Objective To explore the reason of serious interference red blood cell(RBC)parameters in blood routine test and correct method.Methods 30 cases of patients whose results of blood routine RBC parameters obviously abnormal ,According to the interference factors were divided into four groups:cold agglutination (7 cases),severe hemolysis(13 cases),high triglycerides (8 cases),high white blood cell(WBC)(2 例).Take appropriate corrective action for processing respectively.The difference of red blood cell parameters were compared with t test.Results To analysis of interference factors and take appropriate corrective meas-ures,RBC parameters could be more close to the real results.Conclusion We should pay attention to the changes of the RBC pa-rameters,analysis of interference factors,and to take appropriate measures to correct,in order to avoid clinical misdiagnosis and mi-stherapy.

Objective To investigate the genetic characteristic of whole-genome of influenza A/H3N2 viruses in severe acute respiratory infection cases in Beijing area.Methods From 2014 to 2016,the viral RNA was extracted from 32 strains isolated from SARI cases,then sequenced by Ion Torrent PGM Sequencer.The phylogeny and molecular features of whole-genome were analyzed by Mega and Consurf software.Results The HA gene of tested strains isolated in 2014-2015 influenza season belonged to lineage 3C.3a and 3C.2a,while those isolated in 2015-2016 influenza season belonged to cluster 3C.2a.Moreover,compared with the vaccine strains,7 variant amino acids of protein of HA1 were identified,and two of them were located in antigenic sites.All isolates were sensitive to neuraminidase inhibitors while showed resistance to blockers for M2 ion channel.Conclusion The phylogenetic features of isolates studied in this study are similar with that of current circulating strains.However,the difference between isolates and vaccines should not be overlooked.

Chronic osteomyelitis is a common disease. Traditionally, osteomyelitis is treated with parenteral antibiotics for 4 to 6 weeks after thorough debridement. However, this antibiotic treatment course has no documented superiority over other courses of antibiotic treatment. As this disease has been understood more deeply and various treatment technologies have been explored recently, the use of antibiotics has also changed. This article reviews the latest progress concerning the course of antibiotic treatment for chronic osteomyelitis.

Objective To explore the relationship between superantigen and M protein gene (emm)-types genes of Group A Streptococcus pyogenes (GAS) isolated from patients with scarlet fever in Beijing from May 2012 to July 2013 .Methods GAS was isolated from specimens of patients with scarlet fever . Superantigen genes (speA ,speB ,speC ,speF ,speG ,speH ,speI ,speJ ,speL ,speK ,speM ,ssa ,and smeZ) ,and emm gene were amplified by polymerase chain reaction .Rate and proportion were compared by chi-square test .Results Of the 423 GAS strains isolated from patients with scarlet fever from 2012 to 2013 ,most of the isolates possessed speB (97 .6% ) ,speC (99 .8% ) ,speF (98 .3% ) ,speG (99 .8% ) , smeZ (94 .1% ) and ssa (88 .4% ) ,and some of them possessed speH (54 .6% ) ,speI (53 .4% ) ,speA (45 .2% ) and speJ (43 .5% ) ,but very few isolates possessed speK (2 .4% ) ,speL (1 .4% ) and speM (1 .7% ) .Type emm12 (59 .5% ) and type emm1 (37 .4% ) were the main types of GAS .Most of the emm12-type isolates possessed speH (84 .8% ) and speI (84 .0% ) compared with only 4 .0% of speH and 3 .4% of speI in type emm1 .Most of type emm1 possessed speA (95 .3% ) and speJ gene (94 .6% ) compared with only 17 .3% of speA and 14 .8% of speJ in type emm12 .The superantigen genes profiles were significant different between emm 1-type and emm 12-type isolates (P< 0 .05) .Conclusion Type emm1 and type emm12 are epidemic strains in patients with scarlet fever from 2012 to 2013 in Beijing ,and emm gene-types are associated with superantigen genes profiles .

OBJECTIVETo investigate the chemical constituents of tuber of Gymnadenia conopsea.

METHODThe constituents were isolated by using a combination of various chromatographic techniques including column chromatography over silica gel, Sephadex LH-20, and C-18, as well as reversed-phase HPLC. Structures of the isolates were identified by spectroscopic data analysis.

