bluuebunny/crossref_metadata_2025_split huggingface dataset:
Small-molecule PTPN2 Inhibitors Sensitize Resistant Melanoma to Anti-PD-1 Immunotherapy
Authors: Zhu Zhouting , Tang Rachel , Huff Sarah , Kummetha Indrasena Reddy , Wang Lingling , Li Na , Rana Tariq M. 
Published: December 2022

Although immune checkpoint inhibitors targeting T-cell immunoregulatory proteins have revolutionized cancer treatment, they are effective only in a limited number of patients, and new strategies are needed to enhance tumor responses to immunotherapies. Deletion of protein tyrosine phosphatase non-receptor type 2 (Ptpn2), a regulator of growth factor and cytokine signaling pathways, has been shown to sensitize murine B16F10 melanoma cells to IFNγ and anti-PD-1 immunotherapy. Here, we investigated the potential therapeutic utility of small-molecule PTPN2 inhibitors. Ten inhibitors were synthesized on the basis of in silico modeling and structure-based design and functionally tested in vitro and in vivo. We show that the inhibitors had little effect on B16F10 cells alone, but effectively sensitized the tumor cells to IFNγ treatment in vitro and to anti-PD-1 therapy in vivo. Under both conditions, Ptpn2 inhibitor cotreatment suppressed B16F10 cell growth and enhanced Stat1 phosphorylation and expression of IFNγ response genes. In vivo, PTPN2 inhibitor cotreatment significantly reduced melanoma and colorectal tumor growth and enhanced mouse survival compared with anti-PD-1 treatment alone, and this was accompanied by increased tumor infiltration by granzyme B+ CD8+ T cells. Similar results were obtained with representative murine and human colon cancer and lung cancer cell lines. Collectively, these results demonstrate that small-molecule inhibitors of PTPN2 may have clinical utility as sensitizing agents for immunotherapy-resistant cancers.Significance:To enhance the effectiveness of immunotherapies in resistant or nonresponsive cancers, it is important to develop inhibitors of enzymes that negatively influence the outcome of treatments. We have designed and evaluated small-molecule inhibitors of PTPN2 demonstrating that these compounds may have clinical utility as sensitizing agents for immunotherapy-resistant cancers.
Peptide Vaccine Against ADAMTS-7 Ameliorates Atherosclerosis and Postinjury Neointima Hyperplasia
Authors: Ma Zihan , Mao Chenfeng , Chen Xiao , Yang Shiyu , Qiu Zhihua , Yu Baoqi , Jia Yiting , Wu Chao , Wang Yiyi , Wang Yuhui , Gu Rui , Yu Fang , Yin Yanhui , Wang Xian , Xu Qingbo , Liu Chuanju , Liao Yuhua , Zheng Jingang , Fu Yi , Kong Wei 
Published: December 2022

Background:
The metalloprotease ADAMTS-7 (a disintegrin and metalloproteinase with thrombospondin type 1 motif 7) is a novel locus associated with human coronary atherosclerosis. ADAMTS-7 deletion protects against atherosclerosis and vascular restenosis in rodents.

Methods:

We designed 3 potential vaccines consisting of distinct B cell epitopic peptides derived from ADAMTS-7 and conjugated with the carrier protein KLH (keyhole limpet hemocyanin) as well as aluminum hydroxide as an adjuvant. Arterial ligation or wire injury was used to induce neointima in mice, whereas
ApoE
-/-
and
LDLR
-/-
(LDLR [low-density lipoprotein receptor]) mice fed a high-fat diet were applied to assess atherosclerosis. In addition, coronary stent implantation was performed on vaccine-immunized Bama miniature pigs, followed by optical coherence tomography to evaluate coronary intimal hyperplasia.

Results:

A vaccine, ATS7vac, was screened out from 3 candidates to effectively inhibit intimal thickening in murine carotid artery ligation models after vaccination. As well, immunization with ATS7vac alleviated neointima formation in murine wire injury models and mitigated atherosclerotic lesions in both hyperlipidemic
ApoE
-/-
and
LDLR
-/-
mice without lowering lipid levels. Preclinically, ATS7vac markedly impeded intimal hyperplasia in swine stented coronary arteries, but without significant immune-related organ injuries. Mechanistically, ATS7vac vaccination produced specific antibodies against ADAMTS-7, which markedly repressed ADAMTS-7–mediated COMP (cartilage oligomeric matrix protein) and TSP-1 (thrombospondin-1) degradation and subsequently inhibited vascular smooth muscle cell migration but promoted re-endothelialization.

