Characterization and functional analysis of SOCS9 from orange-spotted grouper (Epinephelus coioides) during virus infection.

The suppressor of cytokine signaling (SOCS) proteins family have twelve members including eight known mammalian SOCS members (CISH, SOCS1-7) and four new discovery members (SOCS3b, SOCS5b, SOCS8 and SOCS9) that is regarded as a classic feedback inhibitor of cytokine signaling. Although the function of the mammalian SOCS proteins have been well studied, little is known about the roles of SOCS in fish during viral infection. In this study, the molecular characteristics of SOCS9 from orange-spotted grouper (Epinephelus coioides, EcSOCS9) is investigated. The EcSOCS9 protein encoded 543 amino acids with typical SH2 (389-475aa) and SOCS_box (491-527aa), sharing high identities with reported fish SOCS9. EcSOCS9 was expressed in all detected tissues and highly expressed in kidney. After red-spotted grouper nervous necrosis virus (RGNNV) infection, the expression of EcSOCS9 was significantly induced in vitro. Furthermore, EcSOCS9 overexpression enhanced RGNNV replication, promoted virus-induced mitophagy that evidenced by the increased level of LC3-Ⅱ, BCL2, PGAM5 and decreased level of BNIP3 and FUNDC1. Besides, EcSOCS9 overexpression suppressed the expression levels of ATP6, CYB, ND4, ATP level and induced ROS level. The expression levels of interferon (IFN) related factors (IRF1, IRF3, IRF7, P53), inflammatory factors (IL1-ß, IL8, TLR2, TNF-α) and IFN-3, ISRE, NF-κB, AP1 activities were also reduced by overexpressing EcSOCS9. These date suggests that EcSOCS9 impacts RGNNV infection through modulating mitophagy, regulating the expression levels of IFN- related and inflammatory factors, which will expand our understanding of fish immune responses during viral infection.

Functional properties of ATPIF1 in the orange-spotted grouper (Epinephelus coioides) in response to viral infection.

ATP synthase inhibitory factor 1 (ATPIF1) can activate mitochondrial autophagic pathway and mediates immune response by regulating ATP synthase activity. However, the role of fish ATPIF1 on viral infection is still unknown. In this study, we identified an ATPIF1 homolog (Ec-ATPIF1) from orange-spotted grouper (Epinephelus coioides). Ec-ATPIF1 is mainly expressed in the kidney and liver. The expression of Ec-ATPIF1 was significantly up-regulated after RGNNV stimulation in vitro. Further experiments showed that overexpression of Ec-ATPIF1 inhibited the expression of viral genes (CP and RdRp) and intracellular ATP synthesis. Ec-ATPIF1 overexpression also promoted the expression of mitophagy related genes (PINK1, Parkin, BNIP3, NIX, FUNDC1, LC3), inflammation-related factors (IL-1ß, IL-6, IL-8, IL-10, TNF-α, TLR2) and interferon pathway factors (IRF1, IRF3, IRF7, MX1, ISG15, ISG56, MDA5, TRIF). While the knockdown of Ec-ATPIF1 exhibited the opposite effects on the expression of viral genes and immune-related factors above. These data suggest that Ec-ATPIF1 can impact viral infection by regulating mitophagy, ATP synthesis, the expression of inflammatory factors and interferon pathway factors. These findings will be beneficial to better explore the immune regulatory mechanisms of fish respond to viral infection.

Impacts investigation of gas barrier on effective thermal conductivity and service life of vacuum insulation panel.

Vacuum Insulation Panels (VIPs) are highly efficient thermal insulation materials with extremely low thermal conductivity based on the vacuum principle. With the sealing properties of the gas barrier envelopes, a long service life of the VIP is obtained. The mechanism and influence factors of gas and water vapor permeability were mathematically analyzed to explore the influence of gas barrier envelopes on the thermal performance of VIPs. Three typical gas barriers were studied, and the selection of the gas barrier and other aspects of optimization were involved. The relationships among temperature, humidity, solubility coefficient, diffusion coefficient, and permeability were concluded, which shows that temperature has a much greater effect on the permeability of the gas barrier relative to humidity. The numerical analysis and influencing factors of VIPs' service life were also exemplified with three different types of gas barrier envelopes. The experimental results show that depending on the environment, the temperature has a major impact on the effective thermal conductivity and service life of VIP. The research was significant in the selection of gas barriers, the optimization of the performance, and the development of vacuum insulation material.

