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We study the small initial data Cauchy problem for the three-dimensional Boussinesq equations with the Coriolis force in variable exponent Fourier-Besov spaces. Using the Fourier localization argument and Littlewood-Paley decomposition, we obtain the global well-posedness result for small initial data $ (u_0, \theta_0) $ belonging to the critical variable exponent Fourier-Besov spaces $ \mathcal{F}\mathcal{\dot{B}}_{p(\cdot), q}^{2-\frac{3}{p(\cdot)}} $.

BackgroundImmune checkpoint inhibition holds promise as a novel treatment for pancreatic ductal adenocarcinoma (PDAC). The clinical significance of soluble immune checkpoint (ICK) related proteins have not yet fully explored in PDAC.MethodsWe comprehensively profiled 14 soluble ICK-related proteins in plasma in 70 PDAC patients and 70 matched healthy controls. Epidemiological data of all subjects were obtained through structured interviews, and patients’ clinical data were retrieved from electronical health records. We evaluated the associations between the biomarkers with the risk of PDAC using unconditional multivariate logistic regression. Consensus clustering (k-means algorithm) with significant biomarkers was performed to identify immune subtypes in PDAC patients. Prediction models for overall survival (OS) in PDAC patients were developed using multivariate Cox proportional hazards regression. Harrell’s concordance index (C-index), time-dependent receiver operating characteristic (ROC) curve and calibration curve were utilized to evaluate performance of prediction models. Gene expressions of the identified ICK-related proteins in tumors from TCGA were analyzed to provide insight into underlying mechanisms.ResultsSoluble BTLA, CD28, CD137, GITR and LAG-3 were significantly upregulated in PDAC patients (all q < 0.05), and elevation of each of them was correlated with PDAC increased risk (all p < 0.05). PDAC patients were classified into soluble immune-high and soluble immune-low subtypes, using these 5 biomarkers. Patients in soluble immune-high subtype had significantly poorer OS than those in soluble immune-low subtype (log-rank p = 9.7E-03). The model with clinical variables and soluble immune subtypes had excellent predictive power (C-index = 0.809) for the OS of PDAC patients. Furthermore, the immune subtypes identified with corresponding genes’ expression in PDAC tumor samples in TCGA showed an opposite correlation with OS to that of immune subtypes based on blood soluble ICK-related proteins (log-rank p =0.02). The immune-high subtype tumors displayed higher cytolytic activity (CYT) score than immune-low subtype tumors (p < 2E-16).ConclusionFive soluble ICK-related proteins were identified to be significantly associated with the risk and prognosis of PDAC. Patients who were classified as soluble immune-low subtype based on these biomarkers had better overall survival than those of the soluble immune-high subtype.

BackgroundHepatoid adenocarcinoma of the stomach (HAS) is a highly malignant subtype of gastric carcinoma with specific clinicopathological features and extremely poor prognosis. We present an exceedingly rare case of complete response after chemo-immunotherapy.Case DescriptionA 48-year-old woman with highly elevated serum alpha-fetoprotein (AFP) level was found to have HAS verified by pathological examination based on gastroscopy. Computed tomography scan was done and TNM staging of the tumor was T4aN3aMx. Programmed cell death ligand-1 (PD-L1) immunohistochemistry was performed, revealing a negative PD-L1 expression. Chemo-immunotherapy including oxaliplatin plus S-1 and PD-1 inhibitor terelizumab was given to this patient for 2 months until the serum AFP level decreased from 748.5 to 12.9 ng/mL and the tumor shrank. D2 radical gastrectomy was then performed and histopathology of the resected specimen revealed that the cancerous cells had disappeared. Pathologic complete response (pCR) was achieved and no evidence of recurrence has been found after 1 year of follow-up.ConclusionsWe, for the first time, reported an HAS patient with negative PD-L1 expression who achieved pCR from the combined chemotherapy and immunotherapy. Although no consensus has been reached regarding the therapy, it might provide a potential effective management strategy for HAS patient.

