bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pre-conception clinical risk factors differ between spontaneous and indicated preterm birth in a densely phenotyped EHR cohort
Authors: Costello Jean M. , Takasuka Hannah , Roger Jacquelyn , Yin Ophelia , Tang Alice , Oskotsky Tomiko , Sirota Marina , Capra John A. 
Published: February 2025

Abstract

Background
Preterm birth (PTB) is the leading cause of infant mortality. Risk for PTB is influenced by multiple biological pathways, many of which are poorly understood. Some PTBs result from medically indicated labor following complications from hypertension and/or diabetes, while many others are spontaneous with unknown causes. Previously, investigation of potential risk factors has been limited by a lack of data on maternal medical history and the difficulty of classifying PTBs as indicated or spontaneous. Here, we leverage electronic health record (EHR) data (patient health information including demographics, diagnoses, and medications) and a supplemental curated pregnancy database to overcome these limitations. Novel associations may provide new insight into the pathophysiology of PTB as well as help identify individuals who would be at risk of PTB.

Methods
We quantified associations between maternal diagnoses and preterm birth both with and without controlling for maternal age and socioeconomic factors within a University of California, San Francisco (UCSF), EHR cohort with 10,643 births (n

term
= 9692, n

spontaneous_preterm
= 449, n

indicated_preterm
= 418) and maternal pre-conception diagnoses derived from International Classification of Diseases (ICD) 9 and 10 codes.

Results
Thirty diagnoses significantly and robustly (False Discovery Rate (FDR) < 0.05) associated with indicated PTBs compared to term. We discovered known (hypertension, diabetes, and chronic kidney disease) and less established (blood, cardiac, gynecological, and liver diagnoses) associations. Essential hypertension had the most significant association with indicated PTB (adjusted pBH = 4 × 10–20, adjusted OR = 6 (95% CI 4-8)), and the odds ratios for the significant diagnoses ranged from 2 to 23. The results for indicated PTB largely recapitulated the diagnosis associations with all PTBs. However, no diagnosis significantly associated with spontaneous PTB.

Conclusions
Our study underscores the limitations of approaches that combine indicated and spontaneous births. When combined, significant associations were almost entirely driven by indicated PTBs, although the spontaneous and indicated groups were of a similar size. Investigating the spontaneous population has the potential to reveal new pathways and understanding of the heterogeneity of PTB.
Analytical validation of Exandra: a clinical decision support system for promoting guideline-directed therapy of type-2 diabetes in primary care – a collaborative study with experts from Diabetes Canada
Authors: Grechuta Klaudia , Shokouh Pedram , Bayer Valentina , Kraemer Henrich , Gilbert Jeremy , Jin Susie , Alhussein Ahmad 
Published: February 2025

Abstract

Background
Individuals with type 2 diabetes (T2D) have a high prevalence of cardiovascular and renal comorbidities. Despite clinical practice guidelines recommending the use of cardiorenal protective medications, many people with T2D are not prescribed these medications. A clinical decision support system called Exandra was developed to provide treatment recommendations for individuals with T2D based on current clinical practice guidelines from Diabetes Canada. The current study aimed to medically validate Exandra via review by external medical experts in T2D.

Methods
Validation of Exandra took place in two phases. Test cases using simulated clinical scenarios and recommendations were generated by Exandra. In Phase 1 of the validation, reviewers evaluated whether they agreed with Exandra’s recommendations with a “yes,” “no,” or “not sure” response. In Phase 2, reviewers were interviewed about their “no” and “not sure” responses to determine possible reasons and potential fixes to the Exandra system. The primary outcome was the precision rate of Exandra following the interviews and final adjudication of the cases. The target precision rate was 90%.

Results
Exandra displayed an overall precision rate of 95.5%. A large proportion of cases that were initially labeled “no” or “not sure” by reviewers were changed to “yes” following the interview phase. This was largely due to the validation using a simplified user interface compared with the complexity of the actual Exandra system, and reviewers needing clarification of how the outputs would be displayed on the Exandra platform.

