Search Results (22,879)

Objectives: This systematic literature review aimed to identify studies assessing the clinical efficacy and real-world effectiveness of current and emerging treatments for Fabry disease. Methods: Searches of the MEDLINE, EMBASE, and Cochrane library databases, as well as relevant congress proceedings, were conducted to identify publications reporting on studies in patients of any age, sex, race, or ethnicity who received any approved or experimental treatment for Fabry disease, published before 17 June 2024. Results: Of 1901 publications screened, 247 reported data on renal, cardiac, cerebrovascular, and disease severity outcomes from 231 studies. The majority of reported studies were observational in nature (n = 154; 67%) and involved only adults (n = 176; 76%). Study designs and patient populations were highly heterogeneous, and cross-study conclusions about the effectiveness of different therapies could not be made. Enzyme replacement therapy (ERT) with agalsidase alfa or agalsidase beta stabilized renal function and cardiac structure in patients with Fabry disease. Early initiation of ERT in childhood or young adulthood was associated with better renal and cardiac outcomes than treatment initiation at a later age. The small number of comparator studies of agalsidase alfa and agalsidase beta suggested similar efficacy. Patients treated with migalastat and pegunigalsidase alfa also maintained stable renal function and cardiac structure. Conclusions: Overall, current treatments slow the progression of renal and cardiac decline in patients with Fabry disease. Large cohort studies with long-term follow-up and baseline stratification based on clinical phenotype are needed to address evidence gaps and provide clinicians with robust data to inform treatment decisions. Full article

The spread of COVID-19 is influenced by multiple factors, including control policies, virus characteristics, individual behaviors, and environmental conditions, exhibiting highly complex nonlinear dynamic features. The time series of new confirmed cases shows significant nonlinearity and non-stationarity. Traditional prediction methods that rely solely on one-dimensional case data struggle to capture the multi-dimensional features of the data and are limited in handling nonlinear and non-stationary characteristics. Their prediction accuracy and generalization capabilities remain insufficient, and most existing studies focus on single-step forecasting, with limited attention to multi-step prediction. To address these challenges, this paper proposes a multi-module fusion prediction model—TSMixer-BiKSA network—that integrates multi-feature inputs, Variational Mode Decomposition (VMD), and a dual-branch parallel architecture for 1- to 3-day-ahead multi-step forecasting of new COVID-19 cases. First, variables highly correlated with the target sequence are selected through correlation analysis to construct a feature matrix, which serves as one input branch. Simultaneously, the case sequence is decomposed using VMD to extract low-complexity, highly regular multi-scale modal components as the other input branch, enhancing the model’s ability to perceive and represent multi-source information. The two input branches are then processed in parallel by the TSMixer-BiKSA network model. Specifically, the TSMixer module employs a multilayer perceptron (MLP) structure to alternately model along the temporal and feature dimensions, capturing cross-time and cross-variable dependencies. The BiGRU module extracts bidirectional dynamic features of the sequence, improving long-term dependency modeling. The KAN module introduces hierarchical nonlinear transformations to enhance high-order feature interactions. Finally, the SA attention mechanism enables the adaptive weighted fusion of multi-source information, reinforcing inter-module synergy and enhancing the overall feature extraction and representation capability. Experimental results based on COVID-19 case data from Italy and the United States demonstrate that the proposed model significantly outperforms existing mainstream methods across various error metrics, achieving higher prediction accuracy and robustness. Full article

Life Cycle Impact Assessments (LCIAs) examine the environmental impacts of products using life cycle inventories (LCIs) of quantified inputs and outputs of a product through its life cycle. Currently, estimated impacts from mining are dominated by long-term metal release from tailings due to inaccurate assumptions regarding metal release and transport within and from mine materials. A conceptual model approach is proposed to support the development of a new database of LCI data, applying mechanistic processes required for the release and transport of metals through tailings and categorizing model inputs into ‘bins’. The binning approach argues for accuracy over precision, noting that precise metal release rates are likely impossible with the often-limited data available. Three case studies show the range of forecasted metal release rates, where even after decades of monitoring within the tailings and underlying aquifer, metal release rates span several orders of magnitude (<100 mg/L to >100,000 mg/L sulfate at the Faro Mine). The proposed tool may be useful for the development of a new database of LCI data, as well as to analyze mine’s regional considerations during designs for risk evaluation, management and control prior to development, when data is also scarce. Full article

