E-Nose: Time-Frequency Attention Convolutional Neural Network for Gas Classification and Concentration Prediction.

In the electronic nose (E-nose) systems, gas type recognition and accurate concentration prediction are some of the most challenging issues. This study introduced an innovative pattern recognition method of time-frequency attention convolutional neural network (TFA-CNN). A time-frequency attention block was designed in the network, aiming to excavate and effectively integrate the temporal and frequency domain information in the E-nose signals to enhance the performance of gas classification and concentration prediction tasks. Additionally, a novel data augmentation strategy was developed, manipulating the feature channels and time dimensions to reduce the interference of sensor drift and redundant information, thereby enhancing the model's robustness and adaptability. Utilizing two types of metal-oxide-semiconductor gas sensors, this research conducted qualitative and quantitative analysis on five target gases. The evaluation results showed that the classification accuracy could reach 100%, and the coefficient of the determination (R2) score of the regression task was up to 0.99. The Pearson correlation coefficient (r) was 0.99, and the mean absolute error (MAE) was 1.54 ppm. The experimental test results were almost consistent with the system predictions, and the MAE was 1.39 ppm. This study provides a method of network learning that combines time-frequency domain information, exhibiting high performance in gas classification and concentration prediction within the E-nose system.

cyTRBC1 evaluation rapidly identifies sCD3-negative peripheral T-cell lymphomas and reveals a novel type of sCD3-negative T-cell clone with uncertain significance.

The flow cytometry-based evaluation of TRBC1 expression has been demonstrated as a rapid and specific method for detecting T-cell clones in sCD3-positive TCRαß+ mature T-cell lymphoma. The aim of the study was to validate the utility of surface (s) TRBC1 and cytoplastic (cy) TRBC1 assessment in detecting clonality of sCD3-negative peripheral T-cell lymphomas (PTCLs), as well as exploring the existence and characteristics of sCD3-negative clonal T-cell populations with uncertain significance (T-CUS). Evaluation of sTRBC1 and cyTRBC1 were assessed on 61 samples from 37 patients with sCD3-negative PTCLs, including 26 angioimmunoblastic T-cell lymphoma (AITL) patients and 11 non-AITL patients. The sCD3-negative T-CUS were screened from 1602 patients without T-cell malignancy and 100 healthy individuals. Additionally, the clonality of cells was further detected through T-cell gene rearrangement analysis. We demonstrated the monotypic expression patterns of cyTRBC1 in all sCD3-negative PTCLs. Utilizing the cyTRBC1 evaluation assay, we identified a novel and rare subtype of sCD3-negative T-CUS for the first time among 13 out of 1602 (0.8%) patients without T-cell malignancy. The clonality of these cells was further confirmed through T-cell gene rearrangement analysis. This subset exhibited characteristics such as sCD3-cyCD3 + CD4 + CD45RO+, closely resembling AITL rather than non-AITL. Further analysis revealed that sCD3-negative T-CUS exhibited a smaller clone size in the lymph node and mass specimens compared to AITL patients. However, the clone size of sCD3-negative T-CUS was significantly lower than that of non-AITL patients in both specimen groups. In conclusion, we validated the diagnostic utility of cyTRBC1 in detecting sCD3-negative T-cell clonality, provided a comprehensive analysis of sCD3-negative T-CUS, and established a framework and provided valuable insights for distinguishing sCD3-negative T-CUS from sCD3-negative PTCLs based on their phenotypic properties and clone size.

EH domain-containing protein 2 (EHD2): Overview, biological function, and therapeutic potential.

