Quantitative assessment and correlational analysis of subjective and objective indicators in patients with allergic rhinitis.

Background: The diagnosis of allergic rhinitis is mainly based on the typical medical history, clinical manifestations, and corresponding allergen test results of the patients. However, there are often clinical inconsistencies among the 3. Objective: To study the clinical characteristics of patients with allergic rhinitis from both subjective and objective aspects to determine the correlations between the quantitative assessment outcomes of subjective and objective indicators. Methods: A total of 111 patients with allergic rhinitis who visited our outpatient clinic from June 2022 to December 2022 were selected. The 22-item sino-nasal outcome test (SNOT-22) and the visual analog scale (VAS) for the severity of the disease were used to score the subjective indicators of allergic rhinitis. The objective indicators of allergic rhinitis were evaluated by serum inhalant allergens immunoglobulin E test, nasal endoscopy modified Lund-Kennedy (MLK) scoring method, and acoustic rhinometry. Results: SNOT-22 score, total VAS score for symptoms, and the VAS score for nasal itching were positively correlated with the number of positive allergens (r = 0.266, P = 0.005, r = 0.576, P < 0.001, and r = 0.271, P = 0.004, respectively). No differences were found in all subjective indicators scores between the total immunoglobulin E positive and negative groups (P > 0.05). SNOT-22 score, total VAS score for symptoms, and the VAS score for nasal congestion were positively correlated with MLK total score of nasal endoscopy (r = 0.343, P < 0.001, r = 0.438, P < 0.001, and r = 0.225, P = 0.018, respectively). Parameters of acoustic rhinometry were not correlated with the subjective indicators scores of allergic rhinitis (P > 0.05). Conclusion: A multifaceted quantitative assessment of allergic rhinitis using a combination of subjective and objective methods can help physicians make an accurate diagnosis and create reasonable treatment plans.

E3 ubiquitin ligase TRIM31: A potential therapeutic target.

Ubiquitination is a key mechanism for post-translational protein modification, affecting protein localization, metabolism, degradation and various cellular physiological processes. Dysregulation of ubiquitination is associated with the pathogenesis of various diseases, such as tumors and cardiovascular diseases, making it a primary area of interest in biochemical research and drug development endeavors. E3 ubiquitin ligases play a pivotal role in modulating the ubiquitination of substrate proteins through their unique recognition functions. TRIM31, a member of the TRIM family of E3 ubiquitin ligases, is aberrantly expressed in different pathophysiological conditions. The biological function of TRIM31 is associated with the occurrence and development of diverse diseases. TRIM31 has been demonstrated to inhibit inflammation by promoting ubiquitin-proteasome-mediated degradation of the sensing protein NLRP3 in the inflammasome. TRIM31 mediates ubiquitination of MAVS, inducing the formation of prion-like aggregates, and triggering innate antiviral immune responses. TRIM31 is also implicated in tumor pathophysiology through its ability to promote ubiquitination of the tumor suppressor protein p53. These findings indicate that TRIM31 is a potential therapeutic target, and subsequent in-depth research of TRIM31 is anticipated to provide information on its clinical application in therapy.

Drug-target interaction predictions with multi-view similarity network fusion strategy and deep interactive attention mechanism.

MOTIVATION: Accurately identifying the drug-target interactions (DTIs) is one of the crucial steps in the drug discovery and drug repositioning process. Currently, many computational-based models have already been proposed for DTI prediction and achieved some significant improvement. However, these approaches pay little attention to fuse the multi-view similarity networks related to drugs and targets in an appropriate way. Besides, how to fully incorporate the known interaction relationships to accurately represent drugs and targets is not well investigated. Therefore, there is still a need to improve the accuracy of DTI prediction models. RESULTS: In this study, we propose a novel approach that employs Multi-view similarity network fusion strategy and deep Interactive attention mechanism to predict Drug-Target Interactions (MIDTI). First, MIDTI constructs multi-view similarity networks of drugs and targets with their diverse information and integrates these similarity networks effectively in an unsupervised manner. Then, MIDTI obtains the embeddings of drugs and targets from multi-type networks simultaneously. After that, MIDTI adopts the deep interactive attention mechanism to further learn their discriminative embeddings comprehensively with the known DTI relationships. Finally, we feed the learned representations of drugs and targets to the multilayer perceptron model and predict the underlying interactions. Extensive results indicate that MIDTI significantly outperforms other baseline methods on the DTI prediction task. The results of the ablation experiments also confirm the effectiveness of the attention mechanism in the multi-view similarity network fusion strategy and the deep interactive attention mechanism. AVAILABILITY AND IMPLEMENTATION: https://github.com/XuLew/MIDTI.

