Risk assessment of multiple pesticide residues in Agrocybe aegerita: Based on a 3-year monitoring survey.

The presence of pesticide residues in Agrocybe aegerita has raised an extensive concern. In this paper, based on a 3-year monitoring survey, the dietary exposure risks through A. aegerita consumption for different population subgroups were assessed using both deterministic and semi-probabilistic approaches under the best-case and the worst-case scenarios. Among the 52 targeted pesticides, 28 different compounds were identified in the concentration range of 0.005-3.610 mg/kg, and 87.4 % of samples contained one or more pesticide residues. The most frequently detected pesticide was chlormequat, followed by chlorfenapyr and cyhalothrin. The overall risk assessment results indicated extremely low chronic, acute, and cumulative dietary exposure risks for consumers. Using the ranking matrix, intake risks of pesticides were ranked, revealing endsoluran, chlorpyrifos, and methamidophos to be in the high-risk group. Finally, considering various factors such as the toxicity and risk assessment outcomes of each positive pesticide, use suggestions were proposed for A. aegerita cultivation.

Dietary patterns and hepatocellular carcinoma risk: a systematic review and meta-analysis of cohort and case-control studies.

BACKGROUND: Globally, HCC presents a significant health burden, characterized by high incidence and mortality rates. Epidemiological studies have increasingly suggested a link between dietary patterns and the risk of hepatocellular carcinoma (HCC), yet consensus on this relationship remains elusive. OBJECTIVE: This study aims to synthesize existing literature and provide a comprehensive analysis of the association between dietary patterns and HCC risk through meta-analytical methods. METHODS: A systematic search of PubMed, Embase, and the Cochrane Library databases was conducted to identify studies examining common dietary patterns in relation to HCC, published up to August 2023. Study quality was rigorously evaluated using the Newcastle-Ottawa Scale. We employed a random effects model to synthesize effect sizes, calculating hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: We identified 13 papers, of these 10 investigating a priori dietary patterns(index-based dietary patterns) and 3 focusing on a posterior dietary patterns (data-driven dietary patterns). Analysis of a priori dietary patterns revealed that higher scores in the Healthy Eating Index (HEI) & alternative HEI (HR = 0.67, 95% CI: 0.54-0.85), Dietary Approaches to Stop Hypertension (DASH) (HR = 0.77, 95% CI: 0.66-0.91), and the Mediterranean diet (HR = 0.65, 95% CI: 0.56-0.75) were associated with a reduced risk of HCC. Conversely, pro-inflammatory dietary patterns were linked with an increased risk (HR = 2.21, 95% CI: 1.58-3.09). In a posterior dietary patterns, a vegetable-based diet was negatively correlated with HCC risk (HR = 0.63, 95% CI: 0.49-0.81). CONCLUSION: This meta-analysis underscores a significant association between dietary patterns and the risk of HCC. Adherence to healthy dietary patterns characterized by high in vegetables, whole grains, legumes, nuts, and low in red and processed meats may confer a protective effect against HCC, whereas inflammatory diets appear to elevate risk.

Development and validation of an inflammatory biomarkers model to predict gastric cancer prognosis: a multi-center cohort study in China.

BACKGROUND: Inflammatory factors have increasingly become a more cost-effective prognostic indicator for gastric cancer (GC). The goal of this study was to develop a prognostic score system for gastric cancer patients based on inflammatory indicators. METHODS: Patients' baseline characteristics and anthropometric measures were used as predictors, and independently screened by multiple machine learning(ML) algorithms. We constructed risk scores to predict overall survival in the training cohort and tested risk scores in the validation. The predictors selected by the model were used in multivariate Cox regression analysis and developed a nomogram to predict the individual survival of GC patients. RESULTS: A 13-variable adaptive boost machine (ADA) model mainly comprising tumor stage and inflammation indices was selected in a wide variety of machine learning models. The ADA model performed well in predicting survival in the validation set (AUC = 0.751; 95% CI: 0.698, 0.803). Patients in the study were split into two sets - "high-risk" and "low-risk" based on 0.42, the cut-off value of the risk score. We plotted the survival curves using Kaplan-Meier analysis. CONCLUSION: The proposed model performed well in predicting the prognosis of GC patients and could help clinicians apply management strategies for better prognostic outcomes for patients.

Residue Behaviors and Degradation Dynamics of Insecticides Commonly Applied to Agrocybe aegerita Mushrooms from Field to Product Processing and Corresponding Risk Assessments.

