Search Results (6,222)

Background: Papilledema, an ophthalmic finding associated with increased intracranial pressure, is often induced by dermatological medications, including corticosteroids, isotretinoin, and tetracyclines. Early detection is crucial for preventing irreversible optic nerve damage, but access to ophthalmologic expertise is often limited in rural settings. Artificial intelligence (AI) may enable the automated and accurate detection of papilledema from fundus images, thereby supporting timely diagnosis and management. Objective: The primary objective of this study was to explore the diagnostic capability of ChatGPT-4o, a general large language model with multimodal input, in identifying papilledema from fundus photographs. For context, its performance was compared with a ResNet-based convolutional neural network (CNN) specifically fine-tuned for ophthalmic imaging, as well as with the assessments of two human ophthalmologists. The focus was on applications relevant to dermatological care in resource-limited environments. Methods: A dataset of 1094 fundus images (295 papilledema, 799 normal) was preprocessed and partitioned into a training set and a test set. The ResNet model was fine-tuned using discriminative learning rates and a one-cycle learning rate policy. GPT-4o and two human evaluators (a senior ophthalmologist and an ophthalmology resident) independently assessed the test images. Diagnostic metrics including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and Cohen’s Kappa, were calculated for each evaluator. Results: GPT-4o, when applied to papilledema detection, achieved an overall accuracy of 85.9% with substantial agreement beyond chance (Cohen’s Kappa = 0.72), but lower specificity (78.9%) and positive predictive value (73.7%) compared to benchmark models. For context, the ResNet model, fine-tuned for ophthalmic imaging, reached near-perfect accuracy (99.5%, Kappa = 0.99), while two human ophthalmologists achieved accuracies of 96.0% (Kappa ≈ 0.92). Conclusions: This study explored the capability of GPT-4o, a large language model with multimodal input, for detecting papilledema from fundus photographs. GPT-4o achieved moderate diagnostic accuracy and substantial agreement with the ground truth, but it underperformed compared to both a domain-specific ResNet model and human ophthalmologists. These findings underscore the distinction between generalist large language models and specialized diagnostic AI: while GPT-4o is not optimized for ophthalmic imaging, its accessibility, adaptability, and rapid evolution highlight its potential as a future adjunct in clinical screening, particularly in underserved settings. These findings also underscore the need for validation on external datasets and real-world clinical environments before such tools can be broadly implemented. Full article

We previously developed machine learning (ML) models for predicting cycloplegic spherical equivalent refraction (SER) and myopia using non-cycloplegic data and following a standardized protocol (cycloplegia with 0.5% tropicamide and biometry using NIDEK A-scan), but the models’ performance may not be generalizable to other settings. This study evaluated the performance of ML models in an independent cohort using a different cycloplegic agent and biometer. Chinese students (N = 614) aged 8–13 years underwent autorefraction before and after cycloplegia with 0.5% tropicamide (n = 505) or 1% cyclopentolate (n = 109). Biometric measures were obtained using an IOLMaster 700 (n = 207) or Optical Biometer SW-9000 (n = 407). ML models were evaluated using R², mean absolute error (MAE), sensitivity, specificity, and area under the ROC curve (AUC). The XGBoost model predicted cycloplegic SER very well (R² = 0.95, MAE (SD) = 0.32 (0.30) D). Both ML models predicted myopia well (random forest: AUC 0.99, sensitivity 93.7%, specificity 96.4%; XGBoost: sensitivity 90.1%, specificity 96.8%) and accurately predicted the myopia rate (observed 62.9%; random forest: 60.6%; XGBoost: 58.8%) despite heterogeneous cycloplegia and biometry factors. In this independent cohort of students, XGBoost and random forest performed very well for predicting cycloplegic SER and myopia status using non-cycloplegic data. This external validation study demonstrated that ML may provide a useful tool for estimating cycloplegic SER and myopia prevalence with heterogeneous clinical parameters, and study in additional populations is warranted. Full article

