bluuebunny/crossref_metadata_2025_split huggingface dataset:
Oral vaccination of fish against vibriosis using spore-display technology
Authors: Gonçalves Gabriela , Santos Rafaela A. , Coutinho Filipe , Pedrosa Neide , Curado Maria , Machado Marina , Costas Benjamin , Bonneville Lourenço , Serrano Mónica , Carvalho António Paulo , Díaz-Rosales Patricia , Oliva-Teles Aires , Couto Ana , Serra Cláudia R. 
Published: October 2022

Oral vaccines are highly demanded by the aquaculture sector, to allow mass delivery of antigens without using the expensive and labor-intensive injectable vaccines. These later require individual handling of fish, provoking stress-related mortalities.One possible strategy to create injection-free vaccine delivery vehicles is the use of bacterial spores, extremely resistant structures with wide biotechnological applications, including as probiotics, display systems, or adjuvants. Bacterial spores, in particular those of Bacillus subtilis, have been shown to behave as mucosal vaccine adjuvants in mice models. However, such technology has not been extensively explored against fish bacterial disease.In this study, we used a laboratory strain of B. subtilis, for which a variety of genetic manipulation tools are available, to display at its spores surface either a Vibrio antigenic protein, OmpK, or the green fluorescence protein, GFP. When previously vaccinated by immersion with the OmpK- carrying spores, zebrafish survival upon a bacterial challenge with V. anguillarum and V. parahaemolyticus, increased up to 50 - 90% depending on the pathogen targeted. Further, we were able to detect anti-GFP-antibodies in the serum of European seabass juveniles fed diets containing the GFP-carrying spores and anti-V. anguillarum antibodies in the serum of European seabass juveniles fed the OmpK-carrying spores containing diet. More important, seabass survival was increased from 60 to 86% when previously orally vaccinated with in-feed OmpK- carrying spores. Our results indicate that B. subtilis spores can effectively be used as antigen-carriers for oral vaccine delivery in fish.
Does time to esophagectomy following neoadjuvant immunochemotherapy for locally advanced esophageal squamous cell carcinoma affect outcomes?
Authors: Hong Zhi-Nuan , Huang Zhixin , Weng Kai , Lin Jihong , Kang Mingqiang 
Published: October 2022

ObjectivesNeoadjuvant immunochemotherapy (nICT) is a novel pattern for locally advanced esophageal squamous cell carcinoma (ESCC), and the time to surgery (TTS) is recommended as 4-6 weeks. However, there were some patients with prolonged TTS(&gt; 6 weeks). This study aimed to explore whether prolonged TTS (&gt; 6 weeks) would affect the outcomes.MethodsPatients diagnosed with locally advanced ESCC between January 2020 and March 2022 and undergoing esophagectomy following nICT were identified based on a prospectively collected database. Primary outcome measures were pathological complete response (pCR) and disease-free survival (DFS), and the secondary outcomes were 30-day postoperative mortality and morbidity, surgical time, postoperative hospital stay, and hospital expense.ResultsTotal of 95 patients were included for analysis, with 52 patients in the standard TTS group and 43 patients in the prolonged TTS group. The clinical and demographic characteristics of the two groups were comparable. The prolonged group had a median 18 days longer TTS(P&lt;0.001). The pCR rate was 23.08% (12/52) in the standard group and 16.28% (7/43) in the prolonged group (P=0.41). Multivariate regression analysis further indicated that TTS wasn’t an independent factor in predicting pCR (P=0.41). The median follow-up time was 10.5 months in the standard TTS group and 11.2 months in the prolonged TTS group. A total of five recurrences occurred with two events in the standard TTS group and three events in the prolonged TTS group, and no significant difference was observed in DFS(P=0.60). Both groups were comparable in postoperative hospital stays, total hospital stay, hospital expenses, and comprehensive complications index (CCI). The complications and major complications were also similar in both groups. Spearman test further indicated that there was no linear correlation among TTS with hospital expenses, postoperative hospital stays, hospital stay, CCI index, lymph nodes moved number, or surgical time, with a p-value of 0.48, 0.63, 0.80, 0.92, 0.09, 0.38 respectively.ConclusionsBased on present evidence, TTS after completion of nICT is not of major importance concerning pathological response, disease-free survival, and short-term postoperative outcomes.
Brief Research Report: Serum clara cell 16 kDa protein levels are increased in patients hospitalized for severe SARS-CoV-2 or sepsis infection
Authors: Rohmann Nathalie , Stürmer Paula , Geisler Corinna , Schlicht Kristina , Hartmann Katharina , Türk Kathrin , Hollstein Tim , Tran Florian , Rosenstiel Philip , Franke Andre , Heyckendorf Jan , Schreiber Stefan , Schulte Dominik M. , Laudes Matthias 
Published: October 2022

