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Abstract Background Laparoscopic Sleeve Gastrectomy (LSG) and Laparoscopic Roux-en-Y Gastric Bypass (LRYGB) are the two most commonly performed bariatric surgeries for the treatment of obesity. This meta-analysis was performed with the aim of summarizing the available evidence on weight loss, remission of comorbidities, and quality of life in LRYGB and LSG, complementing the current literature. Methods We searched PubMed, EMBASE and the Cochrane Library from January 2012 to June 2023 for randomized controlled trials and non-randomized interventional studies. We finally selected 18 eligible studies. Results LRYGB resulted in greater weight loss compared with LSG at 5 years [WMD= -7.65 kg/m², 95% confidence interval (CI) -11.54 to -3.76, P = 0.0001], but there exists high heterogeneity with I²=84%. Resolution rate of type 2 diabetes mellitus (T2D) (OR = 0.60, 95%Cl 0.41–0.87, p = 0.007) and dyslipidemia (OR = 0.44, 95%Cl 0.23–0.84, p = 0.01) was higher in the LRYGB group than that in the LSG group at 5 years. There was no difference between LRYGB and LSG for remission of hypertension, and obstructive sleep apnea. No differences were observed in the QoL after LRYGB or LSG. Morbidity was lower in the LSG group (WMD = -0.07, 95% CI: -0.13, -0.02, P = 0.01) than in the LRYGB group. No statistically significant difference was found in mortality between the two procedures. Conclusion At 5 years after surgery, LRYGB resulted in greater weight loss and achieved better remission rate of T2D and dyslipidemia than LSG. However, LSG has a lower morbidity rate than that of LRYGB.

Abstract Purpose The temporal evolution of ventricular trabecular complexity and its correlation with major adverse cardiovascular events (MACE) remain indeterminate in patients presenting with acute ST elevation myocardial infarction (STEMI). Methods This retrospective analysis enrolled patients undergoing primary percutaneous coronary intervention (pPCI) for acute STEMI, possessing cardiac magnetic resonance (CMR) data in the acute (within 7 days), subacute (1 month after pPCI), and chronic phases (6 months after pPCI) from January 2015 to January 2020 at the three participating sites. Fractal dimensions (FD) were measured for the global, infarct, and remote regions of left ventricular trabeculae during each phase. The potential association of FD with MACE was analyzed using multivariate Cox regression. Results Among the 200 analyzed patients (182 men; median age, 61 years; age range, 50–66 years), 37 (18.5%) encountered MACE during a median follow-up of 31.2 months. FD exhibited a gradual decrement (global FD at acute, subacute, and chronic phases: 1.253 ± 0.049, 1.239 ± 0.046, 1.230 ± 0.045, p

Multiple research groups have consistently underscored the intricate interplay between the microbiome and apical periodontitis. However, the presence of variability in experimental design and quantitative assessment have added a layer of complexity, making it challenging to comprehensively assess the relationship. Through an unbiased methodological refinement analysis, we re-analyzed 4 microbiota studies including 120 apical samples from infected teeth (with/without root canal treatment), healthy teeth, using meta-analysis and machine learning. With high-performing machine-learning models, we discover disease signatures of related species and enriched metabolic pathways, expanded understanding of apical periodontitis with potential therapeutic implications. Our approach employs uniform computational tools across datasets to leverage statistical power and define a reproducible signal potentially linked to the development of secondary apical periodontitis (SAP).

ObjectiveTo investigate the effect of walnut oligopeptides (WOPs) on digestive function-related gastric secretion and blood/serum indicators in rats and on small intestinal propulsion in mice.MethodsTotally 130 male Sprague-Dawley (SD) rats and 70 male ICR mice were included in the study. The SD rats were first randomly divided into two subgroups (70 in subgroup Ⅰ and 60 in subgroup Ⅱ). The 70 SD rats of subgroup I and the 70 ICR mice were then randomly assigned into three control groups (normal, model, and whey protein control), three WOPs treatment groups (at dosages of 220, 440 and 880 mg/kg·bw), and a WOPs plus bovine collagen oligopeptides (BCOPs), with 10 rats or mice in each group respectively. The group-specific treatment was conclucted by intragastric administration of once a day for 30 days for the rats and 7 days for the mice; the grouping and treatments in 60 SD rats of subgroup II were the same as those of subgroup I, except for the absence of model control group. By the end of the treatments, the rats of subgroup I underwent pyloric ligation and collection of gastric fluid for detecting gastric acid and gastric tissue pepsin and serum gastrointestinal-associated regulatory hormones were also measured; while, the rats of subgroup II had choledochal cannula for bile collection. After 7-day′s treatment, the mice had another gavage of loperamide hydrochloride for examination of small intestinal propulsive function. ResultsCompared with those in the model control group, the free acid, total acid and total acid excretion of gastric juice were significantly higher and the pepsin activity was significantly lower in the WOPs dose groups (all P < 0.05). The content of growth inhibitory hormone in high WOPs dose (880 mg/kg·bw) group was significantly lower than that in the model control group; the rats with medium (440 mg/kg·bw) and high (880 mg/kg·bw) WOPs treatment and combined treatment of WOPs and BCOPs had significantly higher motilin, substance P, and gastrin than those in the rats of model control group. The small intestinal propulsion rates of the mice in WOPs dose groups were significantly higher than that of model control mice (P < 0.05 for all). ConclusionWOPs can exert pro-digestive effect by regulating the secretions of gastric acid, pepsin, gastrointestinal hormone in rats and by promoting gastrointestinal peristalsis in mice.

The term “glymphatic” emerged roughly a decade ago, marking a pivotal point in neuroscience research. The glymphatic system, a glial-dependent perivascular network distributed throughout the brain, has since become a focal point of investigation. There is increasing evidence suggesting that impairment of the glymphatic system appears to be a common feature of neurodegenerative disorders, and this impairment exacerbates as disease progression. Nevertheless, the common factors contributing to glymphatic system dysfunction across most neurodegenerative disorders remain unclear. Inflammation, however, is suspected to play a pivotal role. Dysfunction of the glymphatic system can lead to a significant accumulation of protein and waste products, which can trigger inflammation. The interaction between the glymphatic system and inflammation appears to be cyclical and potentially synergistic. Yet, current research is limited, and there is a lack of comprehensive models explaining this association. In this perspective review, we propose a novel model suggesting that inflammation, impaired glymphatic function, and neurodegenerative disorders interconnected in a vicious cycle. By presenting experimental evidence from the existing literature, we aim to demonstrate that: (1) inflammation aggravates glymphatic system dysfunction, (2) the impaired glymphatic system exacerbated neurodegenerative disorders progression, (3) neurodegenerative disorders progression promotes inflammation. Finally, the implication of proposed model is discussed.

The advancement of deep learning has resulted in significant improvements on various visual tasks. However, deep neural networks (DNNs) have been found to be vulnerable to well-designed adversarial examples, which can easily deceive DNNs by adding visually imperceptible perturbations to original clean data. Prior research on adversarial attack methods mainly focused on single-task settings, i.e., generating adversarial examples to fool networks with a specific task. However, real-world artificial intelligence systems often require solving multiple tasks simultaneously. In such multi-task situations, the single-task adversarial attacks will have poor attack performance on the unrelated tasks. To address this issue, the generation of multi-task adversarial examples should leverage the generalization knowledge among multiple tasks and reduce the impact of task-specific information during the generation process. In this study, we propose a multi-task adversarial attack method to generate adversarial examples from a multi-task learning network by applying attention distraction with gradient sharpening. Specifically, we first attack the attention heat maps, which contain more generalization information than feature representations, by distracting the attention on the attack regions. Additionally, we use gradient-based adversarial example-generating schemes and propose to sharpen the gradients so that the gradients with multi-task information rather than only task-specific information can make a greater impact. Experimental results on the NYUD-V2 and PASCAL datasets demonstrate that the proposed method can improve the generalization ability of adversarial examples among multiple tasks and achieve better attack performance.

