Construction of a novel model based on PVT1-MYC duet-related genes for predicting survival and characterization of the tumor microenvironment in pancreatic cancer.

Pancreatic cancer is an extremely malignant tumor. PVT1 and MYC signaling has been considered as a therapeutic target recently. Nonetheless, the prognostic values and critical regulatory networks of PVT1-MYC duet in pancreatic cancer remain unclear. Firstly, we identified PVT1-MYC duet-related genes using public databases. Then we analyzed our Hi-C and ChIP-seq data to confirm PVT1-MYC duet. We performed LASSO regression and multivariate Cox regression analysis to build a prognostic model whose effectiveness and robustness were validated by Cox regression, ROC analysis, calibration curve, and nomogram. Besides, we conducted functional enrichment analyses, mutation profiles analyses and the immune features analyses to compare low- and high-risk group. Functional enrichment analyses revealed that several terms associated with cancer progression were enriched in the high-risk group. Mutation profile analysis showed that high-risk group had higher tumor mutation burden, and immune analysis demonstrated high-risk group had more immunosuppressive tumor microenvironment. Finally, we detected PVT1 expression in pancreatic cancer and paracancer tissues from the PUMCH cohort, which showed that PVT1 was significantly upregulated in pancreatic cancer and associated with invasion, metastasis, and poor prognosis. We further performed transwell and proliferation assays and found that PVT1, CDC6, and COL17A1 could promote migration or proliferation of PDAC cells. This study constructed a prognostic model based on three PVT1-MYC duet-related genes, which had a significant potential in predicting the prognosis and tumor microenvironment of pancreatic cancer. These results suggested that targeting PVT1-MYC duet or its regulatory processes could be a therapeutic option with great interests.

MrgprA3 neurons drive cutaneous immunity against helminths through selective control of myeloid-derived IL-33.

Skin uses interdependent cellular networks for barrier integrity and host immunity, but most underlying mechanisms remain obscure. Herein, we demonstrate that the human parasitic helminth Schistosoma mansoni inhibited pruritus evoked by itch-sensing afferents bearing the Mas-related G-protein-coupled receptor A3 (MrgprA3) in mice. MrgprA3 neurons controlled interleukin (IL)-17+ γδ T cell expansion, epidermal hyperplasia and host resistance against S. mansoni through shaping cytokine expression in cutaneous antigen-presenting cells. MrgprA3 neuron activation downregulated IL-33 but induced IL-1ß and tumor necrosis factor in macrophages and type 2 conventional dendritic cells partially through the neuropeptide calcitonin gene-related peptide. Macrophages exposed to MrgprA3-derived secretions or bearing cell-intrinsic IL-33 deletion showed increased chromatin accessibility at multiple inflammatory cytokine loci, promoting IL-17/IL-23-dependent changes to the epidermis and anti-helminth resistance. This study reveals a previously unrecognized intercellular communication mechanism wherein itch-inducing MrgprA3 neurons initiate host immunity against skin-invasive parasites by directing cytokine expression patterns in myeloid antigen-presenting cell subsets.

Integrating spatial transcriptomics and single-nucleus RNA-seq revealed the specific inhibitory effects of TGF-ß on intramuscular fat deposition.

Intramuscular fat (IMF) is a complex adipose tissue within skeletal muscle, appearing specially tissue heterogeneous, and the factors influencing its formation remain unclear. In conditions such as diabetes, aging, and muscle wasting, IMF was deposited in abnormal locations in skeletal muscle, damaged the normal physiological functions of skeletal muscle. Here, we used Longissimus dorsi muscles from pigs with different IMF contents as samples and adopted a method combining spatial transcriptome (ST) and single-nucleus RNA-seq to identify the spatial heterogeneity of IMF. ST revealed that genes involved in TGF-ß signaling pathways were specifically highly enriched in IMF. In lean pigs, IMF autocrine produces more TGF-ß2, while in obese pigs, IMF received more endothelial-derived TGF-ß1. In vitro experiments have proven that porcine endothelial cells in a simulated high-fat environment released more TGF-ß1 than TGF-ß2. Moreover, under obesity mice, the addition of TGF-ß after muscle injury abolished IMF production and slowed muscle repair, whereas TGF-ß inhibition accelerated muscle repair. Our findings demonstrate that the TGF-ß pathway specifically regulates these processes, suggesting it as a potential therapeutic target for managing muscle atrophy in obese patients and enhancing muscle repair while reducing IMF deposition.

