Autophagy flux in bladder cancer: Cell death crosstalk, drug and nanotherapeutics.

Autophagy, a self-digestion mechanism, has emerged as a promising target in the realm of cancer therapy, particularly in bladder cancer (BCa), a urological malignancy characterized by dysregulated biological processes contributing to its progression. This highly conserved catabolic mechanism exhibits aberrant activation in pathological events, prominently featured in human cancers. The nuanced role of autophagy in cancer has been unveiled as a double-edged sword, capable of functioning as both a pro-survival and pro-death mechanism in a context-dependent manner. In BCa, dysregulation of autophagy intertwines with cell death mechanisms, wherein pro-survival autophagy impedes apoptosis and ferroptosis, while pro-death autophagy diminishes tumor cell survival. The impact of autophagy on BCa progression is multifaceted, influencing metastasis rates and engaging with the epithelial-mesenchymal transition (EMT) mechanism. Pharmacological modulation of autophagy emerges as a viable strategy to impede BCa progression and augment cell death. Notably, the introduction of nanoparticles for targeted autophagy regulation holds promise as an innovative approach in BCa suppression. This review underscores the intricate interplay of autophagy with cell death pathways and its therapeutic implications in the nuanced landscape of bladder cancer.

Raman Flow Cytometry and Its Biomedical Applications.

Raman flow cytometry (RFC) uniquely integrates the "label-free" capability of Raman spectroscopy with the "high-throughput" attribute of traditional flow cytometry (FCM), offering exceptional performance in cell characterization and sorting. Unlike conventional FCM, RFC stands out for its elimination of the dependency on fluorescent labels, thereby reducing interference with the natural state of cells. Furthermore, it significantly enhances the detection information, providing a more comprehensive chemical fingerprint of cells. This review thoroughly discusses the fundamental principles and technological advantages of RFC and elaborates on its various applications in the biomedical field, from identifying and characterizing cancer cells for in vivo cancer detection and surveillance to sorting stem cells, paving the way for cell therapy, and identifying metabolic products of microbial cells, enabling the differentiation of microbial subgroups. Moreover, we delve into the current challenges and future directions regarding the improvement in sensitivity and throughput. This holds significant implications for the field of cell analysis, especially for the advancement of metabolomics.

Small extracellular vesicles' enrichment from biological fluids using an acoustic trap.

Small extracellular vesicles (sEVs), a form of extracellular vesicles, are lipid bilayered structures released by all cells. Large-scale studies on sEVs from clinical samples are necessary, but a major obstacle is the lack of rapid, reproducible, efficient, and low-cost methods to enrich sEVs. Acoustic microfluidics have the advantage of being label-free and biocompatible, which have been reported to successfully enrich sEVs. In this paper, we present a highly efficient acoustic microfluidic trap that can offer low and large volume compatible ways of enriching sEVs from biological fluids by flexible structure design. It uses the idea of pre-loading larger seed particles in the acoustic trap to enable sub-micron particle capturing. The microfluidic chip is actuated using a piezoelectric plate transducer attached to a silicon-glass bonding plate with circular cavities. Each cavity works as a resonant unit, excited at the frequency of both the half wave resonance in the main plane and inverted quarter wave resonance in the depth direction, which has the ability to strongly trap seed particles at the center, thereby improving the subsequent nanoparticle capture efficiency. Mean trapping efficiencies of 35.62% and 64.27% were obtained using 60 nm and 100 nm nanobeads, respectively. By the use of this technology, we have successfully enriched sEVs from cell culture conditioned media and blood plasma at a flow rate of 10 µL min-1. The isolated sEV subpopulations are characterized by NTA and TEM, and their protein cargo is determined by WB. This acoustic trapping chip provides a rapid and robust method to enrich sEVs from biofluids with high reproducibility and sufficient quantities. Therefore, it can serve as a new tool for biological and clinical research such as cancer diagnosis and drug delivery.

