A multifunctional near-infrared fluorescent probe based on benzothiazole structure for fluoride-ion detection.

Fluoride ions (F-) are one of the essential trace elements for the human body and are widely existed in nature. In this study, we present a novel fluorescent probe (YF-SZ-F) designed and synthesized for the specific detection of F-. The probe exhibits high sensitivity, excellent selectivity, and low cytotoxicity, making it a promising tool for biomedical applications. Imaging experiments conducted on zebrafish and Arabidopsis roots demonstrate the probe's remarkable cellular permeability and biocompatibility, laying a solid foundation for its potential biomedical utility. Furthermore, the probe holds potential for practical applications in environmental monitoring and public health through its capability to detect fluoride ions in water samples and via mobile phone software. This multifaceted functionality underscores the broad applicability and significance of the fluorescent probe, not only in scientific research but also in real-world scenarios, contributing to the development of more convenient and precise methods for fluoride detection.

A versatile nanoplatform carrying cascade Pt nanozymes remodeling tumor microenvironment for amplified sonodynamic/chemo therapy of thyroid cancer.

Thyroid cancer is increasing globally, with anaplastic thyroid carcinoma (ATC) being the most aggressive type and having a poor prognosis. Current clinical treatments for thyroid cancer present numerous challenges, including invasiveness and the necessity of lifelong medication. Furthermore, a significant portion of patients with ATC experience cancer recurrence and metastasis. To overcome this dilemma, we developed a pH-responsive biomimetic nanocarrier (CLP@HP-A) through the incorporation of Chlorin e6 (Ce6) and Lenvatinib (Len) within hollow polydopamine nanoparticles (HP) that were further modified with platinum nanoparticles (Pt), enabling synergistic chemotherapy and sonodynamic therapy. The CLP@HP-A nanocarriers exhibited specific binding with galectin-3 receptors, facilitating their internalization through receptor-mediated endocytosis for targeted drug delivery. Upon exposure to ultrasound (US) irradiation, Ce6 rapidly generated reactive oxygen species (ROS) to induce significant oxidative stress and trigger apoptosis in tumor cells. Additionally, Pt not only alleviated tumor hypoxia by catalyzing the conversion of H2O2 to oxygen (O2) but also augmented intracellular ROS levels through the production of hydroxyl radicals (•OH), thereby enhancing the efficacy of sonodynamic therapy. Moreover, Len demonstrated a potent cytotoxic effect on thyroid cancer cells through the induction of apoptosis. Transcriptomics analysis findings additionally corroborated that CLP@HP-A effectively triggered cancer cell apoptosis, thereby serving as a crucial mechanism for its cytotoxic effects. In conclusion, the integration of sonodynamic/chemo combination therapy with targeted drug delivery systems offers a novel approach to the management of malignant tumors.

Stabilised pathway and its anti-oxygen/glucose deprived activity about ligustilide, as a pharmacodynamic marker for Angelica sinensis (Oliv) Diles or Ligusticum chuanxiong Hort.

The inherent structural instability and very low bioavailability of ligustilide (Lig) lead to the limited application of the clinical neuroprotection. We developed a stabilised method for Lig, which involved a chemical synthesis between cyclopropylamine and the active phthalides extract included Lig from Angelica sinensis (Oliv) Diles or Ligusticum chuanxiong Hort, which generated correspond phthalide derivatives by nucleophilic additive and substituted reaction. During this process, four phthalide derivatives have been obtained and two compounds (3 and 4) stands out as an unprecedented dimeric phthalide entity. This research has meticulously delineated the stabilised pathway and polymerisation mechanics of Lig or its derivatives, an oxygen/glucose deprived PC12 cells experiment model utilised to screen the anti-stroke activity of this isolated Lig derivatives and the results supported this chemical transformation could achieve the stabilised goal of Lig and improved its anti-oxygen/glucose deprived activity.

Mitochondrial dysfunction in sepsis: mechanisms and therapeutic perspectives.

