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Accurate acquisition of the distribution of flow parameters inside the supersonic combustor is of great significance for hypersonic flight control. It is an interesting attempt to introduce a data-driven model to a supersonic combustor for flow field prediction. This paper proposes a novel method for predicting the flow field in a dual-mode combustor. A flow field prediction convolutional neural network with multiple branches is built. Numerical investigations for a strut variable geometry combustor have been conducted to obtain flow field data for training the network as a flow field prediction model. Rich flow field data are obtained by changing the equivalent ratio, incoming flow condition and geometry of the supersonic combustor. The Mach number distribution can be obtained from the trained flow field prediction model using the combustor wall pressure as input with high accuracy. The accuracy of flow field prediction is discussed in several aspects. Further, the combustion mode detection is implemented on the prediction flow field.

Using natural bamboo fibers (BFs) and nano-SiO2 particles together can produce a certain synergistic effects, which may have a better toughening and strengthening effects than using any one of them separately. This study aims to investigate the effect of natural BFs and nano-SiO2 particles on the mechanical, physical characteristics and erosive wear performances of the BFs/SiO2/epoxy-based ternary composites. The samples were characterized using mechanical and physical testing, Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM) and modified abrasive water jet device. The results showed that the fracture toughness and impact strength of polymer composites were significantly improved; this could be attributed to the excellent strengthening and toughening effects of the natural BFs and nano-silica particles. Additionally, the presence of the natural BFs and nano-SiO2 particles were found not only influence the toughness of the epoxy resin but also the absorptions of the kinetic energy of impact abrasive particles. It was observed that the maximum depth of the pit left on the composite was decreased when the BFs and SiO2 were added. As a result, the BFs/SiO2/epoxy-based ternary composites have improved mechanical and erosive wear properties, especially when the content of natural BFs is 15 wt% and modified nano-scale SiO2 is 3 wt%.

The mixing state of the fuel determines whether the scramjet combustor can work with high performance. The flow field structure and mixing characteristics of the supersonic combustor are studied by using large eddy simulation. The combustor is equipped with struts and uses gaseous kerosene as fuel. The particularity of the strut is that a row of holes in the tail edge of the strut can inject oxygen into the combustor to enhance mixing. First, the flow field structure without oxygen supplementation is studied, and the evolution rule of the flow direction vortex is analyzed. Second, the mixing performance of the fuel and oxidant is evaluated using mixing efficiency. The mixing performance of the combustor under different fuel injection momentum flux ratios is discussed. Then, the differences in the mixing characteristics of the combustor with and without supplemental oxygen are compared. The influence of different fuel/oxygen momentum flux ratio combinations on mixing performance and flow field characteristics is considered. The effect of oxygen supplementation on the fuel diffusion volume is given at last. The results of this work show that oxygen supplementation can change the flow field characteristics and fuel transportation, and significantly improve the mixing performance.

For thousands of years, caries, periodontitis and mucosal diseases, which are closely related to oral microorganisms, have always affected human health and quality of life. These complex microbiota present in different parts of the mouth can cause chronic infections in the oral cavity under certain conditions, some of which can also lead to acute and systemic diseases. With the mutation of related microorganisms and the continuous emergence of drug-resistant strains, in order to prevent and treat related diseases, in addition to the innovation of diagnosis and treatment technology, the development of new antimicrobial drugs is also important. Catechins are polyphenolic compounds in green tea, some of which are reported to provide health benefits for a variety of diseases. Studies have shown that epigallocatechin-3-gallate (EGCG) is the most abundant and effective active ingredient in green tea catechins, which acts against a variety of gram-positive and negative bacteria, as well as some fungi and viruses. This review aims to summarize the research progress on the activity of EGCG against common oral disease-associated organisms and discuss the mechanisms of these actions, hoping to provide new medication strategies for the prevention and treatment of oral infectious diseases, the future research of EGCG and its translation into clinical practice are also discussed.