RESULTThirty-four compounds were isolated. Their structures were identified as six 2-isobutyltartrate benzyl ester glucosides: coelovirin A (1), coelovirin B (2), coelovirin E (3), coelovirin D (4), dactylorhin B (5) and loroglossin (6). Three 2-isobutylmalate benzyl ester glucosides: dactylorhin A (7), dactylorhin E (8) and militarine (9). Three lignans: arctigenin (10), lappaol A (11) and lappaol F (12). Six aromatic acid (alhyde or alcohol) derivatives: 4-beta-D-glucopyranosyloxyl-trans-phenylpropenoic acid (13), 4-beta-D-glucopyranosyloxyl-cis-phenylpropenoic acid (14), gastrodin (15), 4-beta-D-glucopyranosyloxylphenylaldehyde (16), 4-beta-D-glucopyranosyloxylbenzyl methyl ether (17), 4-beta-D-glucopyranosyloxyloxylbenzyl ethyl ether (18), and bis(4-hydroxybenzyl) ether mono 4-O-beta-D-glucopyranoside (19). Four cyclodipeptides: cyclo(L-Leu-L-Tyr) (20), cyclo(L-Leu-L-Pro) (21), cyclo(L-Val-L-Tyr) (22), and cyclo(L-Ala-D-Phe) (23). One N6-substituted andenosine: N6-(4-hydroxybenzyl)-adenine riboside (24). An aromatic amide: N-trans-feruloyltyramine (25). Nine aromatic acids (or aldehyde or alcohol): 3-hydroxybenzoic acid (26), 4-hydroxyisophthalic acid (27), 4-hydroxybenzyl alcohol (28), 4-hydroxybenzyl methyl ether (29), 4-hydroxybenzylaldehyde (30), 4-hydroxybenzoic acic (31), 4-hydroxy-3-methoxybenzoic acid (32), trans-p-hydroxyphenylpropenoic acid (33), and cis-p-hydroxyphenylpropenoic acid (34). At a concentration of 1.0 x 10(-6) mol x L(-1), compounds 10-12 showed antioxidative activity inhibiting Fe(+2) -cystine induced rat liver microsomal lipid peroxidation with inhibitory rates of 53%, 59%, and 52%, respectively(positive control VE with 35% inhibition).

CONCLUSIONThese compounds were obtained from the genus Gymnadenia for the first time except for 5-7, 9, 15, 28-34. Compounds 10-12 possess antioxidant activity.

Animals ; Lipid Peroxidation ; drug effects ; Microsomes, Liver ; drug effects ; metabolism ; Orchidaceae ; chemistry ; Plant Extracts ; analysis ; isolation & purification ; pharmacology ; Rats

OBJECTIVETo investigate chemical constituents of Iodes cirrhosa.

METHODConstituents were isolated by using a combination of various chromatographic techniques including column chromatography over silica gel, Sephadex LH-20, and C-18, as well as reversed-phase HPLC. Structures of the isolates were identified by spectroscopic and chemical methods.