Outcomes, responses, and prognostic analyses of intrathecal combined treatment for leptomeningeal metastasis from lung adenocarcinoma.

BACKGROUND: Leptomeningeal metastasis (LM) is a severe lung cancer complication, with potentially fatal consequences. The use of intrathecal therapy (IT) combined with systemic therapy has shown promise as a treatment approach for LM. Thus, this study aimed to evaluate the features and responses to IT combined therapy and identify determinants affecting patients with leptomeningeal metastasis resulting from lung adenocarcinoma (LM-LA). METHODS: A retrospective analysis of medical records from our hospital database was performed, covering from April 2018 to August 2022, for 37 patients diagnosed with LM-LA and treated with IT combined therapy. Patients who received IT combined therapy for LM-LA were evaluated for demographic characteristics, treatment efficacy, survival, and variables that impacted them. RESULTS: The median overall survival (mOS) of 37 patients was 16.0 months, and the survival rates at 6 and 12 months were 75.7% and 35.1%, respectively. Among the 21 patients with LM-LA who received IT combined with tyrosine kinase inhibitors (TKIs), the mOS was 17.0 months, which was significantly longer than that of patients treated with IT combined with chemotherapy (7.0 months, P = 0.010) and the best supportive care (6.0 months, P = 0.001). However, no significant survival benefit was observed in patients treated with IT combined with TKIs when compared with those treated with IT combined with PD-1 (5.0 months, P = 0.249). Multivariate analysis indicated that the combination of TKIs was an independent favorable prognostic factor for patients with LM-LA. CONCLUSION: Combination treatment is regarded as an additional option for patients with LM-LA. Compared with other combination therapies in our study, IT combined with TKI therapy provided a better survival outcome for patients with LM-LA.

All-natural 2D nanofluidics as highly-efficient osmotic energy generators.

Two-dimensional nanofluidics based on naturally abundant clay are good candidates for harvesting osmotic energy between the sea and river from the perspective of commercialization and environmental sustainability. However, clay-based nanofluidics outputting long-term considerable osmotic power remains extremely challenging to achieve due to the lack of surface charge and mechanical strength. Here, a two-dimensional all-natural nanofluidic (2D-NNF) is developed as a robust and highly efficient osmotic energy generator based on an interlocking configuration of stacked montmorillonite nanosheets (from natural clay) and their intercalated cellulose nanofibers (from natural wood). The generated nano-confined interlamellar channels with abundant surface and space negative charges facilitate selective and fast hopping transport of cations in the 2D-NNF. This contributes to an osmotic power output of ~8.61 W m-2 by mixing artificial seawater and river water, higher than other reported state-of-the-art 2D nanofluidics. According to detailed life cycle assessments (LCA), the 2D-NNF demonstrates great advantages in resource consumption (1/14), greenhouse gas emissions (1/9), and production costs (1/13) compared with the mainstream 2D nanofluidics, promising good sustainability for large-scale and highly-efficient osmotic power generation.

Flotation mechanism and performance of air/condensate bubbles for removing oil droplets in the presence of acetic acid.

Flotation technology is widely utilized to remove emulsified oil droplets from Produced water. Organic acid adsorption on the oil droplet surface affects bubble attachment, reducing oil removal efficiency. This investigation exploited the principle of similar dissolution to synthesize condensate bubbles (CB). The surface properties of oil droplets and CB and air bubbles (AB) were appraised using FTIR, zeta potential, interfacial tension, and contact angle measurements. The research also investigated the effects of acetic acids (AA) on the adhesion of oil droplets to AB and CB along with the underlying mechanism via the Extended Derjaguin-Landau-Verwey-Overbeek (EDLVO) interaction theory and the Stefan-Reynolds model of liquid film thinning, integrated with adhesion times. Flotation efficiency and kinetic dissimilarities between AB and CB were also examined. The results indicated that CB exhibits superior lipophilic hydrophobicity compared to AB, reduced induction and spreading times upon oil droplet attachment, and maximized oil removal efficiency. Furthermore, CB could mitigate the impact of AA on adhesion. The interaction barriers between CB and oil droplets were minimal, and the thinning rate of the hydration film was quicker than in AB. The conventional first-order model proved effective in fitting the AB flotation, whereas a delay constant was applied to the model of the CB flotation rate.

