ObjectiveTo investigate the status of tooth loss in people aged 50 and above, so as to understand their oral health status and provide scientific evidences for promoting oral health of middle-aged and elderly people. MethodsA total of 400 patients who visited the department of stomatology at Sijing Hospital in Songjiang District of Shanghai were performed oral health examinations and their information was collected according to the national epidemiological survey standards for oral health. ResultsThere were statistically significant differences in tooth loss among people aged 50 and above with different ages, educational levels, occupations, types of medical insurance and chronic diseases (P<0.05), but gender and monthly income had no statistically significant correlations with tooth loss (P>0.05). Among lifestyle factors, smoking, alcohol consumption and tea drinking had no statistically significant impacts on the number of remaining teeth (P>0.05), but toothbrushing frequency, flossing frequency, toothpick use frequency, toothbrush replacement frequency, and tooth loosening were statistically associated with the number of remaining teeth (P<0.05). Multiple linear regression analyses indicated that a total of 7 related factors including age, educational level, occupation, medical payment type, chronic disease, tooth loosening and toothpick use frequency were significantly associated with the number level of remaining teeth in individuals aged 50 and above. ConclusionAge, chronic disease, and tooth loosening were influencing factors affecting the number of teeth left in people aged 50 and above. It is recommended to strengthen oral health education and improve healthcare awareness to reduce the risk of tooth loss in people aged 50 and above.

OBJECTIVE To analyze the compositional differences between Fructus Tritici Levis and Triticum aestivum， and to provide reference for identification and quality control of both. METHODS Twenty batches of Fructus Tritici Levis and three batches of T. aestivum were collected， and their fingerprints were acquired by high-performance liquid chromatography and the similarities were evaluated by the Evaluation System of Similarity of Chromatographic Fingerprints of Traditional Chinese Medicine （2012 version）. Cluster analysis （CA）， principal component analysis （PCA） and orthogonal partial least squares-discriminant analysis （OPLS-DA） were performed to analyze the difference of Fructus Tritici Levis and T. aestivum from different regions， and the differential components were screened. The contents of the six identified components in Fructus Tritici Levis and T. aestivum were determined. RESULTS The similarities of the fingerprints of Fructus Tritici Levis ranged from 0.928 to 0.996， and the relative similarities of T. aestivum with Fructus Tritici Levis ranged from 0.761 to 0.773. A total of 19 common peaks were calibrated， and six components including linolenic acid， linoleic acid， 5-heptadecylresorcinol， 5-nonadodecylresorcinol， 5- heneicosylresorcinol， and 5-tricosylresorcinol were identified. The results of CA and PCA showed that Fructus Tritici Levis and T. aestivum could be clearly distinguished； the distribution of Fructus Tritici Levis from Anhui province was relatively concentrated. The results of OPLS-DA showed that linolenic acid， linoleic acid， and other six unknown compounds were the differential components between Fructus Tritici Levis and T. aestivum. The average contents of the six identified components in Fructus Tritici Levis were 0.100 9， 1.094 0， 0.005 1， 0.030 9， 0.098 2，and 0.024 8 mg/g， respectively； the contents of linolenic acid and linoleic acid in Fructus Tritici Levis were significantly higher than those in T. aestivum （P＜0.05）.CONCLUSIONS The established qualitative and quantitative methods are simple and reliable， and can be used for the identification and quality evaluation of Fructus Tritici Levis and T. aestivum. The identified differential components， such as linolenic acid and linoleic acid， can also provide clues for the differentiation and pharmacological study of Fructus Tritici Levis and T. aestivum.

OBJECTIVE To analyze the compositional differences between Fructus Tritici Levis and Triticum aestivum， and to provide reference for identification and quality control of both. METHODS Twenty batches of Fructus Tritici Levis and three batches of T. aestivum were collected， and their fingerprints were acquired by high-performance liquid chromatography and the similarities were evaluated by the Evaluation System of Similarity of Chromatographic Fingerprints of Traditional Chinese Medicine （2012 version）. Cluster analysis （CA）， principal component analysis （PCA） and orthogonal partial least squares-discriminant analysis （OPLS-DA） were performed to analyze the difference of Fructus Tritici Levis and T. aestivum from different regions， and the differential components were screened. The contents of the six identified components in Fructus Tritici Levis and T. aestivum were determined. RESULTS The similarities of the fingerprints of Fructus Tritici Levis ranged from 0.928 to 0.996， and the relative similarities of T. aestivum with Fructus Tritici Levis ranged from 0.761 to 0.773. A total of 19 common peaks were calibrated， and six components including linolenic acid， linoleic acid， 5-heptadecylresorcinol， 5-nonadodecylresorcinol， 5- heneicosylresorcinol， and 5-tricosylresorcinol were identified. The results of CA and PCA showed that Fructus Tritici Levis and T. aestivum could be clearly distinguished； the distribution of Fructus Tritici Levis from Anhui province was relatively concentrated. The results of OPLS-DA showed that linolenic acid， linoleic acid， and other six unknown compounds were the differential components between Fructus Tritici Levis and T. aestivum. The average contents of the six identified components in Fructus Tritici Levis were 0.100 9， 1.094 0， 0.005 1， 0.030 9， 0.098 2，and 0.024 8 mg/g， respectively； the contents of linolenic acid and linoleic acid in Fructus Tritici Levis were significantly higher than those in T. aestivum （P＜0.05）.CONCLUSIONS The established qualitative and quantitative methods are simple and reliable， and can be used for the identification and quality evaluation of Fructus Tritici Levis and T. aestivum. The identified differential components， such as linolenic acid and linoleic acid， can also provide clues for the differentiation and pharmacological study of Fructus Tritici Levis and T. aestivum.

