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Abstract Background This study assessed the diagnosis, staging and treatment guidance of lung cancer (LC) based on seven tumor-associated autoantibodies (TAAbs) —p53, PGP9.5, SOX2, GBU4-5, MAGE A1, CAGE, and GAGE7. Methods ELISA was used to determine the TAAb serum levels in 433 patients diagnosed with LC (161 surgical patients) and 76 patients with benign lung disease (16 surgical patients). The statistical characteristic of the TAAbs was compared among patients with different clinicopathological features. Pre- to postoperative changes in TAAb levels were analyzed to determine their value of LC. Results Among all patients, the positive rate of the seven TAAbs was 23.4%, sensitivity was 26.3%, accuracy was 36.3%, specificity was 93.4%, positive predictive value was 95.8%, and negative predictive value was 18.2%; the positive rate for the LC group (26.3%) was significantly higher than that for the benign group (6.6%; P

Abstract Background Gene variants are responsible for more than half of hearing loss, particularly in nonsyndromic hearing loss (NSHL). The most common pathogenic variant in SLC26A4 gene found in East Asian populations is c.919-2A > G followed by c.2168A > G (p.H723R). This study was to evaluate their variant frequencies in patients with NSHL from special education schools in nine different areas of Southwest China’s Yunnan. Methods We performed molecular characterization by PCR-products directly Sanger sequencing of the SLC26A4 c.919-2AG and c.2168 A > G variants in 1167 patients with NSHL including 533 Han Chinese and 634 ethnic minorities. Results The SLC26A4 c.919-2A > G variant was discovered in 8 patients with a homozygous state (0.69%) and twenty-five heterozygous (2.14%) in 1167 patients with NSHL. The total carrier rate of the c.919-2A > G variant was found in Han Chinese patients with 4.50% and ethnic minority patients with 1.42%. A significant difference existed between the two groups (P G allele variant frequency was ranged from 3.93% in Kunming to zero in Lincang and Nvjiang areas of Yunnan. We further detected the SLC26A4 c.2168 A > G variant in this cohort with one homozygotes (0.09%) and seven heterozygotes (0.60%), which was detected in Baoshan, Honghe, Licang and Pu`er areas. Between Han Chinese group (0.94%) and ethnic minority group (0.47%), there was no statistical significance (P > 0.05). Three Han Chinese patients (0.26%) carried compound heterozygosity for c.919-2A > G and c.2168 A > G. Conclusion These data suggest that the variants in both SLC26A4 c.919-2A > G and c.2168 A > G were relatively less frequencies in this cohort compared to the average levels in most regions of China, as well as significantly lower than that in Han-Chinese patients. These results broadened Chinese population genetic information resources and provided more detailed information for regional genetic counselling for Yunnan.

Abstract Background Hypertrophic cardiomyopathy (HCM), an autosomal dominant genetic disease, is the main cause of sudden death in adolescents and athletes globally. Hypoxia and immune factors have been revealed to be related to the pathology of HCM. There is growing evidence of a role for hypoxia and inflammation as triggers and enhancers in the pathology in HCM. However, the role of hypoxia- and immune-related genes in HCM have not been reported. Methods Firstly, we obtained four HCM-related datasets from the Gene Expression Omnibus (GEO) database for differential expression analysis. Immune cells significantly expressed in normal samples and HCM were then screened by a microenvironmental cell population counter (MCP-counter) algorithm. Next, hypoxia- and immune-related genes were screened by the LASSO + support vector machine recursive feature elimination (SVM-RFE) and weighted gene co-expression network analysis (WGCNA). Single-gene enrichment analysis and expression validation of key genes were then performed. Finally, we constructed a competing endogenous RNA (ceRNA) network of key genes. Results In this study, 35 differentially expressed hypoxia genes were found. By using LASSO + SVM-RFE analysis, 10 more targets with differentially expressed hypoxia genes were identified. The MCP-count algorithm yielded five differentially expressed immune cells, and after assessing them for WGCNA characteristics, 612 immune genes were discovered. When hypoxia and immune genes were combined for cross-tabulation analysis, three hypoxia- and immune-related genes (ATP2A2, DDAH1, and OMA1) were identified. Conclusion Based on hypoxia characteristic genes, three key genes were identified. These were also significantly related to immune activation, which proves a theoretical basis and reference value for studying the relationship between HCM and hypoxia and immunity. Graphical Abstract

