bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reduced irradiation exposure areas enhanced anti-tumor effect by inducing DNA damage and preserving lymphocytes
Authors: Chen Huiqin , Li Yuan , Shen Qiaofeng , Guo Guanqun , Wang Zhigang , Pan Hanyu , Wu Min , Yan Xueqing , Yang Gen 
Published: December 2024

Abstract
Background
Partial stereotactic body radiation therapy (SBRT) targeting hypoxic regions of large tumors (SBRT-PATHY) has been shown to enhance the efficacy of tumor radiotherapy by harnessing the radiation-induced immune response. This approach suggests that reducing the irradiation target volume not only achieves effective anti-tumor effects but also minimizes damage to surrounding normal tissues. In this study, we evaluated the antitumor efficacy of reduced-tumour-area radiotherapy (RTRT) , and explored the relationship between tumor control and immune preservation and the molecular mechanisms underlying of them.

Methods
In mouse breast cancer models, we compared the anti-tumor effects of RTRT and conventional radiotherapy (CNRT) by assessing tumor growth, metastasis, and survival rates. Additionally, we evaluated the peritumoral tissue damage and the immune microenvironment. The maturation of dendritic cells (DCs) and DNA damage induced by irradiated tumor cells were also assessed in vitro.

Results
In pre-clinical models, both RTRT and CNRT significantly inhibited primary tumor growth when compared to non-irradiated controls, with no significant difference between RTRT and CNRT. However, RTRT significantly extended survival times in mice, and increased the likelihood of inducing abscopal effects, thereby providing potential for better control of distant metastases. Further investigations revealed that the enhanced efficacy of RTRT may be attributed to the preservation of lymphocytes within the peritumoral tissue, as well as reduced damage to the surrounding skin and circulating lymphocytes. In vitro assays demonstrated that RTRT induced DNA damage and dsDNA in tumor cells, activating the cGAS-STING pathway. RTRT also triggered the release of damage-associated molecular patterns (DAMPs), which synergistically amplified the anti-tumor immune response.

Conclusions
Our findings suggested that appropriately narrowing the irradiation target volume effectively killed tumor cells while reducing damage to surrounding tissues, and preserving peritumoral lymphocytes. This approach improved the safety of radiotherapy while maintaining its efficacy in tumor control and provided an opportunity for combining high-dose radiotherapy with immunotherapy.
Internal validation of self-reported case numbers in hospital quality reports: preparing secondary data for health services research
Authors: Ji Limei , Geraedts Max , de Cruppé Werner 
Published: December 2024

Abstract
Background
Health services research often relies on secondary data, necessitating quality checks for completeness, validity, and potential errors before use. Various methods address implausible data, including data elimination, statistical estimation, or value substitution from the same or another dataset. This study presents an internal validation process of a secondary dataset used to investigate hospital compliance with minimum caseload requirements (MCR) in Germany. The secondary data source validated is the German Hospital Quality Reports (GHQR), an official dataset containing structured self-reported data from all hospitals in Germany.

Methods
This study conducted an internal cross-field validation of MCR-related data in GHQR from 2016 to 2021. The validation process checked the validity of reported MCR caseloads, including data availability and consistency, by comparing the stated MCR caseload with further variables in the GHQR. Subsequently, implausible MCR caseload values were corrected using the most plausible values given in the same GHQR. The study also analysed the error sources and used reimbursement-related Diagnosis Related Groups Statistic data to assess the validation outcomes.

Results
The analysis focused on four MCR procedures. 11.8–27.7% of the total MCR caseload values in the GHQR appeared ambiguous, and 7.9–23.7% were corrected. The correction added 0.7–3.7% of cases not previously stated as MCR caseloads and added 1.5–26.1% of hospital sites as MCR performing hospitals not previously stated in the GHQR. The main error source was this non-reporting of MCR caseloads, especially by hospitals with low case numbers. The basic plausibility control implemented by the Federal Joint Committee since 2018 has improved the MCR-related data quality over time.