The generalization ability and robustness of data-driven models deteriorate when samples are scarce or input features are outside the training sample space. This research focuses on building a data assimilation (DA) framework that embeds the time sequence prediction model and improves the prediction results by constructing an enhanced system state vector that incorporates model bias parameters and new observation data to achieve the deviation correction and improve the robustness of the model. The DA framework proposed in this study includes three steps: prediction model inference, ensemble Kalman filter (EnKF) online deployment, and model parameter update. Wind tunnel experiments of a supersonic cascade are performed to obtain the original data for training the prediction model and optimizing the DA framework. Long short-term memory network (LSTM) was chosen as the prediction model. The testing set is distributed outside the sample space of the training set to verify the effectiveness of the DA framework for enhancing the time sequence prediction model. The improvement effects of the EnKF-enhanced LSTM model on the time sequence prediction results of the wall pressure in the oscillating flow field and the non-oscillating flow field are studied. The optimization results indicate that the LSTM model embedded in the DA framework can significantly improve the wall pressure prediction results. Thus, the results of this study lay a solid foundation for the condition monitoring and margin determination of the supersonic cascade flow field.

Abstract Lysine (K)-specific demethylase 6B (KDM6B), a stress-inducible H3K27me3 demethylase, plays oncogenic or antitumoral roles in malignant tumors depending on the type of tumor cell. However, how this histone modifier affects the progression of prostate cancer (PCa) is still unknown. Here we analyzed sequenced gene expression data and tissue microarray to explore the expression features and prognostic value of KDM6B in PCa. Further, we performed in vitro cell biological experiments and in vivo nude mouse models to reveal the biological function, upstream and downstream regulation mechanism of KDM6B. In addition, we investigated the effects of a KDM6B inhibitor, GSK-J4, on PCa cells. We showed that KDM6B overexpression was observed in PCa, and elevated KDM6B expression was associated with high Gleason Score, low serum prostate-specific antigen level and shorted recurrence-free survival. Moreover, KDM6B prompted proliferation, migration, invasion and cell cycle progression and suppressed apoptosis in PCa cells. GSK-J4 administration could significantly suppress the biological function of KDM6B in PCa cells. KDM6B is involved in the development of castration-resistant prostate cancer (CRPC), and combination of MDV3100 plus GSK-J4 is effective for CRPC and MDV3100-resistant CRPC. Mechanism exploration revealed that androgen receptor can decrease the transcription of KDM6B and that KDM6B demethylates H3K27me3 at the cyclin D1 promoter and cooperates with smad2/3 to prompt the expression of cyclin D1. In conclusion, our study demonstrates that KDM6B is an androgen receptor regulated gene and plays oncogenic roles by promoting cyclin D1 transcription in PCa and GSK-J4 has the potential to be a promising agent for the treatment of PCa.

Abstract Background Brain is one of the most common target organ of lung cancer metastasis, while descriptions of intraventricular carcinomatosis could hardly be found among previous cases. To date no cases from lung adenocarcinoma have been reported in the literature. Case presentation We report here a case of multiple intraventricular metastases from lung adenocarcinoma with EGFR G719X mutation. This 64-year-old woman was referred to our hospital with complaints of dizziness and vomiting. Target therapy with afatinib was initiated and the lesions in both lung and brain achieved good partial responses. Conclusions This case report revealed a phenomenon of rare intraventricular metastasis from lung cancer, which should be carefully distinguished from primary ventricular tumors. Compared to brain parenchyma metastasis, intraventricular lesions would cause more severe symptoms which may be rapidly progressive. Target therapy could become a potential option in such patients with non-drugresistant EGFR mutations.

Membrane-associated guanylate kinase (MAGUK) family protein MAGUK invert 2 (MAGI-2) has been demonstrated to be involved in the tumorigenic mechanism of prostate cancer. The objective of this study was to investigate the expression of MAGI-2 at mRNA and protein levels. The prognostic value of MAGI-2 in Han Chinese patients with prostate cancer was also investigated. The expression data of MAGI-2 were assessed through database retrieval, analysis of sequencing data from our group, and tissue immunohistochemistry using digital scoring system (H-score). The clinical, pathological, and follow-up data were collected. The expression of MAGI-2 in prostate tumor tissues and prostate normal tissues was evaluated and compared. MAGI-2 expression was associated with clinical parameters including tumor stage, lymph node status, Gleason score, PSA level, and biochemical recurrence of prostate cancer. The relative expression of MAGI-2 mRNA was lower in the tumor tissue in The Cancer Genome Atlas (TCGA) database and sequencing data (P < 0.001). There was no difference in MAGI-2 protein expression between tumor and normal tissues in tissue microarray (TMA) results. MAGI-2 expression was associated with pathological tumor stage (P = 0.02), Gleason score (P = 0.05), and preoperation prostate-specific antigen (PSA; P = 0.04). A positive correlation was identified between MAGI-2 and phosphatase and tensin homolog deleted on chromosome 10 (PTEN) expressions through the analysis of TCGA and TMA data (P < 0.0001). Patients with higher MAGI-2 expression had longer biochemical recurrence-free survival in the univariate analysis (P = 0.005), which indicates an optimal prognostic value of MAGI-2 in Han Chinese patients with prostate cancer. In conclusion, MAGI-2 expression gradually decreases with tumor progression, and can be used as a predictor of tumor recurrence in Chinese patients.

