Assessment of monthly runoff simulations based on a physics-informed machine learning framework: The effect of intermediate variables in its construction.

Hydrological forecasting is of great importance for water resources management and planning, especially given the increasing occurrence of extreme events such as floods and droughts. The physics-informed machine learning (PIML) models effectively integrate conceptual hydrologic models with machine learning (ML) models. In this process, the intermediate variables of PIML models serve as bridges between inputs and outputs, while the impact of intermediate variables on the performance of PIML models remains unclear. To fill this knowledge gap, this study aims to encompass the construction of PIML models based on various hydrologic models, conduct comparative analyses of different intermediate variables based on a case study of 205 CAMELS basins, and further explore the relationship between the performance of PIML models and catchment characteristics. The optimal ML model for constructing PIML is first selected among four ML models within the 205 basins. The PIML models are then developed based on five monthly water balance models, namely TM, XM, MEP, SLM, and TVGM. To quantify the potential impact of difference in intermediate variables, two sets of experiments are further designed and performed, namely S1 with actual evapotranspiration as the intermediate variable and S2 with soil moisture as the intermediate variable. Results show that five PIML models generally outperformed the optimal standalone ML models, i.e., the Lasso model. Specifically, regardless of the choice of intermediate variables, the PIML-XM model consistently outperformed the other models within the same basins. Almost all constructed PIML models are affected by the intermediate variables in monthly runoff simulations. Typically, S1 exhibited better performance compared to S2. A greater impact of aridity index, forest fraction, and catchment area on model performance is observed in S2. These findings improve our understanding of constructing PIML models in hydrology by emphasizing their excellent performance in runoff simulations and highlighting the importance of intermediate variables.

A nested case-control study of serum polychlorinated biphenyls and papillary thyroid cancer risk among U.S. military service members.

BACKGROUND AND OBJECTIVES: Although polychlorinated biphenyls (PCBs) were banned decades ago, populations are continuously exposed to PCBs due to their persistence and bioaccumulation/biomagnification in the environment. Results from limited epidemiologic studies linking PCBs to thyroid cancer have been inconclusive. This study aimed to investigate the association between individual PCBs and PCB mixture and papillary thyroid cancer (PTC), the most common thyroid cancer histologic subtype. METHODS: We carried out a nested case-control study including 742 histologically confirmed PTC cases diagnosed in 2000-2013 and 742 individually matched controls among U.S. military service members. Pre-diagnostic serum samples that were collected on average nine years before PTC diagnosis were used to measure PCB congeners by gas chromatography isotope dilution high resolution mass spectrometry (GC/ID-HRMS). Conditional logistic regression, Bayesian kernel machine regression (BKMR), and weighted quantile sum (WQS) regression were employed to estimate the association between single PCB congeners as well as their mixture and PTC. RESULTS: Four PCB congeners (PCB-74, PCB-99, PCB-105, PCB-118) had significant associations and dose-response relationships with increased risk of PTC in single congener models. When considering the effects from all measured PCBs and their potential interactions in the BKMR model, PCB-118 showed positive trends of association with PTC. Increased exposure to the PCB congeners as a mixturewas also associated with an increased risk of PTC in the WQS model, with the mixture dominated by PCB-118, followed by PCB-74 and PCB-99. One PCB congener, PCB-187, showed an inverse trend of association with PTC in the mixture analysis. DISCUSSION: This study suggests that exposure to certain PCBs as well as a mixture of PCBs were associated with an increased risk of PTC. The observed association was mainly driven by PCB-118, and to a lesser extent by PCB-74 and PCB-99. The findings warrant further investigation.

Cooking stoves and risk of birth defects in urban China.

