Repetitive transcranial magnetic stimulation in Alzheimer's disease: effects on neural and synaptic rehabilitation.

Alzheimer's disease is a neurodegenerative disease resulting from deficits in synaptic transmission and homeostasis. The Alzheimer's disease brain tends to be hyperexcitable and hypersynchronized, thereby causing neurodegeneration and ultimately disrupting the operational abilities in daily life, leaving patients incapacitated. Repetitive transcranial magnetic stimulation is a cost-effective, neuro-modulatory technique used for multiple neurological conditions. Over the past two decades, it has been widely used to predict cognitive decline; identify pathophysiological markers; promote neuroplasticity; and assess brain excitability, plasticity, and connectivity. It has also been applied to patients with dementia, because it can yield facilitatory effects on cognition and promote brain recovery after a neurological insult. However, its therapeutic effectiveness at the molecular and synaptic levels has not been elucidated because of a limited number of studies. This study aimed to characterize the neurobiological changes following repetitive transcranial magnetic stimulation treatment, evaluate its effects on synaptic plasticity, and identify the associated mechanisms. This review essentially focuses on changes in the pathology, amyloidogenesis, and clearance pathways, given that amyloid deposition is a major hypothesis in the pathogenesis of Alzheimer's disease. Apoptotic mechanisms associated with repetitive transcranial magnetic stimulation procedures and different pathways mediating gene transcription, which are closely related to the neural regeneration process, are also highlighted. Finally, we discuss the outcomes of animal studies in which neuroplasticity is modulated and assessed at the structural and functional levels by using repetitive transcranial magnetic stimulation, with the aim to highlight future directions for better clinical translations.

The prognostic role of an optimal machine learning model based on clinical available indicators in HCC patients.

Although methods in diagnosis and therapy of hepatocellular carcinoma (HCC) have made significant progress in the past decades, the overall survival (OS) of liver cancer is still disappointing. Machine learning models have several advantages over traditional cox models in prognostic prediction. This study aimed at designing an optimal panel and constructing an optimal machine learning model in predicting prognosis for HCC. A total of 941 HCC patients with completed survival data and preoperative clinical chemistry and immunology indicators from two medical centers were included. The OCC panel was designed by univariate and multivariate cox regression analysis. Subsequently, cox model and machine-learning models were established and assessed for predicting OS and PFS in discovery cohort and internal validation cohort. The best OCC model was validated in the external validation cohort and analyzed in different subgroups. In discovery, internal and external validation cohort, C-indexes of our optimal OCC model were 0.871 (95% CI, 0.863-0.878), 0.692 (95% CI, 0.667-0.717) and 0.648 (95% CI, 0.630-0.667), respectively; the 2-year AUCs of OCC model were 0.939 (95% CI, 0.920-0.959), 0.738 (95% CI, 0.667-0.809) and 0.725 (95% CI, 0.643-0.808), respectively. For subgroup analysis of HCC patients with HBV, aged less than 65, cirrhosis or resection as first therapy, C-indexes of our optimal OCC model were 0.772 (95% CI, 0.752-0.792), 0.769 (95% CI, 0.750-0.789), 0.855 (95% CI, 0.846-0.864) and 0.760 (95% CI, 0.741-0.778), respectively. In general, the optimal OCC model based on RSF algorithm shows prognostic guidance value in HCC patients undergoing individualized treatment.

Baicalin induces cell death of non-small cell lung cancer cells via MCOLN3-mediated lysosomal dysfunction and autophagy blockage.

