bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of fast release tablet of talinolol using fourth generation carrier of solid dispersion technique
Authors: Atneriya Umesh K , Solanki Dharmendra , Tikariya Komal , Gawshinde Arpit 
Published: July 2023

Talinolol is a beta1-selective adreno receptor antagonist well known for its Cardio protective and antihypertensive activity. Talinolol is a beta blocker. In biopharmaceutical classification system the drugs which come under class II are characterized by more membrane permeability, less dissolution rate. Talinolol is a poor aqueous solubility drug leads to poor bioavailability. So, the aimed of this study was to develop immediate release tablet of talinolol by solid dispersions technique using poloxamer 407 as a carrier. Poloxamer 407 is a hydrophilic synthetic block copolymer widely used as a solubility enhancer. Basically there are three methods used for solid dispersion. Melting or fusion method solvent evaporation method. Melting solvent method. Solvent Evaporation Method In this method a suitable solvent is selected which can capable of solubilizing both drug and hydrophilic carrier. The solvent evaporation technique is one of the most commonly used methods to prepare polymeric nanoparticles, more specifically drug-loaded polymeric systems, for pharmaceutical formulations. The prepared solid dispersions were evaluated for production yield percent, drug content, solubility, FTIR, and DSC study analysis. The prepared formulation of Talinolol with P407 in the ratio of 1:5 gave highest dissolution rate of 75.28% at 30min.So it can be concluded that the combination of solid dispersion technology as well as using superdisintergrants an encouraging and effective technique to prepare efficient fast dissolving tablets of Talinolol.The outcome of this investigation presents poloxamer 407 solid dispersion mediated fast dissolving tablets successfully resolve problem of slow rate of dissolution of talinolol.
The current status of Group B Streptococcus infection in the reproductive tract of late-pregnancy women and its impact on pregnancy outcomes
Authors: Ma Hui , Xu JingWen , Zhang YanHong , Zhang RenYan , Wu Jie 
Published: July 2023

Abstract

Objective
Analyze Group B Streptococcus (GBS) infection in late-pregnancy pregnant women in Shanghai, the risk factors of GBS infection, and its impact on pregnancy outcomes, providing guidance for early prevention and treatment in clinical practice.
Methods
We selected 12132 late-pregnancy pregnant women admitted from January 2022 to December 2022 as the research subjects. Based on the GBS test results of reproductive tract secretion samples from pregnant women, 210 cases of GBS positive pregnant women were randomly selected as the observation group, and 200 cases of GBS negative pregnant women were selected as the control group. The risk factors of infection and the impact on pregnancy outcomes were compared between the two groups.
Results
The GBS colonization rate of pregnant women in this study was 6.52%;The incidence of Vaginal delivery and Neonatal infection in GBS positive group was significantly higher than that in GBS negative group(P＜0.05); With Neonatal infection as the dependent variable, and the GBS infection, Vaginal delivery and GDM of the elderly and women in late pregnancy as independent variables, the results showed that GBS infection of women in late pregnancy was an independent risk factor for Neonatal infection.
Conclusion
Clinical practice should attach great importance to GBS infection in late pregnancy, strengthen GBS screening in late pregnancy, and actively implement the strategy of intrapartum antibiotic intervention (IAP), which is of great significance in reducing the vertical infection rate of maternal and infant GBS and improving the quality of newborn birth.
Data-Driven Earthquake Multi-Impact Modelling: A Comparison of Models
Authors: Patten Hamish William , Loake Max Anderson , Steinsaltz David 
Published: July 2023

