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PurposeThe prognosis of liver cancer remains unfavorable nowadays, making the search for predictive biomarkers of liver cancer prognosis of paramount importance to guide clinical diagnosis and treatment. This study was conducted to explore more prognostic markers for most HCC.Patients and methodsA total of 330 patients were enrolled in this study according to the inclusion and exclusion criteria. Follow-up data were collected for all patients until the cutoff date of the study, February 2023. In addition, patient outcomes were assessed with progression-free survival (PFS) and overall survival (OS). All statistical analysis was conducted using R 4.2.0 software.ResultsUnivariate analysis illustrated that the GD [the product of gamma-glutamyl transpeptidase (GGT) concentration and D-dimer concentration, GD=GGT*D-dimer] levels were related to PFS (p

The folate receptor-positive circulating tumor cell (FR+-CTC) count can be used to improve the diagnosis rate of lung cancer. The lymphocyte count (LC) and derived neutrophil-to-lymphocyte ratio (dNLR) are involved in inflammatory processes. Whether the FR+-CTC count combined with the dNLR or LC is helpful for diagnosing lung cancer recurrence is not clear. Sixty-eight patients who were initially diagnosed with lung cancer and received first-line treatment were included. The clinicopathological characteristics, routine blood examination results and CTC examination results of the patients were collected. The role of the complete blood count and FR+-CTC count in lung cancer treatment response and prognosis was analyzed. The FR+-CTC count after treatment was significantly correlated with the T stage (p=0.005). Multivariate analysis showed that the pathological type and FR+-CTC count were independent predictors of disease-or progression-free survival (DFS/PFS) in patients with lung cancer (p=0.010 and p=0.030, respectively). The FR+-CTC count, LC and dNLR predicted the recurrence of lung cancer (sensitivity and specificity of the FR+-CTC count, 69.2% and 71.4%; the LC, 50.0% and 88.5%; and the dNLR, 50.0% and 88.1%, respectively). The FR+-CTC count combined with the LC or dNLR improved the diagnostic rate of lung cancer recurrence (sensitivity and specificity of the FR+-CTC count plus the LC, 53.8% and 90.5%, and the FR+-CTC count plus the dNLR, 73.1% and 73.8%, respectively). When these three indicators were combined to predict lung cancer recurrence, the AUC value was 0.817. The FR+-CTC count combined with the dNLR and/or LC after treatment can improve the diagnostic rate of lung cancer recurrence. A higher FR+-CTC count predicts worse DFS/PFS in patients with lung cancer.

As an effective strategy for oncotherapy, developing efficacious drug delivery systems for cancer combination therapy remains a major challenge. To improve nanodrug biocompatibility and composite function facilitating their clinical conversion application, a novel nanocarrier was presented by a facile method through conjugating humic acid with gadolinium ions to synthesize HA-Gd with good biocompatibility and dispersity. HA-Gd exhibited high photothermal conversion efficiency up to 38%, excellent photothermal stability, and high doxorubicin (DOX) loading capacity (93%) with pH-responsive release properties. HA-Gd loading DOX showed a combined chemo-photothermal inhibitory effect on tumor cells. Compared with lipid-DOX, HA-Gd-DOX had a more significant inhibitory effect on tumor growth and fewer side effects. T1-weighted MRI contrast toward tumor tissue provided HA-Gd with an MRI-based cancer diagnosis. This study revealed the great potential of humic acids as a novel vector for developing more drug carriers with desirable functions for clinical anticancer therapy.

Chemotherapy resistance in breast cancer is an important factor affecting the prognosis of breast cancer patients. We computationally analyzed the differences in gene expression before and after chemotherapy in breast cancer patients, drug-sensitive groups, and drug-resistant groups. Through functional enrichment analysis, immune microenvironment analysis, and other computational analysis methods, we identified PRC1, GGTLC1, and IRS1 as genes that may mediate breast cancer chemoresistance through the immune pathway. After validation of certain other clinical datasets and in vitro cellular assays, we found that the above three genes influenced drug resistance in breast cancer patients and were closely related to the tumor immune microenvironment. Our finding that chemoresistance in breast cancer could be influenced by the mediation of tumor immunity expanded our knowledge of how to address this problem and could guide future research involving chemoresistance.