INTRODUCTION: Birth defects are a leading cause of infant death. Pregnant women spend a large amount of time indoors, and little research from population-based studies has investigated the association between indoor air pollution and birth defects. We aimed to examine whether using coal, biomass, or electromagnetic stoves for cooking is associated with risk of birth defects compared to using gas stoves. METHODS: A birth cohort study was conducted from 2010 to 2012 in Lanzhou, China. Cases (n = 264) were singleton births with birth defects, which were defined as abnormalities of structure or function, including metabolism, presented at birth based on the International Classification of Diseases (ICD)-10 codes. Controls (n = 9926) were defined as singleton live births without birth defects. Unconditional logistic regression models were employed to estimate the association adjusting for confounding variables. RESULTS: Compared to gas stoves for cooking, biomass (OR = 2.66, 95%CI: 1.38-5.13), and electromagnetic stove (OR = 1.90, 95%CI: 1.26-2.88) for cooking were associated with an increased risk of birth defects. The significant associations remained among non-congenital heart disease (CHD) defects but not CHDs. CONCLUSIONS: Using biomass or electromagnetic stoves for cooking during pregnancy was associated with an increased risk of birth defects. Additional studies are warranted to confirm these novel findings. Studies with larger sample size or greater statistical power are also warranted to better estimate the associations for individual birth defects.

(-)-Epigallocatechin-3-gallate derivatives combined with cisplatin exhibit synergistic inhibitory effects on non-small-cell lung cancer cells.

BACKGROUND: Non-small-cell lung cancer (NSCLC) is the leading cause of cancer-related death worldwide. The inhibition of epidermal growth factor receptor (EGFR) signaling by tyrosine kinase inhibitors or monoclonal antibodies plays a key role in NSCLC treatment. Unfortunately, these treatment strategies are limited by eventual resistance and cell lines with differential EGFR status. Therefore, new therapeutic strategies for NSCLC are urgently required. METHODS: To improve the stability and absorption of (-)-epigallocatechin-3-gallate (EGCG), we synthesized a series of EGCG derivatives. The antitumor activities of EGCG derivatives with or without cisplatin were investigated in vitro and vivo. Cell proliferation, cell cycle distribution and apoptosis were measured in NSCLC cell lines and in vivo in a NCI-H441 xenograft model. RESULTS: We found that the EGCG derivatives inhibited cell viability and colony formation, caused cell cycle redistribution, and induced apoptosis. More importantly, the combination of the EGCG derivative and cisplatin led to increased growth inhibition, caused cell cycle redistribution, and enhanced the apoptosis rate compared to either compound alone. Consistent with the experiments in vitro, EGCG derivatives plus cisplatin significantly reduced tumor growth. CONCLUSIONS: The combination treatment was found to inhibit the EGFR signaling pathway and decrease the expression of p-EGFR, p-AKT, and p-ERK in vitro and vivo. Our results suggest that compound 3 is a novel potential compound for NSCLC patients.

Differential responses of rumen and fecal fermentation and microbiota of Liaoning cashmere goats after 2-hydroxy-4-(methylthio) butanoic acid isopropyl ester supplementation.

The 2-hydroxy-4-(methylthio) butanoic acid isopropyl ester (HMBi), a rumen protective methionine, has been extensively studied in dairy cows and beef cattle and has been shown to regulate gastrointestinal microbiota and improve production performance. However, knowledge of the application of HMBi on cashmere goats and the simultaneous study of rumen and hindgut microbiota is still limited. In this study, HMBi supplementation increased the concentration of total serum protein, the production of microbial protein in the rumen and feces, as well as butyrate production in the feces. The results of PCoA and PERMANOVA showed no significant difference between the rumen microbiota, but there was a dramatic difference between the fecal microbiota of the two groups of Cashmere goats after the HMBi supplementation. Specifically, in the rumen, HMBi significantly increased the relative abundance of some fiber-degrading bacteria (such as Fibrobacter) compared with the CON group. In the feces, as well as a similar effect as in the rumen (increasing the relative abundance of some fiber-degrading bacteria, such as Lachnospiraceae FCS020 group and ASV32), HMBi diets also increased the proliferation of butyrate-producing bacteria (including Oscillospiraceae UCG-005 and Christensenellaceae R-7 group). Overall, these results demonstrated that HMBi could regulate the rumen and fecal microbial composition of Liaoning cashmere goats and benefit the host.

