The Prognostic Significance of Apoptosis-Related Biological Markers in Chinese Gastric Cancer Patients

BACKGROUND AND OBJECTIVE: The prognosis varied among the patients with the same stage, therefore there was a need for new prognostic and predictive factors. The aim of this study was to evaluate the relationship of apoptosis-related biological markers such as p53, bcl-2, bax, and c-myc, and clinicopathological features and their prognostic value. METHODS: From 1996 to 2007, 4426 patients had undergone curative D2 gastrectomy for gastric cancer at Fudan University Shanghai Cancer Center. Among 501 patients, the expression levels of p53, bcl-2, bax, and c-myc were examined by immunohistochemistry. The prognostic value of biological markers and the correlation between biological markers and other clinicopathological factors were investigated. RESULTS: There were 339 males and 162 females with a mean age of 57. The percentages of positive expression of p53, bcl-2, bax, and c-myc were 65%, 22%, 43%, and 58%, respectively. There was a strong correlation between p53, bax, and c-myc expression (P=0.00). There was significant association between bcl-2, and bax expression (P<0.05). p53 expression correlated with histological grade (P=0.01); bcl-2 expression with pathological stage (P=0.00); bax expression with male (P=0.02), histological grade (P=0.01), Borrmann type (P=0.01), tumor location (P=0.00), lymph node metastasis (P=0.03), and pathological stage (P=0.03); c-myc expression with Borrmann type (P=0.00). bcl-2 expression was related with good survival in univariate analysis (P=0.01). Multivariate analysis showed that bcl-2 expression and pathological stage were defined as independent prognostic factors. There were significant differences of overall 5-year survival rates according to bcl-2 expression or not in stage IIB (P=0.03). CONCLUSION: The expression of bcl-2 was an independent prognostic factor for patients with gastric cancer; it might be a candidate for the gastric cancer staging system

MDDL: A Framework for Reinforcement Learning-based Position Allocation in Multi-Channel Feed

Nowadays, the mainstream approach in position allocation system is to utilize a reinforcement learning model to allocate appropriate locations for items in various channels and then mix them into the feed. There are two types of data employed to train reinforcement learning (RL) model for position allocation, named strategy data and random data. Strategy data is collected from the current online model, it suffers from an imbalanced distribution of state-action pairs, resulting in severe overestimation problems during training. On the other hand, random data offers a more uniform distribution of state-action pairs, but is challenging to obtain in industrial scenarios as it could negatively impact platform revenue and user experience due to random exploration. As the two types of data have different distributions, designing an effective strategy to leverage both types of data to enhance the efficacy of the RL model training has become a highly challenging problem. In this study, we propose a framework named Multi-Distribution Data Learning (MDDL) to address the challenge of effectively utilizing both strategy and random data for training RL models on mixed multi-distribution data. Specifically, MDDL incorporates a novel imitation learning signal to mitigate overestimation problems in strategy data and maximizes the RL signal for random data to facilitate effective learning. In our experiments, we evaluated the proposed MDDL framework in a real-world position allocation system and demonstrated its superior performance compared to the previous baseline. MDDL has been fully deployed on the Meituan food delivery platform and currently serves over 300 million users.Comment: 4 pages, 2 figures, accepted by SIGIR 202

MASH Suite Pro: A Comprehensive Software Tool for Top-Down Proteomics

Top-down mass spectrometry (MS)-based proteomics is arguably a disruptive technology for the comprehensive analysis of all proteoforms arising from genetic variation, alternative splicing, and posttranslational modifications (PTMs). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for data analysis in bottom-up proteomics, the data analysis tools in top-down proteomics remain underdeveloped. Moreover, despite recent efforts to develop algorithms and tools for the deconvolution of top-down high-resolution mass spectra and the identification of proteins from complex mixtures, a multifunctional software platform, which allows for the identification, quantitation, and characterization of proteoforms with visual validation, is still lacking. Herein, we have developed MASH Suite Pro, a comprehensive software tool for top-down proteomics with multifaceted functionality. MASH Suite Pro is capable of processing high-resolution MS and tandem MS (MS/MS) data using two deconvolution algorithms to optimize protein identification results. In addition, MASH Suite Pro allows for the characterization of PTMs and sequence variations, as well as the relative quantitation of multiple proteoforms in different experimental conditions. The program also provides visualization components for validation and correction of the computational outputs. Furthermore, MASH Suite Pro facilitates data reporting and presentation via direct output of the graphics. Thus, MASH Suite Pro significantly simplifies and speeds up the interpretation of high-resolution top-down proteomics data by integrating tools for protein identification, quantitation, characterization, and visual validation into a customizable and user-friendly interface. We envision that MASH Suite Pro will play an integral role in advancing the burgeoning field of top-down proteomics

Converting brownmillerite to alternate layers of Oxygen-deficient and conductive nano-sheets with enhanced thermoelectric properties

