Search Results (1,491)

Anxiety and depression affect millions worldwide, yet stigma and long wait times often delay access to care. Mobile mental health apps can decrease these barriers by offering on-demand screening and support. Nevertheless, many machine and deep learning methods used in such tools perform poorly under severe class imbalance, yielding biased, poorly calibrated predictions. To address this challenge, this study proposes MCoG-LDPSNet, a brain-inspired model that combines dual, orthogonal encoding pathways with a novel Loss-Driven Parametric Swish (LDPS) activation. LDPS implements a neurobiologically motivated adaptive-gain mechanism via a learnable β parameter driven by calibration and confidence-aware loss signals that amplifies minority-class patterns while preserving overall reliability, enabling robust predictions under severe data imbalance. On a benchmark mental health corpus, MCoG-LDPSNet achieved AUROC = 0.9920 and G-mean = 0.9451, outperforming traditional baselines like GLMs, XGBoost, state-of-the-art deep models (CNN-BiLSTM-ATTN), and transformer-based approaches. After transfer learning to social media text, the MCoG-LDPSNet maintained a near-perfect AUROC of 0.9937. Integrated into the EmotiZen App with enhanced app features, MCoG-LDPSNet was associated with substantial symptom reductions (anxiety 28.2%; depression 42.1%). These findings indicate that MCoG-LDPSNet is an accurate, imbalance-aware solution suitable for scalable mobile screening of individuals for anxiety and depression. Full article

Influenza is a serious and global health issue, and it is a major cause of morbidity, fatality, and economic loss every year. Seasonal vaccines exist but are not very effective due to strain mismatches, delays in production, and antigenic drift. This comprehensive overview discusses the current situation of influenza vaccination, including the numerous types of vaccines—inactivated, live attenuated, and recombinant vaccines—and their effectiveness, efficacy, and associated challenges. It highlights the effects of the COVID-19 pandemic on the trends of influenza vaccination and the level to which innovation should be practiced. In the future universal influenza vaccines will be developed that target conserved viral antigens to provide long-term protection to people. In the meantime, novel vaccine delivery platforms, such as mRNA technology, virus-like particle (VLP), and nanoparticle-based systems, and less cumbersome and invasive administration routes, as well as immune responses are also under development to increase access and production capacity. Collectively, these innovations have the potential to not only reduce the global influenza epidemic but also to change the way influenza is prevented and prepare the world for a pandemic. Full article

Invasive candidiasis (IC) in Latin America is undergoing a significant epidemiological shift, increasingly driven by non-albicans strains such as Candida tropicalis, Candida parapsilosis, and Candidozyma auris. These pathogens often exhibit multidrug resistance, which complicates treatment and increases mortality. Diagnostic limitations, particularly in rural and public hospitals, delay detection and hinder the provision of rapid care. Environmental pressures, such as climate change and the widespread use of azoles in agriculture, appear to favor the selection of resistant and thermotolerant strains. Migratory birds may also play a role in the environmental transmission of pathogenic fungi. These factors are amplified by socioeconomic inequalities that restrict access to diagnostics and first-line antifungals. To help mitigate this emerging challenge, a One Health-oriented framework combining integrated environmental surveillance, robust antifungal-stewardship programmers, broader diagnostic access, and coordinated cross-sector public health actions should be developed. Reinforcing these pillars could lessen the regional burden of IC and slow the advance of antifungal resistance. Full article

IgA nephropathy (IgAN) is the most prevalent primary glomerulonephritis worldwide, with a heterogeneous clinical course that may progress to end-stage kidney disease (ESKD) in approximately 20% of patients. Despite recent advances, including the U.S. Food and Drug Administration (FDA) approval of three novel agents, optimal therapeutic strategies remain uncertain, and access to new drugs is often limited. This underscores the need to evaluate established and widely available options such as mycophenolate mofetil (MMF). The aim of this review is to critically assess the role of MMF, either as monotherapy or in combination with systemic corticosteroids, in the treatment of IgAN based on evidence cited in the KDIGO 2024 Draft Guidelines. We analyzed seven major clinical studies—five randomized controlled trials and two long-term observational studies—with particular focus on the influence of histological activity on treatment outcomes. The Oxford classification was applied to explore whether specific histological variables correlate with prognosis and predict treatment response. Trials conducted in Chinese cohorts demonstrated significant benefits of MMF, including proteinuria reduction, delayed progression to ESKD, and improved long-term renal outcomes, particularly in patients with recent disease onset and active proliferative lesions such as endocapillary hypercellularity and crescent formation. In contrast, studies from Western populations generally failed to demonstrate comparable benefit possibly due to differences in disease chronicity, histopathological patterns, and genetic background. Overall, MMF appears most effective when initiated early and in patients with histologic evidence of intraglomerular inflammation. It may represent a viable steroid-sparing option in appropriately selected patients, particularly where access to newly approved agents is restricted. These population- and pathology-based differences highlight the need for individualized treatment decisions and further research to refine the therapeutic role of MMF in IgAN. Full article

