Skin fibrosis is primarily characterized by excessive fibroblasts proliferation and aberrant extracellular matrix accumulation, leading to pathological conditions such as hypertrophic scars, keloids, and systemic sclerosis. This dynamic and complex process involves intricate interactions among various resident skin cells and inflammatory cells, ultimately resulting in extracellular matrix deposition and even invasive growth. The maintenance of cellular phenotypes and functions relies on dynamic metabolic responses, and cellular signal transduction is closely coupled with metabolic processes. Given that the coupling of cell metabolism and signaling in the skin fibrosis microenvironment plays a critical role in inflammatory responses and fibrotic activation, modulation of these metabolic pathways may offer novel therapeutic strategies for inhibiting or even reversing the progression of skin fibrosis. This review systematically summarizes the metabolic characteristics of various cell types involved in skin fibrosis, with a focus on core metabolic reprogramming mechanisms such as hyperactive glycolysis, dysregulated fatty acid metabolism, cellular metabolic dysfunction and dysregulated mTOR/AMPK signaling. Furthermore, potential intervention strategies targeting these metabolic pathways are explored, thereby providing new research perspectives for the treatment of skin fibrosis.
Humans ; Fibrosis/metabolism* ; Skin/metabolism* ; Signal Transduction ; Fibroblasts/pathology* ; TOR Serine-Threonine Kinases/metabolism* ; Skin Diseases/pathology* ; Cellular Reprogramming ; Metabolic Reprogramming

ObjectiveTo analyze the temporal trend of knockdown resistance (kdr) gene mutations highly correlated with pyrethroid resistance in field populations of Aedes aegypti in Jinghong City of Yunnan Province, and to provide a scientific basis for formulating rational insecticide use strategies. MethodsAdult mosquito samples of Aedes aegypti from 2016 to 2023 and larvae mosquito samples from July 2022 to June 2023 were collected in Jinghong City of Yunnan Province. Allele specific PCR (AS-PCR) was used to measure kdr mutations at amino acid positions 989, 1016 and 1534 of the voltage-gated sodium ion channel (VGSC) gene. Data such as mutation rate and mutation allele frequency were calculated, SPSS software was used to perform trend chi square tests on mutation rate and mutation allele frequency with year and month, as well as comparison of mutation allele frequencies and genotype distributions between the dry and rainy seasons, thereby delineating the temporal trend of kdr gene mutations. ResultsAmong the 173 samples collected from 2016 to 2023, the mutation rates of S989P and V1016G were 100.00% for each year, while the mutation rate of F1534C ranged from 62.50% to 100.00%. The mutation rate and mutation allele frequency of F1534C were increased over the years (χ²=22.079, P<0.001; χ²=42.971, P<0.001). Concurrently, the proportion of the PPGGCC genotype was increased annually (χ²=60.790, P<0.001). Among the 288 samples collected from July 2022 to June 2023, the monthly mutation rates for S989P, V1016G, and F1534C were consistently 100.00%. There was only one type of mutation present, namely S989P+V1016G+F1534C. In the combinations of the three genotypes, the SPGGCC genotype accounted for 1.39% (4/288), the PPGGFC accounted for 2.78% (8/288), and the PPGGCC had the highest proportion at 95.83% (276/288). After tesiting the samples collected in August 2023, the mutation rates of 989, 1016 and 1534 sites of VGSC in females, males, and larvae of the same generation were all 100.00%. ConclusionSince 2016, the gene mutations at S989P and V1016G loci in the VGSC gene of wild Aedes aegypti in Jinghong City have remained consistently at 100.00%, while the mutation rate and mutant allele frequency of F1534C have increased year by year during the testing period. By 2023, the mutation rates at three loci in the VGSC gene of Aedes aegypti in Jinghong City had all reached 100.00%, and neither changes in insect developmental stage nor gender differences during transmission exerted a detectable impact on the mutation rates. In the control of Aedes aegypti in Jinghong City, the use of pyrethroid insecticides should be stopped or reduced, and regular monitoring of kdr genes should be carried out to promptly detect new mutations.

