bluuebunny/crossref_metadata_2025_split huggingface dataset:
Large airway T cells in adults with former bronchopulmonary dysplasia
Authors: Gao Jing , Um-Bergström Petra , Pourbazargan Melvin , Berggren-Broström Eva , Li ChuanXing , Merikallio Heta , Kaarteenaho Riitta , Reinke Nichole Stacey , Wheelock Craig E , Melén Erik , Anders Lindén , Wheelock Åsa M , Rassidakis Georgios , Ortiz-Villalon Cristian , Sköld Magnus Carl 
Published: February 2024

Abstract
Background
Bronchopulmonary Dysplasia (BPD) in infants born prematurely is a risk factor for chronic airway obstruction later in life. The distribution of T cell subtypes in the large airways is largely unknown.

Objective
To characterize cellular and T cell profiles in the large airways of young adults with a history of BPD.

Methods
Forty-three young adults born prematurely (preterm (n = 20), BPD (n = 23)) and 45 full-term-born (asthma (n = 23), healthy (n = 22)) underwent lung function measurements, and bronchoscopy with large airway bronchial wash (BW). T-cells subsets in BW were analyzed by immunocytochemistry.

Results
The proportions of both lymphocytes and CD8 + T cells in BW were significantly higher in BPD (median, 6.6%, and 78.0%) when compared with asthma (3.4% and 67.8%, p = 0.002 and p = 0.040) and healthy (3.8% and 40%, p < 0.001 and p < 0.001). In all adults born prematurely (preterm and BPD), lymphocyte proportion correlated negatively with forced vital capacity (r= -0.324, p = 0.036) and CD8 + T cells correlated with forced expiratory volume in one second, FEV1 (r=-0.448, p = 0.048). Correlation-based network analysis revealed that lung function cluster and BPD-birth cluster were associated with lymphocytes and/or CD4 + and CD8 + T cells. Multivariate regression analysis showed that lymphocyte proportions and BPD severity qualified as independent factors associated with FEV1.

Conclusions
The increased cytotoxic T cells in the large airways in young adults with former BPD, suggest a similar T-cell subset pattern as in the small airways, resembling features of COPD. Our findings strengthen the hypothesis that mechanisms involving adaptive and innate immune responses are involved in the development of airway disease due to preterm birth.
Quantifying microbial robustness in dynamic environments using microfluidic single-cell cultivation
Authors: Blöbaum Luisa , Torello Pianale Luca , Olsson Lisbeth , Grünberger Alexander 
Published: February 2024

Abstract
Background
Microorganisms must respond to changes in their environment. Analysing the robustness of functions (i.e. performance stability) to such dynamic perturbations is of great interest in both laboratory and industrial settings. Recently, a quantification method capable of assessing the robustness of various functions, such as specific growth rate or product yield, across different conditions, time frames, and populations has been developed for microorganisms grown in a 96-well plate. In micro-titer-plates, environmental change is slow and undefined. Dynamic microfluidic single-cell cultivation (dMSCC) enables the precise maintenance and manipulation of microenvironments, while tracking single cells over time using live-cell imaging. Here, we combined dMSCC and a robustness quantification method to a pipeline for assessing performance stability to changes occurring within seconds or minutes.

Results
Saccharomyces cerevisiae CEN.PK113-7D, harbouring a biosensor for intracellular ATP levels, was exposed to glucose feast-starvation cycles, with each condition lasting from 1.5 to 48 min over a 20 h period. A semi-automated image and data analysis pipeline was developed and applied to assess the performance and robustness of various functions at population, subpopulation, and single-cell resolution. We observed a decrease in specific growth rate but an increase in intracellular ATP levels with longer oscillation intervals. Cells subjected to 48 min oscillations exhibited the highest average ATP content, but the lowest stability over time and the highest heterogeneity within the population.

Conclusion
The proposed pipeline enabled the investigation of function stability in dynamic environments, both over time and within populations. The strategy allows for parallelisation and automation, and is easily adaptable to new organisms, biosensors, cultivation conditions, and oscillation frequencies. Insights on the microbial response to changing environments will guide strain development and bioprocess optimisation.