Abstract Cardiovascular disease (CVD) is the leading cause of noncommunicable disease-related death worldwide, and effective therapeutic strategies against CVD are urgently needed. Mitochondria dysfunction involves in the onset and development of CVD. Nowadays, mitochondrial transplantation, an alternative treatment aimed at increasing mitochondrial number and improving mitochondrial function, has been emerged with great therapeutic potential. Substantial evidence indicates that mitochondrial transplantation improves cardiac function and outcomes in patients with CVD. Therefore, mitochondrial transplantation has profound implications in the prevention and treatment of CVD. Here, we review the mitochondrial abnormalities that occur in CVD and summarize the therapeutic strategies of mitochondrial transplantation for CVD.

Abstract Background Ferroptosis, which is characterized by lipid peroxidation and iron accumulation, is closely associated with the pathogenesis of acute renal injury (AKI). Cyanidin-3-glucoside (C3G), a typical flavonoid that has anti-inflammatory and antioxidant effects on ischemia‒reperfusion (I/R) injury, can induce AMP-activated protein kinase (AMPK) activation. This study aimed to show that C3G exerts nephroprotective effects against I/R-AKI related ferroptosis by regulating the AMPK pathway. Methods Hypoxia/reoxygenation (H/R)-induced HK-2 cells and I/R-AKI mice were treated with C3G with or without inhibiting AMPK. The level of intracellular free iron, the expression of the ferroptosis-related proteins acyl-CoA synthetase long chain family member 4 (ACSL4) and glutathione peroxidase 4 (GPX4), and the levels of the lipid peroxidation markers 4-hydroxynonenal (4-HNE), lipid reactive oxygen species (ROS) and malondialdehyde (MDA) were examined. Results We observed the inhibitory effect of C3G on ferroptosis in vitro and in vivo, which was characterized by the reversion of excessive intracellular free iron accumulation, a decrease in 4-HNE, lipid ROS, MDA levels and ACSL4 expression, and an increase in GPX4 expression and glutathione (GSH) levels. Notably, the inhibition of AMPK by CC significantly abrogated the nephroprotective effect of C3G on I/R-AKI models in vivo and in vitro. Conclusion Our results provide new insight into the nephroprotective effect of C3G on acute I/R-AKI by inhibiting ferroptosis by activating the AMPK pathway.

Abstract Background Although the central scar is an essential imaging characteristic of renal oncocytoma (RO), its utility in distinguishing RO from renal cell carcinoma (RCC) has not been well explored. The study aimed to evaluate whether the combination of CT characteristics of the peripheral tumor parenchyma (PTP) and central hypodense area (CHA) can differentiate typical RO with CHA from RCC. Methods A total of 132 tumors on the initial dataset were retrospectively evaluated using four-phase CT. The excretory phases were performed more than 20 min after the contrast injection. In corticomedullary phase (CMP) images, all tumors had CHAs. These tumors were categorized into RO (n = 23), clear cell RCC (ccRCC) (n = 85), and non-ccRCC (n = 24) groups. The differences in these qualitative and quantitative CT features of CHA and PTP between ROs and ccRCCs/non-ccRCCs were statistically examined. Logistic regression filters the main factors for separating ROs from ccRCCs/non-ccRCCs. The prediction models omitting and incorporating CHA features were constructed and evaluated, respectively. The effectiveness of the prediction models including CHA characteristics was then confirmed through a validation dataset (8 ROs, 35 ccRCCs, and 10 non-ccRCCs). Results The findings indicate that for differentiating ROs from ccRCCs and non-ccRCCs, prediction models with CHA characteristics surpassed models without CHA, with the corresponding areas under the curve (AUC) being 0.962 and 0.914 versus 0.952 and 0.839 respectively. In the prediction models that included CHA parameters, the relative enhancement ratio (RER) in CMP and enhancement inversion, as well as RER in nephrographic phase and enhancement inversion were the primary drivers for differentiating ROs from ccRCCs and non-ccRCCs, respectively. The prediction models with CHA characteristics had the comparable diagnostic ability on the validation dataset, with respective AUC values of 0.936 and 0.938 for differentiating ROs from ccRCCs and non-ccRCCs. Conclusion The prediction models with CHA characteristics can help better differentiate typical ROs from RCCs. When a mass with CHA is discovered, particularly if RO is suspected, EP images with longer delay scanning periods should be acquired to evaluate the enhancement inversion characteristics of CHA.

