Current landscape of fecal microbiota transplantation in treating depression.

Depression, projected to be the predominant contributor to the global disease burden, is a complex condition with diverse symptoms including mood disturbances and cognitive impairments. Traditional treatments such as medication and psychotherapy often fall short, prompting the pursuit of alternative interventions. Recent research has highlighted the significant role of gut microbiota in mental health, influencing emotional and neural regulation. Fecal microbiota transplantation (FMT), the infusion of fecal matter from a healthy donor into the gut of a patient, emerges as a promising strategy to ameliorate depressive symptoms by restoring gut microbial balance. The microbial-gut-brain (MGB) axis represents a critical pathway through which to potentially rectify dysbiosis and modulate neuropsychiatric outcomes. Preclinical studies reveal that FMT can enhance neurochemicals and reduce inflammatory markers, thereby alleviating depressive behaviors. Moreover, FMT has shown promise in clinical settings, improving gastrointestinal symptoms and overall quality of life in patients with depression. The review highlights the role of the gut-brain axis in depression and the need for further research to validate the long-term safety and efficacy of FMT, identify specific therapeutic microbial strains, and develop targeted microbial modulation strategies. Advancing our understanding of FMT could revolutionize depression treatment, shifting the paradigm toward microbiome-targeting therapies.

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge.

Airway-related quantitative imaging biomarkers are crucial for examination, diagnosis, and prognosis in pulmonary diseases. However, the manual delineation of airway structures remains prohibitively time-consuming. While significant efforts have been made towards enhancing automatic airway modelling, current public-available datasets predominantly concentrate on lung diseases with moderate morphological variations. The intricate honeycombing patterns present in the lung tissues of fibrotic lung disease patients exacerbate the challenges, often leading to various prediction errors. To address this issue, the 'Airway-Informed Quantitative CT Imaging Biomarker for Fibrotic Lung Disease 2023' (AIIB23) competition was organized in conjunction with the official 2023 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI). The airway structures were meticulously annotated by three experienced radiologists. Competitors were encouraged to develop automatic airway segmentation models with high robustness and generalization abilities, followed by exploring the most correlated QIB of mortality prediction. A training set of 120 high-resolution computerised tomography (HRCT) scans were publicly released with expert annotations and mortality status. The online validation set incorporated 52 HRCT scans from patients with fibrotic lung disease and the offline test set included 140 cases from fibrosis and COVID-19 patients. The results have shown that the capacity of extracting airway trees from patients with fibrotic lung disease could be enhanced by introducing voxel-wise weighted general union loss and continuity loss. In addition to the competitive image biomarkers for mortality prediction, a strong airway-derived biomarker (Hazard ratio>1.5, p < 0.0001) was revealed for survival prognostication compared with existing clinical measurements, clinician assessment and AI-based biomarkers.

A robot-assisted tracheal intubation system based on a soft actuator?

PURPOSE: Tracheal intubation is the gold standard of airway protection and constitutes a pivotal life-saving technique frequently employed in emergency medical interventions. Hence, in this paper, a system is designed to execute tracheal intubation tasks automatically, offering a safer and more efficient solution, thereby alleviating the burden on physicians. METHODS: The system comprises a tracheal tube with a bendable front end, a drive system, and a tip endoscope. The soft actuator provides two degrees of freedom for precise orientation. It is fabricated with varying-hardness silicone and reinforced with fibers and spiral steel wire for flexibility and safety. The hydraulic actuation system and tube feeding mechanism enable controlled bending and delivery. Object detection of key anatomical features guides the robotic arm and soft actuator. The control strategy involves visual servo control for coordinated robotic arm and soft actuator movements, ensuring accurate and safe tracheal intubation. RESULTS: The kinematics of the soft actuator were established using a constant curvature model, allowing simulation of its workspace. Through experiments, the actuator is capable of 90° bending as well as 20° deflection on the left and right sides. The maximum insertion force of the tube is 2 N. Autonomous tracheal intubation experiments on a training manikin were successful in all 10 trials, with an average insertion time of 45.6 s. CONCLUSION: Experimental validation on the manikin demonstrated that the robot tracheal intubation system based on a soft actuator was able to perform safe, stable, and automated tracheal intubation. In summary, this paper proposed a safe and automated robot-assisted tracheal intubation system based on a soft actuator, showing considerable potential for clinical applications.

