A cuproptosis-based nanomedicine suppresses triple negative breast cancers by regulating tumor microenvironment and eliminating cancer stem cells.

Cuproptosis is a new kind of cell death that depends on delivering copper ions into mitochondria to trigger the aggradation of tricarboxylic acid (TCA) cycle proteins and has been observed in various cancer cells. However, whether cuproptosis occurs in cancer stem cells (CSCs) is unexplored thus far, and CSCs often reside in a hypoxic tumor microenvironment (TME) of triple negative breast cancers (TNBC), which suppresses the expression of the cuproptosis protein FDX1, thereby diminishing anticancer efficacy of cuproptosis. Herein, a ROS-responsive active targeting cuproptosis-based nanomedicine CuET@PHF is developed by stabilizing copper ionophores CuET nanocrystals with polydopamine and hydroxyethyl starch to eradicate CSCs. By taking advantage of the photothermal effects of CuET@PHF, tumor hypoxia is overcome via tumor mechanics normalization, thereby leading to enhanced cuproptosis and immunogenic cell death in 4T1 CSCs. As a result, the integration of CuET@PHF and mild photothermal therapy not only significantly suppresses tumor growth but also effectively inhibits tumor recurrence and distant metastasis by eliminating CSCs and augmenting antitumor immune responses. This study presents the first evidence of cuproptosis in CSCs, reveals that disrupting hypoxia augments cuproptosis cancer therapy, and establishes a paradigm for potent cancer therapy by simultaneously eliminating CSCs and boosting antitumor immunity.

Effect of industrial alkene ozonolysis on atmospheric H2SO4 formation.

This study has employed the master chemical mechanism (MCM) to investigate the influence of the ozone oxidation pathways in the atmospheric formation of H2SO4 from short-chain olefins in industrialized areas. In-situ H2SO4 formation data were obtained using a high-resolution chemical ionization time-of-flight mass spectrometer, and the simulated H2SO4 concentrations calculated using updated parameters for the MCM model exhibited good agreement with observations. In the simulation analysis of different reaction pathways involved in H2SO4 formation, hydroxyl radicals were found to dominate H2SO4 production during the daytime, while olefin ozone oxidation contributed up to 65% of total H2SO4 production during the night-time. A sensitivity analysis of the H2SO4 production parameters has revealed a high sensitivity to changes in sulfur dioxide, and a relatively high sensitivity to olefins with fast ozonolysis reaction rates and bimolecular reaction rates of resulting stabilized Criegee Intermediates. A high relative humidity promotes daytime H2SO4 formation, but has an inhibiting effect during the night-time due to the different dominant reaction pathways.

Pickle water ameliorates castor oil-induced diarrhea in mice by regulating the homeostasis of the gut microbiota and intestinal mucosal barrier.

Introduction: Diarrhea is a common clinical condition that can potentially be fatal. Current treatment options often have side effects, such as constipation and vomiting, and there remains a need for more effective therapies. Pickled vegetables, a famous traditional food in China, have been suggested in clinical studies to alleviate diarrhea in children, particularly through the use of pickle water (PW). However, the pharmacological effects and mechanisms of PW on intestinal health remain unclear. This study aimed to explore the protective effects of PW on castor oil-induced diarrhea in ICR mice and to investigate its potential mechanisms. Methods: To evaluate the antidiarrheal effects of PW, we used a castor oil-induced diarrhea model in ICR mice. Various indices were measured to assess the severity of diarrhea. After euthanizing the mice, oxidative stress markers in the ileum were assessed using biochemical methods, and the expression of tight junction-related proteins in the ileum was analyzed using Western blot. Additionally, 16S rRNA high-throughput sequencing was used to evaluate the diversity and composition of the intestinal flora. Results: The results showed that PW supplementation reduced body weight without significantly affecting organ index and liver function in the castor oil-induced diarrhea mice. PW also effectively reduced the dilution rate, diarrhea index, average loose stool grade, propelling distance of carbon powder, and intestinal propulsive rate while improving the pathological abnormality in the ileum. Furthermore, PW enhanced the activities of total antioxidant capacity (T-AOC), glutathione peroxidase (GSH-PX), and catalase (CAT) while reducing malonaldehyde (MDA) levels. PW also increased the expression of tight junction proteins zonula occludens-1 (ZO-1) and occludin in the ileum. Additionally, the analysis of 16S rDNA revealed that PW increased both α and ß diversity, improved the composition of the intestinal flora, and restored it to a normal level. Discussion: Collectively, dietary PW administration ameliorates Castor oil-induced diarrhea by restoring tight junctions between intestinal mucosal cells, suppressing oxidative stress, and regulating the composition of intestinal flora. These findings suggest that PW may be a promising strategy for managing diarrhea.

