bluuebunny/crossref_metadata_2025_split huggingface dataset:
Electrocardiogram-based machine learning for risk stratification of patients with suspected acute coronary syndrome
Authors: Bouzid Zeineb , Sejdic Ervin , Martin-Gill Christian , Faramand Ziad , Frisch Stephanie , Alrawashdeh Mohammad , Helman Stephanie , Gokhale Tanmay A , Riek Nathan T , Kraevsky-Phillips Karina , Gregg Richard E , Sereika Susan M , Clermont Gilles , Akcakaya Murat , Zègre-Hemsey Jessica K , Saba Samir , Callaway Clifton W , Al-Zaiti Salah S 
Published: January 2025

Abstract

Background and Aims
The importance of risk stratification in patients with chest pain extends beyond diagnosis and immediate treatment. This study sought to evaluate the prognostic value of electrocardiogram feature-based machine learning models to risk-stratify all-cause mortality in those with chest pain.

Methods
This was a prospective observational cohort study of consecutive, non-traumatic patients with chest pain. All-cause death was ascertained from multiple sources, including the CDC National Death Index registry. Six machine learning models were trained for survival analysis using 73 morphological electrocardiogram features (80% training with 10-fold cross-validation and 20% testing), followed by a variational Bayesian Gaussian mixture model to define distinct risk groups. The resulting classification performance was compared against the HEART score.

Results
The derivation cohort included 4015 patients (age 59 ± 16 years, 47% women). The mortality rate was 20.3% after a median follow-up period of 3.05 years (interquartile range 1.75–5.32). Extra Survival Trees outperformed other forecasting models, and the derived risk groups successfully classified patients into low-, moderate-, and high-risk groups (log-rank test statistic = 121.14, P &lt; .001). This model outperformed the HEART score, reducing the rate of missed events by &gt;90% with a negative predictive value and sensitivity of 93.4% and 85.9%, compared to 89.0% and 75.0%, respectively. In an independent external testing cohort (N = 3095, age 59 ± 15 years, 44% women, 30-day mortality 3.5%), patients in the moderate [odds ratio 3.62 (1.35–9.74)] and high [odds ratio 6.12 (2.38–15.75)] risk groups had significantly higher odds of mortality compared to those in the low-risk group.

Conclusions
The externally validated machine learning-based model, exclusively utilizing features from the 12-lead electrocardiogram, outperformed the HEART score in stratifying the mortality risk of patients with acute chest pain. This may have the potential to impact the precision of care delivery and the allocation of resources to those at highest risk of adverse events.
Heart failure risk stratification using artificial intelligence applied to electrocardiogram images: a multinational study
Authors: Dhingra Lovedeep S , Aminorroaya Arya , Sangha Veer , Pedroso Aline F , Asselbergs Folkert W , Brant Luisa C C , Barreto Sandhi M , Ribeiro Antonio Luiz P , Krumholz Harlan M , Oikonomou Evangelos K , Khera Rohan 
Published: January 2025

Abstract

Background and Aims
Current heart failure (HF) risk stratification strategies require comprehensive clinical evaluation. In this study, artificial intelligence (AI) applied to electrocardiogram (ECG) images was examined as a strategy to predict HF risk.

Methods
Across multinational cohorts in the Yale New Haven Health System (YNHHS), UK Biobank (UKB), and Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), individuals without baseline HF were followed for the first HF hospitalization. An AI-ECG model that defines cross-sectional left ventricular systolic dysfunction from 12-lead ECG images was used, and its association with incident HF was evaluated. Discrimination was assessed using Harrell’s C-statistic. Pooled cohort equations to prevent HF (PCP-HF) were used as a comparator.

Results
Among 231 285 YNHHS patients, 4472 had primary HF hospitalizations over 4.5 years (inter-quartile range 2.5–6.6). In UKB and ELSA-Brasil, among 42 141 and 13 454 people, 46 and 31 developed HF over 3.1 (2.1–4.5) and 4.2 (3.7–4.5) years. A positive AI-ECG screen portended a 4- to 24-fold higher risk of new-onset HF [age-, sex-adjusted hazard ratio: YNHHS, 3.88 (95% confidence interval 3.63–4.14); UKB, 12.85 (6.87–24.02); ELSA-Brasil, 23.50 (11.09–49.81)]. The association was consistent after accounting for comorbidities and the competing risk of death. Higher probabilities were associated with progressively higher HF risk. Model discrimination was 0.718 in YNHHS, 0.769 in UKB, and 0.810 in ELSA-Brasil. In YNHHS and ELSA-Brasil, incorporating AI-ECG with PCP-HF yielded a significant improvement in discrimination over PCP-HF alone.

