Personalized immune subtypes based on machine learning predict response to checkpoint blockade in gastric cancer.

Immune checkpoint inhibitors (ICI) show high efficiency in a small fraction of advanced gastric cancer (GC). However, personalized immune subtypes have not been developed for the prediction of ICI efficiency in GC. Herein, we identified Pan-Immune Activation Module (PIAM), a curated gene expression profile (GEP) representing the co-infiltration of multiple immune cell types in tumor microenvironment of GC, which was associated with high expression of immunosuppressive molecules such as PD-1 and CTLA-4. We also identified Pan-Immune Dysfunction Genes (PIDG), a conservative PIAM-derivated GEP indicating the dysfunction of immune cell cooperation, which was associated with upregulation of metastatic programs (extracellular matrix receptor interaction, TGF-ß signaling, epithelial-mesenchymal transition and calcium signaling) but downregulation of proliferative signalings (MYC targets, E2F targets, mTORC1 signaling, and DNA replication and repair). Moreover, we developed 'GSClassifier', an ensemble toolkit based on top scoring pairs and extreme gradient boosting, for population-based modeling and personalized identification of GEP subtypes. With PIAM and PIDG, we developed four Pan-immune Activation and Dysfunction (PAD) subtypes and a GSClassifier model 'PAD for individual' with high accuracy in predicting response to pembrolizumab (anti-PD-1) in advance GC (AUC = 0.833). Intriguingly, PAD-II (PIAMhighPIDGlow) displayed the highest objective response rate (60.0%) compared with other subtypes (PAD-I, PIAMhighPIDGhigh, 0%; PAD-III, PIAMlowPIDGhigh, 0%; PAD-IV, PIAMlowPIDGlow, 17.6%; P = 0.003), which was further validated in the metastatic urothelial cancer cohort treated with atezolizumab (anti-PD-L1) (P = 0.018). In all, we provided 'GSClassifier' as a refined computational framework for GEP-based stratification and PAD subtypes as a promising strategy for exploring ICI responders in GC. Metastatic pathways could be potential targets for GC patients with high immune infiltration but resistance to ICI therapy.

Evidence from an Avian Embryo Model that Zinc-Inducible MT4 Expression Protects Mitochondrial Function Against Oxidative Stress.

BACKGROUND: Metallothioneins (MTs) have a strong affinity for zinc (Zn) and remain at a sufficiently high level in mitochondria. As the avian embryo is highly susceptible to oxidative damage and relatively easy to manipulate in a naturally closed chamber, it is an ideal model of the effects of oxidative stress on mitochondrial function. However, the protective roles and molecular mechanisms of Zn-inducible protein expression on mitochondrial function in response to various stressors are poorly understood. OBJECTIVES: The study aimed to investigate the mechanisms by which Zn-induced MT4 expression protects mitochondrial function and energy metabolism subjected to oxidative stress using the avian embryo and embryonic primary hepatocyte models. METHODS: First, we investigated whether MT4 expression alters mitochondrial function. Then, we examined the effects of Zn-induced MT4 overexpression and MT4 silencing on embryonic primary hepatocytes from breeder hens fed a normal Zn diet subjected to a tert-butyl hydroperoxide (BHP) oxidative stress challenge during incubation. In vivo, the avian embryos from hens fed the Zn-deficient and Zn-adequate diets were used to determine the protective roles of Zn-induced MT4 expression on the function of mitochondria exposed to oxidative stress induced by in ovo BHP injection. RESULTS: An in vitro study revealed that Zn-induced MT4 expression reduced reactive oxygen species accumulation in primary hepatocytes. MT4 silencing exacerbated BHP-mediated mitochondrial dysfunction whereas Zn-inducible MT4 overexpression mitigated it. Another in vivo study disclosed that maternal Zn-induced MT4 expression protected mitochondrial function in chick embryo hepatocytes against oxidative stress by inhibiting the peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α)/peroxisome proliferators-activated receptor-γ (PPAR-γ) pathway. CONCLUSION: This study underscores the potential protective roles of Zn-induced MT4 expression via the downregulation of the PGC-1α/PPAR-γ pathway on mitochondrial function stimulated by the stress challenge in the primary hepatocytes in an avian embryo model. Our findings suggested that Zn-induced MT4 expression could provide a new therapeutic target and preventive strategy for repairing mitochondrial dysfunction in disease.

