Browse Articles

A protocol for development of a microsimulation model platform to evaluate the potential benefits, harms, and cost-effectiveness of risk-tailored melanoma screening

In populations of European descent, melanoma is a high burden cancer in terms of incidence and healthcare costs, with early detection linked to better prognosis. There is no organised population screening program for melanoma in most countries, as more information is required about the potential benefits, harms and costs of population-based screening to develop policy. To assess the cost-effectiveness of a potential risk-tailored organised melanoma screening program in Australia, we have developed a protocol for a comprehensive microsimulation model (Policy1-Melanoma) that can evaluate multiple potential screening strategies. We outline the development of Policy1-Melanoma, a natural history model developed to be flexibly used to evaluate a range of scenarios related to melanoma screening, diagnosis, surveillance and management. We specify the types of data sources used for calibration and validation of Policy1-Melanoma, and the steps in this process.

Isolated dwarfism and sexual dimorphism in a mainland population of the greater short-horned lizard (Phrynosoma hernandesi) and the Great Plains toad (Anaxyrus cognatus)

Body size is an important biological concept as it impacts nearly all aspects of an organism. In mainland systems, body size tends to show clinal variation; however, drastic body size shifts are typically limited to insular systems in correspondence with abrupt changes in climate patterns and resource availability, often in coordination with reduced genetic diversity. We investigate a rare occurrence of dwarfism and its influence on sexual size dimorphism (SSD) among two mainland species inhabiting the San Luis Valley (Valley) using museum and live specimens. The Valley population of the greater short-horned lizard ( Phrynosoma hernandesi ) is 33.7% smaller and the Valley population of the Great Plains toad ( Anaxyrus cognatus ) is 32.9% smaller than populations surrounding the Valley (Outside). The greater short-horned lizard exhibits female-biased SSD range wide, and female-biased SSD among Valley populations is maintained for head length and width but is inconsistent among test groups for radius, hand, and femur length. In the Great Plains toad, SSD is absent among museum specimens from the Outside population and live specimens the Valley population, but shows a weak presence in parotoid gland morphology among museum specimens from the Valley. Although the mechanisms underlying dwarfism and possible selective pressures associated with shifts in female-biased SSD are unknown, we present a rare instance of mainland dwarfism and its influence on SSD.

Placental lesions in stillbirths: A case-control study using the Amsterdam criteria and predictive models at a UK tertiary unit

Introduction The UK stillbirth rate remains higher than in many high-income countries, with placental disorders -particularly maternal vascular malperfusion (MVM) lesions -linked to adverse maternal and fetal outcomes. This study examines placental lesions in stillbirth at one of the largest maternity units in the UK using the Amsterdam criteria for histological classification. It also retrospectively examines whether women with global/partial MVM – where most maternal decidual vessels show pathological changes but are only partially occluded- would have received aspirin and further surveillance if their placental dysfunction risk had been assessed using the Fetal Medicine Foundation (FMF) algorithm from the Tommy’s app in their first trimester. Materials and methods We conducted a case-control study of spontaneous non-anomalous stillbirths (≥24 weeks) at Sheffield maternity unit from 2018 to 2021 (n = 83). We then compared singleton stillbirths at term with matched livebirths. Placental lesions were categorised with the Amsterdam criteria. Using the FMF’s algorithm which has only been recently introduced in our unit, we then retrospectively calculated the risk for placental dysfunction in women who experienced preterm PET stillbirth and also in those whose placentas showed global/partial MVM. Results MVM was the most common placental lesion in stillbirths, significantly more frequent than in livebirths (p < 0.001). The FMF algorithm had higher predictive accuracy for PET than the traditional NICE model in stillbirths [AUC: 0.76 (95% CI 0.65–0.86) vs 0.51 (95% CI 0.39–0.63), p = 0.03], but only when at least one continuous variable such as PAPP-A was included . In women with stillbirth and whose placentas showed global/partial MVM, first-trimester placental risk assessment using the FMF algorithm during the first trimester would have identified most of them as high risk [FMF AUC: 0.7 (0.58–0.80), p = 0.02]. Conclusion MVM is frequently found in stillbirths. Our retrospective placental dysfunction risk assessment suggests that Tommy’s algorithm would have more accurately identified women who went onto experience stillbirth with significant MVM lesions as high risk, leading to aspirin treatment and closer monitoring. Further research is needed to confirm these findings and potentially enhance placental dysfunction screening to reduce stillbirth rates.

