Explore the vast range of titles available.

This review highlights recent progress in exosome-based drug delivery for cancer therapy, covering exosome biogenesis, cargo selection mechanisms, and their application across multiple cancer types. As small extracellular vesicles, exosomes exhibit high biocompatibility and low immunogenicity, making them ideal drug delivery vehicles capable of efficiently targeting cancer cells, minimizing off-target damage and side effects. This review aims to explore the potential of exosomes in cancer therapy, with a focus on applications in chemotherapy, gene therapy, and immunomodulation. Additionally, challenges related to exosome production and standardization are analyzed, highlighting the importance of addressing these issues for their clinical application. In conclusion, exosome-based drug delivery systems offer promising potential for future cancer therapies. Further research should aim to enhance production efficiency and facilitate clinical translation, paving the way for innovative cancer treatment strategies.

ObjectivesWe aimed to characterise the microbial changes associated with histological stages of gastric tumourigenesis.DesignWe performed 16S rRNA gene analysis of gastric mucosal samples from 81 cases including superficial gastritis (SG), atrophic gastritis (AG), intestinal metaplasia (IM) and gastric cancer (GC) from Xi’an, China, to determine mucosal microbiome dysbiosis across stages of GC. We validated the results in mucosal samples of 126 cases from Inner Mongolia, China.ResultsWe observed significant mucosa microbial dysbiosis in IM and GC subjects, with significant enrichment of 21 and depletion of 10 bacterial taxa in GC compared with SG (q<0.05). Microbial network analysis showed increasing correlation strengths among them with disease progression (p<0.001). Five GC-enriched bacterial taxa whose species identifications correspond to Peptostreptococcus stomatis, Streptococcus anginosus, Parvimonas micra, Slackia exigua and Dialister pneumosintes had significant centralities in the GC ecological network (p<0.05) and classified GC from SG with an area under the receiver-operating curve (AUC) of 0.82. Moreover, stronger interactions among gastric microbes were observed in Helicobacter pylori-negative samples compared with H. pylori-positive samples in SG and IM. The fold changes of selected bacteria, and strengths of their interactions were successfully validated in the Inner Mongolian cohort, in which the five bacterial markers distinguished GC from SG with an AUC of 0.81.ConclusionsIn addition to microbial compositional changes, we identified differences in bacterial interactions across stages of gastric carcinogenesis. The significant enrichments and network centralities suggest potentially important roles of P. stomatis, D. pneumosintes, S. exigua, P. micra and S. anginosus in GC progression.

Quantitative measurement of RNA expression levels through RNA-Seq is an ideal replacement for conventional cancer diagnosis via microscope examination. Currently, cancer-related RNA-Seq studies focus on two aspects: classifying the status and tissue of origin of a sample and discovering marker genes. Existing studies typically identify marker genes by statistically comparing healthy and cancer samples. However, this approach overlooks marker genes with low expression level differences and may be influenced by experimental results. This paper introduces “GENESO,” a novel framework for pan-cancer classification and marker gene discovery using the occlusion method in conjunction with deep learning. we first trained a baseline deep LSTM neural network capable of distinguishing the origins and statuses of samples utilizing RNA-Seq data. Then, we propose a novel marker gene discovery method called “Symmetrical Occlusion (SO)”. It collaborates with the baseline LSTM network, mimicking the “gain of function” and “loss of function” of genes to evaluate their importance in pan-cancer classification quantitatively. By identifying the genes of utmost importance, we then isolate them to train new neural networks, resulting in higher-performance LSTM models that utilize only a reduced set of highly relevant genes. The baseline neural network achieves an impressive validation accuracy of 96.59% in pan-cancer classification. With the help of SO, the accuracy of the second network reaches 98.30%, while using 67% fewer genes. Notably, our method excels in identifying marker genes that are not differentially expressed. Moreover, we assessed the feasibility of our method using single-cell RNA-Seq data, employing known marker genes as a validation test.

The microbiota-gut-brain axis has been suggested to play an important role in Parkinson’s disease (PD). Here we performed a cross-sectional study to profile gut microbiota across early PD, REM sleep behavior disorder (RBD), first-degree relatives of RBD (RBD-FDR), and healthy controls, which could reflect the gut-brain staging model of PD. We show gut microbiota compositions are significantly altered in early PD and RBD compared with control and RBD-FDR. Depletion of butyrate-producing bacteria and enrichment of pro-inflammatory Collinsella have already emerged in RBD and RBD-FDR after controlling potential confounders including antidepressants, osmotic laxatives, and bowel movement frequency. Random forest modelling identifies 12 microbial markers that are effective to distinguish RBD from control. These findings suggest that PD-like gut dysbiosis occurs at the prodromal stages of PD when RBD develops and starts to emerge in the younger RBD-FDR subjects. The study will have etiological and diagnostic implications. Microbiota-gut-brain axis may play an important role in Parkinson’s disease (PD). Here, the authors assess gut microbiota in early PD, REM sleep behaviour disorder (RBD) and first-degree relatives of RBD and show PD-like gut dysbiosis occurs in RBD and their first-degree relatives.