Conclusions
This study employed a comprehensive approach to dataset internal validation that encompassed: (1) hospital association level data, (2) hospital site level data and (3) medical department level data, (4) report data spanning six years, and (5) logical plausibility checks. To ensure data completeness, we selected the most plausible values without eliminating incomplete or implausible data. For future practice, we recommend a validation process when using GHQR as a data source for MCR-related research. Additionally, an adapted plausibility control could help to improve the quality of MCR documentation.
The joint effects of inflammation and renal function status on in-hospital outcomes in patients with acute ischemic stroke treated with intravenous thrombolysis
Authors: Huang Zhichao , Zhu Xiaoyue , Xu Xiuman , Wang Yi , Zhu Yafang , Chen Dongqin , Cao Yongjun , Zhang Xia 
Published: December 2024

Abstract
Objective
We aimed to determine the predictive value of renal function status [estimating glomerular filtration rate (eGFR)] in conjunction with inflammatory biomarkers [white blood cell(WBC) and C-reactive protein (CRP)] for in-hospital outcomes in acute ischemic stroke (AIS) patients treated with intravenous thrombolysis (IVT).

Methods
We retrospectively screened a total of 409 AIS patients treated with IVT. The study participants were classified into two groups according to post-stroke pneumonia or functional outcome. They were divided into four groups according to the cut-offs of inflammatory biomarkers and eGFR by receiver operating characteristics(ROC) curves for two outcomes of post-stroke pneumonia and functional status: WBC↓/eGFR↑, WBC↓/eGFR↓, WBC↑/eGFR↑, and WBC↑/eGFR↓for post-stroke pneumonia; and CRP↓/eGFR↑, CRP↓/eGFR↓, CRP↑/eGFR↑, and CRP↑/eGFR↓for functional outcome. Logistic regression models were used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) of post-stroke pneumonia or at-discharge functional outcome, using the WBC↓/eGFR↑group or CRP↓/eGFR↑group as the reference. The Net Reclassification Index (NRI) and the Integrated Discrimination Improvement (IDI) were calculated to analyze the combined predictive value.

Results
Compared with patients in WBC↓/eGFR↑group, those in WBC↑/eGFR↑group had increased risk of post-stroke pneumonia (OR 5.15, 95% CI 1.67–15.87) and poor functional outcome (OR 5.95, 95% CI 2.25–15.74). Furthermore, patients in WBC↑/ eGFR↓group had the highest risk of clinical outcomes (all P value for trend < 0.001), the multivariable-adjusted ORs (95% CIs) were 7.04 (2.42–20.46) for post-stroke pneumonia and 8.64 (3.30–22.65) for poor functional outcome. The addition of WBC and eGFR to the basic model significantly improved risk prediction for post-stroke pneumonia (category-free NRI 69.0%, 95% CI 47.3%–90.7%; IDI 5.4%, 95% CI 2.6%–8.3%) and functional outcome (category-free NRI 59.4%, 95% CI 39.2%–79.9%; IDI 5.3%, 95% CI 2.9%–7.8%). Similarly, when we added CRP and eGFR to the basic model with conventional risk factors, the risk discrimination and prediction for post-stroke pneumonia and functional outcome was also significantly improved.

Conclusion
Combining renal function status and inflammatory biomarkers within 4.5 h after onset could better predict in-hospital outcomes of AIS patients with IVT.
A comparison of acellular dermal matrices (ADM) efficacy and complication profile in women undergoing implant-based breast reconstruction: a systematic review and network meta-analysis
Authors: Glynou Sevasti Panagiota , Sousi Sara , Cook Hannah , Zargaran Alexander , Zargaran David , Mosahebi Afshin 
Published: December 2024

Abstract
Introduction
Breast cancer is the leading cause of cancer amongst women in the United Kingdom, with implant-based reconstruction (IBR) using Acellular Dermal Matrices (ADM) gaining popularity for post-mastectomy procedures. This study compares outcomes of different ADMs that are commonly used in women undergoing IBR, this was short and long-term complications.

Methods
A systematic search of MEDLINE, Embase, CENTRAL, and CDSR databases was performed according to the PRISMA guidelines, focusing on women undergoing IBR with FlexHD, AlloDerm, Bovine, or Porcine ADMs. A network meta-analysis (NMA) was also conducted.

