Visible-Light Self-Powered Photodetector with High Sensitivity Based on the Type-II Heterostructure of CdPSe3/MoS2.

Transition metal thiophosphates (MTPs) are a group of emerging van der Waals materials with widely tunable band gaps. In the MTP family, CdPSe3 is demonstrated to possess a wide energy band gap and high carrier mobility, making it a potential candidate in optoelectronic applications. Here, we reported photoelectric response behaviors of both CdPSe3- and CdPSe3/MoS2-based photodetectors (noted as CPS and CM, respectively); these showed prominent photoelectric performances, and the latter proved to be significantly superior to the former. These devices exhibited ultralow dark current at a magnitude order of 10-12 A and fine cycle and air stabilities. Compared with CPS, CM demonstrated the highest responsivity (91.12 mA/W) and detectivity (1.74 × 1011 Jones) at 5 V under 425 nm light illumination. Besides, CM showed self-powered photoelectric responses at zero bias, which was attributed to the improved separation efficiency of photogenerated carriers by the built-in electric field at the interface of the p-n junction. This work proves a prospect for the CM device in portable, self-powered optoelectronic device applications.

A retrospective study comparing the efficacy of microwave ablation and stereotactic body radiotherapy in colorectal cancer lung metastases.

The purpose of the present study was to assess and compare the efficacy of microwave ablation (MWA) and stereotactic body radiotherapy (SBRT) in the treatment of lung metastases from patients with colorectal cancer (CRC) and to identify the preferable treatment modality based on patient and tumor characteristics. Records of 118 patients with CRC with a total of 307 lung metastases who underwent SBRT or MWA between January 2015 and December 2022 were retrospectively analyzed, including the essential clinicopathological information on patients (age, sex and underlying diseases), diagnosis and treatment information [primary tumor site, levels of carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9], imaging data [diameter of lung metastasis, location of the metastasis (i.e., whether or not the tumor was adjacent to the vessel or bronchus) and internal features] and follow-up data (postoperative therapy, complications or adverse effects and survival outcomes). For statistical analysis of the local tumor progression (LTP), disease-free survival and overall survival (OS) rates, Cox regression analysis, along with the Kaplan-Meier method adjusted using inverse probability of treatment weighting (IPTW), were performed. The median follow-up duration in the present study was 31.5 months. Multivariable Cox regression analysis revealed that the CEA level, metastasis diameter and internal features were independent predictors of OS. In the IPTW-adjusted analysis, no significant difference in the 1-year OS rate was observed between the SBRT and MWA groups (92.9 vs. 93.9%; P=0.483); however, a notable discrepancy in the treatment modalities was noted, leading to significant differences in the 2- and 3-year OS rates (65.9 vs. 57.6%, P=0.001, and 44.7 vs. 36.4%, P<0.001, respectively). A significant interaction effect for the treatment modality was observed for LTP (P=0.021). In conclusion, the present study revealed that SBRT and MWA have similar therapeutic effects in terms of prolonging the survival of patients with CRC with lung metastases; however, regarding the local control of lung metastases, MWA is associated with a number of significant advantages.

Classification of cervical lesions based on multimodal features fusion.

Cervical cancer is a severe threat to women's health worldwide with a long cancerous cycle and a clear etiology, making early screening vital for the prevention and treatment. Based on the dataset provided by the Obstetrics and Gynecology Hospital of Fudan University, a four-category classification model for cervical lesions including Normal, low-grade squamous intraepithelial lesion (LSIL), high-grade squamous intraepithelial lesion (HSIL) and cancer (Ca) is developed. Considering the dataset characteristics, to fully utilize the research data and ensure the dataset size, the model inputs include original and acetic colposcopy images, lesion segmentation masks, human papillomavirus (HPV), thinprep cytologic test (TCT) and age, but exclude iodine images that have a significant overlap with lesions under acetic images. Firstly, the change information between original and acetic images is introduced by calculating the acetowhite opacity to mine the correlation between the acetowhite thickness and lesion grades. Secondly, the lesion segmentation masks are utilized to introduce prior knowledge of lesion location and shape into the classification model. Lastly, a cross-modal feature fusion module based on the self-attention mechanism is utilized to fuse image information with clinical text information, revealing the features correlation. Based on the dataset used in this study, the proposed model is comprehensively compared with five excellent models over the past three years, demonstrating that the proposed model has superior classification performance and a better balance between performance and complexity. The modules ablation experiments further prove that each proposed improved module can independently improve the model performance.