The antidepressant effect of Shexiang Baoxin Pills on myocardial infarction rats with depression may be achieved through the inhibition of the NLRP3 inflammasome pathway.

BACKGROUND: Patients with myocardial infarction (MI) frequently experience a heightened incidence of depression, thereby increasing the risk of adverse cardiovascular events. Consequently, early detection and intervention in depressive symptoms among patients with MI are imperative. Shexiang Baoxin Pills (SBP), a Chinese patent medicine employed for the treatment of MI, exhibits diverse mechanisms targeting this condition. Nevertheless, its therapeutic efficacy on postmyocardial infarction depressive symptoms remains unclear. The aim of this study is to investigate the effectiveness and mechanism of SBP in managing depression during acute myocardial infarction (AMI). METHODS: A rat model combining MI and depression was established, and the rats were randomly divided into four groups: the model (MOD) group, SBP group, Fluoxetine (FLX) group, and Sham group. After 28 days of drug intervention, cardiac function was assessed using echocardiography while behavior was evaluated through sucrose preference test (SPT), forced swimming test (FST), and open-field test (OFT). Additionally, levels of inflammatory factors in serum and hippocampus were measured along with NLRP3 inflammasome-related protein expression via Western blotting and immunofluorescence. RESULTS: SBP can enhance cardiac function in rats with AMI and depression, while significantly ameliorating depressive-like behavior. Compared to the Sham group, levels of IL-1ß, IL-18, TNF-α, and other inflammatory factors were markedly elevated in the MOD group. However, expressions of these inflammatory factors were reduced to varying degrees following treatment with SBP or FLX. Analysis of NLRP3 inflammasome-related proteins in the hippocampus revealed a significant upregulation of IL-1ß, IL-18, NLRP3, ASC, caspase-1, and GSDMD in the MOD group; conversely, these measures were significantly attenuated after SBP intervention. CONCLUSION: We have observed a significant amelioration in depression-like behavior upon SBP administration during the treatment of AMI, suggesting that this effect may be attributed to the inhibition of NLRP3-mediated pyroptosis. (The main findings are summarized in the graphical abstract in the supplementary file.).

Network analysis of smoking-related sleep characteristics in Chinese adults.

The associations between multiple sleep characteristics and smoking behavior are inconsistent, and it is unclear which sleep characteristics are most crucial for tobacco prevention. This study aimed to explore the associations between smoking status/intensity and multiple sleep characteristics and to identify the potential core domain of smoking-related sleep using network analysis. Data were obtained from a survey of cancer-related risk factors among Chinese adults. Logistic regression models were used to quantify the associations between sleep characteristics and smoking status/intensity. Network analyses were employed to identify the core sleep characteristics. A total of 5,228 participants with a median age of 44 years old were included in the study. Current smoking was significantly positively associated with long nap time, difficulty falling asleep, late bedtime, getting up after 7 am, and waking up earlier than expected. There was significant positive association between current smoking and short sleep duration in young adults under 45 years old. Late bedtime and getting up after 7 am were only associated with current heavy smoking, but not current light smoking. Network analyses showed that multiple smoking-related sleep characteristics were interconnected, with difficulty falling asleep and late bedtime as central characteristics in the network. The study found that the associations between sleep characteristics and smoking varied by age and smoking intensity and highlights the potential benefits of sleep health promotion in smoking cessation, with a particular focus on difficulty falling asleep and late bedtime.

Combined healthy lifestyles and risk of depressive symptoms: A baseline survey in China.

