Search Results (8,506)

Background: This systematic review evaluates the efficacy of rehabilitation-focused exercise interventions for lumbar degenerative disc disease (DDD), a leading cause of chronic low back pain. Methods: Following PRISMA guidelines, a comprehensive search was conducted across international and regional databases (PubMed, Scopus, Web of Science, Magiran, SID, and Noormags) covering the period from January 2010 to January 2025. The review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) under registration number CRD420251088811. Using keywords such as “lumbar DDD,” “exercise therapy,” and “rehabilitation,” a total of 2495 records were identified. After screening, 20 studies—including clinical trials, quasi-experimental, and experimental designs—met the inclusion criteria and were assessed using the McMaster Critical Review Form for Quantitative Studies. Results: Interventions such as hydrotherapy, core stability training, Pilates, and suspension exercises were found to significantly reduce pain and improve functional outcomes. While multimodal approaches (e.g., aquatic exercise combined with acupuncture) showed positive effects, the comparative studies revealed no significant differences between modalities. Suspension training demonstrated superior efficacy in pain reduction compared to isolated core stability exercises. The methodological quality of included studies ranged from good to excellent, with the majority rated as very good or excellent (McMaster scores: 8 “excellent,” 7 “very good,” and 5 “good”). Common limitations among the studies included methodological heterogeneity, small sample sizes (n = 14–30), and insufficient long-term follow-up. Conclusions: Exercise-based rehabilitation is an effective strategy for managing lumbar DDD. Evidence particularly supports the use of suspension training and aquatic therapy for superior improvements in pain and functional outcomes. Future research should aim to adopt standardized protocols, recruit larger sample sizes, and include extended follow-up periods to produce more robust and generalizable findings. Full article

Background/Objectives: Cancer represents a significant health challenge, with high mortality and morbidity rates. Its diagnosis often triggers chronic stress, adversely affecting patient outcomes. Exercise has emerged as complementary therapy, enhancing treatment adherence and mitigating the side effects of chemotherapy. This study examines the effects of mild exercise during chemotherapy on patient anxiety. Methods: This prospective paired cohort study was conducted in the General Oncology Hospital of Kifisia “Agioi Anargyroi” in Athens, Greece. Adult cancer patients undergoing chemotherapy participated, excluding those with cognitive, hearing, or motor impairments, those who experienced side effects, or those who declined consent. Anxiety was measured before and after a 20-minute exercise routine performed during chemotherapy, using the Greek-translated State–Trait Anxiety Inventory (STAI). The exercise regimen included warm-up, full-body stretching, and cool-down exercises. Pre- and post-exercise scores were analyzed using the Wilcoxon signed-rank test. Results: Forty-five patients (20 women, 25 men; mean age 69.02 ± 10.62 years) with various cancer backgrounds participated. Pre-intervention anxiety levels were in the borderline “moderate” range, dropping post-exercise to the “low” range. Mean STAI scores decreased from 37.73 ± 13.33 to 32.00 ± 14.22 (p < 0.0001), with a medium-large effect size (Cohen’s d for paired samples = −0.646). No significant correlation was found between age and anxiety scores. Discussion: This study found a significant short-term reduction in anxiety, suggesting that incorporating mild exercise during chemotherapy may help in alleviating patient stress. The medium-to-large effect size supports the potential for meaningful short-term benefits. Conclusions: Incorporating mild exercise during chemotherapy may help reduce anxiety and psychological burden. These findings underscore the need for more comprehensive research in larger, more diverse populations to better understand the benefits of incorporating mild exercise during chemotherapy. Full article

Recently, the incidence of diabetes has increased across all socioeconomic groups, with a notable increase in developing countries. Although advances in medical devices have enhanced healthcare accessibility, these benefits remain largely out of reach for individuals residing in remote areas. Concurrently, a variety of devices have been created to detect glucose biomarkers. Among these, microfluidic paper-based sensors have received substantial attention due to their affordability, disposability, and ease of production. Research on microfluidic paper-based glucose sensors has become particularly prominent owing to their considerable potential and wide applicability, especially in the integration of artificial intelligence and machine learning in glucose sensor processing. This review aims to examine recent advancements and progress in the development of microfluidic paper-based glucose sensors over the past five years, highlighting their advantages, limitations, and prospects. The sensors combined with artificial intelligence and machine learning have potential for future applications. Full article

