Search Results (113)

This systematic review, registered in PROSPERO (CRD42025101243), aimed to evaluate how specific badminton shoe design features influence lower-limb biomechanics, injury risk, and sport-specific performance. A comprehensive search in six databases yielded 445 studies, from which 10 met inclusion criteria after duplicate removal and eligibility screening. The reviewed studies focused on modifications involving forefoot bending stiffness, torsional stiffness, lateral-wedge hardness, insole and midsole hardness, sole structure, and heel curvature. The most consistent biomechanical benefits were associated with moderate levels of forefoot and torsional stiffness (e.g., 60D) and rounded heel designs. Increased forefoot bending stiffness was associated with reduced foot torsion and knee loading during forward lunges. Torsional stiffness around 60D provided favorable ankle support and reduced knee abduction, suggesting potential protection against ligament strain. Rounded heels reduced vertical impact forces and promoted smoother knee–ankle coordination, especially in experienced athletes. Lateral-wedge designs improved movement efficiency by reducing contact time and enhancing joint stiffness. Harder midsoles, however, resulted in increased impact forces upon landing. Excessive stiffness in any component may restrict joint mobility and responsiveness. Studies included 127 male-dominated (aged 18–28) competitive athletes, assessing kinematics, impact forces, and coordination during sport-specific tasks. The reviewed studies predominantly involved male participants, with little attention to sex-specific biomechanical differences such as joint alignment and foot structure. Differences in testing methods and movement tasks further limited direct comparisons. Future research should explore real-game biomechanics, include diverse athlete populations, and investigate long-term adaptations. These efforts will contribute to the development of performance-enhancing, injury-reducing badminton shoes tailored to the unique demands of the sport. Full article

Deformable lung CT registration plays a crucial role in clinical applications such as respiratory motion tracking, disease progression analysis, and radiotherapy planning. While voxel-based registration has traditionally dominated this domain, it often suffers from high computational costs and sensitivity to intensity variations. In this work, we propose a novel point-based deformable registration framework tailored to the unique challenges of lung CT alignment. Our approach combines geometric keypoint attention at coarse resolutions to enhance the global correspondence with attention-based refinement modules at finer scales to accurately model subtle anatomical deformations. Furthermore, we adopt a bi-directional training strategy that enforces forward and backward consistency through cycle supervision, promoting anatomically coherent transformations. We evaluate our method on the large-scale Lung250M benchmark and achieve state-of-the-art results, significantly surpassing the existing voxel-based and point-based baselines in the target registration accuracy. These findings highlight the potential of sparse geometric modeling for complex respiratory motion and establish a strong foundation for future point-based deformable registration in thoracic imaging. Full article

Background: Lung cancer is the leading cause of cancer-related mortality in the United States, which disproportionately affect racial and ethnic minorities. Disparities in lung cancer screening, diagnosis, treatment, and survival outcomes are due to a complex interplay of socioeconomic factors, structural racism, and limited access to high-quality care. This review aims to examine the underlying causes of these disparities and explore potential mitigation strategies to improve lung cancer care equity. Methods: A review of the literature was conducted, evaluating racial and ethnic disparities in lung cancer care. Disparities in lung cancer screening, genomic testing, surgical and systemic treatment, and survival were explored. Additionally, interventional strategies such as risk-based screening, patient navigation programs, and policy reforms were examined. Results: Racial and ethnic minority patients are diagnosed at younger ages with fewer pack-years yet are less likely to qualify for screening under current guidelines. They receive lower rates of guideline-concordant treatment, including surgery, radiation, chemotherapy, and biomarker testing, and have reduced access to specialty care. Socioeconomic barriers, medical mistrust, and geographic disparities further contribute to these inequities. Targeted interventions, including mobile screening programs, financial assistance initiatives, and culturally competent care, have shown promise in improving lung cancer outcomes. Conclusion: A multi-level approach, incorporating healthcare policy changes, improved screening criteria, and an enhanced community engagement strategy, is essential for achieving equitable lung cancer care, ultimately improving outcomes for racial minority populations. Full article