Pituitary pars intermedia dysfunction (PPID) is a common, slowly progressive, neurodegenerative disorder of the older horse. Oxidative damage to the hypothalamic periventricular neurons results in loss of dopaminergic inhibition of the pars intermedia region of the pituitary gland. Consequently, there is increased production of the pro-opiomelanocortin (POMC)-derived hormones normally produced by this region, as well as initial melanocyte hypertrophy and hyperplasia, followed by adenomatous change. Clinical signs that are highly suggestive of the disease are generalised and regional hypertrichosis and delayed/abnormal coat shedding. Numerous clinical signs provide a moderate clinical suspicion, including hyperhidrosis, abnormal fat distribution/regional adiposity, epaxial muscle atrophy/loss of topline, laminitis, weight loss, recurrent infections, behavioural changes/lethargy, polyuria and polydipsia, a pot-bellied appearance, bulging supraorbital fat pads, reduced wound healing, lordosis and infertility. In all animals, a diagnosis of PPID is made based on the signalment, clinical signs and results of further diagnostic tests, with age being a crucial factor to consider. Currently recommended further diagnostic tests are measurement of basal adrenocorticotrophic hormone (ACTH) concentrations (all year) and evaluation of the ACTH response to thyrotrophin-releasing hormone (TRH) using seasonally adjusted references intervals (non-autumn). Animals should also be tested for insulin dysregulation, as laminitis risk in PPID is associated with hyperinsulinaemia. PPID can be managed but not cured; it is a lifelong condition. The individual clinical signs can be managed, e.g., clipping the excessive haircoat and providing unrestricted access to water for individuals with polydipsia. Alternatively, pharmacological management can be employed, and the dopamine-2 receptor agonist pergolide is licensed/approved for the treatment of equine PPID. This should be prescribed in combination with dietary recommendations based on the body condition score and insulin sensitivity status of the individual animal. Full article

Chronic kidney disease (CKD) prevalence is rising worldwide and is projected to become the fifth leading cause of death globally by 2040. The high proportion of undiagnosed early-staged CKD and delayed diagnosis is of significant concern. The access to diagnosis and treatment is also limited in low-resource settings. The majority of individuals with kidney disease succumb to cardiovascular disease complications. Furthermore, heart failure and CKD are closely interconnected, with each condition significantly increasing the risk of developing the other. They share common risk factors, such as high blood pressure and diabetes, and their coexistence worsens prognosis and raises mortality rates. The bidirectional relationship between the heart and kidneys becomes even more complex and challenging in the context of cardiorenal syndrome. Emerging medications, such as sodium–glucose cotransporter 2 inhibitors and mineralocorticoid receptor antagonists, have shown remarkable efficacy in slowing the progression of kidney disease, surpassing the benefits of traditional treatments. This article summarizes the evidence on the early detection of CKD and real-world opportunities to slow the progression of CKD by optimizing cardiorenal guideline-directed medical therapy. Full article

