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Functional near-infrared spectroscopy (fNIRS) provides a direct and objective assessment of cerebral cortex function. It may be used to determine neurophysiological differences between psychiatric disorders with overlapping symptoms, such as major depressive disorder (MDD) and bipolar disorder (BD). Therefore, this preliminary study aimed to compare fNIRS signals during the verbal fluency task (VFT) of English-speaking healthy controls (HC), patients with MDD and patients with BD. Fifteen HCs, 15 patients with MDD and 15 patients with BD were recruited. Groups were matched for age, gender, ethnicity and education. Relative oxy-haemoglobin and deoxy-haemoglobin changes in the frontotemporal cortex was monitored with a 52-channel fNIRS system. Integral values of the frontal and temporal regions were derived as a measure cortical haemodynamic response magnitude. Both patient groups had lower frontal and temporal region integral values than HCs, and patients with MDD had lower frontal region integral value than patients with BD. Moreover, patients could be differentiated from HCs using the frontal and temporal integral values, and patient groups could be differentiated using the frontal region integral values. VFT performance, clinical history and symptom severity were not associated with integral values. These results suggest that prefrontal cortex haemodynamic dysfunction occurs in mood disorders, and it is more extensive in MDD than BD. The fNIRS-VFT paradigm may be a potential tool for differentiating MDD from BD in clinical settings, and these findings need to be verified in a larger sample of English-speaking patients with mood disorders.
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http://dx.doi.org/10.1016/j.jocn.2021.10.009 | DOI Listing |
Purpose Clear cell renal cell carcinoma (ccRCC), the dominant subtype of renal malignancy, has a rising global incidence and mortality. While surgery is the standard of care for localized cases, adjuvant therapy aims to improve outcomes in high-risk postoperative patients. To quantify the clinical value of adjuvant pharmacotherapy, this systematic review and meta-analysis assesses its effect on overall survival (OS), disease-free survival (DFS), and progression-free survival (PFS) in patients with ccRCC.
View Article and Find Full Text PDFGeroscience
September 2025
Department of Biological Sciences, College of Natural Sciences, Kangwon National University, Kangwon, 24341, Republic of Korea.
Alzheimer's disease (AD) represents a growing global health burden, underscoring the urgent need for reliable diagnostic and prognostic biomarkers. Although several disease-modifying treatments have recently become available, their effects remain limited, as they primarily delay rather than halt disease progression. Thus, the early and accurate identification of individuals at elevated risk for conversion to AD dementia is crucial to maximize the effectiveness of these therapies and to facilitate timely intervention strategies.
View Article and Find Full Text PDFOsteoarthritis Cartilage
September 2025
Clinical Epidemiology Unit, Orthopaedics, Department of Clinical Sciences Lund, Lund University, Lund, Sweden. Electronic address:
Aim: To summarise key epidemiological and therapeutic research on osteoarthritis (OA) published between April 2024 and March 2025.
Methods: A narrative review was conducted using the MEDLINE database, focusing on English-language studies involving human participants published between April 1, 2024 and March 31, 2025. Eligible studies included observational longitudinal studies, systematic reviews, meta-analyses, and phase II-IV randomised controlled trials (RCTs) examining OA treatment and epidemiology.
Exp Cell Res
September 2025
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China. Electronic address:
Background: Enteric glial cells (EGCs) have been implicated in colorectal cancer (CRC) progression. This study aimed to develop and validate a prognostic model integrating EGC- and CRC-associated gene expression to predict patient survival, recurrence, metastasis, and therapy response.
Methods: Bulk and single-cell RNA sequencing data were analyzed, and a machine learning-based model was constructed using the RSF random forest algorithm.
Brain Res
September 2025
Institute of Cognitive Neuroscience and Psychology, HUN-REN Research Centre for Natural Sciences, Hungary.
Identifying early predictors of language development is essential for understanding how infants acquire vocabulary during the first years of life. While previous studies have established the importance of infant-directed speech (IDS) and neural speech processing, this longitudinal study introduces a novel approach by combining EEG-based functional connectivity analysis and machine learning to assess the joint contribution of maternal and infant neural factors to language outcomes. Data were collected at birth and nine months, including maternal personality and speech characteristics, alongside infant EEG responses during speech processing.
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