LPYC225 mixture partially modulates the vaginal bacterial community of -infected bacterial vaginosis in mice.

Unlabelled: Bacterial vaginosis (BV) is defined as dysbiosis of the vaginal microbiome associated with the depletion of and excessive growth of commensal or pathogenic bacteria. This study investigated the effects of lactic acid bacteria (LAB) mixture (LM; InoRexyne™) on the vaginal bacterial community of ()-infected BV mice. Single LAB and LM exhibited antibacterial and anti-inflammatory effects by inhibiting growth and pro-inflammatory markers in RAW 264.

The protective effect of L-theanine addition to a cryoprotectant on the storage viability of lactic acid bacteria.

Lactic acid bacteria (LAB) that metabolize sugars to obtain energy and produce a large amount of lactate through the process are well known for their benefits. However, they can be used on a large scale only when good storage stability is guaranteed. The vitality and stability of several LAB strains were effectively protected in this investigation by L-theanine at 1% of the appropriate concentration (Lactiplantibacillus plantarum MG5023, Enterococcus faecium MG5232, Lactococcus lactis MG4668, Streptococcus thermophilus MG5140, and Bifidobacterium animalis subsp.

Tone Image Classification and Weighted Learning for Visible and NIR Image Fusion.

In this paper, to improve the slow processing speed of the rule-based visible and NIR (near-infrared) image synthesis method, we present a fast image fusion method using DenseFuse, one of the CNN (convolutional neural network)-based image synthesis methods. The proposed method applies a raster scan algorithm to secure visible and NIR datasets for effective learning and presents a dataset classification method using luminance and variance. Additionally, in this paper, a method for synthesizing a feature map in a fusion layer is presented and compared with the method for synthesizing a feature map in other fusion layers.

Rainwater-Removal Image Conversion Learning with Training Pair Augmentation.

In this study, we proposed an image conversion method that efficiently removes raindrops on a camera lens from an image using a deep learning technique. The proposed method effectively presents a raindrop-removed image using the Pix2pix generative adversarial network (GAN) model, which can understand the characteristics of two images in terms of newly formed images of different domains. The learning method based on the captured image has the disadvantage that a large amount of data is required for learning and that unnecessary noise is generated owing to the nature of the learning model.

Combined Deep Learning Techniques for Mandibular Fracture Diagnosis Assistance.

Mandibular fractures are the most common fractures in dentistry. Since diagnosing a mandibular fracture is difficult when only panoramic radiographic images are used, most doctors use cone beam computed tomography (CBCT) to identify the patient's fracture location. In this study, considering the diagnosis of mandibular fractures using the combined deep learning technique, YOLO and U-Net were used as auxiliary diagnostic methods to detect the location of mandibular fractures based on panoramic images without CBCT.

Automatic Detection of Mandibular Fractures in Panoramic Radiographs Using Deep Learning.

Mandibular fracture is one of the most frequent injuries in oral and maxillo-facial surgery. Radiologists diagnose mandibular fractures using panoramic radiography and cone-beam computed tomography (CBCT). Panoramic radiography is a conventional imaging modality, which is less complicated than CBCT.

The Relationship between a Spouse's Alcohol Use Disorder and Family Communication.

Background: Alcohol use disorder (AUD) affects not only an individual's health but also their family. This study was conducted to examine effects of a spouse's AUD on family functioning and family communication.

Methods: We conducted a cross-sectional study using data from 890 participants (445 couples) in a Korean family cohort in primary care.