tbuckley/cabot-search huggingface dataset:
Longitudinal Clusters of Long-Term Trajectories in Patients with Early-Onset Chronic Depression: 2 Years of Naturalistic Follow-Up after Extensive Psychological Treatment
Authors: Moritz Elsaesser, Bernd Feige, Levente Kriston, Lea Schumacher, Jasmin Peifer, Martin Hautzinger, Martin Härter, Elisabeth Schramm
Journal: Psychotherapy and Psychosomatics (2023)

&lt;b&gt;&lt;i&gt;Introduction:&lt;/i&gt;&lt;/b&gt; In clinical trials, mostly group-level treatment effects of repeated cross-sectional measures are analyzed. However, substantial heterogeneity regarding individual symptom profiles and the variability of treatment effects are often neglected, especially over the long-term course. To provide effective personalized treatments, investigations of these characteristics are urgently needed. &lt;b&gt;&lt;i&gt;Methods:&lt;/i&gt;&lt;/b&gt; Depression severity ratings over 104 weeks of follow-up after year-long treatment with the Cognitive Behavioral Analysis System of Psychotherapy (CBASP) or Supportive Psychotherapy (SP) were analyzed. Longitudinal cluster analysis and multinomial logistic regression analysis were conducted to investigate intraindividual trajectories from one of the largest psychotherapy trials in early-onset chronic depression. &lt;b&gt;&lt;i&gt;Results:&lt;/i&gt;&lt;/b&gt; Two-year post-study-treatment trajectories of &lt;i&gt;N&lt;/i&gt; = 188 patients with early-onset chronic depression were grouped into four prototypical clusters. Overall, 16.0% of patients remitted (cluster 1) and most of them did not receive any treatment during the 2-year follow-up. However, 84.0% of patients continued to experience subthreshold (37.2% cluster 2) or major depressive symptoms (46.8% clusters 3–4) and spent on average more than half of the follow-up in pharmacological and psychological treatment. Hierarchical regression analysis indicated that previous study treatment with CBASP or SP did not significantly predict cluster allocation, while baseline variables accounted for a large proportion of explained variance (&lt;i&gt;R&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt; &lt;sub&gt;N&lt;/sub&gt; = 0.64). &lt;b&gt;&lt;i&gt;Conclusion:&lt;/i&gt;&lt;/b&gt; While some patients experienced stable remission over 2 years of follow-up, the majority of patients experienced subthreshold or major depressive symptoms regardless of former study treatment with CBASP or SP. This calls for a long-term perspective implementing staging and innovative treatment approaches such as the sequential model or modular psychotherapy.
A Poisson Lognormal-Lindley model for simultaneous estimation of multiple crash-types: Application of multivariate and pooled univariate models
Authors: Hassan Bin Tahir, Shamsunnahar Yasmin, Md Mazharul Haque
Journal: Analytic Methods in Accident Research (2023)

Challenges addressing overdispersion, unobserved heterogeneity, the preponderance of zeros, and correlation in the dependent variables of crash count models are of significant interest. Accounting for all these data issues simultaneously is few and far between. This study proposes a new mixing distribution model that accounts for overdispersion and the preponderance of zeros in crash count models. The proposed mixing distribution model extends to the multivariate structure to account for correlations between dependent variables and unobserved heterogeneity. The empirical analysis is conducted on crash data of Bruce highway involving single-vehicle and multi-vehicle crash types by "fatal and severe injury" and "moderate and minor injury" severity levels on aggregated data over three analysis years (2016, 2017, and 2018). The study demonstrates superior goodness of fit of the proposed multivariate random parameters Poisson lognormal-Lindley model compared to its restricted models. Moreover, pooling the crash data as repeated measures of crash types helped formulate a pooled-univariate random parameters Poisson-Lindley model to estimate multiple crash types by severity. The results showed the pooled-univariate model offers comparable goodness of fit and averaged marginal effects as the complex multivariate modeling structure. Moreover, the proposed pooled-univariate model reduced the model complexity to a one-dimensional integral and offered more efficient parameter estimates. In the empirical context, the modeling results showed that single-vehicle and multi-vehicle crashes by severity are linked with different causality.
Use of oxygen-loaded nanobubbles to improve tissue oxygenation: Bone-relevant mechanisms of action and effects on osteoclast differentiation
Authors: Helen J. Knowles, Alexandra Vasilyeva, Mihir Sheth, Oliver Pattinson, Jonathan May, Robin M.H. Rumney, Philippa A. Hulley, Duncan B. Richards, Dario Carugo, Nicholas D. Evans, Eleanor Stride
Journal: Biomaterials (2023)

