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Social media apps are widely used by health care professionals despite security and regulatory risks. Identifying factors associated with this use is important for developing effective risk-reduction strategies. This study aimed to investigate how medical residents use 6 popular social media apps in professional tasks and to identify factors influencing their adoption in health care, using the validated Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model. An anonymous web-based survey was conducted between June 2024 and November 2024 among medical residents in France. Participants reported demographic characteristics, frequency, and professional contexts of use for 6 apps (Facebook, Instagram, LinkedIn, Messenger, TikTok, and WhatsApp) and completed UTAUT2-based items. The model was adapted by adding a technology trust construct. Descriptive analyses were performed for all apps. With a sufficient sample size, partial least squares structural equation modeling was conducted for WhatsApp to identify factors associated with behavioral intention and use behavior. A total of 137 residents (n=87, 63.5% female participants) across 40 specialties completed the survey. WhatsApp was the most widely and professionally used app (n=127, 92.7%), with 75.9% (n=104) using it at least many times per week. It was primarily used for patient care, including written transmissions (n=86, 62.8%), case discussions (n=76, 55.5%), and specialist advice (n=86, 62.8%), as well as for professional networking (n=62, 45.3%). Messenger was used by 46.7% (n=64) of participants for similar purposes. Facebook (n=35, 25.6%) and LinkedIn (n=20, 14.6%) were mainly used for education and networking, whereas Instagram (n=11, 8%) was rarely used, and TikTok was not used for professional purposes. Regarding adoption factors, WhatsApp had the highest overall scores, including the highest performance expectancy (mean 5.4, SD 1.12), behavioral intention (mean 5.28, SD 1.15), and use behavior (mean 5.91, SD 1.30), with high effort expectancy (mean 6.82, SD 0.55) and facilitating conditions (mean 6.07, SD 0.85). LinkedIn showed the highest social influence (mean 5.05, SD 1.06), whereas Instagram showed the highest hedonic motivation (mean 6.61, SD 0.51). Technology trust scores were low across all apps, ranging from a mean of 2.23 (SD 1.16) for Facebook to a mean of 3.72 (SD 1.39) for LinkedIn. In the partial least squares structural equation modeling analysis for WhatsApp, habit was the only significant predictor of behavioral intention (β=.53; P<.001) and use behavior (β=.45; P<.001). WhatsApp dominates professional use among residents despite low trust in its security, and its use is mainly driven by habit. Secure alternatives with features similar to popular social media apps, supported by institutional policies and digital professionalism training, are needed to encourage physicians to better consider safety when using social media.
Osteoid osteomas (OOs) are benign but painful bone tumors characterized by a vascularized nidus of osteoblastic cells surrounded by sclerotic bone. They affect the spine in 6%-20% of cases, most commonly in the posterior elements. Nonsteroidal anti-inflammatory drugs (NSAIDs) often provide initial relief, but surgery is required when symptoms persist. Complete nidus excision is critical to prevent recurrence. Minimally invasive techniques such as radiofrequency ablation (RFA) have gained popularity, but proximity to neural structures limits their use. Full endoscopic resection has emerged as a promising alternative, offering direct visualization, histologic confirmation, and minimal tissue disruption. This case series evaluates the safety, feasibility, and outcomes of full endoscopic resection for cervical and thoracic spinal OOs. This retrospective series included 4 patients treated at a single academic institution between December 2023 and April 2025. Diagnosis was based on clinical and radiologic findings. All patients underwent full endoscopic resection. Postoperative outcomes were assessed using imaging. Histological confirmation was obtained in all cases. Lesions were located at C7, T1 and T10 (2 cases). All patients reported immediate pain relief within 24 hours. No complications occurred, and all were discharged within 36 hours. Histopathology confirmed OO in every case. Follow-up imaging up to 15 months showed no recurrence. Full endoscopic resection of cervical and thoracic OO is safe, effective, and minimally invasive. It enables complete nidus removal, rapid symptom relief, histologic confirmation, and preservation of spinal stability. Further long-term follow-ups are warranted to validate these findings and evaluate recurrence rates.
