Science Progress最新文献

ObjectiveQuantify recruitment of Native Hawaiian and Pacific Islander (NHPI) participants from 22 Alzheimer's disease (AD) clinical trials over 5 years and utilize choropleth maps as a visual tool to identify where in the Hawaiian community recruited participants are located in order to better inform future recruitment efforts and improve equity and population diversity for future AD clinical trials.MethodsA retrospective chart review was conducted at a dual-site origin clinical trial center in Hawai'i. Inclusion criteria were a diagnosis of mild cognitive impairment and participation in one or more AD clinical trials conducted between 2020 and 2024. Demographic information of clinical trial participants was collected via chart review and included self-identified race/ethnicity, age, residence, and number of clinical trials the patient has participated in. Clinical trial participants were categorized by ZIP codes established by the US Census Bureau. Differences across race/ethnicity groups were assessed using either Pearson's Chi-squared test or Fisher's exact test.ResultsA total of 244 patients participated across the state of Hawai'i in 22 AD clinical trials between 2020 and 2024. Of this total, 169 (69%) patients provided their race/ethnicity, and 75 (31%) did not provide their race/ethnicity. White patients had the highest percentage of participation (44%), followed by Asian patients (34%) and NHPI patients (15%). The population distribution visualized in this study's choropleth maps suggests that NHPI were under-recruited from the west side of O'ahu.ConclusionsOur retrospective study applied choropleth maps to visualize the recruitment data and patterns of AD clinical trials. By utilizing choropleth maps to analyze recruitment areas, the NHPI community and other underrepresented populations may benefit from targeted, culturally informed recruitment strategies.

To address the limitations of flux regulation in traditional permanent magnet synchronous generators and the low power density of electrically excited generators, an interior double-radial asymmetric permanent magnet (PM) and salient-pole electromagnetic hybrid excitation generator are introduced in this study. Equations for the no-load induced electromotive force, the voltage adjustment range, and the total harmonic distortion (THD) are derived theoretically through the analysis of generator parameter relationships. The optimization parameters include the offset angles of the double-layer asymmetric PMs and the structural parameters of the salient-pole rotor. A multi-objective optimization model is established with the no-load induced electromotive force amplitude, the voltage adjustment range, and the THD as the objectives. Samples are generated by Latin Hypercube Sampling, followed by sensitivity analysis of the optimization parameters. The optimization parameters are then screened using Pareto front analysis and a defined parameter matching coefficient. The optimal magnet pole parameters are determined. As a result of optimization, the no-load induced electromotive force amplitude increases by 18.7%, the voltage adjustment range expands by 17.6%, and the THD decreases by 38.2%. Finally, a prototype is fabricated and tested, and the results confirm both the accuracy of the theoretical analysis and the effectiveness of the optimization method. The output characteristics of the designed generator are thereby significantly improved.

The increasing demand for sustainable energy production necessitates the development of innovative technologies for converting municipal waste into valuable energy offering a viable alternative to fossil fuels. This study presents a flexible, portable, and expandable waste-to-energy concept that integrates gasification and pyrolysis processes production of combustible gases and liquid fuels. Particular emphasis is placed on the use of transparent and interpretable modelling approaches to support system optimization and future scalability. The proposed methodology is demonstrated on two experimental systems currently operated at CEET Explorer, VSB - Technical University of Ostrava, Czech Republic: (i) A primary gasification facility equipped with a plasma torch, reactor, hydrogen separator and tank, fuel cells, and renewable grid connections; and (ii) a secondary pyrolysis unit designed to maximize pyrolysis oil production. Both systems are modelled and simulated using in-house software developed in Python, employing stoichiometric balances, symbolic regression, and polynomial regression to represent chemical reactions and energy flows. The findings demonstrate that transparent models - such as stoichiometric modelling combined with interpretable machine learning - can accurately reproduce the operational behaviour of waste-to-energy processes. Gasification is optimized for hydrogen generation and electricity production via fuel cells, whereas pyrolysis favours liquid fuel yield with syngas as a by-product. Molar mass relations are applied to ensure consistent conversion between mass and volume across gasification, pyrolysis, and combustion pathways, maintaining the conservation of mass. Overall, the integration of stoichiometric balance models with symbolic and polynomial regression provides a reliable and interpretable framework for simulating real waste-to-energy systems. The current results, based on bio-wood waste from the Czech Republic, validate the proposed methodology, which is made openly available to promote transparency, reproducibility, and further advancement of sustainable waste-to-energy technologies.

