bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recommending Drug Combinations Using Reinforcement Learning targeting Genes/proteins associated with Heterozygous Familial Hypercholesterolemia: A comprehensive Systematic Review and Net-work Meta-analysis
Authors: Kiaei Ali A. , Boush Mahnaz , Abadijou Sadegh , Momeni Saeb , Safaei Danial , Bahadori Reza , Salari Nader , Mohammadi Masoud 
Published: February 2023

Abstract
Background:
Familial Hypercholesterolemia (FH) is a genetic disorder in lipoprotein metabolism caused by mutations that increase LDL and total cholesterol levels. High LDL and cholesterol levels increase atherosclerosis risk. FH mutations impact the LDL receptor (LDLR) gene, apolipoprotein B, and PCSK9. About 20% of FH cases have a polygenic basis that affects LDL levels. We decided to conduct a systematic review of the available research in this field to provide a thorough genes/proteins network meta-analysis on the impact of drug combinations on the management of heterozygous Familial Hypercholesterolemia (HeFH). This paper reviews and analyzes the literature on the effects of medication combinations on HeFH management. This study investigates articles that analyzed the management and adjuvants of HeFH to recommend forceful drug combinations.
Methods:
This systematic review and network meta-analysis analyzed the Science Direct, Embase, Scopus, PubMed, Web of Science (ISI), and Google Scholar databases without a lower time limit and up to July 2022. The current study consists of three fundamental stages. Firstly, drug combinations are recommended by reinforcement learning. In the second stage, we used a systematic review to analyze RL's outcomes in diverse populations (with a variety of ages, sex, etc.). Natural Language Processing (NLP) employs context to search these articles. We contrasted manual and NLP-based searches and discovered that NLP could find articles based on MeSH, not simply words. In stage three, we analyze RL outcomes using network meta-analysis.
Results:
This study uses the RAIN method to investigate the most effective medication combination for managing Heterozygous Familial Hypercholesterolemia (HeFH). Results from the method indicate that the best-recommended scenario is 2.7 times more efficient than the prescription of Ezetimibe as the initial scenario.
Conclusion:
Our systematic review and network meta-analysis review indicate that a drug combination of Ezetimibe, Pravastatin, and Simvastatin is highly effective. However, additional high-quality clinical trials are required to determine the efficacy and safety of other treatments.
Comparison of a Virtual Reality-Based Visual Field Device (Oculera) with Humphrey Visual Field Analyzer in Glaucoma Patients and Healthy Individuals
Authors: Koylu Mehmet , Yilmaz Alper , Yilmaz Hayati , Ceylan Osman Melih , Çakır Bagım , Bayer Atilla 
Published: February 2023

Abstract
Background/objectives: To examine the correlation between Humphrey visual field analyzer and an automated virtual reality perimetry test (Oculera visual field analyzer) in glaucoma patients and healthy individuals.
Methods: This prospective, single-center study was conducted on 93 eyes of 93 patients, 55 of whom were glaucoma patients (glaucoma group) and 38 healthy subjects (normal group). HFA II (24-2, Swedish Interactive Threshold Algorithm) and Oculera (24-2, Oculera Interactive) tests were applied to all participants. Mean deviation (MD) values ​​of both devices were analyzed. The correlation between the two devices was assessed with statistical analyses on MD. The Bland-Altman plot was used to display the level of agreement between the two devices.
Results: The MDs were -6.36 dB (-31.8 to 2.27) for HFA II MD and -5.80 dB (-29.1 to 2.2) for Oculera MD. The difference between MDs of Oculera and HFA II was -0.56 dB. Dependent t-test showed a statistically significant difference between Oculera and HFA II (mean -0.55; 95% CI -0.885 to -0.229; p < 0.001). Also, the correlation of MDs was quite strong (r = 0.995 and p < 0.001). In the subgroup analysis, comparable results were observed with both devices in all three groups among mild, moderate, and advanced glaucoma patients.
Conclusions: A good correlation was found between standard automatic perimetry and Oculera. Oculera MD results were comparable to HFA II MD results. Oculera may be a useful alternative in clinical practice for functional testing in glaucoma patients. It also offers convenience as it is portable and can be applied at home.
A clinical study to assess the efficacy and safety of MP-AzeFlu (Azelastine Hydrochloride and Fluticasone Propionate) nasal spray in comparison to commercially available nasal sprays in Chinese volunteers with allergic rhinitis
Authors: Zhou Bing , Cheng Lei , Pan Jing , Wang Huizhong , Jin Yongde , Zhao Changqing , Lin Peng , Tan Guolin , Fang Hongyan , Zhang Hua , Zhou Huifang , Dong Yaowu , Kuhl Hans Christian , R Rajesh Kumar , Nguyen Duc Tung 
Published: February 2023