Causal relationship between gut microbiota and functional outcomes after ischemic stroke: A comprehensive Mendelian randomization study.

AIMS: To investigate the association of the genetic predisposition of specific gut microbiotas with the clinical outcome of ischemic stroke. METHODS: We leveraged publicly available genome-wide association study (GWAS) data to perform Mendelian randomization (MR) analysis. The gut microbiota-related GWAS data from 18,340 individuals from the international consortium MiBioGen was used. The summary data for functional outcomes after ischemic stroke was obtained from the Genetics of Ischemic Stroke Functional Outcome (GISCOME) network meta-analysis. The primary outcomes were judged by the modified Rankin Scale (mRS). The principal analyses were conducted using the inverse-variance weighted (IVW) MR method. The Cochran's Q test, weighted median, MR-Egger regression, leave-one-SNP-out analysis, MR-Pleiotropy Residual Sum, and Outlier methods were adopted as sensitivity analyses. Furthermore, we performed bi-directional MR analysis and the MR Steiger directionality test to examine the direction of the causal relations. RESULTS: The results demonstrated that the genetic predisposition of genus Lactococcus, genus Ruminococcaceae NK4A214 group, family Peptostreptococcaceae, and genus Odoribacter was positively associated with favorable functional outcome after ischemic stroke. Genus Collinsella, genus Ruminococcaceae UCG005, genus Akkermansia, genus Eubacterium oxidoreducens group, and family Verrucomicrobiaceae were identified to be associated with worse functional outcomes after ischemic stroke. Our results showed no evidence of heterogeneity, directional pleiotropic effects, or collider bias, and the sensitivity of our analysis was acceptable. CONCLUSION: The genetic predisposition of different gut microbiotas was associated with the clinical outcome of ischemic stroke. Microbiota adjustment was a promising method to improve the clinical outcome of ischemic stroke.

Multi-output neural network model for predicting biochar yield and composition.

In biomass pyrolysis for biochar production, existing prediction models face computational challenges and limited accuracy. This study curated a comprehensive dataset, revealing pyrolysis parameters' dominance in biochar yield (54.8 % importance). Pyrolysis temperature emerged as pivotal (PCC = -0.75), influencing yield significantly. Artificial Neural Network (ANN) outperformed Random Forest (RF) in testing set predictions (R2 = 0.95, RMSE = 3.6), making it apt for complex multi-output predictions and software development. The trained ANN model, employed in Partial Dependence Analysis, uncovered nonlinear relationships between biomass characteristics and biochar yield. Findings indicated optimization opportunities, correlating low pyrolysis temperatures, elevated nitrogen content, high fixed carbon, and brief residence times with increased biochar yields. A multi-output ANN model demonstrated optimal fit for biochar yield. A user-friendly Graphical User Interface (GUI) for biochar synthesis prediction was developed, exhibiting robust performance with a mere 0.52 % prediction error for biochar yield. This study showcases practical machine learning application in biochar synthesis, offering valuable insights and predictive tools for optimizing biochar production processes.

Modifying single-crystal silicon and trimming silicon microring devices by femtosecond laser irradiation.