EH domain-containing protein 2 (EHD2) is a member of the EHD protein family and is mainly located in the plasma membrane, but can also be found in the cytoplasm and endosomes. EHD2 is also a nuclear-cytoplasmic shuttle protein. After entering the cell nuclear, EHD2 acts as a corepressor of transcription to inhibit gene transcription. EHD2 regulates a series of biological processes. As a key regulator of endocytic transport, EHD2 is involved in the formation and maintenance of endosomal tubules and vesicles, which are critical for the intracellular transport of proteins and other substances. The N-terminal of EHD2 is attached to the cell membrane, while its C-terminal binds to the actin-binding protein. After binding, EHD2 connects with the actin cytoskeleton, forming the curvature of the membrane and promoting cell endocytosis. EHD2 is also associated with membrane protein trafficking and receptor signaling, as well as in glucose metabolism and lipid metabolism. In this review, we highlight the recent advances in the function of EHD2 in various cellular processes and its potential implications in human diseases such as cancer and metabolic disease. We also discussed the prospects for the future of EHD2. EHD2 has a broad prospect as a therapeutic target for a variety of diseases. Further research is needed to explore its mechanism, which could pave the way for the development of targeted treatments.

The effects of ambient temperature and feeding regimens on cecum bacteria composition and circadian rhythm in growing rabbits.

Seasonal environmental shifts and improper eating habits are the important causes of diarrhea in children and growing animals. Whether adjusting feeding time at varying temperatures can modify cecal bacterial structure and improve diarrhea remains unknown. Three batches growing rabbits with two groups per batch were raised under different feeding regimens (fed at daytime vs. nighttime) in spring, summer and winter separately, and contents were collected at six time points in 1 day and used 16S rRNA sequencing to investigate the effects of feeding regimens and season on the composition and circadian rhythms of cecum bacteria. Randomized forest regression screened 12 genera that were significantly associated with seasonal ambient temperature changes. Nighttime feeding reduced the abundance of the conditionally pathogenic bacteria Desulfovibrio and Alistipes in summer and Campylobacter in winter. And also increases the circadian rhythmic Amplicon Sequence Variants in the cecum, enhancing the rhythm of bacterial metabolic activity. This rhythmic metabolic profile of cecum bacteria may be conducive to the digestion and absorption of nutrients in the host cecum. In addition, this study has identified 9 genera that were affected by the combination of seasons and feeding time. In general, we found that seasons and feeding time and their combinations affect cecum composition and circadian rhythms, and that daytime feeding during summer and winter disrupts the balance of cecum bacteria of growing rabbits, which may adversely affect cecum health and induce diarrhea risk.

Integrated genomic and proteomic analyses identify PYGL as a novel experimental therapeutic target for clear cell renal cell carcinoma.

Sunitinib, the first-line targeted therapy for metastatic clear cell renal cell carcinoma (ccRCC), faces a significant challenge as most patients develop acquired resistance. Integrated genomic and proteomic analyses identified PYGL as a novel therapeutic target for ccRCC. PYGL knockdown inhibited cell proliferation, cloning capacity, migration, invasion, and tumorigenesis in ccRCC cell lines. PYGL expression was increased in sunitinib-resistant ccRCC cell lines, and CP-91149 targeting the PYGL could restore drug sensitivity in these cell lines. Moreover, chromatin immune-precipitation assays revealed that PYGL upregulation is induced by the transcription factor, hypoxia-inducible factor 1α. Overall, PYGL was identified as a novel diagnostic biomarker by combining genomic and proteomic approaches in ccRCC, and sunitinib resistance to ccRCC may be overcome by targeting PYGL.

Disulfidptosis status influences prognosis and therapeutic response in clear cell renal cell carcinoma.

Disulfidptosis is a recently identified type of programmed cell death. It is characterized by aberrant accumulation of intracellular disulfides. The clinical implications of disulfidptosis in clear cell renal cell carcinoma (ccRCC) remain unclear. A series of bioinformatics approaches were employed to analyze ten disulfidptosis-related molecules. Firstly, the expression patterns of the disulfidptosis-related molecules were different between normal and ccRCC tissues. A comprehensive cohort of patients with ccRCC was then assembled from three public databases and subjected to cluster analysis based on disulfidptosis-related molecules. Consensus cluster analysis revealed three distinct disulfidptosis clusters. We then conducted weighted gene co-expression network analysis (WGCNA) to identify highly correlated genes. 267 hub genes were screened out through WGCNA, and three gene clusters were then determined. Finally, we identified 87 genes with prognostic value and then used them to develop a disulfidptosis scoring (DSscore) system, which was proven to independently predict survival in ccRCC. Patients in the high-DSscore group exhibited a significant survival advantage and better immunotherapeutic responses compared with those in the low-DSscore group. However, the patients in the low-DSscore group exhibited a greater degree of chemotherapeutic response. In addition, the expression of disulfidptosis-related molecules was validated by qRT-PCR, and the potential of disulfidptosis-related molecules to indicate distinct cell subtypes were validated by single-cell RNA-sequencing. In conclusion, DSscore is a promising index for predicting the prognosis and efficacy of immunotherapy in patients with ccRCC and may provide a basis for novel strategies for future studies.