Rapid global urbanization poses complex challenges that demand advanced data-driven forecasting solutions for smart cities. Traditional statistical and standalone Long Short-Term Memory (LSTM) models often struggle to capture non-linear dynamics and long-term dependencies in urban time-series data. This review critically examines hybrid LSTM models that integrate LSTM with complementary algorithms, including CNN, GRU, ARIMA, and SVM. These hybrid architectures aim to enhance prediction accuracy, integrate diverse data sources, and improve computational efficiency. This study systematically reviews principles, trends, and real-world applications, quantitatively evaluating hybrid LSTM models using performance metrics such as mean absolute error (MAE), root mean square error (RMSE), and the coefficient of determination (R²), while identifying key study limitations. The case studies considered include traffic management, environmental monitoring, energy forecasting, public health, infrastructure assessment, and urban waste management. For example, hybrid models have achieved substantial accuracy improvements in traffic congestion forecasting, reducing their mean absolute error by up to 29%. Despite the inherent challenges related to structural complexity, interpretability, and data requirements, ongoing research on attention mechanisms, model compression, and explainable AI has significantly mitigated these limitations. Thus, hybrid LSTM models have emerged as vital analytical tools capable of robust spatiotemporal prediction, effectively supporting sustainable urban development and data-driven decision-making in evolving smart city environments. Full article

Objective: Mandibular expansion remains controversial due to concerns about long-term stability and effectiveness. While maxillary expansion protocols are well established, investigations into mandibular expansion remain limited. This study evaluates the efficacy of the Clara Expander appliance for mandibular expansion in early mixed dentition, assessing skeletal and dental changes using cone-beam computed tomography (CBCT). Materials and Methods: This prospective longitudinal study was conducted in Valencia, Spain, with a population of healthy children aged 6–10 years presenting negative osseodental mandibular discrepancies. CBCT scans were performed before and after treatment to evaluate mandibular dimensional changes, with statistical analyses conducted and a significance threshold of p < 0.05. A total of seven subjects were included in this case series, allowing for a descriptive analysis of treatment outcomes within this specific clinical context. Results: CBCT analysis confirmed significant mandibular expansion following the Clara Expander protocol. Post-treatment findings showed statistically significant increases in dental parameters, including Tooth 6 (furcation, MD = −2.25; p = 0.015), Tooth E (furcation, cementoenamel junction, vestibular, lingual, all p < 0.001), Tooth D (all variables significant), and Tooth C (furcation, MD = −4.18; p = 0.002; cementoenamel junction, MD = −3.56; p = 0.015). Conclusions: The Clara Expander appliance effectively promotes skeletal and dental mandibular expansion, with minimal adverse effects. Its user-friendly, non-invasive design enhances patient compliance and outcomes, contributing valuable data to the field of mandibular expansion and informing future research and clinical applications. Full article

Background: Heart failure (HF) is frequently associated with skeletal muscle wasting, reduced functional capacity, and malnutrition. High-protein diets offer a promising nutritional intervention to improve these outcomes in individuals with HF. Objective: This systematic review evaluated randomized controlled trials of high-protein dietary interventions in HF populations, with emphasis on intervention characteristics, quantitative benefits, and risk of bias. Methods: We conducted a comprehensive search in PubMed, MEDLINE, Embase, and Cochrane CENTRAL from inception to June 2025. Eligible studies enrolled adults (≥18 years) with HF, implemented high-protein regimens (≥1.1 g/kg/day or ~25–30% of energy), and reported on functional capacity, body composition, muscle strength, clinical outcomes, or biochemical markers. Two reviewers independently screened, extracted data, and assessed bias (Cochrane RoB 2). Heterogeneity in dosing, duration, and outcomes precluded meta-analysis; we therefore provide a narrative synthesis. Results: Ten trials (nine randomized controlled trials, one pilot) involving 1080 patients (median n = 38; range 21–652) were included. High-protein interventions yielded mean improvements in six-minute walk distance of +32 ± 14 m, lean body mass gain of +1.6 ± 0.9 kg, and 9 ± 4% enhancement in quality-of-life scores; muscle strength effects varied from −2% to +11%. Two studies reported an 18% reduction in HF readmissions (p < 0.05). The risk-of-bias assessment identified two low-risk, three moderate-risk, and one high-risk study. Key limitations include small sample sizes, varied protein dosing (1.1–1.5 g/kg/day), short follow-up (2–6 months), and outcome heterogeneity. Conclusions: High-protein dietary strategies appear to confer modest, clinically relevant gains in functional capacity, nutritional status, and HF readmission risk. Larger, well-powered trials with standardized dosing and longer follow-up are necessary to establish optimal protein targets, long-term efficacy, and safety. Full article