Abstract
Objective: The objective of the present study was to evaluate the efficacy and safety of MP-AzeFlu nasal spray in comparison to commercially available azelastine and fluticasone sprays in Chinese patients with moderate-to-severe allergic rhinitis (AR).
Methods: This was a multicenter, randomized, double-blind, active controlled prospective clinical study in adult and adolescent patients with AR, who had moderate-to-severe symptoms. The primary efficacy endpoint was the change from baseline in combined 12-hour reflective total nasal symptom score (rTNSS) (Morning [AM] + afternoon [PM]). The safety profile of the study medications was assessed through the recording, reporting, and analysis of baseline medical conditions, adverse events (AEs), vital signs, and focused nasal examination. 300 patients per treatment group were randomized which led to a total sample size estimation of 900 patients.
Results: MP-AzeFlu group showed significantly higher symptom reduction for the entire 2-week treatment period in rTNSS when compared with the AZE group (LS mean difference: -1.96; 95% CI: −2.53, −1.39; p < 0.0001), or the FLU group (LS mean difference: -0.98; 95% CI: −1.55, −0.41; p = 0.0007). The results of Adult RQLQ showed improvement in QoL in all treatment groups. Except for dysgeusia (bitter taste) that was reported by more patients (13 [4.3%]) in the MP-AzeFlu group, the incidence of all other TEAEs in the MP-AzeFlu group was comparable or even lower than in other treatment groups.
Conclusion: MP-AzeFlu, when administered as 1 spray per nostril twice daily for 14 days, alleviated AR symptoms in Chinese patients with moderate-to-severe AR.
Trial registration: Clinicaltrials.gov; NCT03599791, Registered June 29,2018, retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03599791
What are the characteristics of a resilient healthcare system: A Scoping Review
Authors: Emami Seyedeh Gelareh , Lorenzoni Valentina , Pirri Salvatore , Turchetti Giuseppe 
Published: February 2023

Abstract

Background
System resilience has long been studied, and the term is currently being used in various fields. A series of technical failures in dealing with significant health shocks, most notably Ebola in west Africa and the COVID-19 pandemic, prompted health policymakers to focus more on the context of resilience in healthcare systems.
Methods
To identify characteristics of Health Care System Resilience, a scoping literature review was conducted using papers published on PubMed, ScienceDirect, Web of Science, and Scopus between 01/01/2000 and 01/04/2021.
Results
A total of 983 relevant publication was identified. Following the screening process, 47 articles met the inclusion criteria. We summarized and classified the resulting dimensions based on six building blocks according to the World Health Organization (WHO) classification and one additional building block we defined.
Conclusion
Currently, most healthcare systems use non-systematic approaches to address resilience issues. According to our findings: Comprehensive characteristics of health system resilience could aid in developing a systematic approach to implementing a reliable strategy to maintain resilience.
Adaptive fuzzy inference system in modeling the alkaline pre-treatment (NaOH) of elephant grass
Authors: Godinho Emmanuel Zullo , Caneppele Fernando de Lima , Siqueira Jair Antonio Cruz , Filho Luís Roberto Almeida Gabriel , Prates Glaucia Aparecida , Hasan Salah Din Mahmud 
Published: February 2023