Factors associated with SARS-CoV-2 vaccine hesitancy after stroke: a cross-sectional study.

BACKGROUND: The vaccination status of post-stroke patients, who are at high risk of severe outcomes from Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is a significant concern, yet it remains unclear. We aimed to explore the vaccination status, factors associated with vaccine hesitancy, and adverse effects after vaccination among post-stroke patients. METHODS: This multi-center observational study enrolled hospitalized post-stroke patients from six Chinese hospitals (Oct 1, 2020 - Mar 31, 2021), examining vaccine uptake and self-reported reasons for vaccine hesitancy, utilizing logistic regression to investigate risk factors for vaccine hesitancy, and recording any adverse reactions post-vaccination. RESULTS: Of the total 710 post-stroke patients included in the study, 430 (60.6%) had completed the recommended full-3 dose SARS-CoV-2 vaccination, with 176 (24.8%) remaining unvaccinated. The most common reasons for vaccine hesitancy were concerns about vaccine side effects (41.5%) and impaired mobility (33.9%). Logistic regression identified advanced age (aOR = 1.97, 95%CI: 1.36-2.85, P = 0.001), lower Barthel Index score (aOR = 0.88, 95%CI: 0.82-0.93, P = 0.018), higher Modified Rankin Scale score (aOR = 1.85, 95%CI: 1.32-2.56, P = 0.004), and poorer usual activity level of EuroQol 5-Dimension (aOR = 2.82, 95%CI: 1.51-5.28, P = 0.001) as independent risk factors for vaccine hesitancy. Approximately 14.8% reported minor adverse reactions, mainly pain at the injection site. CONCLUSION: We found that post-stroke patients have insufficient SARS-CoV-2 vaccination rates, with key risk factors for vaccine hesitancy including concerns about side effects, advanced age, and functional impairments. No severe adverse reactions were observed among the vaccinated population.

Quantification of Cervical Elasticity During Pregnancy Based on Transvaginal Ultrasound Imaging and Stress Measurement.

Strain elastography and shear wave elastography are two commonly used methods to quantify cervical elasticity. However, the absence of stress information in strain elastography causes difficulty in comparing elasticities acquired in different sessions, and the robustness of shear wave elastography tends to be compromised by the high inhomogeneity of cervical tissue. OBJECTIVE: To overcome these limitations, we develop a quantitative cervical elastography system by adding a stress sensor to a clinically used transvaginal ultrasound imaging system. METHODS: In an imaging session, we use the ultrasound system to record the cervical deformation in B-mode images and use the stress sensor to record the probe-surface stress simultaneously. We develop a feature-tracking algorithm to quantify the deformation automatically and calculate the strain. Then we estimate the cervical Young's modulus through stress-strain linear regression. RESULTS: In phantom experiments, we demonstrate the elastography system's high accuracy (alignment with the quasi-static compression method, p-value = 0.369 > 0.05), robustness (alignment between 60°- and 90°-contact measurements, p-value = 0.638 > 0.05), repeatability (consistency of single sonographers' measurements, coefficient of variation < 0.06), and reproducibility (alignment between two sonographers' measurements, Pearson correlation coefficient = 0.981). Applying it to pregnant participants, we observe significant softening of the cervix during pregnancy (p-value < 0.001) with the cervical Young's modulus decreasing 3.95% per week. We estimate that geometric mean values of cervical Young's moduli during the first (11 to 13 weeks), second, and third trimesters are 13.07 kPa, 7.59 kPa, and 4.40 kPa, respectively. CONCLUSION: The proposed system is accurate, robust, and safe, and enables longitudinal measurements and comparisons between examiners. SIGNIFICANCE: The system applies to different ultrasound machines with minor software updates, which allows for studies of cervical softening patterns in pregnancy for larger populations, facilitating insights into conditions such as preterm birth.