Exploring how Turkish-speaking immigrants understand and express common mental health conditions is crucial, as discrepancies in this area have real-life consequences for treatment. Some key concepts to examine within this are the long-standing belief that Turkish-speaking immigrants somatise emotional difficulties and cannot identify them, and that they predominantly rely on traditional explanatory models of mental health. Accordingly, this study aimed to explore how this population experiences, expresses and understands these conditions and to examine their coping resources and help-seeking attitudes. Qualitative design. Semi-structured interviews were conducted in Turkish with 18 Turkish-speaking immigrants who self-identified as having experienced common mental health difficulties. Data were analysed inductively using reflexive thematic analysis within a critical realist framework. Four themes with ten subthemes were generated: symptom presentation, explanatory models, coping strategies and help-seeking attitudes. Participants reported both emotional and physical symptoms, often expressed through rich idioms and metaphors. They attributed their distress to upbringing, traumatic events, chronic adversities, discrimination, interpersonal relationships and their own perceived shortcomings. Coping included personal, interpersonal, community and religious resources alongside lay resources. While most participants were open to professional help, all expressed distrust towards UK services and many preferred Turkish-speaking professionals. Contrary to popular belief, Turkish-speaking immigrants articulated distress in both emotional and physical terms. Their explanatory model was mainly psychosocial but also included biological and traditional elements, reflecting a dynamic, multi-model approach. Moving beyond reductive stereotypes about Turkish-speaking immigrants and Global South populations is crucial for providing meaningful and effective care.
This study aimed to evaluate the quality of dry eye disease (DED) treatment-related short videos on popular Chinese platforms. To better evaluate the quality of short videos related to DED treatment, the Dry-eye-related Short Videos Standardization Score (DSVSS), a preliminary disease-specific checklist, was developed tailored to DED clinical guidelines. On May 17, 2025, 305 videos (150 from Douyin, 155 from Bilibili) were retrieved using the keyword "dry eye treatment", and their quality and guideline consistency were evaluated with the Global Quality Score (GQS) and the DSVSS checklist. Basic data, including duration, likes, comments, collections, and shares were recorded. Statistical analysis was performed using the Mann-Whitney U test, Kruskal-Wallis H test, and Spearman's rank correlation to assess group differences and correlations. Videos from Douyin were generally shorter but achieved higher user engagement, while videos from Bilibili were longer with lower interaction (both P<0.001). Median GQS was 3 for Douyin and 2 for Bilibili (P=0.041), and median DSVSS was 3 for both (P=0.116). Videos performed poorly in DSVSS checklist in definition and classification [0.05 (IQR 0.03-0.07)], emphasizing chronicity [0.07 (0.05-0.10)], and individualized treatment [0.08 (0.03-0.10)], but performed well in avoiding exaggeration [0.84 (0.63-0.91)], absence of advertising [0.78 (0.66-0.88)], and in providing warnings for special populations [0.91 (0.87-0.96)] (P<0.001). This study effectively identified critical deficiencies of current short-videos on DED treatment, underscoring the necessity for more professional, guideline-based content and stricter platform supervision to improve the quality of online health information.
Wound complications following total hip arthroplasty are a challenging issue facing surgeons, with rates reported anywhere from 1 to 12% of patients. There currently exists a paucity of literature detailing the options for surgeons who encounter soft tissue defects or closure difficulties following total hip arthroplasty. With the increasing popularity of using the anterior and lateral approaches for more complex arthroplasty revisions and reconstructions, detailing options for soft tissue coverage options may prove valuable. This article will provide an overview of soft tissue coverage options for the anterior, posterior, and alternate approaches, and when a plastic surgeon should be consulted for assistance.
