Repetition rate tuning and locking of solitons in a microrod resonator.

Recently, there has been significant interest in the generation of coherent temporal solitons in optical microresonators. In this Letter, we present a demonstration of dissipative Kerr soliton generation in a microrod resonator using an auxiliary-laser-assisted thermal response control method. In addition, we are able to control the repetition rate of the soliton over a range of 200 kHz while maintaining the pump laser frequency, by applying external stress tuning. Through the precise control of the PZT voltage, we achieve a stability level of 3.9 × 10-10 for residual fluctuation of the repetition rate when averaged 1 s. Our platform offers precise tuning and locking capabilities for the repetition frequency of coherent mode-locked combs in microresonators. This advancement holds great potential for applications in spectroscopy and precision measurements.

Development and validation of a prognostic scoring model for mortality risk stratification in patients with recurrent or metastatic gastric carcinoma.

BACKGROUND: Survival times differ among patients with advanced gastric carcinoma. A precise and universal prognostic evaluation strategy has not yet been established. The current study aimed to construct a prognostic scoring model for mortality risk stratification in patients with advanced gastric carcinoma. METHODS: Patients with advanced gastric carcinoma from two hospitals (development and validation cohort) were included. Cox proportional hazards regression analysis was conducted to identify independent risk factors for survival. A prognostic nomogram model was developed using R statistics and validated both in bootstrap and external cohort. The concordance index and calibration curves were plotted to determine the discrimination and calibration of the model, respectively. The nomogram score and a simplified scoring system were developed to stratify patients in the two cohorts. RESULTS: Development and validation cohort was comprised of 401 and 214 gastric cancer patients, respectively. Mucinous or non-mucinous histology, ECOG score, bone metastasis, ascites, hemoglobin concentration, serum albumin level, lactate dehydrogenase level, carcinoembryonic antigen level, and chemotherapy were finally incorporated into prognostic nomogram. The concordance indices were 0.689 (95% CI: 0.664 ~ 0.714) and 0.673 (95% CI: 0.632 ~ 0.714) for bootstrap and external validation. 100 and 200 were set as the cut-off values of nomogram score, patients in development cohort were stratified into low-, intermediate- and high-risk groups with median overall survival time 15.8 (95% CI: 12.2 ~ 19.5), 8.4 (95% CI: 6.7 ~ 10.2), and 3.9 (95% CI: 2.7 ~ 5.2) months, respectively; the cut-off values also worked well in validation cohort with different survival time in subgroups. A simplified model was also established and showed good consistency with the nomogram scoring model in both of development and validation cohorts. CONCLUSION: The prognostic scoring model and its simplified surrogate can be used as tools for mortality risk stratification in patients with advanced gastric carcinoma.

Survival outcomes of adjuvant taxanes, platinum plus fluoropyrimidines versus platinum and fluoropyrimidines for gastric cancer patients after D2 gastrectomy: a retrospective propensity score-matched analysis.

BACKGROUND: To evaluate whether the addition of taxanes to platinum and fluoropyrimidines in adjuvant chemotherapy would result in longer survival than platinum plus fluoropyrimidines in gastric cancer patients who received D2 gastrectomy. METHODS: Data of patients with gastric adenocarcinoma who received D2 gastrectomy and adjuvant chemotherapy with platinum plus fluoropyrimidines or taxanes, platinum plus fluoropyrimidines was retrospectively collected and analyzed. 1:1 Propensity score matching analysis was used to balance baseline characteristics between two groups. Survival curves were estimated using Kaplan-Meier method, and the differences were compared using the log-rank test. RESULTS: Four hundred twenty-five patients in the platinum plus fluoropyrimidines group and 177 patients in the taxanes, platinum plus fluoropyrimidines group were included into analysis. No statistical differences in disease-free survival and overall survival were observed between two groups. After propensity score matching, 172 couples of patients were matched, the baseline characteristics were balanced. The median disease-free survival were 15.8 months (95% CI, 9.3~22.4) in the platinum plus fluoropyrimidines group and 22.6 months (95% CI, 15.9~29.4) in the taxanes, platinum plus fluoropyrimidines group (HR = 0.63; 95% CI, 0.48~0.85; P = 0.002). The median overall survival was 25.4 months for patients in the platinum plus fluoropyrimidines group (95% CI, 19.4~31.3) and 33.8 months (95% CI, 23.5~44.2) for those in the taxanes, platinum plus fluoropyrimidines group (HR = 0.68; 95% CI, 0.53-0.87; log-rank test, P = 0.002). CONCLUSIONS: For gastric adenocarcinoma patients, the adjuvant triplet combination of taxanes, platinum, and fluoropyrimidines regimen after D2 gastrectomy was superior to platinum plus fluoropyrimidines regimen in disease-free survival as well as overall survival. TRIAL REGISTRATION: This project has been registered in the Chinese Clinical Trial Registry ( ChiCTR1800019978 ).

