Established determinants of health in the elderly help guide routines for indicated vaccine administration, while unmeasured frailty may limit vaccine access. We evaluate the performance of the 2024-2025 COVID-19 vaccine adapted to the Omicron JN.1 lineage in a Swedish population aged ≥65 years (N = 245 696). Vaccine effectiveness (VE) on COVID-19-related hospitalization and a negative control outcome (NCO; all-cause mortality) are assessed in various cohorts between October 1, 2024 to March 31, 2025. The VE was 75% (95% CI 70%-79%) overall, and 84% (95% CI 80%-87%) and 65% (95% CI 34%-82%) in individuals with and without vaccination with the prior updated COVID-19 vaccine in 2023-2024, respectively. The NCO in individuals exposed to the study vaccine in 2024-2025 was half of that seen in those not exposed to the vaccine (HR 0.43 [95% CI 0.40-0.45]). Removing individuals hospitalized with COVID-19 from this population did not change the difference in NCO (HR 0.43 [95% CI 0.41-0.46]). These findings suggest the presence of selection effects arising from under-provision of health services to elderly individuals with frailty. The healthy vaccinee effect should be considered in observational studies of the effectiveness of updated COVID-19 vaccines in elderly populations.
Bifid inferior turbinate is a rare anatomical variant of the lateral nasal wall that may be overlooked on nasal endoscopy or mistaken for an abnormality of the uncinate process or middle meatus. A 24-year-old woman presented with long-standing right-sided nasal obstruction, frontal headache, rhinorrhea, snoring, sleep disturbance, and allergic rhinitis. Computed tomography (CT) demonstrated an inferomedially oriented duplication of the left inferior turbinate, bilateral inferior turbinate hypertrophy, an S-shaped septal deviation, and concha bullosa. She underwent septoplasty, inferior turbinoplasty, and concha bullosa resection. Preoperative recognition of bifid inferior turbinate was important because it occurred alongside common obstructive abnormalities requiring surgery. We also provide an updated review of reported cases, focusing on the relationship with the uncinate process, anatomical orientation, and implications for surgical planning. Careful CT assessment may prevent misclassification and help preserve key endoscopic landmarks.
Status dystonicus (SD), also called dystonic storm or dystonic crisis historically, represents a rare and life-threatening exacerbation of dystonia characterized by continuous (tonic) or phasic rapidly recurring dystonic spasms. Common triggers include infections, abrupt changes in medication, and metabolic stress, among others, and necessitate early recognition with multidisciplinary management to prevent multisystemic failure or dysfunction. SD arises in patients with generalized dystonia, more commonly in those with secondary causes, and is associated with basal ganglia dysfunction and predominantly dopaminergic disturbances. The Dystonia Severity Action Plan is a widely accepted staging tool that requires bedside assessment and helps inform therapeutic decisions and intervention levels. Management principles center on identifying and removing triggers, optimizing sedation and airway management, and administering disease-specific therapies. The review aims to provide an overview of the clinical spectrum, the physiological basis, commonly described precipitating factors, and updated management strategies for SD, highlighting a practical approach to the early identification of the syndrome and the bundling of care. A narrative review of peer-reviewed literature from PubMed and Scopus databases was conducted, with emphasis on publications covering etiopathogenesis, risk factors, clinical grading systems, therapeutic options, and outcomes. Key consensus guidelines and case series were appraised. It is evident that early diagnosis and triage, with adequate management, are key to improving survival and neurological outcomes in SD. Adoption of standardized clinical pathways and multicenter data reports will help improve understanding of SD's natural history, clinical evaluation, and therapeutic efficacy across different etiologies.