Temperature Resistance Properties of Unidirectional Laminated Cf/SiC-Al Prepared by PIP and Vacuum Pressure Infiltration.

Material used for aero-engine fan blade requires excellent mechanical properties at high temperature (300 °C). Continuous carbon-fiber-reinforced silicon carbide ceramic matrix composites (Cf/SiC) are necessary candidates in this field, possessing low density, high strength, high modulus, and excellent high-temperature resistance. However, during the preparation process of Cf/SiC, there were inevitably residual pores and defects inside, resulting in insufficient compressive strength and reliability. The vacuum pressure melting infiltration process was used to infiltrate low melting point and high wettability aluminum alloys into the porous Cf/SiC composite material prepared by the precursor impregnation cracking process, repairing the residual pore defects inside the body. The porosity of porous Cf/SiC decreased from 49.65% to 5.1% after aluminum alloy repair and strengthening. The mechanical properties of Cf/SiC-Al composite materials strengthened by aluminum alloy repair after heat treatment were studied. The tensile strength of the as-prepared Cf/SiC-Al was 166 ± 10 MPa, which were degraded by 13~22% after heat treatment. The nonlinear sections of stress-displacement curve of as-treated samples were shorter than that of as-prepared sample. The hardness of aluminum alloy matrix after 300 °C 1 h heat treatment was 58 Hv, which was not obviously reduced compared with the sample without heat treatment. The vacuum infiltration of aluminum alloy is expected to have guiding significance for repairing and strengthening internal defects in ceramic matrix composites.

Validating Healthy Eating Index, Glycemic Index, and Glycemic Load with Modern Diets for E-Health Era.

Predictors of healthy eating parameters, including the Healthy Eating Index (HEI), Glycemic Index (GI), and Glycemic Load (GL), were examined using various modern diets (n = 131) in preparation for personalized nutrition in the e-health era. Using Nutrition Data Systems for Research computerized software and artificial intelligence machine-learning-based predictive validation analyses, we included domains of HEI, caloric source, and various diets as the potentially modifiable factors. HEI predictors included whole fruits and whole grains, and empty calories. Carbohydrates were the common predictor for both GI and GL, with total fruits and Mexican diets being additional predictors for GI. The median amount of carbohydrates to reach an acceptable GL < 20 was predicted as 33.95 g per meal (median: 3.59 meals daily) with a regression coefficient of 37.33 across all daily diets. Diets with greater carbohydrates and more meals needed to reach acceptable GL < 20 included smoothies, convenient diets, and liquids. Mexican diets were the common predictor for GI and carbohydrates per meal to reach acceptable GL < 20; with smoothies (12.04), high-school (5.75), fast-food (4.48), Korean (4.30), Chinese (3.93), and liquid diets (3.71) presenting a higher median number of meals. These findings could be used to manage diets for various populations in the precision-based e-health era.

Large area roll-to-roll printed semiconducting carbon nanotube thin films for flexible carbon-based electronics.

A universal roll-to-roll (R2R) printing approach was developed to construct large area (8 cm × 14 cm) semiconducting single-walled carbon nanotube (sc-SWCNT) thin films on flexible substrates (such as polyethylene terephthalate (PET), paper, and Al foils) at a printing speed of 8 m min-1 using highly concentrated sc-SWCNT inks and crosslinked poly-4-vinylphenol (c-PVP) as the adhesion layer. Bottom-gated and top-gated flexible printed p-type TFTs based on R2R printed sc-SWCNT thin films exhibited good electrical properties with a carrier mobility of ∼11.9 cm2 V-1 s-1, Ion/Ioff ratios of ∼106, small hysteresis, and a subthreshold swing (SS) of 70-80 mV dec-1 at low gate operating voltages (±1 V), and excellent mechanical flexibility. Furthermore, the flexible printed complementary metal oxide semiconductor (CMOS) inverters demonstrated rail-to-rail voltage output characteristics under an operating voltage as low as VDD = -0.2 V, a voltage gain of 10.8 at VDD = -0.8 V, and power consumption as low as 0.056 nW at VDD = -0.2 V. To the best of our knowledge, the electrical properties of the printed SWCNT TFTs (such as Ion/Ioff ratio, mobility, operating voltage, and mechanical flexibility) and printed CMOS inverters based on the R2R printed sc-SWCNT active layer in this work are excellent compared to those of R2R printed SWCNT TFTs reported in the literature. Consequently, the universal R2R printing method reported in this work could promote the development of fully printed low-cost, large-area, high-output, and flexible carbon-based electronics.

