Ambient ultrafine particles exacerbate oxygen desaturation during sleep in patients with chronic obstructive pulmonary disease: New insights into the effect spectrum of ultrafine particles on susceptible populations.

The health effects of ultrafine particles (UFPs) are of growing global concern, but the epidemiological evidence remains limited. Sleep-disordered breathing (SDB) characterized by hypoxemia is a prevalent condition linked to many debilitating chronic diseases. However, the role of UFPs in the development of SDB is lacking. Therefore, this prospective panel study was performed to specifically investigate the association of short-term exposure to UFPs with SDB parameters in patients with chronic obstructive pulmonary disease (COPD). Ninety-one COPD patients completed 226 clinical visits in Beijing, China. Personal exposure to ambient UFPs of 0-7 days was estimated based on infiltration factor and time-activity pattern. Real-time monitoring of sleep oxygen saturation, spirometry, respiratory questionnaires and airway inflammation detection were performed at each clinical visit. Generalized estimating equation was used to estimate the effects of UFPs. Exposure to UFPs was significantly associated with increased oxygen desaturation index (ODI) and percent of the time with oxygen saturation below 90 % (T90), with estimates of 21.50 % (95%CI: 6.38 %, 38.76 %) and 18.75 % (95%CI: 2.83 %, 37.14 %), respectively, per 3442 particles/cm3 increment of UFPs at lag 0-3 h. Particularly, UFPs' exposure within 0-7 days was positively associated with the concentration of alveolar nitric oxide (CaNO), and alveolar eosinophilic inflammation measured by CaNO exceeding 5 ppb was associated with 29.63 % and 33.48 % increases in ODI and T90, respectively. In addition, amplified effects on oxygen desaturation were observed in current smokers. Notably, individuals with better lung function and activity tolerance were more affected by ambient UFPs due to longer time spent outdoors. To our knowledge, this is the first study to link UFPs to hypoxemia during sleep and uncover the key role of alveolar eosinophilic inflammation. Our findings provide new insights into the effect spectrum of UFPs and potential environmental and behavioral intervention strategies to protect susceptible populations.

Guava polysaccharides attenuate high fat and STZ-induced hyperglycemia by regulating gut microbiota and arachidonic acid metabolism.

This study investigated the hypoglycemic mechanism of guava polysaccharides (GP) through the gut microbiota (GM) and related metabolites. Our findings demonstrated that GP significantly mitigated high-fat diet- and streptozotocin-induced hyperglycemia, insulin resistance, hyperlipidemia, elevated alanine aminotransferase, high hepatic inflammation levels, and prevented pancreatic atrophy and hepatomegaly. Interestingly, the benefits of GP were attributed to alterations in the GM. GP decreased the ratio of Firmicutes to Bacteroidetes, significantly inhibiting deleterious bacteria, including Uncultured_f_Desulfovibrionaceae, Bilophila, and Desulfovibrio, while promoting the proliferation of probiotic Bifidobacterium and Bacteroides. In addition, GP promoted the generation of short-chain fatty acids. Notably, the arachidonic acid (AA) metabolism pathway was enriched in liver metabolites. GP significantly elevated hepatic AA and 15-hydroxyeicosatetraenoic acid, while reducing prostaglandin E2 and 5- and 12-hydroxyeicosatetraenoic acid. This modulation is accompanied by the downregulation of hepatic cyclooxygenase-1, 12-lipoxygenase, P38, and c-Jun N-terminal kinase mRNA expression, and the upregulation of cytochrome P4502J5 and insulin receptor substrate 1/2 mRNA expression. However, GP antibiotic treatment did not induce significant alterations in FBG and AA levels or gene expression. Overall, our findings suggest that the hypoglycemic effect of GP may be intricately linked to alterations in AA metabolism, which depends on the GM.

Novel Dynamic Event-Triggered Consensus Control of Multiagent Systems With Markovian Switching Topologies Under DoS Attacks.

