bluuebunny/crossref_metadata_2025_split huggingface dataset:
ZEB1 transcription factor promotes immune escape in melanoma
Authors: Plaschka Maud , Benboubker Valentin , Grimont Maxime , Berthet Justine , Tonon Laurie , Lopez Jonathan , Le-Bouar Myrtille , Balme Brigitte , Tondeur Garance , de la Fouchardière Arnaud , Larue Lionel , Puisieux Alain , Grinberg-Bleyer Yenkel , Bendriss-Vermare Nathalie , Dubois Bertrand , Caux Christophe , Dalle Stéphane , Caramel Julie 
Published: March 2022

BackgroundThe efficacy of immunotherapies in metastatic melanoma depends on a robust T cell infiltration. Oncogenic alterations of tumor cells have been associated to T cell exclusion. Identifying novel cancer cell-intrinsic non-genetic mechanisms of immune escape, the targeting of which would reinstate T cell recruitment, would allow to restore the response to anti-programmed cell death protein 1 (PD-1) antibody therapy. The epithelial-to-mesenchymal transition (EMT)-inducing transcription factor ZEB1 is a major regulator of melanoma cell plasticity, driving resistance to mitogen-activated protein kinase (MAPK) targeted therapies. We thus wondered whether ZEB1 signaling in melanoma cells may promote immune evasion and resistance to immunotherapy.MethodsWe evaluated the putative correlation between ZEB1 expression in melanoma cells and the composition of the immune infiltrate in a cohort of 60 human melanoma samples by combining transcriptomic (RNA-sequencing) and seven-color spatial multi-immunofluorescence analyses. Algorithm-based spatial reconstitution of tumors allowed the quantification of CD8+, CD4+T cells number and their activation state (PD-1, Ki67). ZEB1 gain-of-function or loss-of-function approaches were then implemented in syngeneic melanoma mouse models, followed by monitoring of tumor growth, quantification of immune cell populations frequency and function by flow cytometry, cytokines secretion by multiplex analyses. Chromatin-immunoprecipitation was used to demonstrate the direct binding of this transcription factor on the promoters of cytokine-encoding genes. Finally, the sensitivity to anti-PD-1 antibody therapy upon ZEB1 gain-of-function or loss-of-function was evaluated.ResultsCombined spatial and transcriptomic analyses of the immune infiltrates in human melanoma samples demonstrated that ZEB1 expression in melanoma cells is associated with decreased CD8+T cell infiltration, independently of β-catenin pathway activation. ZEB1 ectopic expression in melanoma cells impairs CD8+T cell recruitment in syngeneic mouse models, resulting in tumor immune evasion and resistance to immune checkpoint blockade. Mechanistically, we demonstrate that ZEB1 directly represses the secretion of T cell-attracting chemokines, including CXCL10. Finally,Zeb1knock-out, by promoting CD8+T cell infiltration, synergizes with anti-PD-1 antibody therapy in promoting tumor regression.ConclusionsWe identify the ZEB1 transcription factor as a key determinant of melanoma immune escape, highlighting a previously unknown therapeutic target to increase efficacy of immunotherapy in melanoma.Trial registration numberNCT02828202.
Oncolytic peptide LTX-315 induces anti-pancreatic cancer immunity by targeting the ATP11B-PD-L1 axis
Authors: Tang Tianyu , Huang Xing , Zhang Gang , Lu Minghao , Hong Zhengtao , Wang Meng , Huang Junming , Zhi Xiao , Liang Tingbo 
Published: March 2022

