Melatonin modulates neuroinflammatory response and microglial activation in mice exposed to dim blue light at night.

Objectives: Dim light at night contributes to neurodegenerative diseases by causing neuroinflammation. In the central nervous system, the activation of microglia is a significant contributor to neuroinflammation. Therefore, there is an urgent need to find an intervention to treat the neuroinflammatory response caused by dim light at night. Melatonin is a rhythmic hormone whose synthesis is suppressed during the day. In this study, we attempt to explore whether and how melatonin improves hippocampal neuroinflammation in mice exposed to dim blue light at night. Materials and Methods: In vivo, a total of 36 male C57BL6/J mice that exposed to no light at night, dim blue light at night, and dim blue light at night with melatonin treatment. In vitro, the corticosterone-induced BV2 cells with or without melatonin treatment were used. Results: Both in vivo and in vitro experiments showed melatonin treatment significantly reduced dim blue light -induced hippocampal microglial activation and the expression of inflammatory factors IL-1ß and TNF-α. This improved effect of melatonin is related to its receptor MT2 rather than MT1. The MT2 blockers significantly increased mRNA levels of M1-type activation marker CD86 and inflammatory cytokines IL-1ß and TNF-α in melatonin-treated BV2 cells. Binding of melatonin to its receptor MT2 downregulated the expression of inflammatory proteins P-P65 and NLRP3, consequently inhibited the CD80 expression and M1-type activation in microglia. Furthermore, consistent with the decrease in microglial activation and inflammatory response after melatonin treatment, we also observed a reduction in hippocampal neuron loss and damage to the HT22 cells. Conclusion: Our findings suggested that melatonin may regulate microglial polarization through MT2/NF-kB-NLRP3 pathway and improves dim blue light -induced hippocampal neuroinflammation in mice.

Neurotoxic mechanisms of mycotoxins: Focus on aflatoxin B1 and T-2 toxin.

Aflatoxin B1 (AFB1) and T-2 toxin are commonly found in animal feed and stored grain, posing a serious threat to human and animal health. Mycotoxins can penetrate brain tissue by compromising the blood-brain barrier, triggering oxidative stress and neuroinflammation, and leading to oxidative damage and apoptosis of brain cells. The potential neurotoxic mechanisms of AFB1 and T-2 toxin were discussed by summarizing the relevant research reports from the past ten years. AFB1 and T-2 toxin cause neuronal damage in the cerebral cortex and hippocampus, leading to synaptic transmission dysfunction, ultimately impairing the nervous system function of the body. The toxic mechanism is related to excessive reactive oxygen species (ROS), oxidative stress, mitochondrial dysfunction, apoptosis, autophagy, and an exaggerated inflammatory response. After passing through the blood-brain barrier, toxins can directly affect glial cells, alter the activation state of microglia and astrocytes, thereby promoting brain inflammation, disrupting the blood-brain barrier, and influencing the synaptic transmission process. We discussed the diverse effects of various concentrations of toxins and different modes of exposure on neurotoxicity. In addition, toxins can also cross the placental barrier, causing neurotoxic symptoms in offspring, as demonstrated in various species. Our goal is to uncover the underlying mechanisms of the neurotoxicity of AFB1 and T-2 toxin and to provide insights for future research, including investigating the impact of mycotoxins on interactions between microglia and astrocytes.

Fungal vaccines and adjuvants: a tool to reveal the interaction between host and fungi.