Single-crystal silicon (c-Si) is a vital component of photonic devices and has obvious advantages. Moreover, femtosecond-pulsed laser interactions with matter have been widely applied in micro/nanoscale processing. In this paper, we report the modification mechanisms of c-Si induced by a femtosecond laser (350 fs, 520 nm) at different pulse fluences, along with the mechanism of this technique to trim the phase error of c-Si-based devices. In this study, several distinct types of final micro/nanostructures, such as amorphization and ablation, were analyzed. The near-surface morphology was characterized using optical microscopy, scanning electron microscopy, and atomic force microscopy. The main physical modification processes were further analyzed using a two-temperature model. By employing Raman spectroscopy, we demonstrated that a higher laser fluence significantly contributes to the formation of more amorphous silicon components. The thickness of the amorphous layer was almost uniform (approximately 30 nm) at different induced fluences, as determined using transmission electron microscopy. From the ellipsometry measurements, we demonstrated that the refractive index increases for amorphization while the ablation decreases. In addition, we investigated the ability of the femtosecond laser to modify the effective index of c-Si microring waveguides by either amorphization or ablation. Both blue and red shifts of resonance spectra were achieved in the microring devices, resulting in double-direction trimming. Our results provide further insight into the femtosecond laser modification mechanism of c-Si and may be a practical method for dealing with the fabrication errors of c-Si-based photonic devices.

Adipose-Derived Stem Cell Exosomes Facilitate Diabetic Wound Healing: Mechanisms and Potential Applications.

Wound healing in diabetic patients is frequently hampered. Adipose-derived stem cell exosomes (ADSC-eoxs), serving as a crucial mode of intercellular communication, exhibit promising therapeutic roles in facilitating wound healing. This review aims to comprehensively outline the molecular mechanisms through which ADSC-eoxs enhance diabetic wound healing. We emphasize the biologically active molecules released by these exosomes and their involvement in signaling pathways associated with inflammation modulation, cellular proliferation, vascular neogenesis, and other pertinent processes. Additionally, the clinical application prospects of the reported ADSC-eoxs are also deliberated. A thorough understanding of these molecular mechanisms and potential applications is anticipated to furnish a theoretical groundwork for combating diabetic wound healing.

Spin-Phonon Coupling in Iron-Doped Ultrathin Bismuth Halide Perovskite Derivatives.

Spin in semiconductors facilitates magnetically controlled optoelectronic and spintronic devices. In metal halide perovskites (MHPs), doping magnetic ions is proven to be a simple and efficient approach to introducing a spin magnetic momentum. In this work, we present a facile metal ion doping protocol through the vapor-phase metal halide insertion reaction to the chemical vapor deposition (CVD)-grown ultrathin Cs3BiBr6 perovskites. The Fe-doped bismuth halide (Fe:CBBr) perovskites demonstrate that the iron spins are successfully incorporated into the lattice, as revealed by the spin-phonon coupling below the critical temperature Tc around 50 K observed through temperature-dependent Raman spectroscopy. Furthermore, the phonons exhibit significant softening under an applied magnetic field, possibly originating from magnetostriction and spin exchange interaction. The spin-phonon coupling in Fe:CBBr potentially provides an efficient way to tune the spin and lattice parameters for halide perovskite-based spintronics.

HAMP predicts a pivotal role in modulating the malignant behaviors of non-small cell lung cancer cells.

BACKGROUND: Hepcidin antimicrobial peptide (HAMP) is a small peptide hormone recognized for its role in iron metabolism and cancer treatment. The purpose of this study was to examine the influence of HAMP in NSCLC. METHODS: The profile of NSCLC cells and tissues was characterized via HAMP. Gain- or loss-of-function cell models of HAMP were constructed, and CCK8, colony formation, and Transwell analyses were used to confirm the influence of HAMP on NSCLC cells. Upstream and downstream HAMP mechanisms in NSCLC were also analysed. Dual-luciferase reporter and pull-down assays confirmed the associations of miR-873-5p with HAMP, miR-873-5p, and the lncRNA KCNQ1OT1/SNHG14/XIST. Moreover, a xenograft model was established in nude mice for confirming the role of HAMP in NSCLC cell growth. RESULTS: In addition, HAMP expression increased in NSCLC cells and tissues. In terms of cellular functions, the HAMP-overexpressing group exhibited elevated NSCLC cell proliferation, invasion, and migration. HAMP knockdown reversed these changes. Bioinformatics analysis indicated that miR-873-5p targeted HAMP, which affected the nuclear factor kappa B (NF-κB) pathway in NSCLC. HAMP activated the NF-κB pathway, which was negatively modulated by miR-873-5p. NF-κB inhibitor JSH-23 can partly suppress the proliferation, invasion, and migration in HAMP-overexpressed cells. Moreover, miR-873-5p was the target miRNA of long noncoding RNAs (lncRNAs), which included KCNQ1OT1, SNHG14, and XIST, and these three lncRNAs promoted HAMP. CONCLUSION: Noncoding RNA-mediated HAMP promotes NSCLC cell proliferation, migration, and invasion by initiating the NF-κB pathway.