Abstract
A broad range of supervised Machine Learning and parametric statistical, geospatial and non-geospatial models are applied to model both aggregated observed impact estimate count data and satellite image-derived geo-located building damage labelled data, via regression- and classification-based models, respectively. For the former, models are ranked via predictive performance of mortality, population displacement, building damage and building destruction for 161 earthquakes in 61 countries. For the latter, models were ranked via classification performance (damaged/unaffected) of 369,813 geo-located buildings for 26 earthquakes in 15 countries. k-fold, 3-repeat cross validation is utilised to ensure out-of-sample predictive performance. Feature importance on several variables used as proxies for disaster-risk vulnerability indicates covariate utility. The 2023 Türkiye-Syria earthquakes event is shown to be unlike any of the other 161 earthquakes, resulting in high prediction error for the aggregated impact models compared to all other events, reflecting model limitations on extreme events. However, training the building damage classifier AdaBoost model on all except the 2023 Türkiye-Syria earthquakes, predictions on the 27,032 held-out buildings have an AUC of 0.93. Therefore, without any geospatial, building-specific or direct satellite image information, this model accurately classifies building damage, with significantly improved performance over satellite-image trained models found in the literature.
CXXC5 Mitigates P. gingivalis-inhibited Cementogenesis by influencing Mitochondrial Biogenesis
Authors: Ma Li , Wang Huiyi , Huang Xin , Huang Hantao , Peng Yan , Liu Heyu , Wang Xiaoxuan , Cao Zhengguo 
Published: July 2023

Abstract
Background
Cementoblasts are tooth-root surface-lining cells responsible for cementum formation (cementogenesis) and sensitive to Porphyromonas gingivalis stimulation. We have previously proved transcription factor CXXC-type zinc finger protein 5 (CXXC5) participates in cementogenesis. Here, we aimed to elucidate the mechanism of CXXC5 in regulating P. gingivalis-inhibited cementogenesis from the perspective of mitochondrial biogenesis.
Methods
In vivo, mouse periapical lesions were induced in mandibular first molars by pulp exposure, and P. gingivalis was applied into the root canals. In vitro, a cementoblast cell line (OCCM-30) was induced cemengenesis and submitted for RNA-sequencing. These cells were co-cultured with P. gingivalis and examined for osteogenic ability and mitochondrial biogenesis. Cells with stable CXXC5 overexpression were constructed by lentivirus transduction, and PGC-1α (central inducer of mitochondrial biogenesis) was down-regulated by siRNA transfection.
Results
Mouse periapical lesions were enlarged and PGC-1α expression were reduced by P. gingivalis treatment. Upon apical inflammation, Cxxc5 expression decreased with Il-6 upregulation. RNA-sequencing showed enhanced expression of osteogenic markers, Cxxc5, and mitochondrial biogenesis markers during cementogenesis. P. gingivalis suppressed osteogenic capacities, mitochondrial biogenesis markers, mitochondrial (mt)DNA copy number, and cellular ATP content of cementoblasts, while CXXC5 overexpression rescued these effects. PGC-1α knockdown impaired cementoblast differentiation dramatically, confirming the regulatory effects of mitochondrial biogenesis on cementogenesis.
Conclusions
To summarize, CXXC5 is a P. gingivalis-sensitive transcription factor that positively regulates cementogenesis by influencing PGC-1α-dependent mitochondrial biogenesis.
Comparison of T-cell Receptor Diversity of people with Myalgic Encephalomyelitis versus controls
Authors: Dibble Joshua J , Ferneyhough Ben , Roddis Matthew , Millington Sam , Fischer Michael D , Parkinson Nick J , Ponting Chris P 
Published: July 2023

Abstract
Objective:
Myalgic Encephalomyelitis (ME; sometimes referred to as Chronic Fatigue Syndrome or CFS) is a chronic disease without laboratory test, detailed aetiological understanding or effective therapy. Its symptoms are diverse, but it is distinguished from other fatiguing illnesses by the experience of post-exertional malaise, the worsening of symptoms even after minor physical or mental exertion. Its frequent onset after infection might indicate that it is an autoimmune disease or that it arises from abnormal T-cell activation.
Results:
To test this hypothesis, we sequenced the genomic loci of a/d, b and g T-cell receptors (TCR) from 40 human blood samples from each of four groups: severely affected people with ME/CFS; mildly or moderately affected people with ME/CFS; people diagnosed with Multiple Sclerosis, as disease controls; and, healthy controls. Seeking to automatically classify these individuals’ samples by their TCR repertoires, we applied P-SVM, a machine learning method. However, despite working well on a simulated data set, this approach did not partition samples into the four subgroups, beyond what was expected by chance alone. Our findings do not support the hypothesis that blood samples from people with ME/CFS frequently contain altered T-cell receptor diversity.
Brain Target Engagement by CNM-Au8 in Parkinson’s Disease and Multiple Sclerosis: Integrated Imaging Results from the REPAIR-PD and REPAIR-MS Phase 2 Clinical Trials
Authors: Ren Jimin , III Richard B. Dewey , Rynders Austin , Evan Jacob , Evan Jeremy , Ligozio Shelia , Ho Karen S , Sguigna Peter V. , Glanzman Robert , Hotchkin Michael T. , Dewey Richard B. , Greenberg Benjamin M. 
Published: July 2023