Sepsis is a severe medical condition characterized by a systemic inflammatory response, often culminating in multiple organ dysfunction and high mortality rates. In recent years, there has been a growing recognition of the pivotal role played by mitochondrial damage in driving the progression of sepsis. Various factors contribute to mitochondrial impairment during sepsis, encompassing mechanisms such as reactive nitrogen/oxygen species generation, mitophagy inhibition, mitochondrial dynamics change, and mitochondrial membrane permeabilization. Damaged mitochondria actively participate in shaping the inflammatory milieu by triggering key signaling pathways, including those mediated by Toll-like receptors, NOD-like receptors, and cyclic GMP-AMP synthase. Consequently, there has been a surge of interest in developing therapeutic strategies targeting mitochondria to mitigate septic pathogenesis. This review aims to delve into the intricate mechanisms underpinning mitochondrial dysfunction during sepsis and its significant impact on immune dysregulation. Moreover, we spotlight promising mitochondria-targeted interventions that have demonstrated therapeutic efficacy in preclinical sepsis models.

Enhanced prediction of atrial fibrillation risk using proteomic markers: a comparative analysis with clinical and polygenic risk scores.

BACKGROUND: Proteomic biomarkers have shown promise in predicting various cardiovascular conditions, but their utility in assessing the risk of atrial fibrillation (AF) remains unclear. This study aimed to develop and validate a protein-based risk score for predicting incident AF and to compare its predictive performance with traditional clinical risk factors and polygenic risk scores in a large cohort from the UK Biobank. METHODS: We analysed data from 36 129 white British individuals without prior AF, assessing 2923 plasma proteins using the Olink Explore 3072 assay. The cohort was divided into a training set (70%) and a test set (30%) to develop and validate a protein risk score for AF. We compared the predictive performance of this score with the HARMS2-AF risk model and a polygenic risk score. RESULTS: Over an average follow-up of 11.8 years, 2450 incident AF cases were identified. A 47-protein risk score was developed, with N-terminal prohormone of brain natriuretic peptide (NT-proBNP) being the most significant predictor. In the test set, the protein risk score (per SD increment, HR 1.94; 95% CI 1.83 to 2.05) and NT-proBNP alone (HR 1.80; 95% CI 1.70 to 1.91) demonstrated superior predictive performance (C-statistic: 0.802 and 0.785, respectively) compared with HARMS2-AF and polygenic risk scores (C-statistic: 0.751 and 0.748, respectively). CONCLUSIONS: A protein-based risk score, particularly incorporating NT-proBNP, offers superior predictive value for AF risk over traditional clinical and polygenic risk scores, highlighting the potential for proteomic data in AF risk stratification.

One step toward precision dosing of caffeine in preterm infants: An external evaluation of published population pharmacokinetic models.

BACKGROUND: Several population pharmacokinetic (PopPK) models of caffeine in preterm infants have been published, but the extrapolation of these models to facilitate model-informed precision dosing (MIPD) in clinical practice is uncertain. This study aimed to comprehensively evaluate their predictive performance using an external, independent dataset. METHODS: Data used for external evaluation were based on an independent cohort of preterm infants. Currently available PopPK models for caffeine in preterm infants were identified and re-established. Prediction- and simulation-based diagnostics were used to assess model predictability. The influence of prior information was assessed using Bayesian forecasting. RESULTS: 120 plasma samples from 76 preterm infants were included in the evaluation dataset. Twelve PopPK models of caffeine in preterm infants were re-established based on our previously published study. Although two models showed superior predictive performance, none of the 12 PopPK models met all the clinical acceptance criteria of these external evaluation items. Besides, the external predictive performances of most models were unsatisfactory in prediction- and simulation-based diagnostics. Nevertheless, the application of Bayesian forecasting significantly improved the predictive performance, even with only one prior observation. CONCLUSIONS: Two models that included the most covariates had the best predictive performance across all external assessments. Inclusion of different covariates, heterogeneity of preterm infant characteristics, and different study designs influenced predictive performance. Thorough evaluation is needed before these PopPK models can be implemented in clinical practice. The implementation of MIPD for caffeine in preterm infants could benefit from the combination of PopPK models and Bayesian forecasting as a helpful tool.

Plasma proteomics for risk prediction of Alzheimer's disease in the general population.

