Pulmonary interstitial lesions in pemphigus mouse model: Verifying pemphigus may not be only limited to skin and mucosa.

Interstitial lung disease (ILD) has been identified as a prevalent complication and significant contributor to mortality in individuals with pemphigus. In this study, a murine model of pemphigus was developed through the subcutaneous administration of serum IgG obtained from pemphigus patients, allowing for an investigation into the association between pemphigus and ILD. Pulmonary interstitial lesions were identified in the lungs of a pemphigus mouse model through histopathology, RT-qPCR and Sircol assay analyses. The severity of these lesions was found to be positively associated with the concentration of IgG in the injected serum. Additionally, DIF staining revealed the deposition of serum IgG in the lung tissue of pemphigus mice, indicating that the subcutaneous administration of human IgG directly impacted the lung tissue of the mice, resulting in damage. This study confirms the presence of pulmonary interstitial lesions in the pemphigus mouse model and establishes a link between pemphigus and ILD.

Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles.

Recent developments in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy (ACT), have encountered challenges such as immune-related adverse events and resistance, especially in solid tumors. To advance the field, a deeper understanding of the molecular mechanisms behind treatment responses and resistance is essential. However, the lack of functionally characterized immune-related gene sets has limited data-driven immunological research. To address this gap, we adopted non-negative matrix factorization on 83 human bulk RNA sequencing (RNA-seq) datasets and constructed 28 immune-specific gene sets. After rigorous immunologist-led manual annotations and orthogonal validations across immunological contexts and functional omics data, we demonstrated that these gene sets can be applied to refine pan-cancer immune subtypes, improve ICB response prediction and functionally annotate spatial transcriptomic data. These functional gene sets, informing diverse immune states, will advance our understanding of immunology and cancer research.

Sustainability-Driven Accelerated Shear-Mediated Immunoassay for Amyotrophic Lateral Sclerosis Detection.

Healthcare facilities produce millions of tons of waste annually, with a significant portion consisting of diagnostic plasticware. Here, we introduce a new detection platform that completely replaces traditional assay plates with a piece of membrane, offering a much greener and more sustainable alternative. The membrane, integrated within the portable vortex fluidic device (P-VFD), enables rapid detection of a clinically relevant protein biomarker, urinary p75ECD. This biomarker is utilized to evaluate the prognosis, disease severity, and progression of amyotrophic lateral sclerosis (ALS). This assay has a limit-of-detection (LOD) of 4.03 pg, which is comparable to the plate-based assay (2.24 pg) and has been optimized through a full factorial design of experiments (DOE). P-VFD has great potential in quantifying p75ECD in human biofluids and can significantly reduce the assay time to 5 min compared to the current plate-based p75ECD ELISA assay (3 days), with at least a 4.4-fold reduction in the usage of the detection antibody.

Biological Evaluation of Lysionotin: a Novel Inhibitor of 5-Lipoxygenase for Anti-glioma.

OBJECTIVE: To explore the potential mechanism of lysionotin in treating glioma. METHODS: First, target prediction based on Bernoulli Naïve Bayes profiling and pathway enrichment was used to predict the biological activity of lysionotin. The binding between 5-lipoxygenase (5-LO) and lysionotin was detected by surface plasmon resonance (SPR) and molecular docking, and the inhibitory effects of lysionotin on 5-LO and proliferation of glioma were determined using enzyme inhibition assay in vitro and cell viability analysis, respectively. Furthermore, the pharmaceutical effect of lysionotin was explored by cell survival rate analysis and liquid chromatography with tandem mass spectrometry (LC-MS/MS). The protein expression, intracellular calcium ion concentration and cytoskeleton detection were revealed by Western blot, flow cytometry and fluorescence labeling, respectively. RESULTS: Target prediction and pathway enrichment revealed that lysionotin inhibited 5-LO, a key enzyme involved in the arachidonic acid metabolism pathway, to inhibit the proliferation of glioma. Molecular docking results demonstrated that 5-LO can be binding to lysionotin through hydrogen bonds, forming bonds with His600, Gln557, Asn554, and His372. SPR analysis further confirmed the interaction between 5-LO and lysionotin. Furthermore, enzyme inhibition assay in vitro and cell survival rate analysis revealed that 50% inhibition concentration of lysionotin and the median effective concentration of lysionotin were 90 and 16.58 µmol/L, respectively, and the results of LC-MS/MS showed that lysionotin inhibited the production of 5S-hydroperoxy-eicosatetraenoic acid (P<0.05), and moreover, the LC-MS/MS results indicated that lysionotin can enter glioma cells well (P<0.01) and inhibit their proliferation. Western blot analysis demonstrated that lysionotin can inhibit the expression of 5-LO (P<0.05) and downstream leukotriene B4 receptor (P<0.01). In addition, the results showed that lysionotin affected intracellular calcium ion concentration by inhibiting 5-LO to affect the cytoskeleton, as determined by flow cytometry and fluorescence labeling. CONCLUSION: Lysionotin binds to 5-LO could suppress glioma by inhibiting arachiodonic acid metabolism pathway.