Fungal infections are incurring high risks in a range from superficial mucosal discomforts (such as oropharyngeal candidiasis and vulvovaginal candidiasis) to disseminated life-threatening diseases (such as invasive pulmonary aspergillosis and cryptococcal meningitis) and becoming a global health problem in especially immunodeficient population. The major obstacle to conquer fungal harassment lies in the presence of increasing resistance to conventional antifungal agents used in newly clinically isolated strains. Although recombinant cytokines and mono-/poly-clonal antibodies are added into antifungal armamentarium, more effective antimycotic drugs are exceedingly demanded. It is comforting that the development of fungal vaccines and adjuvants opens up a window to brighten the prospective way in the diagnosis, prevention and treatment of fungal assaults. In this review, we focus on the progression of several major fungal vaccines devised for the control of Candida spp., Aspergillus spp., Cryptococcus spp., Coccidioides spp., Paracoccidioides spp., Blastomyces spp., Histoplasma spp., Pneumocystis spp. as well as the adjuvants adopted. We then expound the interaction between fungal vaccines/adjuvants and host innate (macrophages, dendritic cells, neutrophils), humoral (IgG, IgM and IgA) and cellular (Th1, Th2, Th17 and Tc17) immune responses which generally experience immune recognition of pattern recognition receptors, activation of immune cells, and clearance of invaded fungi. Furthermore, we anticipate an in-depth understanding of immunomodulatory properties of univalent and multivalent vaccines against diverse opportunistic fungi, providing helpful information in the design of novel fungal vaccines and adjuvants.

Impact of perceived value in virtual brand communities on purchase intention of domestic electric vehicles.

The consumption value seems to be insufficient to explain consumers' domestic electric vehicle purchase behaviour, especially in a highly competitive global environment. This study aims to investigate how consumer ethnocentrism and perceived interactivity influence consumption value and pro-environmental value, subsequently affecting attitude and intention. A total of 353 valid questionnaires were collected through convenience sampling in Xuzhou, China, and the partial least square (PLS) path modelling approach was performed to test the hypotheses. The results show that consumer ethnocentrism and perceived interactivity positively influence function value, emotional value, and social value; perceived interactivity also positively influences altruistic value, biospheric value, and collectivistic value. Function value, social value, and collectivistic value positively influence attitude; however, emotional value, altruistic value and biospheric value did not find a correlation with attitude. Furthermore, attitude positively influences intention to adopt domestic electric vehicles. Finally, the theoretical and practical implications, as well as limitations were discussed accordingly.

A Novel Dry-Cured Ham Broth-Derived Peptide JHBp2 Effectively Inhibits Salmonella typhimurium In Vitro: Integrated Metabolomic, Proteomic, and Molecular Simulation Analyses.

JHBp2 is a peptide purified from Jinhua ham broth with antibacterial activity against Salmonella typhimurium. Untargeted metabolomics and label-free quantitative proteomics were used to analyze metabolic and protein expression changes in S. typhimurium after JHBp2 treatment. Cell wall and membrane damage results indicate that JHBp2 has membrane-disruptive properties, causing leakage of intracellular nucleic acids and proteins. Metabolomics revealed 516 differentially expressed metabolites, involving cofactor biosynthesis, purine metabolism, ABC transporters, glutathione metabolism, pyrimidine metabolism, etc. Proteomics detected 735 differentially expressed proteins, involving pyruvate metabolism, amino acid biosynthesis, purine metabolism, carbon metabolism, glycolysis/gluconeogenesis, etc. RT-qPCR and proteomics results showed a positive correlation, and molecular docking demonstrated stable binding of JHBp2 to some differentially expressed proteins. In summary, JHBp2 could disrupt the S. typhimurium cell wall and membrane structure, interfere with synthesis of membrane-related proteins, trigger intracellular substance leak, and reduce levels of enzymes and metabolites involved in energy metabolism, amino acid anabolism, and nucleotide anabolism.

The Balance Between Shear Flow and Extracellular Matrix in Ovarian Cancer-on-Chip.