Background Water birth is increasingly popular, yet debates persist regarding its safety and efficacy. There is a need to assess the accuracy and sentiment of publicly available water birth content, and it is essential that water birth content be accurate to support informed decision-making. Objective To identify whether certain YouTube video characteristics play a role in determining whether the contents of the video are aligned with the published recommendations set forth by the American College of Obstetricians and Gynecologists.  Materials and methods An analysis of the top 100 English-language YouTube videos on "water birth" sorted by "most viewed" was conducted on March 9, 2023. After applying inclusion and exclusion criteria, a final set of videos met the inclusion criteria and were included in the analysis. Video characteristics were recorded. Video accuracy was assessed against 16 ACOG water birth guidelines. Scores: 1 (accurate), 0 (not mentioned), or -1 (inaccurate). Transcripts were analyzed using MonkeyLearn Sentiment Analyzer to determine sentiment.  Results Of the videos analyzed, the majority were neutral in their accuracy, while a smaller proportion were deemed accurate or contained inaccuracies. Critical safety topics, such as umbilical cord avulsion or neonatal infection risks, were almost universally omitted. Videos created by healthcare professionals demonstrated greater accuracy, while personal vlogs were predominantly neutral. Sentiment analysis revealed that most videos conveyed a negative sentiment, followed by positive and then neutral sentiment. Notable geographic disparities were observed, with North American content exhibiting greater emotional polarization compared to international content. Conclusion Most widely viewed YouTube content on water birth lacks alignment with ACOG guidelines, particularly regarding risk communication, posing misinformation risks.
Aquaculture is a rapidly growing sector in the global food production chain as a recognized fundamental source of high-quality proteins. One of the crucial tasks in aquaculture is phenotype prediction. While machine learning research has mainly focused on classification tasks on Big Data, in many bioinformatics applications, including aquaculture, the real challenge behind prediction problems is dealing with small sample and high-dimensional data. In such contexts, it is in fact common that the number of genetic features (such as SNPs) far exceeds the sample size. As a test case, this study focuses on the prediction of resistance to Viral Nervous Necrosis(VNN) from a population of European sea bass. We explore a range of machine learning techniques, from established methods such as Support Vector Machines and Gradient Boosting, to increasingly popular Deep Learning Approaches, also including a variant of image-based classification based on Chaos Game Representation. Besides standard training-test partitioning, we also considered a more challenging partition of the dataset that maximize the genomic distance among training and testing set to better reflect the kind of generalization problem encountered in breeding practice due to data scarcity typical of non-model species. Although all the animals belong to the same population, this approach offered the most appropriate way to ensure the procedure was sufficiently challenging given the available data. We assessed the performance of learning approaches in different scenarios, reducing the data dimensionality by selecting SNPs on the basis of functional information. Our experiments confirmed the difficult nature of this association task. However, each tested tool showed promising results in at least one scenario. While predicting disease susceptibility remains a challenging task for breeding programs, within the boundaries of the tested scenarios, our results show that machine learning approaches, combined with a controlled amount of additional functional information, can help mitigate the issues arising from high dimensional, low sample size datasets typical in the study of non-model species.