The approach for the diagnosis and treatment of interstitial lung diseases (ILDs) has changed in recent years, mainly for the identification of new entities, such as interstitial lung abnormalities (ILAs) and progressive pulmonary fibrosis (PPF). Clinicians and radiologists are facing new challenges for the screening, diagnosis, prognosis, and follow-up of ILDs. The detection and classification of ILAs or the identification of fibrosis progression at high-resolution computed tomography (HRCT) is difficult, with high inter-reader variability, particularly for non-expert radiologists. In the last few years, various software has been developed for ILD evaluation at HRCT, with excellent results, equal to or more reliable than humans. AI tools can classify ILDs, quantify the extent, analyze the features hidden from the human eye, predict prognosis, and evaluate the progression of the disease. More advanced tools can incorporate clinical and radiological data to obtain personalized prognosis, with the potential ability to steer treatment decisions. To step forward and implement in daily practice such tools, more collaboration is required to collect more homogeneous clinical and radiological data; furthermore, more robust, prospective trials, with the new AI-derived biomarkers compared with each other, are needed to demonstrate the real reliability of the computer-aided evaluation of ILDs. Full article

Bio-based nanomaterials (B-NMs), such as silica oxide (SiO₂)- and lignin (Lig)- based nanoparticles (NPs) derived from biomass waste, have gained attention in the last few years in the view of promoting the sustainability principles in several applications. However, scarce data are available about their safety. Thus, a hazard-testing strategy was designed considering as a reference the safe-and-sustainable-by-design (SSbD) framework for chemicals and materials, prioritizing the use of new approach methodologies (NAMs), such as in vitro and adverse outcome pathways (AOPs) approaches, for generating data about the potential hazard of B-NMs. Literature research was performed to identify the adverse outcomes (AOs) related to the selected B-NMs. All the AOPs investigated shared at least oxidative stress, inflammation and cytotoxicity as key events (KEs) that were investigated in lung and immune cells. The tested B-NMs resulted either non-toxic or moderately toxic towards human cells, validating their biocompatibility when compared to reference NMs of similar composition, but not of bio-origin. However, attention should be given to possible AOs deriving after specific functionalization of the B-NMs. Considering the lack of knowledge in this field, the studies performed represent a step forward in the state of the art of the safety assessment of B-NMs. Full article

(1) Background: Despite previous studies linking inflammatory cytokines to lung adenocarcinoma (LUAD), their causal mechanisms remain unclear. This study aims to explore the causal relationship between inflammatory cytokines and LUAD to fill this knowledge gap. (2) Methods: This study employs a comprehensive approach, integrating Mendelian randomization (MR) analysis, single-cell RNA sequencing (scRNA-seq), and transcriptomic sequencing (RNA-seq) data to investigate the relationship between inflammatory cytokines and LUAD. (3) Results: In forward MR analysis, elevated levels of hepatocyte growth factor (HGF), interleukin-1 receptor antagonist (IL-1RA), IL-5, monocyte chemoattractant protein-3, and monokine induced by interferon-γ were causally associated with an increased risk of LUAD. In reverse MR analysis, LUAD exhibited a positive causal relationship with the levels of regulated upon activation normal T cell expressed and secreted factor (RANTES) and stromal cell-derived factor-1α. The scRNA-seq data further identified specific cell populations that may influence LUAD onset and progression through the expression of particular inflammatory genes and intercellular communication. RNA-seq data analysis highlighted the role of the HGF gene in LUAD diagnosis, demonstrating its strong correlation with patient prognosis and immune cell infiltration within the tumor microenvironment. (4) Conclusions: The findings reveal a causal relationship between inflammatory cytokines and LUAD, with HGF emerging as a potential biomarker of significant clinical relevance. This study provides new insights into the molecular mechanisms underlying LUAD and lays the foundation for future therapeutic strategies. Full article

The ‘forward lunge’ is a crucial movement in badminton that demands effective muscle activation and coordination. This study compared the muscle activation patterns of professional and amateur male badminton players during this movement. A total of 24 players (12 professionals and 12 amateurs) participated, with surface electromyography (sEMG) used to measure the activity of 12 muscles on the right side during the lunge. The movement was divided into swing and support phases based on ground reaction force data. The sEMG signals were analyzed using integral EMG (iEMG) and root-mean-square (RMS) amplitude, and muscle synergy patterns were extracted via non-negative matrix factorization (NNMF) and k-means clustering. The results showed significantly higher iEMG and RMS values in muscles such as the gastrocnemius, biceps femoris, gluteus maximus, external oblique, and latissimus dorsi in professional players (p < 0.05), while no significant differences were observed in the tibialis anterior, vastus medialis, vastus lateralis, deltoideus, biceps, and soleus muscles. Muscle synergy analysis revealed three activation patterns in the professional group, compared to two in the amateur group. The additional synergy pattern in the professional players involved greater recruitment of lower limb and core muscles, especially during the support phase. In contrast, the amateur group showed earlier muscle activation but exhibited less efficient coordination. These findings suggest that muscle activation and coordination patterns in the forward lunge are influenced by playing level, highlighting the importance of lower limb and core training for badminton athletes to optimize performance and reduce injury risk. Full article