Anisotropic MXene@polydopamine- and Dialdehyde Carboxymethyl Cellulose-Modified Collagen Aerogel Supported Form-Stable Phase Change Composites for Light-To-Heat Conversion and Energy Storage.

As a renewable alternative heat source, the inherently intermittent feature of solar energy needs to be coordinated by reliable energy conversion and storage systems for utilizing the most abundant solar energy. Phase change materials (PCMs) are supposed to be advanced mediums for storing a great deal of heat generated by solar light. However, PCMs cannot effectively absorb and utilize solar energy due to leakage, low photothermal conversion efficiency, and poor thermal conductivity. Herein, we developed a collagen-based aerogel modified by dialdehyde carboxymethyl cellulose and polydopamine-modified two-dimensional transition-metal carbide/nitride (MXene@PDA) through bidirectional freeze-drying technology for supporting PCMs, which exhibited anisotropy in structure and properties. In particular, the thermal conductivity of the aerogel was 0.0871 W/(m·K) in the axial direction and 0.0504 W/(m·K) in the radial direction, demonstrating its anisotropic thermal insulation performance. Moreover, the final aerogel composite PCMs had been obtained via impregnating the obtained aerogel supporting matrix into polyethylene glycol (PEG) and hydrophobic treatment of polydimethylsiloxane, which exhibited outstanding solar-thermal conversion ability, good thermal storage capacity, advanced leakage-proof property, and antifouling performance. The loading rate of PEG was as high as 92.2%, and the melting enthalpy was 132.6 J/g. Most importantly, the water contact angle was evaluated to be 156.8°, indicating its superior antifouling performance. This material has intensive application prospects in the fields of solar energy collection, conversion, and storage.

Boosting Oxygen Evolution Reaction Performance on NiFe-Based Catalysts Through d-Orbital Hybridization.

Anion-exchange membrane water electrolyzers (AEMWEs) for green hydrogen production have received intensive attention due to their feasibility of using earth-abundant NiFe-based catalysts. By introducing a third metal into NiFe-based catalysts to construct asymmetrical M-NiFe units, the d-orbital and electronic structures can be adjusted, which is an important strategy to achieve sufficient oxygen evolution reaction (OER) performance in AEMWEs. Herein, the ternary NiFeM (M: La, Mo) catalysts featured with distinct M-NiFe units and varying d-orbitals are reported in this work. Experimental and theoretical calculation results reveal that the doping of La leads to optimized hybridization between d orbital in NiFeM and 2p in oxygen, resulting in enhanced adsorption strength of oxygen intermediates, and reduced rate-determining step energy barrier, which is responsible for the enhanced OER performance. More critically, the obtained NiFeLa catalyst only requires 1.58 V to reach 1 A cm-2 in an anion exchange membrane electrolyzer and demonstrates excellent long-term stability of up to 600 h.

A 25-Year Retrospective of the Use of AI for Diagnosing Acute Stroke: Systematic Review.

BACKGROUND: Stroke is a leading cause of death and disability worldwide. Rapid and accurate diagnosis is crucial for minimizing brain damage and optimizing treatment plans. OBJECTIVE: This review aims to summarize the methods of artificial intelligence (AI)-assisted stroke diagnosis over the past 25 years, providing an overview of performance metrics and algorithm development trends. It also delves into existing issues and future prospects, intending to offer a comprehensive reference for clinical practice. METHODS: A total of 50 representative articles published between 1999 and 2024 on using AI technology for stroke prevention and diagnosis were systematically selected and analyzed in detail. RESULTS: AI-assisted stroke diagnosis has made significant advances in stroke lesion segmentation and classification, stroke risk prediction, and stroke prognosis. Before 2012, research mainly focused on segmentation using traditional thresholding and heuristic techniques. From 2012 to 2016, the focus shifted to machine learning (ML)-based approaches. After 2016, the emphasis moved to deep learning (DL), which brought significant improvements in accuracy. In stroke lesion segmentation and classification as well as stroke risk prediction, DL has shown superiority over ML. In stroke prognosis, both DL and ML have shown good performance. CONCLUSIONS: Over the past 25 years, AI technology has shown promising performance in stroke diagnosis.