Abstract Background Primary cardiac schwannoma remains extremely rare and difficult to distinguish from other myocardial tumours. We report a case of cardiac schwannoma that occurred in the lateral wall of the right ventricle and grew in the myocardial walls. It is the third case of schwannoma that occurred in the free wall of the right ventricle. Moreover, we reviewed and summarised the literature for cases involving benign cardiac schwannomas. Case presentation We present a case of a 64-year-old woman who presented to our centre with syncope for 1–2 min. Echocardiogram and contrast-enhanced computed tomography subsequently revealed a 2.9 × 1.9 cm homogeneous mass originating from the anterior wall of the right ventricle. The patient underwent thoracotomy to resect the mass, which was pathologically verified as Schwann cell tumour. Conclusions This is a rare case added to the limited existing literature on cardiac schwannoma. Comprehensive analysis of various imaging examinations is helpful to determine the extent of the tumour. Complete surgical resection is recommended for similar cases involving cardiac schwannomas, especially when the patient has related symptoms. Patients generally have a good prognosis. The pathogenesis of cardiac schwannoma needs further research in order to prevent and manage this rare lesion.

Abstract Mitochondria-induced cell death is a vital mechanism of heart failure (HF). Thus, identification of mitochondria-related genes (Mito-RGs) based on transcriptome sequencing data of HF might provide novel diagnostic markers and therapeutic targets for HF. First, bioinformatics analysis was conducted on the GSE57338, GSE76701, GSE136547, and GSE77399 datasets in the Gene Expression Omnibus. Next, we analyzed HF-Mito differentially expressed genes (DEGs) using the protein–protein interaction (PPI) network for obtaining critical genes and exploring their functions. Subsequently, immune cell scores of the HF and normal groups were compared. The potential alteration mechanisms of the key genes were investigated by constructing a competing endogenous RNA network. Finally, we predicted potential therapeutic agents and validated the expression levels of the key genes. Twenty-three HF-Mito DEGs were acquired in the GSE57338 dataset, and the PPI network obtained four key genes, including IFIT3, XAF1, RSAD2, and MX1. According to gene set enrichment analysis, the key genes showed high enrichment in myogenesis and hypoxia. Immune cell analysis demonstrated that aDCs, B cells, and 20 other immune cell types varied between the HF and normal groups. Moreover, we observed that H19 might affect the expression of IFIT3, AXF1, and RSAD2. PCGEM1 might regulate RSAD2 expression. A total of 515 potential therapeutic drugs targeting the key genes, such as tretinoin, silicon dioxide, and bisphenol A, were acquired. Finally, IFIT3, RSAD2, and MX1 expression increased in HF samples compared with normal samples in the GSE76701 dataset, conforming to the GSE57338 dataset analysis. This work screened four key genes, namely, IFIT3, XAF1, RSAD2, and MX1, which can be further explored in subsequent studies for their specific molecular mechanisms in HF.

Abstract Background The interaction between tumor microenvironment (TME) and tumors offers various targets in mounting anti-tumor immunotherapies. However, the prognostic biomarkers in endometrial carcinoma (EC) are still limited. Here, we aimed to analyze the TME features and identify novel prognostic biomarkers for EC. Methods ESTIMATE, CIBERSORT, protein-protein interaction (PPI) network, univariate and multivariate Cox regression, and functional enrichment analysis were performed to identify immune- and survival-related hub genes as well as possible molecular mechanisms. The limma package and deconvolution algorithm were adopted to estimate the abundance of tumor-infiltrating immune cells (TICs) and their relationship with the target gene. In the validation section, tissue microarrays (TMAs) of EC and multiplex immunohistochemistry (m-IHC) were evaluated to validate the expression of TNFRSF4, and its correlation with immune markers, including CD4, CD8, and FOXP3. Besides, the receiver operating characteristic (ROC) curve was plotted to determine the diagnostic performance of TNFRSF4, CD4, CD8, and FOXP3 in EC. Results Two genes, TNFRSF4 and S1PR4, were screened out from 386 intersection differential expression genes (DEGs) shared by ImmuneScore and StromalScore in EC. Highlighted by TNFRSF4, we found that it was not only positively correlated with the TICs (mainly CD4+ T cells, CD8+ T cells, and Tregs) but significantly related to the prognosis in patients of EC, both verified by data from The Cancer Genome Altas (TCGA)-EC database and clinical samples. At the same time, the expression trend of TNFRSF4 was further confirmed by an integrated meta-analysis based on six microarrays from the Gene Expression Omnibus database (GEO). Conclusions Collectively, TNFRSF4, a previously unrecognized key player in EC, could serve as a potential biomarker for prognosis prediction and immunomodulation of EC.