Pain is a common condition among older adults and a key factor influencing daily functioning. This cross-sectional study examined how pain presence and distribution (no pain, localized pain [LP], and widespread pain [WP]) are related to limitations in Basic and Instrumental Activities of Daily Living (BADLs and IADLs). Data were drawn from the Survey of Health, Aging, and Retirement in Europe (SHARE) Wave 9, including 68,839 participants aged 50 or older. A clear gradient of functional limitation was observed: Individuals with WP reported the highest number of limitations, followed by those with LP, while those with no pain showed minimal impairment. These associations remained significant after adjusting for age, sex, cognitive status, physical health, and psychosocial factors, with adjusted prevalence ratios (aPRs) for WP of 1.77 for BADLs and 1.22 for IADLs (p < 0.001). Notably, depression, perceived loneliness, long-term illness, physical inactivity, and mobility limitations were especially relevant among participants with WP. The findings suggest the clinical value of assessing and implementing interventions not only in the presence but also in the extent of pain to better identify individuals at greater risk of losing independence in daily life. Full article

Carbon fiber-reinforced polymer (CFRP) laminates have been widely coated on aged and damaged structures for recovering or enhancing their structural performance. The health conditions of the coated composite structures have been given high attention, as they are critically important for assessing operational safety and residual service life. However, the current problem is the lack of an efficient, long-term, and stable monitoring technique to characterize the structural behavior of coated composite structures in the whole life cycle. For this reason, bare and packaged fiber Bragg grating (FBG) sensors have been specially developed and designed in sensing networks to monitor the structural performance of CFRP-coated composite beams under different loads. Some optical fibers have also been inserted in the CFRP laminates to configure the smart CFRP component. Detailed data interpretation has been conducted to declare the strengthening process and effect. Finite element simulation and simplified theoretical analysis have been conducted to validate the experimental testing results and the deformation profiles of steel beams before and after the CFRP coating has been carefully checked. Results indicate that the proposed FBG sensors and sensing layout can accurately reflect the structural performance of the composite beam structure, and the CFRP coating can share partial loads, which finally leads to the downward shift in the centroidal axis, with a value of about 10 mm. The externally bonded sensors generally show good stability and high sensitivity to the applied load and temperature-induced inner stress variation. The study provides a straightforward instruction for the establishment of a structural health monitoring system for CFRP-coated composite structures in the whole life cycle. Full article

Maintaining body symmetry in sports characterized by high lateralization is crucial for optimizing long-term athletic performance and mitigating injury risk. This study aimed to evaluate the extent of morphological asymmetry in anthropometric features among elite professional fencers. Additionally, the presence of functional asymmetry and its associations with morphological asymmetry were assessed. Thirty-two Polish adult female fencers, aged 18–33 yrs, were examined. Data collection involved a questionnaire survey, anthropometric measurements, calculation of anthropological indices, and assessment of functional asymmetry. For the 24 bilateral anthropometric features, small differences were found in seven characteristics: foot length, subscapular skinfold thickness, upper arm circumference, minimum and maximum forearm circumference, upper limb length, and arm circumference in tension. Morphological asymmetry index did not exceed 5%. Left-sided lateralization of either the upper or lower limbs was associated with significantly high asymmetry, specifically indicating larger minimum forearm circumferences in the right limb. Continuous, individualized monitoring of morphological asymmetry and its direction in athletes is essential, demanding concurrent consideration of functional lateralization. This ongoing assessment establishes a critical baseline for evaluating training adaptations, reducing injury susceptibility, and optimizing rehabilitation strategies. Deeper investigation of symmetry within non-dominant limbs is warranted to enhance our understanding. Full article