Integrated analysis of microbiome and metabolome reveals signatures in PDAC tumorigenesis and prognosis.

Pancreatic cancer, predominantly pancreatic ductal adenocarcinoma (PDAC), is one of the most malignant tumors of the digestive system. Emerging evidence suggests the involvement of the microbiome and metabolic substances in the development of PDAC, yet the results remain contradictory. This study aims to identify the alterations and relationships in intratumoral microbiome and metabolites in PDAC. We collected matched tumor and normal adjacent tissue (NAT) samples from 105 PDAC patients and performed a 6-year follow-up. 2bRAD-M sequencing, untargeted liquid chromatography-tandem mass spectrometry, and untargeted gas chromatography-mass spectrometry were performed. Compared with NATs, microbial α-diversity decreased in PDAC tumors. The relative abundance of Staphylococcus aureus, Cutibacterium acnes, and Cutibacterium granulosum was higher in PDAC tumor after adjusting for confounding factors body mass index and M stage, and the presence of Ralstonia pickettii_B was found associated with a worse overall survival. Metabolomic analysis revealed distinctive differences in composition between PDAC and NAT, with 553 discriminative metabolites identified. Differential metabolites were revealed to originate from the microbiota and showed significant interactions with shifted bacterial species through KO (KEGG Orthology) genes. These findings suggest that the PDAC microenvironment harbors unique microbial-derived enzymatic reactions, potentially influencing the occurrence and development of PDAC by modulating the levels of glycerol-3-phosphate, succinate, carbonate, and beta-alanine. IMPORTANCE: We conducted a large sample-size pancreatic adenocarcinoma microbiome study using a novel microbiome sequencing method and two metabolomic assays. Two significant outcomes of our analysis are: (i) commensal opportunistic pathogens Staphylococcus aureus, Cutibacterium acnes, and Cutibacterium granulosum were enriched in pancreatic ductal adenocarcinoma (PDAC) tumors compared with normal adjacent tissues, and (ii) worse overall survival was found related to the presence of Ralstonia pickettii_B. Microbial species affect the tumorigenesis, metastasis, and prognosis of PDAC via unique microbe-enzyme-metabolite interaction. Thus, our study highlights the need for further investigation of the potential associations between pancreatic microbiota-derived omics signatures, which may drive the clinical transformation of microbiome-derived strategies toward therapy-targeted bacteria.

Novel Insights into Causal Effects of Serum Lipids and Apolipoproteins on Cardiovascular Morpho-Functional Phenotypes.

Previous observational studies have explored the association between serum lipids, apolipoproteins, and adverse ventricular/aortic structure and function. However, whether a causal link exists is uncertain. This study employed a two-sample Mendelian randomization (MR), colocalization, reverse, and multivariable MR (MVMR) approach to examine the causal associations among five serum lipids, two apolipoproteins, and 32 cardiac magnetic resonance (CMR) traits. Utilizing single-nucleotide polymorphisms (SNPs) linked to serum lipids and apolipoproteins as instrumental variables. CMR traits from seven independent genome-wide association studies served as preclinical endophenotypes, offering insights into aortic and cardiac structure/function. The primary analysis utilized a random-effects inverse variance method (IVW), followed by sensitivity and validation analyses. In the primary IVW MR analyses, genetically predicted low-density lipoprotein cholesterol (LDL-C) levels were positively correlated with increased descending aorta strain (DAo strain) (ß = 0.098; P = 2.69E-07) and ascending aorta strain (AAo strain) (ß = 0.079; P = 5.19E-05). Genetically predicted high-density lipoprotein cholesterol (HDL-C) levels were positively correlated with left ventricular radial peak diastolic strain rate (LV-PDSRll) (ß = 0.176; P = 2.89E-05) and the left ventricular longitudinal peak diastolic strain rate (LV-PDSRrr) (ß = 0.059; P = 2.44E-06), and negatively correlated with left ventricular regional wall thickness (LVRWT). While apolipoprotein B (ApoB) levels were positively correlated with AAo strain (ß = 0.076; P = 1.16E-05), DAo strain (ß = 0.065; P = 2.77E-05). A shared causal variant was identified to demonstrate the associations of ApoB with AAo strain and DAo strain using colocalization analysis. Sensitivity analyses confirmed the robustness of these associations. Targeting lipid and apolipoprotein levels through interventions may provide novel strategies for the primary prevention of CVDs.