Objective:To investigate the application of combined deep learning and radiomic features derived from enhanced arterial phase CT imaging with clinical data to differentiate between T2 and T3 staging in patients with esophageal cancer.Methods:A retrospective study was conducted using clinical and CT data from 388 patients with pathologically confirmed esophageal cancer treated at The First Affiliated Hospital of Wannan Medical College between May 2015 and April 2024.The dataset was randomly divided into a training set(271 cases)and validation set(117 cases)in a 7:3 ratio.Radiomic and deep learning features were extracted from enhanced arterial phase CT images.The least absolute shrinkage and selection operator algorithm was employed for feature reduction and selection,leading to the development of radiomic(Radscore)and deep learning(Deepscore)scores.Univariate and multivariate Logistic regression analyses were conducted to identify independent risk factors,and clinical,radiomic,deep learning,and combined models were constructed.A nomogram was gener-ated for the combined model.The diagnostic performance of the models was evaluated using the area under the receiver operating charac-teristic curve(AUC)and compared using the DeLong test.Clinical net benefit was assessed through decision curve analysis,and model calib-ration was evaluated using calibration curves.Results:Nine radiomicand 12 deep learning features were selected after dimensionality reduc-tion.Multivariate Logistic regression identified tumor length,boundary,Radscore,and Deepscore as independent risk factors for distinguish-ing between T2 and T3 staging.In the training set,the AUC of the combined model was 0.867,which was significantly higher than that of the clinical(0.774,P<0.001),radiomic(0.795,P<0.001),and deep learning(0.821,P=0.001)models.In the validation set,the AUC of the com-bined model was 0.810,which was significantly higher than that of the clinical(0.653,P=0.002),radiomic(0.719,P=0.033),and deep learn-ing(0.750,P=0.009)models.The decision curve analysis indicated that the combined model provided the highest clinical benefit in both datasets.The calibration curves demonstrated a good fit for both datasets(P=0.084,0.053).Conclusion:The integration of deep learning and radiomic features obtained from enhanced arterial phase CT images with clinical data offers a reliable method for accurately distinguishing between preoperative T2 and T3 staging in esophageal cancer,thereby supporting clinical decision-making for treatment planning.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

ObjectiveTo summarize the echocardiographic features of sinus of Valsalva aneurysm （SVA）， analyze the causes of missed diagnosis， thus explore the diagnostic skills and improve the diagnostic accuracy for SVA. MethodsThe echocardiographic features and clinical data of 52 SVA patients who underwent surgery in the First Affiliated Hospital of Sun Yat-sen University from January 2014 to March 2022 were retrospectively reviewed. The patients were divided into 5 types according to modified Sakakibara classification system. ResultsThere were 32 male and 20 female patients with their age of 18~66 （36.1±11.6） years. Of the 52 aneurysms， 44 originated from the right coronary sinus （RCS）， 8 from noncoronary sinus （NCS） and none from left coronary sinus （LCS）. Among the 35 SVAs protruding into the right ventricle， including type I， type Ⅱ and type Ⅲv， 32 （91.4%） were associated with ventricular septal defect （VSD）. There were 2 （17.6%） associated with VSD among the 17 SVAs protruding into the right atrium or other sites of the heart， including type Ⅲa， type Ⅳ and type Ⅴ. SVA was frequently associated with aortic valve disease， 27 cases （51.9%） of which needed surgical valve replacement or valvoplasty. SVA was missed in 4 patients and VSD in 8， with the misdiagnosis rates of 7.7% and 23.5%， respectively. The most commonly missed VSD diagnosis was subarterial VSD with type I SVA. Of the 19 SVAs associated with infective endocarditis （IE）， 2 were missed， with the misdiagnosis rate of 10.5%. ConclusionThe ultrasound images of SVA are diverse and complex. SVA protruding into the right atrium is rarely associated with VSD， while SVA protruding into the right ventricle is frequently associated with VSD. SVA is also prone to be associated with aortic valve disease and IE， which makes the diagnosis more challenging. Therefore， during ultrasound examination， we must vigilantly and flexibly make use of the multiple scan slices so as to decrease the rate of missed diagnosis and improve the diagnostic accuracy for SVA.