We aimed to develop and validate a protein risk score for predicting Alzheimer's disease (AD) and compare its performance with a validated clinical risk model (Cognitive Health and Dementia Risk Index for AD [CogDrisk-AD]) and apolipoprotein E (APOE) genotypes. The development cohort, consisting of 35,547 participants from England in the UK Biobank, was randomly divided into a 7:3 training-testing ratio. The validation cohort included 4667 participants from Scotland and Wales in the UK Biobank. In the training set, an AD protein risk score was constructed using 31 proteins out of 2911 proteins. In the testing set, the AD protein risk score had a C-index of 0.867 (95% CI, 0.828, 0.906) for AD prediction, followed by CogDrisk-AD risk factors (C-index, 0.856; 95% CI, 0.823, 0.889), and APOE genotypes (C-index, 0.705; 95% CI, 0.660, 0.750). Adding the AD protein risk score to CogDrisk-AD risk factors (C-index increase, 0.050; 95% CI, 0.008, 0.093) significantly improved the predictive performance for AD. However, adding CogDrisk-AD risk factors (C-index increase, 0.040; 95% CI, -0.007, 0.086) or APOE genotypes (C-index increase, 0.000; 95% CI, -0.054, 0.055) to the AD protein risk score did not significantly improve the predictive performance for AD. The top 10 proteins with the highest coefficients in the AD protein risk score contributed most of the predictive power for AD risk. These results were verified in the external validation cohort. EGFR, GFAP, and CHGA were identified as key proteins within the protein network. Our result suggests that the AD protein risk score demonstrated a good predictive performance for AD risk.

First Report of metaplexis yellow mottle-associated virus Infecting Metaplexis japonica (Thunb.) Makino in Shandong, China.

Metaplexis japonica (Thunb.) Makino, commonly known as rough potato, has a wide distribution in China, Japan, Korea, and adjacent Russia. In China, M. japonica is a traditional herbal medicinal plant, which is also cultivated as a vegetable (Shi et al. 2020; Wei et al. 2019). In July 2023, leaves of M. japonica plants growing near a soybean field in Qingdao, Shandong province, exhibited leaf crinkling, mosaic and distorting symptoms of probable virus infection (Supplementary Figure 1). The disease incidence in a 50 m2 area was approximately 40%. To identify the suspected viral etiological agents, symptomatic leaves from 10 M. japonica plants were collected and pooled to perform small RNA deep sequencing (sRNA-Seq). TransZol Up Total RNA Extraction Kit (TransGen Biotech, Beijing, China) was used to extract total RNA. Small RNA library construction and high-throughput sequencing (HTS) were performed on Illumina NovaSeq platform by Genepioneer (Nanjing, China) (Li et al. 2024). A total of 17,384,311 raw reads were obtained. Redundant reads were removed by cutadapt software (version 1.18) to obtain 11,580,876 clean reads with 18 to 26 nucleotide (nt) sizes. The clean reads were assembled using velvet software (version 1.1.07). A total of forty-six small contigs from 42 to 283 nt were identified, with 85 to 100% nucleotide sequence identities, respectively, to metaplexis yellow mottle-associated virus (MeYMaV, genus Caulimovirus, family Caulimoviridae, accession numbers: NC_077108.1). Finally, 1,355,955 reads (11.71% mapped ratio of total reads, cover 56.7% over the MeYMaV genome) were mapped to the genome of MeYMaV by bwa software (version 0.7.17-r1188). To confirm the sRNA-Seq results, PCR was performed with specific primers MeYMaV-N-F/MeYMaV-N-R (5'-TGGTATCAGAGCCTAGTTAA-3'/5'-GGAGTTGGTAATGTATTACC-3') and MeYMaV-C-F/MeYMaV-C-R (5'-AATGGAACGGCTGTTAGTAT3'/TTAATTTCTAGCCCTTGGCTACTTAC). Both the primer pairs were designed using GenBank accession numbers: NC_077108.1 (Yang et al. 2021) to obtain the N and C terminals genome fragments of 10 MeYMaV plants. Two amplicons approximately in 4000-, and 3900-bp sizes were amplified (Supplementary Figure 2), sequenced (tsingke, Beijing, China) and aligned to obtain 7,742-nt complete MeYMaV genome sequence (Accession no. PP892524). BLASTn analysis revealed 90.16% and 92.18% sequence identity, respectively, with the MeYMaV isolate LM-Cau-A (NC_077108.1) based on complete genome and coat protein sequences, respectively. Previously, cucumber mosaic virus and MeYMaV were reported in M. japonica from Jiangsu and Liaoning provinces in China, respectively (Yang et al. 2018; 2021). To our knowledge, this is the first natural infection report of MeYMaV in M. japonica in Shandong, China. The natural occurrence of MeYMaV is not only affects the quality of M. japonica, but also poses a potential threat to surrounding crops. This study enriches information on the disease distribution of MeYMaV and will be helpful for disease management.