Work stress and professional quality of life among Chinese nurses during the COVID-19 pandemic: the chain mediating role of self-compassion and benefit finding.

BACKGROUND: Since the outbreak of the Coronavirus Disease 2019 (COVID-19), front-line nurses have faced not only daily work stress but also a high risk of infection and excessive workload, leading to unsatisfactory professional quality of life (ProQOL). This study aimed to explore whether self-compassion (SC) and benefit finding (BF) play a chain mediating role between work stress and ProQOL among Chinese nurses during the COVID-19 pandemic. METHODS: From March to April 2022, a sample of 13,936 Chinese nurses was recruited through snowball sampling. Demographic information, work stress, SC, BF, and ProQOL were assessed. The SPSS 25.0 software and Amos 24.0 software were used for statistical analysis. The bootstrap method was employed to construct and examine the chain mediating structural equation model. RESULTS: The ProQOL level of Chinese nurses during the COVID-19 pandemic was moderate. The overall fit indices for the compassion satisfaction (CS), burnout (BO), and secondary traumatic stress (STS) models were satisfactory (χ²/df = 2.486, 3.256, 2.553, RMSEA = 0.011, 0.014, 0.011, the GFI, AGFI, NFI, and CFI values were all above 0.90). Work stress had direct effects on CS, BO, and STS (ß=-0.171, 0.334, 0.222, P < 0.001), and also indirectly affected these outcomes through SC (point estimate=-0.010, 0.021, 0.024, P < 0.001), BF (point estimate=-0.033, 0.015, - 0.011, P < 0.001), as well as their chain mediating effect (point estimate=-0.015, 0.006, - 0.005, P < 0.001). CONCLUSIONS: Our study suggests that SC and BF partially mediated the association between work stress and ProQOL in Chinese nurses during the COVID-19 pandemic. Training on SC and BF may be crucial components of interventions aimed at improving ProQOL.

Research progress on physiological processes-based tree-ring width models of Vaganov-Shashkin (VS)and VS-Lite.

The Vaganov-Shashkin (VS) and VS-Lite models are the most widely used physiological processes-based models of tree-ring width. Both models can reveal the intrinsic response mechanism between tree-ring width and external climate factors. The VS model is commonly applied in climate reconstruction, wood phenology prediction, and the simulation of cambial activity, while the VS-Lite model is primarily applied in forecasting growth trends of forest. We collected papers related to the VS and VS-Lite models published between 2005 and 2023, and reviewed the fundamental principles, parameter settings, and historical development of both models, as well as the their applications in research areas of dendroclimatology, xylem phenology, and forest ecology. Then, we summarized the current issues with the models and proposed future research directions. To increase confidence in the simulation results, it is essential to optimize the parameter adjustment method of the models, consider the impact of multiple environmental factors on the physiological processes of trees, and strengthen the comparative study of the VS and VS-Lite model with other vegetation ecological models.

Comprehensive multi-omics profiling identifies novel molecular subtypes of pancreatic ductal adenocarcinoma.

Pancreatic cancer, a highly fatal malignancy, is predicted to rank as the second leading cause of cancer-related death in the next decade. This highlights the urgent need for new insights into personalized diagnosis and treatment. Although molecular subtypes of pancreatic cancer were well established in genomics and transcriptomics, few known molecular classifications are translated to guide clinical strategies and require a paradigm shift. Notably, chronically developing and continuously improving high-throughput technologies and systems serve as an important driving force to further portray the molecular landscape of pancreatic cancer in terms of epigenomics, proteomics, metabonomics, and metagenomics. Therefore, a more comprehensive understanding of molecular classifications at multiple levels using an integrated multi-omics approach holds great promise to exploit more potential therapeutic options. In this review, we recapitulated the molecular spectrum from different omics levels, discussed various subtypes on multi-omics means to move one step forward towards bench-to-beside translation of pancreatic cancer with clinical impact, and proposed some methodological and scientific challenges in store.

