bluuebunny/crossref_metadata_2025_split huggingface dataset:
MacroH2A restricts melanoma progression via inhibition of inflammatory gene expression in cancer-associated fibroblasts
Authors: Filipescu Dan , Hasson Dan , Tung Navpreet , Carcamo Saul , Humblin Etienne , Goldberg Matthew , Vyas Nikki , Beaumont Kristin , Ghiraldini Flavia , Salmon Helene , Sebra Robert , Kamphorst Alice , Merad Miriam , Bernstein Emily 
Published: May 2022

Abstract
The histone variant macroH2A has been implicated as a tumor suppressor in melanoma and other cancers, yet its role in the tumor microenvironment remains unappreciated. Using an autochthonous, immunocompetent mouse model of melanoma, we demonstrate that mice devoid of macroH2A exhibit increased tumor burden compared to wild type counterparts. MacroH2A-deficient tumors display an accumulation of immunosuppressive monocytes and decreased functional cytotoxic T cells, and consistent with this compromised anti-tumor response, exhibit upregulation of pro-inflammatory cytokines including Ccl2, Cxcl1 and Il6. Through single cell transcriptomics of the entire melanoma microenvironment, we identify the source of these pro-tumor myeloid chemoattractants as cancer-associated fibroblasts (CAFs), whose frequency and activation increase in the absence of macroH2A. Furthermore, cytokine genes in CAFs lacking macroH2A are hyper-inducible and their regulatory elements present an altered epigenetic landscape. In sum, we reveal a tumor suppressive role for macroH2A variants through repression of inflammatory gene induction in the tumor stroma.
Interventional continuous negative pressure drainage for bronchopleural fistula: case series and literature review
Authors: Li Xiaobing , Wang Shuai , Liu Chao , Huang Lisha , Ni Ran , Li Xiangnan , Qi Yu , Yin Meipan , Ma Yaozhen , Zhu Ming , Wu Gang 
Published: May 2022

Abstract
Background: Bronchopleural fistula (BPF) is a serious complication of pulmonary resection. The purpose of this study was to evaluate the safety and efficacy of interventional continuous negative pressure drainage (CNPD) in the treatment of post-lobectomy bronchopleural fistula complicated by hydropneumothorax.Methods: A retrospective analysis of patients with BPF complicated by hydropneumothorax who underwent interventional CNPD was performed, in addition to a review of the literature. This study was registered in China clinical trial registry (Registration No.: chictr-ooc-15006036).Results: Among the 5 patients included, the one-time success rate of drainage catheter placement was 100%. No complications such as hemoptysis, hemothorax and asphyxia were reported. The patients' pneumonia severity index score significantly decreased from 99.8 ± 8.90 pre-intervention to 69.8 ± 14.03 three to seven days post-intervention (P < 0.001), with significant improvement and resolution of chest tightness, dyspnea and fever. The average indwelling time was 149.8 ± 56.059 days (95% CI: 39.72 –259.48).Conclusion: Interventional CNPD is minimally invasive, accurate and effective, allowing for rapid lung re-expansion, residual cavity elimination, and symptomatic relief. It thereby carries the potential as a novel treatment for BPF.
Evaluating keystroke dynamics as a biomarker for mental fatigue detection
Authors: Arroyo-Gallego Teresa , Ayala Alejandro Acien , Morales Aythami , Vera-Rodriguez Ruben , Fierrez Julian , Mondesire-Crump Ijah 
Published: May 2022

Abstract
In this paper we study the feasibility of employing keystroke biometrics for mental fatigue detection during natural typing. For this task, we employ TypeNet, a state-of-the-art deep neuronal network, originally intended for user authentication at large scale using keystroke dynamics. We adapted TypeNet for fatigue detection by leveraging the information embedded in TypeNet for person recognition, and applying that information to a different but related task as it is fatigue detection by employing domain adaptation techniques. All experiments were conducted using three keystroke databases that comprise different contexts and data collection protocols. Our preliminary results showed performances ranging between 72.2% and 80.0% for fatigue versus rested sample classification, which is aligned with previously published models on daily alertness and circadian cycles. This demonstrates the potential of our proposed system to characterize mental fatigue fluctuations via natural typing patterns. Finally, we studied the feasibility of an active detection approach that utilizes the continuous monitoring of keystroke biometric patterns for the real-time assessment of subject fatigue.
SARS-CoV-2 and its variants, but not Omicron, induces severe thymic atrophy and impaired T cell development
Authors: Rizvi Zaigham , Sadhu Srikanth , Dandotiya Jyotsna , Binayke Akshay , Sharma Puja , Singha Virendra , Das Vinayaka , Khatri Ritika , Kumar Rajesh , Samal Sweety , Kalia Manjula , Awasthi Amit 
Published: May 2022

