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Accumulation of senescent cells in organs and tissues is a hallmark of aging and known to contribute to age-related diseases. Although aging-associated immune dysfunction, or immunosenescence, is known to contribute to this process, the underlying mechanism remains elusive. Here, we report that type 2 cytokine signaling deficiency accelerated aging and, conversely, that the interleukin-4 (IL-4)-STAT6 pathway protected macrophages from senescence. Mechanistically, activated STAT6 promoted the expression of genes involved in DNA repair both via homologous recombination and Fanconi anemia pathways. Conversely, STAT6 deficiency induced release of nuclear DNA into the cytoplasm to promote tissue inflammation and organismal aging. Importantly, we demonstrate that IL-4 treatment prevented macrophage senescence and improved the health span of aged mice to an extent comparable to senolytic treatment, with further additive effects when combined. Together, our findings support that type 2 cytokine signaling protects macrophages from immunosenescence and thus hold therapeutic potential for improving healthy aging.
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Senescencia Celular , Interleucina-4 , Animales , Ratones , Interleucina-4/metabolismo , Envejecimiento/genética , Macrófagos , InflamaciónRESUMEN
MOTIVATION: A key challenge in metabolomics is annotating measured spectra from a biological sample with chemical identities. Currently, only a small fraction of measurements can be assigned identities. Two complementary computational approaches have emerged to address the annotation problem: mapping candidate molecules to spectra, and mapping query spectra to molecular candidates. In essence, the candidate molecule with the spectrum that best explains the query spectrum is recommended as the target molecule. Despite candidate ranking being fundamental in both approaches, limited prior works incorporated rank learning tasks in determining the target molecule. RESULTS: We propose a novel machine learning model, Ensemble Spectral Prediction (ESP), for metabolite annotation. ESP takes advantage of prior neural network-based annotation models that utilize multilayer perceptron (MLP) networks and Graph Neural Networks (GNNs). Based on the ranking results of the MLP- and GNN-based models, ESP learns a weighting for the outputs of MLP and GNN spectral predictors to generate a spectral prediction for a query molecule. Importantly, training data is stratified by molecular formula to provide candidate sets during model training. Further, baseline MLP and GNN models are enhanced by considering peak dependencies through label mixing and multi-tasking on spectral topic distributions. When trained on the NIST 2020 dataset and evaluated on the relevant candidate sets from PubChem, ESP improves average rank by 23.7% and 37.2% over the MLP and GNN baselines, respectively, demonstrating performance gain over state-of-the-art neural network approaches. However, MLP approaches remain strong contenders when considering top five ranks. Importantly, we show that annotation performance is dependent on the training dataset, the number of molecules in the candidate set and candidate similarity to the target molecule. AVAILABILITY AND IMPLEMENTATION: The ESP code, a trained model, and a Jupyter notebook that guide users on using the ESP tool is available at https://github.com/HassounLab/ESP.
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Aprendizaje Automático , Metabolómica , Redes Neurales de la Computación , Metabolómica/métodos , Algoritmos , MetabolomaRESUMEN
Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent chronic liver disease worldwide. If left untreated, MASLD can progress from simple hepatic steatosis to metabolic dysfunction-associated steatohepatitis (MASH), which is characterized by inflammation and fibrosis. Current treatment options for MASLD remain limited, leaving substantial unmet medical needs for innovative therapeutic approaches. Here, we show that PLIN2, a lipid droplet protein inhibiting hepatic lipolysis, serves as a promising therapeutic target for MASLD. Hepatic PLIN2 levels were markedly elevated in multiple MASLD mouse models induced by diverse nutritional and genetic factors. The liver-specific deletion of Plin2 exhibited significant anti-MASLD effects in these models. To translate this discovery into a therapeutic application, we developed a GalNAc-siRNA conjugate with enhanced stability chemistry and validated its potent and sustained efficacy in suppressing Plin2 expression in mouse livers. This siRNA therapeutic, named GalNAc-siPlin2, was shown to be biosafe in mice. Treatment with GalNAc-siPlin2 for 6-8 weeks led to a decrease in hepatic triglyceride levels by approximately 60% in high-fat diet- and obesity-induced MASLD mouse models, accompanied with increased hepatic secretion of very-low-density lipoprotein (VLDL)-triglyceride and enhanced thermogenesis in brown adipose tissues. 8-week treatment with GalNAc-siPlin2 significantly improved hepatic steatosis, inflammation and fibrosis in high fat/high fructose-induced MASH models compared to control group. As a proof of concept, we developed a GalNAc-siRNA therapeutic targeting human PLIN2, which effectively suppressed hepatic PLIN2 expression and ameliorated MASLD in humanized PLIN2 knock-in mice. Together, our results highlight the potential of GalNAc-siPLIN2 as a candidate MASLD therapeutic for clinical trials.