This article focuses on the issue of novel dynamic event-triggered consensus control of multiagent systems (MASs) with denial-of-service (DoS) attacks. Different from the conventional Markovian switching topologies, the generally uncertain semi-Markovian (GUSM) switching topologies with partially unknown elements and time-dependent uncertainties are constructed for the leader-following MASs by considering the equipment performance and external uncertain environment influence. To save communication resources, the novel dynamic memory event-triggered strategy (DMETS) is presented to decrease the frequency of communication between agents. Some secure consensus control criteria are established for the MASs with GUSM switching topologies and DoS attacks due to the potential system communication disruption caused by attackers. Finally, two physical system examples are designed to prove the effectiveness of the presented method.

From Traditional to Intelligent, A Review of Application and Progress of Sensory Analysis in Alcoholic Beverage Industry.

Sensory analysis is an interdisciplinary field that combines multiple disciplines to analyze food qualitatively and quantitatively. At present, this analysis method has been widely used in product development, quality control, marketing, flavor analysis, safety supervision and inspection of alcoholic beverages. Due to the changing needs of analysis, new and more optimized methods are still emerging. Thereinto, intelligent and biometric technologies with growing attention have also been applied to sensory analysis. This work summarized the sensory analysis methods from three aspects, including traditional artificial sensory analysis, intelligent sensory technology, and innovative technologies. Meanwhile, the application sensory analysis in alcoholic beverages and its industrial production was scientifically emphasized. Moreover, the future tendency of sensory analysis in the alcoholic beverage industry is also highlights.

Commercial markups on pediatric oncology drugs at 340B pediatric hospitals.

Eligible pediatric hospitals can purchase clinician-administered drugs at discounted rates through the 340B Drug Pricing Program and charge payers prices exceeding drug acquisition costs, but the magnitude of these markups is not known. In a study of newly approved oncology drugs at pediatric 340B hospitals, median negotiated prices ranged from 102% (interquartile range [IQR]: 91%-156%) of average sales price (ASP) at Phoenix Children's Hospital to 630% (IQR: 526%-630%) at Driscoll Children's Hospital. Pediatric hospitals participating in the federal 340B Drug Pricing Program can extract steep payments on new drugs from commercial insurers, though with wide variation between and within hospitals.

Detection of Ascorbic Acid by Two-Dimensional Conductive Metal-Organic Framework-Based Electrochemical Sensors.

The realization of efficient and accurate detection of biomolecules has become a key scientific issue in the field of life sciences. With the rapid development of nanotechnology, electrochemical sensors constructed from the superior physical and chemical properties of nanomaterials show faster and more accurate detection. Among nanomaterials, two-dimensional conductive MOF (2D cMOF) is considered to be a star material in electrochemical sensors due to its remarkable conductivity, high porosity, and stability. In this paper, a Cu3(HHTP)2/SPE electrochemical sensor for the detection of ascorbic acid (AA) was constructed by modifying 2D cMOF (Cu3(HHTP)2) on the surface of the screen-printed electrode (SPE). The sensor exhibited excellent catalytic activity in the detection of AA, with a lower detection limit of 2.4 µmol/L (S/N = 3) and a wide linear range of 25-1645 µmol/L. This high catalytic activity can be attributed to the abundant catalytic sites in Cu3(HHTP)2 and the rapid electron transfer between Cu+ and Cu2+, which accelerates the oxidation of AA. This work lays a foundation for the subsequent development of MOFs with special electrochemical catalytic properties and the integration of 2D cMOF into intelligent electrical analysis devices.

Resilience as a moderator of the relationship between stress and different symptom dimensions of depression in adolescents with a history of childhood maltreatment: A multi-wave longitudinal study.

