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Acute kidney injury (AKI) and chronic kidney disease (CKD) are posing great threats to global health within this century. Studies have suggested that estrogen and estrogen receptors (ERs) play important roles in many physiological processes in the kidney. For instance, they are crucial in maintaining mitochondrial homeostasis and modulating endothelin-1 (ET-1) system in the kidney. Estrogen takes part in the kidney repair and regeneration via its receptors. Estrogen also participates in the regulation of phosphorus homeostasis via its receptors in the proximal tubule. The ERα polymorphisms have been associated with the susceptibilities and outcomes of several renal diseases. As a consequence, the altered or dysregulated estrogen/ERs signaling pathways may contribute to a variety of kidney diseases, including various causes-induced AKI, diabetic kidney disease (DKD), lupus nephritis (LN), IgA nephropathy (IgAN), CKD complications, etc. Experimental and clinical studies have shown that targeting estrogen/ERs signaling pathways might have protective effects against certain renal disorders. However, many unsolved problems still exist in knowledge regarding the roles of estrogen and ERs in distinct kidney diseases. Further research is needed to shed light on this area and to enable the discovery of pathway-specific therapies for kidney diseases.

Antagonistic antibodies targeting the inhibitory immune-checkpoint receptor PD-1 or its ligand PD-L1 are used to treat a wide range of cancer types and can substantially improve patient survival. Nevertheless, strategies to overcome intrinsic and acquired resistance are required to respectively increase response rates and durations. PD-L1 is often upregulated in various malignancies, and emerging evidence suggests numerous underlying mechanisms involving distinct oncogenic signalling pathways. Thus, specific small-molecule inhibitors have the potential to simultaneously suppress not only a key oncogenic signalling pathway but also PD-L1 expression and/or activity in particular cancers, thereby presenting attractive candidate drugs for combination with existing immune-checkpoint inhibitors and/or other targeted agents. Herein, we summarize advances in understanding the mechanisms regulating PD-L1 expression at the transcriptional, post-transcriptional, translational and post-translational levels in cancers. We describe the roles of the diverse post-translational modifications of PD-L1, including phosphorylation, palmitoylation, glycosylation, acetylation and ubiquitination. Moreover, we discuss the potential use of small-molecule agents to modulate these mechanisms as well as of predictive biomarkers to stratify patients for optimal treatment, and provide our perspective on potential therapeutic strategies to circumvent resistance to conventional anti-PD-1/PD-L1 antibodies.Antibodies targeting PD-1 or its ligand PD-L1 have revolutionized cancer therapy. Increased understanding of the mechanisms regulating PD-L1 has revealed links with several important oncogenic signalling pathways. Herein, the authors review the transcriptional, post-transcriptional and translational regulation of PD-L1 expression in cancers as well as the diverse post-translational modifications, including phosphorylation, palmitoylation, glycosylation, acetylation and ubiquitination, that affect PD-L1 stability and activity. They also discuss the possibility to simultaneously target key oncogenic pathways and modulate PD-L1 expression using small-molecule agents, which have potential advantages over or might synergize with anti-PD-1/PD-L1 antibodies.

Whether nonalcoholic fatty liver disease (NAFLD) is associated with an increased risk of mortality remains controversial. The present study aimed to clarify this issue. A systematic search of PubMed and Embase was conducted through October 2018. Studies providing risk estimates of NAFLD and mortality were included. A random-effects model was employed to calculate summary risk estimates. Subgroup analyses were performed to identify potential effect modifiers. Fourteen studies, involving 498501 subjects and 24234 deaths, were included. Patients with NAFLD were found to be at an elevated risk of all-cause mortality compared with those without [hazard ratio (HR) = 1.34; 95% confidence interval (CI) 1.17–1.54)]. The significantly positive association between NAFLD and all-cause mortality could not be modified by age, sex, follow-up duration, and adjustment for body mass index, diabetes, smoking or hypertension (all P interaction  > 0.05), and remained in sensitivity analyses. No significant associations of NAFLD with CVD (HR = 1.13; 95% CI 0.92–1.38) and cancer (HR = 1.05; 95% CI 0.89–1.25) mortality were found. In conclusion, NAFLD is a predictor of increased all-cause mortality but not CVD and cancer mortality. These findings have important implications for decision making in public health and clinical practice, and highlight the urgency of developing effective treatments for NAFLD.