FOXP4-mediated induction of PTK7 activates the Wnt/ß-catenin pathway and promotes ovarian cancer development.

Ovarian cancer (OV) poses a significant challenge in clinical settings due to its difficulty in early diagnosis and treatment resistance. FOXP4, belonging to the FOXP subfamily, plays a pivotal role in various biological processes including cancer, cell cycle regulation, and embryonic development. However, the specific role and importance of FOXP4 in OV have remained unclear. Our research showed that FOXP4 is highly expressed in OV tissues, with its elevated levels correlating with poor prognosis. We further explored FOXP4's function through RNA sequencing and functional analysis in FOXP4-deficient cells, revealing its critical role in activating the Wnt signaling pathway. This activation exacerbates the malignant phenotype in OV. Mechanistically, FOXP4 directly induces the expression of protein tyrosine kinase 7 (PTK7), a Wnt-binding receptor tyrosine pseudokinase, which causes abnormal activation of the Wnt signaling pathway. Disrupting the FOXP4-Wnt feedback loop by inactivating the Wnt signaling pathway or reducing FOXP4 expression resulted in the reduction of the malignant phenotype of OV cells, while restoring PTK7 expression reversed this effect. In conclusion, our findings underscore the significance of the FOXP4-induced Wnt pathway activation in OV, suggesting the therapeutic potential of targeting this pathway in OV treatment.

Necessary for seizure forecasting outcome metrics: seizure frequency and benchmark model.

Work is ongoing to advance seizure forecasting, but the performance metrics used to evaluate model effectiveness can sometimes lead to misleading outcomes. For example, some metrics improve when tested on patients with a particular range of seizure frequencies (SF). This study illustrates the connection between SF and metrics. Additionally, we compared benchmarks for testing performance: a moving average (MA) or the commonly used permutation benchmark. Three data sets were used for the evaluations: (1) Self-reported seizure diaries of 3,994 Seizure Tracker patients; (2) Automatically detected (and sometimes manually reported or edited) generalized tonic-clonic seizures from 2,350 Empatica Embrace 2 and Mate App seizure diary users, and (3) Simulated datasets with varying SFs. Metrics of calibration and discrimination were computed for each dataset, comparing MA and permutation performance across SF values. Most metrics were found to depend on SF. The MA model outperformed or matched the permutation model in all cases. The findings highlight SF's role in seizure forecasting accuracy and the MA model's suitability as a benchmark. This underscores the need for considering patient SF in forecasting studies and suggests the MA model may provide a better standard for evaluating future seizure forecasting models.

Stem Cell-Derived Extracellular Vesicles: Promising Therapeutic Opportunities for Diabetic Wound Healing.

Wound healing is a sophisticated and orderly process of cellular interactions in which the body restores tissue architecture and functionality following injury. Healing of chronic diabetic wounds is difficult due to impaired blood circulation, a reduced immune response, and disrupted cellular repair mechanisms, which are often associated with diabetes. Stem cell-derived extracellular vesicles (SC-EVs) hold the regenerative potential, encapsulating a diverse cargo of proteins, RNAs, and cytokines, presenting a safe, bioactivity, and less ethical issues than other treatments. SC-EVs orchestrate multiple regenerative processes by modulating cellular communication, increasing angiogenesis, and promoting the recruitment and differentiation of progenitor cells, thereby potentiating the reparative milieu for diabetic wound healing. Therefore, this review investigated the effects and mechanisms of EVs from various stem cells in diabetic wound healing, as well as their limitations and challenges. Continued exploration of SC-EVs has the potential to revolutionize diabetic wound care.