This study aimed to evaluate the performance of LUS aeration score in predicting extubation failure among mechanically ventilated neonates. This review was conducted in accordance with PRISMA-DTA 2018. Electronic searches were performed in PubMed, ScienceDirect, Wiley, Nature, and Springer. Methodological quality was assessed using QUADAS-3. Diagnostic meta-analysis was performed in Stata 17.0 using MIDAS, while univariable bivariate meta-regression was conducted in R using the mada package. Pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), log diagnostic odds ratio (logDOR), and area under the curve (AUC) were calculated. Clinical applicability was assessed using Fagan nomograms, while sensitivity analysis, subgroup analysis, and Deeks' funnel plot asymmetry test were conducted to evaluate robustness, heterogeneity, and publication bias. Ten studies involving 859 neonates were included. LUS aeration score showed high diagnostic accuracy, with a pooled sensitivity of 0.87, specificity of 0.86, PLR of 6.13, NLR of 0.15, logDOR of 3.71, and AUC of 0.93. Heterogeneity was moderate for sensitivity and substantial for specificity. Anatomical scanning coverage was the only significant moderator in meta-regression (p = 0.049), with posterior-inclusive protocols associated with a lower false-positive rate. Deeks' test showed no significant publication bias. LUS aeration score demonstrates good diagnostic performance for predicting neonatal extubation failure and may support clinical decision-making as an adjunct to conventional extubation readiness assessment. Standardized, validated scoring protocols and age-specific external validation are required before a universal cutoff can be recommended. What is Known: • Extubation failure remains a clinically important complication in mechanically ventilated neonates and is associated with increased morbidity. • Lung ultrasound (LUS) is a bedside, radiation-free imaging method, whereas the LUS aeration score is a quantitative measure of regional aeration loss; reported accuracy for predicting extubation failure varies across studies. What is New: • This updated diagnostic meta-analysis of 10 studies involving 859 neonates found strong pooled diagnostic performance of the LUS aeration score for predicting extubation failure, with a sensitivity of 0.87, specificity of 0.86, and AUC of 0.93. • Exploratory univariable bivariate meta-regression identified anatomical scanning coverage as the only significant overall moderator, with posterior-inclusive protocols associated with a lower false-positive rate.
The Asian Working Group for Sarcopenia (AWGS) updated its diagnostic criteria in 2025 by incorporating body mass index (BMI)-adjusted skeletal muscle mass. This revision may influence the prevalence and clinical interpretation of sarcopenic obesity in heart failure (HF). We conducted a single-center retrospective cohort study of 589 patients aged ≥65 years who were hospitalized for HF. Application of the AWGS 2025 criteria significantly altered classification, increasing the prevalence of sarcopenic obesity from 7.8% to 13.6%. Among the 4 groups defined by sarcopenia (AWGS 2025) and obesity, patients with sarcopenia without obesity had the worst prognosis, whereas those with sarcopenic obesity had preserved survival (log-rank P=0.038). Following the transition from the AWGS 2019 to AWGS 2025 criteria, newly classified patients with sarcopenic obesity were more frequently female and had a higher BMI with preserved height-adjusted muscle mass compared with patients with persistent sarcopenic obesity. Mortality and gait speed were comparable between the persistent and newly classified sarcopenic obesity groups (both P>0.05). The AWGS 2025 sarcopenia-obesity phenotype classification showed no improvement in discrimination or the Akaike information criterion for prognosis compared with the AWGS 2019 classification (both P>0.05). The AWGS 2025 criteria increase the prevalence of sarcopenic obesity by identifying a distinct phenotype in patients with HF. However, this expanded classification does not improve risk stratification.
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To quantify the magnitude and trends the national and subnational burden of Alzheimer's disease and other dementias (ADOD) in Mexico from 1990 to 2023, analyzing patterns by sex and age and exploring their association with the Socio-Demographic Index (SDI) and the Healthcare Access and Quality Index (HAQI). A secondary ecological study was conducted using updated estimates from the Global Burden of Disease and Risk Factors Study (GBD) 2023. Prevalence, incidence, mortality, and disability-adjusted life years (DALYs) were examined. Temporal trends were assessed using joinpoint regression. Pearson correlation and linear regression were used to evaluate associations between DALYs rates and SDI and HAQI. Between 1990 and 2023, ADOD prevalence and incidence increased, despite significant declines in age-standardized prevalence and incidence rates. Females consistently experienced higher mortality and disability, with age-standardized DALYs rates 1.28 times those of males. The ADOD burden increased sharply with age, peaking among those aged 85 years and older, with premature mortality accounting for 63.0% of total DALYs. A significant increase in DALYs rates occurred during 2020-2023 after previous periods of gradual decline. DALYs rates were negatively correlated with both SDI and HAQI. ADOD disproportionately affect women, while higher modeled burden was observed in several states with lower socioeconomic development and weaker health system performance. The post-2020 increase represents an epidemiological signal warranting further investigation into excess mortality among people with dementia, healthcare disruption, social isolation, and changes in long-term care during the COVID-19 period. Strengthening early diagnosis, long-term care, and management of modifiable risk factors is essential to reduce the future burden and persistent regional and sex-based inequalities in ageing populations.