Residual pesticides in Agrocybe aegerita mushroom have emerged as a significant concern and bring much uncertainty due to processing procedures. In this study, a modified QuEChERS sample preparation procedure and UPLC-MS/MS were used to analyze the residual levels of four commonly used pesticides in A. aegerita from field to product processing. The field results showed that dissipation of these targeted chemicals was consistent with the first-order kinetics, and the half-life time ranged from 20.4 h to 47.6 h. The terminal residues of the four pesticides at harvest time ranged from 9.81 to 4412.56 µg/kg in raw mushroom. The processing factors (PFs) of clothianidin, diflubenzuron, chlorbenzuron, and pyridaben ranged from 0.119 to 0.808 for the drying process and from 0.191 to 1 for the washing process. By integrating the data from the field trials, the PFs, and the consumption survey, the chronic dietary risks of the target chemicals via A. aegerita intake ranged from 2.41 × 10-5 to 5.69 × 10-2 for children and from 6.34 × 10-6 to 1.88 × 10-2 for adults, which are considerably below the threshold of 1, indicating no unacceptable risk to consumers in the Fujian province of China. This research offers foundational data for appropriate use and the maximum residue limit (MRL) establishment for these four insecticides in A. aegerita.

Research advances on TIL therapy for colorectal cancer.

Colorectal cancer (CRC) is a prevalent gastrointestinal malignancy. Tumor-infiltrating lymphocyte (TIL) therapy, a form of adoptive cellular therapy (ACT), involves isolating T lymphocytes from tumor tissues, in vitro expansion, and reintroduction into the body to target and eliminate tumor cells. This article presents an overview of the development and application of TIL therapy in CRC, as well as the associated challenges.

The potential of machine learning models to identify malnutrition diagnosed by GLIM combined with NRS-2002 in colorectal cancer patients without weight loss information.

BACKGROUND & AIMS: The key step of the Global Leadership Initiative on Malnutrition (GLIM) is nutritional risk screening, while the most appropriate screening tool for colorectal cancer (CRC) patients is yet unknown. The GLIM diagnosis relies on weight loss information, and bias or even failure to recall patients' historical weight can cause misestimates of malnutrition. We aimed to compare the suitability of several screening tools in GLIM diagnosis, and establish machine learning (ML) models to predict malnutrition in CRC patients without weight loss information. METHODS: This multicenter cohort study enrolled 4487 CRC patients. The capability of GLIM diagnoses combined with four screening tools in predicting survival probability was compared by Kaplan-Meier curves, and the most accurate one was selected as the malnutrition reference standard. Participants were randomly assigned to a training cohort (n = 3365) and a validation cohort (n = 1122). Several ML approaches were adopted to establish models for predicting malnutrition without weight loss data. We estimated feature importance and reserved the top 30% of variables for retraining simplified models. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were calculated to assess and compare model performance. RESULTS: NRS-2002 was the most suitable screening tool for GLIM diagnosis in CRC patients, with the highest hazard ratio (1.59; 95% CI, 1.43-1.77). A total of 2076 (46.3%) patients were malnourished diagnosed by GLIM combined with NRS-2002. The simplified random forest (RF) model outperformed other models with an AUC of 0.830 (95% CI, 0.805-0.854), and accuracy, sensitivity and specificity were 0.775, 0.835 and 0.742, respectively. We deployed an online application based on the simplified RF model to accurately estimate malnutrition probability in CRC patients without weight loss information (https://zzuwtt1998.shinyapps.io/dynnomapp/). CONCLUSIONS: Nutrition Risk Screening 2002 was the optimal initial nutritional risk screening tool in the GLIM process. The RF model outperformed other models, and an online prediction tool was developed to properly identify patients at high risk of malnutrition.

Exploring the optimal indicator of short-term peridiagnosis weight dynamics to predict cancer survival: A multicentre cohort study.