Differential Metabolic Pathways and Metabolites in a C57BL/6J Mouse Model of Alcoholic Liver Disease.

BACKGROUND Alcoholic liver disease (ALD), an important cause of acute or chronic liver injury, results from binge drinking or long-term alcohol consumption. To date, there is no well-established mouse model with a comprehensive metabolic profile that mimics ALD in humans. This study aimed to explore the differential metabolic pathways and related differential metabolites in the liver of an ALD mouse model. MATERIAL AND METHODS A C57BL/6J mouse model of ALD was induced by alcohol feeding for 10 days plus binge alcohol feeding. The metabolomic profiles in the liver of the ALD mouse model was detected through ultra-high-pressure liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UHPLC/Q-TOF-MS). RESULTS A total 35 metabolites were significantly altered during the development of ALD. These metabolites were correlated to multiple metabolic pathways, including purine metabolism, the pentose phosphate pathway, cysteine and methionine metabolism, D-glutamine and D-glutamate metabolism, pyrimidine metabolism, and vitamin B6 metabolism. CONCLUSIONS The findings of the present study reveal potential biomarkers of ALD, and provide further insights into the pathogenesis of ALD.

Nomograms for predicting survival in patients with metastatic gastric adenocarcinoma who undergo palliative gastrectomy.

BACKGROUND: Recently, evidence has emerged that palliative gastrectomy in patients with stage IV gastric cancer may offer some survival benefits. However, the decision whether to perform primary tumor surgery remains challenging for surgeons, and investigations into models that are predictive of prognosis are scarce. Current study aimed to develop and validate prognostic nomograms for patients with metastatic gastric adenocarcinoma treated with palliative gastrectomy. METHODS: The development dataset comprised 1186 patients from the Surveillance, Epidemiology, and End Results Program who were diagnosed with metastatic gastric adenocarcinoma in 2004-2011, while the validation dataset included 407 patients diagnosed in 2012-2015. Variables were incorporated into a Cox proportional hazards model to identify independent risk factors for survival. Both pre- and postoperative nomograms for predicting 1- or 2-year survival probabilities were constructed using the development dataset. The concordance index (c-index) and calibration curves were plotted to determine the accuracy of the nomogram models. Finally, the cut-off value of the calculated total scores based on preoperative nomograms was set and validated by comparing survival with contemporary cases without primary tumor surgery. RESULTS: Age, tumor size, location, grade, T stage, N stage, metastatic site, scope of gastrectomy, number of examined lymph node(s), chemotherapy and radiotherapy were risk factors of survival and were included as variables in the postoperative nomogram; the c-indices of the development and validation datasets were 0.701 (95% confidence interval [CI]: 0.693-0.710) and 0.699 (95% CI: 0.682-0.716), respectively. The preoperative nomogram incorporated age, tumor size, location, grade, depth of invasion, regional lymph node(s) status, and metastatic site. The c-indices for the internal (bootstrap) and external validation sets were 0.629 (95% CI: 0.620-0.639) and 0.607 (95% CI: 0.588-0.626), respectively. Based on the preoperative nomogram, patients with preoperative total score > 28 showed no survival benefit with gastrectomy compared to no primary tumor surgery. CONCLUSIONS: Our survival nomograms for patients with metastatic gastric adenocarcinoma undergoing palliative gastrectomy can assist surgeons in treatment decision-making and prognostication.