Profiles of HBcrAg and pgRNA in Pregnant Women With Chronic HBV Under Different Disease Phases and Antiviral Prophylaxis.

Background: Pregnant women with chronic hepatitis B (CHB) exhibit unique clinical features in terms of postpartum immune system reconstitution and recovery from pregnancy-related changes. However, current studies focus primarily on the outcomes of maternal-infant transmission and postpartum hepatitis flares. We aimed to evaluate the profiles of hepatitis B core-related antigen (HBcrAg) and pregenomic RNA (pgRNA) in pregnant women with CHB. Methods: This retrospective analysis included treatment-naïve pregnant women with CHB who were followed up regularly in an outpatient clinic from 2014 to 2021. Baseline HBcrAg and pgRNA levels were compared in patients with different disease phases. Changes in these parameters were examined in a subset of patients receiving antiviral prophylaxis. HBcrAg and pgRNA levels were measured before treatment, at 32 weeks of gestation, and postpartum. Results: The final analysis included a total of 121 patients, 100 of whom were hepatitis B e antigen (HBeAg)-positive (96 and 4 in the immune-tolerant and -indeterminate phases, respectively) and 21 of whom were HBeAg-negative (6 and 15 in the immune-active and -inactive carrier phases, respectively). The HBeAg-negative group vs the HBeAg-positive group had lower levels of baseline HBcrAg (median [interquartile range {IQR}], 3.7 [3.0-5.9] vs 8.6 [8.4-8.7] log10 U/mL; P < .01) and pgRNA (median [IQR], 0.0 [0.0-2.5] vs 7.8 [7.6-8.1] log10 copies/mL; P < .01). The serum levels of HBcrAg and pgRNA were highest in immune-tolerant carriers and lowest in immune-inactive carriers. In HBeAg-positive patients, the correlation coefficients of HBcrAg and pgRNA with hepatitis B virus (HBV) DNA were 0.40 and 0.43, respectively; in HBeAg-negative patients, they were 0.53 and 0.51, respectively (all P < .05). The correlation coefficients with hepatitis B surface antigen (HBsAg) were 0.55 and 0.52 (P < .05) in HBeAg-positive patients, respectively, while in HBeAg-negative patients they were 0.42 and 0.37, respectively (P > .05). Among 96 patients receiving antiviral prophylaxis, we detected a rapid decrease in HBV DNA to an undetectable level during treatment but relatively stable levels of pgRNA and HBcrAg. Conclusions: HBcrAg and pgRNA levels are lower in HBeAg-negative patients than in HBeAg-positive patients. These 2 markers are significantly associated with HBV DNA irrespective of HBeAg status, while they are significantly associated with HBsAg only in HBeAg-positive patients.

Self-sacrificing-induced defect enhances the oxidase-like activity of MnOOH for total antioxidant capacity evaluation.

Nanozymes is a kind of nanomaterials with enzyme catalytic properties. Compared with natural enzymes, nanozymes merge the advantages of both nanomaterials and natural enzymes, which is highly important in applications such as biosensing, clinical diagnosis, and food inspection. In this study, we prepared ß-MnOOH hexagonal nanoflakes with a high oxygen vacancy ratio by utilizing SeO2 as a sacrificial agent. The defect-rich MnOOH hexagonal nanoflakes demonstrated excellent oxidase-like activity, catalyzing the oxidation substrate in the presence of O2, thereby rapidly triggering a color reaction. Consequently, a colorimetric sensing platform was constructed to assess the total antioxidant capacity in commercial beverages. The strategy of introducing defects in situ holds great significance for the synthesis of a series of high-performance metal oxide nanozymes, driving the development of faster and more efficient biosensing and analysis methods.

To characterize small renal cell carcinoma using diffusion relaxation correlation spectroscopic imaging and apparent diffusion coefficient based histogram analysis: a preliminary study.