Results
A total of 51 studies were captured by the search, of which 27 were included in the network meta-analysis. Alloderm was the most used ADM (54%), followed by Porcine (17%), Bovine (11%), DermAcell (11%), and FlexHD (7%). The mean follow-up was 27.8 months. The complication rates varied. Porcine ADMs had the highest rate of seroma formation (10.3%) and of haematoma formation (2.7%). AlloDerm FD had the highest rate of wound dehiscence (3.1%). Implant failure was highest in AlloDerm FD ADMs (11.8%), followed by Porcine ADMs (11.2%). Infections were most common in Porcine (11.2%) and AlloDerm FD ADMs (11.0%). Capsular contracture was rare across all ADM types, with no significant differences observed. In the NMA, AlloDerm FD showed significantly higher risks of infection, explantation, and wound dehiscence compared to AlloDerm RTU.

Conclusion
The overall complication profiles of ADMs used in IBR are similar, except for the higher risks associated with AlloDerm FD compared to RTU. These findings suggest that the choice of ADM may not significantly impact overall outcomes, except in specific cases like AlloDerm FD. Further high-quality, long-term, double-arm studies are necessary to confirm comparative profile of specific ADM types and to account for potential confounding variables through multivariable regression analysis.
Cognitive impairment at older ages among 8000 men and women living in Mexico City: a cross-sectional analyses of a prospective study
Authors: González-Carballo Carlos , Kuri-Morales Pablo , Chiquete Erwin , Rojas-Russell Mario , Santacruz-Benitez Rogelio , Ramirez-Reyes Raúl , Garcilazo-Ávila Adrián , Berumen Jaime , Trichia Eirini , Friedrichs Louisa Gnatiuc , Orellana Paulina , Ochoa-Rosales Carolina , O’Donovan Gary , Emberson Jonathan R , Tapia-Conyer Roberto , Aguilar-Ramirez Diego , Alegre-Díaz Jesus 
Published: December 2024

Abstract
Background
There is limited population-based evidence on the prevalence of cognitive impairment in Mexico, a country with a rapidly aging population and where key risk factors, such as diabetes and obesity, are common. This study describes the distribution of cognitive impairment in adults from Mexico City.

Methods
This cross-sectional population-based study included participants from the Mexico City Prospective Study which recruited 150,000 adults aged ≥ 35 years in 1998–2004. In 2015–2019 about 10,000 survivors were resurveyed with identical information from the original survey and additional assessments including a cognitive assessment. The main analyses included those aged 50–89 years with complete cognitive assessment and covariate data at resurvey. Cognitive impairment was defined by a score ≤ 24 on the Mini Mental State Examination (MMSE). The distribution of MMSE scores and cognitive impairment by age, sex, and major disease risk factors (diabetes, hypertension, and adiposity) was analyzed among those with complete MMSE data and some degree of self-reported formal education.

Results
Of the 9,288 participants aged 50–89 years at the 2015–2019 resurvey with complete data, 8,197 reported having at least some years of formal education. Among these (mean age 66 years; 31% men), their mean MMSE score was 26.2 (SD 3.6) points, 1,941 (24%) had cognitive impairment, their mean body-mass index (BMI) was 28.6 (SD 5.5) kg/m2, 3,008 (37%) had hypertension and 2,467 (30%) had diabetes. The sex- and district-standardised prevalence of cognitive impairment increased strongly with age, from 10% in those 50–59 years to 55% in those aged 80–89. At any given age, the prevalence of cognitive impairment was higher in women than in men. After accounting for the effects of age, sex, and district there was little difference in the prevalence of cognitive impairment between participants with or without diabetes, hypertension, overweight or obesity (BMI ≥ 25 km/m2), or high levels of fat mass.

Conclusions
In this population of adults aged 50–89 years from Mexico City, the prevalence of cognitive impairment was high, particularly among women. The extent to which cognitive impairment relates to health outcomes in this population needs to be investigated.
A machine learning model to predict the risk factors causing feelings of burnout and emotional exhaustion amongst nursing staff in South Africa
Authors: Van Zyl-Cillié Maria Magdalena , Bührmann Jacoba H. , Blignaut Alwiena J. , Demirtas Derya , Coetzee Siedine K. 
Published: December 2024

Abstract
Background
The demand for quality healthcare is rising worldwide, and nurses in South Africa are under pressure to provide care with limited resources. This demanding work environment leads to burnout and exhaustion among nurses. Understanding the specific factors leading to these issues is critical for adequately supporting nurses and informing policymakers. Currently, little is known about the unique factors associated with burnout and emotional exhaustion among nurses in South Africa. Furthermore, whether these factors can be predicted using demographic data alone is unclear. Machine learning has recently been proven to solve complex problems and accurately predict outcomes in medical settings. In this study, supervised machine learning models were developed to identify the factors that most strongly predict nurses reporting feelings of burnout and experiencing emotional exhaustion.