BACKGROUND: Although childhood maltreatment is a key risk factor for the development of psychopathology including depression in later life, not all children who have been maltreated subsequently become depressed. OBJECTIVE: The study aimed to examine the potentially moderating influence of resilience on the relationship between daily stress and different symptom dimensions of depression in adolescents with a history of childhood maltreatment. PARTICIPANTS AND SETTING: A sample of students (n = 999) aged 12-16 years from middle schools with a history of childhood maltreatment participated in this study. METHODS: A multi-wave longitudinal study was conducted over 12 months. At baseline, adolescent participants completed standardized self-report measures of resilience, depression, and daily stress. The measures of depression and stress were re-administered every three months for the subsequent 12 months. Multi-level modeling was undertaken to analyze the data. RESULTS: In adolescents with a history of childhood maltreatment, lower resilience scores were associated with greater increases in depressed affect, absence of positive affect and somatic symptom, but not the interpersonal concerns symptom dimensions of depression following daily stress. Resilience is therefore as one explanation for the discrepant findings regarding the relationship between stress and different symptom dimensions of depression, especially with regard to the stress-related depressive dimensions. CONCLUSION: Resilience appears to moderate the relationship between daily stress and depression and protect against developing depression in children who have been maltreated. Findings provide potential explanation for the effectiveness of resilience-related therapy in treating depressive symptoms.

Exploration of the mechanism of Traditional Chinese Medicine for anxiety and depression in patients with diarrheal irritable bowel syndrome based on network pharmacology and meta-analysis.

Background: The efficacy of Chinese herbal medicine (CHM) in managing irritable bowel syndrome with diarrhea (IBS-D) accompanied by anxiety and depression remains uncertain. Thus, a systematic review was carried out employing meta-analysis and network pharmacology to ascertain the efficacy and underlying mechanisms of CHM therapy. Methods: By conducting a systematic review, including literature search, screening, and data extraction, we identified 25 randomized controlled trials to assess CHM's effectiveness in treating irritable bowel syndrome alongside anxiety and depression. Network pharmacology was utilized to scrutinize the metabolite utility of CHM in addressing this condition. Potential primary mechanisms were synthesized using information sourced from the PubMed database. Results: Twenty-five studies, including 2055 patients, were analyzed, revealing significant treatment efficacy for IBS-D in the trial group compared to controls [OR = 4.01, 95% CI (2.99, 5.36), I2 = 0%] Additionally, treatment for depression [SMD = -1.08, 95% CI (-1.30, -0.86), p < 0.00001, I2 = 68%; SDS: SMD = -1.69, 95% CI (-2.48, -0.90), p < 0.0001, I2 = 96%] and anxiety [HAMA: SMD = -1.29, 95% CI (-1.68, -0.91), p < 0.00001, I2 = 89%; SAS: SMD = -1.75, 95% CI (-2.55, -0.95), p < 0.00001, I2 = 96%] significantly improved in the trial group. Furthermore, the trial group exhibited a significantly lower disease relapse rate [OR = 0.30, 95% CI (0.20, 0.44), p < 0.00001, I2 = 0%]. CHM treatment consistently improved IBS severity (IBS-SSS) and symptom scores. Network pharmacology analysis identified key chemical metabolites in traditional Chinese medicine formulations, including Beta-sitosterol, Stigmasterol, Quercetin, Naringenin, Luteolin, Kaempferol, Nobiletin, Wogonin, Formononetin, and Isorhamnetin. Utilizing the STRING database and Cytoscape v3.9.0 software, a protein-protein interaction (PPI) network revealed the top eight key targets: IL-6, TNF, PPARG, PTGS2, ESR1, NOS3, MAPK8, and AKT1, implicated in anti-inflammatory responses, antioxidant stress modulation, and neurotransmitter homeostasis maintenance. Conclusion: Chinese Herbal Medicine (CHM) offers a promising and safe treatment approach for patients dealing with Diarrheal Irritable Bowel Syndrome (IBS-D) accompanied by anxiety and depression; thus, indicating its potential for practical implementation. The most active metabolites of CHM could simultaneously act on the pathological targets of IBS-D, anxiety, and depression.The diverse scope of CHM's therapeutic role includes various aspects and objectives, underscoring its potential for broad utilization.

Deciphering the microbial landscape of lower respiratory tract infections: insights from metagenomics and machine learning.