The impact of intransitivity on the Elo rating system

This paper studies the behaviour of the Elo rating system when the underlying modelling assumptions are not met. The Elo rating system is a popular statistical technique used to analyse pairwise comparison data. It is perhaps best known for rating chess players. The crucial assumption behind the Elo rating system is that the probability of which players wins a chess game depends primarily on a real-valued parameter, that quantifies the player’s “skill". This implicitly assumes that the binary relation “more likely to win against" is transitive. This paper studies how the Elo rating system behaves when this assumption is relaxed. First, we prove that once the assumption of transitivity is relaxed, the Elo ratings exhibits the undesirable property that estimated ratings are dependent on who plays who. Second, we prove that even when the assumption of transitivity is relaxed, for a given distribution with which players are selected, there is a unique point where the expected change of Elo ratings at that point is zero. This point represents the maximum likelihood estimator of the Elo ratings, given the observed data. Finally, we introduce a statistic that can be used to measure the intransitivity present in a game. We derive this measurement, and demonstrate on simulated data that it satisfies some useful sanity tests.

Drivers of prognosis and clinical trajectories differ between COVID and non-COVID acute hypoxic respiratory failure

Purpose Examine non-respiratory comorbidities that may affect prognosis in acute hypoxic respiratory failure (AHRF) and respiratory trajectories, comparing those with COVID and non-COVID etiologies of AHRF. Methods This is a retrospective cohort study of patients with AHRF from COVID and non-COVID etiologies treated with high flow oxygen, noninvasive ventilation, or endotracheal intubation in ICUs in two United States hospitals. Results We compared drivers of prognosis and respiratory trajectories between 241 patients with AHRF from COVID and 99 patients with non-COVID AHRF. Patients with COVID had a lower prevalence of major comorbidities or terminal illness (OR 0.14), neurologic disease (OR 0.19), goals of care limitations (OR 0.54), and shock (OR 0.11). A lower proportion of the COVID group were managed with invasive mechanical ventilation (IMV) early in their AHRF course (OR 0.15); however, fewer COVID patients had improvement in AHRF in the first 7 days (OR 0.49), and a greater proportion of COVID patients required IMV on day 14 (OR 2.57). Additionally, fewer COVID patients died or transitioned to comfort care within 14 days following AHRF onset (OR 0.24), and more COVID patients had severe hypoxemia at end-of-life (OR 2.42). Conclusions Patients with AHRF from COVID had fewer non-respiratory comorbidities or goals of care limitations, more prolonged respiratory failure and higher risk of mortality related to hypoxemia. These differences could explain why patients with COVID AHRF may experience greater benefit from disease-specific therapies targeting AHRF compared to patients with non-COVID AHRF.

The absence or the pharmacological blockade of the aryl hydrocarbon receptor promotes neuroprotection in the hippocampus after an ischemic insult