Transforming growth factor β (TGF-β) is a secreted cytokine that regulates cell proliferation, migration, and the differentiation of a plethora of different cell types. Consistent with these findings, TGF-β plays a key role in controlling embryogenic development, inflammation, and tissue repair, as well as in maintaining adult tissue homeostasis. TGF-β elicits a broad range of context-dependent cellular responses, and consequently, alterations in TGF-β signaling have been implicated in many diseases, including cancer. During the early stages of tumorigenesis, TGF-β acts as a tumor suppressor by inducing cytostasis and the apoptosis of normal and premalignant cells. However, at later stages, when cancer cells have acquired oncogenic mutations and/or have lost tumor suppressor gene function, cells are resistant to TGF-β-induced growth arrest, and TGF-β functions as a tumor promotor by stimulating tumor cells to undergo the so-called epithelial-mesenchymal transition (EMT). The latter leads to metastasis and chemotherapy resistance. TGF-β further supports cancer growth and progression by activating tumor angiogenesis and cancer-associated fibroblasts and enabling the tumor to evade inhibitory immune responses. In this review, we will consider the role of TGF-β signaling in cell cycle arrest, apoptosis, EMT and cancer cell metastasis. In particular, we will highlight recent insights into the multistep and dynamically controlled process of TGF-β-induced EMT and the functions of miRNAs and long noncoding RNAs in this process. Finally, we will discuss how these new mechanistic insights might be exploited to develop novel therapeutic interventions.

Backscattering suppression in silicon-on-insulator (SOI) is one of the central issues to reduce energy loss and signal distortion, enabling for capability improvement of modern information processing systems. Valley physics provides an intriguing way for robust information transfer and unidirectional coupling in topological nanophotonics. Here we realize topological transport in a SOI valley photonic crystal slab. Localized Berry curvature near zone corners guarantees the existence of valley-dependent edge states below light cone, maintaining in-plane robustness and light confinement simultaneously. Topologically robust transport at telecommunication is observed along two sharp-bend interfaces in subwavelength scale, showing flat-top high transmission of ~10% bandwidth. Topological photonic routing is achieved in a bearded-stack interface, due to unidirectional excitation of valley-chirality-locked edge state from the phase vortex of a nanoscale microdisk. These findings show the prototype of robustly integrated devices, and open a new door towards the observation of non-trivial states even in non-Hermitian systems. Backscattering is one of the major factors that limit the performance of integrated nanophotonics. Here, He et al. realize topologically protected, robust and unidirectional coupling as well as optical transport on a silicon-on-insulator platform by exploiting the valley degree of freedom.

Aims The dysregulation of TGF‐β signaling is a crucial pathophysiological process in tumorigenesis and progression. LncRNAs have diverse biological functions and are significant participants in the regulation of tumor signaling pathways. However, the clinical value of lncRNAs related to TGF‐β signaling in glioma is currently unclear. Methods Data on glioma's RNA‐seq transcriptome, somatic mutation, DNA methylation data, and clinicopathological information were derived from the CGGA and TCGA databases. A prognostic lncRNA signature was constructed by Cox and LASSO regression analyses. TIMER2.0 database was utilized to deduce immune infiltration characteristics. “ELMER v.2” was used to reconstruct TF‐methylation‐gene regulatory network. Immunotherapy and chemotherapy response predictions were implemented by the TIDE algorithm and GDSC database, respectively. In vitro and in vivo experiments were conducted to verify the results and clarify the regulatory mechanism of lncRNA. Results In glioma, a TGF‐β signaling‐related 15‐lncRNA signature was constructed, including AC010173.1, HOXA‐AS2, AC074286.1, AL592424.1, DRAIC, HOXC13‐AS, AC007938.1, AC010729.1, AC013472.3, AC093895.1, AC131097.4, AL606970.4, HOXC‐AS1, AGAP2‐AS1, and AC002456.1. This signature proved to be a reliable prognostic tool, with high risk indicating an unfavorable prognosis and being linked to malignant clinicopathological and genomic mutation traits. Risk levels were associated with different immune infiltration landscapes, where high risk was indicative of high levels of macrophage infiltration. In addition, high risk also suggested better immunotherapy and chemotherapy response. cg05987823 was an important methylation site in glioma progression, and AP‐1 transcription factor family participated in the regulation of signature lncRNA expression. AGAP2‐AS1 knockdown in in vitro and in vivo experiments inhibited the proliferation, migration, and invasion of glioma cells, as well as the growth of glioma, by downregulating the expression levels of NF‐κB and ERK 1/2 in the TGF‐β signaling pathway. Conclusions A prognostic lncRNA signature of TGF‐β signaling was established in glioma, which can be used for prognostic judgment, immune infiltration status inference, and immunotherapy response prediction. AGAP2‐AS1 plays an important role in glioma progression. A TGF‐β signaling‐related lncRNA signature has been established in glioma, which can be used for prognostic judgment, immune infiltration status speculation, and immunotherapy response prediction. Furthermore, in vitro experiments confirmed that silencing of TGF‐β signaling‐related lncRNA could inhibit the proliferation of glioma cells. This study provides candidate biomarkers with clinical application value for glioma.