MicroRNA (miRNA)-mediated gene regulation is involved in various physiological processes in plants. Flower color is one of the vital ornamental traits of tree peony (Paeonia suffruticosa Andr.). However, the yellow-flowered tree peony cultivars are particularly rare. To elucidate the miRNA-mediated gene regulatory mechanism underlying yellow pigmentation in tree peony, we combined pigment assessment, miRNA identification, expression analysis, and gene functional verification in two contrasting flower color cultivars “High Noon” and “Roufurong.” Flavones/flavonols and anthocyanins were found to be the main contributors to the coloration of “High Noon” and “Roufurong” petals, respectively. Subsequently, miRNA analysis based on available genome data identified 9 differentially expressed miRNAs and 12 relevant target genes implicated in flavonoid biosynthesis. Their dynamic expression patterns determined the key role of mdm-miR156b-PsSPL2 module in yellow pigmentation of tree peony flowers. The sequence analysis and subcellular localization validated that PsSPL2 might function as a nuclear-localized transcription factor. Overexpression of PsSPL2 in tobacco resulted in a decrease of anthocyanin content and down-regulation of NtF3′H and NtDFR transcripts. PsSPL2-silenced petals exhibited lighter yellow color, and the contents of THC, Ap, and Ch decreased significantly. Meanwhile, expression levels of PsCHS, PsCHI, and PsF3H were significantly decreased in the petals with PsSPL2 silencing, while those of PsF3′H and PsDFR were remarkably increased. This study offers a novel insight into yellow pigmentation-related miRNA regulation network in tree peony, and further provides the valuable information on physiological changes during yellow coloring process of tree peony.

The pursuit of high-resolution flow fields is meaningful for the development of hypersonic technology. Flow field super-resolution (SR) based on deep learning is a novel and effective method to provide HR flow fields in a scramjet isolator. Single-path and multiple-path network models based on convolutional neural networks (CNNs) have been developed to augment the spatial resolution of the experimental supersonic flow field. The single-path model uses a simple convolutional layer and fully connected layer serial architecture, and the multiple-path model increases the branch path by adding pooling layers to achieve a fusion structure architecture. Ground experiments of flow in a supersonic isolator at various working conditions are conducted to establish an experimental dataset. The trained single-path and multiple-path CNNs are compared with the traditional interpolation method on the flow field SR reconstruction accuracy. The results demonstrated that single-path CNNs have certain learning ability, but the SR accuracy is not satisfactory; multiple-path CNNs significantly improve the accuracy of flow field SR, and the multiple-path CNN with one branch path achieves the best SR performance.

A general super-resolution (SR) reconstruction strategy is proposed to address the super-resolution reconstruction of temperature fields from low-resolution coarse temperature field data using convolutional neural networks. Two deep learning (DL) models were applied to augment the spatial resolution of temperature fields. One is the classical super-resolution convolutional neural network, and the other is the novel multiple path super-resolution convolutional neural network (MPSRC). Three paths with and without a pooling layer are designed in the MPSRC to fully capture spatial distribution features of temperature. Numerical simulations of combustion in a strut scramjet combustor at various Mach numbers are carried out to establish a dataset for network training and testing. The corresponding high-resolution temperature fields were successfully reconstructed with remarkable accuracy. The reconstruction performances of those models were comprehensively investigated and compared with the bicubic interpolation method. The results demonstrated that both DL methods can greatly improve the super-resolution reconstruction accuracy and the MPSRC can provide a better reconstruction result with a lower mean square error and a higher peak signal-to-noise ratio.