BackgroundLTX-315 is an oncolytic peptide deriving from bovine lactoferrin, with the ability to induce cancer immunogenic cell death. However, the mechanism used by LTX-315 to trigger the antitumor immune response is still poorly understood. The expression of programmed cell death ligand 1 (PD-L1) largely determines the efficacy and effectiveness of cancer immunotherapies targeting this specific immune checkpoint. This study aimed to demonstrate the potential effect and mechanism of LTX-315 in PD-L1 inhibition-induced anti-pancreatic cancer immunity.MethodsBoth immunodeficient and immunocompetent mouse models were used to evaluate the therapeutic efficacy of monotherapy and combination therapy. Flow cytometry and immunohistochemistry were used to assess the immune microenvironment. Multiomic analysis was used to identify the potential target and down-streaming signaling pathway. Both in-house tissue microarray and open accessed The Cancer Genome Atlas data sets were used to evaluate the clinical relevance in pancreatic cancer prognosis.ResultsLTX-315 treatment inhibited PD-L1 expression and enhanced lymphocyte infiltration in pancreatic tumors. ATP11B was identified as a potential target of LTX-315 and a critical regulator in maintaining PD-L1 expression in pancreatic cancer cells. As regards the mechanism, ATP11B interacted with PD-L1 in a CKLF-like MARVEL transmembrane domain containing 6 (CMTM6)-dependent manner. The depletion of ATP11B promoted CMTM6-mediated lysosomal degradation of PD-L1, thus reactivating the immune microenvironment and inducing an antitumor immune response. The significant correlation among ATP11B, CMTM6, and PD-L1 was confirmed in clinical samples of pancreatic cancer.ConclusionsLTX-315 was first identified as a peptide drug inducing PD-L1 downregulation via ATP11B. Therefore, LTX-315, or the development of ATP11B-targeting drugs, might improve the efficacy of cancer immunotherapy.
Exploring the safety, effect on the tumor microenvironment, and efficacy of itacitinib in combination with epacadostat or parsaclisib in advanced solid tumors: a phase I study
Authors: Naing Aung , Powderly John D , Nemunaitis John J , Luke Jason J , Mansfield Aaron S , Messersmith Wells A , Sahebjam Solmaz , LoRusso Patricia M , Garrido-Laguna Ignacio , Leopold Lance , Geschwindt Ryan , Ding Kai , Smith Michael , Berlin Jordan D 
Published: March 2022

BackgroundThis phase I multicenter study was designed to evaluate the safety, tolerability, efficacy, and translational effects on the tumor microenvironment of itacitinib (Janus-associated kinase 1 (JAK1) inhibitor) in combination with epacadostat (indoleamine 2,3-dioxygenase 1 (IDO1) inhibitor) or parsaclisib (phosphatidylinositol 3-kinase δ (PI3Kδ) inhibitor).MethodsPatients with advanced or metastatic solid tumors were enrolled and received itacitinib (100–400 mg once a day) plus epacadostat (50–300 mg two times per day; group A), or itacitinib (100–400 mg once a day) plus parsaclisib or parsaclisib monotherapy (0.3–10 mg once a day; group B).ResultsA total of 142 patients were enrolled in the study. The maximum tolerated dose was not reached for either the combination of itacitinib plus epacadostat (n=47) or itacitinib plus parsaclisib (n=90). One dose-limiting toxicity of serious, grade 3 aseptic meningitis was reported in a patient receiving itacitinib 300 mg once a day plus parsaclisib 10 mg once a day, which resolved when the study drugs were withdrawn. The most common treatment-related adverse events among patients treated with itacitinib plus epacadostat included fatigue, nausea, pyrexia, and vomiting, and for patients treated with itacitinib plus parsaclisib were fatigue, pyrexia, and diarrhea. In the itacitinib plus epacadostat group, no patient had an objective response. Among patients receiving itacitinib 100 mg once a day plus parsaclisib 0.3 mg once a day, three achieved partial response for an objective response rate (95% CI) of 7.1% (1.50 to 19.48). Treatment with itacitinib plus epacadostat demonstrated some increase in tumor CD8+T cell infiltration and minor changes in six plasma proteins, whereas treatment with itacitinib plus high-dose parsaclisib resulted in downregulation of 20 plasma proteins mostly involved in immune cell function, with no observed change in intratumoral CD8+T cell infiltration.ConclusionAdverse events with JAK1 inhibition combined with either IDO1 or PI3Kδ inhibition were manageable, but the combinations demonstrated limited clinical activity or enhancement of immune activation in the tumor microenvironment.Trial registration numberNCT02559492.
Translational randomized phase II trial of cabozantinib in combination with nivolumab in advanced, recurrent, or metastatic endometrial cancer
Authors: Lheureux Stephanie , Matei Daniela E , Konstantinopoulos Panagiotis A , Wang Ben X , Gadalla Ramy , Block Matthew S , Jewell Andrea , Gaillard Stephanie L , McHale Michael , McCourt Carolyn , Temkin Sarah , Girda Eugenia , Backes Floor J , Werner Theresa L , Duska Linda , Kehoe Siobhan , Colombo Ilaria , Wang Lisa , Li Xuan , Wildman Rachel , Soleimani Shirin , Lien Scott , Wright John , Pugh Trevor , Ohashi Pamela S , Brooks David G , Fleming Gini F 
Published: March 2022

