An Optimized Bidirectional Long Short-Term Memory Model Based on Hyperspectral Analysis of Protein Content in Milk Powder.

Protein content is an important index in the assessment of dairy nutrition. As a crucial source of protein absorption in people's daily life, the quality of milk powder products not only has a deep impact on the development of the dairy industry, but also seriously damages the health of consumers. It is of great significance to find a faster and more accurate method for detecting milk protein content.

Breast Tumor Detection and Diagnosis Using an Improved Faster R-CNN in DCE-MRI.

AI-based breast cancer detection can improve the sensitivity and specificity of detection, especially for small lesions, which has clinical value in realizing early detection and treatment so as to reduce mortality. The two-stage detection network performs well; however, it adopts an imprecise ROI during classification, which can easily include surrounding tumor tissues. Additionally, fuzzy noise is a significant contributor to false positives.

Switchable generation and dynamic evolution of vector vortex beams.

The vector vortex beams (VVBs) are endowed with helical phase and vector polarization. The rich optical properties of VVBs have attracted extensive concern. Here the geometric phase is applied to manipulate both the phase and polarization of light for switchable generation of VVBs by vortex plates.

Automatic segmentation-based multi-modal radiomics analysis of US and MRI for predicting disease-free survival of breast cancer: a multicenter study.

Background: Several studies have confirmed the potential value of applying radiomics to predict prognosis of breast cancer. However, the tumor segmentation in these studies depended on delineation or annotation of breast cancer by radiologist, which is often laborious, tedious, and vulnerable to inter- and intra-observer variability. Automatic segmentation is expected to overcome this difficulty.

FS-YOLOv9: A Frequency and Spatial Feature-Based YOLOv9 for Real-time Breast Cancer Detection.

Rationale And Objectives: Breast cancer screening is critical for reducing mortality rates. YOLOv9, a new real-time object-detection model, is ideal for cancer screening. A customized YOLOv9 model with enhancements for detecting breast cancer on the basis of species and morphological diversity has potential clinical significance.

Melatonin Alleviates Osteoarthritis by Regulating NADPH Oxidase 4-Induced Ferroptosis and Mitigating Mitochondrial Dysfunction.

Recent evidence indicates that the damaged regions in osteoarthritis are accompanied by the accumulation of iron ions. Ferroptosis, as an iron-dependent form of cell death, holds significant implications in osteoarthritis. Melatonin, a natural product with strong scavenging abilities against reactive oxygen species and lipid peroxidation, plays a crucial role in the treatment of osteoarthritis.

Preoperative Prediction of Axillary Lymph Node Metastasis in Patients With Breast Cancer Through Multimodal Deep Learning Based on Ultrasound and Magnetic Resonance Imaging Images.

Rationale And Objectives: Deep learning can enhance the performance of multimodal image analysis, which is known for its noninvasive attributes and complementary efficacy, in predicting axillary lymph node (ALN) metastasis. Therefore, we established a multimodal deep learning model incorporating ultrasound (US) and magnetic resonance imaging (MRI) images to predict ALN metastasis in patients with breast cancer.

Materials And Methods: A retrospective cohort of patients with histologically confirmed breast cancer from two hospitals composed of the primary cohort (n = 465) and the external validation cohort (n = 123).

Finite element analysis of a novel anatomical plate in posterolateral plateau fractures.

Objective: This study aims to analyze the biomechanical characteristics of posterolateral plateau fractures fixed by a novel anatomical plate using finite element analysis.

Methods: A three-dimensional digital model of the full length of right tibiofibula was obtained by CT scanning. A posterolateral tibial plateau fracture model was then created.

Surgical pathway for HIV‑infected patients based on the ERAS strategy (Review).

Enhanced recovery after surgery (ERAS), which is based on evidence-based medicine, focuses on patients and aims to reduce the psychological and physiological trauma stress reactions and complications of patients, thus shortening the duration of hospitalization, promoting rapid recovery and reducing medical expenses, readmission rate and mortality rates. Acquired immunodeficiency syndrome (AIDS) is caused by human immunodeficiency virus (HIV) infection. Patients with HIV/AIDS, as with other patient populations, can suffer from several surgical-related diseases.