Meditation apps are increasingly popular but face significant engagement challenges. Most research does not meaningfully capture real-world engagement or associated user characteristics. Engagement patterns and reasons for engaging or disengaging remain relatively unexplored. This study aimed to examine Medito app user engagement over the first 30 days after download and how intended use, demographics, user traits, and mental health factors predict engagement. A prospective online survey was conducted among 668 Medito app users from 30 countries. Factors assessed included demographic factors (eg, age, sex, education, employment, and country of residence); user factors (eg, number of apps tried, hours of experience, meditation-related adverse events, expectations, readiness to change, and personality); and mental health factors (eg, quality of life, perceived stress, psychological distress, well-being, and satisfaction with life). Detailed engagement data included days of use, meditations completed, app opens, and minutes of use obtained via a data-sharing agreement with Medito. Minutes of use in the first 30 days after download served as the main outcome variable. App use was relatively low, with 50% (328/655) of users engaging for a total of 16 minutes or less in the first month after download (median 16.11, IQR 0-74.51 min). Fewer than 20% (124/655, 18.86%) of users continued using the app after 14 days. Intended use (mean 418.56, SD 472.5) significantly exceeded actual use (mean 70.02, SD 176.81; d=0.710; P<.001). In terms of user factors, expectation match (ie, extent to which outcomes from the app matched initial expectations; ρ=0.214; P=.002), expectations for anxiety (ρ=0.102; P=.01), expectations for attention or focus (ρ=0.091; P=.02), and conscientiousness (ρ=0.124; P=.003) were associated with higher engagement. Neuroticism was negatively associated with engagement (ρ=-0.103; P=.010). For mental health factors, satisfaction with life (ρ=0.123; P=.002) and well-being (ρ=0.135, P<.001) were associated with higher engagement, while perceived stress (ρ=-0.107; P=.007), psychological distress (ρ=-0.138, P<.001), and quality of life (ρ=-0.100; P=.011) were associated with lower engagement. Only readiness to change showed unique associations with higher engagement (semipartial r=0.156; P<.001). Regression analysis showed that only perceived stress predicted higher engagement (β=.020; P=.04). However, when mental health was included as a single component, expectations for anxiety (β=.015; P=.049) and readiness to change (β=.011; P=.048) predicted greater engagement, and mental ill health predicted lower engagement (β=-0.008; P=.049). Overall, app engagement is generally quite low. Acute stress motivated meditation app use, while chronic stress disrupted it. Engagement is optimal when experiences match expectations and users are prepared to make a change. More transparency is necessary in the promotion of meditation apps so that users have a realistic understanding of the time and effort required to achieve benefits.
Urban expansion threatens avian biodiversity in high-density cities globally, requiring strategies to enhance habitat connectivity through small-scale interventions. However, conventional ecological network planning often prioritizes biophysical metrics, overlooking the social values and public preferences that shape the long-term acceptance and success of conservation measures. To address this gap, this study integrates public bird preference data with ecological network modeling. Beijing, a megacity characterized by intense urbanization and active biodiversity governance, was selected as a representative case to test this socio-ecological approach. Citizen science observations (2015-2025) of 15 resident-favored bird species were combined with 35 environmental factors to assess habitat suitability for six functional avian groups using Maximum Entropy modeling (AUC: 0.756-0.897). Circuit theory analysis delineated an ecological network of 127 core sources, 260 stepping stones, and 1009 corridors, demonstrating substantial spatial overlap with the existing protected zones of the Beijing Garden City Nature Belts. Multi-scenario simulations showed that compared to random or patch-size-prioritized removal, conserving high-centrality stepping stones delayed connectivity decline and fragmentation by over 60% and preserved 68.6% of post-collapse connectivity. Building on these findings, we propose a three-tiered protection strategy for popular species, ranging from strict protection to adaptive management. In conclusion, by fundamentally shifting public preference from a peripheral to a central input in network analysis, this study establishes a novel, socially informed conservation framework. This integration enables precise identification of critical stepping stones and yields an actionable, prioritized conservation blueprint, thereby enhancing the practical relevance and implementability of ecological network designs for advancing bird-friendly cities worldwide.
The intimate coupling of photocatalysis and biodegradation (ICPB) serves as a promising alternative for rapid, enhanced antibiotics removal, while the concurrent induction of antibiotic resistance genes (ARGs) accumulation has become a critical barrier restricting its further industrial popularization. Here, we tracked ARGs fates in an ICPB reactor treating sulfamethoxazole (SMX) over 30 days, with emphasis on how microbial succession and functional adaptation within algae-bacteria consortia shape ARG dynamics. The ICPB system removed more than 71.7% of SMX within the first 7 days, yet this early-stage performance coincided with increased abundance of sul genes and the overall resistome, likely driven by folate biosynthesis and oxidative stress responses. With prolonged operation to 30 days, total ARGs abundance declined unexpectedly, even though SMX residuals accumulated. This shift was closely associated with sustained illumination that promoted algal proliferation, particularly Cyanobacteria. In parallel, carotenoid production was markedly enhanced through activation of the ε-carotene biosynthesis pathway, which reinforced oxidative stress scavenging and relieved folate-associated selective pressure, thereby mitigating ARGs dissemination. In addition, cyanobacteria-derived photosynthate favored autotrophic metabolism within the bacterial consortium, which reduced the abundance of genes encoding energy-dependent efflux pump transporters and consequently constrained the propagation of energy-intensive ARGs. Collectively, these findings highlight a cyanobacteria-mediated route to attenuate ARGs during prolonged ICPB operation and provide guidance for designing photocatalysis-coupled cyanobacterial biofilms for sustainable wastewater treatment.