BackgroundThe lack of a systematic selection framework for the selection of linear feed mechanisms in precision machine tools results in a mismatch between the performance of the mechanism and the specific application requirements in terms of accuracy, stiffness and load capacity, which restricts the optimization design of high-performance machining systems.ObjectivesWe are committed to establishing a systematic classification system to categorize existing technologies and define their quantified performance boundaries, in order to guide the optimal choices of institutions and future innovation directions.MethodsThis review establishes a structured classification system, dividing mechanisms into four clear categories: typical linear drive mechanisms, linear linkage mechanisms, high-precision feed mechanisms and novel linear mechanisms. We compared and analyzed their working principles based on key parameters such as positioning accuracy, structural stiffness and load capacity; quantified their performance boundaries; and provided their applications. At the end of each section, a table is listed to summarize the content for easy reference.DiscussionsThe analysis reveals that a typical linear feed mechanism, as the basic unit of machine tool linear motion, is widely used but has low accuracy. A linear linkage mechanism may not have high accuracy, but it can help machine tools complete specific structures. A high-precision linear feed mechanism has high precision, usually reaching the micrometer level, and is applied in scenarios with high precision requirements. The new linear feed mechanism represents the direction of technological development and guides the optimization design of machine tools.ResultsThe performance-oriented classification framework developed in this study effectively resolves the selection challenge for precision linear feed mechanisms in machine tools. Its theoretical contribution lies in proposing a systematic performance spectrum, while its practical significance is to provide engineers with a clear decision-making tool for mechanism selection and to illuminate directed pathways for future innovation in precision motion systems.

ObjectiveTraditional indicators of obesity, such as body mass index (BMI), fail to precisely capture the independent impact of fat distribution on gallstone disease (GSD). This study aimed to investigate the nonlinear association between body fat ratio (BFR) and the risk of GSD and to identify a critical threshold value.MethodWe conducted a cross-sectional observational analysis of 1952 adults from the 2017-2018 National Health and Nutrition Examination Survey (NHANES). BFR was measured by dual-energy X-ray absorptiometry, and GSD was defined by standardized questionnaire data. Weighted logistic regression, restricted cubic spline (RCS), and threshold effect models were employed to examine the association between BFR and GSD risk, as well as to determine the inflection point.ResultsA significant J-shaped nonlinear association was observed between BFR and GSD risk (P for non-linearity < 0.001). Threshold analysis identified 29.1% (95% CI: 27.5-30.7%) as the critical inflection point, beyond which each 1% increase in BFR was associated with a 14% higher odds of GSD (OR = 1.14, 95% CI: 1.09-1.19). After multivariate adjustment, each additional 1% increase in BFR remained independently associated with a 7% increased risk (OR = 1.07, 95% CI: 1.02-1.13). Compared with participants in the lowest quartile, those in the highest quartile (BFR≥39.2%) exhibited a 2.66-fold higher risk of GSD. Subgroup analyses demonstrated stronger associations in males (OR ≈ 1.12 per 1% BFR increase) and Hispanics (OR ≈ 1.20 per 1% BFR increase).ConclusionsBFR of ≥29.1% represents a critical threshold beyond which GSD risk significantly increases. These findings suggest an association that warrants further investigation into whether routine monitoring of BFR could serve as a valuable screening tool in high-risk populations, and precise intervention strategies should consider gender and ethnic differences to effectively mitigate metabolic-related gallstone disease.

ObjectivesAlthough bone marrow mesenchymal stromal cells (BMSCs) are extensively used in biomedicine, they have yet to be used in the commercial development of a tissue engineered medicine. It has been argued that the major roadblock in their commercial deployment is the lengthy in vitro culture periods required for the development of implantable tissue surrogates. Macromolecular crowding (MMC) has been shown to enhance and increase extracellular matrix deposition in eukaryotic cell culture, allowing for the accelerated development of tissue facsimiles.MethodsWith these in mind, human BMSCs were cultured under MMC conditions and the developed tissue-engineered medicine was assessed in vitro and in vivo in a humanised athymic nude mouse excisional wound splinting model.ResultsStarting with basic cell function analysis, MMC did not significantly affect cell metabolic activity, viability and proliferation. Electrophoresis and immunofluorescence analyses revealed that MMC significantly increased collagen type I and collagen type IV deposition, without significantly affecting collagen type III deposition. Flow cytometry analysis demonstrated similar CD44, CD73, CD90, CD146, HLA-ABC, CD31, CD45, CD80 and CD86 expression between the without and the with MMC groups. Interestingly though the MMC group had higher CD105 and lower HLA-DR expression than the without MMC group. Preclinical analysis revealed similar wound closure, scar index and epidermal thickness between the without and the with MMC groups, largely attributed to issues encountered with the model.ConclusionsOverall, this preliminary study demonstrates the potential of MMC in the accelerated development of functional and extracellular matrix-rich human BMSC-based tissue-engineered medicines.

