Search Results (55,475)

In recent years, deep learning methods have made breakthroughs in the field of rotating equipment fault diagnosis, thanks to their powerful data analysis capabilities. However, the vibration signals usually incorporate fault features and background noise, and these features may be scattered over multiple frequency levels, which increases the complexity of extracting important information from them. To address this problem, this paper proposes a Masked and Cascaded Multi-Branch Attention Network (MCMBAN), which combines the Noise Mask Filter Block (NMFB) with the Multi-Branch Cascade Attention Block (MBCAB), and significantly improves the noise immunity of the fault diagnostic model and the efficiency of fault feature extraction. NMFB novelly combines a wide convolutional layer and a top k neighbor self-attention masking mechanism, so as to efficiently filter unnecessary high-frequency noise in the vibration signal. On the other hand, MBCAB strengthens the interaction between different layers by cascading the convolutional layers of different scales, thus improving the recognition of periodic fault signals and greatly enhancing the diagnosis accuracy of the model when processing complex signals. Finally, the time–frequency analysis technique is employed to explore the internal mechanisms of the model in depth, aiming to validate the effectiveness of NMFB and MBCAB in fault feature recognition and to improve the feature interpretability of the proposed modes in fault diagnosis applications. We validate the superior performance of the network model in dealing with high-noise backgrounds by testing it on a standard bearing dataset from Case Western Reserve University and a self-constructed composite bearing fault dataset, and the experimental results show that its performance exceeded six of the top current fault diagnosis techniques. Full article

Background/Objectives: Cognitive impairment is one of the most common and debilitating clinical features of Multiple Sclerosis (MS). Neuropsychological assessment, however, is time-consuming and requires personal resources, so, due to limited resources in daily clinical practice, information on cognitive profiles is often lacking, despite its high prognostic relevance. Time-saving and effective tools are required to bridge this gap. This study evaluates the sensitivity and specificity of a revised version of TRACK-MS (TRACK-MS-R), a recently published screening tool to identify cognitive impairment in MS in a fast and reliable way, offering a balance between efficiency and diagnostic yield for the individual patient. Methods: In this prospective cross-sectional study, 102 MS patients and 94 age-, sex-, and education-matched healthy controls (HC) completed an extensive neuropsychological assessment, including TRACK-MS-R, to test for cognitive processing speed (Symbol Digit Modalities Test, SDMT) and verbal fluency (Regensburger Word Fluency Test, RWT). Sensitivity of TRACK-MS-R was assessed by using the BICAMS-M battery as a reference, and specificity was determined by comparing MS patients to HC. Results: TRACK-MS-R demonstrated high sensitivity (97.44%) when compared to the gold standard as represented by BICAMS-M for early and accurately detecting cognitive impairment in MS patients. Additionally, as a potential cognitive marker, TRACK-MS-R showed a specificity of 82.98% in distinguishing MS patients from healthy controls. Conclusions: TRACK-MS-R proves to be a highly sensitive and time-efficient screening tool for detecting cognitive impairment in patients with MS, while demonstrating good specificity compared to HC. Whereas high sensitivity is a prerequisite for a valid screening tool, its relatively modest specificity compared to BICAMS-M (62.9%) calls for caution in interpreting standalone results but instead indicates more extensive neuropsychological testing. Its briefness and diagnostic accuracy support its implementation in routine clinical practice, particularly in time-constrained settings. Full article

This review presents a comprehensive overview of various ultrasound imaging techniques employed in the evaluation of the canine knee joint. It critically analyzes studies conducted on both human and animal subjects, with a focus on the diagnostic accuracy of B-mode ultrasound, Doppler examination, contrast-enhanced ultrasound, and elastography in both normal and pathological conditions. The review underscores the necessity of strict adherence to the protocols of each ultrasound modality and emphasizes the importance of a thorough understanding of the anatomical region to achieve optimal outcomes. The findings suggest that these ultrasound techniques can significantly enhance the diagnostic process, providing valuable insights into anatomy, size, blood supply, and tissue elasticity. Additionally, in cases where advanced imaging modalities such as computed tomography (CT) or magnetic resonance imaging (MRI) are cost-prohibitive or less accessible, ultrasound serves as a reliable alternative, delivering high diagnostic accuracy and critical information regarding mechanical changes in the joint and neovascularization. Full article

