OBJECTIVE To investigate the mechanism by which Qiaobai cold compress solution （QBCS） improves acne vulgaris （AV） based on transcriptomics and animal experiments. METHODS Rats were randomly divided into a blank control group （ n ＝6） and a modeling group （ n ＝30）. AV models were established in the modeling group by topical application of oleic acid to the inner surface of both ears， combined with subcutaneous injection of Cutibacterium acnes suspension into the auricle. Successfully modeled rats were further divided into the model group， positive control group （Tretinoin cream， 0.045 g/kg）， and QBCS low-， medium-， high-dose groups [3.55， 7.11， 14.22 g/kg （calculated by the amount of crude drug） ] ， with 6 rats in each group. Rats in each d rug group were treated with the corresponding drugs once daily for 14 consecutive days. After the final administration， changes in the appearance of the ears and histopathological changes in the ear tissues were observed， and serum levels of inflammatory factors， including tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6） and IL-1β， were measured. Auricular tissues from the blank control group， model group and QBCS medium-dose group were collected for transcriptome sequencing. Differential expressed genes （DEGs） were screened and subjected to Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis， followed by validation using real-time quantitative polymerase chain reaction and Western blot assay. RESULTS Compared with the model group， rats in all QBCS groups showed alleviated auricular acne symptoms， with reduced epidermal thickening， sebaceous gland hyperplasia， and inflammatory cell infiltration. Serum levels of TNF-α （except for the QBCS low-dose group）， IL-6 （except for the QBCS low-dose group） and IL-1β were significantly decreased （ P ＜0.05）. A total of 590 DEGs were identified （blank control group vs. model group）， and 596 DEGs were identified （model group vs. QBCS medium-dose group）. Above DEGs （blank control group vs. model group） were mainly enriched in Toll-like receptor （TLR） and nuclear factor-kappa B （NF-κB） signaling pathways， etc. Validation experiments showed that， compared with model group， low-， medium- and high-dose of QBCS reduced， to varying degrees， the mRNA expression of TNF-α， TLR2， interferon-γ and CXC chemokine ligand 8 in the auricular tissues of AV rats， increased the mRNA expression of peroxisome-proliferator-activated receptor gamma and tumor protein 53， and inhibited the phosphorylation of NF-κB p65 protein as well as the expressions of TLR2 and myeloid differentiation primary response protein 88（MyD88） （ P ＜0.05）. CONCLUSIONS QBCS can alleviate auricular inflammation and skin lesions in AV rats. This effect may be related to inhibition of the TLR/MyD88/NF-κB signaling pathway， thereby suppressing the expression of downstream inflammatory factors such as TNF-α.

Objective:To establish and validate a prediction model based on least absolute shrinkage and selection operator（LASSO）regression and classification and regression tree（CART）algorithm for acute kidney injury（AKI）in PICU.Methods:The prospective derivation cohort consisted of 350 critically ill children admitted to the PICU of Children′s Hospital of Soochow University from September 2020 to January 2021.The external data set consisting of 866 critically ill children admitted to the PICU of Children′s Hospital of Soochow University from February 2021 to February 2022 was employed for the external validation.Clinical data was obtained from the electronic medical record system，including demographic characteristics，laboratory data and the pediatric risk of mortality Ⅲ（PRISM Ⅲ）score.The variables associated with AKI were identified using LASSO regression.Subsequently，a decision tree prediction model was built using the CART algorithm.The predictive value of decision tree prediction model was evaluated using the receiver operating characteristic（ROC）curve，calibration curve，and decision curve analysis.Results:Among the 350 children in the derivation cohort，107（30.6%）developed AKI during the PICU stay；and of 866 children in the external validation cohort，165（19.1%）developed AKI during the PICU stay.The LASSO regression screened 16 candidate variables for further analysis，and the decision tree model ultimately identified 4 variables more closely associated with AKI，including fold change in serum creatinine from baseline，urine volume，PRISM Ⅲ，and C-reactive protein.The decision tree model exhibited high accuracy with AUC of 0.92，0.88，and 0.86 in the training，internal validation，and external validation cohorts，respectively.The model demonstrated good calibration and clinical applicability based on the calibration curve and decision curve analysis.Conclusion:The decision tree model based on the 4 identified clinical indicators，including fold change in serum creatinine from baseline，urine volume，PRISM Ⅲ，and C-reactive protein，is effective for the early prediction of AKI.