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Chlorosomes, the photosynthetic antenna complexes of green sulfur bacteria, are paradigms for light-harvesting elements in artificial designs, owing to their efficient energy transfer without protein participation. We combined magic angle spinning (MAS) NMR, optical spectroscopy and cryogenic electron microscopy (cryo-EM) to characterize the structure of chlorosomes from a bchQ mutant of Chlorobaculum tepidum. The chlorosomes of this mutant have a more uniform composition of bacteriochlorophyll (BChl) with a predominant homolog, [8Ethyl, 12Ethyl] BChl c, compared to the wild type (WT). Nearly complete 13C chemical shift assignments were obtained from well-resolved homonuclear 13C-13C RFDR data. For proton assignments heteronuclear 13C-1H (hCH) data sets were collected at 1.2 GHz spinning at 60 kHz. The CHHC experiments revealed intermolecular correlations between 132/31, 132/32, and 121/31, with distance constraints of less than 5 Å. These constraints indicate the syn-anti parallel stacking motif for the aggregates. Fourier transform cryo-EM data reveal an axial repeat of 1.49 nm for the helical tubular aggregates, perpendicular to the inter-tube separation of 2.1 nm. This axial repeat is different from WT and is in line with BChl syn-anti stacks running essentially parallel to the tube axis. Such a packing mode is in agreement with the signature of the Qy band in circular dichroism (CD). Combining the experimental data with computational insight suggests that the packing for the light-harvesting function is similar between WT and bchQ, while the chirality within the chlorosomes is modestly but detectably affected by the reduced compositional heterogeneity in bchQ.
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Bacterioclorofilas , Chlorobi , Chlorobi/genética , Chlorobi/metabolismo , Bacterioclorofilas/química , Mutación , Complejos de Proteína Captadores de Luz/química , Complejos de Proteína Captadores de Luz/metabolismo , Complejos de Proteína Captadores de Luz/genética , Microscopía por Crioelectrón , Proteínas Bacterianas/química , Proteínas Bacterianas/genética , Proteínas Bacterianas/metabolismoRESUMEN
BACKGROUND: The weight-adjusted waist index (WWI) is a quantitative anthropometric index that can be applied to evaluate obesity. This study examined the relationship between adult United States (US) residents' risk of diabetes mellitus type 2 (T2DM) and WWI. METHODS: The NHANES (National Health and Nutrition Examination Survey) 2001-2018 provided the data for this investigation. This study used multifactorial logistic regression analysis, smoothed curve fitting, subgroup analysis, and interaction tests to assess the association between WWI and T2DM. Additionally, threshold effects were calculated using a two-stage linear regression model. The receiver operating characteristic(ROC) curves evaluated the diagnostic ability of the WWI and commonly used obesity indicators. RESULTS: 20,477 participants were enrolled in the analysis, and patients with greater levels of WWI had a higher prevalence of T2DM. WWI and T2DM have a non-linear relationship, with a positive association found on the left side of the breakpoint (WWI = 12.35) (OR = 1.82, 95%CI:1.64-2.02), whereas, on the right side, no such relationship was found (OR = 0.9, 95%CI:0.61-1.34). For every unit rise in WWI, the probability of having T2DM increased by 67% after controlling for all other variables (OR:1.67,95%CI:1.53-1.83). Based on subgroup analyses, individuals under 40 had a higher correlation between WWI and T2DM (P < 0.001).ROC analyses showed that WWI had the best discrimination and accuracy in predicting T2DM compared to other obesity indicators (WC, BMI, and Weight). CONCLUSION: Higher WWI values had a higher prevalence of T2DM in US individuals, especially in adults under 40. WWI has the strongest ability to predict T2DM. Therefore, the importance of WWI in the early identification of T2DM in US adults should be emphasized.