In-line imaging and recognition of flip chip fabrication defects by real-time photoacoustic remote sensing system.

Microscopic defects in flip chips, originating from manufacturing, significantly affect performance and longevity. Post-fabrication sampling methods ensure product functionality but lack in-line defect monitoring to enhance chip yield and lifespan in real-time. This study introduces a photoacoustic remote sensing (PARS) system for in-line imaging and defect recognition during flip-chip fabrication. We first propose a real-time PARS imaging method based on continuous acquisition combined with parallel processing image reconstruction to achieve real-time imaging during the scanning of flip-chip samples, reducing reconstruction time from an average of approximately 1134 ms to 38 ms. Subsequently, we propose improved YOLOv7 with space-to-depth block (IYOLOv7-SPD), an enhanced deep learning defect recognition method, for accurate in-line recognition and localization of microscopic defects during the PARS real-time imaging process. The experimental results validate the viability of the proposed system for enhancing the lifespan and yield of flip-chip products in chip manufacturing facilities.

S1PR3 suppresses the inflammatory response and extracellular matrix degradation in human nucleus pulposus cells.

Sphingosine 1-phosphate receptor 3 (S1PR3) participates in the inflammatory response in multiple types of diseases. However, the biological role of S1PR3 in intervertebral disc degeneration and the underlying mechanism are unclear. The aim of the present study was to investigate the functional role and the mechanism of S1PR3 in lipopolysaccharide (LPS)-induced human nucleus pulposus cells. The expression of S1PR3 and Toll-like receptor (TLR) 2 in LPS-induced nucleus pulposus (NP) cells was investigated using western blotting. The Cell Counting Kit-8 assay was used to detect cell proliferation, and the levels of inflammatory factors were detected using ELISA. Flow cytometry and western blotting were used for the assessment of apoptosis. The deposition of extracellular matrix (ECM) proteins was investigated using reverse transcription-quantitative PCR and western blotting. In addition, western blotting was used to investigate the protein expression levels of phosphorylated (p)-STAT3, STAT3, p-JNK, JNK, p-ERK, ERK, p-p38 and p38associated with STAT3 and MAPK signaling. S1PR3 expression was reduced, while TLR2 expression was elevated in LPS-induced human nucleus pulposus cells (HNPC). S1PR3 overexpression increased HNPC viability, inhibited the inflammatory response and suppressed apoptosis. Meanwhile, S1PR3 overexpression regulated the expression of ECM-related proteins. Additionally, overexpression of S1PR3 inhibited the expression of the TLR2-regulated STAT3 and MAPK pathways in LPS-induced HNPCs. Furthermore, TLR2 overexpression partially offset the impacts of S1PR3 overexpression on HNPC viability, apoptosis level, inflammation and as ECM degradation. In conclusion, STAT3 overexpression suppressed viability injury, the inflammatory response and the level of apoptosis and alleviated ECM protein deposition in HNPCs through the TLR2/STAT3 and TLR2/MAPK pathways, which may offer a promising candidate for the amelioration of intervertebral disc degeneration.

Adaptive Proton Therapy Using CBCT-Guided Digital Twins.

This study aims to develop a digital twin (DT) framework to enhance adaptive proton stereotactic body radiation therapy (SBRT) for prostate cancer. Prostate SBRT has emerged as a leading option for external beam radiotherapy due to its effectiveness and reduced treatment duration. However, interfractional anatomy variations can impact treatment outcomes. This study seeks to address these uncertainties using DT concept, with the goal of improving treatment quality, potentially revolutionizing prostate radiotherapy to offer personalized treatment solutions. Our study presented a pioneering approach that leverages DT technology to enhance adaptive proton SBRT. The framework improves treatment plans by utilizing patient-specific CTV setup uncertainty, which is usually smaller than conventional clinical setups. This research contributes to the ongoing efforts to enhance the efficiency and efficacy of prostate radiotherapy, with ultimate goals of improving patient outcomes and life quality.

A nomogram of anastomotic stricture after rectal cancer: a retrospective cohort analysis.