Salvage prostatectomy (sRP) is one of several treatment options for localized prostate cancer recurrence after radiation. However, given the complexity of this operation, traditionally high complication rates, and poor functional outcomes, sRP has historically been underutilized. Herein, we aim to review the indications, outcomes, and technical advancements of sRP in modern practice. A literature review was performed using PubMed, Google Scholar, and Scopus for relevant articles that were synthesized in the current work. Improvements in interpretation of magnetic resonance imaging and increased adoption of molecular imaging can better detect local and oligometastatic recurrence. In combination with clinical variables, this can better select patients who may achieve a durable response from sRP. Ten-year biochemical recurrence-free survival after sRP ranges from 28 to 53%, with cancer specific survival ranging from 65 to 83%. While complication rates for sRP are higher than for primary prostatectomy, major complications, especially rectal injury, have decreased significantly. Erectile function is poor after sRP, although most studies report high rates of pre-operative impotence. Continence rates are highly variable (20-80%) secondary to heterogeneous reporting. Due to high rates of lymph node involvement, lymph node dissection should be performed with sRP and has prognostic value. Finally, robotic sRP is gaining popularity and may lead to improvements in continence, although further study is needed. Salvage prostatectomy can achieve durable cancer control in a substantial group of patients. With improving complication rates and functional outcomes in experienced hands, sRP remains an important treatment for radio-recurrent prostate cancer.
Personalized intelligent education's popularity has fueled demand for accurate prediction of learner performance through Knowledge Tracing (KT). However, current concept-level KT methods mainly treat all concepts associated with questions of varying difficulty levels equally, resulting in a lack of specificity in capturing question-related information. Additionally, some approaches learn question embeddings during model training, which can lead to a complex entanglement of question embeddings with the model. To address these issues, our study proposes an attentive pre-training embedding method called Semantic information Retrieval augmentation and Concept Label-Heterogeneous Graph representation for KT (SRHGKT). This method directly learns the interaction between questions and concepts through specialized designs, such as devising hybrid semantic retrieval to construct a knowledge structure that captures rich information about concepts. Furthermore, we design an innovative concept label-guided heterogeneous graph embedding fusion module to combine the advanced information from question-concept interactions with multiple aspects, resulting in pre-training question embeddings. We also introduce a forgetting question similarity attention to model the forgetting patterns of learners. Comprehensive experimental results, conducted on three real-world datasets, demonstrate that SRHGKT outperforms 14 state-of-the-art methods in predicting learner performance. Furthermore, generalizability tests show that our pre-training embeddings exhibits impressive generalization, achieving improvements of over 10% prediction accuracy, when applied to various KT models on the ASSISTment2009 dataset.