Conclusions:
ATS7vac is a novel atherosclerosis vaccine that also alleviates in-stent restenosis. The application of ATS7vac would be a complementary therapeutic avenue to the current lipid-lowering strategy for atherosclerotic disease.
Temporal Mapper: Transition networks in simulated and real neural dynamics
Authors: Zhang Mengsen , Chowdhury Samir , Saggar Manish 
Published: December 2022

Abstract
Characterizing large-scale dynamic organization of the brain relies on both data-driven and mechanistic modeling, which demands a low versus high level of prior knowledge and assumptions about how constituents of the brain interact. However, the conceptual translation between the two is not straightforward. The present work aims to provide a bridge between data-driven and mechanistic modeling. We conceptualize brain dynamics as a complex landscape that is continuously modulated by internal and external changes. The modulation can induce transitions between one stable brain state (attractor) to another. Here, we provide a novel method—Temporal Mapper—built upon established tools from the field of topological data analysis to retrieve the network of attractor transitions from time series data alone. For theoretical validation, we use a biophysical network model to induce transitions in a controlled manner, which provides simulated time series equipped with a ground-truth attractor transition network. Our approach reconstructs the ground-truth transition network from simulated time series data better than existing time-varying approaches. For empirical relevance, we apply our approach to fMRI data gathered during a continuous multitask experiment. We found that occupancy of the high-degree nodes and cycles of the transition network was significantly associated with subjects’ behavioral performance. Taken together, we provide an important first step toward integrating data-driven and mechanistic modeling of brain dynamics.
GeroCast: Using podcasting to deliver living cases in gerontology education
Authors: Auais Mohammad , Cameron Julie , Turnnidge Jennifer , Dalgarno Nancy , Kolomitro Klodiana , Pelland Lucie 
Published: December 2022

Objective: To describe the creation of an educational podcast with ‘living cases’ of older adults to support students’ learning on a gerontology course and report on students’ evaluation of the project. Setting: Gerontology course in a graduate programme. Method: We developed a podcast series based on interviews with older adults in the community following recent guidelines for creating educational podcasts. The podcast episodes were used in a case-based group assignment to work on during the course and to present findings at the end. Evaluation: Student experiences were evaluated using a mixed-methods survey. Results: From November 2019 to January 2021, case-based podcasts, averaging 17 minutes in length, were created and evaluated. Most students found the content of the podcasts relevant to working with older adults and increased their understanding of the issues facing members of that population. Qualitative analysis of the survey findings found that the overall strengths of the podcasts were that they were well structured, provided an authentic, real-world experience, allowed listeners to experience an innovative teaching strategy, promoted reflection, and encouraged students to consider a future career working with older adults. Students also recommended ways to improve the podcasts. Conclusion: Delivering living case studies using podcasts is a feasible, inexpensive and effective teaching method for improving physiotherapy students’ attitudes towards caring for older adults. Students enjoyed learning via the podcasts and found them a valuable way to better understand the issues facing older adults. The living case podcasts could have broad applicability to other aging and health courses.
Long Sleep Duration Increases the Risk of All-Cause Mortality Among Community-Dwelling Older Adults With Frailty: Evidence From NHANES 2009–2014
Authors: Chen Mingzhuang , Lu Chao , Zha Jingru 
Published: December 2022

Objectives: The aim of this study was to determine the effect of sleep duration on all-cause mortality among older adults with frailty. Methods: The prospective cohort study included 5705 community participants aged 60 or above in the National Health and Nutrition Examination Survey (NHANES). Health indicators were selected in the NHANES to obtain the frailty index and sleep duration. The risk of all-cause mortality was estimated by a Cox proportional hazard model. Results: During the follow-up, long sleep duration was associated with higher all-cause mortality (adjusted HR = 1.28, 95% CI 1.03–1.59). The hazard of all-cause mortality was the lowest from the beginning of sleep until sleep duration reached 5.8 hours among older adults with frailty. Discussion: Long sleep duration was associated with higher all-cause mortality among older adults with frailty. There was a U-shaped relationship between sleep duration and all-cause mortality.
Correction of Anticoagulant Therapy in Patients with Severe COVID-19 Virus Infection Using a Thrombodynamics Coagulation Assay
Authors: Vuimo Tatiana S. , Tsarenko Sergey V. , Filimonova Elena V. , Seregina Elena A. , Karamzin Sergey S. 
Published: December 2022