Hydroponic lettuce defective leaves identification based on improved YOLOv5s.

Achieving intelligent detection of defective leaves of hydroponic lettuce after harvesting is of great significance for ensuring the quality and value of hydroponic lettuce. In order to improve the detection accuracy and efficiency of hydroponic lettuce defective leaves, firstly, an image acquisition system is designed and used to complete image acquisition for defective leaves of hydroponic lettuce. Secondly, this study proposed EBG_YOLOv5 model which optimized the YOLOv5 model by integrating the attention mechanism ECA in the backbone and introducing bidirectional feature pyramid and GSConv modules in the neck. Finally, the performance of the improved model was verified by ablation experiments and comparison experiments. The experimental results proved that, the Precision, Recall rate and mAP0.5 of the EBG_YOLOv5 were 0.1%, 2.0% and 2.6% higher than those of YOLOv5s, respectively, while the model size, GFLOPs and Parameters are reduced by 15.3%, 18.9% and 16.3%. Meanwhile, the accuracy and model size of EBG_YOLOv5 were higher and smaller compared with other detection algorithms. This indicates that the EBG_YOLOv5 being applied to hydroponic lettuce defective leaves detection can achieve better performance. It can provide technical support for the subsequent research of lettuce intelligent nondestructive classification equipment.

MEHP activates JNK to inhibit the migration of human foreskin fibroblasts.

This study aimed to investigate the impact of mono(2-ethylhexyl) phthalate (MEHP) on the proliferation, apoptosis, and migration of human foreskin fibroblast cells (HFF-1) and the role of the JNK signaling pathway in cell migration. HFF-1 cells were randomly assigned to the control group with 0 MEHP exposure (M0) or the experimental groups with 25, 50, 100, 200, and 400 µmol/L MEHP exposure (M25, M50, M100, M200, and M400, respectively). After 24 and 48 h of MEHP exposure, the proliferation of HFF-1 cells in any group had no significant change. However, compared with the M0 group, the M200 and M400 groups presented substantially increased apoptosis of HFF-1 cells. Moreover, cell migration ability significantly decreased in all groups (p < 0.05). Additionally, the transcription and phosphorylated protein activation of JNK kinase in HFF-1 cells were substantially upregulated with the increase in MEHP exposure. Subsequently, HFF-1 cells were randomly divided into three groups: the DMSO blank control group, the 100 µM MEHP experimental group (M100), and the 100 µM MEHP plus 10 µM SP600125 (specific JNK inhibitor) experimental group (S10). The activation of JNK protein in HFF-1 cells was substantially downregulated in the S10 group. HFF-1 cells were also divided into the blank control group (M0). They were treated with 100 µM MEHP and varying concentrations of SP600125 (5, 10, and 15 µM for S5, S10, and S15, respectively). As the concentration of the antagonist increased, the migration ability of HFF-1 cells was returned to normal. Finally, the ROS in HFF-1 cells increased under MEHP exposure. This finding indicates that the regulation of cell migration by the JNK signaling pathway may be important in the occurrence of hypospadias.

Modified Tubeless Ureterocutaneostomy in High-Risk Patients After Radical Cystectomy and its Long-Term Clinical Outcomes.