Magnesium Ions Promote the Induction of Immunosuppressive Bone Microenvironment and Bone Repair through HIF-1α-TGF-ß Axis in Dendritic Cells.

The effect of immunoinflammation on bone repair during the recovery process of bone defects needs to be further explored. It is reported that Mg2+ can promote bone repair with immunoregulatory effect, but the underlying mechanism on adaptive immunity is still unclear. Here, by using chitosan and hyaluronic acid-coated Mg2+ (CSHA-Mg) in bone-deficient mice, it is shown that Mg2+ can inhibit the activation of CD4+ T cells and increase regulatory T cell formation by inducing immunosuppressive dendritic cells (imDCs). Mechanistically, Mg2+ initiates the activation of the MAPK signaling pathway through TRPM7 channels on DCs. This process subsequently induces the downstream HIF-1α expression, a transcription factor that amplifies TGF-ß production and inhibits the effective T cell function. In vivo, knock-out of HIF-1α in DCs or using a HIF-1α inhibitor PX-478 reverses inhibition of bone inflammation and repair promotion upon Mg2+-treatment. Moreover, roxadustat, which stabilizes HIF-1α protein expression, can significantly promote immunosuppression and bone repair in synergism with CSHA-Mg. Thus, the findings identify a key mechanism for DCs and its HIF-1α-TGF-ß axis in the induction of immunosuppressive bone microenvironment, providing potential targets for bone regeneration.

Effects of eutrophication on the horizontal transfer of antibiotic resistance genes in microalgal-bacterial symbiotic systems.

Overloading of nutrients such as nitrogen causes eutrophication of freshwater bodies. The spread of antibiotic resistance genes (ARGs) poses a threat to ecosystems. However, studies on the enrichment and spread of ARGs from increased nitrogen loading in algal-bacterial symbiotic systems are limited. In this study, the transfer of extracellular kanamycin resistance (KR) genes from large (RP4) small (pEASY-T1) plasmids into the intracellular and extracellular DNA (iDNA, eDNA) of the inter-algal environment of Chlorella pyrenoidosa was investigated, along with the community structure of free-living (FL) and particle-attached (PA) bacteria under different nitrogen source concentrations (0-2.5 g/L KNO3). The results showed that KR gene abundance in the eDNA adsorbed on solid particles (D-eDNA) increased initially and then decreased with increasing nitrogen concentration, while the opposite was true for the rest of the free eDNA (E-eDNA). Medium nitrogen concentrations promoted the transfer of extracellular KR genes into the iDNA attached to algal microorganisms (A-iDNA), eDNA attached to algae (B-eDNA), and the iDNA of free microorganisms (C-iDNA); high nitrogen contributed to the transfer of KR genes into C-iDNA. The highest percentage of KR genes was found in B-eDNA with RP4 plasmid treatment (66.2%) and in C-iDNA with pEASY-T1 plasmid treatment (86.88%). In addition, dissolved oxygen (DO) significantly affected the bacterial PA and FL community compositions. Nephelometric turbidity units (NTU) reflected the abundance of ARGs in algae. Proteobacteria, Cyanobacteria, Bacteroidota, and Actinobacteriota were the main potential hosts of ARGs. These findings provide new insights into the distribution and dispersal of ARGs in the phytoplankton inter-algal environment.

An anti-TNF-glucocorticoid receptor modulator antibody-drug conjugate is efficacious against immune-mediated inflammatory diseases.