BACKGROUND: Anastomotic stricture significantly impacts patients' quality of life and long-term prognosis. However, current clinical practice lacks accurate tools for predicting anastomotic stricture. This study aimed to develop a nomogram to predict anastomotic stricture in patients with rectal cancer who have undergone anterior resection. METHODS: A total of 1542 eligible patients were recruited for the study. Least absolute shrinkage selection operator (Lasso) analysis was used to preliminarily select predictors. A prediction model was constructed using multivariate logistic regression and presented as a nomogram. The performance of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration diagrams, and decision curve analysis (DCA). Internal validation was conducted by assessing the model's performance on a validation cohort. RESULTS: 72 (4.7%) patients were diagnosed with anastomotic stricture. Participants were randomly divided into training (n = 1079) and validation (n = 463) sets. Predictors included in this nomogram were radiotherapy, diverting stoma, anastomotic leakage, and anastomotic distance. The area under the ROC curve (AUC) for the training set was 0.889 [95% confidence interval (CI) 0.840-0.937] and for the validation set, it was 0.930 (95%CI 0.879-0.981). The calibration curve demonstrated a strong correlation between predicted and observed outcomes. DCA results showed that the nomogram had clinical value in predicting anastomotic stricture in patients after anterior resection of rectal cancer. CONCLUSION: We developed a predictive model for anastomotic stricture following anterior resection of rectal cancer. This nomogram could assist clinicians in predicting the risk of anastomotic stricture, thus improving patients' quality of life and long-term prognosis.

Influencing factors of hospitalization cost of hypertension patients in traditional Chinese medicine hospitals.

Objectives: This study aimed to analyze the influencing factors of hospitalization cost of hypertensive patients in TCM (traditional Chinese medicine, TCM) hospitals, which can provide a scientific basis for hospitals to control the hospitalization cost of hypertension. Methods: In this study, 3,595 hospitalized patients with a primary diagnosis of tertiary hypertension in Tianshui City Hospital of TCM, Gansu Province, China, from January 2017 to June 2022, were used as research subjects. Using univariate analysis to identify the relevant variables of hospitalization cost, followed by incorporating the statistically significant variables of univariate analysis as independent variables in multiple linear regression analysis, and establishing the path model based on the results of the multiple linear regression finally, to explore the factors influencing hospitalization cost comprehensively. Results: The results showed that hospitalization cost of hypertension patients were mainly influenced by length of stay, age, admission pathways, payment methods of medical insurance, and visit times, with length of stay being the most critical factor. Conclusion: The Chinese government should actively exert the characteristics and advantages of TCM in the treatment of chronic diseases such as hypertension, consistently optimize the treatment plans of TCM, effectively reduce the length of stay and steadily improve the health literacy level of patients, to alleviate the illnesses pain and reduce the economic burden of patients.

The Influence of Nonlinear High-Intensity Dynamic Processes on the Standing Wave Precession of a Non-Ideal Hemispherical Resonator.

The properties of small size, low noise, high performance and no wear-out have made the hemispherical resonator gyroscope a good choice for high-value space missions. To enhance the precision of the hemispherical resonator gyroscope for use in tasks with large angular velocities and angular accelerations, this paper investigates the standing wave precession of a non-ideal hemispherical resonator under nonlinear high-intensity dynamic conditions. Based on the thin shell theory of elasticity, a dynamic model of a hemispherical resonator is established by using Lagrange's second kind equation. Then, the dynamic model is equivalently transformed into a simple harmonic vibration model of a point mass in two-dimensional space, which is analyzed using a method of averaging that separates the slow variables from the fast variables. The results reveal that taking the nonlinear terms about the square of the angular velocity and the angular acceleration in the dynamic equation into account can weaken the influence of the 4th harmonic component of a mass defect on standing wave drift, and the extent of this weakening effect varies with the dimensions of the mass defects, which is very important for steering the development of the high-precision hemispherical resonator gyroscope.

Three-dimensional laser micromachining system with integrated sub-100†nm resolution in-situ measurement.

In this study, a three-dimensional (3D) laser micromachining system with an integrated sub-100 nm resolution in-situ measurement system was proposed. The system used the same femtosecond laser source for in-situ measurement and machining, avoiding errors between the measurement and the machining positions. It could measure the profile of surfaces with an inclination angle of less than 10°, and the measurement resolution was greater than 100 nm. Consequently, the precise and stable movement of the laser focus could be controlled, enabling highly stable 3D micromachining. The results showed that needed patterns could be machined on continuous surfaces using the proposed system. The proposed machining system is of great significance for broadening the application scenarios of laser machining.