Abstract
In order to increase its efficiency in the bioethanol production process, the biomass needs to undergo a pre-treatment, which can greatly burden the biochemical process. For this reason, industries are using some mathematical models that optimize internal processes, such as fuzzylogic, as it uses linguistic values ​​instead of numerical ones, which provides the addition of uncertainty to the problem, better understanding by non-specialists, answers faster and lower computational costs. Given the above, the objective of this work was to optimize the independent variables in the alkaline pre-treatment with NaOH in elephant grass to quantify the percentage of cellulose and lignin using fuzzylogic. For the input values ​​of this system, the variables of NaOH concentration and temperature were used, and for the outputs, the percentages of cellulose and lignin. The interpretation of the use of fuzzy logic in this experiment using real laboratory data, managed to optimize the best concentration of NaOH and the best temperature in an alkaline pre-treatment with NaOH to quantify cellulose and lignin, concentrations between 1.15 to 2 .15%, with temperatures between 100.0 to 102.5°C for the highest exposure of cellulose and 0.0 to 1.15% for concentrations and temperatures between 85.5 to 91.5°C for delignification. It was observed that the concentration significantly affects the result of greater exposure of cellulose and biomass delignification in the evaluated parameters, so the mathematical model proved to be efficient for this evaluation.
Serial prophylactic exchange blood transfusion in pregnant women with sickle cell disease (TAPS-2): statistical and qualitative analysis plan for a randomised controlled feasibility trial
Authors: Seed Paul , Brien Sarah , Oakley Laura , Robinson Vicky , Sharif Joseph , Thompson Hilary , Joseph Jeannine , Oteng-Ntim Eugene 
Published: February 2023

Abstract
Background: There are significant knowledge gaps regarding the effectiveness of serial prophylactic exchange blood transfusion (SPEBT) for pregnant women with sickle cell disease (SCD). The protocol for the randomised feasibility trial assessing SPEBT versus usual care in women with SCD (TAPS2 trial) has previously been published. This publication outlines the statistical and qualitative analysis plan for the study.
Methods and design: TAPS2 is a randomised two-arm phase 2 feasibility trial with a nested qualitative study and health economic evaluation. Up to 50 pregnant women with SCD and a singleton pregnancy will be recruited and individually randomised to either SPEBT approximately every 6-10 weeks until delivery (intervention arm) or to usual care (control arm). Information will be collected on a range of feasibility and clinical outcomes.
Results: A summary of the overall study design and qualitative component is presented, along with key updates to the previously published study protocol. The plan for summarising feasibility and outcome data is described, and a set of dummy tables are provided. Further details of the nested qualitative study are provided, alongside proposed methods of analysis.
Conclusion: The publication of this analysis plan is designed to aid transparency and to reduce the potential for reporting bias.
Trial registration: NIH registry (www.clinicaltrials.gov), registration number NCT03975894 (registered 05/06/19); ISRCTN (www.isrctn.com), registration number ISRCTN52684446 (retrospectively registered 02/08/19).
Machine learning approaches for ECG-based models: discrimination and calibration for atrial fibrillation prediction
Authors: Baj Giovanni , Gandin Ilaria , Scagnetto Arjuna , Bortolussi Luca , Cappelletto Chiara , Lenarda Andrea Di , Barbati Giulia 
Published: February 2023

Abstract
Background
Machine learning (ML) methods to build prediction models starting from electrocardiogram (ECG) signals are an emerging research field. The aim of the present study is to investigate the performances of two ML approaches based on ECGs for the prediction of new-onset atrial fibrillation (AF), in terms of discrimination, calibration and sample size dependence.
Methods
We trained two models to predict new-onset AF: a convolutional neural network (CNN), that takes as input the raw ECG signals, and an eXtreme Gradient Boosting model (XGB), that uses the signal’s extracted features. A penalized logistic regression model (LR) was used as a benchmark. Discrimination was evaluated with the area under the ROC curve, while calibration with the integrated calibration index. We investigated the dependence of models’ performances on the sample size and on class imbalance corrections introduced with random under-sampling.
Results
CNN's discrimination was the most affected by the sample size, outperforming XGB and LR only above a certain threshold. Calibration showed only a small dependence on the sample size for all the models considered.
Balancing the training set with random undersampling did not improve discrimination in any of the models. Instead, the main effect of imbalance corrections was to worsen the models’ calibration.
The sample size emerged as a fundamental point for developing the CNN model, especially in terms of discrimination. The effect of the sample size on the other two models was weaker. Imbalance corrections led to poorly calibrated models, for all the approaches considered, reducing the clinical utility of the models.
Conclusions
Our results suggest that the choice of approach in the analysis of ECG should be based on the amount of data available, preferring more standard models for small datasets. Moreover, imbalance correction methods should be avoided when developing clinical prediction models, where calibration is crucial.
Congenital anomalies in offspring exposed to gestational diabetes: A register-based cohort study
Authors: Kinnunen Jenni , Nikkinen Hilkka , Keikkala Elina , Mustaniemi Sanna , Gissler Mika , Laivuori Hannele , Eriksson Johan G. , Kaaja Risto , Pouta Anneli , Kajantie Eero , Vääräsmäki Marja 
Published: February 2023