Glucocorticoids (GCs) are efficacious drugs used for treating many inflammatory diseases, but the dose and duration of administration are limited because of severe side effects. We therefore sought to identify an approach to selectively target GCs to inflamed tissue. Previous work identified that anti-tumor necrosis factor (TNF) antibodies that bind to transmembrane TNF undergo internalization; therefore, an anti-TNF antibody-drug conjugate (ADC) would be mechanistically similar, where lysosomal catabolism could release a GC receptor modulator (GRM) payload to dampen immune cell activity. Consequently, we have generated an anti-TNF-GRM ADC with the aim of inhibiting pro-inflammatory cytokine production from stimulated human immune cells. In an acute mouse model of contact hypersensitivity, a murine surrogate anti-TNF-GRM ADC inhibited inflammatory responses with minimal effect on systemic GC biomarkers. In addition, in a mouse model of collagen-induced arthritis, single-dose administration of the ADC, delivered at disease onset, was able to completely inhibit arthritis for greater than 30 days, whereas an anti-TNF monoclonal antibody only partially inhibited disease. ADC treatment at the peak of disease was also able to attenuate the arthritic phenotype. Clinical data for a human anti-TNF-GRM ADC (ABBV-3373) from a single ascending dose phase 1 study in healthy volunteers demonstrated antibody-like pharmacokinetic profiles and a lack of impact on serum cortisol concentrations at predicted therapeutic doses. These data suggest that an anti-TNF-GRM ADC may provide improved efficacy beyond anti-TNF alone in immune mediated diseases while minimizing systemic side effects associated with standard GC treatment.

Integrated multiomic analysis reveals disulfidptosis subtypes in glioblastoma: implications for immunotherapy, targeted therapy, and chemotherapy.

Introduction: Glioblastoma (GBM) presents significant challenges due to its malignancy and limited treatment options. Precision treatment requires subtyping patients based on prognosis. Disulfidptosis, a novel cell death mechanism, is linked to aberrant glucose metabolism and disulfide stress, particularly in tumors expressing high levels of SLC7A11. The exploration of disulfidptosis may provide a new perspective for precise diagnosis and treatment of glioblastoma. Methods: Transcriptome sequencing was conducted on samples from GBM patients treated at Tiantan Hospital (January 2022 - December 2023). Data from CGGA and TCGA databases were collected. Consensus clustering based on disulfidptosis features categorized GBM patients into two subtypes (DRGclusters). Tumor immune microenvironment, response to immunotherapy, and drug sensitivity were analyzed. An 8-gene disulfidptosis-based subtype predictor was developed using LASSO machine learning algorithm and validated on CGGA dataset. Results: Patients in DRGcluster A exhibited improved overall survival (OS) compared to DRGcluster B. DRGcluster subtypes showed differences in tumor immune microenvironment and response to immunotherapy. The predictor effectively stratified patients into high and low-risk groups. Significant differences in IC50 values for chemotherapy and targeted therapy were observed between risk groups. Discussion: Disulfidptosis-based classification offers promise as a prognostic predictor for GBM. It provides insights into tumor immune microenvironment and response to therapy. The predictor aids in patient stratification and personalized treatment selection, potentially improving outcomes for GBM patients.

High-dimensional generalized median adaptive lasso with application to omics data.

Recently, there has been a growing interest in variable selection for causal inference within the context of high-dimensional data. However, when the outcome exhibits a skewed distribution, ensuring the accuracy of variable selection and causal effect estimation might be challenging. Here, we introduce the generalized median adaptive lasso (GMAL) for covariate selection to achieve an accurate estimation of causal effect even when the outcome follows skewed distributions. A distinctive feature of our proposed method is that we utilize a linear median regression model for constructing penalty weights, thereby maintaining the accuracy of variable selection and causal effect estimation even when the outcome presents extremely skewed distributions. Simulation results showed that our proposed method performs comparably to existing methods in variable selection when the outcome follows a symmetric distribution. Besides, the proposed method exhibited obvious superiority over the existing methods when the outcome follows a skewed distribution. Meanwhile, our proposed method consistently outperformed the existing methods in causal estimation, as indicated by smaller root-mean-square error. We also utilized the GMAL method on a deoxyribonucleic acid methylation dataset from the Alzheimer's disease (AD) neuroimaging initiative database to investigate the association between cerebrospinal fluid tau protein levels and the severity of AD.