CHD4 promotes acquired chemoresistance and tumor progression by activating the MEK/ERK axis.

AIMS: Chemoresistance remains a major challenge in gastric cancer (GC). Chromodomain helicase DNA-binding protein 4 (CHD4) mediated chromatin remodeling plays critical roles in various tumor types, but its role in chemoresistance in GC remains uncharacterized. METHODS: CHD4 expression was examined by immunohistochemistry and Western blotting. The role of CHD4 on cell proliferation and chemoresistance of GC was examined in vitro and in vivo. Immunoprecipitation and liquid chromatography-mass spectrometry were used to identify CHD4-binding proteins and a proximity ligation assay was used to explore protein-protein interaction. RESULTS: Chemoresistance is associated with upregulation of CHD4 in the tumor tissues of GC patients. Overexpression of CHD4 increased chemoresistance and cell proliferation. Knockdown of CHD4 induced cell apoptosis and cell cycle arrest. CHD4 mediates the decrease of the intracellular concentration of cisplatin by inducing drug efflux. Additionally, CHD4 promotes the interaction between ERK1/2 and MEK1/2, resulting in continuous activation of MEK/ERK pathway. Knockdown of CHD4 in GC increased sensitivity to chemotherapy and suppressed tumor growth in a mouse xenograft model. CONCLUSIONS: This study identifies CHD4 dominated multi-drug efflux as a promising therapeutic target for overcoming acquired chemoresistance in GC.

Association of Breastfeeding Practices During the First 3 Months with Infant Sleep Trajectories: A Prospective Cohort Study.

BACKGROUND: Breastfeeding has numerous effects on maternal and child health. The effect of breastfeeding on infant sleep remains inconclusive. OBJECTIVES: We aimed to examine whether full breastfeeding (FBF) during the first 3 mo is associated with longitudinal infant sleep trajectories in their first 2 y of life. METHODS: The study was embedded in the Tongji Maternal and Child Health Cohort study. Information on infant feeding practices was collected at 3 mo of age, and maternal/child pairs were assigned to the FBF or the non-FBF group (including partially breastfeeding and exclusive formula feeding) on the basis of feeding practices during the first 3 mo of life. Sleep data of infants were obtained at 3, 6, 12, and 24 mo. Total, night, and day sleep trajectories across 3 to 24 mo were estimated with group-based models. Each sleep trajectory was differentiated on the basis of sleep duration at 3 mo (long/moderate/short) and the interval from 6 to 24 mo (moderate/short). Multinomial logistic regression was used to investigate the association of breastfeeding practices with infant sleep trajectories. RESULTS: Among the 4056 infants studied, 2558 (63.1%) received FBF for 3 mo. When compared with FBF infants, non-FBF infants had shorter sleep duration at 3, 6, and 12 mo (P < 0.01). Non-FBF infants were more likely to experience Moderate-Short (OR: 1.31; 95% CI: 1.06, 1.61) and Short-Short (OR: 1.56; 95% CI: 1.12, 2.16) total sleep trajectories and more likely to experience Moderate-Short (OR: 1.84; 95% CI: 1.22, 2.77), and Short-Moderate (OR: 1.40; 95% CI: 1.06, 1.85) night sleep trajectories than FBF infants. CONCLUSIONS: Full breastfeeding for ≥3 mo were positively associated with longer infant sleep duration. Infants fully breastfed were more likely to experience better sleep trajectories characterized by longer duration in their first 2 y of life. Full breastfeeding may benefit infants through healthy sleep.

Plasma Manganese Levels and Risk of Gestational Diabetes Mellitus: A Prospective Cohort Study.