Ovarian cancer is the most lethal gynecologic cancer in developed countries. In the tumor microenvironment, the extracellular matrix (ECM) and flow shear stress are key players in directing ovarian cancer cells invasion. Artificial ECM models based only on ECM proteins are used to build an ovarian tumor-on-chip to decipher the crosstalk between ECM and shear stress on the migratory behavior and cellular heterogeneity of ovarian tumor cells. This work shows that in the shear stress regime of the peritoneal cavity, the ECM plays a major role in driving individual or collective ovarian tumor cells migration. In the presence of basement membrane proteins, migration is more collective than on type I collagen regardless of shear stress. With increasing shear stress, individual cell migration is enhanced; while, no significant impact on collective migration is measured. This highlights the central position that ECM and flow shear stress should hold in in vitro ovarian cancer models to deepen understanding of cellular responses and improve development of ovarian cancer therapeutic platforms. In this frame, adding flow provides significant improvement in biological relevance over the authors' previous work. Further steps for enhanced clinical relevance require not only multiple cell lines but also patient-derived cells and sera.

PbBeB2O5: A High-Performance Ultraviolet Nonlinear-Optical Crystal with Functional [BeB2O8]8- Group.

High-performance nonlinear-optical (NLO) crystals need to simultaneously meet multiple basic and conflicting performance requirements. Here, by using a partial chemical substitution strategy, the first noncentrosymmetric (NCS) PbBeB2O5 crystal with a BeB2O8 group was synthesized, exhibiting a two-dimensional [BeB2O5]∞ layer constructed by interconnecting BeB2O8 groups and bridged PbO4 with an active lone pair. The crystal shows a promising UV NLO functional feature, including a strong SHG effect of 3.5 × KDP (KH2PO4), large birefringence realizing phase matchability in the whole transparency region from 246 to 2500 nm, a short UV absorption edge of 246 nm, and single-crystal easy growth. Remarkably, theoretical studies reveal that the BeB2O8 group has high nonlinear activity, which could stimulate the discovery of a series of excellent NLO beryllium borates.

Genome-wide association study and genomic selection of spike-related traits in bread wheat.

KEY MESSAGE: Identification of 337 stable MTAs for wheat spike-related traits improved model accuracy, and favorable alleles of MTA259 and MTA64 increased grain weight and yield per plant. Wheat (Triticum aestivum L.) is one of the three primary global, staple crops. Improving spike-related traits in wheat is crucial for optimizing spike and plant morphology, ultimately leading to increased grain yield. Here, we performed a genome-wide association study using a dataset of 24,889 high-quality unique single-nucleotide polymorphisms (SNPs) and phenotypic data from 314 wheat accessions across eight diverse environments. In total, 337 stable and significant marker-trait associations (MTAs) related to spike-related traits were identified. MTA259 and MTA64 were consistently detected in seven and six environments, respectively. The presence of favorable alleles associated with MTA259 and MTA64 significantly reduced wheat spike exsertion length and spike length, while enhancing thousand kernel weight and yield per plant. Combined gene expression and network analyses identified TraesCS6D03G0692300 and TraesCS6D03G0692700 as candidate genes for MTA259 and TraesCS2D03G0111700 and TraesCS2D03G0112500 for MTA64. The identified MTAs significantly improved the prediction accuracy of each model compared with using all the SNPs, and the random forest model was optimal for genome selection. Additionally, the eight stable and major MTAs, including MTA259, MTA64, MTA66, MTA94, MTA110, MTA165, MTA180, and MTA164, were converted into cost-effective and efficient detection markers. This study provided valuable genetic resources and reliable molecular markers for wheat breeding programs.

Melatonin restores hepatic lipid metabolic homeostasis disrupted by blue light at night in high-fat diet-fed mice.