Iridium nanoparticles supported on polyaniline nanotubes for peroxidase mimicking towards total antioxidant capacity assay of fruits and vegetables.

In this study, a straightforward approach is presented for the first time to anchor Ir nanoparticles on the surface of uniform polyaniline (PANi) nanotubes (NTs), which can be used as an efficient peroxidase (POD)-like catalyst. The morphology and chemical structure of the PANi-Ir nanocomposite are characterized by scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), X-ray diffractometer (XRD), Raman and X-ray photoelectron spectroscopy (XPS) measurements. Owing to the strong interaction between Ir nanoparticles and PANi, a remarkable catalytic enhancement is achieved compared to the bare Ir black catalyst and individual PANi NTs, dominating withan electron transfer mechanism. Furthermore, an efficient colorimetric sensor for ascorbic acid (AA) is developed with a low detection limit of 1.0 µM (S/N = 3), and a total antioxidant capacity (TAC) sensing platform is also constructed for the rigorous detection and analysis of fruits and vegetables.

Epidemiology of Schmorl's Node in the Thoracic Spine: A Subtype Analysis.

STUDY DESIGN: Retrospective observational study. OBJECTIVE: To describe the epidemiology of Schmorl's nodes (SN) of primarily developmental cause (SNd) and SN of primarily acquired cause (SNa) separately in the thoracic spine in subjects aged 35-90 years old. SUMMARY OF BACKGROUND DATA: The epidemiology of SN and its relationship with age and gender remain controversial. Based on a pathophysiological hypothesis and the different morphological characteristics, two subtypes of SN may exist and should be considered separately. PATIENTS AND METHODS: Chest CT scans of subjects who came to our institution for health check aged 35-90 years old were retrospectively reviewed. Presence or absence of SN was recorded for each thoracic vertebra. The SNs were further classified into SNd and SNa. The prevalence, location and relationship with age, gender and bone mineral density (BMD) were evaluated separately for the two subtypes. RESULTS: Of the 848 subjects (407 female, mean age, 53±12.2 y) included, 15.7% had SNs. Of the 303 SNs, 49.2% were SNd and 48.5% were SNa. Aging increased the prevalence of SNa while it was not related to the prevalence of SNd. Males had significantly more SNd than females (11.3% vs 4.7%, P<0.001), while the prevalence of SNa was not different between the two genders (10.2% vs 9.1%, P=0.666). A similar distribution of SNd and SNa among thoracic vertebral levels was appreciated, with T9 most frequently involved. Subjects with SNa had lower lumbar BMD than controls (P=0.006), while no significant difference in BMD was found between subjects with SNd and controls (P=0.166). CONCLUSIONS: The clinical characteristics of SN differ based on the developmental and acquired subtype, including the relationship with age, gender and BMD. The subtypes may be considered as distinct clinical entities as a result.

Machine learning versus multivariate logistic regression for predicting severe COVID-19 in hospitalized children with Omicron variant infection.