Overall survival prediction of gastric cancer using the gene signature of CT-detected extramural venous invasion combined with M2 macrophages infiltration.

BACKGROUND: CT-detected Extramural venous invasion (EMVI) is known as an independent risk factor for distant metastasis in patients with advanced gastric cancer (GC). However, the molecular basis is not clear. In colorectal cancer, M2 macrophages plays a vital role in determining EMVI. This study aimed to investigate the relationship between CT-detected EMVI and the M2 macrophages as well as prognosis predictionusing a radiogenomic approach. METHOD: We utilized EMVI-related genes (from mRNA sequencing of 13 GC samples correlated with EMVI score by spearman analysis, P < 0.01) to overlap the co-expression genes of WGCNA module and M2 macrophages related genes (from mRNA data of 371 GC patients in TCGA database), generating a total of 136 genes. An EMVI-M2-prognosis-related hub gene signature was constructed by COX and least absolute shrinkage and selection operator (LASSO) analysis from a training cohort TCGA database (n = 371) and validated it in a validation cohort from GEO database (n = 357). High- and low-risk groups were divided by hub gene (EGFLAM and GNG11) signature-derived risk scores. We assessed its predictive ability through Kaplan-Meier (K-M) curve and COX analysis. Furthermore, we utilized ESTIMATE to detect tumor mutation burden (TMB) and evaluate sensitivity to immune checkpoint inhibitors (ICIs). Expression of hub genes was tested using western blotting and immunohistochemistry (IHC) analysis. RESULTS: The overall survival (OS) was significantly reduced in the high-risk group (Training/Validation: AUC = 0.701/0.620; P < 0.001/0.003). Furthermore, the risk score was identified as an independent predictor of OS in multivariate COX regression analyses (Training/Validation: HR = 1.909/1.928; 95% CI: 1.225-2.974/1.308-2.844). The low-risk group exhibited significantly higher TMB levels (P = 1.6e- 07) and greater sensitivity to ICIs. Significant higher expression of hub-genes was identified on multiple GC cell lines and original samples. Hub-genes knockdown in gastric cancer cell lines inhibited their proliferation, metastatic and invasive capacity to varying degrees. In vivo experiments indicate that EGFLAM, as one of the hub genes, its high expression can serve as a biomarker for low response to immunotherapy. CONCLUSION: Our study demonstrated EMVI-M2 gene signature could effectively predict the prognosis of GC tissue, reflecting the relationship between EMVI and M2 macrophages.

Effect of controlled release of HGF on extracellular vesicle secretion by urine-derived stem cells.

Introduction: The hepatic growth factor (HGF) stimulates DNA synthesis and cell proliferation and plays a role in tissue protection and regeneration. In this study, we have examined the effect of incubation of HGF with urine-derived stem cells (USCs) on the secretion of small extracellular vesicles (sEV) by the cells. Materials and Methods: HGF in the incubation medium was either a bolus administration or a controlled release of an equivalent amount from microbeads within the size range of 50-200 µm made with ultrapurified low-viscosity high-guluronic acid (UP-LVG) alginate. USCs were incubated with or without HGF for 3 days or 7 days before removal of the incubation media, followed by harvesting sEV by the precipitation method. The protein content of isolated sEV was measured by bicinchoninic acid assay (BCA) for these three groups: control (no HGF beads), bolus HGF, and HGF beads. We also performed nanoparticle tracking analysis (NTA), Western blot assay, and ELISA for the HGF content of samples. Results: We found a significantly higher concentration of proteins in the HGF microbead group (control release group) compared to the bolus group and the control group after 7 days (p < 0.0017). The NTA data aligned with the BCA; they showed a significantly higher concentration of particles within the size range of sEV (<200 nm) in the group treated with HGF beads compared to the two other groups on day 7 (p < 0.0001). Conclusion: We found that administration of HGF to USCs by controlled release of the growth factor significantly enhances the levels of sEV secretion during 7 days of incubation.

A genome-scale deep learning model to predict gene expression changes of genetic perturbations from multiplex biological networks.