A data-driven model containing a symmetrical deep neural network is proposed to reconstruct the flow field structure in a cascade channel by measuring discrete pressure values on the wall of the supersonic cascade channel. The model designed is to demonstrate that the deep neural network can realize the reconstruction and prediction of the flow field structure in the supersonic cascade channel under complicated and changing working conditions. The dataset used for model training is derived from numerical simulation of the supersonic cascade channel. The symmetrical model includes a transposed convolution part and a conventional convolution part, which, respectively, implement up-sampling of the pressure data and further extraction of features. The generalization ability and scalability of the model are analyzed from the contour plots of the pressure and density gradient. In order to verify the ability of the model to reconstruct unknown operating conditions, the organizational form of the training set and testing set has been specially designed to achieve the ability of interpolating outwards. In the testing set, the symmetrical model has a certain ability to realize extrapolation and prediction, and the flow field structure can be accurately reconstructed by using the discrete pressure values on the wall surface of the cascade channel. Moreover, to accurately evaluate the regression model proposed by this study, the correlation analysis was also applied in this study. The results show that the worst linear correlation coefficient is 0.9848 in the testing set, indicating that the model has satisfactory ability to reconstruct and predict the flow field.

BackgroundA composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data.MethodsWe assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation.ResultsThe analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals.ConclusionThe GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

Rab5, the prototypical Rab GTPase and master regulator of the endocytic pathway, is encoded as three differentially expressed isoforms, Rab5A, Rab5B and Rab5C. Here, we examined the differential effects of Rab5 isoform silencing on cell motility and report that Rab5C, but neither Rab5A nor Rab5B, is selectively associated with the growth factor-activation of Rac1 and with enhanced cell motility. Initial observations revealed that silencing of Rab5C expression, but neither Rab5A nor Rab5C, led to spindle-shaped cells that displayed reduced formation of membrane ruffles. When subjected to a scratch wound assay, cells depleted of Rab5C, but not Rab5A or Rab5B, demonstrated reduced cell migration. U937 cells depleted of Rab5C also displayed reduced cell motility in a Transwell plate migration assay. To examine activation of Rac, HeLa cells stably expressing GFP-Rac1 were independently depleted of Rab5A, Rab5B or Rab5C and seeded onto coverslips imprinted with a crossbow pattern. 3-D GFP-Rac1 images of micro-patterned cells show that GFP-Rac1 was less localized to the cell periphery in the absence of Rab5C. To confirm the connection between Rab5C and Rac activation, HeLa cells depleted of Rab5 isoforms were starved and then stimulated with EGF. Rac1 pull-down assays revealed that EGF-stimulated Rac1 activity was significantly suppressed in Rab5C-suppressed cells. To determine whether events upstream of Rac activation were affected by Rab5C, we observed that EGF-stimulated Akt phosphorylation was suppressed in cells depleted of Rab5C. Finally, since spatio-temporal assembly/disassembly of adhesion complexes are essential components of cell migration, we examined the effect of Rab5 isoform depletion on the formation of focal adhesion complexes. Rab5C-depleted HeLa cells have significantly fewer focal adhesion foci, in accordance with the lack of persistent lamellipodial protrusions and reduced directional migration. We conclude that Rab5 isoforms selectively oversee the multiple signaling and trafficking events associated with the endocytic network.

Expression of the hominoid-specific TBC1D3 oncoprotein enhances growth factor receptor signaling and subsequently promotes cellular proliferation and survival. Here we report that TBC1D3 is degraded in response to growth factor signaling, suggesting that TBC1D3 expression is regulated by a growth factor-driven negative feedback loop. To gain a better understanding of how TBC1D3 is regulated, we studied the effects of growth factor receptor signaling on TBC1D3 post-translational processing and turnover. Using a yeast two-hybrid screen, we identified CUL7, the scaffolding subunit of the CUL7 E3 ligase complex, as a TBC1D3-interacting protein. We show that CUL7 E3 ligase ubiquitinates TBC1D3 in response to serum stimulation. Moreover, TBC1D3 recruits F-box 8 (Fbw8), the substrate recognition domain of CUL7 E3 ligase, in pull-down experiments and in an in vitro assay. Importantly, alkaline phosphatase treatment of TBC1D3 suppresses its ability to recruit Fbw8, indicating that TBC1D3 phosphorylation is critical for its ubiquitination and degradation. We conclude that serum- and growth factor-stimulated TBC1D3 ubiquitination and degradation are regulated by its interaction with CUL7-Fbw8.