Chronic obstructive pulmonary disease (COPD) is a major public health concern, affecting estimated 164 million people worldwide. Early detection and intervention strategies are essential to reduce the burden of COPD, but current screening approaches are limited in their ability to accurately predict risk. Machine learning (ML) models offer promise for improved accuracy of COPD risk prediction by combining genetic and electronic medical record data. In this study, we developed and evaluated eight ML models for primary screening of COPD utilizing routine screening data, polygenic risk scores (PRS), additional clinical data, or a combination of all three. To assess our models, we conducted a retrospective analysis of approximately 329,396 patients in the UK Biobank database. Incorporating personal information and blood biochemical test results significantly improved the model’s accuracy for predicting COPD risk, achieving a best performance of 0.8505 AUC, a specificity of 0.8539 and a sensitivity of 0.7584. These results indicate that ML models can be effectively utilized for accurate prediction of COPD risk in individuals aged 20 to 50 years, providing a valuable tool for early detection and intervention.

Summary: Computational pathology for gigapixel whole-slide images (WSIs) at slide level is helpful in disease diagnosis and remains challenging. We propose a context-aware approach termed WSI inspection via transformer (WIT) for slide-level classification via holistically modeling dependencies among patches on WSI. WIT automatically learns feature representation of WSI by aggregating features of all image patches. We evaluate classification performance of WIT and state-of-the-art baseline method. WIT achieved an accuracy of 82.1% (95% CI, 80.7%–83.3%) in the detection of 32 cancer types on the TCGA dataset, 0.918 (0.910–0.925) in diagnosis of cancer on the CPTAC dataset, and 0.882 (0.87–0.890) in the diagnosis of prostate cancer from needle biopsy slide, outperforming the baseline by 31.6%, 5.4%, and 9.3%, respectively. WIT can pinpoint the WSI regions that are most influential for its decision. WIT represents a new paradigm for computational pathology, facilitating the development of digital pathology tools.

Key points Microvascular impairment correlated with native T1 of remote myocardium. Native T1 values of remote myocardium changed dynamically. Native30D T1 and LGE were joint independent predictors of MACE.

In order to improve the plugging performance of high-temperature and high-salt oil reservoir plugging agents, this paper utilizes a copolymer composed of acrylamide and 2-acrylamide-2-methylpropanesulfonic acid (AM/AMPS) as the polymer, polyethyleneimine as the cross-linking agent, and nylon fiber as the stabilizer to develop a high-temperature- and high-salt-resistant gel system. This study analyzed and evaluated the temperature resistance, salt resistance and blocking performance of the gel system. The evaluation results show that the gel-forming strength of this gel system can reach an H level, and it has good thermal stability at the high temperature of 130 °C. At the high salinity of 240,720 mg/L, the syneresis rate remains below 2.5%, and the gel-forming time is greater than 15 h; the higher the temperature, the shorter the gelling time. The results of our sand-filled pipe-plugging experiment show that the gel system can adapt to sand-filled pipes with different levels of permeability, and reaching a plugging rate of 94%.

Cadmium (Cd) pollution is a global problem affecting soil ecology and plant growth. Abscisic acid (ABA) acts as a growth and stress hormone, regulates cell wall synthesis, and plays an important role in plant responses to stress. There are few studies on the mechanisms behind abscisic acid alleviation of cadmium stress in Cosmos bipinnatus, especially in regards to regulation of the root cell wall. This study examined the effects of different concentrations of abscisic acid at different concentrations of cadmium stress. Through adding 5 μmol/L and 30 μmol/L cadmium, followed by spraying 10 μmol/L and 40 μmol/L ABA in a hydroponic experiment, it was found that under two concentrations of cadmium stress, low concentration of ABA improved root cell wall polysaccharide, Cd, and uronic acid content. Especially in pectin, after the application of low concentration ABA, the cadmium concentration was significantly increased by 1.5 times and 1.2 times compared with the Cd concentration under Cd5 and Cd30 treatment alone, respectively. Fourier-Transform Infrared spectroscopy (FTIR) demonstrated that cell wall functional groups such as -OH and -COOH were increased with exposure to ABA. Additionally, the exogenous ABA also increased expression of three kinds of antioxidant enzymes and plant antioxidants. The results of this study suggest that ABA could reduce Cd stress by increasing Cd accumulation, promoting Cd adsorption on the root cell wall, and activating protective mechanisms. This result could help promote application of C. bipinnatus for phytostabilization of cadmium-contaminated soil.

The glymphatic system has recently been shown to be important in neurological diseases, including diabetes. However, little is known about how the progressive onset of diabetes affects the glymphatic system. The aim of this study is to investigate the glymphatic system response to the progressive onset of diabetes in a rat model of type 2 diabetic mellitus. Male Wistar rats (n = 45) with and without diabetes were evaluated using MRI glymphatic tracer kinetics, functional tests, and brain tissue immunohistochemistry. Our data demonstrated that the contrast agent clearance impairment gradually progressed with the diabetic duration. The MRI data showed that an impairment in contrast clearance occurred prior to the cognitive deficits detected using functional tests and permitted the detection of an early DM stage compared to the immuno-histopathology and cognitive tests. Additionally, the quantitative MRI markers of brain waste clearance demonstrated region-dependent sensitivity in glymphatic impairment. The improved sensitivity of MRI markers in the olfactory bulb and the whole brain at an early DM stage may be attributed to the important role of the olfactory bulb in the parenchymal efflux pathway. MRI can provide sensitive quantitative markers of glymphatic impairment during the progression of DM and can be used as a valuable tool for the early diagnosis of DM with a potential for clinical application.

Abstract Background Studies have shown that long noncoding RNAs and N6-methyladenosine play important roles in gastric cancer. The purpose of this study was to determine the correlation and prognostic value of m6A-related lncRNAs and immune infiltration in gastric cancer. Methods We downloaded the clinically related information and RNA-Seq transcriptome data of gastric cancer patients from the TCGA database. Univariate Cox regression analysis and Pearson analysis were used to screen out m6A-related lncRNAs. Consensus cluster analysis was used to divide the sample into two clusters, and LASSO analysis and Cox regression analysis were used to construct a risk scoring model. Results A total of 25 lncRNA expression profiles were screened, and gastric cancer patients were divided into different subtypes. Cluster 2 had a better prognosis, but its stromal score, ESTIMATE score and immune score were low. Cluster 1 was rich in resting memory CD4 T cells, regulatory T cells, monocytes, and resting mast cells, and Cluster 2 was rich in activated memory CD4 T cells and follicular helper T cells. Thirteen lncRNAs were selected to construct a risk model, and the prognosis of gastric cancer patients in the high-risk group was poor. The expression of PD-L1 in tumours is significantly higher than that in normal tissues. Univariate and multivariate Cox regression analysis results showed that the overall survival rate was significantly related to stage and the risk score, which can be used as an independent prognostic factor. The results of the heatmap and scatter plot showed that clusters (P = 0.0045) and grade (G1–2, G3, P = 0.0037) were significantly related to prognosis. The relationship between the risk score and immune cell infiltration showed that memory B cells, resting dendritic cells, M0 macrophages, and M2 macrophages were positively correlated with the risk score, while resting mast cells, monocytes, activated NK cells, and follicular helper T cells were negatively correlated with the risk score. Conclusion The results of this study indicate that m6A-related lncRNAs may play an important role in the prognosis of gastric cancer patients and the tumour immune microenvironment and may provide help for the treatment of gastric cancer patients.