•From 1200 telephone interviews, the COVID-19 vaccine acceptance rate was 37.2%.•Acceptance rate was the highest in adults aged 18–24 years then increased with age.•Government recommendation was the strongest predictive factor of vaccine acceptance.•A key obstacle of acceptance included lack of confidence on vaccine manufacturers.•These predictors provide evidence-based formulation of vaccination strategies. Vaccines for COVID-19 are anticipated to be available by 2021. Vaccine uptake rate is a crucial determinant for herd immunity. We examined factors associated with acceptance of vaccine based on (1). constructs of the Health Belief Model (HBM), (2). trust in the healthcare system, new vaccine platforms and manufacturers, and (3). self-reported health outcomes. A population-based, random telephone survey was performed during the peak of the third wave of COVID-19 outbreak (27/07/2020 to 27/08/2020) in Hong Kong. All adults aged ≥ 18 years were eligible. The survey included sociodemographic details; self-report health conditions; trust scales; and self-reported health outcomes. Multivariable regression analyses were applied to examine independent associations. The primary outcome is the acceptance of the COVID-19 vaccine. We conducted 1200 successful telephone interviews (response rate 55%). The overall vaccine acceptance rate after adjustment for population distribution was 37.2% (95% C.I. 34.5–39.9%). The projected acceptance rates exhibited a “J-shaped” pattern with age, with higher rates among young adults (18–24 years), then increased linearly with age. Multivariable regression analyses revealed that perceived severity, perceived benefits of the vaccine, cues to action, self-reported health outcomes, and trust in healthcare system or vaccine manufacturers were positive correlates of acceptance; whilst perceived access barriers and harm were negative correlates. Remarkably, perceived susceptibility to infection carried no significant association, whereas recommendation from Government (aOR = 10.2, 95% C.I. 6.54 to 15.9, p < 0.001) was as the strongest driving factor for acceptance. Other key obstacles of acceptance included lack of confidence on newer vaccine platforms (43.4%) and manufacturers without track record (52.2%), which are of particular relevance to the current context. Governmental recommendation is an important driver, whereas perceived susceptibility is not associated with acceptance of COVID-19 vaccine. These HBM constructs and independent predictors inform evidence-based formulation and implementation of vaccination strategies.

Subarachnoid hemorrhage (SAH) is a common cerebrovascular disease that can lead to cognitive impairment. Although tetrandrine (Tet) has been proposed as a potential therapeutic agent, its efficacy in the treatment of SAH has not been fully explored. To investigate Tet effects on SAH, a rat model was established and divided into an SAH + vehicle and an SAH + Tet group. Cognitive function and behavioral performance were assessed using the Morris water maze and open field tests. Inflammatory cytokine levels were measured by ELISA, and hippocampal injury was evaluated by hematoxylin-eosin (HE) staining. Neuronal loss was quantified using Nissl staining, while neuronal density was assessed via immunofluorescence. The expression of the TLR4/NF-κB signaling pathway related-proteins was examined by Western blotting, and 16 S rRNA sequencing was conducted to determine differences in gut microbiota composition across the groups. Tet treatment significantly reduced mNSS and SAH assessment scores in SAH rats, suggesting an improvement in neurological and cognitive function. Behavioral analysis demonstrated that Tet increased escape latency, movement speed, and total distance in the Morris water maze. Histological staining revealed attenuated hippocampal damage and decreased neuronal death in the Tet-treated group. These neuroprotective effects were accompanied by reduced expression of TLR4 and NF-κB pathway components, as well as decreased secretion of LPS, TNF-α, IL-1β, and IL-6. Notably, Tet modulated the gut microbiota, restoring microbial diversity and abundance, and this modulation was associated with changes in the CYP51 metabolic pathway. Tet improves cognitive function and reduces neuronal injury in SAH rats by regulating the gut microbiota and its associated CYP51 metabolic pathway, thereby suppressing activation of the TLR4/NF-κB signaling cascade.

In the context of advancing sustainable urban development, the spatial organization of industries plays a critical role in shaping environmental quality, economic vitality, and public health. This study examines the health effects of furniture enterprises agglomeration in Chinese cities, using a unique dataset combining point-of-interest (POI) big data and micro-level survey responses from 13,217 individuals. The results show that a one-unit increase in furniture enterprises agglomeration intensity is associated with a 0.656-unit improvement in physical health and a 0.060-unit improvement in mental health. These benefits are driven by three synergistic mechanisms: environmental improvement, income growth, and enhanced public health services. However, the health gains are unevenly distributed, with greater benefits observed in less-developed cities and among vulnerable groups such as low-skilled and middle-aged workers. We further reveal divergent effects between specialized and diversified agglomeration patterns, moderated by environmental regulation. Our findings underscore the need for health-oriented industrial policies that align with sustainable urban planning, emphasizing spatial adaptation, targeted support for vulnerable populations, and innovative regulatory approaches to foster both industrial growth and resident well-being.