GPCR-mediated natural products and compounds: Potential therapeutic targets for the treatment of neurological diseases.

G protein-coupled receptors (GPCRs), widely expressed in the human central nervous system (CNS), perform numerous physiological functions and play a significant role in the pathogenesis of diseases. Consequently, identifying key therapeutic GPCRs targets for CNS-related diseases is garnering immense interest in research labs and pharmaceutical companies. However, using GPCRs drugs for treating neurodegenerative diseases has limitations, including side effects and uncertain effective time frame. Recognizing the rich history of herbal treatments for neurological disorders like stroke, Alzheimer's disease (AD), and Parkinson's disease (PD), modern pharmacological research is now focusing on the understanding of the efficacy of traditional Chinese medicinal herbs and compounds in modulating GPCRs and treatment of neurodegenerative conditions. This paper will offer a comprehensive, critical review of how certain natural products and compounds target GPCRs to treat neurological diseases. Conducting an in-depth study of herbal remedies and their efficacies against CNS-related disorders through GPCRs targeting will augment our strategies for treating neurological disorders. This will not only broaden our understanding of effective therapeutic methodologies but also identify the root causes of altered GPCRs signaling in the context of pathophysiological mechanisms in neurological diseases. Moreover, it would be informative for the creation of safer and more effective GPCR-mediated drugs, thereby establishing a foundation for future treatment of various neurological diseases.

Fecal microbiota transplantation as a new way for OVA-induced atopic dermatitis of juvenile mice.

Children all over the world suffer from atopic dermatitis (AD), a prevalent condition that impairs their health. Corticosteroids, which have long-term negative effects, are frequently used to treat AD. There has been a growing body of research on the gut microbiota's function in AD. Nevertheless, the function and underlying mechanisms of fecal microbiota transplantation (FMT) in AD children remain to be established. Therefore, in order to assess the preventive effects of FMT treatment on AD and investigate the mechanisms, we constructed an ovalbumin (OVA)-induced juvenile mouse AD model in this investigation. This study explored the role and mechanism of FMT treatment in AD through 16S RNA sequencing, pathological histological staining, molecular biology, and Flow cytometry. Results demonstrated that the FMT treatment improved the gut microbiota's diversity and composition, bringing it back to a level similar to that of a close donor. Following FMT treatment, OVA-specific antibodies were inhibited, immunoglobulin (Ig) E production was decreased, the quantity of mast cells and eosinophils was decreased, and specific inflammatory markers in the skin and serum were decreased. Further mechanistic studies revealed that FMT treatment induced CD103+ DCs and programmed cell death ligand 1 (PD-L1)/programmed cell death 1 (PD-1) expression in skin-draining lymph nodes and promoted Treg production to induce immune tolerance and suppress skin inflammation. Meanwhile, changes in the gut microbiota were substantially correlated with Th2 cytokines, OVA-specific antibodies, and PD-L1/PD-1. In conclusion, FMT regulates the Th1/Th2 immunological balance and the gut microbiota. It may also inhibit AD-induced allergy responses through the PD-L1/PD-1 pathway, and providing a unique idea and possibly a fresh approach to the treatment of AD.

HunFlair2 in a cross-corpus evaluation of biomedical named entity recognition and normalization tools.