Summary: Exponential accumulation of single-cell transcriptomes poses great challenge for efficient assimilation. Here, we present an approach entitled generative pretraining from transcriptomes (tGPT) for learning feature representation of transcriptomes. tGPT is conceptually simple in that it autoregressive models the ranking of a gene in the context of its preceding neighbors. We developed tGPT with 22.3 million single-cell transcriptomes and used four single-cell datasets to evalutate its performance on single-cell analysis tasks. In addition, we examine its applications on bulk tissues. The single-cell clusters and cell lineage trajectories derived from tGPT are highly aligned with known cell labels and states. The feature patterns of tumor bulk tissues learned by tGPT are associated with a wide range of genomic alteration events, prognosis, and treatment outcome of immunotherapy. tGPT represents a new analytical paradigm for integrating and deciphering massive amounts of transcriptome data and it will facilitate the interpretation and clinical translation of single-cell transcriptomes.

The purpose of this study is to investigate the use of SiO2 nanoparticles in assisting with surfactants and polymers for tertiary oil recovery, with the aim of enhancing oil recovery. The article characterizes the performance of SiO2 nanoparticles, including particle size, dispersion stability, and zeta potential, evaluates the synergistic effects of nanoparticles with alpha-olefin sulfonate sodium (AOS) surfactants and hydrolyzed polyacrylamide (HPAM) on reducing interfacial tension and altering wettability, and conducts core flooding experiments in rock cores with varying permeabilities. The findings demonstrate that the particle size decreased from 191 nm to 125 nm upon the addition of SiO2 nanoparticles to AOS surfactant, but increased to 389 nm upon the addition of SiO2 nanoparticles to HPAM. The dispersibility experiment showed that the SiO2 nanoparticle solution did not precipitate over 10 days. After adding 0.05% SiO2 nanoparticles to AOS surfactant, the zeta potential was −40.2 mV, while adding 0.05% SiO2 nanoparticles to 0.1% HPAM resulted in a decrease in the zeta potential to −25.03. The addition of SiO2 nanoparticles to AOS surfactant further reduced the IFT value to 0.19 mN/m, altering the rock wettability from oil-wet to strongly water-wet, with the contact angle decreasing from 110° to 18°. In low-permeability rock core oil displacement experiments, the use of AOS surfactants and HPAM for enhanced oil recovery increased the recovery rate by 24.5% over water flooding. The recovery rate increased by 21.6% over water flooding in low-permeability rock core experiments after SiO2 nanoparticles were added and surfactants and polymers were utilized for oil displacement. This is because the nanoparticles blocked small pore throats, resulting in increased resistance and hindered free fluid flow. The main causes of this plugging are mutual interference and mechanical entrapment, which cause the pressure differential to rise quickly. In high-permeability rock core oil displacement experiments, the use of AOS surfactants and HPAM for oil recovery increased the recovery rate by 34.6% over water flooding. Additionally, the recovery rate increased by 39.4% over water flooding with the addition of SiO2 nanoparticles and the use of AOS surfactants and HPAM for oil displacement. Because SiO2 nanoparticles create wedge-shaped structures inside highly permeable rock cores, they create structural separation pressure, which drives crude oil forward and aids in diffusion. This results in a comparatively small increase in pressure differential. Simultaneously, the nanoparticles change the rock surfaces’ wettability, which lowers the amount of crude oil that adsorbs and improves oil recovery.

Abstract The excellent outcomes seen in patients treated with adjuvant trastuzumab emtansine (T-DM1) in the ATEMPT trial and the favorable toxicity profile associated with this agent make T-DM1 a potential therapeutic option for select patients with stage I HER2-positive breast cancer. Moreover, T-DM1 is an established adjuvant treatment for patients with HER2-positive breast cancer with the residual invasive disease after neoadjuvant therapy. Given that cardiotoxicity is the most significant adverse event of trastuzumab, which is a main molecular component of T-DM1, we conducted a sub-analysis of the ATEMPT trial to determine the cardiac safety of adjuvant T-DM1. In this analysis, the incidence of grade 3–4 left ventricular systolic dysfunction (LVSD) in T-DM1 or trastuzumab plus paclitaxel arms were respectively 0.8 and 1.8%. In addition, three (0.8%) patients in the T-DM1 arm and six (5.3%) patients in the adjuvant paclitaxel with trastuzumab (TH) arm experienced a significant asymptomatic left ventricular ejection fraction (LVEF) decline that per-protocol required holding T-DM1 or trastuzumab. All patients with available follow-up data experienced full resolution of cardiac symptoms and LVEF normalization. Furthermore, we performed an exploratory analysis to assess the relationship between age, baseline LVEF, and body mass index with cardiac outcomes. No significant association between these baseline characteristics and the incidence of significant asymptomatic LVEF decline or symptomatic LVSD was identified. The low incidence of significant cardiac adverse events in this population during therapy with adjuvant T-DM1 suggests that studies on the cost-effectiveness of cardiac monitoring during adjuvant therapy using anthracycline-free regimens are needed. Clinical Trial Registration: ClinicalTrials.gov, NCT01853748

A randomized phase 2 clinical trial has recently shown no benefit of the combination eribulin and pembrolizumab over pembrolizumab alone in HR + metastatic breast cancer patients (NCT03051659). Here, the authors are reporting the final OS data and biomarker analyses on a subset of samples to analyze molecular correlates

People living with HIV-1 (PLWH) exhibit more rapid antibody decline following routine immunization and elevated baseline chronic inflammation than people without HIV-1 (PWOH), indicating potential for diminished humoral immunity during SARS-CoV-2 infection. Conflicting reports have emerged on the ability of PLWH to maintain humoral protection against SARS-CoV-2 coinfection during convalescence. It is unknown whether peak COVID-19 severity, along with HIV-1 infection status, associates with the quality and quantity of humoral immunity following recovery. Using a cross-sectional observational cohort from the United States and Peru, adults were enrolled 1–10 weeks after SARS-CoV-2 infection diagnosis or symptom resolution. Serum antibodies were analyzed for SARS-CoV-2–specific response rates, binding magnitudes, ACE2 receptor blocking, and antibody-dependent cellular phagocytosis. Overall, (a) PLWH exhibited a trend toward decreased magnitude of SARS-CoV-2–specific antibodies, despite modestly increased overall response rates when compared with PWOH; (b) PLWH recovered from symptomatic outpatient COVID-19 had comparatively diminished immune responses; and (c) PLWH lacked a corresponding increase in SARS-CoV-2 antibodies with increased COVID-19 severity when asymptomatic versus symptomatic outpatient disease was compared.

