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Inflammatory bowel disease (IBD) represents a highly recurrent gastrointestinal disorder and global public health issue. However, it lacks effective and safe strategies for its control. Although Ginkgo biloba extract (GBE) has been suggested to exhibit preventive and therapeutic activity for the control of IBD, whether its activity is associated with its ability to modulate intestinal microbiota remains to be addressed. To investigate the effect of GBE on controlling IBD, a Citrobacter Rodentium (CR)-induced mouse colitis model was used, and then histopathological examinations, biochemical assays, immunohistochemistry, and immunoblotting were performed to detect histological changes, cytokines, and tight junction (TJ) proteins in the intestine samples. We also studied 16s rRNA to detect changes in intestinal microbiota and used GC-MS to determine the microbiota-related metabolites short chain fatty acids (SCFAs). The results of our studies revealed that pre-treatment with GBE was sufficient for protecting the animals from CR-induced colitis. As a mechanism for GBE activity, GBE treatment was able to modulate the intestinal microbiota and increase the SCFAs capable of decreasing the pro-inflammatory factors and up-regulating the anti-inflammatory factors while elevating the intestinal-barrier-associated proteins to maintain the integrity of the intestines. Accordingly, our results led to a strong suggestion that GBE should be seriously considered in the preventive control of CR-induced colitis and in the development of effective and safe therapeutic strategies for controlling IBD.

Starting from childhood, the human brain restructures and rewires throughout life. Characterizing such complex brain development requires effective analysis of longitudinal and multi-modal neuroimaging data. Here, we propose such an analysis approach named Longitudinal Correlation Analysis (LCA). LCA couples the data of two modalities by first reducing the input from each modality to a latent representation based on autoencoders. A self-supervised strategy then relates the two latent spaces by jointly disentangling two directions, one in each space, such that the longitudinal changes in latent representations along those directions are maximally correlated between modalities. We applied LCA to analyze the longitudinal T1-weighted and diffusion-weighted MRIs of 679 youths from the National Consortium on Alcohol and Neurodevelopment in Adolescence. Unlike existing approaches that focus on either cross-sectional or single-modal modeling, LCA successfully unraveled coupled macrostructural and microstructural brain development from morphological and diffusivity features extracted from the data. A retesting of LCA on raw 3D image volumes of those subjects successfully replicated the findings from the feature-based analysis. Lastly, the developmental effects revealed by LCA were inline with the current understanding of maturational patterns of the adolescent brain.

Multi-modal MRIs are widely used in neuroimaging applications since different MR sequences provide complementary information about brain structures. Recent works have suggested that multi-modal deep learning analysis can benefit from explicitly disentangling anatomical (shape) and modality (appearance) information into separate image presentations. In this work, we challenge mainstream strategies by showing that they do not naturally lead to representation disentanglement both in theory and in practice. To address this issue, we propose a margin loss that regularizes the similarity in relationships of the representations across subjects and modalities. To enable robust training, we further use a conditional convolution to design a single model for encoding images of all modalities. Lastly, we propose a fusion function to combine the disentangled anatomical representations as a set of modality-invariant features for downstream tasks. We evaluate the proposed method on three multi-modal neuroimaging datasets. Experiments show that our proposed method can achieve superior disentangled representations compared to existing disentanglement strategies. Results also indicate that the fused anatomical representation has potential in the downstream task of zero-dose PET reconstruction and brain tumor segmentation. The code is available at https://github.com/ouyangjiahong/representation-disentanglement.

A fluorescent probe, Nap-MOR, based on the naphthalimide fluorophore, was designed and developed for pH measurement in aqueous solutions. Nap-MOR had a close linear relationship between fluorescence intensity and pH, in the range 4.5-8, which covers the full range of pH found in normal fresh, defective and spoiled meat. pH measurement with Nap-MOR was free from interference by a wide range of ions and biochemicals found in meat and the results were not significantly different in comparison with a pH meter. Therefore, Nap-MOR is a robust and convenient way to evaluate the freshness of chicken breast meat by measuring its pH.

BackgroundChimeric antigen receptor (CAR) T cell therapy has been successfully applied in treating lymphoma malignancies, but not in solid tumors. CD47 is highly expressed on tumor cells and its overexpression is believed to inhibit phagocytosis by macrophages and dendritic cells. Given the antitumor activity against preclinical model of CD47-blocking to induce the innate and adaptive immune system in the tumor microenvironment, here we developed a CAR-T cell secreting CD47 blocker signal regulatory protein α (SIRPα)-Fc fusion protein (Sirf CAR-T) to boost CAR-T cell therapeutic effect in solid tumor therapy.MethodsMurine T cells were transduced to express a conventional anti-Trop2 CAR and Sirf CAR. The expression of SIRPα-Fc fusion protein in the supernatant of CAR-T cells and its effect on macrophage phagocytosis were tested in vitro. In vivo antitumor efficacy of CAR-T cells was evaluated in immunocompetent mice and analysis of the tumor microenvironment in the tumor-bearing mice was performed.ResultsWe found that Sirf CAR-T cells dramatically decreased tumor burden and significantly prolonged survival in several syngeneic immunocompetent tumor models. Furthermore, we found that Sirf CAR-T cells induced more central memory T cells (TCM) and improved the persistence of CAR-T cells in tumor tissue, as well as decreased PD-1 expression on the CAR-T cell surface. In addition, we demonstrated that Sirf CAR-T cells could modulate the tumor microenvironment by decreasing myeloid-derived stem cells as well as increasing CD11c+ dendritic cells and M1-type macrophages in tumor tissue.ConclusionsIn summary, our findings indicate that CD47 blocker SIRPα-Fc enhances the antitumor efficacy of CAR-T cells and propose to block CD47/SIRPα signaling effect on CAR-T cells function, which could provide a new strategy for successful cancer immunotherapy by rationalizing combination of CD47 blocker and CAR-T cell therapy.