Systematic characterization of biological effects to genetic perturbation is essential to the application of molecular biology and biomedicine. However, the experimental exhaustion of genetic perturbations on the genome-wide scale is challenging. Here, we show TranscriptionNet, a deep learning model that integrates multiple biological networks to systematically predict transcriptional profiles to three types of genetic perturbations based on transcriptional profiles induced by genetic perturbations in the L1000 project: RNA interference, clustered regularly interspaced short palindromic repeat, and overexpression. TranscriptionNet performs better than existing approaches in predicting inducible gene expression changes for all three types of genetic perturbations. TranscriptionNet can predict transcriptional profiles for all genes in existing biological networks and increases perturbational gene expression changes for each type of genetic perturbation from a few thousand to 26 945 genes. TranscriptionNet demonstrates strong generalization ability when comparing predicted and true gene expression changes on different external tasks. Overall, TranscriptionNet can systemically predict transcriptional consequences induced by perturbing genes on a genome-wide scale and thus holds promise to systemically detect gene function and enhance drug development and target discovery.

Regular Mobile Phone Use and Incident Cardiovascular Diseases: Mediating Effects of Sleep Patterns, Psychological Distress, and Neuroticism.

BACKGROUND: The relationship between mobile phone use and incident cardiovascular disease (CVD) is uncertain. We aimed to examine the association of regular mobile phone use with incident CVD and explore the mediating effects of sleep and mental health. METHODS: A total of 444,027 individuals from the UK Biobank without a history of CVD were included. Regular mobile phone use was defined as at least 1 call per week. Weekly mobile phone usage time was self-reported as the average time of calls per week over the previous 3 months. The primary outcome was incident CVD. The secondary outcomes included each component of CVD and increased carotid intima-media thickness (CIMT). We applied Cox proportional hazard models to assess the association between mobile phone use and incident CVD, and mediation analyses to investigate the role of sleep patterns, psychologic distress, and neuroticism. RESULTS: In a median follow-up period of 12.3 years, 56,181 individuals developed incident CVD. Compared with nonregular mobile phone users, regular mobile phone users had a significantly higher risk of incident CVD (hazard ratio 1.04, 95% confidence interval 1.02-1.06) and increased CIMT (odds ratio 1.11, 95% CI 1.04-1.18). Among regular mobile phone users, weekly mobile phone usage time was positively associated with the risk of incident CVD, especially in current smokers (P for interaction = 0.001) and diabetic individuals (P for interaction = 0.037). Of the relationship between weekly mobile phone usage time and incident CVD, 5.11% was mediated by sleep patterns, 11.5% by psychological distress, and 2.25% by neuroticism. CONCLUSIONS: Weekly mobile phone usage time was positively associated with incident CVD risk, which was partly explained by poor sleep, psychologic distress, and neuroticism.

Risk factors for low back pain following percutaneous vertebroplasty in patients with osteoporotic vertebral compression fracture.

OBJECTIVE: To investigate the occurrence and risk factors for low back pain post-percutaneous vertebroplasty (PVP) in osteoporotic vertebral compression fractures (OVCF) patients. METHODS: A retrospective analysis was conducted of 148 OVCF patients treated from March 2020 to 2023. The incidence of low back pain post-PVP was recorded, and logistic regression analysis was used to identify associated risk factors. RESULTS: Low back pain occurred in 34 out of 148 patients (22.97%). Logistic regression identified age (>75) (P=0.039), number of fractured vertebrae (≥2) (P=0.004), presence of lumbar spine comorbidity (P=0.019), emotional status (P=0.006), site of fracture (P=0.006), and preoperative fascial injury (P=0.039) as independent risk factors influencing the development of low back pain after PVP in OVCF patients. Receiver operating characteristic (ROC) curve analysis showed that age (>75), number of fractured vertebrae (≥2), lumbar spine comorbidities, and site of fracture had area under the curve (AUC) values of 0.626, 0.614, 0.623, and 0.667, respectively, in predicting low back pain post-PVP. CONCLUSION: Age, number of fractured vertebrae, presence of lumbar spine comorbidities, emotional status, site of fracture, and preoperative fascial injury are significant independent risk factors for the occurrence of low back pain after PVP in patients with OVCF. These findings are crucial for alleviating postoperative low back pain and provide valuable insight for postoperative pain management.

Exosome-mediated renal protection: Halting the progression of fibrosis.

