Next generation sequencing (NGS) technology is playing an increasingly important role in the diagnosis of genetic diseases. Whole exome sequencing (WES), which targets the coding regions of the genome, has been widely used in the diagnosis of genetic diseases for its low cost and high efficiency. However, compared to conventional methods, the Next Generation Sequencing (NGS) process is intricate, and there is variability in the expertise of data analysts and variant interpreters, which may lead to inconsistencies in the outcomes. To ensure the quality of testing and enhance the diagnostic rate of diseases, this consensus has provided recommendations regarding the laboratory setup, operational procedures, data analysis, result interpretation, and quality control for WES, with an aim to standardize its application in the detection of genetic disorders.

Thoracolumbar spine fracture often leads to severe pain, functional impairments, and neurological deficits, for which open reduction and internal fixation can effectively restore the spinal structural stability. Open decompression and reduction with internal fixation can help relieve spinal cord compression and improve spinal function in cases of concomitant cord injury. Although spinal stability can be restored through surgery, patients often face chronic pain and functional impairments postoperatively. A postoperative rehabilitation program is critical in optimizing therapeutic outcomes, reducing complications, and minimizing the risk of secondary injuries. However, current rehabilitation methods, such as physical therapy, functional training, and pain management, are confronted with problems in clinical practice, including significant variation in efficacy, poor patient adherence, and prolonged rehabilitation period. There is an urgent need for a unified rehabilitation strategy to address these problems. To this end, the Spinal Trauma Group of the Orthopedic Physicians Branch of the Chinese Medical Association and the Spine Health Professional Committee of the Chinese Human Health Technology Promotion Association organized experts from relevant fields to formulate Evidence-based guidelines for rehabilitation treatment after internal fixation of thoracolumbar spine fracture in adults ( version 2025) by integrating evidences from clinical researches and advanced rehabilitation concepts at home and abroad. A total number of 14 recommendations concerning the rehabilitation treatment with multimodal analgesia, psychological intervention, deep vein thrombosis prevention, core muscle and extremity exercise, appropriate use of braces, early weight-bearing, device-aided rehabilitation exercise, neuroregulatory therapy, rehabilitation team were put forward, aiming to standardize the post-operative rehabilitation process following internal fixation, promote the functional recovery, and enhance patients′ quality of life.

Objective:To evaluate the impact of implementing a regional hierarchical medical management model based on the medical internet of things (medical IoT) on the frequency of emergency department visits and hospitalizations, as well as related medical expenses, in patients with chronic obstructive pulmonary disease (COPD).Methods:This retrospective study included COPD patients enrolled in the regional hierarchical medical management system based on Medical IoT across 21 community health service centers in Songjiang District, Shanghai, between July 2017 and May 2018. Utilizing patient data from the year prior to enrollment as the baseline, changes in the number of emergency visits, hospitalizations, and associated medical costs during the first and second years of management were compared. Changes for patients receiving drug treatment were also analyzed.Results:A total of 973 COPD patients were enrolled. The mean age was 75.2±17.0 years, and 64.34% (626/973) were male. Compared to baseline, all COPD patients in the first year of management showed significant reductions: emergency visits decreased by 33.67%, total emergency costs by 45.60%, hospitalizations by 27.15%, and total hospitalization costs by 25.42%. In the second year, reductions were: emergency visits by 28.08%, total emergency costs by 36.10%, hospitalizations by 35.26%, and total hospitalization costs by 18.13% (all P<0.05). Among patients receiving drug therapy, reductions in the first year were: emergency visits by 39.66%, total emergency costs by 47.54%, hospitalizations by 25.19%, and total hospitalization costs by 28.40%. In the second year, reductions were: emergency visits by 46.98%, total emergency costs by 45.99%, hospitalizations by 41.98%, and total hospitalization costs by 24.94% (all P<0.05). No significant differences were observed before and after management for patients without drug treatment. Conclusion:The implementation of the regional hierarchical medical management model based on Medical IoT significantly reduced the frequency of emergency visits and hospitalizations, as well as related costs, for COPD patients.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective To observe the therapeutic effect of Qiwei Tangmaishu capsules on type 2 diabetes mice,and explore the mechanisms of its treatment of type 2 diabetes based on network pharmacology.Methods TCMSP,ETCM databases were used to query all components and of Qiwei Tangmaishu capsules and their targets.OMIM and DrugBank databases were used to search for targets of type 2 diabetes.The targets of type 2 diabetes and Qiwei Tangmaishu capsules were intersected by Venny 2.1.0.to perform GO and KEGG pathway enrichment analysis on those intersecting targets using the Metascape website.Then,a mouse model of type 2 diabetes was established,and Qiwei Tangmaishu capsules were given to low,medium,and high dose groups(234,468,and 936 mg/kg,respectively),and metformin(MET)group(200 mg/kg)for 2 weeks.The weight of each mouse was measured before and after treatment,and fasting blood glucose was also measured.After the 2 weeks,fasting insulin was measured;ELISA was used to detect levels of inflammatory factors IL-1β,TNF-α,IL-6,TLR4,and NF-κB in serum;Hematoxylin eosin staining was used to observe the morphology of pancreatic islets;and Caspase 3 and INS immunofluorescence were used to detect apoptosis of pancreatic islet cells and the number of pancreatic beta cells.Western Blot assay was used to detect the expression levels of pancreatic tissue proteins such as p-Akt,Akt,p-PI3K,PI3K,Bax,Bcl2.Results 1260 active ingredient targets were identified in Qiwei Tangmaishu capsules;1205 targets of type 2 diabetes were found.Of these,312 targets were intersected by Venny,with core targets involving Akt1,TNF,IL-6,TLR4,among others.Enrichment analysis identified 240 KEGG pathways,among which"insulin resistance""PI3K/Akt signaling pathway"were the key pathways enriched.The animal experiment result showed that compared with the model group,the intervention of Qiwei Tangmaishu capsules and metformin significantly improved blood glucose and insulin resistance;the content of inflammatory factors in serum decreased,and the apoptosis rate of pancreatic islet cells significantly decreased;the number of pancreatic beta cells significantly increased;the expression of pro-apoptotic protein Bax decreased,the expression of anti-apoptotic protein Bcl2 significantly increased,and the expression of p-PI3K and p-Akt was upregulated.Conclusions Qiwei Tangmaishu capsules can significantly reduce blood glucose levels,restore insulin sensitivity,and reduce islet cell apoptosis in type 2 diabetic mice.The mechanism may be related to the activation of the PI3K/Akt signaling pathway.

