Discovery of anti-melanogenic components in persimmon (Diospyros kaki) leaf using LC-MS/MS-MN, AlphaFold2-enabled virtual screening and biological validation.

Persimmon (Diospyros kaki) leaf is widely used as a tea substitute in East Asia, offering potential health benefits. Although studies have highlighted their effects on hyperpigmentation disorders, the active components remain unidentified. This study introduces a novel approach combining LC-MS/MS-based molecular networking with AlphaFold2-enabled virtual screening to expedite the identification of bioactive components in persimmon leaf. A total of 105 compounds were identified by MS/MS analysis. Further, virtual screening identified five flavonoids with potential anti-melanogenic properties. Bioassays confirmed myricetin, quercetin, and kaempferol inhibited melanogenesis in human melanocytes in a dose-dependent manner. Biolayer interferometry assays revealed strong binding affinity between these flavonols and hsTYR, with KD values of 23.26 ± 11.77 for myricetin, 12.43 ± 0.37 for quercetin, and 14.99 ± 3.80 µM for kaempferol. Molecular dynamics simulations provided insights into the binding interactions of these flavonols with hsTYR, particularly highlighting the essential role of the 3-OH group on the C-ring. This study elucidates the bioactive components responsible for the anti-melanogenic effects of persimmon leaf, supporting their use in product development.

Comparison of outcomes for general and local anesthesia in the management of nasal bone fractures: a meta-analysis.

BACKGROUND: This meta-analysis aimed to perform a head-to-head comparison of the role of general anesthesia (GA) and local anesthesia (LA) in the management of patients with nasal bone fractures (NBFs). METHODS: PubMed, Embase, and Web of Science were comprehensively searched. Studies investigating the clinical outcomes of GA and LA in the management of NBFs were included. Pooled odds ratios (OR) with the respective 95% confidence intervals (CIs) were calculated. Heterogeneity between the included studies was evaluated. The risk of bias in the included studies was assessed. RESULTS: Eight studies were included in this meta-analysis. The pooled ORs for cosmetic results, residual septal deformity, the need for further surgery, patients' satisfaction with the anesthesia procedure, and patients' satisfaction with the surgery results were 0.70 (95% CI 0.18, 2.64; z = - 0.53, p = 0.5957), 1.11 (95% CI 0.37, 3.30; z = 0.18, p = 0.8558), 1.19 (95% CI 0.65, 2.20; z = 0.56, p = 0.5760), 1.57 (95% CI 0.92, 2.69; z = 1.65, p = 0.0982), and 1.00 (95% CI 0.55, 1.80; z = - 0.00, p = 0.9974). CONCLUSIONS: Insignificant difference on clinical outcomes was observed between GA and LA in the manipulation of patients with NBFs, and the choice of anesthetic approach should be based on the tolerability of the methods and the severity of nasal fractures.

miR-27b-3p reduces muscle fibrosis during chronic skeletal muscle injury by targeting TGF-ßR1/Smad pathway.

BACKGROUND: Fibrosis is a significant pathological feature of chronic skeletal muscle injury, profoundly affecting muscle regeneration. Fibro-adipogenic progenitors (FAPs) have the ability to differentiate into myofibroblasts, acting as a primary source of extracellular matrix (ECM). the process by which FAPs differentiate into myofibroblasts during chronic skeletal muscle injury remains inadequately explored. METHOD: mouse model with sciatic nerve denervated was constructed and miRNA expression profiles between the mouse model and uninjured mouse were analyzed. qRT/PCR and immunofluorescence elucidated the effect of miR-27b-3p on fibrosis in vivo and in vitro. Dual-luciferase reporter identified the target gene of miR-27b-3p, and finally knocked down or overexpressed the target gene and phosphorylation inhibition of Smad verified the influence of downstream molecules on the abundance of miR-27b-3p and fibrogenic differentiation of FAPs. RESULT: FAPs derived from a mouse model with sciatic nerves denervated exhibited a progressively worsening fibrotic phenotype over time. Introducing agomiR-27b-3p effectively suppressed fibrosis both in vitro and in vivo. MiR-27b-3p targeted Transforming Growth Factor Beta Receptor 1 (TGF-ßR1) and the abundance of miR-27b-3p was negatively regulated by TGF-ßR1/Smad. CONCLUSION: miR-27b-3p targeting the TGF-ßR1/Smad pathway is a novel mechanism for regulating fibrogenic differentiation of FAPs. Increasing abundance of miR-27b-3p, suppressing expression of TGF-ßR1 and inhibiting phosphorylation of smad3 presented potential strategies for treating fibrosis in chronic skeletal muscle injury.