With the development of the automotive industry, the performance of commercial vehicle braking systems is crucial for road traffic safety. However, traditional braking systems are no longer able to meet the growing demand for response speed, control accuracy, and adaptability to complex operating conditions. To this end, this article focuses on improving the braking performance of commercial vehicles, designs and develops a new integrated high-response-speed EBS, explains its structure and function, proposes a pressure delay compensation control method for wire-controlled braking systems, establishes relevant models, designs control processes, and conducts braking simulations. Braking experiments are also conducted on a commercial 6 × 4 tractor on different road surfaces. The research results show that the system has good braking response performance under typical working conditions such as low adhesion, high adhesion, and opposite docking. The braking time is short (for example, the initial braking time at 40 km/h on high-adhesion roads is only 2.209 s, and the initial braking time at 50 km/h on opposite roads is 6.68 s), and the braking safety performance is superior, meeting the requirements of relevant standards. The contribution of this study lies in the proposed time delay compensation control method for wire-controlled braking, which effectively solves the problem of low control accuracy caused by time delay in wire-controlled braking systems. The integrated EBS designed integrates multiple functions, improves driving safety and comfort, and provides strong support for the upgrade of commercial vehicle braking technology, with good application prospects. Full article

Lactoferrin (LF) is an 80 kDa iron-binding glycoprotein primarily found in milk, saliva, tears, and nasal secretions. LF is well known for its antibacterial and immunomodulatory effects. However, the extraction of LF from milk is inadequate for large-scale therapeutic applications, presenting a challenge for economic mass production. Recombinant protein expression systems offer a solution to overcome this challenge and efficient production of LF. This review discusses recent progress in the translational research of LF gene transfer and biopharming, focusing on different expression systems such as bacteria, yeast, filamentous fungi, transgenic crops, and animals as well as purification methods. The optimization of expression yields, prospects for genetic engineering, and biotechnology to enhance LF production for biomedical applications are emphasized. This review systematically sourced the literature from 1987 to 2025 from leading scientific databases, including PubMed, Scopus, Web of Science, and Google Scholar. Despite ongoing debates, progress in this field indicates a viable path towards the effective use of LF in therapeutic settings. Full article

Hyperspectral remote sensing plays a crucial role in guiding and supporting various mineral prospecting activities. Combined with artificial intelligence, hyperspectral remote sensing technology becomes a powerful and versatile tool for a wide range of mineral exploration activities. This study investigates the effectiveness of ensemble learning (EL) algorithms for lithological classification and mineral exploration using EnMAP hyperspectral imagery (HSI) in a semi-arid region. The Moroccan Anti-Atlas mountainous region is known for its complex geology, high mineral potential and rugged terrain, making it a challenging for mineral exploration. This research applies core and heterogeneous ensemble learning methods, i.e., boosting, stacking, voting, bagging, blending, and weighting to improve the accuracy and robustness of lithological classification and mapping in the Moroccan Anti-Atlas mountainous region. Several state-of-the-art models, including support vector machines (SVMs), random forests (RFs), k-nearest neighbors (k-NNs), multi-layer perceptrons (MLPs), extra trees (ETs) and extreme gradient boosting (XGBoost), were evaluated and used as individual and ensemble classifiers. The results show that the EL methods clearly outperform (single) base classifiers. The potential of EL methods to improve the accuracy of HSI-based classification is emphasized by an optimal blending model that achieves the highest overall accuracy (96.69%). The heterogeneous EL models exhibit better generalization ability than the baseline (single) ML models in lithological classification. The current study contributes to a more reliable assessment of resources in mountainous and semi-arid regions by providing accurate delineation of lithological units for mineral exploration objectives. Full article