Surgical options and survival prognosis in geriatric patients beyond average lifespan with locally advanced gastric cancer: a propensity score-matched analysis.

BACKGROUND: The appropriateness of laparoscopic gastrectomy (LG) for super-geriatric patients with locally advanced gastric cancer (LAGC) is inconclusive, and the prognostic factors are also yet to be elucidated. Herein, we aimed to investigate the surgical and oncological outcomes of LG versus open gastrectomy (OG) for geriatric patients with LAGC who have outlived the average lifespan of the Chinese population (≥ 78 years). METHODS: This is a monocentric, retrospective, comparative study. A 1:1 propensity score matching (PSM) was performed to minimize selection bias and ensure well-balanced characteristics. The primary endpoint of interest was 3-year overall survival, while secondary endpoints included procedure-related variables, postoperative recovery indices, and complications. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify unfavorable prognostic factors. RESULTS: Of 196 eligible individuals, 107 underwent LG and 89 underwent OG, with a median age (interquartile range [IQR]) of 82 [79, 84] years. PSM yielded 61 matched pairs, with comparable demographic and tumor characteristics. The LG group had a significantly lower overall complication rate than the OG group (31.1% vs. 49.2%, P = 0.042), as well as shorter duration of postoperative hospital stay [12 (11, 13) vs. 13 (12, 15.5) d, P < 0. 001], less intraoperative blood loss [95 (75, 150) vs. 230 (195, 290) mL, P < 0.001], but a longer operative time [228 (210, 255.5) vs. 196 (180, 219.5) min, P < 0.001]. The times to first aerofluxus, defecation, liquid diet, and half-liquid diet were comparable. Kaplan-Meier analyses revealed no significant difference in 3-year overall survival between the groups, either in the entire cohort or in subgroups with different TNM staging. Moreover, Age-adjusted Charlson Comorbidity Index scores of > 6 [hazard ratio (HR) 4.003; P = 0.021] and pathologic TNM stage III (HR 3.816, P = 0.023) were independent unfavorable prognostic factors for long-term survival. CONCLUSIONS: LG performed by experienced surgeons offers the benefits of comparable or better surgical and oncological safety profiles than OG for super-geriatric patients with LAGC.

Deep learning radiomics-based prediction model of metachronous distant metastasis following curative resection for retroperitoneal leiomyosarcoma: a bicentric study.

BACKGROUND: Combining conventional radiomics models with deep learning features can result in superior performance in predicting the prognosis of patients with tumors; however, this approach has never been evaluated for the prediction of metachronous distant metastasis (MDM) among patients with retroperitoneal leiomyosarcoma (RLS). Thus, the purpose of this study was to develop and validate a preoperative contrast-enhanced computed tomography (CECT)-based deep learning radiomics model for predicting the occurrence of MDM in patients with RLS undergoing complete surgical resection. METHODS: A total of 179 patients who had undergone surgery for the treatment of histologically confirmed RLS were retrospectively recruited from two tertiary sarcoma centers. Semantic segmentation features derived from a convolutional neural network deep learning model as well as conventional hand-crafted radiomics features were extracted from preoperative three-phase CECT images to quantify the sarcoma phenotypes. A conventional radiomics signature (RS) and a deep learning radiomics signature (DLRS) that incorporated hand-crafted radiomics and deep learning features were developed to predict the risk of MDM. Additionally, a deep learning radiomics nomogram (DLRN) was established to evaluate the incremental prognostic significance of the DLRS in combination with clinico-radiological predictors. RESULTS: The comparison of the area under the curve (AUC) values in the external validation set, as determined by the DeLong test, demonstrated that the integrated DLRN, DLRS, and RS models all exhibited superior predictive performance compared with that of the clinical model (AUC 0.786 [95% confidence interval 0.649-0.923] vs. 0.822 [0.692-0.952] vs. 0.733 [0.573-0.892] vs. 0.511 [0.359-0.662]; both P < 0.05). The decision curve analyses graphically indicated that utilizing the DLRN for risk stratification provided greater net benefits than those achieved using the DLRS, RS and clinical models. Good alignment with the calibration curve indicated that the DLRN also exhibited good performance. CONCLUSIONS: The novel CECT-based DLRN developed in this study demonstrated promising performance in the preoperative prediction of the risk of MDM following curative resection in patients with RLS. The DLRN, which outperformed the other three models, could provide valuable information for predicting surgical efficacy and tailoring individualized treatment plans in this patient population. TRIAL REGISTRATION: Not applicable.