Small molecule inhibitors targeting BRAF mutations at V600 and downstream MEK represent a significant advancement in treating BRAF-mutant melanoma. However, resistance mechanisms, often involving reactivation of the MAPK pathway via ERK1/2, limit their efficacy. The ERK1/2 inhibitor ravoxertinib (GDC0994) was tested on melanoma cell lines with and without resistance to BRAFi or BRAFi + MEKi. Short-term assays evaluated cell viability, apoptosis induction, and pathway modulation via Western Blot, while long-term effects were assessed using a colony formation assay. Resistant and parental melanoma cells responded to long-term ERKi treatment with reduced growth, independent of sensitivity to BRAF or MEK inhibitors. Adding ERKi to BRAFi/MEKi significantly enhanced apoptosis and growth inhibition, particularly in resistant lines. Although ravoxertinib alone showed limited antitumor activity, its combination with BRAFi/MEKi yielded substantial benefits, especially in chronic settings. These findings suggest that combinatorial regimens incorporating ERK inhibitors represent a promising therapeutic strategy for BRAF-mutant melanoma. Full article

The integration of renewable energy sources (RES) into energy systems is becoming increasingly widespread around the world, driven by various factors, the most relevant of which is the high environmental friendliness of these types of energy resources and the possibility of creating stable generation systems that are independent of the economic and geopolitical situation. The large-scale involvement of green energy leads to the creation of distributed energy networks that combine several different methods of generation, each with its own characteristics. As a result, the issues of data collection and processing necessary for optimizing the operation of such energy systems are becoming increasingly relevant. The first stage of renewable energy integration involves building models to assess theoretical potential, allowing the feasibility of using a particular type of resource in specific geographical conditions to be determined. The second stage of assessment involves determining the technical potential, which allows the actual energy values that can be obtained by the consumer to be determined. The paper discusses a method for assessing the technical potential of solar energy using the example of a private consumer’s energy system. For this purpose, a generator circuit with load models was implemented in the SimInTech dynamic simulation environment, accepting various sets of parameters as input, which were obtained using an intelligent information search procedure and intelligent forecasting methods. This approach makes it possible to forecast the amount of incoming solar insolation in the short term, whose values are then fed into the simulation model, allowing the forecast values of the technical potential of solar energy for the energy system configuration under consideration to be determined. The implementation of such a hybrid assessment system allows not only the technical potential of RES to be determined based on historical datasets but also provides the opportunity to obtain forecast values for energy production volumes. This allows for flexible configuration of the parameters of the elements used, which makes it possible to scale the solution to the specific configuration of the energy system in use. The proposed solution can be used as one of the elements of distributed energy systems with RES, where the concept of demand distribution and management plays an important role. Its implementation is impossible without predictive models. Full article

Content delivery networks (CDNs) face steadily rising, uneven demand, straining heuristic cache replacement. Reinforcement learning (RL) is promising, but most work assumes a fully observable Markov Decision Process (MDP), unrealistic under delayed, partial, and noisy signals. We model cache replacement as a Partially Observable MDP (POMDP) and present the Miss-Triggered Cache Transformer (MTCT), a Transformer-decoder Q-learning agent that encodes recent histories with self-attention. MTCT invokes its policy only on cache misses to align compute with informative events and uses a delayed-hit reward to propagate information from hits. A compact, rank-based action set (12 actions by default) captures popularity–recency trade-offs with complexity independent of cache capacity. We evaluate MTCT on a real trace (MovieLens) and two synthetic workloads (Mandelbrot–Zipf, Pareto) against Adaptive Replacement Cache (ARC), Windowed TinyLFU (W-TinyLFU), classical heuristics, and Double Deep Q-Network (DDQN). MTCT achieves the best or statistically comparable cache-hit rates on most cache sizes; e.g., on MovieLens at $M=600$, it reaches $0.4703$ (DDQN $0.4436$, ARC $0.4513$). Miss-triggered inference also lowers mean wall-clock time per episode; Transformer inference is well suited to modern hardware acceleration. Ablations support $CL=50$ and show that finer action grids improve stability and final accuracy. Full article