Nanotechnologies bring a rapid paradigm shift in hard and soft bone tissue regeneration (BTR) through unprecedented control over the nanoscale structures and chemistry of biocompatible materials to regenerate the intricate architecture and functional adaptability of bone. This review focuses on the transformative analyses and prospects of current and next-generation nanomaterials in designing bioactive bone scaffolds, emphasizing hierarchical architecture, mechanical resilience, and regenerative precision. Mainly, this review elucidated the innovative findings, new capabilities, unmet challenges, and possible future opportunities associated with biocompatible inorganic ceramics (e.g., phosphates, metallic oxides) and the United States Food and Drug Administration (USFDA) approved synthetic polymers, including their nanoscale structures. Furthermore, this review demonstrates the newly available approaches for achieving customized standard porosity, mechanical strengths, and accelerated bioactivity to construct an optimized nanomaterial-oriented scaffold. Numerous strategies including three-dimensional bioprinting, electro-spinning techniques and meticulous nanomaterials (NMs) fabrication are well established to achieve radical scientific precision in BTR engineering. The contemporary research is unceasingly decoding the pathways for spatial and temporal release of osteoinductive agents to enhance targeted therapy and prompt healing processes. Additionally, successful material design and integration of an osteoinductive and osteoconductive agents with the blend of contemporary technologies will bring radical success in this field. Furthermore, machine learning (ML) and artificial intelligence (AI) can further decode the current complexities of material design for BTR, notwithstanding the fact that these methods call for an in-depth understanding of bone composition, relationships and impacts on biochemical processes, distribution of stem cells on the matrix, and functionalization strategies of NMs for better scaffold development. Overall, this review integrated important technological progress with ethical considerations, aiming for a future where nanotechnology-facilitated bone regeneration is boosted by enhanced functionality, safety, inclusivity, and long-term environmental responsibility. Therefore, the assimilation of a specialized research design, while upholding ethical standards, will elucidate the challenge and questions we are presently encountering. Full article

Coffee is one of the most widely consumed beverages globally, with over 60% of Americans drinking it daily. This review examines coffee’s multifaceted impact on health and well-being, drawing on decades of research. Overall, the consensus is that moderate coffee intake is more beneficial than harmful across a wide range of health outcomes. Numerous large-scale, prospective cohort studies from around the world have consistently shown that moderate coffee consumption—typically three to five cups per day—is associated with reduced overall mortality and lower risk of major diseases such as cardiovascular diseases, diabetes, stroke, respiratory conditions, cognitive decline, and potentially several types of cancer, including liver and uterine cancers. Both caffeinated and decaffeinated coffee have shown benefits. The addition of sugar and cream to coffee may attenuate coffee’s positive health effects. Despite historical concerns, coffee consumption is not linked to increased risks of cancer, hypertension, or arrhythmia. However, some concerns remain. For pregnant women, coffee consumption should be limited to lower amounts, such that the daily intake of caffeine does not exceed 200 mg/day. Also, excessive caffeinated coffee intake may cause anxiety or sleep disturbances. Coffee’s health-promoting mechanisms include improved glucose balancing, increased physical activity, increased fat oxidation, improved lung function, and reduced inflammation. Beyond mortality and chronic diseases, coffee consumption affects many aspects of well-being: it supports hydration, boosts mental acuity, enhances physical performance, and may aid bowel recovery after surgery. While the field is well-studied via long-term observational cohorts, future research should focus on randomized controlled trials, Mendelian randomization studies, and granular analyses of coffee types and additives. Full article

This research aimed to evaluate the impact of using brick waste powder (BWP) and varying lengths of polyester fibers (PFs) on the performance properties of asphalt concrete (AC) mixtures. BWP was utilized as a replacement for traditional limestone powder (LS) filler, while PFs of three lengths (3 mm, 8 mm, and 15 mm) were introduced. The study employed the response surface methodology (RSM) for experimental design and analysis of variance (ANOVA) to identify the influence of BWP and PF on the selected performance indicators. These indicators included bulk density, air voids, voids in the mineral aggregate, voids filled with asphalt, Marshall stability, Marshall flow, Marshall quotient, indirect tensile strength, wet tensile strength, and the tensile strength ratio. The findings demonstrated that BWP improved moisture resistance and the mechanical performance of AC mixes. Moreover, incorporating PF alongside BWP further enhanced these properties, resulting in superior overall performance. Using multi-objective optimization through RSM-based empirical models, the study identified the optimal PF length of 5 mm in combination with BWP for achieving the best AC properties. Validation experiments confirmed the accuracy of the predicted results, with an error margin of less than 8%. The study emphasizes the intriguing prospect of BWP and PF as sustainable alternatives for improving the durability, mechanical characteristics, and cost-efficiency of asphalt pavements. Full article