Objective:To analyze the effect of meridian scraping combined with thunder fire moxibustion in improving the motor function and hemorheology of patients with shoulder hand syndrome (SHS) after ischemic stroke, in order to provide reference for clinical intervention of SHS patients after ischemic stroke.Methods:A prospective study was conducted using a simple random sampling method to select SHS patients after ischemic stroke admitted to Shijiazhuang Hospital of Traditional Chinese Medicine from January 2020 to June 2023, and were randomly divided into two groups. The thunder-fire moxibustion group were given routine nursing and thunder-fire moxibustion therapy, and the combined group were additionally given scraping therapy along meridians on the basis of thunder-fire moxibustion group. The Upper Limb Fugl-Meyer Motor Function Assessment Scale (U-FMA) score, Visual Analogue Scale (VAS) score, Action Research Arm Test (ARAT) score, shoulder joint activity score, hemorheological indicators (hematocrit, plasma viscosity, platelet adhesion rate) and activities of daily living (Barthel Index), etc. were compared between two groups before and after intervention.Results:Finally, 86 patients with SHS after ischemic stroke were included, with 42 patients in the thunder-fire moxibustion group, including 25 males and 17 females, aged (59.37 ± 7.64) years; 44 patients in the combined group, including 24 males and 20 females, aged (59.52 ± 7.61) years. Before intervention, there was no statistical significance in U-FMA score, VAS score, ARAT score, shoulder joint activity score, hemorheology index level and Barthel Index between two groups (all P>0.05). After intervention, the U-FMA score, ARAT score and Barthel Index in the combined group were (48.21 ± 4.85), (40.22 ± 4.64), (56.43 ± 9.76) points, respectively, which were higher than (44.56 ± 4.23), (35.98 ± 4.37), (51.97 ± 8.31) points in the thunder-fire moxibustion group, the differences were statistically significant ( t =3.71, 4.36, 2.28, all P<0.05). The VAS score, shoulder joint mobility score, blood cell volume, plasma viscosity and platelet adhesion rate in the combined group were (2.44 ± 0.87) points, (1.23 ± 0.25) points, 0.44 ± 0.02, (1.35 ± 0.32) mPa·s, (53.56 ± 5.71)%, respectively, which were lower than (3.05 ± 0.99) points, (1.58 ± 0.22) points, 0.46 ± 0.02, (1.72 ± 0.36) mPa·s, (62.53 ± 5.94)% in the thunder-fire moxibustion group, the differences were statistically significant ( t values were 3.04-7.14, all P<0.05). Conclusions:Scraping along meridians combined with thunder-fire moxibustion therapy can achieve good intervention effect in patients with SHS after ischemic stroke, improve the upper limb motor function and hemorheology of patients, and enhance the activities of daily living.