Background: Impaired cerebral waste clearance (CWC) has been associated with a broad range of both physiological and pathophysiological neurologic conditions.1,2 Because of the unique anatomy of the brain parenchyma, theoretically, in the brain parenchyma, biochemically inert waste such as magnetic resonance imaging (MRI) contrast agents can only be removed through two possible pathways: cerebrospinal fluid (CSF) pathway, and/or vascular pathway. Despite the controversy, there seems to be a solid consensus on the participation of the CSF pathway in CWC.3 In contrast to the CSF system, the current consensus is that the parenchymal vascular system does not participate in CWC. Considering there is a big difference in flow rate between the blood (2 mL/min) and the CSF (3.7 µL/min) and the brain is the most bioactive, energy-consuming organ (20% nutrition for about 5% of body weight) in the body, it is illogical that the brain would rely on the slow CSF circulation for CWC while less bioactive tissues outside the brain require both the fast vascular and slow lymphatic systems to remove waste in a timely manner.4,5 Methods: Superparamagnetic iron oxide–enhanced susceptibility-weighted imaging (SPIO-SWI) and quantitative susceptibility mapping (QSM) methods were used to simultaneously study 7 T MRI signal changes in parenchymal veins, arteries, and their corresponding para-vascular spaces in 26 rats, following intra-cisterna magna (ICM) infusion of different CSF tracers (FeREX, ferumoxytol, Fe-Dextran) to determine the amount of tracer in the artery and vein quantitatively. Results: The parenchymal venous system participated in CSF tracer clearance following ICM infusion of different MRI tracers with different concentrations of iron. Parenchymal venous participation was more obvious when 75 μg iron was injected. In the parenchymal veins, the relative mean (±SE) value of the susceptibility increased by 13.5±1.0% at 15 min post-tracer infusion (p

Abstract Young women with breast cancer experience unique treatment and survivorship issues centering on treatment-related amenorrhea (TRA), including fertility preservation and management of ovarian function as endocrine therapy. The Young Women’s Breast Cancer Study (YWS) is a multi-center, prospective cohort study of women diagnosed at age ≤40, enrolled from 2006 to 2016. Menstrual outcomes were self-reported on serial surveys. We evaluated factors associated with TRA using logistic regression. One year post-diagnosis, 286/789 (36.2%) experienced TRA, yet most resumed menses (2-year TRA: 120/699; 17.2%). Features associated with 1-year TRA included older age (OR ≤30vs36-40 = 0.29 (0.17–0.48), OR31-35vs36-40 = 0.67 (0.46–0.94), p = 0.02); normal body mass index (BMI) (OR ≥25vs18.5-24. =0.59 (0.41–0.83), p

Background: Inflammatory breast cancer (IBC) is a rare and understudied disease, with 40% of cases presenting with human epidermal growth factor receptor 2 (HER2)-positive subtype. The goals of this study were to (i) assess the pathologic complete response (pCR) rate of short-term neoadjuvant dual-HER2-blockade and paclitaxel, (ii) contrast baseline and on-treatment transcriptional profiles of IBC tumor biopsies associated with pCR, and (iii) identify biological pathways that may explain the effect of neoadjuvant therapy on tumor response. Patients and Methods: A single-arm phase II trial of neoadjuvant trastuzumab (H), pertuzumab (P), and paclitaxel for 16 weeks was completed among patients with newly diagnosed HER2-positive IBC. Fresh-frozen tumor biopsies were obtained pretreatment (D1) and 8 days later (D8), following a single dose of HP, prior to adding paclitaxel. We performed RNA-sequencing on D1 and D8 tumor biopsies, identified genes associated with pCR using differential gene expression analysis, identified pathways associated with pCR using gene set enrichment and gene expression deconvolution methods, and compared the pCR predictive value of principal components derived from gene expression profiles by calculating and area under the curve for D1 and D8 subsets. Results: Twenty-three participants were enrolled, of whom 21 completed surgery following neoadjuvant therapy. Paired longitudinal fresh-frozen tumor samples (D1 and D8) were obtained from all patients. Among the 21 patients who underwent surgery, the pCR and the 4-year disease-free survival were 48% (90% CI 0.29–0.67) and 90% (95% CI 66–97%), respectively. The transcriptional profile of D8 biopsies was found to be more predictive of pCR (AUC = 0.91, 95% CI: 0.7993–1) than the D1 biopsies (AUC = 0.79, 95% CI: 0.5905–0.9822). Conclusions: In patients with HER2-positive IBC treated with neoadjuvant HP and paclitaxel for 16 weeks, gene expression patterns of tumor biopsies measured 1 week after treatment initiation not only offered different biological information but importantly served as a better predictor of pCR than baseline transcriptional analysis. Trial Registration: ClinicalTrials.gov identifier: NCT01796197 ( https://clinicaltrials.gov/ct2/show/NCT01796197 ); registered on February 21, 2013.

Abstract Background Early recurrence of oesophageal squamous cell carcinoma (SCC) is defined as recurrence after surgery within 1 year, and appears as local recurrence, distant recurrence, and lymph node positive and disseminated recurrence. Contrast-enhanced computed tomography (CECT) is recommended for diagnosis of primary tumor and initial staging of oesophageal SCC, but it cannot be used to predict early recurrence. It is reported that radiomics can help predict preoperative stages of oesophageal SCC, lymph node metastasis before operation, and 3-year overall survival of oesophageal SCC patients following chemoradiotherapy by extracting high-throughput quantitative features from CT images. This study aimed to develop models based on CT radiomics and clinical features of oesophageal SCC to predict early recurrence of locally advanced cancer. Methods We collected electronic medical records and image data of 197 patients with confirmed locally advanced oesophageal SCC. These patients were randomly allocated to 137 patients in the training cohort and 60 in the test cohort. 352 radiomics features were extracted by delineating region-of-interest (ROI) around the lesion on CECT images and clinical signature was generated by medical records. The radiomics model, clinical model, the combined model of radiomics and clinical features were developed by radiomics features and/or clinical characteristics. Predicting performance of the three models was assessed with area under receiver operating characteristic curve (AUC), accuracy and F-1 score. Results Eleven radiomics features and/or six clinical signatures were selected to build prediction models related to recurrence of locally advanced oesophageal SCC after trimodal therapy. The AUC of integration of radiomics and clinical models was better than that of radiomics or clinical model for the training cohort (0.821 versus 0.754 or 0.679, respectively) and for the validation cohort (0.809 versus 0.646 or 0.658, respectively). Integrated model of radiomics and clinical features showed good performance in predicting early recurrence of locally advanced oesophageal SCC for both the training and validation cohorts (accuracy = 0.730 and 0.733, and F-1score = 0.730 and 0.778, respectively). Conclusions The integrated model of CECT radiomics and clinical features may be a potential imaging biomarker to predict early recurrence of locally advanced oesophageal SCC after trimodal therapy.