HIV transmission between spouses living in Lu'an city, Anhui province, China: a longitudinal study.

This study aims to investigate the human immunodeficiency virus (HIV) transmission rate in HIV serodiscordant couples, in addition to the relevant influencing factors. From January 1999 to August 2016, patients with HIV/AIDS (index cases) along with their fixed partners were registered and monitored to determine the rate of HIV transmission between couples, as well as relevant influencing factors. A total of 231 HIV-positive couples were investigated, of these, 45-negative (19.48%) partners were infected with HIV via sexual transmission prior to diagnosis of the first case detected in couples. After diagnosis, the transmission rate between spouses was 0.39 per 100 person-years (2/507.7), and the cumulative transmission rate was 1.08% (2/186), which was significantly lower than the transmission rate before diagnosis (χ2 = 35.714, P < 0.001). Among the 119 HIV/AIDS patients who received antiretroviral therapy (ART), the transmission rate was 0 (0/119), whereas the transmission rate was 2.99% (2/67) in HIV/AIDS patients who did not receive ART. In addition, HIV transmission rate in serodiscordant couples was high prior to diagnosis of the index case. However, following diagnosis, the transmission rate was reduced, and the risk of transmission in the index case with antiviral treatment was null. Therefore, a prompt intervention in HIV discordant couples with ART of index case is vital to reduce the risk of HIV transmission.

The doses of plasmid backbone plays a major role in determining the HBV clearance in hydrodynamic injection mouse model.

BACKGROUND: Hepatitis B virus (HBV) chronically infects approximately 350 million people worldwide, causing a major risk of liver disease and hepatocellular carcinoma (HCC). Many mouse models have been tried to establish HBV infection through injection with various HBV-containing plasmids. However, it is not well understood that different plasmids, all of which contain the similar HBV genome, even the same plasmids with different dose, results in opposite immune responses toward HBV. METHODS: In this study, we investigated the role of HBV-containing plasmid backbones and the HBcAg in determining the HBV persistence. C57BL/6 mice were injected hydrodynamically with 6 µg or 20 µg of WT pAAV/HBV1.2 plasmid, e/core-null pAAV/HBV1.2 plasmid, or none-HBV genome pAAV/control plasmid. Serum levels of HBV-related markers were measured by quantitative immunoradiometric assay (IRMA). Liver HBcAg expression was detected by immunohistochemical staining. The mRNA levels of cytokines and Th1-related immune factors were quantified by qRT-PCR. RESULTS: All mice injected with 6 µg of the pAAV/HBV1.2 plasmid shows HBsAg positive at week 6 after hydrodynamic injection (AHI) as previously investigated. However, the mice injected with 20 µg pAAV/HBV1.2 or 6µgpAAV/HBV1.2 plus 14µgpAAV/control plasmid results in HBV clearance within 4 weeks AHI, indicating the anti-HBV activity is induced by 20 µg plasmid DNA, but not by the inserted viral genome. This anti-HBV activity is independent of HBcAg and Toll like receptor (TLR) signaling pathway, since the lack of HBcAg in pAAV/HBV1.2 plasmid or stimulation with TLRs agonists does not influence the kinetics of serum HBsAg in mice. The mRNA levels of t-bet and cxcr3 were dramatically up-regulated in the liver of the mice injected with 20 µg plasmid DNA. CONCLUSION: Our studies demonstrate that plasmid backbones are responsible for modulating immune responses to determine HBV persistence or clearance in our HBV mouse model by hydrodynamic injection of HBV-containing plasmid, and Th1 cells play key roles on HBV clearance.

Bone metastasis is a late-onset and unfavorable event in survivors of gastric cancer after radical gastrectomy: Results from a clinical observational cohort.

