior professional title, 84.14 percent people had doctorate or master degree, 57.24 percent people had participated in project research at provincial or ministerial level as key personnel, 35.17 percent people had participated in a key disease research as directors, 65.52 percent people had taken methodology training of clinical research,30.34% of who trained by evidence-based medicine. The majority of these people had clear understanding in methodology of clinical research, who believed that evidence-based medicine and system evaluation are the most difficult subjects to understand and practice, hoping to learn more about the knowledge on statistics. Conclusion Clinical researchers of state clinical research facility of TCM had sound basis for scientific research, but relatively lacking of key disease research and systematic knowledge of scientific methodology, which needed to be enhanced.