Gas-loaded nanobubbles have potential as a method of oxygen delivery to increase tumour oxygenation and therapeutically alleviate tumour hypoxia. However, the mechanism(s) whereby oxygen-loaded nanobubbles increase tumour oxygenation are unknown; with their calculated oxygen-carrying capacity being insufficient to explain this effect. Intra-tumoural hypoxia is a prime therapeutic target, at least partly due to hypoxia-dependent stimulation of the formation and function of bone-resorbing osteoclasts which establish metastatic cells in bone. This study aims to investigate potential mechanism(s) of oxygen delivery and in particular the possible use of oxygen-loaded nanobubbles in preventing bone metastasis via effects on osteoclasts. Lecithin-based nanobubbles preferentially interacted with phagocytic cells (monocytes, osteoclasts) via a combination of lipid transfer, clathrin-dependent endocytosis and phagocytosis. This interaction caused general suppression of osteoclast differentiation via inhibition of cell fusion. Additionally, repeat exposure to oxygen-loaded nanobubbles inhibited osteoclast formation to a greater extent than nitrogen-loaded nanobubbles. This gas-dependent effect was driven by differential effects on the fusion of mononuclear precursor cells to form pre-osteoclasts, partly due to elevated potentiation of RANKL-induced ROS by nitrogen-loaded nanobubbles. Our findings suggest that oxygen-loaded nanobubbles could represent a promising therapeutic strategy for cancer therapy; reducing osteoclast formation and therefore bone metastasis via preferential interaction with monocytes/macrophages within the tumour and bone microenvironment, in addition to known effects of directly improving tumour oxygenation.
Findings from the KNOW-CKD Study indicate that higher systolic blood pressure time in target range is associated with a lower risk of chronic kidney disease progression
Authors: Cheol Ho Park, Hyung Woo Kim, Young Su Joo, Jung Tak Park, Tae Ik Chang, Tae-Hyun Yoo, Sue Kyung Park, Yeong Hoon Kim, Suah Sung, Young Youl Hyun, Kook-Hwan Oh, Shin-Wook Kang, Seung Hyeok Han
Journal: Kidney International (2023)
Nanointegrative Glycoengineering‐Activated Necroptosis of Triple Negative Breast Cancer Stem Cells Enables Self‐Amplifiable Immunotherapy for Systemic Tumor Rejection
Authors: Youbo Zhao, Yanan Li, Jing He, Menghuan Li, Xuemei Yao, Huocheng Yang, Zhong Luo, Peng Luo, Min Su
Journal: Advanced Healthcare Materials (2023)

Triple-negative breast cancer stem cells (TCSCs) are considered as the origin of recurrence and relapse. It is difficult to kill not only for its resistance, but also the lacking of targetable molecules on membrane. Here, it is confirmed that ST6 β-galactoside alpha-2,6-sialyltransferase 1 (ST6Gal-1) is highly expressed in TCSCs that may be the key enzyme involved in glycoengineering via sialic acid (SA) metabolism. SA co-localizes with a microdomain on cell membrane termed as lipid rafts that enrich CSCs marker and necroptosis proteins mixed lineage kinase domain-like protein (MLKL), suggesting that TCSCs may be sensitive to necroptosis. Thus, the triacetylated N-azidoacetyl-d-mannosamine (Ac
B-cell infiltration is associated with survival outcomes following programmed cell death protein 1 inhibition in head and neck squamous cell carcinoma
Authors: N. Gavrielatou, E. Fortis, A. Spathis, M. Anastasiou, P. Economopoulou, G.R.P. Foukas, I.M. Lelegiannis, S. Rusakiewicz, I. Vathiotis, T.N. Aung, S. Tissot, A. Kastrinou, I. Kotsantis, E.M. Vagia, I. Panayiotides, D.L. Rimm, G. Coukos, K. Homicsko, P. Foukas, A. Psyrri
Journal: Annals of Oncology (2023)

