bluuebunny/crossref_metadata_2025_split huggingface dataset:
SARS-CoV-2 Vaccine-Induced Immune Responses Among Hematopoietic Stem Cell Transplant Recipients
Authors: Kokogho Afoke , Crowell Trevor A , Aleissa Muneerah , Lupan Ana-Mihaela , Davey Sonya , Park Chang Jun Bai , Baden Lindsey R , Walsh Stephen R , Sherman Amy C 
Published: July 2023

Abstract

Background
Although severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination reduces the risk and severity of coronavirus disease 2019 (COVID-19), several variables may impact the humoral response among patients undergoing hematopoietic stem cell transplantation (HSCT).

Methods
A retrospective chart review was conducted among SARS-CoV-2-vaccinated HSCT recipients between 2020 and 2022 at a single center in Boston, Massachusetts. Patients age ≥18 years who received doses of Pfizer, Moderna, or J&J vaccines were included. Anti-spike (S) immunoglobulin G (IgG) titer levels were measured using the Roche assay. Responders (≥0.8 U/mL) and nonresponders (&lt;0.8 U/mL) were categorized and analyzed. Multivariable linear and logistic regression were used to estimate the correlation coefficient and odds ratio of response magnitude and status.

Results
Of 152 HSCT recipients, 141 (92.8%) were responders, with a median (interquartile range [IQR]) anti-S IgG titer of 2500 (107.9–2500) U/mL at a median (IQR) of 80.5 (36–153.5) days from last dose, regardless of the number of doses received. Higher quantitative titers were associated with receipt of more vaccine doses (coeff, 205.79; 95% CI, 30.10 to 381.47; P = .022), being female (coeff, 343.5; 95% CI, −682.6 to −4.4; P = .047), being younger (&lt;65 years; coeff, 365.2; 95% CI, −711.3 to 19.1; P = .039), and not being on anti-CD20 therapy (coeff, −1163.7; 95% CI, −1717.7 to −609.7; P = .001). Being male (odds ratio [OR], 0.11; 95% CI, 0.01 to 0.93; P = .04) and being on anti-CD20 therapy (OR, 0.16; 95% CI, 0.03 to 0.70; P = .016) were associated with nonresponse.

Conclusions
Overall, most HSCT recipients had high SARS-CoV-2 antibody responses. More vaccine doses improved the magnitude of immune responses. Anti-S IgG monitoring may be useful for identifying attenuated vaccine-induced responses.
A proposed method of grading malaria chemoprevention efficacy
Authors: White N J , Bonnington C , Nosten F H 
Published: July 2023

ABSTRACT
The efficacy and effectiveness of antimalarial drugs are threatened by increasing levels of resistance and therefore require continuous monitoring. Chemoprevention is increasingly deployed as a malaria control measure, but there are no generally accepted methods of assessment. We propose a simple method of grading the parasitological response to chemoprevention (focusing on seasonal malaria chemoprevention) that is based on pharmacometric assessment.
Telephone Triage Simulation in an Asynchronous Advanced Practice Nursing Course
Authors: Neuman Michelle E. 
Published: July 2023

Abstract
The use of simulation in advanced practice nursing programs is widespread; however, few simulations focus on telehealth skills. Those that do typically consist of synchronous activities. This article describes an innovative activity in an asynchronous course using the VoiceThread platform. The activity simulates a telephone triage call a family or pediatric nurse practitioner might receive in actual practice.
Optimal examined lymph node number for accurate staging and long-term survival in rectal cancer: a population-based study
Authors: Guan Xu , Jiao Shuai , Wen Rongbo , Yu Guanyu , Liu Jungang , Miao Dazhuang , Wei Ran , Zhang Weiyuan , Hao Liqiang , Zhou Leqi , Lou Zheng , Liu Shucheng , Zhao Enliang , Wang Guiyu , Zhang Wei , Wang Xishan 
Published: July 2023

Background:
Although the recommended minimal examined lymph node (ELN) number in rectal cancer (RC) is 12, this standard remains controversial because of insufficient evidence. We aimed to refine this definition by quantifying the relationship between ELN number, stage migration and long-term survival in RC.