The role of small dense LDL-C/large buoyant LDL-C ratio as an independent risk factor in patients with type 2 diabetes mellitus and metabolic syndrome

Dyslipidemia plays a key role in metabolic syndrome (MS), intricately linked to type 2 diabetes mellitus (T2DM). This study aimed to investigate the differences in low-density lipoprotein cholesterol (LDL-C) subfraction levels between T2DM and T2DM with MS, and identify the risk factors associated with the disease. A total of 246 individuals diagnosed with T2DM, including 144 T2DM patients with MS, and 147 healthy subjects were recruited. All participants underwent a comprehensive clinical evaluation. Lipoprotein subfraction analysis was performed using the Lipoprint LDL system. Multivariate logistic regression analysis revealed that several lipid markers, including triglyceride (TG), LDL-C, large buoyant LDL-C (lbLDL-C), small dense LDL-C (sdLDL-C), LDLC2-5, and sdLDL-C/lbLDL-C ratio, were identified as independent risk factors for T2DM. Additionally, TG, sdLDL-C, LDLC-4, LDLC-5, and sdLDL-C/lbLDL-C ratio were found to be independent risk factors for T2DM with MS. Furthermore, the results of the receiver operating characteristic (ROC) curves demonstrated that sdLDL-C, LDLC-4, LDLC-3, and sdLDL-C/lbLDL-C ratio exhibited excellent predictive performance for the risk of T2DM (AUC > 0.9). The sdLDL-C/lbLDL-C ratio emerges as a shared independent risk factor for T2DM and MS complications. Furthermore, sdLDL-C/lbLDL-C ratio, along with LDL-4 and LDL-3, exhibits noteworthy predictive capabilities for T2DM.

The Interrelationships between Cognitive Biases for Pain: An Experimental Study.

Contemporary pain models highlight cognitive-processing biases (i.e., attention (AB), interpretation (IB), and memory bias (MB)) as key processes that contribute to poor pain outcomes. However, existing research has yielded inconsistent findings regarding the presence and impact of these biases on pain outcomes. Recognizing the need to explore these biases simultaneously, contemporary pain models suggest that cognitive biases (CBs) are interrelated, and may have a combined impact upon pain problems. The current study aims to investigate the interrelationships between cognitive biases using the PainAIM paradigm, a novel approach enabling simultaneous evaluation of pain-related AB, IB, and MB using cues signaling actual pain rather than symbolic information. We hypothesized the presence and positive associations of biases for pain-related cues and the predictive value of combined AB and IB for poor pain outcomes. Eighty-four healthy participants completed the PainAIM paradigm, followed by a cold pressor task probing pain experience and pain-related task interference. Results indicated an inverse relationship between AB and IB for ambiguous pain cues. In addition, there was a positive association between participants' AB for ambiguous pain and their MB for the same cues. Contrary to our hypotheses, CB indices did not predict experimental pain outcomes. These findings provide support for the interrelationships between pain-related CBs. However, future research on the temporal order of CBs and their combined impact on pain outcomes is needed. By overcoming limitations associated with traditional paradigms, the PainAIM paradigm offers a promising research tool for the further study of combined CBs in the context of pain. PERSPECTIVE: The current study provides insight into the associations between pain-related cognitive biases (attention, interpretation, memory) using ecologically valid (ambiguous) pain cues. Results indicated an inverse association between pain-related AB and IB, while a positive association was found between AB and MB. Cognitive biases did however not predict experimental pain outcomes.