Graphical Abstract
Melanoma biology and treatment: a review of novel regulated cell death-based approaches
Authors: Hsieh Ming-yun , Hsu Sheng-Kai , Liu Tzu-Yu , Wu Chang-Yi , Chiu Chien-Chih 
Published: February 2024

AbstractThe incidence of melanoma, the most lethal form of skin cancer, has increased due to ultraviolet exposure. The treatment of advanced melanoma, particularly metastatic cases, remains challenging with poor outcomes. Targeted therapies involving BRAF/MEK inhibitors and immunotherapy based on anti-PD1/anti-CTLA4 antibodies have achieved long-term survival rates of approximately 50% for patients with advanced melanoma. However, therapy resistance and inadequate treatment response continue to hinder further breakthroughs in treatments that increase survival rates. This review provides an introduction to the molecular-level pathogenesis of melanoma and offers an overview of current treatment options and their limitations. Cells can die by either accidental or regulated cell death (RCD). RCD is an orderly cell death controlled by a variety of macromolecules to maintain the stability of the internal environment. Since the uncontrolled proliferation of tumor cells requires evasion of RCD programs, inducing the RCD of melanoma cells may be a treatment strategy. This review summarizes studies on various types of nonapoptotic RCDs, such as autophagy-dependent cell death, necroptosis, ferroptosis, pyroptosis, and the recently discovered cuproptosis, in the context of melanoma. The relationships between these RCDs and melanoma are examined, and the interplay between these RCDs and immunotherapy or targeted therapy in patients with melanoma is discussed. Given the findings demonstrating melanoma cell death in response to different stimuli associated with these RCDs, the induction of RCD shows promise as an integral component of treatment strategies for melanoma.
NY-ESO-1-specific T cell receptor-engineered T cells and Tranilast, a TRPV2 antagonist bivalent treatment enhances the killing of esophageal cancer: a dual-targeted cancer therapeutic route
Authors: Amissah Obed Boadi , Chen Wenfang , de Dieu Habimana Jean , Sun Yirong , Lin Lihui , Liu Yujie , Wang Ling , Liu Zhaoming , Mukama Omar , Basnet Rajesh , Liu Hohua , Li Junyi , Ding Xuanyan , Lv Lingshuang , Chen Min , Liang Yalin , Huang Rongqi , Li Zhiyuan 
Published: February 2024

Abstract
Background
Esophageal cancer (EC) is a global canker notorious for causing high mortality due to its relentless incidence rate, convoluted with unyielding recurrence and metastasis. However, these intricacies of EC are associated with an immoderate expression of NY-ESO-1 antigen, presenting a lifeline for adoptive T cell therapy. We hypothesized that naturally isolated higher-affinity T cell receptors (TCRs) that bind to NY-ESO-1 would allow T lymphocytes to target EC with a pronounced antitumor response efficacy. Also, targeting TRPV2, which is associated with tumorigenesis in EC, creates an avenue for dual-targeted therapy. We exploited the dual-targeting antitumor efficacy against EC.

Methods
We isolated antigen-specific TCRs (asTCRs) from a naive library constructed with TCRs obtained from enriched cytotoxic T lymphocytes. The robustness of our asTCRs and their TCR-T cell derivatives, Tranilast (TRPV2 inhibitor), and their bivalent treatment were evaluated with prospective cross-reactive human-peptide variants and tumor cells.

Results
Our study demonstrated that our naive unenhanced asTCRs and their TCR-Ts perpetuated their cognate HLA-A*02:01/NY-ESO-1(157–165) specificity, killing varying EC cells with higher cytotoxicity compared to the known affinity-enhanced TCR (TCRe) and its wild-type (TCR0) which targets the same NY-ESO-1 antigen. Furthermore, the TCR-Ts and Tranilast bivalent treatment showed superior EC killing compared to any of their monovalent treatments of either TCR-T or Tranilast.

Conclusion
Our findings suggest that dual-targeted immunotherapy may have a superior antitumor effect. Our study presents a technique to evolve novel, robust, timely therapeutic strategies and interventions for EC and other malignancies.
Deep neural networks for wearable sensor-based activity recognition in Parkinson’s disease: investigating generalizability and model complexity
Authors: Davidashvilly Shelly , Cardei Maria , Hssayeni Murtadha , Chi Christopher , Ghoraani Behnaz 
Published: February 2024

Abstract
Background
The research gap addressed in this study is the applicability of deep neural network (NN) models on wearable sensor data to recognize different activities performed by patients with Parkinson’s Disease (PwPD) and the generalizability of these models to PwPD using labeled healthy data.