Abstract
Impaired brain energy metabolism has been observed in many neurodegenerative diseases, including Parkinson’s disease (PD) and multiple sclerosis (MS). In both diseases, mitochondrial dysfunction and energetic impairment can lead to neuronal dysfunction and death. CNM-Au8® is a suspension of faceted, clean-surfaced gold nanocrystals that catalytically improves energetic metabolism in CNS cells, supporting neuroprotection and remyelination in multiple, independent preclinical models. The objective of the Phase 2 REPAIR-MS and REPAIR-PD clinical trials was to investigate the effects of CNM-Au8, administered orally once daily for twelve or more weeks, on brain phosphorous-containing energy metabolite levels in participants with diagnoses of relapsing MS or PD, respectively. Brain metabolites were measured using 7-Tesla 31P-MRS in two disease cohorts, 11 participants with stable relapsing MS and 13 participants with PD (n = 24 evaluable post-baseline scans). Compared to pre-treatment baseline, the mean NAD+/NADH ratio in the brain, a measure of energetic capacity, was significantly increased by 10.4% after 12 + weeks of treatment with CNM-Au8 (0.584 units, SD: 1.3; p = 0.037, paired t-test) in prespecified analyses of the combined treatment cohorts. Each disease cohort concordantly demonstrated increases in the NAD+/NADH ratio but did not reach significance individually (p = 0.11 and p = 0.14 for the PD and MS cohorts, respectively). Significant treatment effects were also observed for secondary and exploratory imaging outcomes, including beta-ATP and phosphorylation potential across both cohorts. Results demonstrate brain target engagement of CNM-Au8 as a direct modulator of brain energy metabolism, and support the further investigation of CNM-Au8 as a potential disease modifying drug for PD and MS.
Assessing Latent Tuberculosis Infections Prior to Biologic Therapy in Psoriasis: A New Diagnostic Approach with an Online Interpreter
Authors: Metin Zuhal , Özyurt Kemal , Atasoy Mustafa , Yontar Efşan Gürbüz , Ertaş Ragıp , Görgülü Özkan 
Published: July 2023

Abstract
The use of biological agents, particularly anti-TNF-alpha treatments, in psoriasis patients is associated with an elevated risk of tuberculosis (TB). Hence, a comprehensive assessment of latent tuberculosis infection (LTBI) before biologic therapies is imperative. The objective of this study was to evaluate the utility of an online tuberculin skin test (TST)/ interferon-γ release assay (IGRA) interpreter (OI-TST/IGRA) in assessing the risk of LTBI prior to initiating biological therapies in psoriasis patients. One hundred-sixteen psoriasis patients who were previously evaluated for TB by a pulmonologist before being treated with a biologic agent were re-evaluated retrospectively with OI-TST/IGRA (tstin3d.com). Mean positive predictive value (PPV), mean annual risk of development of active tuberculosis (ARDATB), and mean cumulative risk of active tuberculosis (CRATB) values were calculated with OI-TST/IGRA and compared with previous results. Chi-square, Fisher-Freeman-Halton exact tests, Cohen's Kappa, and Mann-Whitney U-test were used in comparisons of groups. The PPV of the LTBI-positive group was significantly higher than the LTBI-negative group. The PPV, ARDATB and CRATB values of the TST size of > 15 mm group were significantly higher than the TST size of 5–9 mm and TST size of 10–15 mm groups. The PPV, ARDATB, and CRATB values of the QuantiFERON-TB Gold In-tube test (QFT-GIT)-positive group were significantly higher than the QFT-GIT-negative group. And the same values of the chest X-ray (CXR)-positive group were significantly higher than the CXR-negative group. The PPV, ARDATB, and CRATB values were positively correlated with QFT-GIT and CXR results. In addition, the PPV was positively correlated with previous LTBI decisions and TSTs. OI-TST/IGRA in which many factors are questioned and PPV, ARDATB, and CRATB values are evaluated together, may be a valuable tool for assessing the risk of active TB in psoriasis patients and preventing overdiagnosis and unnecessary prophylaxis.
In-Context Learning for Data Generation in Aspect-Based Opinion Extraction
Authors: Moreira Johny , Barbosa Luciano 
Published: July 2023