BackgroundCombining immunotherapy and antiangiogenic agents is a promising treatment strategy in endometrial cancer. To date, no biomarkers for response have been identified and data on post-immunotherapy progression are lacking. We explored the combination of a checkpoint inhibitor (nivolumab) and an antiangiogenic agent (cabozantinib) in immunotherapy-naïve endometrial cancer and in patients whose disease progressed on previous immunotherapy with baseline biopsy for immune profiling.Patients and methodsIn this phase II trial (ClinicalTrials.govNCT03367741, registered December 11, 2017), women with recurrent endometrial cancer were randomized 2:1 to nivolumab with cabozantinib (Arm A) or nivolumab alone (Arm B). The primary endpoint was Response Evaluation Criteria in Solid Tumors-defined progression-free survival (PFS). Patients with carcinosarcoma or prior immune checkpoint inhibitor received combination treatment (Arm C). Baseline biopsy and serial peripheral blood mononuclear cell (PBMC) samples were analyzed and associations between patient outcome and immune data from cytometry by time of flight (CyTOF) and PBMCs were explored.ResultsMedian PFS was 5.3 (90% CI 3.5 to 9.2) months in Arm A (n=36) and 1.9 (90% CI 1.6 to 3.4) months in Arm B (n=18) (HR=0.59, 90% CI 0.35 to 0.98; log-rank p=0.09, meeting the prespecified statistical significance criteria). The most common treatment-related adverse events in Arm A were diarrhea (50%) and elevated liver enzymes (aspartate aminotransferase 47%, alanine aminotransferase 42%). In-depth baseline CyTOF analysis across treatment arms (n=40) identified 35 immune-cell subsets. Among immunotherapy-pretreated patients in Arm C, non-progressors had significantly higher proportions of activated tissue-resident (CD103+CD69+) ɣδ T cells than progressors (adjusted p=0.009).ConclusionsAdding cabozantinib to nivolumab significantly improved outcomes in heavily pretreated endometrial cancer. A subgroup of immunotherapy-pretreated patients identified by baseline immune profile and potentially benefiting from combination with antiangiogenics requires further investigation.
Bachu Mushroom Polysaccharide Alleviates Colonic Injury by Modulating the Gut Microbiota
Authors: Abdureyim Zumrat , Wang Lei , Tao Qing , Xu Jing , Yimiti Delixiati , Gao Qian 
Published: March 2022

Objective. This study was to define the protective effect of purified Helvella leucopus polysaccharide (p-HLP) against dextran sulfate sodium- (DSS-) induced colitis. Methods. The novel p-HLP was isolated from Bachu mushroom through hot water extraction, ethanol precipitation, and column chromatography. Then, we evaluated the potential effects of p-HLP on colonic histopathology, inflammation, and microbiota composition in DSS-induced colitis mice. Results. p-HLP was a homopolysaccharide with an average molecular weight of

39.14
×

10

8

Da

. Functionally, p-HLP significantly attenuated DSS-induced body weight loss and colon shortening. The histological score of the colon lesion was significantly decreased upon p-HLP treatment. Also, p-HLP treatment led to decreased expression of proinflammatory cytokines and mediators (IL-6, IL-1β and TNF-α, and COX-2 and iNOS) and increased expression of anti-inflammatory cytokine (IL-10) in the colon tissues. Illumina MiSeq sequencing revealed that p-HLP modulated the composition of the gut microbiota. Conclusion. p-HLP is a potent regulator that protects the lesions from DSS-induced colitis.
Circulating Immune Bioenergetic, Metabolic, and Genetic Signatures Predict Melanoma Patients' Response to Anti–PD-1 Immune Checkpoint Blockade
Authors: Triozzi Pierre L. , Stirling Elizabeth R. , Song Qianqian , Westwood Brian , Kooshki Mitra , Forbes M. Elizabeth , Holbrook Beth C. , Cook Katherine L. , Alexander-Miller Martha A. , Miller Lance D. , Zhang Wei , Soto-Pantoja David R. 
Published: March 2022

Abstract

Purpose:
Immunotherapy with checkpoint inhibitors is improving the outcomes of several cancers. However, only a subset of patients respond. Therefore, predictive biomarkers are critically needed to guide treatment decisions and develop approaches to the treatment of therapeutic resistance.

Experimental Design:
We compared bioenergetics of circulating immune cells and metabolomic profiles of plasma obtained at baseline from patients with melanoma treated with anti–PD-1 therapy. We also performed single-cell RNA sequencing (scRNAseq) to correlate transcriptional changes associated with metabolic changes observed in peripheral blood mononuclear cells (PBMC) and patient plasma.