Identification of hub genes and potential molecular mechanisms related to drug sensitivity in acute myeloid leukemia based on machine learning.

Background: Acute myeloid leukemia (AML) is the most common form of leukemia among adults and is characterized by uncontrolled proliferation and clonal expansion of hematopoietic cells. There has been a significant improvement in the treatment of younger patients, however, prognosis in the elderly AML patients remains poor. Methods: We used computational methods and machine learning (ML) techniques to identify and explore the differential high-risk genes (DHRGs) in AML. The DHRGs were explored through multiple in silico approaches including genomic and functional analysis, survival analysis, immune infiltration, miRNA co-expression and stemness features analyses to reveal their prognostic importance in AML. Furthermore, using different ML algorithms, prognostic models were constructed and validated using the DHRGs. At the end molecular docking studies were performed to identify potential drug candidates targeting the selected DHRGs. Results: We identified a total of 80 DHRGs by comparing the differentially expressed genes derived between AML patients and normal controls and high-risk AML genes identified by Cox regression. Genetic and epigenetic alteration analyses of the DHRGs revealed a significant association of their copy number variations and methylation status with overall survival (OS) of AML patients. Out of the 137 models constructed using different ML algorithms, the combination of Ridge and plsRcox maintained the highest mean C-index and was used to build the final model. When AML patients were classified into low- and high-risk groups based on DHRGs, the low-risk group had significantly longer OS in the AML training and validation cohorts. Furthermore, immune infiltration, miRNA coexpression, stemness feature and hallmark pathway analyses revealed significant differences in the prognosis of the low- and high-risk AML groups. Drug sensitivity and molecular docking studies revealed top 5 drugs, including carboplatin and austocystin-D that may significantly affect the DHRGs in AML. Conclusion: The findings from the current study identified a set of high-risk genes that may be used as prognostic and therapeutic markers for AML patients. In addition, significant use of the ML algorithms in constructing and validating the prognostic models in AML was demonstrated. Although our study used extensive bioinformatics and machine learning methods to identify the hub genes in AML, their experimental validations using knock-out/-in methods would strengthen our findings.

Spatially Resolved Anion Diffusion and Tunable Waveguides in Bismuth Halide Perovskites.

Bismuth halide perovskites are widely regarded as nontoxic alternatives to lead halide perovskites for optoelectronics and solar energy harvesting applications. With a tailorable composition and intriguing optical properties, bismuth halide perovskites are also promising candidates for tunable photonic devices. However, robust control of the anion composition in bismuth halide perovskites remains elusive. Here, we established chemical vapor deposition and anion exchange protocols to synthesize bismuth halide perovskite nanoflakes with controlled dimensions and variable compositions. In particular, we demonstrated the gradient bromide distribution by controlling the anion exchange and diffusion processes, which is spatially resolved by time-of-flight secondary ion mass spectrometry. Moreover, the optical waveguiding properties of bismuth halide perovskites can be modulated by flake thicknesses and anion compositions. With a unique gradient anion distribution and controllable optical properties, bismuth halide perovskites provide new possibilities for applications in optoelectronic devices and integrated photonics.

CXXC5 drove inflammation and ovarian cancer proliferation via transcriptional activation of ZNF143 and EGR1.