B4GALNT2 gene encodes the enzyme β1,4-N-acetylgalactosaminyltransferase 2 that biosynthesizes the histo-blood group antigen Sda, which is expressed on the surface of erythrocytes and in body secretions. Analysis of The Cancer Genome Atlas (TCGA) database revealed that this gene was highly expressed in breast cancer tissues in comparison with adjacent healthy ones. In-vitro lentivirus-assisted B4GALNT2 gene knockdown experiments in model triple negative breast cancer (TNBC) cell lines (HCC1937 and MDA-MB-231) showed inhibition in cell proliferation, decrease in cell viability, promotion of cell apoptosis and inhibitions in cell migration and invasiveness abilities in comparison with empty lentivirus transfectant controls. Also, in cell cycle tests, the number of cells in the G1 phase increased, in the S phase decreased and did not change in the G2/M phase (indicative of the presence of a block in the G1 phase). In-vivo tumor formation experiments in mice revealed that knockdown of the B4GALNT2 gene in MDA-MB-231 cells inhibited their proliferation. Using co-immunoprecipitation (Co-IP) mass spectroscopy-assisted analysis, it was found that HLA-B protein [a product of the human leukocyte antigen (HLA) class I gene] interacts with B4GALNT2 protein. In-vitro overexpression of HLA-B in B4GALNT2-knocked down MDA-MB-231 cell lines significantly recovered the cell proliferation, viability and migration ability of B4GALNT2 gene. These indicate that HLA-B is one of the interaction proteins in the downstream pathway of the B4GALNT2 gene.

The dysfunction of the intestinal epithelial barrier contributes to local or systemic infection and inflammation. Some lactic acid bacteria (LAB) strains had been shown to improve the conditions of barrier function and, for this reason, are recognized as probiotics. Weissella cibaria, a species belonging to the LAB group, is known to promote several health benefits. However, the role of W. cibaria in regulating the integrity of the intestinal epithelial barrier has not yet been investigated. In this study, W. cibaria MW01 was isolated from Chinese sauerkraut and was selected based on its functional features, such as gastric juice and bile salt tolerance, besides antagonistic activity against pathogenic bacteria. In a cellular model of the intestinal barrier, it was observed that W. cibaria was able to adhere more efficiently than Lactobacillus rhamnosus GG in Caco-2 cells. Moreover, the LPS-induced inflammation in Caco-2 cells was attenuated by the treatment with W. cibaria MW01, which reduced the synthesis of TNF-α, IL-6, and IL-8. In addition, it was noted that the treatment with W. cibaria MW01 recovered the integrity of the Caco-2 cell monolayer exposed to LPS. Furthermore, W. cibaria MW01 significantly alleviated LPS-induced downregulation of tight junction proteins (TJP) (claudin, occludin, and tight junction protein-1). Mechanistically, W. cibaria MW01 inhibited the translocation of NF-κB to the nucleus and deactivated the MLCK-pMLC pathway during LPS exposure. Thus, W. cibaria MW01, as a potential probiotic, can protect intestinal epithelial barrier function by regulating inflammation and expression of TJP via the NF-κB-mediated MLCK-pMLC pathway.

IntroductionMixed neuroendocrine non-neuroendocrine neoplasm (MiNEN) is a rare form of neuroendocrine neoplasms (NENs). The purpose of this study was to investigate the characteristics and survival profile of appendiceal MiNENs, with a view of providing robust clinical features of this rare disease.MethodsPatients were selected from the Surveillance, Epidemiology, and End Results database (2004–2016). The prognosis of MiNEN (n = 315) was compared with other histological subtypes including neuroendocrine tumor (NETs) (n = 1734), neuroendocrine carcinoma (NECs) (n = 375), goblet cell carcinoid (GCC) (n = 968), signet ring cell carcinoma (n = 463), mucinous adenocarcinoma (MAC) (n = 2355), and non-mucinous adenocarcinoma (NMAC) (n = 1187) in the appendix. Age-adjusted incidence was calculated using Joinpoint regression. The Cox proportional hazards model and the Fine–Gray competing risk model were used to perform overall survival (OS) and cancer-specific mortality (CSM) analyses, respectively.ResultsThe age-adjusted incidence of MiNENs increased from 0.01/100,000 person-years in 2004 to 0.07/100,000 person-years in 2016. The 3-, 5-, and 10-year OS rates for MiNENs were 69.5, 57.4, and 43.7%, respectively, and the corresponding CSM rates were 23.1, 36.4, and 45.1%, respectively. Multivariate analysis revealed that the prognosis of MiNENs was worse than that of NETs, NECs, GCC, and MAC but better than that of NMAC and signet ring cell carcinoma. Tumor extension was the only independent factor influencing the prognosis of MiNENs, but tumor size, grade, and surgical approaches were not. Moreover, when compared with local excision or appendectomy, extensive surgery such as hemicolectomy or colectomy did not prolong the survival of individuals with MiNENs.ConclusionMiNEN is a rare but aggressive tumor with a poor prognosis differing from NENs, GCC and adenocarcinomas. To improve the prognosis of the disease, early diagnosis and comprehensive evaluation are necessary.