BACKGROUND: Little evidence exists about whether a combination of healthy lifestyle factors is associated with a lower risk of depressive symptoms among Chinese population. We aimed to investigate the association between combined healthy lifestyle factors and risk of depressive symptoms. METHODS: We conducted a baseline survey from July 2021 to December 2023, including 53,642 Chinese adults from general population. A healthy lifestyle score was constructed based on six lifestyle factors (physical activity, smoking status, alcohol consumption, diet, sleep duration, and body mass index). Logistic regression models were used to estimate odds ratios (ORs) and 95 % confidence intervals (CIs) adjusted for confounding variables. RESULTS: Each additional healthy lifestyle score was associated with a 20 % lower risk of having depressive symptoms (OR (95 % CI): 0.80 (0.78-0.81)). Compared with individuals with ≤2 healthy lifestyle factors, individuals with all the six healthy lifestyle factors had a 58 % reduced risk of having depressive symptoms (0.42 (0.37-0.47)). After stratification by gender, education and urbanization, the significant inverse association with healthy lifestyle score was stronger in women, individuals with high education, and urban residents. Besides, the significant negative association between healthy lifestyle score and depressive symptoms remained for different severity of depressive symptoms. LIMITATIONS: Given the cross-sectional nature of data, we cannot make causal inferences. CONCLUSIONS: Our study indicated that adherence to healthy lifestyle factors was associated with a reduced risk of having depressive symptoms among Chinese adults. The observed associations were modified by gender, education and urbanization. These findings warrant further verification in interventional studies.

Crowdsourcing participatory evaluation of medical pictograms using Amazon Mechanical Turk.

BACKGROUND: Consumer and patient participation proved to be an effective approach for medical pictogram design, but it can be costly and time-consuming. We proposed and evaluated an inexpensive approach that crowdsourced the pictogram evaluation task to Amazon Mechanical Turk (MTurk) workers, who are usually referred to as the "turkers". OBJECTIVE: To answer two research questions: (1) Is the turkers' collective effort effective for identifying design problems in medical pictograms? and (2) Do the turkers' demographic characteristics affect their performance in medical pictogram comprehension? METHODS: We designed a Web-based survey (open-ended tests) to ask 100 US turkers to type in their guesses of the meaning of 20 US pharmacopeial pictograms. Two judges independently coded the turkers' guesses into four categories: correct, partially correct, wrong, and completely wrong. The comprehensibility of a pictogram was measured by the percentage of correct guesses, with each partially correct guess counted as 0.5 correct. We then conducted a content analysis on the turkers' interpretations to identify misunderstandings and assess whether the misunderstandings were common. We also conducted a statistical analysis to examine the relationship between turkers' demographic characteristics and their pictogram comprehension performance. RESULTS: The survey was completed within 3 days of our posting the task to the MTurk, and the collected data are publicly available in the multimedia appendix for download. The comprehensibility for the 20 tested pictograms ranged from 45% to 98%, with an average of 72.5%. The comprehensibility scores of 10 pictograms were strongly correlated to the scores of the same pictograms reported in another study that used oral response-based open-ended testing with local people. The turkers' misinterpretations shared common errors that exposed design problems in the pictograms. Participant performance was positively correlated with their educational level. CONCLUSIONS: The results confirmed that crowdsourcing can be used as an effective and inexpensive approach for participatory evaluation of medical pictograms. Through Web-based open-ended testing, the crowd can effectively identify problems in pictogram designs. The results also confirmed that education has a significant effect on the comprehension of medical pictograms. Since low-literate people are underrepresented in the turker population, further investigation is needed to examine to what extent turkers' misunderstandings overlap with those elicited from low-literate people.

Physical activity and risk of lung cancer: A systematic review and dose-response meta-analysis of cohort studies.

