[This corrects the article DOI: 10.1016/j.apsb.2022.05.019.].

Preeclampsia is a placenta-originated disorder closely associated with impaired placental development and immune imbalance at the maternal-fetal interface. As a critical process in the regulation of cellular homeostasis, autophagy plays a pivotal role in trophoblast syncytialization, invasion, and immune tolerance at the maternal-fetal interface. Moderate autophagy enhances trophoblast function and promotes spiral artery remodeling, whereas insufficient or excessive autophagy correlates with placental pathological features of preeclampsia, including impaired syncytialization, protein aggregate accumulation, and immune dysregulation. Although trophoblast-specific autophagy deficiencies in animal models can manifest preeclampsia-like phenotypes, clinical studies reveal tissue-specific variability in autophagy-related protein expression, which may be attributable to placental regional heterogeneity, disease subtypes, and sampling timepoints. Future investigations integrating multi-stage clinical cohorts, multicellular models, and genetically modified animals are warranted to elucidate the dynamic role of autophagy in preeclampsia pathogenesis and establish its causal relationship with disease progression, thereby providing a basis for targeted therapeutic strategies.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Preeclampsia is a placenta-originated disorder closely associated with impaired placental development and immune imbalance at the maternal-fetal interface. As a critical process in the regulation of cellular homeostasis, autophagy plays a pivotal role in trophoblast syncytialization, invasion, and immune tolerance at the maternal-fetal interface. Moderate autophagy enhances trophoblast function and promotes spiral artery remodeling, whereas insufficient or excessive autophagy correlates with placental pathological features of preeclampsia, including impaired syncytialization, protein aggregate accumulation, and immune dysregulation. Although trophoblast-specific autophagy deficiencies in animal models can manifest preeclampsia-like phenotypes, clinical studies reveal tissue-specific variability in autophagy-related protein expression, which may be attributable to placental regional heterogeneity, disease subtypes, and sampling timepoints. Future investigations integrating multi-stage clinical cohorts, multicellular models, and genetically modified animals are warranted to elucidate the dynamic role of autophagy in preeclampsia pathogenesis and establish its causal relationship with disease progression, thereby providing a basis for targeted therapeutic strategies.

Objective To explore the correlation of glucose and lipid metabolism indicators combined with antiphospholipid antibodies with the prognosis of patients with atherosclerosis.Methods A total of 128 patients with atherosclerosis treated in our hospital from April 2021 to March 2023 were selected as study group,and 48 healthy individuals as control group.Glycolipid metabolism indexes and antiphospholipid antibody level of the two groups were compared,and the predictive value of glycolipid metabolism indexes,antiphospholipid antibodies and combined detection for the prognosis of patients with atherosclerosis were analyzed by ROC.Results TC,TG,ACL,and anti-β2-GP1 in the study group was higher than that in the control group(P＜0.05).The study group was divided into two sub-groups according to the prognosis.The expression level of TC,TG,ACL,and anti-β 2-GP1 in poor prognosis group was higher than that in good prognosis group(P＜0.05).TC,TG,ACL,and anti-β 2-GP1 was positively correlated with the poor prognosis of patients with atherosclerosis(P＜0.05).ROC curve showed that the predictive value of six combined tests for the prognosis of patients with atherosclerosis was higher than that of single test of TC,TG,ACL,and anti-β2-GP1(P＜0.05).Conclusion The combined detection of TC,TG,ACL,and anti-β2-GP1 has high predictive value for the prognosis of patients with atherosclerosis.

Metabolic reprogramming is a hallmark of cancer, including lung cancer. However, the exact underlying mechanism and therapeutic potential are largely unknown. Here we report that protein arginine methyltransferase 6 (PRMT6) is highly expressed in lung cancer and is required for cell metabolism, tumorigenicity, and cisplatin response of lung cancer. PRMT6 regulated the oxidative pentose phosphate pathway (PPP) flux and glycolysis pathway in human lung cancer by increasing the activity of 6-phospho-gluconate dehydrogenase (6PGD) and α-enolase (ENO1). Furthermore, PRMT6 methylated R324 of 6PGD to enhancing its activity; while methylation at R9 and R372 of ENO1 promotes formation of active ENO1 dimers and 2-phosphoglycerate (2-PG) binding to ENO1, respectively. Lastly, targeting PRMT6 blocked the oxidative PPP flux, glycolysis pathway, and tumor growth, as well as enhanced the anti-tumor effects of cisplatin in lung cancer. Together, this study demonstrates that PRMT6 acts as a post-translational modification (PTM) regulator of glucose metabolism, which leads to the pathogenesis of lung cancer. It was proven that the PRMT6-6PGD/ENO1 regulatory axis is an important determinant of carcinogenesis and may become a promising cancer therapeutic strategy.

Objective:To evaluate the safety and long-term effectiveness of endoscopic foam sclerotherapy (FS) combined with endoscopic rubber band ligation (ERBL)in the treatment of grade Ⅱ-Ⅲ internal hemorrhoids.Methods:Consecutive patients diagnosed as having grade Ⅱ-Ⅲ internal hemorrhoids in Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from January to December 2020 were prospectively enrolled in the study, and randomly divided into ERBL group and FS combined with ERBL group. The 24 h visual analogue scale (VAS) for pain and 1-week degree of bleeding were evaluated after the treatment. After follow-up of 6 months, the effectiveness of treatment was evaluated.Results:A total of 84 patients with age of 54.4±7.9 years were enrolled, 57.1% (48/84) males, and 73.8% (62/84)grade Ⅱ internal hemorrhoids. Forty-three patients were assigned to the ERBL group and 41 to the FS combined with ERBL group. There was no significant difference between the two groups in baseline data ( P>0.05). In the FS combined with ERBL group, the mean amount of polidocanol foam was 13.8±2.5 mL, the mean number of injection site was 4.7±1.2, and the median scores of VAS was 0 (0, 3), which was significantly lower than that of ERBL group [2 (0, 4), Z=-2.116, P=0.034]. The bleeding rate 1 week after treatment in the ERBL and FS combined with ERBL group were 20.9% (9/43) and 29.3% (12/41), respectively, and mild bleeding was the main symptom. There was no significant difference between the two groups in the bleeding degree ( U=807.0, P=0.378). After 6 months of follow-up, the total effective rates in the ERBL group and the FS combined with ERBL group were 81.4% (35/43) and 90.2% (37/41), respectively ( U=684.5, P=0.044). Conclusion:FS combined with ERBL can effectively relieve post-treatment perianal pain, and improve the long-term effectiveness.