Background: The timing and incidence of recurrent bone metastasis (BM) after radical gastrectomy in patients with gastric cancer (GC) as well as the survival of these patients were not fully understood. The aim of this study was to analyze the data of an observational GC cohort and identify patients who underwent curative gastrectomy and had recurrent BM to describe and clarify the pattern and profile of BM evolution after surgery. Methods: Data were retrieved from a hospital-based GC cohort, and patients who underwent upfront radical gastrectomy were selected. The time points of specific organ metastatic events were recorded, and the person-year incidence rate of metastatic events was calculated. The latency period of BM events after gastrectomy was measured and compared with that of the other two most common metastatic events, liver metastasis (LM) and distant lymph node metastasis (LNM), using analysis of variance. Propensity score matching and subgroup analysis were used for sensitivity analysis. Results: A total of 1324 GC cases underwent radical gastrectomy between January 2011 and December 2021. Of these, 67 BM, 218 LM, and 248 LNM occurred before the last follow-up. The incidence of BM events was 1.7/100 person-years, which was approximately 3-fold lower than that of LM and distant LNM events (5.5 and 6.3 per 100 person-years, respectively). BM events had a significantly longer latency (median time, 16.5 months) than LM and LNM events (11.1 and 12.0 months, respectively). Recurrent BM led to a worse prognosis (median survival, 4.5 months) than those of LM and LNM events (median survival, 7.7 and 7.1 months, respectively). However, no difference in overall survival after gastrectomy was observed among the groups. Conclusions: Compared with other common metastatic events, BM in GC after gastrectomy is a late-onset event indicating poor survival. Trial registration: No. ChiCTR1800019978; http://www.chictr.org.cn/.

Melatonin overcomes apoptosis resistance in human hepatocellular carcinoma by targeting survivin and XIAP.

Apoptosis resistance in hepatocellular carcinoma (HCC) is one of the most significant factors for hepatocarcinogenesis and tumor progression, and leads to resistance to conventional chemotherapy. It is well known that inhibitor of apoptosis proteins (IAPs) play key roles in apoptosis resistance, it has become an important target for antitumor therapy. In this study, we examined if melatonin, the main secretory product of the pineal gland, targeted IAPs, leading to the inhibition of apoptosis resistance. To accomplish this, we first observed that four members of IAPs (cIAP-1, cIAP-2, survivin, and XIAP) were overexpressed in human HCC tissue. Interestingly, melatonin significantly inhibited the growth of HepG2 and SMMC-7721 cells and promoted apoptosis along with the downregulation of survivin and XIAP, but had no effect on the expression of cIAP-1 and cIAP-2. These data suggest that the inhibition of survivin and XIAP by melatonin may play an important part in reversing apoptosis resistance. Notably, cIAP-1, survivin and XIAP were significantly associated with the coexpression of COX-2 in human HCC specimens. Melatonin also reduced the expression of COX-2 and inhibited AKT activation in HepG2 and SMMC-7721 cells. Inhibition of COX-2 activity with the selective inhibitor, NS398, and inhibition of AKT activation using the PI3K inhibitor, LY294002, in tumor cells confirmed that melatonin-induced apoptosis was COX-2/PI3K/AKT-dependent, suggesting that the COX-2/PI3K/AKT pathway plays a role in melatonin inhibition of IAPs. Taken together, these results suggest that melatonin overcomes apoptosis resistance by the suppressing survivin and XIAP via the COX-2/PI3K/AKT pathway in HCC cells.

Melatonin reverses tunicamycin-induced endoplasmic reticulum stress in human hepatocellular carcinoma cells and improves cytotoxic response to doxorubicin by increasing CHOP and decreasing survivin.