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has significantly increased depression rates, particularly in emerging adults. The aim of this study was to examine longitudinal changes in depression risk before and during COVID-19 in a cohort of emerging adults in the U.S. and to determine whether prior drinking or sleep habits could predict the severity of depressive symptoms during the pandemic.MethodsParticipants were 525 emerging adults from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA), a five-site community sample including moderate-to-heavy drinkers. Poisson mixed-effect models evaluated changes in the Center for Epidemiological Studies Depression Scale (CES-D-10) from before to during COVID-19, also testing for sex and age interactions. Additional analyses examined whether alcohol use frequency or sleep duration measured in the last pre-COVID assessment predicted pandemic-related increase in depressive symptoms.ResultsThe prevalence of risk for clinical depression tripled due to a substantial and sustained increase in depressive symptoms during COVID-19 relative to pre-COVID years. Effects were strongest for younger women. Frequent alcohol use and short sleep duration during the closest pre-COVID visit predicted a greater increase in COVID-19 depressive symptoms.ConclusionsThe sharp increase in depression risk among emerging adults heralds a public health crisis with alarming implications for their social and emotional functioning as this generation matures. In addition to the heightened risk for younger women, the role of alcohol use and sleep behavior should be tracked through preventive care aiming to mitigate this looming mental health crisis.

Intramuscular fat (IMF) content is associated with lamb flavor and largely varies between individuals of the same breed. However, studies investigating the effects of IMF variations on lipid profiles and aroma compounds are limited. Here, we performed lipidomic and volatilomic profiling of high-IMF and low-IMF Hu lambs. Triglycerides and diglycerides in the high-IMF group were significantly higher than those in the low-IMF group (p 0.05). Seventy-nine of 842 lipids identified were significantly different between the groups under positive and negative ion modes (variable importance in projection 1, p 0.05). Volatilomic analyses revealed that the aroma profiles also differed between the groups. Fifteen aroma compounds, mainly originating from lipid oxidation, could be responsible for this difference. Thus, our findings provide a comprehensive understanding of the increases in IMF content that drive consumers' satisfaction and also provide a basis for underpinning breeding value for IMF.

Background. Lung cancer (LC) has become the top cause responsible for cancer-related deaths. Cell division cycle-associated (CDCA) genes exert an important role in the life process. Dysregulation in the process of cell division may lead to malignancy. Methods. Transcriptional data on CDCA gene family and patient survival data were examined for lung cancer (LC) patients from the GEPIA, Oncomine, cBioPortal, and Kaplan–Meier Plotter databases. Results. CDCA1/2/3/4/5/7/8 expression levels were higher in lung adenocarcinoma tissues, and the CDCA1/2/3/4/5/6/7/8 expression levels were increased in squamous cell LC tissues compared with those in noncarcinoma lung tissues. The expression levels of CDCA1/2/3/4/5/8 showed correlation with tumor classification. The Kaplan–Meier Plotter database was employed to carry out survival analysis, indicating that increased CDCA1/2/3/4/5/6/7/8 expression levels were obviously related to poor overall survival (OS) and progression-free survival (PFS) (P<0.05). Only LC patients with increased CDCA3/4/5/8 expression were significantly related to lower post-progression survival (PPS) (P<0.05). The following processes were affected by CDCA genes’ alteration: R-HAS-2500257: resolution of sister chromatid cohesion; GO:0051301: cell division; CORUM: 1118: chromosomal passenger complex (CPC, including CDCA8, INCENP, AURKB, and BIRC5); CORUM: 127: NDC80 kinetochore complex; M129: the PID PLK1 pathway; and GO: 0007080: mitotic metaphase plate congression, all of which were remarkably modulated since the alterations affected CDCA genes. Conclusions. Upregulated CDCA genes’ expression levels in LC tissues probably play a crucial part in LC oncogenesis. The upregulated CDCA genes’ expression levels are used as the potential prognostic markers to improve patient survival and the LC prognostic accuracy. CDCA genes probably exert their functions in tumorigenesis through the PLK1 pathway.

Se-methylselenocysteine (MeSeCys) is a natural organic selenium (Se) supplement. However, its effects on animal nutrition are poorly understood. This study compared the effects of sodium selenite (SeNa), MeSeCys, and selenomethionine (SeMet) on immune function, tissue Se concentration, meat quality, and selenoprotein gene expression in pigs. A total of 72 finishing pigs were divided into four groups, which received a basal diet (BD, 0.1 mg Se/kg) without Se supplementation or one supplemented with SeNa, MeSeCys, or SeMet at a concentration of 0.25 mg Se/kg. Organic Se supplementation significantly increased the immune globulin A (IgA), IgG, and IgM serum levels compared with BD and SeNa groups (P 0.05). There were no statistically significant differences in growth performance among the four groups. SeMet was more efficient in increasing Se concentrations in the heart, muscle, and liver than MeSeCys and SeNa (P 0.05), while no statistically significant differences were observed between MeSeCys and SeNa. Se supplementation significantly decreased the pressing muscle loss compared with the BD group (P 0.05). Meat color and pH were not significantly affected. Se supplement effects on liver selenoprotein gene mRNA level enhancement were ranked as follows: MeSeCysSeMetSeNa (P 0.05). In muscle tissues, only the SELENOW mRNA level was significantly increased by the MeSeCys and SeMet treatment, compared with the SeNa group. In conclusion, SeMet was more efficient in increasing Se concentrations than MeSeCys and SeNa in pigs, while MeSeCys was more efficient in enhancing selenoprotein gene expression than SeMet and SeNa.