γδ T cells and the PD-1/PD-L1 axis: a love-hate relationship in the tumor microenvironment.

Gamma delta (γδ) T cells demonstrate strong cytotoxicity against diverse cancer cell types in an MHC-independent manner, rendering them promising contenders for cancer therapy. Although amplification and adoptive transfer of γδ T cells are being evaluated in the clinic, their therapeutic efficacy remains unsatisfactory, primarily due to the influence of the immunosuppressive tumor microenvironment (TME). Currently, the utilization of targeted therapeutic antibodies against inhibitory immune checkpoint (ICP) molecules is a viable approach to counteract the immunosuppressive consequences of the TME. Notably, PD-1/PD-L1 checkpoint inhibitors are considered primary treatment options for diverse malignancies, with the objective of preserving the response of αß T cells. However, γδ T cells also infiltrate various human cancers and are important participants in cancer immunity, thereby influencing patient prognosis. Hence, it is imperative to comprehend the reciprocal impact of the PD-1/PD-L1 axis on γδ T cells. This understanding can serve as a therapeutic foundation for improving γδ T cells adoptive transfer therapy and may offer a novel avenue for future combined immunotherapeutic approaches.

Updated Efficacy and Safety of Lorlatinib in a Phase 2 Study in Chinese Patients With Previously Treated Advanced ALK-Positive Non-small Cell Lung Cancer.

OBJECTIVES: Lorlatinib, a brain-penetrant, third-generation anaplastic lymphoma kinase (ALK) inhibitor, demonstrated robust overall and intracranial antitumor activity in patients with advanced ALK-positive non-small cell lung cancer (NSCLC) previously treated with an ALK inhibitor in a global phase 1/2 study (NCT01970865) and a multicenter phase 2 study conducted in China (NCT03909971). We report updated 3-year follow-up data from the phase 2 study. MATERIALS AND METHODS: Chinese patients with locally advanced or metastatic ALK-positive NSCLC that progressed after crizotinib as the only prior ALK inhibitor (cohort 1) or after 1 non-crizotinib ALK inhibitor (cohort 2), were enrolled in the study. All patients received lorlatinib 100 mg once daily. RESULTS: At data cutoff, of 109 enrolled patients, the median duration of follow-up for progression-free survival (PFS) was 35.8 months in cohort 1 (n = 67) and 33.1 months in cohort 2 (n = 42). Median PFS (95% CI) per independent central review was 26.3 months (16.6-35.9) and 5.6 months (2.9-12.4), respectively. The median duration of follow-up for overall survival (OS) was 36.4 months and 37.5 months, respectively. Median OS (95% CI) was not reached (NR; NR-NR) and 21.9 months (11.9-NR), respectively. Median intracranial time to progression (95% CI) was NR (NR-NR) and NR (9.7 months-NR), respectively. No new safety signals emerged with long-term treatment. CONCLUSION: The long-term data confirm robust overall and intracranial clinical activity of lorlatinib, with no new safety signals emerging. These results support using lorlatinib in Chinese patients with previously treated ALK-positive NSCLC with or without brain metastases. CLINICALTRIALS: gov NCT03909971.

