Patent output and patent transfer network in China universities: Moderating roles of absorptive capacity and desorptive capacity.

Although absorptive capacity and desorptive capacity has been widely present in university-industry relationships, there has been no research on their potential impact on the relationship between university patent output and university patent transfer network. We constructed datasets of patent applications and patent transfers to firms from 383 universities between 2002 and 2021 in China, and empirically demonstrated the effect of the patent output on university patent transfer network using negative binomial regression models. We also examined the moderating effects of absorptive capacity and desorptive capacity.

[Semen quality of infertile men carrying hepatitis B virus].

Objective: To study the semen parameters of infertile men carrying hepatitis B virus (HBV) and the influence of HBV infection on semen quality.

Methods: We collected the semen samples from 782 infertility males aged 25－35 years old. According to the results of serological examinations, we divided the patients into groups A (HBsAg, HBeAb and HBcAb positive, n = 286), B (HBsAg, HBeAg and HBcAb positive, n = 230) and C (non-HBV control, n = 266), and comparatively analyzed the routine semen parameters, sperm acrosin activity, sperm DNA fragmentation index (DFI) and high DNA stainability (HDS) among the three groups of patients.

Cross sectional study of chronic hepatitis B prevalence among healthcare workers in an urban setting, Sierra Leone.

Introduction: Hepatitis B is a serious public health problem across sub-Saharan Africa. Sierra Leone has no national hepatitis B strategy plan or high quality estimates of prevalence. Healthcare workers are perceived as an at-risk group for hepatitis B.

Cumulative review and meta-analyses on the association between MTHFR rs1801133 polymorphism and breast cancer risk: a pooled analysis of 83 studies with 74,019 participants.

Background: The association between methylenetetrahydrofolate reductase (MTHFR) gene polymorphisms and breast cancer risk has been extensively explored, but their results are conflicting rather than conclusive. To clarify the precise effects of MTHFR polymorphisms on the risk of breast cancer, a systemic review and most comprehensive meta-analysis of all available studies relating MTHFR rs1801133 gene polymorphism to the risk of breast cancer was conducted.

Methods: Eligible articles were identified by search of databases including Medline (Mainly PubMed), Embase, Web of Science, Chinese Biomedical Literature database (CBM), CNKI and Wanfang Medical databases.

Effect of hGC-MSCs from human gastric cancer tissue on cell proliferation, invasion and epithelial-mesenchymal transition in tumor tissue of gastric cancer tumor-bearing mice.

Objective: To study the effect of hGC-MSCs from human gastric cancer tissue on cell proliferation, invasion and epithelial-mesenchymal transition in tumor tissue of gastric cancer tumor-bearing mice.

Methods: BABL/c nude mice were selected as experimental animals and gastric cancer tumor-bearing mice model were established by subcutaneous injection of gastric cancer cells, randomly divided into different intervention groups. hGC-MSCs group were given different amounts of gastric cancer cells for subcutaneous injection, PBS group was given equal volume of PBS for subcutaneous injection.

Single nucleotide polymorphisms of MIR-149 gene rs2292832 contributes to the risk of hepatocellular carcinoma, but not overall cancer: a meta-analysis.

Introduction: Single nucleotide polymorphism in miRNAs can alter its expression, thus can lead to the development of cancers. Numerous studies have explored the association between MIR-149 gene rs2292832 polymorphism and hepatocellular carcinoma (HCC) risk, but the results remains inconsistent. So, we performed this pooled analyses in order to get a precise result.

Single nucleotide polymorphisms of miR-149 gene rs2292832 contributes to the risk of hepatocellular carcinoma, but not overall cancer: a meta-analysis.

Background: Single nucleotide polymorphism in miRNAs can alter its expression, thus lead to the development of cancers. Numerous studies have explored the association between miR-149 gene rs2292832 polymorphism and hepatocellular carcinoma risk, but the results remains inconsistent. So, we performed this pooled analyses in order to get a precise result.

Directed graph based image registration.

In this paper, a novel image registration method is proposed to achieve accurate registration between images having large shape differences with the help of a set of appropriate intermediate templates. We first demonstrate that directionality is a key factor in both pairwise image registration and groupwise registration, which is defined in this paper to describe the influence of the registration direction and paths on the registration performance. In our solution, the intermediate template selection and intermediate template guided registration are two coherent steps with directionality being considered.