Fully-Solution-Processed Enhancement-Mode Complementary Metal-Oxide-Semiconductor Carbon Nanotube Thin Film Transistors Based on BiI3 -Doped Crosslinked Poly(4-Vinylphenol) Dielectrics for Ultralow-Power Flexible Electronics.

The threshold voltage (Vth ) adjustment of complementary metal-oxide-semiconductor (CMOS) thin film transistors (TFTs) is one of the research hotspots due to its key role in energy consumption control of CMOS circuits. Here, ultralow-power flexible CMOS circuits based on well-matched enhancement-mode (E-mode) CMOS single-walled carbon nanotube (SWCNT) TFTs are successfully achieved through tuning the work function of gate electrodes, electron doping, and printing techniques. E-mode P-type CMOS SWCNT TFTs with the full-solution procedure are first obtained through decreasing the work function of Ag gate electrodes directly caused by the deposition of bismuth iodide (BiI3 )-doped solid-state electrolyte dielectrics. After synthetic optimization of dielectric compositions and semiconductor printing process, the flexible printed E-mode SWCNT TFTs show the high Ion /Ioff ratios of ≈106 , small subthreshold swing (SS) of 70-85 mV dec-1 , low operating voltages of ≈0.5 to -1.5 V, good stability and excellent mechanical flexibility during 10 000 bending cycles. E-mode N-type SWCNT TFTs are then selectively achieved via printing the polarity conversion ink (2-Amino-2-methyl-1-propanol (AMP)  as electron  doping agent) in P- type TFT channels. Last, printed SWCNT CMOS inverters are successfully constructed with full rail-to-rail output characteristics and the record unit static power consumption of 6.75 fW µm-1 at VDD of 0.2 V.

A novel circRNA, hsa_circ_0069382, regulates gastric cancer progression.

Aberrant expression of circRNAs is closely associated with the progression of gastric cancer; however, the specific mechanisms involved remain unclear. Our aim was to identify new gastric cancer biomarkers and explore the molecular mechanisms of gastric cancer progression. Therefore, we analyzed miRNA and circRNA microarrays of paired early-stage gastric cancer samples. Our study identified a new circRNA called hsa_circ_0069382, that had not been reported before and was expressed at low levels in gastric cancer tissues. Our study also included bioinformatics analyses which determined that the high expression of hsa_circ_0069382 regulated the BTG anti-proliferation factor 2 (BTG2)/ focal adhesion kinase (FAK) axis in gastric cancer lines by sponging for miR-15a-5p. Therefore, proliferation, invasion, and migration of gastric cancer is impacted. miR-15a-5p overexpression partially restored the effects of hsa_circ_0069382. This study provides potential new therapeutic options and a future direction to explore for gastric cancer treatment, and biomarkers.

Research on Small Target Detection Technology Based on the MPH-SSD Algorithm.

To address the problems of less semantic information and low measurement accuracy when the SSD (single shot multibox detector) algorithm detects small targets, an MPH-SSD (multiscale pyramid hybrid SSD) algorithm that integrates the attention mechanism and multiscale double pyramid feature enhancement is proposed in this paper. In this algorithm, firstly, the SSD algorithm is used to extract the feature map of small targets, and the shallow feature enhancement module is added to expand the receptive field of the shallow feature layer so as to enrich the semantic information in the feature layer for small targets and improve the expression ability of shallow features. The processed shallow feature layer and deep feature layer are fused at multiple scales, and the semantic information and location information are fused together to obtain a feature map with rich information. Secondly, the cascaded double pyramid structure is used to transfer from the deep layer to the shallow layer so that the context information between different feature layers can be effectively transferred and the feature information can be further strengthened. The hybrid attention mechanism can retain more context information in the network, adaptively adjust the feature map after addition and fusion, and reduce the background interference. The experimental analysis of MPH-SSD algorithm on Pascal VOC and MS COCO datasets shows that the map of this algorithm is 87.7% and 51.1%, respectively. The results show that the MPH-SSD algorithm can make better use of the feature information in the shallow feature layer in the process of small target detection and has better detection performance for small targets.