Chemoresistance in hepatocellular carcinoma (HCC) is associated with multiple cellular responses to environmental stresses, such as nutrient deprivation and hypoxia. Nevertheless, whether ER stress resulting from nutrient deprivation and tumor hypoxia contributes to drug resistance remains unclear. Melatonin increased the efficacy of chemotherapeutic drugs in hepatocellular carcinoma in our previous studies. However, the effects of melatonin on endoplasmic reticulum (ER) stress-induced resistance to chemotherapeutic agents in HCC have not been tested. The effect of the endoplasmic reticulum (ER) stress response during resistance of human hepatocellular carcinoma cells against doxorubicin was investigated in this study. Pretreatment of HepG2 and SMMC-7721 cells (two human hepatocellular carcinoma cell lines) with tunicamycin, an ER stress inducer, drastically decreased the rate of apoptosis generated by doxorubicin. Interestingly, co-pretreatment with tunicamycin and melatonin significantly increased apoptosis induced by doxorubicin. Simultaneously, the expression of phosphorylated AKT (p-AKT) was elevated in HepG2 and SMMC-7721 cells given tunicamycin but reduced in the presence of melatonin. Furthermore, consistent with inhibition of AKT activation by using the PI3K inhibitor LY294002, melatonin elevated the levels of CHOP (C/EBP-homologous protein) and reduced the levels of Survivin (a member of the inhibitor of apoptosis protein family)suggesting that inhibition of the PI3K/AKT pathway by melatonin-reversed ER stress-induced resistance to doxorubicin in human hepatocellular carcinoma cells. These results demonstrate that melatonin attenuates ER stress-induced resistance to doxorubicin in human hepatocellular carcinoma cells by down-regulating the PI3K/AKT pathway, increasing the levels of CHOP and decreasing the levels of Survivin.

Prediction of common labels for universal domain adaptation.

Universal domain adaptation (UniDA) is an unsupervised domain adaptation that selectively transfers the knowledge between different domains containing different label sets. However, the existing methods do not predict the common labels of different domains and manually set a threshold to discriminate private samples, so they rely on the target domain to finely select the threshold and ignore the problem of negative transfer. In this paper, to address the above problems, we propose a novel classification model named Prediction of Common Labels (PCL) for UniDA, in which the common labels are predicted by Category Separation via Clustering (CSC). It is noted that we devise a new evaluation metric called category separation accuracy to measure the performance of category separation. To weaken negative transfer, we select source samples by the predicted common labels to fine-tune model for better domain alignment. In the test process, the target samples are discriminated by the predicted common labels and the results of clustering. Experimental results on three widely used benchmark datasets indicate the effectiveness of the proposed method.

Incorporation of liver chemistry score in predicting survival of liver-involved advanced gastric cancer patients who received palliative chemotherapy.

BACKGROUND: Gastric cancer liver metastasis (GCLM) patients usually accompany by abnormal serum liver function tests (LFTs) more or less; however, the prognostic value of LFTs is not fully understood. This study aimed to develop a liver chemistry score (LCS) based on LFTs and incorporate it into prognosis determination for GCLM patients who received palliative chemotherapy. METHODS: Data were derived from hospitalized GCLM patients in two general hospitals in China. LCS was generated based on the results of LFTs by LASSO regression. Cutoff value of the score was determined by restricted cubic spline. The score was then incorporated into Cox regression analysis to construct a predictive nomogram; the model was then evaluated internally and externally by AUC of time-dependent receiver operating characteristic curves (ROC) and calibration curves. RESULTS: Three hundred and thirty-six and 72 patients were included in development and validation cohort, respectively. LASSO regression analysis in development cohort finally reached a two-parametric LCS calculated on AST and ALP levels as 0.03343515 × ln (AST, U/L) + 0.02687997 × ln (ALP, U/L), and 0.232 was set as optimal cutoff value. Patients in low (LCS < 0.232) or high (LCS ≥ 0.232) score group experienced different survival times; median OS was 13.54 (95% CI: 11.1-15.6) months in the low LCS group and 7.3 (6.6-9.3) months in the high LCS group (p < 0.001). A nomogram including LCS and other clinical parameters was constructed and showed superior performance than model not including LCS. AUC of 6-month ROC improved from 0.647 (95% CI: 0.584-0.711) to 0.699 (0.638-0.759) in internal validation, and 0.837 (0.734-0.940) to 0.875 (0.784-0.966) in external validation. CONCLUSIONS: Liver chemistry score is useful in determining the prognosis of gastric cancer patients with liver metastasis and may be helpful to clinicians in decision-making.

Melatonin sensitizes human hepatoma cells to endoplasmic reticulum stress-induced apoptosis.