Recurrent laryngeal nerve (RLN) injury is a serious complication of thyroidectomy. Here, the degradable poly(lactic-co-glycolic acid) (PLGA) nerve guide conduits (NGCs) with microgroove or smooth inner surface were fabricated using a phase inversion-based dry-jet wet spinning method for RLN regeneration. The morphology and mechanical properties of NGCs were observed by scanning electron microscope (SEM) and a universal testing machine, showing that the porous NGC has good mechanical properties and is suitable for implantation. Further, in vitro PC12 cells cultured on the NGCs showed that microgroove conduit (GNGC) exhibited better cell adhesion, proliferation, and cell orientation. Both smooth and microgroove conduit (SNGC and GNGC) were transplanted into Sprague-Dawley (SD) rat models for assessing the repair effect on the 5-mm RLN gap. The results showed that GNGC was superior to SNGC in nerve regeneration and had similar effects to the autograft group in reducing muscle atrophy and restoring target organ function. Therefore, the degradable NGCs combined with groove structure could guide the regeneration of injured RLN, promote the partial functional recovery of target organs and prevent secondary surgical injury. This study contributes to the design and fabrication of nerve guide conduits and the application of tissue engineering in the field of RLN injury repair.

Mammary epithelial cells are the only cells of mammary glands with lactation capacity. They are closely related to mammary development and milk yield. Our earlier studies showed that the transformation of goat fibroblasts into induced mammary epithelial cells (iMECs) was closely correlated with SMAD3 overexpression. Therefore, we further explored the role of SMAD3 on iMECs reprogramming in this study. The SMAD3 gene was overexpressed in goat ear fibroblasts using the tetracycline-induced expression method. The outcomes demonstrated that goat ear fibroblasts can be converted into iMECs by overexpressing the SMAD3 gene. In contrast, it was discovered that SMAD3 downregulation by RNA interference significantly decrease the reprogramming efficiency of iMECs. These results show that SMAD3 plays a key regulatory role in the reprogramming of iMECs. Surprisingly, we also found a parabolic relationship between SMAD3 expression level and iMECs reprogramming efficiency, and that the reprogramming efficiency was maximum when the addition of doxycycline concentration was 5 μg/ml. In light of this, our findings may offer new perspectives on the regulatory mechanism governing mammary epithelial cell fate in goats as well as a fresh approach to studying mammary development and differentiation in vitro.

Abstract Background Surgical resection is the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC) and the survival of patients after radical resection is closely related to relapse. We aimed to develop models to predict the risk of relapse using machine learning methods based on multiple clinical parameters. Methods Data were collected and analysed of 262 PDAC patients who underwent radical resection at 3 institutions between 2013 and 2017, with 183 from one institution as a training set, 79 from the other 2 institution as a validation set. We developed and compared several predictive models to predict 1- and 2-year relapse risk using machine learning approaches. Results Machine learning techniques were superior to conventional regression-based analyses in predicting risk of relapse of PDAC after radical resection. Among them, the random forest (RF) outperformed other methods in the training set. The highest accuracy and area under the receiver operating characteristic curve (AUROC) for predicting 1-year relapse risk with RF were 78.4% and 0.834, respectively, and for 2-year relapse risk were 95.1% and 0.998. However, the support vector machine (SVM) model showed better performance than the others for predicting 1-year relapse risk in the validation set. And the k neighbor algorithm (KNN) model achieved the highest accuracy and AUROC for predicting 2-year relapse risk. Conclusions By machine learning, this study has developed and validated comprehensive models integrating clinicopathological characteristics to predict the relapse risk of PDAC after radical resection which will guide the development of personalized surveillance programs after surgery.

Effective and accurate delivery of drugs to tissue with spinal cord injury (SCI) is the key to rehabilitating neurological deficits. Sustained-release microspheres (MS) have excellent degradability and can aid in the long-term release of drugs. However, the burst release phenomenon can cause unexpected side effects. Herein, we developed and optimized an injectable poly(lactic-co-glycolic acid) (PLGA) MS loaded with melatonin(Mel), which were mixed further with Laponite hydrogels (Lap/MS@Mel, a micro-gel compound) in order to reduce the burst release of MS. Thus, these MS were able to achieve stable and prolonged Mel release, as well as synergistic Lap hydrogel in order to repair neural function in SCI by in situ injection. In clinical practice, patients with SCI have complicated conditions and significant inter-individual differences, which means that a single route of administration does not meet actual clinical needs. Thus, the nanospheres are synthesized and subsequently coated with platelet membrane (PM) in order to form PM/MS@Mel (nano-PM compound) for sustained and precision-targeted delivery of Mel intravenously in the SCI. Notably, optimized microsphere delivery systems have improved Mel regulation polarization of spinal microglial/macrophages, which can reduce loss of biomaterials due to macrophage-induced immune response during implantation of spinal cord tissue. These two new delivery systems that are based on MS provide references for the clinical treatment of SCI, according to different requirements.