Background: Accurate and timely molecular testing in patients with non-small cell lung cancer (NSCLC) is mandatory for targeted therapies and improved outcomes. Real-world obstacles, including geographic distance from specialized lung cancer services, along with comorbidities, may delay molecular diagnosis and subsequent treatment, therefore hampering survival. Methods: We conducted a retrospective, multi-departmental observational study of 927 patients with newly diagnosed NSCLC that were referred to a tertiary hospital in western Greece between January 2021 and December 2024. Patients were classified based on distance of residence (<30 km vs. ≥30 km). Clinical characteristics, time elapsed from pathological to final molecular diagnosis, and survival outcomes were analyzed and compared. Multivariable Cox regression was used to identify independent predictors of overall survival. Results: Patients residing ≥30 km away (61.2%) experienced delays in molecular testing (median 31 vs. 26 days, p = 0.002) and were less likely to undergo such testing (p = 0.012) compared to those residing <30km. Patients residing >30 km also had a higher prevalence of COPD (42.5% vs. 31.2%, p = 0.002). Median survival from initial pathological diagnosis to death was significantly shorter in non-urban patients (129 vs. 215 days, p = 0.010). A molecular testing delay >35 days was independently associated with worse survival (HR = 0.684, 95% CI: 0.508–0.923, p = 0.013). No differences in TNM stage distribution were observed between geographical groups. Conclusions: Geographic disparities significantly impact access to advanced lung cancer services and molecular diagnostics and may provisionally affect prognosis in NSCLC. Improving testing pathways, incorporating reflex testing in pathological molecular analysis, and optimizing referral systems in rural areas may help to reduce inequalities and improve patient outcomes. Full article

Background: Armed conflicts impose complex logistical and behavioral challenges on healthcare systems, particularly in managing acute conditions such as ST-elevation myocardial infarction (STEMI) and ischemic stroke. Although both diagnoses require timely intervention, their clinical pathways differ significantly. Few studies have systematically compared their management during active warfare, particularly within the warzone. Methods: This retrospective cohort study was conducted at Soroka University Medical Center (SUMC), the sole tertiary hospital in southern Israel and the main referral center for cardiovascular and neurological emergencies in the region. We included all adult patients (≥18 years) admitted with new-onset STEMI or ischemic stroke during three-month periods of wartime (October–December 2023) and matched routine periods in 2021 and 2022. Patients with in-hospital events, inter-hospital transfers, or foreign citizenship were excluded. Data on demographics, comorbidities, arrival characteristics, treatment timelines, and outcomes were extracted from electronic medical records. Categorical variables were compared using Chi-squared or Fisher’s exact test, and continuous variables using t-tests or Mann–Whitney U tests, as appropriate. Multivariable logistic and linear regression models were adjusted for age, sex, Charlson Comorbidity Index (CCI), and mode of arrival. Interaction terms assessed whether wartime modified the associations differently for STEMI and stroke. Results: A total of 410 patients were included (193 with STEMI and 217 with stroke). Patients with STEMI were significantly more likely to arrive by self-transport during the war (38, 57.6% vs. 32, 25.2%, p < 0.001) and had higher rates of late arrival beyond 12 h (19, 28.8% vs. 13, 10.2%, p = 0.002). These findings support the conclusion that patients were more prone to delayed and unstructured presentations during a crisis. In contrast, patients with stroke showed a reduction of 354 min in symptom-to-door times during the war [median 246 (30–4320 range) vs. 600 min (12–2329 range), p = 0.026]. Regression models revealed longer delays for stroke vs. STEMI in routine settings [β = 543.07 min (239.68–846.47 95% CI), p < 0.001], along with significantly lower in-hospital (OR = 0.39, 95% CI= 0.15–0.97, p = 0.05) and 30-day mortality (OR = 0.43, 95% CI= 0.19–0.94, p = 0.04). However, these differences were no longer significant during wartime. Patients with STEMI showed a trend toward lower 180-day mortality during the war (OR = 0.33, 95% CI = 0.09–0.99; p = 0.07), although this difference did not reach statistical significance. Conclusions: During wartime, patients with stroke arrived earlier and in greater numbers, while patients with STEMI showed reduced admissions and delayed, self-initiated transport. Despite these shifts, treatment timelines and short-term outcomes were maintained. These diagnosis-specific patterns highlight the importance of reinforcing EMS access for STEMI and preserving centralized protocol-based coordination for stroke during crises. Full article

We investigated aspects of language and cognitive development in three bimodal bilingual deaf children in hearing families. Some previous research finds cognitive delays for deaf children, which may be due to an early lack of access to language input. Studies of children having strong early language access through parental use of American Sign Language (ASL) support the hypothesis that language delays are behind such cognitive delays. We ask whether hearing parents who are novice learners of ASL provide sufficient support for early language and cognitive development. The three case studies in this report used both ASL and English, with support for ASL development provided by our ASL specialist. We assessed the children’s general cognition, executive function, ASL vocabulary, English vocabulary, and overall language ability in both ASL and English. We found strong language development outcomes and correspondingly, age-appropriate cognitive development. These results are consistent with the conclusion that novice signer parents can support their children’s development as ASL-English bilinguals, establishing a strong foundation for further cognitive and linguistic growth. Full article