BackgroundProgrammed cell death protein 1(PD-1) axis blockade has become the mainstay in the treatment of recurrent and/or metastatic (R/M) head and neck squamous cell cancer (HNSCC). PD-L1 is the only approved biomarker for patient selection; however, response rate is limited even among high expressors. Our primary objective was to investigate the association of immune-cell-related biomarkers in the tumor and tumor microenvironment with PD-1 checkpoint inhibitors' outcomes in patients with R/M HNSCC.Patients and methodsNCT03652142 was a prospective study in nivolumab-treated platinum-refractory R/M HNSCC, aiming to evaluate biomarkers of response to treatment. Tumor biopsies and blood samples were collected from 60 patients at baseline, post-treatment, and at progression. Immune cells in the tumor and stromal compartments was quantified by immunofluorescence using a five-protein panel (CD3, CD8, CD20, Foxp3, Cytokeratin). Tertiary lymphoid structures (TLS), PD-L1 expression, and peripheral blood immune-cell composition were also evaluated for associations with outcome. Our findings were validated by gene set enrichment analysis (GSEA) mRNA in situ expression data from the same patients, for B-cell and TLS associated genes.ResultsHigh pre-treatment density of stromal B-cells was associated with prolonged progression-free survival (PFS) (p=0.011). This result was validated by GSEA, as stromal enrichment with B-cell-associated genes showed association with response to nivolumab. PD-L1 positivity combined with high B-cell counts in stroma defined a subgroup with significantly longer PFS and overall survival (p=0.013 and p=0.0028, respectively).ConclusionsIncreased B-cells in pre-treatment HNSCC biopsy samples correlate with prolonged benefit from PD-1-based immunotherapy and could further enhance the predictive value of PD-L1 expression.
Adaptive Spatial–Temporal Aware Graph Learning for EEG-Based Emotion Recognition
Authors: Weishan Ye, Jiyuan Wang, Lin Chen, Lifei Dai, Zhe Sun, Zhen Liang
Journal: Cyborg and Bionic Systems (2023)

An intelligent emotion recognition system based on electroencephalography (EEG) signals shows considerable potential in various domains such as healthcare, entertainment, and education, thanks to its portability, high temporal resolution, and real-time capabilities. However, the existing research in this field faces limitations stemming from the nonstationary nature and individual variability of EEG signals. In this study, we present a novel EEG emotion recognition model, named GraphEmotionNet, designed to enhance the accuracy of EEG-based emotion recognition through the incorporation of a spatiotemporal attention mechanism and transfer learning. The proposed GraphEmotionNet model can effectively learn the intrinsic connections between EEG channels and construct an adaptive graph. This graph's adaptive nature is crucial in optimizing spatial-temporal graph convolutions, which in turn enhances spatial-temporal feature characterization and contributes to the process of emotion classification. Moreover, an integration of domain adaptation aligns the extracted features across different domains, further alleviating the impact of individual EEG variability. We evaluate the model performance on two benchmark databases, employing two types of cross-validation protocols: within-subject cross-validation and cross-subject cross-validation. The experimental results affirm the model's efficacy in extracting EEG features linked to emotional semantics and demonstrate its promising performance in emotion recognition.
Blood Monocyte Phenotype Is A Marker of Cardiovascular Risk in Type 2 Diabetes
Authors: Jean-Baptiste Julla, Diane Girard, Marc Diedisheim, Pierre-Jean Saulnier, Bao Tran Vuong, Camille Blériot, Elena Carcarino, Joe De Keizer, Lucie Orliaguet, Ivan Nemazanyy, Charline Potier, Kennan Khider, Dorothy Chepngenoh Tonui, Tina Ejlalmanesh, Raphaelle Ballaire, Hendrick Mambu Mambueni, Stéphane Germain, Bénédicte Gaborit, Tiphaine Vidal-Trécan, Jean-Pierre Riveline, Henri-Jean Garchon, François Fenaille, Sophie Lemoine, Aurélie Carlier, Florence Castelli, Louis Potier, David Masson, Ronan Roussel, Claire Vandiedonck, Samy Hadjadj, Fawaz Alzaid, Jean-François Gautier, Nicolas Venteclef
Journal: Circulation Research (2023)

