Comprehensive investigation of malignant epithelial cell-related genes in clear cell renal cell carcinoma: development of a prognostic signature and exploration of tumor microenvironment interactions.

Clear cell renal cell carcinoma (ccRCC) is a prevalent malignancy with complex heterogeneity within epithelial cells, which plays a crucial role in tumor progression and immune regulation. Yet, the clinical importance of the malignant epithelial cell-related genes (MECRGs) in ccRCC remains insufficiently understood. This research aims to undertake a comprehensive investigation into the functions and clinical relevance of malignant epithelial cell-related genes in ccRCC, providing valuable understanding of the molecular mechanisms and offering potential targets for treatment strategies. Using data from single-cell sequencing, we successfully identified 219 MECRGs and established a prognostic model MECRGS (MECRGs' signature) by synergistically analyzing 101 machine-learning models using 10 different algorithms. Remarkably, the MECRGS demonstrated superior predictive performance compared to traditional clinical features and 92 previously published signatures across six cohorts, showcasing its independence and accuracy. Upon stratifying patients into high- and low-MECRGS subgroups using the specified cut-off threshold, we noted that patients with elevated MECRGS scores displayed characteristics of an immune suppressive tumor microenvironment (TME) and showed worse outcomes after immunotherapy. Additionally, we discovered a distinct ccRCC tumor cell subtype characterized by the high expressions of PLOD2 (procollagen-lysine,2-oxoglutarate 5-dioxygenase 2) and SAA1 (Serum Amyloid A1), which we further validated in the Renji tissue microarray (TMA) cohort. Lastly, 'Cellchat' revealed potential crosstalk patterns between these cells and other cell types, indicating their potential role in recruiting CD163 + macrophages and regulatory T cells (Tregs), thereby establishing an immunosuppressive TME. PLOD2 + SAA1 + cancer cells with intricate crosstalk patterns indeed show promise for potential therapeutic interventions.

CC4S: Encouraging Certainty and Consistency in Scribble-Supervised Semantic Segmentation.

Deep learning-based solutions have achieved impressive performance in semantic segmentation but often require large amounts of training data with fine-grained annotations. To alleviate such requisition, a variety of weakly supervised annotation strategies have been proposed, among which scribble supervision is emerging as a popular one due to its user-friendly annotation way. However, the sparsity and diversity of scribble annotations make it nontrivial to train a network to produce deterministic and consistent predictions directly. To address these issues, in this paper we propose holistic solutions involving the design of network structure, loss and training procedure, named CC4S to improve Certainty and Consistency for Scribble-Supervised Semantic Segmentation. Specifically, to reduce uncertainty, CC4S embeds a random walk module into the network structure to make neural representations uniformly distributed within similar semantic regions, which works together with a soft entropy loss function to force the network to produce deterministic predictions. To encourage consistency, CC4S adopts self-supervision training and imposes the consistency loss on the eigenspace of the probability transition matrix in the random walk module (we named neural eigenspace). Such self-supervision inherits the category-level discriminability from the neural eigenspace and meanwhile helps the network focus on producing consistent predictions for the salient parts and neglect semantically heterogeneous backgrounds. Finally, to further improve the performance, CC4S uses the network predictions as pseudo-labels and retrains the network with an extra color constraint regularizer on pseudo-labels to boost semantic consistency in color space. Rich experiments demonstrate the excellent performance of CC4S. In particular, under scribble supervision, CC4S achieves comparable performance to those from fully supervised methods. Comprehensive ablation experiments verify the effectiveness of the design choices in CC4S and its robustness under extreme supervision cases, i.e., when scribbles are shrunk proportionally or dropped randomly. The code for this work has been open-sourced at https://github.com/panzhiyi/CC4S.

AcrAB-TolC efflux pump overexpression and tet(A) gene mutation increase tigecycline resistance in Klebsiella pneumoniae.