OBJECTIVES: This work aimed to prevent stoma stenosis and achieve tubeless cutaneous ureterostomy in elderly and high-risk patients with our modified cutaneous ureterostomy. METHODS: We retrospectively analyzed 40 and 49 patients (176 renal units) who underwent Toyoda (group 1) and modified cutaneous ureterostomy (group 2) between 2012 and 2021. The average follow-up period was 44 months. The primary results of our study were the catheter-free rate and clinical outcomes, especially renal function and urinary diversion-related complications. Significant differences in catheter-free rate and urinary diversion-related complications were found between our modified method and the Toyoda technique. RESULTS: A total of 56 (71.8%) of 78 renal units in group 1 and 89 (90.8%) of 98 renal units in group 2 remained catheter free. Compared with group 1, group 2 had a higher catheter-free rate (P = .001). Multivariate analysis indicated that the surgical procedure (HR = 0.268; P = .001) and body mass index (HR = 3.127; P = .002) were the predictors independently associated with catheter insertion. During follow-up, renal deterioration was observed in 32 (36.0%) patients. Patients with catheter insertion were more likely to suffer from renal deterioration (P < .001), postoperative pyelonephritis (P < .001), and urolithiasis (P < .001) than their counterparts. CONCLUSION: Our modified cutaneous ureterostomy method may provide an effective and simple approach to tubeless cutaneous ureterostomy in elderly and high-risk patients.

Optimizing Feeding Strategies for Growing Rabbits: Impact of Timing and Amount on Health and Circadian Rhythms.

Mammals exhibit circadian rhythms in their behavior and physiological activities to adapt to the diurnal changes of the environment. Improper feeding methods can disrupt the natural habits of animals and harm animal health. This study investigated the effects of feeding amount and feeding time on growing rabbits in northern China during spring. A total of 432 healthy 35-day-old weaned rabbits with similar body weight were randomly assigned to four groups: whole day diet-unrestricted feeding (WUF), whole day diet-restricted feeding (WRF), nighttime diet-unrestricted feeding (NUF), and nighttime diet-restricted feeding (NRF). The results showed that nighttime diet-unrestricted feeding improved performance, circadian rhythm of behavior, and body temperature, while reducing the risk of diarrhea and death. WRF group increased daytime body temperature but had no significant difference in feed conversion rate. The study suggests that nighttime diet-unrestricted feeding in spring can improve the growth and welfare of rabbits in northern China. Our study underscores the pivotal role of feeding timing in enhancing animal health. Future investigations should delve into the underlying mechanisms and expand the application of this strategy across seasons and regions to improve rabbit husbandry practices.

Prediction of clinically significant prostate cancer using a novel 68Ga-PSMA PET-CT and multiparametric MRI-based model.

Background: There are some limitations in the commonly used methods for the detection of prostate cancer. There is a lack of nomograms based on multiparametric magnetic resonance imaging (mpMRI) and 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography-computed tomography (PET-CT) for the prediction of prostate cancer. The study seeks to compare the performance of mpMRI and 68Ga-PSMA PET-CT, and design a novel predictive model capable of predicting clinically significant prostate cancer (csPCa) before biopsy based on a combination of 68Ga-PSMA PET-CT, mpMRI, and patient clinical parameters. Methods: From September 2020 to June 2021, we prospectively enrolled 112 consecutive patients with no prior history of prostate cancer who underwent both 68Ga-PSMA PET-CT and mpMRI prior to biopsy at our clinical center. Univariate and multivariate regression analyses were used to identify predictors of csPCa, with a predictive model and its nomogram incorporating 68Ga-PSMA PET-CT, mpMRI, and the clinical predictors then being generated. The constructed model was evaluated using receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis, and further validated with the internal and external cohorts. Results: The model incorporated prostate-specific antigen density (PSAd), Prostate Imaging Reporting and Data System (PI-RADS) category, and maximum standardized uptake value (SUVmax), and it exhibited excellent predictive efficacy when applying to evaluate both training and validation cohorts [area under the curve (AUC): 0.936 and 0.940, respectively]. Compared with SUVmax alone, the model demonstrated excellent diagnostic performance with improved specificity (0.910, 95% CI: 0.824-0.963) and positive predictive values (0.811, 95% CI: 0.648-0.920). Calibration curve and decision curve analysis further confirmed that the model exhibited a high degree of clinical net benefit and low error rate. Conclusions: The constructed model in this study was capable of accurately predicting csPCa prior to biopsy with excellent discriminative ability. As such, this model has the potential to be an effective non-invasive approach for the diagnosis of csPCa.

sTRBC1 and cyTRBC1 Expression Distinguishes Indolent T-Lymphoblastic Proliferations From T-Lymphoblastic Leukemia/Lymphoma.