Objective: To synthesize the knowledge about the association of total physical activity (TPA), leisure-time physical activity (LTPA), occupational physical activity (OPA) and lung cancer risk and explore the dose-response relationship between LTPA level and lung cancer. Methods: PubMed and Web of Science were searched up to 17 November 2021. The summary relative risks (RRs) and 95% confidence intervals (CIs) were calculated by random-effects or fixed-effects model. The dose-response analysis was conducted with restricted cubic splines. Results: We identified 25 articles (42 cohort studies) that assessed the physical activity-lung cancer association, including 9,983,295 study participants and 85,988 incident cases of lung cancer. When comparing the highest to the lowest level of TPA and LTPA, lung cancer risk reduced 22% (RR, 0.78; 95% CI: 0.70, 0.86) and 12% (RR, 0.88; 95% CI: 0.83, 0.93), respectively. We found an approximately U-shaped association between LTPA and lung cancer (P non-linearity < 0.001), with the lowest risk at 15 metabolic equivalent of task hours per week (h/wk) of LTPA. Compared to participants with sitting occupations, lung cancer risk significantly increased among those being unemployed (RR, 1.33; 95% CI: 1.17, 1.51) or with standing occupations (RR, 1.37; 95% CI: 1.15, 1.63), but not among those with light or high OPA. Conclusions: Our meta-analysis supported a protective effect of TPA and LTPA, but not OPA, on lung cancer risk. The novel finding of a U-shaped association between LTPA and lung cancer risk warrants further investigation.

Physical activity domains and patterns with risk of depressive symptoms: A cross-sectional study in China.

BACKGROUND: The health benefits of domain-specific physical activity (PA) on depressive symptoms were inconclusive. Few studies explored PA patterns and depressive symptoms. This study aimed to investigate the associations of PA domains and patterns with depressive symptoms. METHODS: We conducted a cross-sectional study in China with 5047 adults. Latent class analysis was applied to identify the PA patterns and logistic regression analysis was used to calculate odds ratios (ORs) and 95 % confidence intervals (CIs). RESULTS: The ORs (95 % CIs) for the active versus inactive groups were 0.79 (0.69-0.91) for leisure-time PA, 0.57 (0.49-0.65) for transport PA, 0.95 (0.82-1.09) for household PA, and 1.38 (1.18-1.62) for occupational PA. We found non-linear associations between leisure-time PA, transport PA and depressive symptoms, with the lowest risk at 11 METs-h/week of leisure-time PA (equal to 147 min/week moderate PA or 88 min/week vigorous PA) and 23 METs-h/week of transport PA. There was a marginal inverse association with household PA for men while not for women. We identified four PA patterns and found a lower risk of depressive symptoms associated with "low occupational PA pattern" versus "moderate PA level pattern" (0.45 (0.38-0.52)). LIMITATIONS: Given the cross-sectional design, causality cannot be inferred. CONCLUSIONS: Our study supported an inverse association of leisure-time PA and transport PA with depressive symptoms and a positive association of occupational PA. The observed inconsistent association of household PA among men and women, and the finding that "low occupational PA pattern" was associated with a lower risk of depressive symptoms warrant further investigation.

Elasticity and damping ratio measurement of droplets on super-hydrophobic surfaces.

The measurement of the droplets' elasticity is vitally important in microfluidic and ink-jet printing. It refers to the ability of the droplet to restore its original shape and strong robustness. This study investigated a novel method to measure elasticity. The plate coated with super-hydrophobic layers pressed on a droplet and the elastic force was recorded by an electronic balance. Meanwhile, a mathematical model was constructed to calculate the changes of the droplet area under the force. The measurement showed that external work mainly converts into surface energy and the damping ratio increases from 0.068 to 0.261 with the increase of mass fraction from 0 to 80 wt%. It also indicates that the novel method can accurately and efficiently measure the elasticity of droplets.

Higher Neutrophil to Lymphocyte Ratio at Admission is Association with Post-PCI Depressive Symptoms in Patients with ACS.

