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Ultrasonics Sonochemistry Jun 2024Sonoporation is a non-invasive method that uses ultrasound for drug and gene delivery for therapeutic purposes. Here, both Finite Element Method (FEM) and Lattice...
Sonoporation is a non-invasive method that uses ultrasound for drug and gene delivery for therapeutic purposes. Here, both Finite Element Method (FEM) and Lattice Boltzmann Method (LBM) are applied to study the interaction physics of microbubble oscillation and collapse near flexible tissue. After validating the Finite Element Method with the nonlinear excited lipid-coated microbubble as well as the Lattice Boltzmann Method with experimental results, we have studied the behavior of a three-dimensional compressible microbubble in the vicinity of tissue. In the FEM phase, the oscillation microbubble with a lipid shell interacts with the boundary. The range of pressure and ultrasound frequency have been considered in the field of therapeutic applications of sonoporation. The viscoelastic and interfacial tension as the coating properties of the microbubble shell have been investigated. The presence of an elastic boundary increases the resonance frequency of the microbubble compared to that of a free microbubble. The increase in pressure leads to an expansion in the range of the microbubble's motion, the velocity induced in the fluid, and the shear stress on the boundary walls of tissue. An enhancement in the surface tension of the microbubble can influence fluid flow and reduce the shear stress on the boundary. The multi-pseudo-potential interaction LBM is used to reduce thermodynamic inconsistency and high-density ratio in a two-phase system for modeling the cavitation process. The three-dimensional shape of the microbubble during the collapse stages and the counter of pressure are displayed. There is a time difference between the occurrence of maximum velocity and pressure. All results in detail are presented in the article bodies.
PubMed: 38941703
DOI: 10.1016/j.ultsonch.2024.106972 -
JMIR Public Health and Surveillance Jun 2024Suicide is a significant public health issue. Many risk prediction tools have been developed to estimate an individual's risk of suicide. Risk prediction models can go...
BACKGROUND
Suicide is a significant public health issue. Many risk prediction tools have been developed to estimate an individual's risk of suicide. Risk prediction models can go beyond individual risk assessment; one important application of risk prediction models is population health planning. Suicide is a result of the interaction among the risk and protective factors at the individual, health care system, and community levels. Thus, policy and decision makers can play an important role in suicide prevention. However, few prediction models for the population risk of suicide have been developed.
OBJECTIVE
This study aims to develop and validate prediction models for the population risk of suicide using health administrative data, considering individual-, health system-, and community-level predictors.
METHODS
We used a case-control study design to develop sex-specific risk prediction models for suicide, using the health administrative data in Quebec, Canada. The training data included all suicide cases (n=8899) that occurred from January 1, 2002, to December 31, 2010. The control group was a 1% random sample of living individuals in each year between January 1, 2002, and December 31, 2010 (n=645,590). Logistic regression was used to develop the prediction models based on individual-, health care system-, and community-level predictors. The developed model was converted into synthetic estimation models, which concerted the individual-level predictors into community-level predictors. The synthetic estimation models were directly applied to the validation data from January 1, 2011, to December 31, 2019. We assessed the performance of the synthetic estimation models with four indicators: the agreement between predicted and observed proportions of suicide, mean average error, root mean square error, and the proportion of correctly identified high-risk regions.
RESULTS
The sex-specific models based on individual data had good discrimination (male model: C=0.79; female model: C=0.85) and calibration (Brier score for male model 0.01; Brier score for female model 0.005). With the regression-based synthetic models applied in the validation data, the absolute differences between the synthetic risk estimates and observed suicide risk ranged from 0% to 0.001%. The root mean square errors were under 0.2. The synthetic estimation model for males correctly predicted 4 of 5 high-risk regions in 8 years, and the model for females correctly predicted 4 of 5 high-risk regions in 5 years.
CONCLUSIONS
Using linked health administrative databases, this study demonstrated the feasibility and the validity of developing prediction models for the population risk of suicide, incorporating individual-, health system-, and community-level variables. Synthetic estimation models built on routinely collected health administrative data can accurately predict the population risk of suicide. This effort can be enhanced by timely access to other critical information at the population level.
Topics: Humans; Quebec; Male; Suicide; Female; Case-Control Studies; Adult; Risk Assessment; Middle Aged; Aged; Adolescent; Young Adult; Risk Factors
PubMed: 38941610
DOI: 10.2196/52773 -
JMIR Research Protocols Jun 2024Osteoarthritis (OA) is a disabling condition that affects more than one-third of people older than 65 years. Currently, 80% of these patients report movement...