LFMNet: a lightweight model for identifying leaf diseases of maize with high similarity.

Maize leaf diseases significantly impact yield and quality. However, recognizing these diseases from images taken in natural environments is challenging due to complex backgrounds and high similarity of disease spots between classes.This study proposes a lightweight multi-level attention fusion network (LFMNet) which can identify maize leaf diseases with high similarity in natural environment.

Classification and recognition of milk somatic cell images based on PolyLoss and PCAM-Reset50.

Somatic cell count (SCC) is a fundamental approach for determining the quality of cattle and bovine milk. So far, different classification and recognition methods have been proposed, all with certain limitations. In this study, we introduced a new deep learning tool, i.

An Online Mammography Database with Biopsy Confirmed Types.

Breast carcinoma is the second largest cancer in the world among women. Early detection of breast cancer has been shown to increase the survival rate, thereby significantly increasing patients' lifespan. Mammography, a noninvasive imaging tool with low cost, is widely used to diagnose breast disease at an early stage due to its high sensitivity.

Splenic Artery Steal Syndrome in Patients with Liver Cirrhosis: A Retrospective Clinical Study.

BACKGROUND Splenic artery steal syndrome (SASS) can aggravate liver damage in patients with cirrhosis. This study explored whether SASS could be an effective therapeutic target for improving hepatic artery perfusion and liver function in patients with decompensated cirrhosis. MATERIAL AND METHODS Based on inclusion and exclusion criteria, 87 patients with hepatitis B cirrhosis and portal hypertension hypersplenism admitted to our General Surgery Department for splenectomy and pericardial devascularization surgery were selected.

Quantitative detection of high-order Poincaré sphere beams and their polarization evolution.

The high-order Poincaré sphere (PS) introduces a mapping whereby any vector beams with spatially homogeneous ellipticity are represented by a specific point on the surface of the sphere. We propose the quantitative detection of high-order PS beams by introducing three sets of nonuniform polarization bases in the high-order Stokes parameters. Overall polarization detection is realized by directly separating and measuring the respective intensity of different nonuniform polarization bases based on S-plate.

Risk of primary osteoporosis score (RPOPs): an algorithm model for primary osteoporosis risk assessment in grass-roots hospital.

Background: This study aimed to develop and validate a lasso regression algorithm model which was established by correlation factors of bone mineral density (BMD) and could be accurately predicted a high-risk population of primary osteoporosis (POP). It provides a rapid, economical and acceptable early screening method for osteoporosis in grass-roots hospitals.

Methods: We collected 120 subjects from primary osteoporosis screening population in Zhejiang Quhua Hospital between May 2021 and November 2021 who were divided into three groups (normal, osteopenia and osteoporosis) according to the BMD T-score.

A radiomics-based model can predict recurrence-free survival of hepatocellular carcinoma after curative ablation.

Background: Prediction of early recurrence (ER) of HCC after radical treatment is of great significance for follow-up and subsequent treatment, and there is a lot of unmet needs. Here, our goal is to develop and validate a radiomics nomogram that can predict ER after curative ablation.

Objective: The aim of this study was to evaluate the efficacy and safety of regorafenib after disease progression with sorafenib in Chinese patients with advanced HCC through this retrospective analysis.

Real-Life Experience of Regorafenib in Patients With Advanced Hepatocellular Carcinoma.

The RESORCE trial reported that regorafenib was effective as the second-line treatment for patients with hepatocellular carcinoma (HCC) after progression on sorafenib. Real-world data are needed to assess clinical outcomes and adverse events in the setting of daily practice. We aimed to evaluate the efficacy and safety of regorafenib after disease progression with sorafenib in Chinese patients with advanced HCC.