This paper focuses on the efficient fine-tuning of large language models within the federated learning framework. To address the performance bottlenecks caused by multi-source heterogeneity and structural inconsistency, a structure-aware federated fine-tuning method is proposed. The method incorporates a graph representation module (GRM) to model internal structural relationships within text and employs a segmentation mechanism (SM) to reconstruct and align semantic structures across inputs, thereby enhancing structural robustness and generalization under non-IID (non-Independent and Identically Distributed) settings. During training, the method ensures data locality and integrates structural pruning with gradient encryption (SPGE) strategies to balance privacy preservation and communication efficiency. Compared with representative federated fine-tuning baselines such as FedNLP and FedPrompt, the proposed method achieves consistent accuracy and F1-score improvements across multiple tasks. To evaluate the effectiveness of the proposed method, extensive comparative experiments are conducted across tasks of text classification, named entity recognition, and question answering, using multiple datasets with diverse structures and heterogeneity levels. Experimental results show that the proposed approach significantly outperforms existing federated fine-tuning strategies on most tasks, achieving higher performance while preserving privacy, and demonstrating strong practical applicability and generalization potential. Full article

Background: Repeat induced abortion (defined as ≥two lifetime procedures) is becoming more common worldwide, yet its independent influence on women’s psychological health remains contested, particularly in settings where access to modern contraception is restricted. Objectives: This review sought to quantify the burden of depression, anxiety, stress, and generic quality of life (QoL) among women with repeat abortions and to determine how barriers to contraceptive access alter those outcomes. Methods: Following the preregistered PRISMA-2020 protocol, PubMed, Embase and Scopus were searched from inception to 31 June 2025. Results: Eight eligible studies comprising approximately 262,000 participants (individual sample sizes up to 79,609) revealed wide variation in psychological morbidity. Prevalence of clinically significant symptoms ranged from 5.5% to 24.8% for depression, 8.3% to 31.2% for anxiety, and 18.8% to 27% for perceived stress; frequent mental distress affected 12.3% of women in neutral policy environments but rose to 21.9% under highly restrictive abortion legislation. Having three or more abortions, compared with none or one, increased the odds of depressive symptoms by roughly one-third (pooled OR ≈ 1.37, 95% CI 1.13–1.67). Contextual factors exerted comparable or stronger effects: abortions sought for socioeconomic reasons elevated depression odds by 34%, unwanted disclosure of the abortion episode increased depressive scores by 0.62 standard deviations, and low partner support raised them by 0.67 SD. At the structural level, every standard deviation improvement in a state’s reproductive rights index reduced frequent mental distress odds by 5%, whereas enactment of a near-total legal ban produced an absolute increase of 6.8 percentage points. QoL outcomes were less frequently reported; where measured, denied or heavily delayed abortions were associated with a 0.41-unit decrement on a seven-point life satisfaction scale. Conclusions: Psychological morbidity after abortion clusters where legal hostility, financial hardship, or interpersonal coercion constrain contraceptive autonomy while, in comparison, the mere number of procedures is a weaker predictor. Interventions that integrate stigma-free mental health support with confidential, affordable, and rights-based contraception are essential to protect well-being in women who experience repeat abortions. Full article

(1) Background: The global increase in life expectancy has generated growing interest in strategies that support functional independence and quality of life among older adults. Functional fitness—including strength, mobility, flexibility, and aerobic endurance—is essential for preserving autonomy during aging. In this context, physical exercise, particularly High-Intensity Interval Training (HIIT), has gained attention for its time efficiency and physiological benefits. This randomized controlled trial aimed to evaluate the effects of a group-based HIIT program on functional fitness in older adults; (2) Methods: Functional outcomes were assessed before, during, and after a 65-week intervention using standardized field tests, including measures of upper and lower body strength, flexibility, aerobic endurance, and agility. This study was prospectively registered at ClinicalTrials.gov (NCT07170579); (3) Results: Significant improvements were observed in the HIIT group across multiple domains of functional fitness compared to the control group, notably in upper body strength, lower limb flexibility, cardiorespiratory endurance, and mobility; (4) Conclusions: These results suggest that HIIT is an effective and adaptable strategy for improving functional fitness in older adults, with the potential to enhance performance in daily activities and support healthy aging in community settings. Full article