Objective To investigate the clinical features of hypopituitarism with nonalcoholic fatty liver disease (NAFLD) in children after sellar tumor surgery and the association between hypopitarism and NAFLD in children. Methods A retrospective analysis was performed for the clinical data of children with hypopituitarism and NAFLD after sellar tumor surgery who were followed up regularly in Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, from January 2017 to December 2021, and their clinical features were analyzed. Results There were 32 children with regular follow-up and complete clinical data after sellar tumor surgery, and 10 children (31.25%) developed NAFLD, among whom there were 5 boys and 5 girls. Among these 10 children, 9 had craniopharyngioma and underwent surgical treatment, and 1 had germinoma and underwent local radiotherapy. The 10 children had a median age of 8.4(6.29.8) years at the diagnosis of hypopituitarism and a median age of 11.9(8.7-12.6) years at the diagnosis of NAFLD. The median number of years from the diagnosis of hypopituitarism to the diagnosis of NAFLD was 2.0(1.4-4.0) years. At the diagnosis of NAFLD, all 10 children had obesity, and body mass index (BMI) was increased by 7.26±4.25 kg/m 2 on average since the diagnosis of hypopituitarism; the 10 children had a mean fasting blood glucose level of 4.67±0.55 mmol/L, a mean fasting insulin level of 25.40±5.93 μIU/ml, and a mean HOMA-IR index of 5.26±1.29. Among these 10 children, 9 had hypertriglyceridemia, and 1 had elevated triglyceride, with a mean level of 3.08±1.09 mmol/L; 6 children had hypercholesterolemia, with a mean level of 5.67±1.25 mmol/L; 8 children had high-density lipoprotein cholesterolemia, with a mean level of 3.97±1.27 mmol/L. After the diagnosis of NAFLD, 2 children were treated with recombinant human growth hormone and metformin and achieved reductions in BMI, HOMA-IR, and triglyceride after treatment, and total cholesterol and low-density lipoprotein cholesterol were reduced to the normal range. Conclusion Children may experience weight gain, hypopituitarism, insulin resistance, and dyslipidemia after sellar tumor surgery, which may lead to the onset of NAFLD. Weight management and active pituitary hormone replacement therapy are recommended for such children, as well as routine screening and management of fatty liver disease.

The aim of this study was to investigate the effect and molecular mechanism of Xuebijing Injection in the treatment of sepsis-associated acute respiratory distress syndrome(ARDS) based on network pharmacology and in vitro experiment. The active components of Xuebijing Injection were screened and the targets were predicted by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP). The targets of sepsis-associated ARDS were searched against GeneCards, DisGeNet, OMIM, and TTD. Weishengxin platform was used to map the targets of the main active components in Xuebijing Injection and the targets of sepsis-associated ARDS, and Venn diagram was established to identify the common targets. Cytoscape 3.9.1 was used to build the "drug-active components-common targets-disease" network. The common targets were imported into STRING for the building of the protein-protein interaction(PPI) network, which was then imported into Cytoscape 3.9.1 for visualization. DAVID 6.8 was used for Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment of the common targets, and then Weishe-ngxin platform was used for visualization of the enrichment results. The top 20 KEGG signaling pathways were selected and imported into Cytoscape 3.9.1 to establish the KEGG network. Finally, molecular docking and in vitro cell experiment were performed to verify the prediction results. A total of 115 active components and 217 targets of Xuebijing Injection and 360 targets of sepsis-associated ARDS were obtained, among which 63 common targets were shared by Xuebijing Injection and the disease. The core targets included interleukin-1 beta(IL-1β), IL-6, albumin(ALB), serine/threonine-protein kinase(AKT1), and vascular endothelial growth factor A(VEGFA). A total of 453 GO terms were annotated, including 361 terms of biological processes(BP), 33 terms of cellular components(CC), and 59 terms of molecular functions(MF). The terms mainly involved cellular response to lipopolysaccharide, negative regulation of apoptotic process, lipopolysaccharide-mediated signaling pathway, positive regulation of transcription from RNA polyme-rase Ⅱ promoter, response to hypoxia, and inflammatory response. The KEGG enrichment revealed 85 pathways. After diseases and generalized pathways were eliminated, hypoxia-inducible factor-1(HIF-1), tumor necrosis factor(TNF), nuclear factor-kappa B(NF-κB), Toll-like receptor, and NOD-like receptor signaling pathways were screened out. Molecular docking showed that the main active components of Xuebijing Injection had good binding activity with the core targets. The in vitro experiment confirmed that Xuebijing Injection suppressed the HIF-1, TNF, NF-κB, Toll-like receptor, and NOD-like receptor signaling pathways, inhibited cell apoptosis and reactive oxygen species generation, and down-regulated the expression of TNF-α, IL-1β, and IL-6 in cells. In conclusion, Xuebijing Injection can regulate apoptosis and response to inflammation and oxidative stress by acting on HIF-1, TNF, NF-κB, Toll-like receptor, and NOD-like receptor signaling pathways to treat sepsis-associated ARDS.
Humans ; Network Pharmacology ; Vascular Endothelial Growth Factor A ; NF-kappa B ; Interleukin-6 ; Lipopolysaccharides ; Molecular Docking Simulation ; Respiratory Distress Syndrome ; Tumor Necrosis Factor-alpha ; Sepsis/genetics* ; NLR Proteins