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Diabetes Mellitus Tipo 2 , Encuestas Nutricionales , Obesidad , Humanos , Masculino , Femenino , Diabetes Mellitus Tipo 2/epidemiología , Diabetes Mellitus Tipo 2/diagnóstico , Estados Unidos/epidemiología , Persona de Mediana Edad , Adulto , Obesidad/epidemiología , Circunferencia de la Cintura , Factores de Riesgo , Anciano , Valor Predictivo de las Pruebas , Prevalencia , Estudios Transversales , Medición de Riesgo/métodosRESUMEN
OBJECTIVES: We determined the common clinical characteristics of patients infected with Helicobacter pylori (H. pylori) and investigated the relationship between H. pylori infection, and clinical symptoms, and gastroscopic manifestations. Our focus was specifically on the clinical manifestations in asymptomatic patients. METHODS: We obtained the physical examination data of patients who underwent the 14C urea breath test between January 2018 and December 2020 at our Hospital. Basic demographic data, questionnaire data on clinical symptoms, and clinical examination data of the patients were also collected, and the correlation analysis was performed. RESULTS: A total of 2863 participants were included in the study. The overall H. pylori infection rate was 26.30%. The clinical symptoms between H. pylori-positive patients and H. pylori-negative patients did not differ significantly (P > .05). However, H. pylori-positive patients exhibited more severe gastroscopic manifestations (P < .001). The 14C urea breath test disintegrations per minute (DPM) values in H. pylori-positive patients correlated with their serum pepsinogen and gastrin-17 levels. With an increase in the DPM value, more combinations of clinical symptoms appeared in the patients. Among H. pylori-positive patients, DPM levels in asymptomatic patients were lower than those in symptomatic patients (P < .001). However, gastroscopic manifestations did not vary significantly between asymptomatic and symptomatic patients (P > .05). CONCLUSION: Patients infected with H. pylori showed no specific gastrointestinal symptoms. Patients with asymptomatic infection showed lower DPM levels, but their gastroscopic manifestations were similar to those of patients with symptomatic infection, and their lesions were more severe than H. pylori-negative people.
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Infecciones por Helicobacter , Helicobacter pylori , Humanos , Infecciones Asintomáticas/epidemiología , Urea/análisis , Gastroscopía , Infecciones por Helicobacter/diagnóstico , Infecciones por Helicobacter/epidemiología , Radioisótopos de CarbonoRESUMEN
In this study, a microcosm experiment was conducted to investigate the effects of Na2S2O8 preoxidation combined with biostimulation on petroleum-contaminated soil remediation. The response of microbial community during this process was explored using BIOLOG ECO microplate carbon utilization method and 16â¯s rDNA high-throughput sequencing. The results showed that use of 10â¯mg/g Na2S2O8 removed 19.8â¯% of the petroleum hydrocarbons, reduced soil biotoxicity and did not affect soil microbial activity compared to other concentrations. Therefore, sodium persulfate of ca. 10â¯mg/g was used to oxidize petroleum in soil before the biostimulation experiment with organic and inorganic fertilizers. Our finding showed that the content of total petroleum hydrocarbons (TPHs) in soil was reduced by 43.3â¯% in inorganic fertilizer treatment after 60 days. The results of BIOLOG ECO microplate carbon utilization analysis and 16â¯S rDNA high-throughput sequencing further confirmed that biostimulation quickly restored the microbial activities in oxidant treated soil. The main marker bacteria in chemical oxidation combined with biostimulation remediation were Arthrobacter and Paenarthrobacter, and their relative abundances were both significantly negatively correlated with the content of petroleum hydrocarbons in soil.