Abstract
In-Context Learning (ICL), a strategy that generates text by passing a list of input-output examples to a Large Language Model, has shown state-of-the-art performance (SOTA) for many Natural Language Processing tasks. In this work, we aim to apply ICL for the synthetic generation of opinionated triples (sentence, aspect, and opinion) to enhance the training of models in two Aspect-Based Sentiment Analysis (ABSA) tasks: Target-oriented Opinion Words Extraction (TOWE) and Aspect-Based Opinion Pair Extraction (AOPE). Our approach first adapts a pre-trained Language Model (LM) to a downstream task using Task-adaptive Pretraining (TAPT). Next, it uses ICL prompting approaches on the adapted LM to generate the opinionated triples. Finally, a post-processing step applies some heuristics to clean and format the triples. We evaluate the quality of these generated samples by augmenting existing benchmark datasets with them and comparing the performance of four SOTA models on these tasks. The results show that these models trained on the generated synthetic data outperform those trained on a small percentage of human-labelled data. We manually inspected these triples with three human raters, which validated their quality.
Assessing PM 2.5 in a Protected Ecosystem in the South Atlantic under Massive Port Activities - Evidence of High Concentrations and Multiple Sources
Authors: Gurgatz Bruno Martins , Natalino Luiza , Albrecht Julia Stefany Chagas , Moreira Camila Arielle Bufato , Garcia Marina Reback , Joucoski Emerson , Godoi Ricardo Henrique Moreton , Martins César C. , Reis Rodrigo Arantes 
Published: July 2023

Abstract
Long-term exposure to atmospheric fine particulate matter (PM2.5) is a major human health concern; respiratory and cardiovascular diseases are the main consequences. In this study, we present the source apportionment of PM2.5 in a large port region in the South Atlantic, located in a Natural Heritage Estuary, which is a particularly sensitive ecosystem and a marine protected area. The PM2.5 mean concentration was 15.26 ± 7.5 µg m− 3, with a range from 0.7 to 41.0 µg m− 3, exceeding both World Health Organization target thresholds 3 and 4, as well as the Air Quality Guideline level. Notably, 10% (n = 34) of the samples exceeded the Brazilian environmental quality threshold for PM2.5 24-hour mean (25 µg m− 3), which is significant since the guidelines recommend a maximum of 3 to 4 exceedance days per year. Bivariate plots with meteorological data and positive matrix factorization (PMF) were employed to estimate the sources of PM2.5 from soluble ions and trace and major metal compositions. The findings suggest that truck activity in a nearby parking lot is the primary source of PM2.5, and the presence of a transportation structure linked to grain transportation was identified as a secondary source. Additionally, the findings of this study demonstrate an urgent need to address the impact of the Brazilian soybean export industry on human health and biodiversity in the region, given the context of excessive PM2.5 concentrations and the risks they presumably pose.
WITHDRAWN: Association between serum C1q and the efficacy of immune checkpoint inhibitors in patients with advanced non-small cell lung cancer
Authors: Tang Jiazhuo , fu yang , Song Yuxiao , Yin Jiaxin , Wang Jun , Bicheng Zhang 
Published: July 2023