Abstract
Pathogenic infections cause thymic atrophy, perturb thymic-T cell development and alter immunological response. Previous studies reported dysregulated T cell function and lymphopenia in coronavirus disease-19 (COVID-19) patients. However, immune-pathological changes, in the thymus, post severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection have not been elucidated. Here, we report SARS-CoV-2 infects thymocytes, depletes CD4 + CD8+ (double positive; DP) T cell population associated with an increased apoptosis of thymocytes, which leads to severe thymic atrophy in K18-hACE2-Tg mice. CD44 + CD25- T cells were found to be enriched in infected thymus, indicating an early arrest in the T cell developmental pathway. Further, Interferon gamma (IFN-γ) was crucial for thymic atrophy, as anti-IFN-g antibody neutralization rescued the loss of thymic involution. Therapeutic use of remdesivir (prototype anti-viral drug) was also able to rescue thymic atrophy. While Omicron variant of SARS-CoV2 caused marginal thymic atrophy, delta variant of SARS-CoV-2 exhibited most profound thymic atrophy characterized by severely depleted DP T cells. Recently characterized broadly SARS-CoV-2 neutralizing monoclonal antibody P4A2 was able to rescue thymic atrophy and restore thymic developmental pathway of T cells. Together, we provide the first report of SARS-CoV-2 associated thymic atrophy resulting from impaired T cell developmental pathway and also explains dysregulated T cell function in COVID-19.
First clinical application of cord blood mesenchymal stromal cells in children with multi-drug resistant nephrotic syndrome.
Authors: Morello William , Budelli Silvia , Bernstein Daniel Ari , Montemurro Tiziana , Montelatici Elisa , Lavazza Cristiana , Ghio Luciana , Edefonti Alberto , Peruzzi Licia , Molino Daniela , Benetti Elisa , Gianoglio Bruno , Mehmeti Florian , Catenacci Laura , Rotella Jessica , Tamburello Chiara , Moretta Antonia , Lazzari Lorenza , Giordano Rosaria , Montini Giovanni 
Published: May 2022

Abstract
Background and objectives. Children with multi-drug resistant idiopathic nephrotic syndrome (MDR-INS) usually progress to end-stage kidney disease with a consistent risk of disease recurrence after transplantation. New therapeutic options are needed for these patients. Mesenchymal stromal cells (MSCs) are multipotential non-hematopoietic cells with several immunomodulatory properties and growing clinical applications. Cord blood-derived MSC have peculiar anti-inflammatory and immunosuppressive properties.We aimed at assessing safety and efficacy of cord-blood derived MSCs (CB-MSCs) in children with MDR-INS.Design, setting, participants. Prospective, open-label, single arm phase I-II pilot study. Pediatric patients with MDR-INS, resistant to at least two lines of therapy, were enrolled. Allogenic CB-MSCs were administered intravenously on days 0, 14, and 21 at a dose of 1.5 x 106 cells/kg. Patients were followed for at least 12 months. The primary outcomes were safety and toxicity. The secondary outcome was remission at 12 months evaluated by urinary protein/urinary creatinine ratio (uPr/uCr). Circulating regulatory T cells (Tregs) were monitored.Results. Eleven pediatric patients with MDR-INS (10 females, median age 13 years) resistant to a median of 3 previous lines of therapy were enrolled. All patients completed the CB-MSC infusion schedule. No patient experienced any infusion-related adverse event or toxicity.Nine patients were assessable for efficacy. At the 12 months follow-up after the treatment, the median uPr/uCr did not change significantly from baseline (8.13 vs 9.07; p = 0.98), while 3 patients were in partial or complete remission. A lower baseline uPr/uCr was a predictor of remission (2.55 vs 8.74; p = 0.0238). Tregs count was not associated with CB-MSCs therapy.Conclusions CB-MSCs are safe and may have a role in the immunosuppressive therapy of pediatric patients with MDR-INS. This preliminary experience paves the way towards further phase II studies addressing MSC efficacy in immune mediated kidney diseases.
Effects of a comprehensive brain computed tomography deep-learning model on radiologist detection accuracy: a multireader, multicase study
Authors: Buchlak Quinlan , Tang Cyril , Seah Jarrel , Johnson Andrew , Holt Xavier , Bottrell Georgina , Wardman Jeffrey , Samarasinghe Gihan , Pinheiro Leonardo , Xia Hongze , Ahmad Hassan , Pham Hung , Chiang Jason , Ektas Nalan , Milne Michael , Chiu Christopher , Hachey Ben , Ryan Melissa , Johnston Benjamin , Esmaili Nazanin , Bennett Christine , Goldschlager Tony , Hall Jonathan , Vo Duc Tan , Oakden-Rayner Lauren , Leveque Jean-Christophe , Farrokhi Farrokh , Jones Catherine , Edelstein Simon , Brotchie Peter 
Published: May 2022