Background: Depression and elevated blood biomarkers of inflammation are common in patients with acute coronary syndrome (ACS) after percutaneous coronary intervention (PCI). Neutrophil to lymphocyte ratio (NLR) is an indicator of peripheral inflammation and has been proved to be associated with both ACS and depression. Purpose: Our aim was to evaluate the possible association between NLR at admission and post-PCI depressive symptoms at 1 month. Patients and Methods: A total of 224 patients with ACS who underwent PCI for the first time were recruited and completed 1-month follow-up. The 24-item Hamilton Depression Scale (HAMD-24) was used to measure depressive symptoms at 1 month after PCI. Logistic regression was used to analyze the relationship between different NLR levels and post-PCI depressive symptoms. A receiver operating characteristic (ROC) curve analysis was performed to assess the value of NLR for predicting post-PCI depressive symptoms and to determine its critical value. Results: Of the 224 enrolled patients, 52 (23.2%) patients were diagnosed with depressive symptoms at 1 month after PCI. Patients with depressive symptoms showed significantly higher level of NLR at admission than patients without depressive symptoms (4.33 (3.26, 7.01) vs 2.57 (1.72, 3.91), P < 0.001). The proportion of depressive symptoms in post-PCI patients increases progressively along with NLR quartile. In the results of multivariate-adjusted logistic regression analysis, the odds ratio (OR) of post-PCI depressive symptoms was 12.028 (95% CI, 2.642-54.752) for the lowest quartile of NLR compared with the highest quartile. According to the receiver operating characteristic curve (ROC), the area under the curve (AUC) for predicting post-PCI depressive symptoms was 0.716 (95% CI, 0.641-0.791; P < 0.001), and the optimal cutoff of NLR levels was 3.235 (sensitivity: 76.9%, specificity: 66.9%). Conclusion: Higher NLR levels at admission were associated with post-PCI depressive symptoms at 1 month, suggesting that NLR might be useful inflammatory markers to predict post-PCI depressive symptoms at 1 month.

Comparative physiological, transcriptomic, and WGCNA analyses reveal the key genes and regulatory pathways associated with drought tolerance in Tartary buckwheat.

Drought stress is one of the major abiotic stress factors that affect plant growth and crop productivity. Tartary buckwheat is a nutritionally balanced and flavonoid-rich pseudocereal crop and also has strong adaptability to different adverse environments including drought. However, little is known about its drought tolerance mechanism. In this study, we performed comparative physiological and transcriptomic analyses of two contrasting drought-resistant Tartary buckwheat genotypes under nature drought treatment in the reproductive stage. Under drought stress, the drought-tolerant genotype XZSN had significantly higher contents of relative water, proline, and soluble sugar, as well as lower relative electrolyte leakage in the leaves than the drought-susceptible LK3. A total of 5,058 (2,165 upregulated and 2,893 downregulated) and 5,182 (2,358 upregulated and 2,824 downregulated) potential drought-responsive genes were identified in XZSN and LK3 by transcriptome sequencing analysis, respectively. Among the potential drought-responsive genes of XZSN, 1,206 and 1,274 genes were identified to be potential positive and negative contributors for XZSN having higher drought resistance ability than LK3. Furthermore, 851 out of 1,206 positive drought-resistant genes were further identified to be the core drought-resistant genes of XZSN based on WGCNA analysis, and most of them were induced earlier and quicker by drought stress than those in LK3. Functional annotation of the 851 core drought-resistant genes found that a large number of stress-responsive genes were involved in TFs, abscisic acid (ABA) biosynthesis, signal transduction and response, non-ABA signal molecule biosynthesis, water holding, oxygen species scavenging, osmotic adjustment, cell damage prevention, and so on. Transcriptional regulatory network analyses identified the potential regulators of these drought-resistant functional genes and found that the HD-ZIP and MYB TFs might be the key downstream TFs of drought resistance in Tartary buckwheat. Taken together, these results indicated that the XZSN genotype was more drought-tolerant than the LK3 genotype as evidenced by triggering the rapid and dramatic transcriptional reprogramming of drought-resistant genes to reduce water loss, prevent cell damage, and so on. This research expands our current understanding of the drought tolerance mechanisms of Tartary buckwheat and provides important information for its further drought resistance research and variety breeding.

