Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

ObjectiveTo analyze the expression level of triggering receptor expressed on myeloid cells-1 （TREM-1） in serum and ascites of patients with cirrhotic ascites， and to investigate its correlation with clinical features and inflammatory markers and its role in the diagnosis of infection and prognostic evaluation. MethodsA total of 110 patients with cirrhotic ascites who were hospitalized in The Fifth Hospital of Shijiazhuang from January 2019 to December 2020 were enrolled， and according to the presence or absence of intra-abdominal infection， they were divided into infection group with 72 patients and non-infection group with 38 patients. The patients with infection were further divided into improvement group with 38 patients and non-improvement group with 34 patients. Clinical data and laboratory markers were collected from all patients. Serum and ascites samples were collected， and ELISA was used to measure the level of TREM-1. The independent-samples t test was used for comparison of normally distributed continuous data between two groups； the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups， and the Kruskal-Wallis H test was used for comparison between multiple groups； the chi-square test was used for comparison of categorical data between two groups. A Spearman correlation analysis was used to investigate the correlation between indicators. A multivariate Logistic regression analysis was used to identify the influencing factors for the prognosis of patients with cirrhotic ascites and infection. The receiver operating characteristic （ROC） curve was used to evaluate the diagnostic and prognostic efficacy of each indicator， and the Delong test was used for comparison of the area under the ROC curve （AUC）. ResultsThe level of TREM-1 in ascites was significantly positively correlated with that in serum （r=0.50， P<0.001）. Compared with the improvement group， the non-improvement group had a significantly higher level of TREM-1 in ascites （Z=-2.391， P=0.017） and serum （Z=-2.544， P=0.011）， and compared with the non-infection group， the infection group had a significantly higher level of TREM-1 in ascites （Z=-3.420， P<0.001）， while there was no significant difference in the level of TREM-1 in serum between the two groups （P>0.05）. The level of TREM-1 in serum and ascites were significantly positively correlated with C-reactive protein （CRP）， procalcitonin （PCT）， white blood cell count， and neutrophil-lymphocyte ratio （r=0.288， 0.344， 0.530， 0.510， 0.534， 0.454， 0.330， and 0.404， all P<0.05）. The ROC curve analysis showed that when PCT， CRP， and serum or ascitic TREM-1 were used in combination for the diagnosis of cirrhotic ascites with infection， the AUCs were 0.715 and 0.740， respectively. The multivariate Logistic regression analysis showed that CRP （odds ratio ［OR］=1.019， 95% confidence interval ［CI］： 1.001‍ ‍—‍ ‍1.038， P=0.043） and serum TREM-1 （OR=1.002， 95%CI： 1.000‍ ‍—‍ ‍1.003， P=0.016） were independent risk factors for the prognosis of patients with cirrhotic ascites and infection， and the combination of these two indicators had an AUC of 0.728 in predicting poor prognosis. ConclusionThe level of TREM-1 is closely associated with the severity of infection and prognosis in patients with cirrhotic ascites， and combined measurement of TREM-1 and CRP/PCT can improve the diagnostic accuracy of infection and provide support for prognostic evaluation.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Three 2,3-diketoquinoxaline alkaloids were isolated from Heterosmilax yunnanensis Gagnep. Their structures were determined through 1D and 2D NMR, HR-ESI-MS, UV, and IR as 1-[5′-(3″-hydroxy-3″-methyl) glutaryl] ribityl-2,3-diketo-1,2,3,4-tetrahydro-6,7-dimethylquinoxaline (1), 1-[2′-(3″-hydroxy-3″-methyl) glutaryl]ribityl-2,3-diketo-1,2,3,4-tetrahydro-6,7-dimethylquinoxaline (2), and 1-ribityl-2,3-diketo-1,2,3,4-tetrahydro-6,7-dimethylquinoxaline (3). Compounds 1 and 2 are novel compounds, and 3 was isolated from H. yunnanensis for the first time. The hepatoprotective activity of these three compounds was evaluated, with compound 3 showing promising hepatoprotective activity.