In pediatric endodontic procedures, final crown placement is often delayed, requiring the use of temporary filling materials to seal the access cavity. Given the importance of antibacterial properties in temporary restorations and the known antimicrobial effects of nanoclay particles, this study aimed to evaluate the antibacterial efficacy of a nanoclay-infused temporary dressing against cariogenic and residual intracanal bacteria. A commercial temporary material (CAVISOL, Tehran, Iran) was blended with nanoclay (SOUTHERN, Gonzalez, TX, USA; average size 95 nm), using eugenol as a wetting agent. The antibacterial effects on Streptococcus mutans, Enterococcus faecalis, and Escherichia coli were assessed using disc diffusion, well diffusion, and microtiter plate assays after 24 h of incubation at 37 °C (six material groups, three bacterial strains, three replications for each antibacterial test). Statistical analyses were performed using Shapiro–Wilk and ANOVA tests (p < 0.05). The results showed that formulations containing 60% and 80% nanoclay significantly inhibited the growth of all tested bacteria, outperforming pure Cavit (p < 0.05). The most substantial inhibition was observed in E. coli, while S. mutans exhibited the least susceptibility (p < 0.05). These findings suggest that incorporating nanoclay into temporary fillings may enhance efficacy to increase the success rate of pediatric endodontic treatments, although further physicochemical and clinical evaluations are warranted. Full article

Convolutional neural networks (CNNs) have achieved remarkable success in computer vision tasks, driving the rapid development of hardware accelerators. However, memory efficiency remains a key challenge, as conventional accelerators adopt layer-by-layer processing, leading to frequent external memory accesses (EMAs) of intermediate feature data, which increase energy consumption and latency. While layer fusion has been proposed to enhance inter-layer feature reuse, existing approaches typically rely on fixed data management tailored to specific architectures, introducing on-chip memory overhead and requiring trade-offs with EMAs. Moreover, prevalent residual connections further weaken fusion benefits due to diverse data reuse distances. To address these challenges, we propose layer-centric tile fusion, which integrates residual data loading with feature merging by leveraging receptive field relationships among feature tiles. A reuse distance-aware caching strategy is introduced to support flexible storage for various data types. We also develop a modeling framework to analyze the trade-off between on-chip memory usage and EMA-induced energy-delay product (EDP). Experimental results demonstrate that our method achieves 5.04–43.44% EDP reduction and 20.28–58.33% memory usage reduction compared to state-of-the-art designs on ResNet-18 and SRGAN. Full article

Sign language avatar systems have emerged as a promising solution to bridge communication gaps where human sign language interpreters are unavailable. However, the design of these avatars often fails to account for the diversity in how users acquire and perceive sign language. This study presents a rapid review of 17 empirical studies (2020–2025) to synthesize how linguistic and cognitive variability affects sign language perception and how these findings can guide avatar development. We extracted and synthesized key constructs, participant profiles, and capture techniques relevant to avatar fidelity. This review finds that delayed exposure to sign language is consistently linked to persistent challenges in syntactic processing, classifier use, and avatar comprehension. In contrast, early-exposed signers demonstrate more robust parsing and greater tolerance of perceptual irregularities. Key perceptual features, such as smooth transitions between signs, expressive facial cues for grammatical clarity, and consistent spatial placement of referents, emerge as critical for intelligibility, particularly for late learners. These findings highlight the importance of participatory design and user-centered validation in advancing accessible, culturally responsive human–computer interaction through next-generation avatar systems. Full article