Follicular lymphoma (FL) is one of the most common types of non-Hodgkin’s lymphomas. The tumor is characterized by a wide range of clinical manifestations, ranging from indolent forms to early transformation and progression with a poor prognosis. The search for clinically significant genetic changes is essential for personalized risk assessment and treatment selection. The CREBBP gene is frequently mutated in this type of lymphoma, with changes occurring at the level of the earliest tumor precursor cells. However, the prognostic and diagnostic significance of the CREBBP gene mutation status in FL has not been fully established. In this study, we analyzed sequencing data of exons 22–30 of the CREBBP gene in 86 samples from patients with different grades of FL (1–3B), including those in the 3A–3B subgroup without the t(14;18) translocation. We also investigated the prognostic significance of CREBBP gene mutations in relation to the treatment options, namely high-dose chemotherapy with autologous hematopoietic stem cell transplantation (HDCT/auto-HSCT) and conventional chemotherapy programs (CCT). It was found that FL patients with a single missense mutation in the KAT domain of the CREBBP gene experienced an extremely low number of early adverse events related to lymphoma and had better long-term survival rates, regardless of treatment option. In contrast, when comparing patients with FL without a missense mutation in the KAT domain or those with multiple mutations in the CREBBP gene, overall and progression free survival were worse, and early progression and histological transformation were more common. Compared to standard therapy, patients who underwent HDCT/auto-HSCT in the FL 1–3B (14;18)-positive group without a single missense mutation in the KAT domain had better survival rates and lower rates of transformation and early progression. In addition, among patients with FL 3A–3B (14;18)-negative, we found that there were no cases of a missense mutation in the KAT domain of the CREBBP gene. This suggests that a single missense mutation in the CREBBP gene may be a feature that discriminates 14;18-positive FL with a favorable prognosis from a high-risk disease. FL 3A–3B (14;18)-negative may represent a distinct variant with different biology and underlying mechanisms of development compared to classical FL. Full article

As Environmental, Social, and Governance (ESG) gradually become the common language for sustainable development of international society and international cooperation in China, it is worth discussing whether ESG practices can help Chinese enterprises shape a responsible international image, overcome the liability of foreignness (LOF) and improve the long-term performance of cross-border mergers and acquisitions (M&As). On the basis of theoretical discussion, combined with the panel data of cross-border M&As of China A-share listed companies from 2010 to 2021, this paper empirically examines that the ESG performance of acquirers has a significant positive impact on the long-term performance of cross-border mergers and acquisitions (M&As) of China A-share listed companies. Furthermore, the ESG performance of environment and governance dimensions and heavily polluting enterprises has stronger incentive effects on the long-term performance of cross-border M&As. The ESG performance of the acquirer positively affects the long-term performance of cross-border M&As of China A-share listed companies by acquiring capital market resources, product market competitiveness, regulatory legitimacy, and enhancing internal synergy. Full article

Background: Myocarditis is associated with increased mortality due to complications such as cardiogenic shock and arrhythmia. Trends of myocarditis-related mortality in the United States, along with demographic and regional disparities and changes during the COVID-19 pandemic, are unknown. Methods: We used the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database to extract data for myocarditis deaths from 1999 to 2023. The Joinpoint Regression Program was used to analyze long-term trends in mortality, and R Studio (version 4.4.1) was used to calculate expected and excess mortality for 2020 to 2023. Results: There were 33,016 myocarditis-related deaths from 1999 to 2023. The age-adjusted mortality rate (AAMR) of myocarditis deaths decreased by 46.08% from 7.40 (95% CI: 7.04–7.76) in 1999 to 3.99 (95% CI: 3.74–4.23) in 2019, with an APC of −2.59 (95% CI: −2.97 to −2.24). From 2019 to 2021, the AAMR increased by 46.62% to 5.85 (95% CI: 5.56–6.14) by 2021 (2019–2021 APC 22.3%*), reversing the gains of the previous two decades. By 2023, the AAMR recovered to 4.33 (95% CI: 4.09 to 4.58), though mortality was still higher than expected from pre-pandemic trends. From 2020 to 2023, there were 40.12% more deaths than expected, with 54.94% higher mortality in 2021. Briefly, 70.33% of excess myocarditis-related deaths also had COVID-19, with a peak of 76.15% of excess myocarditis deaths in 2021 being reported as involving COVID-19 infection. Significant disparities in mortality trends persisted, with males, NH Black or African Americans, and the elderly having higher mortality rates. Conclusions: Myocarditis mortality decreased in the United States from 1999 to 2019 but significantly increased during the COVID-19 pandemic years 2020 and 2021. At the height of the pandemic, COVID-19 infection contributed to almost three-quarters of excess myocarditis mortality. Significant disparities in myocarditis mortality persisted from 1999 to 2023. Full article