Background According to the Classification and Catalogue of Occupational Diseases, brucellosis is one of the notifiable occupational infectious diseases, which occurs from time to time in the occupational population. Objective To compare the work-related injury appraisal process and results of 13 cases of brucellosis at both provincial and municipal levels, analyze and summarize the bias in the practical work of labor capacity identification for occupational diseases such as brucellosis by appraisal management departments and experts, and propose suggestions for optimizing appraisal work. Methods A comparative study was conducted on the objective examination results and labor capacity appraisal conclusions based on the occupational contact history, clinical diagnosis, occupational disease diagnosis staging, and labor capacity appraisal of 13 patients with brucellosis. The reasons for the inconsistency between the initial appraisal conclusion by institutions at the municipal level and the final appraisal conclusion by institutions at the provincial level were compared and analyzed. Results All of the 13 patients with brucellosis applied for municipal-level labor capacity identification after being identified as work-related injuries, 11 of which did not receive a disability level, and 2 were rated as level 10 disability. Four of those who did not receive the disability rate applied for provincial-level labor capacity identification. As a result, 2 cases were maintained original appraisal conclusions, while the other 2 changed the conclusions to level 9 disability and level 10 disability respectively. It was the first time in Shijiangzhuang municipal-level primary labor capacity appraisal and Hebei provincial-level labor capacity re-appraisal that the work-related injury caused by occupational brucellosis was rated as level 9 disability or level 10 disability. Hence, the lessons learned from this comparative analysis are that the degree of target organ damage and (or) organ dysfunction are the direct basis for work-related injury appraisal; an objective and scientific labor capacity identification for occupational brucellosis should base on the each case of disability evaluation, identify the relevant target organ damage and the degree of dysfunction, and rate the disability level after a comprehensive appraisal. Conclusion This analysis would be a guidance to the identification of labor capacity for occupational brucellosis in Hebei Province and the whole country. There is a hysteresis issue in the occupational disease provisions in the national standard GB/T 16180—2014 Standard for identify work ability—Gradation of disability caused by work-related injuries and occupatiaonal diseases. In current situation, appraisal experts should not only search for clauses that directly correspond to the occupational diseases and injuries, but also target conditions not covered in the clauses and conduct assessment based on the characteristics of occupational diseases, with scientific, accurate, and flexible application of the clauses in the standard and appendix, so as to make fair, just, and professional appraisal conclusions.

Objective To investigate the therapeutic effect of Huatan Jieyu Anshen Decoction(mainly with the actions of resolving phlegm,relieving depression and calming mind)combined with abdominal vibration tuina manipulations on chronic insomnia in the elderly.Methods Ninety-four cases of elderly patients with chronic insomnia of phlegm-heat harassing the interior type were randomly divided into the observation group and the control group,with 47 cases in each group.The control group was given Huatan Jieyu Anshen Decoction orally,while the observation group was given oral use of Huatan Jieyu Anshen Decoction combined with abdominal vibration tuina manipulations.The course of treatment for the two groups lasted for 4 weeks.Before and after the treatment,the two groups were observed in the changes of traditional Chinese medicine(TCM)syndrome scores,Pittsburgh Sleep Quality Index(PSQI)score,Athens Insomnia Scale(AIS)score,Fatigue Scale-14(FS-14)score,World Health Organization Quality-of-Life Brief Scale(WHOQOL-BREF)score,and the serum levels of melatonin(MT),dopamine(DA),and cortisol(CORT).After treatment,the clinical efficacy of the two groups was evaluated.Results(1)After 4 weeks of treatment,the total effective rate of the observation group was 97.88%(46/47),while that of the control group was 87.23%(41/47),and the intergroup comparison(tested by chi-square test)showed that the therapeutic efficacy of the observation group was superior to that of the control group(P＜0.01).