Machine learning-based prognostic and metastasis models of kidney cancer.

Background: Kidney cancer originates from the urinary tubule epithelial system of the renal parenchyma, accounting for 20% of all urinary system tumors. Approximately 70% of cases are localized at diagnosis, and 30% are metastatic. Most localized kidney cancers can be cured by surgery, but most metastatic patients relapse after surgery and eventually die of kidney cancer. Therefore, accurately predicting patient survival and identifying high-risk metastatic patients will effectively guide interventions and improve prognosis. Methods: This study used the data of 12,394 kidney cancer patients from the surveillance, epidemiology, and end results database to construct a research cohort related to kidney cancer survival and metastasis. Eight machine learning models (including support vector machines, logistic regression, decision tree, random forest, XGBoost, AdaBoost, K-nearest neighbors, and multilayer perceptron) were developed to predict the survival and metastasis of kidney cancer and six evaluation indicators (accuracy, precision, sensitivity, specificity, F1 score, and area under the receiver operating characteristic [AUROC]) were used to verify, evaluate, and optimize the models. Results: Among the eight machine learning models, Logistic Regression has the highest AUROC in both prediction scenarios. For 3-year survival prediction, the Logistic Regression model had an accuracy of 0.684, a sensitivity of 0.702, a specificity of 0.670, a precision of 0.686, an F1 score of 0.683, and an AUROC of 0.741. For tumor metastasis prediction, the Logistic Regression model had an accuracy of 0.800, a sensitivity of 0.540, a specificity of 0.830, a precision of 0.769, an F1 score of 0.772, and an AUROC of 0.804. Conclusion: In this study, we selected appropriate variables from both statistical and clinical significance and developed and compared eight machine learning models for predicting 3-year survival and metastasis of kidney cancer. The prediction results and evaluation results demonstrated that our model could provide decision support for early intervention for kidney cancer patients.

International patterns and trends of childhood and adolescent cancer, 1978-2012.

Background: This study aimed to provide a detailed analysis of the temporal trends of cancer incidence rates for individuals aged 0-19 years in selected regions globally from 1978 to 2012. Methods: Data were obtained from Volumes V-XI of Cancer Incidence in Five Continents (CI5), published by the International Agency for Research on Cancer. A total of 53 registries in 23 regions from the Americas, Asia, Europe, and Oceania that contained information on cancer incidence throughout 1978-2012 (35 years) were included in this study. Joinpoint regression was used for the analysis of trends. Results: Most regions showed increasing trends in overall childhood cancer among children (aged 0-14 years) and adolescents (aged 15-19 years). Nearly all regions showed rising trends in childhood and adolescent leukemia incidence rates, whereas the incidence of lymphoma among children generally decreased. Only France, Australia, and New Zealand showed decreasing trends for malignant central nervous system (CNS) tumors among adolescents. Kidney cancer and bone cancer incidence rates remained stable for most regions. The incidence of thyroid cancer among adolescents increased in most regions and that of testicular cancer decreased in approximately one-half of the regions studied. Conclusion: The international temporal trends of cancer incidents among children and adolescents are varied by region, cancer type, age group, and gender, and have changed over time.

Etiology of lung cancer: Evidence from epidemiologic studies.

Lung cancer is one of the leading causes of cancer incidence and mortality worldwide. While smoking, radon, air pollution, as well as occupational exposure to asbestos, diesel fumes, arsenic, beryllium, cadmium, chromium, nickel, and silica are well-established risk factors, many lung cancer cases cannot be explained by these known risk factors. Over the last two decades the incidence of adenocarcinoma has risen, and it now surpasses squamous cell carcinoma as the most common histologic subtype. This increase warrants new efforts to identify additional risk factors for specific lung cancer subtypes as well as a comprehensive review of current evidence from epidemiologic studies to inform future studies. Given the myriad exposures individuals experience in real-world settings, it is essential to investigate mixture effects from complex exposures and gene-environment interactions in relation to lung cancer and its subtypes.