Diabetes is a major risk factor for atherosclerotic cardiovascular diseases with a 2-fold higher risk of cardiovascular events in people with diabetes compared with those without. Circulating monocytes are inflammatory effector cells involved in both type 2 diabetes (T2D) and atherogenesis.
Leave It to Large Language Models! Correct and Planning with Memory Integration
Authors: Yuan Zhang, Chao Wang, Juntong Qi, Yan Peng
Journal: Cyborg and Bionic Systems (2023)

As humans, we can naturally break down a task into individual steps in our daily lives and we are able to provide feedback or dynamically adjust the plan when encountering obstacles. Similarly, our aim is to facilitate agents in comprehending and carrying out natural language instructions in a more efficient and cost-effective manner. For example, in Vision-Language Navigation (VLN) tasks, the agent needs to understand instructions such as "go to the table by the fridge". This understanding allows the agent to navigate to the table and infer that the destination is likely to be in the kitchen. The traditional VLN approach mainly involves training models using a large number of labeled datasets for task planning in unseen environments. However, manual labeling incurs a high cost for this approach. Considering that large language models (LLMs) already possess extensive commonsense knowledge during pre-training, some researchers have started using LLMs as decision modules in embodied tasks, although this approach shows the LLMs' reasoning ability to plan a logical sequence of subtasks based on global information. However, executing subtasks often encounters issues, such as obstacles that hinder progress and alterations in the state of the target object. Even one mistake can cause the subsequent tasks to fail, which makes it challenging to complete the instructions through a single plan. Therefore, we propose a new approach-C (Correction) and P (Planning) with M (Memory) I (Integration)-that centered on an LLM for embodied tasks. In more detail, the auxiliary modules of the CPMI facilitate dynamic planning by the LLM-centric planner. These modules provide the agent with memory and generalized experience mechanisms to fully utilize the LLM capabilities, allowing it to improve its performance during execution. Finally, the experimental results on public datasets demonstrate that we achieve the best performance in the few-shot scenario, improving the efficiency of the successive task while increasing the success rate.
Cluster-based prognostication in glioblastoma: Unveiling heterogeneity based on diffusion and perfusion similarities
Authors: Martha Foltyn-Dumitru, Tobias Kessler, Felix Sahm, Wolfgang Wick, Sabine Heiland, Martin Bendszus, Philipp Vollmuth, Marianne Schell
Journal: Neuro-Oncology (2023)

