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Exploring the relationship between mental health and urban green space soundscapes: A scoping review

Urban soundscapes, particularly those experienced in green spaces, have been increasingly recognized as factors that influence human mental health. This scoping review explores the existing literature on soundscapes within urban green spaces and their associated mental health outcomes. It aims to classify the methodologies used in this domain, identify mental health outcomes related to urban green space soundscapes, and examine specific soundscape elements and their correlations with mental health. A systematic search of peer-reviewed studies was conducted. After screening titles, abstracts, and full texts, 22 studies met the inclusion criteria. Diverse methodological approaches were identified, with an emphasis on quantitative multi-method designs. Commonly studied mental health outcomes include stress reduction, mood enhancement, perceived restorativeness, and cognitive restoration. Standardized psychometric tools, such as the Perceived Stress Scale (PSS-14), Positive and Negative Affect Schedule (PANAS) and Perceived Restorativeness Soundscape Scale (PRSS) are frequently used as outcome measures. Natural soundscape elements such as birdsong, water sounds, and rustling leaves had a positive association with relaxation and perceived mental restoration throughout all studies, while mechanical sounds, such as traffic noise were linked to adverse mental health outcomes. These findings highlight that natural soundscapes in urban green spaces have a potential positive relationship with mental health by reducing stress and enhancing mood. However, the cross-sectional design and methodological heterogeneity of the included studies limit causal interpretation. Future research should explore multi-sensory experiences and examine soundscapes in diverse urban contexts to provide more robust insights into their relationship with mental health. The practical implications suggest that urban planners should prioritize integrating natural sound elements into urban areas to improve mental health. The study protocol of this scoping review had been registered at OSF (osf.io/4r7gd).

Analysis of chemiluminescence and liquid chromatography-mass spectrometry in 25-hydroxyvitamin D detection using fuzzy logic

Abstract Vitamin D is an essential nutrient closely associated with the prevention of multiple diseases, including osteoporosis, diabetes, and cardiovascular disorders. The serum level of 25-hydroxyvitamin D [25(OH)D] is the primary biomarker for assessing vitamin D status, and its precise quantification is critical for clinical diagnosis and treatment. Chemiluminescence immunoassay (CLIA) and liquid chromatography–tandem mass spectrometry (LC-MS/MS) are widely used analytical methods; however, methodological discrepancies often lead to inconsistent results that may be further influenced by demographic factors such as age and gender. In this study, we evaluated the consistency and correlation between CLIA and LC-MS/MS measurements using a Generative Fuzzy Inference System (GENFIS). Analysis of 138 serum samples showed that LC-MS/MS produced significantly higher 25(OH)D concentrations than CLIA ( p  < 0.01; mean difference = 1.33 ± 3.71; 95% CI: − 5.95 to 8.61), though the two methods exhibited strong linear correlation and agreement (Cohen’s Kappa = 0.8257; R² = 0.9075; intraclass correlation coefficient = 0.93). GENFIS analysis indicated a possible 30–40-year female pattern of larger between the detection differences of two methods. To verify this finding, an additional 59 samples were analyzed, revealing a relative risk (RR) of 3.18 (95% CI: 1.71–5.93; p  < 0.05) for this subgroup compared with other populations, supporting the GENFIS inference. These results highlight age- and gender-related differences in 25(OH)D measurement between CLIA and LC-MS/MS, providing valuable insights for improving the standardization and clinical interpretation of vitamin D testing.