Assessment of the Feasibility of Objective Parameters as Primary End Points for Patients Affected by Knee Osteoarthritis: Protocol for a Pilot, Open Noncontrolled Trial (:SMILE:).
BACKGROUND
Osteoarthritis (OA) is a disabling condition that affects more than one-third of people older than 65 years. Currently, 80% of these patients report movement limitations, 20% are unable to perform major activities of daily living, and approximately 11% require personal care. In 2014, the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis (ESCEO) recommended, as the first step in the pharmacological treatment of knee osteoarthritis, a background therapy with chronic symptomatic slow-acting osteoarthritic drugs such as glucosamine sulfate, chondroitin sulfate, and hyaluronic acid. The latter has been extensively evaluated in clinical trials as intra-articular and oral administration. Recent reviews have shown that studies on oral hyaluronic acid generally measure symptoms using only subjective parameters, such as visual analog scales or quality of life questionnaires. As a result, objective measures are lacking, and data validity is generally impaired.
OBJECTIVE
The main goal of this pilot study with oral hyaluronic acid is to evaluate the feasibility of using objective tools as outcomes to evaluate improvements in knee mobility. We propose ultrasound and range of motion measurements with a goniometer that could objectively correlate changes in joint mobility with pain reduction, as assessed by the visual analog scale. The secondary objective is to collect data to estimate the time and budget for the main double-blind study randomized trial. These data may be quantitative (such as enrollment rate per month, number of screening failures, and new potential outcomes) and qualitative (such as site logistical issues, patient reluctance to enroll, and interpersonal difficulties for investigators).
METHODS
This open-label pilot and feasibility study is conducted in an orthopedic clinic (Timisoara, Romania). The study includes male and female participants, aged 50-70 years, who have been diagnosed with symptomatic knee OA and have experienced mild joint discomfort for at least 6 months. Eight patients must be enrolled and treated with Syalox 300 Plus (River Pharma) for 8 weeks. It is a dietary supplement containing high-molecular-weight hyaluronic acid, which has already been marketed in several European countries. Assessments are made at the baseline and final visits.
RESULTS
Recruitment and treatment of the 8 patients began on February 15, 2018, and was completed on May 25, 2018. Data analysis was planned to be completed by the end of 2018. The study was funded in February 2019. We expect the results to be published in a peer-reviewed clinical journal in the last quarter of 2024.
CONCLUSIONS
The data from this pilot study will be used to assess the feasibility of a future randomized clinical trial in OA. In particular, the planned outcomes (eg, ultrasound and range of motion), safety, and quantitative and qualitative data must be evaluated to estimate in advance the time and budget required for the future main study. Finally, the pilot study should provide preliminary information on the efficacy of the investigational product.
TRIAL REGISTRATION
ClinicalTrials.gov NCT03421054; https://clinicaltrials.gov/study/NCT03421054.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)
RR1-10.2196/13642.
Topics: Humans; Osteoarthritis, Knee; Pilot Projects; Feasibility Studies; Hyaluronic Acid; Male; Female; Aged; Middle Aged; Quality of Life; Endpoint Determination
PubMed: 38941599
DOI: 10.2196/13642 -
Medicine Jun 2024Primary sclerosing cholangitis (PSC), a chronic cholestatic liver condition, is frequently associated with inflammatory bowel disease. Specific immune cells have been...
