Endoscopic ultrasound-based radiomics for predicting pathologic upgrade in esophageal low-grade intraepithelial neoplasia.

Background: There is no consensus on managing patients with endoscopic suspicion of early esophageal squamous cell carcinoma (ESCC) but biopsy-confirmed low-grade intraepithelial neoplasia (LGIN). The aim of this study is to evaluate the utility of an endoscopic ultrasound (EUS)-based radiomics nomogram for predicting esophageal LGIN pathological progression before diagnostic endoscopic submucosal dissection (ESD).

Methods: In the development phase, EUS images of 535 patients who had biopsy-confirmed LGIN and were undergoing ESD were retrospectively included.

Immunosuppressant nonadherence profile in kidney transplant recipients and the impact of medication adherence on transplant outcomes.

Background: Despite the fact that 1-year graft and recipient survival rates are above 90% in most transplant centers, improving long-term graft survival remains an important challenge. Immunosuppressant nonadherence has been recognized as one of the important risk factors for long-term graft failure. Understanding the modifiable correlates and risk factors for medication non-adherence is essential to develop interventions to improve adherence and thus long-term transplantation outcomes.

A Multicenter Cohort Study on Ultrasound-based Deep Learning Nomogram for Predicting Post-Neoadjuvant Chemotherapy Axillary Lymph Node Status in Breast Cancer Patients.

Rationale And Objectives: The aim of this study was to evaluate the capability of an ultrasound (US)-based deep learning (DL) nomogram for predicting axillary lymph node (ALN) status after neoadjuvant chemotherapy (NAC) in breast cancer patients and its potential to assist radiologists in diagnosis.

Methods: Two medical centers retrospectively recruited 535 node-positive breast cancer patients who had undergone NAC. Center 1 included 288 patients in the training cohort and 123 patients in the internal validation cohort, while center 2 enrolled 124 patients for the external validation cohort.

Impact of several sludge dewatering conditioners on municipal sludge pyrolysis properties, kinetics, by-products, and environmental risk assessment.

The pyrolysis characteristics of four different types of conditioned sludge were ascertained, and PAM, CaO, KFeO, and KFeO-CaO-PAM (KCP) conditioners were employed as sludge dewatering conditioners. The sludge pyrolysis reaction's activation energy (E) dropped with the addition of four conditioners. CaO, PAM, KCP, and KFeO were the sequences of E needed for the pyrolysis of four different types of conditioned sludge.

Radiomics of pericoronary adipose tissue on computed tomography angiography predicts coronary heart disease in patients with type 2 diabetes mellitus.

Background: Diabetes is a common chronic metabolic disease. The progression of the disease promotes vascular inflammation and the formation of atherosclerosis, leading to cardiovascular disease. The coronary artery perivascular adipose tissue attenuation index based on CCTA is a new noninvasive imaging biomarker that reflects the spatial changes in perivascular adipose tissue attenuation in CCTA images and the inflammation around the coronary arteries.

Compact optical fiber sensor based on Vernier effect with speckle patterns.

We propose a Vernier effect-based sensor for temperature and salinity measurements. This sensor utilizes the correlation speckle pattern generated by spatial multimode interference and has undergone testing to validate its effectiveness. The speckle demodulation method is used to solve the problem of inconsistent envelope measurement when tracking with different upper and lower envelopes.

Endoscopic retrograde cholangiopancreatography for diagnosing and treating pediatric biliary and pancreatic diseases.

Background: This study evaluated the safety and effectiveness of endoscopic retrograde cholangiopancreatography (ERCP) in pediatric patients with biliary and pancreatic diseases. A retrospective analysis was conducted on 57 ERCP procedures performed in 41 children, primarily for treating pancreatic diseases. The overall success rate was 91.

Analysis of the gut microbiota in children with gastroesophageal reflux disease using metagenomics and metabolomics.

Background: There is no direct evidence of gut microbiota disturbance in children with gastroesophageal reflux disease (GERD). This study aimed to provide direct evidence and a comprehensive understanding of gut microbiota disturbance in children with GERD through combined metagenomic and metabolomic analysis.

Methods: 30 children with GERD and 30 healthy controls (HCs) were continuously enrolled, and the demographic and clinical characteristics of the subjects were collected.

Integrated Fiber Ring Laser Temperature Sensor Based on Vernier Effect with Lyot-Sagnac Interferometer.

The Vernier effect created using an incorporated Lyot-Sagnac loop is used to create an ultra-high sensitivity temperature sensor based on a ring laser cavity. Unlike standard double Sagnac loop systems, the proposed sensor is fused into a single Sagnac loop by adjusting the welding angle between two polarization-maintaining fibers (PMFs) to achieve effective temperature sensitivity amplification. The PMFs are separated into two arms of 0.

Pretreatment ultrasound-based deep learning radiomics model for the early prediction of pathologic response to neoadjuvant chemotherapy in breast cancer.

Objectives: To investigate the predictive performance of the deep learning radiomics (DLR) model integrating pretreatment ultrasound imaging features and clinical characteristics for evaluating therapeutic response after neoadjuvant chemotherapy (NAC) in patients with breast cancer.

Methods: A total of 603 patients who underwent NAC were retrospectively included between January 2018 and June 2021 from three different institutions. Four different deep convolutional neural networks (DCNNs) were trained by pretreatment ultrasound images using annotated training dataset (n = 420) and validated in a testing cohort (n = 183).

High-speed ADC based on photonic time-stretched technology with dispersion-tunable CFBG.

We propose a photonic time-stretched analog-to-digital converter (PTS-ADC) based on dispersion-tunable chirped fiber Bragg grating (CFBG), by demonstrating a economical ADC system with seven different stretch factors. The stretch factors are tunable by changing the dispersion of CFBG, in order to obtain different sampling points. Accordingly, the total sampling rate of the system can be improved.