Abstract
Background: Gestational diabetes mellitus (GDM) is a common pregnancy-related disorder and a well-known risk factor for adverse pregnancy outcomes. There are conflicting findings on the association of GDM with the risk of congenital anomalies (CAs) in offspring. In this study, we aimed to determine study whether maternal GDM is associated with an increased risk of major CAs in offspring.
Methods: This Finnish Gestational Diabetes (FinnGeDi) register-based study included 6,597 women with singleton pregnancies and a diagnosis of GDM and 51,981 singleton controls with no diabetes identified from the Finnish Medical Birth Register (MBR) in 2009. Data from MBR were combined in this study with the Register of Congenital Malformations, which includes the data of CAs. We used logistic regression to calculate odds ratios (OR) for CAs, together with their 95% confidence intervals (CIs), adjusting for maternal age, parity, pre-pregnancy body mass index (BMI), and maternal smoking status.
Results: The risk of major CAs was higher in the GDM-exposed (n = 336, 5.1%) than in the non-exposed group (n = 2,269, 4.4%) (OR: 1.18, 95% CI: 1.05-1.33, p = 0.005). The adjusted OR (aOR) was 1.13 (95% CI: 1.00-1.29, p = 0.058). There was a higher overall prevalence of CAs, particularly chromosomal abnormalities, in the GDM-exposed group (OR: 2.49, 95% Cl: 1.69-3.66, p < 0.001). The aOR was 1.92 (95% Cl: 1.24-2.98, p = 0.004).
Conclusions: Offspring exposed to GDM have a higher prevalence of major CAs. Of note, risk factors other than GDM, such as older maternal age and a higher pre-pregnancy BMI, diminished the between group differences in the prevalence of major CAs. Nevertheless, our findings suggest that offspring exposed to maternal GDM are more likely to be diagnosed with a chromosomal abnormality, independent of maternal age, parity, pre-pregnancy BMI, and smoking.
Preparation and identification of a novel monoclonal antibody against African swine fever virus p15 protein
Authors: He Jian , Zhang Teng , Luo Mingzhan , Yao Jiale , Zhang Mengyang , Hu Xiaomin , Liu Yangkun , Yao Lunguang 
Published: February 2023

Abstract
Background

African swine fever (ASF) is a highly lethal infectious disease caused by the African swine fever virus (ASFV). Due to the lack of effective vaccines and antiviral drugs was available, slaughter of infected and exposed pigs was the currently prevention and control measures. Therefore, early diagnosis is crucial for the prevention and control of ASFV, and the p15 protein is crucial for the maturation of ASFV particles. In this study, four novel anti-ASFV p15 protein monoclonal antibodies were developed, and two conserved epitopes were reported for the first time, which laid the foundation for the rapid diagnosis of ASFV.

Results

Four monoclonal antibodies (3C, 4B, 5D and 8F) were prepared by hybridoma technology, all of which could specifically recognize exogenously expressed p15 protein. Furthermore, this epitope was originally mapped by six overlapping, truncated p15 proteins. The results showed that the epitopes recognized by 3C, 5D and 8F were located at P49-N65, which were highly conserved among genotypes I, II, VII, IX, X, and XX. In addition, the antigenic epitopes were initially mapped by six overlapping p15 truncated proteins. Results showed epitopes recognized by 3C, 5D and 8F located in P49-N65, which was highly conserved in genotypes I, II, VII, IX, X, and XX. In contrast, 4B identified an epitope located at K105-R132, which is conserved only in genotypes I, II, andXX ASFV.