Background: Silibinin is widely utilized drug in various cancer treatments, though its application in cholangiocarcinoma has not yet been explored. For the first time, we evaluated the anticancer potential and underlying molecular mechanism of silibinin in treatment of cholangiocarcinoma treatment.Methods: HuCCT-1 and CCLP-1 cells were chosen to be an in vitro study model and were exposed to various concentrations of silibinin for indicated times. Cell viability was evaluated by the cell counting kit-8 (CCK-8) assay and half maximal inhibitory (IC50) concentrations were calculated. Cell proliferation capacity was determined through the use of colony formation and 5-Ethynyl-2′- deoxyuridine (EdU) assays. Cell apoptosis and cycle arrest were assessed by Live/Dead staining assay and flow cytometry (FCM). The protein levels of extracellular regulated protein kinases (ERK)/mitochondrial apoptotic pathway were evaluated through western blotting (WB). Mitochondrial membrane potential changes were determined via 5,5′,6,6′-Tetrachloro-1,1′,3,3′-tetraethyl-imidacarbocyanine iodide (JC-1). A cholangiocarcinoma cell line xenograft model was used to assess the anti-tumor activity of silibinin in vivo.Results: Inhibition of the ERK protein by silibinin led to a significant decrease in mitochondrial membrane potential, which, in turn, caused Cytochrome C to be released from the mitochondria. The activation of downstream apoptotic pathways led to apoptosis of cholangiocarcinoma cells. In general, silibinin inhibited the growth of cholangiocarcinoma cell line xenograft tumors.Conclusions: Silibinin is able to inhibit cholangiocarcinoma through the ERK/mitochondrial apoptotic pathway, which makes silibinin a potential anti-tumor drug candidate for cholangiocarcinoma treatment.

ABSTRACT: Background: The high recurrence rate after radical resection of pancreatic ductal adenocarcinoma (PDAC) leads to its poor prognosis. We aimed to develop a model to preoperatively predict the risk of recurrence based on computed tomography (CT) radiomics and multiple clinical parameters. Methods: Datasets were retrospectively collected and analysed of 220 PDAC patients who underwent contrast-enhanced computed tomography (CE-CT) and received radical resection at 3 institutions in China between 2013 and 2017, with 153 from one institution as a training set, the remaining 67 as a validation set. For each patient, CT radiomics features were extracted from intratumoral and peritumoral regions to establish intratumoral, peritumoral and combined radiomics models using artificial neural network (ANN) algorithm. By incorporating clinical factors, radiomics-clinical nomograms were finally built by multivariable logistic regression analysis to predict 1- and 2-year recurrence risk. Findings: The developed radiomics model integrating intratumoral and peritumoral radiomics features was superior to the conventionally constructed model merely using intratumoral radiomics features. Further, radiomics-clinical nomograms outperformed other models in predicting 1-year recurrence with an area under the receiver operating characteristic curve (AUROC) of 0.916 (95%CI, 0.860-0.955) in the training set and 0.764 (95%CI, 0.644-0.859) in the validation set, and 2-year recurrence with an AUROC of 0.872 (95%CI: 0.809-0.921) in the training set and 0.773 (95%CI, 0.654-0.866) in the validation set. Interpretation: This study has developed and externally validated a radiomics-clinical nomogram integrating intra- and peritumoral CT radiomics signature as well as clinical factors to predict the recurrence risk of PDAC after radical resection, which will facilitate optimized and individualized treatment strategies. Funding: This work was supported by the National Key R&D Program of China [grant number: 2018YFE0114800], the General Program of National Natural Science Foundation of China [grant number: 81772562, 2017; 81871351, 2018], the Fundamental Research Funds for the Central Universities [grant number: 2021FZZX005-08], and Zhejiang Provincial Key Projects of Technology Research [grant number: WKJ-ZJ-2033].