Objective: To describe the gene mutation profile of newly diagnosed pediatric B-acute lymphoblastic leukemia (B-ALL) and analyze its effect on minimal residual disease (MRD). Methods: A total of 506 newly diagnosed B-ALL children treated in Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences from September 2018 to July 2021 were enrolled in this retrospective cohort study. The enrolled children were divided into MRD ≥1.00% group and <1.00% group according to MRD results on the 19th day since chemotherapy, and MRD ≥0.01% group and <0.01% group according to MRD results on the 46th day. Clinical characteristics and gene mutations of two groups were compared. Comparisons between groups were performed with chi-square test or Fisher's exact test. Independent risk factors of MRD results on the 19th day and the 46th day were analyzed by Logistic regression model. Results: Among all 506 patients, there were 318 males and 188 females. On the 19th day, there were 114 patients in the MRD ≥1.00% group and 392 patients in the MRD <1.00% group. On the 46th day, there were 76 patients in the MRD ≥0.01% group and 430 patients in the MRD <0.01% group. A total of 187 gene mutations were detected in 487 (96.2%) of 506 children. The most common gene mutations were signal transduction-related KRAS gene mutations in 111 cases (22.8%) and NRAS gene mutations in 99 cases (20.3%). Multivariate analysis showed that PTPN11 (OR=1.92, 95%CI 1.00-3.63), KMT2A (OR=3.51, 95%CI 1.07-11.50) gene mutations and TEL-AML1 (OR=0.48, 95%CI 0.27-0.87), BCR-ABL1 (OR=0.27, 95%CI 0.08-0.92) fusion genes and age >10 years (OR=1.91, 95%CI 1.12-3.24) were independent influencing factors for MRD ≥1.00% on the 19th day. BCORL1 (OR=2.96, 95%CI 1.18-7.44), JAK2 (OR=2.99, 95%CI 1.07-8.42) and JAK3 (OR=4.83, 95%CI 1.50-15.60) gene mutations and TEL-AML1 (OR=0.43, 95%CI 0.21-0.87) fusion gene were independent influencing factors for MRD ≥0.01% on the 46th day. Conclusions: Children with B-ALL are prone to genetic mutations, with abnormalities in the RAS signaling pathway being the most common. Signal transduction related PTPN11, JAK2 and JAK3 gene mutations, epigenetic related KMT2A gene mutation and transcription factor related BCORL1 gene mutation are independent risk factors for MRD.
Child ; Female ; Male ; Humans ; High-Throughput Nucleotide Sequencing ; Neoplasm, Residual/genetics* ; Retrospective Studies ; Genomics ; Precursor Cell Lymphoblastic Leukemia-Lymphoma

The global COVID-19 coronavirus pandemic has infected over 109 million people, leading to over 2 million deaths up to date and still lacking of effective drugs for patient treatment. Here, we screened about 1.8 million small molecules against the main protease (M^pro) and papain like protease (PL^pro), two major proteases in severe acute respiratory syndrome-coronavirus 2 genome, and identified 1851M^pro inhibitors and 205 PL^pro inhibitors with low nmol/l activity of the best hits. Among these inhibitors, eight small molecules showed dual inhibition effects on both M^pro and PL^pro, exhibiting potential as better candidates for COVID-19 treatment. The best inhibitors of each protease were tested in antiviral assay, with over 40% of M^pro inhibitors and over 20% of PL^pro inhibitors showing high potency in viral inhibition with low cytotoxicity. The X-ray crystal structure of SARS-CoV-2 M^pro in complex with its potent inhibitor 4a was determined at 1.8 Å resolution. Together with docking assays, our results provide a comprehensive resource for future research on anti-SARS-CoV-2 drug development.
Humans ; Antiviral Agents/chemistry* ; COVID-19 ; COVID-19 Drug Treatment ; High-Throughput Screening Assays ; Molecular Docking Simulation ; Protease Inhibitors/chemistry* ; SARS-CoV-2/enzymology* ; Viral Nonstructural Proteins