ObjectiveTo investigate the predictive factors for HBsAg clearance in chronic hepatitis B （CHB） patients with a low level of hepatitis B surface antigen （HBsAg） treated with pegylated interferon α-2b （PEG-IFN-α-2b）， to establish a combined predictive model and a nomogram based on multiple factors， and to provide a reference for formulating individualized treatment regimens and predicting treatment outcome in clinical practice. MethodsA retrospective analysis was performed for 167 CHB patients with HBsAg <1 500 IU/mL who attended The Third People’s Hospital of Kunming from January 2022 to January 2024 and were treated with PEG-IFN-α-2b. According to whether clinical cure was achieved， the patients were divided into HBsAg clearance group and HBsAg non-clearance group. Related data were collected， including general information and serological/biochemical/virological indicators at different time points during treatment. The independent samples t-test was used for comparison of normally distributed continuous data， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data； the chi-square test was used for comparison of categorical data. The multivariate logistic regression analysis was used to identify independent influencing factors. The receiver operating characteristic （ROC） curve was used to assess the value of indicators used alone or in combination in predicting clinical cure， and calibration curves were plotted to assess the risk prediction model. ResultsThe univariate analysis showed that there were significant differences between the two groups in age （t=-6.839， P<0.05）， history of nucleos（t）ide analogue treatment for over 1 year （χ²=59.339， P<0.05）， genotype （χ²=4.610， P<0.05）， nonalcoholic fatty liver disease （χ²=5.319， P<0.05）， hepatitis B virus DNA status before treatment （χ²=60.861， P <0.05）， compensated liver cirrhosis （χ²=10.960， P<0.05）， HBeAg status before treatment （χ²=19.060， P<0.05）， a history of interferon treatment （χ²=8.162， P<0.05）， presence of interferon antibodies after treatment （χ²=12.858， P<0.05）， HBsAg level before treatment （Z=-7.412， P<0.05）， alanine aminotransaminase （ALT） level at baseline （Z=-6.117， P<0.05）， ALT level at 12 weeks of treatment （Z=-7.171， P<0.05）， platelet count （PLT） at 24 weeks of treatment （Z=-3.622， P<0.05）， and thyroid stimulating hormone （TSH） level at 24 weeks of treatment （Z=-2.830， P<0.05）. The multivariate logistic regression analysis showed that age （odds ratio ［OR］=1.230， P=0.007）， history of nucleos（t）ide analogue treatment for over 1 year （OR=0.008， P=0.011）， HBeAg status before treatment （OR=0.003， P=0.012）， HBsAg level before treatment （OR=1.005， P=0.014）， ALT level at baseline （OR=0.949， P=0.014）， ALT level at 12 weeks of treatment （OR=0.969， P=0.016）， PLT at 24 weeks of treatment （OR=0.969， P=0.022）， and TSH level at 24 weeks of treatment （OR=3.608， P=0.045） were independent influencing factors for HBsAg clearance at 48 weeks of treatment in CHB patients with HBsAg <1 500 IU/mL. The Hosmer-Lemeshow goodness-of-fit test yielded χ²=1.398， P=0.994， indicating that the model had good fitting. The Bootstrap method was used to perform internal validation of the nomogram model， and there was a good degree of fitting between the calibration curve and the ideal curve， with a mean absolute error of 0.029. The ROC curve analysis showed that the combination of predictive factors had an area under the ROC curve of 0.982 （95% confidence interval： 0.961 — 0.999）， with a sensitivity of 94.10% and a specificity of 93.10%， suggesting that the nomogram model had a good discriminatory ability. For the CHB patients with HBsAg <1 500 IU/mL and different features， further analysis of HBsAg clearance rate at 48 weeks of treatment showed an HBsAg clearance rate of 69.60% for those with HBsAg ≤67.65 IU/mL before treatment， 58.30% for those with a baseline ALT level of ≥62.50 U/L， 68.30% for those with an ALT level of ≥92.50 U/L at 12 weeks of treatment， 42.40% for those with PLT ≥104×10⁹/L at 24 weeks of treatment， and 48.30% for those with a TSH level of ≤1.38 μIU/mL at 24 weeks of treatment， with significant differences between the two groups （all P<0.001）. ConclusionAge， history of nucleos（t）ide analogue treatment for over 1 year， HBeAg status before treatment， HBsAg level before treatment， baseline ALT level， ALT level at 12 weeks of treatment， PLT level at 24 weeks， and TSH level at 24 weeks of treatment are independent predictive factors. The combined prediction nomogram model constructed in this study has a relatively high value in predicting clinical cure at 48 weeks of PEG-IFN-α-2b treatment in CHB patients with HBsAg<1 500 IU/mL， thereby providing a reference for selecting suitable treatment population and predicting clinical cure.