Tigecycline-non-susceptible Klebsiella pneumoniae (TNSKP) is increasing and has emerged as a global public health issue. However, the mechanism of tigecycline resistance remains unclear. The objective of this study was to investigate the potential role of efflux pump system in tigecycline resistance. 29 tigecycline-non-susceptible Klebsiella pneumoniae (TNSKP) strains were collected and their minimum inhibitory concentrations (MIC) were determined by the broth microdilution method. The ramR, acrR, rpsJ, tet(A), and tet(X) were amplified by polymerase chain reaction (PCR). The mRNA expression of different efflux pump genes and regulator genes were analyzed by real-time PCR. Additionally, KP14 was selected for genome sequencing. KP14 genes without acrB, oqxB, and TetA were modified using suicide plasmids and MIC of tigecycline of KP14 with target genes knocked out was investigated. It was found that MIC of tigecycline of 20 out of the 29 TNSKP strains decreased by over four folds once combined with phenyl-arginine-ß-naphthylamide dihydrochloride (PaßN). Most strains exhibited upregulation of AcrAB and oqxAB efflux pumps. The strains with acrB, oqxB, and tetA genes knocked out were constructed, wherein the MIC of tigecycline of KP14∆acrB and KP14∆tetA was observed to be 2 µg/mL (decreased by 16 folds), the MIC of tigecycline of KP14ΔacrBΔTetA was 0.25 µg/mL (decreased by 128 folds), but the MIC of tigecycline of KP14∆oqxB remained unchanged at 32 µg/mL. The majority of TNSKP strains demonstrated increased expression of AcrAB-TolC and oqxAB, while certain strains showed mutations in other genes associated with tigecycline resistance. In KP14, both overexpression of AcrAB-TolC and tet(A) gene mutation contributed to the mechanism of tigecycline resistance.

Ergothioneine Protects Against UV-Induced Oxidative Stress Through the PI3K/AKT/Nrf2 Signaling Pathway.

Background: Ergothioneine (EGT) is an antioxidant, which could be detected in human tissues, and human skin cells could utilize EGT and play an anti-oxidative role in keratinocytes. And in this study we are going to elucidate whether EGT could protect the skin from photoaging by Ultraviolet (UV) exposure in mice and its molecule pathway. Methods: Histological analysis was performed for evaluating the skin structure change. Malondialdehyde (MDA) and superoxide dismutase (SOD) levels were measured with biological assay for evaluating oxidative and antioxidative ability of skin exposed to UV light. And the level of marker molecules in mouse skin were detected by hydroxyproline (Hyp) assay, immunohistochemical analysis, Western blot, and quantitative real-time PCR (qRT-PCR). The markers of skin aging and cell death were tested by cell culture and treatment, Western blot and qRT-PCR. Results: EGT decreased the levels of inflammatory factors induced by UV exposure in mouse skin. MDA and SOD activity detection showed that EGT decreased MDA levels, increased SOD activity, and upregulated PI3K/Akt/Nrf2 signals in mouse skin exposed to UV, which further activated Nrf2 in the nucleus and enhanced the expression of Nrf2 target genes. In the cell model, we revealed that EGT could inhibit the increase in senescence-associated ß-galactosidase-positive cells and p16 and γ-H2A.X positive cells induced by etoposide and activate PI3K/Akt/Nrf2 signaling. Moreover, a PI3K inhibitor blocked EGT protection against etoposide-induced cell death. Conclusion: The study showed EGT may play an important protective role against cell damage or death through the PI3K/Akt/Nrf2 signaling pathway in skin.

Strategies and Recent Advances on Improving Efficient Antitumor of Lenvatinib Based on Nanoparticle Delivery System.

Lenvatinib (LVN) is a potentially effective multiple-targeted receptor tyrosine kinase inhibitor approved for treating hepatocellular carcinoma, metastatic renal cell carcinoma and thyroid cancer. Nonetheless, poor pharmacokinetic properties including poor water solubility and rapid metabolic, complex tumor microenvironment, and drug resistance have impeded its satisfactory therapeutic efficacy. This article comprehensively reviews the uses of nanotechnology in LVN to improve antitumor effects. With the characteristic of high modifiability and loading capacity of the nano-drug delivery system, an active targeting approach, controllable drug release, and biomimetic strategies have been devised to deliver LVN to target tumors in sequence, compensating for the lack of passive targeting. The existing applications and advances of LVN in improving therapeutic efficacy include improving longer-term efficiency, achieving higher efficiency, combination therapy, tracking and diagnosing application and reducing toxicity. Therefore, using multiple strategies combined with photothermal, photodynamic, and immunoregulatory therapies potentially overcomes multi-drug resistance, regulates unfavorable tumor microenvironment, and yields higher synergistic antitumor effects. In brief, the nano-LVN delivery system has brought light to the war against cancer while at the same time improving the antitumor effect. More intelligent and multifunctional nanoparticles should be investigated and further converted into clinical applications in the future.