BACKGROUND: Non-small cell lung cancer (NSCLC) accounts for 85 % of lung cancer, becoming the most mortality of all cancers globally. Blockage of autophagy in NSCLC represents a promising therapeutic strategy that inhibits angiogenesis and overcomes drug resistance. Natural ingredients in anti-tumor adjuvants are increasingly reported to promote cell death with less side effects and the potential to increase chemotherapeutic drugs sensitivity. Baicalin, a Scutellaria baicalensis-extracted flavonoid glycoside, is reported to induce death of NSCLC cells, however, its effects on autophagy in NSCLC cells remain unclear. PURPOSE: This study aimed to investigate the effect of baicalin on autophagic flux in NSCLC cells, unraveling the underlying mechanism including potential target and its role in cell death of NSCLC cells. METHODS: In vitro anti-cancer effects of baicalin were verified by evaluating proliferation, clone formation, cell cycle, and cell migration in three NSCLC cell lines (A549, H1299, and PC-9). In vivo anti-tumor efficacies of baicalin were evaluated in subcutaneous xenograft tumor model in nude mice. Autophagy characterization in NSCLC cells included autophagic marker detection by western blot and immunofluorescence staining, subcellular structure observation by TEM, lysosomal function by RNA-seq and fluorescence staining (LysoTracker®, LysoSensor®, and acridine orange). Based on RNA-seq and molecular biological verification using apoptotic, autophagic, and lysosomal inhibitors, potential target molecule of baicalin was verified via Ca2+ flux assay, MCOLN3 knockdown by shRNA, and virtual molecular docking. RESULTS: Baicalin inhibited NSCLC cell proliferation and migration, and suppressed tumor growth in vivo. Baicalin blocked the autophagic flux via activating the membranal cation channel MCOLN3 of lysosome, which disrupted its Ca2+ balance and induced lysosome dysfunction, leading to failure of autolysosome degradation. The cytoplasmic Ca2+ imbalance further resulted in depolarization of mitochondrial membrane potentials and ROS accumulation in NSCLC cells, mediating autophagy-related apoptosis. CONCLUSION: This study demonstrated that baicalin inhibited autolysosome degradation by activating MCOLN3, leading to dysfunction in lysosomal pH elevation, thereby inhibiting autophagy in NSCLC, leading to apoptotic death of NSCLC cells. These findings enriched the existing theories of cancer therapy based on autophagy inhibition and underlying mechanisms of flavonoids as antitumor agents, paving the way for their clinical application in future.

Fluoride induces hepatointestinal damage and vitamin B2 mitigation by regulating IL-17A and Bifidobacterium in ileum.

INTRODUCTION: Fluorosis is a global public health disease affecting more than 50 countries and 500 million people. Excessive fluoride damages the liver and intestines, yet the mechanisms and therapeutic approaches remain unclear. OBJECTIVES: To explore the mechanisms by which fluoride-induced intestinal-hepatic damage and vitamin B2 alleviation. METHODS: Fluoride and/or vitamin B2-treated IL-17A knockout and wild-type mouse models were established, the morphological and functional changes of liver and gut, total bile acid biosynthesis, metabolism, transport, and regulation of FXR-FGF15 signaling pathways were evaluated, the ileal microbiome was further analyzed by 16S rDNA sequence. Finally, Bifidobacterium supplementation mouse model was designed and re-examined the above indicators. RESULTS: The results demonstrated that fluoride induced hepatointestinal injury and enterohepatic circulation disorder by altering the synthesis, transporters, and FXR-FGF15 pathway regulation of total bile acid. Importantly, the ileum was found to be the most sensitive and fluoride changed ileal microbiome particularly by reducing abundance of Bifidobacterium. While vitamin B2 supplementation attenuated fluoride-induced enterohepatic circulation dysfunction through IL-17A and ileal microbiome, Bifidobacterium supplementation also reversed fluoride-induced hepatointestinal injury. CONCLUSION: Fluoride induces morphological and functional impairment of liver and gut tissues, as well as enterohepatic circulation disorder by altering total bile acid (TBA) synthesis, transporters, and FXR-FGF15 signaling regulation. Vitamin B2 attenuated fluoride-induced enterohepatic circulation disorder through IL-17A knockout and ileal microbiome regulation. The ileum was found to be the most sensitive to fluoride, leading to changes in ileal microbiome, particularly the reduction of Bifidobacterium. Furthermore, Bifidobacterium supplementation reversed fluoride-induced hepatointestinal injury. This study not only elucidates a novel mechanism by which fluoride causes hepatointestinal toxicity, but also provides a new physiological function of vitamin B2, which will be useful in the therapy of fluorosis and other hepatoenterological diseases.

Effects of functional defects in the NMD pathway on rice phenotype and transcriptome.