Abstract
Background: Non-contrast computed tomography of the brain (NCCTB) is commonly used in clinical practice to detect intracranial pathology but is subject to interpretation errors. Machine learning is capable of augmenting clinical decision making and there is an opportunity to apply deep learning to improve the clinical interpretation of NCCTB scans. This retrospective detection accuracy study assessed the performance changes of radiologists assisted by a deep learning model designed to identify many NCCTB clinical findings and also compared the standalone performance of the model with that of unassisted radiologists. Methods: A deep learning model was trained on 212,484 CT scan images of the brain. Thirty-two radiologists each reviewed 2,848 NCCTB cases in a test dataset with and without the assistance of the deep learning model. The consensus of three subspecialist neuroradiologists with access to reports and clinical history was used as a ground truth baseline for comparison. Performance metrics including area under the receiver operating characteristic curve (AUC) were calculated for the unassisted and assisted radiologists. Average assisted and unassisted radiologist performance was also compared to that of the model for each clinical finding. Findings: Use of the deep learning model by radiologists significantly improved interpretation performance. Assisted and unassisted radiologists demonstrated an average AUC of 0.79 and 0.73 across the 22 grouped parent findings and 0.72 and 0.68 across all 189 child findings combined, respectively. When the model was used as an assistant, change in radiologist AUC was positive and significant for 91 child findings and 158 findings were clinically non-inferior. AUC decrements were identified for 17 findings. The model alone demonstrated an average AUC of 0.93 across all 144 model findings. Interpretation: The assistance of a comprehensive NCCTB deep learning model in a non-clinical setting significantly improved radiologist detection accuracy across a wide range of clinical findings. This study demonstrated the potential of the evaluated model to improve NCCTB interpretation.
HDR Image-Based Deep Learning Approach for Automatic Detection of Split Defects on Sheet Metal Stamping Parts
Authors: Singh Aru Ranjan , Bashford-Rogers Thomas , Marnerides Demetris , Debattista Kurt , Hazra Sumit 
Published: May 2022

Abstract
Sheet metal stamping is widely used for high-volume production. Despite the wide adoption, it can lead to defects in the manufactured components, making their quality unacceptable. Because of the variety of defects that can occur on the final product, human inspectors are frequently employed to detect them. However, they can be unreliable and costly, particularly at speeds that match the stamping rate. In this paper, we propose an automatic inspection framework for the stamping process that is based on computer vision and deep learning techniques. The low cost, remote sensing capability and simple implementation mean that it can be easily deployed in an industrial setting. A particular focus of the framework is to account for the harsh lighting conditions found in manufacturing environments that affect optical sensing techniques by making it difficult to capture the details of a scene. To test the framework, sheet metal ’Nakajima’ samples were manufactured with an industrial stamping press. Then optimally exposed, sequence of exposures, tone-mapped and high-dynamic-range images of the samples were used to train convolutional neural network based detectors. Analysis of the resulting models showed that HDR-based models achieved substantially higher accuracy and minimal false-positive predictions.
Retrospective evaluation of CT-head scans for the association between posterior atlanto-occipital membrane ossification with cervicogenic headache and migraine
Authors: Sudip Kumar , Patil Utkarsh Chandrakant , Wasadikar Anajli Pravinkumar 
Published: May 2022