Bearing fault diagnosis based on particle swarm optimization fusion convolutional neural network.

Bearings are the most basic and important mechanical parts. The stable and safe operation of the equipment requires bearing fault diagnosis in advance. So, bearing fault diagnosis is an important technology. However, the feature extraction quality of the traditional convolutional neural network bearing fault diagnosis is not high and the recognition accuracy will decline under different working conditions. In response to these questions, a bearing fault model based on particle swarm optimization (PSO) fusion convolution neural network is proposed in this paper. The model first adaptively adjusts the hyperparameters of the model through PSO, then introduces residual connections to prevent the gradient from disappearing, uses global average pooling to replace the fully connected layer to reduce the training parameters of the model, and finally adds a dropout layer to prevent network overfitting. The experimental results show that the model is under four conditions, two of which can achieve 100% recognition, and the other two can also achieve more than 98% accuracy. And compared with the traditional diagnosis method, the model has higher accuracy under variable working conditions. This research has important research significance and economic value in the field of the intelligent machinery industry.

Ultra-Light and Ultra-Low Thermal Conductivity of Elastic Silica Nanofibrous Aerogel with TiO2 Opacifier Particles as Filler.

The thermal radiation phenomenon is more crucial than other thermal transportation phenomena at elevated temperatures (>300 °C). Therefore, infrared radiation resistance and its performance on thermal conduction of nanofibrous aerogel with Titanium oxide (TiO2) filler have been investigated compared to control groups (silica nanofibrous aerogels with and without filler). Nanofibrous aerogel has been produced by electrospun silica nanofibers. Later, TiO2 opacifier and a non-opacifier filled materials were prepared by a solution homogenization method and then freeze-dried to obtain particle-filled nanofibrous aerogel. Moreover, the thermal radiation conductivity of the composite was calculated by numerical simulation, and the effect of the anti-infrared radiation of the TiO2 opacifier was obtained. The fascinating inhibited infrared radiation transmission performance (infrared transmittance ~67% at 3 µm) and excellent thermal insulation effect (thermal conductivity of 0.019 Wm−1K−1 at room temperature) and maximum compressive strengths (3.22 kPa) of silica nanofibrous aerogel with TiO2 opacifier were verified. Excellent thermal insulation, compression and thermal stability properties show its potential for practical application in industrial production. The successful synthesis of this material may shed light on the development of other insulative ceramic aerogels.

Microstructure and Mechanical Properties of Unidirectional, Laminated Cf/SiC Composites with α-Al2O3 Nanoparticles as Filler.

The effects of an α-Al2O3 nanoparticle filler in the SiC matrix on the mechanical properties and failure mechanism of the unidirectional, laminated carbon fiber-reinforced SiC composites were investigated in this work. First, α-Al2O3 nanoparticles were added to the carbon fiber bundles using a slurry impregnation method, and then the Cf/SiC composite with an α-Al2O3 nanoparticle filler (Cf/SiC-Al2O3) was fabricated using a precursor infiltration and pyrolysis method. The microstructure of the Cf/SiC-Al2O3 composite showed chemical compatibility between the α-Al2O3 and the pyrolysis SiC. The Cf/SiC-Al2O3 composite with a low porosity of ~6.67% achieved a good flexural strength of 629.3 MPa and a good fracture toughness of 25.2 MPa·m1/2. The interlaminar shear strength of the Cf/SiC-Al2O3 composite was 11.7 MPa. The SiC-Al2O3 matrix also presented a considerable Young's modulus of 138.2 ± 8.66 GPa and hardness of 10.3 ± 1.03 GPa. Further analysis indicated that the good mechanical properties with the addition of an α-Al2O3 filler were not only related to the dense matrix and the improvement of the mechanical properties of the matrix. They also originated from the thermal residual compressive stress in the SiC matrix close to the α-Al2O3 nanoparticles caused by the thermal expansion mismatch, which could reflect and close the cracks in the matrix. The findings of this study provide more methods for designing new composites exhibiting a good performance.

Clinical evaluation of a novel atlas-based PET/CT brain image segmentation and quantification method for epilepsy.