The aryl hydrocarbon receptor (AhR) is a transcription factor that acts as a nuclear receptor mediating xenobiotic metabolism and environmental responses. Recent evidence suggests that the AhR is implicated in maintaining homeostasis or triggering pathological effects by modulating different physiological responses in the nervous system. However, the underlying mechanisms of the AhR-induced effects in the hippocampus remain unclear. Herein, we report a previously unknown role for the AhR in the pathogenesis of a transient global ischemic insult. Comparative analysis of the expression of HIF-1α, nNOS, iNOS, IL6, KAT II, and claudin 5 in the hippocampus of AhR +/+ and AhR -/- mice after bilateral common carotid artery occlusion revealed differential modulation. We report that AhR -/- mice significantly reduced the blood-brain barrier (BBB) dysfunction and neuronal death in hippocampus-CA1 caused by the ischemic insult, inducing neuroprotection. In addition, blocking the AhR with Resveratrol (a competitive antagonist) decreased neuronal degeneration and preserved the integrity of the BBB in the hippocampus associated with a neuroprotective effect. In summary, we showed that the AhR is an essential regulator for maintaining the BBB in the hippocampus and responds to inflammatory conditions and oxidative stress; further pharmacological targeting of AhR signaling may reduce the pathologic changes caused by an ischemic insult in the hippocampus.

Optimized steam boiler for soil steam disinfection: Structural design, CFD simulation, and field application

Soil steam disinfection offers a chemical-free solution to soil-borne pathogens and continuous cropping obstacles; however, its adoption in facility agriculture is severely limited by the lack of mobile and efficient steam generation systems. Conventional electric or coal-powered boilers are too bulky and immobile for practical field application. To bridge this technological gap, this study developed an optimized gasoline-powered steam boiler utilizing an innovative Helmholtz-type pulse combustion system. Key components, including a dual-carburetor Y-shaped throat and a helical tailpipe configuration, were designed to enhance compactness and thermal efficiency—achieving a 67.11% reduction in length and 204% increase in heat transfer area compared to a straight pipe equivalent. Computational fluid dynamics simulations systematically optimized the spatial arrangement of four pulse combustors, revealing layout as a critical performance factor. The optimal configuration reduced water heating time to 407.1 s, 15.52 s faster than the average across 12 designs. Field validation demonstrated that a double-layer steam injection needle significantly improved thermal retention, maintaining soil temperatures ≥80°C for 63.84 minutes—27.02% longer than a single-layer design following 6 minutes of steam injection. These findings confirm the system’s efficacy in delivering lethal thermal dosage to soil pathogens. This work not only provides a practical mobile soil steam disinfection solution but also advances fundamental insights into the design of efficient thermal fluid systems for agricultural applications.

Spiritual well-being as a protective factor for endothelial dysfunction in clinically healthy adults

Background Endothelial dysfunction (ED) is an early marker of cardiovascular disease (CVD), influenced by both physiological and psychosocial factors. While depression and anxiety are known contributors to ED, the role of spiritual well-being (SWB) in vascular health has been relatively less explored in the literature. Objective To investigate the association between SWB and ED in clinically healthy adults, controlling for mental health variables and conventional cardiovascular risk factors. Methods In this cross-sectional study, 148 individuals aged 18–60 years were assessed using validated instruments: FACIT-Sp for SWB, PHQ-9 for depression, GAD-7 for anxiety, and brachial artery flow-mediated dilation (FMD) for endothelial function. Logistic regression and discriminant analyses were performed to identify independent predictors of ED and the spiritual dimensions most associated with vascular health. Results ED was identified in 39.2% of participants. Multivariate logistic regression indicated that SWB (OR = 0.929; p  = 0.005), body mass index (OR = 1.130; p  = 0.016), generalized anxiety disorder (OR = 2.551; p  = 0.035), and major depressive episode (OR = 3.740; p  = 0.038), were significantly associated with ED. Among these, SWB was significantly inversely associated with ED even after excluding participants with anxiety or depression. Discriminant analysis further indicated that inner peace and life purpose—but not faith—significantly distinguished individuals with and without ED. Conclusion SWB, particularly dimensions related to inner peace and meaning, is independently associated with preserved endothelial function in healthy adults. These findings support the inclusion of psychosocial and spiritual dimensions in cardiovascular risk assessment and prevention strategies.