Some discrete Wirtinger-Northcott inequalities are established in this paper. Let Dx and Δx be the periodic difference and non-periodic difference of a vector x ∈ R n , respectively. For 1 ≤ p ≤ ∞ , we give the maximum and the minimum of ‖ D x ‖ ∞ , ‖ Δ x ‖ ∞ , ‖ D x ‖ − ∞ and ‖ Δ x ‖ − ∞ in the l p -ball B p , 0 n . In particular, we prove that, for p = ∞ , the result min B ∞ , 0 n ⁡ ‖ D x ‖ ∞ = { 4 / n , n is even , 4 n / ( n 2 − 1 ) , n is odd , is equivalent to the well-known discrete first Northcott inequality established by Fan, Taussky and Todd.

Anaerobic ammonium oxidation (anammox) is carbon friendly biological nitrogen removal process, and recently more focus is given to improving the anammox activity. Because of its high adsorption and modifiability, graphene and its derivative in wastewater treatment have received much attention. However, the specific effects and mechanisms of graphene oxide (GO) and reduced graphene oxide (RGO) on anammox are still controversial. Extensive data analysis was performed to explore the effects of GO and RGO on anammox. Statistical analysis revealed that 100 mg/L GO significantly promoted the anammox process, while 200 mg/L of GO inhibited the anammox process. The promotion of anammox performance under the influence of RGO was dependent on the temperature. The Logistic model was utilized for depicting the variation of nitrogen removal efficiency under promoting dosage of graphene oxides. A neural network model-based analysis was performed to reach anammox's potential mechanisms under the influence of two graphene oxides. Spearman correlation analysis showed that GO and RGO had significant positive correlations with nitrogen removal efficiency and specific anammox activity (p 0.01), especially for RGO. In addition, the abundance of Planctomycetes and Nitrospirae was positively correlated with the addition of graphene oxides. This work comprehensively unraveled the role of graphene oxide materials on the anammox process and provided practical directions for the enhancement of anammox.

Capsaicin is a pungent alkaloid abundantly present in peppers with outstanding biological activities, including the anti-atherosclerosis effect. Previous studies revealed that gut microbiota played an important role in the beneficial effects of capsaicin, but whether it is essential for the anti-atherosclerosis effect of capsaicin is unclear. This study evaluated the anti-atherosclerosis effect of capsaicin in ApoE−/− mice and further explored the role of depleting gut microbiota in the improvement of atherosclerosis. The results showed that capsaicin administration could prevent the development of atherosclerosis and improve serum lipids and inflammation, while antibiotic intervention abolished the alleviation of atherosclerosis by capsaicin. In addition, capsaicin administration could significantly increase the abundance of Turicibacter, Odoribacter, and Ileibacterium in feces, and decrease the abundance of deoxycholic acid, cholic acid, hypoxanthine, and stercobilin in cecal content. Our study provides evidence that gut microbiota plays a critical role in the anti-atherosclerosis effect of capsaicin.

Milk species adulteration has become an altering issue worldwide. In this study, a robust quantification method based on LC-HRMS for the simultaneous detection and differentiation of milk type from eight different animal species (namely: cow, water buffalo, wild yak, goat, sheep, donkey, horse, and camel) was established by detecting nine signature peptides originating from casein. The developed method was in-house validated in terms of sensitivity, accuracy, and precision. As a result, limits of quantification (LOQ) were ranging from 5 to 30 µg/L, recoveries ranged from 95.2% to 104.5%, and intra-day and inter-day variability were lower than 11.4% and 12.6%, respectively, for all the targeted peptides. Furthermore, this method was successfully applied to 46 commercial minor species' milk, in which 15 samples were false labeling. The obtained results indicate the necessity to monitor milk species adulteration in order to protect consumers from consuming misleading labeled minor species animal's milk.

Nutritional muscle dystrophy is associated with selenium (Se) deficiency; however, the underlying mechanism remains unclear.This study aimed to understand the crosstalk among redox status, energy metabolism, and inflammation in nutritional muscle dystrophy induced by dietary Se deficiency.Eighteen castrated male pigs (Yorkshire, 45 d old) were fed Se-deficient (Se-D; 0.007 mg Se/kg) or Se-adequate (Se-A; in the form of selenomethionine, 0.3 mg Se/kg) diets for 16 wk. The muscle Se concentrations; antioxidant capacity; and gene expression, transcriptome, global proteome, metabolome, and lipidome profiles were analyzed. The transcriptome, metabolome, and proteome profiles were analyzed with biostatistics, bioinformatics, and pathway enrichment analysis; other data were analyzed with Student's 2-sided t tests.The muscle Se content in the Se-D group was 96% lower than that in the Se-A group (P 0.05). The activity of glutathione peroxidase (GPX) and thioredoxin reductase (TXNRD) in the Se-D group was 42%-69% lower than that in the Se-A group (P 0.05). The mRNA levels of 10 selenoprotein genes were 25%-84% lower than those in the Se-A group (P 0.05). Multi-omics analyses indicated that the levels of 1378 transcripts, 83 proteins, 22 metabolites, and 55 lipid molecules were significantly altered in response to Se deficiency. Se deficiency-induced redox imbalance led to muscle central carbon and lipid metabolism reprogramming, which enhanced the glycolysis pathway and decreased phospholipid synthesis. Inflammation and apoptosis were observed in response to Se deficiency-induced muscle oxidative stress, which may have been associated with extracellular matrix (ECM) remodeling, suppressed focal adhesion and phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling, and activation of the NF-κB signaling pathway.These results contributed to understanding the crosstalk among redox, energy metabolism, and inflammation in Se deficiency-induced muscle dystrophy in pigs, and may provide intervention targets for muscle disease treatment.