Background: Lower respiratory tract infections represent prevalent ailments. Nonetheless, current comprehension of the microbial ecosystems within the lower respiratory tract remains incomplete and necessitates further comprehensive assessment. Leveraging the advancements in metagenomic next-generation sequencing (mNGS) technology alongside the emergence of machine learning, it is now viable to compare the attributes of lower respiratory tract microbial communities among patients across diverse age groups, diseases, and infection types. Method: We collected bronchoalveolar lavage fluid samples from 138 patients diagnosed with lower respiratory tract infections and conducted mNGS to characterize the lung microbiota. Employing various machine learning algorithms, we investigated the correlation of key bacteria in patients with concurrent bronchiectasis and developed a predictive model for hospitalization duration based on these identified key bacteria. Result: We observed variations in microbial communities across different age groups, diseases, and infection types. In the elderly group, Pseudomonas aeruginosa exhibited the highest relative abundance, followed by Corynebacterium striatum and Acinetobacter baumannii. Methylobacterium and Prevotella emerged as the dominant genera at the genus level in the younger group, while Mycobacterium tuberculosis and Haemophilus influenzae were prevalent species. Within the bronchiectasis group, dominant bacteria included Pseudomonas aeruginosa, Haemophilus influenzae, and Klebsiella pneumoniae. Significant differences in the presence of Pseudomonas phage JBD93 were noted between the bronchiectasis group and the control group. In the group with concomitant fungal infections, the most abundant genera were Acinetobacter and Pseudomonas, with Acinetobacter baumannii and Pseudomonas aeruginosa as the predominant species. Notable differences were observed in the presence of Human gammaherpesvirus 4, Human betaherpesvirus 5, Candida albicans, Aspergillus oryzae, and Aspergillus fumigatus between the group with concomitant fungal infections and the bacterial group. Machine learning algorithms were utilized to select bacteria and clinical indicators associated with hospitalization duration, confirming the excellent performance of bacteria in predicting hospitalization time. Conclusion: Our study provided a comprehensive description of the microbial characteristics among patients with lower respiratory tract infections, offering insights from various perspectives. Additionally, we investigated the advanced predictive capability of microbial community features in determining the hospitalization duration of these patients.

The landscape of programmed cell death-related lncRNAs in Alzheimer's disease and Parkinson's disease.

This study delivers a thorough analysis of long non-coding RNAs (lncRNAs) in regulating programmed cell death (PCD), vital for neurodegenerative diseases like Alzheimer's disease (AD) and Parkinson's disease (PD). We propose a new framework PCDLnc, and identified 20 significant lncRNAs, including HEIH, SNHG15, and SNHG5, associated with PCD gene sets, which were known for roles in proliferation and apoptosis in neurodegenerative diseases. By using GREAT software, we identified regulatory functions of top lncRNAs in different neurodegenerative diseases. Moreover, lncRNAs cis-regulated mRNAs linked to neurodegeneration, including JAK2, AKT1, EGFR, CDC42, SNCA, and ADIPOQ, highlighting their therapeutic potential in neurodegenerative diseases. A further exploration into the differential expression of mRNA identified by PCDLnc revealed a role in apoptosis, ferroptosis and autophagy. Additionally, protein-protein interaction (PPI) network analysis exposed abnormal interactions among key genes, despite their consistent expression levels between disease and normal samples. The randomforest model effectively distinguished between disease samples, indicating a high level of accuracy. Shared gene subsets in AD and PD might serve as potential biomarkers, along with disease-specific gene sets. Besides, we also found the strong relationship between AD and immune infiltration. This research highlights the role of lncRNAs and their associated genes in PCD in neurodegenerative diseases, offering potential therapeutic targets and diagnostic markers for future study and clinical application.

Adaptive soft sensor using stacking approximate kernel based BLS for batch processes.

To deal with the highly nonlinear and time-varying characteristics of Batch Process, a model named adaptive stacking approximate kernel based broad learning system is proposed in this paper. This model innovatively introduces the approximate kernel based broad learning system (AKBLS) algorithm and the Adaptive Stacking framework, giving it strong nonlinear fitting ability, excellent generalization ability, and adaptive ability. The Broad Learning System (BLS) is known for its shorter training time for effective nonlinear processing, but the uncertainty brought by its double random mapping results in poor resistance to noisy data and unpredictable impact on performance. To address this issue, this paper proposes an AKBLS algorithm that reduces uncertainty, eliminates redundant features, and improves prediction accuracy by projecting feature nodes into the kernel space. It also significantly reduces the computation time of the kernel matrix by searching for approximate kernels to enhance its ability in industrial online applications. Extensive comparative experiments on various public datasets of different sizes validate this. The Adaptive Stacking framework utilizes the Stacking ensemble learning method, which integrates predictions from multiple AKBLS models using a meta-learner to improve generalization. Additionally, by employing the moving window method-where a fixed-length window slides through the database over time-the model gains adaptive ability, allowing it to better respond to gradual changes in industrial Batch Process. Experiments on a substantial dataset of penicillin simulations demonstrate that the proposed model significantly improves predictive accuracy compared to other common algorithms.