Conclusions
An AI model applied to a single ECG image defined the risk of future HF, representing a digital biomarker for stratifying HF risk.
Epidemiological pattern of dengue fever in Afghanistan in the period 2021–22
Authors: Tahoun Mohamed M , Mashal Mohammad O , Laiq Abdul Rahman , Amiri Abdul Wahid , Elnossery Sherein T A , Salem Marwa Rashad , Hegazy Nelly S , Eldeeb Sherif E , Alizai Fazal Elahi , Misbah Ehsanullah , Tanoli Jamshed A , Abouzeid Alaa H 
Published: January 2025

Abstract
Dengue fever is considered as an emerging disease in Afghanistan. Since the first outbreak was reported in 2019, other outbreaks have been reported in the following years. The current study aims to describe the epidemiological features and clinical manifestations of suspected and confirmed cases of dengue fever detected by the National Disease Surveillance and Response (NDSR) Department of the Ministry of Public Health (MoPH) during 2021 and 2022 to prevent further spread and minimize its impact on the country’s health system and on the limited number of health workers. Through a retrospective analysis of historical data related to suspected dengue fever cases in Afghanistan detected by the National Disease Surveillance and Response Department during 2021 and 2022, several variables were identified, including demographic characteristics, clinical features, clinical management, the outcome of infection, laboratory data, and epidemiological factors. All statistical analyses were developed using Microsoft 365 (Excel). The mean age of the 1977 reported suspected dengue fever cases was 30.4 ± 14.9 years, with males 70.7%. The epidemic curve showed a steep rise in cases in 2022, starting from week 39, with a peak reached in week 45, which was higher than that observed in 2021. The majority of cases (97.9%) were reported from Nangarhar Province, east of the country. Regarding symptoms, fever, headache, and muscle pain were expressed in nearly all cases. The reverse transcription polymerase chain reaction was positive in 379 cases out of 497 cases (76.3%). For the management of cases, 97.6% received antipyretics. Less than 5% of cases were admitted to health care units, with death reported in only two cases (case fatality rate of 0.1%). The number of suspected cases of dengue fever reported in Afghanistan was increasing. The trends for 2021 and 2022 followed almost the same pattern, with a higher peak in 2022. Understanding the epidemiological and clinical characteristics of dengue fever cases is fundamental for preparedness for upcoming seasons.
Bartonellosis in World Health Organization Eastern Mediterranean Region, a systematic review and meta-analysis
Authors: Tahmasebi Ashtiani Zahra , Bagheri Amiri Fahimeh , Ahmadinezhad Mozhgan , Mostafavi Ehsan , Esmaeili Saber 
Published: January 2025

Abstract
Bartonella is a vector-borne zoonotic pathogen, which could also be transmitted directly and cause a variety of clinical illnesses. This study aimed to investigate the prevalence of Bartonella in countries in the WHO Eastern Mediterranean Region (WHO-EMR) region. We searched using the keywords Bartonella and the name of each country in the WHO-EMR in databases such as PubMed, ISI (Web of Science), Scopus, and Google Scholar, with a publication date range of 1990–2022 and limited to English articles. We evaluated the quality of the studies using the STROBE 6-item checklist and used the random effects model to integrate the findings of the included studies. A total of 45 papers out of 240 were included in the analysis. The results showed the prevalence of Bartonella infection among endocarditis patients was 3.8% (95% CI: 0.2–7.4) and the seroprevalence of Bartonella among other people was 27.5% (95% CI: 13.5–41.5). The overall prevalence of Bartonella spp. among animals, as determined by molecular, serological, and culture methods, was 11.9% (95% CI: 5.7–18.2), 38.9% (95% CI: 27.5–50.2), and 1.7% (95% CI: 0.5–2.9), respectively. Furthermore, the prevalence of Bartonella spp. in ectoparasites was 3.9% (95% CI: 3.5–5.2), with fleas (6.2%) showing a higher prevalence compared to lice (4.9%) and ticks (1.0%). The detection of Bartonella in all animal and ectoparasites species and human populations in the WHO-EMR with prevalence ranging from 0.3% to 23% is concerning, emphasizes the importance of conducting more comprehensive studies to gain a deeper understanding of the spread of Bartonella in these areas.
An epidemiological risk assessment of imported malaria cases and potential local transmission in Qatar
Authors: Bansal Devendra , Assaad Nada , Mohamed Hend Omar , Shanmugakonar Muralitharan , Pacate Dorothy , Mohamed Khider , Balakrishnan Perumal , Ramiscal Redentor Cuizon , Ganesan Nandakumar , Al-Shamali Maha Hammam M A , Sultan Ali A , Munir Waqar , Abukhattab Mohammed , Schaffner Francis , Al-Maslamani Muna A , Eid Al-Romaihi Hamad , Al-Thani Mohammed , Al Khayat Fatima , Farag Elmoubashar Abd 
Published: January 2025