Methods
The experiments were carried out utilizing three datasets containing wearable motion sensor readings on common activities of daily living. The collected readings were from two accelerometer sensors. PAMAP2 and MHEALTH are publicly available datasets collected from 10 and 9 healthy, young subjects, respectively. A private dataset of a similar nature collected from 14 PwPD patients was utilized as well. Deep NN models were implemented with varying levels of complexity to investigate the impact of data augmentation, manual axis reorientation, model complexity, and domain adaptation on activity recognition performance.

Results
A moderately complex model trained on the augmented PAMAP2 dataset and adapted to the Parkinson domain using domain adaptation achieved the best activity recognition performance with an accuracy of 73.02%, which was significantly higher than the accuracy of 63% reported in previous studies. The model’s F1 score of 49.79% significantly improved compared to the best cross-testing of 33.66% F1 score with only data augmentation and 2.88% F1 score without data augmentation or domain adaptation.

Conclusion
These findings suggest that deep NN models originating on healthy data have the potential to recognize activities performed by PwPD accurately and that data augmentation and domain adaptation can improve the generalizability of models in the healthy-to-PwPD transfer scenario. The simple/moderately complex architectures tested in this study could generalize better to the PwPD domain when trained on a healthy dataset compared to the most complex architectures used. The findings of this study could contribute to the development of accurate wearable-based activity monitoring solutions for PwPD, improving clinical decision-making and patient outcomes based on patient activity levels.
Individualized detection of TMPRSS2-ERG fusion status in prostate cancer: a rank-based qualitative transcriptome signature
Authors: Li Yawei , Su Hang , Liu Kaidong , Zhao Zhangxiang , Wang Yuquan , Chen Bo , Xia Jie , Yuan Huating , Huang De-Shuang , Gu Yunyan 
Published: February 2024

Abstract
Background
TMPRSS2-ERG (T2E) fusion is highly related to aggressive clinical features in prostate cancer (PC), which guides individual therapy. However, current fusion prediction tools lacked enough accuracy and biomarkers were unable to be applied to individuals across different platforms due to their quantitative nature. This study aims to identify a transcriptome signature to detect the T2E fusion status of PC at the individual level.

Methods
Based on 272 high-throughput mRNA expression profiles from the Sboner dataset, we developed a rank-based algorithm to identify a qualitative signature to detect T2E fusion in PC. The signature was validated in 1223 samples from three external datasets (Setlur, Clarissa, and TCGA).

Results
A signature, composed of five mRNAs coupled to ERG (five ERG-mRNA pairs, 5-ERG-mRPs), was developed to distinguish T2E fusion status in PC. 5-ERG-mRPs reached 84.56% accuracy in Sboner dataset, which was verified in Setlur dataset (n = 455, accuracy = 82.20%) and Clarissa dataset (n = 118, accuracy = 81.36%). Besides, for 495 samples from TCGA, two subtypes classified by 5-ERG-mRPs showed a higher level of significance in various T2E fusion features than subtypes obtained through current fusion prediction tools, such as STAR-Fusion.

Conclusions
Overall, 5-ERG-mRPs can robustly detect T2E fusion in PC at the individual level, which can be used on any gene measurement platform without specific normalization procedures. Hence, 5-ERG-mRPs may serve as an auxiliary tool for PC patient management.
Analysis of differences in intestinal flora associated with different BMI status in colorectal cancer patients
Authors: Huang Yongqi , Huang Xiaoliang , Wang Zhen , He Fuhai , Huang Zigui , Chen Chuanbin , Tang Binzhe , Qin Mingjian , Wu Yongzhi , Long Chenyan , Tang Weizhong , Mo Xianwei , Liu Jungang 
Published: February 2024

Abstract
Background
Overweight is known to be an important risk factor for colorectal cancer (CRC), and the differences in intestinal flora among CRC patients with different BMI status have not been clearly defined. The purpose of this study was to elucidate the differences in the abundance, composition and biological function of intestinal flora in CRC patients with different BMI status.