This study assessed the seroprevalence of anti-Anisakis simplex antibodies in Norwegian patients with inflammatory bowel disease (IBD), specifically ulcerative colitis (UC) and Crohn’s disease (CD), compared with healthy controls. Associations between anti-A. simplex antibody positivity and clinical or laboratory parameters in IBD were also explored. A total of 86 UC patients, 68 CD patients, and 41 healthy controls were prospectively enrolled from four Norwegian hospitals (2013–2022). Diagnosis and disease activity were established using standard clinical, endoscopic, and biomarker criteria. Serum samples were analyzed for total Ig, IgG, IgM, IgA, and IgE antibodies against A. simplex and Pseudoterranova decipiens using ELISA. Anti-A. simplex IgG seroprevalence was 4.9% in controls and 3.2% in IBD (3.5% UC, 2.9% CD). IgM seroprevalence was 0% in all groups. IgA seroprevalence was higher in IBD (16.2%) than controls (4.9%), with 14.0% in UC and 19.1% in CD. IgE seroprevalence was low across all groups. Smoking correlated with lower antibody levels and higher surgery rates. In UC, higher anti-A. simplex IgG and IgE levels were associated with milder disease and better prognosis. Anti-TNFα and azathioprine treatments were linked to higher anti-A. simplex IgA. Norwegian UC and CD patients had significantly higher anti-A. simplex total Ig and IgA seroprevalence than healthy controls, indicating increased exposure or immune response. Anti-A. simplex IgG and IgE may serve as markers of clinical activity in UC. Further research is warranted to clarify the clinical significance of these findings. Full article

Sunflower (Helianthus annuus L.) is an important oilseed crop in Northwest China, exhibiting resistance to salt and drought. Mining its excellent tolerance genes can be used for breeding. However, the current platforms for identifying gene function in sunflower is inadequate. The transient transformation system, which can rapidly validate gene function, shows promising prospects in research. In this study, we established an efficient transient expression transformation system for sunflower using three methods: Agrobacterium-mediated infiltration, injection, and ultrasonic-vacuum. The detailed procedures were as follows: Agrobacterium GV3101 carrying a GUS reporter gene on the pBI121 vector with an OD₆₀₀ of 0.8 as the bacterial suspension and 0.02% Silwet L-77 as the surfactant were utilized in all three approaches. For the infiltration method, seedlings grown hydroponically for 3 days were immersed in a bacterial suspension containing 0.02% Silwet L-77 for 2 h; for the injection method, the same solution was injected into the cotyledons of seedlings grown in soil for 4 to 6 days. Subsequently, the seedlings were cultured in the dark at room temperature for three days; for the ultrasonic-vacuum method, seedlings cultured in Petri dishes for 3 days were first subjected to ultrasonication at 40 kHz for 1 min, followed by vacuum infiltration at 0.05 kPa for 5–10 min. Agrobacterium-mediated transient transformation efficiency achieved by the three methods exceeded 90%, with gene expression being sustained for at least 6 days. Next, we employed the infiltration-based sunflower transient transformation technology with the Arabidopsis stable transformation platform to confirm salt and drought stress tolerance of candidate gene HaNAC76 from sunflower responding to various abiotic stresses. Altogether, this study successfully established an Agrobacterium-mediated transient transformation system for sunflower using these three methods, which can rapidly identify gene function and explore the molecular mechanisms underlying sunflower’s resistance traits. Full article

Variable-thrust liquid rocket engines are essential for precision landing in deep-space exploration, reusable launch vehicle recovery, high-accuracy orbital maneuvers, and emergency obstacle evasions of space drones. However, with the increasingly complex space missions, challenges remain with the development of different technical schemes. In view of these issues, this paper systematically reviews the technology’s evolution through mechanical throttling, electromechanical precision regulation, and commercial space-driven deep throttling. Then, the development of key variable thrust technologies for liquid rocket engines is summarized from the perspective of thrust regulation and control strategy. For instance, thrust regulation requires synergistic flow control devices and adjustable pintle injectors to dynamically match flow rates with injection pressure drops, ensuring combustion stability across wide thrust ranges—particularly under extreme conditions during space drones’ high-maneuver orbital adjustments—though pintle injector optimization for such scenarios remains challenging. System control must address strong multivariable coupling, response delays, and high-disturbance environments, as well as bottlenecks in sensor reliability and nonlinear modeling. Furthermore, prospects are made in response to the research progress, and breakthroughs are required in cryogenic wide-range flow regulation for liquid oxygen-methane propellants, combustion stability during deep throttling, and AI-based intelligent control to support space drones’ autonomous orbital transfer, rapid reusability, and on-demand trajectory correction in complex deep-space missions. Full article