Methods:
Data from a Chinese multi-institutional registry (2009-2018) and the Surveillance, Epidemiology, and End Results (SEER) database (2008-2017) on stages I–III resected RC were analysed to determine the relationship between ELN count, stage migration, and overall survival (OS) using multivariable models. The series of odds ratios (ORs) for negative-to-positive node stage migration and hazard ratios (HRs) for survival with more ELNs were fitted using a Locally Weighted Scatterplot Smoothing (LOWESS) smoother, and structural breakpoints were determined using the Chow test. The relationship between ELN and survival was evaluated on a continuous scale using restricted cubic splines (RCS).

Results:
The distribution of ELN count between the Chinese registry (n=7694) and SEER database (n=21 332) was similar. With increasing ELN count, both cohorts exhibited significant proportional increases from node-negative to node-positive disease (SEER, OR, 1.012, P<0.001; Chinese registry, OR, 1.016, P=0.014) and serial improvements in OS (SEER: HR, 0.982; Chinese registry: HR, 0.975; both P<0.001) after controlling for confounders. Cut-point analysis showed an optimal threshold ELN count of 15, which was validated in the two cohorts, with the ability to properly discriminate probabilities of survival.

Conclusions:
A higher ELN count is associated with more precise nodal staging and better survival. Our results robustly conclude that 15 ELNs are the optimal cut-off point for evaluating the quality of lymph node examination and stratification of prognosis.
A multicenter, single-arm, open study of neoadjuvant or conversion atezolizumab in combination with chemotherapy in resectable small cell lung cancer (neoSCI) (Cohort Study)
Authors: Duan Hongtao , Shi Liang , Shao Changjian , Wang Yuanyong , wang Zhaoyang , Ni Yunfeng , Zhao Jinbo , Sun Jianyong , Tong Liping , Lei Jie , Jiang Tao , Liu Zhe , Yan Xiaolong 
Published: July 2023

Background:
This study aimed to investigate the prospects of using chemotherapy in combination with atezolizumab in the neoadjuvant or conversion treatment of small cell lung cancer (SCLC).

Methods:
Prior to surgery, untreated patients with limited-stage SCLC received 3 cycles of neoadjuvant or conversion atezolizumab combined with chemotherapy of etoposide and platinum. The primary endpoint of the trial was pathological complete response (pCR) in the per-protocol (PP) cohort. In addition, safety was assessed based on treatment-related adverse events (AEs) and postoperative complications.

Results:
Overall, thirteen of seventeen patients (including fourteen males and three females) underwent surgery. In the PP cohort, pCR and MPR were observed in eight (8/13, 61.5%) and twelve (12/13, 92.3%) patients, respectively. According to the intention-to-treat (ITT) analysis, the pCR and major pathological response (MPR) in the ITT cohort were 47.1% (8/17) and 70.6% (12/17), respectively. In addition, an ORR of 100% was recorded in the PP cohort. Moreover, fifteen (15/17, 88.2%) patients and one (1/17, 5.9%) in the ITT cohort attained partial remission (PR), and complete remission (CR), respecstively, with an overall response rate (ORR) of 94.1%. The median OS of the patients of pCR and the median EFS of the patients on surgery had not achieved. However, the median OS of the patients of non-pCR was 18.2 months and the median EFS of the non-surgical patients was 9.5 months. During the neoadjuvant treatment, the incidence of grade 3 or higher AEs was 58.8% (10/17). Additionally, three patients (17.6%) developed immune-related adverse event (irAE, grade 1-2).

Conclusion:
In patients with SCLC, neoadjuvant or conversion atezolizumab combined with chemotherapy significantly improved pCR with manageable AEs. Therefore, this regimen may be considered a safe and effective treatment for SCLC.
Diagnostic Accuracy of Urinary PCA3 for Prostate Cancer in Thai Patients With PSA Levels of 3 to 10 ng/ml Undergoing an Initial Prostate Biopsy
Authors: Limudomporn Pasin , Sathirapongsasuti Nuankanya , Worawichawong Suchin , Sirisreetreeru Pokket , Kongcharoensombat Wisoot , Kijvikai Kittinut , Jittawera Samapat , Kocharoenwat Jitpanu , Jenjitranant Pocharapong 
Published: July 2023

Purpose:
To examine the diagnostic accuracy of the urinary prostate cancer gene 3 score for prostate cancer in Thai patients with prostate-specific antigen levels of 3 to 10 ng/ml undergoing an initial prostate biopsy.