Lung cancer still represents one of the main causes of cancer-related mortality, highlighting the necessity for precise, effective, and minimally intrusive diagnostic methods. This research presents an innovative approach to classifying lung lesions using Doppler ultrasound imagery combined with a feed-forward neural network (FNN). This study integrates Doppler mode ultrasound vascularization features—blood vessel area, tortuosity index, and orientation—into an FNN to classify lung lesions as benign or malignant. A dataset of 565 Doppler ultrasound pictures was extended using augmentation techniques to enhance robustness, yielding a training dataset of 3390 images. The FNN architecture was trained utilizing the Levenberg–Marquardt algorithm, achieving a classification accuracy of 98%, demonstrating its potential as a diagnostic aid. The results indicate that integrating all three vascularization factors significantly improves diagnosis accuracy compared with individual modules. This method offers a non-invasive and cost-effective complementary tool to conventional techniques such as CT scans, with the potential to improve early detection and treatment planning for lung cancer patients. Full article

Background/Objectives: This study aims to retrospectively analyze the clinical and imaging data of 101 patients with lung adenocarcinoma who underwent [¹⁸F]FDG PET/CT examination and were pathologically confirmed in the Department of Nuclear Medicine at Peking University Cancer Hospital. This study explores the predictive value and important features of [¹⁸F]FDG PET/CT radiomics for PD-L1 expression levels in lung adenocarcinoma patients, assisting in screening patients who may benefit from immunotherapy. Methods: 101 patients with histologically confirmed lung adenocarcinoma who received pre-treatment [¹⁸F] FDG PET/CT were included. Among them, 44 patients were determined to be PD-L1 positive and 57 patients were determined to be PD-L1 negative based on immunohistochemical assays. Clinical data, PET/CT radiomics parameters, conventional metabolic parameters, and observed CT characteristics were included in the modeling. Random Forest was used in feature denoising, while Forward Stepwise Regression and the Least Absolute Shrinkage and Selection Operator were used in feature selection. Models based on Tree, Discriminant, Logistic Regression, and Support Vector Machine were trained and evaluatedto explore the value of clinical data, PET/CT radiomics parameters, conventional metabolic parameters, and observed CT characteristics. Results: All models showed some predictive ability in distinguishing PD-L1 positive from PD-L1 negative samples. Among the multimodal imaging, clinical data were incorporated into the models, with clinical stage and gender selected by Forward Stepwise Regression, while clinical stage, smoking history, and gender were selected by LASSO. When incorporating clinical data and thin-section CT-derived images into the models, nodular type, spiculation, and CT Shape Flatness were selected by Forward Stepwise Regression, while nodular type and spiculation were selected by LASSO. When incorporating clinical data, PET/CT radiomics, observed CT characteristics, and conventional metabolic information. Forward Stepwise Regression selected TLGlean, MTV, nodule component, PET Shape Sphericity, while LASSO selected SULmax, MTV, nodular type, PET Shape Sphericity, and spiculation. Conclusions: The integration of clinical data, PET/CT radiomics, and conventional metabolic parameters effectively predicted PD-L1 expression, thereby assisting the selection of patients who would benefit from immunotherapy. Observed CT characteristics and conventional metabolic information play an important role in predicting PD-L1 expression levels. Full article