Machine learning-based prediction of glioma grading

Objective Gliomas are among the most common and heterogeneous primary tumours of the central nervous system. Accurate grading is essential for treatment planning and prognosis, yet conventional histopathological approaches are limited by subjectivity and poor reproducibility. This study aimed to develop a machine learning–based prediction model that integrates clinical and molecular characteristics to improve early glioma grading, thereby enhancing diagnostic accuracy and supporting individualized treatment strategies. Methods An efficient prediction model for low-grade gliomas (LGGs) and glioblastoma (grade IV, GBM) was developed by utilizing the clinical and molecular characteristics of gliomas from The Cancer Genome Atlas (TCGA) dataset. A novel integration of recursive feature elimination (RFE) with random forest (RF) and elastic net regression (ENR) was implemented to select features efficiently. Additionally, the synthetic minority oversampling technique (SMOTE) was applied to balance the training set, and K-nearest neighbours (KNN), support vector machine (SVM), and other algorithms were optimized through random-search hyper-parameter optimization (HPO) with five-fold cross-validation, yielding nine distinct machine learning (ML) models. Ultimately, by applying the voting and stacking algorithms, 34 ensemble learning models were constructed. Furthermore, all the models were externally validated using the Chinese Glioma Genome Atlas (CGGA) dataset. Finally, SHapley Additive exPlanations (SHAP) analysis was conducted to elucidate the prediction processes of the ensemble models. Results Feature selection revealed 11 key grading features, including Tumour Protein 53 (TP53) and Isocitrate Dehydrogenase 1 (IDH1). Among the 9 basic models constructed by combining optimization techniques such as SMOTE, the RF model had the best performance (Area Under Curve (AUC) of 0.916 for TCGA and 0.797 for CGGA). Among the 34 integrated models constructed, the Voting25 model integrating RF, Extreme Gradient Boosting (XGBoost), and KNN achieved AUC values of 0.928 and 0.794, respectively, on the TCGA and CGGA datasets, demonstrating overall optimal predictive performance. Conclusion Eleven key features have been identified that facilitate molecular detection and personalized targeted therapy for glioma. Nine models were developed and optimized, and the RF model was observed to provide the best performance, potentially guiding future ML-related research in glioma. Additionally, the voting ensemble method, which integrates RF, XGBoost, and KNN, was shown to achieve superior performance, thereby enhancing both accuracy and robustness. Finally, all the models were successfully validated on the CGGA dataset, indicating strong generalizability.

Stabilization of interdependent networks with two sub-networks of non-identical nodes

This paper explores the stabilization of interdependent networks comprising two sub-networks with non-identical nodes, in which one of the sub-networks is connected to the other in one-to-many mode. Firstly, we establish a mathematical model where the sub-networks possess different number of nodes. Besides, the outer coupling matrix is not required to satisfy the diffusive coupling condition. Then, based on some useful assumptions, adaptive decentralized controllers are designed to realize asymptotic stabilization of the system, the validity of the proposed controllers is rigorously established using Lyapunov stability methods. Finally, their effectiveness is demonstrated through two simulation examples.

Local Weather Types (LWTs) associated with Urban Heat Islands (UHIs) and hot days in the Grenoble area, France

Urban heat extremes are intensified by both global warming and the urban heat island (UHI) effect, particularly in summer. This study investigates the meteorological conditions driving extreme summer temperatures in Grenoble (French Prealps), a city with complex topography. The objectives are threefold: 1/ Assess the performance of the local weather types (LWTs) classification method in this context; 2/ Adapt and optimizing the method for topographically and climatically heterogeneous environments and 3/ Identify LWTs associated with extreme heat events—heatwaves, tropical nights and UHIs—for operational used by local authorities. Daily meteorological data (precipitation, temperature range, wind speed, wind direction and specific humidity), which are utilized for classification, are sourced from: (i) ERA5 reanalysis at the nearest the rural grid point (1960–2001 and 2002–2022), compensating for the lack of long-term representative data for the area; and (ii) a dense urban observation network (2019–2022). In this study, in order to better represent the complexity of meteorological conditions due to the incised topography, the original LWT method is modified. Methodological adjustments include discretizing precipitation into three categories and excluding wind direction, shown to have negligible influence due to topographic constraints. Results demonstrate that the modified LWT method effectively captures local meteorological variability and is transferable to similar contexts. LWTs linked to extreme heat events in Grenoble are characterized by high diurnal temperature ranges, dry conditions, elevated specific humidity, and low wind speeds.