ObjectiveTo investigate the influencing factors for hepatic hydrothorax （HH） before intervention for primary hepatic carcinoma （PHC）， and to construct and assess the nomogram risk prediction model. MethodsA retrospective analysis was performed for the clinical data of 353 hospitalized patients who attended the Third People’s Hospital of Kunming for the first time from October 2012 to October 2021 and there diagnosed with PHC， and according to the presence or absence of HH， they were divided into HH group with 153 patients and non-HH group with 200 patients. General data and the data of initial clinical testing after admission were collected from all PHC 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 groups. After the multicollinearity test was performed for the variables with statistical significance determined by the univariate analysis， the multivariate Logistic regression analysis was used to identify independent influencing factors. The “rms” software package was used to construct a nomogram risk prediction model， and the Hosmer-Lemeshow test and the receiver operating characteristic （ROC） curve were used to assess the risk prediction model； the “Calibration Curves” software package was used to plot the calibration curve， and the “rmda” software package was used to plot the clinical decision curve and the clinical impact curve. ResultsAmong the 353 patients with PHC， there were 153 patients with HH， with a prevalence rate of 43.34%. Child-Pugh class B （odds ratio ［OR］=2.652， 95% confidence interval ［CI］： 1.050 — 6.698， P=0.039）， Child-Pugh class C （OR=7.963， 95%CI： 1.046‍ ‍—‍ ‍60.632， P=0.045）， total protein （OR=0.947， 95%CI： 0.914‍ ‍—‍ ‍0.981， P=0.003）， high-sensitivity C-reactive protein （OR=1.007， 95%CI： 1.001‍ ‍—‍ ‍1.014， P=0.025）， and interleukin-2 （OR=0.801， 95%CI： 0.653‍ ‍—‍ ‍0.981， P=0.032） were independent influencing factors for HH before PHC intervention， and a nomogram risk prediction model was established based on these factors. The Hosmer-Lemeshow test showed that the model had a good degree of fitting （χ²=5.006， P=0.757）， with an area under the ROC curve of 0.752 （95%CI： 0.701‍ ‍—‍ ‍0.803）， a sensitivity of 78.40%， and a specificity of 63.50%. The calibration curve showed that the model had good consistency in predicting HH before PHC intervention， and the clinical decision curve and the clinical impact curve showed that the model had good clinical practicability within a certain threshold range. ConclusionChild-Pugh class， total protein， interleukin-2， and high-sensitivity C-reactive protein are independent influencing factors for developing HH before PHC intervention， and the nomogram model established based on these factors can effectively predict the risk of developing HH.

ObjectiveTo investigate the influencing factors for recompensation in patients with decompensated hepatitis C cirrhosis， and to establish a predictive model. MethodsA total of 217 patients who were diagnosed with decompensated hepatitis C cirrhosis and were admitted to The Third People’s Hospital of Kunming l from January， 2019 to December， 2022 were enrolled， among whom 63 patients who were readmitted within at least 1 year and had no portal hypertension-related complications were enrolled as recompensation group， and 154 patients without recompensation were enrolled as control group. Related clinical data were collected， and univariate and multivariate analyses were performed for the factors that may affect the occurrence of recompensation. The independent-samples t test was used for comparison of normally distributed measurement data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed measurement 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 investigate the influencing factors for recompensation in patients with decompensated hepatitis C cirrhosis， and the receiver operating characteristic （ROC） curve was used to assess the predictive performance of the model. ResultsAmong the 217 patients with decompensated hepatitis C cirrhosis， 63 （29.03%） had recompensation. There were significant differences between the recompensation group and the control group in HIV history （χ²=4.566， P=0.034）， history of partial splenic embolism （χ²=6.687， P=0.014）， Child-Pugh classification （χ²=11.978， P=0.003）， grade of ascites （χ²=14.229， P<0.001）， albumin （t=4.063， P<0.001）， prealbumin （Z=-3.077， P=0.002）， high-density lipoprotein （t=2.854， P=0.011）， high-sensitivity C-reactive protein （Z=-2.447， P=0.014）， prothrombin time （Z=-2.441， P=0.015）， carcinoembryonic antigen （Z=-2.113， P=0.035）， alpha-fetoprotein （AFP） （Z=-2.063， P=0.039）， CA125 （Z=-2.270， P=0.023）， TT3 （Z=-3.304， P<0.001）， TT4 （Z=-2.221， P=0.026）， CD45⁺ （Z=-2.278， P=0.023）， interleukin-5 （Z=-2.845， P=0.004）， tumor necrosis factor-α （Z=-2.176， P=0.030）， and portal vein width （Z=-5.283， P=0.005）. The multivariate analysis showed that history of partial splenic embolism （odds ratio ［OR］=3.064， P=0.049）， HIV history （OR=0.195， P=0.027）， a small amount of ascites （OR=3.390， P=0.017）， AFP （OR=1.003， P=0.004）， and portal vein width （OR=0.600， P<0.001） were independent influencing factors for the occurrence of recompensation in patients with decompensated hepatitis C cirrhosis. The ROC curve analysis showed that HIV history， grade of ascites， history of partial splenic embolism， AFP， portal vein width， and the combined predictive model of these indices had an area under the ROC curve of 0.556， 0.641， 0.560， 0.589， 0.745， and 0.817， respectively. ConclusionFor patients with decompensated hepatitis C cirrhosis， those with a history of partial splenic embolism， a small amount of ascites， and an increase in AFP level are more likely to experience recompensation， while those with a history of HIV and an increase in portal vein width are less likely to experience recompensation.

ObjectiveTo investigate the value of noninvasive imaging detection （FibroScan）， two serological models of gamma-glutamyl transpeptidase-to-platelet ratio （GPR） score and S index， and two inflammatory factors of interleukin-6 （IL-6） and tumor necrosis factor-α （TNF-α） in predicting liver fibrosis in patients with HBeAg-positive chronic hepatitis B （CHB）， as well as the consistency of liver biopsy in pathological staging， and to provide early warning for early intervention of CHB. MethodsA retrospective analysis was performed for 131 HBeAg-positive CHB patients who underwent liver biopsy in The Third People’s Hospital of Kunming from January 2019 to December 2023. The results of liver biopsy were collected from all patients， and related examinations were performed before liver biopsy， including total bilirubin， alanine aminotransferase， platelet count， gamma-glutamyl transpeptidase， albumin， IL-6， TNF-α， liver stiffness measurement （LSM）， and abdominal ultrasound. An analysis of variance was used for comparison of normally distributed continuous data between groups， and the Kruskal-Wallis H test was used for comparison of non-normally distributed continuous data between groups； the chi-square test was used for comparison of categorical data between groups. A Kappa analysis was used to investigate the consistency between LSM noninvasive histological staging and pathological staging based on liver biopsy， and the Spearman analysis was used to investigate the correlation between each variable and FibroScan in the diagnosis of liver fibrosis stage. The Logistic regression analysis was used to construct joint predictive factors. The receiver operating characteristic （ROC） curve was used to evaluate the value of each indicator alone and the joint predictive model in the diagnosis of liver fibrosis， and the Delong test was used for comparison of the area under the ROC curve （AUC）. ResultsIn the consistency check， inflammation degree based on liver biopsy had a Kappa value of 0.807 （P<0.001）， and liver fibrosis degree based on liver biopsy had a Kappa value of 0.827 （P<0.001）， suggesting that FibroScan noninvasive histological staging and liver biopsy showed good consistency in assessing inflammation degree and liver fibrosis stage. Age was positively correlated with LSM， GPR score， S index， IL-6， and TNF-α （all P<0.05）， and GPR score， S index， IL-6， and TNF-α were positively correlated with LSM （all P<0.05）. GPR score， S index， IL-6， and TNF-α were all independent risk factors for diagnosing significant liver fibrosis （≥S2） and progressive liver fibrosis （≥S3） （all P<0.05）. As for each indicator alone， GPR score had the highest value in the diagnosis of significant liver fibrosis （≥S2）， followed by S index， IL-6， and TNF-α， while S index had the highest value in the diagnosis of progressive liver fibrosis （≥S3）， followed by GPR score， TNF-α， and IL-6. The joint model had a higher predictive value than each indicator alone （all P<0.05）. ConclusionThere is a good consistency between FibroScan noninvasive histological staging and pathological staging based on liver biopsy. GPR score， S index， IL-6， and TNF-α are independent risk factors for evaluating different degree of liver fibrosis in CHB， and the combined prediction model established by them can better diagnose liver fibrosis.