Manganese (Mn) intake has been found to be linked with risk of type 2 diabetes. However, the role of Mn in the development of gestational diabetes mellitus (GDM) remains to be investigated. This prospective study included pregnant women from the Tongji Maternal and Child Health Cohort. A total of 2327 participants with plasma specimens before 20 weeks were included. Among the pregnant women, 9.7% (225/2327) were diagnosed with GDM. After adjustment, pregnant women with the third and highest quartile of plasma Mn levels had 1.31-fold (RR, 2.31 [1.48, 3.61]) and 2.35-fold (RR, 3.35 [2.17, 5.17]) increased risk of GDM compared with those with the lowest quartile. A 1 standard deviation increment of ln-transformed plasma Mn levels (0.53 µg/L) was related to elevated risks of GDM with RRs of 1.28 [1.17, 1.40]. The positive associations between Mn and GDM remained consistent in all the subgroups. The weighted quantile sum index was significantly related to GDM (RR, 1.60 [1.37, 1.86]). The contribution of Mn (58.69%) to the metal mixture index was the highest related to GDM. Higher plasma Mn levels were found to be linked with elevated fasting and 2 h post-load blood glucose. This study revealed relationships of higher plasma Mn levels in early pregnancy and increased risk of GDM, suggesting that though essential, excess Mn in the body might be a potential important risk factor for GDM.

Dietary patterns and cognitive function in older adults residing in rural China.

BACKGROUND AND OBJECTIVES: Research has produced inconsistent findings on the association between dietary patterns and cognitive function. In the present study, we examined the association between dietary patterns and cognitive function among rural China's older adults and aimed to identify major dietary patterns. METHODS AND STUDY DESIGN: This cross-sectional study included 1176 individuals aged 65-85 years. Dietary intake was assessed using a food frequency questionnaire. Factor analysis and the Chinese Dietary Balance Index were respectively employed to determine dietary patterns and assess dietary quality. Cognitive function was evaluated using the Mini-Mental State Examination, and logistic regression analysis was performed to examine the relationship between dietary patterns and cognitive decline. RESULTS: Three main dietary patterns were identified and named on the basis of foods with high content: a "healthy dietary pattern," a "multigrain dietary pattern," and a "snack dietary pattern." With the increase in the score of the healthy dietary pattern, the Mini-Mental State Examination total score exhibited a significant downward trend (p<0.001). Moreover, we observed a prominent negative association between the healthy dietary pattern and mild cognitive impairment (4th to 1st quartile, OR=0.36; 95%CI, 0.24-0.54; p<0.001). After we adjusted for potential covariates, the negative correlation remained (4th to 1st quartile, OR=0.48; 95%CI, 0.28-0.81; p=0.006). However, no relation was observed between mild cognitive impairment and either the multigrain or snack dietary patterns. CONCLUSIONS: The healthy dietary pattern, which is based on the consumption of rice and flour, red meat, chicken, vegetables, seafood, and fruits, protects against cognitive dysfunction.

Maternal high-fructose consumption provokes placental oxidative stress resulting in asymmetrical fetal growth restriction in rats.

We aimed to determine the impact of high-fructose intake during pregnancy on the fetal-placental unit in rats, which may be the initial mechanism of the programming effect of fructose. Pregnant Sprague-Dawley rats were randomly assigned to three groups and respectively provided tap water (n = 10), 10% (w/v) fructose solution (n = 10), and 10% (w/v) glucose solution (n = 10) from embryonic day 0 to 20. Compared with the control and glucose groups, significantly lower fetal length, fetal weight, placental weight, and fetus/placenta ratio were found in the fructose group on embryonic day 20 (all p<0.05). In parallel with markedly increased uric acid concentrations in the dams, significantly decreased antioxidant enzymes activities and mRNA expression levels were observed in placentas in the fructose group (all p<0.05). In the fructose group, placental mRNA and protein expression of nuclear factor erythroid 2-related factor 2 was markedly downregulated and kelch-like ECH-associated protein 1 was significantly upregulated (all p<0.05). In conclusion, high-fructose consumption during pregnancy drives augmented oxidative stress in rats. Placental insufficiency under oxidative stress contributes to asymmetrical fetal growth restriction.

Food consumption and mild cognitive impairment in Qingdao rural elderly: A cross-sectional study.