In response to the inability to quickly assess wind noise performance during the early stages of automotive styling design, this paper proposes a method for predicting interior wind noise by integrating automotive point cloud models with the Gray Wolf Optimization Residual Network model (GWO-ResNet). Based on wind tunnel test data under typical operating conditions, the point cloud model of the test vehicle is compressed using an auto-encoder and used as input features to construct a nonlinear mapping model between the whole vehicle point cloud and the wind noise level at the driver’s left ear. Through adaptive optimization of key hyperparameters of the ResNet model using the gray wolf optimization algorithm, the accuracy and generalization of the prediction model are improved. The prediction results on the test set indicate that the proposed GWO-ResNet model achieves prediction results that are consistent with the actual measured values for the test samples, thereby validating the effectiveness of the proposed method. A comparative analysis with traditional ResNet models, GWO-LSTM models, and LSTM models revealed that the GWO-ResNet model achieved Mean Absolute Percentage Error (MAPE) and mean squared error (MSE) of 9.72% and 20.96, and 9.88% and 19.69, respectively, on the sedan and SUV test sets, significantly outperforming the other comparison models. The prediction results on the independent validation set also demonstrate good generalization ability and stability (MAPE of 10.14% and 10.15%, MSE of 23.97 and 29.15), further proving the reliability of this model in practical applications. The research results provide an efficient and feasible technical approach for the rapid evaluation of wind noise performance in vehicles and provide a reference for wind noise control in the early design stage of vehicles. At the same time, due to the limitations of the current test data, it is impossible to predict the wind noise during the actual driving of the vehicle. Subsequently, the wind noise during actual driving can be predicted by the test data of multiple working conditions. Full article

Introduction: In minimally invasive, off-clamp partial nephrectomy (ocMIPN), the reconstructive strategy profoundly influences functional outcomes. Traditional nephrometry scores aid preoperative planning but do not directly inform the choice of closure technique. This dual-institutional study aimed primarily to identify preoperative CT-derived parameters predictive of renorrhaphy versus a sutureless approach, and secondarily to compare perioperative and functional outcomes between these techniques. Methods: We retrospectively analyzed 201 consecutive ocMIPN cases performed using a standardized off-clamp technique by two experienced surgical teams across robotic platforms and conventional laparoscopy. Preoperative CT scans were centrally reviewed to quantify morphometric features, including contact surface area (CSA), tumor radius, and Gerota’s fascia thickness. Univariable and multivariable logistic regression models—one restricted to radiologic variables and one expanded with RENAL score terms—were generated to identify independent predictors. Perioperative outcomes, renal functional metrics, and Trifecta rates were compared between cohorts. Results: Among the 201 patients, 101 (50.2%) underwent sutureless reconstruction and 100 (49.8%) renorrhaphy. Cohorts were comparable at baseline except for tumor size (3.1 vs. 3.6 cm; p = 0.04). In multivariable analysis, CSA > 15 cm² (OR 3.93; 95% CI 1.26–12.26; p = 0.02) and tumor radius (OR 1.14 per mm; 95% CI 1.01–1.29; p = 0.04) consistently predicted renorrhaphy, while Gerota’s fascia < 10 mm emerged as significant only in the expanded specification (OR 0.08; 95% CI 0.01–0.70; p = 0.02). Integration with RENAL improved predictive performance (ΔAUC 0.06; NRI 0.14; IDI 0.07), and the final model demonstrated strong discrimination (AUC 0.81) with satisfactory calibration. Perioperative outcomes, postoperative renal function, and Trifecta achievement were similar between groups (all p ≥ 0.21). Conclusions: A concise set of CT-derived morphologic markers—CSA, tumor radius, and perinephric fascia thickness—anticipated reconstructive strategy in ocMIPN and augmented the discriminatory power of RENAL nephrometry. When anatomy was favorable, sutureless repair was not associated with statistically significant differences in perioperative safety or renal function, although the study was not powered for formal equivalence testing. These findings support the integration of radiologic markers into preoperative planning frameworks for nephron-sparing surgery. Full article