RESULTTwenty-four compounds were obtained from a H2O-soluble portion of an ethanolic extract of the root of lodes cirrhosa Turcz. Structures of the isolates were identified as (-)-(7R,8S,7'E) -4,7,9,9'-tetrahydroxy-3,3'-dimethoxy-8,4'-oxyneolign-7'-ene-9'-O-beta-D-glucopyra-noside (1), (-)-(7S,8S,7'E)-4,7,9,9'-tetrahydroxy-3,3'-dimethoxy-8,4'-oxyneolign-7'-ene-9'-O-beta-D-glucopyranoside(2), (+)-(7S,8S)-syringylglycerol 8-O-beta-D-glucopyranoside (3), (+)-(7S, 8S)-guaiacylglycerol 8-O-P-D-glucopyranoside (4), (-)-(7S, 8S)-4,7,9, 9'-tetrahydroxy-3,3'-dimethoxy-8,4'-oxyneolignan-7-O-beta-D-glucopyranoside (5),(-)-alaschanisoside A (6), (-)-(2R)-1-O-beta-D-glucopyranosyl-2-(2-methoxy-4-[1-(E)-propen-3-ol] phenoxyl propane-3-ol(7), (-)-(2R)-1-O-beta-D-glucopyranosyl-2-{2,6-dimethoxy-4-[1-(E)-propen-3-ol] phenoxyl} propane-3-ol(8), (-)-liriodendrin(9), (-)-(7S, 8R)-guaiacylglycerol 9-O-beta-D-glucopyranoside(10), (-)-(7R, 8R)-guaiacylglycerol 9-O-beta-D-glucopyranoside(11),(-)-(7R,8R)-syringylglycerol 9-O-beta-D-glucopyranoside(12), (-)-(7R,8R)-guaiacylglycerol 7-O-beta-D-glucopyranoside(13), (-)-11,13-dihydrodeacylcynaropicrin 3-O-beta-D-glucopyranoside(14), (-)-sweroside (15), (-)-2-hydroxy-5-(2-hydroxyethyl) phenyl beta-D-glucopyranoside(16), (-)-(1'R)-1'-(3-hydroxy-4-methoxyphenyl) ethane-1',2'-diol-3-O-beta-D-glucopyranoside(17), (-)-tachioside(18), (-)-3,5-dimethoxy-4-hydroxyphenyl beta-D-glucopyranoside(19), (-)-3-hydroxy-1-(4-hydroxy-3-methoxyphenyl)-1-propanone-3-O-beta-D-glucopy ranoside(20), (-)-2-methoxy4-(1-propionyl) phenyl beta-D-glucopyranoside(21), (-)-4-propionyl-3, 5-dimethoxyphenyl beta-D-glucopyranoside(22), erigeside C(23), and scopoletin beta-D-xylopyranosyl-(1-->6)-beta-D-glucopyranoside(24).

CONCLUSIONCompounds 1-24 were obtained from the genus for the first time.

Drugs, Chinese Herbal ; analysis ; Ethanol ; chemistry ; Glucosides ; analysis ; Isomerism ; Magnoliopsida ; chemistry ; Plant Roots ; chemistry ; Solubility ; Water ; chemistry

Objective:To investigate the correlation between triglyceride-glucose (TyG) index on admission and unfavorable outcomes of patients with moderate-to-severe traumatic brain injury (msTBI) at 6 months postinjury.Methods:A retrospective cohort study was conducted to analyze the clinical data of 277 patients with msTBI admitted to Affiliated Jiangyin Hospital of Nantong University from January 2019 to December 2022, including 208 males and 69 females, aged 18-88 years [(57.0±15.1)years]. Glasgow Coma Scale (GCS) scores on admission were 3-8 points in 168 patients and 9-12 points in 109. According to the Glasgow Outcome Scale-Extended (GOSE) assessment at 6 months after injury, there were 121 patients with unfavorable outcomes (GOSE≤4 points) and 156 with favorable outcomes (GOSE≥5 points). The following indicators of the patients were recorded, including gender, age, history of diabetes, cause of injury, admission GCS, GCS motor score (GCSM), pupillary light reflex, worst Marshall CT classification within the first 24 hours after admission, admission TyG index, Mean Amplitude of Glycemic Excursions (MAGE) within 24 hours after admission, GCSM decline≥2 points within 72 hours after admission, craniotomy or not after admission, and prognosis, etc. TyG index served as the exposure variable focused in this study, which was calculated with fasting triglycerides and fasting blood glucose within 24 hours after admission. The 6-month prognosis of the patients was designated as the outcome variable of the study. After the patients were divided into different groups according to the three quantiles of the TyG index and unfavorable or favorable outcomes, the univariate analysis was conducted on watch variables, and variables with statistically significant differences were included in directed acyclic graphs (DAGs) for further identification of confounding variables. Factors which were found with no statistical significance in the univariate analysis but might affect insulin resistance after injury according to the authors′ previous researches were also included in the DAGs analysis. Three Logistic regression models were designed (Model 1 without correction, Model 2 with core variables of International Mission for Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) corrected, and Model 3 with confounding variables screened by DAGs corrected) to analyze whether the TyG index was an independent risk factor for the prognosis of msTBI patients. The optimal Logistic regression model was selected and then restricted cubic spline (RCS) was employed to investigate the relationship between the TyG index and the unfavorable outcomes.Results:The univariate analysis suggested that there were significant differences in gender, history of diabetes, MAGE, GCSM decline, and prognosis among the three quantiles of the TyG index ( P<0.05 or 0.01). Significant differences in age, history of diabetes, GCSM, pupillary light reflex, Marshall CT classification, TyG index, MAGE and GCSM decline were observed between unfavorable and favorable outcome groups ( P<0.05 or 0.01). The results of Logistic regression analysis that identified the confounding variables that influenced the correlation between the TyG index and unfavorable prognosis with DAGs suggested that a high TyG index level was significantly correlated with unfavorable outcomes in msTBI patients. Moreover, Model 3 that was corrected with confounding variables screened by DAGs had an optimal goodness-of-fit and adaptability. Model 3-based further RCS analysis indicated that the risk of unfavorable outcomes following msTBI may increase approximately linearly with the increase in TyG index within a certain range (TyG index<9.79). Conclusions:A high TyG index level on admission is the identified as an independent risk factor for unfavorable outcomes of patients with msTBI at 6 months postinjury. As the TyG index level increases, the risk of unfavorable outcomes also rises and may show a linear increasing trend within a certain range (TyG index<9.79).