Constructing Photocatalytic Covalent Organic Frameworks with Aliphatic Linkers.

Photocatalytic covalent organic frameworks (COFs) are typically constructed with rigid aromatic linkers for crystallinity and extended π-conjugation. However, the essential hydrophobicity of the aromatic backbone can limit their performances in water-based photocatalytic reactions. Here, we for the first time report the synthesis of hydrophilic COFs with aliphatic linkers [tartaric acid dihydrazide (TAH) and butanedioic acid dihydrazide] that can function as efficient photocatalysts for H2O2 and H2 evolution. In these hydrophilic aliphatic linkers, the specific multiple hydrogen bonding networks not only enhance crystallization but also ensure an ideal compatibility of crystallinity, hydrophilicity, and light harvesting. The resulting aliphatic linker COFs adopt an unusual ABC stacking, giving rise to approximately 0.6 nm nanopores with an improved interaction with water guests. Remarkably, both aliphatic linker-based COFs show strong visible light absorption, along with a narrow optical band gap of ∼1.9 eV. The H2O2 evolution rate for TAH-COF reaches up to 6003 µmol h-1 g-1, in the absence of sacrificial agents, surpassing the performance of all previously reported COF-based photocatalysts. Theoretical calculations reveal that the TAH linker can enhance the indirect two-electron oxygen reduction reaction for H2O2 production by improving the O2 adsorption and stabilizing the *OOH intermediate. This study opens a new avenue for constructing semiconducting COFs using nonaromatic linkers.

Fast connectivity gradient approximation: maintaining spatially fine-grained connectivity gradients while reducing computational costs.

Brain connectome analysis suffers from the high dimensionality of connectivity data, often forcing a reduced representation of the brain at a lower spatial resolution or parcellation. This is particularly true for graph-based representations, which are increasingly used to characterize connectivity gradients, capturing patterns of systematic spatial variation in the functional connectivity structure. However, maintaining a high spatial resolution is crucial for enabling fine-grained topographical analysis and preserving subtle individual differences that might otherwise be lost. Here we introduce a computationally efficient approach to establish spatially fine-grained connectivity gradients. At its core, it leverages a set of landmarks to approximate the underlying connectivity structure at the full spatial resolution without requiring a full-scale vertex-by-vertex connectivity matrix. We show that this approach reduces computational time and memory usage while preserving informative individual features and demonstrate its application in improving brain-behavior predictions. Overall, its efficiency can remove computational barriers and enable the widespread application of connectivity gradients to capture spatial signatures of the connectome. Importantly, maintaining a spatially fine-grained resolution facilitates to characterize the spatial transitions inherent in the core concept of gradients of brain organization.

A membrane-targeting magnolol derivative for the treatment of methicillin-resistant Staphylococcus aureus infections.

Multidrug-resistant bacterial infections are a major global health challenge, especially the emergence and rapid spread of methicillin-resistant Staphylococcus aureus (MRSA) urgently require alternative treatment options. Our study has identified that a magnolol derivative 6i as a promising agent with significant antibacterial activity against S. aureus and clinical MRSA isolates (MIC = 2-8 µg/mL), showing high membrane selectivity. Unlike traditional antibiotics, 6i demonstrated rapid bactericidal efficiency and a lower propensity for inducing bacterial resistance. Compound 6i also could inhibit biofilm formation and eradicate bacteria within biofilms. Mechanistic studies further revealed that 6i could target bacterial cell membranes, disrupting the integrity of the cell membrane and leading to increased DNA leakage, resulting in potent antibacterial effects. Meanwhile, 6i also showed good plasma stability and excellent biosafety. Notably, 6i displayed good in vivo antibacterial activity in a mouse skin abscess model of MRSA-16 infection, which was comparable to the positive control vancomycin. These findings indicated that the magnolol derivative 6i possessed the potential to be a novel anti-MRSA infection agent.