[Tofacitinib inhibits the transformation of lung fibroblasts into myofibroblasts through JAK/STAT3 pathway].

OBJECTIVE: To investigate the effect of tofacitinib, a pan-Janus kinase (JAK) inhibitor, on transforming growth factor-beta 1 (TGF-ß1)-induced fibroblast to myofibroblast transition (FMT) and to explore its mechanism. To provide a theoretical basis for the clinical treatment of connective tissue disease-related interstitial lung disease (CTD-ILD). METHODS: (1) Human fetal lung fibroblast 1 (HFL-1) were cultured in vitro, and 6 groups were established: DMSO blank control group, TGF-ß1 induction group, and TGF-ß1 with different concentrations of tofacitinib (0.5, 1.0, 2.0, 5.0 µmol/L) drug intervention experimental groups. CCK-8 was used to measure the cell viability, and wound-healing assay was performed to measure cell migration ability. After 48 h of combined treatment, quantitative real-time PCR (RT-PCR) and Western blotting were used to detect the gene and protein expression levels of α-smooth muscle actin (α-SMA), fibronectin (FN), and collagen type Ⅰ (COL1). (2) RT-PCR and enzyme-linked immunosorbnent assay (ELISA) were used to detect the interleukin-6 (IL-6) gene and protein expression changes, respectively. (3) DMSO carrier controls, 1.0 µmol/L and 5.0 µmol/L tofacitinib were added to the cell culture media of different groups for pre-incubation for 30 min, and then TGF-ß1 was added to treat for 1 h, 6 h and 24 h. The phosphorylation levels of Smad2/3 and signal transducer and activator of transcription 3 (STAT3) protein were detected by Western blotting. RESULTS: (1) Tofacitinib inhibited the viability and migration ability of HFL-1 cells after TGF-ß1 induction. (2) The expression of α-SMA, COL1A1 and FN1 genes of HFL-1 in the TGF-ß1-induced groups was significantly up-regulated compared with the blank control group (P < 0.05). Compared with the TGF-ß1 induction group, α-SMA expression in the 5.0 µmol/L tofacitinib intervention group was significantly inhi-bited (P < 0.05). Compared with the TGF-ß1-induced group, FN1 gene was significantly inhibited in each intervention group at a concentration of 0.5-5.0 µmol/L (P < 0.05). Compared with the TGF-ß1-induced group, the COL1A1 gene expression in each intervention group did not change significantly. (3) Western blotting results showed that the protein levels of α-SMA and FN1 in the TGF-ß1-induced group were significantly higher than those in the control group (P < 0.05), and there was no significant difference in the expression of COL1A1. Compared with the TGF-ß1-induced group, the α-SMA protein level in the intervention groups with different concentrations decreased. And the differences between the TGF-ß1-induced group and 2.0 µmol/L or 5.0 µmol/L intervention groups were statistically significant (P < 0.05). Compared with the TGF-ß1-induced group, the FN1 protein levels in the intervention groups with different concentrations showed a downward trend, but the difference was not statistically significant. There was no difference in COL1A1 protein expression between the intervention groups compared with the TGF-ß1-induced group. (4) After TGF-ß1 acted on HFL-1 cells for 48 h, the gene expression of the IL-6 was up-regulated and IL-6 in culture supernatant was increased, the intervention with tofacitinib partly inhibited the TGF-ß1-induced IL-6 gene expression and IL-6 in culture supernatant. TGF-ß1 induced the increase of Smad2/3 protein phosphorylation in HFL-1 cells for 1 h and 6 h, STAT3 protein phosphorylation increased at 1 h, 6 h and 24 h, the pre-intervention with tofacitinib inhibited the TGF-ß1-induced Smad2/3 phosphorylation at 6 h and inhibited TGF-ß1-induced STAT3 phosphorylation at 1 h, 6 h and 24 h. CONCLUSION: Tofacitinib can inhibit the transformation of HFL-1 cells into myofibroblasts induced by TGF-ß1, and the mechanism may be through inhibiting the classic Smad2/3 pathway as well as the phosphorylation of STAT3 induced by TGF-ß1, thereby protecting the disease progression of pulmonary fibrosis.