The global spread of Mpox virus (MPXV) underscores the urgent need for rapid, field-deployable diagnostic tools, especially in low-resource settings. We evaluated a loop-mediated isothermal amplification (LAMP) assay, termed LAMPOX, developed by Coris BioConcept. The assay was tested in three formats—two liquid versions and a dried, ready-to-use version—targeting only the ORF F3L (Liquid V1) or both the ORF F3L and N4R (Liquid V2 and dried) genomic regions. Analytical sensitivity and specificity were assessed using 60 clinical samples from confirmed MPXV-positive patients. Sensitivity on clinical samples was 81.7% for Liquid V1 and 88.3% for Liquid V2. The dried LAMPOX assay demonstrated a sensitivity of 88.3% and a specificity of 100% in a panel of 112 negative controls, with most positive samples detected in under 7 min. Additionally, a simplified sample lysis protocol was developed to facilitate point-of-care use. While this method showed slightly reduced sensitivity compared to standard DNA extraction, it proved effective for samples with higher viral loads. The dried format offers key advantages, including ambient-temperature stability and minimal equipment needs, making it suitable for point-of-care testing. These findings support LAMPOX as a promising tool for rapid MPXV detection during outbreaks, especially in resource-limited settings where traditional PCR is impractical. Full article

Background/Objectives: Schizophrenia exhibits symptoms linked to the hippocampus and parahippocampal gyrus. This includes the entorhinal cortex (ERC) and perirhinal cortex (PRC) as anterior parts, along with the posterior segment known as the parahippocampal cortex (PHC). However, recent research has detailed atlases based on cytoarchitectural characteristics and the hippocampus divided into four subregions: cornu ammonis (CA), dentate gyrus (DG), subiculum (SUB), and hippocampal–amygdaloid transition (HATA). This study aimed to explore the functional connectivity (FC) changes between these hippocampal subregions and the parahippocampal gyrus structures (ERC, PRC, and PHC) as well as between hippocampal subregions and various functional brain networks in schizophrenia. Methods: In total, 50 individuals with schizophrenia and 50 matched healthy subjects were examined using resting state functional magnetic resonance imaging (rs-fMRI). Results: The results showed alterations characterized by increases and decreases in the strength of the positive connectivity between the parahippocampal gyrus structures and the four hippocampal subregions when comparing patients with schizophrenia with healthy subjects. Alterations were observed among the hippocampal subregions and functional brain networks, as well as the formation of new connections and absence of connections. Conclusions: There is strong evidence that the different subregions of the hippocampus have unique functions and their connectivity with the parahippocampal cortices and brain networks are affected by schizophrenia. Full article

Background/Objectives: Diffuse Large B-Cell Lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma and demands precise segmentation and classification of nuclei for effective diagnosis and disease severity assessment. This study aims to evaluate the performance of HoVerNet, a deep learning model, for nuclei segmentation and classification in CMYC-stained whole slide images and to assess its integration into a user-friendly diagnostic tool. Methods: A dataset of 122 CMYC-stained whole slide images (WSIs) was used. Pre-processing steps, including stain normalization and patch extraction, were applied to improve input consistency. HoVerNet, a multi-branch neural network, was used for both nuclei segmentation and classification, particularly focusing on its ability to manage overlapping nuclei and complex morphological variations. Model performance was validated using metrics such as accuracy, precision, recall, and F1 score. Additionally, a graphic user interface (GUI) was developed to incorporate automated segmentation, cell counting, and severity assessment functionalities. Results: HoVerNet achieved a validation accuracy of 82.5%, with a precision of 85.3%, recall of 82.6%, and an F1 score of 83.9%. The model showed powerful performance in differentiating overlapping and morphologically complex nuclei. The developed GUI enabled real-time visualization and diagnostic support, enhancing the efficiency and usability of DLBCL histopathological analysis. Conclusions: HoVerNet, combined with an integrated GUI, presents a promising approach for streamlining DLBCL diagnostics through accurate segmentation and real-time visualization. Future work will focus on incorporating Vision Transformers and additional staining protocols to improve generalizability and clinical utility. Full article