Objective:Using methylation characteristics of human genes to construct machine learning predictive models for screening cervical cancer and precancerous lesions.Methods:Human DNA methylation detection was performed on 224 cervical exfoliated cell specimens from the Cancer Hospital of the Chinese Academy of Medical Sciences, Tianjin Central Hospital of Gynecology Obstetrics, Xinmi Maternal and Child Health Hospital of Henan Province, West China Second Affiliated Hospital of Sichuan University, and Heping Hospital Affiliated to Changzhi Medical College collected during April 2014 and March 2015. The hypermethylated gene fragments related to cervical cancer were selected by high-density, high-association, and hypermethylated gene fragment screening and the LASSO regression algorithm. Taking cervical intraepithelial neoplasia grade 2 (CIN2) or more severe lesions as the research outcome, machine learning predictive models based on the random forest (RF), naive Bayes (NB), and support vector machine (SVM) algorithm, respectively, were constructed. A total of 144 outpatient specimens were used as the training set and 80 cervical exfoliated cell specimens from women participating in the cervical cancer screening program were used as the test set to verify the predictive models. Using histological diagnosis results as the gold standard, the detection efficacy for CIN2 or more severe lesions of the three machine learning predictive models were compared with that of the human papilloma virus (HPV) detection and cytological diagnosis.Results:In the training set of 144 cases, there were 34 cases of HPV positivity, with a positive rate of 23.61%. Cytologically, there were 37 cases diagnosed as no intraepithelial lesion or malignancy (NILM), and 107 cases diagnosed as atypical squamous cells of undetermined significance (ASC-US) or above. Histologically, there were 28 cases without cervical intraepithelial neoplasia or benign cervical lesions, 31 cases of CIN1, 18 cases of CIN2, 31 cases of CIN3, and 36 cases of squamous cell carcinoma. Seven hypermethylated gene fragments were selected from 45 genes, and three machine learning prediction models based on the RF, NB, and SVM algorithm, respectively, were constructed. In the validation set of 80 cases, there were 28 cases of HPV positivity, with a positive rate of 35.00%. Cytologically, there were 65 cases diagnosed as NILM and 15 cases as ASC-US or above. Histologically, there were 39 cases without cervical intraepithelial neoplasia or benign cervical lesions, 10 cases of CIN1, 10 cases of CIN2, 11 cases of CIN3, and 10 cases of squamous cell carcinoma. In the validation set, the area under the curve (AUC) values of the RF model, NB model, SVM model, HPV detection, and cytological diagnosis of CIN2 or above were 0.90, 0.88, 0.82, 0.68, and 0.45, respectively. The DeLong test showed that there was no statistically significant difference in the AUC values between the RF, NB, and SVM models (all P＞0.05), and the AUC values of the RF and NB models were higher than that of HPV detection (both P＜0.01), and the AUC values of the RF, NB, and SVM models were higher than that of cytological diagnosis (all P＜0.01). Compared with the NB model, the sensitivity of the RF model was similar (80.65% vs. 77.42%), but the specificity of the NB model was much higher than that of the RF model (93.88% vs. 73.47%). Conclusion:Among the machine learning prediction models for cervical cancer and precancerous lesions constructed based on human DNA methylation, the NB model has good predictive performance for CIN2 and above lesions, and may be used for screening of cervical cancer and precancerous lesions.

Objective:Using methylation characteristics of human genes to construct machine learning predictive models for screening cervical cancer and precancerous lesions.Methods:Human DNA methylation detection was performed on 224 cervical exfoliated cell specimens from the Cancer Hospital of the Chinese Academy of Medical Sciences, Tianjin Central Hospital of Gynecology Obstetrics, Xinmi Maternal and Child Health Hospital of Henan Province, West China Second Affiliated Hospital of Sichuan University, and Heping Hospital Affiliated to Changzhi Medical College collected during April 2014 and March 2015. The hypermethylated gene fragments related to cervical cancer were selected by high-density, high-association, and hypermethylated gene fragment screening and the LASSO regression algorithm. Taking cervical intraepithelial neoplasia grade 2 (CIN2) or more severe lesions as the research outcome, machine learning predictive models based on the random forest (RF), naive Bayes (NB), and support vector machine (SVM) algorithm, respectively, were constructed. A total of 144 outpatient specimens were used as the training set and 80 cervical exfoliated cell specimens from women participating in the cervical cancer screening program were used as the test set to verify the predictive models. Using histological diagnosis results as the gold standard, the detection efficacy for CIN2 or more severe lesions of the three machine learning predictive models were compared with that of the human papilloma virus (HPV) detection and cytological diagnosis.Results:In the training set of 144 cases, there were 34 cases of HPV positivity, with a positive rate of 23.61%. Cytologically, there were 37 cases diagnosed as no intraepithelial lesion or malignancy (NILM), and 107 cases diagnosed as atypical squamous cells of undetermined significance (ASC-US) or above. Histologically, there were 28 cases without cervical intraepithelial neoplasia or benign cervical lesions, 31 cases of CIN1, 18 cases of CIN2, 31 cases of CIN3, and 36 cases of squamous cell carcinoma. Seven hypermethylated gene fragments were selected from 45 genes, and three machine learning prediction models based on the RF, NB, and SVM algorithm, respectively, were constructed. In the validation set of 80 cases, there were 28 cases of HPV positivity, with a positive rate of 35.00%. Cytologically, there were 65 cases diagnosed as NILM and 15 cases as ASC-US or above. Histologically, there were 39 cases without cervical intraepithelial neoplasia or benign cervical lesions, 10 cases of CIN1, 10 cases of CIN2, 11 cases of CIN3, and 10 cases of squamous cell carcinoma. In the validation set, the area under the curve (AUC) values of the RF model, NB model, SVM model, HPV detection, and cytological diagnosis of CIN2 or above were 0.90, 0.88, 0.82, 0.68, and 0.45, respectively. The DeLong test showed that there was no statistically significant difference in the AUC values between the RF, NB, and SVM models (all P＞0.05), and the AUC values of the RF and NB models were higher than that of HPV detection (both P＜0.01), and the AUC values of the RF, NB, and SVM models were higher than that of cytological diagnosis (all P＜0.01). Compared with the NB model, the sensitivity of the RF model was similar (80.65% vs. 77.42%), but the specificity of the NB model was much higher than that of the RF model (93.88% vs. 73.47%). Conclusion:Among the machine learning prediction models for cervical cancer and precancerous lesions constructed based on human DNA methylation, the NB model has good predictive performance for CIN2 and above lesions, and may be used for screening of cervical cancer and precancerous lesions.