BACKGROUND: Body weight and its changes have been associated with cancer outcomes. However, the associations of short-term peridiagnosis weight dynamics in standardized, clinically operational time frames with cancer survival remain largely unknown. This study aimed to screen for and evaluate the optimal indicator of short-term peridiagnosis weight dynamics to predict overall survival (OS) in patients with cancer. METHODS: This multicentre cohort study prospectively collected data from 7460 patients pathologically diagnosed with cancer between 2013 and 2019. Body weight data were recorded 1 month before, at the time of and 1 month following diagnosis. By permuting different types (point value in kg, point height-adjusted value in kg/m2, absolute change in kg or relative change in percentage) and time frames (prediagnosis, postdiagnosis or peridiagnosis), we generated 12 different weight-related indicators and compared their prognostic performance using Harrell's C-index, integrated discrimination improvement, continuous net reclassification improvement and time-dependent C-index. We analysed associations of peridiagnosis relative weight change (RWC) with OS using restricted cubic spine (RCS), Kaplan-Meier analysis and multivariable-adjusted Cox regression models. RESULTS: The study enrolled 5012 males and 2448 females, with a median age of 59 years. During a median follow-up of 37 months, 1026 deaths occurred. Peridiagnosis (1 month before diagnosis to 1 month following diagnosis) RWC showed higher prognostic performance (Harrell's C-index = 0.601, 95% confidence interval [CI] = [0.583, 0.619]) than other types of indicators including body mass index (BMI), absolute weight change, absolute BMI change, prediagnosis RWC and postdiagnosis RWC in the study population (all P < 0.05). Time-dependent C-index analysis also indicated that peridiagnosis RWC was optimal for predicting OS. The multivariable-adjusted RCS analysis revealed an N-shaped non-linear association between peridiagnosis RWC and OS (PRWC < 0.001, Pnon-linear < 0.001). Univariate survival analysis showed that the peridiagnosis RWC groups could represent distinct mortality risk stratifications (P < 0.001). Multivariable survival analysis showed that, compared with the maintenance group (weight change < 5%), the significant (gain >10%, hazard ratio [HR] = 0.530, 95% CI = [0.413, 0.680]) and moderate (gain 5-10%, HR = 0.588, 95% CI = [0.422, 0.819]) weight gain groups were both associated with improved OS. In contrast, the moderate (loss 5-10%, HR = 1.219, 95% CI = [1.029, 1.443]) and significant (loss >10%, HR = 1.280, 95% CI = [1.095, 1.497]) weight loss groups were both associated with poorer OS. CONCLUSIONS: The prognostic performance of peridiagnosis RWC is superior to other weight-related indicators in patients with cancer. The findings underscore the importance of expanding the surveillance of body weight from at diagnosis to both past and future, and conducting it within clinically operational time frames, in order to identify and intervene with patients who are at risk of weight change-related premature deaths.

Algorithm design of a combinatorial mathematical model for computer random signals.

To improve the processing effect of computer random signals, the manuscript employs the intelligent signal recognition algorithm to design a combinatorial mathematical model for computer random signals, and studies the parameter estimation of conventional frequency hopping signal (FHS) based on optimizing kernel function (KF). First, the mathematical form and graphical representation of the ambiguity function of the conventional FHS are explored. Furthermore, a new KF is presented according to its fuzzy function (FF) and the parameters of conventional FHSs are estimated according to the time-frequency distribution corresponding to the KF. Then, simulation experiments are carried out in different types of interference noise environments. The proposed combinatorial mathematical model for computer random signals shows a practical impact, and can effectively improve the effect of random signal combination.

Value of the modified Patient-Generated Subjective Global Assessment in indicating the need for nutrition intervention and predicting overall survival in patients with malignant tumors in at least two organs.

BACKGROUND: Although the Patient-Generated Subjective Global Assessment (PG-SGA) is a reference standard used to assess a patient's nutrition status, it is cumbersome to administer. The aim of the present study was to estimate the value of a simpler and easier-to-use modified PG-SGA (mPG-SGA) to evaluate the nutrition status and need for intervention in patients with malignant tumors present in at least two organs. METHODS: A total of 591 patients (343 male and 248 female) were included from the INSCOC study. A Pearson correlation analysis was conducted to assess the correlation between the mPG-SGA and nutrition-related factors, with the optimal cut-off defined by a receiver operating characteristic curve (ROC). The consistency between the mPG-SGA and PG-SGA was compared in a concordance analysis. A survival analysis was used to determine the effects of nutritional intervention among different nutrition status groups. Univariable and multivariable Cox analyses were applied to evaluate the association of the mPG-SGA with the all-cause mortality. RESULTS: The mPG-SGA showed a negative association with nutrition-related factors. Individuals with an mPG-SGA ≥ 5 (rounded from 4.5) were considered to need nutritional intervention. Among the malnourished patients (mPG-SGA ≥ 5), the overall survival (OS) of those who received nutrition intervention was significantly higher than that of patients who did not. However, the OS was not significantly different in the better-nourished patients (mPG-SGA < 5). CONCLUSION: Our findings support that the mPG-SGA is a feasible tool that can be used to guide nutritional interventions and predict the survival of patients with malignant tumors affecting at least two organs.