Modernizing irrigation systems (ISs) from traditional gravity methods to sprinkler and drip technologies has significantly improved water use efficiency. However, it has simultaneously increased electricity demand and operational costs. Integrating photovoltaic generators into ISs represents a promising solution, as solar energy availability typically aligns with peak irrigation periods. Despite this potential, photovoltaic pumping systems (PVPSs) often face reliability issues due to fluctuations in solar irradiance, resulting in frequent start/stop cycles and premature equipment wear. The IEC 62253 standard establishes procedures for evaluating PVPS performance but primarily addresses steady-state conditions, neglecting transient regimes. As the main contribution, the current paper proposes a non-intrusive, high-resolution monitoring system and a methodology to assess the performance of an isolated, high-power PVPS, considering also transient regimes. The system records critical electrical, hydraulic and environmental parameters every second, enabling in-depth analysis under various weather conditions. Two performance indicators, pumped volume efficiency and equivalent operating time, were used to evaluate the system’s performance. The results indicate that near-optimal performance is only achievable under clear sky conditions. Under the appearance of clouds, control strategies designed to protect the system reduce overall efficiency. The proposed methodology enables detailed performance diagnostics and supports the development of more robust PVPSs. Full article

Kidney transplantation is the treatment of choice for patients with end-stage kidney disease. Despite significant advances in graft survival, rejection continues to pose a major clinical challenge. Conventional monitoring tools, such as serum creatinine, donor-specific antibodies, and proteinuria, lack sensitivity and specificity for early detection of graft injury. Moreover, while biopsy remains the current gold standard for diagnosing rejection, it is prone to confounders, invasive, and associated with procedural risks. However, non-invasive novel biomarkers have emerged as promising alternatives for earlier rejection detection and improved immunosuppression management. This review focuses on the leading candidate biomarkers currently under clinical investigation, with an emphasis on their diagnostic performance, prognostic value, and potential to support personalised immunosuppressive strategies in kidney transplantation. Full article

Mature teratomas account for approximately 20% of all ovarian tumors identified in pathological studies. Benign or malignant somatic neoplasms developing within teratomas can arise from any tissue in up to 2% of mature cystic teratomas, including low-grade malignant mucinous neoplasms. This report presents the case of a 34-year-old woman with no previous gynecological or general health issues, who was admitted to our Hospital after an asymptomatic pelvic mass was detected during a routine exam. A transvaginal ultrasound revealed a unilateral pelvic mass in the left adnexal region, measuring 8 cm. The CT scan showed a cystic-appearing formation measuring nearly 12 cm, which indented the bladder dome. Final diagnosis indicated a mucinous carcinoma arising from a mucinous borderline lesion within the context of a mature ovarian teratoma. No other involvement or lymphadenopathies were detected on 18FDG-PET CT scan, and the patient is now well and free of recurrences. Full article

Background/Objectives: Artificial intelligence (AI) is rapidly emerging as a transformative force in healthcare education, including orthodontics. This systematic review and meta-analysis aimed to evaluate the integration of AI into orthodontic training programs, focusing on its effectiveness in improving diagnostic accuracy, learner engagement, and the perceived quality of AI-generated educational content. Materials and Methods: A comprehensive literature search was conducted across PubMed, Scopus, Web of Science, and Embase through May 2025. Eligible studies involved AI-assisted educational interventions in orthodontics. A mixed-methods approach was applied, combining meta-analysis and narrative synthesis based on data availability and consistency. Results: Seven studies involving 1101 participants—including orthodontic students, clinicians, faculty, and program directors—were included. AI tools ranged from cephalometric landmarking platforms to ChatGPT-based learning modules. A fixed-effects meta-analysis using two studies yielded a pooled Global Quality Scale (GQS) score of 3.69 (95% CI: 3.58–3.80), indicating moderate perceived quality of AI-generated content (I² = 64.5%). Due to methodological heterogeneity and limited statistical reporting in most studies, a narrative synthesis was used to summarize additional outcomes. AI tools enhanced diagnostic skills, learner autonomy, and perceived satisfaction, particularly among students and junior faculty. However, barriers such as limited curricular integration, lack of training, and faculty skepticism were recurrent. Conclusions: AI technologies, especially ChatGPT and digital cephalometry tools, show promise in orthodontic education. While learners demonstrate high acceptance, full integration is hindered by institutional and perceptual challenges. Strategic curricular reforms and targeted faculty development are needed to optimize AI adoption in clinical training. Full article