Artificial light at night (ALAN) is an emerging environmental pollutant that threatens public health. Recently, ALAN has been identified as a risk factor for obesity; however, the role of ALAN and its light wavelength in hepatic lipid metabolic homeostasis remains undetermined. We showed that chronic dim (~5 lx) ALAN (dLAN) exposure significantly promoted hepatic lipid accumulation in obese or diabetic mice, with the most severe effect of blue light and little effect of green or red light. These metabolic phenotypes were attributed to blue rather than green or red dLAN interfering with hepatic lipid metabolism, especially lipogenesis and lipolysis. Further studies found that blue dLAN disrupted hepatic lipogenesis and lipolysis processes by inhibiting hepatic REV-ERBs. Mechanistically, feeding behavior mediated the regulation of dLAN on hepatic REV-ERBs. In addition, different effects of light wavelengths at night on liver REV-ERBs depended on the activation of the corticosterone (CORT)/glucocorticoid receptor (GR) axis. Blue dLAN could activate the CORT/GR axis significantly while other wavelengths could not. Notably, we demonstrated that exogenous melatonin could effectively inhibit hepatic lipid accumulation and restore the hepatic GR/REV-ERBs axis disrupted by blue dLAN. These findings demonstrate that dLAN promotes hepatic lipid accumulation in mice via a short-wavelength-dependent manner, and exogenous melatonin is a potential therapeutic approach. This study strengthens the relationship between ALAN and hepatic lipid metabolism and provides insights into directing ambient light.

The Effect Mechanism of N6-adenosine Methylation (m6A) in Melatonin Regulated LPS-induced Colon Inflammation.

Colon inflammation is characterized by disturbances in the intestinal microbiota and inflammation. Melatonin (Mel) can improve colon inflammation. However, the underlying mechanism remains unclear. Recent studies suggest that m6A methylation modification may play an important role in inflammatory responses. This study aimed to explore the effects of melatonin and LPS-mediated m6A methylation on colon inflammation. Our study found that melatonin inhibits M1 macrophages, activates M2 macrophages, inhibit the secretion of pro-inflammatory factors, maintain colon homeostasis and improves colon inflammation through MTNR1B. In addition, the increased methylation level of m6A is associated with the occurrence of colon inflammation, and melatonin can also reduce the level of colon methylation to improve colon inflammation. Among them, the main methylated protein METTL3 can be inhibited by melatonin through MTNR1B. In a word, melatonin regulates m6A methylation by improving abnormal METTL3 protein level to reshape the microflora and activate macrophages to improve colon inflammation, mainly through MTNR1B.

Neuropeptides affecting social behavior in mammals: Oxytocin.

Oxytocin (OXT), a neuropeptide consisting of only nine amino acids, is synthesized in the paraventricular and supraoptic nuclei of the hypothalamus. Although OXT is best known for its role in lactation and parturition, recent research has shown that it also has a significant impact on social behaviors in mammals. However, a comprehensive review of this topic is still lacking. In this paper, we systematically reviewed the effects of OXT on social behavior in mammals. These effects of OXT from the perspective of five key behavioral dimensions were summarized: parental behavior, anxiety, aggression, attachment, and empathy. To date, researchers have agreed that OXT plays a positive regulatory role in a wide range of social behaviors, but there have been controversially reported results. In this review, we have provided a detailed panorama of the role of OXT in social behavior and, for the first time, delved into the underlying regulatory mechanisms, which may help better understand the multifaceted role of OXT. Levels of OXT in previous human studies were also summarized to provide insights for diagnosis of mental disorders.

CodLncScape Provides a Self-Enriching Framework for the Systematic Collection and Exploration of Coding LncRNAs.

Recent studies have revealed that numerous lncRNAs can translate proteins under specific conditions, performing diverse biological functions, thus termed coding lncRNAs. Their comprehensive landscape, however, remains elusive due to this field's preliminary and dispersed nature. This study introduces codLncScape, a framework for coding lncRNA exploration consisting of codLncDB, codLncFlow, codLncWeb, and codLncNLP. Specifically, it contains a manually compiled knowledge base, codLncDB, encompassing 353 coding lncRNA entries validated by experiments. Building upon codLncDB, codLncFlow investigates the expression characteristics of these lncRNAs and their diagnostic potential in the pan-cancer context, alongside their association with spermatogenesis. Furthermore, codLncWeb emerges as a platform for storing, browsing, and accessing knowledge concerning coding lncRNAs within various programming environments. Finally, codLncNLP serves as a knowledge-mining tool to enhance the timely content inclusion and updates within codLncDB. In summary, this study offers a well-functioning, content-rich ecosystem for coding lncRNA research, aiming to accelerate systematic studies in this field.