PURPOSE: To study the capability of diffusion-relaxation correlation spectroscopic imaging (DR-CSI) on subtype classification and grade differentiation for small renal cell carcinoma (RCC). Histogram analysis for apparent diffusion coefficient (ADC) was studied for comparison. MATERIALS AND METHODS: A total of 61 patients with small RCC (< 4 cm) were included in the retrospective study. MRI data were reviewed, including a multi-b (0-1500 s/mm2) multi-TE (51-200 ms) diffusion weighted imaging (DWI) sequence. Region of interest (ROI) was delineated manually on DWI to include solid tumor. For each patient, a D-T2 spectrum was fitted and segmented into 5 compartments, and the volume fractions VA, VB, VC, VD, VE were obtained. ADC mapping was calculated, and histogram parameters ADC 90th, 10th, median, standard deviation, skewness and kurtosis were obtained. All MRI metrices were compared between clear cell RCC (ccRCC) and non-ccRCC group, and between high-grade and low-grade group. Receiver operator curve analysis was used to assess the corresponding diagnostic performance. RESULTS: Significantly higher ADC 90th, ADC 10th and ADC median, and significantly lower DR-CSI VB was found for ccRCC compared to non-ccRCC. Significantly lower ADC 90th, ADC median and significantly higher VB was found for high-grade RCC compared to low-grade. For identifying ccRCC from non-ccRCC, VB showed the highest area under curve (AUC, 0.861) and specificity (0.882). For differentiating high- from low-grade, ADC 90th showed the highest AUC (0.726) and specificity (0.786), while VB also displayed a moderate AUC (0.715). CONCLUSION: DR-CSI may offer improved accuracy in subtype identification for small RCC, while do not show better performance for small RCC grading compared to ADC histogram.

Nitrate transformation and source tracking of Yarlung Tsangpo River using a multi-tracer approach combined with Bayesian stable isotope mixing model.

Excessive levels of nitrate nitrogen (NO3--N) could lead to ecological issues, particularly in the Yarlung Tsangpo River (YTR) region located on the Qinghai Tibet Plateau. Therefore, it is crucial to understand the fate and sources of nitrogen to facilitate pollution mitigation efforts. Herein, multiple isotopes and source resolution models were applied to analyze key transformation processes and quantify the sources of NO3-. The δ15N-NO3- and δ18O-NO3- isotopic compositions in the YTR varied between 1.23‰ and 13.64‰ and -7.88‰-11.19‰, respectively. The NO3--N concentrations varied from 0.08 to 0.86 mg/L in the dry season and 0.20-1.19 mg/L during the wet season. Nitrification remained the primary process for nitrogen transformation in both seasons. However, the wet season had a widespread effect on increasing nitrate levels, while denitrification had a limited ability to reduce nitrate. The elevated nitrate concentrations during the flood season were caused by increased release of NO3- from manure & sewage (M&S) and chemical fertilizers (CF). Future endeavors should prioritize enhancing management strategies to improve the utilization efficiency of CF and hinder the direct entry of untreated sewage into the water system.

Motif-Aware miRNA-Disease Association Prediction Via Hierarchical Attention Network.

As post-transcriptional regulators of gene expression, micro-ribonucleic acids (miRNAs) are regarded as potential biomarkers for a variety of diseases. Hence, the prediction of miRNA-disease associations (MDAs) is of great significance for an in-depth understanding of disease pathogenesis and progression. Existing prediction models are mainly concentrated on incorporating different sources of biological information to perform the MDA prediction task while failing to consider the fully potential utility of MDA network information at the motif-level. To overcome this problem, we propose a novel motif-aware MDA prediction model, namely MotifMDA, by fusing a variety of high- and low-order structural information. In particular, we first design several motifs of interest considering their ability to characterize how miRNAs are associated with diseases through different network structural patterns. Then, MotifMDA adopts a two-layer hierarchical attention to identify novel MDAs. Specifically, the first attention layer learns high-order motif preferences based on their occurrences in the given MDA network, while the second one learns the final embeddings of miRNAs and diseases through coupling high- and low-order preferences. Experimental results on two benchmark datasets have demonstrated the superior performance of MotifMDA over several state-of-the-art prediction models. This strongly indicates that accurate MDA prediction can be achieved by relying solely on MDA network information. Furthermore, our case studies indicate that the incorporation of motif-level structure information allows MotifMDA to discover novel MDAs from different perspectives. The data and codes are available at https://github.com/stevejobws/MotifMDA.