BACKGROUND AND OBJECTIVES: Diet plays a crucial role in cognition. Mild cognitive impairment has a high prevalence in rural elderly people. However, few studies have investigated the relationship between diet and mild cognitive impairment among rural elderly people in China. The study evaluated the association between diet and the risk of mild cognitive impairment among them. METHODS AND STUDY DESIGN: In this cross-sectional study, we enrolled 1262 participants (≥65 years) living in rural Qingdao, China. Cognitive function was assessed using the Mini-Mental State Examination, and dietary consumption was measured using a food frequency questionnaire. Logistic regression models were used to assess the associations. RESULTS: In all, 315 (25%) participants had mild cognitive impairment. The weekly frequency of food consumption was lower in the mild cognitive impairment group than in the no mild cognitive impairment group. After adjusting for covariates, compared with participants who consumed never/less than once a week, daily consumption of coarse cereals (OR: 0.64, 95% CI: 0.44-0.91), potatoes (OR: 0.54, 95% CI: 0.34-0.87), fruits (OR: 0.49, 95% CI: 0.35-0.69), livestock and poultry meat (OR: 0.66, 95% CI: 0.44-0.99), eggs (OR: 0.67, 95% CI: 0.47-0.97), and nuts (OR: 0.47, 95% CI: 0.28-0.80) was inversely associated with mild cognitive impairment (all p<0.05). CONCLUSIONS: Higher dietary diversity and more frequent consumption of coarse cereals, potatoes, fruits, livestock and poultry meat, eggs, and nuts were associated with a lower risk of mild cognitive impairment. Elderly people should develop healthy dietary habits to prevent or delay cognitive decline.

Integrative nomogram of CT imaging, clinical, and hematological features for survival prediction of patients with locally advanced non-small cell lung cancer.

OBJECTIVES: To determine the integrative value of clinical, hematological, and computed tomography (CT) radiomic features in survival prediction for locally advanced non-small cell lung cancer (LA-NSCLC) patients. METHODS: Radiomic features and clinical and hematological features of 118 LA-NSCLC cases were firstly extracted and analyzed in this study. Then, stable and prognostic radiomic features were automatically selected using the consensus clustering method with either Cox proportional hazard (CPH) model or random survival forest (RSF) analysis. Predictive radiomic, clinical, and hematological parameters were subsequently fitted into a final prognostic model using both the CPH model and the RSF model. A multimodality nomogram was then established from the fitting model and was cross-validated. Finally, calibration curves were generated with the predicted versus actual survival status. RESULTS: Radiomic features selected by clustering combined with CPH were found to be more predictive, with a C-index of 0.699 in comparison to 0.648 by clustering combined with RSF. Based on multivariate CPH model, our integrative nomogram achieved a C-index of 0.792 and retained 0.743 in the cross-validation analysis, outperforming radiomic, clinical, or hematological model alone. The calibration curve showed agreement between predicted and actual values for the 1-year and 2-year survival prediction. Interestingly, the selected important radiomic features were significantly correlated with levels of platelet, platelet/lymphocyte ratio (PLR), and lymphocyte/monocyte ratio (LMR) (p values all < 0.05). CONCLUSIONS: The integrative nomogram incorporated CT radiomic, clinical, and hematological features improved survival prediction in LA-NSCLC patients, which would offer a feasible and practical reference for individualized management of these patients. KEY POINTS: • An integrative nomogram incorporated CT radiomic, clinical, and hematological features was constructed and cross-validated to predict prognosis of LA-NSCLC patients. • The integrative nomogram outperformed radiomic, clinical, or hematological model alone. • This nomogram has value to permit non-invasive, comprehensive, and dynamical evaluation of the phenotypes of LA-NSCLC and can provide a feasible and practical reference for individualized management of LA-NSCLC patients.

[Lung nodule segmentation based on fuzzy c-means clustering and improved random walk algorithm].

Accurate segmentation of pulmonary nodules is an important basis for doctors to determine lung cancer. Aiming at the problem of incorrect segmentation of pulmonary nodules, especially the problem that it is difficult to separate adhesive pulmonary nodules connected with chest wall or blood vessels, an improved random walk method is proposed to segment difficult pulmonary nodules accurately in this paper. The innovation of this paper is to introduce geodesic distance to redefine the weights in random walk combining the coordinates of the nodes and seed points in the image with the space distance. The improved algorithm is used to achieve the accurate segmentation of pulmonary nodules. The computed tomography (CT) images of 17 patients with different types of pulmonary nodules were selected for segmentation experiments. The experimental results are compared with the traditional random walk method and those of several literatures. Experiments show that the proposed method has good accuracy in the segmentation of pulmonary nodule, and the accuracy can reach more than 88% with segmentation time is less than 4 seconds. The results could be used to assist doctors in the diagnosis of benign and malignant pulmonary nodules and improve clinical efficiency.

