Fibrosis, the pathological scarring of vital organs, is a severe and often irreversible condition that leads to progressive organ dysfunction. It is particularly pronounced in organs like the liver, kidneys, lungs, and heart. Despite its clinical significance, the full understanding of its etiology and complex pathogenesis remains incomplete, posing substantial challenges to diagnosing, treating, and preventing the progression of fibrosis. Among the various molecular players involved, platelet-derived growth factor-C (PDGF-C) has emerged as a crucial factor in fibrotic diseases, contributing to the pathological transformation of tissues in several key organs. PDGF-C is a member of the PDGFs family of growth factors and is synthesized and secreted by various cell types, including fibroblasts, smooth muscle cells, and endothelial cells. It acts through both autocrine and paracrine mechanisms, exerting its biological effects by binding to and activating the PDGF receptors (PDGFRs), specifically PDGFRα and PDGFRβ. This binding triggers multiple intracellular signaling pathways, such as JAK/STAT, PI3K/AKT and Ras-MAPK pathways. which are integral to the regulation of cell proliferation, survival, migration, and fibrosis. Notably, PDGF-C has been shown to promote the proliferation and migration of fibroblasts, key effector cells in the fibrotic process, thus accelerating the accumulation of extracellular matrix components and the formation of fibrotic tissue. Numerous studies have documented an upregulation of PDGF-C expression in various fibrotic diseases, suggesting its significant role in the initiation and progression of fibrosis. For instance, in liver fibrosis, PDGF-C stimulates hepatic stellate cell activation, contributing to the excessive deposition of collagen and other extracellular matrix proteins. Similarly, in pulmonary fibrosis, PDGF-C enhances the migration of fibroblasts into the damaged areas of lungs, thereby worsening the pathological process. Such findings highlight the pivotal role of PDGF-C in fibrotic diseases and underscore its potential as a therapeutic target for these conditions. Given its central role in the pathogenesis of fibrosis, PDGF-C has become an attractive target for therapeutic intervention. Several studies have focused on developing inhibitors that block the PDGF-C/PDGFR signaling pathway. These inhibitors aim to reduce fibroblast activation, prevent the excessive accumulation of extracellular matrix components, and halt the progression of fibrosis. Preclinical studies have demonstrated the efficacy of such inhibitors in animal models of liver, kidney, and lung fibrosis, with promising results in reducing fibrotic lesions and improving organ function. Furthermore, several clinical inhibitors, such as Olaratumab and Seralutinib, are ongoing to assess the safety and efficacy of these inhibitors in human patients, offering hope for novel therapeutic options in the treatment of fibrotic diseases. In conclusion, PDGF-C plays a critical role in the development and progression of fibrosis in vital organs. Its ability to regulate fibroblast activity and influence key signaling pathways makes it a promising target for therapeutic strategies aiming at combating fibrosis. Ongoing research into the regulation of PDGF-C expression and the development of PDGF-C/PDGFR inhibitors holds the potential to offer new insights and approaches for the diagnosis, treatment, and prevention of fibrotic diseases. Ultimately, these efforts may lead to the development of more effective and targeted therapies that can mitigate the impact of fibrosis and improve patient outcomes.

Objective To explore the severity of loneliness among the elderly in communities in Shanghai,and to identify factors associated with social and emotional loneliness respectively.Methods A cross-sectional study was conducted in older adults aged 65 years or above in Pudong New Area,Jing'an District and Huangpu District in Shanghai from Mar to Jun 2021.In Pudong New Area,multi-stage stratified random sampling was conducted based on the age and gender distribution of Shanghai,while in Huangpu District and Jing'an District convenience sampling was conducted.A total of 635 samples were included in the study.Loneliness was assessed using the De Jong Gierveld Loneliness Scale with social and emotional loneliness subscales.Logistic regression analyses were conducted to identify factors associated with social and emotional loneliness.Results Among the 635 participants,only 53 older adults(8.4%)were not lonely.Female(OR=0.46,95%CI:0.31-0.70),higher self-efficacy(OR=0.97,95%CI:0.94-1.00),more objective social support(OR=0.96,95%CI:0.93-0.99)were associated with less severe social loneliness.Meanwhile,higher level of education(secondary education,OR=0.56,95%CI:0.34-0.95;college or above,OR=0.30,95%CI:0.11-0.83)and higher self-efficacy(OR=0.96,95%CI:0.93-0.99)were associated with less severe emotional loneliness,while depression(OR=3.41,95%CI:1.76-6.60)and worse social capital(OR=2.02,95%CI:1.29-3.16)were associated with more severe emotional loneliness.Conclusion Up to 91.6%of the elderly in our study sample were moderately lonely or above.The factors associated with social loneliness include self-efficacy,gender and social support.The factors associated with emotional loneliness are self-efficacy,education level,depression,and social capital.