Adzuki bean consumption has many health benefits, but its effects on obesity and regulating gut microbiota imbalances induced by a high-fat diet (HFD) have not been thoroughly studied. Mice were fed a low-fat diet, a HFD, and a HFD supplemented with 15% adzuki bean (HFD-AB) for 12 weeks. Adzuki bean supplementation significantly reduced obesity, lipid accumulation, and serum lipid and lipopolysaccharide (LPS) levels induced by HFD. It also mitigated liver function damage and hepatic steatosis. In particular, adzuki bean supplementation improved glucose homeostasis by increasing insulin sensitivity. In addition, it significantly reversed HFD-induced gut microbiota imbalances. Adzuki bean significantly reduced the ratio of Firmicutes/Bacteroidetes (F/B), enriched the occurrence of Bifidobacterium, Prevotellaceae, Ruminococcus_1, norank_f_Muribaculaceae, Alloprevotella, Muribaculum, Turicibacter, Lachnospiraceae_NK4A136_group, and Lachnoclostridium, and returned HFD-dependent taxa (Desulfovibrionaceae, Bilophila, Ruminiclostridium_9, Blautia, and Ruminiclostridium) back to normal status. PICRUSt2 analysis showed that the changes in gut microbiota induced by adzuki bean supplementation may be associated with the metabolism of carbohydrates, lipids, sulfur, and cysteine and methionine, and LPS biosynthesis, and valine, leucine, and isoleucine degradation.

Rechargeable alkaline nickel-zinc (Ni-Zn) batteries are attracting increased attention owing to their exceptional inherent safety and high specific capacity. Unfortunately, the limited power and cycling performances of these Ni-Zn batteries are still challenging. Herein, bimetal nickel–cobalt sulfide/ reduced graphene oxide (NiCo-S/RGO) composites with tunable compositions are synthesized by rational designing precursor and subsequent sulfidation treatment. NiCo-S is evenly anchored on RGO surface, resulting in increased number of electrochemical active sites, accelerated electrolyte ion diffusion, and enhanced electrical conductivity. Particularly, by tuning the Ni and Co composition ratios in NiCo-S, NiCo-S/RGO with a Ni to Co ratio of 2:1 (NiCo-S-2/RGO) shows a specific capacity of 145.7 mA h g−1 at 1 A g−1 and long-life cycling retention of 84.7% after 1000 cycles, and the above performances are superior than the controlled samples with other Ni to Co ratios. Furthermore, the as-assembled alkaline zinc batteries of NiCo-S-2/RGO//Zn deliver an impressive specific energy of 333.2 W h kg−1, showing great potential in practical applications. This experiment hopefully provides new idea for construction of high-performance electrodes of aqueous rechargeable batteries.

Many neurological diseases are characterized by gradual deterioration of brain structure and function. Large longitudinal MRI datasets have revealed such deterioration, in part, by applying machine and deep learning to predict diagnosis. A popular approach is to apply Convolutional Neural Networks (CNN) to extract informative features from each visit of the longitudinal MRI and then use those features to classify each visit via Recurrent Neural Networks (RNNs). Such modeling neglects the progressive nature of the disease, which may result in clinically implausible classifications across visits. To avoid this issue, we propose to combine features across visits by coupling feature extraction with a novel longitudinal pooling layer and enforce consistency of the classification across visits in line with disease progression. We evaluate the proposed method on the longitudinal structural MRIs from three neuroimaging datasets: Alzheimer's Disease Neuroimaging Initiative (ADNI, N=404), a dataset composed of 274 normal controls and 329 patients with Alcohol Use Disorder (AUD), and 255 youths from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA). In all three experiments our method is superior to other widely used approaches for longitudinal classification thus making a unique contribution towards more accurate tracking of the impact of conditions on the brain. The code is available at https://github.com/ouyangjiahong/longitudinal-pooling., Accepted by Journal of Biomedical and Health Informatics (JBHI)

Hypoxia as one of the most prominent features in tumors, has presented negative effects on tumor therapies including photodynamic therapy, radiotherapy, and chemotherapies, leading to the tumor regeneration and metastasis. Recently, nanomedicines have been proposed to handle the hypoxia dilemma. Some nanomedicines alleviated hypoxia to enhance the therapeutic effect, others used hypoxia-sensitive substances to treat tumor. Among them, macromolecular nanomaterials-based nanomedicine has attracted increased research interest. However, the complicated tumor microenvironment disturbs the practical application of macromolecular nanomaterials to deal with hypoxia. This review highlights the influence of hypoxia on tumor therapy and some new strategies of using macromolecular nanomaterials to overcome hypoxia for effective tumor therapy.

Titania nanotubes (TNT) generated on titanium implant are emerged as important modification technique to facilitate bone regeneration. Mesenchymal stem cells (MSCs)-derived exosomes are membrane bound extracellular vesicles (EVs), which play an important role in tissue regeneration. The objective of this study was to generate an EVs hybrid TNT aiming at regulating inflammation, MSCs recruitment and osteogenesis. We isolated EVs from MSCs (MSCs EVs) and 3-day osteogenically differentiated MSCs (3d EVs). MSC EVs and 3d EVs exhibited round morphology under TEM, which also showed robust internalization by human bone marrow derived MSCs (hBMSCs). Next, we fabricated 3d EVs/MSC EVs hybrid TNT. When inflammatory macrophages were co-cultured with EVs hybrid TNT, the gene and protein expression of inflammatory cytokine were significantly reduced. Macrophage morphology was also examined by confocal laser scanning microscopy (CLSM) and scanning electron microscopy (SEM). Further migratory ability study using hBMSCs indicated significant enhancement of MSCs migration in EVs hybrid TNT. In addition, we further demonstrated significant increase of osteogenic differentiation of hBMSCs in EVs hybrid TNT. This study suggests that EVs hybrid TNT may serve as a viable therapeutic approach to enhance osteogenesis and bone regeneration.