Impact of Cancer Therapy on Clonal Hematopoiesis Mutations and Subsequent Clinical Outcomes.

Exposure to cancer therapies is associated with an increased risk of clonal hematopoiesis (CH). The objective of our study was to investigate the genesis and evolution of CH following cancer therapy. In this prospective study, we undertook error-corrected duplex DNA sequencing in blood samples collected prior to and at two timepoints following chemoradiation in patients with esophageal or lung cancer recruited from 2013-2018. We applied a customized workflow to identify the earliest changes in CH mutation count and clone size and determine their association with clinical outcomes. Our study included 29 patients (87 samples). Their median age was 67 years, 76% (n = 22) were male; the median follow-up period was 3.9 years. The most mutated genes were DNMT3A, TET2, TP53, and ASXL1. We observed a two-fold increase in the number of mutations from before to after treatment in TP53, which differed from all other genes examined (P < .001). Among mutations detected before and after treatment, we observed an increased clone size in 38% and a decreased clone size in 5% of TP53 mutations (odds ratio = 3.7; 95% CI = 1.75-7.84; P < .001). Changes in mutation count and clone size were not observed in other genes. Individuals with an increase in the number of TP53 mutations following chemoradiation experienced shorter overall survival (hazard ratio = 7.07; 95% CI = 1.50-33.46; P = .014). In summary, we found an increase in the number and size of TP53 CH clones following chemoradiation that were associated with clinical outcomes.

Endometrial stem cell-derived exosomes repair cisplatin-induced premature ovarian failure via Hippo signaling pathway.

Stem cells have been documented as a new therapeutic method for ovarian injuries such as premature ovarian failure (POF). However, effects of exosomes (Exos) derived from human endometrial stem cells (EnSCs) on diminished ovarian failure remain to be carefully elucidated. Our study aims to investigate the mechanisms of EnSC-Exos in the recovery of the cisplatin-induced granulosa cell injury model in vitro or POF mouses model in vivo and whether the Hippo signaling pathway is involved in the regulation. In this study, we established successful construction of the cisplatin-induced granulosa cell injury model and evaluated Hippo signaling pathway activation in cisplatin-damaged granulosa cells (GCs). Furthermore, laser scanning confocal microscope and immunofluorescence demonstrated that EnSC-Exos can be transferred to cisplatin-damaged GCs to decrease apoptosis. In addition, the enhanced expression of YAP at the protein level as well as YAP/TEAD target genes, such as CTGF, ANKRD1, and the increase of YAP into the nucleus in immunofluorescence staining after the addition of EnSC-Exos to cisplatin-damaged GCs confirmed the suppression of Hippo signaling pathway. While in vivo, EnSC-Exos successfully remedied POF in a mouse model. Collectively, our findings suggest that chemotherapy-induced POF was associated with the activating of Hippo signaling pathway. Human EnSC-Exos significantly elevated the proliferation of ovarian GCs and the ovarian function by regulating Hippo signaling pathway. These findings provide new insights for further understanding of EnSC-Exos in the recovery of ovary function.

Application of a feedforward control-based intervention for preventing hypothermia in trauma patients in a pre-hospital emergency setting.

OBJECTIVE: To investigate the efficacy of a feedforward control-based intervention strategy for preventing hypothermia among trauma patients during pre-hospital emergency care. METHODS: We conducted a retrospective analysis comparing trauma patients treated before and after implementing the intervention, with 40 cases in each group. All patients received emergency care from the Fuzhou Emergency Center on the scene. Multivariate analysis was used to explore the risk factors for hypothermia. The effective rate, incidence of adverse reactions, quality of body temperature management, medical staff's knowledge, attitudes, and behaviors regarding mild hypothermia prevention, coagulation function, treatment time at various stages, prognosis score, and treatment situation were compared between the two groups. RESULTS: The adverse reactions, intervention methods, and degree of cognitive improvement were influencing factors for hypothermia. The effective rate (92.50%) in the feedforward control group was higher than that in the non-feedforward control group (65.00%), with a lower incidence of adverse reactions (2.50%). The temperature management quality score of the feedforward control group (6.23±0.62) was higher. The feedforward control group achieved a higher quality score for temperature management (6.23±0.62) and exhibited a greater understanding of hypothermia prevention among trauma patients (P<0.05). Compared to the non-feedforward control group, the feedforward control group showed improved coagulation function, better performance in treatment time at each node, and higher prognosis scores. CONCLUSION: The intervention model based on feedforward control can effectively improve the standard of pre-hospital emergency care and prevent the incidence of hypothermia in trauma patients.