Abstract Background We aimed to examine the safety and efficacy of bevacizumab and carboplatin in patients with breast cancer brain metastases. Methods We enrolled patients with breast cancer and > 1 measurable new or progressive brain metastasis. Patients received bevacizumab 15 mg/kg intravenously (IV) on cycle 1 day 1 and carboplatin IV AUC = 5 on cycle 1 day 8. Patients with HER2-positive disease also received trastuzumab. In subsequent cycles, all drugs were administered on day 1 of each cycle. Contrast-enhanced brain MRI was performed at baseline, 24–96 h after the first bevacizumab dose (day + 1), and every 2 cycles. The primary endpoint was objective response rate in the central nervous system (CNS ORR) by composite criteria. Associations between germline VEGF single nucleotide polymorphisms (rs699947, rs2019063, rs1570360, rs833061) and progression-free survival (PFS) and overall survival (OS) were explored, as were associations between early (day + 1) MRI changes and outcomes. Results Thirty-eight patients were enrolled (29 HER2-positive, 9 HER2-negative); all were evaluable for response. The CNS ORR was 63% (95% CI, 46–78). Median PFS was 5.62 months and median OS was 14.10 months. As compared with an Eastern Cooperative Oncology Group performance status (ECOG PS) of 0, patients with ECOG PS 1–2 had significantly worse PFS and OS (all P

Abstract Background Compared to adults, there are relatively few studies on COVID-19 infection in children, and even less focusing on the unique features of COVID-19 in children in terms of laboratory findings, locations of computerized tomography (CT) lesions, and the role of CT in evaluating clinical recovery. The objective of this study is to report the results from patients at Wuhan Children’s Hospital, located within the initial center of the outbreak. Methods Clinical, imaging, and laboratory data of 76 children were collected retrospectively and analyzed with the Fisher exact test and Cox regression statistical methods. Results Among 50 children with a positive COVID-19 real-time reverse-transcriptase polymerase chain reaction (PCR), five had negative PCR results initially but showed positive results in subsequent tests. Eight (16%) patients had lymphopenia, seven (14%) with thrombocytopenia, four (8%) with lymphocytosis, two (4%) with thrombocytosis, ten (20%) with elevated C-reactive protein, four (8%) with hemoglobin above, and six (12%) with below standard reference values. Seven (14%) of the 50 had no radiologic evidence of disease on chest CT. For the 43 patients who had abnormal CT findings, in addition to previously reported patterns of ground-glass opacity (67%), local patchy shadowing (37%), local bilateral patchy shadowing (21%), and lesion location of lower lobes (65%), other CT features include that an overwhelming number of pediatric patients had lesions in the subpleural area (95%) and 22 of the 28 lower lobe lesions were in the posterior segment (78%). Lesions in most of the 15 patients (67%) who received chest CT at discharge were not completely absorbed, and 26% of these pediatric patients had CT lesions that were either unchanged or worse. Conclusions There were a few differences between COVID-19 children and COVID-19 adults in terms of laboratory findings and CT characteristics. CT is a powerful tool to detect and characterize COVID-19 pneumonia but has little utility in evaluating clinical recovery for children. These results oppose current COVID-19 hospital discharge criteria in China, as one requirement is that pulmonary imaging must show significant lesion absorption prior to discharge. These differences between pediatric and adult cases of COVID-19 may necessitate pediatric-specific discharge criteria.

Gastric cancer is the fifth most common type of human cancer and the third leading cause of cancer-related death. The purpose of this study is to investigate the immune infiltration signatures of gastric cancer and their relation to prognosis. We identified two distinct subtypes of gastric cancer (C1/C2) characterized by different immune infiltration signatures. C1 is featured by immune resting, epithelial–mesenchymal transition, and angiogenesis pathways, while C2 is featured by enrichment of the MYC target, oxidative phosphorylation, and E2F target pathways. The C2 subtype has a better prognosis than the C1 subtype (HR = 0.61, 95% CI: 0.44–0.85; log-rank test, p = 0.0029). The association of C1/C2 with prognosis remained statistically significant (HR = 0.62, 95% CI: 0.44–0.87; p = 0.006) after controlling for age, gender, and stage. The prognosis prediction of C1/C2 was verified in four independent cohorts (including an internal cohort). In summary, our study is helpful for better understanding of the association between immune infiltration and the prognosis of gastric cancer.

Quasi-dry CO2 fracturing technology is a new CO2 fracturing technology that combines liquid CO2 fracturing (dry CO2 fracturing) and water-based fracturing. It uses a liquid CO2 system containing a small amount of water-based fracturing fluid to carry sand, and it is characterized by sand blending at normal pressure, convenient preparation, the integrated application of resistance reduction and sand carrying, and no dedicated closed sand blender requirement. We developed a self-crosslinking emulsion-type water-based fracturing fluid (ZJL-1), which contained ionic bonds, hydrogen bonds, van der Waals forces, and hydrophobic associations, for quasi-dry CO2 fracturing, and the comprehensive properties of the ZJL-1 fracturing fluid were evaluated. The results showed that the ZJL-1 fracturing fluid had obvious viscoelastic characteristics, a heat loss rate of less than 10% at 200 °C, a good thermal stability, sufficient rheology under high temperature and high shear conditions, and a good thermal stability. The resistance reduction rate reached 70%, which demonstrates a good resistance reduction performance. Compared with conventional guar fracturing fluid, ZJL-1 can carry more sand and has a lower core damage rate. The on-site use of quasi-dry fracturing showed that optimizing the mixing ratio of liquid CO2 fracturing fluid and ZJL-1 fracturing fluid effectively enhanced oil and gas recovery. This can be used to optimize quasi-dry fracturing and can be used as a reference.

Automatic pain estimation plays an important role in the field of medicine and health. In the previous studies, most of the entire image frame was directly imported into the model. This operation can allow background differences to negatively affect the experimental results. To tackle this issue, we propose the parallel CNNs framework with regional attention for automatic pain intensity estimation at the frame level. This modified convolution neural network structure combines BlurPool methods to enhance translation invariance in network learning. The improved networks can focus on learning core regions while supplementing global information, thereby obtaining parallel feature information. The core regions are mainly based on the tradeoff between the weights of the channel attention modules and the spatial attention modules. Meanwhile, the background information of the non-core regions is shielded by the DropBlock algorithm. These steps enable the model to learn facial pain features adaptively, not limited to a single image pattern. The experimental result of our proposed model outperforms many state-of-the-art methods on the RMSE and PCC metrics when evaluated on the diverse pain levels of over 12,000 images provided by the publicly available UNBC dataset. The model accuracy rate has reached 95.11%. The experimental results show that the proposed method is highly efficient at extracting the facial features of pain and predicts pain levels with high accuracy.

Summary: We developed Miscell, a self-supervised learning approach with deep neural network as latent feature encoder for mining information from single-cell transcriptomes. We demonstrated the capability of Miscell with canonical single-cell analysis tasks including delineation of single-cell clusters and identification of cluster-specific marker genes. We evaluated Miscell along with three state-of-the-art methods on three heterogeneous datasets. Miscell achieved at least comparable or better performance than the other methods by significant margin on a variety of clustering metrics such as adjusted rand index, normalized mutual information, and V-measure score. Miscell can identify cell-type specific markers by quantifying the influence of genes on cell clusters via deep learning approach.

Based on the characteristics of low-permeability oil and gas reservoirs and the requirements for profile control and water plugging and for water cut decrease and production increase in the high water cut stage of the middle and late exploitation periods, ultrafine temperature-resistant and salt-tolerant swellable particles DS-1 suitable for low permeability oilfields were prepared by introducing N,N-dimethylacrylamide(DMAA) monomers into the 2-acrylamido-2-methylpropanesulfonic acid (AMPS)/acrylamide(AM)/N,N-dimethylbisacrylamide ternary crosslinking system. The median of initial particle size was 22.00 μm, and is compatible with formation pore throats. A static water absorption experiment showed that the particles can still maintain a high swelling ratio after 15 days at a high temperature and high mineralization degree, so they have long-term stability. The physical and chemical properties of the particles were analyzed microscopically using the infrared spectrum method and the scanning electron microscope (SEM) method. A dynamic displacement experiment confirmed that the particles can effectively plug dominant channels of waterflooding, increase the injection pressure, and improve the interlayer and intralayer heterogeneity. In the field experiment, the swellable particles DS-1 were used as a main slug for water plugging operations, and a good water cut decrease and oil production increase effect was obtained.