Bayesian machine learning enables discovery of risk factors for hepatosplenic multimorbidity related to schistosomiasis

Abstract One in 25 deaths worldwide is related to liver disease, and often with multiple hepatosplenic conditions. Yet, little is understood of the risk factors for hepatosplenic multimorbidity, especially in the context of chronic infections. We present a novel Bayesian multitask learning framework to jointly model 45 hepatosplenic conditions assessed using point-of-care B-mode ultrasound for 3155 individuals aged 5-91 years within the SchistoTrack cohort across rural Uganda, where chronic intestinal schistosomiasis is endemic. We identify distinct and shared biomedical, socioeconomic, and spatial risk factors for individual conditions and hepatosplenic multimorbidity, and introduce methods for measuring condition dependencies as risk factors. Notably, for gastro-oesophageal varices, we discover key risk factors of older age, lower haemoglobin concentration, and schistosomal periportal fibrosis. Our findings provide a compendium of risk factors to inform surveillance, triage, and follow-up, while our model enables improved prediction of hepatosplenic multimorbidity, and if validated on other anatomical systems, general multimorbidity.

Assessment of physical status and analysis of lipidomic and metabolomic alterations in patients with Post-COVID-19 condition

The development and persistence of symptoms following SARS-CoV-2 infection, known as Post-COVID-19 Condition (PCC) or “long COVID,” represents a global health challenge. In this prospective cross-sectional study, we conducted a detailed assessment of the physical condition of 46 patients using handgrip dynamometry, ergoespirometry, and the 6-minute walk test (6MWT). The results revealed a loss of muscle strength and poor exercise tolerance primarily due to peripheral muscle involvement. To complement and better understand these findings, we compared the blood metabolome and lipidome of 13 patients with PCC, 13 patients with acute COVID-19 infection, and 13 healthy controls using magnetic resonance spectroscopy (1H-NMR). PCC patients showed lower levels of HDL-cholesterol, as well as medium and dense HDL particles, which could contribute to a pro-atherogenic and pro-inflammatory state. Although no significant differences were observed in glycoproteins, we found decreased glucose and increased lactate levels, supporting the hypothesis of mitochondrial dysfunction in PCC patients. Additionally, elevated glycine and reduced glutamate levels may be related to the neurological symptoms associated with the condition. We also observed increased levels of glutamine, leucine, and isoleucine, indicating protein hypercatabolism and metabolic stress. These findings suggest that alterations in the metabolome and lipidome of PCC patients may be contributing to the persistence of their symptoms.

Hybrid EfficientNet B4 and SVM framework for rapid and accurate bone cancer diagnosis from X-rays

Abstract The early and correct diagnosis of bone cancer is important for treating both primary and metastatic conditions effectively. Traditional imaging techniques, like CT, MRI, and X-ray scans, depend exclusively on manual review, which is time-consuming and prone to human errors. Recently, ML and DL have enabled automated diagnostic systems that are more accurate, reliable, and efficient. Still, many of the existing approaches using DL suffer from high computational complexity, overfitting, and limited availability of robust datasets. This work proposes a novel diagnostic model for bone cancer, called OsteoCancerNet, which combines EfficientNetB4 for feature extraction with a support vector machine using the RBF kernel for classification. EfficientNetB4 captures efficiently both quantitative and qualitative features from X-ray images, and the SVM ensures robust binary classification. Extensive experiments using a large dataset with 29,952 X-ray images demonstrate that OsteoCancerNet provides 98% precision, 97.47% recall, 98% accuracy, and a 98% F1-score, thus outperforming traditional machine learning, deep learning, and transfer learning methods. Of note, the model maintains fast inference times of 41 milliseconds per image, making it suitable for real-time clinical applications. By combining deep learning feature extraction with traditional machine learning classification, OsteoCancerNet provides an efficient, accurate, and practical approach for the early detection of bone cancer. This approach has the potential to aid radiologists in timely diagnosis, decrease workload, and improve treatment outcomes, thus underlining the advantages of integrating DL and ML techniques within medical imaging. Keywords: OsteoCancerNet; computer-assisted diagnosis; bone cancer diagnosis; EfficientNet B4 model; SVM model; X-ray image analysis.