BackgroundClara cell 16 kDa protein (CC16) is a secretory protein primarily expressed in epithelial cells in the lungs. Previous studies show that CC16 exerts anti-inflammatory and immune-modulatory properties in both acute and chronic pulmonary diseases. However, despite the evidence of CC16’s high biomarker potential, evaluation of its role in infectious diseases is yet very limited.MethodsSerum CC16 concentrations were measured by ELISA and assessed in two different types of severe infections. Using a case-control study design, patients treated for either severe SARS-CoV-2 or severe non-pulmonary sepsis infection were compared to age- and sex-matched healthy human subjects.ResultsSerum CC16 was significantly increased in both types of infection (SARS-CoV-2: 96.22 ± 129.01 ng/ml vs. healthy controls: 14.05 ± 7.48 ng/ml, p = 0.022; sepsis: 35.37 ± 28.10 ng/ml vs. healthy controls: 15.25 ± 7.51 ng/ml, p = 0.032) but there were no distinct differences between infections with and without pulmonary focus (p = 0.089). Furthermore, CC16 serum levels were positively correlated to disease duration and inversely to the platelet count in severe SARS-CoV-2 infection.ConclusionsIncreased CC16 serum levels in both SARS-CoV-2 and sepsis reinforce the high potential as a biomarker for epithelial cell damage and bronchoalveolar−blood barrier leakage in pulmonary as well as non-pulmonary infectious diseases.
The add-on effect of Shufeng Jiedu capsule for treating COVID-19: A systematic review and meta-analysis
Authors: Sheng Xiaodi , Chen Chao , Jiang Guowang , Ji Zhaochen , Guo Zehui , Hu Haiyin , Wang Hui , Zhai Jingbo , Zhang Dong , Zhang Junhua , Guo Liping 
Published: October 2022

IntroductionShufeng Jiedu capsule (SFJD) is a commonly used Chinese patent medicine in China. Some studies have reported that SFJD has therapeutic effects in patients diagnosed with COVID-19. This systematic review aimed to critically evaluate the efficacy and safety of SFJD combined with western medicine (WM) for treating COVID-19.MethodsA literature search by using WHO COVID-19 database, PubMed, Embase, Cochrane Library, the Web of Science, CKNI, Wanfang, VIP, SinoMed, and clinical trial registries was conducted, up to 1 August 2022. Randomized controlled trials (RCTs), non-RCTs, cohort studies and case series of SFJD combined with WM for COVID-19 were included. Literature screening, data extraction, and quality assessment were performed independently by two reviewers in line with the same criteria. We used the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) to assess the certainty of evidence. Meta-analyses were performed with Revman 5.3 if possible. The descriptive analysis was conducted when the studies could not be meta-analyzed.ResultsTotally 10 studies with 1,083 patients were included. Their methodological quality were moderate. The results demonstrated that compared to WM group, SFJD + WM group remarkably increased the nucleic acid negative conversion rate (RR = 1.40, 95%CI: 1.07–1.84), total effective rate (RR = 1.18, 95%CI: 1.07–1.31), cure rate (RR = 4.06, 95%CI: 2.19–7.53), and the chest CT improvement rate (RR = 1.19, 95%CI: 1.08–1.31), shorten nucleic acid negative conversion time (MD = −0.70, 95%CI: −1.14 to −0.26), reduced the clinical symptom disappearance time (fever, diarrhea, cough, fatigue, pharyngalgia, nasal congestion, and rhinorrhea), as well as improved the levels of laboratory outcomes (CRP, IL-6, Lym, and Neu). Additionally, the incidence of adverse reactions did not exhibit any statistically significant difference between SFJD + WM group and WM group.ConclusionSFJD combined with WM seems more effective than WM alone for the treatment of COVID-19. However, more well-designed RCTs still are warranted.Systematic review registration[https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD42022306307].
A 16S rDNA sequencing-based analysis of airway microecology in patients with an acute exacerbation of chronic obstructive pulmonary disease: A cross-sectional study in Inner Mongolia, China
Authors: Zhu Shu-fen , Wu Xin-xin , Guo Yan , Li Peng-fei , Wang Jing-ran , Liu Miao , Luo Cheng-wen , Yuan Xiang-zhen , Li Shao-wei 
Published: October 2022