Nonsense-mediated mRNA decay (NMD) is an important RNA quality control pathway. It aids in degrading harmful erroneous mRNA, thereby preserving a stable and healthy internal environment. In this study, we employed CRISPR/Cas9 and amiRNA technology to generate knock out or knock down mutants of realted genes in the rice NMD pathway. Through transcriptome sequencing and observing phenotype changes, the study explored the impact of NMD pathway defects on rice gene expression and alternative splicing. The results suggest that even partial defects will induce phenotypic changes such as plant height and pollen vitality to different degrees, showing necessity of NMD factors. Gene expression analysis reveals that most differentially expressed genes are upregulated in the mutants, with ko-upf1-like and kd-upf1 defects having a more significant impact than kd-upf2 and kd-upf3. Specifically, NMD pathway defects result in increased expression levels of rice defense response-related genes and decreased expression levels of secondary metabolism-related genes, with a wider range of affected genes observed in 60-day-old senescence mutants. Transcript analysis indicates that different NMD related genes defects alter hundreds of alternative splicing events, mostly enriched in genes involving alternative splicing regulatory pathways. Approximately half of these events are shared among different mutants, and a substantial number of affected transcripts show NMD target features. NMD could affect both the transcript abundance and their splicing subtypes to regulate the defense response and early-senescence associated pathways, which plays a vital role in rice growth and reproduction.

Widely Targeted Metabolomic Analysis Reveals the Improvement in Panax notoginseng Triterpenoids Triggered by Arbuscular Mycorrhizal Fungi via UPLC-ESI-MS/MS.

Panax notoginseng is a highly valued perennial medicinal herb in China and is widely used in clinical treatments. The main purpose of this study was to elucidate the changes in the composition of P. notoginseng saponins (PNSs), which are the main bioactive substances, triggered by arbuscular mycorrhizal fungi (AMF) via ultrahigh-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS). A total of 202 putative terpenoid metabolites were detected, of which 150 triterpene glycosides were identified, accounting for 74.26% of the total. Correlation analysis, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) of the metabolites revealed that the samples treated with AMF (group Ce) could be clearly separated from the CK samples. In total, 49 differential terpene metabolites were identified between the Ce and CK groups, of which 38 and 11 metabolites were upregulated and downregulated, respectively, and most of the upregulated differentially abundant metabolites were mainly triterpene glycosides. The relative abundances of the two major notoginsenosides (MNs), ginsenosides Rd and Re, and 13 rare notoginsenosides (RNs), significantly increased. The differential saponins, especially RNs, were more easily clustered into one branch and had a high positive correlation. It could be concluded that the biosynthesis and accumulation of some RNs share the same pathways as those triggered by AMF. This study provides a new way to obtain more notoginsenoside resources, particularly RNs, and sheds new light on the scientization and rationalization of the use of AMF agents in the ecological planting of medicinal plants.

Ruxolitinib Plus Basiliximab Therapy for Steroid-Refractory Acute Graft-Versus-Host Disease in Unrelated Cord Blood Transplantation: A Large-Scale Study.

Steroid-refractory (SR) acute graft-versus-host disease (aGVHD) is a major cause of mortality after allogeneic hematopoietic stem cell transplantation. We aimed to evaluate the effectiveness and safety of ruxolitinib plus basiliximab for treating SR-aGVHD after unrelated cord blood transplantation (UCBT). Among the 1154 patients with hematological malignancies who underwent UCBT between February 2014 and May 2022, 198 patients with grade II to IV SR-aGVHD were enrolled, 112 of whom were treated with basiliximab alone (basiliximab group) and 86 of whom received basiliximab plus ruxolitinib (combined therapy group). The combined therapy group demonstrated a significantly higher complete response rate (CRR) on day 28 (36.0%) than did the basiliximab group (12.5%, P < .001). SR-aGVHD patients were further stratified into standard-risk and high-risk groups using the refined Minnesota aGVHD risk score. For standard-risk patients, combined therapy significantly improved the CRR (51.1% versus 13.6%, P < .001) and 3-year overall survival (74.5% versus 52.4%, P = .033). However, high-risk patients did not exhibit the same benefits. Compared with basiliximab monotherapy, ruxolitinib plus basiliximab therapy was an effective therapy for patients with standard-risk SR-aGVHD following UCBT. The effectiveness of combined therapy in high-risk patients was not apparent, indicating the need for other treatments.

Machine Learning Approach in Dosage Individualization of Isoniazid for Tuberculosis.