MRI-Based Radiomics Features to Predict Treatment Response to Neoadjuvant Chemotherapy in Locally Advanced Rectal Cancer: A Single Center, Prospective Study.

This is a prospective, single center study aimed to evaluate the predictive power of peritumor and intratumor radiomics features assessed using T2 weight image (T2WI) of baseline magnetic resonance imaging (MRI) in evaluating pathological good response to NAC in patients with LARC (including Tany N+ or T3/4a Nany but not T4b). In total, 137 patients with LARC received NAC between April 2014 and August 2020. All patients were undergoing contrast-enhanced MRI and 129 patients contained small field of view (sFOV) sequence which were performed prior to treatment.

Recognition of bovine milk somatic cells based on multi-feature extraction and a GBDT-AdaBoost fusion model.

Traditional laboratory microscopy for identifying bovine milk somatic cells is subjective, time-consuming, and labor-intensive. The accuracy of the recognition directly through a single classifier is low. In this paper, a novel algorithm that combined the feature extraction algorithm and fusion classification model was proposed to identify the somatic cells.

Cascaded stimulated Brillouin scattering erbium-doped fiber laser generating orbital angular momentum beams at tunable wavelengths.

We experimentally demonstrate a method to obtain central wavelength tunable orbital angular momentum beams with switchable topological charges (+1 or -1) in a stimulated Brillouin scattering erbium-doped fiber laser. Multiwavelength operation is achieved through cascaded stimulated Brillouin scattering in a single-mode fiber with a length of 6 km initiated by an external Brillouin pump. High-efficiency mode conversion between the fundamental mode and the orbital angular momentum modes is realized through a broadband two-mode long-period fiber grating.

Ultrasound-Based Radiomics Analysis for Predicting Disease-Free Survival of Invasive Breast Cancer.

Background: Accurate prediction of recurrence is crucial for personalized treatment in breast cancer, and whether the radiomics features of ultrasound (US) could be used to predict recurrence of breast cancer is still uncertain. Here, we developed a radiomics signature based on preoperative US to predict disease-free survival (DFS) in patients with invasive breast cancer and assess its additional value to the clinicopathological predictors for individualized DFS prediction.

Methods: We identified 620 patients with invasive breast cancer and randomly divided them into the training (n = 372) and validation (n = 248) cohorts.

A practical study of the hepatic vascular system anatomy of the caudate lobe.

Background: This study aimed to examine the inflow and outflow vascular system of the caudate lobe and determine its relevance to hepatobiliary surgery.

Methods: A total of 41 cadaveric liver specimens were dissected in 2019 to evaluate the inflow and outflow vascular system of the caudate lobe.

Results: The Glisson's pedicles of the paracaval portion were mainly from the right pedicle in 14 cases (34.

Radiomics Model Based on Gadoxetic Acid Disodium-Enhanced MR Imaging to Predict Hepatocellular Carcinoma Recurrence After Curative Ablation.

Background: A practical prognostic prediction model is absent for hepatocellular carcinoma (HCC) patients after curative ablation. We aimed to develop a radiomics model based on gadoxetic acid disodium-enhanced magnetic resonance (MR) images to predict HCC recurrence after curative ablation.

Methods: We retrospectively enrolled 132 patients with HCC who underwent curative ablation.

Radiomics-based model using gadoxetic acid disodium-enhanced MR images: associations with recurrence-free survival of patients with hepatocellular carcinoma treated by surgical resection.

Purpose: To develop a prediction model that combined magnetic resonance images (MRI)-based radiomics features with clinical factors to predict recurrence-free survival (RFS) of hepatocellular carcinoma (HCC) patients treated with surgical resection.

Methods: HCC patients treated with surgical resection (n = 153) were randomly divided into training (n = 107) and validation (n = 46) datasets. The volumes of interest were manually outlined around the lesion and additional 2 mm and 5 mm peritumoral areas were created with automated dilatation in MRI to extract tumoral (T) and peritumoral (PT) radiomics features.