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As a common air pollutant, formaldehyde is widely present in nature, industrial production and consumer products. Endogenous formaldehyde is mainly produced through the oxidative deamination of methylamine catalysed by semicarbazide‐sensitive amine oxidase (SSAO) and is ubiquitous in human body fluids, tissues and cells. Vascular endothelial cells and smooth muscle cells are rich in this formaldehyde‐producing enzyme and are easily damaged owing to consequent cytotoxicity. Consistent with this, increasing evidence suggests that the cardiovascular system and stages of heart development are also susceptible to the harmful effects of formaldehyde. Exposure to formaldehyde from different sources can induce heart disease such as arrhythmia, myocardial infarction (MI), heart failure (HF) and atherosclerosis (AS). In particular, long‐term exposure to high concentrations of formaldehyde in pregnant women is more likely to affect embryonic development and cause heart malformations than long‐term exposure to low concentrations of formaldehyde. Specifically, the ability of mouse embryos to effect formaldehyde clearance is far lower than that of the rat embryos, more readily allowing its accumulation. Formaldehyde may also exert toxic effects on heart development by inducing oxidative stress and cardiomyocyte apoptosis. This review focuses on the current progress in understanding the influence and underlying mechanisms of formaldehyde on cardiovascular disease and heart development.

Tissue-resident macrophages play an important role in the local maintenance of homeostasis and immune surveillance. In the central nervous system (CNS), brain macrophages are anatomically divided into parenchymal microglia and non-parenchymal border-associated macrophages (BAMs). Among these immune cell populations, microglia have been well-studied for their roles during development as well as in health and disease. BAMs, mostly located in the choroid plexus, meningeal and perivascular spaces, are now gaining increased attention due to advancements in multi-omics technologies and genetic methodologies. Research on BAMs over the past decade has focused on their ontogeny, immunophenotypes, involvement in various CNS diseases, and potential as therapeutic targets. Unlike microglia, BAMs display mixed origins and distinct self-renewal capacity. BAMs are believed to regulate neuroimmune responses associated with brain barriers and contribute to immune-mediated neuropathology. Notably, BAMs have been observed to function in diverse cerebral pathologies, including Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, ischemic stroke, and gliomas. The elucidation of the heterogeneity and diverse functions of BAMs during homeostasis and neuroinflammation is mesmerizing, since it may shed light on the precision medicine that emphasizes deep insights into programming cues in the unique brain immune microenvironment. In this review, we delve into the latest findings on BAMs, covering aspects like their origins, self-renewal capacity, adaptability, and implications in different brain disorders.

In the paper, we compute the correlation functions in 2D N = (1 , 1) and N = (2 , 2) superconformal field theories with T T ¯ deformation up to the first order of the deformation in terms of perturbation theory. With the help of superconformal Ward identity in N = (1 , 1) and N = (2 , 2) theories and careful regularization, the correlation functions in the deformed theory can be obtained up to the first order perturbation. This study is the extension from previous bosonic T T ¯ deformation to the supersymmetric one.

We describe pLink 2, a search engine with higher speed and reliability for proteome-scale identification of cross-linked peptides. With a two-stage open search strategy facilitated by fragment indexing, pLink 2 is ~40 times faster than pLink 1 and 3~10 times faster than Kojak. Furthermore, using simulated datasets, synthetic datasets, 15 N metabolically labeled datasets, and entrapment databases, four analysis methods were designed to evaluate the credibility of ten state-of-the-art search engines. This systematic evaluation shows that pLink 2 outperforms these methods in precision and sensitivity, especially at proteome scales. Lastly, re-analysis of four published proteome-scale cross-linking datasets with pLink 2 required only a fraction of the time used by pLink 1, with up to 27% more cross-linked residue pairs identified. pLink 2 is therefore an efficient and reliable tool for cross-linking mass spectrometry analysis, and the systematic evaluation methods described here will be useful for future software development. The identification of cross-linked peptides at a proteome scale for interactome analyses represents a complex challenge. Here the authors report an efficient and reliable search engine pLink 2 for proteome-scale cross-linking mass spectrometry analyses, and demonstrate how to systematically evaluate the credibility of search engines.

A bstract In the holographic framework, we argue that the partial entanglement entropy (PEE) can be explicitly interpreted as the component flow flux in a locking bit thread configuration. By applying the locking theorem of bit threads, and constructing a concrete locking scheme, we obtain a set of uniquely determined component flow fluxes from this viewpoint, and successfully derive the PEE proposal and its generalized version in the multipartite cases. Moreover, from this perspective of bit threads, we also present a coherent explanation for the coincidence between the BPE (balanced partial entanglement)/EWCS (entanglement wedge cross section) duality proposed recently and the EoP (entanglement of purification)/EWCS duality. We also discuss the issues implied by this coincident between the idea of the PEE and the picture of locking thread configuration.

We report a combination of electrocatalysis and photoredox catalysis to perform selective C(sp 3 )–H arylation/alkylation of alkanes, in which a binary catalytic system based on earth-abundant iron and nickel is applied. Reaction selectivity between two-component C(sp 3 )–H arylation and three-component C(sp 3 )–H alkylation is tuned by modulating the applied current and light source. Importantly, an ultra-low anodic potential (~0.23 V vs. Ag/AgCl) is applied in this protocol, thus enabling compatibility with a variety of functional groups (>70 examples). The robustness of the method is further demonstrated on a preparative scale and applied to late-stage diversification of natural products and pharmaceutical derivatives. The combination of electrochemistry and photochemistry in the context of organic synthesis is in its infancy. Here, the authors report selective C(sp3)–H arylation/alkylation of alkanes, using Earth-abundant bimetallic transition metal catalysis, under photo- and electrochemical conditions.