To evaluate the efficacy and safety of oral PCSK9 inhibitors in adults with hypercholesterolemia by synthesizing evidence from randomised controlled trials. This systematic review and meta-analysis followed PRISMA guidelines and was registered on PROSPERO (CRD420261303350). PubMed, Embase and Scopus were searched from inception to March 2026 for randomised controlled trials comparing oral PCSK9 inhibitors with placebo in adults with hypercholesterolemia. Primary outcomes were changes in low-density lipoprotein cholesterol (LDL-C) and triglycerides. Secondary outcomes included other lipid parameters, adverse events and mortality. Random-effects models were used to calculate mean differences (MD) and risk ratios (RR) with 95% confidence intervals (CI). Quality of the included studies was assessed using the RoB2 tool and certainty of evidence was assessed using the GRADE approach. Five randomised controlled trials (n = 4268) were included. Oral PCSK9 inhibitors significantly reduced LDL-C (MD -49.49 mg/dL; 95% CI -54.81 to -44.18; p < 0.00001) and triglycerides (MD -11.65 mg/dL; 95% CI -15.53 to -7.78; p < 0.00001). Significant reductions were also observed in non-HDL cholesterol, apolipoprotein B, lipoprotein(a) and total cholesterol. Dose-dependent effects were noted, with greater reductions at higher doses. No significant differences were observed in mortality or overall adverse events. Treatment discontinuation due to adverse events was lower with intervention. Oral PCSK9 inhibitors were associated with clinically meaningful improvements in multiple lipid parameters while maintaining a favourable short-term safety profile. However, the available evidence is derived primarily from short-term randomised trials evaluating surrogate lipid outcomes. Larger randomised trials with longer follow-up and cardiovascular outcome data are needed to better define the long-term clinical role of oral PCSK9 inhibitors.
Pediatric dental behavior management is difficult to teach because learners need safe opportunities to practice. Digital simulation tools offer new opportunities for safer and more structured training. However, the use of these approaches in pediatric dental behavior management education has not been systematically synthesized. This systematic review aimed to synthesize the evidence on digital simulation tools in pediatric dental behavior management education, focusing on their design, implementation, and educational outcomes, and the extent to which virtual reality (VR) and serious game-based approaches have been studied. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, PubMed, Scopus, Web of Science, Embase, the Cochrane Library, and the CNKI were searched for studies published between January 1, 2015, and December 10, 2025. An updated search using the same strategy across all 6 databases was performed on June 5, 2026. Only original research studies were eligible. Study characteristics, intervention design, implementation approaches, and educational outcomes were extracted, including technical skill acquisition, soft-skill and affective competency development, and learner experience and acceptability. Risk of bias was assessed independently by 2 reviewers using design-specific appraisal tools. Due to substantial heterogeneity in study designs, interventions, and outcome measures, findings were synthesized narratively rather than through meta-analysis. A total of 21 studies were included, including 20 studies identified in the original search and 1 study identified in the updated search. The identified evidence focused mainly on VR, haptic virtual reality simulation systems, augmented reality, 3D-printed models, and AI-driven chatbots. No eligible studies on gamification or serious games were identified, despite the inclusion of serious games and gamification terms in the search strategy. VR scenario simulations enhanced learners' empathy and self-efficacy in communicating with child patients, although these effects appeared to require reinforcement through repeated use. Haptic virtual reality simulation showed advantages in supporting specific procedural skills. Augmented reality improved local anesthesia training efficiency. The 3D-printed models and role-playing with professional actors enhanced clinical realism and communication skills, while AI-driven chatbots improved caregiver oral health knowledge and behaviors. Across studies, these tools were positioned as complements, rather than replacements for, traditional teaching. Evidence suggests that digital simulation tools, especially VR-based approaches, may support pediatric dental behavior management education by enhancing procedural practice, empathy, communication, confidence, and caregiver-related learning. However, substantial heterogeneity, reliance on self-reported measures, and the rapid evolution of digital simulation technologies limit the strength and currency of the evidence. The absence of eligible serious game studies indicates an important research gap. This review highlights their practical value for curriculum development and future educational tool design. Future work should evaluate VR and serious game-based approaches using stronger study designs, standardized outcomes, longer follow-up, and implementation strategies.