Background The average frequency of thrombosis in patients with COVID-19 is still high despite low molecular weight heparin (LMWH) prophylactic. Global hemostasis assays, particularly thrombodynamics (TD), known to be sensitive to both hypercoagulation and heparin effects, could potentially be useful for individual management of anticoagulant therapy. Methods A total of 74 patients with lung involvement >50% were randomized into two groups: Group A (44 patients) received weight-based dosing of LMWH, and Group B (30 patients) received the first LMWH dose by a weight-based dosing protocol and then received an adjusted dose based on TD daily results. The endpoints of the study were thrombosis and bleeding as well as discharge or death of the patient. Results The incidence of thrombosis was 3 times lower in Group B under TD control compared to Group A without TD control: 7% versus 23 respectively ( p = .05). The relative risk of thrombosis if the average clot growth rate V in TD exceeded the threshold value of 25 μm/min was 14.3 ( p = .0005, 95% confidence interval 3.2-63.7). There were no clinically significant bleeding episodes in Group B while there were 7% in unregulated Group A. Mortality in Group B under TD control was lower than that in Group A without control: 27% versus 36%, respectively ( p = .13). Conclusions The dosing LMWH under thrombodynamics control in severe patients with COVID-19 allows for a significant reduction in thrombotic complications. Long-term hypercoagulation revealed by thrombodynamics (3 and more days) is a strong predictor of thrombosis (AUC = 0.83).
Sugar-free chewing gum versus conventional analgesic drugs for pain relief with fixed orthodontic appliances. A systematic review and meta-analysis
Authors: Jabr Luay , Altuhafy Maryam , Barmak Abdul Basir , Rossouw Paul Emile , Michelogiannakis Dimitrios 
Published: December 2022

Objective: To compare the effect of chewing sugar-free gum towards alleviating self-reported orthodontic treatment (OT) pain compared with conventional analgesic drugs (CADs). Search sources: An unrestricted search of indexed databases and manual searching was performed up to September 2021. Data selection: Randomised controlled trials (RCTs) comparing the impact of chewing gum and CADs on relieving self-reported orthodontic pain were included. Data extraction: Data screening, extraction and risk of bias (RoB) assessment were performed by two authors. Meta-analyses were performed using a random-effects model. The quality of available evidence was assessed using the Grades of Recommendation, Assessment, Development and Evaluation approach. Results: Nine RCTs were included. Eight RCTs used the Visual Analogue Scale for self-reported pain assessment, while one RCT used the Numeric Rating Scale. Five RCTs had a high RoB and four RCTs had a moderate RoB. Power analysis for sample size estimation was performed in six RCTs. Separate meta-analyses were performed by pooling quantitative data from five RCTs that compared self-reported orthodontic pain between chewing gum and ibuprofen groups for the following timepoints: baseline; immediately; 2 hours; 6 hours; bedtime; 24 hours; 2 days; 3 days; 5 days; and 7 days after the placement of orthodontic appliances. None of the timepoints individually indicated a difference in self-reported pain scores between chewing sugar-free gum and ibuprofen groups. The overall level of evidence was very low. Conclusion: Chewing sugar-free gum is a potentially useful alternative to CADs towards pain alleviation during fixed OT.
Subsequent Surgery Up to 10 Years After Osteochondral Allograft and Osteochondral Autograft: An Analysis of More Than 2000 Patients
Authors: Burroughs Patrick J. , Kahan Joseph B. , Moran Jay , Gillinov Stephen M. , Joo Peter Y. , Schneble Christopher A. , Moore Harold G. , Grauer Jonathan N. , Medvecky Michael J. 
Published: December 2022