Waste clearance (WC) is an essential process for brain homeostasis, which is required for the proper and healthy functioning of all cerebrovascular and parenchymal brain cells. This review features our current understanding of brain WC, both within and external to the brain parenchyma. We describe the interplay of the blood-brain barrier (BBB), interstitial fluid (ISF), and perivascular spaces within the brain parenchyma for brain WC directly into the blood and/or cerebrospinal fluid (CSF). We also discuss the relevant role of the CSF and its exit routes in mediating WC. Recent discoveries of the glymphatic system and meningeal lymphatic vessels, and their relevance to brain WC are highlighted. Controversies related to brain WC research and potential future directions are presented.

Background: Recent emerging evidence has highlighted the potential critical role of cerebrospinal fluid (CSF) in cerebral waste clearance and immunomodulation. It is already very well-established that the central nervous system (CNS) is completely submerged in CSF on a macro-level; but to what extent is this true on a micro-level? Specifically, within the peri-neural and peri-vascular spaces within the CNS parenchyma. Therefore, the objective of this study was to use magnetic resonance imaging (MRI) to simultaneously map the presence of CSF within all peri-neural (cranial and spinal nerves) and peri-vascular spaces in vivo in humans. Four MRI protocols each with five participants were used to image the CSF in the brain and spinal cord. Our findings indicated that all CNS neuro- and vascular-communication channels are surrounded with CSF. In other words, all peri-neural spaces surrounding the cranial and spinal nerves as well as all peri-vascular spaces surrounding MRI-visible vasculature were filled with CSF. These findings suggest that anatomically, substance exchange between the brain parenchyma and outside tissues including lymphatic ones can only occur through CSF pathways and/or vascular pathways, warranting further investigation into its implications in cerebral waste clearance and immunity.

Triple-negative breast cancer is an aggressive form of the disease. Here, the authors identify EGFL9 as a mediator of metastasis in TNBC through interactions with cMET.

Abstract Background Computed tomography (CT) is commonly used in all stages of oesophageal squamous cell carcinoma (SCC) management. Compared to basic CT features, CT radiomic features can objectively obtain more information about intratumour heterogeneity. Although CT radiomics has been proved useful for predicting treatment response to chemoradiotherapy in oesophageal cancer, the best way to use CT radiomic biomarkers as predictive markers for determining resectability of oesophageal SCC remains to be developed. This study aimed to develop CT radiomic features related to resectability of oesophageal SCC with five predictive models and to determine the most predictive model. Methods Five hundred ninety-one patients with oesophageal SCC undergoing contrast-enhanced CT were enrolled in this study, and were composed by 270 resectable cases and 321 unresectable cases. Of the 270 resectable oesophageal SCCs, 91 cases were primary resectable tumours; and the remained 179 cases received neoadjuvant therapy after CT, shrank on therapy, and changed to resectable tumours. Four hundred thirteen oesophageal SCCs including 189 resectable cancers and 224 unresectable cancers were randomly allocated to the training cohort; and 178 oesophageal SCCs including 81 resectable tumours and 97 unresectable tumours were allocated to the validation group. Four hundred ninety-five radiomic features were extracted from CT data for identifying resectability of oesophageal SCC. Useful radiomic features were generated by dimension reduction using least absolute shrinkage and selection operator. The optimal radiomic features were chosen using multivariable logistic regression, random forest, support vector machine, X-Gradient boost and decision tree classifiers. Discriminating performance was assessed with area under receiver operating characteristic curve (AUC), accuracy and F-1score. Results Eight radiomic features were selected to create radiomic models related to resectability of oesophageal SCC (P-values

Face alignment is a crucial step in face recognition. Through making the position of face consistent, face alignment reduces intra-class variability due to factors such as lighting, background, pose, and perspective transformation, and further facilitating the recognition tasks. In this paper, we propose a new face alignment method for pose-invariant face recognition, called adaptive pose alignment (APA), which can greatly reduce the intra-class difference and correct the noise caused by the traditional method in the alignment process, especially in unconstrained settings. Instead of aligning all faces to the pre-defined, uniform frontal shape, we adaptively learn the alignment templates according to the facial poses and then align each face of training or testing sets to its related template. To further improve face recognition performance, we propose a simple, yet effective feature normalization method which can generate more discriminative feature representation of a face or a set of faces (template) combined with the APA method. Furthermore, we introduce a pose-invariant face recognition pipeline that sequentially applies APA-based alignment, deep representation by softmax or ArcFace loss function, and the effective feature normalization procedure. We empirically show that APA-based images can accelerate the training of deep face recognition model by aligning all the images to the optimal templates. Moreover, experimental results show that the proposed method achieves the state-of-the-art performance on popular challenging face datasets including IJB-A, IJB-C, and CPLFW datasets.

PURPOSE: To validate Gaussian normalized cerebral blood volume (GN-nCBV) by association with overall survival (OS) in newly diagnosed glioblastoma patients and compare this association with current standard white matter normalized cerebral blood volume (WN-nCBV). METHODS: We retrieved spin-echo echo-planar dynamic susceptibility contrast MRI acquired after maximal resection and prior to radiation therapy between 2006 and 2011 in 51 adult patients (28 male, 23 female; age 23-87 years) with newly diagnosed glioblastoma. Software code was developed in house to perform Gaussian normalization of CBV to the standard deviation of the whole brain CBV. Three expert readers manually selected regions of interest in tumor and normal-appearing white matter on CBV maps. Receiver operating characteristics (ROC) curves associating nCBV with 15-month OS were calculated for both GN-nCBV and WN-nCBV. Reproducibility and interoperator variability were compared using within-subject coefficient of variation (wCV) and intraclass correlation coefficients (ICCs). RESULTS: GN-nCBV ICC (≥0.82) and wCV (≤21%) were superior to WN-nCBV ICC (0.54-0.55) and wCV (≥46%). The area under the ROC curve analysis demonstrated both GN-nCBV and WN-nCBV to be good predictors of OS, but GN-nCBV was consistently superior, although the difference was not statistically significant. CONCLUSION: GN-nCBV has a slightly better association with clinical gold standard OS than conventional WM-nCBV in our glioblastoma patient cohort. This equivalent or superior validity, combined with the advantages of higher reproducibility, lower interoperator variability, and easier automation, makes GN-nCBV superior to WM-nCBV for clinical and research use in glioma patients. We recommend widespread adoption and incorporation of GN-nCBV into commercial dynamic susceptibility contrast processing software.

There is an urgent need for better detection and understanding of vascular abnormalities at the micro-level, where critical vascular nourishment and cellular metabolic changes occur. This is especially the case for structures such as the midbrain where both the feeding and draining vessels are quite small. Being able to monitor and diagnose vascular changes earlier will aid in better understanding the etiology of the disease and in the development of therapeutics. In this work, thirteen healthy volunteers were scanned with a dual echo susceptibility weighted imaging (SWI) sequence, with a resolution of 0.22 ​× ​0.44 ​× ​1 ​mm3 at 3T. Ultra-small superparamagnetic iron oxides (USPIO) were used to induce an increase in susceptibility in both arteries and veins. Although the increased vascular susceptibility enhances the visibility of small subvoxel vessels, the accompanying strong signal loss of the large vessels deteriorates the local tissue contrast. To overcome this problem, the SWI data were acquired at different time points during a gradual administration (final concentration ​= ​4 ​mg/kg) of the USPIO agent, Ferumoxytol, and the data was processed to combine the SWI data dynamically, in order to see through these blooming artifacts. The major vessels and their tributaries (such as the collicular artery, peduncular artery, peduncular vein and the lateral mesencephalic vein) were identified on the combined SWI data using arterio-venous maps. Dynamically combined SWI data was then compared with previous histological work to validate that this protocol was able to detect small vessels on the order of 50 ​μm–100 ​μm. A complex division-based phase unwrapping was also employed to improve the quality of quantitative susceptibility maps by reducing the artifacts due to aliased voxels at the vessel boundaries. The smallest detectable vessel size was then evaluated by revisiting numerical simulations, using estimated true susceptibilities for the basal vein and the posterior cerebral artery in the presence of Ferumoxytol. These simulations suggest that vessels as small as 50 ​μm should be visible with the maximum dose of 4 ​mg/kg.