Efficacy and safety of Xian-Lian-Jie-Du optimization decoction as an adjuvant treatment for prevention of recurrence in patients with stage IIIB/IIIC colon cancer: study protocol for a multicentre, randomized controlled trial.

INTRODUCTION: Colon cancer remains one of the most prevalent cancers worldwide. Unfortunately, there are no recognized and effective therapeutic strategies to prevent tumor recurrence after radical resection and chemotherapy, and the disease-free survival (DFS) in patients with stage IIIB or IIIC disease remains unsatisfactory. Xian-Lian-Jie-Du optimization decoction (XLJDOD) is a Chinese herbal medicine (CHM) empirical prescription, which has been validated experimentally and clinically that could inhibit the progression of colorectal cancer and ameliorate the symptoms. The purpose of this study is to evaluate the efficacy and safety of XLJDOD in prevention of recurrence of colon cancer. METHODS: This study is a multi-center, double-blind, randomized, placebo-controlled trial conducted at 13 hospitals of China. Following the completion of surgery and adjuvant 5- fluorouracil-based chemotherapy, a total of 730 subjects with stage IIIB or IIIC colon cancer will be randomized in a 1:1 ratio to an intervention group (n = 365; XLJDOD compound granule) and a control group (n = 365; Placebo). Patients will receive 6-month treatments and be followed up with 3 monthly assessments for 2 years. The primary outcome is 2-year DFS rate and the secondary outcomes are 1, 2-year relapse rate (RR), overall survival (OS) and quality of life (QoL). Safety outcomes such as adverse events will be also assessed. A small number of subgroup analysis will be carried out to explore the heterogeneity of effects of XLJDOD. DISCUSSION: The outcomes from this randomized controlled trial will provide objective evidences to evaluate XLJDOD's role as an adjuvant treatment in colon cancer. TRIAL REGISTRATION: www. CLINICALTRIALS: gov , identifier: NCT05709249. Registered on 31 Jan 2023.

Berberine inhibits high fat diet-associated colorectal cancer through modulation of the gut microbiota-mediated lysophosphatidylcholine.

Dietary fat intake is positively associated with elevated risk of colorectal cancer (CRC). Currently, clinical treatments remian inadequate bacause of the complex pathogenesis of CRC induced by a high-fat diet (HFD). Mechanistically, imbalances in gut microbiota are associated with HFD-associated colorectal tumourigenesis. Therefore, we investigated the anti-tumor activity of berberine (BBR) in modulating the dysregulated gut microbiota and related metabolites by preforming 16S rDNA sequencing and liquid chromatography/mass spectrometry. As expected, BBR treatment significantly decreased the number of colonic polyps, ameliorated gut barrier disruption, and inhibited colon inflammation and related oncogenic pathways in AOM/DSS-induced CRC model mice fed with an HFD. Furthermore, BBR alleviated gut microbiota dysbiosis and increased the abundance of beneficial gut microorganisms, including Akkermansia and Parabacteroides, in HFD-fed CRC mice. In addition, metabolomics analysis demonstrated significantly altered the glycerophospholipid metabolism during the progression of HFD-associated CRC in mice, whereas BBR treatment reverted these changes in glycerophospholipid metabolites, particularly lysophosphatidylcholine (LPC), which was confirmed to promote CRC cell proliferation and ameliorate cell junction impairment. Notably, BBR had no clear anti-tumor effects on HFD-fed CRC model mice with gut microbiota depletion, whereas transplantation of BBR-treated gut microbiota to gut microbiota-depleted CRC mice recapitulated the inhibitory effects of BBR on colorectal tumourigenesis and LPC levels. This study demonstrated that BBR inhibited HFD-associated CRC directly through modulating gut microbiota-regulated LPC levels, thereby providing a promising microbiota-modulating therapeutic strategy for the clinical prevention and treatment of Western diet-associated CRC.

Comparison of the performance of the GLIM criteria, PG-SGA and mPG-SGA in diagnosing malnutrition and predicting survival among lung cancer patients: A multicenter study.