Abstract Background While the association between diffusion and perfusion magnetic resonance imaging (MRI) and survival in glioblastoma is established, prognostic models for patients are lacking. This study employed clustering of functional imaging to identify distinct functional phenotypes in untreated glioblastomas, assessing their prognostic significance for overall survival. Methods A total of 289 patients with glioblastoma who underwent preoperative multimodal MR imaging were included. Mean values of apparent diffusion coefficient normalized relative cerebral blood volume and relative cerebral blood flow were calculated for different tumor compartments and the entire tumor. Distinct imaging patterns were identified using partition around medoids (PAM) clustering on the training dataset, and their ability to predict overall survival was assessed. Additionally, tree-based machine-learning models were trained to ascertain the significance of features pertaining to cluster membership. Results Using the training dataset (231/289) we identified 2 stable imaging phenotypes through PAM clustering with significantly different overall survival (OS). Validation in an independent test set revealed a high-risk group with a median OS of 10.2 months and a low-risk group with a median OS of 26.6 months (P = 0.012). Patients in the low-risk cluster had high diffusion and low perfusion values throughout, while the high-risk cluster displayed the reverse pattern. Including cluster membership in all multivariate Cox regression analyses improved performance (P ≤ 0.004 each). Conclusions Our research demonstrates that data-driven clustering can identify clinically relevant, distinct imaging phenotypes, highlighting the potential role of diffusion, and perfusion MRI in predicting survival rates of glioblastoma patients.
Targeting of the CD161 inhibitory receptor enhances T-cell–mediated immunity against hematological malignancies
Authors: Francesca Alvarez Calderon, Byong H. Kang, Oleksandr Kyrysyuk, Shiwei Zheng, Hao Wang, Nathan D. Mathewson, Adrienne M. Luoma, Xiaohan Ning, Jason Pyrdol, Xuan Cao, Mario L. Suvà, Guo-Cheng Yuan, K. Dane Wittrup, Kai W. Wucherpfennig
Journal: Blood (2023)
Developmental trajectories and cooperating genomic events define molecular subtypes of <i>BCR</i>::<i>ABL1</i>-positive ALL
Authors: Lorenz Bastian, Thomas Beder, Malwine J. Barz, Sonja Bendig, Lorenz Bartsch, Wencke Walter, Nadine Wolgast, Björn Brändl, Christian Rohrandt, Björn-Thore Hansen, Alina M. Hartmann, Katharina Iben, Dennis Das Gupta, Miriam Denker, Johannes Zimmermann, Michael Wittig, Guranda Chitadze, Martin Neumann, Folker Schneller, Walter Fiedler, Björn Steffen, Matthias Stelljes, Christoph Faul, Stefan Schwartz, Franz-Josef Müller, Gunnar Cario, Lana Harder, Claudia Haferlach, Heike Pfeifer, Nicola Gökbuget, Monika Brüggemann, Claudia D. Baldus
Journal: Blood (2023)

Abstract Distinct diagnostic entities within BCR::ABL1-positive acute lymphoblastic leukemia (ALL) are currently defined by the International Consensus Classification of myeloid neoplasms and acute leukemias (ICC): “lymphoid only”, with BCR::ABL1 observed exclusively in lymphatic precursors, vs “multilineage”, where BCR::ABL1 is also present in other hematopoietic lineages. Here, we analyzed transcriptomes of 327 BCR::ABL1-positive patients with ALL (age, 2-84 years; median, 46 years) and identified 2 main gene expression clusters reproducible across 4 independent patient cohorts. Fluorescence in situ hybridization analysis of fluorescence-activated cell-sorted hematopoietic compartments showed distinct BCR::ABL1 involvement in myeloid cells for these clusters (n = 18/18 vs n = 3/16 patients; P &amp;lt; .001), indicating that a multilineage or lymphoid BCR::ABL1 subtype can be inferred from gene expression. Further subclusters grouped samples according to cooperating genomic events (multilineage: HBS1L deletion or monosomy 7; lymphoid: IKZF1-/- or CDKN2A/PAX5 deletions/hyperdiploidy). A novel HSB1L transcript was highly specific for BCR::ABL1 multilineage cases independent of HBS1L genomic aberrations. Treatment on current German Multicenter Study Group for Adult ALL (GMALL) protocols resulted in comparable disease-free survival (DFS) for multilineage vs lymphoid cluster patients (3-year DFS: 70% vs 61%; P = .530; n = 91). However, the IKZF1-/- enriched lymphoid subcluster was associated with inferior DFS, whereas hyperdiploid cases showed a superior outcome. Thus, gene expression clusters define underlying developmental trajectories and distinct patterns of cooperating events in BCR::ABL1-positive ALL with prognostic relevance.
Plasma miRNAs and Treatment Failure in Participants in the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) Study
Authors: Pandora L. Wander, Theo K. Bammler, James W. MacDonald, Sengeo Srinouanprachanh, Edward J. Boyko, Daniel A. Enquobahrie
Journal: Diabetes Care (2023)