Insulin/IGF-1 signaling plays a pivotal role in the regulation of cellular homeostasis through its control of glucose metabolism as well as due to its effects on cell proliferation. Aberrant regulation of insulin signaling has been repeatedly implicated in uncontrolled cell growth and malignant transformations. TBC1D3 is a hominoid specific gene previously identified as an oncogene in breast and prostate cancers. Our efforts to identify the molecular mechanisms of TBC1D3-induced oncogenesis revealed the role of TBC1D3 in insulin/IGF-1 signaling pathway. We document here that TBC1D3 intensifies insulin/IGF-1-induced signal transduction through intricate, yet elegant fine-tuning of signaling mechanisms. We show that TBC1D3 expression substantially delayed ubiquitination and degradation of insulin receptor substrate-1 (IRS-1). This effect is achieved through suppression of serine phosphorylation at S636/639, S307 and S312 of IRS-1, which are key phosphorylation sites required for IRS-1 degradation. Furthermore, we report that the effect of TBC1D3 on IRS-1:S636/639 phosphorylation is mediated through TBC1D3-induced activation of protein phosphatase 2A (PP2A), followed by suppression of T389 phosphorylation on p70 S6 kinase (S6K). TBC1D3 specifically interacts with PP2A regulatory subunit B56γ, indicating that TBC1D3 and PP2A B56γ operate jointly to promote S6K:T389 dephosphorylation. These findings suggest that TBC1D3 plays an unanticipated and potentially unique role in the fine-tuning of insulin/IGF-1 signaling, while providing novel insights into the regulation of tumorigenesis by a hominoid-specific protein.

The DegreePlus program at Western Carolina University is a newly developed initiative to help students develop transferable skills, including professionalism, cultural responsiveness, leadership and teamwork, by attendance at specific extracurricular events. The program was first implemented in the 2017-2018 academic year as a pilot with Honors College students, conditionally admitted students and students in specific living-learning communities. Participation by these student groups was encouraged through targeted marketing, transition courses, required attendance at DegreePlus events, and gamification. This research addresses how these methods impacted student participation. We concluded that requiring early participation influenced some students to continue their involvement in DegreePlus, and gamification helped students get interested in the program, but students also recognized the intrinsic value of the program and planned to continue their involvement. Targeted marketing helped to increase awareness and understanding of the program and how it works.

Chronic lung allograft dysfunction (CLAD) remains the major complication limiting long-term survival among lung transplant recipients (LTRs). Limited understanding of CLAD immunopathogenesis and a paucity of biomarkers remain substantial barriers for earlier detection and therapeutic interventions for CLAD. We hypothesized the airway transcriptome would reflect key immunologic changes in disease. We compared airway brush-derived transcriptomic signatures in CLAD (n = 24) versus non-CLAD (n = 21) LTRs. A targeted assessment of the proteome using concomitant bronchoalveolar lavage (BAL) fluid for 24 cytokines/chemokines and alloimmune T cell responses was performed to validate the airway transcriptome. We observed an airway transcriptomic signature of differential genes expressed (DGEs) in CLAD marked by Type-1 immunity and striking upregulation of two endogenous immune regulators: indoleamine 2, 3 dioxygenase 1 (IDO-1) and tumor necrosis factor receptor superfamily 6B (TNFRSF6B). Advanced CLAD staging was associated with a more intense airway transcriptome signature. In a validation cohort using the identified signature, we found an area under the curve (AUC) of 0.77 for CLAD LTRs. Targeted proteomic analyses revealed a predominant Type-1 profile with detection of IFN-γ, TNF-α, and IL-1β as dominant CLAD cytokines, correlating with the airway transcriptome. The airway transcriptome provides novel insights into CLAD immunopathogenesis and biomarkers that may impact diagnosis of CLAD.