INTRODUCTION: Isoniazid is a first-line antituberculosis agent with high variability, which would profit from individualized dosing. Concentrations of isoniazid at 2 h (C2h), as an indicator of safety and efficacy, are important for optimizing therapy. OBJECTIVE: The objective of this study was to establish machine learning (ML) models to predict the C2h, that can be used for establishing an individualized dosing regimen in clinical practice. METHODS: Published population pharmacokinetic (PopPK) models for adults were searched based on PubMed and ultimately four reliable models were selected for simulating individual C2h datasets under different conditions (demographics, genotype, ethnicity, etc.). Machine learning models were trained on simulated C2h obtained from the four PopPK models. Five different algorithms were used for ML model building to predict C2h. Real-world data were used for predictive performance evaluations. Virtual trials were used to compare ML-optimized doses with PopPK model-optimized doses. RESULTS: Categorical boosting (CatBoost) exhibited the highest prediction ability. Target C2h can be predicted using the ML model combined with the dosing regimen and three covariates (N-acetyltransferase 2 [NAT2] genotypes, weight and race [Asians and Africans]). Real-world data validation results showed that the ML model can achieve an overall prediction accuracy of 93.4%. Using the final ML model, the mean absolute prediction error value decreased by 45.7% relative to the average of PopPK models. Using the ML-optimized dosing regimen, the probability of target attainment increased by 43.7% relative to the PopPK model-optimized dosing regimens. CONCLUSION: Machine learning models were developed with great predictive performance, which can be used to determine the individualized initial dose of isoniazid in adult patients.

Depressive and anxiety symptoms among schizophrenia patients.

BACKGROUND: Depressive and anxiety symptoms commonly manifested throughout the progression of schizophrenia. However, the prevalence of these symptoms, alongside their co-occurrence, remains uncertain, and clinical correlates remain elusive. OBJECTIVES: This study seeks to investigate the prevalence of such symptoms and their demographic and clinical associations among patients diagnosed with schizophrenia. METHODS: The study included 19,623 patients diagnosed with schizophrenia based on the ICD-10 criteria. Participants were recruited from community-dwelling patients registered in the local health system in Hangzhou of China between August 1 and October 30, 2022. RESULTS: The prevalence rates of depressive and anxiety symptoms, as well as their co-occurrence, were determined to be 19 % (95%CI = 18.5-19.6 %), 37.4 % (95%CI = 36.8-38.0 %), and 17.7 % (95%CI = 17.2-18.2 %), respectively. Patients prescribed quetiapine, olanzapine, and risperidone exhibited significantly lower prevalence rates of these symptoms (P < 0.01). Spearman's correlation analysis revealed a significant correlation between depressive symptoms and anxiety symptoms (r = 0.60, P = 0.006). Additionally, age, social relationships, and sleep status were significantly associated with depressive and anxiety symptoms, and their co-occurrence, in both univariate and multivariate analyses. CONCLUSION: Given the pervasive nature and detrimental consequences of these symptoms among individuals diagnosed with schizophrenia, comprehensive evaluation and implementation of efficacious interventions are highly recommended.

Residential quality, physical activity, and restorative perceptions: A seasonal longitudinal study.

While the restorative benefits of residential environments are known, the influence of residents' physical activity on their perceptions of restorativeness in different settlements is unclear. This study aimed to investigate the mediating and moderating roles of residents' physical activities and seasons on restorative perceptions using survey data from three settlements in Harbin, China, involving a baseline survey conducted in June 2023 and questionnaires administered at 30-day intervals from July to December 2023 (534 interviews). Residents' restorative perceptions and physical activity levels were highest in autumn, with settlement quality having a seasonal moderating effect and physical activity having a mediating effect.

Application of Artificial Intelligence in rehabilitation science: A scientometric investigation Utilizing Citespace.