Batch Normalization (BN) and its variants have delivered tremendous success in combating the covariate shift induced by the training step of deep learning methods. While these techniques normalize feature distributions by standardizing with batch statistics, they do not correct the influence on features from extraneous variables or multiple distributions. Such extra variables, referred to as metadata here, may create bias or confounding effects (e.g., race when classifying gender from face images). We introduce the Metadata Normalization (MDN) layer, a new batch-level operation which can be used end-to-end within the training framework, to correct the influence of metadata on feature distributions. MDN adopts a regression analysis technique traditionally used for preprocessing to remove (regress out) the metadata effects on model features during training. We utilize a metric based on distance correlation to quantify the distribution bias from the metadata and demonstrate that our method successfully removes metadata effects on four diverse settings: one synthetic, one 2D image, one video, and one 3D medical image dataset., Accepted to CVPR 2021. Project page: https://mml.stanford.edu/MDN/

The age- and time-dependent effects of binge-drinking on adolescent brain development have not been well characterized even though binge drinking is a health crisis among adolescents. The impact of binge drinking on gray matter volume development was examined using longitudinal data from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA). Non-binge drinkers (n=177) were matched to binge drinkers (n=164) on potential confounders. Number of binge drinking episodes in the past year was linked to decreased volumes for total gray matter, frontal, parietal, temporal, and occipital lobes (psps

The age- and time-dependent effects of binge drinking on adolescent brain development have not been well characterized even though binge drinking is a health crisis among adolescents. The impact of binge drinking on gray matter volume (GMV) development was examined using 5 waves of longitudinal data from the National Consortium on Alcohol and NeuroDevelopment in Adolescence study. Binge drinkers (n = 166) were compared with non-binge drinkers (n = 82 after matching on potential confounders). Number of binge drinking episodes in the past year was linked to decreased GMVs in bilateral Desikan–Killiany cortical parcellations (26 of 34 with P

A naphthalimide-based fluorescent probe, Nap-I, with iodoacetamide as the alkylating group, has been synthesized, and its specific fluorescent staining of proteins containing cysteine (Cys) and selenocysteine (Sec) residues in sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) has been evaluated. This molecule shows good fluorescence properties in the labeling of protein Cys/Sec residues, while reducing steric hindrance and minimizing changes in the water solubility of proteins. Reaction parameters, such as labeling time and pH, have been investigated, and the optimal labeling conditions for Cys-containing proteins have been determined. Thioredoxin reductase (TXNRD) is best stained at low pH. The probe Nap-I has been successfully used for the quantification of serum proteins and hemoglobin in Tan sheep serum, and TXNRD in Tan sheep liver and muscle has been labeled at low pH. Based on the probe Nap-I, we have also distinguished TXNRD1 and TXNRD2 by SDS-PAGE. The results showed that, compared with the normal microenvironment in which the protein resides, the lower the pH value, the greater the TXNRD activity.

The study was conducted to investigate the effects of replacing antibiotic growth promoters (AGPs) with an egg immunoglobulin (IgY) combined with phytomolecules (PM) on the growth rate, serum immunity, and intestinal health of weaned pigs challenged with Escherichia coli K88 (E. coli K88). A total of 192 piglets were weaned at 28 days old with an average weight of 7.29 (± 0.04) kg. They were randomly divided into four treatments containing eight replicates with six piglets per replicate. The treatment groups were NC and PC fed a basal diet, AGP fed a basal diet supplemented with 75 mg/kg chlortetracycline, 50 mg/kg oxytetracycline calcium, and 40 mg/kg zinc bacitracin, IPM fed a basal diet supplemented with IgY at dose of 2.5 g/kg and 1.0 g/kg and PM at dose of 300 mg/kg and 150 mg/kg during days 1 to 17 and 18 to 42, respectively. On days 7 to 9 of the experiment, piglets in the PC, AGP, and IPM groups were orally challenged with 20 mL E. coli K88 (109 CFU/mL), while piglets in the NC group were challenged with 20 mL medium without E. coli K88. The E. coli K88 challenge model was successful as the incidence of post-weaning diarrhea (PWD) of piglets challenged with E. coli K88 was significantly higher than that of those unchallenged piglets during the challenge time (days 7 to 9) and days 1 to 7 of post-challenge (p &lt, 0.05). A diet with combinations of IgY and PM and AGPs significantly decreased the incidence of PWD during the challenge time and days 1 to 7 of post-challenge (p &lt, 0.05) compared to the PC group and significantly improved the ratio of feed to weight gain (F:G) during days 1 to 17 of the experiment compared to the NC and PC groups (p &lt, 0.05). In comparison with the PC group, piglets in the IPM group had significantly higher serum levels of IgA, IgG, and IgM (p &lt, 0.05), but lower serum IL-1β on day 17 of experiement (p &lt, 0.05). Besides, diet supplementation with AGP significantly decreased serum IL-1β, IL-6, and TNF-α on days 17 and 42 (p &lt, 0.05) with comparison to the PC group. Piglets in the IPM group showed a significantly lower level of fecal coliforms (p &lt, 0.05), but a higher villus height of jejunum and ileum and higher ratio of villus height to crypt depth of duodenum and jejunum (p &lt, 0.05) than those piglets in the PC group. In summary, diet supplementation with a mixture of IgY and PM decreased the incidence of PWD and coliforms, increased feed conversion ratio, and improved intestinal histology and immune function.