Disease relapse remains the leading cause of failure following allogeneic hematopoietic cell transplantation (HCT). As novel prophylactic strategies increasingly aim to universally eliminate all forms of graft‑versus‑host disease (GVHD), how these approaches may inadvertently sacrifice graft‑versus‑leukemia (GVL) activity in the post‑transplant cyclophosphamide (PTCy) era is unclear. To evaluate the associations between time‑updated GVHD phenotypes and clinical outcomes, including relapse, non‑relapse mortality (NRM), and overall survival (OS), in patients undergoing PTCy‑based haploidentical or mismatched unrelated donor (MMUD) HCT. This was a retrospective cohort study using the Center for International Blood and Marrow Transplant Research registry. Participants included 7,055 patients with hematologic malignancies who received a first haploidentical or MMUD HCT with PTCy from 2013-2021. Associations with relapse, NRM and OS were evaluated using multi‑state time‑dependent Cox proportional hazards models and a multi‑state random survival forest (MS‑RSF). Time‑updated acute and chronic GVHD phenotypes included isolated grade II acute GVHD (aGVHD), grade III-IV aGVHD, mild chronic GVHD (cGVHD), and immunosuppressive therapy-requiring (IST‑requiring) cGVHD. IST‑requiring cGVHD without antecedent aGVHD was associated with a lower modeled relapse hazard compared with remaining GVHD‑free (Hazard Ratio [HR], 0.74; 95% confidence interval [CI], 0.62-0.89; False Discovery Rate (FDR)-adjusted p (q)=0.006) and lower overall mortality (HR 0.62; 95% CI, 0.53-0.73; q < 0.001). In contrast, grade III-IV aGVHD was associated with significantly higher modeled NRM (HR, 3.15; 95% CI, 2.57-3.84; q < 0.001). Mild cGVHD and isolated grade II aGVHD showed intermediate patterns without consistent associations. These associations were directionally consistent across multiple analytic approaches, including standard time‑dependent Cox regression, dynamic and fixed landmark analyses, and MS‑RSF. In this large PTCy‑treated mismatched donor cohort, IST‑requiring cGVHD was the GVHD phenotype most consistently associated with lower relapse incidence, whereas severe aGVHD was associated with higher NRM. These findings highlight heterogeneity in GVHD phenotypes and suggest that strategies distinguishing toxic acute GVHD from chronic alloreactivity patterns may better balance morbidity and long‑term disease control. Given that relapse remains the predominant cause of post‑transplant mortality, approaches aiming to universally eliminate all GVHD warrant careful reconsideration.
This study aims to map ethical, legal, social, professional, and implementation issues associated with artificial intelligence (AI) in neonatal intensive care units (NICUs). A JBI-informed scoping review using the population-concept-context framework was reported according to PRISMA-ScR. Peer-reviewed English-language articles published from 1 January 2016 to 31 May 2026 were eligible. Because the original exports and screening log were unavailable, a documented updated rerun was completed on 13 July 2026 using public PubMed-indexed bibliographic searching, supplementary publisher and bibliographic web searching, and backward and forward citation chaining. Exact strategies and record-level decisions are provided as online resources. The retrieval log contained 78 record captures. After removal of 21 duplicates, 57 unique records were screened; 45 full texts were assessed, 14 were excluded with documented reasons, and 31 sources were included. Eight recurring domains were identified: data governance; bias and fairness; transparency and explainability; human oversight; accountability and surveillance; parental engagement; professional readiness and workflow; and equitable implementation. Empirical evidence was concentrated on parent and nurse perceptions, pain assessment, counseling, and explainability, whereas consent processes, subgroup fairness, liability, and post-deployment safety remained under-studied.  Ethically responsible NICU AI requires secure governance, local and subgroup validation, understandable communication, active clinician oversight, defined accountability, staff and family engagement, and prospective monitoring. Generative AI should remain supervised and should not replace clinician-family communication. • Artificial intelligence is increasingly being developed for neonatal outcome prediction, monitoring, pain assessment, clinical decision support, documentation, and family communication, but relatively few systems have progressed to validated routine NICU use. • The use of AI in neonatal care raises concerns regarding privacy, algorithmic bias, explainability, accountability, human oversight, parental trust, and equitable access. • This scoping review identifies eight recurring ethical and implementation domains for NICU AI: data governance, fairness, transparency, human oversight, accountability, parental engagement, professional readiness, and equitable implementation. • Current empirical evidence is concentrated on stakeholder perceptions, pain assessment, counseling, and explainability, while consent processes, subgroup fairness, legal responsibility, and post-deployment safety monitoring remain insufficiently studied.