Age and gender disparities in administration of opioid for cardiac chest pain in the emergency department

Background Previous data have shown sex differences in pain management for patients with cardiac chest pain in the emergency department (ED); however, the joint effect of sex and age on opioid administration has not been well studied. This study aimed to evaluate the combined effect of age and sex on the administration of opioid analgesics, specifically morphine and fentanyl, in ED patients presenting with cardiac chest pain. Methods This retrospective observational study included adults aged 18 years and older who presented to a single tertiary academic ED with acute cardiac chest pain between 2021 and 2025. Patients were categorized into four age–sex groups: older women (>57 years), younger women (18–57 years), older men (>57 years), and younger men (18–57 years). The primary outcome was the administration of intravenous (IV) morphine or fentanyl during the ED visit. Multivariable logistic regression was used to examine the association between these groups and the administration of opioids. Findings Among 1,870 eligible patients, 474 (25.4%) were older women, 323 (17.3%) were younger women, 659 (35.2%) were older men, and 414 (22.1%) were younger men. Compared to older women, all other age–sex groups had higher odds of receiving IVmorphine. Younger men had the highest odds (OR 2.19; 95% CI: 1.58–3.04; p < 0.001), followed by older men (OR 1.99; 95% CI: 1.22–3.26; p = 0.006) and younger women (OR 1.48; 95% CI: 0.87–2.52; p = 0.15), although the latter was not statistically significant. IV fentanyl use was low overall and did not differ significantly between groups. Conclusions Older women were significantly less likely to receive IV morphine than men. These findings suggest the need for standardized pain protocols and targeted clinician education to reduce potential bias in ED pain management.

Retraction: A deep learning-based ensemble for autism spectrum disorder diagnosis using facial images

How does it feel to run in minimalist and advanced footwear technology shoes: A qualitative study involving male recreational runners

We examined the perceptions and experiences of male recreational runners when using minimalist racing flats (FLAT, Saucony Endorphin Racer 2) and advanced footwear technology (AFT, Nike Vaporfly 4%) shoes, compared with their habitual shoes (OWN). Eighteen runners completed three 1.5 km outdoor trials, running in OWN first, followed by FLAT and AFT in a randomised counter-balanced order. Semi-structured interviews conducted before and after each trial provided qualitative data, analysed using a six-phase reflexive thematic approach. Five interconnected themes emerged: ‘novelty and familiarity’, ‘feel’, ‘performance’, ‘biomechanics’, and ‘injury’. Runners’ perceptions were shaped by iterative feedback loops combining experiential, educated, and instinctual assessments. OWN shoes were generally ranked highest for comfort and lowest for perceived injury risk due to familiarity and balanced design. Novel shoes elicited mixed reactions. FLAT shoes were valued for their lightweight and natural feel, but raised concerns about discomfort and potential injury from minimal cushioning and support. AFT shoes were appreciated for their bounciness and performance potential, but raised concerns about instability and excessive cushioning. Findings indicate that footwear comfort is multifaceted, context-dependent, and not always aligned with performance or injury reduction. Runners often prioritised performance over comfort in competitive scenarios, highlighting the inherent trade-offs in footwear selection and the importance of personalised approaches. Concerns about injury and biomechanics changes underscore the need for gradual transitions to novel footwear. By adopting a real-world approach, this study advances understanding of footwear perceptions, emphasises the dynamic and subjective nature of runners’ experiences, and offers practical implications for runners, clinicians, and shoe manufacturers.