Odontogenic cysts are well-known maxillofacial pathologies with variable biological behaviour. Decompression has been widely used as a conservative, structure-preserving management strategy. This report presents a radiographic comparison of reduction patterns following decompression in two individual cases, one dentigerous cyst and one odontogenic keratocyst. Two patients presenting with cystic jaw lesions - one detected during radiographic investigation and the other presenting with progressive swelling - were managed using decompression as the initial treatment. Standardised radiographic measurements were performed, and the Standard Lesion Area Index and Percentage of Reduction were calculated at serial follow-up intervals. The dentigerous cyst demonstrated gradual reduction, achieving 94.4% shrinkage at 12 months and complete radiographic resolution by 44 months, with no radiographic evidence of recurrence. In contrast, the odontogenic keratocyst showed a more rapid initial reduction, with 58% shrinkage at 5 months, followed by a plateau at approximately 90% shrinkage by 24 months and radiographic evidence of recurrence at 44 months. Direct long-term radiographic comparison of dentigerous cyst and odontogenic keratocyst reduction following the same decompression protocol remains limited in the published literature. The literature synthesis indicated that decompression typically requires 8 to 24 months, with dentigerous cysts generally demonstrating more favourable radiographic responses than odontogenic keratocysts. Decompression and marsupialisation are non-definitive approaches, as definitive management requires subsequent enucleation of the lesions. These case-based observations suggest that decompression may be sufficient for selected dentigerous cysts, whereas odontogenic keratocysts require prolonged monitoring and are more likely to necessitate secondary surgical intervention. The findings should be interpreted cautiously in view of the very small number of cases.

ObjectiveSepsis is a heterogeneous syndrome, and identifying its subphenotypes may enhance clinical management. Hypothermia may be an indicator of poor outcomes in septic patients.MethodsThis retrospective observational study included septic patients with hypothermia identified from the Medical Information Mart for Intensive Care (MIMIC)-IV database. Group-based trajectory modeling was used to identify temperature trajectory subphenotypes. Cox proportional hazards model, inverse probability of treatment weighting, and doubly robust estimation were used to explore the association between the subphenotypes and clinical outcomes.ResultsA total of 1816 patients were included in the analysis, and their 48-hour temperature trajectories were categorized into three classes. The Cox proportional hazard model revealed that compared with class 2, class 1 was associated with increased 7-day mortality (HR 1.90; 95% CI 1.18-3.07; P = 0.009), whereas class 3 was associated with reduced 28-day mortality (HR 0.81; 95% CI 0.66-1.00; P = 0.045). The doubly robust estimation methods yield similar results.ConclusionsWe identified three temperature trajectories from septic patients with hypothermia, with significant variability in clinical characteristics and outcomes. A better understanding of temperature trajectories may help with the early identification of deteriorating patients with "cold sepsis."

Medial meniscus extrusion (MME) is the displacement of the meniscus beyond the edge of the medial tibial plateau. Proposed etiologies for MME include biologic degeneration of meniscal tissue, the result of a medial meniscus posterior root tear (MMPRT), and the failure of the meniscotibial ligament. Standard MMPRT repairs do not address this MME, as it often persists or worsens postoperatively, even with successful root healing. New techniques, such as centralization sutures, have been developed to supplement the standard MMPRT repair technique. Systematic reviews and randomized controlled trials confirm that the addition of a centralization suture significantly reduces MME, improves joint contact pressures, and enhances patient-reported outcomes. Even though postoperative extrusion still exists after centralization suture use, likely due to the degenerative nature of the meniscus, this represents a shift towards improved knee joint preservation. Continuing progress in this field requires standardization of measurement and diagnosis, establishing the minimal clinically important difference of postoperative extrusion for a successful MMPRT repair, and long-term clinical evidence. This narrative review will explore current understanding of MME, current treatment options, and topics to guide future research.

ObjectiveTo validate a serial multimodal ultrasound (MMUS) protocol for assessing dynamic tibialis anterior changes in detecting intensive care unit-acquired weakness (ICUAW) and to develop a diagnostic algorithm.MethodsIn a prospective cohort of 97 high-risk adults (mean age 60.7±13.7 years; 73.2% male; SOFA score ≥8 for ≥3 days), MMUS quantified structural (thickness, echogenicity), hemodynamic (perfusion grade, peak systolic velocity [PSV]), and mechanical (elastic modulus) parameters of the tibialis anterior at ICU admission (Day 1) and Day 7. ICUAW was diagnosed per American Thoracic Society guidelines. Serum biomarkers (IL-6, PCT, CRP) were correlated with sonographic changes. Diagnostic models were constructed using binary logistic regression and evaluated by ROC analysis.Results31 patients (32.0%) developed ICUAW. By Day 7, the ICUAW group showed greater structural deterioration (echogenicity progression: 54.8% vs. 16.7%, P < 0.001), hemodynamic changes (PSV: 7.60 ± 1.72 vs. 6.35 ± 1.78 cm/s, P < 0.001), and faster stiffness increase (elastic modulus rate: 14.1±12.3% vs. 5.4±6.0%, P < 0.001). Day 7 PSV correlated with IL-6 (r = 0.59), PCT (r = 0.50), and CRP (r = 0.68) (all P < 0.05). A 7-parameter model achieved an AUC of 0.917 (95%CI: 0.857-0.978) with an NPV of 92.4%.ConclusionDynamic MMUS captures ICUAW pathophysiology. The proposed algorithm shows potential as a non-invasive bedside tool for early risk stratification, pending multicenter validation.