Methods
The PyCaret 3.3 package was used to develop classification machine learning models on 1165 collected survey responses from nurses across South Africa in medical-surgical units. The models were evaluated on their accuracy score, Area Under the Curve (AUC) score and confusion matrix performance. Additionally, the accuracy score of models using demographic data alone was compared to the full survey data models. The features with the highest predictive power were extracted from both the full survey data and demographic data models for comparison. Descriptive statistical analysis was used to analyse survey data according to the highest predictive factors.

Results
The gradient booster classifier (GBC) model had the highest accuracy score for predicting both self-reported feelings of burnout (75.8%) and emotional exhaustion (76.8%) from full survey data. For demographic data alone, the accuracy score was 60.4% and 68.5%, respectively, for predicting self-reported feelings of burnout and emotional exhaustion. Fatigue was the factor with the highest predictive power for self-reported feelings of burnout and emotional exhaustion. Nursing staff’s confidence in management was the second highest predictor for feelings of burnout whereas management who listens to employees was the second highest predictor for emotional exhaustion.

Conclusions
Supervised machine learning models can accurately predict self-reported feelings of burnout or emotional exhaustion among nurses in South Africa from full survey data but not from demographic data alone. The models identified fatigue rating, confidence in management and management who listens to employees as the most important factors to address to prevent these issues among nurses in South Africa.
PharmRL: pharmacophore elucidation with deep geometric reinforcement learning
Authors: Aggarwal Rishal , R. Koes David 
Published: December 2024

Abstract
Background
Molecular interactions between proteins and their ligands are important for drug design. A pharmacophore consists of favorable molecular interactions in a protein binding site and can be utilized for virtual screening. Pharmacophores are easiest to identify from co-crystal structures of a bound protein-ligand complex. However, designing a pharmacophore in the absence of a ligand is a much harder task.

Results
In this work, we develop a deep learning method that can identify pharmacophores in the absence of a ligand. Specifically, we train a CNN model to identify potential favorable interactions in the binding site, and develop a deep geometric Q-learning algorithm that attempts to select an optimal subset of these interaction points to form a pharmacophore. With this algorithm, we show better prospective virtual screening performance, in terms of F1 scores, on the DUD-E dataset than random selection of ligand-identified features from co-crystal structures. We also conduct experiments on the LIT-PCBA dataset and show that it provides efficient solutions for identifying active molecules. Finally, we test our method by screening the COVID moonshot dataset and show that it would be effective in identifying prospective lead molecules even in the absence of fragment screening experiments.

Conclusions
PharmRL addresses the need for automated methods in pharmacophore design, particularly in cases where a cognate ligand is unavailable. Experimental results demonstrate that PharmRL generates functional pharmacophores. Additionally, we provide a Google Colab notebook to facilitate the use of this method.
Health checks for autistic adults: study protocol for a cluster randomised controlled trial
Authors: Parr Jeremy R. , Taylor Helen , Wilson Colin , Scarlett Clare , Al-Asmori Sarah , Buckley Carole , Cooper Sally-Ann , Fernandez-Garcia Cristina , Finch Tracy , Lees Rhianna , Lennox Nicholas , Merrick Hannah , Moss Sebastian , Nicolaidis Christina , Osbourne Malcolm , Raymaker Dora M. , Robinson Tomos , Urbanowicz Anna , Wason James M. S. , Ingham Barry 
Published: December 2024

Abstract
Background
Autistic people commonly have physical and mental health conditions. They also frequently experience barriers to accessing healthcare, contributing to problems identifying and treating health conditions. These factors may lead to increased and earlier morbidity and lower average life expectancy for autistic people. Health checks specifically designed for autistic people, incorporating adjustments to healthcare, may help to overcome these barriers and reduce health inequalities. This trial aims to investigate the clinical and cost-effectiveness of a primary care health check for autistic adults and explore factors related to implementation such as acceptability and feasibility of delivery. The trial is co-designed and delivered by health professionals, autistic people, carers and supporters, and researchers.