BackgroundIndoor daylight levels can directly affect the physical and psychological state of people. However, the effect of indoor daylight levels on the clinical recovery process of the patient remains controversial. This study was to evaluate the effect of indoor daylight levels on hospital costs and the average length of stay (LOS) of a large patient population in general surgery wards.MethodsData were collected retrospectively and analyzed of patients in the Second Affiliated Hospital of Zhejiang University, School of Medicine between January 2015 and August 2020. We measured daylight levels in the patient rooms of general surgery and assessed their association with the total hospital costs and LOS of the patients.ResultsA total of 2,998 patients were included in this study with 1,478 each assigned to two daylight level groups after matching. Overall comparison of hospital total costs and LOS among patients according to daylight levels did not show a significant difference. Subgroup analysis showed when exposed to higher intensity of indoor daylight, illiterate patients had lower total hospital costs (CNY ¥13070.0 vs. ¥15210.3, p = 0.018) and shorter LOS (7 vs. 10 days, p = 0.011) as compared to those exposed to a lower intensity.ConclusionsIndoor daylight levels were not associated with the hospital costs and LOS of patients in the wards of general surgery, except for those who were illiterate. It might be essential to design guidelines for medical staff and healthcare facilities to enhance the indoor environmental benefits of daylight for some specific populations.

Abstract Background High‐quality randomized controlled trials have demonstrated the benefit of radiotherapy (RT) in patients with radical resected gastric cancer (GC), however, utilization rates of postoperative RT remain remarkably low. Patterns, incidences, and time of recurrence provide biological bases for clinical monitoring of GC patients and guiding potential complementary therapies. Thus, the aim of this study is to understand the location of locoregional recurrence which may allow individualized RT strategies and minimize radiation‐related toxic effects. Methods A relatively large sample of GC patients in a single institution who had undergone curative D2 resection was retrospectively reviewed and the relevant recurrence patterns were illustrated. Independent recurrence‐related risk factors were analyzed by logistic regression analysis. New logistic regression models were further developed to predict the probability of recurrence. Results Overall, among 776 GC patients who had continuous and complete follow‐up data, 300 cases relapsed after curative resection. Lymphovascular invasion, lymph node metastases, and tumor stage were indicators for early recurrence. Peritoneal, regional, local, and distant recurrence initially occurred in 51 (6.6%), 151 (19.4%), 56 (7.2%), and 164 (21.1%) patients, respectively. Among patients with regional recurrence, the most common sites were lymph node stations 16a2, 8, 12, 16b1, and 9. Remnant stomach recurrence was not so prominent that it seemed reasonable to be excluded from an irradiation field for patients with negative surgical/pathologic margins. Conclusions For GC patients who underwent radical D2 resection, distant and regional recurrences were still common. Besides, optimizing regional control of lymph nodes outside the D2 dissected area was crucial for rational design of the RT field. Furthermore, the new logistic regression models might act as useful tools to evaluate recurrence risk and determine which patients should receive postoperative chemoradiotherapy.

Based on the bioactivities of blood protein, the nutritional appraisal and antidiabetic activity of a kind of mixed plasma proteolytic peptide from Tachpleus tridentatus (PPPT) were studied in this work. Results indicated that the amino acid level of PPPT could meet an adult’s FAO/WHO recommended standard; PPPT also manifested inhibitory activity on α-glucosidase with IC50 at 2.62 mg/mL in vitro, and relieved symptoms of type II diabetic mouse in vivo by improving glucose tolerance, increasing insulin secretion by 5.15 mIU/L in the PPPT-4 group and by 4.54 mIU/L in the PPPT-1 group, reducing blood glucose values to nearly normal levels 120 min after intragastric administration, and restoring pathological damage in the thymus. Thus, PPPT can be developed into both a healthcare product and an adjuvant for type II diabetes in the future.