This research delves into the application of Federated Learning (FL) models for detecting fraud across different financial bodies. FL facilitates decentralized training of models using local data, ensuring privacy, crucial for handling sensitive financial data. The comparison involves three machine learning models - Artificial Neural Networks (ANN), Random Forest (RF), and Convolutional Neural Networks (CNN) - to assess their efficacy in the FL context. While ANN and CNN demonstrate strong capacity in identifying complex fraud patterns, their communication efficiency and overfitting challenges are significant. In contrast, RF offers more robustness to Non-independent and Identically Distributed (non-IID) data and is less prone to overfitting, though it poses communication overhead issues. This paper also highlights the challenges of FL in fraud detection, including data heterogeneity, communication costs, and security risks. This paper proposed future research directions, emphasizing model personalization, communication optimization, and advanced privacy-preserving techniques. By addressing these challenges, FL can offer scalable, secure solutions for real-time fraud detection, ensuring the protection of sensitive financial data while enhancing detection accuracy across diverse data sources.

Major depressive disorder (MDD) is a common and disabling mental health condition; the currently available treatments for MDD are insufficient to meet clinical needs due to their limited efficacy and slow onset of action. Hypidone hydrochloride (YL-0919) is a sigma-1 receptor agonist and a novel fast-acting antidepressant that is currently under clinical development. To further understand the fast-acting antidepressant activity of YL-0919, this study focused on the role of 5-HTergic neurons in the dorsal raphe nucleus (DRN) in mice. Using fiber photometry to assess neural activity and two behavioral assays (tail suspension test and forced swimming test) to evaluate antidepressant-like activity. It was found that 3 or 7 days of YL-0919 treatment significantly activated serotonin (5-HT) neurons in the DRN and had significant antidepressant-like effects on mouse behaviors. Chemogenetic inhibition of 5-HTergic neurons in the DRN significantly blocked the antidepressant-like effect of YL-0919. In addition, YL-0919 treatment significantly increased the 5-HT levels in the prefrontal cortex (PFC). These changes were drastically different from those of the selective serotonin reuptake inhibitor (SSRI) fluoxetine, which suggested that the antidepressant-like effects of the two compounds were mechanistically different. Together, these results reveal a novel role of 5-HTergic neurons in the DRN in mediating the fast-acting antidepressant-like effects of YL-0919, revealing that these neurons are potential novel targets for the development of fast-acting antidepressants for the clinical management of MDD.

A bstract We propose a surface growth approach to reconstruct the bulk spacetime geometry, motivated by Huygens’ principle of wave propagation. We show that our formalism can be explicitly realized with the help of the surface/state correspondence and the one-shot entanglement distillation (OSED) method. We first construct a tensor network corresponding to a special surface growth picture with spherical symmetry and fractal feature using the OSED method and show that the resulting tensor network can be identified with the MERA-like tensor network, which gives a proof that the MERA-like tensor network is indeed a discretized version of the time slice of AdS spacetime, rather than just an analogy. Furthermore, we generalize the original OSED method to describe more general surface growth picture by using of the surface/state correspondence and the generalized RT formula, which leads to a more profound interpretation for the surface growth process and provides a concrete and intuitive way for the idea of entanglement wedge reconstruction.

Continental crust forms in magmatic arcs and transforms through collision, as seen in the Tibetan crust shaped by Neo‐Tethyan subduction and India‐Asia collision. We examine zircons from crustal granulite xenoliths using U‐Pb depth profiling to reveal a 220‐million‐year evolutionary history in southern Tibet. Our data provide age history consistent with the Gangdese magmatic rocks. From 100 Ma, our results show numerous age peaks linked to the arrival of the Indian continent, associated with fast convergence, slab rollback, and eventual slab breakoff. During the post‐collisional stage, the growth of zircon rims indicates a resurgence of metamorphism and anatexis, and contemporaneous shifts in Th/U ratios and (Dy/Yb)N values reflect an increase in crustal thickness. We suggest the capacity of zircon overgrowth to capture geological episodes during crustal evolution. In this case, granulite xenoliths from single areas through zircon depth profiling can offer substantial insights into the geological processes shaping the collisional orogen. Plain Language Summary The Earth's continental crust is built and altered through multi‐stage activity within collisional zones. The Tibetan Plateau is an example of how these forces shape large orogens, with its crust formed and modified over millions of years due to the collision between the Indian and Asian continents. In this study, we analyzed zircon from crustal granulite xenoliths brought to the surface in southern Tibet by the Miocene magmatism. Using the depth profiling method, we reconstruct the 220‐million‐year evolution of the Gangdese belt. Our results identified several major events in the region's history. These include intense magmatic activity during the Neo‐Tethyan subduction period and major tectonic shifts linked to the India‐Asia collision stages. During the later stage of the India‐Asia collision, the crust thickened and reheated, sparking renewed metamorphism and anatexis, as shown by changes in Th/U ratios and (Dy/Yb)N values. This study provides a clearer picture of how large‐scale collisions shape the Earth's crust over time. We can gain detailed insights into the processes that form and reshape large orogen by analyzing zircons in small xenoliths. Key Points Micro‐structures of zircons reconstruct the 220‐million‐year evolution of the Gangdese belt during the India‐Asia convergence The alignment between our data and regional magmatic history suggests highly synchronous evolution across the Gangdese belt We suggest that depth profiling of appropriate crustal xenoliths can effectively reconstruct the geological history of an orogen