Background: Non-small cell lung cancer (NSCLC) has been the most common cancer globally in the recent decade. CT is the most common imaging modality for the initial diagnosis of NSCLC. The gold standard for definitive diagnosis is the histological evaluation of a biopsy or surgical sample, which usually requires a long processing time for the confirmation of diagnosis. This study aims to develop artificial intelligence models to predict overall staging based on patient demographics and radiomics retrieved from the initial CT images, so as to prioritize later-stage patients for histology evaluation to facilitate cancer diagnosis. Method: Two cohorts of NSCLC patient datasets were utilized for this study. The NSCLC-radiomics dataset from The Cancer Imaging Archive (TCIA) was divided into 70% for the training group and 30% for the internal testing group. Another cohort from a local hospital was collected for the an external testing group. Patient demographics and 107 radiomic features were retrieved from the gross tumor volume delineated by clinical oncologists on CT images. Artificial neural networks were used to build models for NSCLC overall staging (stage I, II, or III) prediction. Four traditional classifiers were also adopted to build models for comparison. Result: The proposed feed-forward neural network (FFNN) model showed good performance in predicting overall staging with an accuracy of 88.84%, 76.67%, and 74.52% in overall accuracies in validation, internal cohort testing, and external cohort testing, respectively. The sensitivity and specificity are balanced in all the stages, with average precision and F1 score in each of the stages. Conclusion: The FFNN demonstrated good performance in overall staging prediction for NSCLC patients. It has the benefit of predicting multiple overall stages in a single model. The software required and the proposed model are simple. It can be operated on a general-purpose computer in the radiology department. The application will eventually be used as a prediction tool to prioritize the biopsy or surgery sample for histological analysis and molecular investigation, thus shortening the time for diagnosis by pathologists, which supports the triage of patients for further testing. Full article

Background: The forward lunge is a closed-chain weight-bearing multi-joint exercise simulating the activities of daily living, such as walking or stair climbing, which mainly activates hip, knee, and ankle musculature and is also used by athletes and other individuals to train lower-extremity musculature. Objectives: The purpose of this study is to compare lower-extremity muscle recruitment patterns between stride and step length variations in forward lunges. Methods: Twenty participants had a mean (±SD) age, mass, and height of 26 ± 6 y, 79 ± 8 kg, and 176 ± 7 cm, respectively, for males, and 27 ± 4 y, 62 ± 6 kg, and 161 ± 7 cm, respectively, for females. All participants used their 12-repetition maximum weight while performing a short step and long step forward lunge with a stride (striding forward and pushing back to the starting position) and without a stride (lunging up and down with feet stationary). During each lunge variation, surface electromyography (EMG) data were collected from the quadriceps, hamstrings, gastrocnemius, hip adductors, gluteus maximus, and gluteus medius muscles, and then normalized as a percent of each muscle’s maximum voluntary isometric contraction. A repeated measures two-way analysis of variance was employed (p < 0.01), with step length and stride comprising the two factors. Results: The following had no significant interactions: (1) quadriceps, hamstrings, gastrocnemius, hip adductor, and gluteus maximus EMG activities were significantly greater in lunges with a long step compared to lunges with a short step; and (2) gluteus maximus and gluteus medius EMG activities were significantly greater in lunges with a stride compared to lunges without a stride. The following had significant interactions: (1) gluteus medius EMG activities were significantly greater in lunges with a long step with and without a stride compared to lunges with a short step with and without a stride; (2) quadriceps EMG activities were generally significantly greater in lunges with long and short steps with a stride compared to lunges with long and short steps without a stride, in lunges with a long step with a stride compared to lunges with a short step with a stride, and in lunges with a short step without a stride compared to lunges with a long step without a stride; (3) hamstring and hip adductor EMG activities were significantly greater in lunges with a long step with a stride compared to lunges with a long step without a stride, and in lunges with a long step with and without a stride compared to lunges with a short step with and without a stride; and (4) gastrocnemius EMG activities were significantly greater in lunges with a long step with and without a stride compared to lunges with a short step with and without a stride. Conclusions: Lower-extremity muscle activity is generally greater in forward lunges with a long step compared to a short step, and greater in lunges with a stride compared to without a stride. During the externally loaded forward lunge, high to very high muscle activity occurs in the quadriceps, gluteus maximus, and gluteus medius, thus enhancing muscle hypertrophy and strength in these muscles, while moderate muscle activity occurs in the hamstrings, gastrocnemius, and adductor longus. Full article