Background: Osteochondral allograft transplant (OCA) and osteochondral autograft transfer (OAT) replace damaged cartilage with a plug of bone and overlying articular cartilage; however, limited research is available regarding the survival of these osteoarticular grafting procedures. Hypothesis: We hypothesized that patients who underwent OCA would have a higher rate of subsequent surgery over the course of 5 years compared with patients who underwent OAT. Study Design: Cohort study; Level of evidence, 3. Methods: The PearlDiver Mariner administrative database was used to identify patients 10 to 59 years old who had undergone OCA or OAT between 2010 and 2018. All included patients were assessed for subsequent knee surgeries, defined by the occurrence of a subsequent osteochondral procedure (OCA or OAT) or any type of knee arthroplasty for the duration of the time they were included in the data set (maximum of 10 years). Analyses were performed for the total population and those with allograft versus autograft (compared using the Fisher exact test). The 5-year Kaplan-Meier survival curves for operation-free survival were compared using a Mantel-Cox log-rank test. Results: In total, 2598 patients were identified: 1631 patients who underwent OCA (34.5 ± 12.1 years old; 51.6% female) and 967 patients who underwent OAT (32.1 ± 12.9 years old; 51.0% female). Both groups had similarly high rates of subsequent knee surgeries (23.9% vs 21.9%, respectively; P = .249), with no statistical differences in rates of subsequent surgery between groups. Kaplan-Meier survival curves comparing operation-free survival at 5 years indicated no significant difference between the groups (OCA, 88.0% vs OAT, 89.5%; P = .235). Conclusion: Both osteochondral grafting procedures carried a relatively high rate of secondary surgery, which increased with time. The 5-year survival analysis revealed similarly high rates of subsequent surgery.
Zebrafish: an efficient vertebrate model for understanding role of gut microbiota
Authors: Xia Hui , Chen Huimin , Cheng Xue , Yin Mingzhu , Yao Xiaowei , Ma Jun , Huang Mengzhen , Chen Gang , Liu Hongtao 
Published: December 2022

AbstractGut microbiota plays a critical role in the maintenance of host health. As a low-cost and genetically tractable vertebrate model, zebrafish have been widely used for biological research. Zebrafish and humans share some similarities in intestinal physiology and function, and this allows zebrafish to be a surrogate model for investigating the crosstalk between the gut microbiota and host. Especially, zebrafish have features such as high fecundity, external fertilization, and early optical transparency. These enable the researchers to employ the fish to address questions not easily addressed in other animal models. In this review, we described the intestine structure of zebrafish. Also, we summarized the methods of generating a gnotobiotic zebrafish model, the factors affecting its intestinal flora, and the study progress of gut microbiota functions in zebrafish. Finally, we discussed the limitations and challenges of the zebrafish model for gut microbiota studies. In summary, this review established that zebrafish is an attractive research tool to understand mechanistic insights into host-microbe interaction.
GCNCPR-ACPs: a novel graph convolution network method for ACPs prediction
Authors: Wu Xiujin , Zeng Wenhua , Lin Fan 
Published: December 2022

Abstract
Background
Anticancer peptide (ACP) inhibits and kills tumor cells. Research on ACP is of great significance for the development of new drugs, and the prediction of ACPs and non-ACPs is the new hotspot.

Results
We propose a new machine learning-based method named GCNCPR-ACPs (a Graph Convolutional Neural Network Method based on collapse pooling and residual network to predict the ACPs), which automatically and accurately predicts ACPs using residual graph convolution networks, differentiable graph pooling, and features extracted using peptide sequence information extraction. The GCNCPR-ACPs method can effectively capture different levels of node attributes for amino acid node representation learning, GCNCPR-ACPs uses node2vec and one-hot embedding methods to extract initial amino acid features for ACP prediction.

Conclusions
Experimental results of ten-fold cross-validation and independent validation based on different metrics showed that GCNCPR-ACPs significantly outperformed state-of-the-art methods. Specifically, the evaluation indicators of Matthews Correlation Coefficient (MCC) and AUC of our predicator were 69.5% and 90%, respectively, which were 4.3% and 2% higher than those of the other predictors, respectively, in ten-fold cross-validation. And in the independent test, the scores of MCC and SP were 69.6% and 93.9%, respectively, which were 37.6% and 5.5% higher than those of the other predictors, respectively. The overall results showed that the GCNCPR-ACPs method proposed in the current paper can effectively predict ACPs.
Non-negative low-rank representation based on dictionary learning for single-cell RNA-sequencing data analysis
Authors: Wang Juan , Zhang Nana , Yuan Shasha , Shang Junliang , Dai Lingyun , Li Feng , Liu Jinxing 
Published: December 2022