Learning shared template representation with augmented feature for multi-object pose estimation.

Template matching pose estimation methods based on deep learning have made significant advancements via metric learning or reconstruction learning. Existing approaches primarily build distinct template representation libraries (codebooks) from rendered images for each object, which complicate the training process and increase memory cost for multi-object tasks. Additionally, they struggle to effectively handle discrepancies between the distributions of training and test sets, particularly for occluded objects, resulting in suboptimal matching accuracy. In this study, we propose a shared template representation learning method with augmented semantic features to address these issues. Our method learns representations concurrently using metric and reconstruction learning as similarity constraints, and augments response of network to objects through semantic feature constraints for better generalization performance. Furthermore, rotation matrices serve as templates for codebook construction, leading to excellent matching accuracy compared to rendered images. Notably, it contributes to the effective decoupling of object categories and templates, necessitating the maintenance of only a shared codebook in multi-object pose estimation tasks. Extensive experiments on Linemod, Linemod-Occluded and TLESS datasets demonstrate that the proposed method employing shared templates achieves superior matching accuracy. Moreover, proposed method exhibits robustness on a collected aircraft dataset, further validating its efficacy.

Individualized radiology screening for newly diagnosed nasopharyngeal carcinoma.

OBJECTIVES: Current guidelines recommend universal PET/CT screening for metastases staging in newly diagnosed nasopharyngeal carcinoma (NPC) despite the low rate of synchronous distant metastasis (SDM). The study aims to achieve individualized screening recommendations of NPC based on the risk of SDM. METHODS AND MATERIALS: 18 pre-treatment peripheral blood indicators was retrospectively collected from 2271 primary NPC patients. A peripheral blood risk score (PBRS) was constructed by indicators associated with SDM on least absolute shrinkage and selection operator (LASSO) regression. The PBRS-based distant metastases (PBDM) model was developed from features selected by logistic regression analyses in the training cohort and then validated in the validation cohort. Receiver operator characteristic curve analysis, calibration curves, and decision curve analysis were applied to evaluate PBDM model performance. RESULTS: Pre-treatment Epstein-Barr viral DNA copy number, percentage of total lymphocytes, serum lactate dehydrogenase level, and monocyte-to-lymphocyte ratio were most strongly associated with SDM in NPC and used to construct the PBRS. Sex (male), T stage (T3-4), N stage (N2-3), and PBRS (≥1.076) were identified as independent risk factors for SDM and applied in the PBDM model, which showed good performance. Through the model, patients in the training cohort were stratified into low-, medium-, and high-risk groups. Individualized screening recommendations were then developed for patients with differing risk levels. CONCLUSION: The PBDM model offers individualized recommendations for applying PET/CT for metastases staging in NPC, allowing more targeted screening of patients with greater risk of SDM compared with current recommendations.

Protective effects of nodosin against lipopolysaccharide-induced acute kidney injury through regulation of oxidative stress, inflammation, and ferroptosis in rats.