Introducing large oxygen deficiencies while retaining low resistivity is important for enhancing the overall thermoelectric properties in 3d transition-metal oxides. In this study, a new synthesis route to reconstruct the insulating brownmillerite SrCoO2.5 is adapted. Through a step-by-step nano-blocks modification, a series of highly-conductive layered structures is evolved, which are [Sr2O2H2]0.5CoO2, [Sr2O2]0.4CoO2, and [Sr2CoO3]0.57CoO2, while still retaining considerable Seebeck coefficient (˜100 µV K-1). Coexistence of low resistivity and high oxygen deficiency is realized in the latter two polymorphs by forming a majority of sintered oxygen vacancies in the rock-salt layer and a minority of normal oxygen vacancies in the CoO2 layer. A room-temperature in-plane power factor of 3.6 mW K-2 m-1, power output density of 4.5 W m-2 at a temperature difference of 28 K, and an out-of-plane thermal conductivity of 0.33 W K-1 m-1 are obtained in the [Sr2O2]0.4CoO2 thin film that exhibits the highest oxygen deficiency (d = 2.95), which is on par with Bi2Te3, the benchmark. It is pointed out that proper distribution of oxygen vacancy is essential in tailoring the physical and chemical properties of transition-metal oxides. The sintered/normal oxygen vacancy layer model provides guidance to the exploration of materials with both low electric resistivity and thermal conductivity.Peer ReviewedPostprint (author's final draft

High-conductive protonated layered oxides from H2O vapor-annealed brownmillerites

Protonated 3d transition-metal oxides often display low electronic conduction, which hampers their application in electric, magnetic, thermoelectric, and catalytic fields. Electronic conduction can be enhanced by co-inserting oxygen acceptors simultaneously. However, the currently used redox approaches hinder protons and oxygen ions co-insertion due to the selective switching issues. Here, a thermal hydration strategy for systematically exploring the synthesis of conductive protonated oxides from 3d transition-metal oxides is introduced. This strategy is illustrated by synthesizing a novel layered-oxide SrCoO3H from the brownmillerite SrCoO2.5. Compared to the insulating SrCoO2.5, SrCoO3H exhibits an unprecedented high electronic conductivity above room temperature, water uptake at 250 °C, and a thermoelectric power factor of up to 1.2 mW K-2 m-1 at 300 K. These findings open up opportunities for creating high-conductive protonated layered oxides by protons and oxygen ions co-doping.CC acknowledges support from the Spanish Ministry of Science, Innovation, and Universities under the “Ramón y Cajal” fellowship RYC2018-024947-I.Peer ReviewedPostprint (author's final draft

Long-Term Results and Prognostic Factors of Gastric Cancer Patients with Microscopic Peritoneal Carcinomatosis

BACKGROUND: Clinical significance of microscopic peritoneal carcinomatosis remained unclear. The aim of this study was to evaluate the prognostic value of microscopic peritoneal carcinomatosis in gastric cancer. METHODS: From 1996 to 2007, 4426 patients underwent gastrectomy for gastric cancer at Fudan University Shanghai Cancer Center. The clinical and pathological data were reviewed to identify patients with microscopic peritoneal carcinomatosis (group 1). The clinicopathological features and prognosis were examined. Additionally, 242 stage-matched gastric cancer patients without microscopic peritoneal carcinomatosis (group 2) and 118 with macroscopic peritoneal carcinomatosis (group 3) were selected as control groups. RESULTS: Microscopic peritoneal carcinomatosis was found in 121 patients. There were 85 males and 36 females (2.36:1). There was a higher incidence rate of large size tumor (≥5 cm) (P = 0.045), Borrmann IV (P = 0.000), and serosal invasion (P = 0.000) in gastric cancer with microscopic peritoneal carcinomatosis compared with the control group. The 5-year survival rate of gastric cancer with microscopic peritoneal carcinomatosis was 24%, significantly poorer than that of the stage-matched control group but better than that of patients with macroscopic peritoneal carcinomatosis. The independent prognostic factors identified included pathological stage and operative curability. CONCLUSIONS: The presence of microscopic peritoneal carcinomatosis was associated with worse prognosis for gastric cancer, but curative surgery showed potential to improve prognosis

Identification of mutations in porcine STAT5A that contributes to the transcription of CISH

