Suicidal behaviors are significant public health issues. The aim of the current study is to examine the effects of perceived stress and resilience on suicidal ideation (SI), plan (SP), and attempt ...(SA) among early adolescents. A longitudinal study was conducted with data collected from 1035 junior high-school students at baseline and 1-year follow-up. Participants were assessed for suicidal behaviors, resilience, and perceived stress. Logistic regression was performed to analyze for the associations between independent variables and suicidal behaviors. 210 (20.3%) of the participants reported to have SI, 59 (5.7%) had SP, and 49 (4.7%) had SA at baseline. Perceived stress was a strong risk factor (
p
< 0.001) for SI (OR 1.16–1.18), SP (OR 1.20–1.21), and SA (OR 1.12–1.16) while accounting for different dimensions of resilience. Students with persistent high stress during the 1-year follow-up period had significantly increased risk of SI (OR 7.14–9.64), SP (OR 3.92–6.37), and SA (OR 3.76–3.84) than the persistent low-stress group (
p
< 0.01). Increased perceived stress scale (PSS) (OR 2.89–3.15) and decreased PSS (OR 2.47) also had a higher risk for SI than persistent low PSS group. Moreover, students with high perceived stress who reported to have higher hope and optimism were less likely to show SI (OR 0.90,
p
= 0.001) and SP (OR 0.87,
p
= 0.002) at baseline, and the problem-solving and cognitive maturity mature dimension of resilience showed a significant protective effect on SP longitudinally (OR 0.25,
p
= 0.003). Perceived stress substantially increased the risk for suicidal behaviors, and moderates the protective effect of resilience on suicide. Considering both risk and protective factors of suicidal behaviors is essential in designing future suicide prevention and intervention programs.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, ODKLJ, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, SIK, UILJ, UKNU, UL, UM, UPUK, VKSCE, VSZLJ, ZAGLJ
Summary Background Major adjuvant treatments for pancreatic adenocarcinoma include fluorouracil, gemcitabine, chemoradiation, and chemoradiation plus fluorouracil or gemcitabine. Since the optimum ...regimen remains inconclusive, we aimed to compare these treatments in terms of overall survival after tumour resection and in terms of grade 3–4 toxic effects with a systematic review and random-effects Bayesian network meta-analysis. Methods We searched PubMed, trial registries, and related reviews and abstracts for randomised controlled trials comparing the above five treatments with each other or observation alone before April 30, 2013. We estimated relative hazard ratios (HRs) for death and relative odds ratios (ORs) for toxic effects among different therapies by combining HRs for death and survival durations and ORs for toxic effects of included trials. We assessed the effects of prognostic factors on survival benefits of adjuvant therapies with meta-regression. Findings Ten eligible articles reporting nine trials were included. Compared with observation, the HRs for death were 0·62 (95% credible interval 0·42–0·88) for fluorouracil, 0·68 (0·44–1·07) for gemcitabine, 0·91 (0·55–1·46) for chemoradiation, 0·54 (0·15–1·80) for chemoradiation plus fluorouracil, and 0·44 (0·10–1·81) for chemoradiation plus gemcitabine. The proportion of patients with positive lymph nodes was inversely associated with the survival benefit of adjuvant treatments. After adjustment for this factor, fluorouracil (HR 0·65, 0·49–0·84) and gemcitabine (0·59, 0·41–0·83) improved survival compared with observation, whereas chemoradiation resulted in worse survival than fluorouracil (1·69, 1·12–2·54) or gemcitabine (1·86, 1·04–3·23). Chemoradiation plus gemcitabine was ranked the most toxic, with significantly higher haematological toxic effects than second-ranked chemoradiation plus fluorouracil (OR 13·33, 1·01–169·36). Interpretation Chemotherapy with fluorouracil or gemcitabine is the optimum adjuvant treatment for pancreatic adenocarcinoma and reduces mortality after surgery by about a third. Chemoradiation plus chemotherapy is less effective in prolonging survival and is more toxic than chemotherapy. Funding None.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Plant-based diets, characterized by a higher consumption of plant foods and a lower consumption of animal foods, are associated with a favorable cardiovascular disease (CVD) risk, but evidence ...regarding the association between plant-based diets and CVD (including coronary heart disease (CHD) and stroke) incidence remain inconclusive. A literature search was conducted using the PubMed, EMBASE and Web of Science databases through December 2020 to identify prospective observational studies that examined the associations between plant-based diets and CVD incidence among adults. A systematic review and a meta-analysis using random effects models and dose–response analyses were performed. Ten studies describing nine unique cohorts were identified with a total of 698,707 participants (including 137,968 CVD, 41,162 CHD and 13,370 stroke events). Compared with the lowest adherence, the highest adherence to plant-based diets was associated with a lower risk of CVD (RR 0.84; 95% CI 0.79–0.89) and CHD (RR 0.88; 95% CI 0.81–0.94), but not of stroke (RR 0.87; 95% CI 0.73–1.03). Higher overall plant-based diet index (PDI) and healthful PDI scores were associated with a reduced CVD risk. These results support the claim that diets lower in animal foods and unhealthy plant foods, and higher in healthy plant foods are beneficial for CVD prevention. Protocol was published in PROSPERO (No. CRD42021223188).