Abstract
Preventing local transmission of malaria from imported cases is crucial for achieving and maintaining malaria elimination. This study aimed to investigate the epidemiological characteristics of imported malaria cases and assess the distribution of malaria vectors in Qatar. Data from January 2016 to December 2022 on imported malaria, including demographic and epidemiological characteristics, travel-related information, and diagnostic results, were collected and analysed using descriptive statistics. Field surveys conducted in 2021–22 collected mosquitoes using various traps across Qatar. The collected samples underwent morphological and molecular characterization at Qatar University. A total of 2693 cases were reported, with a mean incidence of 13.5/100 000 population, decreasing from 18.8/100 000 in 2016 to 5.5/100 000 in 2020. Most cases were Plasmodium vivax (57.4%) followed by P. falciparum (40.4%). The median age was 32.9 ± 12.5 years, primarily males (86.7%), expatriates (99.6%) and notified during the hot months (July to September). Cases were mainly imported from the Eastern Mediterranean Region followed by the African and South-East Asia Region with no deaths and indigenous cases. Anopheles stephensi was identified as a widely distributed species, but none carried the Plasmodium pathogen. Despite no reports of local transmission, the presence of An. stephensi and favourable environmental conditions pose a risk in Qatar. Strengthening surveillance for imported malaria and reviewing epidemic protocols are necessary. Conventional field studies are imperative to address knowledge gaps in Anopheles mosquito ecology and biting habits in Qatar, accurately assessing the risk of local malaria transmission to support Qatar’s malaria-free status.
Digest: Evolution of dragline silk in araneids show super tensile performance in web-building and non-web-building spiders
Authors: Chakraborty Snata 
Published: January 2025

Abstract
Wolff (2024) takes a comparative phylogenetic approach to study the evolution of dragline silk in 164 species of spiders, including both araneid and non-araneid species. Many structural and mechanical properties of dragline silk showed no correlations; however, both tensile strength and toughness correlated with birefringence—an indicator for the directional ordering of protein materials in the silk fibre. These properties do not seem to differ between web-building and non-web-building spiders; many spider families were found to include species that produce super-performing silk as well as species that produce weak-performing silk.
Investigation of the mesencephalic astrocyte-derived neurotrophic factor–endoplasmic reticulum stress pathway in mood disorders
Authors: Ali Mohammad , Wollenhaupt-Aguiar Bianca , Wang Yifan , Abu-Hijleh Fahed , Rigg Nicolette , de Azevedo Cardoso Taiane , Ahmed Imran , Gopalakrishnan Ridhi , Jansen Karen , de Mattos Souza Luciano Dias , Azevedo da Silva Ricardo , Mondin Thaise Campos , Kapczinski Flavio , Moreira Fernanda Pedrotti , Lofts Andrew , Gwynne William D , Hoare Todd , Mishra Ram , Frey Benicio N 
Published: January 2025

Abstract

Background
Bipolar disorder (BD) has been associated with impaired cellular resilience. Recent studies have shown abnormalities in the unfolded protein response (UPR) in BD. The UPR is the cellular response to endoplasmic reticulum (ER) stress. Mesencephalic astrocyte-derived neurotrophic factor (MANF), a trophic factor, decreases ER stress by modulating the UPR. The objective of this study is to investigate the MANF-ER stress pathway in BD and major depressive disorder (MDD) compared to healthy controls (HC).

Methods
MANF protein concentration and MANF and GRP78 gene expression were assessed in peripheral blood from individuals with BD, MDD, and HC (protein: 40 BD, 55 MDD, 55 HC; gene expression: 52 BD, 61 MDD, 69 HC). MANF protein and gene expression along with GRP78 gene expression were also analyzed in postmortem brain tissue (20 BD, 20 MDD, 19 HC). MANF protein was quantified using an ELISA assay while quantitative polymerase chain reaction was used for MANF and GRP78 gene expression.