Machine learning guided prediction of warfarin blood levels for personalized medicine based on clinical longitudinal data from cardiac surgery patients: a prospective observational study.

BACKGROUND: Warfarin is a common oral anticoagulant, and its effects vary widely among individuals. Numerous dose-prediction algorithms have been reported based on cross-sectional data generated via multiple linear regression or machine learning. This study aimed to construct an information fusion perturbation theory and machine learning prediction model of warfarin blood levels based on clinical longitudinal data from cardiac surgery patients. METHODS AND MATERIAL: The data of 246 patients were obtained from electronic medical records. Continuous variables were processed by calculating the distance of the raw data with the moving average (MA ∆vki(sj)), and categorical variables in different attribute groups were processed using Euclidean distance (ED ǁ∆vk(sj)ǁ). Regression and classification analyses were performed on the raw data, MA ∆vki(sj), and ED ǁ∆vk(sj)ǁ. Different machine-learning algorithms were chosen for the STATISTICA and WEKA software. RESULTS: The random forest (RF) algorithm was the best for predicting continuous outputs using the raw data. The correlation coefficients of the RF algorithm were 0.978 and 0.595 for the training and validation sets, respectively, and the mean absolute errors were 0.135 and 0.362 for the training and validation sets, respectively. The proportion of ideal predictions of the RF algorithm was 59.0%. General discriminant analysis (GDA) was the best algorithm for predicting the categorical outputs using the MA ∆vki(sj) data. The GDA algorithm's total true positive rate (TPR) was 95.4% and 95.6% for the training and validation sets, respectively, with MA ∆vki(sj) data. CONCLUSIONS: An information fusion perturbation theory and machine learning model for predicting warfarin blood levels was established. A model based on the RF algorithm could be used to predict the target international normalized ratio (INR), and a model based on the GDA algorithm could be used to predict the probability of being within the target INR range under different clinical scenarios.

Antibiofilm Efficacy and Mechanism of the Marine Chlorinated Indole Sesquiterpene Against Methicillin-Resistant Staphylococcus aureus.

Methicillin-resistant Staphylococcus aureus (MRSA) can easily form biofilms on food surfaces, thus leading to cross-contamination, which is difficult to remove. Therefore, there is an urgent need to find alternatives with good antibacterial and antibiofilm effects. In this study, two indole sesquiterpene compounds, xiamycin (1) and chlorinated metabolite chloroxiamycin (2), were isolated from the fermentation liquid of marine Streptomyces sp. NBU3429 for the first time. The chemical structures of the two compounds were characterized by spectroscopic data interpretation, including 1D NMR and HRESIMS analysis. Antimicrobial test showed that chloroxiamycin (2) (minimum inhibitory concentration, MIC = 16 µg/mL) exhibited superior antibacterial activity than xiamycin (1) (MIC = 32 µg/mL) against MRSA ATCC43300. Moreover, compound (2) decreased the biofilm formation rate of MRSA ATCC43300 by 12.7%-84.6% in the concentration range of 32-512 µg/mL, which is relatively stronger than xiamycin (1) (4.1%-49.9%) as well. Antibacterial/antibiofilm mechanism investigation indicated that chloroxiamycin (2) could disrupt the cell wall and membrane of MRSA, inhibiting the production of biofilm extracellular polysaccharides. All these results illustrated that chloroxiamycin (2) is an effective antibacterial/antibiofilm agent, which makes it an attractive candidate for food preservatives.

Systematic identification and functional analysis of root meristem growth factors (RGFs) reveals role of PgRGF1 in modulation of root development and ginsenoside production in Panax ginseng.