Association of gout and depression: A systematic review and meta-analysis.

OBJECTIVE: Several studies have shown that gout is associated with depression symptoms. In this study, a systematic review and meta-analysis was performed to explore the relationship between gout and depression. METHODS: Published articles were identified through a comprehensive review of PUBMED and EMBASE. Data from studies reporting relative risks, odds ratios, or hazard ratios comparing the risk of depression among participants who had gout versus those without gout were analyzed. A random-effect model was used to calculate pooled odds ratios and 95% confident intervals (CI). RESULTS: Seven studies, which included 411 745 participants, aligned with our inclusion criteria and were included in the meta-analysis. Pooled analysis showed an association between gout and depression, with an odds ratio of 1.19 (95%CI, 1.11, 1.29; I2  = 60.2%). Subgroup-analysis adjusted (or not) by study type or study quality showed a statistically significant association of gout and depression in all subgroups. Sensitivity analysis by 1-study removed analysis, excluding articles of self-reported gout assessment or male-only, confirmed the robustness of our results. CONCLUSION: Our meta-analysis demonstrates a positive association between gout and depression. Further large-scale prospective cohort studies are needed to investigate the causality between gout and depression.

[Analysis of serum ferritin and high sensitive C reactive protein in patients with gout].

OBJECTIVE: To analyze the relationship between serum ferritin(SF) level and high sensitive C reactive protein( hs-CRP) in men and the risk of gout. METHODS: We chosed 600 male patients diagnosed with gout as gout group, 600 male patients with hyperuricemia were diagnosed as hyperuricemia group, and randomly selected 600 cases of the same period of male health examination as the control group. The detection information of physical examination and related indicators of three groups were collected, such as height, weight, serum ferritin, high sensitive C reactive protein, uric acid( UA), fasting blood glucose( FPG), triglyceride(TG), total cholesterol( TC) and so on. RESULTS: Serum ferritin( SF) higher than that of hyperuricemia group 114. 45 µg/L( P<0. 05)and the control group 76. 02 µg/L( P<0. 05), while the level of hs-CRP in gout patients up to 0. 3 mg/dL, was significantly higher than that 0. 13 mg/dL in hyperuricemia group and 0. 09 mg/dL in control group( all P<0. 05). After adjusting for BMI, TG, TC, FPG and UA five confounding factors, SF was positively correlated with hs-CRP levels in the hyperuricemia group and the gout group, while there was no association between SF and hs-CRP levels in the control group. The multivariate logistic regression analysis showed that SF( ≥ 69. 01 µg/L) had significantly increased risk of HUA, after adjusting for BMI, TG, TC, FPG and UA five confounding factors, the high level of SF( ≥155. 78µg/L) had significantly increased risk of gout, with OR of 2. 678( 95% CI 1. 484-4. 833), and higher levels of hs-CRP( > 0. 9 mg/dL) was also a risk factor of gout, with OR of 3. 104( 95% CI 1. 727-5. 580). However, SF and hs-CRP were not risk factors of hyperuricemia. CONCLUSION: Serum ferritin level and high sensitive C reactive protein levels are significantly elevated in patients with gout. It is revealed that hs-CRP, SF may be involved in the pathogenesis of gout patients.

Maternal vitamin D deficiency during pregnancy results in insulin resistance in rat offspring, which is associated with inflammation and Iκbα methylation.