This study presents a scientometric analysis of the intersection between rehabilitation science and artificial intelligence (AI) technologies, using data from the Web of Science (WOS) database from 2002 to 2022. The analysis employed a comprehensive search query with key AI-related terms, focusing on a wide range of publications in rehabilitation science. Utilizing the Citespace tool, the study visualizes and quantifies the relationships between key terms, identifies research trends, and assesses the impact of AI technologies in rehabilitation science. Findings reveal a significant increase in AI-related research in this field, particularly from 2017 onwards, peaking in 2021. The United States has been a leading contributor, followed by countries like England, Australia, Germany, and Canada. Major institutional contributions come from Harvard University and the Pennsylvania Commonwealth System of Higher Education, among others. A keyword co-occurrence network constructed through Citespace identifies nine distinct hot topics and various research frontiers, highlighting evolving focus areas within the field. Burst analysis of keywords indicates a shift from performance and injury-related research to an increasing emphasis on AI and deep learning in recent years. The study also predicts the potential impact of papers, spotlighting works by Kunze KN and others as significantly influencing future research directions. Additionally, it examines the evolution of knowledge bases in AI-related rehabilitation science research, revealing a multidisciplinary core that includes neurology, rehabilitation, and ophthalmology, extending to complementary fields such as medicine and social sciences. This scientometric analysis provides a comprehensive overview of AI's application in rehabilitation science, offering insights into its evolution, impact, and emerging trends over the past two decades. The findings suggest strategic directions for future research, policy-making, and interdisciplinary collaboration in rehabilitation science and AI.

Development of graphitic carbon nitride quantum dots-based oxygen self-sufficient platforms for enhanced corneal crosslinking.

Keratoconus, a disorder characterized by corneal thinning and weakening, results in vision loss. Corneal crosslinking (CXL) can halt the progression of keratoconus. The development of accelerated corneal crosslinking (A-CXL) protocols to shorten the treatment time has been hampered by the rapid depletion of stromal oxygen when higher UVA intensities are used, resulting in a reduced cross-linking effect. It is therefore imperative to develop better methods to increase the oxygen concentration within the corneal stroma during the A-CXL process. Photocatalytic oxygen-generating nanomaterials are promising candidates to solve the hypoxia problem during A-CXL. Biocompatible graphitic carbon nitride (g-C3N4) quantum dots (QDs)-based oxygen self-sufficient platforms including g-C3N4 QDs and riboflavin/g-C3N4 QDs composites (RF@g-C3N4 QDs) have been developed in this study. Both display excellent photocatalytic oxygen generation ability, high reactive oxygen species (ROS) yield, and excellent biosafety. More importantly, the A-CXL effect of the g-C3N4 QDs or RF@g-C3N4 QDs composite on male New Zealand white rabbits is better than that of the riboflavin 5'-phosphate sodium (RF) A-CXL protocol under the same conditions, indicating excellent strengthening of the cornea after A-CXL treatments. These lead us to suggest the potential application of g-C3N4 QDs in A-CXL for corneal ectasias and other corneal diseases.

Crystallographic phase identifier of a convolutional self-attention neural network (CPICANN) on powder diffraction patterns.

Spectroscopic data, particularly diffraction data, are essential for materials characterization due to their comprehensive crystallographic information. The current crystallographic phase identification, however, is very time consuming. To address this challenge, we have developed a real-time crystallographic phase identifier based on a convolutional self-attention neural network (CPICANN). Trained on 692 190 simulated powder X-ray diffraction (XRD) patterns from 23 073 distinct inorganic crystallographic information files, CPICANN demonstrates superior phase-identification power. Single-phase identification on simulated XRD patterns yields 98.5 and 87.5% accuracies with and without elemental information, respectively, outperforming JADE software (68.2 and 38.7%, respectively). Bi-phase identification on simulated XRD patterns achieves 84.2 and 51.5% accuracies, respectively. In experimental settings, CPICANN achieves an 80% identification accuracy, surpassing JADE software (61%). Integration of CPICANN into XRD refinement software will significantly advance the cutting-edge technology in XRD materials characterization.

KIAA1429 increases FOXM1 expression through YTHDF1-mediated m6A modification to promote aerobic glycolysis and tumorigenesis in multiple myeloma.