AbstractIn the analysis of single-cell RNA-sequencing (scRNA-seq) data, how to effectively and accurately identify cell clusters from a large number of cell mixtures is still a challenge. Low-rank representation (LRR) method has achieved excellent results in subspace clustering. But in previous studies, most LRR-based methods usually choose the original data matrix as the dictionary. In addition, the methods based on LRR usually use spectral clustering algorithm to complete cell clustering. Therefore, there is a matching problem between the spectral clustering method and the affinity matrix, which is difficult to ensure the optimal effect of clustering. Considering the above two points, we propose the DLNLRR method to better identify the cell type. First, DLNLRR can update the dictionary during the optimization process instead of using the predefined fixed dictionary, so it can realize dictionary learning and LRR learning at the same time. Second, DLNLRR can realize subspace clustering without relying on spectral clustering algorithm, that is, we can perform clustering directly based on the low-rank matrix. Finally, we carry out a large number of experiments on real single-cell datasets and experimental results show that DLNLRR is superior to other scRNA-seq data analysis algorithms in cell type identification.
Machine learning framework for gut microbiome biomarkers discovery and modulation analysis in large-scale obese population
Authors: Liu Yaoliang , Zhu Jinlin , Wang Hongchao , Lu Wenwei , LEE Yuan Kun , Zhao Jianxin , Zhang Hao 
Published: December 2022

Abstract
Background
The gut microbiome has proven to be an important factor affecting obesity; however, it remains a challenge to identify consistent biomarkers across geographic locations and perform precisely targeted modulation for obese individuals.

Results
This study proposed a systematic machine learning framework and applied it to 870 human stool metagenomes across five countries to obtain comprehensive regional shared biomarkers and conduct a personalized modulation analysis. In our pipeline, a heterogeneous ensemble feature selection diagram is first developed to determine an optimal subset of biomarkers through the aggregation of multiple techniques. Subsequently, a deep reinforcement learning method was established to alter the targeted composition to the desired healthy target. In this manner, we can realize personalized modulation by counterfactual inference. Consequently, a total of 42 species were identified as regional shared biomarkers, and they showed good performance in distinguishing obese people from the healthy group (area under curve (AUC) =0.85) when demonstrated on validation datasets. In addition, by pooling all counterfactual explanations, we found that Akkermansia muciniphila, Faecalibacterium prausnitzii, Prevotella copri, Bacteroides dorei, Bacteroides eggerthii, Alistipes finegoldii, Alistipes shahii, Eubacterium sp. _CAG_180, and Roseburia hominis may be potential broad-spectrum targets with consistent modulation in the multi-regional obese population.

Conclusions
This article shows that based on our proposed machine-learning framework, we can obtain more comprehensive and accurate biomarkers and provide modulation analysis for the obese population. Moreover, our machine-learning framework will also be very useful for other researchers to further obtain biomarkers and perform counterfactual modulation analysis in different diseases.
Plant gene silencing signals move from the phloem to influence gene expression in shoot apical meristems
Authors: Minow Mark A. A. , Coneva Viktoriya , Lesy Victoria , Misyura Max , Colasanti Joseph 
Published: December 2022

AbstractBackgroundSmall RNAs (sRNA) are potent regulators of gene expression that can diffuse short distances between cells and move long distances through plant vasculature. However, the degree to which sRNA silencing signals can move from the phloem to the shoot apical meristem (SAM) remains unclear.ResultsTwo independent transgenic approaches were used to examine whether phloem sRNA silencing can reach different domains of the SAM and silence SAM-expressed genes. First, the phloem companion-cell specificSUCROSE-PROTON SYMPORTER2(SUC2) promoter was used to drive expression of an inverted repeat to target theFDgene, an exclusively SAM-localized floral regulator. Second, theSUC2promoter was used to express an artificial microRNA (aMiR) designed to target a syntheticCLAVATA3(CLV3) transgene in SAM stem cells. Both phloem silencing signals phenocopied the loss of function of their targets and altered target gene expression suggesting that a phloem-to-SAM silencing communication axis exists, connecting distal regions of the plant to SAM stem cells.ConclusionsDemonstration of phloem-to-SAM silencing reveals a regulatory link between somatic sRNA expressed in distal regions of the plant and the growing shoot. Since the SAM stem cells ultimately produce the gametes, we discuss the intriguing possibility that phloem-to-SAM sRNA trafficking could allow transient somatic sRNA expression to manifest stable, transgenerational epigenetic changes.