CXXC5, a zinc-finger protein, is known for its role in epigenetic regulation via binding to unmethylated CpG islands in gene promoters. As a transcription factor and epigenetic regulator, CXXC5 modulates various signaling processes and acts as a key coordinator. Altered expression or activity of CXXC5 has been linked to various pathological conditions, including tumorigenesis. Despite its known role in cancer, CXXC5's function and mechanism in ovarian cancer are unclear. We analyzed multiple public databases and found that CXXC5 is highly expressed in ovarian cancer, with high expression correlating with poor patient prognosis. We show that CXXC5 expression is regulated by oxygen concentration and is a direct target of HIF1A. CXXC5 is critical for maintaining the proliferative potential of ovarian cancer cells, with knockdown decreasing and overexpression increasing cell proliferation. Loss of CXXC5 led to inactivation of multiple inflammatory signaling pathways, while overexpression activated these pathways. Through in vitro and in vivo experiments, we confirmed ZNF143 and EGR1 as downstream transcription factors of CXXC5, mediating its proliferative potential in ovarian cancer. Our findings suggest that the CXXC5-ZNF143/EGR1 axis forms a network driving ovarian cell proliferation and tumorigenesis, and highlight CXXC5 as a potential therapeutic target for ovarian cancer treatment.

The EIF3H-HAX1 axis increases RAF-MEK-ERK signaling activity to promote colorectal cancer progression.

Eukaryotic initiation translation factor 3 subunit h (EIF3H) plays critical roles in regulating translational initiation and predicts poor cancer prognosis, but the mechanism underlying EIF3H tumorigenesis remains to be further elucidated. Here, we report that EIF3H is overexpressed in colorectal cancer (CRC) and correlates with poor prognosis. Conditional Eif3h deletion suppresses colorectal tumorigenesis in AOM/DSS model. Mechanistically, EIF3H functions as a deubiquitinase for HAX1 and stabilizes HAX1 via antagonizing ßTrCP-mediated ubiquitination, which enhances the interaction between RAF1, MEK1 and ERK1, thereby potentiating phosphorylation of ERK1/2. In addition, activation of Wnt/ß-catenin signaling induces EIF3H expression. EIF3H/HAX1 axis promotes CRC tumorigenesis and metastasis in mouse orthotopic cancer model. Significantly, combined targeting Wnt and RAF1-ERK1/2 signaling synergistically inhibits tumor growth in EIF3H-high patient-derived xenografts. These results uncover the important roles of EIF3H in mediating CRC progression through regulating HAX1 and RAF1-ERK1/2 signaling. EIF3H represents a promising therapeutic target and prognostic marker in CRC.

The novel miR-873-5p-YWHAE-PI3K/AKT axis is involved in non-small cell lung cancer progression and chemoresistance by mediating autophagy.

Non-small cell lung cancer (NSCLC) encompasses approximately 85% of all lung cancer cases and is the foremost cancer type worldwide; it is prevalent in both sexes and known for its high fatality rate. Expanding scientific inquiry underscores the indispensability of microRNAs in NSCLC. Here, we probed the impact of miR-873-5p on NSCLC development and chemoresistance. qRT‒PCR was used to measure the miR-873-5p level in NSCLC cells with or without chemoresistance. A model of miR-873-5p overexpression was constructed. The proliferation and viability of NSCLC cells were evaluated through CCK8 and colony formation experiments. Cell migration and invasion were monitored via Transwell assays. Western blotting was used to determine the levels of YWHAE, PI3K, AKT, EMT, apoptosis, and autophagy-related proteins. The sensitivity of NSCLC cells to the chemotherapeutic agent gefitinib was assessed. Additionally, the correlation of YWHAE with miR-873-5p was validated via a dual-luciferase reporter assay and RNA immunoprecipitation (RIP). Overexpressed miR-873-5p suppressed migration, proliferation, invasion, and EMT while concurrently stimulating apoptotic processes. miR-873-5p was downregulated in NSCLC cells resistant to gefitinib. Upregulating miR-873-5p reversed gefitinib resistance by inducing autophagy. YWHAE was confirmed to be a downstream target of miR-873-5p. YWHAE overexpression promoted the malignant behaviors of NSCLC cells and boosted tumor growth, while these effects were reversed following miR-873-5p overexpression. Subsequent investigations revealed that overexpressing YWHAE promoted PI3K/AKT pathway activation, with miR-873-5p displaying inhibitory effects on the YWHAE-mediated PI3K/AKT signaling cascade. miR-873-5p affects proliferation, invasion, migration, EMT, autophagy, and chemoresistance in NSCLC by controlling the YWHAE/PI3K/AKT axis.