Abstract
Objective
To evaluate the association between serum complement component 1q (C1q) and the efficacy of immune checkpoint inhibitors (ICIs) in patients with advanced non-small cell lung cancer (NSCLC).
Methods
Baseline characteristics and laboratory data of the patients with advanced NSCLC who received ICIs in the Renmin Hospital of Wuhan University from July 2018 to January 2023, were collected for the evaluation of survival analysis. The efficacy was estimated according to the response evaluation criteria in solid tumors (RECIST) 1.1. Kaplan-Meier method and Log-rank test were used for progression-free survival (PFS) and overall survival(OS). Univariate and multivariate Cox proportional hazard regression models and t-test were used to testify the correlation of survival with serum C1q levels and clinical characteristics.
Results
A total of 168 patients were included in this study, of which 39 patients achieved objective response [2 of complete response (CR), 37 of partial response (PR)], and 111 patients (66.07%) had the best efficacy of stable disease (SD). The objective response rate (ORR) was 23.21% and the disease control rate (DCR) was 89.28%. There was no correlation between pre-treatment C1q and PFS (P = 0.515) or OS (P = 0.185). Patients whose PFS longer than median PFS showed lower post-treatment serum C1q levels (P = 0.025). The median PFS of patients whose post-treatment serum C1q level ≥ 75th percentile of total was significantly shorter (P = 0.029). Moreover, the change of C1q levels between pre-treatment and post-treatment was strongly associated with the PFS and OS. In addition, the median PFS of patients whose age < 75 years old (P = 0.020) or Eastern Cooperative Oncology Group performance status (ECOG-PS) score 0–1 (P = 0.001) was significantly longer. The median OS of patients whose ECOG-PS score 0–1 (P < 0.001), or without brain metastasis (P = 0.036), or accepting previous chemotherapy was significantly longer.
Conclusion
This research showed that increasing serum C1q and ECOG-PS ≥ 2 may be related to a worse efficacy of NSCLC immunotherapy.
Predictive Modelling of Overall Survival in Adult Patients with Primary
Diffuse Large B-cell Lymphoma of the Breast Using the Surveillance,
Epidemiology, and End Results (SEER) Database
Authors: Liu Yishuai , Han Haifeng , Wei Hong , Wang Xinlong , Luan Zhaotang , Jiang Kun 
Published: July 2023

Objective:
We aimed to identify critical clinical features to develop an accurate webbased
prediction model for estimating the overall survival (OS) of primary breast diffuse large Bcell
lymphoma (PB-DLBCL) adult patients.

Methods:
We first included all PB-DLBCL cases with available covariates retrieved from the Surveillance,
Epidemiology, and End Results database. We sequentially performed univariate and
multivariate Cox regression approaches to identify the predictors independently associated with
prognosis, and all the predictors that passed these tests were then constructed to build a nomogram
for predicting 3-, 5-, and 10-year survival rates of patients. The C-index and the receiver operating
characteristic curve (ROC) were used to evaluate the prediction discrimination, and the calibration
curve was applied to estimate the calibration.

Results:
A total of PB-DLBCL adult patients were included (median age was 69 with the interquartile
range [IQR] of 57-79 years), of which 466 (70%) were randomly allocated to the development
cohort, and the remaining cases were collected for validation. Using three identified independent
predictors (i.e., age, stage, and radiation), an accurate nomogram for predicting OS was
developed and validated. The C-indices of our nomogram were both relatively acceptable, with
0.74 (95% CI: 0.71-0.78) and 0.72 (95% CI: 0.70-0.75) for the development and validation cohorts,
respectively. The calibration curves also accurately predicted the prognosis of PB-DLBCL
in all cases. In addition, ROC curves showed our nomogram to possess superior predictive ability
compared to any single variable. To visually present this prediction model, a convenient webbased
tool was implemented based on our prognostic nomogram.

Conclusion:
For patients with PB-DLBCL, a more convenient and accurate web-based prediction
model was developed and validated, which showed relatively good performances in both discrimination
and calibration during model development and validation. External evaluation and validation
are warranted by further independent studies.