To determine the persistent effects of the pandemic on mental health in young adults, we categorized depressive symptom trajectories and sought factors that promoted a reduction in depressive symptoms in high-risk individuals. Specifically, longitudinal analysis investigated changes in the risk for depression before and during the pandemic until December 2021 in 399 young adults (57% female; age range: 22.8 ± 2.6 years) in the United States (U.S.) participating in the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study. The Center for Epidemiologic Studies Depression Scale (CES-D-10) was administered multiple times before and during the pandemic. A score ≥10 identified individuals at high-risk for depression. Self-reported sleep behavior, substance use, and coping skills at the start of the pandemic were assessed as predictors for returning to low-risk levels while controlling for demographic factors. The analysis identified four trajectory groups regarding depression risk, with 38% being at low-risk pre-pandemic through 2021, 14% showing persistent high-risk pre-pandemic through 2021, and the remainder converting to high-risk either in June 2020 (30%) or later (18%). Of those who became high-risk in June 2020, 51% were no longer at high-risk in 2021. Logistic regression revealed that earlier bedtime and, for the older participants (mid to late twenties), better coping skills were associated with this declining risk. Results indicate divergence in trajectories of depressive symptoms, with a considerable number of young adults developing persistent depressive symptoms. Healthy sleep behavior and specific coping skills have the potential to promote remittance from depressive symptoms in the context of the pandemic.

This study assessed the potential and mechanism of action of astaxanthin, to improve the stability of docosahexaenoic acid (22:6(n-3); DHA) enriched egg products, during storage at 4 °C. The reduction in DHA content after 42 days of storage in astaxanthin-DHA eggs (from hens fed supplemental astaxanthin and DHA) was3%, whereas the reduction in regular-DHA eggs (hens fed DHA only) was over 17%. Astaxanthin also decreased production of oxidation products including 4-hydroxy-2-hexenal, 4-hydroxy-2-nonenal and malondialdehyde in eggs during storage, thus markedly improving the oxidative stability of DHA-enriched eggs. The yolk lipidomic profile showed higher intensities for most DHA-containing lipids, especially DHA-phosphatidylcholine, DHA-phosphatidylethanolamine and DHA-non-esterified fatty acid, compared with regular-DHA eggs. Astaxanthin acts primarily by suppressing oxidation of DHA-non-esterified fatty acid, which minimizes the degradation of DHA and appears to be the primary protection mode of yolk DHA during storage.

Longitudinal MRIs are often used to capture the gradual deterioration of brain structure and function caused by aging or neurological diseases. Analyzing this data via machine learning generally requires a large number of ground-truth labels, which are often missing or expensive to obtain. Reducing the need for labels, we propose a self-supervised strategy for representation learning named Longitudinal Neighborhood Embedding (LNE). Motivated by concepts in contrastive learning, LNE explicitly models the similarity between trajectory vectors across different subjects. We do so by building a graph in each training iteration defining neighborhoods in the latent space so that the progression direction of a subject follows the direction of its neighbors. This results in a smooth trajectory field that captures the global morphological change of the brain while maintaining the local continuity. We apply LNE to longitudinal T1w MRIs of two neuroimaging studies: a dataset composed of 274 healthy subjects, and Alzheimer's Disease Neuroimaging Initiative (ADNI, N=632). The visualization of the smooth trajectory vector field and superior performance on downstream tasks demonstrate the strength of the proposed method over existing self-supervised methods in extracting information associated with normal aging and in revealing the impact of neurodegenerative disorders. The code is available at \url{https://github.com/ouyangjiahong/longitudinal-neighbourhood-embedding.git}., Provisional Accepted by Medical Image Computing and Computer Assisted Intervention (MICCAI) 2021

Parkinson’s disease (PD) is a brain disorder that primarily affects motor function, leading to slow movement, tremor, and stiffness, as well as postural instability and difficulty with walking/balance. The severity of PD motor impairments is clinically assessed by part III of the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), a universally-accepted rating scale. However, experts often disagree on the exact scoring of individuals. In the presence of label noise, training a machine learning model using only scores from a single rater may introduce bias, while training models with multiple noisy ratings is a challenging task due to the inter-rater variabilities. In this paper, we introduce an ordinal focal neural network to estimate the MDS-UPDRS scores from input videos, to leverage the ordinal nature of MDS-UPDRS scores and combat class imbalance. To handle multiple noisy labels per exam, the training of the network is regularized via rater confusion estimation (RCE), which encodes the rating habits and skills of raters via a confusion matrix. We apply our pipeline to estimate MDS-UPDRS test scores from their video recordings including gait (with multiple Raters, R = 3) and finger tapping scores (single rater). On a sizable clinical dataset for the gait test (N = 55), we obtained a classification accuracy of 72% with majority vote as ground-truth, and an accuracy of ∼84% of our model predicting at least one of the raters’ scores. Our work demonstrates how computer-assisted technologies can be used to track patients and their motor impairments, even when there is uncertainty in the clinical ratings. The latest version of the code will be available at https://github.com/mlu355/PD-Motor-Severity-Estimation.