MOTIVATION: With the exponential growth of the life sciences literature, biomedical text mining (BTM) has become an essential technology for accelerating the extraction of insights from publications. The identification of entities in texts, such as diseases or genes, and their normalization, i.e. grounding them in knowledge base, are crucial steps in any BTM pipeline to enable information aggregation from multiple documents. However, tools for these two steps are rarely applied in the same context in which they were developed. Instead, they are applied "in the wild", i.e. on application-dependent text collections from moderately to extremely different from those used for training, varying e.g. in focus, genre or text type. This raises the question whether the reported performance, usually obtained by training and evaluating on different partitions of the same corpus, can be trusted for downstream applications. RESULTS: Here, we report on the results of a carefully designed cross-corpus benchmark for entity recognition and normalization, where tools were applied systematically to corpora not used during their training. Based on a survey of 28 published systems, we selected five, based on pre-defined criteria like feature richness and availability, for an in-depth analysis on three publicly available corpora covering four entity types. Our results present a mixed picture and show that cross-corpus performance is significantly lower than the in-corpus performance. HunFlair2, the redesigned and extended successor of the HunFlair tool, showed the best performance on average, being closely followed by PubTator Central. Our results indicate that users of BTM tools should expect a lower performance than the original published one when applying tools in "the wild" and show that further research is necessary for more robust BTM tools. AVAILABILITY AND IMPLEMENTATION: All our models are integrated into the NLP framework flair: Https://github.com/flairNLP/flair. Code to reproduce our results is available at: Https://github.com/hu-ner/hunflair2-experiments. SUPPLEMENTARY INFORMATION: Supplementary information are available at Bioinformatics online.

Reliability of the Unilateral Hearing Loss in Youth Instrument for Children With Single-Sided Deafness.

PURPOSE: While general practice parameter recommendations for children with unilateral hearing loss or single-sided deafness (SSD) have been published, clinically utilized subjective instruments specifically designed to assess this population are scarce. Treatment options are evaluated using audiometric data, speech perception data, and quality of life instruments. The Unilateral Hearing Loss in Youth (uniHELO) is a subjective assessment instrument that aims to evaluate the listening challenges in this population, but it has not yet been studied in a clinical setting. This study examined the reliability of the uniHELO among children with SSD. METHOD: This was a prospective within-subject study. Nine patients with SSD, aged 8-14 years, were enrolled. Participants had not used a personal hearing device for at least 6 months prior to enrollment. The uniHELO instrument was administered at two clinic visits separated by 3-4 weeks. For comparison, the Pediatric and Parent Speech, Spatial, and Qualities of Hearing Scale (SSQ) instruments were administered during the same visits. RESULTS: uniHELO scores were not significantly different between the first and second visits. The correlations of scale scores over time were: .96 for the uniHELO, which suggests excellent test-retest reliability; .84 for the Parent SSQ, which also suggests excellent test-retest reliability; and .27 for the Pediatric SSQ, which suggests poor test-retest reliability compared to the Parent SSQ and uniHELO. CONCLUSIONS: Within-subject scale uniHELO scores between clinic visits showed excellent test-retest reliability across items. The test-retest reliability scores for the uniHELO were also stronger than those for the Parent and Pediatric SSQ. These data support the use of the uniHELO to evaluate listening challenges in children with SSD.

Identification of MYC genes in four Cucurbitaceae species and their roles in the response to temperature stress.

BACKGROUND: Myelocytomatosis (MYC) transcription factors are crucial mediators of the response of plants to environmental stresses through via binding to DNA regulatory regions. However, few systematic characterizations of MYC genes are available in Cucurbitaceae species. RESULTS: In this study, we identified 10, 8, 12, and 10 MYC genes in Cucumis sativus, Cucumis melo, Citrullus lanatus, and Benincasa hispida, respectively. Characterization revealed that all of the MYC proteins contain a highly conserved H4-V5-E6-E8-R9-R11-R12 sequence, which is essential for the binding of DNA regulatory regions. Evolutionary analysis enabled us to categorize 40 predicted MYC proteins from seven species into five distinct groups and revealed that the expansion of the MYC genes occurred before the divergence of monocots and dicots. The upstream promoter regions of the MYC genes contain a variety of developmental, stress, and hormone-responsive regulatory elements. The expression of cucumber MYC genes varies significantly across organs, with particularly high expression of CsaV3_3G001710 observed across all organs. Transcriptomic analysis revealed that certain cucumber MYC genes undergo specific upregulation or downregulation in response to both biotic and abiotic stressors. In particular, under temperature stress, the cucumber genes CsaV3_3G007980 and CsaV3_3G001710 were significantly upregulated. Interestingly, the homologs of these two genes in C. lanatus presented a similar expression pattern to that in C. sativus, whereas in B. hispida, they presented the opposite pattern, i.e., significant downregulation. These findings indicated that these two genes indeed respond to temperature stress but with different expression patterns, highlighting the divergent functions of homologous genes across different species. CONCLUSIONS: This study analyzed the size and composition of the MYC gene family in four Cucurbitaceae species and investigated stress-responsive expression profiles, especially under temperature stress. All the results showed that MYC genes play important roles in development and stress responses, laying a theoretical foundation for further investigations of these response mechanisms.