Identification of causative genes or genetic variants associated with phenotype traits benefits the genetic improvement of animals. CISH plays a role in immunity and growth, however, the upstream transcriptional factors of porcine CISH and the genetic variations in these factors remain unclear. In this study, we firstly identified the minimal core promoter of porcine CISH and confirmed the existence of STATx binding sites. Overexpression and RT-qPCR demonstrated STAT5A increased CISH transcriptional activity (P &lt; 0.01) and mRNA expression (P &lt; 0.01), while GATA1 inhibited CISH transcriptional activity (P &lt; 0.01) and the following mRNA expression (P &lt; 0.05 or P &lt; 0.01). Then, the putative functional genetic variations of porcine STAT5A were screened and a PCR-SSCP was established for genotype g.508A&gt;C and g.566C&gt;T. Population genetic analysis showed the A allele frequency of g.508A&gt;C and C allele frequency of g.566C&gt;T was 0.61 and 0.94 in Min pigs, respectively, while these two alleles were fixed in the Landrace population. Statistical analysis showed that Min piglets with CC genotype at g.566C&gt;T or Hap1: AC had higher 28-day body weight, 35-day body weight, and ADG than TC or Hap3: CT animals (P &lt; 0.05, P &lt; 0.05). Further luciferase activity assay demonstrated that the activity of g.508A&gt;C in the C allele was lower than the A allele (P &lt; 0.05). Collectively, the present study demonstrated that STAT5A positively regulated porcine CISH transcription, and SNP g.566C&gt;T in the STAT5A was associated with the Min piglet growth trait

SIRT1 mediated gastric cancer progression under glucose deprivation through the FoxO1-Rab7-autophagy axis

PurposeSilent mating type information regulator 2 homolog 1 (SIRT1) and autophagy have a two-way action (promoting cell death or survival) on the progression and treatment of gastric cancer (GC) under different conditions or environments. This study aimed to investigate the effects and underlying mechanism of SIRT1 on autophagy and the malignant biological behavior of GC cells under conditions of glucose deprivation (GD).Materials and methodsHuman immortalized gastric mucosal cell GES-1 and GC cell lines SGC-7901, BGC-823, MKN-45 and MKN-28 were utilized. A sugar-free or low-sugar (glucose concentration, 2.5 mmol/L) DMEM medium was used to simulate GD. Additionally, CCK8, colony formation, scratches, transwell, siRNA interference, mRFP-GFP-LC3 adenovirus infection, flow cytometry and western blot assays were performed to investigate the role of SIRT1 in autophagy and malignant biological behaviors (proliferation, migration, invasion, apoptosis and cell cycle) of GC under GD and the underlying mechanism.ResultsSGC-7901 cells had the longest tolerance time to GD culture conditions, which had the highest expression of SIRT1 protein and the level of basal autophagy. With the extension of GD time, the autophagy activity in SGC-7901 cells also increased. Under GD conditions, we found a close relationship between SIRT1, FoxO1 and Rab7 in SGC-7901 cells. SIRT1 regulated the activity of FoxO1 and upregulated the expression of Rab7 through deacetylation, which ultimately affected autophagy in GC cells. In addition, changing the expression of FoxO1 provided feedback on the expression of SIRT1 in the cell. Reducing SIRT1, FoxO1 or Rab7 expression significantly inhibited the autophagy levels of GC cells under GD conditions, decreased the tolerance of GC cells to GD, enhanced the inhibition of GD in GC cell proliferation, migration and invasion and increased apoptosis induced by GD.ConclusionThe SIRT1-FoxO1-Rab7 pathway is crucial for the autophagy and malignant biological behaviors of GC cells under GD conditions, which could be a new target for the treatment of GC

Characterization of the Nucleocytoplasmic Transport Mechanisms of Epstein-Barr Virus BFLF2

Background/Aims: Epstein-Barr virus (EBV) BFLF2, the homologue of herpes simplex virus 1 (HSV-1) UL31, is crucial for the efficient viral DNA packaging and primary egress across the nuclear membrane. However, we still do not know its subcellular transport mechanisms. Methods: Interspecies heterokaryon assays were utilized to detect the nucleocytoplasmic shuttling of BFLF2, and mutation analysis, plasmid transfection and fluorescence microscopy assays were performed to identify the functional nuclear localization sequence (NLS) and nuclear export sequence (NES) of BFLF2 in live cells. Furthermore, the nuclear import and export of BFLF2 were assessed by confocal microscopy, co-immunoprecipitation and immunoblot assays. Results: BFLF2 was confirmed to shuttle between the nucleus and cytoplasm. Two predicted NESs were shown to be nonfunctional, yet we proved that the nuclear export of BFLF2 was mediated through transporter associated with antigen processing (TAP), but not chromosomal region maintenance 1 (CRM1) dependent pathway. Furthermore, one functional NLS, 22RRLMHPHHRNYTASKASAH40, was identified, and the aa22-23, aa22-25, aa28-30 and aa37-40 had an important role in the nuclear localization of BFLF2. Besides, the nuclear import of BFLF2 was demonstrated through Ran-, importin α7-, importin β1- and transportin-1-dependent mechanism that does not require importin α1, α3 and α5. Conclusion: These works are of significance for the further study of the functions of BFLF2 during EBV infection, as well as for further insights into the design of new antiviral drug target and vaccine development against EBV