Efficacy and safety of GST-HG171 in adult patients with mild to moderate COVID-19: a randomised, double-blind, placebo-controlled phase 2/3 trial.

Background: GST-HG171 is a potent, broad-spectrum, orally bioavailable small-molecule 3C like protease inhibitor that has demonstrated greater potency and efficacy compared to Nirmatrelvir in pre-clinical studies. We aimed to evaluate the efficacy and safety of orally administered GST-HG171 plus Ritonavir in patients with coronavirus disease 2019 (COVID-19) infected with emerging XBB and non-XBB variants. Methods: This randomised, double-blind, placebo-controlled phase 2/3 trial was conducted in 47 sites in China among adult patients with mild-to-moderate COVID-19 with symptoms onset ≤72 h. Eligible patients were randomised 1:1 to receive GST-HG171 (150 mg) plus Ritonavir (100 mg) or corresponding placebo tablets twice daily for 5 days, with stratification factors including the risk level of disease progression and vaccination status. The primary efficacy endpoint was time to sustained recovery of clinical symptoms within 28 days, defined as a score of 0 for 11 COVID-19-related target symptoms for 2 consecutive days, assessed in the modified intention-to-treat (mITT) population. This trial was registered at ClinicalTrials.gov (NCT05656443) and Chinese Clinical Trial Registry (ChiCTR2200067088). Findings: Between Dec 19, 2022, and May 4, 2023, 1525 patients were screened. Among 1246 patients who underwent randomisation, most completed basic (21.2%) or booster (74.9%) COVID-19 immunization, and most had a low risk of disease progression at baseline. 610 of 617 who received GST-HG171 plus Ritonavir and 603 of 610 who received placebo were included in the mITT population. Patients who received GST-HG171 plus Ritonavir showed shortened median time to sustained recovery of clinical symptoms compared to the placebo group (13.0 days [95.45% confidence interval 12.0-15.0] vs. 15.0 days [14.0-15.0], P = 0.031). Consistent results were observed in both SARS-CoV-2 XBB (45.7%, 481/1053 of mITT population) and non-XBB variants (54.3%, 572/1053 of mITT population) subgroups. Incidence of adverse events was similar in the GST-HG171 plus Ritonavir (320/617, 51.9%) and placebo group (298/610, 48.9%). The most common adverse events in both placebo and treatment groups were hypertriglyceridaemia (10.0% vs. 14.7%). No deaths occurred. Interpretation: Treatment with GST-HG171 plus Ritonavir has demonstrated benefits in symptom recovery and viral clearance among low-risk vaccinated adult patients with COVID-19, without apparent safety concerns. As most patients were treated within 2 days after symptom onset in our study, confirming the potential benefits of symptom recovery for patients with a longer duration between symptom onset and treatment initiation will require real-world studies. Funding: Fujian Akeylink Biotechnology Co., Ltd.

An Innovative and Efficient Fluorescent Detection Technique for Salmonella in Animal-Derived Foods Using the CRISPR/Cas12a-HCR System Combined with PCR/RAA.

Here, we present a method for Salmonella detection using clustered regularly interspaced short palindromic repeats associated with the CRISPR-associated protein 12a-hybridization chain reaction (CRISPR/Cas12a-HCR) system combined with polymerase chain reaction/recombinase-assisted amplification (PCR/RAA) technology. The approach relies on the Salmonella invA gene as a biorecognition element and its amplification through PCR and RAA. In the presence of the target gene, Cas12a, guided by crRNA, recognizes and cleaves the amplification product, initiating the HCR. Fluorescently labeled single-stranded DNA (ssDNA) H1 and H2 were introduced, and the Salmonella concentration was determined based on the fluorescence intensity from the triggered HCR. Both assays demonstrate high specificity, sensitivity, simplicity, and rapidity. The detection range was 2 × 101-2 × 109 CFU/mL, with an LOD of 20 CFU/mL, and the entire process enabled specific and rapid Salmonella detection within 85-105 min. Field-incurred spiked recovery tests were conducted in mutton and beef samples using both assays, demonstrating satisfactory recovery and accuracy in animal-derived foods. By combining CRISPR/Cas12a with hybridization chain reaction technology, this study presents a rapid and sensitive Salmonella detection method that is crucial for identifying pathogenic bacteria and monitoring food safety.