Objective To investigate the independent risk factors for portal vein thrombosis(PVT)in patients with viral hepatitis-related decompensated cirrhosis,and to establish and validate a nomogram risk prediction model.Methods A retrospective analysis was performed for the clinical data of 1 116 patients with decompensated HBV/HCV cirrhosis who attended The Third People's Hospital of Kunming for the first time from January 2022 to December 2023,and according to the presence or absence of PVT,they were divided into PVT group and control group.The independent samples t-test or the Mann-Whitney U test was used for comparison of continuous data between groups,and the chi-square test was used for comparison of categorical data between groups.Univariate analysis and least absolute shrinkage and selection operator(LASSO)regression analysis were used to identify variables,and a binary logistic regression analysis was used to obtain independent influencing factors and establish a predictive model,which was visualized using a nomogram.The model was validated based on the receiver operating characteristic(ROC)curve,the area under the ROC curve(AUC),the Hosmer-Lemeshow test,Bootstrap sampling(1 000 iterations),the calibration curve,the decision curve analysis(DCA),and the clinical impact curve(CIC).Results There were 178 patients in the PVT group and 938 patients in the control group,and the prevalence rate of PVT was 15.9%(178/1 116).Male patients accounted for 68.5%(764/1 116),and the patients with drinking,Child-Pugh class B liver function,and ascites accounted for 51.0%(569/1 116),78.8%(879/1 116),and 67.1%(749/1 116),respectively.Compared with the control group,the PVT group had significantly higher age(Z=-2.362,P<0.05),prothrombin time(Z=-2.403,P<0.05),international normalized ratio(Z=-2.470,P<0.05),free thyroxine(Z=-5.910,P<0.05),D-dimer(Z=-5.764,P<0.05),interleukin-6(Z=-6.581,P<0.05),interleukin-10(IL-10)(Z=-3.915,P<0.05),interleukin-8(Z=-3.705,P<0.05),diameter of the portal vein(Z=-9.690,P<0.05),and spleen thickness(Z=-7.183,P<0.05),as well as significantly lower levels of white blood cell count(Z=-2.115,P<0.05),platelet count(Z=-3.026,P<0.05),fibrinogen(Z=-2.169,P<0.05),alanine aminotransferase(Z=-3.151,P<0.05),prealbumin(Z=-3.509,P<0.05),cholinesterase(Z=-3.415,P<0.05),alpha-fetoprotein(Z=-3.513,P<0.05),triglycerides(Z=-2.679,P<0.05),CD3 cell count(Z=-6.059,P<0.05),CD4 cell count(Z=-7.257,P<0.05),CD8 cell count(Z=-2.340,P<0.05),CD4+/CD8+cell ratio(Z=-4.479,P<0.05),triiodothyronine(Z=-3.338,P<0.05),free triiodothyronine(FT3)(Z=-9.560,P<0.05),and portal blood flow velocity(Z=-4.568,P<0.05).The multivariate logistic regression analysis was performed for the variables with statistical significance identified by the LASSO regression analysis,and the results showed that age(odds ratio[OR]=1.046,95%confidence interval[CI]:1.026-1.066),CD4+/CD8+cell ratio(OR=0.568,95%CI:0.410-0.787),FT3(OR=0.956,95%CI:0.944-0.968),IL-10(OR=1.021,95%CI:1.001-1.042),diameter of the portal vein(OR=1.446,95%CI:1.329-1.574),and spleen thickness(OR=1.035,95%CI:1.014-1.055)were independent influencing factors.A model was established as Logit(P)=-8.784+0.045×age-0.566×CD4+/CD8+-0.046×FT3+0.021×IL-10+0.369×diameter of the portal vein+0.034×spleen thickness,and a nomogram model was established and validated based on this model,with an AUC of 0.859(95%CI:0.833-0.887).The Hosmer-Lemeshow test showed that the model had a high goodness of fit(χ2=11.349,P=0.183).Bootstrap internal validation showed a mean absolute error of 0.006 and a C-index of 0.855.The decision curve analysis showed that the model had a high net clinical benefit within a wide range of thresholds.Conclusion Age,CD4+/CD8+ratio,FT3,IL-10,diameter of the portal vein,and spleen thickness may be independent influencing factors for PVT in patients with decompensated HBV/HCV cirrhosis.The predictive model established based on these six variables can help to predict the risk of PVT in patients with hepatitis-related decompensated cirrhosis in the early stage in clinical practice.