Conclusion
Exandra displayed a high level of accuracy and precision in providing guideline-directed recommendations for managing T2D and its common comorbidities. The results of this study indicate that Exandra is a promising tool for improving the management of T2D and its comorbidities.
miR-485-5p/NQO1 axis drives colorectal cancer progression by regulating apoptosis and aerobic glycolysis
Authors: Wang Yixuan , Zhou Houkun , Liu Ying , Zhao Xingyu , Wang Shuhao , Lin Zhenhua 
Published: February 2025

Abstract

Background
Cancer cells undergo a metabolic shift termed the Warburg effect, transitioning from oxidative phosphorylation to aerobic glycolysis and promoting rapid tumor proliferation. Quinone oxidoreductase (NQO1), a cytosolic flavoprotein, is important for reprogramming cancer cell metabolism. Therefore, NQO1’s function in aerobic glycolysis and impact on colorectal cancer (CRC) development and progression was investigated.

Methods
The clinical significance of NQO1 was evaluated by analyzing online databases and was substantiated in CRC specimens. NQO1’s influence on proliferation, epithelial-mesenchymal transition (EMT), metastasis, apoptosis, and glycolytic pathways in CRC cells was evaluated using in vitro and in vivo experiments. The molecular interactions between NQO1 and microRNA-485-5p (miR-485-5p) were ascertained via quantitative reverse transcription PCR and dual luciferase reporter assays. The molecular mechanisms underlying the miR-485-5p/NQO1 axis and its effects on progression of malignancy and aerobic glycolysis in CRC cell lines were investigated.

Results
NQO1 promoted CRC cell proliferation and EMT, augmented their metastatic potential, and suppressed their apoptosis. The NQO1 overexpression-mediated enhancement of glycolytic activity is implicated in the increased proliferation, EMT, and metastatic abilities of, and reduced apoptosis in, CRC cells. Further, miR-485-5p may inhibit the proliferative and invasive traits of CRC cells by directly targeting the 3′ untranslated region of NQO1 mRNA.

Conclusions
miR-485-5p/NQO1 signaling axis orchestrates aerobic glycolysis, thereby modulating CRC cell proliferation, metastasis, and apoptosis. Our study provides mechanistic perspectives regarding the role of NQO1 in CRC progression.
Where is the hard-to-reach population? Spatial analysis from a cross-sectional study on the access to bed net and malaria vaccine in the Lake Victoria Region, Kenya
Authors: Ko Yura K. , Kagaya Wataru , Yoneoka Daisuke , Kongere James , Opiyo Victor , Oginga Jared , Omondi Protus , Musyoka Kelvin B. , Chan Chim W. , Kanoi Bernard N. , Gitaka Jesse , Kaneko Akira 
Published: February 2025

Abstract

Background
Long-lasting insecticidal nets (LLIN) and vaccines are effective malaria control tools. However, inadequate uptake has been reported in countries where both interventions are available. To maximize the impact these tools provide, it is crucial to identify populations that are not being reached and the barriers to uptake.

Methods
In a cross-sectional study conducted in April 2024 in Kanyamwa Kologi Ward in Homa Bay County, Kenya, 4,662 households in 58 randomely selected villages were visited and interviewed. The proportions of households that (1) received at least one new LLIN within the previous five months (net distribution), (2) reported all children used LLIN (net usage), (3) reported at least one child had received one dose of the RTS,S vaccine (vaccine uptake), and (4) reported all children had received four doses of the vaccine (vaccine completion) were examined. Bayesian spatial autoregression analyses were used to estimate adjusted odds ratio (aOR) and its credible intervals (CrI) to identify the association between the household-level characteristics and the four outcomes.

Results
The overall uptake proportions were 89.9% for net distribution, 84.4% for net usage, 88.2% for vaccine uptake, and 53.7% for vaccine completion. All four outcomes showed geographical heterogeneity with significant (p < 0.05) Moran's I. Households headed by adults of > 40 years had higher odds of having received a new LLIN (aOR = 2.02, 95% CrI 1.02–5.42), having one child who had received one vaccine dose (aOR = 1.83, 0.69–4.66), and having all children fully vaccinated (aOR = 2.36, 1.09–5.46), but lower odds of net usage by all children (aOR = 0.62, 0.40–0.96). Households with five or more children had higher odds of having received a new LLIN (aOR = 5.36, 2.24–27.0) but lower odds of net usage by all children (aOR = 0.24, 0.14–0.38) and having all children fully vaccinated (aOR = 0.20, 0.04–0.61). Distance to the nearest health centre was negatively associated with all outcomes. Household wealth was positively associated with all outcomes.