Background/Objectives: Cerebral palsy (CP) is one of the most common causes of permanent motor disability in children, and its consequences for upper limb function have a significant impact on the patient’s independence and quality of life. Virtual reality is attracting increasing interest as a modern, engaging and effective method of physiotherapy for children with cerebral palsy. This systematic literature review aimed to synthesize current scientific data on the impact of virtual-reality-based physiotherapy on upper limb function in children with cerebral palsy. Methods: The review was conducted in accordance with PRISMA 2020 guidelines. PubMed, Science Direct, Scopus, Web of Science, Research Gate and Google Scholar databases were searched for studies published between 2010 and 2025. Six original studies meeting the following criteria were included in the analysis: virtual reality therapy, population of children with cerebral palsy, physiotherapy goals related to the upper limb and availability of full text. Results: All included studies demonstrated a positive impact of virtual reality on at least one functional parameter of the upper limb, including range of motion, muscle strength, coordination and manual precision. Task-oriented training, immersive virtual reality environments and home-based therapy supported by remote monitoring proved to be the most effective. The effects were particularly noticeable in children with moderate impairment at GMFCS I–III. Conclusions: Virtual reality represents a safe and promising technology to support upper limb physiotherapy in children with cerebral palsy. It can be used both in clinical and home settings, contributing to increased exercise intensity and motivation. Further long-term studies using high-quality methodology are needed to determine the sustainability of the effects and their impact on everyday living. Full article

In this paper, we prove the theorems on the simultaneous approximation of a pair of analytic functions by discrete shifts $(\zeta (s+ik{h}_1),\zeta (s+ik{h}_2,\alpha ))$, $h_1>0$, $h_2>0$ of the Riemann zeta function $\zeta \left(s\right)$ and Hurwitz zeta function $\zeta (s,\alpha )$. The lower density and density of the above approximating shifts are considered in short intervals $[N,N+M]$ as $N\to \infty$ with $M=o\left(N\right)$. If the set $\{(h_{1}logp:p\in \mathbb{P}),(h_{2}log(m+\alpha ):m\in {\mathbb{N}}_0),2\pi \}$ is linearly independent over $\mathbb{Q}$, the class of approximated pairs is explicitly given. If $\alpha$ and $h_1$, $h_2$ are arbitrary, then it is known that the set of approximated pairs is a certain non-empty closed subset of ${\mathbb{H}}^2(\Delta )$, where $\mathbb{H}(\Delta )$ is the space of analytic functions on the strip $\Delta =\{s\in \mathbb{C}:1/2<\mathrm{Re}s<1\}$. For the proof, limit theorems on weakly convergent probability measures in the space $H^2(\Delta )$ are applied. Full article

Background: Musculoskeletal (MSK) pain is a frequent but under-addressed concern during pregnancy. In Bangladesh, challenges such as limited antenatal care (ANC) access and heavy maternal workloads make this issue particularly urgent for maternal health. This study aimed to determine the prevalence and predictors of MSK pain among pregnant women attending government ANC clinics in Bangladesh. Methods: A facility-based cross-sectional study was conducted among 300 pregnant women recruited from two government hospitals in Dhaka Division. Data were collected using structured interviewer-administered questionnaires covering patient characteristics, pain-related characteristics, and pregnancy-related characteristics. Pain was measured using the Numeric Pain Rating Scale (NPRS; mild <4, moderate 4–7, severe >7), and body mass index (BMI) was calculated based on self-reported height and weight. Descriptive statistics, chi-square tests, and multivariable logistic regression were employed to identify factors independently associated with MSK pain. Results: Overall, 67% of women reported MSK pain, most frequently in the lower back and lower abdomen. Women in later trimesters had about twice the odds of experiencing pain, while those with obesity had nearly six times higher odds compared to women with normal body mass index (BMI). Conclusions: MSK pain is common among pregnant women in Bangladesh and shows associations with later gestational stages and obesity. These findings suggest that integrating routine screening and non-pharmacological management into ANC may help support maternal health and reduce preventable complications in resource-limited settings. Full article