Background: Recurrence after surgery is largely responsible for the extremely poor outcomes for patients with pancreatic ductal adenocarcinoma (PDAC). Ferroptosis is implicated in chemotherapy sensitivity and tumor recurrence, we aimed to find out survival-associated ferroptosis-related genes and use them to build a practical risk model with the purpose to predict PDAC recurrence.Methods: Univariate Cox regression analysis was conducted to obtain prognostic ferroptosis-related genes in The Cancer Genome Atlas (TCGA, N = 140) cohort. Multivariate Cox regression analysis was employed to construct a reliable and credible gene signature. The prognostic performance was verified in a MTAB-6134 (N = 286) validation cohort and a PACA-CA (N = 181) validation cohort. The stability of the signature was tested in TCGA and MTAB-6134 cohorts by ROC analyses. Pathway enrichment analysis was adopted to preliminary illuminate the biological relevance of the gene signature.Results: Univariate and multivariate Cox regression analyses identified a 5-gene signature that contained CAV1, DDIT4, SLC40A1, SRXN1 and TFAP2C. The signature could efficaciously stratify PDAC patients with different recurrence-free survival (RFS), both in the training and validation cohorts. Results of subgroup receiver operating characteristic curve (ROC) analyses confirmed the stability and the independence of this signature. Our signature outperformed clinical indicators and previous reported models in predicting RFS. Moreover, the signature was found to be closely associated with several cancer-related and drug response pathways.Conclusion: This study developed a precise and concise prognostic model with the clinical implication in predicting PDAC recurrence. These findings may facilitate individual management of postoperative recurrence in patients with PDAC.

Background: Previous prognostic signatures of pancreatic ductal adenocarcinoma (PDAC) are mainly constructed to predict the overall survival (OS), and their predictive accuracy needs to be improved. Gene signatures that efficaciously predict both OS and disease-free survival (DFS) are of great clinical significance but are rarely reported.Methods: Univariate Cox regression analysis was adopted to screen common genes that were significantly associated with both OS and DFS in three independent cohorts. Multivariate Cox regression analysis was subsequently performed on the identified genes to determine an optimal gene signature in the MTAB-6134 training cohort. The Kaplan–Meier (K-M), calibration, and receiver operating characteristic (ROC) curves were employed to assess the predictive accuracy. Biological process and pathway enrichment analyses were conducted to elucidate the biological role of this signature.Results: Multivariate Cox regression analysis determined a 7-gene signature that contained ASPH, DDX10, NR0B2, BLOC1S3, FAM83A, SLAMF6, and PPM1H. The signature had the ability to stratify PDAC patients with different OS and DFS, both in the training and validation cohorts. ROC curves confirmed the moderate predictive accuracy of this signature. Mechanically, the signature was related to multiple cancer-related pathways.Conclusion: A novel OS and DFS prediction model was constructed in PDAC with multi-cohort and cross-platform compatibility. This signature might foster individualized therapy and appropriate management of PDAC patients.

Purpose: The purpose of this study was to construct a novel risk scoring model with prognostic value that could elucidate tumor immune microenvironment of hepatocellular carcinoma (HCC).Samples and methods: Data were obtained through The Cancer Genome Atlas (TCGA) database. Univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox analysis were carried out to screen for glycolysis-related long noncoding RNAs (lncRNAs) that could provide prognostic value. Finally, we established a risk score model to describe the characteristics of the model and verify its prediction accuracy. The receiver operating characteristic (ROC) curves of 1, 3, and 5 years of overall survival (OS) were depicted with risk score and some clinical features. ESTIMATE algorithm, single-sample gene set enrichment analysis (ssGSEA), and CIBERSORT analysis were employed to reveal the characteristics of tumor immune microenvironment in HCC. The nomogram was drawn by screening indicators with high prognostic accuracy. The correlation of risk signature with immune infiltration and immune checkpoint blockade (ICB) therapy was analyzed. After enrichment of related genes, active behaviors and pathways in high-risk groups were identified and lncRNAs related to poor prognosis were validated in vitro. Finally, the impact of MIR4435-2HG upon ICB treatment was uncovered.Results: After screening through multiple steps, four glycolysis-related lncRNAs were obtained. The risk score constructed with the four lncRNAs was found to significantly correlate with prognosis of samples. From the ROC curve of samples with 1, 3, and 5 years of OS, two indicators were identified with high prognostic accuracy and were used to draw a nomogram. Besides, the risk score significantly correlated with immune score, immune-related signature, infiltrating immune cells (i.e. B cells, etc.), and ICB key molecules (i.e. CTLA4,etc.). Gene enrichment analysis indicated that multiple biological behaviors and pathways were active in the high-risk group. In vitro validation results showed that MIR4435-2HG was highly expressed in the two cell lines, which had a significant impact on the OS of samples. Finally, we corroborated that MIR4435-2HG had intimate relationship with ICB therapy in hepatocellular carcinoma.Conclusion: We elucidated the crucial role of risk signature in immune cell infiltration and immunotherapy, which might contribute to clinical strategies and clinical outcome prediction of HCC.