Anxiety and depression impose substantial clinical and economic burdens worldwide, with high prevalence, impaired functioning, and elevated health care costs. Digital self-help interventions offer scalable and potentially cost-effective strategies; however, evidence from rigorously controlled economic evaluations remains sparse. This trial aims to evaluate the effectiveness and cost-effectiveness of 2 Norwegian mental health apps: Tankevirus (cognitive behavioral therapy-based) and Grubl (metacognitive therapy-based), compared with a digital placebo in reducing anxiety and depression symptoms, improving health-related quality of life, and generating quality-adjusted life years. The Mental Health Intervention With Digital Applications (MIND-APP) trial is a 3-arm randomized controlled trial (1:1:1 allocation) conducted fully remotely via a bespoke smartphone research platform. A total of 1000 Norwegian residents aged 16 years or older with mild to moderate symptoms of anxiety and/or depression will be recruited through national digital outreach. Coprimary outcomes are changes in anxiety (Generalized Anxiety Disorder-7) and depression (Patient Health Questionnaire-9) scores from baseline to postintervention (2-4 weeks). Secondary outcomes include health-related quality of life (EQ-5D-5L), quality-adjusted life years accrued over 6 months, functional impairment (Work and Social Adjustment Scale), health care resource use, and adverse events. Incremental cost-effectiveness ratios for Tankevirus and Grubl relative to placebo will be estimated from the perspective of public health services. Funding was secured in April 2025, with ethical approvals, licensing, and app development planned through 2026. Recruitment will commence in 2027, with follow-up through 2027 and early 2028. An extension of the timetable has been approved by the funding agent to allow inclusion of an updated version of the Tankevirus app, which will be ready for testing around May 2027. Results are expected to be published in autumn 2028 and will provide robust evidence on the clinical and economic value of scalable app-based interventions for common mental health disorders. This trial will be among the first large-scale registered reports to combine rigorous clinical and economic evaluation of digital mental health interventions. Findings will inform health policy and resource allocation by determining whether low-cost, app-based programs represent cost-effective solutions for reducing the burden of anxiety and depression. ClinicalTrials.gov NCT07627204; https://clinicaltrials.gov/study/NCT07627204. PRR1-10.2196/84096.
To investigate recruitment and retention of older people with dementia in clinical trials focused on evaluating pharmacological interventions for the treatment of cognitive symptoms of dementia. A scoping review conducted using Joanna Briggs Institute methodological guidance. A systematic search of five databases and the International Clinical Trials Registry Platform was conducted from inception to July 2023, and updated in January 2025. Randomised controlled trials of any type in English were eligible if they included people ≥65 years, with a dementia diagnosis (any sub-type/stage), focused on pharmacological management of cognitive symptoms of dementia in any setting. Following screening and data extraction, findings were tabulated descriptively to present study characteristics and approaches to recruitment and retention. 131 trials were included. Reasons for participant exclusion were having no carer present (n = 131 studies), and using specific medications such as anticholinergics (n = 28 studies). A small number of studies (n = 12) provided limited details on recruitment approaches. Recruitment strategies ranged from clinical referrals by investigators and treating physicians to community advertising and the re-engagement of previous trial participants. Reporting of retention approaches was limited across included studies. The mean sample size was 427 participants, and the mean retention rate was 75.4%, with adverse events, carer unavailability and withdrawal of consent among the most commonly reported reasons for discontinuation. Trials involving older people with dementia may not provide generalisable findings due to recruitment and retention challenges. Future research should focus on overcoming these challenges and clearly reporting strategies that may be of benefit to other researchers.