(2)After treatment,the scores of primary and secondary TCM symptoms in the two groups were significantly decreased compared with those before treatment(P＜0.05),and the decrease of the scores of primary and secondary TCM symptoms in the observation group was significantly superior to that in the control group(P＜0.01).(3)After treatment,the PSQI scores,AIS scores,and FS-14 scores in the two groups were significantly decreased compared with those before treatment(P＜0.05),and the WHOQOL-BREF scores were significantly increased compared with those before treatment(P＜0.05).The decrease of the PSQI scores,AIS scores and FS-14 scores as well as the increase of the WHOQOL-BREF scores in the observation group was significantly superior to that in the control group(P＜0.01).(4)After treatment,the serum MT level of both groups was significantly higher than that before treatment(P＜0.05),and the serum DA and CORT levels were significantly lower than those before treatment(P＜0.05).The increase in serum MT level and the decrease in serum DA and CORT levels of the observation group were significantly superior to those of the control group(P＜0.01).Conclusion The combined therapy of Huatan Jieyu Anshen Decoction combined with vibration tuina manipulations can achieve satisfactory efficacy in the elderly patients with chronic insomnia of phlegm-heat harassing the interior syndrome.The therapy is effective on regulating the central nervous system of the patients,improving the quality of the sleep,and promoting the relief of fatigue and the enhancement of the quality of life,which has great significance to the enhancement of the overall therapeutic efficacy of insomnia.

Objective To analyze the acupoint selection rules of acupuncture for the treatment of tic disorders in children based on data mining techniques.Methods A computerized search was conducted for the clinical research literature on acupuncture treatment of tic disorders in children included in the CNKI,Wanfang,VIP,SinoMed,and PubMed databases from January 1992 to December 2022.A database was established by Excel 2019 to count the commonly used treatment methods and analyze the high-frequency application methods acupuncture(high-frequency acupoints,channel entry of acupoints,acupoint association rules,and acupoint clustering),auricular point seed-pressing(high-frequency auricular points,and acupoint association rules),and the high frequency division of cluster needling of scalp point.Results A total of 190 valid literature articles were included,involving 270 acupuncture prescriptions;among them,184 acupoints were counted in the acupuncture method,with a total application frequency of 1 906 times,and the high-frequency application of the acupoints in descending order were Baihui(DU20),Taichong(LR3),Fengchi(GB20),Hegu(LI4),Sanyinjiao(SP6),Neiguan(PC6),Shenmen(HT7),Zusanli(ST36),Yintang(EX-HN3),Sishencong(EX-HN1);and the high-frequency meridians were governor vessol,foot taiyang stomach meridian,foot taiyang stomach meridian,foot shaoyang gallbladder meridian,hand taiyang large intestine meridian,foot taiyang bladder meridian,foot jueyin gallbladder meridian;three sets of strong association rules and five clusters of acupoints were analyzed by SPSS modeler 18.0 and IBM SPSS Statistics 26.0 software.There were 29 acupoints of auricular point seed-pressing,application total frequency was 206 times,high-frequency application of auricular points in descending order of Shenmen(HT7),liver,heart,subcortex,kidney;four groups of acupoint strong association rules were obtained through the analysis of SPSS modeler 18.0 software.A total of 14 zones were involved in the application of cephalic acupoint plexus zoning,of which the high-frequency zones were parietal anterior temporal diagonal,parietal parietal 1,and chorea tremor control zone.Conclusion Acupuncture treatment of tic disorders in children,according to its pathogenesis(liver hyperactivity,kidney depletion,spleen deficiency,phlegm disturbance,etc.)and tic site,select acupoints compatibility,and mostly choose yang meridian acupoints,which is related to the nature and treatment characteristics of wind pathogen.Children's tic disorders are closely related to emotional disorders,therefore acupuncture and auricular acupoints all emphasize the method of soothing the liver and clearing the heart,and regulating the emotional state.Cluster needling of scalp point mostly used parietal temporal anterior oblique line,parietal 1 line,and dance tremor control area for the treatment of tic disorders.For children,auricular point seed-pressing and cluster needling of scalp point has the minimun of pain,the effect of treatment is long,and it is not easy to have dangerous situations such as bent needle,broken needle and so on.