IGF-1 is involved in the growth and development of mammals,but its role in sebaceous gland excretion,B16 cell proliferation,and migration in the skin has not been reported yet.This study aims to reveal the function of IGF-1 by detecting its expression in animal skin.Using nano-body screening and purification methods,IGF-1 nanobodies(IGF-1-VHH)were obtained.Using IGF-1-VHH as the primary antibody,Western blot and immunohistochemistry were used to detect the expression of IGF-1 in bovine skin and alpaca acne.IGF-1-VHH was added to melanoma B16 cell culture medium,and CCK-8 and scratch healing methods were used to detect the effects of IGF-1 nanobodies on B16 cell proliferation and migration,as well as their possible molecular mech-anisms.The results showed that the obtained IGF-1-VHH could be applied in immunohistochemis-try and Western blot detection methods,with strong IGF-1 positive expression signals in bovine sebaceous glands and alpaca acne.IGF-1-VHH binds to IGF-1 in cells and has a certain inhibitory effect on the proliferation and migration of B16 cells by regulating the expression of RAS,ERK,and RAF.In summary,IGF-1 maybe involved in the secretion and excretion of sebum in animal skin.IGF-1-VHH inhibits the proliferation and migration of B16 cells by binding to IGF-1,provi-ding a new theoretical basis for ensuring normal physiological function of the skin and clinical di-agnosis and treatment of melanoma.

Objective To analyze the influencing factors of chronic liver failure in patients with primary hepatic carcinoma(PHC)before intervention,and to establish and evaluate a nomogram risk prediction model.Methods A retrospective analysis was conducted by collecting general data and clinical test data within 24 hours of admission for PHC patients.Univariate analysis and Lasso regression were used for variable selection,followed by multivariate logistic regression analysis to identify independent influencing factors for CLF before PHC intervention,leading to the establishment of a nomogram risk prediction model.The model was evaluated using the Hosmer-Lemeshow test,receiver operating characteristic(ROC)curve,calibration curve,clinical decision curve,and clinical impact curve.Result A total of 353 cases of PHC patients were collected,including 153 cases in the liver failure group and 200 cases in the non-liver failure group,with a prevalence rate of 43.3％.Variables selected by Lasso regression included gastrointestinal bleeding,prothrombin time(PT),albumin(ALB),total bilirubin(TBIL),and gamma glutamyl transferase(GGT).Multivariate logistic regression analysis showed that gastrointestinal bleeding(OR=13.549,95％CI:2.899～63.322,P=0.001),PT(OR=1.599,95％CI:1.282～1.995,P＜0.001),TBIL(OR=1.016,95％CI:1.006～1.025,P=0.002),and GGT(OR=1.002,95％CI:1.000～1.003,P=0.028)were independent risk factors for chronic liver failure prior to PHC intervention,leading to the establishment of a nomogram risk prediction model.The Hosmer Lemeshow test showed that the model had a good fit(x2=6.152,P＞0.05);the area under ROC was 0.902(0.869-0.934),with a sensitivity of 80.4％and a specificity of 87.5％.The calibration curve indicated that the model predicts chronic liver failure prior to PHC intervention with good consistency.Clinical decision curve analysis and clinical impact curve analysis showed that the model has good clinical utility within a certain threshold range.Conclusion Gastrointestinal bleeding,PT ≥16.05s,TBIL≥37.80 mmol/L,and GGT≥ 99.00 U/L are independent risk factors for the occurrence of chronic liver failure before PHC intervention.The established nomogram risk prediction model has certain clinical application value in predicting the risk of chronic liver failure before PHC intervention.

