Glycosylation profiling of triple-negative breast cancer: clinical and immune correlations and identification of LMAN1L as a biomarker and therapeutic target.

Introduction: Breast cancer (BC) is the most prevalent malignant tumor in women, with triple-negative breast cancer (TNBC) showing the poorest prognosis among all subtypes. Glycosylation is increasingly recognized as a critical biomarker in the tumor microenvironment, particularly in BC. However, the glycosylation-related genes associated with TNBC have not yet been defined.

Biodegradable Sodium Alginate/Carrageenan/Cellulose Composite Hydrogel Wound Dressings Containing Herbal Extracts for Promoting Blood Coagulation and Wound Healing.

Accelerating the coagulation process and preventing wound infection are major challenges in the wound care process. Therefore, new multifunctional wound dressings with procoagulant, antibacterial, and antioxidant properties have enormous potential for clinical application. In this work, biodegradable hydrogels containing herbal extracts are prepared for wound dressings.

Preliminary study of AI-assisted diagnosis using FDG-PET/CT for axillary lymph node metastasis in patients with breast cancer.

Background: To improve the diagnostic accuracy of axillary lymph node (LN) metastasis in breast cancer patients using 2-[F]FDG-PET/CT, we constructed an artificial intelligence (AI)-assisted diagnosis system that uses deep-learning technologies.

Materials And Methods: Two clinicians and the new AI system retrospectively analyzed and diagnosed 414 axillae of 407 patients with biopsy-proven breast cancer who had undergone 2-[F]FDG-PET/CT before a mastectomy or breast-conserving surgery with a sentinel lymph node (LN) biopsy and/or axillary LN dissection. We designed and trained a deep 3D convolutional neural network (CNN) as the AI model.

Chronic gastritis classification using gastric X-ray images with a semi-supervised learning method based on tri-training.

High-quality annotations for medical images are always costly and scarce. Many applications of deep learning in the field of medical image analysis face the problem of insufficient annotated data. In this paper, we present a semi-supervised learning method for chronic gastritis classification using gastric X-ray images.

Effect of acupuncture at 3 anti-fatigue acupoints in the treatment of cancer-related fatigue in patients with cancer: Protocol for a systematic review and meta-analysis of randomized controlled trials.

Background: Cancer-related fatigue (CRF), is a common distressing symptom of cancer. What's more, "Three anti-fatigue acupoints" is one of the most important components of "Jin's 3-needle therapy" created by Rui Jin, a professor of Guangzhou University of Chinese Medicine, which can be used in the treatment of CRF. In this article, researchers will assess the safety and effect of acupuncture at 3 anti-fatigue acupoints on CRF in patients with cancer.

Coupling of Spinons with Defects and Phonons in the Spin Chain Compound Ca_{2}CuO_{3}.

Extrinsic spinon scattering by defects and phonons instead of intrinsic spinon-spinon coupling is responsible for resistive magnetic heat transport in one-dimensional (1D) quantum magnets. Here we report an investigation of the elusive extrinsic effect in the 1D Heisenberg S=1/2 spin chain compound Ca_{2}CuO_{3}, where the defect concentration is determined from the measured specific heat and first-principles calculations are used to separate the lattice component of the measured thermal conductivity to isolate a large magnetic contribution (κ_{m}). The obtained temperature-dependent spinon-defect and spinon-phonon mean free paths can enable a quantitative understanding of both κ_{m} and the spinon-induced spin Seebeck effect.

Dietary magnesium intake and risk of depression.

Background: Depression is an important public health problem. The aim of the present study is to examine the association of dietary magnesium intake with risk of depression.

Methods: We assessed the association between dietary magnesium intake and risk of depression in a nationally representative sample of 17,730 adults from the 2007-2014 National Health and Nutrition Examination Survey.

Association between Serum Copper and Serum Lipids in Adults.

Background: As an essential trace element, copper has been considered to play an important role in lipid metabolism. However, the associations of serum copper with lipid concentration and dyslipidemia are still controversial.

Methods: We used the 2011-2014 National Health and Nutrition Examination Survey to examine the relationship between serum copper and lipid concentration among participants aged 20 years and older.

LiN-Modified Garnet Electrolyte for All-Solid-State Lithium Metal Batteries Operated at 40 °C.

Lithium carbonate on the surface of garnet blocks Li conduction and causes a huge interfacial resistance between the garnet and electrode. To solve this problem, this study presents an effective strategy to reduce significantly the interfacial resistance by replacing LiCO with Li ion conducting LiN. Compared to the surface LiCO on garnet, LiN is not only a good Li conductor but also offers a good wettability with both the garnet surface and a lithium metal anode.

Exploration of the association between dietary fiber intake and depressive symptoms in adults.

Objective: Current evidence on the association between dietary fiber intake and the risk of depressive symptoms is inconsistent. Thus, the purpose of the present study was to explore their association.

Methods: Data from the National Health and Nutrition Examination Survey 2007 to 2014 were used in this cross-sectional study.

A deep 3D residual CNN for false-positive reduction in pulmonary nodule detection.

Purpose: The automatic detection of pulmonary nodules using CT scans improves the efficiency of lung cancer diagnosis, and false-positive reduction plays a significant role in the detection. In this paper, we focus on the false-positive reduction task and propose an effective method for this task.

Methods: We construct a deep 3D residual CNN (convolution neural network) to reduce false-positive nodules from candidate nodules.

Exposure to Chinese famine in early life and the risk of dyslipidemia in adulthood.

Purpose: Early life exposure to famine may affect the susceptibility to metabolic disorders including dyslipidemia. However, few studies explored the association between them in Chinese population. We aimed to evaluate the association between Chinese famine (1959-1961) exposure during early life and the risk of dyslipidemia in adulthood.

Association of total zinc, iron, copper and selenium intakes with depression in the US adults.

Background: The aim of present study was to examine the associations of total zinc, iron, copper and selenium intakes from diet and supplements with depression.

Methods: Cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) 2009-2014 in the present study. Logistic regression models and restricted cubic spline models were applied to examine the associations of total zinc, iron, copper and selenium intakes with depression.

Growth Model of van der Waals Epitaxy of Films: A Case of AlN Films on Multilayer Graphene/SiC.

"Volmer-Weber" island nucleation and step-flow growth model are the classical processes of the conventional epitaxy of films. However, a growth model of van der Waals epitaxy (vdWE) of films is still not very well-documented. Here, we present an example of vdWE of AlN films on multilayer graphene (MLG)/SiC by hydride vapor phase epitaxy at a high temperature of 1100 °C and reveal the orientation relationship of AlN, MLG, and SiC as (0001)[1-100]||(0001)[1-100]||(0001)[11-20], which suggests that the vdWE heterointerface is not an usual covalent bond and no excessive strain during the growth process owing to the incommensurate in-plane lattices.

Dietary zinc and iron intake and risk of depression: A meta-analysis.

The associations between dietary zinc and iron intake and risk of depression remain controversial. Thus, we carried out a meta-analysis to evaluate these associations. A systematic search was performed in PubMed, Embase, Web of Science, Chinese National Knowledge Infrastructure (CNKI) and Wanfang databases for relevant studies up to January 2017.

Supervised Learning Based Hypothesis Generation from Biomedical Literature.

Nowadays, the amount of biomedical literatures is growing at an explosive speed, and there is much useful knowledge undiscovered in this literature. Researchers can form biomedical hypotheses through mining these works. In this paper, we propose a supervised learning based approach to generate hypotheses from biomedical literature.