Background: Endometrial cancer (EC) is the most common gynecological malignancy, increasingly affecting premenopausal women. While hysterectomy is the standard treatment, it eliminates reproductive potential, highlighting the need for effective fertility-sparing alternatives. Current ESHRE/ESGO/ESGE guidelines recommend progestin-based therapies, often with hysteroscopic resection. However, these are based on limited pharmacological options and moderate to low-quality evidence. Novel and combination therapies have shown promise but remain absent from current clinical guidelines. This review aims to evaluate the efficacy and safety of fertility-preserving treatments for early-stage EC, emphasizing the need to update current strategies based on emerging data. Methods: A systematic review and meta-analysis will follow PRISMA guidelines and the Cochrane Handbook. Eligible studies, including randomized and non-randomized designs, will assess fertility-preserving treatments for early-stage EC. Data will be extracted on complete response, recurrence, and long-term fertility outcomes. The GRADE system will assess evidence certainty. Risk of bias will be evaluated using RoB 2 for RCTs and ROBINS-I for non-randomized studies. Meta-analysis will be performed if sufficient data are available. Conclusions: This review will provide a comprehensive analysis of fertility-sparing treatments for early-stage EC, support personalized strategies, identify evidence gaps, and guide future research. Trial registration—Prospero: CRD420251032161. Full article

This study conducted uniaxial creep tests on coal samples under both natural and water-saturated conditions for durations of about 180 days per sample to study the stability of coal pillar dams of the Daliuta Coal Mine underground reservoir. Combined with synchronized acoustic emission (AE) monitoring, the research systematically revealed the time-dependent deformation mechanisms and damage evolution laws of coal under prolonged water immersion and natural conditions. The results indicate that water-immersed coal exhibits a unique negative creep phenomenon at the initial stage, with the strain rate down to −0.00086%/d, attributed to non-uniform pore compaction and elastic rebound effects. During the steady-state creep phase, the creep rates under water-immersed and natural conditions were comparable. However, water immersion led to an 11.4% attenuation in elastic modulus, decreasing from 2300 MPa to 2037 MPa. Water immersion would also suppress AE activity, leading to the average daily AE events of 128, which is only 25% of that under natural conditions. In the accelerating creep stage, the AE event rate surged abruptly, validating its potential as an early warning indicator for coal pillar instability. Based on the identified long-term strength of the coal sample, it is recommended to maintain operational loads below the threshold of 9 MPa. This research provides crucial theoretical foundations and experimental data for optimizing the design and safety monitoring of coal pillar dams in CMURs. Full article

The real-time acquisition of an accurate underwater sound velocity profile (SSP) is crucial for tracking the propagation trajectory of underwater acoustic signals, making it play a key role in ocean communication positioning. SSPs can be directly measured by instruments or inverted leveraging sound field data. Although measurement techniques provide a good accuracy, they are constrained by limited spatial coverage and require a substantial time investment. The inversion method based on the real-time measurement of acoustic field data improves operational efficiency but loses the accuracy of SSP estimation and suffers from limited spatial applicability due to its stringent requirements for ocean observation infrastructures. To achieve accurate long-term ocean SSP estimation independent of real-time underwater data measurements, we propose a semi-transformer neural network (STNet) specifically designed for simulating sound velocity distribution patterns from the perspective of time series prediction. The proposed network architecture incorporates an optimized self-attention mechanism to effectively capture long-range temporal dependencies within historical sound velocity time-series data, facilitating an accurate estimation of current SSPs or prediction of future SSPs. Through the architectural optimization of the transformer framework and integration of a time encoding mechanism, STNet could effectively improve computational efficiency. For long-term forecasting (using the Pacific Ocean as a case study), STNet achieved an annual average RMSE of 0.5811 m/s, outperforming the best baseline model, H-LSTM, by 26%. In short-term forecasting for the South China Sea, STNet further reduced the RMSE to 0.1385 m/s, demonstrating a 51% improvement over H-LSTM. Comparative experimental results revealed that STNet outperformed state-of-the-art models in predictive accuracy and maintained good computational efficiency, demonstrating its potential for enabling accurate long-term full-depth ocean SSP forecasting. Full article