Single-Shot Laser-Induced Switching of an Exchange Biased Antiferromagnet.

Ultrafast manipulation of magnetic order has challenged the understanding of the fundamental and dynamic properties of magnetic materials. So far single-shot magnetic switching has been limited to ferrimagnetic alloys, multilayers, and designed ferromagnetic (FM) heterostructures. In FM/antiferromagnetic (AFM) bilayers, exchange bias (He) arises from the interfacial exchange coupling between the two layers and reflects the microscopic orientation of the antiferromagnet. Here the possibility of single-shot switching of the antiferromagnet (change of the sign and amplitude of He) with a single femtosecond laser pulse in IrMn/CoGd bilayers is demonstrated. The manipulation is demonstrated in a wide range of fluences for different layer thicknesses and compositions. Atomistic simulations predict ultrafast switching and recovery of the AFM magnetization on a timescale of 2 ps. The results provide the fastest and the most energy-efficient method to set the exchange bias and pave the way to potential applications for ultrafast spintronic devices.

Significance of neutrophil extracellular traps-related gene in the diagnosis and classification of atherosclerosis.

Atherosclerosis (AS) is a pathological process associated with various cardiovascular diseases. Upon different stimuli, neutrophils release reticular complexes known as neutrophil extracellular traps (NETs). Numerous researches have indicated a strong correlation between NETs and AS. However, its role in cardiovascular disease requires further investigation. By utilizing a machine learning algorithm, we examined the genes associated with NETs that were expressed differently in individuals with AS compared to normal controls. As a result, we identified four distinct genes. A nomogram model was built to forecast the incidence of AS. Additionally, we conducted analysis on immune infiltration, functional enrichment and consensus clustering in AS samples. The findings indicated that individuals with AS could be categorized into two groups, exhibiting notable variations in immune infiltration traits among the groups. Furthermore, to measure the NETs model, the principal component analysis algorithm was developed and cluster B outperformed cluster A in terms of NETs. Additionally, there were variations in the expression of multiple chemokines between the two subtypes. By studying AS NETs, we acquired fresh knowledge about the molecular patterns and immune mechanisms implicated, which could open up new possibilities for AS immunotherapy.

Neutrophil extracellular trap-related mechanisms in acne vulgaris inspire a novel treatment strategy with adipose-derived stem cells.

Acne vulgaris is a type of chronic skin disorder caused by Propionibacterium acnes (P. acnes). Neutrophil extrinsic traps (NETs) play key role in many types of inflammatory skin diseases. Adipose-derived stem cells (ADSCs) was reported modulate immune responses and neutrophil activity. Here, we explored the potential role of ADSCs and the potential mechanism associated with neutrophil extracellular traps (NETs) in relieving acne vulgaris. In the P. acnes-infected ear skin model, histological staining was used to evaluate the inflammatory infiltration and NET formation in control, P. acnes, and P. acnes + ADSCs groups. Besides, western blot was used to detect the expression levels of cit-H3, MPO, and Nrf2 in ear tissue. In vitro, the immunofluorescence staining of MPO and cit-H3, and SYTOX green staining were performed to measure the NET formation. CCK-8 assay, EdU staining, and wound healing assay were used to detect the proliferation and migration abilities of keratinocytes. ELISA assay was utilized to detect the secretion of inflammatory cytokines. In P. acnes-infected ear skin, ADSC treatment significantly attenuated inflammation and NET formation via activating Nrf2 signaling pathway. In vitro, the conditioned medium of ADSCs reduced the formation of P. acne-induced NETs. Besides, ADSCs could inhibit that the NETs efficiently promoted the proliferation, migration, and inflammatory cytokine secretion of keratinocytes. Our study suggested that ADSCs could attenuate P. acne-related inflammation by inhibiting NET formation. This study provides a novel therapeutic perspective of ADSCs in combating acne vulgaris.