This research aimed to explore the impact of nodosin on lipopolysaccharide (LPS)-induced acute kidney injury (AKI) in rats. The study involved administering nodosin orally at doses of 2 and 4 mg/kg body weight orally to rats for 7 days before induction of AKI. Toward the end of the study, urine, blood, and kidneys were gathered from the rats to undergo biochemical and molecular examination after sacrificing them. Serum Scr, BUN, urine NGAL, and KIM-1 levels were significantly decreased in nodosin-treated AKI rats. Besides, nodosin administration resulted in a significant reduction in kidney MDA and 4-HNE levels. In contrast, antioxidant enzymes such as SOD, CAT, GPx, and GST levels increased, as well as Nrf2, NQO1, and HO-1 levels increased, while Keap-1 mRNA levels decreased in AKI rats. In addition, AKI rats treated with nodosin reversed excessive ferroptosis in the kidneys of LPS-induced AKI rats, as evidenced by increased mRNA and protein levels of GPX4, SLC7A11, and FTH-1. The administration of nodosin significantly reduced levels of inflammatory markers including TLR4, MYD88, NF-κB p65, IkKß, and IL-1ß, while IL-10 levels increased in the AKI-induced rats. Besides, histopathological changes were reduced in AKI-induced rats treated with nodosin. Nodosin proves highly beneficial in safeguarding the kidney from AKI by regulating oxidative stress, inflammation, and ferroptosis. The treatment of AKI could greatly benefit from this option.

Comprehensive analysis of the complete mitochondrial genome of Lilium tsingtauense reveals a novel multichromosome structure.

KEY MESSAGE: Lilium tsingtauense mitogenome comprises 27 independent chromosome molecules, it undergoes frequent genomic recombination, and the rate of recombination and mutation between different repetitive sequences affects the formation of multichromosomal structures. Given the extremely large genome of Lily, which likely harbors additional genetic resources, it serves as an ideal material for studying the phylogenetic evolution of organisms. Although the Lilium chloroplast genome has been documented, the sequence of its mitochondrial genome (mitogenome) remains uncharted. Using BGI short reads and Nanopore long reads, we sequenced, assembled, and annotated the mitogenome of Lilium tsingtauense. This effort culminated in the characterization of Lilium's first complete mitogenome. Comparative analysis with other angiosperms revealed the unique multichromosomal structure of the L. tsingtauense mitogenome, spanning 1,125,108 bp and comprising 27 independent circular chromosomes. It contains 36 protein-coding genes, 12 tRNA genes, and 3 rRNA genes, with a GC content of 44.90%. Notably, three chromosomes in the L. tsingtauense mitogenome lack identifiable genes, hinting at the potential existence of novel genes and noncoding elements. The high degree of observed genome fragmentation implies frequent reorganization, with recombination and mutation rates among diverse repetitive sequences likely driving the formation of multichromosomal structures. Our comprehensive analysis, covering genome size, coding genes, structure, RNA editing, repetitive sequences, and sequence migration, sheds light on the evolutionary and molecular biology of multichromosomal mitochondria in Lilium. This high-quality mitogenome of L. tsingtauense not only enriches our understanding of multichromosomal mitogenomes but also establishes a solid foundation for future genome breeding and germplasm innovation in Lilium.

Double-Tube Multiplex TaqMan Real-Time PCR for the Detection of Eight Animal-Derived Dairy Ingredients.

Milk and dairy products represent important sources of nutrition in our daily lives. The identification of species within dairy products holds importance for monitoring food adulteration and ensuring traceability. This study presented a method that integrated double-tube and duplex real-time polymerase chain reaction (PCR) with multiplex TaqMan probes to enable the high-throughput detection of animal-derived ingredients in milk and dairy products. The detection system utilized one pair of universal primers, two pairs of specific primers, and eight animal-derived specific probes for cow, buffalo, goat, sheep, camel, yak, horse, and donkey. These components were optimized within a double-tube and four-probe PCR multiplex system. The developed double-tube detection system could simultaneously identify the above eight targets with a detection limit of 10-0.1 pg/µL. Validation using simulated adulterated milk samples demonstrated a detection limit of 0.1%. The primary advantage of this method lies in the simplification of the multiplex quantitative real-time PCR (qPCR) system through the use of universal primers. This method provides an efficient approach for detecting ingredients in dairy products, providing powerful technical support for market supervision.

Formation, characterization, and application of natural bioactive phytosterol-based oleogels: A review.