Acute cardiovascular disorders are incriminated in up to 33% of maternal deaths, and the presence of sickle cell anemia (SCA) aggravates the risk of peripartum complications. Herein, we present a 24-year-old Caribbean woman with known SCA who developed a vaso-occlusive crisis at 36 weeks of gestation that required emergency Cesarean section. In the early postpartum period, she experienced fever with rapid onset of acute respiratory distress in the context of COVID-19 infection that required tracheal intubation and mechanical ventilatory support with broad-spectrum antibiotics and blood exchange transfusion. Shortly thereafter, transthoracic echocardiography documented severe biventricular dysfunction associated with raising levels of cardiac troponin and ECG signs of myocardial ischemia. Medical treatment with incremental dobutamine and noradrenaline infusion failed to improve cardiac output and blood gas exchange. After consultation with the regional cardiac center, a prompt decision was made to provide cardiac and respiratory support via implantation of femoral cannula and initiation of veno-arterial extracorporeal membrane oxygenation (ECMO, Cardiohelp^®). Under stable ECMO, the patient was transferred by helicopter to a specialized cardiac center. There were no signs of ongoing hemolysis, and progressive recovery of the right and left ventricular function facilitated forward blood flow through the aortic valve. Three days after implantation, ECMO was weaned, and the cannula were removed. One day later, the patient’s chest X-rays showed partial resolution of lung edema. The patient was successfully extubated, and non-invasive ventilation with pulmonary rehabilitation was initiated to speed up her functional recovery. Full article

Patellofemoral pain syndrome (PFPS) ranks among the most prevalent factors causing anterior knee pain. Quadriceps exercises such as forward lunges are important to treat PFPS. Aim: We investigated whether there is a difference in muscle activity between the vastus medialis oblique (VMO) and vastus lateralis (VL) muscles and the center of pressure (CoP) among three hip positions, namely, hip adduction forward lunge (HADF), hip neutral forward lunge (HNEF), and hip abduction forward lunge (HABF), in healthy subjects. Method: This was a randomized controlled pilot study that included twenty healthy (age: 23.7 ± 2.51) volunteers. The CoP was measured using a “Wii Balance Board” from Nintendo, and VMO and VL muscle activity were measured via wireless surface electromyography. Results: The CoP outcomes showed significant differences among the three positions in terms of position (p < 0.001), sum distance (p < 0.001), range (p < 0.001), and max distance (p < 0.001). VMO (p < 0.000), and VL (p < 0.005) muscle activity and the ratio of VMO/VL (p < 0.000) significantly differed among the three positions. Conclusions: Although VMO and VL muscle activity increased in the HADF and HABF, excessive changes in the CoP occurred in the two positions. The change in the CoP during the HADF and HABF may result in valgus, varus, and loading of the knee joint, which may worsen PFPS. The HNEF is recommended for quadriceps strengthening in healthy subjects and PFPS patients. Full article

Background: Lung transplantation is the most effective treatment for end-stage respiratory diseases, but its application is limited by the shortage of organs. Ex vivo lung perfusion (EVLP) has emerged as a promising technique to evaluate and recondition donor lungs previously deemed unsuitable for transplantation. However, limitations such as lung contusions, air leaks, and perfusate extravasation, especially in portable EVLP systems, hinder the procedure. Despite prolonged perfusions that can result in blood pooling at the lung bases due to fixed lung positioning and diminished oncotic pressure, in some cases, extending perfusion time beyond the typical 5–6 h could benefit extended-criteria lungs, addressing factors such as edema or logistical complications. Methods: We present an innovative protocol involving prolonged EVLP, pronation of the graft, and the addition of anti-edematous drugs to the perfusate. Results: This novel approach, previously tested in animal models, enhances lung reconditioning and expands the donor pool. Conclusions: Our findings suggest that this strategy overcomes key limitations of standard EVLP, offering a valuable solution for improving the availability of transplantable lungs. Full article

The remarkable increase in published medical imaging datasets for chest X-rays has significantly improved the performance of deep learning techniques to classify lung diseases efficiently. However, large datasets require special arrangements to make them suitable, accessible, and practically usable in remote clinics and emergency rooms. Additionally, it increases the computational time and image-processing complexity. This study investigates the efficiency of converting the 2D chest X-ray into one-dimensional texture representation data using descriptive statistics and local binary patterns, enabling the use of feed-forward neural networks to efficiently classify lung diseases within a short time and with cost effectiveness. This method bridges diagnostic gaps in healthcare services and improves patient outcomes in remote hospitals and emergency rooms. It also could reinforce the crucial role of technology in advancing healthcare. Utilizing the Guangzhou and PA datasets, our one-dimensional texture representation achieved 99% accuracy with a training time of 10.85 s and 0.19 s for testing. In the PA dataset, it achieved 96% accuracy with a training time of 38.14 s and a testing time of 0.17 s, outperforming EfficientNet, EfficientNet-V2-Small, and MobileNet-V3-Small. Therefore, this study suggests that the dimensional texture representation is fast and effective for lung disease classification. Full article