NiO/AgNPs nanowell enhanced SERS sensor for efficient detection of micro/nanoplastics in beverages.

The ubiquity of plastic products has led to an increased exposure to micro and nano plastics across diverse environments, presenting a novel class of pollutants with substantial health implications. Emerging research indicates their capacity to infiltrate human organs, posing risks of tissue damage and carcinogenesis. Given the prevalent consumption of beverages as a primary vector for these plastics' entry into the human system, there is an imperative need for the advancement of precise detection methodologies in liquids. In this study, we introduce a substrate comprising a Nickel Oxide (NiO) nanosheet array decorated with Silver Nanoparticles (AgNPs) for the Surface-Enhanced Raman Spectroscopy (SERS) analysis of micro//nano plastics. This configuration, leveraging a unique nanowell architecture alongside silver plasmonic enhancement, demonstrates unparalleled sensitivity and repeatability in signal, facilitating the accurate quantification of these contaminants. Through the application of a portable Raman apparatus, this study successfully identifies prevalent micro/nano plastics including polystyrene (PS), polyethylene (PE), and polypropylene (PP), achieving detection sensitivities of 5 µg/mL, 25 µg/mL, and 25 µg/mL, respectively. Moreover, the substrate's efficacy extends to the detection of PS within commonly consumed beverages such as water, milk, and liquor with sensitivities of 25 µg/mL, 50 µg/mL, and 50 µg/mL, respectively. These findings highlight the substrate's potential as an expedient and effective sensor for the real-time monitoring of micro/nano plastic pollutants.

The relationship between psychological capital and self-directed learning ability among undergraduate nursing students-a cross-sectional study.

Background: Psychological capital has become a prominent focus in positive psychology, highlighting the positive influence of higher psychological capital on individuals. Self-directed learning ability is a fundamental skill for students, vital for enhancing academic performance and professional development, and is integral to the continuous learning process of nursing students. Recognizing the relationship between psychological capital and self-directed learning ability is crucial for the progress and development of undergraduate nursing students. Objective: This study aims to investigate the correlation between psychological capital and self-directed learning ability in undergraduate nursing students, as well as to explore the factors that influence these variables. Methods: A cross-sectional survey was conducted with 667 full-time undergraduate nursing students from a nursing school in Taizhou, China. Psychological capital and self-directed learning ability were assessed using the Psychological Capital Questionnaire and Self-Directed Learning Scale, respectively. Correlation and stepwise multiple regression analyses were then carried out to evaluate the relationship between psychological capital and self-directed learning ability among the participants. Results: The study revealed that the psychological capital score averaged at 103.24 ± 15.51, while the self-directed learning scale score averaged at 230.67 ± 27.66. Variations in psychological capital scores were noted based on factors including grade level, being an only child, growth environment, monthly living expenses, parental education level, voluntary selection of nursing major, and club experience. Similarly, differences in self-directed learning scores were associated with factors such as grade level, gender, parental education level, and voluntary selection of nursing major. Moreover, a positive correlation was identified between the overall psychological capital scores and the total self-directed learning ability scores among nursing students. Notably, the multiple regression analysis highlighted that optimism and resilience played significant roles as predictors of self-directed learning ability. Conclusion: Psychological capital is positively correlated with the self-directed learning ability of nursing students, with optimism and resilience identified as crucial predictors. Nursing educators can utilize strategies rooted in positive psychology and perseverance to improve the self-directed learning ability of nursing students.

A glance at structural biology in advancing rice blast fungus research.