Efficient CRISPR-mediated genome editing can be initiated by embryonic injection but not by ovarian delivery in the beetle Tribolium castaneum.

The clustered regularly interspaced small palindromic repeats (CRISPR) / CRISPR-associated nuclease 9 (Cas9)-mediated gene editing technology has revolutionized the study of fundamental biological questions in various insects. Diverse approaches have been developed to deliver the single-guide RNA (sgRNA) and Cas9 to the nucleus of insect embryos or oocytes to achieve gene editing, including the predominant embryonic injection methods and alternative protocols through parental ovary delivery. However, a systematic comparative study of these approaches is limited, especially within a given insect. Here, we focused on revealing the detailed differences in CRISPR/Cas9-mediated gene editing between the embryo and ovary delivery methods in the beetle Tribolium castaneum, using the cardinal and tyrosine hydroxylase (TH) as reporter genes. We demonstrated that both genes could be efficiently edited by delivering Cas9/sgRNA ribonucleoproteins to the embryos by microinjection, leading to the mutant phenotypes and indels in the target gene sites. Next, the Cas9/sgRNA complex, coupled with a nanocarrier called Branched Amphiphilic Peptide Capsules (BAPC), were delivered to the ovaries of parental females to examine the efficacy of BAPC-mediated gene editing. Although we observed that a small number of beetles' progeny targeting the cardinal exhibited the expected white-eye phenotype, unexpectedly, no target DNA indels were found following subsequent sequencing analysis. In addition, we adopted a novel approach termed "direct parental" CRISPR (DIPA-CRISPR). However, we still failed to find gene-editing events in the cardinal or TH gene-targeted insects. Our results indicate that the conventional embryonic injection of CRISPR is an effective method to initiate genome editing in T. castaneum. However, it is inefficient by the parental ovary delivery approach.

A new species of the genus Serangium Blackburn (Coleoptera, Coccinellidae) from China, with description of the immature stages.

A new species Serangiumxinpingensis Huang & Wang, sp. nov. is described from Yunnan Province, China, as a newly discovered predator on Bemisiatabaci Gennadius (Hemiptera, Sternorrhyncha, Aleyrodidae). The new species is a valuable addition to the 14 species of this genus in China known before. A diagnosis, detailed description, including the structure of its immature stages, illustrations, and the distribution of the new species are provided.

Prediction and interpretive of motor vehicle traffic crashes severity based on random forest optimized by meta-heuristic algorithm.

Providing accurate prediction of the severity of traffic collisions is vital to improve the efficiency of emergencies and reduce casualties, accordingly improving traffic safety and reducing traffic congestion. However, the issue of both the predictive accuracy of the model and the interpretability of predicted outcomes has remained a persistent challenge. We propose a Random Forest optimized by a Meta-heuristic algorithm prediction framework that integrates the spatiotemporal characteristics of crashes. Through predictive analysis of motor vehicle traffic crash data on interstate highways within the United States in 2020, we compared the accuracy of various ensemble models and single-classification prediction models. The results show that the Random Forest (RF) model optimized by the Crown Porcupine Optimizer (CPO) has the best prediction results, and the accuracy, recall, f1 score, and precision can reach more than 90 %. We found that factors such as Temperature and Weather are closely related to vehicle traffic crashes. Closely related indicators were analyzed interpretatively using a geographic information system (GIS) based on the characteristic importance ranking of the results. The framework enables more accurate prediction of motor vehicle traffic crashes and discovers the important factors leading to motor vehicle traffic crashes with an explanation. The study proposes that in some areas consideration should be given to adding measures such as nighttime lighting devices and nighttime fatigue driving alert devices to ensure safe driving. It offers references for policymakers to address traffic management and urban development issues.