Objective To investigate the risk factors for portopulmonary hypertension(POPH)in liver cirrhosis,and to construct a noninvasive predictive model.Methods A retrospective analysis was performed for the clinical data of 310 cirrhotic patients with portal hypertension who were hospitalized in The Third Affiliated Hospital of Hebei Medical University from January 2013 to August 2022,and according to whether pulmonary artery systolic pressure was≥40 mmHg on ultrasound,the patients were divided into POPH group with 31 patients and non-POPH group with 279 patients.The independent-samples t test was used for comparison of normally distributed continuous data between two groups,and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups;the chi-square test or the Fisher's exact test was used for comparison of categorical data between two groups.A binary Logistic regression analysis was used to determine the independent risk factors for POPH,and a nomogram prediction model was constructed.The Bootstrap resampling method was used for internal validation,and C-index and calibration curve were used to assess the discriminatory ability and consistency of the model.The rms package was used to plot the nomogram.Results Compared with the non-POPH group,the POPH group had a significantly younger age,a significantly higher proportion of women or patients with hepatic encephalopathy or Child-Pugh class C disease,and significantly higher levels of direct bilirubin,Model for End-Stage Liver Disease score,albumin-bilirubin(ALBI)score,international normalized ratio,prothrombin time,FIB-4 index,LOK score,and Forns index,as well as significantly lower levels of serum albumin,alanine aminotransferase,gamma-glutamyl transpeptidase,hemoglobin,total cholesterol,and triglycerides(all P<0.05).The multivariate analysis showed that sex(odds ratio[OR]=0.172,95%confidence interval[CI]:0.064-0.462,P<0.001),age(OR=0.944,95%CI:0.901-0.989,P=0.016),ALBI score(OR=3.091,95%CI:1.100-8.687,P=0.032),and hepatic encephalopathy(OR=3.466,95%CI:1.331-9.031,P=0.011)were independent risk factors for POPH.A predictive model for POPH in liver cirrhosis was established based on the above independent risk factors,with a C-index of 0.796(95%CI:0.701-0.890),suggesting that the model had good discriminatory ability,and the calibration curve showed that the model had good calibration ability,suggesting that the model had certain predictive efficacy.Conclusion Young female individuals,elevated ALBI score,and comorbidity with hepatic encephalopathy are independent risk factors for POPH in patients with liver cirrhosis,and the predictive model established based on these factors has a certain clinical application value.

177Lu-prostate specific membrane antigen(PSMA)radio-ligand therapy has been approved abroad for advanced prostate cancer and has been in several clinical trials in China.Based on domestic clinical practice and experimental data and referred to international experience and viewpoints,the expert group forms a consensus on the clinical application of 177Lu-PSMA radio-ligand therapy in prostate cancer to guide clinical practice.

Objective To explore the relationship between the polymorphism of excision repair cross-complementation group 1 (ERCC1) C8092A locus and the efficacy and prognosis of platinum-based chemotherapy for lung cancer (LC), and to provide a theoretical basis for precision treatment of LC. Methods From January 2014 to October 2017, 120 patients from two tertiary hospitals in Haikou City, and with pathologically confirmed lung cancer treated with platinum-based chemotherapy were selected as the research objects. After informed consent was obtained, peripheral blood samples were collected for DNA extraction, and the genotype of ERCC1 C8092A locus was detected by mass spectrometry. WHO's Response Evaluation Criteria in Solid Tumours (RECIST) was used to judge patients' chemotherapy efficacy and patients' survival status was obtained by telephone follow-up and other means. Results Among the 120 LC patients, the genotype frequencies of ERCC1 C8092A locus were 67 cases of CC wildtype (55.8%), 45 cases of CA heterozygous type (37.5%), and 8 cases of AA rare mutation type (6.7%), which conformed to Hardy-Weinberg equilibrium (χ2=0.140, P>0.05). The total effective rate of chemotherapy was 32.5%, with the highest effective rate in patients with the CA genotype (42.2%) at the ERCC1 C8092A locus and the lowest in patients with the CC genotype (25.4%). The overall one-year survival rate was 68.3% and the three-year survival rate was 35.8%. The patients with ERCC1 C8092A AA genotype had the lowest survival rate, with a one-year survival rate of 50.0% and three-year survival rate of only 25.0%. However, there were no statistical differences in the overall survival rate among the three genotypes of carriers of ERCC1 C8092A (χ2=0.328, P=0.849). Conclusions The polymorphism of ERCC1 C8092A locus is associated with the efficacy of platinum-based chemotherapy for LC, and patients with CA genotype have the highest efficacy. The one-year and three-year survival rates of patients with CC genotype are significantly higher than those of CA and AA genotypes.