Accelerating the phase demodulation process for heterodyne Φ-OTDR using spatial phase shifting.

An effective orthogonal signal generation method for heterodyne-detection-based phase-sensitive optical time-domain reflectometer systems is proposed to accelerate the phase demodulation process. The demodulation principle is based on the spatial phase shifting technique. By exploiting the relative phase difference between adjacent spatial sampling channels, the orthogonal signal is easily obtained from basic algebra calculations.

Salinity and Temperature Dual-Parameter Sensor Based on Fiber Ring Laser with Tapered Side-Hole Fiber Embedded in Sagnac Interferometer.

This paper presented a new kind of salinity and temperature dual-parameter sensor based on a fiber ring laser (FRL) with tapered side-hole fiber (SHF) embedded in a Sagnac interferometer. The sensing structure is majorly composed of tapered SHF located in the middle of SHF inside the Sagnac interferometer loop structure. The influences of the SHF's diameters of different tapered in the Sagnac interferometer loop on the FRL sensing system are studied.

Adaptive Fiber-Ring Lasers Based on Isopropanol Filled Microfiber Coupler for High-Sensitivity Temperature Sensing.

We demonstrated a new method for temperature measurement inside a fiber ring laser (FRL) cavity. Different from traditional FRL temperature sensing system which need additional filter working as a sensor, a micro-fiber coupler (MFC) was designed as a beam splitter, filter, and temperature sensor. In addition, isopropanol, a liquid with very high photothermal coefficient, is selectively filled in the MFC in order to improve the sensitivity of the system on temperature.

Evaluation of the Ecological Environment Quality of the Kuye River Source Basin Using the Remote Sensing Ecological Index.

Landsat remote sensing images obtained from 2000, 2005, 2010, 2015, and 2020 were analyzed. The normalized vegetation index (NDVI), moisture index (WET), land surface temperature (LST), and normalized building-soil index (NDBSI) were extracted based on the four aspects of greenness, humidity, heat, and dryness. The Remote Sensing Ecological Index (RSEI) was calculated using principal component analysis to quantitatively analyze and dynamically monitor and evaluate the ecological environment changes in the Kuye River Basin over the past 20 years.

Data Reduction in Phase-Sensitive OTDR with Ultra-Low Sampling Resolution and Undersampling Techniques.

Data storage is a problem that cannot be ignored in the long-term monitoring of a phase-sensitive optical time-domain reflectometry (Φ-OTDR) system. In this paper, we proposed a data-reduction approach for heterodyne Φ-OTDR using an ultra-low sampling resolution and undersampling techniques. The operation principles were demonstrated and experiments with different sensing configurations were carried out to verify the proposed method.

Ultra-low sampling resolution technique for heterodyne phase-OTDR based distributed acoustic sensing.

Phase-sensitive optical time-domain reflectometry (Φ-OTDR) based on heterodyne detection is widely used for its simple structure and high signal-to-noise ratio (SNR). However, the large amount of raw data of Φ-OTDR places a heavy burden on the storage device and also limits the transferability of the data. In this Letter, we propose an ultra-low sampling resolution technique to solve the data storage problem in heterodyne Φ-OTDR.

Droplet-engineered organoids recapitulate parental tissue transcriptome with inter-organoid homogeneity and inter-tumor cell heterogeneity.

Organoids are expected to function as effective human organ models for precision cancer studies and drug development. Currently, primary tissue-derived organoids, termed non-engineered organoids (NEOs), are produced by manual pipetting or liquid handling that compromises organoid-organoid homogeneity and organoid-tissue consistency. Droplet-based microfluidics enables automated organoid production with high organoid-organoid homogeneity, organoid-tissue consistency, and a significantly improved production spectrum.

Quantitative demodulation of distributed low-frequency vibration based on phase-shifted dual-pulse phase-sensitive OTDR with direct detection.

Phase-sensitive optical time-domain reflectometry (Φ-OTDR) has been proposed for distributed vibration sensing purpose over recent years. Emerging applications, including seismic and hydroacoustic wave detection, demand accurate low-frequency vibration reconstruction capability. We propose to use the direct-detection Φ-OTDR configuration to achieve quantitative demodulation of external low-frequency vibrations by phase-shifted dual-pulse probes.

Real-Time Multi-Class Disturbance Detection for Φ-OTDR Based on YOLO Algorithm.

This paper proposes a real-time multi-class disturbance detection algorithm based on YOLO for distributed fiber vibration sensing. The algorithm achieves real-time detection of event location and classification on external intrusions sensed by distributed optical fiber sensing system (DOFS) based on phase-sensitive optical time-domain reflectometry (Φ-OTDR). We conducted data collection under perimeter security scenarios and acquired five types of events with a total of 5787 samples.

Optical curvature sensor with high resolution based on in-line fiber Mach-Zehnder interferometer and microwave photonic filter.

Curvature measurement plays an important role in structural health monitoring, robot-pose measuring, etc. High-resolution curvature measurement is highly demanded. In this paper, an optical curvature sensor with high resolution based on in-fiber Mach-Zehnder interferometer (MZI) and microwave photonic filter (MPF) is proposed and experimentally demonstrated.

Automatic lens-splitting optimization algorithm for spherical aberration correction.

This paper proposes the automatic lens-splitting optimization algorithm to correct spherical aberration by the interaction between ZEMAX and MATLAB. This method tackled the problem that classic optimization cannot add the elements automatically. A high numerical aperture collimator is considered for the test sample, and the selection of four thickness constraints (minimum center and edge of glass and air thickness constraints) is discussed.