Renal fibrosis is a complex and multifactorial process that involves inflammation, cell proliferation, collagen, and fibronectin deposition in the kidney, ultimately leading to chronic kidney disease and even end-stage renal disease. The main goal of treatment is to slow down or halt the progression of fibrosis and to improve or preserve kidney function. Despite significant progress made in understanding the underlying mechanisms of renal fibrosis, current therapies have limited renal protection as the disease progresses. Exosomes derived from stem cells are a newer area of research for the treatment of renal fibrosis. Exosomes as nano-sized extracellular vesicles carry proteins, lipids, and nucleic acids, which can be taken up by local or distant cells, serving as mediators of intercellular communication and as drug delivery vehicles. Exosomes deliver molecules that reduce inflammation, renal fibrosis and extracellular matrix protein production, and promote tissue regeneration in animal models of kidney disease. Additionally, they have several advantages over stem cells, such as being non-immunogenic, having low risk of tumor formation, and being easier to produce and store. This review describes the use of natural and engineered exosomes containing therapeutic agents capable of mediating anti-inflammatory and anti-fibrotic processes during both acute kidney injury and chronic kidney disease. Exosome-based therapies will be compared with stem cell-based treatments for tissue regeneration, with a focus on renal protection. Finally, future directions and strategies for improving the therapeutic efficacy of exosomes are discussed.

Global burden of benign prostatic hyperplasia, urinary tract infections, urolithiasis, bladder cancer, kidney cancer, and prostate cancer from 1990 to 2021.

BACKGROUND: The burden of common urologic diseases, including benign prostatic hyperplasia (BPH), urinary tract infections (UTI), urolithiasis, bladder cancer, kidney cancer, and prostate cancer, varies both geographically and within specific regions. It is essential to conduct a comprehensive and precise assessment of the global burden of urologic diseases. METHODS: We obtained data on incidence, prevalence, mortality, and disability-adjusted life-years (DALYs) for the aforementioned urologic diseases by age, sex, location, and year from the Global Burden of Disease (GBD) 2021. We analyzed the burden associated with urologic diseases based on socio-demographic index (SDI) and attributable risk factors. The trends in burden over time were assessed using estimated annual percentage changes (EAPC) along with a 95% confidence interval (CI). RESULTS: In 2021, BPH and UTI were the leading causes of age-standardized incidence rate (ASIR) and age-standardized prevalence rate (ASPR), with rates of 5531.88 and 2782.59 per 100,000 persons, respectively. Prostate cancer was the leading cause of both age-standardized mortality rate (ASMR) and age-standardized DALYs rate (ASDR), with rates of 12.63 and 217.83 per 100,000 persons, respectively. From 1990 to 2021, there was an upward trend in ASIR, ASPR, ASMR, and ASDR for UTI, while urolithiasis showed a downward trend. The middle and low-middle SDI quintile levels exhibited higher incidence, prevalence, mortality, and DALYs related to UTI, urolithiasis, and BPH, while the high and high-middle SDI quintile levels showed higher rates for the three cancers. The burden of these six urologic diseases displayed diverse age and sex distribution patterns. In 2021, a high body mass index (BMI) contributed to 20.07% of kidney cancer deaths worldwide, while smoking accounted for 26.48% of bladder cancer deaths and 3.00% of prostate cancer deaths. CONCLUSIONS: The global burden of 6 urologic diseases presents a significant public health challenge. Urgent international collaboration is essential to advance the improvement of urologic disease management, encompassing the development of effective diagnostic screening tools and the implementation of high-quality prevention and treatment strategies.

Bioresponsive Nanoparticles Boost Starvation Therapy and Prevent Premetastatic Niche Formation for Pulmonary Metastasis Treatment.

In the process of tumor metastasis, tumor cells can acquire invasion by excessive uptake of nutrients and energy and interact with the host microenvironment to shape a premetastatic niche (PMN) that facilitates their colonization and progression in the distal sites. Pyruvate is an essential nutrient that engages in both energy metabolism and remodeling of the extracellular matrix (ECM) in the lungs for PMN formation, thus providing a target for tumor metastasis treatment. There is a paucity of strategies focusing on PMN prevention, which is key to metastasis inhibition. Here, we design a bioresponsive nanoparticle (HP/GU) based on a disulfide-cross-linked hyperbranched polyethylenimine (D-PEI) core and a hyaluronic acid (HA) shell with a reactive oxygen species (ROS)-sensitive cross-linker between them to encapsulate glucose oxidase (GOX) and a mitochondrial pyruvate carrier (MPC) inhibitor via electrostatic interaction, which reinforces starvation therapy and reduces PMN formation in the lungs via inhibiting pyruvate metabolism. In tumor cells, GOX and MPC inhibitors can be rapidly released and synergistically reduce the energy supply of tumor cells by consuming glucose and inhibiting pyruvate uptake to decrease tumor cell invasion. MPC inhibitors can also reduce ECM remodeling by blocking cellular pyruvate metabolism to prevent PMN formation. Consequently, HP/GU achieves an efficient inhibition of both primary and metastatic tumors and provides an innovative strategy for the treatment of tumor metastases.