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Biodegradación Ambiental , Oxidación-Reducción , Petróleo , Microbiología del Suelo , Contaminantes del Suelo , Contaminantes del Suelo/toxicidad , Contaminantes del Suelo/análisis , Fertilizantes/análisis , Sulfatos , Hidrocarburos , Compuestos de Sodio/toxicidad , Suelo/química , Arthrobacter , Restauración y Remediación Ambiental/métodos , Bacterias/efectos de los fármacos , Bacterias/genéticaRESUMEN
MOTIVATION: Despite experimental and curation efforts, the extent of enzyme promiscuity on substrates continues to be largely unexplored and under documented. Providing computational tools for the exploration of the enzyme-substrate interaction space can expedite experimentation and benefit applications such as constructing synthesis pathways for novel biomolecules, identifying products of metabolism on ingested compounds, and elucidating xenobiotic metabolism. Recommender systems (RS), which are currently unexplored for the enzyme-substrate interaction prediction problem, can be utilized to provide enzyme recommendations for substrates, and vice versa. The performance of Collaborative-Filtering (CF) RSs; however, hinges on the quality of embedding vectors of users and items (enzymes and substrates in our case). Importantly, enhancing CF embeddings with heterogeneous auxiliary data, specially relational data (e.g. hierarchical, pairwise or groupings), remains a challenge. RESULTS: We propose an innovative general RS framework, termed Boost-RS that enhances RS performance by 'boosting' embedding vectors through auxiliary data. Specifically, Boost-RS is trained and dynamically tuned on multiple relevant auxiliary learning tasks Boost-RS utilizes contrastive learning tasks to exploit relational data. To show the efficacy of Boost-RS for the enzyme-substrate prediction interaction problem, we apply the Boost-RS framework to several baseline CF models. We show that each of our auxiliary tasks boosts learning of the embedding vectors, and that contrastive learning using Boost-RS outperforms attribute concatenation and multi-label learning. We also show that Boost-RS outperforms similarity-based models. Ablation studies and visualization of learned representations highlight the importance of using contrastive learning on some of the auxiliary data in boosting the embedding vectors. AVAILABILITY AND IMPLEMENTATION: A Python implementation for Boost-RS is provided at https://github.com/HassounLab/Boost-RS. The enzyme-substrate interaction data is available from the KEGG database (https://www.genome.jp/kegg/).
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Aprendizaje AutomáticoRESUMEN
Invited for the cover of this issue are Andrea Pannwitz, Sylvestre Bonnet and co-workers at Leiden University and Johns Hopkins University. The image depicts an observer watching over a lipid bilayer "landscape" and a sky full of luminescent giant vesicles. Read the full text of the article at 10.1002/chem.202003391.
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Photosystem I (PS I) is a transmembrane protein that assembles perpendicular to the membrane, and performs light harvesting, energy transfer, and electron transfer to a final, water-soluble electron acceptor. We present here a supramolecular model of it formed by a bicationic oligofluorene 12+ bound to the bisanionic photoredox catalyst eosin Y (EY2- ) in phospholipid bilayers. According to confocal microscopy, molecular modeling, and time dependent density functional theory calculations, 12+ prefers to align perpendicularly to the lipid bilayer. In presence of EY2- , a strong complex is formed (Ka =2.1±0.1×106 m-1 ), which upon excitation of 12+ leads to efficient energy transfer to EY2- . Follow-up electron transfer from the excited state of EY2- to the water-soluble electron donor EDTA was shown via UV-Vis absorption spectroscopy. Overall, controlled self-assembly and photochemistry within the membrane provides an unprecedented yet simple synthetic functional mimic of PS I.