Materials and methods:
In this prospective, single-center study, urine samples were collected after prostate massage. Urinary prostate cancer gene 3 mRNA levels were measured by real-time quantitative polymerase chain reaction. Data, including age, biopsy results, preoperative prostate-specific antigen levels, prostate-specific antigen density, prostate-specific antigen velocity, prostate volume, and prostate imaging findings, were collected between June 1, 2020, and May 15, 2021.

Results:
The median prostate-specific antigen level of the 70 included patients was 6.31 ng/ml. Sixteen patients had positive biopsy results (22.9%). The prostate cancer gene 3 score (695.09 vs 268.79, P < .01), prostate-specific antigen density (0.19 vs 0.13, P < .01), and prostate-specific antigen velocity (2.68 vs 0.44, P < .01) significantly differed between the positive and negative biopsy groups. The predictive power of the prostate cancer gene 3 score was evaluated using receiver operating characteristic curves. At a prostate cancer gene 3 score threshold of 366.02, the sensitivity and specificity were 78.57% and 79.25%, respectively. Meanwhile, the areas under the curve of the prostate cancer gene 3 score, prostate-specific antigen velocity, and prostate-specific antigen density were better than that of prostate-specific antigen for predicting a positive biopsy.

Conclusion:
Our study confirmed the diagnostic accuracy of prostate cancer gene 3 for predicting a positive biopsy in Thai men with prostate-specific antigen levels of 3 to 10 ng/mL. Combining the prostate cancer gene 3 score and prostate-specific antigen derivatives might be helpful for identifying patients who can avoid unnecessary biopsies and subsequent complications.
Deep Learning–Based Kernel Adaptation Enhances Quantification of Emphysema on Low-Dose Chest CT for Predicting Long-Term Mortality
Authors: Park Hyungin , Hwang Eui Jin , Goo Jin Mo 
Published: July 2023

Objectives
The aim of this study was to ascertain the predictive value of quantifying emphysema using low-dose computed tomography (LDCT) post deep learning–based kernel adaptation on long-term mortality.

Materials and Methods
This retrospective study investigated LDCTs obtained from asymptomatic individuals aged 60 years or older during health checkups between February 2009 and December 2016. These LDCTs were reconstructed using a 1- or 1.25-mm slice thickness alongside high-frequency kernels. A deep learning algorithm, capable of generating CT images that resemble standard-dose and low-frequency kernel images, was applied to these LDCTs. To quantify emphysema, the lung volume percentage with an attenuation value less than or equal to −950 Hounsfield units (LAA-950) was gauged before and after kernel adaptation. Low-dose chest CTs with LAA-950 exceeding 6% were deemed emphysema-positive according to the Fleischner Society statement. Survival data were sourced from the National Registry Database at the close of 2021. The risk of nonaccidental death, excluding causes such as injury or poisoning, was explored according to the emphysema quantification results using multivariate Cox proportional hazards models.

Results
The study comprised 5178 participants (mean age ± SD, 66 ± 3 years; 3110 males). The median LAA-950 (18.2% vs 2.6%) and the proportion of LDCTs with LAA-950 exceeding 6% (96.3% vs 39.3%) saw a significant decline after kernel adaptation. There was no association between emphysema quantification before kernel adaptation and the risk of nonaccidental death. Nevertheless, after kernel adaptation, higher LAA-950 (hazards ratio for 1% increase, 1.01; P = 0.045) and LAA-950 exceeding 6% (hazards ratio, 1.36; P = 0.008) emerged as independent predictors of nonaccidental death, upon adjusting for age, sex, and smoking status.

Conclusions
The application of deep learning for kernel adaptation proves instrumental in quantifying pulmonary emphysema on LDCTs, establishing itself as a potential predictive tool for long-term nonaccidental mortality in asymptomatic individuals.
Application of Immediate Implant Placement Techniques in Peri-implantitis Modeling
Authors: Zhang Hongming , Yuan Yun , Wu Xiaolin , Xue Hanxiao , Yu Runping , Huang Hui 
Published: July 2023

Objectives:
To explore the use of immediate implant placement technique in peri-implantitis modeling, shorten the modeling period, and obtain similar effects.