[Effect of Exogenous Chitosan on Physiological Properties, Antioxidant Activity, and Cadmium Uptake of Wheat (Triticum aestivum L.) Seedlings Under Cadmium Stress].

This research aimed to clarify the effects of exogenously applied chitosan on the physiological characteristics, antioxidant activities, and Cd accumulation of wheat (Triticum aestivum L.) seedlings under cadmium (Cd) stress and to identify the key indicators based on the partial least squares model. The wheat variety studied was Bainong207 (BN207), and Cd-stress was achieved by growing seedlings in a hydroponic culture experiment with 10 and 25 µmol·L-1 Cd2+ added to the culture solution. It was found that both Cd-stress at 10 and 25 µmol·L-1 significantly inhibited the chlorophyll content, photosynthesis, and biomass accumulation of wheat seedlings. Seedling roots became shorter and thicker, and the lateral roots decreased under Cd-stress. The Cd-stress also increased H2O2 and MDA accumulation and the degree of cell membrane lipid peroxidation and affected the activities of antioxidant enzymes such as superoxide dismutase (SOD) and peroxidase (POD). Under Cd stress, exogenous chitosan decreased the Cd content in the aboveground and underground parts of wheat by 13.22 %-21.63 % and 7.92 %-28.32 % and reduced Cd accumulation in the aboveground and underground parts by 5.37 %-6.71 % and 1.91 %-4.09 %, respectively. Whereas exogenous chitosan application significantly reduced the content of H2O2 in roots and aboveground parts of wheat by 38.21 %-47.46 % and 45.81 %-55.73 % and MDA content by 37.65 %-48.12 % and 29.87 %-32.51 %, it increased the activities of SOD and POD in roots by 2.78 %-5.61 % and 13.81 %-18.33 %, respectively. In summary, exogenous chitosan can improve the photosynthetic characteristics and antioxidant enzyme activities of wheat seedlings under Cd stress, reduce the content and accumulation of Cd in the root and aboveground parts of wheat, and alleviate the damage of lipid peroxidation to the cell membrane. All of these results provide the basal data for the application of exogenous chitosan to alleviate Cd toxicity to wheat seedlings.

Cerebrospinal fluid soluble insulin receptor levels in Alzheimer's disease.

INTRODUCTION: Brain insulin resistance and deficiency is a consistent feature of Alzheimer's disease (AD). Insulin resistance can be mediated by the surface expression of the insulin receptor (IR). Cleavage of the IR generates the soluble IR (sIR). METHODS: We measured the levels of sIR present in cerebrospinal fluid (CSF) from individuals along the AD diagnostic spectrum from two cohorts: Seattle (n = 58) and the Consortium for the Early Identification of Alzheimer's Disease-Quebec (CIMA-Q; n = 61). We further investigated the brain cellular contribution for sIR using human cell lines. RESULTS: CSF sIR levels were not statistically different in AD. CSF sIR and amyloid beta (Aß)42 and Aß40 levels significantly correlated as well as CSF sIR and cognition in the CIMA-Q cohort. Human neurons expressing the amyloid precursor protein "Swedish" mutation generated significantly greater sIR and human astrocytes were also able to release sIR in response to both an inflammatory and insulin stimulus. DISCUSSION: These data support further investigation into the generation and role of sIR in AD. Highlights: Cerebrospinal fluid (CSF) soluble insulin receptor (sIR) levels positively correlate with amyloid beta (Aß)42 and Aß40.CSF sIR levels negatively correlate with cognitive performance (Montreal Cognitive Assessment score).CSF sIR levels in humans remain similar across Alzheimer's disease diagnostic groups.Neurons derived from humans with the "Swedish" mutation in which Aß42 is increased generate increased levels of sIR.Human astrocytes can also produce sIR and generation is stimulated by tumor necrosis factor α and insulin.