Methods
This is a clinical and cost-effectiveness, cluster randomised controlled trial of a primary care health check for autistic adults. Primary care practices will be randomised into one of two groups (intervention or control). Two hundred autistic adults (aged 18 years and over) who provide baseline data will be recruited via participating practices. Data will be collected through quantitative and qualitative methods. The primary outcome will be the incidence of new health needs/conditions detected and met at 9 months (data gathered from participant’s GP records). Secondary outcomes will include the following: cost-effectiveness, measured as incremental cost per quality-adjusted life year gained over 9 months; the extent of health monitoring and health promotion needs met at 9 months; the incidence of social care needs identified at 9 months; changes in participant or carer general health; changes in quality of life; primary and secondary health and social care resource usage and costs. A qualitative study will explore views about the acceptability of the health check, its utility and future use.

Discussion
This study will examine the effectiveness and cost-effectiveness of a primary care health check for autistic adults in identifying new health conditions and needs. If the intervention is effective, it would provide strong evidence for implementation into routine healthcare, therefore enabling earlier health condition diagnosis and opportunities for treatment, reducing the health inequalities experienced by autistic people.

Trial registration
ISRCTN, retrospectively registered on 20 July 2023. https://www.isrctn.com/ISRCTN30156776 (ISRCTN registration number: 30156776).
Comparison of baseline global gene expression profiles of prostate cancer cell lines LNCaP and DU145
Authors: Ahmed Khalid , Omarova Zhannur , Sheikh Alisalman , Abuova Gulzhan , Ghias Kulsoom , Abidi Syed Hani 
Published: December 2024

Abstract
Introduction
DU145 and LNCaP are classic prostate cancer cell lines. Characterizing their baseline transcriptomics profiles (without any intervention) can offer insights into baseline genetic features and oncogenic pathways that should be considered while interpreting findings after various experimental interventions such as exogenous gene transfection or drug treatment.

Methods
LNCaP and DU145 cell lines were cultured under normal conditions, followed by RNA extraction, cDNA conversion, library preparation, and RNA sequencing using the Illumina NovaSeq platform. The sequences were analyzed to identify differentially expressed genes (DEGs) and for gene ontology (GO) and pathway enrichment.

Results
A total of 3916 and 2301 genes were found to be differentially upregulated and downregulated between LNCaP and DU145 cell lines, respectively. The GO and pathway analysis of up-regulated DEGs indicated significant enrichment of genes involved in extracellular matrix organization and cell-substrate adhesion, while down-regulated genes are involved in epithelial cell migration, cell death regulation, and cell proliferation.

Conclusion
The results showed significant differences in baseline gene expression and cellular pathways that may account for the varying metastatic potentials between LNCaP and DU145 cell lines, which should be considered when interpreting findings after experimental interventions.
Effect of Sugar Cane Bagasse Ash Incorporated as Viscosity Modifying Agent on Fresh, Microstructure and Mechanical Properties of Self-Compacting Concrete
Authors: Amjad Usman , Sarir Muhammad , Khan Diyar , Haq Inzimam Ul , Khawaja Muhammad Wajahat Ali , Mahmood Khalid 
Published: December 2024

AbstractThe global construction industry faces a crucial challenge reconciling economic growth with environmental sustainability, notably due to the significant environmental impact of cement production, particularly in countries like Pakistan. As the demand for cement grows, so does the carbon footprint and environmental degradation, necessitating the exploration of sustainable alternatives like sugarcane bagasse ash (SBA), a byproduct of sugarcane processing, to mitigate these issues while also addressing rising costs in concrete production. Embracing SBA offers a promising avenue to alleviate environmental concerns and enhance the sustainability of the construction sector. This study investigated the SBA properties and effectiveness as a viscosity modifying agent (VMA) in self-compacting concrete (SCC), examining varying SBA content effects on fresh and hardened SCC properties. The hydration and microstructure properties were evaluated by using X-ray diffraction (XRD), scanning electron microscopy (SEM), and mercury intrusion porosimetry (MIP) to investigate SBA-based SCC. The results indicate that SBA has the potential to enhance mechanical and microstructural properties by possibly increasing the formation of Calcium Silicate Hydrate (CSH) gel. Adding 5% SBA demonstrated favorable fresh properties while incorporating up to 15% SBA showed improvements in compressive strength. Overall, adding SBA to cement manufacturing during clinkerization can reduce environmental pollution and lower production costs.