Materials and Methods:
Eighty rats were divided into 4 groups: immediate placement (IP), delayed placement (DP), IP-ligation (IP-L) and DP-ligation (DP-L). In the DP and DP-L groups, implants were placed 4 weeks after tooth extraction. In the IP and IP-L groups, implants were placed immediately. Four weeks later, the implants were ligated to induce peri-implantitis in the DP-L and IP-L groups.

Results:
Nine implants were lost (3 in the IP-L and 2 each in the IP, DP, and DP-L group). The bone level decreased after ligation, and the buccal and lingual bone levels were lower in IP-L versus DP-L. The implant pullout strength was decreased after ligation. Micro-CT showed bone parameters were decreased after ligation, and the percent bone volume was higher in IP versus DP. Histology showed that the percent of CD4+ cells and IL-17+ cells was increased after ligation and higher in IP-L versus DP-L.

Conclusions:
We successfully introduced immediate implant placement into the modeling of peri-implantitis and observed similar bone resorption and more soft tissue inflammation in a shorter time.
Reconstruction of Medial Canthal Ligament With Autogenous Fascia Lata Graft
Authors: Wang Yan , Yuan Yuan , Pang Long 
Published: July 2023

Background:
An eyelid malignant tumor invading the medial canthus is a serious eyelid disease that requires extensive resection and complex destruction. The medial canthus ligament is especially difficult to repair because its reconstruction often requires special materials. In this study, we described our reconstruction technique using autogenous fascia lata.

Methods:
Data from 4 patients (4 eyes) who had medial canthal ligament defects after Mohs resection of eyelid malignant tumors were reviewed from September 2018 to August 2021. The reconstruction of the medial canthal ligament using autogenous fascia lata was performed in all of the patients. If combined with the upper and lower tarsus defects, autogenous fascia lata was split into 2 branches to repair the tarsal plate.

Results:
The pathologic diagnosis was basal cell carcinoma in all patients. The mean follow-up time was 13.6±3.51 months (range, 8–24 mo). There was no tumor recurrence, infection, or graft rejection. All patients achieved good eyelid movement and function and were satisfied with their medial angular shape and cosmetic contour.

Conclusions:
Autogenous fascia lata is a good material to repair medial canthal defects. It is easy to take and effectively maintains eyelid movement and function with satisfactory postoperative effects.
Spatial pattern and differential expression analysis with spatial transcriptomic data
Authors: Qin Fei , Luo Xizhi , Cai Bo , Xiao Feifei , Cai Guoshuai 
Published: July 2023

ABSTRACTThe emergence of spatial transcriptomic technologies has opened new avenues to investigate gene activities while preserving the spatial context of tissues. Utilizing data generated by such technologies, the identification of spatially variable (SV) genes is an essential step in investigating tissue landscapes and biological processes. Particularly in typical experimental designs such as case-control or longitudinal studies, identifying SV genes between groups is crucial for discovering significant biomarkers or developing targeted therapies for diseases. However, current methods available for analyzing spatial transcriptomic data are still in their infancy, and none of the existing methods are capable of identifying SV genes between groups. To overcome this challenge, we developed SPADE forspatialpatternanddifferentialexpression analysis to identify SV gene in spatial transcriptomic data. SPADE is based on a machine learning model of Gaussian process regression with a gene-specific Gaussian kernel, enabling the detection of SV genes both within and between groups. Through extensive simulations and real data analyses, we have demonstrated the superior performance of SPADE compared to existing methods in detecting SV genes within and between groups. The SPADE source code and documentation are publicly available athttps://github.com/thecailab/SPADE.
Detecting differential transcript usage in complex diseases with SPIT
Authors: Erdogdu Beril , Varabyou Ales , Hicks Stephanie C. , Salzberg Steven L. , Pertea Mihaela 
Published: July 2023