The effect of different exercise on physical fitness, cognition, and mental health in healthy older adults.

Objective: This study aimed to examine the effects of different exercise programs on physical fitness, cognition, and mental health in healthy older adults. Methods: A randomized controlled study was performed with 89 healthy older adults. They were separated into four groups: the control (Con; n = 20), physical activity (PA; n = 23), cognitive training (CT; n = 23), and physical activity coupled with cognitive training groups (PA + CT; n = 23). The subjects in PA, CT, and PA + CT groups received exercise programs that lasted 40 min daily, conducted at least three days a week for 20 weeks. The PA group received regular aerobic physical activity interventions, the CT group received cognitive training interventions, and the PA + CT group received physical activity combined with cognitive training interventions. Physical fitness (by chair stand, biceps curl, 2-min step, 8-step up and walk, and sit and reach tests), cognitive function (attention, simple reaction time, and spatial memory), and mental health (anxiety and depression status) were evaluated before and after 20 weeks. Results: The body composition results reveal no significant effects among the four groups after 20 weeks before and after aerobic exercise interventions (p > 0.05). Compared with Con, the PA, CT, and PA + CT groups significantly improved physical fitness parameters (p < 0.05). The post-hoc analysis demonstrated that the PA and PA + CT groups had higher fitness levels than the CT group. Similarly, a significant difference was observed in the cognitive index among the four groups (p < 0.05). As determined by post-hoc analysis, attention and simple reaction time differed sequentially between the Con, PA, CT, and PA + CT groups. The spatial memory was superior in the PA, CT, and PA + CT groups compared to the Con group (p < 0.05), with the PA + CT group exhibiting the highest level of performance. However, there was no significant difference in the mental health parameters among all the groups (p < 0.05). Conclusion: A 20-week intervention involving different exercise methods can enhance physical fitness, cognition, and mental health in older adults. These methods include physical activity, cognitive training, and a combination of physical and cognitive training. The combined physical activity and cognitive training interventions yielded more favorable outcomes than individual physical or cognitive training interventions.

Comprehensive multi-omics profiling identifies novel molecular subtypes of pancreatic ductal adenocarcinoma.

Pancreatic cancer, a highly fatal malignancy, is predicted to rank as the second leading cause of cancer-related death in the next decade. This highlights the urgent need for new insights into personalized diagnosis and treatment. Although molecular subtypes of pancreatic cancer were well established in genomics and transcriptomics, few known molecular classifications are translated to guide clinical strategies and require a paradigm shift. Notably, chronically developing and continuously improving high-throughput technologies and systems serve as an important driving force to further portray the molecular landscape of pancreatic cancer in terms of epigenomics, proteomics, metabonomics, and metagenomics. Therefore, a more comprehensive understanding of molecular classifications at multiple levels using an integrated multi-omics approach holds great promise to exploit more potential therapeutic options. In this review, we recapitulated the molecular spectrum from different omics levels, discussed various subtypes on multi-omics means to move one step forward towards bench-to-beside translation of pancreatic cancer with clinical impact, and proposed some methodological and scientific challenges in store.

Study on the uptake of Gastrodin in the liver.

Background: Gastrodin is the active monomer of the Chinese herb Rhizoma Gastrodiae with the largest quantity of active components. Gastrodin is commonly used in the treatment of central nervous system disorders such as headaches and epilepsy due to its sedating and hypnotic properties. Its pharmacological mechanism and clinical application have been extensively explored due to its low toxicity. Methods: To investigate the molecular mechanism of hepatic uptake of Gastrodin in rats, animals were randomly assigned to three groups: control group, rifampicin (RIF) group, and adrenalone (ADR) group. Blood samples were collected through the cardiac puncture 90, 180, and 300 min after injection, respectively. Rats were sacrificed 300 min after administration, and liver tissue was collected. Gastrodin concentration was determined by HPLC, and the Kp value was calculated. Results: After administering the inhibitors of organic cation transporters (OCTs) and organic anion transporting polypeptides (OATPs), the KP values in the experimental groups were significantly lower compared to the blank control group (P < 0.05). Conclusions: These findings imply that Gastrodin may be a substrate for both OCTs and OATPs.