Primary sclerosing cholangitis (PSC), a chronic cholestatic liver condition, is frequently associated with inflammatory bowel disease. Specific immune cells have been implicated in PSC pathogenesis with the emergence of the "microbiota" and "gut lymphocyte homing" hypotheses, albeit their identities remain controversial. The first genome-wide association analysis leveraged nonoverlapping data from 3757 Europeans to evaluate 731 immunophenotypes. A genome-wide association analysis comprising 2871 cases and 12,019 controls yielded summary statistics for PSC. An inverse-variance weighted (IVW) analysis was performed to identify immunophenotypes causally related to PSC, and the results were validated using weighted mode, MR-Egger, and weighted median methods. Comprehensive sensitivity analyses were performed to verify the robustness, heterogeneity, and horizontal pleiotropy of the results. IVW analysis revealed 26 immune traits exhibiting causal associations with PSC. CD3 on HLA-DR+ CD4+ (IVW odds ratio [OR]: 0.904; 95% confidence interval [CI]: 0.828-0.986, P = .023) and CD3 on secreting Treg (IVW OR: 0.893; 95% CI: 0.823-0.969, P = .007) were negatively associated with PSC susceptibility and demonstrated high consistency across the 3 validation methods. Moreover, 7 other immune traits, including CD39+ resting Treg absolute cell (IVW OR = 1.083, 95% CI: 1.013-1.157, P = .019), CD39+ secreting Treg absolute cell (IVW OR = 1.063, 95% CI: 1.012-1.118, P = .015), CD3 on naive CD8br (IVW OR = 0.907, 95% CI: 0.835-0.986, P = .022), CD3 on CD39+ activated Treg (IVW OR = 0.927, 95% CI: 0.864-0.994, P = .034), CD28 on resting Treg (IVW OR = 0.724, 95% CI: 0.630-0.833, P = 5.95E-06), and CD39 on CD39+ CD4+ (IVW OR = 1.055, 95% CI: 1.001-1.112, P = .044) exhibited consistent results in the Weighted Median and Weighted Mode validation methods. Moreover, no significant heterogeneity or horizontal pleiotropy was observed across the single nucleotide polymorphisms. The leave-one-out results revealed that sequentially eliminating each single nucleotide polymorphism had no significant influence on model effect estimates or qualitative inference. This study evaluated potential causal links between 731 immune traits and PSC susceptibility. Twenty-six immune traits were identified using the IVW method. Verification across multiple methods revealed 9 immune traits with a plausible causal connection to PSC. These findings may uncover mechanistic pathways and novel therapeutic approaches.
Topics: Cholangitis, Sclerosing; Humans; Mendelian Randomization Analysis; Genome-Wide Association Study; Immunophenotyping; Genetic Predisposition to Disease; Polymorphism, Single Nucleotide
PubMed: 38941430
DOI: 10.1097/MD.0000000000038626 -
Medicine Jun 2024This study investigates the correlation between thyroid hormone levels and metabolic dysfunction in patients with type 2 diabetes mellitus (T2DM) who exhibit normal...
BACKGROUND
This study investigates the correlation between thyroid hormone levels and metabolic dysfunction in patients with type 2 diabetes mellitus (T2DM) who exhibit normal thyroid function and metabolic dysfunction associated with steatotic liver disease (MASLD).
OBJECTIVE
The objective is to identify a scientific basis for the management of T2DM complicated by MASLD, aiming to refine clinical strategies and enhance patient well-being.
METHODS
Statistical analysis was conducted using SPSS 26.0, employing independent sample t-tests for normally distributed data and logarithmic transformations for non-normal data to meet analysis prerequisites. Multifactorial logistic regression analysis elucidated the impact of various factors on the risk of MASLD in T2DM patients.
RESULTS
Elevated levels of FT3 may be associated with an increased risk of nonalcoholic fatty liver disease. Additionally, the FT3/FT4 ratio has been validated as an effective serological marker for predicting the risk of MASLD. In patients with DM2 and normal thyroid function, changes in thyroid hormone levels are closely related to the occurrence of MASLD. Elevated levels of FT3, total triiodothyronine (TT3), and thyroid-stimulating hormone are associated with an increased risk of MASLD.
CONCLUSION
FT3, TT3, and thyroid-stimulating hormone have important clinical value in the diagnosis of patients with T2DM complicated with MASLD.
Topics: Humans; Diabetes Mellitus, Type 2; Male; Female; Middle Aged; Triiodothyronine; Thyroid Hormones; Aged; Non-alcoholic Fatty Liver Disease; Thyrotropin; Biomarkers; Risk Factors; Thyroid Function Tests; Adult
PubMed: 38941427
DOI: 10.1097/MD.0000000000038643 -
Medicine Jun 2024This study aimed to investigate immune score and stromal score-related signatures associated with preeclampsia (PE) and identify key genes for diagnosing PE using...