BACKGROUND & AIMS: The present study aimed to compare the ability of the GLIM criteria, PG-SGA and mPG-SGA to diagnose malnutrition and predict survival among Chinese lung cancer (LC) patients. METHODS: This was a secondary analysis of a multicenter, prospective, nationwide cohort study, 6697 LC inpatients were enrolled between July 2013 and June 2020. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), area under the curve (AUC), and quadratic weighted Kappa coefficients were calculated to compare the ability to diagnose malnutrition. There were 754 patients who underwent follow-up for a median duration of 4.5 years. The associations between the nutritional status and survival were analyzed by the Kaplan-Meier method and multivariable Cox proportional hazard regression models. RESULTS: The median age of LC patients was 60 (53, 66), and 4456 (66.5%) were male. There were 617 (9.2%), 752 (11.2%), 1866 (27.9%), and 3462 (51.7%) patients with clinical stage Ⅰ, Ⅱ, Ⅲ, and Ⅳ LC, respectively. Malnutrition was present in 36.1%-54.2% (as evaluated using different tools). Compared with the PG-SGA (used as the diagnostic reference), the sensitivity of the mPG-SGA and GLIM was 93.7% and 48.3%; the specificity was 99.8% and 78.4%; and the AUC was 0.989 and 0.633 (P < 0.001). The weighted Kappa coefficients were 0.41 for the PG-SGA vs. GLIM, 0.44 for the mPG-SGA vs. GLIM, and 0.94 for the mPG-SGA vs PG-SGA in patients with stage Ⅰ-Ⅱ LC. These values were respectively 0.38, 0.39, and 0.93 in patients with stage Ⅲ-Ⅳ of LC. In a multivariable Cox analysis, the mPG-SGA (HR = 1.661, 95%CI = 1.348-2.046, P < 0.001), PG-SGA (HR = 1.701, 95%CI = 1.379-2.097, P < 0.001) and GLIM (HR = 1.657, 95%CI = 1.347-2.038, P < 0.001) showed similar death hazard ratios. CONCLUSIONS: The mPG-SGA provides nearly equivalent power to predict the survival of LC patients as the PG-SGA and the GLIM, indicating that all three tools are applicable for LC patients. The mPG-SGA has the potential to be an alternative replacement for quick nutritional assessment among LC patients.

AIWW: a new nutrition-screening tool for the oncologic population.

Malnutrition is a common comorbidity among patients with cancer. However, no nutrition-screening tool has been recognized in this population. A quick and easy screening tool for nutrition with high sensitivity and easy-to-use is needed. Based on the previous 25 nutrition-screening tools, the Delphi method was made by the members of the Chinese Society of Nutritional Oncology to choose the most useful item from each category. According to these results, we built a nutrition-screening tool named age, intake, weight, and walking (AIWW). Malnutrition was defined based on the scored patient-generated subjective global assessment (PG-SGA). Concurrent validity was evaluated using the Kendall tau coefficient and kappa consistency between the malnutrition risks of AIWW, nutritional risk screening 2002 (NRS-2002), and malnutrition screening tool (MST). Clinical benefit was calculated by the decision curve analysis (DCA), integrated discrimination improvement (IDI), and continuous net reclassification improvement (cNRI). A total of 11,360 patients (male, n=6,024 (53.0%) were included in the final study cohort, and 6,363 patients had malnutrition based on PG-SGA. Based on AIWW, NRS-2002, and MST, 7,545, 3,469, and 1,840 patients were at risk of malnutrition, respectively. The sensitivities of AIWW, NRS-2002, and MST risks were 0.910, 0.531, and 0.285, and the specificities were 0.768, 0.946, and 0.975. The Kendall tau coefficients of AIWW, NRS-2002, and MST risks were 0.588, 0.501, and 0.326, respectively. The area under the curve of AIWW, NRS-2002, and MST risks were 0.785, 0.739, and 0.630, respectively. The IDI, cNRI, and DCA showed that AIWW is non-inferior to NRS-2002 (IDI: 0.002 (-0.009, 0.013), cNRI: -0.015 (-0.049, 0.020)). AIWW scores can also predict the survival of patients with cancer. The missed diagnosis rates of AIWW, NRS-2002, and MST were 0.09%, 49.0%, and 73.2%, respectively. AIWW showed a better nutrition-screening effect than NRS-2002 and MST for patients with cancer and could be recommended as an alternative nutrition-screening tool for this population.