Panax ginseng C.A. Mey., known for its medicinal and dietary supplement properties, primarily contains pharmacologically active ginsenosides. However, the regulatory mechanisms linking ginseng root development with ginsenoside biosynthesis are still unclear. Root meristem growth factors (RGFs) are crucial for regulating plant root growth. In our study, we identified five ginseng RGF peptide sequences from the ginseng genome and transcriptome libraries. We treated Arabidopsis and ginseng adventitious roots with exogenous Panax ginseng RGFs (PgRGFs) to assess their activities. Our results demonstrate that PgRGF1 influences gravitropic responses and reduces lateral root formation in Arabidopsis. PgRGF1 has been found to restrict the number and length of ginseng adventitious root branches in ginseng. Given the medicinal properties of ginseng, We determined the ginsenoside content and performed transcriptomic analysis of PgRGF1-treated ginseng adventitious roots. Specifically, the total ginsenoside content in ginseng adventitious roots decreased by 19.98 % and 63.71 % following treatments with 1 µM and 10 µM PgRGF1, respectively, compared to the control. The results revealed that PgRGF1 affects the accumulation of ginsenosides by regulating the expression of genes associated with auxin transportation and ginsenoside biosynthesis. These findings suggest that PgRGF1, as a peptide hormone regulator in ginseng, can modulate adventitious root growth and ginsenoside accumulation.

Liquid crystal monomers disrupt photoreceptor patterning of zebrafish larvae via thyroid hormone signaling.

Liquid crystal monomers (LCMs) are the raw material for liquid crystal displays, and their use is steadily increasing in electronic products. Recently, LCMs have been reported to be novel endocrine disrupting chemicals, however, the mechanisms underlying their potential for thyroid hormone disruption and visual toxicity are not well understood. In this study, six widely used fluorinated LCMs (FLCMs) were selected to determine putative mechanisms underlying FLCM-induced toxicity to the zebrafish thyroid and visual systems. Exposure to FLCMs caused damage to retinal structures and reduced cell density of ganglion cell layer, inner nuclear layer, and photoreceptor layer approximately 12.6-46.1%. Exposure to FLCMs also disrupted thyroid hormone levels and perturbed the hypothalamic-pituitary-thyroid axis by affecting key enzymes and protein in zebrafish larvae. A thyroid hormone-dependent GH3 cell viability assay supported the hypothesis that FLCMs act as thyroid hormone disrupting chemicals. It was also determined that FLCMs containing aliphatic ring structures may have a higher potential for T3 antagonism compared to FLCMs without an aliphatic ring. Molecular docking in silico suggested that FLCMs may affect biological functions of thyroxine binding globulin, membrane receptor integrin, and thyroid receptor beta. Lastly, the visual motor response of zebrafish in red- and green-light was significantly inhibited following exposure to FLCMs. Taken together, we demonstrate that FLCMs can act as thyroid hormone disruptors to induce visual dysfunction in zebrafish via several molecular mechanisms.

Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles.

Recent developments in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy, have encountered challenges such as immune-related adverse events and resistance, especially in solid tumors. To advance the field, a deeper understanding of the molecular mechanisms behind treatment responses and resistance is essential. However, the lack of functionally characterized immune-related gene sets has limited data-driven immunological research. To address this gap, we adopted non-negative matrix factorization on 83 human bulk RNA-seq datasets and constructed 28 immune-specific gene sets. After rigorous immunologist-led manual annotations and orthogonal validations across immunological contexts and functional omics data, we demonstrated that these gene sets can be applied to refine pan-cancer immune subtypes, improve ICB response prediction and functionally annotate spatial transcriptomic data. These functional gene sets, informing diverse immune states, will advance our understanding of immunology and cancer research.

Blockade of histamine receptor H1 augments immune checkpoint therapy by enhancing MHC-I expression in pancreatic cancer cells.