Application and Quality of Model-Based Meta-Analysis in Pharmaceutical Research: A Systematic Cross-Sectional Analysis and Practical Considerations.

Model-based meta-analysis (MBMA) can be used in assisting drug development and optimizing treatment in clinical practice, potentially reducing costs and accelerating drug approval. We aimed to assess the application and quality of MBMA studies. We searched multiple databases to identify MBMA in pharmaceutical research. Eligible MBMA should incorporate pharmacological concepts to construct mathematical models and quantitatively examine and/or predict drug effects. Relevant information was summarized to provide an overview of the application of MBMA. We used AMSTAR-2 and PRISMA 2020 checklists to evaluate the methodological and reporting quality of included MBMA, respectively. A total of 143 MBMA studies were identified. MBMA was increasingly used over time for one or more areas: drug discovery and translational research (n = 8, 5.6%), drug development decision making (n = 42, 29.4%), optimization of clinical trial design (n = 46, 32.2%), medication in special populations (n = 15, 10.5%), and rationality and safety of drug use (n = 71, 49.7%). The included MBMA covered 17 disease areas, with the top three being nervous system diseases (n = 19, 13.2%), endocrine/nutritional/metabolic diseases (n = 17, 11.8%), and neoplasms (n = 16, 11.1%). Of these MBMA studies, 138 (96.5%) were rated as very low quality. The average rate of compliance with PRISMA was only 51.4%. Our findings suggested that MBMA was mainly used to evaluate the efficacy and safety of drugs, with a focus on chronic diseases. The methodological and reporting quality of MBMA should be further improved. Given AMSTAR-2 and PRISMA checklists were not specifically designed for MBMA, adapted assessment checklists for MBMA should be warranted.

Analysis of risk factors associated with pre-myopia among primary school students in the Mianyang Science City.

Objectives To find out the prevalence rate of pre-myopia among primary school students in the Mianyang Science City Area, analyze its related risk factors, and thus provide a reference for local authorities to formulate policies on the prevention and control of myopia for primary school students. Methods From September to October 2021, Cluster sampling was adopted by our research group to obtain the vision levels of primary school students employing a diopter test in the Science City Area. In addition, questionnaires were distributed to help us find the risk factors associated with pre-myopia. Through the statistical analysis, we identify the main risk factors for pre-myopia and propose appropriate interventions. Results The prevalence rate of pre-myopia among primary school students in the Science City Area was 45.27% (1020/2253), of which 43.82% were boys and 46.92% were girls, with no statistically significant difference in the prevalence rate of myopia between boys and girls (2 =2.171, P=0.141). The results of the linear trend test showed that the prevalence rate of pre-myopia tends to decrease with increasing age (Z=296.521, P=0.000). Logistic regression analysis demonstrated that the main risk factors for pre-myopia were having at least one parent with myopia, spending less than 2 hours a day outdoors, using the eyes continuously for more than 1 hour, looking at electronic screens for more than 2 hours, and having an improper reading and writing posture. Conclusion The Science City Area has a high prevalence rate of pre-myopia among primary school students. It is proposed that students, schools, families, and local authorities work together to increase the time spent outdoors, reduce digital screens and develop scientific use of eye habits.

A machine learning-based diagnosis modeling of IgG4 Hashimoto's thyroiditis.