Objective: To establish a dynamic syndromic surveillance system in the border areas of Yunnan Province based on information technology, evaluate its effectiveness and timeliness in the response to common communicable disease epidemics and improve the communicable disease prevention and control in border areas. Methods: Three border counties were selected for full coverage as study areas, and dynamic surveillance for 14 symptoms and 6 syndromes were conducted in medical institutions, the daily collection of information about students' school absence in primary schools and febrile illness in inbound people at border ports were conducted in these counties from January 2016 to February 2018 to establish an early warning system based on mobile phone and computer platform for a field experimental study. Results: With syndromes of rash, influenza-like illness and the numbers of primary school absence, the most common communicable disease events, such as hand foot and mouth disease, influenza and chickenpox, can be identified 1-5 days in advance by using EARS-3C and Kulldorff time-space scanning models with high sensitivity and specificity. The system is easy to use with strong security and feasibility. All the information and the warning alerts are released in the form of interactive charts and visual maps, which can facilitate the timely response. Conclusions: This system is highly effective and easy to operate in the detection of possible outbreaks of common communicable diseases in border areas in real time, so the timely and effective intervention can be conducted to reduce the risk of local and cross-border communicable disease outbreaks. It has practical application value.
Humans ; Influenza, Human ; Sentinel Surveillance ; Syndrome ; China ; Cell Phone

Objective    To investigate the diagnostic value and safety of electromagnetic navigation bronchoscopy combined with radial endobronchial ultrasound in peripheral pulmonary nodules. Methods    The clinical imaging, surgical and pathological data of 60 patients with 76 peripheral pulmonary nodules who underwent electromagnetic navigation bronchoscopy combined with radial endobronchial ultrasound guided biopsy in the Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School from June 2020 to June 2021 were retrospectively analyzed. The diagnosis rate and complications were analyzed and summarized. The 76 pulmonary nodules were divided into a small pulmonary nodules group (10 nodules, diameter≤1 cm) and a pulmonary nodules group (1 cm

【Objective】 To investigate the effect of transfusion-transmitted Zika virus (ZIKV) on the expression of non-coding circular RNA (hsa_circ_0001613) and the role of hsa_circ_0001613 in Zika virus replication. 【Methods】 Human adenocarcinomic alveolar basal epithelial cells (A549) were seeded on a 12-well plate at 1.8×10⁵/ well and infected with ZIKV at 0.05 MOI. The Total RNAs were isolated every day for 5 days after infection, and the relative expression level of hsa_circ_0001613 was detected by qRT-PCR. In addition, 10nM siRNA-hsa_circ_0001613 was transfected into 2×10⁵/ well A549 cells to specifically knock down the expression level of hsa_circ_0001613. 24h later, the cells were infected with ZIKV (MOI=0.05). Total RNAs were isolated at day 1-5 post-infection, proteins were extracted 96h post-infection. ZIKV replication, relative host antiviral gene expression, and interferon stimulated response element (ISRE) activity were tested using qRT-PCR, western blot and dual luciferase assay, respectively. 【Results】 The relative expression of hsa_circ_0001613 decreased significantly after 1-5 days of ZIKV infection. Knockdown of hsa_circ_0001613 inhibited ZIKV replication. Meanwhile, hsa_circ_0001613 knockdown significantly upregulated IFN-α/β and its downstream interferon-stimulated genes (ISGs) expression, also increased ISRE activity. 【Conclusion】 ZIKV infection significantly suppressed hsa_circ_0001613 expression in A4549 cells. Preliminary study indicated that hsa_circ_0001613 knockdown inhibited ZIKV replication possibly through activating type-Ⅰ IFN signaling pathway as showed by increased ISGs expression and ISRE activity.