OBJECTIVE To identify plasma miRNAs related to treatment failure in youth with type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS We examined whether a panel of miRNAs could predict treatment failure in training/test data sets among participants in the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) study (N = 209). We also examined whether individual miRNAs were associated with treatment failure. RESULTS Participants were age 14.5 years, and 62% were female. A panel of miRNAs did not predict treatment failure. However, for each doubling, miR-4306 was associated with a 12% decrease (P = 0.040) and miR-483-3p was marginally associated with a 12% increase (P = 0.080) in failure independently of sex, race/ethnicity, BMI, Tanner stage, HbA1c, maternal diabetes, oral disposition index, and treatment arm. The addition of both miRNAs improved model fit (log likelihood without vs. with miRNAs −360.3 vs. −363.5; P = 0.040). CONCLUSIONS miR-483-3p and miR-4306 may be associated with treatment failure in youth with T2D.
Insulin Secretion, Sensitivity, and Kidney Function in Young Individuals With Type 2 Diabetes
Authors: Petter Bjornstad, Ye Ji Choi, Carson Platnick, Susan Gross, Phoom Narongkiatikhun, Isabella Melena, Lauryn Remmers, Madison Baca, Grant Schutte, Tyler Dobbs, Tim Vigers, Laura Pyle, Lynette Driscoll, Kalie Tommerdahl, Jessica Kendrick, Helen C. Looker, Allison Dart, David Cherney, Daniel H. van Raalte, Anand Srivastava, Luping Li, Pottumarthi Prasad, Pierre Saulnier, Robert G. Nelson, Richard J. Johnson, Kristen J. Nadeau, Nicholas Becker, Kyla Best, Carissa Birznieks, Michelle Bui, Diego Carrasco, Daniel Casillas, Maureen Flynn, Audrey Gruszcynski, Lucy Hall, Madeline Harbour, Melissa Leroux, Kelly Nash, Nhung Nguyen, Emily Sell, Callyn Rountree-Jablin
Journal: Diabetes Care (2023)

OBJECTIVE β-cell dysfunction and insulin resistance magnify the risk of kidney injury in type 2 diabetes. The relationship between these factors and intraglomerular hemodynamics and kidney oxygen availability in youth with type 2 diabetes remains incompletely explored. RESEARCH DESIGN AND METHODS Fifty youth with type 2 diabetes (mean age ± SD 16 ± 2 years; diabetes duration 2.3 ± 1.8 years; 60% female; median HbA1c 6.4% [25th, 75th percentiles 5.9, 7.6%]; BMI 36.4 ± 7.4 kg/m2; urine albumin-to-creatinine ratio [UACR] 10.3 [5.9, 58.0] mg/g) 21 control participants with obesity (OCs; age 16 ± 2 years; 29% female; BMI 37.6 ± 7.4 kg/m2), and 20 control participants in the normal weight category (NWCs; age 17 ± 3 years; 70% female; BMI 22.5 ± 3.6 kg/m2) underwent iohexol and p-aminohippurate clearance to assess glomerular filtration rate (GFR) and renal plasma flow, kidney MRI for oxygenation, hyperglycemic clamp for insulin secretion (acute C-peptide response to glucose [ACPRg]) and disposition index (DI; ×103 mg/kg lean/min), and DXA for body composition. RESULTS Youth with type 2 diabetes exhibited lower DI (0.6 [0.0, 1.6] vs. 3.8 [2.4, 4.5] × 103 mg/kg lean/min; P &amp;lt; 0.0001) and ACPRg (0.6 [0.3, 1.4] vs. 5.3 [4.3, 6.9] nmol/L; P &amp;lt; 0.001) and higher UACR (10.3 [5.9, 58.0] vs. 5.3 [3.4, 14.3] mg/g; P = 0.003) and intraglomerular pressure (77.8 ± 11.5 vs. 64.8 ± 5.0 mmHg; P &amp;lt; 0.001) compared with OCs. Youth with type 2 diabetes and OCs had higher GFR and kidney oxygen availability (relative hyperoxia) than NWCs. DI was associated inversely with intraglomerular pressure and kidney hyperoxia. CONCLUSIONS Youth with type 2 diabetes demonstrated severe β-cell dysfunction that was associated with intraglomerular hypertension and kidney hyperoxia. Similar but attenuated findings were found in OCs.