Background Nucleosome assembly protein 1-like 1 (NAP1L1) is highly expressed in various types of cancer and plays an important role in carcinogenesis, but its specific role in tumor development and progression remains largely unknown. In this study, we suggest the potential of NAP1L1 as a prognostic biomarker and therapeutic target for the treatment of ovarian cancer (OC). Methods In our study, a tissue microarray (TMA) slide containing specimens from 149 patients with OC and 11 normal ovarian tissues underwent immunohistochemistry (IHC) to analyze the correlation between NAP1L1 expression and clinicopathological features. Loss-of- function experiments were performed by transfecting siRNA and following lentiviral gene transduction into SKOV3 and OVCAR3 cells. Cell proliferation and the cell cycle were assessed by the Cell Counting Kit-8, EDU assay, flow cytometry, colony formation assay, and Western blot analysis. In addition, co-immunoprecipitation (Co-IP) and immunofluorescence assays were performed to confirm the relationship between NAP1L1 and its potential targets in SKOV3/OVCAR3 cells. Results High expression of NAP1L1 was closely related to poor clinical outcomes in OC patients. After knocking down NAP1L1 by siRNA or shRNA, both SKOV3 and OVCAR3 cells showed inhibition of cell proliferation, blocking of the G1/S phase, and increased apoptosis in vitro. Mechanism analysis indicated that NAP1L1 interacted with hepatoma-derived growth factor (HDGF) and they were co-localized in the cytoplasm. Furthermore, HDGF can interact with jun proto-oncogene (C-JUN), an oncogenic transformation factor that induces the expression of cyclin D1 (CCND1). Overexpressed HDGF in NAP1L1 knockdown OC cells not only increased the expression of C-JUN and CCND1, but it also reversed the suppressive effects of si-NAP1L1 on cell proliferation. Conclusions Our data demonstrated that NAP1L1 could act as a prognostic biomarker in OC and can interact with HDGF to mediate the proliferation of OC, and this process of triggered proliferation may contribute to the activation of HDGF/C-JUN signaling in OC cells.

Background Alterations of gut microbiota are associated with colorectal cancer (CRC) in different populations and several bacterial species were found to contribute to the tumorigenesis. The potential use of gut microbes as markers for early diagnosis has also been reported. However, cohort specific noises may distort the structure of microbial dysbiosis in CRC and lead to inconsistent results among studies. In this regard, our study targeted at exploring changes in gut microbiota that are universal across populations at species level. Results Based on the combined analysis of 526 metagenomic samples from Chinese, Austrian, American, and German and French cohorts, seven CRC-enriched bacteria ( Bacteroides fragilis , Fusobacterium nucleatum , Porphyromonas asaccharolytica , Parvimonas micra , Prevotella intermedia , Alistipes finegoldii , and Thermanaerovibrio acidaminovorans ) have been identified across populations. The seven enriched bacterial markers classified cases from controls with an area under the receiver-operating characteristics curve (AUC) of 0.80 across the different populations. Abundance correlation analysis demonstrated that CRC-enriched and CRC-depleted bacteria respectively formed their own mutualistic networks, in which the latter was disjointed in CRC. The CRC-enriched bacteria have been found to be correlated with lipopolysaccharide and energy biosynthetic pathways. Conclusions Our study identified potential diagnostic bacterial markers that are robust across populations, indicating their potential universal use for non-invasive CRC diagnosis. We also elucidated the ecological networks and functional capacities of CRC-associated microbiota.

Lysine lactylation (Kla), first described in 2019, is an emerging post-translational modification that converts lactate availability into changes in chromatin state and protein function. In cancer, where glycolysis and microenvironmental hypoxia often elevate lactate, lactylation has been linked to transcriptional reprogramming, immune modulation, cellular plasticity, and therapy resistance. Here, we synthesize current evidence across major organ systems to clarify how lactylation is generated, interpreted, and removed, and how it interacts with tumor metabolism and the tumor microenvironment. We summarize enzymatic and non-enzymatic routes to Kla formation, discuss candidate writers, erasers, and readers, and highlight recurring mechanistic patterns spanning histone and non-histone substrates, including regulation of immune-evasive signaling, ferroptosis susceptibility, DNA repair, and stress-adaptation programs. We also integrate translational considerations, outlining druggable nodes within lactate production and transport pathways and within acetyltransferase and deacylase systems, and discuss how lactylation measurements could support patient stratification, pharmacodynamic monitoring, and rational combination strategies. Finally, we identify key open questions that currently limit clinical translation, including site-level causality, cell-type and spatial attribution in patient tissues, assay specificity and quantitative stoichiometry, and the conditions under which lactylation promotes versus restrains tumor progression. Together, this framework aims to guide mechanistic studies and accelerate the development of clinically actionable lactylation-directed interventions.