Cortisol dysregulation in anxiety infertile women and the influence on IVF treatment outcome

IntroductionDysregulation of the stress-regulatory hormone cortisol is associated with anxiety, but its potential impact on infertile women and in vitro fertilization (IVF) treatment remains unclear. This prospective cross-sectional study aimed at evaluating the dysregulation of cortisol and its correlation to anxiety in infertile women. The influence of stress on IVF outcomes was also investigated.MethodsA point-of-care test was used for the measurement of morning serum cortisol in 110 infertile women and 112 age-matching healthy individuals. A Self-Rating Anxiety Scale (SAS) was used for the anxiety assessment of infertile women, and 109 of them underwent IVF treatment starting with the GnRH-antagonist protocol. If clinical pregnancy was not achieved, more IVF cycles were conducted with adjusted protocols until the patients got pregnant or gave up.ResultsHigher morning serum cortisol level was identified for infertile patients, especially for the elder. Women with no anxiety showed significant differences in cortisol levels, monthly income, and BMI compared with those with severe anxiety. A strong correlation was found between the morning cortisol level and the SAS score. When the cutoff value is 22.25 μg/dL, cortisol concentration could predict the onset of anxiety with high accuracy (95.45%) among infertile women. After IVF treatments, women with high SAS scores (>50) or cortisol levels (>22.25 μg/dL) demonstrated a lower rate of pregnancy (8.0%-10.3%) and more IVF cycles, although the impact of anxiety was not affirmative.ConclusionHypersecretion of cortisol related to anxiety was prevalent among infertile women, but the influence of anxiety on multi-cycle IVF treatment was not affirmative due to the complicated treatment procedures. This study suggested that the assessment of psychological disorders and stress hormone dysregulation should not be overlooked. An anxiety questionnaire and rapid cortisol test might be included in the treatment protocol to provide better medical care

A SURF4-to-proteoglycan relay mechanism that mediates the sorting and secretion of a tagged variant of sonic hedgehog

SignificanceSonic Hedgehog (Shh) is a key signaling molecule that plays important roles in embryonic patterning, cell differentiation, and organ development. Although fundamentally important, the molecular mechanisms that regulate secretion of newly synthesized Shh are still unclear. Our study reveals a role for the cargo receptor, SURF4, in facilitating export of Shh from the endoplasmic reticulum (ER) via a ER export signal. In addition, our study provides evidence suggesting that proteoglycans promote the dissociation of SURF4 from Shh at the Golgi, suggesting a SURF4-to-proteoglycan relay mechanism. These analyses provide insight into an important question in cell biology: how do cargo receptors capture their clients in one compartment, then disengage at their destination?</p

Implementation and performances of the IPbus protocol for the JUNO Large-PMT readout electronics

The Jiangmen Underground Neutrino Observatory (JUNO) is a large neutrino detector currently under construction in China. Thanks to the tight requirements on its optical and radio-purity properties, it will be able to perform leading measurements detecting terrestrial and astrophysical neutrinos in a wide energy range from tens of keV to hundreds of MeV. A key requirement for the success of the experiment is an unprecedented 3% energy resolution, guaranteed by its large active mass (20 kton) and the use of more than 20,000 20-inch photo-multiplier tubes (PMTs) acquired by high-speed, high-resolution sampling electronics located very close to the PMTs. As the Front-End and Read-Out electronics is expected to continuously run underwater for 30 years, a reliable readout acquisition system capable of handling the timestamped data stream coming from the Large-PMTs and permitting to simultaneously monitor and operate remotely the inaccessible electronics had to be developed. In this contribution, the firmware and hardware implementation of the IPbus based readout protocol will be presented, together with the performances measured on final modules during the mass production of the electronics

Mass testing of the JUNO experiment 20-inch PMTs readout electronics

The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose, large size, liquid scintillator experiment under construction in China. JUNO will perform leading measurements detecting neutrinos from different sources (reactor, terrestrial and astrophysical neutrinos) covering a wide energy range (from 200 keV to several GeV). This paper focuses on the design and development of a test protocol for the 20-inch PMT underwater readout electronics, performed in parallel to the mass production line. In a time period of about ten months, a total number of 6950 electronic boards were tested with an acceptance yield of 99.1%

Validation and integration tests of the JUNO 20-inch PMTs readout electronics

The Jiangmen Underground Neutrino Observatory (JUNO) is a large neutrino detector currently under construction in China. JUNO will be able to study the neutrino mass ordering and to perform leading measurements detecting terrestrial and astrophysical neutrinos in a wide energy range, spanning from 200 keV to several GeV. Given the ambitious physics goals of JUNO, the electronic system has to meet specific tight requirements, and a thorough characterization is required. The present paper describes the tests performed on the readout modules to measure their performances.Comment: 20 pages, 13 figure

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Molecular classification of human papilloma virus-negative head and neck squamous cell carcinomas: Cell cycle-based classifier and prognostic signature.

The molecular classification of human papillomavirus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs) remains questionable. Differentially expressed genes were detected between tumor and normal tissues and GSEA showed they are associated with cell cycle pathways. This study aimed to classify HPV-negative HNSCCs based on cell cycle-related genes. The established gene pattern was correlated with tumor progression, clinical prognosis, and drug treatment efficacy. Biological analysis was performed using HNSCC patient sample data obtained from the Cancer Genome Atlas (TCGA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), and Gene Expression Omnibus (GEO) databases. All samples included in this study contained survival information. RNA sequencing data from 740 samples were used for the analysis. Previously characterized cell cycle-related genes were included for unsupervised consensus clustering. Two subtypes of HPV-negative HNSCCs (C1, C2) were identified. Subtype C1 displayed low cell cycle activity, 'hot' tumor microenvironment (TME), earlier N stage, lower pathological grade, better prognosis, and higher response rate to the immunotherapy and targeted therapy. Subtype C2 was associated with higher cell cycle activity, 'cold' TME, later N stage, higher pathological grade, worse prognosis, and lower response rate to the treatment. According to the nearest template prediction method, classification rules were established and verified. Our work explored the molecular mechanism of HPV-negative HNSCCs in the view of cell cycle and might provide new sights for personalized anti-cancer treatment

Face recognition of a Lorisidae species based on computer vision

The slow loris is a group of endangered small arboreal primates. In recent decades, illegal hunting and habitat degradation have led to a sharp decline in wild populations. The individuals are challenging to be identified both in captive and natural environments due to their cryptic nocturnal behavior. Computer vision has emerged as a new approach to face recognition for domestic and wild animals. We used a YOLOv5 +U-Net+VGG framework to realize the face identification of Bengal slow lorises (Nycticebus bengalensis) based on 1480 images of 30 individuals housed in Dehong Wildlife Rescue Center, China. This is the first human-annotated face image dataset of Lorisidae primates. The accuracy rate of this deep learning model set for face recognition reached 96.27 %. The results indicated that computer vision and deep learning technology could be used in individual identification of slow lorises, contributing to further study and conservation of this endangered taxa