PURPOSE: This study aims to develop a non-invasive diagnosis model using machine learning (ML) for identifying high-risk IgG4 Hashimoto's thyroiditis (HT) patients. METHODS: A retrospective cohort of 93 HT patients and a prospective cohort of 179 HT patients were collected. According to the immunohistochemical and pathological results, the patients were divided into IgG4 HT group and non-IgG4 HT group. Serum TgAb IgG4 and TPOAb IgG4 were detected by ELISAs. A logistic regression model, support vector machine (SVM) and random forest (RF) were used to establish a clinical diagnosis model for IgG4 HT. RESULTS: Among these 272 patients, 40 (14.7%) were diagnosed with IgG4 HT. Patients with IgG4 HT were younger than those with non-IgG4 HT (P < 0.05). Serum levels of TgAb IgG4 and TPOAb IgG4 in IgG4 HT group were significantly higher than those in non-IgG4 HT group (P < 0.05). There were no significant differences in gender, disease duration, goiter, preoperative thyroid function status, preoperative TgAb or TPOAb levels, and thyroid ultrasound characteristics between the two groups (all P > 0.05). The accuracy, sensitivity, and specificity were 57%, 78%, and 79% for logistic regression model of IgG4 HT, 80 ± 7%, 84.7% ± 2.6%, and 75.4% ± 9.6% for the RF model and 78 ± 5%, 89.8% ± 5.7%, and 64.7% ± 5.7% for the SVM model. The RF model works better than SVM. The area under the ROC curve of RF ranged 0.87 to 0.92. CONCLUSION: A clinical diagnosis model for IgG4 HT established by RF model might help the early recognition of the high-risk patients of IgG4 HT.

A new gold(I) phosphine complex induces apoptosis in prostate cancer cells by increasing reactive oxygen species.

Thioredoxin reductase (TrxR) is a pivotal regulator of redox homeostasis. It is frequently overexpressed in various cancer cells, including prostate cancer, making it a promising target for the development of anti-cancer drugs. In this study, we screened a series of newly designed complexes of gold(I) phosphine. Specifically, Compound 5 exhibited the highest cytotoxicity against prostate cancer cells and demonstrated stronger antitumor effects than commonly used drugs, such as cisplatin and auranofin. Importantly, our mechanistic study revealed that Compound 5 effectively inhibits the TrxR system in vitro. Additionally, Compound 5 promoted intracellular accumulation of reactive oxygen species (ROS), leading to mitochondrial dysfunction and irreversible apoptosis in prostate cancer cells. Our in vivo xenograft study further demonstrated that Compound 5 has excellent antitumor activity against prostate cancer cells, but does not cause severe side effects. These findings provide a promising lead Compound for the development of novel antitumor agents targeting prostate cancer and offer a valuable tool for investigating biological pathways involving TrxR and ROS modulation.

Dipole Moment Influences the Reversibility and Corrosion of Lithium Metal Anodes.

Lithium metal batteries (LMBs) must have both long cycle life and calendar life to be commercially viable. However, "trial and error" methodologies remain prevalent in contemporary research endeavors to identify favorable electrolytes. Here, a guiding principle for the selection of solvents for LMBs is proposed, which aims to achieve high Coulombic efficiency while minimizing the corrosion. For the first time, this study reveals that the dipole moment and orientation of solvent molecules have significant impacts on lithium metal reversibility and corrosion. Solvents with high dipole moments are more likely to adsorb onto lithium metal surfaces, which also influence the solid electrolyte interphase. Using this principle, the use of LiNO3 is demonstrated as the sole salt in LiNi0.8Co0.1Mn0.1O2/Li cells can achieve excellent cycling stability. Overall, this work bridges the molecular structure of solvents to the reversibility and corrosion of lithium metal, and these concepts can be extended to other metal-based batteries.

Advanced Patch-Based Affine Motion Estimation for Dynamic Point Cloud Geometry Compression.

The substantial data volume within dynamic point clouds representing three-dimensional moving entities necessitates advancements in compression techniques. Motion estimation (ME) is crucial for reducing point cloud temporal redundancy. Standard block-based ME schemes, which typically utilize the previously decoded point clouds as inter-reference frames, often yield inaccurate and translation-only estimates for dynamic point clouds. To overcome this limitation, we propose an advanced patch-based affine ME scheme for dynamic point cloud geometry compression. Our approach employs a forward-backward jointing ME strategy, generating affine motion-compensated frames for improved inter-geometry references. Before the forward ME process, point cloud motion analysis is conducted on previous frames to perceive motion characteristics. Then, a point cloud is segmented into deformable patches based on geometry correlation and motion coherence. During the forward ME process, affine motion models are introduced to depict the deformable patch motions from the reference to the current frame. Later, affine motion-compensated frames are exploited in the backward ME process to obtain refined motions for better coding performance. Experimental results demonstrate the superiority of our proposed scheme, achieving an average 6.28% geometry bitrate gain over the inter codec anchor. Additional results also validate the effectiveness of key modules within the proposed ME scheme.