BackgroundFor pancreatic ductal adenocarcinoma (PDAC) patients, chemotherapy failure is the major reason for postoperative recurrence and poor outcomes. Establishment of novel biomarkers and models for predicting chemotherapeutic efficacy may provide survival benefits by tailoring treatments.MethodsUnivariate cox regression analysis was employed to identify EMT-related genes with prognostic potential for DFS. These genes were subsequently submitted to LASSO regression analysis and multivariate cox regression analysis to identify an optimal gene signature in TCGA training cohort. The predictive accuracy was assessed by Kaplan–Meier (K-M), receiver operating characteristic (ROC) and calibration curves and was validated in PACA-CA cohort and our local cohort. Pathway enrichment and function annotation analyses were conducted to illuminate the biological implication of this risk signature.ResultsLASSO and multivariate Cox regression analyses selected an 8-gene signature comprised DLX2, FGF9, IL6R, ITGB6, MYC, LGR5, S100A2, and TNFSF12. The signature had the capability to classify PDAC patients with different DFS, both in the training and validation cohorts. It provided improved DFS prediction compared with clinical indicators. This signature was associated with several cancer-related pathways. In addition, the signature could also predict the response to immune-checkpoint inhibitors (ICIs)-based immunotherapy.ConclusionWe established a novel EMT-related gene signature that was capable of predicting therapeutic response to adjuvant chemotherapy and immunotherapy. This signature might facilitate individualized treatment and appropriate management of PDAC patients.

The aim of any surgical resection for pancreatic ductal adenocarcinoma (PDAC) is to achieve tumor-free margins (R0). R0 margins give rise to better outcomes than do positive margins (R1). Nevertheless, postoperative morbidity after R0 resection remains high and prognostic gene signature predicting recurrence risk of patients in this subgroup is blank. Our study aimed to develop a DNA replication-related gene signature to stratify the R0-treated PDAC patients with various recurrence risks. We conducted Cox regression analysis and the LASSO algorithm on 273 DNA replication-related genes and eventually constructed a 7-gene signature. The predictive capability and clinical feasibility of this risk model were assessed in both training and external validation sets. Pathway enrichment analysis showed that the signature was closely related to cell cycle, DNA replication, and DNA repair. These findings may shed light on the identification of novel biomarkers and therapeutic targets for PDAC.

Background: Accumulating evidence shows that the elevated expression of DCBLD2 (discoidin, CUB and LCCL domain-containing protein 2) is associated with unfavorable prognosis of various cancers. However, the correlation of DCBLD2 expression value with the diagnosis and prognosis of pancreatic ductal adenocarcinoma (PDAC) has not yet been elucidated. Methods: Univariate Cox regression analysis was used to screen robust survival-related genes. Expression pattern of selected genes was investigated in PDAC tissues and normal tissues from multiple cohorts. Kaplan–Meier (K–M) survival curves, ROC curves and calibration curves were employed to assess prognostic performance. The relationship between DCBLD2 expression and immune cell infiltrates was conducted by CIBERSORT software. Biological processes and KEGG pathway enrichment analyses were adopted to clarify the potential function of DCBLD2 in PDAC. Results: Univariate analysis, K–M survival curves and calibration curves indicated that DCBLD2 was a robust prognostic factor for PDAC with cross-cohort compatibility. Upregulation of DCBLD2 was observed in dissected PDAC tissues as well as extracellular vesicles from both plasma and serum samples of PDAC patients. Both DCBLD2 expression in tissue and extracellular vesicles had significant diagnostic value. Besides, DCBLD2 expression was correlated with infiltrating level of CD8+ T cells and macrophage M2 cells. Functional enrichment revealed that DCBLD2 might be involved in cell motility, angiogenesis, and cancer-associated pathways. Conclusion: Our study systematically analyzed the potential diagnostic, prognostic and therapeutic value of DCBLD2 in PDAC. All the findings indicated that DCBLD2 might play a considerably oncogenic role in PDAC with diagnostic, prognostic and therapeutic potential. These preliminary results of bioinformatics analyses need to be further validated in more prospective studies.