Objective To develop a three-dimensional(3D)deep neural network based preoperative classification model for coronary computed tomography angiography(CTA)in atrial fibrillation patients,and to explore the effects of transfer learning on the performance of medical image classification models,thereby providing preoperative decision support for catheter ablation to advance atrial fibrillation treatment toward precision and personalization.Methods Utilizing 3D ConvNet and 3D ResNet as backbone network,the three-dimensional classification features were extracted from coronary CTA sequences.The publicly available pre-trained weights were used for transfer learning.The model performance was evaluated through metrics such as confusion matrix,classification accuracy,and area under the curve(AUC).A comparative analysis was also conducted to evaluate the performance differences between the transfer learning model and the initialized training model.Results Transfer learning yielded significant performance improvements over the initialized training models,attaining AUC improvement of 9.1%-16.7%and accuracy enhancement of 6.2%-23.5%.Among all models,3D-ResNet18 model with MedicalNet pre-training weights performed the best,achieving an AUC of 0.77 and an accuracy of 0.71.Conclusion The proposed three-dimensional deep network enhanced by transfer learning can effectively identify atrial fibrillation patients requiring additional ablation besides pulmonary vein isolation through preoperative coronary CTA,which will assist clinicians in optimizing surgical strategies and improving treatment outcomes,thereby reducing long-term postoperative recurrence rates.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Objective To develop a three-dimensional(3D)deep neural network based preoperative classification model for coronary computed tomography angiography(CTA)in atrial fibrillation patients,and to explore the effects of transfer learning on the performance of medical image classification models,thereby providing preoperative decision support for catheter ablation to advance atrial fibrillation treatment toward precision and personalization.Methods Utilizing 3D ConvNet and 3D ResNet as backbone network,the three-dimensional classification features were extracted from coronary CTA sequences.The publicly available pre-trained weights were used for transfer learning.The model performance was evaluated through metrics such as confusion matrix,classification accuracy,and area under the curve(AUC).A comparative analysis was also conducted to evaluate the performance differences between the transfer learning model and the initialized training model.Results Transfer learning yielded significant performance improvements over the initialized training models,attaining AUC improvement of 9.1%-16.7%and accuracy enhancement of 6.2%-23.5%.Among all models,3D-ResNet18 model with MedicalNet pre-training weights performed the best,achieving an AUC of 0.77 and an accuracy of 0.71.Conclusion The proposed three-dimensional deep network enhanced by transfer learning can effectively identify atrial fibrillation patients requiring additional ablation besides pulmonary vein isolation through preoperative coronary CTA,which will assist clinicians in optimizing surgical strategies and improving treatment outcomes,thereby reducing long-term postoperative recurrence rates.