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Transferencia de Energía/efectos de la radiación , Luz , Membrana Dobles de Lípidos/química , Membrana Dobles de Lípidos/efectos de la radiación , Fosfolípidos/química , Fosfolípidos/efectos de la radiación , Complejo de Proteína del Fotosistema I/efectos de la radiación , Transporte de Electrón/efectos de la radiación , FotoquímicaRESUMEN
Antibodies are capable of potently and specifically binding individual antigens and, in some cases, disrupting their functions. The key challenge in generating antibody-based inhibitors is the lack of fundamental information relating sequences of antibodies to their unique properties as inhibitors. We develop a pipeline, Antibody Sequence Analysis Pipeline using Statistical testing and Machine Learning (ASAP-SML), to identify features that distinguish one set of antibody sequences from antibody sequences in a reference set. The pipeline extracts feature fingerprints from sequences. The fingerprints represent germline, CDR canonical structure, isoelectric point and frequent positional motifs. Machine learning and statistical significance testing techniques are applied to antibody sequences and extracted feature fingerprints to identify distinguishing feature values and combinations thereof. To demonstrate how it works, we applied the pipeline on sets of antibody sequences known to bind or inhibit the activities of matrix metalloproteinases (MMPs), a family of zinc-dependent enzymes that promote cancer progression and undesired inflammation under pathological conditions, against reference datasets that do not bind or inhibit MMPs. ASAP-SML identifies features and combinations of feature values found in the MMP-targeting sets that are distinct from those in the reference sets.
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Anticuerpos , Biología Computacional/métodos , Aprendizaje Automático , Análisis de Secuencia de Proteína/métodos , Programas Informáticos , Algoritmos , Anticuerpos/química , Anticuerpos/metabolismo , Bases de Datos de Proteínas , Humanos , Inhibidores de la Metaloproteinasa de la Matriz/química , Inhibidores de la Metaloproteinasa de la Matriz/metabolismo , Metaloproteinasas de la Matriz/química , Metaloproteinasas de la Matriz/metabolismoRESUMEN
Machine Reading Comprehension (MRC) research concerns how to endow machines with the ability to understand given passages and answer questions, which is a challenging problem in the field of natural language processing. To solve the Chinese MRC task efficiently, this paper proposes an Improved Extraction-based Reading Comprehension method with Answer Re-ranking (IERC-AR), consisting of a candidate answer extraction module and a re-ranking module. The candidate answer extraction module uses an improved pre-training language model, RoBERTa-WWM, to generate precise word representations, which can solve the problem of polysemy and is good for capturing Chinese word-level features. The re-ranking module re-evaluates candidate answers based on a self-attention mechanism, which can improve the accuracy of predicting answers. Traditional machine-reading methods generally integrate different modules into a pipeline system, which leads to re-encoding problems and inconsistent data distribution between the training and testing phases; therefore, this paper proposes an end-to-end model architecture for IERC-AR to reasonably integrate the candidate answer extraction and re-ranking modules. The experimental results on the Les MMRC dataset show that IERC-AR outperforms state-of-the-art MRC approaches.