A binary mixture is mixed in a rotating drum composed by 19 rings with different inner diameters. It is found that the larger particles are concentrated in the rings with smaller inner diameters. The ...collection of the larger particles in these rings is due to the particle dynamic angle of repose. The transition from the particle segregation core pattern at the end wall to the good radial mixing rings is through a transient turning comet segregation pattern. This transition is closely related to the distance from the ring with the smallest inner diameter to the ring with the largest inner diameter. Having a higher fraction of larger particles in a ring requires both the collection ring having a smaller inner diameter and a smoother inner diameter transition to the neighboring rings.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
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•Laminarizer consisting 15 tubes is assembled at the cyclone entrance.•Laminarizer allows more particles flowing in the outer part of entrance.•Laminarizer reduces 50% cut size and ...gives higher separation efficiency.•Laminarizer slightly increases the pressure drop.•Laminarizer slightly decreases the tangential gas velocity.
A laminarizer consisting of a bank of 15 tubes was assembled at the entrance of a cyclone. Experiments and numerical simulations were performed to examine the influence of the laminarizer on the pressure drop across the cyclone, partial separation efficiency, gas tangential velocity distribution, particle distribution at the entrance, and 50% cut size. Using the laminarizer slightly increased the pressure drop across the cyclone and slightly reduced the gas tangential velocity. The laminarizer altered the air mass flow rate and particle flow distribution at the entrance. It increased the air mass flow rate through the outer part of the entrance. At an inlet gas velocity of 11m/s, installing the laminarizer reduced the number of particles flowing through the inner part of the entrance by 20.2%. Higher particle concentrations were found at the outer part of the entrance, where the particles were more easily captured after entering the main body. At an inlet gas velocity of 11m/s, using the laminarizer increased the pressure drop across the cyclone by 8.1% and reduced the 50% cut size of the cyclone from 2.04μm to 1.89μm.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
In the wake of recent advances in scientific research, personalized medicine using deep learning techniques represents a new paradigm. In this work, our goal was to establish deep learning models ...which distinguish responders from non-responders, and also to predict possible antidepressant treatment outcomes in major depressive disorder (MDD). To uncover relationships between the responsiveness of antidepressant treatment and biomarkers, we developed a deep learning prediction approach resulting from the analysis of genetic and clinical factors such as single nucleotide polymorphisms (SNPs), age, sex, baseline Hamilton Rating Scale for Depression score, depressive episodes, marital status, and suicide attempt status of MDD patients. The cohort consisted of 455 patients who were treated with selective serotonin reuptake inhibitors (treatment-response rate = 61.0%; remission rate = 33.0%). By using the SNP dataset that was original to a genome-wide association study, we selected 10 SNPs (including
rs4917029,
rs9419139,
rs704329,
rs6978272,
rs7954376,
rs4352778,
rs2139423,
rs2956406,
rs4810894, and
rs139863958) which were associated with antidepressant treatment response. Furthermore, we pinpointed 10 SNPs (including
rs11022778,
rs2724812,
rs12904459,
rs35864549,
rs9878985,
rs483986,
rs12046378,
rs73103153,
rs17134927, and
rs77554113) in relation to remission. Then, we employed multilayer feedforward neural networks (MFNNs) containing 1-3 hidden layers and compared MFNN models with logistic regression models. Our analysis results revealed that the MFNN model with 2 hidden layers (area under the receiver operating characteristic curve (AUC) = 0.8228 ± 0.0571; sensitivity = 0.7546 ± 0.0619; specificity = 0.6922 ± 0.0765) performed maximally among predictive models to infer the complex relationship between antidepressant treatment response and biomarkers. In addition, the MFNN model with 3 hidden layers (AUC = 0.8060 ± 0.0722; sensitivity = 0.7732 ± 0.0583; specificity = 0.6623 ± 0.0853) achieved best among predictive models to predict remission. Our study indicates that the deep MFNN framework may provide a suitable method to establish a tool for distinguishing treatment responders from non-responders prior to antidepressant therapy.