Brain shift during neurosurgical tumor resection reduces the reliability of preoperative image-based navigation and increases the need for updated intraoperative image interpretation. Intraoperative ultrasound (iUS) provides accessible intraoperative anatomical information but remains difficult to interpret because of speckle noise, weak contrast, and ambiguous tumor appearance. This study aims to develop an iUS-based brain tumor segmentation framework with boundary-overlay visualization to support surgical assistance. We propose a multi-scale attention-based tumor segmentation framework. Volumetric ultrasound features are extracted by a 3D convolutional backbone and hierarchically aggregated across scales. Cascaded attention refines tumor-relevant features, followed by multi-scale context aggregation to improve robustness to tumor size and appearance variations. The predicted mask is converted into a boundary overlay for intuitive iUS visualization. The method was evaluated on the public RESECT dataset and illustrated on two external clinical cases. A segmentation-assisted interpretation assessment examined whether algorithm-derived overlays improve junior neurosurgeon annotation consistency relative to a senior expert reference. On the RESECT dataset, the proposed framework showed segmentation performance comparable to established volumetric baselines while providing a more sensitive tumor-region detection profile. Precision, specificity, and surface-distance metrics allowed the sensitivity gain to be interpreted together with false-positive behavior and surface agreement. Ablation studies supported the contribution of cascaded attention and multi-scale contextual aggregation. In the interpretation assessment, mean junior-senior agreement improved from 76.56% DSC without algorithm assistance to 90.60% DSC after reviewing the algorithm-derived overlay. The proposed iUS-based tumor segmentation framework provides segmentation-derived boundary-overlay visualization for intraoperative interpretation. The results support its potential as a computer-assisted intraoperative interpretation tool, while further validation on larger multi-center cohorts, multiple observers, and multiple intraoperative time points remains necessary.
Acute myocarditis is an inflammatory disease of the myocardium with an annual incidence of 4-14 per 100,000 individuals, predominantly affecting young adults. Its clinical features are frequently nonspecific, mimicking acute coronary syndrome, which makes early recognition and management challenging. The disease results from infectious (predominantly viral) and noninfectious triggers, including autoimmune disorders, immune checkpoint inhibitors and mRNA vaccines. Pathophysiology involves a dysregulated interplay between innate immunity and adaptive immunity. Presentation is typically dominated by chest pain, with dyspnea and syncope reported less frequently. Cardiac magnetic resonance (CMR), with the 2018 updated Lake Louise criteria, has become the cornerstone of noninvasive diagnosis, whereas endomyocardial biopsy (EMB), in experienced centres, remains the gold standard for histological characterization and guiding immunosuppressive therapy. Uncomplicated myocarditis usually resolves spontaneously. However, approximately 25% of patients with myocarditis have left ventricular systolic dysfunction, ventricular arrhythmias or acute heart failure. Mortality ranges from 1% to 7%, depending on presentation, aetiology and specific populations. Treatment centers on guideline-directed heart failure therapy, with immunosuppression reserved for complicated presentations and virus-negative, autoimmune or histologically specific subtypes. Mechanical circulatory support is critical in fulminant cases, where mortality is high. This clinical review synthesizes recent guideline updates and emerging trial data, primarily from literature published in the past 10 years, to support a phenotype-driven approach to acute myocarditis, in which management is guided by clinical severity, suspected aetiology, selective use of CMR and EMB and targeted therapy. Ongoing trials investigating corticosteroids, targeted biologics and novel therapies may further refine personalized immunomodulatory strategies.
Five new Oriental species of Ptychoptera Meigen, 1803 are herein described and illustrated: Ptychoptera hantu Kolcsár & Fasbender, sp. nov. from Singapore, representing the first record of the family from the country; P. phutphi Kolcsár & Fasbender, sp. nov. from western Thailand; P. pseudosimilis Fasbender, sp. nov. from Arunachal Pradesh, India; P. vietnamensis Paramonov, sp. nov. from northwestern Vietnam; and P. srilankaensis Paramonov, sp. nov. from central Sri Lanka. In addition, P. annandalei Brunetti, 1918, P. perbona Alexander, 1946, and P. persimilis Alexander, 1947 are redescribed, with P. annandalei newly recorded from Thailand and P. perbona from both Thailand and Vietnam. Ptychoptera cordata Zhang & Kang, 2021 is synonymized with P. annandalei and P. perbona flaviventris Alexander, 1946 with P. perbona. An updated key for identifying males of the P. formosensis species group is presented.