Cross-tissue human fibroblast atlas reveals myofibroblast subtypes with distinct roles in immune modulation.

Fibroblasts, known for their functional diversity, play crucial roles in inflammation and cancer. In this study, we conduct comprehensive single-cell RNA sequencing analyses on fibroblast cells from 517 human samples, spanning 11 tissue types and diverse pathological states. We identify distinct fibroblast subpopulations with universal and tissue-specific characteristics. Pathological conditions lead to significant shifts in fibroblast compositions, including the expansion of immune-modulating fibroblasts during inflammation and tissue-remodeling myofibroblasts in cancer. Within the myofibroblast category, we identify four transcriptionally distinct subpopulations originating from different developmental origins, with LRRC15+ myofibroblasts displaying terminally differentiated features. Both LRRC15+ and MMP1+ myofibroblasts demonstrate pro-tumor potential that contribute to the immune-excluded and immune-suppressive tumor microenvironments (TMEs), whereas PI16+ fibroblasts show potential anti-tumor functions in adjacent non-cancerous regions. Fibroblast-subtype compositions define patient subtypes with distinct clinical outcomes. This study advances our understanding of fibroblast biology and suggests potential therapeutic strategies for targeting specific fibroblast subsets in cancer treatment.

Cell-based therapies reverse the heart failure-altered right ventricular proteome.

Background: Congenital heart defects can lead to right ventricular (RV) pressure-overload and heart failure. Cell-based therapies, including mesenchymal stromal cells (MSCs) and c-kit positive cells (CPCs) have been studied clinically as options to restore heart function in disease states. Many studies have indicated these cells act through paracrine mechanisms to prevent apoptosis, promote cellular function, and regulate gene/protein expression. We aimed to determine the proteomic response of diseased hearts to cell therapy. Methods: We utilized an animal model of RV pressure overload created by banding the pulmonary artery (PAB). Two weeks post-banding, bone marrow-derived mesenchymal stromal cells (MSCs) and 3 populations of CPCs (nCPCs, cCPCs, ES-CPCs) were delivered to the RV free wall. RV function and cellular retention were measured for four weeks post-injection, at which point hearts were extracted and the RV was excised for liquid chromatography and tandem mass spectrometry. Resulting RV proteomes were compared and analyzed using systems biology and bioinformatics. Results: Proteomic profiling identified 1156 total proteins from the RV, of which 5.97% were significantly changed after PAB. This disease-altered proteome was responsive to cellular therapy, with 72% of the PAB-altered proteome being fully or partially reversed by MSC therapy. This was followed by nCPCs (54%), ES-CPCs (52%), and cCPCs (39%). Systems biology and bioinformatics analysis showed MSC, nCPC, or ES-CPC cell therapy is associated with a decrease in predicted adverse cardiac effects. We also observed an effect of cell therapy on the non-altered RV proteome, however, this was associated with minor predicted pathological endpoints. Conclusions: Our data indicate MSCs, ES-CPCs, and nCPCs significantly reverse the PAB-altered proteome towards a pre-disease state. These results indicate cell-based therapies show promise in improving RV function after pressure overload through partial restoration of the disease-altered cardiac proteome.

Malware Identification Method in Industrial Control Systems Based on Opcode2vec and CVAE-GAN.

Industrial Control Systems (ICSs) have faced a significant increase in malware threats since their integration with the Internet. However, existing machine learning-based malware identification methods are not specifically optimized for ICS environments, resulting in suboptimal identification performance. In this work, we propose an innovative method explicitly tailored for ICSs to enhance the performance of malware classifiers within these systems. Our method integrates the opcode2vec method based on preprocessed features with a conditional variational autoencoder-generative adversarial network, enabling classifiers based on Convolutional Neural Networks to identify malware more effectively and with some degree of increased stability and robustness. Extensive experiments validate the efficacy of our method, demonstrating the improved performance of malware classifiers in ICSs. Our method achieved an accuracy of 97.30%, precision of 92.34%, recall of 97.44%, and F1-score of 94.82%, which are the highest reported values in the experiment.