Mediating role of right superior corona microstructural changes in linking attentional control and trait anxiety among youth with childhood maltreatment.

This study explores the neural correlates between attentional control and trait anxiety among youth with a history of childhood maltreatment. Using diffusion tensor imaging, we investigated the microstructural integrity of brain white matter, particularly focusing on the right superior corona radiata (SCA-R). A total of 173 university students with experiences of childhood maltreatment underwent behavioral assessments using the Attentional Control Scale and trait anxiety measurements via the Spielberger State-Trait Anxiety Inventory. Our analysis found significant correlations between fractional anisotropy values in the SCA-R and trait anxiety levels, controlled for age and sex. Notably, SCA-R fractional anisotropy values partially mediated the relationship between attentional control and trait anxiety, suggesting a potential pathway through which attentional control could mitigate trait anxiety. These insights highlight attentional control as a potential mitigating factor against trait anxiety, particularly noting the partial mediation role of the SCA-R. Importantly, this study is descriptive and correlative, highlighting associations rather than causal relationships among the variables studied. These findings enhance our understanding of the neural mechanisms underlying anxiety in individuals with a history of childhood maltreatment.

Vitamin D is involved in the regulation of Cl- uptake in zebrafish (Danio rerio).

Cl- is a major anion in the bodily fluids of vertebrates, and maintaining its homeostasis is essential for normal physiological functions. Fishes inhabiting freshwater (FW) passively lose body fluid ions, including Cl-, to the external environment because of the electrochemical gradient of ions across the body surface. Therefore, FW fishes have to actively absorb Cl- from the surroundings to maintain ion homeostasis in their bodily fluids. Hormonal control is vital for modulating ion uptake in fish. Vitamin D is involved in the regulation of Ca2+ uptake and acid secretion in fish. In the present study, we found that the levels of bioactive vitamin D, 1α,25-dihydroxyvitamin D3 (1α,25(OH)2D3), significantly increased in zebrafish embryos and adults after exposure to water containing low levels of Cl-. Moreover, the administration of 1α,25(OH)2D3 treatment (20 µg/L) in zebrafish embryos, and intraperitoneal (i.p.) injection of 1α,25(OH)2D3 (5 µg/kg body mass) in zebrafish adults, resulting the increased Cl- content in bodily fluid in zebrafish. Na+-Cl- cotransporter 2b (NCC2b) and Cl- channel 2c (CLC2c) are specifically expressed during Cl- uptake by ionocytes in zebrafish. Our results indicated that the mRNA and protein expression of NCC2b and CLC2c considerably increased in the zebrafish with exogenous 1α,25(OH)2D3 treatment. Additionally, exogenous 1α,25(OH)2D3 administration increased the number of NCC2b- and CLC2c-expressing cells in yolk skins of zebrafish embryos and the gill filaments of zebrafish adults. Transcript signals of vitamin D receptors (VDRs) were identified in NCC2b-expressing cells. Knockdown of VDRa and VDRb significantly reduced the expression of NCC2b and CLC2c and the number of NCC2b- and CLC2c-expressing cells. These results indicate that vitamin D can affect Cl- uptake in zebrafish and extend our knowledge of the role of vitamin D in fish physiology.

Tsallis Entropy-Based Complexity-IPE Casualty Plane: A Novel Method for Complex Time Series Analysis.