Objective To compare the efficacy of Tenofovir Alafenamide(TMF)and Tenofovir Disoproxil Fumarate(TDF)in terms of liver function restoration,virus clearance,immune regulation,anti liver fibrosis,lipid metabolism,bone and renal safety,and adverse reactions.Methods A retrospective analysis was conducted on 110 patients with chronic hepatitis B(CHB)admitted to Kunming Third People's Hospital from January 2022 to December 2022.Patients were divided into the TMF treatment group(n=55)and the TDF treatment group(n=55)based on their treatment regimen.We compared the levels of transaminase levels,antiviral efficacy,T cell subsets,renal function electrolytes,lipid metabolism,four liver fibrosis-related indicators,and changes in liver stiffness grading before and after treatment in two groups of patients.The incidence of adverse reactions post-treatment was also compared.Results After 48 weeks of treatment,the levels of TBIL,ALT,AST,GGT,and GLOB in both groups of patients were significantly lower than pre-treatment levels(P<0.05).The decrease in AST levels in the TMF group was lower than that in the TDF group(P<0.05).After 48 weeks of treatment,the HBV-DNA seroconversion rate in the TMF group(90.90%)was higher than that in the TDF group(83.64%).The serological HBsAg clearance rate in the TMF group(7.3%)was lower than that in the TDF group(9.1%),while the HBeAg clearance rate in the TMF group(38.2%)was significantly higher than that in the TDF group(18.2%),with statistical significance(P<0.05).After 48 weeks of treatment,levels of CD3+,CD4+,and CD8+in both groups were significantly elevated compared to pre-treatment levels(P<0.05);notably,the TMF group had higher post-treatment levels of CD3+,CD4+,and CD8+than the TDF group.After 48 weeks,the average values of HA,IV-C,and LN among the TMF group for liver fibrosis indicators were significantly lower than those in the TDF group(P<0.05).The proportions of F0 and F2 in both groups significantly increased post-treatment,while the proportions of F3 and F4 significantly decreased(P to be supplemented);furthermore,the proportions of F0 and F2 in the TMF group were significantly higher than those in the TDF group,and the proportions of F3 and F4 in the TMF group were significantly lower than those in the TDF group(P<0.05).After 48 weeks,HDL-C levels in the TMF group increased compared to pre-treatment(P<0.05).There were no significant differences in TG,TC,HDL-C,or LDL-C levels in the TDF group compared to pre-treatment(P>0.05).After 48 weeks of treatment,there was no difference in the levels of BUN、Cr、P+,and Ca+in the TMF group compared to pre-treatment(P>0.05);however,BUN and Cr levels in the TDF group were significantly higher than pre-treatment levels,while P+and Ca+levels were significantly lower(P<0.05).The incidence of elevated uric acid and bone pain was significantly higher in the TMF group compared to the TDF group(P<0.05);the incidence of diarrhea and abdominal pain was slightly higher in the TMF group compared to the TDF group(P>0.05).Conclusion Compared to TDF,TMF demonstrates a higher rate of liver function recovery,a greater virological response,enhanced anti fibrotic efficacy,and improved drug safety,making it worthy of clinical application in the future.

IGF-1 is involved in the growth and development of mammals,but its role in sebaceous gland excretion,B16 cell proliferation,and migration in the skin has not been reported yet.This study aims to reveal the function of IGF-1 by detecting its expression in animal skin.Using nano-body screening and purification methods,IGF-1 nanobodies(IGF-1-VHH)were obtained.Using IGF-1-VHH as the primary antibody,Western blot and immunohistochemistry were used to detect the expression of IGF-1 in bovine skin and alpaca acne.IGF-1-VHH was added to melanoma B16 cell culture medium,and CCK-8 and scratch healing methods were used to detect the effects of IGF-1 nanobodies on B16 cell proliferation and migration,as well as their possible molecular mech-anisms.The results showed that the obtained IGF-1-VHH could be applied in immunohistochemis-try and Western blot detection methods,with strong IGF-1 positive expression signals in bovine sebaceous glands and alpaca acne.IGF-1-VHH binds to IGF-1 in cells and has a certain inhibitory effect on the proliferation and migration of B16 cells by regulating the expression of RAS,ERK,and RAF.In summary,IGF-1 maybe involved in the secretion and excretion of sebum in animal skin.IGF-1-VHH inhibits the proliferation and migration of B16 cells by binding to IGF-1,provi-ding a new theoretical basis for ensuring normal physiological function of the skin and clinical di-agnosis and treatment of melanoma.