A tomato automatic detection method based on an improved YOLOv8s model is proposed to address the low automation level in tomato harvesting in agriculture. The proposed method provides technical support for the automatic harvesting and classification of tomatoes in agricultural production activities. The proposed method has three key components. Firstly, the depthwise separable convolution (DSConv) technique replaces the ordinary convolution, which reduces the computational complexity by generating a large number of feature maps with a small amount of calculation. Secondly, the dual-path attention gate module (DPAG) is designed to improve the model’s detection precision in complex environments by enhancing the network’s ability to distinguish between tomatoes and the background. Thirdly, the feature enhancement module (FEM) is added to highlight the target details, prevent the loss of effective features, and improve detection precision. We built, trained, and tested the tomato dataset, which included 3098 images and 3 classes. The proposed algorithm’s performance was evaluated by comparison with the SSD, faster R-CNN, YOLOv4, YOLOv5, and YOLOv7 algorithms. Precision, recall rate, and mAP (mean average precision) were used for evaluation. The test results show that the improved YOLOv8s network has a lower loss and 93.4% mAP on this dataset. This improvement is a 1.5% increase compared to before the improvement. The precision increased by 2%, and the recall rate increased by 0.8%. Moreover, the proposed algorithm significantly reduced the model size from 22 M to 16 M, while achieving a detection speed of 138.8 FPS, which satisfies the real-time detection requirement. The proposed method strikes a balance between model size and detection precision, enabling it to meet agriculture’s tomato detection requirements. The research model in this paper will provide technical support for a tomato picking robot to ensure the fast and accurate operation of the picking robot.

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease worldwide, characterized by progressive neuron degeneration or loss due to excessive accumulation of β-amyloid (Aβ) peptides, formation of neurofibrillary tangles (NFTs), and hyperphosphorylated tau. The treatment of AD has been only partially successful as the majority of the pharmacotherapies on the market may alleviate some of the symptoms. In the occurrence of AD, increasing attention has been paid to neurodegeneration, while the resident glial cells, like microglia are also observed. Microglia, a kind of crucial glial cells associated with the innate immune response, functions as double-edge sword role in CNS. They exert a beneficial or detrimental influence on the adjacent neurons through secretion of both pro-inflammatory cytokines as well as neurotrophic factors. In addition, their endocytosis of debris and toxic protein like Aβ and tau ensures homeostasis of the neuronal microenvironment. In this review, we will systematically summarize recent research regarding the roles of microglia in AD pathology and latest microglia-associated therapeutic targets mainly including pro-inflammatory genes, anti-inflammatory genes and phagocytosis at length, some of which are contradictory and controversial and warrant to further be investigated.

ChatGPT has promising applications in health care, but potential ethical issues need to be addressed proactively to prevent harm. ChatGPT presents potential ethical challenges from legal, humanistic, algorithmic, and informational perspectives. Legal ethics concerns arise from the unclear allocation of responsibility when patient harm occurs and from potential breaches of patient privacy due to data collection. Clear rules and legal boundaries are needed to properly allocate liability and protect users. Humanistic ethics concerns arise from the potential disruption of the physician-patient relationship, humanistic care, and issues of integrity. Overreliance on artificial intelligence (AI) can undermine compassion and erode trust. Transparency and disclosure of AI-generated content are critical to maintaining integrity. Algorithmic ethics raise concerns about algorithmic bias, responsibility, transparency and explainability, as well as validation and evaluation. Information ethics include data bias, validity, and effectiveness. Biased training data can lead to biased output, and overreliance on ChatGPT can reduce patient adherence and encourage self-diagnosis. Ensuring the accuracy, reliability, and validity of ChatGPT-generated content requires rigorous validation and ongoing updates based on clinical practice. To navigate the evolving ethical landscape of AI, AI in health care must adhere to the strictest ethical standards. Through comprehensive ethical guidelines, health care professionals can ensure the responsible use of ChatGPT, promote accurate and reliable information exchange, protect patient privacy, and empower patients to make informed decisions about their health care.