Objective To investigate the biological basis of disease and syndrome by studying the spectrum of myocardial tissue metabolites in the rat model of coronary heart disease with heart blood stasis syndrome.Methods SD rats were randomly divided into sham-operation group and model group.The left anterior descending coronary artery was ligated to prepare the rat model of coronary heart disease with heart blood stasis syndrome.The general condition was observed,and the tongue chromaticity,electrocardiogram,cardiac function were detected.HE staining and transmission electron microscopy were used to observe myocardial tissue morphology and ultrastructure.UPLC-MS technology was used to investigate the differential metabolites in rat myocardial tissue,and enrichment analysis was conducted on metabolic pathways.Results Compared with the sham-operation group,the tongue chromaticity R,G,B values of model group rats were significantly reduced(P<0.05),ECG heart rate and ST segment elevation amplitude significantly increased(P<0.05),LVEF and LVFS significantly decreased,and LVIDs and LVIDd significantly increased(P<0.05).Myocardial tissue pathology revealed that the structure was blurred,inflammatory cells infiltrated,mitochondria swelled,ruptured,and dissolved,and crista structure fracture decreased.A total of 29 potential biomarkers with significant differences between the sham-operation group and the model group were identified in metabolomics(7 upregulated and 22 downregulated),with the majority of 10 pathways enriched in thiamine metabolism,arginine biosynthesis,purine metabolism,aminoacyl-tRNA biosynthesis,alanine,aspartate and glutamate metabolism,pentose and glucuronate interconversions,glycolysis/gluconeogenesis,valine,leucine and isoleucine degradation,TCA cycle,pyruvate metabolism.Conclusion Ligation of the left anterior descending coronary artery can mimic the pathological process of coronary heart disease with blood stasis syndrome in a good way,and its pathological mechanism involves the disruption of multi-level metabolic networks such as glucose metabolism,mitochondrial energy metabolism,amino acid metabolism,protein biosynthesis,and purine metabolism.

Objective:To investigate the clinical value of deep learning model based on contrast enhanced ultrasound (CEUS) video in the differential diagnosis of benign and malignant liver tumors.Methods:Between May 2010 and June 2022, 1 213 patients who underwent CEUS examination for liver masses in the Affiliated Hospital of Southwest Medical University were retrospectively collected, and the enrolled patients were divided into training and independent test cohorts with December 31, 2021 as the time cut-off. In the training cohort, the TimeSformer algorithm was used as the infrastructure, and multiple fixed-time segments were obtained from CEUS arterial videos by using the sliding window of the video, and the classification results of the entire video were obtained after fusing the features of multiple segments, so as to build a deep learning model based on CEUS videos. In the independent test cohort, ROC curves were used to verify the validity of the model and compared with three radiologists with different CEUS experience (R1, R2, and R3, with 3, 6, and 10 years of CEUS experience, respectively).Results:A total of 1 213 patients with liver masses were included in the study, including 1 066 patients in the training cohort (426 cases of malignancy) and 147 patients in the independent test cohort (50 cases of malignancy). The area under curve (AUC)value of deep learning model was 0.93±0.01 in the training cohort and 0.89±0.01 in the independent test cohort, and the accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 80.42%, 74.19%, 92.00%, 94.52% and 65.71%, respectively. Among the three radiologists, R1 had the lowest diagnostic performance, with accuracy, sensitivity, specificity, PPV and NPV of 67.83%, 51.61%, 98.00%, 97.96% and 52.13%, respectively, while the above indicators of R3 were 82.52%, 76.36%, 94.00%, 95.95% and 68.12%, respectively. McNemar′s test showed that the difference between R1 and the deep learning model was statistically significant ( P<0.001), while the differences between R2 and R3 and the deep learning model were not statistically significant ( P=0.720, 0.868). In addition, the analysis time of the model for a single case was (340.24±16.32)ms, while the average analysis time of radiologists was 62.9 s. Conclusions:The deep learning model based on CEUS can better identify benign and malignant liver masses, and may reach the diagnostic level of experienced radiologists.

