The LIDPAD Mouse Model Captures the Multisystem Interactions and Extrahepatic Complications in MASLD.

Metabolic dysfunction-associated steatotic liver disease (MASLD) represents an impending global health challenge. Current management strategies often face setbacks, emphasizing the need for preclinical models that faithfully mimic the human disease and its comorbidities. The liver disease progression aggravation diet (LIDPAD), a diet-induced murine model, extensively characterized under thermoneutral conditions and refined diets is introduced to ensure reproducibility and minimize species differences. LIDPAD recapitulates key phenotypic, genetic, and metabolic hallmarks of human MASLD, including multiorgan communications, and disease progression within 4 to 16 weeks. These findings reveal gut-liver dysregulation as an early event and compensatory pancreatic islet hyperplasia, underscoring the gut-pancreas axis in MASLD pathogenesis. A robust computational pipeline is also detailed for transcriptomic-guided disease staging, validated against multiple harmonized human hepatic transcriptomic datasets, thereby enabling comparative studies between human and mouse models. This approach underscores the remarkable similarity of the LIDPAD model to human MASLD. The LIDPAD model fidelity to human MASLD is further confirmed by its responsiveness to dietary interventions, with improvements in metabolic profiles, liver histopathology, hepatic transcriptomes, and gut microbial diversity. These results, alongside the closely aligned changing disease-associated molecular signatures between the human MASLD and LIDPAD model, affirm the model's relevance and potential for driving therapeutic development.

A missing jigsaw within the hygiene hypothesis: Low-dose bisphenol A exposure attenuates lipopolysaccharide-induced asthma protection.

The rising occurrence of allergic asthma in early life across industrialized countries suggests that environmental factors play a crucial role in determining asthma susceptibility and severity. While prior exposure to microbial lipopolysaccharides (LPSs) has been found to offer protection against allergic asthma, infants residing in urban environments are increasingly exposed to environmental pollutants. Utilizing limulus lysate test screens and virtual screening models, we identified pollutants that can modulate LPS bioactivity. This investigation revealed that bisphenol A (BPA), a chemical commonly used in numerous household items and previously implicated in obesity and cancer, effectively neutralizes LPS. In-depth mechanistic analyses showed that BPA specifically binds to the lipid A component of LPS, leading to inactivation. This interaction eliminates the immunostimulatory activity of LPS, making mice more susceptible to house dust mite (HDM)-induced allergic asthma. BPA reactivates lung epithelial cells, consequently amplifying type 2 responses to HDMs in dendritic cells. This chemical interplay provides new insights into the pathophysiology of asthma in relation to human exposure. Understanding the intricate relationships between environmental chemicals and microbial antigens, as well as their impacts on innate immunity, is critical for the development of intervention strategies to address immune disorders resulting from urbanization.

Systematic review of deep learning image analyses for the diagnosis and monitoring of skin disease.

Skin diseases affect one-third of the global population, posing a major healthcare burden. Deep learning may optimise healthcare workflows through processing skin images via neural networks to make predictions. A focus of deep learning research is skin lesion triage to detect cancer, but this may not translate to the wider scope of >2000 other skin diseases. We searched for studies applying deep learning to skin images, excluding benign/malignant lesions (1/1/2000-23/6/2022, PROSPERO CRD42022309935). The primary outcome was accuracy of deep learning algorithms in disease diagnosis or severity assessment. We modified QUADAS-2 for quality assessment. Of 13,857 references identified, 64 were included. The most studied diseases were acne, psoriasis, eczema, rosacea, vitiligo, urticaria. Deep learning algorithms had high specificity and variable sensitivity in diagnosing these conditions. Accuracy of algorithms in diagnosing acne (median 94%, IQR 86-98; n = 11), rosacea (94%, 90-97; n = 4), eczema (93%, 90-99; n = 9) and psoriasis (89%, 78-92; n = 8) was high. Accuracy for grading severity was highest for psoriasis (range 93-100%, n = 2), eczema (88%, n = 1), and acne (67-86%, n = 4). However, 59 (92%) studies had high risk-of-bias judgements and 62 (97%) had high-level applicability concerns. Only 12 (19%) reported participant ethnicity/skin type. Twenty-four (37.5%) evaluated the algorithm in an independent dataset, clinical setting or prospectively. These data indicate potential of deep learning image analysis in diagnosing and monitoring common skin diseases. Current research has important methodological/reporting limitations. Real-world, prospectively-acquired image datasets with external validation/testing will advance deep learning beyond the current experimental phase towards clinically-useful tools to mitigate rising health and cost impacts of skin disease.