Background: Positron emission tomography (PET)/computed tomography (CT) with [18F]fluorodeoxyglucose {[18F]FDG} has been shown to be an effective imaging method for the lateralization and localization of epilepsy. However, the efficacy of PET/CT image processing and analysis needs to be improved for clinical application. Our previous research proposed a novel atlas-based image method for PET brain image segmentation and quantification; in this study, we evaluated its effectiveness in clinical patients. Methods: For image segmentation, a head anatomy template was registered to the subject image by integrating dual-modality image registration and landmark-constraint. The localizations of abnormalities were examined by quantitative comparison using the collected database. The PET/CT images of 20 reference patients and 11 patients with epilepsy were used to compare results between the proposed manual method and statistical parameter mapping (SPM). A dice coefficient analysis was performed on the six central brain regions to assess the segmentation effectiveness, and the diagnostic results of the epileptic regions were examined using pathological results as a reference. Results: The dice results of the proposed method were generally higher than those of SPM, with the averaged dice values for the proposed method and SPM being 0.78 and 0.55, respectively, in the reference group (P<0.001), and 0.73 and 0.48, respectively, in the epileptic group (P<0.001). Our proposed method detected all the pathologically reported epileptic defects; however, using the visual assessment method, epileptic defects were missed in three patients. Both the proposed and visual assessment methods incorrectly identified non-epileptic areas as epileptic areas. Conclusions: The results provide strong evidence of the feasibility of using our proposed method for accurate brain region segmentation in the diagnosis of epilepsy. Our atlas-based approach has promise for clinical application in the image processing and diagnosis of patients with epilepsy.

In silico development and validation of a novel glucose and lipid metabolism-related gene signature in gastric cancer.

Background: Abnormal glucose and lipid metabolism plays a critical role in gastric carcinogenesis and development. Hence, we presented a systematic analysis of glucose and lipid metabolism-related genes to explore their function and prognostic value in gastric cancer (GC). Methods: The consensus clustering algorithm was used to identify the molecular subtypes based on glucose and lipid metabolism-related genes. Subsequently, cox regression analysis and lasso regression analysis were utilized to establish a risk prediction model. A clinical nomogram was constructed to assist prognosis assessment. In addition, ESTIMATE and single-sample gene set enrichment analysis (ssGSEA) algorithms were performed to evaluate the immune infiltration of the metabolic model, and GSEA was used for enrichment analysis of the metabolic signature. Finally, we explored the association between the risk model and anti-cancer therapy for the purpose of clinical application for GC treatment. Results: GC samples were divided into 2 subtypes based on glucose and lipid metabolism-related genes, patients in cluster 2 had a better overall survival (OS) than those in cluster 1. Fifty-two genes were identified by univariable regression analysis. Finally, a 13-gene metabolic signature (CACNA1H, CHST1, IGFBP3, NASP, STC1, VCAN, NUP205, NUP43, PGM2L1, CAV1, ELOVL4, PRKAA2, TNFAIP8L3) was successfully constructed that demonstrated good performance in different datasets, as well as an independent hazardous factor for prognosis. In addition, the nomogram constructed with the clinical variables showed higher predictive efficacy for predicting the 1-, 3-, and 5-year OS. The 13-gene metabolic signature was significantly associated with immune scores and immune cell infiltration in high-risk group. Moreover, GSEA analysis revealed that cancer- and immune-related pathways were enriched in the high-risk group. Finally, our results indicated that there might exist an immunosuppressive status in the high-risk groups. Conclusions: This study demonstrated that glucose and lipid metabolism-related genes were significantly associated with prognosis. Meanwhile, it will provide novel insights into exploring the immunoregulation roles of these genes.

Association between bilirubin and nonalcoholic fatty liver disease in the non-obese Chinese population: a cross-sectional study.