With the emergence of the Omicron variant, the number of pediatric Coronavirus Disease 2019 (COVID-19) cases requiring hospitalization and developing severe or critical illness has significantly increased. Machine learning and multivariate logistic regression analysis were used to predict risk factors and develop prognostic models for severe COVID-19 in hospitalized children with the Omicron variant in this study. Of the 544 hospitalized children including 243 and 301 in the mild and severe groups, respectively. Fever (92.3%) was the most common symptom, followed by cough (79.4%), convulsions (36.8%), and vomiting (23.2%). The multivariate logistic regression analysis showed that age (1-3 years old, odds ratio (OR): 3.193, 95% confidence interval (CI): 1.778-5.733], comorbidity (OR: 1.993, 95% CI:1.154-3.443), cough (OR: 0.409, 95% CI:0.236-0.709), and baseline neutrophil-to-lymphocyte ratio (OR: 1.108, 95% CI: 1.023-1.200), lactate dehydrogenase (OR: 1.993, 95% CI: 1.154-3.443), blood urea nitrogen (OR: 1.002, 95% CI: 1.000-1.003) and total bilirubin (OR: 1.178, 95% CI: 1.005-3.381) were independent risk factors for severe COVID-19. The area under the curve (AUC) of the prediction models constructed by multivariate logistic regression analysis and machine learning (RandomForest + TomekLinks) were 0.7770 and 0.8590, respectively. The top 10 most important variables of random forest variables were selected to build a prediction model, with an AUC of 0.8210. Compared with multivariate logistic regression, machine learning models could more accurately predict severe COVID-19 in children with Omicron variant infection.

Screening of novel biomarkers for acute kidney transplant rejection using DIA-MS based proteomics.

BACKGROUND: Kidney transplantation is the preferred treatment for patients with end-stage renal disease. However, acute rejection poses a threat to the graft long-term survival. The aim of this study was to identify novel biomarkers to detect acute kidney transplant rejection. METHODS: The serum proteomic profiling of kidney transplant patients with T cell-mediated acute rejection (TCMR) and stable allograft function (STA) was analyzed using data-independent acquisition mass spectrometry (DIA-MS). The differentially expressed proteins (DEPs) of interest were further verified by enzyme-linked immunosorbent assay (ELISA). RESULTS: A total of 131 DEPs were identified between STA and TCMR patients, 114 DEPs were identified between mild and severe TCMR patients. The verification results showed that remarkable higher concentrations of serum amyloid A protein 1 (SAA1) and insulin like growth factor binding protein 2 (IGFBP2), and lower fetuin-A (AHSG) concentration were found in TCMR patients when compared with STA patients. We also found higher SAA1 concentration in severe TCMR group when compared with mild TCMR group. The receiver operating characteristics (ROC) analysis further confirmed that combination of SAA1, AHSG, and IGFBP2 had excellent performance in the acute rejection diagnosis. CONCLUSIONS: Our data demonstrated that serum SAA1, AHSG, and IGFBP2 could be effective biomarkers for diagnosing acute rejection after kidney transplantation. DIA-MS has great potential in biomarker screening of kidney transplantation.

Effect of black wolfberry anthocyanin and maltitol on the gelation and microstructural properties of curdlan/gellan gum hybrid gels.

BACKGROUND: Laboratory scale experiments have shown that curdlan and gellan gum gelled together as curdlan/gellan gum (CG) hybrid gels showed better gel properties than the individual curdlan and gellan gum. In this study, CG and black wolfberry anthocyanin (BWA), CG and maltitol (ML) hybrid gels were constructed using CG hybrid gel as matrix. The effects of BWA or ML on the gel properties and microstructure of CG hybrid gels were investigated and a confectionery gel was developed. RESULTS: The presence of BWA increased the storage modulus (G') value of CG at 0.1 Hz, whereas ML had little effect on the G' value of CG. The addition of BWA (5 g L-1 ) and ML (0.3 mol L-1 ) increased the melting and gelling temperatures of CG hybrid gels to 42.4 °C and 34.1 °C and 44.2 °C and 33.2 °C, respectively. Meanwhile, the relaxation time T22 in CG-ML and CG-BWA hybrid gels was reduced to 91.96 and 410.27 ms, indicating the strong binding between BWA and CG, ML and CG. The hydrogen bond interaction between BWA or ML and CG was confirmed by the shift in the hydroxyl stretching vibration peak. Moreover, the microstructures of CG-ML and CG-BWA hybrid gels were denser than that of CG. In addition, confectionery gel containing CG-BWA-ML has good chewing properties. CONCLUSION: These results indicated that the incorporation of BWA or ML could improve the structure of CG hybrid gels and assign a sustainability potential for the development of confectionery gels based on CG complex. © 2024 Society of Chemical Industry.