YWHAG Deficiency Disrupts the EMT-Associated Network to Induce Oxidative Cell Death and Prevent Metastasis.

Metastasis involves epithelial-to-mesenchymal transition (EMT), a process that is regulated by complex gene networks, where their deliberate disruption may yield a promising outcome. However, little is known about mechanisms that coordinate these metastasis-associated networks. To address this gap, hub genes with broad engagement across various human cancers by analyzing the transcriptomes of different cancer cell types undergoing EMT are identified. The oncogenic signaling adaptor protein tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein gamma (YWHAG) is ranked top for its clinical relevance and impact. The cellular kinome and transcriptome data are surveyed to construct the regulome of YWHAG, revealing stress responses and metabolic processes during cancer EMT. It is demonstrated that a YWHAG-dependent cytoprotective mechanism in the regulome is embedded in EMT-associated networks to protect cancer cells from oxidative catastrophe through enhanced autophagy during EMT. YWHAG deficiency results in a rapid accumulation of reactive oxygen species (ROS), delayed EMT, and cell death. Tumor allografts show that metastasis potential and overall survival time are correlated with the YWHAG expression level of cancer cell lines. Metastasized tumors have higher expression of YWHAG and autophagy-related genes than primary tumors. Silencing YWHAG diminishes primary tumor volumes, prevents metastasis, and prolongs the median survival period of the mice.

Corrigendum: Modulated TRPC1 Expression Predicts Sensitivity of Breast Cancer to Doxorubicin and Magnetic Field Therapy: Segue Towards a Precision Medicine Approach.

[This corrects the article DOI: 10.3389/fonc.2021.783803.].

High Glucose Restraint of Acetylcholine-Induced Keratinocyte Epithelial-Mesenchymal Transition Is Mitigated by p38 Inhibition.

Non-neuronal acetylcholine (Ach) plays important roles in various aspects of cell biology and homeostasis outside the neural system. Keratinocytes (KCs) have a functional cholinergic mechanism, suggesting that they respond to Ach. However, the physiological role and mechanism by which Ach modulates wound KC behavior in both nondiabetic and diabetic conditions are unexplored. We found an enrichment in neurotransmitter-related pathways in microdissected-migrating nondiabetic and diabetic KCs. We showed that Ach upregulated TGFßRII through Src-extracellular signal‒regulated kinase 1/2 pathway to potentiate TGFß1-mediated epithelial‒mesenchymal transition in normoglycemic condition. Unexpectedly, KCs were nonresponsive to the elevated endogenous Ach in a hyperglycemic environment. We further showed that the activation of p38 MAPK in high glucose condition interferes with Src-extracellular signal‒regulated kinase 1/2 signaling, resulting in Ach resistance that could be rescued by inhibiting p38 MAPK. A better understanding of the cholinergic physiology in diabetic KCs could improve wound management and care. The finding suggests that mitigating the inhibitory effect of diabetic wound microenvironment has a direct clinical implication on the efficacy and safety of various wound healing agents to improve chronic diabetic wounds.

Modulated TRPC1 Expression Predicts Sensitivity of Breast Cancer to Doxorubicin and Magnetic Field Therapy: Segue Towards a Precision Medicine Approach.