This study aims at investigating whether the livestock, lactation stage, or geographical origin of specialty milk in China could be classified by the elemental contents. Samples of goat, buffalo, and yak milk were collected from main production provinces in China and the contents of nine elements in milk from different livestock, regions, and lactation stages were determined. Statistical analysis indicated that the contents of Mn, Cu, As, Se, Cs, and Mo in mature milk were significantly different between the three livestock (p

Background The objective of this study was to determine the causal relationship between habitual alcohol consumption with meals and lung cancer. Methods Public genetic summary data from two large consortia [the Neale Lab and the International Lung Cancer Consortium (ILCCO)] were used for analysis. As the instrumental variables of habitual alcohol consumption with meals, data on genetic variants were retrieved from Neale Lab. Additionally, genetic data from other consortia [Global Lipid Genetics Consortium (GLGC), Tobacco, Alcohol and Genetics (TAG), Genetic Investigation of Anthropocentric Traits (GIANT)] were utilized to determine whether alcohol could causally alter some general risk factors for lung cancer. The primary outcome was the risk of lung cancer (11,348 cases and 15,861 controls in the ILCCO). The R package TwoSampleMR was used for analysis. Results Based on the inverse variance weighted method, the results of the two-sample Mendelian randomization (MR) analyses indicated that commonly consuming alcohol with meals was a protective factor, reducing lung cancer risk [odds ratio (OR) 0.175, 95% confidence interval (CI): 0.045-0.682, P=0.012]. The heterogeneity analysis revealed that the causal relationship analyses of different types of lung cancer all had low heterogeneity (P>0.05). The horizontal pleiotropic study showed that major bias was unlikely. The MR assumptions did not seem to be violated. The causal relationship analyses between habitual alcohol consumption with meals and some risk factors for cancers showed that this alcohol consumption habit was a beneficial factor for reducing body mass index (BMI) and the number of cigarettes smoked per day. Conclusions Habitual appropriate alcohol consumption with meals is a protective factor for the development of lung cancer.

Presence of bias (in datasets or tasks) is inarguably one of the most critical challenges in machine learning applications that has alluded to pivotal debates in recent years. Such challenges range from spurious associations between variables in medical studies to the bias of race in gender or face recognition systems. Controlling for all types of biases in the dataset curation stage is cumbersome and sometimes impossible. The alternative is to use the available data and build models incorporating fair representation learning. In this paper, we propose such a model based on adversarial training with two competing objectives to learn features that have (1) maximum discriminative power with respect to the task and (2) minimal statistical mean dependence with the protected (bias) variable(s). Our approach does so by incorporating a new adversarial loss function that encourages a vanished correlation between the bias and the learned features. We apply our method to synthetic data, medical images (containing task bias), and a dataset for gender classification (containing dataset bias). Our results show that the learned features by our method not only result in superior prediction performance but also are unbiased. The code is available at https://github.com/QingyuZhao/BR-Net/., Comment: WACV 2021

For prevention of the coronavirus disease 2019 caused by the novel coronavirus SARS-CoV-2, an effective vaccine is critical. Herein, several potential peptide epitopes from the spike protein of SARS-CoV-2 have been synthesized and covalently linked with the cross-reactive material (CRM197). Immunization of mice with the resulting conjugates induced high titers of IgG antibodies against the spike protein. Importantly, the post-immune sera effectively neutralized SARS-CoV-2 pseudovirus, suggesting the epitopes identified are protective, and these conjugates are promising leads for anti-SARS-CoV-2 vaccine development.

Additional file 3: Figure S1 Relative mRNA levels of ferroptosis related genes in the spleen in the Se-adequate group and Se-deficient group

Additional file 2: Supplemental Table 2. List of primers used for real-time PCR analysis

Additional file 1: Supplemental Table 1. Ingredient and nutrient composition of the basal diet

IMPORTANCE: Maturation of white matter fiber systems subserves cognitive, behavioral, emotional, and motor development during adolescence. Hazardous drinking during this active neurodevelopmental period may alter the trajectory of white matter microstructural development, potentially increasing risk for developing alcohol-related dysfunction and alcohol use disorder in adulthood. OBJECTIVE: To identify disrupted adolescent microstructural brain development linked to drinking onset and to assess whether the disruption is more pronounced in younger rather than older adolescents. DESIGN, SETTING, AND PARTICIPANTS: This case-control study, conducted from January 13, 2013, to January 15, 2019, consisted of an analysis of 451 participants from the National Consortium on Alcohol and Neurodevelopment in Adolescence cohort. Participants were aged 12 to 21 years at baseline and had at least 2 usable magnetic resonance diffusion tensor imaging (DTI) scans and up to 5 examination visits spanning 4 years. Participants with a youth-adjusted Cahalan score of 0 were labeled as no-to-low drinkers; those with a score of greater than 1 for at least 2 consecutive visits were labeled as heavy drinkers. Exploratory analysis was conducted between no-to-low and heavy drinkers. A between-group analysis was conducted between age- and sex-matched youths, and a within-participant analysis was performed before and after drinking. EXPOSURES: Self-reported alcohol consumption in the past year summarized by categorical drinking levels. MAIN OUTCOMES AND MEASURES: Diffusion tensor imaging measurement of fractional anisotropy (FA) in the whole brain and fiber systems quantifying the developmental change of each participant as a slope. RESULTS: Analysis of whole-brain FA of 451 adolescents included 291 (64.5%) no-to-low drinkers and 160 (35.5%) heavy drinkers who indicated the potential for a deleterious association of alcohol with microstructural development. Among the no-to-low drinkers, 142 (48.4%) were boys with mean (SD) age of 16.5 (2.2) years and 149 (51.2%) were girls with mean (SD) age of 16.5 (2.1) years and 192 (66.0%) were White participants. Among the heavy drinkers, 86 (53.8%) were boys with mean (SD) age of 20.1 (1.5) years and 74 (46.3%) were girls with mean (SD) age of 20.5 (2.0) years and 142 (88.8%) were White participants. A group analysis revealed FA reduction in heavy-drinking youth compared with age- and sex-matched controls (t(154) = –2.7, P = .008). The slope of this reduction correlated with log of days of drinking since the baseline visit (r(156) = –0.21, 2-tailed P = .008). A within-participant analysis contrasting developmental trajectories of youths before and after they initiated heavy drinking supported the prediction that drinking onset was associated with and potentially preceded disrupted white matter integrity. Age-alcohol interactions (t(152) = 3.0, P = .004) observed for the FA slopes indicated that the alcohol-associated disruption was greater in younger than older adolescents and was most pronounced in the genu and body of the corpus callosum, regions known to continue developing throughout adolescence. CONCLUSIONS AND RELEVANCE: This case-control study of adolescents found a deleterious association of alcohol use with white matter microstructural integrity. These findings support the concept of heightened vulnerability to environmental agents, including alcohol, associated with attenuated development of major white matter tracts in early adolescence.