Due to its capacity to unveil the dynamic characteristics of time series data, entropy has attracted growing interest. However, traditional entropy feature extraction methods, such as permutation entropy, fall short in concurrently considering both the absolute amplitude information of signals and the temporal correlation between sample points. Consequently, this limitation leads to inadequate differentiation among different time series and susceptibility to noise interference. In order to augment the discriminative power and noise robustness of entropy features in time series analysis, this paper introduces a novel method called Tsallis entropy-based complexity-improved permutation entropy casualty plane (TC-IPE-CP). TC-IPE-CP adopts a novel symbolization approach that preserves both absolute amplitude information and inter-point correlations within sequences, thereby enhancing feature separability and noise resilience. Additionally, by incorporating Tsallis entropy and weighting the probability distribution with parameter q, it integrates with statistical complexity to establish a feature plane of complexity and entropy, further enriching signal features. Through the integration of multiscale algorithms, a multiscale Tsallis-improved permutation entropy algorithm is also developed. The simulation results indicate that TC-IPE-CP requires a small amount of data, exhibits strong noise resistance, and possesses high separability for signals. When applied to the analysis of heart rate signals, fault diagnosis, and underwater acoustic signal recognition, experimental findings demonstrate that TC-IPE-CP can accurately differentiate between electrocardiographic signals of elderly and young subjects, achieve precise bearing fault diagnosis, and identify four types of underwater targets. Particularly in underwater acoustic signal recognition experiments, TC-IPE-CP achieves a recognition rate of 96.67%, surpassing the well-known multi-scale dispersion entropy and multi-scale permutation entropy by 7.34% and 19.17%, respectively. This suggests that TC-IPE-CP is highly suitable for the analysis of complex time series.

Regulation of SETD2 maintains immune regulatory function in macrophages to suppress airway allergy.

SET domain-containing 2 (SETD2) is a histone methyltransferase. It regulates the activity of H3K36me3 to enhance gene transcription. Macrophages (Mϕs) are one of the cell types involved in immune response. The purpose of this study is to clarify the role of SETD2 in regulating the immune property of Mϕ. The Mφs were isolated from the bronchoalveolar lavage fluid (BALF) and analysed through flow cytometry and RNA sequencing. A mouse strain carrying Mφs deficient in SETD2 was used. A mouse model of airway allergy was established with the ovalbumin/alum protocol. Less expression of SETD2 was observed in airway Mϕs in patients with allergic asthma. SETD2 of M2 cells was associated with the asthmatic clinical response. Sensitization reduced the expression of SETD2 in mouse respiratory tract M2 cells, which is associated with the allergic reaction. Depletion of SETD2 in Mφs resulted in Th2 pattern inflammation in the lungs. SETD2 maintained the immune regulatory ability in airway M2 cells. SETD2 plays an important role in the maintenance of immune regulatory property of airway Mφs.

Characterization of the immune suppressive functions of eosinophils.

Eosinophils account for a significant portion of immune cells in the body. It is well known that eosinophils play a role in the pathogenesis of many diseases. In which the interaction between eosinophils and other immune cells is incompletely understood. The aim of this study is to characterize the immune suppressive functions of eosinophils. In this study, an irway allergy mouse model was established. Eosinophils were isolated from the airway tissues using flow cytometry cell sorting. The RAW264.7 cell line was used to test the immune suppressive functions of eosinophils. We observed that eosinophils had immune suppressive functions manifesting inhibiting immune cell proliferation and cytokine release from other immune cells. The eosinophil's immune suppressive functions were mediated by eosinophil-derived molecules, such as eosinophil peroxidase (EPX) and major basic protein (MBP). The expression of Ras-like protein in the brain 27a (Rab27a) was detected in eosinophils, which controlled the release of MBP and EPX by eosinophils. Eosinophil mediators had two contrast effects on inducing inflammatory responses or rendering immune suppressive effects, depending on the released amounts. Administration of an inhibitor of Rab27a at proper dosage could alleviate experimental airway allergy. To sum up, eosinophils have immune suppressive functions and are also inflammation inducers. Rab27a governs the release of EPX and MBP from eosinophils, which leads to immune suppression or inflammation. Modulation of Rab27a can alleviate airway allergy responses by modulating eosinophil's immune suppressive functions, which has the translational potential for the management of eosinophil-related diseases.

Sleep disturbance in Angelman syndrome patients.