Oleogels are innovative structured fat systems that can replace detrimental lipids and saturated fats. Among the various gelators used to construct oleogels, phytosterols are regarded as potential oleogelators due to ability to lower blood cholesterol levels and protect patients from cardiovascular illnesses, although little research has been conducted on phytosterols. This article examines the formation, characterization, and application of phytosterol-based oleogels in detail. The oleogelation behaviors of phytosterol-based oleogels are affected by their formulation, which includes phytosterol type, combined oleogelator, proportion, concentration and oil type. These oleogels exhibit potential applications as solid fat substitutes without affecting the texture or sensory properties of food products or as effective delivery vehicles. To encourage the research and implementation of phytosterol-based oleogels, we will ultimately not only highlight problems related to their use in food processing, but also provide a few viewpoints, with the goal of providing fresh insights for advancing trends.

Novel f-CaO soft sensor for cement clinker based on integrated model of dual-parallel structure.

Aiming at the problem that the cement production process is inherently affected by uncertainty, time delay, and strong coupling among variables, this paper proposed a novel soft sensor of free calcium oxide in a cement clinker. The model utilizes a dual-parallel integrated structure with an optimized integration of one-dimensional convolutional neural networks, long and short-term memory networks, graphical neural networks, and extreme gradient boosting. The proposed model can mitigate the risks associated with overfitting while incorporating the strengths of each individual model and excels in extracting both local and global features as well as temporal and spatial characteristics from the original time series data, ensuring its stability. The experimental results demonstrate that this dual-parallel integrated model exhibits superior robustness, predictive accuracy, and generalization capabilities when compared to single models or enhancements made to other deep learning algorithms.

Unlocking the power of Zc3h12c: Orchestrating Macrophage activation and elevating the innate immune response.

The activation of macrophages, essential for the innate defense against invading pathogens, revolves around Toll-like receptors (TLRs). Nevertheless, a comprehensive understanding of the molecular mechanisms governing TLR signaling in the course of macrophage activation remains to be fully clarified. Although Zc3h12c was originally identified as being enriched in organs associated with macrophages, its precise function remains elusive. In this study, we observed a significant induction of Zc3h12c in macrophages following stimulation with TLR agonists and pathogens. Overexpression of Zc3h12c significantly mitigated the release of TNF-α and IL-6 triggered by lipopolysaccharide (LPS), whereas depletion of Zc3h12c increased the production of the cytokines mentioned above. Notably, the expression of IFN-ß was not influenced by Zc3h12c. Luciferase reporter assays revealed that Zc3h12c could suppress the TNF-α promoter activity. Moreover, Zc3h12c exerted a notable inhibitory effect on JNK, ERK, p38, and NF-κB signaling induced by LPS. In summary, the findings of our study suggest that Zc3h12c functions as a robust suppressor of innate immunity, potentially playing a role in the pathogenesis of infectious diseases.

ChineseEEG: A Chinese Linguistic Corpora EEG Dataset for Semantic Alignment and Neural Decoding.

An Electroencephalography (EEG) dataset utilizing rich text stimuli can advance the understanding of how the brain encodes semantic information and contribute to semantic decoding in brain-computer interface (BCI). Addressing the scarcity of EEG datasets featuring Chinese linguistic stimuli, we present the ChineseEEG dataset, a high-density EEG dataset complemented by simultaneous eye-tracking recordings. This dataset was compiled while 10 participants silently read approximately 13 hours of Chinese text from two well-known novels. This dataset provides long-duration EEG recordings, along with pre-processed EEG sensor-level data and semantic embeddings of reading materials extracted by a pre-trained natural language processing (NLP) model. As a pilot EEG dataset derived from natural Chinese linguistic stimuli, ChineseEEG can significantly support research across neuroscience, NLP, and linguistics. It establishes a benchmark dataset for Chinese semantic decoding, aids in the development of BCIs, and facilitates the exploration of alignment between large language models and human cognitive processes. It can also aid research into the brain's mechanisms of language processing within the context of the Chinese natural language.