Splicing perturbation in cancers contribute to different aspects of cancer cell progression. However, the complete functional impact of cancer-associated splicing have not been fully characterized. Comprehensive large-scale studies are essential to unravel the dominant patterns of cancer-associated splicing. Here we analyzed the genome-wide splicing data in 16 cancer types with normal samples, identified differential splicing events in each cancer type. Then we took a network-based and modularized approach to reconstruct cancer-associated splicing networks, determine the module structures, and evaluate their prognosis relevance. This approach in total identified 51 splicing modules, among which 10/51 modules are related to patient survival, 8/51 are related to progression-free interval, and 5/51 are significant in both. Most of the 51 modules show significant enrichment of important biological functions, such as stem cell proliferation, cell cycle, cell growth, DNA repair, receptor or kinase signaling, and VEGF vessel development. Module-based clustering grouped cancer types according to their tissue-of-origins, consistent with previous pan-cancer studies based on integrative clustering. Interestingly, 13/51 modules are highly common across different cancer types, suggesting the existence of pan-cancer splicing perturbations. Together, modularized perturbation of splicing represents an functionally important and common mechanism across cancer types.

ObjectiveThis study aimed to develop a predictive model for assessing bleeding risk in dual antiplatelet therapy (DAPT) patients.MethodsA total of 18,408 DAPT patients were included. Data on patients’ demographics, clinical features, underlying diseases, past history, and laboratory examinations were collected from Affiliated Dongyang Hospital of Wenzhou Medical University. The patients were randomly divided into two groups in a proportion of 7:3, with the most used for model development and the remaining for internal validation. LASSO regression, multivariate logistic regression, and six machine learning models, including random forest (RF), k-nearest neighbor imputing (KNN), decision tree (DT), extreme gradient boosting (XGBoost), light gradient boosting machine (LGBM), and Support Vector Machine (SVM), were used to develop prediction models. Model prediction performance was evaluated using area under the curve (AUC), calibration curves, decision curve analysis (DCA), clinical impact curve (CIC), and net reduction curve (NRC).ResultsThe XGBoost model demonstrated the highest AUC. The model features were comprised of seven clinical variables, including: HGB, PLT, previous bleeding, cerebral infarction, sex, Surgical history, and hypertension. A nomogram was developed based on seven variables. The AUC of the model was 0.861 (95% CI 0.847–0.875) in the development cohort and 0.877 (95% CI 0.856–0.898) in the validation cohort, indicating that the model had good differential performance. The results of calibration curve analysis showed that the calibration curve of this nomogram model was close to the ideal curve. The clinical decision curve also showed good clinical net benefit of the nomogram model.ConclusionsThis study successfully developed a predictive model for estimating bleeding risk in DAPT patients. It has the potential to optimize treatment planning, improve patient outcomes, and enhance resource utilization.

ObjectiveThe purpose of this retrospective study was to establish a numerical model for predicting the risk of pulmonary embolism (PE) in neurology department patients.MethodsA total of 1,578 subjects with suspected PE at the neurology department from January 2012 to December 2021 were considered for enrollment in our retrospective study. The patients were randomly divided into the training cohort and the validation cohort in the ratio of 7:3. The least absolute shrinkage and selection operator regression were used to select the optimal predictive features. Multivariate logistic regression was used to establish the numerical model, and this model was visualized by a nomogram. The model performance was assessed and validated by discrimination, calibration, and clinical utility.ResultsOur predictive model indicated that eight variables, namely, age, pulse, systolic pressure, hemoglobin, neutrophil count, low-density lipoprotein, D-dimer, and partial pressure of oxygen, were associated with PE. The area under the receiver operating characteristic curve of the model was 0.750 [95% confidence interval (CI): 0.721–0.783] in the training cohort and 0.742 (95% CI: 0.689–0.787) in the validation cohort, indicating that the model showed a good differential performance. A good consistency between the prediction and the real observation was presented in the training and validation cohorts. The decision curve analysis in the training and validation cohorts showed that the numerical model had a good net clinical benefit.ConclusionWe established a novel numerical model to predict the risk factors for PE in neurology department suspected PE patients. Our findings may help doctors to develop individualized treatment plans and PE prevention strategies.