Conclusion
Uptake of LLIN and malaria vaccine in Homa Bay County, Kenya varied by geography and household characteristics. These findings suggest that different sets of actions should be considered to improve the coverage and compliance of these interventions in different areas.
SHP Buddy: a QGIS plugin for generating shapefiles to support remote sensing in plant breeding and agronomic experiments
Authors: Burner Nathaniel , Harris Donna K. , Li Zenglu 
Published: February 2025

Abstract

Background
Shapefiles are a geospatial vector data format used to indicate geographic features in geographic information systems (GIS) software. Shapefiles are used in high-throughput phenotyping plant breeding and agronomic studies to identify plots from aerial imagery and extract remote sensing data. However, the process of manually creating shapefiles is tedious and error prone. Current options that assist in shapefile generation suffer from issues such as installation processes that require a degree of programming knowledge or inefficient methods for incorporating plot-level information from field books. In this study, we have developed a program called ‘SHP Buddy’, a QGIS plugin that provides accessible and intuitive functions that quickly generate shapefiles for common experimental layouts used in agricultural research.

Results
SHP Buddy is a free and open source QGIS plugin that is easily downloaded directly from the QGIS plugin repository. It provides options for generating serpentine replicated and unreplicated experimental layouts. Further, SHP Buddy is the first of its type to provide an intuitive method for removing non-experimental plots, such as non-experimental “fill” plots at the end of experiments or plots in irrigation wheel tracks. Plot information is easily incorporated by uploading a field book CSV file that contains a column of matching plot numbers. Lastly, plot dimensions can be modified to produce more precise regions of interest.

Conclusions
SHP Buddy substantially reduces the time and increases the accuracy of shapefile generation. This results in reliable shapefiles that improve record keeping and the quality of high-throughput phenotyping data extracted. By working natively in QGIS, SHP Buddy provides an efficient solution to shapefile generation while maintaining a low learning curve.
Functional outcome after Brachytherapy with bi-nuclide (Ru-106/Iodine-125) plaques in large uveal melanomas
Authors: Jabbarli Leyla , Fiorentzis Miltiadis , Rating Philipp , Schmidt Boerge , Biewald Eva , Guberina Nika , Flühs Dirk , Bornfeld Norbert , Sauerwein Wolfgang , Stuschke Martin , Bechrakis Nikolaos E. , Guberina Maja 
Published: February 2025

Abstract

Objective
Preservation of visual acuity remains a challenging issue after globe sparing therapy of large uveal melanoma. The aim of our study was analyzing the functional outcome after brachytherapy with bi-nuclide plaques (BBNP), maintaining prognostic factors for legal blindness (LB).

Methods
We have analyzed all consecutive patients with large uveal melanoma treated with BBNP at our institution between 01/1999 and 12/2020. The post-treatment follow-up data were screened up to 06/2023. Univariate and multivariate Cox regression analysis was performed to identify predictive factors for development of LB following BBNP.

Results
Overall, 570 patients with median age of 65.6 years (interquartile range [IQR]: 54.5–74.0) underwent BBNP. During the median post-treatment follow-up of 30.8 months (IQR: 12.9–57.3), LB was diagnosed in 287 (50.4%) patients. Patients’ age (> 67 years, adjusted hazard ratio [aHR] = 1.58, 95%-confidence interval [CI] = 1.24–2.00, p < 0.0001), tumor thickness (> 8.5 mm, aHR = 1.43, 95%-CI = 1.12–1.82, p = 0.004), VA (> 0.5 LogMAR, aHR = 1.59, 95%-CI = 1.25–2.02, p < 0.0001), and ciliary body involvement (aHR = 0.77, 95%-CI = 0.60–0.97, p = 0.029) were confirmed as independent predictors of LB in the final multivariable Cox regression analysis.