The filamentous fungus Magnaporthe oryzae is widely recognized as a notorious plant pathogen responsible for causing rice blasts. With rapid advancements in molecular biology technologies, numerous regulatory mechanisms have been thoroughly investigated. However, most recent studies have predominantly focused on infection-related pathways or host defence mechanisms, which may be insufficient for developing novel structure-based prevention strategies. A substantial body of literature has utilized cryo-electron microscopy and X-ray diffraction to explore the relationships between functional components, shedding light on the identification of potential drug targets. Owing to the complexity of protein extraction and stochastic nature of crystallization, obtaining high-quality structures remains a significant challenge for the scientific community. Emerging computational tools such as AlphaFold for structural prediction, docking for interaction analysis, and molecular dynamics simulations to replicate in vivo conditions provide novel avenues for overcoming these challenges. In this review, we aim to consolidate the structural biological advancements in M. oryzae, drawing upon mature experimental experiences from other species such as Saccharomyces cerevisiae and mammals. We aim to explore the potential of protein construction to address the invasion and proliferation of M. oryzae, with the goal of identifying new drug targets and designing small-molecule compounds to manage this disease.

FecBB mutation enhances follicle stimulating hormone sensitivity of granulosa cells by up-regulating the SMAD1/5-USF1-FSHR signaling pathway.

The FecBB mutation, a single-point mutation (c.A746G; p.Q249R) in bone morphogenetic protein receptor type 1 B (BMPR1B), is associated with increased ovulation quotas and litter size in sheep. However, the regulatory mechanism of the FecBB mutation in increased fecundity remains to be elucidated. Therefore, creating an immortal cell model harboring the FecBB mutation would elucidate the regulatory mechanism of this mutation. Here, we report the creation of a human granulosa cell, COV434, model containing a homozygous FecBB mutation through homology-directed repair (HDR) induced by clustered, regularly-interspaced, short palindromic repeats-CRISPR-associated protein 9 along with a single-stranded oligodeoxynucleotide (ssODN) template. We found that the FecBB mutation enhanced the basal SMAD1/5 signaling activity in COV434 cells, leading to increased expression of FSHR, probably through increased formation of the SMAD1/5-SMAD4 complex to bind to the SBE element, which in turn promotes the binding of USF1 to the regulatory element E-box in the promoter of FSHR. Furthermore, the FecBB mutation substantially enhanced estradiol (E2) synthesis in granulosa cells under follicle stimulating hormone (FSH) stimulation, indicating an enhanced sensitivity to FSH, which may promote the growth of more small follicles into mature follicles, leading to increased fecundity. Our study provides novel insights into the possible regulatory mechanisms of FecBB mutations in increased fecundity.

The Correlation between Epicardial Adipose Tissue Thickness Measured by Echocardiography and P-Wave Dispersion and Atrial Fibrillation.

Background: Recent studies have indicated a close relationship between the thickness of epicardial adipose tissue (EAT) and the occurrence as well as persistence of atrial fibrillation (AF). However, the pathogenesis of this association is still in the exploratory stage. The aim of this study is to explore the correlation EAT, as measured by echocardiography, and P-wave dispersion (Pd) in the context of atrial fibrillation. Additionally, the study seeks to analyze the utility of EAT at different anatomical sites in identifying individuals who are predisposed to atrial fibrillation. Methods: A total of 136 subjects were enrolled and categorized into groups based on the guidelines: paroxysmal atrial fibrillation group (PAF group), persistent atrial fibrillation group (AF group), and non-atrial fibrillation group. Comprehensive clinical data, including general information and medications that could impact the occurrence of atrial fibrillation, were gathered for all patients. Echocardiography was employed to measure the maximum EAT thickness near the apex of the heart on the anterior right ventricular wall and near the base of the right ventricle for each participant. Pd values were computed for each patient based on standard 12-lead synchronous electrocardiogram (ECG). The study involved comparing the disparity in EAT thickness between the two specified sites across the three groups. Additionally, correlation analyses were performed to assess the relationship between EAT thickness at the two sites and Pd. Regression analysis was applied to explore potential risk factors for atrial fibrillation. The diagnostic value of EAT at each site in predicting atrial fibrillation was evaluated using Receiver Operating Characteristic curve (ROC) analysis. Results: EAT thickness of the anterior wall near the apex of the heart and near the base of the right ventricle were significantly positively correlated with Pd (p < 0.05), EAT thickness near the base and left atrial diameter were independent risk factors for atrial fibrillation (OR = 13.673, 95% CI 2.819~66.316, p = 0.001; OR = 2.294, 95% CI 1.020~5.156, p = 0.045). ROC analysis showed that the area under the curve of EAT thickness near the heart base was 0.723, and the best threshold for predicting the occurrence of AF was 1.05 cm. Conclusions: The echocardiography-measured epicardial adipose tissue thickness, particularly in proximity to the heart base, exhibits a significant correlation with Pd. Notably, EAT thickness near the heart base demonstrates superior predictive capability for atrial fibrillation compared to thickness near the apex.