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has rapidly involved the entire world and exposed the pressing need for collaboration between public health and other stakeholders from the clinical, scientific, regulatory, pharmaceutical, and medical device and technology communities. To discuss how to best protect people with diabetes from serious outcomes from COVID-19, Diabetes Technology Society, in collaboration with Sansum Diabetes Research Institute, hosted the "International COVID-19 and Diabetes Virtual Summit" on August 26-27, 2020. This unique, unprecedented real-time conference brought together physicians, scientists, government officials, regulatory experts, industry representatives, and people with diabetes from six continents to review and analyze relationships between COVID-19 and diabetes. Over 800 attendees logged in. The summit consisted of five sessions: (I) Keynotes, (II) Preparedness, (III) Response, (IV) Recovery, and (V) Surveillance; eight parts: (A) Background, (B) Resilience, (C) Outpatient Care, (D) Inpatient Care, (E) Resources, (F) High-Risk Groups, (G) Regulation, and (H) The Future; and 24 sections: (1) Historic Pandemics and Impact on Society, (2) Pathophysiology/Risk Factors for COVID-19, (3) Social Determinants of COVID-19, (4) Preparing for the Future, (5) Medications and Vaccines, (6) Psychology of Patients and Caregivers, (7) Outpatient Treatment of Diabetes Mellitus and Non-Pharmacologic Intervention, (8) Technology and Telehealth for Diabetes Outpatients, (9) Technology for Inpatients, (10) Management of Diabetes Inpatients with COVID-19, (11) Ethics, (12) Accuracy of Diagnostic Tests, (13) Children, (14) Pregnancy, (15) Economics of Care for COVID-19, (16) Role of Industry, (17) Protection of Healthcare Workers, (18) People with Diabetes, (19) International Responses to COVID-19, (20) Government Policy, (21) Regulation of Tests and Treatments, (22) Digital Health Technology, (23) Big Data Statistics, and 24) Patient Surveillance and Privacy. The two keynote speeches were entitled (1) COVID-19 and Diabetes-Meeting the Challenge and (2) Knowledge Gaps and Research Opportunities for Diabetes and COVID-19. While there was an emphasis on diabetes and its interactions with COVID-19, the panelists also discussed the COVID-19 pandemic in general. The meeting generated many novel ideas for collaboration between experts in medicine, science, government, and industry to develop new technologies and disease treatment paradigms to fight this global pandemic.

Abstract Background Diabetes is a common disease with self-management a key aspect of care. Large prospective trials have shown that maintaining glycated hemoglobin less than 7% greatly reduces complications but translating this level of control into everyday clinical practice can be difficult. Intensive improvement programs are successful in attaining control in patients with type 2 diabetes, however, many patients experience glycemic relapse once returned to routine care. This early relapse is, in part, due to decreased adherence in self-management behaviors. Objective This paper describes the design of the Glycemic Relapse Prevention study. The purpose of this study is to determine the optimal frequency of maintenance intervention needed to prevent glycemic relapse. The primary endpoint is glycemic relapse, which is defined as glycated hemoglobin greater than 8% and an increase of 1% from baseline. Methods The intervention consists of telephonic contact by a nurse practitioner with a referral to a dietitian if indicated. This intervention was designed to provide early identification of self-care problems, understanding the rationale behind the self-care lapse and problem solve to find a negotiated solution. A total of 164 patients were randomized to routine care (least intensive), routine care with phone contact every three months (moderate intensity) or routine care with phone contact every month (most intensive). Conclusion The baseline patient characteristics are similar across the treatment arms. Intervention fidelity analysis showed excellent reproducibility. This study will provide insight into the important but poorly understood area of glycemic relapse prevention.

Summary: Background: Up to 50% of adolescents who undergo metabolic and bariatric surgery (MBS) have obesity 3 years post‐MBS, placing them at continued risk for the consequences of obesity. Objectives: We conducted an open‐label, 16‐week pilot study of liraglutide in adolescents with obesity after sleeve gastrectomy (SG) to investigate liraglutide effects on weight and body mass index (BMI) post‐SG. Methods: Adolescents aged 12–20.99 years with obesity and a history of SG ≥1 year prior were enrolled. Liraglutide was initiated at 0.6 mg/day, escalated weekly to a maximum of 3 mg/day, with treatment duration 16 weeks. Fasting laboratory assessments and an oral glucose tolerance test were performed at baseline and end‐treatment. Results: A total of 43 participants were screened, 34 initiated liraglutide (baseline BMI 41.2 ± 7.7 kg/m2), and 31 (91%) attended the end‐treatment visit. BMI decreased by 4.3% (p < 0.001) with liraglutide. Adolescents who had poor initial response to SG (<20% BMI reduction at BMI nadir) had less weight loss with liraglutide. Fasting glucose and haemoglobin A1C concentrations significantly decreased. There were no serious treatment‐emergent adverse events reported. Conclusions: Liraglutide treatment was feasible and associated with a BMI reduction of 4.3% in adolescents who had previously undergone SG, quantitatively similar to results obtained in adolescents with obesity who have not undergone MBS. [ABSTRACT FROM AUTHOR]