China has become the world's second largest consumer market for cosmetics. The rapid development of the cosmetics industry requires that its regulatory management and standard and regulation also need to keep pace with the times and constantly improve. This paper compares domestic and foreign standards for skin sensitisation test, skin phototoxicity test and skin photoallergy test, and analysis the specific problems of the current standards and make recommendations.

Objective:To investigate the diagnostic performance of different thyroid imaging reporting and data systems (TI-RADS) in the diagnosis of medullary thyroid carcinoma (MTC) .Methods:A total of 160 thyroid nodules diagnosed as MTC by postoperative pathology from Aug. 2011 to Aug. 2022 at the First Affiliated Hospital of Zhengzhou University were included. Additionally, 160 papillary thyroid carcinomas (PTC) and 160 benign nodules were randomly selected as controls during the same period. Differences in gender, age, nodule diameter and various ultrasound features were observed. The nodules were classified according to American College of Radiology (ACR) TI-RADS, artificial intelligence (AI) TI-RADS and Chinese (C TI-RADS). Then, receiver operating characteristic curve (ROC) were plotted to calculate the diagnostic value. The Kendall concordance coefficient was used to evaluate the interobserver consistency of each TI-RADS system.Results:There was no statistically significant difference in gender among the three groups ( χ2=1.17, P=0.558). However, significant differences were observed in age and nodule diameter ( F=12.08,40.12, P<0.001 for both). The area under ROC (AUC) for diagnosing MTC and benign nodules using ACR, AI, and C-TIRADS were 0.762, 0.773, and 0.761, respectively, with no statistically significant differences ( Z=1.33, 0.01, 0.87, P=0.183, 0.994, 0.386). However, the sensitivity of C TI-RADS (87.5%) was lower than that of ACR and AI TI-RADS (both 95.0%) ( P=0.018). After combining the biopsy threshold, the false negative rate of C-TIRADS was lower than that of ACR (30.6% vs. 41.3%) ( P=0.048) and AI TIRADS (30.6% vs. 43.1%) ( P=0.020). The inter-observer diagnostic consistency of C-TIRADS was superior to ACR (0.884 vs. 0.819, P<0.001) and AI TIRADS (0.884 vs. 0.839) ( P<0.001) . Conclusions:AI and ACR TI-RADS have higher sensitivity in diagnosing MTC, while C TI-RADS has a lower puncture missed diagnosis rate. AI has similar diagnostic performance to ACR TI-RADS and can replace ACR TI-RADS.

Purpose::To identify the risk factors for training-related lower extremity muscle injuries in young males by a non-invasive method of body composition analysis.Methods::A total of 282 healthy young male volunteers aged 18 -20 years participated in this cohort study. Injury location, degree, and injury rate were adjusted by a questionnaire based on the overuse injury assessment methods used in epidemiological studies of sports injuries. The occurrence of training injuries is monitored and diagnosed by physicians and treated accordingly. The body composition was measured using the BodyStat QuadScan 4000 multifrequency Bio-impedance system at 5, 50, 100 and 200 kHz to obtain 4 impedance values. The Shapiro-Wilk test was used to check whether the data conformed to a normal distribution. Data of normal distribution were shown as mean ± SD and analyzed by t-test, while those of non-normal distribution were shown as median (Q 1, Q 3) and analyzed by Wilcoxon rank sum test. The receiver operator characteristic curve and logistic regression analysis were performed to investigate risk factors for developing training-related lower extremity injuries and accuracy. Results::Among the 282 subjects, 78 (27.7%) developed training injuries. Lower extremity training injuries revealed the highest incidence, accounting for 23.4% (66 cases). These patients showed higher percentages of lean body mass ( p = 0.001), total body water (TBW, p=0.006), extracellular water ( p=0.020) and intracellular water ( p=0.010) as well as a larger ratio of basal metabolic rate/total weight ( p=0.006), compared with those without lower extremity muscle injuries. On the contrary, the percentage of body fat ( p=0.001) and body fat mass index ( p=0.002) were lower. Logistic regression analysis showed that TBW percentage > 65.35% ( p=0.050, odds ratio =3.114) and 3rd space water > 0.95% ( p=0.045, odds ratio =2.342) were independent risk factors for lower extremity muscle injuries. Conclusion::TBW percentage and 3rd space water measured with bio-impedance method are potential risk factors for predicting the incidence of lower extremity muscle injuries in young males following training.