Data-balanced transformer for accelerated ionizable lipid nanoparticles screening in mRNA delivery.

Despite the widespread use of ionizable lipid nanoparticles (LNPs) in clinical applications for messenger RNA (mRNA) delivery, the mRNA drug delivery system faces an efficient challenge in the screening of LNPs. Traditional screening methods often require a substantial amount of experimental time and incur high research and development costs. To accelerate the early development stage of LNPs, we propose TransLNP, a transformer-based transfection prediction model designed to aid in the selection of LNPs for mRNA drug delivery systems. TransLNP uses two types of molecular information to perceive the relationship between structure and transfection efficiency: coarse-grained atomic sequence information and fine-grained atomic spatial relationship information. Due to the scarcity of existing LNPs experimental data, we find that pretraining the molecular model is crucial for better understanding the task of predicting LNPs properties, which is achieved through reconstructing atomic 3D coordinates and masking atom predictions. In addition, the issue of data imbalance is particularly prominent in the real-world exploration of LNPs. We introduce the BalMol block to solve this problem by smoothing the distribution of labels and molecular features. Our approach outperforms state-of-the-art works in transfection property prediction under both random and scaffold data splitting. Additionally, we establish a relationship between molecular structural similarity and transfection differences, selecting 4267 pairs of molecular transfection cliffs, which are pairs of molecules that exhibit high structural similarity but significant differences in transfection efficiency, thereby revealing the primary source of prediction errors. The code, model and data are made publicly available at https://github.com/wklix/TransLNP.

Functional Chitosan and Its Derivative-Related Drug Delivery Systems for Nano-Therapy: Recent Advances.

In the struggle against diseases, the development of nano-therapy has certainly been a tremendous progression owing to the various superiority, and chitosan is no doubt a kind of prominent biopolymer material with versatility for applications in disease treatments. For the rational construction of chitosan-related nano-biodevices, it is necessary to pay full attention to the material itself, where it is the material properties that guide the design criteria. Additionally, the well-matched preparation methods between material carriers and therapeutic agents draw much attention to the final construction since they seem to be more realistic. In detail, we present a comprehensive overview of recent advances in rational construction of chitosan-related nano-therapies with respect to material-property-oriented design criteria and preparation methods in the current review article, based on the foundation of continuous investigations. Based on this review, a portion of the various uses of chitosan-related nano-biodevices for biomedical applications are specifically discussed. Here, the strategies demonstrate the versatility of chitosan well, and the concept of being simple yet effective is well illustrated and vividly communicated. Altogether, a fresh concept concerning multi-functional chitosan and its derivative-related drug delivery systems for nano-therapy is proposed in this review, and this could be applied to other materials, which seems to be a novel angle.

Single-Molecule Fluorescent In Situ Hybridization (smFISH) for RNA Detection in the Fungal Pathogen Candida albicans.

Candida albicans is the most prevalent human fungal pathogen. Its pathogenicity is linked to the ability of C. albicans to reversibly change morphology and to grow as yeast, pseudohyphae, or hyphal cells in response to environmental stimuli. Understanding the molecular regulation controlling those morphological switches remains a challenge that, if solved, could help eradicate C. albicans infections.While numerous studies investigated gene expression changes occurring during C. albicans morphological switches using bulk approaches (e.g., RNA sequencing), here we describe a single-cell and single-molecule RNA imaging and analysis protocol to measure absolute mRNA counts in morphologically intact cells. To detect endogenous mRNAs in single fixed cells, we optimized a single-molecule fluorescent in situ hybridization (smFISH) protocol for C. albicans, which allows one to quantify the differential expression of mRNAs in yeast, pseudohyphae, or hyphal cells. We quantified the expression of two mRNAs, a cell cycle-controlled mRNA (CLB2) and a transcription factor (EFG1), which show expression changes in the different morphological cell types and nutrient conditions. In this protocol, we described in detail the major steps of this approach: growth and fixation, hybridization, imaging, cell segmentation, and mRNA spot analysis. Raw data is provided with the protocol to favor reproducibility. This approach could benefit the molecular characterization of C. albicans and other filamentous fungi, pathogenic or nonpathogenic.