OBJECTIVETo study the chemical constituents of Iodes cirrhosa and evaluate their bioactivity.

METHODThe compounds were isolated and purified by various kinds of column chromatography methods and their structures were determined by spectroscopic data analysis. Neuroprotective assay against serum deprivation induced SH-SYSY-JNK3 cell apoptosis was evaluated by MTr method while potassium channel-blocking activity was assayed in both non-specific and specific K+ channel-regulator screening models.

RESULTTwenty-one compounds were obtained from an EtOAc portion of an ethanolic extract of the root of I. cirrhosa. Their structures were elucidated as 1beta, 3beta-dihydroxyurs-9(11),12-diene(1), bauerenyl acetate(2),3beta-hydroxy-11-oxo-olean-12-enyl palmitate(3), 3beta-acetoxy-urs-12-ene-11-one(4), betulinic acid(5), stigmasta-5, 22-diene-3beta-ol(6), 7beta-hydroxystigmasterol(7), stigmasta-5, 22diene-3beta-ol3-O-beta-D-glucopyranoside(8),scopoletin(9),scopolin(10),clovamide(11),methyl 3,5-di-O-caffeoylquinate(12),3,5-dicaffeoylquinic acid(13),2,6-dimethoxy-1,4-benzoquinone(14), protocatechualdehyde(15), vanillin(16), protocatechuic acid(17), vanillic acid(18),caffeic acid(19),azelaic acid(20),and succinic acid(21). Compound 3,4,6,9,10,14,15,18 and 20 showed neuroprotective activities against serum deprivation induced SH-SYSY-JNK3 cell apoptosis at a concentration of 1.0 x 10(6) mol x L(1) with relative protection rates of 177%, 144%, 137%, 137%, 143%, 145%, 137%, 189%, 130%, respectivley. Compound 16 could increase DiBAC4(3) fluorescence response in both non-specific and specific K+ channel-regulator screening models at the concentration of 1.0 x 10(-5) mol x L(-1).

CONCLUSIONCompound 1 was a new compound and all compounds were isolated from this genus for the first time. Compounds 3,4,6,9,10,14,15,18 and 20 showed neuroprotective activities while 16 exhibited K+ channel-blocking activity.

Apoptosis ; drug effects ; Cell Line, Tumor ; Humans ; Magnoliopsida ; chemistry ; Neuroprotective Agents ; chemistry ; pharmacology ; Plant Extracts ; chemistry ; pharmacology ; Potassium Channels ; drug effects