Neuroinflammation has been increasingly implicated in epileptogenesis and drug-resistant epilepsy, leading to growing research interest beyond the traditional focus on neuronal hyperexcitability. Despite the rapid expansion of research in this interdisciplinary field, a comprehensive structural mapping of its intellectual evolution and emerging frontiers is lacking. We performed a systematic bibliometric analysis of 1989 publications (2005-2026) retrieved from Web of Science Core Collection and Scopus. Analytical tools including CiteSpace, VOSviewer, and the Bibliometrix R package were employed to visualize collaboration networks, citation structures, and thematic transitions. The literature search was updated to include publications indexed up to January 4, 2026. Research output followed an exponential growth pattern (R2=0.97), peaking in 2025. China and the USA dominated the global landscape, with the Journal of Neuroinflammation and Epilepsia identified as core academic hubs. Highly cited works, led by pioneers such as Vezzani A and Aronica E, established a knowledge base centered on microglial activation and cytokine signaling. Keyword clustering identified several interconnected thematic domains. Long-standing topics included oxidative stress and hippocampal vulnerability, whereas recent citation bursts indicated increasing attention to autoimmune encephalitis, blood-brain barrier (BBB) dynamics, and the gut-brain axis. Furthermore, emerging trends highlight the ketogenic diet and network pharmacology as promising immunometabolic strategies for seizure control. This study provides the first systematic bibliometric landscape of neuroinflammation in epilepsy over the past two decades. Our findings suggest a gradual transition from studies of glial, cytokine, and vascular mechanisms toward translational interest in systemic immune-CNS interactions. These quantitative insights identify the gut-microbiota-inflammation axis and personalized immunotherapy as the next frontiers, offering a strategic roadmap for future disease-modifying interventions in refractory epilepsy.
The global population is ageing at an unprecedented rate, creating substantial pressures on healthcare systems to deliver personalised, proactive, and cost-effective care for older adults. Digital twin (DT) technology, where dynamic virtual replicas of physical entities are continuously updated through real-time data, has emerged as a transformative tool in precision medicine. Despite its growing application across clinical specialties, its specific utility within geriatrics and gerontology remains underexplored in the academic literature. This narrative review aims to synthesise existing evidence on the applications of digital twin technology in geriatric and gerontological care, examine associated challenges and identify future research priorities. A narrative review methodology was employed, with a systematic search of PubMed, Scopus, Web of Science, and IEEE Xplore databases covering publications from January 2014 to December 2025. Studies were selected based on relevance to digital twins, ageing populations, or geriatric clinical domains, with data synthesised thematically. Digital twins demonstrate significant potential benefit across multiple geriatric domains, with use in cardiovascular monitoring, fall prevention, dementia management, polypharmacy optimisation, and chronic disease self-management. Key enablers include advances in Internet of Things (IoT), artificial intelligence, and electronic health records. Persistent challenges include data privacy concerns, interoperability deficits, computational costs, and ethical questions surrounding autonomy and consent in cognitively impaired populations. Digital twin technology holds considerable promise for revolutionising geriatric and gerontological care, by enabling hyper-personalised clinical decision-making, predictive risk management, and remote patient monitoring. Translating this potential into practice requires focused investment in regulatory frameworks, equitable access infrastructure, and interdisciplinary collaboration. Future research should prioritise standardisation, caregiver integration, and longitudinal validation studies within older adult populations.
Infrared and visible image fusion (IVIF) targets to integrate thermal saliency and rich textures into a single image that is not only visually appealing but also beneficial to downstream vision tasks. However, conventional methods relying on heuristic visual criteria struggle to guarantee task utility. Conversely, task-driven fusion paradigms typically employ fixed-weight scalarization, which suffers from potentially conflicting objectives among heterogeneous tasks, leading to rigid compromises and sub-optimal generalization in multi-task scenarios. To overcome these bottlenecks, this paper proposes a symbiotic evolutionary learning framework for task-adaptive IVIF, termed EvoFuse. Rather than relying on static loss weights, we formulate the fusion-perception correlation from a multi-objective perspective. To structurally instantiate this formulation, we first develop a re-parameterizable fusion architecture that accommodates multi-branch representational capacity during training, yet analytically folds into an ultra-compact single-branch model for efficient inference. To navigate the conflicting multi-task objectives, we introduce an evolutionary search mechanism that dynamically evolves task-aware loss-weight configurations. This enables a mutual adaptation process where the fusion network and task models are jointly updated under a Pareto-inspired non-degradation criterion. Furthermore, a novel saliency discriminative loss is designed to explicitly emphasize semantically crucial regions. Extensive experiments across eleven datasets covering fusion and downstream perception tasks demonstrate that the proposed method achieves competitive or better results in most evaluated metrics, while maintaining efficient inference under the considered task settings.