Abstract Background Metformin is a first-line drug in type 2 diabetes mellitus (T2DM) treatment, yet whether metformin may increase all-cause or cardiovascular mortality of T2DM patients remains inconclusive. Methods We searched PubMed and Embase for data extracted from inception to July 14, 2020, with a registration in PROSPERO (CRD42020177283). This study included randomized controlled trials (RCT) assessing the cardiovascular effects of metformin for T2DM. This study is followed by PRISMA and Cochrane guideline. Risk ratio (RR) with 95% CI was pooled across trials by a random-effects model. Primary outcomes include all-cause mortality and cardiovascular mortality. Results We identified 29 studies that randomly assigned patients with 371 all-cause and 227 cardiovascular death events. Compared with untreated T2DM patients, metformin-treated patients was not associated with lower risk of all-cause mortality (RR: 0.98; 95%CI: 0.69–1.38; P = 0.90), cardiovascular mortality (RR: 1.13; 95% CI: 0.60, 2.15; P = 0.70), macrovascular events (RR: 0.87; 95%CI: 0.70–1.07; P = 0.19), heart failure (RR: 1.02; 95% CI:0.61–1.71; P = 0.95), and microvascular events (RR: 0.78; 95% CI:0.54–1.13; P = 0.19). Combination of metformin with another hypoglycemic drug was associated with higher risk of all-cause mortality (RR: 1.49; 95% CI: 1.02, 2.16) and cardiovascular mortality (RR: 2.21; 95% CI: 1.22, 4.00) compared with hypoglycemic drug regimens with no metformin. Conclusion The combination of metformin treatment may impose higher risk in all-cause and cardiovascular mortality. This finding, at least in part, shows no evidence for benefits of metformin in combination in terms of all-cause/cardiovascular mortality and cardiovascular events for T2DM. However, the conclusion shall be explained cautiously considering the limitations from UK Prospective Diabetes Study (UKPDS).

Abstract Background To establish pharmacokinetic parameters and a radiomics model based on dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) for predicting sentinel lymph node (SLN) metastasis in patients with breast cancer. Methods A total of 164 breast cancer patients confirmed by pathology were prospectively enrolled from December 2017 to May 2018, and underwent DCE-MRI before surgery. Pharmacokinetic parameters and radiomics features were derived from DCE-MRI data. Least absolute shrinkage and selection operator (LASSO) regression method was used to select features, which were then utilized to construct three classification models, namely, the pharmacokinetic parameters model, the radiomics model, and the combined model. These models were built through the logistic regression method by using 10-fold cross validation strategy and were evaluated on the basis of the receiver operating characteristics (ROC) curve. An independent validation dataset was used to confirm the discriminatory power of the models. Results Seven radiomics features were selected by LASSO logistic regression. The radiomics model, the pharmacokinetic parameters model, and the combined model yielded area under the curve (AUC) values of 0.81 (95% confidence interval [CI]: 0.72 to 0.89), 0.77 (95% CI: 0.68 to 0.86), and 0.80 (95% CI: 0.72 to 0.89), respectively, for the training cohort and 0.74 (95% CI: 0.59 to 0.89), 0.74 (95% CI: 0.59 to 0.90), and 0.76 (95% CI: 0.61 to 0.91), respectively, for the validation cohort. The combined model showed the best performance for the preoperative evaluation of SLN metastasis in breast cancer. Conclusions The model incorporating radiomics features and pharmacokinetic parameters can be conveniently used for the individualized preoperative prediction of SLN metastasis in patients with breast cancer.