This study aimed to investigate immune score and stromal score-related signatures associated with preeclampsia (PE) and identify key genes for diagnosing PE using bioinformatics analysis. Four microarray datasets, GSE75010, GSE25906, GSE44711, and GSE10588 were obtained from the Gene Expression Omnibus database. GSE75010 was utilized for differential expressed gene (DEGs) analysis. Subsequently, bioinformatic tools such as gene ontology, Kyoto Encyclopedia of Genes and Genomes, weighted gene correlation network analysis, and gene set enrichment analysis were employed to functionally characterize candidate target genes involved in the pathogenesis of PE. The least absolute shrinkage and selection operator regression approach was employed to identify crucial genes and develop a predictive model. This method also facilitated the creation of receiver operating characteristic (ROC) curves, enabling the evaluation of the model's precision. Furthermore, the model underwent external validation through the other three datasets. A total of 3286 DEGs were identified between normal and PE tissues. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed enrichments in functions related to cell chemotaxis, cytokine binding, and cytokine-cytokine receptor interaction. weighted gene correlation network analysis identified 2 color modules strongly correlated with immune and stromal scores. After intersecting DEGs with immune and stromal-related genes, 13 genes were selected and added to the least absolute shrinkage and selection operator regression. Ultimately, 7 genes were screened out to establish the risk model for discriminating preeclampsia from controls, with each gene having an area under the ROC curve >0.70. The constructed risk model demonstrated that the area under the ROC curves in internal and the other three external datasets were all greater than 0.80. A 7-gene risk signature was identified to build a potential diagnostic model and performed well in the external validation group for PE patients. These findings illustrated that immune and stromal cells played essential roles in PE during its progression.
Topics: Humans; Pre-Eclampsia; Female; Pregnancy; Computational Biology; Gene Expression Profiling; ROC Curve; Databases, Genetic; Gene Ontology; Gene Regulatory Networks
PubMed: 38941397
DOI: 10.1097/MD.0000000000038638 -
Medicine Jun 2024The mortality rate related to variceal bleeding is high in patients with liver cirrhosis. Early detection and treatment of varices can reduce the risk of hemorrhage and...
The mortality rate related to variceal bleeding is high in patients with liver cirrhosis. Early detection and treatment of varices can reduce the risk of hemorrhage and thus decrease the mortality rate related to variceal bleeding. The study comprised 81 cirrhotic patients in training set, who were categorized into 2 groups: the patients with esophageal varices (EVs group) and the patients without esophageal varices (non-EVs group). The disparity in Cystatin C/albumin ratio (CAR) was assessed between these 2 groups. Subsequently, a regression model was constructed by generating a receiver operating characteristic (ROC) curve to calculate the area under the curve (AUC). Then an external validation was performed in 25 patients. Among patients with cirrhosis in training set, a statistically significant difference in CAR was observed between the EVs group and non-EVs group (P < .05). At the CAR cutoff value of 2.79*10-5, the AUC for diagnosing EVs were 0.666. Further, a multivariate logistic regression model was constructed, after adjusting the model, the AUC for EVs diagnosis were 0.855. And the external validation showed that the model could not be considered as a poor fit. CAR exhibits potential as an early detection marker for EVs in liver cirrhosis, and the regression model incorporating CAR demonstrates a strong capability for early EVs diagnosis.
Topics: Humans; Esophageal and Gastric Varices; Liver Cirrhosis; Cystatin C; Male; Female; Middle Aged; Early Diagnosis; Biomarkers; ROC Curve; Aged; Serum Albumin; Adult; Retrospective Studies; Area Under Curve
PubMed: 38941375
DOI: 10.1097/MD.0000000000038481 -
Medicine Jun 2024As chronic autoimmune inflammatory diseases, rheumatoid arthritis (RA) and Crohn disease (CD) are closely associated and display a significant positive correlation....
As chronic autoimmune inflammatory diseases, rheumatoid arthritis (RA) and Crohn disease (CD) are closely associated and display a significant positive correlation. However, the underlying mechanisms and disease markers responsible for their cooccurrence remain unknown and have not been systematically studied. Therefore, this study aimed to identify key molecules and pathways commonly involved in both RA and CD through bioinformatic analysis of public sequencing databases. Datasets for RA and CD were downloaded from the GEO database. Overlapping genes were identified using weighted gene co-expression network analysis and differential analysis crossover, and enrichment analysis was conducted for these genes. Protein-protein interaction networks were then constructed using these overlapping genes to identify hub genes. Expression validation and receiver operating characteristic curve validation were performed for these hub genes using different datasets. Additionally, the immune cell correlation, single-cell expression cluster, and the immune cell expression cluster of the core gene were analyzed. Furthermore, upstream shared microRNAs (miRNA) were predicted and a miRNA-gene network was constructed. Finally, drug candidates were analyzed and predicted. These core genes were found to be positively correlated with multiple immune cells that are infiltrated by the disease. Analysis of gene expression clusters revealed that these genes were mostly associated with inflammatory and immune responses. The miRNA-genes network analysis suggested that hsa-miR-31-5p may play an important role in the common mechanism of RA and CD. Finally, tamibarotene, retinoic acid, and benzo[a]pyrene were identified as potential treatment options for patients with both RA and CD. This bioinformatics study has identified ITGB2, LCP2, and PLEK as key diagnostic genes in patients with both RA and CD. The study has further confirmed that inflammation and immune response play a central role in the development of both RA and CD. Interestingly, the study has highlighted hsa-miR-31-5p as a potential key player in the common mechanism of both diseases, representing a new direction in research and a potential therapeutic target. These shared genes, potential mechanisms, and regulatory networks offer new opportunities for further research and may provide hope for future treatment of patients with both RA and CD.