Prevalence and factors associated with Intestinal parasitosis among adults with diabetes mellitus attending a tertiary care facility in Northern Uganda: A hospital-based cross-sectional study

Intestinal parasitosis (IP) constitutes a significant public health problem in developing countries, where more than three billion people worldwide are infected with one or more intestinal parasites. Diabetes mellitus (DM) is associated with an increased risk of acquiring IP. This study aimed to determine the prevalence and associated factors of IP among patients with DM attending Gulu Regional Referral Hospital (GRRH) in Northern Uganda. A hospital-based cross-sectional study was conducted using a semi-structured questionnaire and stool sample analysis. Descriptive statistics were used to summarize patient characteristics, and bivariate logistic regression was performed to assess associated factors of IP among DM patients attending GRRH. Out of the 267 eligible patients, 201 participated, indicating a response rate of 75.3%. The majority were female (68.2%, n = 137), with a mean age of 55.8 ± 12.8 years. Almost all participants had type 2 diabetes mellitus (99.0%, n = 199), with a mean duration of 7.0 ± 6.8 years and a mean fasting blood glucose of 11.9 ± 6.4 mmol/L. The prevalence of intestinal parasitosis was 19.4% (39/201). Entamoeba coli , a non-pathogenic commensal, accounted for 35 cases (89.7%), while the four pathogenic parasites; Hymenolepis nana, Giardia duodenalis, Entamoeba histolytica, and Iodamoeba buetschlii, were each identified in one case (2.6%). Patients who did not seek medical attention for the abdominal symptoms were three times more likely to have intestinal parasitoses (cOR =3.0, 95% CI: 1.18–7.53, P = 0.014). The notable prevalence of IP among patients with DM suggests heightened susceptibility in this population, which may adversely affect their quality of life. Routine screening for intestinal parasites is therefore recommended for diabetic patients.

Self-reflection, sense of agency, and underlying neural correlates: A pilot study

The sense of agency refers to the feeling of controlling one’s actions to influence the outside world. The association between an individual’s sense of agency and their psychological or behavioral characteristics has been extensively studied in recent years. However, the direct impact of self-reflection, a key strategy for modulating one’s cognitive state, on implicit measures of agency remains largely unexplored. We employed a between-subjects experimental design, to investigate the effect of two types of self-reflection - self-centered and selfless upon the implicit sense of agency. Additionally, we explored neural activity during self-reflection to see if there are any correlations with the sense of agency. Agency was measured using intentional time binding experiments, assessing the ability to perceive event sequences over time. Results indicated that self-centered reflection enhances time binding and agency, while selfless reflection has the opposite effect. Traditional spectral density measures and topological data analysis revealed distinct neural patterns for each type of reflection. Specifically, selfless reflection showed increased Hodge spectral entropy and persistent entropy compared to self-centered and control groups, indicating greater topological complexity in EEG time series. A significant negative correlation between second-order Hodge spectral entropy and time binding effect was observed. The study provided initial evidence that topological EEG features could serve as potential neural markers of the sense of agency modulated through self-reflection.

Cross-cultural measurement invariance of the multidimensional competitive orientation inventory: Non-clinical samples in South Korea and Hungary

The Multidimensional Competitive Orientation Inventory (MCOI) aims to assess competitive orientations including self-developmental, hypercompetitive, avoidant, and indifferent attitudes. The present study tested its cross-cultural applicability and examined cross-national differences between South Korea ( n  = 350) and Hungary ( n  = 343), taking cultural traits into account. Using a revised 10-item version (two low-loading items removed), multi-group CFA with WLSMV supported configural and scalar invariance across countries. Factor variances were invariant, whereas factor covariances were not, indicating that inter-factor correlations differed across countries despite a shared structure. For criterion validity analyses, we conducted cross-group comparisons only for measures that demonstrated invariance; noninvariant measures were interpreted within each country. Overall, the results suggest that the MCOI can be used cross-culturally with appropriate scale adjustment. However, competitive orientations may manifest differently across individualistic and collectivistic cultures in both the motivations for and consequences of competition, underscoring the need for further research. Implications for the practical use of the MCOI and directions for future research are discussed.