The main purpose of this study was to analyze the effects of Chief Executive Officer (CEO) Key attributes on the financial performance of banks. Current literature gives little attention to the important characteristics of CEOs, therefore, this paper investigates the effects of characteristics of CEOs, such as education, experience, nationality, military background (MTB), and political connectedness (PC), on the financial (return on assets) performance of listed private commercial banks in Pakistan. This research sample included 20 private commercial banks of Pakistan and used Secondary data that was derived from 2011 to 2020, which contained 200 sample observations. This paper used the Fixed effect model, Normality test, Breush–Pagan, white test, multi-collinearity, and Augmented Dickey–Fuller test to investigate the study hypotheses. The main results revealed that CEO MTB and PC significantly and positively affected the financial performance of the bank. It is also found that the CEO's education and Experience have a significant and positive relationships with bank profitability. In contrast, the nationality of the CEO has no significant relationship with the financial performance of the bank.

Objective: To analyze the risk factors of hypoparathyroidism after total thyroidectomy.Methods: Clinical data of patients who undergo total thyroidectomy in the Luwan Branch of Ruijin Hospital Affiliated to Medical College of Shanghai Jiaotong University was collected from January 2015 to December 2018, retrospectively. Logistic regression was used to analyze the risk factors associated with transient and long-term hypoparathyroidism.Results: A total of 537 patients were collected. The patients' average age included in the study was 47.3 ± 12.7 years old, including 135 males (25.1%) and 702 females (74.9%). There were 194 patients (36.1%) with transient postoperative hypoparathyroidism, and 21 patients (3.9%) had long-term postoperative hypoparathyroidism. After multivariate analysis, the main risk factors related to postoperative transient hypoparathyroidism were gender (P = 0.038, OR 0.686), combined lymph node dissection (P = 0.008, OR 1.569), and the maximum diameter of the thyroid (P = 0.011, OR 1.192), second operation (P = 0.001, OR 1.974), preoperative blood calcium (P < 0.001, OR 0.028). The main risk factors associated with long-term postoperative hypoparathyroidism are combined with lymph node dissection (P = 0.011, OR 1.594), maximum thyroid diameter (P = 0.032, OR 1.254), and PTH on the first day after surgery (P < 0.001, OR 1.199).Conclusions: Gender, combined lymph node dissection, maximum thyroid diameter, a second surgery, and preoperative blood calcium are risk factors for transient hypoparathyroidism after thyroid surgery. The combined lymphatic dissection and the thyroid gland's maximum diameter are risk factors for long-term hypoparathyroidism after thyroid surgery. PTH on the first day after surgery has a predictive effect on patients with long-term hypoparathyroidism.

Bacterial symbionts associated with insects are often involved in host development and ecological fitness. In aphids, the role of these symbionts is variable and not fully understood across different host species. Here, we investigated the symbiont diversity of the grain aphid, Sitobion miscanthi (Takahashi), from 17 different geographical areas. Of these, two strains with the same symbiont profile, except for the presence of Hamiltonella defensa, were selected using PCR. The Hamiltonella-infected strain, YX, was collected from a Yuxi wheat field in Yunnan Province, China. The Hamiltonella-free strain, DZ, was collected from a Dezhou wheat field in Shandong Province, China. Using artificial infection with H. defensa and antibiotic treatment, a Hamiltonella-re-infected strain (DZ-H) and Hamiltonella-significantly decreased strain (DZ-HT) were established and compared to the Hamiltonella-free DZ strain in terms of ecological fitness. Infection with the DZ-H strain increased the fitness of S. miscanthi, which led to increases in adult weight, percent of wingless individuals, and number of offspring. Meanwhile, decreased abundance of H. defensa (DZ-HT strain) resulted in a lower adult weight and wingless aphid rate compared to the DZ-H strain. However, the indices of longevity in both the DZ-H and DZ-HT strains decreased slightly, but were not significantly different, compared to the DZ strain. Furthermore, quantitative PCR showed that the relative abundance of the primary symbiont Buchnera aphidicola in the DZ-H strain was significantly higher than in the DZ strain in all but the first developmental stage. These results indicate that H. defensa may indirectly improve the fitness of S. miscanthi by stimulating the proliferation of B. aphidicola.