Confidence-guided sequential label fusion for multi-atlas based segmentation.

Label fusion is a key step in multi-atlas based segmentation, which combines labels from multiple atlases to make the final decision. However, most of the current label fusion methods consider each voxel equally and independently during label fusion. In our point of view, however, different voxels act different roles in the way that some voxels might have much higher confidence in label determination than others, i.

A novel framework for longitudinal atlas construction with groupwise registration of subject image sequences.

Longitudinal atlas construction plays an important role in medical image analysis. Given a set of longitudinal images from different subjects, the task of longitudinal atlas construction is to build an atlas sequence which can represent the trend of anatomical changes of the population. The major challenge for longitudinal atlas construction is how to effectively incorporate both the subject-specific information and population information to build the unbiased atlases.

Iterative multi-atlas-based multi-image segmentation with tree-based registration.

In this paper, we present a multi-atlas-based framework for accurate, consistent and simultaneous segmentation of a group of target images. Multi-atlas-based segmentation algorithms consider concurrently complementary information from multiple atlases to produce optimal segmentation outcomes. However, the accuracy of these algorithms relies heavily on the precise alignment of the atlases with the target image.

A novel longitudinal atlas construction framework by groupwise registration of subject image sequences.

Longitudinal atlas construction is a challenging task in medical image analysis. Given a set of longitudinal images of different subjects, the task is how to construct the unbias longitudinal atlas sequence reflecting the anatomical changes over time. In this paper, a novel longitudinal atlas construction framework is proposed.

Infant brain atlases from neonates to 1- and 2-year-olds.

Background: Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications.

SharpMean: groupwise registration guided by sharp mean image and tree-based registration.

Groupwise registration has become more and more popular due to its attractiveness for unbiased analysis of population data. One of the most popular approaches for groupwise registration is to iteratively calculate the group mean image and then register all subject images towards the latest estimated group mean image. However, its performance might be undermined by the fuzzy mean image estimated in the very beginning of groupwise registration procedure, because all subject images are far from being well-aligned at that moment.

Feature-based groupwise registration by hierarchical anatomical correspondence detection.

Groupwise registration has been widely investigated in recent years due to its importance in analyzing population data in many clinical applications. To our best knowledge, most of the groupwise registration algorithms only utilize the intensity information. However, it is well known that using intensity only is not sufficient to achieve the anatomically sound correspondences in medical image registration.

Groupwise registration by hierarchical anatomical correspondence detection.

We present a novel feature-based groupwise registration method to simultaneously warp the subjects towards the common space. Due to the complexity of the groupwise registration, we resort to decoupling it into two easy-to-solve tasks, i.e.

Registration of longitudinal image sequences with implicit template and spatial-temporal heuristics.

Accurate measurement of longitudinal changes of anatomical structure is important and challenging in many clinical studies. Also, for identification of disease-affected regions due to the brain disease, it is extremely necessary to register a population data to the common space simultaneously. In this paper, we propose a new method for simultaneous longitudinal and groupwise registration of a set of longitudinal data acquired from multiple subjects.

Groupwise registration with sharp mean.

Groupwise registration has received more and more attention in the area of medical image analysis, due to its importance in analysis of population data. One popular way for groupwise registration is to alternatively estimate the group mean image and register all subject images to the estimated group mean. However, for achieving better registration performance, it is important to always keep the sharpness of the group mean image during the registration, which has not been well investigated yet in the literature.

Intermediate templates guided groupwise registration of diffusion tensor images.

Registration of a population of diffusion tensor images (DTIs) is one of the key steps in medical image analysis, and it plays an important role in the statistical analysis of white matter related neurological diseases. However, pairwise registration with respect to a pre-selected template may not give precise results if the selected template deviates significantly from the distribution of images. To cater for more accurate and consistent registration, a novel framework is proposed for groupwise registration with the guidance from one or more intermediate templates determined from the population of images.

ABSORB: Atlas Building by Self-organized Registration and Bundling.

To achieve more accurate and consistent registration in an image population, a novel hierarchical groupwise registration framework, called Atlas Building by Self-Organized Registration and Bundling (ABSORB), is proposed in this paper. In this new framework, the global structure, i.e.