Infectious chronic refractory wounds are common in the department of dermatology,and have a great influence on the quality of life of patients.Their incidence is increasing year by year.The pathogensis of infectious chronic refractory wounds is due to the exuberance of pathogenic heat and toxin,disharmony between nutritive qi and defensive qi,and imbalance of zang-fu organs,which is related with the theory of qi-fluid and sweat pores.Therefore,it is proposed that stagnation and obstruction of sweat pores contribute to the pathological basis for the onset of infectious chronic refractory wounds,and therapeutic principle of opening sweat pores was presented.In the medication view of treating the skin diseases with the skin-related Chinese medicinals,skin-related Chinese medicinals are good at treating skin diseases,and consequently the application of skin-related Chinese medicinals to open sweat in treating infectious chronic refractory wounds was discussed.It is suggested that for the treatment of infectious chronic refractory wounds due to pathogenic fire-toxin accumulation in sweat pores,therapy of clearing heat and expelling fire to open sweat pores should be exployed,and skin-related Chinese medicinals such as Phellodendri Chinensis Cortex,Dictamni Cortex and Fraxini Cortex can be selected;for the treatment of infectious chronic refractory wounds due to blood-stasis stagnation in sweat pores,therapy of cooling and activating blood to open sweat pores should be exployed,and skin-related Chinese medicinals such as Moutan Cortex and Lycii Cortex can be selected;for the treatment of infectious chronic refractory wounds due to wind and dampness obstructing sweat pores,therapy of expelling wind and eliminating dampness to unblock sweat pores should be exployed,and skin-related Chinese medicinals such as Acanthopanacis Cortex,Citri Reticulatae Pericarpium,and Poriae Cutis can be selected;for the treatment of infectious chronic refractory wounds due to healthy qi deficiency resulting in the obstruction of sweat pores,therapy of invigorating spleen and tonifying kidney to nourish sweat pores should be exployed,and skin-related Chinese medicinals such as Cinnamomi Cortex,Eucommiae Cortex,and black soybean testa(Testa Glycinea Macids)can be chosen.Guided by the theory of qi-fluid and sweat pores,this paper explored the application of skin-related Chinese medicinals in the treating infectious chronic refractory wounds,which provides theoretical basis for such an approach,enriches the theory of traditional Chinese medicine for the treatment of infectious chronic refractory wounds,and expands the clinical application of the theory of sweat pores.

As an innovative dosage form, traditional Chinese medicine(TCM) dry powder inhalers have emerged as a focal point in the research and development of new preparations due to its high efficiency, safety, and bioavailability. This paper systematically reviewed the relevant literature and patents associated with TCM dry powder inhalers to analyze the origins and the current research and development status. Furthermore, this paper probed into the research and development ideas of TCM dry powder inhalers regarding clinical positioning, prescription screening, and druggability. Additionally, the paper thoroughly analyzed the technical barriers in druggability studies and elaborated on corresponding research techniques and coping measures. Furthermore, it emphasized the need for improved regulations and policies governing TCM dry powder inhalers, advocated for strengthened oversight, and called for the establishment of a scientific quality evaluation system. Measures such as promoting production-education-research collaboration, enhancing personnel training, and fostering international exchanges were proposed to provide a scientific and systematic reference for the future research, development, and application of TCM dry powder inhalers, thereby facilitating the rapid modernization of TCM.
Humans ; Dry Powder Inhalers/trends* ; Drugs, Chinese Herbal/chemistry* ; Medicine, Chinese Traditional/instrumentation* ; Administration, Inhalation

OBJECTIVE: To detect and analyze the expression and clinical significance of long non-coding RNA tyrosine kinase non-catalytic region adaptor protein 1-antisense RNA1 (NCK1-AS1) in patients with acute myeloid leukemia (AML). METHODS: 89 AML patients and 23 healthy controls were included from the People's Hospital Affiliated to Jiangsu University. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression levels of NCK1-AS1 and NCK1 in bone marrow samples. The relationship between the expression of NCK1-AS1 and the clinical characteristics of patients were analyzed, as well as the correlation between NCK1-AS1 and NCK1. RESULTS: The expression level of NCK1-AS1 in all AML, non-M3 AML and cytogenetically normal AML (CN-AML) patients was significantly higher than that in the control group (P < 0.01, P < 0.05, P < 0.01, respectively). In non-M3 AML, patients with high NCK1-AS1 expression had a significantly lower hemoglobin level than those with low NCK1-AS1 expression (P =0.036), furthermore, NCK1-AS1 ^high patients had shorter overall survival than NCK1-AS1^low patients (P =0.0378). Multivariate analysis showed that NCK1-AS1 expression was an independent adverse factor in patients with non-M3 AML ( HR =2.392, 95% CI :1.089-5.255, P =0.030). In addition, NCK1 expression was also significantly upregulated in all AML, non-M3 AML and CN-AML patients compared with controls (P < 0.01, P < 0.01, P < 0.001, respectively). There was a certain correlation between NCK1-AS1 and NCK1 expression (r =0.37, P =0.0058). CONCLUSION High expression of NCK1-AS1 in AML indicates poor prognosis of AML patients.
Humans ; Leukemia, Myeloid, Acute/genetics* ; RNA, Long Noncoding/genetics* ; Oncogene Proteins/genetics* ; Adaptor Proteins, Signal Transducing/genetics* ; Prognosis ; Male ; Female ; Middle Aged ; Adult ; Case-Control Studies ; Clinical Relevance