Method
A total of 170 CRC patients were included and grouped according to the BMI data of CRC patients. BMI ≥ 24 kg/m2 was defined as overweight group, and BMI within the range of 18.5–23.9 kg/m2 was defined as normal weight group. Preoperative stool collection of patients in both groups was used for 16S rRNA sequencing. Total RNA was extracted from 17 CRC tumor tissue samples for transcriptome sequencing, and then CIBERSORT algorithm was used to convert the transcriptome data into the relative content matrix of 22 kinds of immune cells, and the correlation between different intestinal flora and immune cells and immune-related genes under different BMI states was analyzed. Finally, we identified BMI-related differential functional pathways and analyzed the correlation between these pathways and differential intestinal flora.

Result
There was no significant difference in α diversity and β diversity analysis between overweight group and normal weight group. Partial least square discriminant analysis (PLS-DA) could divide the flora into two different clusters according to BMI stratification. A total of 33 BMI-related differential flora were identified by linear discriminant effect size analysis (LEfSe), among which Actinomyces, Desulfovibrio and Bacteroides were significantly enriched in overweight group. ko00514: Other types of O-glycan biosynthesis are significantly enriched in overweight group. There was a significant positive correlation between Clostridium IV and Macrophages M2 and T cells regulatory (Tregs). There was a significant negative correlation with Dendritic cells activated and T cells CD4 memory activated.

Conclusions
The richness and diversity of intestinal flora of CRC patients may be related to different BMI status, and the enrichment of Actinomyces, Desulphurvibrio and Bacteroides may be related to overweight status of CRC patients. The tumor microenvironment in which BMI-related differential flora resides has different immune landscapes, suggesting that some intestinal flora may affect the biological process of CRC by regulating immune cell infiltration and immune gene expression, but further experiments are needed to confirm this.
Enhanced molecular release from elderly bone samples using collagenase I: insights into fatty acid metabolism alterations
Authors: Malvandi Amir Mohammad , Halilaj Esra , Faraldi Martina , Mangiavini Laura , Cristoni Simone , Leoni Valerio , Lombardi Giovanni 
Published: February 2024

Abstract
Background
Bone is a metabolically active tissue containing different cell types acting as endocrine targets and effectors. Further, bone is a dynamic depot for calcium, phosphorous and other essential minerals. The tissue matrix is subjected to a constant turnover in response to mechanical/endocrine stimuli. Bone turnover demands high energy levels, making fatty acids a crucial source for the bone cells. However, the current understanding of bone cell metabolism is poor. This is partly due to bone matrix complexity and difficulty in small molecules extraction from bone samples. This study aimed to evaluate the effect of metabolite sequestering from a protein-dominated matrix to increase the quality and amount of metabolomics data in discovering small molecule patterns in pathological conditions.

Methods
Human bone samples were collected from 65 to 85 years old (the elderly age span) patients who underwent hip replacement surgery. Separated cortical and trabecular bone powders were treated with decalcifying, enzymatic (collagenase I and proteinase K) and solvent-based metabolite extraction protocols. The extracted mixtures were analyzed with the high-resolution mass spectrometry (HRMS). Data analysis was performed with XCMS and MetaboAnalystR packages.

Results
Fast enzymatic treatment of bone samples before solvent addition led to a significantly higher yield of metabolite extraction. Collagenase I and proteinase K rapid digestion showed more effectiveness in cortical and trabecular bone samples, with a significantly higher rate (2.2 folds) for collagenase I. Further analysis showed significant enrichment in pathways like de novo fatty acid biosynthesis, glycosphingolipid metabolism and fatty acid oxidation-peroxisome.