AimTo study the microecological characteristics of the airway and similarities and differences between healthy people and patients with the acute exacerbation of chronic obstructive pulmonary disease (AECOPD) in Inner Mongolia, and analyze the correlation between the characteristics of the airway microecological structure and clinical indicators of AECOPD patients.MethodsSputum samples from 36 healthy volunteers and 34 patients with AECOPD were detected by 16S rDNA high-throughput sequencing, and the airway microecological characteristics of healthy people and AECOPD patients were revealed by an alpha diversity analysis, beta diversity analysis, and LefSe difference analysis.ResultsThere were differences in the airway microecological structure between healthy people and AECOPD patients in Inner Mongolia. The airway microbiota composition of AECOPD patients showed an increase in the abundance of common pathogens and a decrease in the abundance of commensal bacteria, and the airway microbial diversity in AECOPD patients was lower than that in healthy people. Long-term use of inhaled glucocorticoid + long-acting β2 agonist mixture (ICS + LABA), procalcitonin (PCT), blood monocyte count (MONO), hemoglobin (HGB), D-dimer (D-D), and body temperature were negatively correlated with the alpha diversity of the airway micro-ecosystem.ConclusionThe airway microecological composition of the AECOPD population in Inner Mongolia was different from that of the healthy population, and the airway microecological diversity was lower than that of the healthy population. The long-term use of ICS + LABA preparation by patients with AECOPD leads to lower alpha diversity. Alpha diversity was negatively correlated with inflammatory markers (PCT, MONO, D-dimer, body temperature) and HGB in AECOPD patients.
Depletion of ALMS1 affects TGF-β signalling pathway and downstream processes such as cell migration and adhesion capacity
Authors: Bea-Mascato Brais , Neira-Goyanes Elena , Iglesias-Rodríguez Antía , Valverde Diana 
Published: October 2022

Background:ALMS1 is a ubiquitous gene associated with Alström syndrome (ALMS). The main symptoms of ALMS affect multiple organs and tissues, generating at last, multi-organic fibrosis in the lungs, kidneys and liver. TGF-β is one of the main pathways implicated in fibrosis, controlling the cell cycle, apoptosis, cell migration, cell adhesion and epithelial-mesenchymal transition (EMT). Nevertheless, the role of ALMS1 gene in fibrosis generation and other implicated processes such as cell migration or cell adhesion via the TGF- β pathway has not been elucidated yet.Methods: Initially, we evaluated how depletion of ALMS1 affects different processes like apoptosis, cell cycle and mitochondrial activity in HeLa cells. Then, we performed proteomic profiling with TGF-β stimuli in HeLa ALMS1 −/− cells and validated the results by examining different EMT biomarkers using qPCR. The expression of these EMT biomarkers were also studied in hTERT-BJ-5ta ALMS1 −/−. Finally, we evaluated the SMAD3 and SMAD2 phosphorylation and cell migration capacity in both models.Results: Depletion of ALMS1 generated apoptosis resistance to thapsigargin (THAP) and C2-Ceramide (C2-C), and G2/M cell cycle arrest in HeLa cells. For mitochondrial activity, results did not show significant differences between ALMS1 +/+ and ALMS1 −/−. Proteomic results showed inhibition of downstream pathways regulated by TGF-β. The protein-coding genes (PCG) were associated with processes like focal adhesion or cell-substrate adherens junction in HeLa. SNAI1 showed an opposite pattern to what would be expected when activating the EMT in HeLa and BJ-5ta. Finally, in BJ-5ta model a reduced activation of SMAD3 but not SMAD2 were also observed. In HeLa model no alterations in the canonical TGF-β pathway were observed but both cell lines showed a reduction in migration capacity.Conclusion:ALMS1 has a role in controlling the cell cycle and the apoptosis processes. Moreover, the depletion of ALMS1 affects the signal transduction through the TGF-β and other processes like the cell migration and adhesion capacity.
Assessment of Alzheimer’s disease-related biomarkers in patients with obstructive sleep apnea: A systematic review and meta-analysis
Authors: Cui Wenqi , Duan Zhenghao , Li Zijian , Feng Juan 
Published: October 2022