Results:
Pretreatment PBMC from responders had a higher reserve respiratory capacity and higher basal glycolytic activity compared with nonresponders. Metabolomic analysis revealed that responder and nonresponder patient samples cluster differently, suggesting differences in metabolic signatures at baseline. Differential levels of specific lipid, amino acid, and glycolytic pathway metabolites were observed by response. Further, scRNAseq analysis revealed upregulation of T-cell genes regulating glycolysis. Our analysis showed that SLC2A14 (Glut-14; a glucose transporter) was the most significant gene upregulated in responder patients' T-cell population. Flow cytometry analysis confirmed significantly elevated cell surface expression of the Glut-14 in CD3+, CD8+, and CD4+ circulating populations in responder patients. Moreover, LDHC was also upregulated in the responder population.

Conclusions:
Our results suggest a glycolytic signature characterizes checkpoint inhibitor responders; consistently, both ECAR and lactate-to-pyruvate ratio were significantly associated with overall survival. Together, these findings support the use of blood bioenergetics and metabolomics as predictive biomarkers of patient response to immune checkpoint inhibitor therapy.
Depression prognosis using natural language processing and machine learning from social media status
Authors: Hossain Md. Tazmim , Talukder Md. Arafat Rahman , Jahan Nusrat 
Published: March 2022

<p><span>Depression is an acute problem throughout the world. Due to worst and prolong depression many people dies in every year. The problem is that most of the people are not concern of the fact that they are suffering from depression. In this research, our aim was to find out whether an individual is depressed or not by analyzing social media status. Therefore, we focused on real data. Our dataset consists of 2000 sentences, which was collected from different social media platforms Facebook, Twitter, and Instagram. Then, we have performed five data pre-processing approaches for natural language processing (NLP) such as tokenization, removal of stop words, removing empty string, removing punctuations, stemming and lemmatization. For our selected model, we considered that processed data as an input. Finally, we applied six machine learning (ML) classifiers multinomial Naive Bayes (NB), logistic regression, liner support vector classifier, random forest, K-nearest neighbour, and decision tree to achieve better accuracy over our dataset. Among six algorithms, multinomial NB and logistic regression performed well on our dataset and obtained 98% accuracy.</span></p>
HapPart: partitioning algorithm for multiple haplotyping from haplotype conflict graph
Authors: Abdullah Abu-Bakar Muhammad , Hossain Md. Monowar , Shill Pintu Chandra 
Published: March 2022

<span>Each chromosome in the human genome has two copies. The haplotype assembly challenge entails reconstructing two haplotypes (chromosomes) using aligned fragments genomic sequence. Plants viz. wheat, paddy and banana have more than two chromosomes. Multiple haplotype reconstruction has been a major research topic. For reconstructing multiple haplotypes for a polyploid organism, several approaches have been designed. The researchers are still fascinated to the computational challenge. This article introduces a partitioning algorithm, HapPart for dividing the fragments into </span><em><span>k</span></em><span>-groups focusing on reducing the computational time. HapPart uses minimum error correction curve to determine the value of </span><em><span>k</span></em><span> at which the growth of gain measures for two consecutive values of </span><em><span>k</span></em><span>-multiplied by its diversity is maximum. Haplotype conflict graph is used for constructing all possible number of groups. The dissimilarity between two haplotypes represents the distance between two nodes in graph. For merging two nodes with the minimum distance between them this algorithm ensures minimum error among fragments in same group. Experimental results on real and simulated data show that HapPart can partition fragments efficiently and with less computational time.</span>
Establishing a cyclic schedule for nurse in the health unit
Authors: Natheer Alkallak Isra , Zedan Shaban Ruqaya 
Published: March 2022

<p><span>This research presents the interleaving two approaches. These are intelligence's ideas as well as heuristic ‎technique as 8-puzzle and sudoku grid to solve the nurse rostering. The research proposed algorithm ‎to assign shifts cyclically. It is considered by three shifts in one day to 9 nurses, each nurse has 8 days work with ‎a holiday in the cyclically scheduling. The task appeared the allocation of nursing staff in health unit management ‎theoretically. There are three shifts which cover 24 hours. The shifts are early, late, and night. This algorithm ‎simulated the shifts through the directions of blank’s move in 8-puzzle with the methodology of sudoku grid with ‎hard constraints should be met at all times. In our solution do on two goals first, we create a ‎schedule that meets all the tough constraints and guarantees fairness. The second objective is to try to verify as many ‎of the soft constraints as possible, by shifting and rotating while maintaining the soft constraints. The approach ‎was implemented as a simulation, and a satisfactory result was demonstrated. experimental effects are extremely ‎convenient and versatile to find appropriate nursing rostering schedule, rather than using manual techniques. The code developed to simulate it in MATLAB.‎</span></p>
The susceptible-infected-recovered-dead model for long-term identification of key epidemiological parameters of COVID-19 in Indonesia
Authors: Nanda Muhammad Achirul , Faricha Anifatul , Ulyah Siti Maghfirotul , Tamimah Ni'matut , Indasyah Enny , Malich Salaz Muhammad Falahudin , Mawadatur Rohmah Qurrotun 'Ayun , Abqari Ulfah 
Published: March 2022