Global research trends between gut microbiota and lung cancer from 2011 to 2022: A bibliometric and visualization analysis.

Background: An increasing number of studies have found that the gut microbiota was related to the occurrence and development of lung cancer. Nonetheless, publication trends and research hotspots in this field remain unknown. The study aimed to perform a bibliometric analysis to systematically identify publication trends and research hotspots in the field of gut microbiota and lung cancer research within a 12-year panorama. Methods: Publications related to the gut microbiota and lung cancer between 1 January 2011 and 25 October 2022 were retrieved from the Web of Science Core Collection (WoSCC) database. The online analytic tool of the WoSCC was used to analyze various bibliometric parameters. The bibliometrics website, CiteSpace, and VOSviewer were used to identify research trends and hotspots. Results: A total of 375 publications related to the gut microbiota and lung cancer were extracted from WoSCC and identified for analysis. The number of annual publications has grown rapidly since 2018 and reached a peak in 2022. China was the most prolific country in this field, with 120 publications, followed by the United States (114), with the highest H-index of 31. Additionally, France ranked the highest with an average of 133 citations, while the leading institution and journal were the Unicancer and the International Journal of Molecular Sciences, respectively. Interestingly, Routy Bertrand was the most prolific author and also the most cited author in terms of H-index and citations. Reference and keyword burst detection indicated that the research hotspots mainly included 1) the gut microbiota directly affects the efficacy of immunotherapy for lung cancer, 2) the application of different gut bacteria on lung cancer, and 3) the mechanism of the gut microbiota on lung cancer. Conclusion: The findings of this study revealed the general publication trends and evolving research hotspots in the field of gut microbiota and lung cancer at a global level. The research hotspots focused on the clinical application of the gut microbiota combined with immunotherapy in lung cancer and its mechanism. The findings of this study provide new perspectives on the field, which may shed light on a beneficial impact on further etiological studies, diagnosis, and treatment for lung cancer.

Effects of systemic inflammation and frailty on survival in elderly cancer patients: Results from the INSCOC study.

Background: Frailty and systemic inflammation are parameters, which are easy to evaluate, can be used to predict disease outcomes, and are potentially modifiable. The combination of frailty and inflammation-based data may help identify elderly cancer patients predisposed to adverse clinical outcomes. The aim of this study was to examine the association of systemic inflammation and frailty at admission, and to determine whether these risk factors interact and may predict the survival of elderly cancer patients. Methods: A prospective Investigation on Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) with 5,106 elderly cancer patients admitted from 2013 through 2020 was included in this study. The primary marker of inflammation was the neutrophil-to-lymphocyte ratio (NLR), with the reference group having NLR<3, which indicated no inflammation. Frailty was assessed using the FRAIL scale, and patients with≥3 positives out of a total of five components were assumed to be frail. The primary outcome was all-cause mortality. We classified participants according to the presence (or absence) of frailty and high inflammation and assessed their association with overall survival using the Cox proportional hazards models adjusted for demographic, tumor, and treatment factors. Results: Among the 5,106 patients enrolled in the study, 3396 individuals (66.51%) were male and the mean( ± SD) age at diagnosis was 70.92( ± 5.34). Over a median of 33.5 months follow-up, we observed 2,315 deaths. Increasing NLR was associated with frailty (compared with NLR<3, odds ratio=1.23, 95%CI=1.08-1.41 for NLR≥3). An NLR≥3 and frailty independently predicted the overall survival [hazard ratio(HR)=1.35, 95%CI=1.24-1.47 and HR=1.38, 95%CI=1.25-1.52, respectively). Patients with both frailty and NLR≥3 had the lowest overall survival(HR=1.83, 95%CI=1.59-2.04) than patients with no risk factors. The mortality rate increased with the presence of the frailty components. Conclusions: Systemic inflammation was positively associated with frailty. Frail elderly cancer patients with elevated systemic inflammation had low survival rate.

Thiol oxidative stress-dependent degradation of transglutaminase2 via protein S-glutathionylation sensitizes 5-fluorouracil therapy in 5-fluorouracil-resistant colorectal cancer cells.