Active Anchoring Stimuli-Responsive Nano-Craft to Relieve Pulmonary Vasoconstriction by Targeting Smooth Muscle Cell for Hypoxic Pulmonary Hypertension Treatment.

Recently, nanotechnology-based drug delivery platforms in treating pulmonary arterial hypertension (PAH) have gradually emerged. However, large mechanical stress and shear stress in blood vessels greatly affect the retention of nanopreparative materials at lesion sites, severely limiting nanotechnology-based drug delivery. Herein, a stimuli-responsive nanocraft is rationally designed by actively anchoring E-selectin overexpressed on pulmonary arterial endothelial cells (PAECs), under hypoxic conditions, allowing effective accumulation and retention of the drug at the lesion site. Briefly, a nitrobenzene group is incorporated into the framework of a nanocarrier, and then it is simultaneously linked with chitosan. Additionally, the surface of the nanocarrier with sialic acid (SA) and encapsulated the clinically used drug ambrisentan (Am), which enables the anchoring of E-selectin and subsequent drug delivery is modifed. This system facilitates intercellular transport to pulmonary artery smooth muscle cells (PASMCs) when targeting PAECs and specifically responds to a reductive hypoxic microenvironment with elevated nitroreductase in PASMCs. Moreover, compared with free Am, nanoencapsulation and SA-PEG2000-NH2 prolong the blood circulation time, achieving better therapeutic outcomes in preventing vascular remodeling and reversing systolic dysfunction. The originality and contribution of this work reveal the promising value of this pulmonary arterial anchoring stimuli-responsive nanocraft as a novel therapeutic strategy for satisfactory PAH treatment.

Time series models in prediction of severe fever with thrombocytopenia syndrome cases in Shandong province, China.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by the SFTS virus (SFTSV). Predicting the incidence of this disease in advance is crucial for policymakers to develop prevention and control strategies. In this study, we utilized historical incidence data of SFTS (2013-2020) in Shandong Province, China to establish three univariate prediction models based on two time-series forecasting algorithms Autoregressive Integrated Moving Average (ARIMA) and Prophet, as well as a special type of recurrent neural network Long Short-Term Memory (LSTM) algorithm. We then evaluated and compared the performance of these models. All three models demonstrated good predictive capabilities for SFTS cases, with the predicted results closely aligning with the actual cases. Among the models, the LSTM model exhibited the best fitting and prediction performance. It achieved the lowest values for mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE). The number of SFTS cases in the subsequent 5 years in this area were also generated using this model. The LSTM model, being simple and practical, provides valuable information and data for assessing the potential risk of SFTS in advance. This information is crucial for the development of early warning systems and the formulation of effective prevention and control measures for SFTS.

Physical impediment to sodium houttuyfonate conversely reinforces ß-glucan exposure stimulated innate immune response to Candida albicans.