Targeting the MCP-GPX4/HMGB1 Axis for Effectively Triggering Immunogenic Ferroptosis in Pancreatic Ductal Adenocarcinoma.

Induction of ferroptosis can inhibit cancer cells in vitro, however, the role of ferroptosis in treatment in vivo is controversial. The immunosuppressive cells activated by the ferroptotic tumor cells can promote the growth of residual tumor cells, hindering the application of ferroptosis stimulation in tumor treatment. In this study, a new strategy is aimed to be identified for effectively triggering immunogenic ferroptosis in pancreatic ductal adenocarcinoma (PDAC) and simultaneously stimulating antitumor immune responses. Toward this, several molecular and biochemical experiments are performed using patient-derived organoid models and a KPC mouse model (LSL-KrasG12D /+, LSL-Trp53R172H/+, Pdx-1-Cre). It is observed that the inhibition of macrophage-capping protein (MCP) suppressed the ubiquitin fold modifier (UFM)ylation of pirin (PIR), a newly identified substrate of UFM1, thereby decreasing the transcription of GPX4, a marker of ferroptosis, and promoting the cytoplasmic transportation of HMGB1, a damage-associated molecular pattern. GPX4 deficiency triggered ferroptosis, and the pre-accumulated cytosolic HMGB1 is released rapidly. This altered release pattern of HMGB1 facilitated the pro-inflammatory M1-like polarization of macrophages. Thus, therapeutic inhibition of MCP yielded dual antitumor effects by stimulating ferroptosis and activating antitumor pro-inflammatory M1-like macrophages. The nanosystem developed for specifically silencing MCP is a promising tool for treating PDAC.

Stress-induced ordering evolution of 1D segmented heteronanostructures and their chemical post-transformations.

Investigations of one-dimensional segmented heteronanostructures (1D-SHs) have recently attracted much attention due to their potentials for applications resulting from their structure and synergistic effects between compositions and interfaces. Unfortunately, developing a simple, versatile and controlled synthetic method to fabricate 1D-SHs is still a challenge. Here we demonstrate a stress-induced axial ordering mechanism to describe the synthesis of 1D-SHs by a general under-stoichiometric reaction strategy. Using the continuum phase-field simulations, we elaborate a three-stage evolution process of the regular segment alternations. This strategy, accompanied by easy chemical post-transformations, enables to synthesize 25 1D-SHs, including 17 nanowire-nanowire and 8 nanowire-nanotube nanostructures with 13 elements (Ag, Te, Cu, Pt, Pb, Cd, Sb, Se, Bi, Rh, Ir, Ru, Zn) involved. This ordering evolution-driven synthesis will help to investigate the ordering reconstruction and potential applications of 1D-SHs.

A prognostic signature established based on genes related to tumor microenvironment for patients with hepatocellular carcinoma.

BACKGROUND: Complex cellular signaling network in the tumor microenvironment (TME) could serve as an indicator for the prognostic classification of hepatocellular carcinoma (HCC) patients. METHODS: Univariate Cox regression analysis was performed to screen prognosis-related TME-related genes (TRGs), based on which HCC samples were clustered by running non-negative matrix factorization (NMF) algorithm. Furthermore, the correlation between different molecular HCC subtypes and immune cell infiltration level was analyzed. Finally, a risk score (RS) model was established by LASSO and Cox regression analyses (CRA) using these TRGs. Functional enrichment analysis was performed using gene set enrichment analysis (GSEA). RESULTS: HCC patients were divided into three molecular subtypes (C1, C2, and C3) based on 704 prognosis-related TRGs. HCC subtype C1 had significantly better OS than C2 and C3. We selected 13 TRGs to construct the RS model. Univariate and multivariate CRA showed that the RS could independently predict patients' prognosis. A nomogram integrating the RS and clinicopathologic features of the patients was further created. We also validated the reliability of the model according to the area under the receiver operating characteristic (ROC) curve value, concordance index (C-index), and decision curve analysis. The current findings demonstrated that the RS was significantly correlated with CD8+ T cells, monocytic lineage, and myeloid dendritic cells. CONCLUSION: This study provided TRGs to help classify patients with HCC and predict their prognoses, contributing to personalized treatments for patients with HCC.