Increasing evidence links Alzheimer’s disease (AD) to various sleep disorders, including obstructive sleep apnea (OSA). The core AD cerebrospinal fluid (CSF) biomarkers, including amyloid-β 42 (Aβ42), total tau (t-tau), and phosphorylated tau (p-tau), can reflect key elements of AD pathophysiology before the emergence of symptoms. Besides, the amyloid-β (Aβ) and tau burden can also be tested by positron emission tomography (PET) scans. Electronic databases (PubMed, Embase, Web of Science, and The Cochrane Library) were searched until August 2022 to assess the AD-related biomarkers measured by PET scans and CSF in OSA patients. The overall analysis showed significant differences in Aβ42 levels (SMD = −0.93, 95% CI:−1.57 to −0.29, P &lt; 0.001) and total tau (t-tau) levels (SMD = 0.24, 95% CI: 0.01–0.48, P = 0.308) of CSF, and Aβ burden (SMD = 0.37, 95% CI = 0.13–0.61, P = 0.69) tested by PET scans between the OSA and controls. Furthermore, CSF Aβ42 levels showed significant differences in patients with moderate/severe OSA compared with healthy control, and levels of CSF Aβ42 showed differences in OSA patients with normal cognition as well. Besides, age and BMI have influences on heterogeneity. Our meta-analysis indicated abnormal AD-related biomarkers (CSF and PET scans) in patients with OSA, supporting the current hypothesis that OSA, especially moderate/severe OSA, may start the AD neuropathological process.Systematic review registration[https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD42021289559].
A nomogram for predicting atrial fibrillation detected after acute ischemic stroke
Authors: Pang Ming , Li Zhuanyun , Sun Lin , Zhao Na , Hao Lina 
Published: October 2022

BackgroundAtrial fibrillation detected after stroke (AFDAS) is associated with an increased risk of ischemic stroke (IS) recurrence and death. Early diagnosis can help identify strategies for secondary prevention and improve prognosis. However, there are no validated predictive tools to assess the population at risk for AFDAS. Therefore, this study aimed to develop and validate a predictive model for assessing the incidence of AFDAS after acute ischemic stroke (AIS).MethodsThis study was a multicenter retrospective study. We collected clinical data from 5332 patients with AIS at two hospitals between 2014.01 and 2021.12 and divided the development and validation of clinical prediction models into a training cohort (n = 3173) and a validation cohort (n = 2159). Characteristic variables were selected from the training cohort using the least absolute shrinkage and selection operator (LASSO) algorithm and multivariable logistic regression analysis. A nomogram model was developed, and its performance was evaluated regarding calibration, discrimination, and clinical utility.ResultsWe found the best subset of risk factors based on clinical characteristics and laboratory variables, including age, congestive heart failure (CHF), previous AIS/transient ischemia attack (TIA), national institutes of health stroke scale (NIHSS) score, C-reactive protein (CRP), and B-type natriuretic peptide (BNP). A predictive model was developed. The model showed good calibration and discrimination, with calibration values of Hosmer-Lemeshow χ2 = 4.813, P = 0.732 and Hosmer-Lemeshow χ2 = 4.248, P = 0.834 in the training and validation cohorts, respectively. The area under the ROC curve (AUC) was 0.815, 95% CI (0.777–0.853) and 0.808, 95% CI (0.770–0.847). The inclusion of neuroimaging variables significantly improved the performance of the integrated model in both the training cohort (AUC. 0.846 (0.811–0.882) vs. 0.815 (0.777–0.853), P = 0.001) and the validation cohort (AUC: 0.841 (0.804–0.877) vs. 0.808 (0.770–0.847), P = 0.001). The decision curves showed that the integrated model added more net benefit in predicting the incidence of AFDAS.ConclusionPredictive models based on clinical characteristics, laboratory variables, and neuroimaging variables showed good calibration and high net clinical benefit, informing clinical decision-making in diagnosing and treating patients with AFDAS.
Cross-sectional analysis of clinical aspects in patients with long-COVID and post-COVID syndrome
Authors: Schulze Hannah , Charles James Jeyanthan , Trampe Nadine , Richter Daniel , Pakeerathan Thivya , Siems Nadine , Ayzenberg Ilya , Gold Ralf , Faissner Simon 
Published: October 2022