AbstractDifferential transcript usage (DTU) plays a crucial role in determining how gene expression differs among cells, tissues, and different developmental stages, thereby contributing to the complexity and diversity of biological systems. In abnormal cells, it can also lead to deficiencies in protein function, potentially leading to pathogenesis of diseases. Detecting such events for single-gene genetic traits is relatively uncomplicated; however, the heterogeneity of populations with complex diseases presents an intricate challenge due to the presence of diverse causal events and undetermined subtypes. SPIT is the first statistical tool that quantifies the heterogeneity in transcript usage within a population and identifies predominant subgroups along with their distinctive sets of DTU events. We provide comprehensive assessments of SPIT’s methodology in both single-gene and complex traits and report the results of applying SPIT to analyze brain samples from individuals with schizophrenia. Our analysis reveals previously unreported DTU events in six candidate genes.
Molecular and structural basis of the heterochromatin-specific chromatin remodeling activity byArabidopsisDDM1
Authors: Osakabe Akihisa , Takizawa Yoshimasa , Horikoshi Naoki , Hatazawa Suguru , Negishi Lumi , Berger Frédéric , Kakutani Tetsuji , Kurumizaka Hitoshi 
Published: July 2023

AbstractThe chromatin remodeler DECREASE IN DNA METHYLATION 1 (DDM1) deposits the histone H2A variant H2A.W and silences transposons inArabidopsis thaliana. However, the molecular mechanisms by which DDM1 specifically targets the nucleosome containing H2A.W and allows chromatin writers to access heterochromatin remained elusive. Here, we show that DDM1 promotes remodeling of the H2A.W nucleosome and requires interactions with the H2A.W-specific C-terminal tail. The cryo-EM structure of the DDM1-H2A.W nucleosome complex revealed that DDM1 binds to the N-terminal tail of H4 and the nucleosomal DNA. Comparison with the cryo-EM structure of the nucleosome containing H2A.W suggested that DDM1 increases the DNA end flexibility of nucleosomes. Based on these biochemical and structural results, we propose that the chromatin remodeling activity of DDM1 with the heterochromatin-specific H2A.W contributes to the maintenance of repressive epigenetic marks in heterochromatin by providing DNA methyltransferases with access to nucleosomal DNA.
Convolutional neural network-based deep learning model for air quality prediction in October city of Egypt
Authors: Elshaboury Nehal , Mohammed Abdelkader Eslam , Al-Sakkaf Abobakr 
Published: July 2023

Purpose
Modern human society has continuous advancements that have a negative impact on the quality of the air. Daily transportation, industrial and residential operations churn up dangerous contaminants in our surroundings. Addressing air pollution issues is critical for human health and ecosystems, particularly in developing countries such as Egypt. Excessive levels of pollutants have been linked to a variety of circulatory, respiratory and nervous illnesses. To this end, the purpose of this research paper is to forecast air pollution concentrations in Egypt based on time series analysis.

Design/methodology/approach
Deep learning models are leveraged to analyze air quality time series in the 6th of October City, Egypt. In this regard, convolutional neural network (CNN), long short-term memory network and multilayer perceptron neural network models are used to forecast the overall concentrations of sulfur dioxide (SO2) and particulate matter 10 µm in diameter (PM10). The models are trained and validated by using monthly data available from the Egyptian Environmental Affairs Agency between December 2014 and July 2020. The performance measures such as determination coefficient, root mean square error and mean absolute error are used to evaluate the outcomes of models.

Findings
The CNN model exhibits the best performance in terms of forecasting pollutant concentrations 3, 6, 9 and 12 months ahead. Finally, using data from December 2014 to July 2021, the CNN model is used to anticipate the pollutant concentrations 12 months ahead. In July 2022, the overall concentrations of SO2 and PM10 are expected to reach 10 and 127 µg/m3, respectively. The developed model could aid decision-makers, practitioners and local authorities in planning and implementing various interventions to mitigate their negative influences on the population and environment.

Originality/value
This research introduces the development of an efficient time-series model that can project the future concentrations of particulate and gaseous air pollutants in Egypt. This research study offers the first time application of deep learning models to forecast the air quality in Egypt. This research study examines the performance of machine learning approaches and deep learning techniques to forecast sulfur dioxide and particular matter concentrations using standard performance metrics.