AIMS/HYPOTHESIS: We aimed to investigate the impact of maternal vitamin D deficiency during pregnancy on insulin resistance in male offspring and examine its mechanism. METHODS: Pregnant Sprague-Dawley rats were maintained on a vitamin-D-free diet with ultraviolet-free light during pregnancy (early-VDD group). Insulin resistance in the male offspring was assessed by HOMA-IR, OGTT and euglycaemic clamp. NEFA, oxidative stress and inflammation levels were estimated as risk factors for insulin resistance. DNA methylation was examined by bisulfate sequencing PCR analysis. Luciferase reporter assay was performed to validate the effect of DNA methylation. RESULTS: The offspring in the early-VDD group had significantly higher fasting insulin and HOMA-IR levels, markedly reduced glucose tolerance and significantly lower tissue sensitivity to exogenous insulin at 16 weeks (all p < 0.05) compared with control offspring. Significantly higher serum and liver IL-1ß, IL-6, IL-8 and TNF-α concentrations were observed in the offspring of the early-VDD group at 0, 3, 8 and 16 weeks. Expression of hepatic Iκbα (also known as Nfkbia) mRNA and nuclear factor κB inhibitor α (IκBα) protein was persistently lower in the early-VDD offspring at all time points, and their hepatic Iκbα methylation levels at the cytosine phosphate guanine site +331 were significantly higher at 0 and 16 weeks (all p < 0.01). Methylation at Iκbα first exon +331 markedly decreased the luciferase activity (p < 0.05). CONCLUSIONS/INTERPRETATION: Maternal vitamin D deficiency during pregnancy results in insulin resistance in the offspring, which is associated with persistently increased inflammation. Persistently decreased Iκbα expression, potentially caused by changes in Iκbα methylation, plays an important role in persistent inflammation.

MCPL: Multi-modal Collaborative Prompt Learning for Medical Vision-Language Model.

Multi-modal prompt learning is a high-performance and cost-effective learning paradigm, which learns text as well as image prompts to tune pre-trained vision-language (V-L) models like CLIP for adapting multiple downstream tasks. However, recent methods typically treat text and image prompts as independent components without considering the dependency between prompts. Moreover, extending multi-modal prompt learning into the medical field poses challenges due to a significant gap between general- and medical-domain data. To this end, we propose a Multi-modal Collaborative Prompt Learning (MCPL) pipeline to tune a frozen V-L model for aligning medical text-image representations, thereby achieving medical downstream tasks. We first construct the anatomy-pathology (AP) prompt for multi-modal prompting jointly with text and image prompts. The AP prompt introduces instance-level anatomy and pathology information, thereby making a V-L model better comprehend medical reports and images. Next, we propose graph-guided prompt collaboration module (GPCM), which explicitly establishes multi-way couplings between the AP, text, and image prompts, enabling collaborative multi-modal prompt producing and updating for more effective prompting. Finally, we develop a novel prompt configuration scheme, which attaches the AP prompt to the query and key, and the text/image prompt to the value in self-attention layers for improving the interpretability of multi-modal prompts. Extensive experiments on numerous medical classification and object detection datasets show that the proposed pipeline achieves excellent effectiveness and generalization. Compared with state-of-the-art prompt learning methods, MCPL provides a more reliable multi-modal prompt paradigm for reducing tuning costs of V-L models on medical downstream tasks. Our code: https://github.com/CUHK-AIM-Group/MCPL.

MGIML: Cancer Grading With Incomplete Radiology-Pathology Data via Memory Learning and Gradient Homogenization.

Taking advantage of multi-modal radiology-pathology data with complementary clinical information for cancer grading is helpful for doctors to improve diagnosis efficiency and accuracy. However, radiology and pathology data have distinct acquisition difficulties and costs, which leads to incomplete-modality data being common in applications. In this work, we propose a Memory- and Gradient-guided Incomplete Modal-modal Learning (MGIML) framework for cancer grading with incomplete radiology-pathology data. Firstly, to remedy missing-modality information, we propose a Memory-driven Hetero-modality Complement (MH-Complete) scheme, which constructs modal-specific memory banks constrained by a coarse-grained memory boosting (CMB) loss to record generic radiology and pathology feature patterns, and develops a cross-modal memory reading strategy enhanced by a fine-grained memory consistency (FMC) loss to take missing-modality information from well-stored memories. Secondly, as gradient conflicts exist between missing-modality situations, we propose a Rotation-driven Gradient Homogenization (RG-Homogenize) scheme, which estimates instance-specific rotation matrices to smoothly change the feature-level gradient directions, and computes confidence-guided homogenization weights to dynamically balance gradient magnitudes. By simultaneously mitigating gradient direction and magnitude conflicts, this scheme well avoids the negative transfer and optimization imbalance problems. Extensive experiments on CPTAC-UCEC and CPTAC-PDA datasets show that the proposed MGIML framework performs favorably against state-of-the-art multi-modal methods on missing-modality situations.