Machine learning helps to strongly reduce future warming uncertainty

Real-world clinical effectiveness of trimethoprim–sulfamethoxazole for primary prophylaxis of pneumocystis pneumonia in non-hodgkin lymphoma patients treated with rituximab

There are no definitive clinical practice guidelines regarding the necessity and dosage of trimethoprim–sulfamethoxazole (TMP/SMX) prophylaxis for Pneumocystis jirovecii pneumonia (PJP) in individuals undergoing rituximab therapy. This retrospective study evaluated the effectiveness and safety of various TMP–SMX prophylactic dosing regimens over a 1-year period in 690 patients with non-Hodgkin lymphoma treated with rituximab at a university hospital in Thailand from 2013 to 2022. Out of these patients, 622 (90.1%) received TMP/SMX, with a mean duration of prophylaxis of 265.7 days (SD 85.66). The overall incidence of PJP was 1% (7 patients), which was significantly higher in the non-prophylaxis group (5.8%, 4 patients) compared to the prophylaxis group (0.6%, 3 patients). No cases of PJP occurred among those receiving standard prophylaxis or a single-strength tablet every other day, three times a week. However, instances in the prophylaxis cohort were reported in patients who took two single-strength tablets twice daily, twice a week. Prophylaxis resulted in a significant reduction in the one-year incidence of PJP, with a hazard ratio of 0.105 (95% CI: 0.023–0.469). Mild adverse reactions were noted in 3.05% of patients, all of whom recovered. These findings suggest that TMP/SMX prophylaxis was associated with a lower incidence of PJP and was well tolerated. Future studies should explore optimal dosing strategies while considering patient selection bias and concurrent immunosuppressive therapy.

Toward robust automated cardiovascular arrhythmia detection using self-supervised learning and 1-dimensional vision transformers

Alpha frequency shapes perceptual sensitivity by modulating optimal phase likelihood

Do whale-watching experiences and tourist expectations align? A comparison of three Macaronesian destinations

This study examines the alignment between whale-watching experiences and tourist expectations in three different destinations. Whale-watching is a global tourist activity, with locations such as the Canary Islands (Spain) and the Azores (Portugal) in Macaronesia rapidly becoming prime spots for these marine activities. Those locations attract a significant number of tourists with varying recreational interests and diverse perceptions of each destination and its natural resources, including marine wildlife megafauna species that can be seen. While often marketed as sustainable tourism, the ecological impacts of whale-watching are a matter of concern. Evolving whale-watching practices may reinforce or diminish the effectiveness of conservation and environmental education efforts. In this regard, exploring whale watchers’ expectatives, preferences, previous experiences, level of satisfaction, and environmental information may help to assess better practices and sustainable tourism initiatives. This study employed a multidisciplinary approach, incorporating a series of questionnaires that explored whale watchers’ expectations and overall satisfaction before and after sea trips in the Tenerife and El Hierro Islands (Canary Islands, Spain), as well as in São Miguel (Azores, Portugal). The findings highlight differences across three study cases: El Hierro attracted more experienced and oriented tourists, while Tenerife and São Miguel received more generalist visitors. Satisfaction was closely linked to the number of cetacean sightings. Many participants who did not mention specific species expressed open preferences such as wanting to “see everything” or “whatever is possible”, reflecting limited prior knowledge. The study highlights the importance of tailoring whale-watching strategies to tourist profiles by enhancing communication, adjusting group sizes and vessel types, and reinforcing conservation messaging to ensure both positive experiences and long-term ecological sustainability.

Autonomous nursing professional development framework using blockchain technology

Lasing-like dynamics with virtual gain driven by complex-frequency excitations

Retraction: Population growth poses a significant threat to forest ecosystems: A case study from the Hindukush-Himalayas of Pakistan

Multiplex real-time PCR with high-resolution melting analysis for rapid identification of carbapenem and colistin resistance genes in clinical Enterobacterales isolates

Stereoselective depolymerization of chiral polyesters

Retraction: High Glucose Induced Oxidative Stress and Apoptosis in Cardiac Microvascular Endothelial Cells Are Regulated by FoxO3a

Towards velocity-dependent nonlinear elasticity of human forefinger soft tissue for specification construction

Topological magneto-optical Kerr effect without spin-orbit coupling in spin-compensated antiferromagnet