Sibling Death in Childhood and Early Adulthood and Risk of Early-Onset Cardiovascular Disease.

Importance: Sibling death is a highly traumatic event, but empirical evidence on the association of sibling death in childhood and early adulthood with subsequent risk of incident cardiovascular disease (CVD) remains limited. Objective: To evaluate the association between sibling death in the early decades of life and subsequent risk of incident early-onset CVD. Design, Setting, and Participants: This population-based cohort study included 2 098 659 individuals born in Denmark from 1978 to 2018. Follow-up started at age 1 year or the date of the first sibling's birth, whichever occurred later, and it ended at the first diagnosis of CVD, the date of death, emigration, or December 31, 2018, whichever came first. Data analyses were conducted from November 1, 2021, through January 10, 2022. Exposures: The death of a sibling. Main Outcomes and Measures: The outcome was early-onset CVD. Cox models were used to estimate hazard ratios (HRs) with 95% CIs. Results: This study included 2 098 659 individuals (1 076 669 [51.30%] male; median [IQR] age at death of sibling, 11.48 [4.68-21.32] years). During the median (IQR) follow-up of 17.52 (8.85-26.05) years, 1286 and 76 862 individuals in the bereaved and nonbereaved groups, respectively, were diagnosed with CVD. Sibling death in childhood and early adulthood was associated with a 17% increased risk of overall CVD (HR, 1.17; 95% CI, 1.10-1.23; cumulative incidence in bereaved individuals, 1.96% [1.61%-2.34%]; cumulative incidence in nonbereaved individuals at age 41 years, 1.35% [1.34%-1.37%]; cumulative incidence difference: 0.61% [95% CI, 0.24%-0.98%]). Increased risks were also observed for most type-specific CVDs, in particular for myocardial infarction (HR, 1.66; 95% CI, 1.12-2.46), ischemic heart disease (HR, 1.52; 95% CI, 1.22-1.90), and heart failure (HR, 1.50; 95% CI, 1.00-2.26). The association was observed whether the sibling died due to CVD (HR, 2.54; 95% CI, 2.04-3.17) or non-CVD (HR, 1.13; 95% CI, 1.06-1.19) causes. The increased risk of CVD was more pronounced for individuals who lost a twin or younger sibling (HR, 1.25; 95% CI, 1.15-1.36) than an elder sibling (HR, 1.11; 95% CI, 1.03-1.20). Conclusions and Relevance: In this cohort study of the Danish population, sibling death in childhood and early adulthood was associated with increased risks of overall and most type-specific early-onset CVDs, with the strength of associations varying by cause of death and age difference between sibling pairs. The findings highlight the need for extra attention and support to the bereaved siblings to reduce CVD risk later in life.

Effects of cognitive behavioral and psychological intervention on social adaptation, psychological resilience and level of hope in patients with nasopharyngeal carcinoma in radiotherapy.

Objective: To evaluate the effects of cognitive behavioral and psychological intervention(CBPI) on social adaptation, psychological resilience, and the level of hope in patients with nasopharyngeal carcinoma(NPC) in radiotherapy. Methods: This is application research. Eighty patients undergoing radiotherapy for NPC at Affiliated Hospital of Hebei University from November 20, 2020 to November 15, 2022 were randomized into control and study groups at a 1:1 ratio. While the control group was provided with standard specialized nursing care, the study group was offered CBPI in addition to the exact nursing care. Differences in quality of life, psychological resilience, level of hope, emotional state, and patient satisfaction between the groups were compared and analyzed before and after treatment. Results: After an intervention, significantly improved physical, mental, and social functions and material living conditions were observed in the study group compared with the control group (all p< 0.05). Although both groups scored higher on the selected psychological resilience scale following the intervention, the study group showed better results as compared to control group in adaptability, tenacity, control, and goal orientation (all p< 0.05). While both groups had elevated scores of temporality and future, interconnectedness, and positive readiness and expectancy at the end of the intervention, the improvements were more pronounced in the study group (all p< 0.05). Conclusion: CBPI supports radiotherapy for NPC by improving patients' quality of life, confidence in treatment, the hope of recovery, psychological resilience, anxiety, depression, and patient satisfaction. Therefore, this treatment strategy is worthy of wide application in clinical settings.