Acinetobacter baumannii is one of the most challenging nosocomial pathogens associated with a variety of hospital infections, such as ventilator-associated pneumonia, wound and urinary tract infections, meningitis, and sepsis, primarily in patients treated in critical care settings. Its classification as a high-priority pathogen is due to the emergence of multidrug-resistant strains in healthcare environments and its tendency to spread clonally. A. baumannii belongs to the Acinetobacter calcoaceticus–Acinetobacter baumannii (Acb) complex, a group of genotypically and phenotypically similar species. Differentiating between the species is important because of their distinct clinical significance. However, conventional phenotypic methods, both manual and automated, often fail to provide accurate species-level identification. This review aims to summarize current phenotypic and genotypic methods for the identification of species within the Acb complex, evaluating their strengths and limitations to offer guidance for their appropriate application in diagnostic settings and epidemiological investigations. Full article

Cardiorenal syndrome (CRS) is a term used to describe the combined dysfunction of the heart and kidneys. This complex disorder is widely acknowledged to be challenging in both its diagnosis and management, and this is the case particularly in the elderly population, due to multi-morbidity, polypharmacy, and age-related physiological changes. Given advancements in medicine and more prolonged cumulative exposure to risk factors in the elderly population, it is likely that the prevalence of chronic kidney disease (CKD) and heart failure (HF) will continue to rise going forward. Hence, understanding the mechanisms involved in the development of CRS is paramount. There are five different CRS types—they are categorised depending on the primary organ involved the acuity of disease. The pathophysiological process behind CRS is complex, involving the interplay of many processes including hemodynamic changes, neurohormonal activation, inflammation, oxidative stress, and endothelial dysfunction and vascular stiffness. The numerous diagnostic and management challenges associated with CRS are significantly further exacerbated in an elderly population. Biomarkers used to aid the diagnosis of CRS, such as serum creatinine and brain natriuretic peptide (BNP), can be challenging to interpret in the elderly population due to age-related renal senescence and multiple comorbidities. Polypharmacy can contribute to the development of CRS and therefore, before initiating treatment, coordinating a patient-centred, multi-speciality, holistic review to assess potential risks versus benefits of prescribed treatments is crucial. The overall prognosis of CRS in the elderly remains poor. Treatments are primarily directed at addressing the sequelae of the underlying aetiology, which often involves the removal of fluid through diuretics or ultrafiltration. Careful considerations when managing elderly patients with CRS is essential due to the high prevalence of frailty and functional decline. As such, in these patients, early discussions around advance care planning should be prioritised. Full article