Conclusions
Approximately a half of patients with large uveal melanoma develop LB around 2.5 years after brachytherapy. Further optimization of treatment strategies, including both therapeutic and preventive measures, has the potential to enhance the functional outcome after episcleral plaque therapy for large UMs.
An IgE antibody targeting HER2 identified by clonal selection restricts breast cancer growth via immune-stimulating activities
Authors: Palhares Lais C. G. F. , Grandits Melanie , Stoker Katie , Chauhan Jitesh , Sow Heng Sheng , Fruhwirth Gilbert O. , Tsoka Sophia , Birtley James , Partington Leanne , Wilson Tim , Hardaker Elizabeth , Karagiannis Sophia N. , Bax Heather J. , FitzGerald Kevin 
Published: February 2025

Abstract

Background
Tumor-targeting IgE antibodies have elicited potent tumor-restricting effects by recruiting immune effector mechanisms. However, a dedicated platform for the generation, selection and evaluation of novel IgEs based on target antigen recognition and functional profiles has not been reported.

Methods
By establishing an IgE class antibody therapeutic design platform to allow selection of lead candidates, we generated a panel of IgEs recognising the human epidermal growth factor receptor 2 (HER2), overexpressed in 15–20% of breast cancers. From 1840 phage display-generated variable region sequences panned against HER2, we engineered 30 full length IgE antibodies. We selected three clones based on biophysical properties, reactivity to HER2 + cancer cells, epitope reactivity and Fc-mediated anti-tumor profiles in vitro. Clones with cross-reactivity to rat HER2 were selected to allow functional evaluations in a fully immunocompetent syngeneic HER2 + rat breast cancer model.

Results
IgE antibodies induced degranulation and antibody-dependent cellular cytotoxicity against human and rat HER2-expressing tumor cells in vitro. IgE antibody 26 demonstrated anti-tumor activity in a syngeneic HER2 + rat model, and a human HER2 + breast cancer xenograft model in mice reconstituted with human immune cells. Treatment was associated with enhanced immune cell infiltration and pro-inflammatory immune signatures, and downregulated cancer progression signaling pathways, in the tumor microenvironment.

Conclusions
This study pioneers the design and generation of anti-HER2 IgE lead antibody candidates with immune-stimulating and tumor-restricting effects. The present work may pave the way for antibody engineering therapeutic opportunities for challenging-to-treat HER2-expressing cancers.
Naringenin-loaded nanoparticles modulate HIF-driven oxygen-sensing pathways in lung adenocarcinoma cells
Authors: Ragab Eman M. , El Gamal Doaa M. , Mohamed Tarek M. , Khamis Abeer A. 
Published: February 2025

Abstract

Background
Hypoxia is a common symptom of lung cancer. Proliferation and neovascularization mediated by hypoxia-inducible factors (HIF) influence several adaptations. It has recently been established that naringenin (NAR) and its nanoparticles are chemo-preventive flavonoids in lung cancer.

Aim
Adjust HIF activity by reviving oxygen-sensing enzyme activity while considering possible therapeutic targets.

Method
The bindings of NAR to target proteins were examined using computational modeling techniques. Additionally, NAR nanoparticles (NARNPs) were synthesized and characterized. Normal fibroblast cells and A549 cells were used to determine cytotoxicity. Colorimetric analysis of α-ketoglutarate detection for hydroxylases.

Results
According to molecular modeling, NAR and target proteins have a high affinity. The PHD and FIH activities in A549 are significantly stimulated.

Conclusion
NAR and NARNPs diminish hypoxia in lung cancer by stimulating oxygen-sensing hydroxylases.
Early findings on home delivery of buprenorphine and retention in treatment for opioid use disorder
Authors: C. Lira Marlene , E. Hendy Lauren , Liakas Alisha , Turanchik Laura , Pritchard Clare , Jimes Cynthia , Justin Coffey M. 
Published: February 2025