BACKGROUND: Although immune checkpoint blockade (ICB) therapy has proven to be extremely effective at managing certain cancers, its efficacy in treating pancreatic ductal adenocarcinoma (PDAC) has been limited. Therefore, enhancing the effect of ICB could improve the prognosis of PDAC. In this study, we focused on the histamine receptor H1 (HRH1) and investigated its impact on ICB therapy for PDAC. METHODS: We assessed HRH1 expression in pancreatic cancer cell (PCC) specimens from PDAC patients through public data analysis and immunohistochemical (IHC) staining. The impact of HRH1 in PCCs was evaluated using HRH1 antagonists and small hairpin RNA (shRNA). Techniques including Western blot, flow cytometry, quantitative reverse transcription polymerase chain reaction (RT-PCR), and microarray analyses were performed to identify the relationships between HRH1 and major histocompatibility complex class I (MHC-I) expression in cancer cells. We combined HRH1 antagonism or knockdown with anti-programmed death receptor 1 (αPD-1) therapy in orthotopic models, employing IHC, immunofluorescence, and hematoxylin and eosin staining for assessment. RESULTS: HRH1 expression in cancer cells was negatively correlated with HLA-ABC expression, CD8+ T cells, and cytotoxic CD8+ T cells. Our findings indicate that HRH1 blockade upregulates MHC-I expression in PCCs via cholesterol biosynthesis signaling. In the orthotopic model, the combined inhibition of HRH1 and αPD-1 blockade enhanced cytotoxic CD8+ T cell penetration and efficacy, overcoming resistance to ICB therapy. CONCLUSIONS: HRH1 plays an immunosuppressive role in cancer cells. Consequently, HRH1 intervention may be a promising method to amplify the responsiveness of PDAC to immunotherapy.

Scalable Customization of Crystallographic Plane Controllable Lithium Metal Anodes for Ultralong-Lasting Lithium Metal Batteries.

A formidable challenge to achieve the practical applications of rechargeable lithium (Li) metal batteries (RLMBs) is to suppress the uncontrollable growth of Li dendrites. One of the most effective solutions is to fabricate Li metal anodes with specific crystal plane, but still lack of a simple and high-efficient approach. Herein, a facile and controllable way for the scalable customization of polished Li metal anodes with highly preferred (110) and (200) crystallographic orientation (donating as polished Li(110) and polished Li(200), respectively) by regulating the times of accumulative roll bonding, is reported. According to the inherent characteristics of polished Li(110)/Li(200), the influence of Li atomic structure on the electrochemical performance of RLMBs is deeply elucidated by combining theoretical calculations with relative experimental proofs. In particular, a polished Li(110) crystal plane is demonstrated to induce Li+ uniform deposition, promoting the formation of flat and dense Li deposits. Impressively, the polished Li(110)||LiFePO4 full cells exhibit unprecedented cycling stability with 10 000 cycles at 10 C almost without capacity degradation, indicating the great potential application prospect of such textured Li metal. More valuably, this work provides an important reference for low-cost, continued, and large-scale production of Li metal anodes with highly preferred crystal orientation through roll-to-roll manufacturability.

On the additive artificial intelligence-based discovery of nanoparticle neurodegenerative disease drug delivery systems.

Neurodegenerative diseases are characterized by slowly progressing neuronal cell death. Conventional drug treatment strategies often fail because of poor solubility, low bioavailability, and the inability of the drugs to effectively cross the blood-brain barrier. Therefore, the development of new neurodegenerative disease drugs (NDDs) requires immediate attention. Nanoparticle (NP) systems are of increasing interest for transporting NDDs to the central nervous system. However, discovering effective nanoparticle neuronal disease drug delivery systems (N2D3Ss) is challenging because of the vast number of combinations of NP and NDD compounds, as well as the various assays involved. Artificial intelligence/machine learning (AI/ML) algorithms have the potential to accelerate this process by predicting the most promising NDD and NP candidates for assaying. Nevertheless, the relatively limited amount of reported data on N2D3S activity compared to assayed NDDs makes AI/ML analysis challenging. In this work, the IFPTML technique, which combines information fusion (IF), perturbation theory (PT), and machine learning (ML), was employed to address this challenge. Initially, we conducted the fusion into a unified dataset comprising 4403 NDD assays from ChEMBL and 260 NP cytotoxicity assays from journal articles. Through a resampling process, three new working datasets were generated, each containing 500,000 cases. We utilized linear discriminant analysis (LDA) along with artificial neural network (ANN) algorithms, such as multilayer perceptron (MLP) and deep learning networks (DLN), to construct linear and non-linear IFPTML models. The IFPTML-LDA models exhibited sensitivity (Sn) and specificity (Sp) values in the range of 70% to 73% (>375,000 training cases) and 70% to 80% (>125,000 validation cases), respectively. In contrast, the IFPTML-MLP and IFPTML-DLN achieved Sn and Sp values in the range of 85% to 86% for both training and validation series. Additionally, IFPTML-ANN models showed an area under the receiver operating curve (AUROC) of approximately 0.93 to 0.95. These results indicate that the IFPTML models could serve as valuable tools in the design of drug delivery systems for neurosciences.