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BACKGROUND/AIMS: The present study aimed to explore the function of NEAT1 on non-small cell lung cancer (NSCLC), as well as its underlying mechanisms. METHODS: Quantitative realtime PCR (qRT-PCR) was used to measure NEAT1 expression in NSCLC tissues and cells. MTT assay and transwell assay were performed to detect cell proliferation, migration and invasion. Potential target genes were identified via luciferase reporter assay. Protein analysis was performed through western blotting. RESULTS: The expressions of NEAT1 were significantly higher in both of NSCLC tissues and cells than in normal controls. High expression of NEAT1 was significantly associated with TNM stage (P=0.000) and metastasis (P=0.000). NEAT1 knockdown inhibited the proliferation, migration and invasion of NSCLC cells. Hypoxia induction mediated by HIF-2α promoted EMT and NEAT1 expressions. Moreover, miR-101-3p was a target of NEAT1. We also found that SOX9 was a target of miR-101-3p. Oncogenic function of NEAT1 on NSCLC progression was mediated by miR-101-3p/SOX9/Wnt/ß-catenin signaling pathway. CONCLUSION: NEAT1 up-regulation induced by HIF-2α over-expression could promote the progression of NSCLC under hypoxic condition. Moreover, NEAT1 also takes part in NSCLC progression via miR-101-3p/SOX9/Wnt/ß-catenin axis.
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Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico/metabolismo , Carcinoma de Pulmón de Células no Pequeñas/patología , Neoplasias Pulmonares/patología , MicroARNs/metabolismo , ARN Largo no Codificante/metabolismo , Factor de Transcripción SOX9/metabolismo , Antagomirs/metabolismo , Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico/genética , Carcinoma de Pulmón de Células no Pequeñas/metabolismo , Estudios de Casos y Controles , Línea Celular Tumoral , Movimiento Celular , Proliferación Celular , Femenino , Humanos , Neoplasias Pulmonares/metabolismo , Masculino , MicroARNs/antagonistas & inhibidores , MicroARNs/genética , Persona de Mediana Edad , Estadificación de Neoplasias , Interferencia de ARN , ARN Largo no Codificante/antagonistas & inhibidores , ARN Largo no Codificante/genética , ARN Interferente Pequeño/metabolismo , Factor de Transcripción SOX9/antagonistas & inhibidores , Factor de Transcripción SOX9/genética , Vía de Señalización Wnt , beta Catenina/metabolismoRESUMEN
ABSTRACT: The usage of electronic cigarettes (e-cigarettes) sparked an outbreak of unidentified vaping-related lung disease in the US during late 2019. With e-cigarettes becoming more and more popular, smokers have more options other than conventional cigarettes. Under these circumstances, a comprehensive evaluation of the general safety of new tobacco and tobacco-related products, represented by e-cigarettes, to human health is necessary. In this review, we summarize the current research on potential negative impacts of e-cigarette exposure on human health. In particular, studies detailing the relationship between e-cigarettes and the digestive system are summarized, with mechanisms mainly including hepatic metabolic dysfunction, impaired gut barrier, and worsened outcomes of inflammatory bowel disease (IBD). Although believed to be safer than traditional cigarettes, e-cigarettes exert adverse effects on systemic health and induce the development of multiple diseases including asthma, cardiovascular disease, and IBD. Moreover, nicotine-containing e-cigarettes have a negative impact on the childhood development and increase the risk of arterial stiffness compared to the non-nicotine e-cigarettes. However, non-nicotine e-cigarette components have detrimental effects including promoting liver damage and metabolic disorders.
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Sistemas Electrónicos de Liberación de Nicotina , Humanos , Vapeo/efectos adversos , Nicotina/efectos adversosRESUMEN
The basic helix-loop-helix (bHLH) gene family is integral to various aspects of plant development and the orchestration of stress response. This study focuses on the bHLH genes within Populus × canescens, a poplar species noted for its significant tolerance to cadmium (Cd) stress. Through our comprehensive genomic analysis, we have identified and characterized 170 bHLH genes within the P. canescens genome. These genes have been systematically classified into 22 distant subfamilies based on their evolutionary relationships. A notable conservation in gene structure and motif compositions were conserved across these subfamilies. Further analysis of the promoter regions of these genes revealed an abundance of essential cis-acting element, which are associated with plant hormonal regulation, development processes, and stress response pathway. Utilizing quantitative PCR (qPCR), we have documented the differential regulation of PcbHLHs in response to elevated Cd concentrations, with distinct expression patterns observed across various tissues. This study is poised to unravel the molecular mechanism underpinning Cd tolerance in P. canescens, offering valuable insights for the development of new cultivars with enhanced Cd accumulation capacity and tolerance. Such advancements are crucial for implementing effective phytoremediation strategies to mitigate soil pollution caused by Cd.