Intermittent hypoxic pretreatment exacerbates house dust mite-induced asthma airway inflammation.

BACKGROUND: Asthma is widely recognized as an inflammatory disorder. In the context of this inflammatory microenvironment, the involvement of hypoxia and its impact on related pathways have drawn considerable attention. However, the exact role of hypoxia, a prevalent environmental factor, in the development and progression of asthma remains poorly understood. METHODS: Mice were treated with house dust mite (HDM) extracts for 23 days to induce asthma. Mice were divided into room air (RA) group and intermittent hypoxic (IH) group by exposing to different conditions and IH preconditioning (IHP) were underwent to the above groups before the hypoxic regimen. Airway inflammation in mice was evaluated by airway hyperresponsiveness, excessive mucus secretion, and recruitment of inflammatory cells. Immunohistochemistry was employed to quantify the expression levels of NF-κB. Subsequently, the dose of allergen was modified to investigate whether the impact of hypoxia on asthma is affected by different doses of allergens. RESULT: Compared to the RA and IH groups, HDM-treated mice in the IHP group exhibited aggravated inflammatory cell infiltration and airway hyperresponsiveness (p＜.05). Moreover, there was an increased release of inflammatory mediators and higher expression levels of NF-κB (p＜.05). Importantly, the impact ia on asthma was found to be influenced by high dose of allergen (p＜.05). CONCLUSION: IHP treatment potentially exacerbates HDM-induced airway inflammation in asthma, with the involvement of NF-κB, particularly under high-dose allergen stimulation.

TNF-α: A serological marker for evaluating the severity of hippocampal sclerosis in medial temporal lobe epilepsy?

OBJECTIVE: By analysing the difference in TNF-α levels in the peripheral blood of patients with medial temporal lobe epilepsy (mTLE) with or without hippocampal sclerosis and the correlation between TNF-α and N-acetylaspartate levels in the hippocampus, we explored the relationship between TNF-α and the degree of damage to hippocampal sclerosis neurons in medial temporal lobe epilepsy. METHODS: This is a prospective, population-based study. A total of 71 Patients with medial temporal lobe epilepsy diagnosed by clinical seizures, video-EEG, epileptic sequence MRI, and other imaging examinations were recruited from October 2020 to July 2022 in the Department of Neurology, Affiliated Hospital of Xuzhou Medical University. Twenty age-matched healthy subjects were selected as the control group. The patients were divided into two groups: the medial temporal epilepsy with hippocampal sclerosis group (positive group, mTLE-HS-P group) and the medial temporal epilepsy without hippocampal sclerosis group (negative group, mTLE-HS-N group). The levels of IL-1ß, IL-5, IL-6, IL-8, IL-17, IFN-γ and TNF-α in the peripheral blood of the patients in the three groups were detected by multimicrosphere flow immunofluorescence assay. The level of N-acetylaspartate (NAA) in the hippocampus was measured by 1H-MRS. The differences in cytokine levels among the three groups were analysed, and the correlation between cytokine and NAA levels was analysed. RESULTS: The level of TNF-α in the peripheral blood of the patients in the mTLE-HS-P group was significantly higher than that of the patients in the mTLE-HS-N and healthy control groups, and the level of TNF-α in the patients in the mTLE-HS-N group was significantly higher than that of the patients in the healthy control group. The NAA level in mTLE-HS-P group patients was significantly lower than that of mTLE-HS-N patients and healthy controls, but there was no significant difference between mTLE-HS-N patients and healthy controls (P > 0.05). Spearman correlation analysis showed that TNF-α level (rs = -0.437, P < 0.05) and the longest duration of a single seizure (rs = -0.398, P < 0.05) were negatively correlated with NAA level. Logistic regression analysis showed that there was no significant correlation between the longest duration of a single seizure and hippocampal sclerosis, but TNF-α level was closely related to hippocampal sclerosis in patients with mTLE (OR = 1.315, 95 % CI 1.084-1.595, P = 0.005). CONCLUSION: The level of TNF-α in the peripheral blood of patients with medial temporal lobe epilepsy with hippocampal sclerosis was higher, and it was correlated with NAA and hippocampal sclerosis. The high expression of TNF-α may be of important value in the evaluation of hippocampal sclerosis patients.