A Biomimetic Visual Detection Model: Event-Driven LGMDs Implemented With Fractional Spiking Neuron Circuits.

OBJECTIVE: As biological wide-field visual neurons in locusts, lobula giant motion detectors (LGMDs) can effectively predict collisions and trigger avoidance before the collision occurs. This capability has extensive potential applications in autonomous driving, unmanned aerial vehicles, and more. Currently, describing the LGMD characteristics is divided into two viewpoints, one emphasizing the presynaptic visual pathway and the other emphasizing the postsynaptic LGMDs neuron. Indeed, both have their research support leading to the emergence of two computational models, but both lack a biophysical description of the behavior in the individual LGMD neuron. This paper aims to mimic and explain LGMD's behavior based on fractional spiking neurons and construct a biomimetic visual model for the LGMD compatible with these two characteristics. METHODS: We implement the visual model in the form of spikes by choosing an event camera rather than a conventional CMOS camera to simulate the photoreceptors and follow the topology of the ON/OFF visual pathway, enabling it to incorporate the lateral inhibition to mimic the LGMD's system from the bottom up. Second, most computational models of motion perception use only the dendrites within the LGMD neurons as the ideal pathway for linear summation, ignoring dendritic effects inducing neuronal properties. Thus, we introduced fractional spiking neuron (FSN) circuits into the model by altering dendritic morphological parameters to simulate multi-scale spike frequency adaptation (SFA) observed in LGMDs. In addition, we have attempted to add one more circuit of dendritic trees into fractional spiking neurons to be compatible with the postsynaptic FFI in LGMDs and provide a novel explanatory approach and a predictive model for studying LGMD neurons. RESULTS: Finally, we test that the event-driven biomimetic visual model can achieve collision detection and looming selection in different complex scenes, especially fast-moving objects.

Marinicella meishanensis sp. nov., a novel Marinicella member isolated from coastal mudflat sediment of Meishan Islandin the East China Sea.

A Gram-negative, rod-shaped, non-motile and strictly aerobic strain, designated NBU2979T, was isolated from a coastal mudflat located on Meishan Island in the East China Sea. Strain NBU2979T grew optimally at 32 °C, with 2.0 % NaCl (w/v) and at pH 7.0-7.5. The predominant fatty acid (>10 %) was iso-C15 : 0. The major polar lipids included phosphatidylglycerol, phosphatidylethanolamine, diphosphatidylglycerol, phosphatidyldimethylethanolamine, phosphatidylcholine, an unidentified glycolipid, two unidentified aminophospholipids, an unidentified phospholipid and an unidentified lipid. The only respiratory quinone was ubiquinone-8. Comparative analysis of 16S rRNA gene sequences showed that strain NBU2979T exhibited highest similarity to Marinicella sediminis F2T (98.0 %), Marinicella marina S1101T (97.5 %), Marinicella litoralis KMM 3900T (96.6 %), Marinicella rhabdoformis 3539T (95.5 %), Marinicella pacifica sw153T (95.2 %) and Marinicella gelatinilytica S6413T (94.9 %). Phylogenetic analyses indicated that strain NBU2979T clustered with the genus Marinicella and was closely related to strain M. sediminis F2T. The average nucleotide identity and digital DNA-DNA hybridization values between strain NBU2979T and related species of genus Marinicella were well below the threshold limit for prokaryotic species delineation. The DNA G+C content of strain NBU2979T was 51.6 mol%. Based on its phenotypic, chemotaxonomic and genotypic data, strain NBU2979T (=KCTC 82911T=MCCC 1K06402T) is considered to be a representative of a novel species in the genus Marinicella, for which the name Marinicella meishanensis sp. nov. is proposed.

Genomic Analysis of Kitasatospora setae to Explore Its Biosynthetic Potential Regarding Secondary Metabolites.