Background: Midportion Achilles tendinopathy (Mid-AT) is a complex condition that may be exacerbated by anatomical variations of the plantaris tendon. Recent anatomical studies, particularly the classification proposed by Olewnik et al., have enhanced the understanding of plantaris–Achilles interactions and their clinical implications. Objective: This review aims to assess the anatomical types of the plantaris tendon, their imaging correlates, and the impact of the Olewnik classification on diagnosis, treatment planning, and surgical outcomes in patients with Mid-AT. Methods: We present an evidence-based analysis of the six anatomical types of the plantaris tendon and their relevance to Achilles tendinopathy, with emphasis on MRI and ultrasound (USG) evaluation. A diagnostic and therapeutic algorithm is proposed, and clinical outcomes of both conservative and operative management are compared across tendon types. Results: Types I and V were most strongly associated with symptomatic conflict and showed the highest benefit from surgical resection. Endoscopic approaches were effective in Types II and III, while Type IV typically responded to conservative treatment. Type VI, often misdiagnosed as tarsal tunnel syndrome, required combined neurolysis. The classification significantly improves surgical decision-making, reduces overtreatment, and enhances diagnostic precision. Conclusions: The Olewnik classification provides a reproducible, clinically relevant framework for individualized management of Mid-AT. Its integration into imaging protocols and treatment algorithms may improve therapeutic outcomes and guide future research in orthopaedic tendon pathology. Full article

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease. It has known multifactorial pathophysiology, but the impact of social determinants of health (SDOH) on the rising prevalence of MASLD is poorly understood. We conducted a retrospective cross-sectional study to examine the influence of SDOH on MASLD using nationwide data from the 2017–2018 National Health and Nutrition Examination Survey (NHANES) study. Methods: We identified participants with MASLD based on liver ultrasound-based controlled attenuation parameter measurements consistent with diagnostic guidelines. We then used logistic regression models to examine associations between SDOH variables and MASLD, with a pre-specified focus on education and income, sequentially adjusting for sociodemographic factors, medical comorbidities, and other SDOH. Results: Our study found that higher education (odds ratio [OR] 0.77, 95% confidence interval [CI] 0.62–0.97, p = 0.024) but not higher income (OR 1.12, 95% CI 0.91–1.37, p = 0.3) was associated with lower odds of MASLD in multivariable adjusted models. We also identified a significant interaction between education level and food security, as well as interactions between food security and other significant SDOH. In the stratified analyses, higher education was significantly associated with lower odds of MASLD among participants with food security (OR 0.71, 95% CI 0.55–0.91, p = 0.007) but not among those with food insecurity (OR 1.26, 95% CI 0.76–2.11, p = 0.4). Conclusions: Our findings identify the potential impact of SDOH on odds of MASLD and suggest increased importance of food security relative to other SDOH. Full article

Background/Objectives: Lysophosphatidylcholine (LPC) is composed of various lipid species, some of which exert pro-inflammatory and others anti-inflammatory activities. However, most of the LPC species analyzed to date are reduced in the serum of patients with inflammatory bowel disease (IBD) compared to healthy controls. To our knowledge, the correlation between serum LPC species levels and measures of inflammation, as well as their potential as markers for monitoring IBD activity, has not yet been investigated. Methods: Thirteen LPC species, varying in acyl chain length and number of double bonds, were measured in the serum of 16 controls and the serum of 57 patients with IBD. Associations with C-reactive protein (CRP) and fecal calprotectin levels as markers of IBD severity were assessed. Results: Serum levels of LPC species did not differ between the healthy controls and the entire patient cohort. In patients with IBD, serum levels of LPC 16:1, 18:0, 18:3, 20:3, and 20:5, as well as total LPC concentrations, showed inverse correlations with both CRP and fecal calprotectin levels, indicating an association with inflammatory activity. Nine LPC species were significantly reduced in patients with high fecal calprotectin compared to those with low values. LPC species with 22 carbon atoms and 4 to 6 double bonds were not related to disease activity. Stool consistency and gastrointestinal symptoms did not influence serum LPC profiles. Corticosteroid treatment was associated with lower serum LPC 20:3 and 22:5 levels, while mesalazine, anti-TNF, and anti-IL-12/23 therapies had no significant impact on LPC concentrations. There was a strong positive correlation between LPC species containing 15 to 18 carbon atoms and serum cholesterol, triglycerides, and phosphatidylcholine levels. However, there was no correlation with markers of liver disease. Conclusions: Shorter-chain LPC species are reduced in patients with active IBD and reflect underlying hypolipidemia. While these lipid alterations provide insight into IBD-associated metabolic changes, they appear unsuitable as diagnostic or disease monitoring biomarkers. Full article