Objective To investigate the independent risk factors for portal vein thrombosis(PVT)in patients with viral hepatitis-related decompensated cirrhosis,and to establish and validate a nomogram risk prediction model.Methods A retrospective analysis was performed for the clinical data of 1 116 patients with decompensated HBV/HCV cirrhosis who attended The Third People's Hospital of Kunming for the first time from January 2022 to December 2023,and according to the presence or absence of PVT,they were divided into PVT group and control group.The independent samples t-test or the Mann-Whitney U test was used for comparison of continuous data between groups,and the chi-square test was used for comparison of categorical data between groups.Univariate analysis and least absolute shrinkage and selection operator(LASSO)regression analysis were used to identify variables,and a binary logistic regression analysis was used to obtain independent influencing factors and establish a predictive model,which was visualized using a nomogram.The model was validated based on the receiver operating characteristic(ROC)curve,the area under the ROC curve(AUC),the Hosmer-Lemeshow test,Bootstrap sampling(1 000 iterations),the calibration curve,the decision curve analysis(DCA),and the clinical impact curve(CIC).Results There were 178 patients in the PVT group and 938 patients in the control group,and the prevalence rate of PVT was 15.9%(178/1 116).Male patients accounted for 68.5%(764/1 116),and the patients with drinking,Child-Pugh class B liver function,and ascites accounted for 51.0%(569/1 116),78.8%(879/1 116),and 67.1%(749/1 116),respectively.Compared with the control group,the PVT group had significantly higher age(Z=-2.362,P<0.05),prothrombin time(Z=-2.403,P<0.05),international normalized ratio(Z=-2.470,P<0.05),free thyroxine(Z=-5.910,P<0.05),D-dimer(Z=-5.764,P<0.05),interleukin-6(Z=-6.581,P<0.05),interleukin-10(IL-10)(Z=-3.915,P<0.05),interleukin-8(Z=-3.705,P<0.05),diameter of the portal vein(Z=-9.690,P<0.05),and spleen thickness(Z=-7.183,P<0.05),as well as significantly lower levels of white blood cell count(Z=-2.115,P<0.05),platelet count(Z=-3.026,P<0.05),fibrinogen(Z=-2.169,P<0.05),alanine aminotransferase(Z=-3.151,P<0.05),prealbumin(Z=-3.509,P<0.05),cholinesterase(Z=-3.415,P<0.05),alpha-fetoprotein(Z=-3.513,P<0.05),triglycerides(Z=-2.679,P<0.05),CD3 cell count(Z=-6.059,P<0.05),CD4 cell count(Z=-7.257,P<0.05),CD8 cell count(Z=-2.340,P<0.05),CD4+/CD8+cell ratio(Z=-4.479,P<0.05),triiodothyronine(Z=-3.338,P<0.05),free triiodothyronine(FT3)(Z=-9.560,P<0.05),and portal blood flow velocity(Z=-4.568,P<0.05).The multivariate logistic regression analysis was performed for the variables with statistical significance identified by the LASSO regression analysis,and the results showed that age(odds ratio[OR]=1.046,95%confidence interval[CI]:1.026-1.066),CD4+/CD8+cell ratio(OR=0.568,95%CI:0.410-0.787),FT3(OR=0.956,95%CI:0.944-0.968),IL-10(OR=1.021,95%CI:1.001-1.042),diameter of the portal vein(OR=1.446,95%CI:1.329-1.574),and spleen thickness(OR=1.035,95%CI:1.014-1.055)were independent influencing factors.A model was established as Logit(P)=-8.784+0.045×age-0.566×CD4+/CD8+-0.046×FT3+0.021×IL-10+0.369×diameter of the portal vein+0.034×spleen thickness,and a nomogram model was established and validated based on this model,with an AUC of 0.859(95%CI:0.833-0.887).The Hosmer-Lemeshow test showed that the model had a high goodness of fit(χ2=11.349,P=0.183).Bootstrap internal validation showed a mean absolute error of 0.006 and a C-index of 0.855.The decision curve analysis showed that the model had a high net clinical benefit within a wide range of thresholds.Conclusion Age,CD4+/CD8+ratio,FT3,IL-10,diameter of the portal vein,and spleen thickness may be independent influencing factors for PVT in patients with decompensated HBV/HCV cirrhosis.The predictive model established based on these six variables can help to predict the risk of PVT in patients with hepatitis-related decompensated cirrhosis in the early stage in clinical practice.