Abstract The magneto-optical Kerr effect (MOKE), the differential reflection of oppositely circularly polarized light, has traditionally been associated with relativistic spin-orbit coupling (SOC), which links a particle’s spin with its orbital motion. In ferromagnets, large MOKE signals arise from the combination of magnetization and SOC, while in certain coplanar antiferromagnets, SOC-induced Berry curvature enables MOKE despite zero net magnetization. Theoretically, large MOKE can also arise in a broader class of magnetic materials with compensated spins, without relying on SOC - for example, in systems exhibiting real-space scalar spin chirality. The experimental verification has remained elusive. Here, we demonstrate such a SOC- and magnetization-free MOKE in the noncoplanar antiferromagnet Co 1/3 TaS 2 . Using a Sagnac interferometer microscope, we image domains of scalar spin chirality and their reversal. Our findings establish experimentally a new mechanism for generating large MOKE signals and position chiral spin textures in compensated magnets as a compelling platform for ultrafast, stray-field-immune opto-spintronic applications.

Methodological review of the design, objectives and sample size of Research for Patient Benefit (RfPB) applications that use an external randomised controlled pilot trial design: A protocol

Background The National Institute for Health and Care Research accepts applications for pilot and feasibility studies to their Research for Patient Benefit (RfPB) programme. There has been limited work describing the design practices of these applications and funding status. Knowing some of the qualities which may contribute towards a pilot or feasibility study application successfully gaining funding could help researchers improve the quality of their applications. Therefore, this study describes the protocol for a review looking at the characteristics of funded and non-funded external pilot trial applications. In particular, the primary objective is to describe the planned sample size and sample size justifications. Methods The study will be conducted on 100 applications from Competition 31–37 with a randomised feasibility design, identified and given access to us by RfPB where the lead applicant has consented. We will screen these applications to identify the external pilot trials, first looking through the titles and then the full text. Following this, we will extract data on information such as medical area, study design, objective(s), sample size, sample size justification, and funding outcome stage one and two. Validation will be performed on 20% of the data extracted; discrepancies will be resolved by discussion or a third reviewer will decide if there is no consensus. We will use descriptive statistics to summarise quantitative data, and will analyse qualitative data using thematic analysis. Findings will be summarised through discussion with the project contributors to produce a reader-friendly guidance document. Discussion This work will provide a more complete picture of RfPB external randomised pilot and feasibility trials. The findings will assist researchers when planning their pilot trials, and could help improve the quality of submitted applications. Protocol Registration Open Science Framework protocol registration DOI: https://doi.org/10.17605/OSF.IO/PYKVG .

Brain connectivity and its relation to cognitive function in patients with post-COVID 19 condition after mild infection

Abstract Neurological symptoms are common in post-COVID-19 condition (PCC) and have been linked to underlying brain alterations. However, in individuals with PCC following a mild infection without hospitalization, such alterations are rarely detected using conventional neuroimaging techniques. This study aims to investigate brain connectivity in patients with PCC with cognitive symptoms after mild COVID-19 infection, using resting-state functional magnetic resonance imaging (rs-fMRI). Additional aims were to explore associations between brain connectivity, neuropsychological performance, and self-reported fatigue and emotional status. Patients with PCC ( n  = 22) and lasting cognitive symptoms and fatigue were consecutively recruited from a regional rehabilitation unit and compared with a convenience sample of non-symptomatic controls ( n  = 19). The assessments were conducted on average 32 months post-infection and included 3 Tesla rs-fMRI, neuropsychological testing, and self-report measures of fatigue (MFI-20), anxiety, and depression (HADS). Patients with PCC had elevated functional connectivity in brain regions associated with the default mode network (DMN) compared to controls. No significant correlations were found between functional connectivity, neuropsychological test performance, fatigue, anxiety, or depression. Our findings suggest persistent alterations in DMN connectivity in PCC with cognitive symptoms and fatigue, underscoring the need for continued larger studies on brain functioning in this patient group. Clinical trial registration : No. NCT06042530.