Chemotherapy is the mainstream treatment modality for invasive breast cancer. Unfortunately, chemotherapy-associated adverse events can result in early termination of treatment. Paradoxical effects of chemotherapy are also sometimes observed, whereby prolonged exposure to high doses of chemotherapeutic agents results in malignant states resistant to chemotherapy. In this study, potential synergism between doxorubicin (DOX) and pulsed electromagnetic field (PEMF) therapy was investigated in: 1) MCF-7 and MDA-MB-231 cells in vitro; 2) MCF-7 tumors implanted onto a chicken chorioallantoic membrane (CAM) and; 3) human patient-derived and MCF-7 and MDA-MB-231 breast cancer xenografts implanted into NOD-SCID gamma (NSG) mice. In vivo, synergism was observed in patient-derived and breast cancer cell line xenograft mouse models, wherein PEMF exposure and DOX administration individually reduced tumor size and increased apoptosis and could be augmented by combined treatments. In the CAM xenograft model, DOX and PEMF exposure also synergistically reduced tumor size as well as reduced Transient Receptor Potential Canonical 1 (TRPC1) channel expression. In vitro, PEMF exposure alone impaired the survival of MCF-7 and MDA-MB-231 cells, but not that of non-malignant MCF10A breast cells; the selective vulnerability of breast cancer cells to PEMF exposure was corroborated in human tumor biopsy samples. Stable overexpression of TRPC1 enhanced the vulnerability of MCF-7 cells to both DOX and PEMF exposure and promoted proliferation, whereas TRPC1 genetic silencing reduced sensitivity to both DOX and PEMF treatments and mitigated proliferation. Chronic exposure to DOX depressed TRPC1 expression, proliferation, and responses to both PEMF exposure and DOX in a manner that was reversible upon removal of DOX. TRPC1 channel overexpression and silencing positively correlated with markers of epithelial-mesenchymal transition (EMT), including SLUG, SNAIL, VIMENTIN, and E-CADHERIN, indicating increased and decreased EMT, respectively. Finally, PEMF exposure was shown to attenuate the invasiveness of MCF-7 cells in correlation with TRPC1 expression. We thus demonstrate that the expression levels of TRPC1 consistently predicted breast cancer sensitivity to DOX and PEMF interventions and positively correlated to EMT status, providing an initial rationale for the use of PEMF-based therapies as an adjuvant to DOX chemotherapy for the treatment of breast cancers characterized by elevated TRPC1 expression levels.

PPARß/δ Agonism Upregulates Forkhead Box A2 to Reduce Inflammation in C2C12 Myoblasts and in Skeletal Muscle.

Daily activities expose muscles to innumerable impacts, causing accumulated tissue damage and inflammation that impairs muscle recovery and function, yet the mechanism modulating the inflammatory response in muscles remains unclear. Our study suggests that Forkhead box A2 (FoxA2), a pioneer transcription factor, has a predominant role in the inflammatory response during skeletal muscle injury. FoxA2 expression in skeletal muscle is upregulated by fatty acids and peroxisome proliferator-activated receptors (PPARs) but is refractory to insulin and glucocorticoids. Using PPARß/δ agonist GW501516 upregulates FoxA2, which in turn, attenuates the production of proinflammatory cytokines and reduces the infiltration of CD45+ immune cells in two mouse models of muscle inflammation, systemic LPS and intramuscular injection of carrageenan, which mimic localized exercise-induced inflammation. This reduced local inflammatory response limits tissue damage and restores muscle tetanic contraction. In line with these results, a deficiency in either PPARß/δ or FoxA2 diminishes the action of the PPARß/δ agonist GW501516 to suppress an aggravated inflammatory response. Our study suggests that FoxA2 in skeletal muscle helps maintain homeostasis, acting as a gatekeeper to maintain key inflammation parameters at the desired level upon injury. Therefore, it is conceivable that certain myositis disorders or other forms of painful musculoskeletal diseases may benefit from approaches that increase FoxA2 activity in skeletal muscle.