OBJECTIVE: Multiple myeloma (MM) is a deadly plasma cell malignancy with elusive pathogenesis. N6-methyladenosine (m6A) is critically engaged in hematological malignancies. The function of KIAA1429, the largest component of methyltransferases, is unknown. This study delved into the mechanism of KIAA1429 in MM, hoping to offer novel targets for MM therapy. METHODS: Bone marrow samples were attained from 55 MM patients and 15 controls. KIAA1429, YTHDF1, and FOXM1 mRNA levels were detected and their correlation was analyzed. Cell viability, proliferation, cell cycle, and apoptosis were testified. Glycolysis-enhancing genes (HK2, ENO1, and LDHA), lactate production, and glucose uptake were evaluated. The interaction between FOXM1 mRNA and YTHDF1, m6A-modified FOXM1 level, and FOXM1 stability were assayed. A transplantation tumor model was built to confirm the mechanism of KIAA1429. RESULTS: KIAA1429 was at high levels in MM patients and MM cells and linked to poor prognoses. KIAA1429 knockdown restrained MM cell viability, and proliferation, arrested G0/G1 phase, and increased apoptosis. KIAA1429 mRNA in plasma cells from MM patients was positively linked with to glycolysis-enhancing genes. The levels of glycolysis-enhancing genes, glucose uptake, and lactate production were repressed after KIAA1429 knockdown, along with reduced FOXM1 levels and stability. YTHDF1 recognized KIAA1429-methylated FOXM1 mRNA and raised FOXM1 stability. Knockdown of YTHDF1 curbed aerobic glycolysis and malignant behaviors in MM cells, which was nullified by FOXM1 overexpression. KIAA1429 knockdown also inhibited tumor growth in animal experiments. CONCLUSION: KIAA1429 knockdown reduces FOXM1 expression through YTHDF1-mediated m6A modification, thus inhibiting MM aerobic glycolysis and tumorigenesis.

Causal associations between the gut microbiota and multiple myeloma: a two-sample Mendelian randomization study.

Background: Previous observational studies have indicated a potential association between the gut microbiota and multiple myeloma (MM). However, the relationship between the gut microbiota and MM remains unclear. This study aimed to ascertain the existence of a causal link between the gut microbiota and MM. Methods: To investigate the potential causal relationship between gut microbiota and MM, a two-sample Mendelian randomization (MR) analysis was conducted. Exposure data was obtained from the MiBioGen consortium, which provided genetic variants associated with 211 bacterial traits. MM outcome data was obtained from the FinnGen consortium. The selection of Single nucleotide polymorphisms estimates was performed through meta-analysis using inverse-variance weighting, and sensitivity analyses were conducted using weighted median, MR Egger, Simple mode, and MR-PRESSO. Results: The results of the study demonstrated a significant positive correlation between the genus Eubacterium ruminantium group and the risk of MM (OR 1.71, 95% CI 1.21 to 2.39). Conversely, the genus: Dorea (OR 0.46, 95% CI 0.24 to 0.86), Coprococcus1 (OR 0.47, 95% CI 0.22 to 1.00), RuminococcaceaeUCG014 (OR 0.57, 95% CI 0.33 to 0.99), Eubacterium rectale group (OR 0.37, 95% CI 0.18 to 0.77), and order: Victivallales (OR 0.62, 95% CI 0.41-0.94), class: Lentisphaeria (OR 0.62, 95% CI 0.41 to 0.94), exhibited a negative association with MM. The inverse variance weighting analysis provided additional support for these findings. Conclusion: This study represents an inaugural exploration of MR to investigate the connections between gut microbiota and MM, thereby suggesting potential significance for the prevention and treatment of MM.

Enhanced Intrusion of Exogenous Airborne Fine Particles toward Eyes in Humans and Animals: Where Damaged Blood-Ocular Barrier Plays a Crucial Role.

Emerging data suggest a close correlation between ambient fine particle (AFP) exposure and eye disorders and pinpoint potential threats of AFPs to eye health in humans. However, the possible passage (including direct intrusion) and the interactions of AFPs with the eye microenvironment in addition to morphological and physiological injuries remain elusive. To this end, the likely transport of AFPs into the eyes via blood-ocular barrier (BOB) in humans and animals was investigated herein. Exogenous particles were recognized inside human eyes with detailed structural and chemical fingerprints. Importantly, comparable AFPs were found in sera with constant structural and chemical fingerprints, hinting at the translocation pathway from blood circulation into the eye. Furthermore, we found that the particle concentrations in human eyes from patients with diabetic retinopathy were much higher than those from patients with no fundus pathological changes (i.e., myopia), indicating that the damaged BOB increased the possibility of particle entrance. Our diseased animal model further corroborated these findings. Collectively, our results offer a new piece of evidence on the intrusion of exogenous particles into human eyes and provide an explanation for AFP-induced eye disorders, with substantially increased risk in susceptible individuals with BOB injuries.