Time Division Multiplexing Passive Optical Networks (TDM-PONs) serve as a key enabler for the evolution of broadband access network infrastructure. As TDM-PONs adapt to support 6G networks, reducing energy consumption becomes increasingly critical. Sleep modes have been widely adopted as an effective energy-saving solution. However, their use can introduce delays that compromise performance. This issue becomes especially problematic in 6G PONs, where ultra-low latency and stringent service requirements leave minimal tolerance for delay-related inefficiencies. In this paper, we propose a novel sleep synchronization mechanism for both single and multiple TDM-PONs, allowing Optical Network Units (ONUs) to join one or more sleep/wake-up groups based on the service type and delay tolerance. Our practical design framework incorporates delay-based grouping and existing sleep modes to address the operational complexities of multi-PON systems while remaining fully compatible with current PON standards. The simulation results show that our approach satisfies the requirements of delay-sensitive traffic and achieves up to 37% energy savings. Compared to baseline methods such as adaptive scheduling and fixed-interval cyclic sleep, it offers a 15–20% improvement in the energy–delay trade-off. These results demonstrate the potential for near-term deployment of 6G PONs and lay the foundation for more advanced, delay-aware energy management strategies in next-generation optical access networks. Full article

Background: Congenital anomalies impact 52 million infants worldwide with an estimated 94% living in low- and middle-income countries (LMICs). Approximately 200,000 children are born with a neural tube defect (NTD) in LMICs annually. Zambia is an LMIC with a high burden of myelomeningocele (MMC; a severe form of NTD). This study sought to characterize the barriers influencing access to healthcare for children born with MMC in Zambia. Methods: Two cross-sectional surveys were administered to healthcare providers at referring public health facilities and mothers of infants born with MMC undergoing surgical closure. The survey among mothers was nested in a longitudinal study evaluating surgical closure in Lusaka, Zambia from 28 May 2024 to 21 January 2025. Results: Sixty-nine mother–MMC baby dyads and 123 providers from 21 facilities were enrolled in the study. The median age at presentation for MMC was 7.5 (range 0–244) days old. Most patients were referred from rural district hospitals (51%; n = 35) and travelled greater than 250 km to access care (80%; n = 55). Seventy-seven percent (n = 53) of mothers reported receiving at least one antenatal ultrasound, with 62% (n = 43) undergoing an ultrasound after 20 weeks estimated gestational age. Of these, only 3% (n = 2) received an MMC diagnosis prior to delivery. Referring patients with MMC for further care greater than six hours after birth was reported by 59% providers (n = 73). Hospitals further away from the tertiary center were more likely to report late referrals (p < 0.001). Conclusions: There is a delay in the diagnosis and referral of infants with MMC to specialized care in Zambia, which may be attributed to inadequate in utero diagnosis capabilities and distance from the tertiary facility. Improving the accuracy of prenatal diagnosis and strengthening referral pathways to facilitate access to care among infants with MMC in Zambia are important for improving incidence and outcomes. Full article

Background/Objectives. Intracranial hemorrhages (ICHs) require immediate diagnosis for optimal clinical outcomes. Artificial intelligence (AI) is considered a potential solution for optimizing neuroimaging under conditions of radiologist shortage and increasing workload. This study aimed to directly compare diagnostic effectiveness between standalone AI services and AI-assisted radiologists in detecting ICHs on brain CT. Methods. A prospective, multicenter comparative study was conducted in 67 medical organizations in Moscow over 15+ months (April 2022–December 2024). We analyzed 3409 brain CT studies containing 1101 ICH cases (32.3%). Three commercial AI services with state registration were compared with radiologist conclusions formulated with access to AI results as auxiliary tools. Statistical analysis included McNemar’s test for paired data and Cohen’s h effect size analysis. Results. Radiologists with AI assistance statistically significantly outperformed AI services across all diagnostic metrics (p < 0.001): sensitivity 98.91% vs. 95.91%, specificity 99.83% vs. 87.35%, and accuracy 99.53% vs. 90.11%. The radiologists’ diagnostic odds ratio exceeded that of AI by 323-fold. The critical difference was in false-positive rates: 293 cases for AI vs. 4 for radiologists (73-fold increase). Complete complementarity of ICH misses was observed: all 12 cases undetected by radiologists were identified by AI, while all 45 cases missed by AI were diagnosed by radiologists. Agreement between methods was 89.6% (Cohen’s kappa 0.776). Conclusions. Radiologists maintain their role as the gold standard in ICH diagnosis, significantly outperforming AI services. Error complementarity indicates potential for improvement through systematic integration of AI as a “second reader” rather than a primary diagnostic tool. However, the high false-positive rate of standalone AI requires substantial algorithm refinement. The optimal implementation strategy involves using AI as an auxiliary tool within radiologist workflows rather than as an autonomous diagnostic system, with potential for delayed verification protocols to maximize diagnostic sensitivity while managing the false-positive burden. Full article