Giant unruptured sinus of Valsalva aneurysms causing angina pectoris.

BACKGROUND: Sinus of Valsalva aneurysm (SVA) is a rare cardiac anomaly which can be congenital or acquired. Patients with SVA are commonly asymptomatic when the occupying effect of SVA is insignificant, while ruptured SVA usually causes severe symptoms including heart failure and myocardial ischemia. CASE PRESENTATION: We present an unusual case of a 64-year-old female manifesting with exertional dyspnea as well as angina pectoris for three months. Echocardiography and cardiac computed tomographic angiography confirmed unruptured left-coronary and non-coronary SVAs. The left anterior descending artery and left circumflex artery were stretched and compressed by the SVA which causing myocardial ischemia. The patient finally received aortic root replacement (Bentall procedure) and got symptom relieved. CONCLUSIONS: Giant unruptured SVA originating from left coronary sinus is extremely rare. Our case highlights that giant SVA should be considered in cases with angina pectoris. Echocardiography and coronary computed tomographic angiography are useful and important for diagnosis. Surgery is highly recommended in patients with SVA.

Quantification of the aromatase inhibitor letrozole and its carbinol metabolite in mouse plasma by UHPLC-MS/MS.

A liquid chromatography - electrospray ionization-mass spectrometry (LC-ESI-MS) method was developed for the quantification of letrozole, a third-generation aromatase inhibitor, and its main carbinol metabolite (CM) in support of murine pharmacokinetic studies. Using polarity switching, simultaneous ESI-MS measurement of letrozole and CM was achieved in positive and negative mode, respectively. The assay procedure involved a one-step protein precipitation and extraction of all analytes from mouse plasma requiring only 5 µL of sample. Separation was optimized on an Accucore aQ column with gradient elution at a flow rate of 0.4 mL/min in 5 min. Two calibration curves per day over four consecutive measurement days showed satisfactory linear responses (r2 > 0.99) over concentration ranges of 5-1000 ng/mL and 20-2000 ng/mL for letrozole and CM, respectively. No matrix effect was found, and the mean extraction recoveries were 103-108 % for letrozole and 99.8-107 % for CM. Precision and accuracy within a single run and over four consecutive measurement days were verified to be within acceptable limits. Application of the developed method to preclinical pharmacokinetic studies in mice receiving oral letrozole at a dose 1 or 10 mg/kg revealed that the systemic exposure to letrozole was dose-, formulation-, and strain-dependent. These findings may inform the future design of preclinical studies aimed at refining the pharmacological profile of this clinically important drug.

An improvement method for pancreas CT segmentation using superpixel-based active contour.