Construction and validation of a nomogram for predicting cancer-specific survival in middle-aged patients with advanced hepatocellular carcinoma: A SEER-based study.

Hepatocellular carcinoma is the predominant form of primary liver cancer and is the leading cause of cancer-related death. The aim of this study was to construct a nomogram to predict cancer-specific survival (CSS) in middle-aged patients with advanced hepatocellular carcinoma. Clinical data were downloaded from the Surveillance, Epidemiology and End Results (SEER) database for middle-aged patients diagnosed with advanced hepatocellular carcinoma (AJCC stage III and IV) from 2000 to 2019. The patients were randomized in a 7:3 ratio into training cohort and validation cohort. Univariate and multivariate Cox regression analyses were performed in the training cohort to screen for independent risk factors associated with cancer-specific survival for the construction of nomogram. The nomogram was examined and evaluated using the consistency index (C-index), area under the curve (AUC), and calibration plots. The clinical application value of the model was evaluated using decision curve analysis (DCA). A total of 3026 patients were selected, including 2244 in the training cohort and 962 in the validation cohort. Multivariate analysis revealed gender, marital status, American Joint Committee on Cancer (AJCC) stage, tumor size, bone metastasis, lung metastasis, alpha-fetoprotein (AFP) level, surgery, radiotherapy, chemotherapy as independent risk factors, which were all included in the construction of the nomogram. In the training cohort, the AUC values were 0.74 (95% CI: 0.76-0.72), 0.78 (95% CI: 0.82-0.75), and 0.82 (95% CI: 0.86-0.78) at 1-, 3-, and 5-year CSS, respectively. The calibration plots showed good consistency between the actual and predicted values. The DCA curves indicated that the nomogram model could more accurately predict CSS at 1-, 3-, and 5-year in middle-aged patients with advanced hepatocellular carcinoma compared with the AJCC staging system. Highly similar results to the training cohort were also observed in the validation cohort. In the risk stratification system, good differentiation was shown between the 2 groups, and Kaplan-Meier survival analysis indicated that surgery could prolong patient survival. In this study, we developed a nomogram and risk stratification system for predicting CSS in middle-aged patients with advanced hepatocellular carcinoma. The prediction model has good predictive performance and can help clinicians in judging prognosis and clinical decision making.

Investigation of the dissolution rate and oral bioavailability of atenolol-irbesartan co-amorphous systems.

Irbesartan (IBS), a common drug to treat hypertension, has poor oral bioavailability because of its limited aqueous solubility. Recently, co-amorphous systems (CAMs) have demonstrated the ability to improve the solubility of poorly water-soluble drugs. In this study, IBS was co-amorphized with a pharmacologically relevant drug atenolol (ATL) by melt-quenching. The structures of the resulting ATL-IBS CAMs, which were formulated in molar ratios of 2:1, 1:1, 1:2 and 1:4, were characterized by the polarizing microscopy, powder X-ray diffraction, differential scanning calorimetry, and Fourier-infrared transform spectroscopy. ATL-IBS CAM1:1 showed higher IBS dissolution than crystalline IBS, amorphous IBS (IBS AM) and the other CAMs. The results of the supersaturated solution stability showed that ATL enhanced the supersaturation maintenance of IBS by extensive interactions. The CAMs exhibited excellent physical stability at 25°C/60% RH. The pharmacokinetics experiments showed that the relative oral bioavailability of IBS was 2.78-fold higher than bulk IBS (p < 0.001) after oral administration of ATL-IBS CAM1:1 to rats. The results of this study demonstrate that CAMs provide an alternative option for the development of fixed dose combination of ATL and IBS.