Exploration and Development of PPAR Modulators in Health and Disease: An Update of Clinical Evidence.

Peroxisome proliferator-activated receptors (PPARs) are nuclear receptors that govern the expression of genes responsible for energy metabolism, cellular development, and differentiation. Their crucial biological roles dictate the significance of PPAR-targeting synthetic ligands in medical research and drug discovery. Clinical implications of PPAR agonists span across a wide range of health conditions, including metabolic diseases, chronic inflammatory diseases, infections, autoimmune diseases, neurological and psychiatric disorders, and malignancies. In this review we aim to consolidate existing clinical evidence of PPAR modulators, highlighting their clinical prospects and challenges. Findings from clinical trials revealed that different agonists of the same PPAR subtype could present different safety profiles and clinical outcomes in a disease-dependent manner. Pemafibrate, due to its high selectivity, is likely to replace other PPARα agonists for dyslipidemia and cardiovascular diseases. PPARγ agonist pioglitazone showed tremendous promises in many non-metabolic disorders like chronic kidney disease, depression, inflammation, and autoimmune diseases. The clinical niche of PPARß/δ agonists is less well-explored. Interestingly, dual- or pan-PPAR agonists, namely chiglitazar, saroglitazar, elafibranor, and lanifibranor, are gaining momentum with their optimistic outcomes in many diseases including type 2 diabetes, dyslipidemia, non-alcoholic fatty liver disease, and primary biliary cholangitis. Notably, the preclinical and clinical development for PPAR antagonists remains unacceptably deficient. We anticipate the future design of better PPAR modulators with minimal off-target effects, high selectivity, superior bioavailability, and pharmacokinetics. This will open new possibilities for PPAR ligands in medicine.

Targeting metabolic flexibility via angiopoietin-like 4 protein sensitizes metastatic cancer cells to chemotherapy drugs.

Overcoming multidrug resistance has always been a major challenge in cancer treatment. Recent evidence suggested epithelial-mesenchymal transition plays a role in MDR, but the mechanism behind this link remains unclear. We found that the expression of multiple ABC transporters was elevated in concordance with an increased drug efflux in cancer cells during EMT. The metastasis-related angiopoietin-like 4 (ANGPTL4) elevates cellular ATP to transcriptionally upregulate ABC transporters expression via the Myc and NF-κB signaling pathways. ANGPTL4 deficiency reduced IC50 of anti-tumor drugs and enhanced apoptosis of cancer cells. In vivo suppression of ANGPTL4 led to higher accumulation of cisplatin-DNA adducts in primary and metastasized tumors, and a reduced metastatic tumor load. ANGPTL4 empowered cancer cells metabolic flexibility during EMT, securing ample cellular energy that fuels multiple ABC transporters to confer EMT-mediated chemoresistance. It suggests that metabolic strategies aimed at suppressing ABC transporters along with energy deprivation of EMT cancer cells may overcome drug resistance.

Improved ArtGAN for Conditional Synthesis of Natural Image and Artwork.

This paper proposes a series of new approaches to improve Generative Adversarial Network (GAN) for conditional image synthesis and we name the proposed model as "ArtGAN". One of the key innovation of ArtGAN is that, the gradient of the loss function w.r.t. the label (randomly assigned to each generated image) is back-propagated from the categorical discriminator to the generator. With the feedback from the label information, the generator is able to learn more efficiently and generate image with better quality. Inspired by recent works, an autoencoder is incorporated into the categorical discriminator for additional complementary information. Last but not least, we introduce a novel strategy to improve the image quality. In the experiments, we evaluate ArtGAN on CIFAR-10 and STL-10 via ablation studies. The empirical results showed that our proposed model outperforms the state-of-the-art results on CIFAR-10 in terms of Inception score. Qualitatively, we demonstrate that ArtGAN is able to generate plausible-looking images on Oxford-102 and CUB-200, as well as able to draw realistic artworks based on style, artist, and genre. The source code and models are available at: https://github.com/cs-chan/ArtGAN.