Indolent T-lymphoblastic proliferation (iT-LBP) consists of a proliferation of non-neoplastic TdT + T cells in extrathymic tissues, requiring no treatment. However, due to overlapping clinical and histologic features, distinguishing iT-LBP from T-cell acute lymphoblastic leukemia/lymphoblastic lymphoma (T-ALL/LBL) can be challenging. Recently, flow cytometry-based evaluation of TRBC1 has been used to detect of T-cell clonality in TCRαß + mature T-cell lymphomas and aid in the differential diagnosis between T-ALL and normal thymocytes. We present a case of iT-LBP with high-grade serous ovarian carcinoma (HGSOC). To investigate the potential utility of TRBC1 expression in distinguishing iT-LBP from T-ALL/LBL, we assessed both surface (s) and cytoplasmic (cy) TRBC1 expression patterns on blast cells from the patient with iT-LBP and HGSOC as well as 11 patients diagnosed with T-ALL/LBL. The results revealed that sTRBC1 and cyTRBC1 exhibited polytypic expression patterns in patient with iT-LBP and HGSOC, while cyTRBC1 showed monotypic expression in those with T-ALL/LBL. This suggests that evaluation of sTRBC1 and cyTRBC1 expression can serve as a simple, rapid, and effective approach to differentiate between iT-LBP and T-ALL/LBL.

Anti-apoptotic effect of adrenomedullin gene delivery on Leydig cells by suppressing TGF-ß1 via the Hippo signaling pathway.

This study aims to establish whether adrenomedullin (ADM) is capable to restore the steroidogenic functions of Leydig cells by suppressing transforming growth factor-ß1 (TGF-ß1) through Hippo signaling. Primary Leydig cells were treated with lipopolysaccharide (LPS), an adeno-associated virus vector that expressed ADM (Ad-ADM) or sh-RNA of TGF-ß1 (Ad-sh-TGF-ß1). The cell viability and medium concentrations of testosterone were detected. Gene expression and protein levels were determined for steroidogenic enzymes, TGF-ß1, RhoA, YAP, TAZ and TEAD1. The role of Ad-ADM in the regulation of TGF-ß1 promoter was confirmed by ChIP and Co-IP. Similar to Ad-sh-TGF-ß1, Ad-ADM mitigated the decline in the number of Leydig cells and plasma concentrations of testosterone by restoring the gene and protein levels of SF-1, LRH1, NUR77, StAR, P450scc, 3ß-HSD, CYP17 and 17ß-HSD. Similar to Ad-sh-TGF-ß1, Ad-ADM not only inhibited the LPS-induced cytotoxicity and cell apoptosis but also restored the gene and protein levels of SF-1, LRH1, NUR77, StAR, P450scc, 3ß-HSD, CYP17 and 17ß-HSD, along with the medium concentrations of testosterone in LPS-induced Leydig cells. Like Ad-sh-TGF-ß1, Ad-ADM improved LPS-induced TGF-ß1 expression. In addition, Ad-ADM suppressed RhoA activation, enhanced the phosphorylation of YAP and TAZ, reduced the expression of TEAD1 which interacted with HDAC5 and then bound to TGF-ß1 gene promoter in LPS-exposed Leydig cells. It is thus suspected that ADM can exert anti-apoptotic effect to restore the steroidogenic functions of Leydig cells by suppressing TGF-ß1 through Hippo signaling.

CLIP-Based Adaptive Graph Attention Network for Large-Scale Unsupervised Multi-Modal Hashing Retrieval.