Regulated necrosis is an emerging type of cell death independent of caspase. Recently, with increasing findings of regulated necrosis in the field of biochemistry and genetics, the underlying molecular mechanisms and signaling pathways of regulated necrosis are gradually understood. Nowadays, there are several modes of regulated necrosis that are tightly related to cancer initiation and development, including necroptosis, ferroptosis, parthanatos, pyroptosis, and so on. What’s more, accumulating evidence shows that various compounds can exhibit the anti-cancer effect via inducing regulated necrosis in cancer cells, which indicates that caspase-independent regulated necrosis pathways are potential targets in cancer management. In this review, we expand the molecular mechanisms as well as signaling pathways of multiple modes of regulated necrosis. We also elaborate on the roles they play in tumorigenesis and discuss how each of the regulated necrosis pathways could be therapeutically targeted.

Background To evaluate the clinical characteristics and indications for surgery for bezoar-induced small bowel obstruction (BI-SBO). Methods Forty patients with BI-SBO were treated at our hospital from January 2017 to December 2019, and these patients’ clinical and computed tomography (CT) data were analyzed. Results Twenty-seven and 13 BI-SBO patients constituted the non-ST group and ST group, respectively. The clinical manifestations of BI-SBO in both groups were abdominal pain, nausea, vomiting, and lack of defecation. Comparing the non-ST vs ST groups, respectively: mean age (years): 63.15 ± 16.15 vs 60.38 ± 12.47; duration of symptoms (hours): 55.11 ± 44.08 vs 59.33 ± 72.90; mean bezoar length (cm): 5.31 ± 0.74 vs 3.72 ± 0.53; mean bezoar width (cm): 3.74 ± 0.48 vs 2.9 ± 0.64; bezoar CT maximum Hounsfield units (HU): 97.23 ± 12.36 vs 21.11 ± 7.27; total hospital stay (days): 5.56 ± 4.23 vs 7.12 ± 6.12 (mean: 8.62 ± 2.81); and total hospitalization costs (RMB): 6378.02 ± 3015.68 vs 8213.71 ± 5564.29. Mean operation time was 85.00 ± 8.90 minutes, and mean operation blood loss was 32.31 ± 19.64 mL. Bezoars were located 60 to 160 cm from the ileocecal junction. Univariate analysis demonstrated that bezoar length and width and maximum CT value were significant risk factors for surgery. Conclusion Large bezoar size and high CT values may be indications for surgery. Surgery is necessary and effective when nonsurgical treatment is ineffective.

The split feasibility problem SFP has received much attention due to its various applications in signal processing and image reconstruction. In this paper, we propose two inertial relaxed CQ algorithms for solving the split feasibility problem in real Hilbert spaces according to the previous experience of applying inertial technology to the algorithm. These algorithms involve metric projections onto half-spaces, and we construct new variable step size, which has an exact form and does not need to know a prior information norm of bounded linear operators. Furthermore, we also establish weak and strong convergence of the proposed algorithms under certain mild conditions and present a numerical experiment to illustrate the performance of the proposed algorithms.