Background: Atherogenic dyslipidemia is defined by the coexistence of high triglyceride concentrations, low levels of high-density lipoprotein cholesterol (HDL-C), and an excess of small, dense particles of low-density lipoprotein cholesterol (LDL-C). This lipid profile is strongly associated with an increased burden of cardiovascular disease and represents a leading cause of global morbidity and mortality. To better capture this risk, composite lipid ratios—including total cholesterol to HDL-C (TC/HDL-C), LDL-C to HDL-C (LDL-C/HDL-C), triglycerides to HDL-C (TG/HDL-C), and the atherogenic dyslipidemia index (AD)—have emerged as robust markers of cardiometabolic health, frequently demonstrating superior predictive capacity compared with isolated lipid measures. Despite extensive evidence linking these ratios to cardiovascular disease, few large-scale studies have examined their association with sociodemographic characteristics, lifestyle behaviors, and social isolation in working populations. Methods: We conducted a cross-sectional analysis of a large occupational cohort of Spanish workers evaluated between January 2021 and December 2024. Anthropometric, biochemical, and sociodemographic data were collected through standardized clinical protocols. Indices of atherogenic risk—namely the ratios TC/HDL-C, LDL-C/HDL-C, TG/HDL-C, and the atherogenic dyslipidemia index (AD)—were derived from fasting lipid measurements. The assessment of lifestyle factors included tobacco use, physical activity evaluated through the International Physical Activity Questionnaire (IPAQ), adherence to the Mediterranean dietary pattern using the MEDAS questionnaire, and perceived social isolation measured by the Lubben Social Network Scale. Socioeconomic classification was established following the criteria proposed by the Spanish Society of Epidemiology. Logistic regression models were fitted to identify factors independently associated with moderate-to-high risk for each lipid indicator, adjusting for potential confounders. Results: A total of 117,298 workers (71,384 men and 45,914 women) were included. Men showed significantly higher odds of elevated TG/HDL-C (OR 4.22, 95% CI 3.70–4.75) and AD (OR 2.95, 95% CI 2.70–3.21) compared with women, whereas LDL-C/HDL-C ratios were lower (OR 0.86, 95% CI 0.83–0.89). Advancing age was positively associated with all lipid ratios, with the highest risk observed in participants aged 60–69 years. Lower social class, smoking, physical inactivity, poor adherence to the Mediterranean diet, and low social isolation scores were consistently linked to higher atherogenic risk. Physical inactivity showed the strongest associations across all indicators, with ORs ranging from 3.54 for TC/HDL-C to 7.12 for AD. Conclusions: Atherogenic dyslipidemia and elevated lipid ratios are strongly associated with male sex, older age, lower socioeconomic status, unhealthy lifestyle behaviors, and reduced social integration among Spanish workers. These findings highlight the importance of workplace-based cardiovascular risk screening and targeted prevention strategies, particularly in high-risk subgroups. Interventions to promote physical activity, healthy dietary patterns, and social connectedness may contribute to lowering atherogenic risk in occupational settings. Full article

Background: Traumatic Brain Injury (TBI) in children is a major cause of morbidity and mortality worldwide. Ocular manifestations are common but often overlooked, despite their potential to cause long-term visual impairment. This study aimed to evaluate the prevalence and characteristics of ocular findings in pediatric TBI patients admitted to the intensive care unit (ICU). Method: We prospectively reviewed records of pediatric patients (≤16 years) with TBI admitted to the Neurosurgery ICU at King Abdullah University Hospital (January 2022–December 2024). TBI was defined using U.S. CDC criteria and confirmed by clinical and radiological findings. Ocular manifestations were identified from ophthalmology consultations, neurosurgical notes, and bedside examinations. Demographics, injury details, and clinical outcomes were recorded. Statistical analyses included Chi-square, Fisher’s exact, and Mann–Whitney U tests, with significance set at p ≤ 0.05. Results: Thirty-eight patients (median age: 8 years; 55.3% male) were included. Ocular findings were present in 20 patients (52.6%). These patients were significantly older (median age 10 vs. 6 years, p = 0.007) and had lower admission GCS scores (11 vs. 14, p = 0.016). Male predominance was higher in the ocular group (75.0% vs. 33.3%, p = 0.030). Ocular findings were significantly associated with surgical intervention (60.0% vs. 22.2%, p = 0.025), orbital fractures (40.0% vs. 5.6%, p = 0.021), basal skull fracture signs (p = 0.036), and extraocular muscle limitation (p = 0.048). On multivariable analysis, orbital fracture remained the only independent predictor of ocular findings (aOR 2.22, 95% CI 1.17–3.57, p = 0.02). Conclusion: Over half of pediatric ICU TBI patients demonstrated ocular manifestations, closely linked to greater injury severity and craniofacial trauma. Routine, comprehensive ophthalmological evaluation should be integrated into the multidisciplinary management of severe pediatric TBI to optimize visual and functional outcomes. Full article