With the proliferation of multi-modal data generated by various sensors, unsupervised multi-modal hashing retrieval has been extensively studied due to its advantages in storage, retrieval efficiency, and label independence. However, there are still two obstacles to existing unsupervised methods: (1) As existing methods cannot fully capture the complementary and co-occurrence information of multi-modal data, existing methods suffer from inaccurate similarity measures. (2) Existing methods suffer from unbalanced multi-modal learning and data semantic structure being corrupted in the process of hash codes binarization. To address these obstacles, we devise an effective CLIP-based Adaptive Graph Attention Network (CAGAN) for large-scale unsupervised multi-modal hashing retrieval. Firstly, we use the multi-modal model CLIP to extract fine-grained semantic features, mine similar information from different perspectives of multi-modal data and perform similarity fusion and enhancement. In addition, this paper proposes an adaptive graph attention network to assist the learning of hash codes, which uses an attention mechanism to learn adaptive graph similarity across modalities. It further aggregates the intrinsic neighborhood information of neighboring data nodes through a graph convolutional network to generate more discriminative hash codes. Finally, this paper employs an iterative approximate optimization strategy to mitigate the information loss in the binarization process. Extensive experiments on three benchmark datasets demonstrate that the proposed method significantly outperforms several representative hashing methods in unsupervised multi-modal retrieval tasks.

Feature Fusion and Metric Learning Network for Zero-Shot Sketch-Based Image Retrieval.

Zero-shot sketch-based image retrieval (ZS-SBIR) is an important computer vision problem. The image category in the test phase is a new category that was not visible in the training stage. Because sketches are extremely abstract, the commonly used backbone networks (such as VGG-16 and ResNet-50) cannot handle both sketches and photos. Semantic similarities between the same features in photos and sketches are difficult to reflect in deep models without textual assistance. To solve this problem, we propose a novel and effective feature embedding model called Attention Map Feature Fusion (AMFF). The AMFF model combines the excellent feature extraction capability of the ResNet-50 network with the excellent representation ability of the attention network. By processing the residuals of the ResNet-50 network, the attention map is finally obtained without introducing external semantic knowledge. Most previous approaches treat the ZS-SBIR problem as a classification problem, which ignores the huge domain gap between sketches and photos. This paper proposes an effective method to optimize the entire network, called domain-aware triplets (DAT). Domain feature discrimination and semantic feature embedding can be learned through DAT. In this paper, we also use the classification loss function to stabilize the training process to avoid getting trapped in a local optimum. Compared with the state-of-the-art methods, our method shows a superior performance. For example, on the Tu-berlin dataset, we achieved 61.2 + 1.2% Prec200. On the Sketchy_c100 dataset, we achieved 62.3 + 3.3% mAPall and 75.5 + 1.5% Prec100.

Local adrenomedullin gene delivery inhibits Leydig cell dysfunction by rescuing steroidogenic enzymes in vivo.

Adrenomedullin (ADM) has beneficial effects on Leydig cells under pathological conditions, including lipopolysaccharide (LPS)-induced orchitis. Our previous studies demonstrated that ADM exerts a restorative effect on steroidogenesis in LPS-treated primary rat Leydig cells by attenuating oxidative stress, inflammation and apoptosis. In this study, we aim to investigate whether ADM inhibits Leydig cell dysfunction by rescuing steroidogenic enzymes in vivo. Rats were administered with LPS and injected with Ad-ADM, an adeno-associated virus vector that expressed ADM. Then, rat testes were collected for 3ß-hydroxysteroid dehydrogenase (3ß-HSD) immunofluorescence staining. Steroidogenic enzymes or steroidogenic regulatory factors or protein, including steroidogenic factor-1 (SF-1), liver receptor homologue-1 (LRH1), Nur77, steroidogenic acute regulatory protein (StAR), cytochrome P450 cholesterol side chain cleavage enzyme (P450scc), 3ß-HSD, cytochrome P450 17α-hydroxylase/17, 20 lyase (CYP17) and 17ß-hydroxysteroid dehydrogenase (17ß-HSD), were detected via gene expression profiling and western blot analysis. Plasma testosterone concentrations were measured. Results showed that ADM may inhibit Leydig cell dysfunction by rescuing steroidogenic enzymes and steroidogenic regulatory factors in vivo. The reduction in the number of Leydig cells after LPS exposure was reversed by ADM. ADM rescued the gene or protein levels of SF-1, LRH1, Nur77, StAR, P450scc, 3ß-HSD, CYP17 and 17ß-HSD and plasma testosterone concentrations. To summarize ADM could rescue some important steroidogenic enzymes, steroidogenic regulatory factors and testosterone production in Leydig cells in vivo.