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Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico , Cadmio , Regulación de la Expresión Génica de las Plantas , Populus , Estrés Fisiológico , Populus/genética , Populus/metabolismo , Populus/efectos de los fármacos , Cadmio/toxicidad , Cadmio/metabolismo , Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico/genética , Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico/metabolismo , Regulación de la Expresión Génica de las Plantas/efectos de los fármacos , Estrés Fisiológico/genética , Estrés Fisiológico/efectos de los fármacos , Proteínas de Plantas/genética , Proteínas de Plantas/metabolismo , Familia de Multigenes , Genoma de Planta , Regiones Promotoras Genéticas/genéticaRESUMEN
The incidence of chronic wound healing is promoted by the growing trend of elderly population, obesity, and type II diabetes. Although numerous wound dressings have been studied over the years, it is still challenging for many wound dressings to perfectly adapt to the healing process due to the dynamic and complicated wound microenvironment. Aiming at an optimal reproduction of the physiological environment, multifunctional electrospinning nanofibrous membranes (ENMs) have emerged as a promising platform for the wound treatment owing to their resemblance to extracellular matrix (ECM), adjustable preparation processes, porousness, and good conformability to the wound site. Moreover, profiting from the booming development of human-machine interaction and artificial intelligence, a next generation of intelligent electrospinning nanofibrous membranes (iENMs) based wound dressing substrates that could realize the real-time monitoring of wound proceeding and individual-based wound therapy has evoked a surge of interest. In this regard, general wound-related biomarkers and process are overviewed firstly and representative iENMs stimuli-responsive materials are briefly summarized. Subsequently, the emergent applications of iENMs for the wound healing are highlighted. Finally, the opportunities and challenges for the development of next-generation iENMs as well as translating iENMs into clinical practice are evaluated.
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Observations of low-lying dark states in several photosynthetic complexes challenge our understanding of the mechanisms behind their efficient energy transfer processes. Computational models are necessary for providing novel insights into the nature and function of dark states, especially since these are not directly accessible in spectroscopy experiments. Here, we will focus on signatures of dark-type states in chlorosomes, a light-harvesting complex from green sulfur bacteria well-known for uniting a broad absorption band with very efficient energy transfer. In agreement with experiments, our simulations of two-dimensional electronic spectra capture the ultrafast exciton transfer occurring in 100s of femtoseconds within a single chlorosome cylinder. The sub-100 fs process corresponds to relaxation within the single-excitation manifold in a single chlorosome tube, where all initially created populations in the bright exciton states are quickly transferred to dark-type exciton states. Structural inhomogeneities on the local scale cause a redistribution of the oscillator strength, leading to the emergence of these dark-type exciton states, which dominate ultrafast energy transfer. The presence of the dark-type exciton states suppresses energy loss from an isolated chlorosome via fluorescence quenching, as observed experimentally. Our results further question whether relaxation to dark-exciton states is a leading process or merely competes with transfer to the baseplate within the photosynthetic apparatus of green sulfur bacteria.
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The transmembrane channel-like (TMC) protein family comprises eight members, with TMC1 and TMC2 being extensively studied. This study demonstrates substantial co-expression of TMC7 with the mechanosensitive channel Piezo2 in somatosensory neurons. Genetic deletion of TMC7 in primary sensory ganglia neurons in vivo enhances sensitivity in both physiological and pathological mechanosensory transduction. This deletion leads to an increase in proportion of rapidly adapting (RA) currents conducted by Piezo2 in dorsal root ganglion (DRG) neurons and accelerates RA deactivation kinetics. In HEK293 cells expressing both proteins, TMC7 significantly suppresses the current amplitudes of co-expressed Piezo2. Our findings reveal that TMC7 and Piezo2 exhibit physical interactions, and both proteins also physically interact with cytoskeletal ß-actin. We hypothesize that TMC7 functions as an inhibitory modulator of Piezo2 in DRG neurons, either through direct inhibition or by disrupting the transmission of mechanical forces from the cytoskeleton to the channel.