The high-proportion integration of renewable energy sources, represented by wind power and photovoltaics, into active distribution networks (ADNs) can effectively alleviate the pressure associated with advancing China’s dual-carbon goals. However, the high uncertainty in renewable energy output leads to increased system voltage fluctuations and localized voltage violations, posing safety challenges. Consequently, research on optimal dispatch for ADNs with a high penetration of renewable energy has become a current focal point. This paper provides a comprehensive review of research in this domain over the past decade. Initially, it analyzes the voltage impact patterns and control principles in distribution networks under varying levels of renewable energy penetration. Subsequently, it introduces optimization dispatch models for ADNs that focus on three key objectives: safety, economy, and low carbon emissions. Furthermore, addressing the challenge of solving non-convex and nonlinear models, the paper highlights model reformulation strategies such as semidefinite relaxation, second-order cone relaxation, and convex inner approximation methods, along with summarizing relevant intelligent solution algorithms. Additionally, in response to the high uncertainty of renewable energy output, it reviews stochastic optimization dispatch strategies for ADNs, encompassing single-stage, two-stage, and multi-stage approaches. Meanwhile, given the promising prospects of large-scale deep reinforcement learning models in the power sector, their applications in ADN optimization dispatch are also reviewed. Finally, the paper outlines potential future research directions for ADN optimization dispatch. Full article

Ozone (O₃) occurs in nature as a chemical compound made of three oxygen atoms. It is an unstable, highly oxidative gas that rapidly decomposes into oxygen. The therapeutic use of O₃ dates back to the beginning of the 20th century and is currently based on the application of low doses, inducing a moderate oxidative stress that stimulates the antioxidant cellular defenses without causing cell damage. Low O₃ doses also induce anti-inflammatory and regenerative effects, and their anticancer potential is under investigation. In addition, the oxidative properties of O₃ make it an excellent antibacterial, antimycotic, and antiviral agent. Thanks to these properties, O₃ is currently widely used in several medical fields. However, its chemical instability represents an application limit, and ozonated oil is the only stabilized form of medical O₃. In recent years, novel O₃ formulations have been proposed for their sustained and more efficient administration, based on nanotechnology. This review offers an overview of the nanocarriers designed for the delivery of medical O₃, and of their therapeutic applications. The reviewed articles demonstrate that research is active and productive, though it is a rather new entry in the nanotechnological field. Liposomes, nanobubbles, nanoconstructed hydrogels, polymeric nanoparticles, and niosomes were designed to deliver O₃ and have been proven to exert antiseptic, anticancer, and pro-regenerative effects when administered in vitro and in vivo. Improving the therapeutic administration of O₃ through nanocarriers is a just-started challenge, and multiple prospects may be foreseen. Full article

With the rapid increase in global lithium demand, the exploration of newly discovered lithium in the bauxite of the Wenshan area in southeastern Yunnan has become increasingly important. However, the current research on clay-type lithium in the Wenshan area has primarily focused on local exploration, and large-scale predictive metallogenic studies remain limited. To address this, this study utilized multi-source remote sensing data from ZY1-02D and ASTER, combined with ALOS 12.5 m DEM and Sentinel-2 imagery, to carry out remote sensing mineral identification, structural interpretation, and prospectivity mapping for clay-type lithium in the Wenshan area. This study indicates that clay-type lithium in the Wenshan area is controlled by NW, EW, and NE linear structures and are mainly distributed in the region from north of the Wenshan–Malipo fault to south of the Guangnan–Funing fault. High-value areas of iron-rich silicates and iron–magnesium minerals revealed by ASTER data indicate lithium enrichment, while montmorillonite and cookeite identification by ZY1-02D have strong indicative significance for lithium. Field verification samples show the highest Li₂O content reaching 11,150 μg/g, with six samples meeting the comprehensive utilization criteria for lithium in bauxite (Li₂O ≥ 500 μg/g) and also showing an enrichment of rare earth elements (REEs) and gallium (Ga). By integrating stratigraphic, structural, mineral identification, geochemical characteristics, and field verification data, ten mineral exploration target areas were delineated. This study validates the effectiveness of remote sensing technology in the exploration of clay-type lithium and provides an applicable workflow for similar environments worldwide. Full article