Preoperative intravenous iron has become increasingly popular as a strategy to optimize hemoglobin before major surgery. However, its potential benefit in non-anaemic patients undergoing cardiac surgery remains unclear. To address this uncertainty, we conducted a systematic review and meta-analysis to investigate whether preoperative IV iron reduces red blood cell transfusion requirements and improves hematologic and clinical outcomes in adults with normal baseline hemoglobin undergoing cardiac surgery. We conducted a systematic review and meta-analysis following PRISMA 2020 guidelines. We searched PubMed, Embase, Scopus, Web of Science, and the Cochrane Library until October 2025 for randomized controlled trials. Eligible studies compared preoperative IV iron to a control (placebo, saline, or standard care) in non-anaemic (per WHO definition) adult patients (≥ 18 years) undergoing cardiac surgery. The primary outcomes were the incidence of postoperative RBC transfusion and the number of units transfused. Secondary outcomes included postoperative hemoglobin level, Postoperative iron indices, length of ICU stay, length of hospital stay (LOS), overall postoperative infection, All-cause mortality, and adverse events possibly related to IV iron (hypersensitivity, anaphylaxis). We used the Cochrane ROB 2 tool for bias assessment and for evidence certainty. Pooled Risk ratios, odds ratios, mean difference, and standardized mean difference with 95% confidence intervals were calculated using random-effects models, with the fixed-effects model applied when heterogeneity was absent or low (I² < 10%). From 529 initial records, 3 RCTs met the inclusion criteria, encompassing 338 patients. The overall risk of bias was low to moderate. Preoperative IV iron significantly reduced the incidence of postoperative RBC transfusion compared to the control group (Risk Ratio [RR] = 0.62; 95% CI 0.43-0.88; p = 0.008; I² = 0%), representing a 38% relative risk reduction. Furthermore, IV iron significantly decreased the mean number of RBC units transfused (Mean Difference [MD] = - 1.08 units; 95% CI - 1.61 to - 0.54; I² = 0%). While no significant difference was observed in hemoglobin levels at 48 h or one week postoperatively, the IV iron group showed significantly higher hemoglobin at 4-6 weeks (MD = 0.84 g/dL; 95% CI 0.41-1.26; p = 0.0001). IV iron also significantly increased postoperative serum ferritin and transferrin saturation. There were no statistically significant differences in overall postoperative infection rates (RR = 1.16; 95% CI 0.64-2.08) or all-cause mortality (Risk Difference = - 0.00; 95% CI - 0.03 to 0.03). The GRADE certainty of evidence for the primary outcome was moderate. In non-anaemic adult patients undergoing cardiac surgery, preoperative IV iron administration significantly reduces the incidence of postoperative RBC transfusion and the total volume of blood transfused. This intervention also improves hemoglobin levels during the 4-6 week recovery period without an increased risk of infection or mortality. The moderate-certainty evidence suggests this is a beneficial strategy, though further adequately powered RCTs are warranted to strengthen these findings. CRD420251161421.
This study aimed to investigate the clinical feasibility of artificial intelligence-rapid on-site evaluation (AI-ROSE) based on exfoliated cell blotting from percutaneous puncture biopsy specimens for diagnosing pulmonary lesions and to provide a reference for intraoperative rapid diagnosis. A total of 266 patients with pulmonary lesions who underwent computed tomography (CT)-guided percutaneous core needle biopsy between June 11 and November 27, 2024, were enrolled. Exfoliated cell prints from biopsy specimens were stained with Diff-Quik, followed by diagnosis using AI-ROSE. Using the final histopathological diagnosis as the standard, the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of AI-ROSE and conventional cytological diagnoses were compared. The consistency between the methods and histopathological diagnosis was analyzed. The diagnostic times for AI-ROSE, cytology, and histopathology were recorded and compared. Postoperative complications were documented, and the correlation between lesion characteristics and complications was analyzed. Compared with histopathological results, AI-ROSE achieved a sensitivity of 95.67%, specificity of 79.31%, diagnostic accuracy of 92.11%, PPV of 94.31%, and NPV of 83.64% in diagnosing pulmonary lesions, with good consistency (κ = 0.764, P < 0.001). No significant difference in the AI-ROSE diagnostic accuracy was observed among the different pathological types (P > 0.05). Conventional cytological diagnosis showed a sensitivity of 87.50%, specificity of 85.71%, and accuracy of 87.10%, with lower consistency and histopathology (κ = 0.665, P < 0.001) than those of AI-ROSE. The mean diagnostic time of AI-ROSE was 254.60 ± 13.88 s, which was significantly shorter than that of cytology (1.48 ± 0.86 days) and histopathology (2.37 ± 1.42 days). The overall incidence of postoperative complications was 22.93%, including pneumothorax (12.78 %) and needle tract bleeding/mild hemoptysis (9.77%), with no fatal complications. A smaller nodule volume was associated with a higher risk of puncture bleeding (P = 0.004), whereas lesion size and puncture path length were not significantly correlated with pneumothorax risk (P > 0.05). AI-ROSE enables rapid intraoperative diagnosis of pulmonary lesions in percutaneous biopsy with high diagnostic performance and consistency with histopathological results, demonstrating its favorable value for clinical application and popularization.