Folic Acid Rescues Dopaminergic Neurons in MPTP-Induced Mice by Inhibiting the NLRP3 Inflammasome and Ameliorating Mitochondrial Impairment.

Parkinson's disease (PD) is marked by the degeneration of dopaminergic neurons of the substantia nigra (SN), with neuroinflammation and mitochondrial dysfunction being key contributors. The neuroprotective potential of folic acid (FA) in the dopaminergic system of PD was assessed in a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced mouse model. MPTP (20 mg/kg of body weight) was administered to C57BL/6J mice to simulate PD symptoms followed by FA treatment (5 mg/kg of body weight). Behavioral tests, pole, rotarod, and open-field tests, evaluated motor function, while immunohistochemistry, ELISA, RT-qPCR, and Western blotting quantified neuroinflammation, oxidative stress markers, and mitochondrial function. FA supplementation considerably improved motor performance, reduced homocysteine levels and mitigated oxidative damage in the SN. The FA-attenuated activation of the NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome lessened glial cell activity and reduced neuroinflammation. At the molecular level, FA reduced DNA damage, downregulated phosphorylated p53, and induced the expression of peroxisome proliferator-activated receptor α coactivator 1α (PGC-1α), enhancing mitochondrial function. Therefore, FA exerts neuroprotection in MPTP-induced PD by inhibiting neuroinflammation via NLRP3 inflammasome suppression and promoting mitochondrial integrity through the p53-PGC-1α pathway. Notable limitations of our study include its reliance on a single animal model and the incompletely elucidated mechanisms underlying the impact of FA on mitochondrial dynamics. Future investigations will explore the clinical utility of FA and its molecular mechanisms, further advancing it as a potential therapeutic for managing and delaying the progression of PD.

Bifidobacterium animalis subsp. lactis F1-7 Alleviates Lipid Accumulation in Atherosclerotic Mice via Modulating Bile Acid Metabolites to Downregulate Intestinal FXR.

The dysfunction of intestinal microbiota and bile acid metabolism is related to the pathogenesis of atherosclerosis. This study we explored the mechanism of Bifidobacterium animalis subsp. lactis F1-7 (Bif. animalis F1-7), improving atherosclerosis by regulating the bile acid metabolism and intestinal microbiota in the ApoE-/- mice. The Bif. animalis F1-7 effectively reduced aortic plaque accumulation and improved the serum and liver lipid levels in atherosclerotic mice. The untargeted metabolomics revealed that Bif. animalis F1-7 reduced the glycine-conjugated bile acids and the levels of differential metabolite lithocholic acid (LCA) significantly. Downregulation of LCA decreased the intestinal levels of the farnesoid X-activated receptor (FXR) and regulated the bile acid metabolism through the FXR/FGF15/CYP7A1 pathway. Furthermore, the 16srRNA gene sequencing analysis revealed that structural changes in intestinal microbiota with an increase in the abundance of Bifidobacterium, Lactobacillus, Faecalibaculum, Desulfovibrio, and a decrease in Dubosiella, Clostridium_sensu_stricto_1, and Turicibacter following the Bif. animalis F1-7 intervention. Correlation analysis showed that the changes in intestinal microbiota mentioned above were significantly correlated with bile acid metabolism in atherosclerotic mice. In conclusion, this study sheds light on the mechanisms by which Bif. animalis F1-7 regulates atherosclerosis.

MHD-Net: Memory-Aware Hetero-Modal Distillation Network for Thymic Epithelial Tumor Typing With Missing Pathology Modality.