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Ganglios Espinales , Canales Iónicos , Mecanotransducción Celular , Células Receptoras Sensoriales , Humanos , Células Receptoras Sensoriales/metabolismo , Animales , Canales Iónicos/metabolismo , Canales Iónicos/genética , Ganglios Espinales/metabolismo , Células HEK293 , Ratones , Proteínas de la Membrana/metabolismo , Proteínas de la Membrana/genética , Ratones Endogámicos C57BL , Actinas/metabolismoRESUMEN
We report that diazepam binding inhibitor (DBI) is a glial messenger mediating crosstalk between satellite glial cells (SGCs) and sensory neurons in the dorsal root ganglion (DRG). DBI is highly expressed in SGCs of mice, rats, and humans, but not in sensory neurons or most other DRG-resident cells. Knockdown of DBI results in a robust mechanical hypersensitivity without major effects on other sensory modalities. In vivo overexpression of DBI in SGCs reduces sensitivity to mechanical stimulation and alleviates mechanical allodynia in neuropathic and inflammatory pain models. We further show that DBI acts as an unconventional agonist and positive allosteric modulator at the neuronal GABAA receptors, particularly strongly affecting those with a high-affinity benzodiazepine binding site. Such receptors are selectively expressed by a subpopulation of mechanosensitive DRG neurons, and these are also more enwrapped with DBI-expressing glia, as compared with other DRG neurons, suggesting a mechanism for a specific effect of DBI on mechanosensation. These findings identified a communication mechanism between peripheral neurons and SGCs. This communication modulates pain signaling and can be targeted therapeutically.
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Inhibidor de la Unión a Diazepam , Ganglios Espinales , Neuroglía , Animales , Ganglios Espinales/metabolismo , Neuroglía/metabolismo , Ratones , Ratas , Humanos , Inhibidor de la Unión a Diazepam/metabolismo , Inhibidor de la Unión a Diazepam/genética , Masculino , Células Receptoras Sensoriales/metabolismo , Receptores de GABA-A/metabolismo , Receptores de GABA-A/genética , Hiperalgesia/metabolismo , Hiperalgesia/genética , Hiperalgesia/patología , Ratas Sprague-Dawley , Mecanotransducción Celular , Ratones Endogámicos C57BLRESUMEN
Electrical stimulation therapy is effective in promoting wound healing by rescuing the decreased endogenous electrical field, where self-powered and miniaturized devices such as nanogenerators become the emerging trends. While high-voltage and unidirectional electric field may pose thermal effect and damage to the skin, nanogenerators with lower voltages, pulsed or bidirectional currents, and less invasive electrodes are preferred. Herein, we construct a polydopamine (PDA)-modified poly-L-lactic acid (PLLA) /MXene (PDMP/MXene) nanofibrous composite membrane that generates piezoelectric voltages matching the transepithelial potential (TEP) to accelerate wound healing. PDA coating not only enhances the piezoelectricity of PLLA by dipole attraction and alignment, but also increases its hydrophilicity and facilitates subsequent MXene adhesion for electrical conductivity and stability in physiological environment. When applied as wound dressings in mice, the PDMP/MXene membranes act as a nanogenerators with reduced internal resistances and satisfactory piezoelectric performances that resemble bioelectric potentials (~10 mV) responding to physical activities. The membrane significantly accelerates wound closure by facilitating fibroblast migration, collagen deposition and angiogenesis, and suppressing the expression of inflammatory responses. This piezoelectric fibrous membrane therefore provides a convenient solution for speeding up wound healing by sustained low voltage mimicking bioelectricity, better cell affinity.