Results
Peripheral MANF protein levels were reduced in individuals with BD in a depressive state compared to controls (P = .031) and euthymic BD participants (P = .013). No significant differences in MANF or GRP78 gene expression were observed in BD irrespective of mood state, or MDD compared to HC (all P &gt; .05). No differences were observed regarding MANF/GRP78 protein or gene expression levels in postmortem tissue (P &gt; .05).

Conclusions
Individuals with BD who were in an acute depressive phase were found to have reduced peripheral MANF levels potentially signifying abnormal UPR and supporting the notion that BD is associated with increased ER stress.
Stability of stationary states for mean field models with multichromatic interaction potentials
Authors: Bertoli Benedetta , Goddard Benjamin D , Pavliotis Grigorios A 
Published: January 2025

Abstract
We consider weakly interacting diffusions on the torus, for multichromatic interaction potentials. We consider interaction potentials that are not $H$-stable, leading to phase transitions in the mean field limit. We show that the mean field dynamics can exhibit multipeak stationary states, where the number of peaks is related to the number of nonzero Fourier modes of the interaction. We also consider the effect of a confining potential on the structure of nonuniform steady states. We approach the problem by means of analysis, perturbation theory and numerical simulations for the interacting particle systems and the PDEs.
Pharmacodynamics of NOSO-502 studied in vitro and in vivo: determination of the dominant pharmacodynamic index driver
Authors: van den Berg Sanne , Attwood Marie G L , Griffin Pippa , Sassen Sebastiaan D T , Muller Anouk E , Raaphorst Merel N , Gualtieri Maxime , Racine Emilie , Das Shampa , Noel Alan R , Meletiadis Joseph , MacGowan Alasdair P 
Published: January 2025

Abstract

Background
NOSO-5O2 is the first clinical candidate of a new antimicrobial class—the odilorhabdins. The pharmacodynamics of NOSO-502 were studied in vitro and in vivo to establish the pharmacodynamic index (PDI) driver.

Methods
A dilutional pharmacokinetic system was used for in vitro experiments. In vivo experiments were conducted in the neutropenic murine thigh infection model. Three Escherichia coli and two Klebsiella pneumoniae strains were used. NOSO-502 pharmacokinetics (PK) in mice were described in a population PK model. Dose fractionation and escalation exposures were performed and bacteriostatic and 1 log10 and 2 log10 kill effects were determined using an Emax model. The coefficient of determination (R2) was used to estimate the variance that might be due to regression with various PDIs (fAUC/MIC, fCmax/MIC, %fT&gt;MIC and fAUC/MIC per length of dosing interval fAUC/MIC·1/tau).

Results
Exposure fractionation in both in vitro and in vivo studies indicated that 6-hourly dosing resulted in a greater reduction in K. pneumoniae bacterial burden compared with either 12- or 24-hourly dosing. Similar observations were made with three E. coli strains in vitro and a single strain of E. coli in vivo. For K. pneumoniae, R2 for fAUC/MIC·1/tau was 0.8376 in vitro and 0.6001 in vivo, which was greater than R2 with other PDIs. Analysis of pooled in vitro data from three strains of E. coli produced an R2 of 0.7073 for fAUC/MIC and 0.6100 for fAUC/MIC·1/tau.

Conclusions
NOSO-502 exhibits both dose- and time-dependent in vitro and in vivo activity against both E. coli and K. pneumoniae.
Determination of Positivity Cutoff for an Automated Aspergillus fumigatus-Specific Immunoglobulin-G Assay in a National Reference Laboratory
Authors: Lozier Bucky , Martins Thomas , Slev Patricia , Saadalla Abdulrahman 
Published: January 2025

Abstract

Background
Detection of serum-specific immunoglobulin G (sIgG) to Aspergillus fumigatus traditionally relied on precipitin assays, which lack standardization and have poor analytical sensitivity. Automated quantitative immunoassays are now more widely used alternatives. A challenge, however, is determining reference interval (RI) cutoffs indicative of disease presence.

Methods
Sera from 152 local healthy donors were tested for Aspergillus fumigatus sIgG using the ImmunoCAP assay to calculate a nonparametric RI cutoff. Results from 178 patient samples cotested by the precipitin and ImmunoCAP assays were analyzed using receiver operator characteristic (ROC) curve to determine an optimal sIgG concentration for precipitin positivity. Clinical information available for 46 patients tested by the ImmunoCAP assay was also used to estimate an optimal sIgG cutoff for pulmonary aspergillosis diagnosis.