Advancing the Harmonization of Biopredictive Methodologies through the Product Quality Research Institute (PQRI) Consortium: Biopredictive Dissolution of Dipyridamole Tablets.

Biorelevant dissolution and its concept have been widely accepted and further developed to meaningfully predict the bioperformance of oral drug products. Biorelevant methodologies have been applied to design and optimize oral formulations, to facilitate formulation bridging, and to predict the outcome of bioperformance by coupling the results with modeling. Yet, those methodologies have often been independently customized to align with specific aspects of the oral drug products being developed. Therefore, the evolution of biorelevant dissolution methodologies has taken slightly diverse pathways rather than being standardized like compendial quality control (QC) methodologies. This manuscript presents an effort through the Product Quality Research Institute (PQRI, https://pqri.org) consortium entitled: the standardization of "in vivo predictive dissolution methodologies and in silico bioequivalent study working group" to find the key parameters for biorelevant dissolution, to identify the best practices, and to move toward standardization of biorelevant dissolution methodologies. This working group is composed of members from 10 pharmaceutical companies and academic institutes. The consortium project will be accomplished in five phases, whereby the first two phases have already been completed and published. In this paper, the next two phases are addressed by reporting the biorelevant dissolution profiles of dipyridamole, a weak base model drug, then incorporating the dissolution results into physiologically based biopharmaceutics modeling (PBBM) to determine whether they would lead to bioequivalence (BE) or non-BE.

Only FLT3-ITD co-mutation did not have a deleterious effect on acute myeloid leukemia patients with NPM1 mutation, but concomitant with DNMT3A co-mutation or a < 3log reduction of MRD2 predicted poor survival.

Co-occurring mutations are frequently observed in acute myeloid leukemia (AML) with NPM1 mutation, and NPM1 measurable residual disease (MRD) is an effective prognostic biomarker. This retrospective study investigated the impact of gene co-mutations and NPM1 MRD on outcomes in these patients. Among 234 patients, 11.5% carried the rare type NPM1 mutation (NPM1RT). The median age was 49 years (IQR 36-58), with a median follow-up of 30.4 months (IQR 12.1-55.7). Nine genes were mutated in > 10%, with DNMT3A (53.8%) and FLT3-ITD (44.4%) being most prevalent. Univariable analysis in 137 patients showed FLT3-ITD, DNMT3A co-mutations, and MRD2 < 3 log reduction predicted poorer survival. FLT3-ITD and DNMT3A co-mutations correlated with the lowest event-free (EFS) and overall survival (OS) (3-year EFS 30.0%; 3-year OS 34.4%; both p < 0.001). FLT3-ITD alone did not worsen survival compared to patients without FLT3-ITD. Multivariable analysis identified DNMT3A co-mutation [EFS, HR = 1.9, p = 0.021; OS, HR = 2.2, p = 0.023] and MRD2 ≥ 3 log reduction (EFS, HR = 0.2; OS, HR = 0.1, both p < 0.001) as independent survival predictors. Patients with FLT3-ITD and DNMT3A co-mutations or a MRD2 < 3 log reduction were identified as high risk, but allogeneic hematopoietic stem cell transplantation (allo-HSCT) improved survival significantly compared to chemotherapy only (3-year EFS, 57.9% vs. 30.0%, p = 0.012; 3-year OS, 72.9% vs. 34.4%, p = 0.001). In AML patients with NPM1 mutation, the detrimental impact of FLT3-ITD mutation was exacerbated by DNMT3A co-mutation. Poor-risk younger patients identified by FLT3-ITD and DNMT3A co-mutations or MRD2 < 3 log reduction benefit from allo-HSCT.

METTL3-mediated m6A modification of OTUD1 aggravates press overload induced myocardial hypertrophy by deubiquitinating PGAM5.