Growing evidence suggests the link between gut microbiota and mood regulation. The current study aimed to identify microbiota targets for major depressive disorder (MDD) and mood-related traits in ...Taiwanese samples, while taking into account the influence of dietary patterns. We recruited 36 MDD patients and 37 healthy controls for 16S rRNA gene sequencing. We assessed nutrient content using food frequency questionnaire, and mood related phenotypes, including depressive severity, anxiety, and perceived stress. Analysis of composition of microbiomes (ANCOM) models were performed to evaluate microbiota compositions between patients and controls, while adjusted for fat intake% and sequencing platforms. We found 23 taxa (4 phyla, 7 families and 12 genera) to be associated with depression and beta diversity was differed between groups. Phylum Actinobacteria and Firmicutes were overrepresented in MDD patients. At genus level, Bifidobacterium (7%) and Blautia (8%) had relatively high abundance among MDD patients, while Prevotella (16%) had high abundance in controls. Holdemania exhibited moderate correlation with anxiety (r = 0.65) and perceived stress level (r = 0.49) mainly in MDD patients but not controls. Pathway analyses revealed that pentose phosphate and starch and sucrose metabolism processes were important pathways for depression via microbiota functions. In conclusion, our results revealed microbiota targets for depression that are independent of fat intake. It is worthwhile to conduct further studies to replicate the current findings and to integrate with biochemistry and metabolomics data to better understand the functions of identified targets.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Pyruvate kinase muscle isozymes (PKMs) have crucial roles in regulating metabolic changes during carcinogenesis. A switch from PKM1 to PKM2 isoform was thought to lead to aerobic glycolysis promoting ...carcinogenesis, and was considered as one of the cancer signatures. However, recent evidence has argued against the existence of PKM isoform switch and related metabolic effects during cancer progression. We compared the effects of PKM1 and PKM2 in cell invasiveness and metastasis of pancreatic ductal adenocarcinoma (PDAC). Both PKM1 and PKM2 expression affected cell migration and invasion abilities of PDAC cells, but only knockdown of PKM2 suppressed metastasis in a xenograft model. By comparing the established PKM2 mutants in the regulation of cell invasion, we found that PKM2 may control cell mobility through its protein kinase and phopho-peptide binding abilities. Further survey for PKM2-associated proteins identified PAK2 as a possible phosphorylation target in PDAC. In vitro binding and kinase assays revealed that PKM2 directly phosphorylated PAK2 at Ser20, Ser141, and Ser192/197. Knockdown of PKM2 decreased PAK2 protein half-life by increasing ubiquitin-dependent proteasomal degradation. Moreover, we identified PAK2 as an HSP90 client protein and the mutation at Ser192/197 of PAK2 reduced PAK2-HSP90 association. Knockdown of PAK2 diminished in vitro cell mobility and in vivo metastatic ability of PKM2 overexpressed PDAC cells. PKM2 and PAK2 protein expression also positively correlated with each other in PDAC tissues. Our findings indicate that PKM2-PAK2 regulation is critical for developing metastasis in PDAC, and suggest that targeting the PKM2/HSP90/PAK2 complex has a potential therapeutic value in this deadly disease.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Background and Aim
Approximately 42–95% of working channels have been reported to show the presence of residual fluid despite endoscope reprocessing. The aim of this study was to design two novel ...protocols for cleaning residual simethicone and demonstrate its efficiency by evaluating the residual fluid and cleanliness in the working channels of patient‐ready duodenoscopes.
Methods
The designed protocol for cleaning residual simethicone was implemented in manual cleaning and/or high‐level disinfection (HLD). The residual fluid inside the working channels was estimated by visual inspection. Adenosine triphosphate (ATP) values were evaluated to determine cleanliness after manual cleaning.
Results
Manual cleaning with novel simethicone cleaning protocol demonstrated a significant decrease in fluid droplets (14.6 ± 29.9 vs 0 ± 0, P < 0.001) and ATP values (157 ± 196 relative light units RLUs vs 52 ± 41 RLUs, P = 0.031). HLD with simethicone cleaning protocol, using either enzymatic detergent with effective for cleaning simethicone or cleaning time set in the automatic endoscope reprocessor program for 8 min, demonstrated significant decrease in the number of fluid droplets. Follow‐up after the implementation of the simethicone cleaning protocol showed a significant decrease in fluid droplets (37.4 ± 41.0 vs 2.1 ± 5.5, P = 0.003) and ATP values (271 ± 268 RLUs vs 82 ± 136 RLUs, P = 0.021).
Conclusions
Simethicone cleaning protocol is advantageous for significantly decreasing fluid droplets and ATP values within endoscope working channels. After manual cleaning with the simethicone cleaning protocol, in particular, no retained fluid droplet was observed in patient‐ready duodenoscopes.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
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