Conclusions

These findings contribute to further understanding of the protein function of p15 and provide potential support for the development of diagnostic tools for ASFV.
Evaluation of clinical effects of a multidisciplinary-collaborated cancer support team for gastrointestinal cancer chemotherapy: prospective observational study protocol of M-CAST study
Authors: Iimura Yohei , Nakazawa Mitsuko , Tsuru Yukari , Togashi Hitomi , Honda Tomoe , Baba Keisuke , Ishibashi Masaaki , Sasuga Chieko , Furukawa Naoki , Sato Tomoko , Matsubara Yasuo , Kamisato Ayako , Yoshii Eiko , Kuroda Seiichiro , Boku Narikazu 
Published: February 2023

Abstract
Background: Although the multidisciplinary-collaborated team approach in cancer treatment has recently become popular, prospectively evaluated evidence is limited. We started a multidisciplinary-collaborated cancer support team (MCST) to facilitate cooperation across multidisciplinary medical staff in our hospital and established clinical evidence of supportive care. This study aimed to prospectively evaluate the clinical activity and effect of MCST in patients with gastrointestinal cancer receiving chemotherapy.
Methods: This is a single-center, single-arm, observational study. Patients with gastrointestinal cancer scheduled to receive chemotherapy are enrolled and supported by the MCST. The primary endpoints are the number of interventions by medical staff and the number of patients who showed improvement in side effects. The secondary endpoints are the severity of side effects, medical expenses, number of consultations, the acceptance rate of prescription recommendations, adjuvant chemotherapy completion rates, dose intensity, and time required for co-medical intervention. In addition, medical staff and attending physicians evaluate all adverse events.
Discussion: This study is expected to contribute to establishing new cancer-supportive care teams for patients with gastrointestinal cancer receiving chemotherapy and those with cancer receiving chemotherapy.
Trial Registration:
This trial was registered in the Japan Registry of Clinical Trials (jRCT) as jRCT1030220495.
Registered November 29, 2022, https://jrct.niph.go.jp/search
Protocol version
V.1.0, October 11, 2022.
All-photonic one-way quantum repeaters
Authors: Shapourian Hassan , Niu Daoheng , Zhang Yuxuan , Shabani Alireza 
Published: February 2023

Abstract
Quantum repeater is the key technology enabler for long-distance quantum communication. To date, most of the existing quantum repeater protocols are designed based on specific quantum codes or graph states. In this paper, we propose a general framework for all-photonic one-way quantum repeaters based on the measurement-based error correction, which can be adapted to any Calderbank-Shor-Steane code including the recently discovered quantum low density parity check (QLDPC) codes. We present a novel decoding scheme, where the error correction process is carried out at the destination based on the accumulated data from the measurements made across the network. This procedure not only outperforms the conventional protocols with independent repeaters but also simplifies the local quantum operations at repeaters. As an example, we numerically show that the [[48,6,8]] generalized bicycle code (as a small but efficient QLDPC code) has an equally good performance while reducing the resources by at least an order of magnitude.
Essential role of momentum-forbidden dark exciton in the energy transfer responses of monolayer transition-metal-dichalcogenides
Authors: Cheng Shun-Jen , Lin Jhen-Dong , Lo Ping-Yuan , Peng Guan-Hao , Li Wei-Hua , Huang Shiang-Yu , Chen Guang-Yin 
Published: February 2023

Abstract
We present a theoretical investigation of exciton-mediated Förster resonant energy transfers (FRET’s) from photoexcited quantum dots (QD’s) to transition-metal-dichalcogenide monolayers (TMD-ML’s), implemented by the quantum theory of FRET on the base of first-principles-calculated exciton fine structures. With the enhanced electron-hole Coulomb interactions, atomically thin TMD-ML’s are shown to serve as an exceptional platform for FRET that are mediated purely by excitons and take full advantage of the superior excitonic properties. Remarkably, the energy-transfer responses of atomically thin TMD-ML’s are shown to be dictated by the momentum-forbidden dark excitons rather than the commonly recognized bright ones. Specifically, the longitudinal dark exciton states following the exchange-driven light-like linear band dispersion play a key role in grading up the efficiency and robustness of FRET of TMDML against the inhomogeneity of QD-donor ensembles. With the essential involvement of dark exciton, the FRET responses of TMD-ML’s no longer follow the distance power law as classically predicted and, notably, cannot manifest the dimensionality of the donor-acceptor system.