Role of ZNF334 in cervical cancer: implications for EMT reversal and tumor suppression.

Zinc-finger proteins are involved in many biological processes. However, the role of Zinc-finger protein 334 (ZNF334) in cervical cancer remains unidentified. This study showed that promoter methylation of ZNF334 was responsible for its reduced expression. ZNF334 suppressed malignant biological behaviors in cervical cancer. Notably, ZNF334 reversed the EMT process both in vitro and in vivo. RNA-seq coupled with bioinformatics analysis caught P3H3 which is upregulated by ZNF334. Dual-luciferase reporter and Chromatin immunoprecipitation assays illustrated that ZNF334 directly regulate P3H3. Knockdown of P3H3 attenuated the reversal of EMT induced by ZNF334. Additionally, ZNF334 overexpression sensitized cervical cancer cells to the cytotoxic effects of paclitaxel, cyclosporine and sunitinib. In conclusions, this study illustrated that DNA methylation-based silencing ZNF334 played a vital role in cervical cancer, by regulating P3H3 in turn affects EMT. ZNF334 has the potential to become a novel diagnostic biomarker and a potential treatment target for cervical cancer.

Deciphering the spatiotemporal transcriptional landscape of intestinal diseases (Review).

The intestines are the largest barrier organ in the human body. The intestinal barrier plays a crucial role in maintaining the balance of the intestinal environment and protecting the intestines from harmful bacterial invasion. Single­cell RNA sequencing technology allows the detection of the different cell types in the intestine in two dimensions and the exploration of cell types that have not been fully characterized. The intestinal mucosa is highly complex in structure, and its proper functioning is linked to multiple structures in the proximal­distal intestinal and luminal­mucosal axes. Spatial localization is at the core of the efforts to explore the interactions between the complex structures. Spatial transcriptomics (ST) is a method that allows for comprehensive tissue analysis and the acquisition of spatially separated genetic information from individual cells, while preserving their spatial location and interactions. This approach also prevents the loss of fragile cells during tissue disaggregation. The emergence of ST technology allows us to spatially dissect enzymatic processes and interactions between multiple cells, genes, proteins and signals in the intestine. This includes the exchange of oxygen and nutrients in the intestine, different gradients of microbial populations and the role of extracellular matrix proteins. This regionally precise approach to tissue studies is gaining more acceptance and is increasingly applied in the investigation of disease mechanisms related to the gastrointestinal tract. Therefore, this review summarized the application of ST in gastrointestinal diseases.

Innovative Nanotechnology in Drug Delivery Systems for Advanced Treatment of Posterior Segment Ocular Diseases.

Funduscopic diseases, including diabetic retinopathy (DR) and age-related macular degeneration (AMD), significantly impact global visual health, leading to impaired vision and irreversible blindness. Delivering drugs to the posterior segment of the eye remains a challenge due to the presence of multiple physiological and anatomical barriers. Conventional drug delivery methods often prove ineffective and may cause side effects. Nanomaterials, characterized by their small size, large surface area, tunable properties, and biocompatibility, enhance the permeability, stability, and targeting of drugs. Ocular nanomaterials encompass a wide range, including lipid nanomaterials, polymer nanomaterials, metal nanomaterials, carbon nanomaterials, quantum dot nanomaterials, and so on. These innovative materials, often combined with hydrogels and exosomes, are engineered to address multiple mechanisms, including macrophage polarization, reactive oxygen species (ROS) scavenging, and anti-vascular endothelial growth factor (VEGF). Compared to conventional modalities, nanomedicines achieve regulated and sustained delivery, reduced administration frequency, prolonged drug action, and minimized side effects. This study delves into the obstacles encountered in drug delivery to the posterior segment and highlights the progress facilitated by nanomedicine. Prospectively, these findings pave the way for next-generation ocular drug delivery systems and deeper clinical research, aiming to refine treatments, alleviate the burden on patients, and ultimately improve visual health globally.