Background: Serum bilirubin may play a role in preventing antioxidant and cytoprotective effects in physiological conditions. Serum bilirubin levels are inversely correlated with insulin resistance and the prevalence of cardiovascular diseases and diabetes mellitus. However, the correlation between serum bilirubin and nonalcoholic fatty liver disease (NAFLD) is unclear. NAFLD in non-obese participants may lead to serious health problems, calling for prompt recognition and early management. This study aimed at investigating the relationship between the serum bilirubin levels and NAFLD in non-obese Chinese adults. Methods: We evaluated 4,900 non-obese subjects (body mass index <25 kg/m2) residing in Wuwei, China. The subjects received a baseline questionnaire, physical examination, abdominal ultrasonography, and laboratory check-ups. Fasting serum bilirubin was measured with an automated biochemical analyzer. NAFLD was diagnosed based on imaging findings of fatty liver disease on ultrasonography, without excessive alcohol intake and other known causes for chronic liver disease. A logistic regression model was applied to calculate the association between serum bilirubin level and NAFLD in non-obese subjects. Results: NAFLD was diagnosed in 408 (203 men) of the subjects, and they had a mean age of 51-year-old. Non-obese NAFLD patients had lower serum direct bilirubin (DBIL) levels than control group did [2.50 (1.80-3.25) vs. 2.60 (1.90-3.50), P=0.004], but no significant differences in indirect bilirubin (IBIL) and total bilirubin (TBIL) levels of the two groups was seen (both P>0.05). After adjusting confounding factors such as age, gender, body mass index, blood glucose, and blood lipids, multivariate analysis showed serum DBIL (OR: 0.96, 95% CI: 0.83-1.11, P trend =0.6022), IBIL (OR: 1.02, 95% CI: 0.89-1.17, P trend =0.7756), and TBIL (OR: 1.00, 95% CI: 0.87-1.15, P trend =0.991) levels were not associated with NAFLD in the non-obese population. In addition, subgroup analyses (stratified according to age, gender, and medical histories of hypertension, and diabetes mellitus) suggested no independent association between NAFLD and DBIL, IBIL, or TBIL. Conclusions: Our data suggest that serum bilirubin levels are unlikely to be associated with NAFLD in non-obese subjects.

A Novel Matrisomal-Related LncRNA Signature Associated With Survival Outcome and Immune Evasion in Patients With Gastric Cancer.

Background: Different matrisomal patterns are shared across carcinomas. However, little is known about whether there exists a unique tumor matrisome that modulates GC progression and immune regulation. Methods: We conducted a genome-wide analysis based on matrisomal-related lncRNAs (MRLs) in 375 patients with GC from the Cancer Genome Atlas (TCGA) database. Patients were split into the training set and validation set at a ratio of 1:1 using the R package cart. Pearson correlation analysis (PCA) was performed to identify lncRNAs that correlated with matrisome based on differential expression genes. Subsequently, we performed univariate Cox regression analyses and lasso Cox analysis on these lncRNAs to construct a risk model. Considering the primary effect of GRASLND on the GC prognosis, we chose it for further validation in an experimental setting. Results: We identified a 15-MRL signature to predict overall survival and immune cell infiltration of patients with GC. The AUC values to predict 5-year outcome in three sets were 0.89, 0.65, and 0.78, respectively. Further analyses suggested that the high-risk group showed more obvious immune cell infiltration, and demonstrated an immunologically "cold" profile. In vitro, knockdown of GRASLND could inhibit the invasion capability of GC cells, and downregulate the protein expression of crucial matrisomal-related gene MMP9. Conclusions: The 15-MRL gene signature might serve as a relatively good predictive tool to manage patients with GC.

Antibacterial Activity and Mechanism of GO/Cu2O/ZnO Coating on Ultrafine Glass Fiber.

A GO (graphene oxide)/ZnO/Cu2O antibacterial coating was successfully sprayed on the ultrafine glass fibers using room temperature hydrothermal synthesis and air spraying techniques. The microstructures of the antibacterial coating were characterized, and the results showed that the Cu2ONPs (nano particles)/ZnONPs were uniformly dispersed on the surface of GO. Then, the antibacterial properties of the GO/ZnO/Cu2O (GZC) antibacterial coating were evaluated using the disc diffusion test. It was found that the coating exhibits excellent antibacterial properties and stability against E. coli and S. aureus, and the antibacterial rate of each group of antibacterial powder against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) was 100%. To explore the antibacterial mechanism of the GZC antibacterial powder on the ultrafine glass fibers based on the photocatalysis/oxidative stress method, the photoelectric coupling synergistic effect between GZC antibacterial coating was analyzed deeply. The results all showed that the photochemical activity of GZC antibacterial powder was significantly improved compared with pure component materials. The enhancement of its photochemical activity is beneficial to the generation of ROS (including hydroxyl radicals, superoxide anion radicals, etc.), which further confirms the speculation of the photocatalytic/oxidative stress mechanism.

Obesity, peptic ulcer disease and metabolic status in the Wuwei Cohort of northwest China: A cross-sectional study.