T oilfield is the fractured-vuggy carbonate reservoir at a temperature of around 130 °C, with salinity of up to 22 × 104 mg/L. In order to solve the problem of the high water cut in the late development stage of T oilfield, we selected XN-T from 27 kinds of swelling retarding particles by testing their swelling capacity, and coated a thin film to improve its retarding swelling capacity. The mechanisms of strong water absorption and water-holding abilities of particles were analyzed by infrared spectrometry and SEM. In the core flow experiment, the plugging rate was found to be 98.42%. Finally, the injection parameters of the coated particles were optimized to maximize the water plugging and profile control ability, resulting in an optimal particle size of 0.4–0.6 mm and a mass fraction of 10%.

The authors would like to correct spelling mistakes (undenatured type II collagen) in the title, as well as in the main manuscript including the tables and figures in the title paper [...]

Abstract Background Accurate and early prognosis of disease is essential to clinical decision making, particularly in diseases, such as HCC, that are typically diagnosed at a late stage in the course of disease and therefore carry a poor prognosis. CDCA5 is a cell cycle regulatory protein that has shown prognostic value in several cancers. Methods We retrospectively evaluated 178 patients with HCC treated with curative liver resection between September 2009 and September 2012 at Nanchong Central Hospital in Nanchong, Sichuan Province, China. Patients were screened for their CDCA5 expression levels and assigned to either the high or low expression group. Patient demographics, comorbidities, clinicopathologic data, such as tumor microvascular invasion status and size, and long-term outcomes were compared between the two groups. The effect of CDCA5 on the proliferation of liver cancer cells was analyzed using in vitro and in vivo assays. Results The present study found that increased CDCA5 expression was associated with increased tumor diameter and microvascular invasion in HCC. It was also found that CDCA5 overexpression may be associated with liver cancer cells. Additionally, this study confirmed that CDCA5 expression was increased in HCC tissue versus normal liver tissue, that CDCA5 expression was associated with decreased survival and that CDCA5 knockdown using shRNA led to cell cycle arrest in the G2/M phase. Conclusions These findings suggest that CDCA5 expression is associated with poor prognosis in patients with hepatocellular carcinoma.

ABSTRACT: Purpose: This study aimed to evaluate the value of precise localization of nodules using pre-video-assisted thoracic surgery (VATS) Xper–CT in combination with real-time fluoroscopy-guided coil in the resection of pulmonary nodules using VATS.Materials and Methods: Precise localization of nodules using Xper-CT in combination with real-time fluoroscopy-guided coil and wedge resection using VATS were conducted on 15 patients with 17 small pulmonary nodules (diameter 0.5–1.5 cm) from April 2015 to January 2016. The value of localization was evaluated in terms of procedure time, type of coils, associated complications of localization, and VATS success rate.Results: The success rate of coil localization was found to be 100% in the primary stage (as shown by the CT scan), and the average procedure time was 30–45 min (35.6 ± 3.05 min). No deaths or major complications occurred. Minor complications included five incidents of pneumothorax (the morbidity was 29.4%, 5/17; no patient required chest tube drainage). The dislocation of coil was found in one patient. The results of pathological examination of 17 small pulmonary nodules revealed 11 primary lung cancers, 1 mesenchymal tumor, 3 nonspecific chronic inflammations, 1 hamartoma, and 1 tuberculosis. Two patients with primary lung cancer underwent lobectomy with mediastinal lymph node dissection.Conclusion: The preoperative precise localization of small pulmonary nodules using Xper-CT-guided coil is an effective and safe technique. It helps in the resection of nodules using VATS. It increases the rate of lung wedge resection with few complications and allows for proper diagnosis with a low thoracotomy conversion rate. Keywords:: CT-guided coil localization, pulmonary nodule, video-assisted thoracic surgery

Feature extraction is vital for face recognition. In this paper, we focus on the general feature extraction framework for robust face recognition. We collect about 300 papers regarding face feature extraction. While some works apply handcrafted features, other works employ statistical learning methods. We believe that a general framework for face feature extraction consists of four major components: filtering, encoding, spatial pooling, and holistic representation. We analyze each component in detail. Each component could be applied in a task with multiple levels. Then, we provide a brief review of deep learning networks, which can be seen as a hierarchical extension of the framework above. Finally, we provide a detailed performance comparison of various features on LFW and FERET face database.

With the rapid development of computer science and technology, the Chinese petroleum industry has ushered in the era of big data. In this study, by collecting fracturing data from 303 horizontal wells in the Fuling Shale Gas Demonstration Area in China, a series of big data analysis studies was conducted using Pearson’s correlation coefficient, the unweighted pair group with arithmetic means method, and the graphical plate method to determine which is best. The fracturing parameters were determined through a series of big data analysis studies. The big data analysis process is divided into three main steps. The first is data preprocessing to screen out eligible, high-yielding wells. The second is a fracturing parameter correlation clustering analysis to determine the reasonableness of the parameters. The third is a big data panel method analysis of specific fracturing construction parameters to determine the optimal parameter range. The analyses revealed that the current amount of 100 mesh sand in the Fuling area is unreasonable; further, there are different preferred areas for different fracturing construction parameters. We have combined different fracturing parameter schemes by preferring areas. This analysis process is expected to provide new ideas regarding fracturing scheme design for engineers working on the frontline.

Ageing-related bone impairment due to exposure to hyperglycemic environment is scarcely researched. The aim was to confirm the improvement effects of undenatured type II collagen (UC II) on bone impairment in ageing db/db mice, and the ageing model was established by normal feeding for 48-week-old. Then, the ageing db/db mice were randomly assigned to UC II intervention, the ageing model, and the chondroitin sulfate + glucosamine hydrochloride control groups. After 12 weeks of treatment, femoral microarchitecture and biomechanical parameters were observed, biomarkers including bone metabolism, inflammatory cytokines, and oxidative stress were measured, and the gastrocnemius function and expressions of interleukin (IL) 1β, receptor activator of nuclear factor (NF)-κB ligand (RANKL), and tartrate-resistant acid phosphatase (TRAP) were analyzed. The results showed that the mice in the UC II intervention group showed significantly superior bone and gastrocnemius properties than those in the ageing model group, including bone mineral density (287.65 ± 72.77 vs. 186.97 ± 32.2 mg/cm3), gastrocnemius index (0.46 ± 0.07 vs. 0.18 ± 0.01%), muscle fiber diameter (0.0415 ± 0.005 vs. 0.0330 ± 0.002 mm), and cross-sectional area (0.0011 ± 0.00007 vs. 0.00038 ± 0.00004 mm2). The UC II intervention elevated bone mineralization and formation and decreased bone resorption, inflammatory cytokines, and the oxidative stress. In addition, lower protein expression of IL-1β, RANKL, and TRAP in the UC II intervention group was observed. These findings suggested that UC II improved bones impaired by T2DM during ageing, and the likely mechanism was partly due to inhibition of inflammation and oxidative stress.