Abstract Background The torsion of normal adnexa is rare during pregnancy, especially in the third trimester. Nonspecific symptoms and signs as well as the limitations of ultrasound (US) make the diagnosis difficult, resulting in the loss of adnexa and fetal compromise. The magnetic resonance imaging (MRI) features of the torsion of normal adnexa are not classically described during pregnancy and only reported in a few cases. We find some different MRI features of the torsion of normal adnexa in late pregnancy and its diagnosis and treatment values are discussed in our report. Case presentation A 27-year-old woman at 31 + 5 weeks’ gestation presented to the emergency department with a three-day history of the left lower abdominal pain. US discovered a mass of 87 × 61 mm in the left abdomen, but did not show whether the mass originated from the left ovary or the uterus. MRI showed the left ovary was increased in size to 82 × 42 × 85 mm with peripheral follicles. On fat-suppressed T2-weighted images, the signal intensity of the lesion was significantly decreased compared with the right ovary. The adjacent fallopian tube was found to be thickened. The radiologists diagnosed ovary infarction secondary to adnexal torsion. With the provisional diagnosis of adnexal torsion, the patient was taken to surgery. The left adnexal torsion was found during surgery. There was extensive hemorrhage and necrosis, so a left salpingo-oophorectomy was performed. The histopathology confirmed an extensively hemorrhagic fallopian tube and ovary with partial necrosis. Conclusion We believe MRI is helpful where US is indeterminate in diagnosis of the torsion of normal adnexa in advanced pregnancy. We found that aside from hyperintensity on fat-saturated T1-weighted images, the low signal intensity on T2-weighted images can also reflect adnexal hemorrhage in conjunction with the torsion of normal adnexa.

Abstract Background Cardiovascular disease (CVD) is a risk factor for cognitive impairment in the elderly. Manifestations of subclinical CVDs can be found in patients with cognitive impairment. The aim of the present study was to test the hypothesis that patients with mild cognitive impairment (MCI) have different magnetic resonance imaging (MRI)-derived regional myocardial motion indices compared with healthy controls. Methods Eleven MCI patients (age, 65.5 years ±5.9; range, 55–81 years old) and 11 sex−/age-matched healthy volunteers were enrolled. All of the participants underwent a head MRI and cardiac MRI. Global cortical atrophy (GCA) was graded on the head MRI. The left ventricular ejection fraction (LVEF) and regional strain, strain rate, displacement and velocity were measured on cine images. The GCA scores, global cardiac function and regional myocardial motion indices were compared between MCI patients and healthy controls using the t-test. Results MCI patients had a higher GCA score than healthy controls (p = 0.048). However, there was no significant difference in LVEF between MCI patients and controls. Compared to healthy controls, MCI patients had a lower peak radial strain (29.1% ± 24.1% vs. 46.4% ± 43.4%, p

Abstract Background Aging is characterized by a gradual breakdown of cellular structures. Nuclear abnormality is a hallmark of progeria in human. Analysis of age-dependent nuclear morphological changes in Caenorhabditis elegans is of great value to aging research, and this calls for an automatic image processing method that is suitable for both normal and abnormal structures. Results Our image processing method consists of nuclear segmentation, feature extraction and classification. First, taking up the challenges of defining individual nuclei with fuzzy boundaries or in a clump, we developed an accurate nuclear segmentation method using fused two-channel images with seed-based cluster splitting and k-means algorithm, and achieved a high precision against the manual segmentation results. Next, we extracted three groups of nuclear features, among which five features were selected by minimum Redundancy Maximum Relevance (mRMR) for classifiers. After comparing the classification performances of several popular techniques, we identified that Random Forest, which achieved a mean class accuracy (MCA) of 98.69%, was the best classifier for our data set. Lastly, we demonstrated the method with two quantitative analyses of C. elegans nuclei, which led to the discovery of two possible longevity indicators. Conclusions We produced an automatic image processing method for two-channel C. elegans nucleus-labeled fluorescence images. It frees biologists from segmenting and classifying the nuclei manually.