Endoplasmic reticulum stress-mediated cell apoptosis is implicated in the development of cancer. Melatonin induces apoptosis in hepatocellular carcinoma (HCC) in experimental studies, but the effects of melatonin on endoplasmic reticulum (ER) stress-induced apoptosis in HCC have not been tested. Differences in ER stress-induced apoptosis in human hepatoma cells and normal human hepatocyte were investigated by exposure to tunicamycin (ER stress inducer). Significant differences were observed in the rate of apoptosis between HepG2 cells (hepatoma cells) and HL-7702 cells (normal human hepatocyte cells). The expression of cyclooxygenase-2 (COX-2) was increased in HepG2 cells but not in HL-7702 cells. Furthermore, down-regulation of COX-2 expression using the COX-2 inhibitor, celecoxib, increased tunicamycin-induced apoptosis concomitant with the up-regulation of pro-apoptotic transcription factor CHOP (GADD153) and down-regulation of B-cell lymphoma 2/Bcl-2-associated X protein (Bcl-2/Bax) ratio, suggesting that inhibition of COX-2 sensitized human hepatoma cells to ER stress-induced apoptosis. Interestingly, co-treatment with tunicamycin and melatonin also decreased the expression of COX-2 and significantly increased the rate of apoptosis by elevating the levels of CHOP and reducing the Bcl-2/Bax ratio. These results demonstrate that melatonin sensitizes human hepatoma cells to ER stress-induced apoptosis by down-regulating COX-2 expression, increasing the levels of CHOP and decreasing the Bcl-2/Bax ratio.

Determination of Survival of Gastric Cancer Patients With Distant Lymph Node Metastasis Using Prealbumin Level and Prothrombin Time: Contour Plots Based on Random Survival Forest Algorithm on High-Dimensionality Clinical and Laboratory Datasets.

PURPOSE: This study aimed to identify prognostic factors for patients with distant lymph node-involved gastric cancer (GC) using a machine learning algorithm, a method that offers considerable advantages and new prospects for high-dimensional biomedical data exploration. MATERIALS AND METHODS: This study employed 79 features of clinical pathology, laboratory tests, and therapeutic details from 289 GC patients whose distant lymphadenopathy was presented as the first episode of recurrence or metastasis. Outcomes were measured as any-cause death events and survival months after distant lymph node metastasis. A prediction model was built based on possible outcome predictors using a random survival forest algorithm and confirmed by 5×5 nested cross-validation. The effects of single variables were interpreted using partial dependence plots. A contour plot was used to visually represent survival prediction based on 2 predictive features. RESULTS: The median survival time of patients with GC with distant nodal metastasis was 9.2 months. The optimal model incorporated the prealbumin level and the prothrombin time (PT), and yielded a prediction error of 0.353. The inclusion of other variables resulted in poorer model performance. Patients with higher serum prealbumin levels or shorter PTs had a significantly better prognosis. The predicted one-year survival rate was stratified and illustrated as a contour plot based on the combined effect the prealbumin level and the PT. CONCLUSIONS: Machine learning is useful for identifying the important determinants of cancer survival using high-dimensional datasets. The prealbumin level and the PT on distant lymph node metastasis are the 2 most crucial factors in predicting the subsequent survival time of advanced GC. TRIAL REGISTRATION: ChiCTR Identifier: ChiCTR1800019978.

Machine learning models for predicting one-year survival in patients with metastatic gastric cancer who experienced upfront radical gastrectomy.

Tumor metastasis is a common event in patients with gastric cancer (GC) who previously underwent curative gastrectomy. It is meaningful to employ high-volume clinical data for predicting the survival of metastatic GC patients. We aim to establish an improved machine learning (ML) classifier for predicting if a patient with metastatic GC would die within 12 months. Eligible patients were enrolled from a Chinese GC cohort, and the complete detailed information from medical records was extracted to generate a high-dimensional dataset. Appropriate feature engineering and feature filter were conducted before modeling with eight algorithms. A 10-fold cross validation (CV) nested in a holdout CV (8:2) was employed for hyperparameter tuning and model evaluation. Model selection was based on the area under the receiver operating characteristic (AUROC) curve, recall, and precision. The selected model was globally explained using interpretable surrogate models. Of the total 399 cases (median survival of 8.2 months), 242 patients survived less than 12 months. The linear discriminant analysis (LDA), support vector machine (SVM), and random forest (RF) model had the highest AUROC (0.78 ± 0.021), recall (0.93 ± 0.031), and precision (0.80 ± 0.026), respectively. The LDA model created a new function that generally separated the two classes. The predicted probability of the SVM model was interpreted using a linear regression model visualized by a nomogram. The predicted class of the RF model was explained using a decision tree model. In summary, analyzing high-volume medical data by ML is helpful to produce an improved model for predicting the survival in patients with metastatic GC. The algorithm should be carefully selected in different practical scenarios.