Biocompatibility and antimicrobial efficacy of iodine-supported titania nanotubes on 3D-printed Ti-6Al-4V implants

Implant-associated infections (IAI) are a significant concern within the field of orthopedics. To develop an implant with antimicrobial properties, titania nanotubes (TNTs) supported with iodine were synthesized on 3D-printed Ti-6Al-4V implants using the electrochemical anodization (ECA) technique. This study aims to analyze the release profile of iodine and the antimicrobial efficacy and cytotoxicity of the iodine-supported TNT (I-TNTs) on the 3D-printed Ti-6Al-4V implant. 3D-printed Ti-6Al-4V samples were doped with six different iodine formulations, including four test groups containing TNT and two control groups without TNT. As printed 3D Ti-6Al-4V samples and TNTs samples without iodine were also utilized as control groups. In vitro assays were performed to assess the drug elution, cytotoxicity, and antimicrobial efficacy. All tested I-TNTs samples exhibited sustained iodine release over 28 days without an initial burst. Notably, the amount of iodine released from I-TNTs was significantly higher compared to the control group. TNTs with a higher aspect ratio (AR) and the ECA process using higher potassium iodide (KI) concentration were found to have better cumulative iodine release profiles. No cytotoxicity was observed when tested against the mouse calvaria-derived preosteoblast cell line (MC3T3-E1). The antibacterial property of the implant surface became evident within 24 hours, with complete inhibition of S. aureus and MRSA in I-TNTs samples. This innovative approach is an intriguing alternative for preventing infections on 3D-printed Ti-6Al-4V implants.

SSE forecasts based on market–sentiment dual anchoring

Anchoring is widely considered one of the most robust and consistently observed effects in experimental psychology. This study employs the highest and lowest indices of the Shanghai Stock Exchange (SSE) alongside the highest and lowest bullish sentiments over a 52-week period as anchors, in conjunction with Fibonacci retracement levels, to develop a dual market–sentiment anchoring multivariate feature matrix. Based on this feature matrix, we propose a forecasting model called Market Sentiment Dual Anchoring CNN2D-ABiLSTM (MSD-CNN2D-ABiLSTM). This model employs CNN2D to extract spatial features from market and sentiment data, utilizes BiLSTM networks to process and integrate temporal features, and incorporates an attention mechanism to emphasize essential spatial and temporal information. Experimental results indicate that this model achieves a prediction accuracy exceeding 90% and an R 2 value greater than 95% for lags of 1–2 trading days, enabling precise forecasting of the SSE index. Additionally, the model demonstrates effective forecasting performance for up to 10 trading days ahead, significantly outperforming traditional baseline models. Furthermore, structural sensitivity tests reveal that the extraction of local spatial features by CNN2D provides a predictive advantage over the short-term temporal features captured by CNN1D in complex market structures.

A research protocol using ECG monitoring for detection of palpitations-associated arrhythmias in breast cancer survivors

Palpitations are common but understudied in breast cancer survivors (BCS). Palpitations may relate to severe arrhythmias, resulting in life-threatening events or cardiac death. However, how palpitations relate to arrhythmias and electrocardiogram abnormalities is unknown. The purpose of the proposed project is to demonstrate the feasibility of using wearable electrocardiogram (ECG) monitors in BCS to detect and characterize arrhythmias associated with self-reported palpitations and to gain a comprehensive understanding of palpitations using an investigator-designed Palpitations Assessment Tool (PAT). We will conduct a prospective cohort study of 84 BCS (54 BCS with palpitations and 30 without). Eligible participants will include breast cancer patients who completed chemotherapy at least six months ago and no more than three years ago. Palpitations and arrhythmias will be recorded using an ECG monitor for two 7-day periods, one month apart. Feasibility, acceptability, and retention, as measured by completion of the PAT and monitored wearing for 7 days, will be evaluated using frequency distribution in recruitment and retention logs. We will generate descriptive summaries of the prevalence of primary outcomes, including frequency of palpitations and changes in cardiac rate and rhythm, and examine associations between these outcomes.