5-Fluorouracil (5-Fu) is a first-line drug for colorectal cancer (CRC) therapy. However, the development of 5-Fu resistance limits its chemotherapeutic effectiveness and often leads to poor prognoses of CRC. Transglutaminase 2 (TGM2), a member of the transglutaminase family, is considered to be associated with chemoresistance through apoptotic prevention in various cancers including CRC. TGM2 was found to be overexpressed in two 5-Fu-resistant CRC cell lines and down-regulated by increased thiol oxidative stress induced by inhibition of glutathione reductase (GR). The present study aimed to explore the role of TGM2 in 5-Fu-resistant CRC and the mechanism of action by which the elevated thiol oxidative stress down-regulates TGM2 protein level. The results revealed that 5-Fu-resistance induced by overexpression of TGM2 in CRC cells was reversed through up-regulation of thiol oxidative stress. Knockdown of TGM2 increased the chemosensitivity of CRC cells to 5-Fu. Thiol oxidative stress potentially enhanced the therapeutic effect of 5-Fu in the resistant CRC cells by promotion of 5-Fu-induced apoptosis through down-regulation of TGM2. The elevated thiol oxidative stress increased the S-glutathionylation of TGM2 and led to proteasomal degradation of TGM2. Furthermore, Cys193 was identified as the S-glutathionylation site in TGM2, and its mutation resulted in thiol oxidative stress-mediated CRC cell apoptotic resistance. TGM2-induced EMT was also suppressed by the elevated thiol oxidative stress. A xenograft tumor model confirmed the effect of thiol oxidative stress in the reversal of 5-Fu resistance in CRC cells in vivo. TGM2 protein expression level was found to be significantly higher in human CRC specimens than in non-cancerous colorectal tissues. Taken together, the present data suggest an important role of TGM2 in 5-Fu resistance in CRC cells. Up-regulation of thiol oxidative stress could be a potential therapeutic approach for treating 5-Fu-resistant CRC and TGM2 may serve as a potential therapeutic target of thiol oxidative stress.

Systemic inflammation with sarcopenia predicts survival in patients with gastric cancer.

OBJECTIVE: The levels of platelet-related inflammation indicators and sarcopenia have been reported to affect the survival of patients with cancer. To evaluate the prognostic influence of platelet count (PLT), platelet lymphocyte ratio (PLR), and systemic immune inflammation index (SII), and SII combined with sarcopenia on the survival of patients with gastric cancer (GC). METHODS: A total of 1133 patients with GC (812 male and 321 female, average age: 59.43 years) were evaluated. Receiver-operating characteristic curves were used to determine the best cutoff values of PLT, PLR, and SII, and univariate and multivariate Cox risk regression models were used to evaluate whether SII is an independent predictor of overall survival (OS). The prognostic SS (SII-sarcopenia) was established based on SII and sarcopenia. Finally, a comprehensive analysis of the prognostic SS was performed. RESULTS: SII had the strongest prognostic effect. The SII and OS of patients with GC were in an inverted U-shape (adjusted HR = 1.07; 95% CI 0.97-1.19; adjusted P = 0.179). In patients with SII > 1800, SII was negatively correlated with OS (adjusted HR = 0.57; 95% CI 0.29-1.12; adjusted P = 0.102), however, there is no statistical difference. Interestingly, a high SS was associated with a poorer prognosis. The higher the SS score was, the worse the OS (P < 0.001). CONCLUSION: SII is an independent prognostic indicator of GC, and high SII is related to poor prognosis. A higher SS score had worse survival. Thus, the prognostic SS is a reliable predictor of OS in patients with GC.

Assessing transfer of aluminum during tea brewing and associated population health risks.

Tea is consumed widely around the world owing to its refreshing taste and potential health benefits. However, drinking tea is considered a major route for dietary aluminum exposure in areas where tea consumption is relatively large. To assess the health risk associated with drinking tea, the contamination level of aluminum was determined in 81 tea samples. The transfer rate of aluminum during tea brewing was investigated. Then based on the site-specific exposure parameters such as consumption data and body weight for six different subpopulations in Fujian, the exposure risks were estimated using a probabilistic approach. Results demonstrate that the contents of aluminum in green tea, white tea, oolong tea, and black tea were significantly different according to the one-way ANOVA analysis (p < 0.05). The transfer rate of aluminum were 32.6%, 31.6%, 26.3%, and 14% for white tea, black tea, oolong tea, and green tea, respectively. With respect to the oral reference dose, the exposure of inhabitants in Fujian to aluminum through drinking tea is under control (even at the 99th percentile).