Background/Objectives: Attention bias (AB) toward food is associated with obesity, but it is unclear if programs designed to reduce AB can impact adolescents' eating behavior. We investigated whether a two-week, smartphone-delivered attention retraining (AR) program (vs a control program) altered food AB in adolescent girls with overweight. Methods: Participants completed three food-cue visual-probe trainings/day. The AR and control programs directed attention away from food stimuli during 100% and 50% of trainings, respectively. Before and after completion of the programs, girls completed a food-cue visual-probe task while undergoing magnetoencephalography (MEG), and then a laboratory test meal. Results: Sixty-eight adolescents were randomized; 58 completed post-program visits. There was minimal effect of condition on AB scores (β [95%CI] = −1.9 [−20.8, 16.9]; d = −0.06). There was a small effect of condition on energy intake (EMMcontrol = 1017 kcal, EMMAR = 1088 kcal, d = 0.29). Within the AR group, there was slightly blunted initial engagement in brain areas associated with reward response and subsequent increased goal-directed attention and action control. Conclusions: We found preliminary support for efficacy of an intensive smartphone-delivered AR program to alter neural correlates of attention processing in adolescent girls with overweight or obesity. Studies with larger sample sizes are needed to elucidate if AR trainings disrupt the link between food AB and eating behavior. [ABSTRACT FROM AUTHOR]

Respiratory viral infections remain a leading cause of morbidity and mortality. Using a murine model of human metapneumovirus, we identified recruitment of a C1q-expressing inflammatory monocyte population concomitant with viral clearance by adaptive immune cells. Genetic ablation of C1q led to reduced CD8+ T-cell function. Production of C1q by a myeloid lineage was necessary to enhance CD8+ T-cell function. Activated and dividing CD8+ T cells expressed a C1q receptor, gC1qR. Perturbation of gC1qR signaling led to altered CD8+ T-cell IFN-γ production, metabolic capacity, and cell proliferation. Autopsy specimens from fatal respiratory viral infections in children exhibited diffuse production of C1q by an interstitial population. Humans with severe coronavirus disease (COVID-19) infection also exhibited upregulation of gC1qR on activated and rapidly dividing CD8+ T cells. Collectively, these studies implicate C1q production from monocytes as a critical regulator of CD8+ T-cell function following respiratory viral infection. [ABSTRACT FROM AUTHOR]

Writing is often difficult for individuals with autism spectrum disorder (ASD), yet relatively little literature exists that profiles specific strengths and needs within this area. This preliminary investigation compares the written language skills of adolescents with ASD without intellectual disability (n = 14) to typically developing (TD) adolescents (n = 12). Writing samples from persuasive, expository, and narrative genres were elicited. Variables of sample length, writing productivity, syntax, lexical diversity, and macrostructure were analyzed. In the persuasive and expository genres, the ASD group scored significantly lower than the TD group on sample length and some aspects of macrostructure. The ASD group scored higher than the TD group on lexical diversity in the persuasive genre. Other comparisons yielded large effect sizes but were not statistically significant.

Despite the discovery of key pattern recognition receptors and CD4+ T cell subsets in laboratory mice, there is ongoing discussion of the value of murine models to reflect human disease. Pneumocystis is an AIDS-defining illness, in which risk of infection is inversely correlated with peripheral CD4+ T cell counts. Due to medical advances in the control of HIV, the current epidemiology of Pneumocystis infection is predominantly due to primary human immunodeficiencies and immunosuppressive therapies. To this end, we found that every human genetic immunodeficiency associated with Pneumocystis infection that has been tested in mice recapitulated susceptibility. For example, humans with a loss-of-function IL21R mutation are severely immunocompromised. We found that IL-21R, in addition to CD4+ T cell intrinsic STAT3 signaling, were required for generating protective antifungal class-switched antibody responses, as well as effector T cell-mediated protection. Furthermore, CD4+ T cell intrinsic IL-21R/STAT3 signaling was required for CD4+ T cell effector responses, including IL-22 production. Recombinant IL-22 administration to Il21r-/- mice induced the expression of a fungicidal peptide, cathelicidin antimicrobial peptide, which showed in vitro fungicidal activity. In conclusion, SPF laboratory mice faithfully replicate many aspects of human primary immunodeficiency and provide useful tools to understand the generation and nature of effector CD4+ T cell immunity.