Objective:To explore the microcirculation formation mechanism of contrast-enhanced ultrasonography imaging performance in rabbits with limb muscle crush injury.Methods:Seventy-two New Zealand white rabbits were randomly divided into two groups. A limb muscle crush injury model was created by airing a balloon cuff device with a force of 40 kPa. Contrast-enhanced ultrasonography parameters were detected in the first group.In vivo microcirculation parameters were detected in the second group. Fine blood vessel diameter and blood flow velocity were calculated before extrusion and 0.5 h, 2 h, 6 h, 24 h, and 3 days after decompression.Results:Totally six animals died before the end of the experiment (3 rabbits in ultrasonic imaging and microcirculation detection groups, respectively). Compared with the uninjured muscle, the reperfusion of the injured muscle showed early and high enhancement in contrast-enhanced ultrasonography images. The peak intensity and area under the curve were significantly higher than those of the control subgroup at each time point after decompression(all P<0.05), and reached the peak at 24 h after decompression. The time-intensity curve showed a trend of rapid elevation and gradual drop. In the microcirculation group, compared with the control group, fine artery and vein diameters in the experimental group were wider and the blood flow velocity was slower, especially in the fine veins(all P<0.05). At each time point after decompression, there was a statistical difference between the control subgroup and the control subgroup, and the change reached the peak at 24 h after decompression. The blood flow state showed that the arterioles were dominated by linear flow and linear grain flow at each time point after decompression, and linear grain flow, grain flow and grain pendulum flow were observed in the fine veins. Blood flow stagnation and adhesion of white blood cells and white microthrombus were also observed in the fine veins. Correlation analysis showed that the peak intensity and area under the curve were positively correlated with the inner diameter of arterioles and veins( r=0.84, 0.94; r=0.85, 0.94; all P<0.05), and negatively correlated with the flow velocity of arterioles and veins( r=-0.94, -0.96; r=-0.93, -0.96; all P<0.05). Conclusions:In vivo microcirculation detection can reflect changes in muscle microvascular diameter and blood flow velocity, which have a correlation with quantitative ultrasound imaging parameters.

Objective:To investigate the clinical significance of neutrophil-to-lymphocyte ratio (NLR) in classification of patients with coronavirus disease 2019 (COVID-19).Methods:A retrospective analysis was performed on 72 patients with COVID-19 admitted to the critical ward of Cancer Center of Union Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology in Wuhan from February to March in 2020. The patients were divided into two groups: moderate type (non-severe group) and severe/critical type (severe group). The results of white blood cell count (WBC), neutrophil count (NEU), lymphocyte count (LYM), interleukin-6 (IL-6) and D-dimer were collected at the 2nd day after admission from the two groups, and the NLR was calculated. The diagnostic value of WBC, NEU, LYM, IL-6, D-dimer and NLR on COVID-19 classification was evaluated by the receiver operating characteristic (ROC) curve.Results:A total of 72 COVID-19 patients were enrolled, among whom 52 were moderate, 17 were severe, and 3 were critical. The most common clinical manifestations of patients were fever (70.8%), cough (36.1%), chest tightness and breathlessness (37.5%), diarrhea (15.3%), fatigue (15.3%), vomiting and nausea (11.1%), occasionally accompanied by acute dyspnea (2.8%), and only one patient had no clinical symptom (1.4%). The levels of WBC, NEU, IL-6, D-dimer and NLR in the severe group were significantly higher than those in the non-severe group [WBC (×10 9/L): 7.81±3.65 vs. 5.34±1.69, NEU (×10 9/L): 5.83±3.13 vs. 3.24±1.53, IL-6 (ng/L): 133.63 (71.09, 249.61) vs. 28.05 (6.41, 101.24), D-dimer (mg/L): 0.86 (0.31, 2.56) vs. 0.33 (0.20, 0.71), NLR: 6.14±4.75 vs. 2.66±1.93, all P < 0.05], and the level of LYM was significantly lower than that in the non-severe group (×10 9/L: 1.09±0.56 vs. 1.49±0.74, P < 0.05). The results of ROC curve analysis showed that the areas under ROC curve (AUC) of WBC, NEU, LYM, IL-6, D-dimer and NLR for COVID-19 classification were 0.790 [95% confidence interval (95% CI) was 0.684-0.897), 0.869 (95% CI was 0.789-0.949), 0.719 (95% CI was 0.592-0.847), 0.790 (95% CI was 0.682-0.898), 0.676 (95% CI was 0.526-0.827), and 0.888 (95% CI was 0.814-0.963) respectively. The AUC of NLR was the highest, which was of high diagnostic value; when the optimum cut-off value of NLR was 3.00, the sensitivity was 100%, and the specificity was 73.1%. Conclusion:NLR can be used as a biomarker to predict classification of COVID-19 patients independently, which can provide a theoretical basis for the classification management of COVID-19 patients.