Resveratrol Enhances Anticancer Effects of Silybin on HepG2 Cells and H22 Tumor-bearing Mice via Inducing G2/M Phase Arrest and Increasing Bax/Bcl-2 Ratio.

BACKGROUND: Silybin, a major flavonoid extracted from the seeds of milk thistle, has a strong hepatoprotective but weak anti-hepatoma activity. Screening another natural ingredient and combining it with silybin is expected to improve the anti-hepatoma efficacy of silybin. OBJECTIVE: The objective of this study was to investigate the synergistic anti-hepatoma effect of resveratrol and silybin on HepG2 cells and H22 tumor-bearing mice in hepatocellular carcinoma (HCC) in vitro and in vivo, respectively. METHODS: Cell viability, scratch wound, clone formation, cell apoptosis, cell cycle, and western blot analysis of HepG2 cells were used to investigate the synergistic effects in vitro of the combination resveratrol with silybin. Growth rates, tumor weights, organ indexes, and histological pathological examination in H22 tumor-bearing mice were used to investigate the synergistic effects in vivo. RESULTS: The combination of resveratrol (50 µg/mL) and silybin (100 µg/mL) significantly suppressed cell viability, whose combination index (CI) was 1.63 (>1.15), indicating the best synergism. The combination exhibited the synergistic effect in blocking the migration and proliferative capacity of HepG2 cells in the measurement in vitro. In particular, resveratrol enhanced the upregulation of Bcl-2 expression and the downregulation of Bax expression with a concurrent increase in the Bax/Bcl-2 ratio. The combination of resveratrol (50 mg/kg) and silybin (100 mg/kg) reduced the tumor weight, inhibited the growth rate, increased the organ indexes, and destroyed the tumor tissue morphology in H22 tumor-bearing mice. CONCLUSION: Resveratrol was found to exhibit synergistic anti-cancer effects with silybin on HepG2 cells and H22 tumor-bearing mice.

Rational design of bimetal phosphide embedded in carbon nanofibers for boosting oxygen evolution.

The development of non-precious metal electrocatalysts for oxygen evolution reaction (OER) is crucial for generating large-scale hydrogen through water electrolysis. In this work, bimetal phosphides embedded in electrospun carbon nanofibers (P-FeNi/CNFs) were fabricated through a reliable electrospinning-carbonization-phosphidation strategy. The incorporation of P-FeNi nanoparticles within CNFs prevented them from forming aggregation and further improved their electron transfer property. The bimetal phosphides helped to weaken the adsorption of O intermediate, promoting the OER activity, which was confirmed by the theoretical results. The as-prepared optimized P-Fe1Ni2/CNFs catalyst exhibited very high OER electrocatalytic performance, which required very low overpotentials of just 239 and 303 mV to reach 10 and 1000 mA cm-2, respectively. It is superior to the commercial RuO2 and many other related OER electrocatalysts reported so far. In addition, the constructed alkaline electrolyzer based on the P-Fe1Ni2/CNFs catalyst and Pt/C delivered a cell voltage of 1.52 V at 10 mA cm-2, surpassing the commercial RuO2||Pt/C (1.61 V) electrolyzer. It also offered excellent alkaline OER performance in simulated seawater electrolyte. This demonstrated its potential for practical applications across a broad range of environmental conditions. Our work provides new ideas for the ration design of highly efficient non-precious metal-based OER catalysts for water electrolysis.