Fusing multi-modal radiology and pathology data with complementary information can improve the accuracy of tumor typing. However, collecting pathology data is difficult since it is high-cost and sometimes only obtainable after the surgery, which limits the application of multi-modal methods in diagnosis. To address this problem, we propose comprehensively learning multi-modal radiology-pathology data in training, and only using uni-modal radiology data in testing. Concretely, a Memory-aware Hetero-modal Distillation Network (MHD-Net) is proposed, which can distill well-learned multi-modal knowledge with the assistance of memory from the teacher to the student. In the teacher, to tackle the challenge in hetero-modal feature fusion, we propose a novel spatial-differentiated hetero-modal fusion module (SHFM) that models spatial-specific tumor information correlations across modalities. As only radiology data is accessible to the student, we store pathology features in the proposed contrast-boosted typing memory module (CTMM) that achieves type-wise memory updating and stage-wise contrastive memory boosting to ensure the effectiveness and generalization of memory items. In the student, to improve the cross-modal distillation, we propose a multi-stage memory-aware distillation (MMD) scheme that reads memory-aware pathology features from CTMM to remedy missing modal-specific information. Furthermore, we construct a Radiology-Pathology Thymic Epithelial Tumor (RPTET) dataset containing paired CT and WSI images with annotations. Experiments on the RPTET and CPTAC-LUAD datasets demonstrate that MHD-Net significantly improves tumor typing and outperforms existing multi-modal methods on missing modality situations.

Fucoidan Improves D-Galactose-Induced Cognitive Dysfunction by Promoting Mitochondrial Biogenesis and Maintaining Gut Microbiome Homeostasis.

Recent studies have indicated that fucoidan has the potential to improve cognitive impairment. The objective of this study was to demonstrate the protective effect and possible mechanisms of fucoidan in D-galactose (D-gal)-induced cognitive dysfunction. Sprague Dawley rats were injected with D-galactose (200 mg/kg, sc) and administrated with fucoidan (100 mg/kg or 200 mg/kg, ig) for 8 weeks. Our results suggested that fucoidan significantly ameliorated cognitive impairment in D-gal-exposed rats and reversed histopathological changes in the hippocampus. Fucoidan reduced D-gal-induced oxidative stress, declined the inflammation level and improved mitochondrial dysfunction in hippocampal. Fucoidan promoted mitochondrial biogenesis by regulating the PGC-1α/NRF1/TFAM pathway, thereby improving D-gal-induced mitochondrial dysfunction. The regulation effect of fucoidan on PGC-1α is linked to the upstream protein of APN/AMPK/SIRT1. Additionally, the neuroprotective action of fucoidan could be related to maintaining intestinal flora homeostasis with up-regulation of Bacteroidota, Muribaculaceae and Akkermansia and down-regulation of Firmicutes. In summary, fucoidan may be a natural, promising candidate active ingredient for age-related cognitive impairment interventions.

A Healthy, Low-Carbohydrate Diet During Pregnancy Is Associated With a Reduced Risk of Gestational Diabetes Mellitus.

CONTEXT: Evidence on the associations of low-carbohydrate diet (LCD) during pregnancy with gestational diabetes mellitus (GDM) has been limited and inconsistent. OBJECTIVE: We aimed to prospectively evaluate the risk of GDM associated with the LCD considering the quality of macronutrients. METHODS: All participants were from a prospective cohort in Wuhan, China. The overall, healthy LCD (emphasizing low-quality carbohydrates, plant protein, and unsaturated fat), and unhealthy LCD (emphasizing high-quality carbohydrates, animal protein, and saturated fat) scores were calculated according to the percentage of energy intake from carbohydrates, protein, and fat. GDM was screened by a 75-g oral glucose tolerance test between 24 and 28 weeks. Poisson regression models were used to calculate relative risks (RRs) and 95% CIs. RESULTS: Of 2337 pregnant women, 257 (11.0%) were diagnosed with GDM. Overall LCD score was not associated with risk of GDM, but the healthy and unhealthy LCD scores were associated with the risk of GDM. The multivariable-adjusted RRs (95% CI) were 0.68 (0.49-0.94) and 1.52 (1.11-2.08) for healthy and unhealthy LCD scores comparing the highest with the lowest quartile. Substituting high-quality carbohydrates for low-quality carbohydrates and animal protein, and substituting unsaturated fat for saturated fat, were associated with a 13% to 29% lower risk of GDM. CONCLUSION: A healthy LCD during pregnancy characterized by high-quality carbohydrates, plant protein, and unsaturated fat was associated with a lower risk of GDM, whereas an unhealthy LCD consisting of low-quality carbohydrates, animal protein, and saturated fat was associated with a higher risk of GDM.