Abstract Background Solid papillary carcinoma (SPC) is a rare variant of breast papillary carcinoma with unique pathological morphology and biological behavior. There is only one case report on T1-MRI of SPC. In this study, we report our findings on this new category of papillary carcinoma to fill the gap in MRI characterization of SPC. Methods This retrospective study included four pathology-confirmed in situ SPC patients. Conventional MRI, diffusion weighted imaging (DWI), and magnetic resonance spectroscopy (MRS) were performed with a 1.5 T whole-body MR scanner before surgical operation. The following characteristics of each lesion were recorded: signal intensity on T2WI/STIR and T1FSPGR, morphology, maximum lesion size, and time intensity curve (TIC) on dynamic contrast enhancement MRI (DCE-MRI), apparent diffusion coefficient (ADC) value from DWI, and Cho peak from MRS. Results Signal intensities of all lesions were heterogenous on T2WI/STIR and T1FSPGR. Mass enhancements were observed for all lesions with either oval or irregular shapes on DCE-MRI. The maximum lesion size ranged from 0.8 cm to 3.2 cm. All lesion margins were circumscribed, and internal enhancements were homogeneous or heterogeneous from DCE-MRI. TIC appeared with a rapid increase in initial contrast phases of all lesions. All lesions on DWI (b = 1000s/mm2) were slightly hyperintense with an ADC value range of 1.3 × 10−3 mm2/s to 1.9 × 10−3 mm2/s. Cho peak was absent at 3.2 ppm for all lesions. Conclusions MRI characteristics of SPC include heterogeneous signal intensity within the lesion on T2WI/STIR and T1FSPGR, mass enhancement with circumscribed margins, either oval or irregular shapes, and a rapid initial enhancement of TIC on DCE-MRI. ADC values and the absence of Cho peak may provide valuable information to distinguish SPC from other invasive breast carcinomas.

Abstract This study assessed the extent of fibrosis and the relationship between the ADC value and systolic strain in hypertensive patients with left ventricular hypertrophy (HTN LVH) and hypertensive patients without LVH (HTN non-LVH) using cardiac diffusion-weighted imaging and T1 mapping. T1 mapping was performed in 13 HTN LVH (mean age, 56.23 ± 3.30 years), 17 HTN non-LVH (mean age, 56.41 ± 2.78 years), and 12 normal control subjects (mean age, 55.67 ± 3.08 years) with 3.0 T MRI using cardiac diffusion-weighted imaging and T1 mapping. HTN LVH subjects had higher native T1 (1233.12 ± 79.01) compared with controls (1133.88 ± 27.40) (p

One major topic for robust face recognition could be the efficient encoding of facial descriptors. Among various encoders, Fisher vector (FV) is one of the probabilistic methods that yield promising results. However, its huge representation is fairly forbidding. In this paper, we present approaches to efficiently compress FV and retain its robustness. First, we put forward a new Compact FV (CFV) descriptor. The CFV is obtained by zeroing out small posteriors, calculating first-order statistics and reweighting its elements properly. Second, in light of Iterative Quantization (ITQ) scheme, we present a Generalized ITQ (GITQ) method to binarize our CFV. Finally, we apply our CFV and GITQ to encode convolutional activations of convolutional neural networks. We evaluate our methods on FERET, LFW, AR, and FRGC 2.0 datasets, and our experiments reveal the advantage of such a framework.

Application of the hashing method to large-scale image retrieval has drawn much attention because of the high efficiency and favorable accuracy of the method. Its related research generally involves two basic problems: similarity-preserving projection and information-preserving quantization. Most previous works focused on learning projection approaches, while the importance of quantization strategies was ignored. Although several hashing quantization models have been recently proposed to improve retrieval performance by assigning multiple bits to projected directions, these models still suffer from suboptimal results, as the critical information loss that occurs in the quantization procedure is not considered. In this paper, to construct an effective quantization model, we utilize rate-distortion theory in the hashing quantization procedure and minimize the distortion to reduce the information loss. Furthermore, combining principal component analysis with our quantization strategy, we present a quantization-based hashing method named distortion minimization hashing. Extensive experiments involving one synthetic data set and three image data sets demonstrate the superior performance of our proposed methods over several quantization techniques and state-of-the-art hashing methods.

Subclinical depression (SD) has been considered as the precursor to major depressive disorder. Accurate prediction of SD and identification of its etiological origin are urgent. Bursts within the lateral habenula (LHb) drive depression in rats, but whether dysfunctional LHb is associated with SD in human is unknown. Here we develop connectome-based biomarkers which predict SD and identify dysfunctional brain regions and connections. T1 weighted images and resting-state functional MRI (fMRI) data were collected from 34 subjects with SD and 40 healthy controls (HCs). After the brain is parcellated into 48 brain regions (246 subregions) using the human Brainnetome Atlas, the functional network of each participant is constructed by calculating the correlation coefficient for the time series of fMRI signals of each pair of subregions. Initial candidates of abnormal connections are identified by the two-sample t-test and input into Support Vector Machine models as features. A total of 24 anatomical-region-based models, 231 sliding-window-based models, and 100 random-selection-based models are built. The performance of these models is estimated through leave-one-out cross-validation and evaluated by measures of accuracy, sensitivity, confusion matrix, receiver operating characteristic curve, and the area under the curve (AUC). After confirming the region with the highest accuracy, subregions within the thalamus and connections associated with subregions of LHb are compared. It is found that five prediction models using connections of the thalamus, posterior superior temporal sulcus, cingulate gyrus, superior parietal lobule, and superior frontal gyrus achieve an accuracy >0.9 and an AUC >0.93. Among 90 abnormal connections associated with the thalamus, the subregion of the right posterior parietal thalamus where LHb is located has the most connections (n = 18), the left subregion only has 3 connections. In SD group, 10 subregions in the thalamus have significantly different node degrees with those in the HC group, while 8 subregions have lower degrees ( p < 0.01), including the one with LHb. These results implicate abnormal brain connections associated with the thalamus and LHb to be associated with SD. Integration of these connections by machine learning can provide connectome-based biomarkers to accurately diagnose SD.

Cartoon images are one of the important carriers for the inheritance of folk literature and culture. We should pay attention to the positive role of cartoon images in the inheritance of intangible culture. So the study aims to design and develop cartoon images of main characters in the Legend of the White snake based on audience intention. So that the cartoon image can be endowed with historical and modern cultural connotations. In this way, it can play a role in inheriting intangible cultural heritage and enhance the cultural confidence. Through the combination of qualitative and quantitative method, it compared the main characters of the Legend of the White snake at home and abroad. After carrying out desk research on the historical background of the legend, we used the concept of participatory design to conduct a questionnaire survey on the preference of cartoon images and analyzed the problems of character design, carrier, communication, and etc. Finally, based on the audience's extraction and combination of design elements, the cartoon image of the main characters in the Legend of the White Snake was generated, which meets the perceptual needs of modern people. By making full use of the narrative function of cartoon images, the creatively designed cartoon images of the main characters in the Legend of the White Snake are deeply rooted in the hearts of the people. It can also raise public interest in the culture of the White Snake and arouse emotional resonance. In this way, it promotes the inheritance and development of the intangible cultural heritage, the White Snake, and provides a certain reference for the design of cartoon images of similar characters in folk literature.