Angelman syndrome (AS) is a neurodevelopmental disorder caused by abnormal expression of the maternal ubiquitin protein ligase E3A gene (UBE3A). As one of the most challenging symptoms and important focuses of new treatment, sleep disturbance is reported to occur in 70-80% of patients with AS and has a serious impact on the lives of patients and their families. Although clinical studies and animal model studies have provided some clues, recent research into sleep disorders in the context of AS is still very limited. It is generally accepted that there is an interaction between neurodevelopment and sleep; however, there is no recognized mechanism for sleep disorders in AS patients. Accordingly, there are no aetiologically specific clinical treatments for AS-related sleep disorders. The most common approaches involve ameliorating symptoms through methods such as behavioural therapy and symptomatic pharmacotherapy. In recent years, preclinical and clinical studies on the targeted treatment of AS have emerged. Although precision therapy for restoring the UBE3A level and the function of its signalling pathways is inevitably hindered by many remaining obstacles, this approach has the potential to address AS-related sleep disturbance.

HO-1 upregulation promotes mitophagy-dependent ferroptosis in PM2.5-exposed hippocampal neurons.

Fine particulate matter (PM2.5) has been extensively implicated in the pathogenesis of neurodevelopmental disorders, but the underlying mechanism remains unclear. Recent studies have revealed that PM2.5 plays a role in regulating iron metabolism and redox homeostasis in the brain, which is closely associated with ferroptosis. In this study, the role and underlying mechanism of ferroptosis in PM2.5-induced neurotoxicity were investigated in mice, primary hippocampal neurons, and HT22 cells. Our findings demonstrated that exposure to PM2.5 could induce abnormal behaviors, neuroinflammation, and neuronal loss in the hippocampus of mice. These effects may be attributed to ferroptosis induced by PM2.5 exposure in hippocampal neurons. RNA-seq analysis revealed that the upregulation of iron metabolism-related protein Heme Oxygenase 1 (HO-1) and the activation of mitophagy might play key roles in PM2.5-induced ferroptosis in HT22 cells. Subsequent in vitro experiments showed that PM2.5 exposure significantly upregulated HO-1 in primary hippocampal neurons and HT22 cells. Moreover, PM2.5 exposure activated mitophagy in HT22 cells, leading to the loss of mitochondrial membrane potential, alterations in the expression of autophagy-related proteins LC3, P62, and mTOR, as well as an increase in mitophagy-related protein PINK1 and PARKIN. As a heme-degradation enzyme, the upregulation of HO-1 promotes the release of excess iron, genetically inhibiting the upregulation of HO-1 in HT22 cells could prevent both PM2.5-induced mitophagy and ferroptosis. Furthermore, pharmacological inhibition of mitophagy in HT22 cells reduced levels of ferrous ions and lipid peroxides, thereby preventing ferroptosis. Collectively, this study demonstrates that HO-1 mediates PM2.5-induced mitophagy-dependent ferroptosis in hippocampal neurons, and inhibiting mitophagy or ferroptosis may be a key therapeutic target to ameliorate neurotoxicity following PM2.5 exposure.

Patient-derived tumor-like cell clusters for personalized chemo- and immunotherapies in non-small cell lung cancer.

Many patient-derived tumor models have emerged recently. However, their potential to guide personalized drug selection remains unclear. Here, we report patient-derived tumor-like cell clusters (PTCs) for non-small cell lung cancer (NSCLC), capable of conducting 100-5,000 drug tests within 10 days. We have established 283 PTC models with an 81% success rate. PTCs contain primary tumor epithelium self-assembled with endogenous stromal and immune cells and show a high degree of similarity to the original tumors in phenotypic and genotypic features. Utilizing standardized culture and drug-response assessment protocols, PTC drug-testing assays reveal 89% overall consistency in prospectively predicting clinical outcomes, with 98.1% accuracy distinguishing complete/partial response from progressive disease. Notably, PTCs enable accurate prediction of clinical outcomes for patients undergoing anti-PD1 therapy by combining cell viability and IFN-γ value assessments. These findings suggest that PTCs could serve as a valuable preclinical model for personalized medicine and basic research in NSCLC.