Abstract
Purpose- The objective of the study was to find the prevalence of arcuate foramen and its association with cervicogenic headache and migraine. To study various demographic parameters associated with the anomaly and to correlate the extent of ossification of posterior atlanto-occipital membrane with the severity of symptoms. Methods- A cross sectional study was done to analyze CT-head scans of patients with cervicogenic headache and migraine for the presence of arcuate foramen. Demographic parameters of the patients were collected from the detailed case report from achieves. The collected data was analyzed using SPSS, a p-value of <0.05 were considered significant. Results- Arcuate foramen was prevalent in 41.8% of symptomatic patients. No significant association between the incidence of arcuate foramen and age group was found. Incidence is increased incidence among the male patients (61%). Patients who are labourer by occupation showed increased incidence (34.78%). A positive correlation (0.755) was found between the extent of ossification and the severity of clinical symptoms. The foramen was more commonly found on the left side and majority of patients presented with unilateral anomaly (27.27%). Conclusion- Arcuate foramen is fairly prevalent among the symptomatic patients and is often neglected as an etiologic agent and leads delay in diagnosis and management. It can lead to injury to vertebral artery during screw placement if misidentified as broad posterior arch. Therefore, it must be screened in symptomatic patients and those patients undergoing lateral neck surgery using lateral cephalogram, if detected must be documented on health records of the patient.
Serum Lactate Monitoring Predict Neurological Function Impairment Caused by Acute Metabolism Crisis
Authors: Liu Dandan , Li Guanggang , Yao Qing , Song Bin , Sun Yue , Ju Hongyan 
Published: May 2022

Abstract
Objective: To investigate the predictive value of the serum lactate on neurological function impairment attributed to acute metabolism crisis (ACMC) .Methods: In this retrospective study, all the adult patients admitted to ICU more than 24h after general anesthesia elective neurosurgery from January 2018 to January 2019 were recruited. The data of the serum lactate every 8 h during the 24 h of ICU admission were acquired and analyzed.Results: 169 patients were included in the outcomes analysis. The average serum lactate after ICU admission was (3.7(0.7), mmol/L), higher than normal, suggesting that ACMC commonly existed. The serum lactate at ICU admission (lactateserum0h) was not correlated with the outcomes,but the predictive value increased with the extension of the monitoring time. The lactateserum8h, the lactateserum16h and the lactateserum24h were found to be associated with the primary outcome(difference of GCS scores before the surgery and after 24 h of ICU admission (ΔGCS24h)(p<0.05). The lactateserum16h and the lactateserum 24h were associated with all the outcomes except the hospital LOS. The ROC curve revealed that the lactateserum24h had the best predictive value. The graph of the dynamic changes of the serum lactate indicated that patients with serum lactate non-recovered trend after 24 h of ICU stay had decreased GCS scores, and vice versa. To find an index predicting ACMC earlier, the predictive value of the serum glucose/serum lactate ratio at ICU admission (G/Lserum) was analyzed and found to be associated with the ΔGCS24h(p<0.05), the G/Lserum can predict the ACMC earlier.Conclusions: Dynamic serum lactate monitoring and the G/Lserum at ICU admission have predictive value on neurological function impairment attributed to ACMC.
Efficacy of Enzalutamide for Patients with Castration-Resistant Prostate Cancer in Real-World Clinical Practice: A Retrospective Single Institutional Analysis with 5-Year Follow-up
Authors: Taniguchi Hisanori , Yanishi Masaaki , Saito Ryoichi , Kinoshita Hidefumi 
Published: May 2022

Abstract
Background
Enzalutamide’s efficacy and prognosis for patients with castration-resistant prostate cancer (CRPC) in real-world clinical practice have not been sufficiently examined.
Methods
We retrospectively investigated data on 135 consecutive CRPC patients who had received enzalutamide. Prostate-specific antigen (PSA) response ( > = 50% PSA decline from baseline), progression-free survival (PFS), overall survival (OS), and poor prognostic factors related to PFS and OS were analyzed.
Results
The median follow-up period was 63 months. Of all, 46 cases were post-chemo, 90 were metastatic, and 38 were prior-abiraterone acetate use. PSA responses were observed in 55.6% of patients, and no statistically significant differences between chemo-naive and post-chemo groups were noted. The median PFS of all CRPC patients was 301 days (95% CI, 239–363); in patients with prior abiraterone acetate use, PFS was shorter than the others (HR 0.56, 95% CI, 0.36–0.83, p = 0.010). Median OS from initiation of enzalutamide was 790 days and shorter in patients in the post-chemo and metastatic groups. On the other hand, the median OS from CRPC diagnosis was 1514 days and shorter only in the metastatic group (HR 0.44, 95% CI, 0.19–1.01, p = 0.0052). In multivariate analysis, the time between androgen deprivation therapy (ADT) initiation and CRPC diagnosis being < 20 months (i.e., time to CRPC < 20 mo.), prior-docetaxel use, and prior-abiraterone acetate use were risk factors for shorter PFS. Time to CRPC < 20 mo. and prior-docetaxel use were factors influencing shorter OS from initiation of enzalutamide, and only time to CRPC < 20 mo. was related to shorter OS from CRPC diagnosis.
Conclusions
This study revealed the efficacy of enzalutamide for CRPC patients in a real-world clinical setting. We could use enzalutamide at any time during CRPC treatment. These findings are valuable for clinical decision-making during CRPC patients’ treatment.
Cross-calibration of two dual-energy X-ray absorptiometry devices for the measurement of body composition in young children
Authors: Lyons-Reid Jaz , Kenealy Timothy , Albert Benjamin B. , Ward Kate A. , Harvey Nicholas , Godfrey Keith M. , Chan Shiao-Yng , Cutfield Wayne S. 
Published: May 2022