The combination of mean and maximum Hounsfield Unit allows more accurate prediction of uric acid stones.

Based on mean Hounsfield Unit (HuMean), we aimed to evaluate the additional use of standard deviation of Hounsfield Unit (HuStd), minimum Hounsfield Unit (HuMin), and maximum Hounsfield Unit (HuMax) in noncontrast computed tomography (NCCT) to evaluate uric acid (UA) stones more accurately. The data of patients who underwent the NCCT examination and infrared spectroscopy in our hospital from August 2017 to December 2021 were analyzed retrospectively. Based on CT scans, the HuMean, HuStd, HuMin, and HuMax of all patients were measured. The patients were divided into groups according to the stone composition. The attenuation value of mixed stones was in the middle of their pure stones. Except for Str, statistically significant differences between UA stones and other pure stones were observed for HuMean, HuStd, HuMin, and HuMax. A moderate correlation was found between HuMean, HuStd, HuMin, and HuMax and UA stones (rs showed -0.585, -0.409, -0.492, and -0.577, respectively). Receiver operator characteristic (ROC) curve showed that the area under the curve (AUC) of HuMean and HuMax were higher than those of HuStd and HuMin (AUC = 0.896, AUC = 0.891 vs. AUC = 0.777, AUC = 0.833). Higher AUC (0.904), specificity (0.899) and positive predictive value (PPV) (0.712) can be obtained by combining HuMean and HuMax in the diagnosis of UA stones. In conclusion, HuMean and HuMax can better predict UA stones than HuStd and HuMin. The combined use of HuMean and HuMax can lead to higher accuracy.

Modeling and Analysis of Learners' Emotions and Behaviors Based on Online Forum Texts.

Under the continuous impact of the epidemic, online learning methods represented by MOOC have developed rapidly. The course forum area has produced a large amount of text-based unstructured data, which can reflect the potential characteristics of learners' emotional states and behavioral interactions, and has an important impact on students' learning outcomes. To this end, this paper constructs an emotional and behavioral analysis model based on online forum texts, obtains forum data from the "Python Language Programming" course on the Chinese University MOOC platform, uses domain dictionary emotion classification method to analyze learning emotions, and based on the method of cognitive behavior coding table and knowledge construction behavior coding table analyzes learners' cognitive behavior and knowledge construction behavior. It can dynamically analyze learners' emotions, behavior changes, and evolutionary trends. This research provides opinions and suggestions on the improvement of platform interactive functions for teachers' online teaching, students' online learning, and platform management, which can effectively improve the efficiency and effectiveness of online learning.

Value of noncontrast computer tomography in predicting the characteristics of obstructive uropathy.

OBJECTIVE: To explore the diagnostic value of noncontrast computed tomography (NCCT) in differentiating pyonephrosis from nonpyogenic hydronephrosis on the basis of CT values (in Horsfield unit [HU]). METHODS: Data from patients diagnosed with obstructive uropathy at the First affiliated hospital of University of South China from November 2017 to January 2021 were subjected to retrospective analysis. In accordance with the gold standard-the presence of pus during the operation-all patients were divided into the nonpyogenic hydronephrosis group and the pyonephrosis group. The relationship between CT values and the presence or absence of pyonephrosis was performed using binary logistic regression. A receiver operating characteristic (ROC) curve was constructed to determine threshold values for classification on the basis of mean HU. RESULTS: A total of 207 patients, including 100 males and 107 females, were enrolled. Out of the 207 cases, 124 cases of obstructive uropathy were nonpyogenic hydronephrosis and 83 cases were of pyonephrosis. The CT values of the pyonephrosis group were significantly higher than that of the nonpyogenic hydronephrosis group (t = 9.15, P < 0.05). The CT values were dependent on the presence or absence of pyonephrosis (P < 0.05). A HU threshold value of 9.75 could be applied to diagnose the presence of pyonephrosis. CONCLUSION: The CT values of hydronephrosis might predict the presence of pyonephrosis in the kidney, and the CT value of 9.75 HU might be the appropriate threshold for its prediction.