ObjectiveRegarding pathogenesis, clinical manifestations, at-risk individuals, and diagnostic methods for stratifying patients for therapeutic approaches, our understanding of post-COVID syndrome is limited. Here, we set out to assess sociodemographic and clinical aspects in patients with the long-COVID and post-COVID syndrome.MethodsWe performed a cross-sectional analysis of patients presenting at our specialized university hospital outpatient clinic. We assessed patients' clinical presentation, fatigue, symptoms of depression and anxiety, and impairment of smell.ResultsA total of 101 patients were included (73.3% female), of whom 78.2% had a mild course of COVID-19. At presentation, 93.1% suffered from fatigue, 82.2% from impaired concentration, and 79.2% from impaired memory, 53.5% had impaired sleep. The most common secondary diagnosis found in our cohort was thyroid disease. Fatigue analysis showed that 81.3% of female and 58.8% of male patients had severe combined fatigue. Female gender was an independent risk factor for severe fatigue (severe cognitive fatigue OR = 8.045, p = 0.010; severe motor fatigue OR = 7.698, p = 0.013). Males suffered from more depressive symptoms, which correlated positively with the duration of symptom onset. 70.3% of patients with anamnestic smell impairment had hyposmia, and 18.9% were anosmic.InterpretationMost long-COVID patients suffered from severe fatigue, with the female sex as an independent risk factor. Fatigue was not associated with symptoms of depression or anxiety. Patients with long-COVID symptoms should receive an interdisciplinary diagnostic and therapeutic approach depending on the clinical presentation.
Clinical implementation of artificial intelligence in neuroradiology with development of a novel workflow-efficient picture archiving and communication system-based automated brain tumor segmentation and radiomic feature extraction
Authors: Aboian Mariam , Bousabarah Khaled , Kazarian Eve , Zeevi Tal , Holler Wolfgang , Merkaj Sara , Cassinelli Petersen Gabriel , Bahar Ryan , Subramanian Harry , Sunku Pranay , Schrickel Elizabeth , Bhawnani Jitendra , Zawalich Mathew , Mahajan Amit , Malhotra Ajay , Payabvash Sam , Tocino Irena , Lin MingDe , Westerhoff Malte 
Published: October 2022

PurposePersonalized interpretation of medical images is critical for optimum patient care, but current tools available to physicians to perform quantitative analysis of patient’s medical images in real time are significantly limited. In this work, we describe a novel platform within PACS for volumetric analysis of images and thus development of large expert annotated datasets in parallel with radiologist performing the reading that are critically needed for development of clinically meaningful AI algorithms. Specifically, we implemented a deep learning-based algorithm for automated brain tumor segmentation and radiomics extraction, and embedded it into PACS to accelerate a supervised, end-to- end workflow for image annotation and radiomic feature extraction.Materials and methodsAn algorithm was trained to segment whole primary brain tumors on FLAIR images from multi-institutional glioma BraTS 2021 dataset. Algorithm was validated using internal dataset from Yale New Haven Health (YHHH) and compared (by Dice similarity coefficient [DSC]) to radiologist manual segmentation. A UNETR deep-learning was embedded into Visage 7 (Visage Imaging, Inc., San Diego, CA, United States) diagnostic workstation. The automatically segmented brain tumor was pliable for manual modification. PyRadiomics (Harvard Medical School, Boston, MA) was natively embedded into Visage 7 for feature extraction from the brain tumor segmentations.ResultsUNETR brain tumor segmentation took on average 4 s and the median DSC was 86%, which is similar to published literature but lower than the RSNA ASNR MICCAI BRATS challenge 2021. Finally, extraction of 106 radiomic features within PACS took on average 5.8 ± 0.01 s. The extracted radiomic features did not vary over time of extraction or whether they were extracted within PACS or outside of PACS. The ability to perform segmentation and feature extraction before radiologist opens the study was made available in the workflow. Opening the study in PACS, allows the radiologists to verify the segmentation and thus annotate the study.ConclusionIntegration of image processing algorithms for tumor auto-segmentation and feature extraction into PACS allows curation of large datasets of annotated medical images and can accelerate translation of research into development of personalized medicine applications in the clinic. The ability to use familiar clinical tools to revise the AI segmentations and natively embedding the segmentation and radiomic feature extraction tools on the diagnostic workstation accelerates the process to generate ground-truth data.