<span>The COVID-19 epidemic has spread massively to almost all countries including Indonesia, in just a few months. An important step to overcoming the spread of the COVID-19 is understanding its epidemiology through mathematical modeling intervention. Knowledge of epidemic dynamics patterns is an important part of making timely decisions and preparing hospitals for the outbreak peak. In this study, we developed the susceptible-infected-recovered-dead (SIRD) model, which incorporates the key epidemiological parameters to model and estimate the long-term spread of the COVID-19. The proposed model formulation is data-based analysis using public COVID-19 data from March 2, 2020 to May 15, 2021. Based on numerical analysis, the spread of the pandemic will begin to fade out after November 5, 2021. As a consequence of this virus attack, the cumulative number of infected, recovered, and dead people were estimated at ≈ 3,200,000, ≈ 3,437,000 and ≈ 63,000 people, respectively. Besides, the key epidemiological parameter indicates that the average reproduction number value of COVID-19 in Indonesia is 7.32. The long-term prediction of COVID-19 in Indonesia and its epidemiology can be well described using the SIRD model. The model can be applied in specific regions or cities in understanding the epidemic pattern of COVID-19.</span>
Reasoning in inconsistent prioritized knowledge bases: an argumentative approach
Authors: Ho Loan Thi-Thuy , Arch-int Somjit , Arch-int Ngamnij 
Published: March 2022

<p>A study of query answering in prioritized ontological knowledge bases (KBs) has received attention in recent years. While several semantics of query answering have been proposed and their complexity is rather well-understood, the problem of explaining inconsistency-tolerant query answers has paid less attention. Explaining query answers permits users to understand not only what is entailed or not entailed by an inconsistent DL-LiteR KBs in the presence of priority, but also why. We, therefore, concern with the use of argumentation frameworks to allow users to better understand explanation techniques of querying answers over inconsistent DL-LiteR KBs in the presence of priority. More specifically, we propose a new variant of Dung’s argumentation frameworks, which corresponds to a given inconsistent DL-LiteR KB. We clarify a close relation between preferred subtheories adopted in such prioritized DL-LiteR setting and acceptable semantics of the corresponding argumentation framework. The significant result paves the way for applying algorithms and proof theories to establish preferred subtheories inferences in prioritized DL-LiteR KBs.</p>
Design for Biological Research: Upjohn, Will Burtin, and the Cell
Authors: Olave Diana Cristóbal 
Published: March 2022

Abstract
This article discusses the role of design in collaborative scientific research, through an analysis of the human-scaled models produced by designer Will Burtin for the pharmaceutical conglomerate Upjohn. It argues that such models triggered an intimate co-dependence between architectural techniques and biological theories, consolidating biology into a form of construction—a form of building. Within the context of corporate-sponsored scientific research of American postwar, Upjohn embraced unorthodox methods of mass media communication to engage the public with scientific narratives. It was through such unconventional techniques that design concerns—form, scale, construction, aesthetics—were placed at the forefront of scientific debates.
Analysis of Pioneering Computable Biomedical Knowledge Repositories and their Emerging Governance Structures
Authors: Amara Philip Sahr , Conte Marisa , Flynn Allen , Platt Jodyn , Trinidad Marie Grace 
Published: March 2022

Abstract
A growing interest in producing and sharing computable biomedical knowledge artifacts (CBKs) is increasing the demand for repositories that validate, catalog, and provide shared access to CBKs. However, there is a lack of evidence on how best to manage and sustain CBK repositories. In this paper, we present the results of interviews with several pioneering CBK repository owners. These interviews were informed by the Trusted Repositories Audit and Certification (TRAC) framework. Insights gained from these interviews suggest that the organizations operating CBK repositories are somewhat new, that their initial approaches to repository governance are informal, and that achieving economic sustainability for their CBK repositories is a major challenge. To enable a learning health system to make better use of its data intelligence, future approaches to CBK repository management will require enhanced governance and closer adherence to best practice frameworks to meet the needs of myriad biomedical science and health communities. More effort is needed to find sustainable funding models for accessible CBK artifact collections.