Islet transplantation is being considered as an alternative treatment for type 1 diabetes. Despite recent progress, transplant recipients continue to experience progressive loss of insulin independence. Cyanidin-3-O-Glucoside (C3G) has shown to be protective against damage that may lead to post-transplant islet loss. In this study, human islets cultured with or without C3G were treated with human amylin, Aβ1-42, H2O2, or rapamycin to mimic stresses encountered in the post-transplant environment. Samples of these islets were collected and assayed to determine C3G's effect on cell viability and function, reactive oxygen species (ROS), oxidative stress, amyloid formation, and the presence of inflammatory as well as autophagic markers. C3G treatment of human islets exposed to either amylin or Aβ1-42 increased cell viability (p

Objectives Gastric cancer (GC) is the leading cause of cancer-related deaths worldwide; however, the underlying molecular mechanisms of GC remain unclear. This study investigated the role of the miR-877–AQP3 axis in GC tumorigenesis. Methods The levels of miR-877 expression were measured in GC tissues and cell lines by qRT-PCR. Functional assays were performed to elucidate the role of miR-877 in GC development. Results Our results showed that miR-877 levels were lower in GC tissues and cell lines compared with the corresponding controls. Additionally, reduced miR-877 levels were associated with unfavorable prognoses. Increased miR-877 expression suppressed proliferation, invasion, and epithelial-mesenchymal transition, while promoting apoptosis in GC cells. Luciferase reporter assays showed that aquaporin 3 (AQP3) was a direct downstream target of miR-877. Overexpression of AQP3 partially rescued the tumor suppressive effects of miR-877 in GC cells. Moreover, miR-877 was negatively correlated with AQP3 mRNA expression in GC tissues. Conclusions This study demonstrated that miR-877 plays a suppressive role in GC tumorigenesis by regulating AQP3.

With the speedy progress in electrical engineering field globally, power electronics course has aroused attention from academic community. English immersion teaching methods applied to power electronics course aim to introduce advanced counterpart academic knowledge from abroad to China and equip students and teaching staffs with international views as well as English-oriented logical and critical thinking in power electronics, and thus to promote power electronics development in China in the long term. By utilizing English immersion teaching methods for power electronics course, which involves problem-based learning, English-project-based assessment method and English-based laboratory operation, the challenges that the innovative teaching methods confront could be solved during each process of power electronics course. For further illustration, English immersion teaching methods for energy storage will be analysed as a study case. Consequently, the new English immersion teaching methods for power electronics course in China can be spread and applied in other non-native English-speaking countries to upgrade and reform power electronics course and related discipline.

Abstract Prospective epidemiological studies have consistently suggested that pancreatic cancer-associated new-onset diabetes mellitus (PC-DM) represents a potential platform for early diagnose of pancreatic cancer (PC). Despite the studies performed, the mechanism behind this phenomenon remains ambiguous. In this study, we explored the effects of two types of exosomes released by murine pancreatic cancer and ductal epithelial cells on murine skeletal muscle cells. The results show that PC-derived exosomes can readily enter C2C12 myotubes, triggering lipidosis and glucose intake inhibition. We also demonstrate that PC-derived exosomes can inhibit insulin and PI3K/Akt signalling, in which insulin-induced FoxO1 nuclear exclusion is preserved and Glut4 trafficking is impaired. Microarray and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses show that exosomal microRNAs (miRNAs) probably play key roles in this process, an assumption that is corroborated by in vitro studies. These results confirm that the insulin resistance (IR) of skeletal muscle cells is governed by PC-derived exosomes through the insulin and PI3K/Akt/FoxO1 signalling pathways, where exosomal miRNAs potentially contribute to this phenomenon. These novel findings pave the way towards a comprehensive understanding of the cancer theories: “metabolic reprogramming” and “metabolic crosstalk”.

Abstract Background The aim of this study is to assess the validity of the measurement of pepsinogen as a screening test for chronic atrophic gastritis (AG) in health check-up populations in China. Methods Patients from consecutive regular health check-up were enrolled from January 2014 to June 2015. Endoscopy, combined with monitoring the Helicobacter pylori (Hp) infections, and measuring the serum pepsinogen (PG) were used to determine the diagnostic accuracy of PG for the screening of atrophic gastritis. Histopathology was assessed by the Operative Link on Gastritis Assessment (OLGA) system. Statistical analysis was performed using SPSS statistical software. Results The total Hp infection rate was 40%. Based on pathology, the 996 participants were divided into three groups: non-atrophic (NAG), mild-moderate atrophic (MAG): stage I and II of the OLGA classification, and severe atrophic (SAG): stage III and IV of the OLGA classification. Compared with NAG and MAG groups, PGR decreased significantly in SAG group (p