Background/Aims: The accuracy of endosonographers in diagnosing gastric subepithelial lesions (SELs) using endoscopic ultrasonography (EUS) is influenced by experience and subjectivity. Artificial intelligence (AI) has achieved remarkable development in this field. This study aimed to develop an AI-based EUS diagnostic model for the diagnosis of SELs, and evaluated its efficacy with external validation. Methods: We developed the EUS-AI model with ResNeSt50 using EUS images from two hospitals to predict the histopathology of the gastric SELs originating from muscularis propria. The diagnostic performance of the model was also validated using EUS images obtained from four other hospitals. Results: A total of 2,057 images from 367 patients (375 SELs) were chosen to build the models, and 914 images from 106 patients (108 SELs) were chosen for external validation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the model for differentiating gastrointestinal stromal tumors (GISTs) and non-GISTs in the external validation sets by images were 82.01%, 68.22%, 86.77%, 59.86%, and 78.12%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in the external validation set by tumors were 83.75%, 71.43%, 89.33%, 60.61%, and 80.56%, respectively. The EUS-AI model showed better performance (especially specificity) than some endosonographers.The model helped improve the sensitivity, specificity, and accuracy of certain endosonographers. Conclusions We developed an EUS-AI model to classify gastric SELs originating from muscularis propria into GISTs and non-GISTs with good accuracy. The model may help improve the diagnostic performance of endosonographers. Further work is required to develop a multi-modal EUS-AI system.

Objective:To clarify the M protein ( emm gene) types and drug susceptibility characteristic variations of Group A Streptococcus (GAS) in children in Beijing. Methods:The GAS strains isolated from throat swab samples of children diagnosed with scarlet fever and pharyngeal infection in scarlet fever etiology surveillance sentinel hospitals in 16 districts of Beijing in 2018, 2019 and 2021 were analyzed retrospectively.PCR amplification and sequencing were used for emm genotyping, and the minimum inhibitory concentrations (MIC) of 10 antibiotics were determined by the broth microdilution method.The data were analyzed using χ2 test and Fisher′ s exact method between groups. Results:A total of 557 GAS strains were collected, and 11 emm genotypes ( emm1, emm3, emm4, emm6, emm11, emm12, emm22, emm75, emm89, emm128, and emm212) were detected.Of 557 strains, 238 trains were of emm1 type (42.73%), 271 strains were of emm12 type (48.65%) and 48 strains were of other emm types (8.62%). The detection rates of emm1, emm12 and other emm type genes in 2018, 2019, and 2021 were [37.50% (105/280 strains), 57.14% (160/280 strains), 5.36% (15/280 strains)], [49.05% (129/263 strains), 39.54% (104/263 strains), 11.41% (30/263 strains)], and [28.57% (4/14 strains), 50.00% (7/14 strains), 21.43% (3/14 strains)], respectively.In children infected with emm12 in 2018 and 2019, there were more children under 6 years old than children over 6 years old (62.50% vs.46.88%, 46.36% vs.30.36%) (χ 2=7.182, 6.973; all P<0.05). Drug susceptibility testing results suggested that 225 randomly selected GAS strains were all 100.00% sensitive to 7 antibiotics including Penicillin, Levofloxacin, Meropenem, Linezolid, Cefotaxime, Cefepime and Vancomycin.The rates of resistance to Erythromycin, Tetracycline and Clindamycin were [88.57% (93/105 strains), 87.62% (92/105 strains), 86.67% (91/105 strains)], and [94.34% (100/106 strains), 94.34% (100/106 strains), 87.74% (93/106 strains)] in 2018 and 2019, respectively.The test strains were 100.00% (14/14 strains) resistant to the above 3 antibiotics in 2021.MIC 50 and MIC 90 values of Penicillin in 2018, 2019, and 2021 were (0.03 mg/L, 0.03 mg/L), (0.03 mg/L, 0.06 mg/L), and (0.06 mg/L, 0.06 mg/L), respectively.Among 225 GAS strains, 207 strains had drug resistance and were resistant to more than one drug.Specifically, 94.69% (196/207 strains) were resistant to Erythromycin, Tetracycline and Clindamycin.About 4.35% (9/207 strains) were resistant to both Erythromycin and Clindamycin.A total of 0.97% (2/207 strains) were resistant to Erythromycin and Tetracycline. Conclusions:The emm genotypes of GAS in children in Beijing are diverse in 2018, 2019 and 2021.The dominant genotypes are emm12 and emm1, and emm12 is the main epidemiological type.GAS strains maintain highly resistant to Erythromycin, Clindamycin and Tetracycline, and sensitive to Penicillin and other antibiotics.However, MIC 50 and MIC 90 of Penicillin shows an ascending trend.