Autoantibodies ; China ; Cohort Studies ; Follow-Up Studies ; Humans ; Idiopathic Pulmonary Fibrosis

To ensure the safety of medications, it is vital to accurately authenticate species of the Apocynaceae family, which is rich in poisonous medicinal plants. We identified Apocynaceae species by using nuclear internal transcribed spacer 2 (ITS2) and psbA-trnH based on experimental data. The identification ability of ITS2 and psbA-trnH was assessed using specific genetic divergence, BLAST1, and neighbor-joining trees. For DNA barcoding, ITS2 and psbA-trnH regions of 122 plant samples of 31 species from 19 genera in the Apocynaceae family were amplified. The PCR amplification for ITS2 and psbA-trnH sequences was 100%. The sequencing success rates for ITS2 and psbA-trnH sequences were 81% and 61%, respectively. Additional data involved 53 sequences of the ITS2 region and 38 sequences of the psbA-trnH region were downloaded from GenBank. Moreover, the analysis showed that the inter-specific divergence of Apocynaceae species was greater than its intra-specific variations. The results indicated that, using the BLAST1 method, ITS2 showed a high identification efficiency of 97% and 100% of the samples at the species and genus levels, respectively, via BLAST1, and psbA-trnH successfully identified 95% and 100% of the samples at the species and genus levels, respectively. The barcode combination of ITS2/psbA-trnH successfully identified 98% and 100% of samples at the species and genus levels, respectively. Subsequently, the neighbor joining tree method also showed that barcode ITS2 and psbA-trnH could distinguish among the species within the Apocynaceae family. ITS2 is a core barcode and psbA-trnH is a supplementary barcode for identifying species in the Apocynaceae family. These results will help to improve DNA barcoding reference databases for herbal drugs and other herbal raw materials.

In December 2019, an outbreak of viral pneumonia began in Wuhan, Hubei Province, which caused the spread of infectious pneumonia to a certain extent in China and neighboring countries and regions, and triggered the epidemic crisis. The coronavirus disease 2019(COVID-19) is an acute respiratory infectious disease listed as a B infectious disease, which is managed according to standards for A infectious disease. Traditional Chinese medicine and integrated traditional Chinese and Western medicine have played an active role in the prevention and control of this epidemic. China's ethnomedicine has recognized infectious diseases since ancient times, and formed a medical system including theory, therapies, formula and herbal medicines for such diseases. Since the outbreak of the COVID-19 epidemic, Tibet Autonomous Region, Qinghai Province, Inner Mongolia Autonomous Region, Xinjiang Uygur Autonomous Region and Chuxiong Autonomous Prefecture of Yunnan, Qiandongnan Autonomous Prefecture of Guizhou have issued the prevention and control programs for COVID-19 using Tibetan, Mongolian, Uygur, Yi and Miao medicines. These programs reflect the wisdom of ethnomedicine in preventing and treating diseases, which have successfully extracted prescriptions and preventive measures for the outbreak of the epidemic from their own medical theories and traditional experiences. In this paper, we summarized and explained the prescriptions and medicinal materials of ethnomedicine in these programs, and the origin of Tibetan medicine prescriptions and Mongolian medicine prescriptions in ancient books were studied. These become the common characteristics of medical prevention and treatment programs for ethnomedicine to formulate therapeutic programs under the guidance of traditional medicine theories, recommend prescriptions and prevention and treatment methods with characteristics of ethnomedicine, and focus on the conve-nience and standardization. However, strengthening the support of science and technology and the popularization to the public, and improving the participation of ethnomedicine in national public health services and the capacity-building to deal with sudden and critical diseases are key contents in the development of ethnomedicine in the future.
Betacoronavirus ; China ; Coronavirus Infections ; drug therapy ; Humans ; Medicine, Traditional ; Pandemics ; Pneumonia, Viral ; drug therapy ; Tibet