Two-stage battery recharge scheduling and vehicle-charger assignment policy for dynamic electric dial-a-ride services.

Coordinating the charging scheduling of electric vehicles for dynamic dial-a-ride services is challenging considering charging queuing delays and stochastic customer demand. We propose a new two-stage solution approach to handle dynamic vehicle charging scheduling to minimize the costs of daily charging operations of the fleet. The approach comprises two components: daily vehicle charging scheduling and online vehicle-charger assignment. A new battery replenishment model is proposed to obtain the vehicle charging schedules by minimizing the costs of vehicle daily charging operations while satisfying vehicle driving needs to serve customers. In the second stage, an online vehicle-charger assignment model is developed to minimize the total vehicle idle time for charges by considering queuing delays at the level of chargers. An efficient Lagrangian relaxation algorithm is proposed to solve the large-scale vehicle-charger assignment problem with small optimality gaps. The approach is applied to a realistic dynamic dial-a-ride service case study in Luxembourg and compared with the nearest charging station charging policy and first-come-first-served minimum charging delay policy under different charging infrastructure scenarios. Our computational results show that the approach can achieve significant savings for the operator in terms of charging waiting times (-74.9%), charging times (-38.6%), and charged energy costs (-27.4%). A sensitivity analysis is conducted to evaluate the impact of the different model parameters, showing the scalability and robustness of the approach in a stochastic environment.

Identification of Key Genes for Hepatitis Delta Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis.

BACKGROUND: It has been proposed that hepatitis delta virus (HDV) induces hepatic carcinogenesis by distinct molecular events compared with hepatocellular carcinoma (HCC) that is commonly induced by other hepatitis viruses. This study aimed to explore the underlying mechanism by identifying the key genes for HDV-HCC using bioinformatics analysis. METHODS: The GSE107170 dataset was downloaded and the differentially expressed genes (DEGs) were obtained by the online tool GEO2R. Gene otology (GO) functional analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using R packages. The protein-protein interaction (PPI) network was constructed by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). Hub genes were selected by Cytoscape software according to degree algorithm. The hub genes were further validated in terms of expression and survival analysis based on public databases. RESULTS: A total of 93 commonly upregulated genes and 36 commonly downregulated genes were found. The top 5 upregulated hub genes were TFRC, ACTR2, ARPC1A, ARPC3, and ARPC2. The top 5 downregulated hub genes were CTNNB1, CCND1, CDKN1B, CDK4, and CDKN1A. In the validation analysis, the expressions of ARPC1A, ARPC3, and CDK4 were promoted in general liver cancer samples. Higher expressions of ARPC2 and CDK4 and lower expressions of CDKN1A, CCND1, and CDKN1B were associated with worse prognosis in general HCC patients. CONCLUSION: The present study identifies a series of key genes that may be involved in the carcinogenesis of HDV-HCC and used as prognostic factors.

Performances of Prognostic Models in Stratifying Patients with Advanced Gastric Cancer Receiving First-line Chemotherapy: a Validation Study in a Chinese Cohort.