Wighteone exhibits an antitumor effect against EGFR L858R/T790M mutation non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) harboring activating EGFR mutations were initially treated by first-generation EGFR tyrosine kinase inhibitors (EGFR-TKIs), unfortunately, the efficacy of these drugs is limited, mostly frequent due to T790M mutation. Although osimertinib has been approved to treat patients with T790M-positive NSCLC, the majority of patients will develop C797S mutation and suffer diseases again. Therefore, more novel therapeutic strategies for T790M mutation-positive NSCLC are urgently required. We hypothesized that wighteone, a natural compound isolated from plant derivatives, has antitumor effects against NSCLC with T790M mutation. In this study, we created a Ba/F3 cell line harboring EGFR L858R/T790M mutation (Ba/F3 EGFR L858R/T790M cell line), and then used this cell line and a human NSCLC cell line with EGFR L858R/T790M mutation (NCI-H1975) to investigate the effects and mechanism of wighteone. The results showed that wighteone inhibited cell proliferation, suppressed EGFR signaling pathway, caused cell cycle redistribution and induced cell apoptosis. Our studies suggest that wighteone may provide a novel potential therapeutic strategy for NSCLC patients with T790M mutation.

The oxidation of (-)-epigallocatechin-3-gallate inhibits T-cell acute lymphoblastic leukemia cell line HPB-ALL via the regulation of Notch1 expression.

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy, and commonly associated with activating mutations in the Notch1 pathway. (-)-Epigallocatechin-3-gallate (EGCG) is the most abundant and active catechin and has been shown to regulate Notch signaling. Taking into account the highly oxidizable and unstable of EGCG, we proposed that EGCG oxides may have greater potential to regulate Notch signaling than EGCG. In this study, we isolated and identified EGCG oxides (compound 2-4), using a chemical oxidation strategy, and evaluated for cytotoxicity against T-cell acute lymphoblastic leukemia cell line (HPB-ALL) by using the MTS assay. We found compound 3 significantly induced cell proliferation inhibition (38.3858 ± 1.67106 µM), cell apoptosis and cell cycle arrest in a dose-dependent manner. Remarkably, compound 3 inhibited expression of Notch1 compared with EGCG in HPB-ALL cells. Meanwhile, we found that compound 3 significantly inhibited c-Myc and Hes1, which are downstream target genes of Notch1. The findings demonstrate for the first time that an oxidation product of EGCG (compound 3) inhibits T-cell acute lymphoblastic leukemia cell line (HPB-ALL) and is a promising agent for cancer therapy deserving further research.

Hydrogen sulfide alleviates cognitive deficiency and hepatic dysfunction in a mouse model of acute liver failure.

Acute liver failure (ALF) is a devastating clinical syndrome with a high mortality rate if not treated promptly. Previous studies have demonstrated the beneficial effects of hydrogen sulfide (H2S) on the brain and liver. The present study aimed to investigate the potential protective effects of H2S in ALF. A mouse model of ALF was established following treatment with thioacetamide (TAA). Mice with TAA-induced ALF were intraperitoneally injected with 30 or 100 µmol/kg/day sodium hydrosulfide (NaHS; a H2S donor drug) for two weeks. According to results from novel object recognition and Y-maze tests, in the present study, NaHS treatment alleviated cognitive deficiency and preserved spatial orientation learning ability in TAA-induced ALF mice compared with those of untreated mice. In addition, NaHS treatment reduced serum levels of aspartate transaminase (AST), alanine transaminase (ALT) and the concentration of ammonia compared with those that received control treatment, resulting in weight loss prevention. These findings suggested a beneficial effect of H2S on liver function. In conclusion, results from the present study suggested that H2S treatment may alleviate cognitive deficiency and hepatic dysfunction in mice with ALF, indicating the potential therapeutic benefits of applying H2S for the treatment of ALF.