BACKGROUND AND OBJECTIVES: Peptic ulcer disease is a common digestive system disease. However, whether peptic ulcer disease and obesity are related is unclear. We assessed the associations of obesity and metabolic status with peptic ulcer disease. METHODS AND STUDY DESIGN: We conducted a cross-sectional study of 3561 individuals from the Wuwei cohort. We evaluated the associations of general and abdominal adiposity, as defined by different anthropometric indices, with peptic ulcer disease. Odds ratios and 95% confidence intervals were determined through binary logistic regression. RESULTS: The odds ratio for peptic ulcer disease was 2.37 (1.46-3.84) for women with obesity, compared with the normal group. The association remained significant in Models 2 and 3, with odds ratios of 2.23 (1.35-3.69) and 2.03 (1.19-3.49), respectively. In Model 1, women with obesity had an odds ratio for duodenal ulcer of 2.76 (1.41-5.42) compared with the control group; this result remained significant in Models 2 and 3, with odds ratios of 2.52 (1.24-5.13) and 2.44 (1.13-5.28), respectively. In Model 1, women with metabolically healthy and unhealthy obesity had odds ratios for peptic ulcer disease of 2.26 (1.19-4.28) and 2.15 (1.12-4.15), respectively, compared with the control group. After adjustments for major covariates and H. pylori status, these respective odds ratios became 2.27 (1.20-4.30) and 2.17 (1.12-4.20) in Model 2 and 2.2 (1.15-4.20) and 2.16 (1.11-4.19) in Model 3. CONCLUSIONS: General adiposity defined by body mass index is associated with peptic ulcer disease in women.

Obesity-Associated Differentially Methylated Regions in Colon Cancer.

Obesity with adiposity is a common disorder in modern days, influenced by environmental factors such as eating and lifestyle habits and affecting the epigenetics of adipose-based gene regulations and metabolic pathways in colorectal cancer (CRC). We compared epigenetic changes of differentially methylated regions (DMR) of genes in colon tissues of 225 colon cancer cases (154 non-obese and 71 obese) and 15 healthy non-obese controls by accessing The Cancer Genome Atlas (TCGA) data. We applied machine-learning-based analytics including generalized regression (GR) as a confirmatory validation model to identify the factors that could contribute to DMRs impacting colon cancer to enhance prediction accuracy. We found that age was a significant predictor in obese cancer patients, both alone (p = 0.003) and interacting with hypomethylated DMRs of ZBTB46, a tumor suppressor gene (p = 0.008). DMRs of three additional genes: HIST1H3I (p = 0.001), an oncogene with a hypomethylated DMR in the promoter region; SRGAP2C (p = 0.006), a tumor suppressor gene with a hypermethylated DMR in the promoter region; and NFATC4 (p = 0.006), an adipocyte differentiating oncogene with a hypermethylated DMR in an intron region, are also significant predictors of cancer in obese patients, independent of age. The genes affected by these DMR could be potential novel biomarkers of colon cancer in obese patients for cancer prevention and progression.

Validating Accuracy of a Mobile Application against Food Frequency Questionnaire on Key Nutrients with Modern Diets for mHealth Era.

In preparation for personalized nutrition, an accurate assessment of dietary intakes on key essential nutrients using smartphones can help promote health and reduce health risks across vulnerable populations. We, therefore, validated the accuracy of a mobile application (app) against Food Frequency Questionnaire (FFQ) using artificial intelligence (AI) machine-learning-based analytics, assessing key macro- and micro-nutrients across various modern diets. We first used Bland and Altman analysis to identify and visualize the differences between the two measures. We then applied AI-based analytics to enhance prediction accuracy, including generalized regression to identify factors that contributed to the differences between the two measures. The mobile app underestimated most macro- and micro-nutrients compared to FFQ (ranges: -5% for total calories, -19% for cobalamin, -33% for vitamin E). The average correlations between the two measures were 0.87 for macro-nutrients and 0.84 for micro-nutrients. Factors that contributed to the differences between the two measures using total calories as an example, included caloric range (1000-2000 versus others), carbohydrate, and protein; for cobalamin, included caloric range, protein, and Chinese diet. Future studies are needed to validate actual intakes and reporting of various diets, and to examine the accuracy of mobile App. Thus, a mobile app can be used to support personalized nutrition in the mHealth era, considering adjustments with sources that could contribute to the inaccurate estimates of nutrients.