Background: Pathological cardiac hypertrophy, a condition that contributes to heart failure, is characterized by its intricate pathogenesis. The meticulous regulation of protein function, localization, and degradation is a crucial role played by deubiquitinating enzymes in cardiac pathophysiology. This study clarifies the participation and molecular mechanism of OTUD1 (OTU Deubiquitinase 1) in pathological cardiac hypertrophy. Methods: We generated a cardiac-specific Otud1 knockout mouse line (Otud1-CKO) and adeno-associated virus serotype 9-Otud1 mice to determine the role of Otud1 in cardiac hypertrophy. Its impact on cardiomyocytes enlargement was investigated using the adenovirus. RNA immunoprecipitation was used to validate the specific m6a methyltransferase interacted with OTUD1 transcript. RNA sequencing in conjunction with immunoprecipitation-mass spectrometry analysis was employed to identify the direct targets of OTUD1. A series of depletion mutant plasmids were constructed to detect the interaction domain of OTUD1 and its targets. Results: Ang II-stimulated neonatal rat cardiac myocytes and mice hearts subjected to transverse aortic constriction (TAC) showed increased protein levels of Otud1. Cardiac hypertrophy and dysfunction were less frequent in Otud1-CKO mice during TAC treatment, while Otud1 overexpression worsened cardiac hypertrophy and remodeling. METTL3 mediated m6A modification of OTUD1 transcript promoted mRNA stability and elevated protein expression. In terms of pathogenesis, Otud1 plays a crucial role in cardiac hypertrophy by targeting Pgam5, leading to the robust activation of the Ask1-p38/JNK signal pathway to accelerate cardiac hypertrophy. Significantly, the pro-hypertrophy effects of Otud1 overexpression were largely eliminated when Ask1 knockdown. Conclusion: Our findings confirm that targeting the OTUD1-PGAM5 axis holds significant potential as a therapeutic approach for heart failure associated with pathological hypertrophy.

Cynaropicrin attenuates inflammatory cytokines in LPS-induced RAW264.7 cells and ovalbumin-induced asthmatic mice.

This study examines the anti-inflammatory activity of cynaropicrin against lipopolysaccharide (LPS) in vitro and ovalbumin (OVA)-challenged asthma in mice. Cynaropicrin's antimicrobial effects were tested on Escherichia coli (E. coli) and Streptococcus pyogenes (S. pyogenes) using the disc diffusion technique. Cytotoxicity was assessed with an (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide) assay. The anti-inflammatory property was evaluated in LPS-induced RAW264.7 cells, while OVA-challenged asthmatic mice were treated with 10 mg/kg of cynaropicrin. Key inflammatory and antioxidant markers were quantified, and lung histology was examined to confirm therapeutic roles. The antimicrobial studies proved that cynaropicrin effectively inhibited the growth of E. coli and S. pyogenes. Cynaropicrin displayed no cytotoxicity on RAW264.7 cells. Furthermore, it significantly inhibited inflammatory cytokine synthesis upon LPS induction. Cynaropicrin treatment decreased the inflammatory cell counts and also suppressed specific allergic markers in OVA-challenged mice. It also decreased nitric oxide and myeloperoxidase levels and reduced pulmonary edema. Cynaropicrin increased antioxidant levels and decreased proinflammatory cytokines in the asthmatic mice. Lung histological examination confirms the ameliorative potency of cynaropicrin against OVA-induced asthmatic pulmonary inflammation in mice. Our findings suggest cynaropicrin possesses significant ameliorative potency against allergen-induced pulmonary inflammation.

Concepts and applications of digital twins in healthcare and medicine.

The digital twin (DT) is a concept widely used in industry to create digital replicas of physical objects or systems. The dynamic, bi-directional link between the physical entity and its digital counterpart enables a real-time update of the digital entity. It can predict perturbations related to the physical object's function. The obvious applications of DTs in healthcare and medicine are extremely attractive prospects that have the potential to revolutionize patient diagnosis and treatment. However, challenges including technical obstacles, biological heterogeneity, and ethical considerations make it difficult to achieve the desired goal. Advances in multi-modal deep learning methods, embodied AI agents, and the metaverse may mitigate some difficulties. Here, we discuss the basic concepts underlying DTs, the requirements for implementing DTs in medicine, and their current and potential healthcare uses. We also provide our perspective on five hallmarks for a healthcare DT system to advance research in this field.