OBJECTIVE: To preliminarily investigate the effect of buccal acupuncture therapy on ameliorating postoperative pain and enhancing recovery quality among patients undergoing radical resection of gastrointestinal cancers. METHODS: Fifty-two participants were randomized at a 1:1 ratio to either the buccal acupuncture or the control group. The acupuncture protocol entailed targeting 5 predetermined acupoints [CA-2 (Upper jiao), CA-3 (Middle jiao), CA-4 (Lower jiao), CA-6 (back), and CA-7 (waist) and two adjustable acupoints [CA-1 (head) and CA-8 (sacrum)] on each side of the face. The outcomes included the Numeric Rating Scale (NRS) scores for each day within 7 days postoperatively, 15-Item Quality of Recovery Scale (QoR-15) scores, analgesics consumption during and after surgery, incidences of postoperative nausea and vomiting, and perioperative levels of interleukin-6 and glucose. Adverse events related to acupuncture were recorded. RESULTS: Of the initial 52 participants, 46 completed the study and were included in the analysis. Findings indicated that the buccal acupuncture group experienced significantly reduced resting NRS scores in post-anesthesia care unit and throughout the postoperative phase (P=0.001 and P=0.003, respectively), along with enhanced QoR-15 scores on the 3rd postoperative day (P=0.008), compared to the control group. No notable differences were identified in the remaining indicators (P>0.05). CONCLUSION Buccal acupuncture therapy demonstrated significant effectiveness in reducing postoperative pain and improving recovery quality for patients undergoing radical resection of gastrointestinal cancers, presenting a viable intervention without associated adverse outcomes. (Trial registration No. ChiCTR2200060441).
Humans ; Male ; Pilot Projects ; Female ; Acupuncture Therapy/methods* ; Pain, Postoperative/therapy* ; Middle Aged ; Gastrointestinal Neoplasms/surgery* ; Aged ; Acupuncture Points ; Adult

Objective:To establish and validate a prediction model based on least absolute shrinkage and selection operator（LASSO）regression and classification and regression tree（CART）algorithm for acute kidney injury（AKI）in PICU.Methods:The prospective derivation cohort consisted of 350 critically ill children admitted to the PICU of Children′s Hospital of Soochow University from September 2020 to January 2021.The external data set consisting of 866 critically ill children admitted to the PICU of Children′s Hospital of Soochow University from February 2021 to February 2022 was employed for the external validation.Clinical data was obtained from the electronic medical record system，including demographic characteristics，laboratory data and the pediatric risk of mortality Ⅲ（PRISM Ⅲ）score.The variables associated with AKI were identified using LASSO regression.Subsequently，a decision tree prediction model was built using the CART algorithm.The predictive value of decision tree prediction model was evaluated using the receiver operating characteristic（ROC）curve，calibration curve，and decision curve analysis.Results:Among the 350 children in the derivation cohort，107（30.6%）developed AKI during the PICU stay；and of 866 children in the external validation cohort，165（19.1%）developed AKI during the PICU stay.The LASSO regression screened 16 candidate variables for further analysis，and the decision tree model ultimately identified 4 variables more closely associated with AKI，including fold change in serum creatinine from baseline，urine volume，PRISM Ⅲ，and C-reactive protein.The decision tree model exhibited high accuracy with AUC of 0.92，0.88，and 0.86 in the training，internal validation，and external validation cohorts，respectively.The model demonstrated good calibration and clinical applicability based on the calibration curve and decision curve analysis.Conclusion:The decision tree model based on the 4 identified clinical indicators，including fold change in serum creatinine from baseline，urine volume，PRISM Ⅲ，and C-reactive protein，is effective for the early prediction of AKI.