Actinomycetes have long been recognized as important sources of clinical antibiotics. However, the exploration of rare actinomycetes, despite their potential for producing bioactive molecules, has remained relatively limited compared to the extensively studied Streptomyces genus. The extensive investigation of Streptomyces species and their natural products has led to a diminished probability of discovering novel bioactive compounds from this group. Consequently, our research focus has shifted towards less explored actinomycetes, beyond Streptomyces, with particular emphasis on Kitasatospora setae (K. setae). The genome of K. setae was annotated and analyzed through whole-genome sequencing using multiple bio-informatics tools, revealing an 8.6 Mbp genome with a 74.42% G + C content. AntiSMASH analysis identified 40 putative biosynthetic gene clusters (BGCs), approximately half of which were recessive and unknown. Additionally, metabolomic mining utilizing mass spectrometry demonstrated the potential for this rare actinomycete to generate numerous bioactive compounds such as glycosides and macrolides, with bafilomycin being the major compound produced. Collectively, genomics- and metabolomics-based techniques confirmed K. setae's potential as a bioactive secondary metabolite producer that is worthy of further exploration.

Deficiency of UCHL1 results in insufficient decidualization accompanied by impaired dNK modulation and eventually miscarriage.

BACKGROUND: Miscarriage is a frustrating complication of pregnancy that is common among women of reproductive age. Insufficient decidualization which not only impairs embryo implantation but disturbs fetomaternal immune-tolerance, has been widely regarded as a major cause of miscarriage; however, the underlying mechanisms resulting in decidual impairment are largely unknown. METHODS: With informed consent, decidual tissue from patients with spontaneous abortion or normal pregnant women was collected to detect the expression profile of UCHL1. Human endometrial stromal cells (HESCs) were used to explore the roles of UCHL1 in decidualization and dNK modulation, as well as the mechanisms involved. C57/BL6 female mice (7-10 weeks old) were used to construct pregnancy model or artificially induced decidualization model to evaluate the effect of UCHL1 on mice decidualization and pregnancy outcome. RESULTS: The Ubiquitin C-terminal hydrolase L1 (UCHL1), as a deubiquitinating enzyme, was significantly downregulated in decidua from patients with miscarriage, along with impaired decidualization and decreased dNKs. Blockage of UCHL1 led to insufficient decidualization and resultant decreased expression of cytokines CXCL12, IL-15, TGF-ß which were critical for generation of decidual NK cells (dNKs), whereas UCHL1 overexpression enhanced decidualization accompanied by increase in dNKs. Mechanistically, the promotion of UCHL1 on decidualization was dependent on its deubiquitinating activity, and intervention of UCHL1 inhibited the activation of JAK2/STAT3 signaling pathway, resulting in aberrant decidualization and decreased production of cytokines associated with dNKs modulation. Furthermore, we found that inhibition of UCHL1 also disrupted the decidualization in mice and eventually caused adverse pregnancy outcome. CONCLUSIONS: UCHL1 plays significant roles in decidualization and dNKs modulation during pregnancy in both humans and mice. Its deficiency indicates a poor pregnancy outcome due to defective decidualization, making UCHL1 a potential target for the diagnosis and treatment of miscarriage.

Multi-frequency signal acquisition and phase measurement in space gravitational wave detection.

To enhance the accuracy of phase measurement and to prevent tracking errors, it is crucial to effectively read the multi-frequency signal in space gravitational wave detection. In this paper, a novel signal acquisition method called the multi-frequency acquisition algorithm is proposed and implemented. Different from the traditional single-frequency acquisition, the signal characteristics of amplitude and frequency are both considered to better distinguish different frequency components. A phasemeter integrated with the acquisition method and narrow-bandwidth digital phase-locked loop is constructed for the method test and verification. The results show that the multi-frequency acquisition unit can capture all the frequencies of an input signal in several milliseconds. The precision is better than ±200 Hz under a low SNR (signal-to-noise ratio) of 0 dB. The phase noise can reach 2 µrad/Hz1/2 in the frequency range of 0.1-1 Hz and satisfy the requirement of the space gravitational wave detection in all frequency ranges.