Multi-omics Analysis to Identify Key Immune Genes for Osteoporosis based on Machine Learning and Single-cell Analysis.

OBJECTIVE: Osteoporosis is a severe bone disease with a complex pathogenesis involving various immune processes. With the in-depth understanding of bone immune mechanisms, discovering new therapeutic targets is crucial for the prevention and treatment of osteoporosis. This study aims to explore novel bone immune markers related to osteoporosis based on single-cell and transcriptome data, utilizing bioinformatics and machine learning methods, in order to provide novel strategies for the diagnosis and treatment of the disease. METHODS: Single cell and transcriptome data sets were acquired from Gene Expression Omnibus (GEO). The data was then subjected to cell communication analysis, pseudotime analysis, and high dimensional WGCNA (hdWGCNA) analysis to identify key immune cell subpopulations and module genes. Subsequently, ConsensusClusterPlus analysis was performed on the key module genes to identify different diseased subgroups in the osteoporosis (OP) training set samples. The immune characteristics between subgroups were evaluated using Cibersort, EPIC, and MCP counter algorithms. OP's hub genes were screened using 10 machine learning algorithms and 113 algorithm combinations. The relationship between hub genes and immunity and pathways was established by evaluating the immune and pathway scores of the training set samples through the ESTIMATE, MCP-counter, and ssGSEA algorithms. Real-time fluorescence quantitative PCR (RT-qPCR) testing was conducted on serum samples collected from osteoporosis patients and healthy adults. RESULTS: In OP samples, the proportions of bone marrow-derived mesenchymal stem cells (BM-MSCs) and neutrophils increased significantly by 6.73% (from 24.01% to 30.74%) and 6.36% (from 26.82% to 33.18%), respectively. We found 16 intersection genes and four hub genes (DND1, HIRA, SH3GLB2, and F7). RT-qPCR results showed reduced expression levels of DND1, HIRA, and SH3GLB2 in clinical blood samples of OP patients. Moreover, the four hub genes showed positive correlations with neutrophils (0.65-0.90), immature B cells (0.76-0.92), and endothelial cells (0.79-0.87), while showing negative correlations with myeloid-derived suppressor cells (negative 0.54-0.73), T follicular helper cells (negative 0.71-0.86), and natural killer T cells (negative 0.75-0.85). CONCLUSION: Neutrophils play a crucial role in the occurrence and development of osteoporosis. The four hub genes potentially inhibit metabolic activities and trigger inflammation by interacting with other immune cells, thereby significantly contributing to the onset and diagnosis of OP.

Neural Encoding for Spatial Release from Informational Masking and its Correlation with Behavioral Metrics.

The central auditory system encompasses two primary functions: identification and localization. Spatial release from masking (SRM) highlights speech recognition in competing noise and improves the listening experience when a spatial cue is introduced between noise and target speech. This assessment focuses on the integrity of auditory function and holds clinical significance. However, infants or pre-lingual subjects sometimes provide less reliable results. This study investigates the value of cortical auditory evoked potentials (CAEPs) onset and acoustic change complex (ACC) as an objective measurement of SRM. Thirty normal-hearing young adults (11 males) were recruited. We found the spatial separation of signals and noise (±90 degrees symmetrically) resulted in a signal-to-noise ratio (SNR) improvement of 9.00 ± 1.71 dB behaviorally. It significantly enhanced cortical processing at all SNR levels, shortened CAEPs latencies, and increased amplitudes, resulting in a greater number of measurable peaks for ACC. SRM showed mild to moderate correlations with the differences between the two conditions in CAEP measures. The regression model combining N1'-P2' amplitude at 5 dB SNR (R2 = 0.26), P1 amplitude at 0 dB SNR (R2 = 0.14), and P1 latency at -5 dB SNR (R2 = 0.15), explained 45.3% of the variance in SRM. Our study demonstrates that introducing spatial cues can improve speech perception and enhance central auditory processing in normal-hearing young adults. CAEPs may contribute to predictions about SRM and hold potential for practical application.