Amyloid-mediated proteotoxicity underlies over 50 diseases. Cryo-EM establishes direct links between filament morphologies and pathology, although microbial functional amyloids illustrate that this fold can evolve to serve physiological roles, unlike their pathogenic counterparts. Despite the growing popularity of the processing software cryoSPARC for single-particle analyses, RELION remains the dominant software platform for performing helical reconstruction of amyloid structures, highlighting an area for further development. Here, we present comprehensive processing guidelines for helical reconstruction of helical amyloids using cryoSPARC. Through systematic reprocessing and validation of publicly deposited datasets, we demonstrate the current capabilities and identify the key limitations, emphasizing the need for amyloid-specific parameter optimization within cryoSPARC workflows. Our findings showcase a potential for developing unsupervised processing workflows to meet the demanding throughput requirements of time-resolved in vitro studies and large-scale compound-screening initiatives, thereby accelerating therapeutic drug development. Ultimately, our goal is to shift the focus of amyloid cryo-EM from computationally intensive processing challenges towards addressing fundamental biological questions that enhance our capacity for treatment discovery.
Electronic cigarettes (e-cigarettes) have gained popularity as a less harmful alternative to conventional cigarettes, yet their associations with lung cancer risk after smoking cessation remain uncertain. Here we evaluated 4,524,895 adults with a conventional smoking history who participated in the Korean National Health Screening Program in 2018 (baseline), with prior records from 2012-2014. Participants were classified as current smokers, short-term quitters or long-term quitters, and followed up to December 2023. Daily e-cigarette use at baseline was used to define post-cessation e-cigarette use. Lung cancer incidence and lung cancer-specific death (LCSD) were assessed using multivariable Cox models. Over 24,182,543 person-years, 35,887 lung cancers and 12,807 LCSD events occurred. Compared with complete quitters, e-cigarette use after smoking cessation was associated with higher risks of lung cancer incidence (adjusted hazard ratio (aHR) 1.56, 95% confidence interval (CI) 1.24-1.97) and LCSD (aHR 2.00, 95% CI 1.28-3.15). Associations were directionally consistent in short-term and long-term quitters and were prominent in the high-risk subgroup (incidence: aHR 1.91, 95% CI 1.44-2.53; LCSD: aHR 1.92, 95% CI 1.13-3.24). Although causality cannot be established, these findings suggest that e-cigarette use after smoking cessation may attenuate the benefits of complete cessation for lung cancer prevention.
Vocal humming occupies a distinctive position in Indian popular music as an emotive bridge linking melody, memory, and mood. Zubeen Garg's characteristic humming style, noted for its fluidity and expressive warmth, invites systematic investigation of what acoustically defines its appeal. This study presents a quantitative acoustic profiling of Garg's humming, focusing on how measurable voice parameters contribute to its distinct sonic character. A detailed set of temporal, spectral, and timbral features was extracted, including jitter, shimmer, harmonic-to-noise ratio, spectral centroid, rolloff, tilt, roughness, and Mel-frequency cepstral coefficients (MFCCs). The analyses reveal characteristic temporal patterns (mean jitter ≈ 0.34, shimmer ≈ 0.18). Statistical comparisons show highly significant differences in fundamental frequency between Garg's humming and singing (P < 0.01) and in jitter between his humming and other singers' humming (P < 0.01). Multiple MFCCs also showed significant distinctions (P < 0.05), indicating limited timbral differentiation in harmonic structure. Spectral features showed non-significant trends toward lower centroid (P ≈ 0.11) and elevated roughness (P ≈ 0.06). These results indicate that a subset of temporal and timbral features contributes to an acoustic profile associated with Garg's humming. While no perceptual testing was undertaken, interpretations are grounded in established psychoacoustic literature linking acoustic measures to perceived attributes such as tonal warmth and vocal steadiness. Within this interpretive framework, the findings suggest that Garg's humming exhibits an acoustically measurable combination of selected temporal and spectral characteristics that may be associated with its perceived resonant quality.