Abstract
Individuals with opioid use disorder face barriers accessing first-line pharmacotherapy. Home delivery interventions have been shown to improve medication adherence for other chronic diseases, but the relationship between buprenorphine home delivery and opioid use disorder treatment outcomes has not been assessed. We evaluated the association between medication home delivery and retention in treatment in a feasibility study of adults who initiated telemedicine treatment for opioid use disorder and received one or more prescriptions. We described the characteristics of patients and estimated the odds of attending a telemedicine visit three and six months after enrollment as a function of home delivery use using logistic regression. The sample consisted of 337 adults with the following characteristics: mean age 40.8 years (SD 10.1), 51.0% male, and 70.9% commercially insured. In the first 30 days of treatment 6.8% (n = 23) of patients used home delivery. At three months, the percentages of individuals retained among those with and without home delivery were 82.6% and 58.9%, respectively (odds ratio [OR]: 3.31, 95% confidence interval [CI]: 1.10–9.96). At six months, the percentages of individuals retained among those with and without home delivery were 78.6% and 45.5%, respectively (OR: 4.39, 95% CI: 1.19–16.25, n = 203). Although uptake of medication delivery through the pharmacy partner was low within this sample of patients receiving treatment for opioid use disorder, its use was associated with increased retention in care at three and six months. Given the small sample size, low uptake, and limited statistical power, additional research is warranted.
The impact of regular sauerkraut consumption on the human gut microbiota: a crossover intervention trial
Authors: Schropp Nelly , Bauer Alexander , Stanislas Virginie , Huang Kun D. , Lesker Till-Robin , Bielecka Agata Anna , Strowig Till , Michels Karin B. 
Published: February 2025

Abstract

Background
Sauerkraut is a fermented food that has been suspected to have a beneficial impact on the gut microbiome, but scientific evidence is sparse. In this crossover intervention trial with 87 participants (DRKS00027007), we investigated the impact of daily consumption of fresh or pasteurized sauerkraut for 4 weeks on gut microbial composition and the metabolome in a healthy study population.

Results
Using shotgun metagenomic sequencing, we observed changes in single bacterial species following fresh and pasteurized sauerkraut consumption. More pronounced changes were observed in the pasteurized sauerkraut intervention arm. Only pasteurized sauerkraut consumption increased serum short-chain fatty acids (SCFAs).

Conclusions
The gut microbiome of healthy individuals is rather resilient to short-term dietary interventions even though single species might be affected by sauerkraut consumption.
Secondary sclerosing cholangitis: an unusual presentation of leptospirosis
Authors: Aponso Tilan , Wanninayake W. M. D. A. S. , Wijesinghe I. P. , Jayasekara Nethma , Iddamalgoda Waruna , Wanasinghe W. M. M. A. 
Published: February 2025

Abstract
Sclerosing cholangitis is a rare progressive cholestatic disease that is classified as secondary sclerosing cholangitis when it is caused by an identifiable cause. Sclerosing cholangitis has been linked to infections like COVID-19 and parasitic infections like Clonorchis sinensis and Ascaris lumbricoides. However, leptospirosis has not been linked to sclerosing cholangitis in the medical literature. In this article, we report a 37-year-old gentleman who was diagnosed with leptospirosis, worsened by painless cholestasis, while he was improving from leptospirosis. Magnetic resonance cholangiopancreatography revealed multiple short-segment biliary strictures, segmental dilatation, and mural irregularities in both intrahepatic ducts confirming the diagnosis of sclerosing cholangitis. After ruling out other potential causes and considering the initial presentation during a leptospirosis infection, we concluded that leptospirosis caused secondary sclerosing cholangitis. We report this as the first case of secondary sclerosing cholangitis in a leptospirosis patient without renal, respiratory, or cardiac complications, emphasizing the importance of ruling out this cause in a leptospirosis patient with persistent cholestasis.
Unveiling market dynamics: a machine and deep learning approach to Egyptian stock prediction
Authors: Fattoh Ibrahim Eldesouky , El Maghawry Ibrahim Marwa , Mousa Farid Ali 
Published: February 2025

Abstract
Accurate stock price forecasting is essential for making smart investing choices. In the context of the Egyptian stock market, this study examines the predictive capabilities of several machine learning and deep learning models for stock price prediction. Five different datasets with historical stock price information from significant Egyptian companies are used in the study methods such as Random Forest, Linear Regression, LSTM, and Bi-LSTM which were employed and evaluated using performance metrics including Mean Squared Error (MSE), Mean Absolute Error (MAE), and R-Squared. Among these, the Bi-LSTM model consistently delivered the most accurate price forecasts due to its superior ability to capture complex patterns and relationships inherent in stock market data. Additionally, statistical models ARIMA and GARCH were implemented for comparative purposes, but the machine learning and deep learning models outperformed these traditional approaches. This study contributes to a deeper understanding of stock price behavior in the Egyptian market, providing valuable insights for financial analysts and investors.