A review of long non-coding RNAs in ankylosing spondylitis: pathogenesis, clinical assessment, and therapeutic targets.

Ankylosing spondylitis (AS) is a chronic immune-mediated type of inflammatory arthritis characterized by inflammation, bone erosion, and stiffness of the spine and sacroiliac joints. Despite great efforts put into the investigation of the disease, the pathogenesis of AS remains unclear, posing challenges in identifying ideal targets for diagnosis and treatment. To enhance our understanding of AS, an increasing number of studies have been conducted. Some of these studies reveal that long non-coding RNAs (lncRNAs) play crucial roles in the etiology of AS. Some certain lncRNAs influence the development of AS by regulating inflammatory responses, autophagy, apoptosis, and adipogenesis, as well as the proliferation and differentiation of cells. Additionally, some lncRNAs demonstrate potential as biomarkers, aiding in monitoring disease progression and predicting prognosis. In this review, we summarize recent studies concerning lncRNAs in AS to elucidate the underlying mechanisms in which lncRNAs are involved and their potential values as biomarkers for disease assessment and druggable targets for therapy.

Reconfigurable optoelectronic transistors for multimodal recognition.

Biological nervous system outperforms in both dynamic and static information perception due to their capability to integrate the sensing, memory and processing functions. Reconfigurable neuromorphic transistors, which can be used to emulate different types of biological analogues in a single device, are important for creating compact and efficient neuromorphic computing networks, but their design remains challenging due to the need for opposing physical mechanisms to achieve different functions. Here we report a neuromorphic electrolyte-gated transistor that can be reconfigured to perform physical reservoir and synaptic functions. The device exhibits dynamics with tunable time-scales under optical and electrical stimuli. The nonlinear volatile property is suitable for reservoir computing, which can be used for multimodal pre-processing. The nonvolatility and programmability of the device through ion insertion/extraction achieved via electrolyte gating, which are required to realize synaptic functions, are verified. The device's superior performance in mimicking human perception of dynamic and static multisensory information based on the reconfigurable neuromorphic functions is also demonstrated. The present study provides an exciting paradigm for the realization of multimodal reconfigurable devices and opens an avenue for mimicking biological multisensory fusion.

Single-cell sequencing analysis confirms the association of ANRIL with the increased smooth muscle cell proliferation and migration gene signatures in pulmonary artery hypertension in silico.

PURPOSE: Smooth muscle cell (SMC) dysregulation is part of the pathological basis of pulmonary artery hypertension (PAH). We aimed to explore the heterogeneity of SMCs in PAH. METHODS: The profile GSE210248 was obtained from NCBI Gene Expression Omnibus, containing the scRNA-seq data of pulmonary arteries (PA) from three patients with PAH and three healthy donors. After quality control, normalization, and dimension reduction, cell clustering analysis was performed. Differential expression analysis and functional enrichment analysis were carried out successively in smooth muscle cells (SMCs). The enrichment scores of cell cycle and cell migration gene sets in SMCs were calculated. Then, the Spearman correlation coefficients between antisense non-coding RNA in the INK4 locus (ANRIL) expression and two gene sets were computed. RESULTS: Eight cell clusters were identified in PA from samples. The proportion of SMCs was increased in PAH samples. SMCs were divided into five subclusters with diverse biological functions. Muscle contraction-related SMC1 was decreased, while extracellular matrix organization-related SMC2, immune and inflammatory response-related SMC4 and SMC5 were increased in PAH samples compared with healthy donors. The enrichment scores of cell cycle and cell migration gene sets in SMCs were higher in PAH samples than in donors. ANRIL was down-regulated significantly in PAH samples and was negatively related to the scores of two gene sets. CONCLUSION: SMCs exhibited significant heterogeneity in PAH. The altered abilities of SMC proliferation and migration in PAH were associated with ANRIL expression.