Results
Specific-IgG concentration at 81.5 mcg/mL corresponded to the 97.5th percentile of tested healthy donors. The ROC-driven optimal IgG cutoff for precipitin positivity was at 40.4 mcg/mL with 67.8% sensitivity [95% confidence interval (CI): 54.4% to 79.4%%] and 72.3% specificity (95% CI: 63.3% to 80.1%). Using clinical diagnoses, an IgG concentration at 64.7 mcg/mL had optimal sensitivity (77.8%; 95% CI: 61.9% to 88.3%) and specificity (66.7%, 95% CI 39.1% to 86.2%) for pulmonary aspergillosis.

Conclusions
Our healthy donor-driven RI cutoff was higher than estimated optimal sIgG values based on precipitin positivity and disease presence. As fungal sIgG levels can be impacted by local environmental exposures, and given the limited size of our clinical dataset, adopting an assay cutoff based on precipitin results (40.4 mcg/mL) can be more objective.
Development of alginate hydrogel baits for the management of longlegged ant (Hymenoptera: Formicidae)
Authors: Lee Ching-Chen , Lu Ming-Yi , Chen Joanne Tzu-Chia , Tay Jia-Wei , Yang Chin-Cheng Scotty , Lin Chung-Chi 
Published: January 2025

Abstract
The longlegged ant, Anoplolepis gracilipes, is a globally destructive invasive species owning to its devastating impacts on biodiversity and ecosystem functions in the regions where it has been introduced. In Taiwan, invasion of A. gracilipes has been associated with the declining of land crab populations in several hotspots. While liquid baiting program has been implemented in those areas, the operation is costly and labor-intensive since it typically requires the use and maintenance of bait stations. The goal of the current study was to evaluate the potential and effectiveness of hydrogel baits laced with borax as an alternative tool to control A. gracilipes. Laboratory studies demonstrated that hydrogel baits containing 3% borax achieved higher A. gracilipes mortality than those containing 2% and 1% borax. Specifically, hydrogel baits containing 3% borax resulted in &gt;90% worker mortality within 21 d post-treatment (LT50 = 5.1 d), along with significant reduction in brood weight (&gt;90%) and substantial queen death (&gt;80% of colony fragments). Furthermore, field experiment indicated that A. gracilipes workers preferentially retrieved small-size hydrogel beads (3.1 mm OD; proportion removed = 1.00 ± 0.00) compared to the larger ones (6.2 mm OD; proportion removed = 0.03 ± 0.03), which will facilitate efficient transfer of toxicant within the colony and may minimize nontarget impact. In conclusion, alginate hydrogel baits with 3% borax appear to be a promising tool against A. gracilipes, although their field efficacy against large supercolonial populations remains to be investigated.
Nondestructive detection and rapid segmentation of the development process of Sitophilus zeamais in single wheat kernels based on CT and MV-UNet
Authors: Gao Ju , Zhou Ying , Hui Yanbo , Zhang Yongzhen , Wang Qiao , Liu Juanjuan , Wang Xiaoliang , Wang Hongxiao , Ding Hao , Ding Haiyang 
Published: January 2025

Abstract
Wheat is prone to insect infestations during harvesting, transportation, and storage, leading to heat, mold, and deterioration. Timely pest detection is vital for effective prevention and improved storage quality. Traditional methods, such as manual identification and biological information detection, have limitations, including low efficiency, grain damage, and difficulty in identifying pest larvae. This study proposed a method for detecting Sitophilus zeamais (S. zeamais) in the interior of wheat based on computed tomography technology and the Multi-feature and Vision Transformer U-Net model. The U-Net was enhanced with the Multi-Feature Extraction block and the Residual Vision Transformer block. After 200 training iterations, the model achieved a mean Intersection over Union of 94.4%. To use image processing technology to segment S. zeamais, create 3D models, and extract features such as volume, surface area, and length. S. zeamais develops through stages: egg, early larva, late larva, pupal, and adult. From epidermal erosion into the endosperm, it transitions from a round egg stage to a columnar shape and then develops various organs. The volume of the S. zeamais increases from 0.008 to 0.018 mm³ during the egg stage to 0.89 to 1.16 mm³ in the adult stage, and its length grows from 0.176 to 0.284 mm during the egg stage to 2.416 to 2.865 mm in the adult stage. This method offers accurate, rapid extraction and visualization of S. zeamais developmental information, supporting early-stage variation analysis and enhancing wheat quality and pest control.