Conclusion
This work presents a novel approach for bone sample preparation for HRMS metabolomics. The disruption of bone matrix conformation at the molecular level helps the molecular release into the extracting solvent and, therefore, can lead to higher quality results and trustable biomarker discovery. Our results showed β-oxidation alteration in the aged bone sample. Future work covering more patients is worthy to identify the effective therapeutics to achieve healthy aging.
A 4D-CBCT correction network based on contrastive learning for dose calculation in lung cancer
Authors: Cao Nannan , Wang Ziyi , Ding Jiangyi , Zhang Heng , Zhang Sai , Gao Liugang , Sun Jiawei , Xie Kai , Ni Xinye 
Published: February 2024

Abstract
Objective
This study aimed to present a deep-learning network called contrastive learning-based cycle generative adversarial networks (CLCGAN) to mitigate streak artifacts and correct the CT value in four-dimensional cone beam computed tomography (4D-CBCT) for dose calculation in lung cancer patients.

Methods
4D-CBCT and 4D computed tomography (CT) of 20 patients with locally advanced non-small cell lung cancer were used to paired train the deep-learning model. The lung tumors were located in the right upper lobe, right lower lobe, left upper lobe, and left lower lobe, or in the mediastinum. Additionally, five patients to create 4D synthetic computed tomography (sCT) for test. Using the 4D-CT as the ground truth, the quality of the 4D-sCT images was evaluated by quantitative and qualitative assessment methods. The correction of CT values was evaluated holistically and locally. To further validate the accuracy of the dose calculations, we compared the dose distributions and calculations of 4D-CBCT and 4D-sCT with those of 4D-CT.

Results
The structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) of the 4D-sCT increased from 87% and 22.31 dB to 98% and 29.15 dB, respectively. Compared with cycle consistent generative adversarial networks, CLCGAN enhanced SSIM and PSNR by 1.1% (p < 0.01) and 0.42% (p < 0.01). Furthermore, CLCGAN significantly decreased the absolute mean differences of CT value in lungs, bones, and soft tissues. The dose calculation results revealed a significant improvement in 4D-sCT compared to 4D-CBCT. CLCGAN was the most accurate in dose calculations for left lung (V5Gy), right lung (V5Gy), right lung (V20Gy), PTV (D98%), and spinal cord (D2%), with the relative dose difference were reduced by 6.84%, 3.84%, 1.46%, 0.86%, 3.32% compared to 4D-CBCT.

Conclusions
Based on the satisfactory results obtained in terms of image quality, CT value measurement, it can be concluded that CLCGAN-based corrected 4D-CBCT can be utilized for dose calculation in lung cancer.
Pectoral muscle mass is not a robust prognostic factor for survival after left ventricular assist device (LVAD) implantation
Authors: Jenkins Freya Sophie , Minol Jan-Philipp , Akar Tarik , Yilmaz Esma , Immohr Moritz Benjamin , Dalyanoglu Ismail , Korbmacher Bernhard , Aissa Joel , Boeken Udo , Lichtenberg Artur , Akhyari Payam , Dalyanoglu Hannan 
Published: February 2024

Abstract
Background
Left ventricular assist devices (LVAD) are an established treatment for end-stage left ventricular heart failure. Parameters are needed to identify the most appropriate patients for LVADs. This study aimed to evaluate pectoral muscle mass and density as prognostic parameters.

Methods
This single-center study included all patients with LVAD implantation between January 2010 and October 2017 and a preoperative chest CT scan. Pectoral muscle mass was assessed using the Pectoralis Muscle Index (PMI, surface area indexed to height, cm2/m2) and pectoral muscle density by Hounsfield Units (HU). Overall mortality was analyzed with Kaplan–Meier survival analysis and 1-year and 3-year mortality with receiver operating characteristic (ROC) curves and Cox regression models.

Results
57 patients (89.5% male, mean age 57.8 years) were included. 64.9% of patients had end-stage left ventricular failure due to ischemic heart disease and 35.1% due to dilated cardiomyopathy. 49.2% of patients had preoperative INTERMACS profile of 1 or 2 and 33.3% received mechanical circulatory support prior to LVAD implantation. Total mean PMI was 4.7 cm2/m2 (± 1.6), overall HU of the major pectoral muscle was 39.0 (± 14.9) and of the minor pectoral muscle 37.1 (± 16.6). Mean follow-up was 2.8 years (± 0.2). Mortality rates were 37.5% at 1 year and 48.0% at 3 years. Neither PMI nor HU were significantly associated with overall mortality at 1-year or 3-year.

Conclusions
The results of our study do not confirm the association between higher pectoral muscle mass and better survival after LVAD implantation previously described in the literature.