Candida albicans is a dimorphic opportunistic pathogen in immunocompromised individuals. We have previously demonstrated that sodium houttuyfonate (SH), a derivative of medicinal herb Houttuynia cordata Thunb, was effective for antifungal purposes. However, the physical impediment of SH by C. albicans ß-glucan may weaken the antifungal activity of SH. In this study, the interactions of SH with cell wall (CW), extracellular matrix (EM), CW ß-glucan, and a commercial ß-glucan zymosan A (ZY) were inspected by XTT assay and total plate count in a standard reference C. albicans SC5314 as well as two clinical fluconazole-resistant strains Z4935 and Z5172. After treatment with SH, the content and exposure of CW ß-glucan, chitin, and mannan were detected, the fungal clearance by phagocytosis of RAW264.7 and THP-1 was examined, and the gene expressions and levels of cytokines TNF-ɑ and IL-10 were also monitored. The results showed that SH could be physically impeded by ß-glucan in CW, EM, and ZY. This impediment subsequently triggered the exposure of CW ß-glucan and chitin with mannan masked in a time-dependent manner. SH-induced ß-glucan exposure could significantly enhance the phagocytosis and inhibit the growth of C. albicans. Meanwhile, the SH-pretreated fungal cells could greatly stimulate the cytokine gene expressions and levels of TNF-ɑ and IL-10 in the macrophages. In sum, the strategy that the instant physical impediment of C. albicans CW to SH, which can induce the exposure of CW ß-glucan may be universal for C. albicans in response to physical deterrent by antifungal drugs.

Comprehensive evaluation of molecule property prediction with ChatGPT.

The versatility of ChatGPT in performing a diverse range of tasks has elicited considerable interest on its potential applications within professional fields. Taking drug discovery as a testbed, this paper provides a comprehensive evaluation of ChatGPT's ability on molecule property prediction. The study focuses on three aspects: 1) Effects of different prompt settings, where we investigate the impact of varying prompts on the prediction outcomes of ChatGPT; 2) Comprehensive evaluation on molecule property prediction, where we conduct a comprehensive evaluation on 53 ADMET-related endpoints; 3) Analysis of ChatGPT's potential and limitations, where we make comparisons with models tailored for molecule property prediction, thus gaining a more accurate understanding of ChatGPT's capabilities and limitations in this area. Through comprehensive evaluation, we find that 1) With appropriate prompt settings, ChatGPT can attain satisfactory prediction outcomes that are competitive with specialized models designed for those tasks. 2) Prompt settings significantly affect ChatGPT's performance. Among all prompt settings, the strategy of selecting examples in few-shot has the greatest impact on results. Scaffold sampling greatly outperforms random sampling. 3) The capacity of ChatGPT to accomplish high-precision predictions is significantly influenced by the quality of examples provided, which may constrain its practical applicability in real-world scenarios. This work highlights ChatGPT's potential and limitations on molecule property prediction, which we hope can inspire future design and evaluation of Large Language Models within scientific domains.

Research on the variation law of floor stress information entropy in upper protective layer mining based on Brillouin optical fiber sensing.

The characteristics of floor failure and stress changes during the mining process of protective layers are crucial for determining the effectiveness of pressure relief. Three boreholes were designed in the 21104 fully mechanized mining face of Hulusu Coal Mine to implant optical fibers into the floor of the working face. A fiber optic monitoring system was established to monitor the dynamic evolution of stress in the floor rock mass at different mining distances. Based on the information entropy in information theory, the monitoring results in the fiber optic monitoring system are calculated to obtain the stress information entropy at different mining distances. A quantitative dynamic analysis is conducted on the stress change process of the mining floor rock layer, and the stress change law of the protective layer after mining is verified through numerical calculation and similar simulation experiments. The results indicate that the evolution of stress information entropy can be divided into four stages, namely the original rock stress stage, stress concentration stage, stress release stage, and stress recovery stage. The stress information entropy shows a fluctuating upward trend, indicating that coal seam mining leads to a decrease in the orderliness of the overlying rock system and an increase in disorder. In different spatial evolution processes, there are also significant differences in stress information entropy. In the vertical direction, the entropy value of shallow rock layers changes greatly, while the entropy value of deep rock layers changes slightly. Mining leads to a decrease in the orderliness of the entire overlying rock system, an increase in stress information entropy, and a fluctuating upward trend in stress information entropy. The information entropy of overlying rock deformation and re compaction increases, but the degree of change of the former is greater than that of the latter. The Brillouin fiber optic sensing technology provides a new method for monitoring the stress changes in the protective layer mining floor, achieving quantitative analysis of floor rock failure.