In this work, MgCo

The application of data-driven deep learning to identify sex differences in developing brain structures of pre-adolescents has heretofore not been accomplished. Here, the approach identifies sex differences by analyzing the minimally processed MRIs of the first 8144 participants (age 9 and 10 years) recruited by the Adolescent Brain Cognitive Development (ABCD) study. The identified pattern accounted for confounding factors (i.e., head size, age, puberty development, socioeconomic status) and comprised cerebellar (corpus medullare, lobules III, IV/V, and VI) and subcortical (pallidum, amygdala, hippocampus, parahippocampus, insula, putamen) structures. While these have been individually linked to expressing sex differences, a novel discovery was that their grouping accurately predicted the sex in individual pre-adolescents. Another novelty was relating differences specific to the cerebellum to pubertal development. Finally, we found that reducing the pattern to a single score not only accurately predicted sex but also correlated with cognitive behavior linked to working memory. The predictive power of this score and the constellation of identified brain structures provide evidence for sex differences in pre-adolescent neurodevelopment and may augment understanding of sex-specific vulnerability or resilience to psychiatric disorders and presage sex-linked learning disabilities.

In order to reveal the mechanical characteristics of the unsaturated undisturbed Ili loess in westerly region, the isotropic compression tests controlling suction, the triaxial shrinkage tests controlling net mean stress and consolidation shear tests controlling net confining pressure and suction were carried out under different soluble salt contents. The objective of investigation is to explore the normalized characteristics of compression curve, soil water characteristic curve and critical state line. The results show that the ratio of void ratio to initial void ratio and the ratio of net mean stress to yield net mean stress are suitable to normalize the compression curves under different suctions in the isotropic compression test. The soil water characteristic curves under different net mean stresses in the triaxial shrinkage test can be normalized by the ratio of water content to saturated water content and the ratio of suction to air entry value. In the consolidation shear test controlling constant suction, the unsaturated critical state lines under different suctions can be normalized by the corresponding saturated critical state line in the plane of effective net mean stress and deviator stress. The unsaturated critical state lines under different suctions in the plane of void ratio and net mean stress can be normalized by means of degree of gas saturation and the ratio of unsaturated void ratio to saturated void ratio under the same effective net mean stress. The results provide potential benefits for the constructions of large-scale water conservancy projects in the special area of Central Asia.

Minor artifacts introduced during image acquisition are often negligible to the human eye, such as a confined field of view resulting in MRI missing the top of the head. This cropping artifact, however, can cause suboptimal processing of the MRI resulting in data omission or decreasing the power of subsequent analyses. We propose to avoid data or quality loss by restoring these missing regions of the head via variational autoencoders (VAE), a deep generative model that has been previously applied to high resolution image reconstruction. Based on diffusion weighted images (DWI) acquired by the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA), we evaluate the accuracy of inpainting the top of the head by common autoencoder models (U-Net, VQVAE, and VAE-GAN) and a custom model proposed herein called U-VQVAE. Our results show that U-VQVAE not only achieved the highest accuracy, but also resulted in MRI processing producing lower fractional anisotropy (FA) in the supplementary motor area than FA derived from the original MRIs. Lower FA implies that inpainting reduces noise in processing DWI and thus increases the quality of the generated results. The code is available at https://github.com/RdoubleA/DWI-inpainting.

Atherosclerotic plaques consist mostly of smooth muscle cells (SMC), and genes that influence SMC biology can modulate coronary artery disease (CAD) risk. Allelic variation at 15q22.33 has been identified by genome-wide association studies to modify the risk of CAD, and is associated with expression of SMAD3 in SMC, but the mechanism by which this gene modifies CAD risk remains poorly understood. SMC-specific deletion of Smad3 in a murine atherosclerosis model resulted in greater plaque burden, positive remodeling, and increased vascular calcification. Single-cell transcriptomic analyses revealed that loss of Smad3 altered SMC progeny phenotype toward the previously described chondromyocyte fate, but importantly also promoted transition to a novel cell-state that governs remodeling and recruitment of inflammatory cells. This new remodeling population was marked by uniquely high Mmp3 and Cxcl12 expression, and its appearance correlated with higher-risk plaque features such as increased positive remodeling and macrophage content. Further, investigation of transcriptional mechanisms by which Smad3 alters SMC cell-fate revealed novel roles for Hox and Sox transcription factors whose direct interaction with Smad3 regulate an extensive transcriptional program balancing remodeling and vascular ECM with significant implications for human Mendelian aortic aneurysmal diseases. Together, these data suggest that Smad3 expression in SMC inhibits the emergence of specific SMC phenotypic transition cells that mediate adverse plaque features, including positive remodeling, monocyte recruitment, and vascular calcification.