Introduction Cigarette smoking is the leading cause of preventable death and disease and arises due to prolonged and repeated inhalational exposure to chemical toxicants found in cigarette smoke. Within this context, vaping products, also termed e‑cigarettes or electronic nicotine delivery systems, have been positioned by public health bodies as being substantially less harmful than combustible cigarettes. Furthermore, evidence also suggests that vaping products may be more effective in supporting smoking cessation than traditional support such as nicotine replacement therapy. The UK National Health Service "Swap to Stop" initiative operationalised a harm reduction approach to support smokers' use of vaping products in switching from cigarette smoking, by providing vaping starter kits via Stop Smoking Services (SSS). Objectives The aims of this study were to assess the provision of vaping products and provider-reported aggregate quit rates for vaping products compared with other forms of smoking cessation support, among UK SSS, using data obtained from Freedom of Information requests. Methods Questionnaires were sent to 43 local authorities in the UK and, of these, 31 (72.1%) responded. Two authorities (4.7%) withheld permission for the information they provided to be shared or reused for news/reporting. Consequently, responses from 29 (67.4%) local authorities were analysed. Results Vaping products are now provided to smokers by the majority (n = 26; 89.7%) of SSS providers, and this is predominantly through the provision of open systems. The majority of providers provide a variety of flavoured vaping products, including fruit, mint/menthol, and tobacco flavours, and among those providing flavour information, 78.9% of service providers (n = 15) reported that 'fruit' flavours were most popular or most frequently provided. Quit rates were variable across the different service providers, ranging from 43% to 77% for vaping products and from 35% to 81% for other forms of cessation support. Among those providers who reported quit rates for both vaping products and other forms of support, the average quit rates were 61.5% for vaping products and 56.2% for other forms of support (p = 0.04). Conclusions Overall, these findings support that vaping products may provide smoking cessation support to smokers that exceeds that of other forms of support and that flavoured vaping products are highly provided and utilised by UK SSS providers.
One of the most peculiar behaviors of rodents is tail-rattling, a rapid vibration of the tail which can produce a rattling sound when performed against a hard surface. Tail-rattling is widespread across rodents, having been observed in 32 species from 19 genera, including Mus and Rattus. Rodent tail-rattling has been known from the eighteenth century, when it was described as part of the defensive behavior of the crested porcupine. From the 1940s, comparative psychologist John Scott systematically studied tail-rattling in laboratory mice, making it widely popular among laboratory researchers as one of the main components of the mouse agonistic ethogram. Currently, tail-rattling is interpreted almost exclusively as a threat display. However, historically, tail-rattling has been described in a great variety of different contexts, including intraspecies agonism, antipredator behavior, male-to-female courtship, female proceptive behavior, caressing by a human caregiver, social isolation, home-cage change, footshock-induced fear and decisional conflict. This wide range of contexts indicates that tail-rattling is not just a sign of aggressiveness, but can be associated with a set of emotions comprising anger, fear, distress, uncertainty, sexual arousal and physical pleasure. Notably, tail-rattling is expressed by rodents in emotional contexts of both negative and positive affective value. In the present article, firstly we provide a historical overview of rodent tail-rattling observations, starting from porcupines and ending with mice, covering a period from the 1770s to 2026. We then discuss what emotional state tail-rattling may express. Subsequently, we evaluate the possible functions of rodent tail-rattling. Additionally, we present our explanatory model of tail-rattling, the discharge model. Finally, we propose future directions for rodent tail-rattling research, including the employment of tail-rattling as a marker of animal welfare in laboratory and zoo rodents.