Topics: Humans; Crohn Disease; Arthritis, Rheumatoid; Computational Biology; MicroRNAs; Protein Interaction Maps; Gene Regulatory Networks; Biomarkers; Gene Expression Profiling
PubMed: 38941374
DOI: 10.1097/MD.0000000000038690 -
Medicine Jun 2024This study aimed to establish an effective predictive model for postoperative delirium (POD) risk assessment after total knee arthroplasty (TKA) in older patients. The...
This study aimed to establish an effective predictive model for postoperative delirium (POD) risk assessment after total knee arthroplasty (TKA) in older patients. The clinical data of 446 older patients undergoing TKA in the Orthopedics Department of our University from January to December 2022 were retrospectively analyzed, and the POD risk prediction model of older patients after TKA was established. Finally, 446 patients were included, which were divided into training group (n = 313) and verification group (n = 133). Logistic regression method was used to select meaningful predictors. The prediction model was constructed with nomographs, and the model was evaluated with correction curve and receiver operating characteristic curve. The logistic regression analysis showed that age, educational level, American Society of Anesthesiologists grade, accompaniment of chronic obstructive pulmonary disease, accompaniment of cerebral stroke, postoperative hypoxemia, long operation time, and postoperative pain were independent risk factors for POD after TKA (P < .05). The nomogram prediction model established. The area under receiver operating characteristic curve of the model group and the validation group were 0.954 and 0.931, respectively. The calibration curve of the prediction model has a high consistency between the 2 groups. The occurrence of POD was associated with age, educational level, American Society of Anesthesiologists grade, accompaniment of chronic obstructive pulmonary disease, accompaniment of cerebral stroke, postoperative hypoxemia, long operation time, and postoperative pain in TKA patients.
Topics: Humans; Arthroplasty, Replacement, Knee; Male; Female; Aged; Retrospective Studies; Risk Factors; Risk Assessment; Postoperative Complications; Delirium; ROC Curve; Middle Aged; Nomograms; Age Factors; Aged, 80 and over; Logistic Models
PubMed: 38941370
DOI: 10.1097/MD.0000000000038745 -
PloS One 2024To improve the accuracy of modal analysis for a four-stage centrifugal-pump rotor system with a balancing disc based on the concentrated-mass analytical method, a...
To improve the accuracy of modal analysis for a four-stage centrifugal-pump rotor system with a balancing disc based on the concentrated-mass analytical method, a simplified concentrated mass mathematical model and an ANSYS simulation model are established. The results from these two models are compared to determine factors that cause significant differences in the mode shapes. Subsequently, an optimized mathematical model based on the corrected mass moment of an inertia matrix and stiffness correction coefficients is proposed, and the effectiveness of this optimized mathematical model is validated using a four-stage centrifugal pump with back blades. The results show that the natural frequencies obtained from the ANSYS simulations are consistently higher than those obtained using the analytical method. The simplification of the moment of inertia at the impeller and balancing disc contributes primarily to the calculated errors. The optimized mathematical model reduces the errors in the natural frequencies from 12.96%, 12.13%, 9.96%, 5.85%, and 8.74% to 2.45%, 1.56%, 0.65%, 5.34%, and 2.28%, respectively. The optimization of natural frequencies offers better performance at lower-order modes, whereas its effects on higher-order modes are less significant. The optimization method is applicable to centrifugal pumps with back blades and reduces the error in theoretical calculations, based on reductions in the concentrated mass from 13.11%, 12.85%, 9.91%, and 7.2% to 3.7%, 3.86%, 0.57%, and 2.87%, respectively, thus further confirming the feasibility of the optimized model design.
Topics: Centrifugation; Models, Theoretical; Computer Simulation; Equipment Design
PubMed: 38941321
DOI: 10.1371/journal.pone.0306061