Abstract
Objectives: To cross-calibrate body composition measures from the GE Lunar Prodigy and GE Lunar iDXA in a cohort of young children. Methods: 28 children (mean age 3.4 years) were measured on the iDXA followed by the Prodigy. Prodigy scans were subsequently reanalysed using enCORE v17 enhanced analysis (“Prodigy enhanced”). Body composition parameters were compared across three measurement conditions (Prodigy, Prodigy enhanced, iDXA), and adjustment equations were developed. Results: There were significant differences in the three measurement conditions for all body composition parameters. Body fat percentage (%BF) from the iDXA was approximately 1.5-fold greater than the Prodigy, whereas bone mineral density (BMD) was approximately 20% lower. Reanalysis of Prodigy scans with enhanced software attenuated these differences (%BF: -2.7% [95% CI: -3.5, -1.9]; and BMD: 1.0% [95% CI: 0.0, 1.9]), although significant differences remained for all parameters except total body less head (TBLH) total mass and TBLH BMD, and some regional estimates. Conclusions: There were large differences between the Prodigy and iDXA, with these differences related both to scan resolution and software. Reanalysis of Prodigy scans with enhanced analysis resulted in body composition values much closer to those obtained on the iDXA, although differences remained. As manufacturers update models and software, researchers and clinicians need to be aware of the impact this may have on the longitudinal assessment of body composition, as results may not be comparable across devices and software versions.
Modelling and Planning Operation of Directly Coupled Solar PV Pump Operated Drip Irrigation System
Authors: HADOLE MAHESH Vinayak , Bajpai Prabodh , Tiwari Kamlesh Narayan 
Published: May 2022

Abstract
A dynamic simulation model of a directly coupled solar photovoltaic (SPV) pump operated drip irrigation (DI) system is presented in this study. The model is applied for preparing a plan of DI system operation to meet the irrigation schedule of the Okra crop considered in the case study. The fundamental mathematical expressions of the SPV array, variable frequency drive, submersible pump, and DI system are used to create a general model in the Matlab/Simulink. The hourly solar irradiation, temperature, and groundwater level are input parameters to the model. The SPV power output, pump discharge and pressure head, and emitter discharges are simulated on hourly basis. The simulated values of these parameters for the same time period are compared with the measured values to assess the model’s accuracy. The simulation accuracy of the model is tested using statistical indicators such as model efficiency (ME), coefficient of residual mass (CRM), root mean square error (RMSE), and normalized mean absolute error (NMAE). The higher ME values (close to 1) and lower NMAE and RMSE values indicated that the simulation model outputs are fairly accurate and within acceptable limits. The negative values of CRM indicate the model’s over-prediction tendency. However, the degree of over-prediction is minimal. The results indicated that the developed simulation model is capable of accurately predicting the system parameters. The developed simulation model is applied in a case study to operate different subunit manifolds of DI system installed in an Okra crop field of 1.2 ha. Based on the simulation results an additional area of 0.19 ha Okra crop can be brought under irrigation using the same SPV powered pumping system. A plan of operation of different sub-main manifolds of DI system are prepared using the simulation model for Okra crop. Similarly, the developed model can be applied to any SPV pump integrated DI system to evaluate and prepare the plan of operation of different sub-main manifolds in the field, thereby effective utilization of energy and water, which is the novelty of this study.