Objective.Pancreas is one of the most challenging organs for Computed Tomograph (CT) image automatic segmentation due to its complex shapes and fuzzy edges. It is simple and universal to use the traditional segmentation method as a post-processor of deep learning method for segmentation accuracy improvement. As the most suitable traditional segmentation method for pancreatic segmentation, the active contour model (ACM), still suffers from the problems of weak boundary leakage and slow contour evolution speed. Therefore, a convenient post-processor for any deep learning methods using superpixel-based active contour model (SbACM) is proposed to improve the segmentation accuracy.Approach.Firstly, the superpixels with strong adhesion to edges are used to guide the design of narrowband and energy function. A multi-scale evolution strategy is also proposed to reduce the weak boundary leakage and comprehensively improve the evolution speed. Secondly, using the original image and the coarse segmentation results obtained from deep learning methods as inputs, the proposed SbACM method is used as a post-processor for fine segmentation. Finally, the pancreatic segmentation public dataset TCIA from the National Institutes of Health(NIH, USA) is used for evaluation, and the Wilcoxon Test confirmed that the improvement of proposed method is statistically significant.Main results.(1) the superpixel-based narrowband shape and dynamic edge energy of the proposed SbACM work for boundary leakage reduction, as well as the multi-scale evolution strategy and dynamic narrowband width for the evolution speed improvement; (2) as a post-processor, SbACM can increase the Dice similarity coefficients (DSC) of five typical UNet-based models, including UNet, SS-UNet, PBR UNet, ResDSN, and nnUNet, 2.35% in average and 9.04% in maximum. (3) Based on the best backbone nnUNet, the proposed post-processor performs better than either adding edge awareness or adding edge loss in segmentation enhancement without increasing the complexity and training time of deep learning models.Significance.The proposed SbACM can improve segmentation accuracy with the lowest cost, especially in cases of squeezed fuzzy edges with similar neighborhood , and complex edges.

vEpiNet: A multimodal interictal epileptiform discharge detection method based on video and electroencephalogram data.

To enhance deep learning-based automated interictal epileptiform discharge (IED) detection, this study proposes a multimodal method, vEpiNet, that leverages video and electroencephalogram (EEG) data. Datasets comprise 24 931 IED (from 484 patients) and 166 094 non-IED 4-second video-EEG segments. The video data is processed by the proposed patient detection method, with frame difference and Simple Keypoints (SKPS) capturing patients' movements. EEG data is processed with EfficientNetV2. The video and EEG features are fused via a multilayer perceptron. We developed a comparative model, termed nEpiNet, to test the effectiveness of the video feature in vEpiNet. The 10-fold cross-validation was used for testing. The 10-fold cross-validation showed high areas under the receiver operating characteristic curve (AUROC) in both models, with a slightly superior AUROC (0.9902) in vEpiNet compared to nEpiNet (0.9878). Moreover, to test the model performance in real-world scenarios, we set a prospective test dataset, containing 215 h of raw video-EEG data from 50 patients. The result shows that the vEpiNet achieves an area under the precision-recall curve (AUPRC) of 0.8623, surpassing nEpiNet's 0.8316. Incorporating video data raises precision from 70% (95% CI, 69.8%-70.2%) to 76.6% (95% CI, 74.9%-78.2%) at 80% sensitivity and reduces false positives by nearly a third, with vEpiNet processing one-hour video-EEG data in 5.7 min on average. Our findings indicate that video data can significantly improve the performance and precision of IED detection, especially in prospective real clinic testing. It suggests that vEpiNet is a clinically viable and effective tool for IED analysis in real-world applications.

MSUT2 regulates tau spreading via adenosinergic signaling mediated ASAP1 pathway in neurons.

Inclusions comprised of microtubule-associated protein tau (tau) are implicated in a group of neurodegenerative diseases, collectively known as tauopathies, that include Alzheimer's disease (AD). The spreading of misfolded tau "seeds" along neuronal networks is thought to play a crucial role in the progression of tau pathology. Consequently, restricting the release or uptake of tau seeds may inhibit the spread of tau pathology and potentially halt the advancement of the disease. Previous studies have demonstrated that the Mammalian Suppressor of Tauopathy 2 (MSUT2), an RNA binding protein, modulates tau pathogenesis in a transgenic mouse model. In this study, we investigated the impact of MSUT2 on tau pathogenesis using tau seeding models. Our findings indicate that the loss of MSUT2 mitigates human tau seed-induced pathology in neuron cultures and mouse models. In addition, MSUT2 regulates many gene transcripts, including the Adenosine Receptor 1 (A1AR), and we show that down regulation or inhibition of A1AR modulates the activity of the "ArfGAP with SH3 Domain, Ankyrin Repeat, and PH Domain 1 protein" (ASAP1), thereby influencing the internalization of pathogenic tau seeds into neurons resulting in reduction of tau pathology.