PURPOSE: While several prognostic models for the stratification of death risk have been developed for patients with advanced gastric cancer receiving first-line chemotherapy, they have seldom been tested in the Chinese population. This study investigated the performance of these models and identified the optimal tools for Chinese patients. MATERIALS AND METHODS: Patients diagnosed with metastatic or recurrent gastric adenocarcinoma who received first-line chemotherapy were eligible for inclusion in the validation cohort. Their clinical data and survival outcomes were retrieved and documented. Time-dependent receiver operating characteristic (ROC) and calibration curves were used to evaluate the predictive ability of the models. Kaplan-Meier curves were plotted for patients in different risk groups divided by 7 published stratification tools. Log-rank tests with pairwise comparisons were used to compare survival differences. RESULTS: The analysis included a total of 346 patients with metastatic or recurrent disease. The median overall survival time was 11.9 months. The patients were different into different risk groups according to the prognostic stratification models, which showed variability in distinguishing mortality risk in these patients. The model proposed by Kim et al. showed relative higher predicting abilities compared to the other models, with the highest χ2 (25.8) value in log-rank tests across subgroups, and areas under the curve values at 6, 12, and 24 months of 0.65 (95% confidence interval [CI]: 0.59-0.72), 0.60 (0.54-0.65), and 0.63 (0.56-0.69), respectively. CONCLUSIONS: Among existing prognostic tools, the models constructed by Kim et al., which incorporated performance status score, neutrophil-to-lymphocyte ratio, alkaline phosphatase, albumin, and tumor differentiation, were more effective in stratifying Chinese patients with gastric cancer receiving first-line chemotherapy.

[An investigation of Gram-positive bacteria infection in an intensive care unit during 6 years].

OBJECTIVE: To retrospectively investigate the risk factors, distribution, antibiotic resistance of infection with Gram-positive (G+) bacteria in an intensive care unit (ICU), so as to provide the reference for clinical prevention and treatment. METHODS: A retrospective analysis of clinical data of 83 patients with G+ bacteria infection in ICU from January 2003 to December 2008 was done. RESULTS: Of the 125 strains of G+ bacteria from 83 patients, Staphylococcus was the main organism (63.2%, 79/125). The prognosis of the patient was related with surgical operation (chi2=9.107, P=0.003), gastric intubation (chi2=4.053, P=0.044), complication (chi2 5.908, P=0.015) and the use of immunosuppressant (chi2=5.761, P=0.016). Multi-bacterial infection was related with surgery (chi2=8.847, P=0.003) and tracheostomy (chi2=10.445, P=0.001). The antibiotic susceptibility test in vitro showed that G+ bacteria displayed multi-resistance to antibiotics, but all of G+ bacteria were sensitive to vancomycin (resistance rate was 0). CONCLUSION: Staphylococcus was the most common pathogen of G+ bacterial infection in ICU. Further surveillance of bacterial resistance is warranted in ICU, and antimicrobial drugs should be used according to the result of susceptibility test. Taking account of the antibiotic resistance and risk factors of G+ bacteria infection in ICU, the infection could be controlled and the death rate could be cut down when appropriate measures are taken.

Poorer prognosis of ovarian squamous cell carcinoma than serous carcinoma: a propensity score matching analysis based on the SEER database.

BACKGROUND: Ovarian squamous cell carcinoma (SCC) is a rare cancer with possible poor survival, however no direct evidence supports this viewpoint and the independent prognostic factors are controversial. Patients with ovarian SCC and serous carcinoma (SC) who were diagnosed between 2004 and 2016 were selected using the recent released SEER database. Propensity score matching was used to balance the characteristics of the two groups. The difference of survival between patients with ovarian SCC and SC was explored using Kaplan-Meier method. Cox regression analyses were performed to further identify the independent prognostic factors among patients with ovarian SCC. RESULTS: Of 15,286 patients (15,106 SC cases and 180 SCC cases), 304 were identified in the matched cohort (200 SC cases and 104 SCC cases). The overall survival and cause-specific survival for patients with SCC were significantly poorer (Plog-rank < 0.001). The median survival time was 21 months for SCC and 95 months for SC. Patients who underwent bilateral salpingo-oophorectomy with hysterectomy and omentectomy seemed to have a better outcome. In multivariate analysis, older age at diagnosis, larger tumor size, bilateral and FIGO stage IV malignancy were the independent risk factors for poor disease outcome. CONCLUSIONS: The prognosis of ovarian SCC is worse than ovarian SC. Older age at diagnosis, advanced disease stage, larger tumor size and bilateral malignancy are the independent risk factors for poor survival.