Clinical prediction factors of nonchronic total occlusion lesion progression in patients with unstable angina receiving percutaneous coronary intervention for chronic total occlusion lesions.

Background: In this study, we investigated clinical prediction factors of nonchronic total occlusion lesion (NCTOL) progression in patients who underwent percutaneous coronary intervention (PCI) for chronic total occlusion (CTO) lesions. Methods: In total, 450 patients with unstable angina (mean age = 57.1 ± 9.2 years) who underwent PCI for CTO lesions between January 2016 and December 2018 at Beijing Anzhen Hospital were enrolled in this study. A clinical and angiographic follow-up examination was performed 12 months postoperatively. The patients were divided into NCTOL progression (145 cases) and control (305 cases) groups based on the outcome of the 12-month angiographic follow-up. The clinical and angiographic features of the participants were analyzed. Results: The adenosine diphosphate-induced platelet aggregation (ADP-IPA) rate and levels of lipoprotein (a) (Lp(a)) in the NCTOL progression group were significantly higher than those in the control group (51.89 ± 14.81 vs. 39.63 ± 17.12, P < 0.01; 0.22 ± 0.26 vs. 0.14 ± 0.18, P < 0.05, respectively). Logistic regression showed that the ADP-IPA rate (odds ratio = 1.047, 95 % confidence interval: 1.014-1.082, P = 0.005) and Lp(a) (odds ratio = 11.972, 95 % confidence interval: 1.230-116.570, P = 0.033) were independent predictors of NCTOL progression. Partial correlation analysis demonstrated that the ADP-IPA rate was positively correlated with NCTOL progression (r = 0. 351, P < 0.001). Receiver operating characteristic curve showed that the boundary point of the ADP-IPA rate to predict NCTOL progression was 30 % (sensitivity, 86.2 %; specificity, 68.9 %). Conclusions: NCTOL progression is an important cause of recurrent PCI in patients with coronary artery disease after PCI for CTO lesions. The ADP-IPA rate is a useful predictor for NCTOL progression in patients with unstable angina who undergo PCI for CTO lesions.

MGCNSS: miRNA-disease association prediction with multi-layer graph convolution and distance-based negative sample selection strategy.

Identifying disease-associated microRNAs (miRNAs) could help understand the deep mechanism of diseases, which promotes the development of new medicine. Recently, network-based approaches have been widely proposed for inferring the potential associations between miRNAs and diseases. However, these approaches ignore the importance of different relations in meta-paths when learning the embeddings of miRNAs and diseases. Besides, they pay little attention to screening out reliable negative samples which is crucial for improving the prediction accuracy. In this study, we propose a novel approach named MGCNSS with the multi-layer graph convolution and high-quality negative sample selection strategy. Specifically, MGCNSS first constructs a comprehensive heterogeneous network by integrating miRNA and disease similarity networks coupled with their known association relationships. Then, we employ the multi-layer graph convolution to automatically capture the meta-path relations with different lengths in the heterogeneous network and learn the discriminative representations of miRNAs and diseases. After that, MGCNSS establishes a highly reliable negative sample set from the unlabeled sample set with the negative distance-based sample selection strategy. Finally, we train MGCNSS under an unsupervised learning manner and predict the potential associations between miRNAs and diseases. The experimental results fully demonstrate that MGCNSS outperforms all baseline methods on both balanced and imbalanced datasets. More importantly, we conduct case studies on colon neoplasms and esophageal neoplasms, further confirming the ability of MGCNSS to detect potential candidate miRNAs. The source code is publicly available on GitHub https://github.com/15136943622/MGCNSS/tree/master.

Testing multiplexed anti-ASFV CRISPR-Cas9 in reducing African swine fever virus.

African swine fever (ASF) is a highly fatal viral disease that poses a significant threat to domestic pigs and wild boars globally. In our study, we aimed to explore the potential of a multiplexed CRISPR-Cas system in suppressing ASFV replication and infection. By engineering CRISPR-Cas systems to target nine specific loci within the ASFV genome, we observed a substantial reduction in viral replication in vitro. This reduction was achieved through the concerted action of both Type II and Type III RNA polymerase-guided gRNA expression. To further evaluate its anti-viral function in vivo, we developed a pig strain expressing the multiplexable CRISPR-Cas-gRNA via germline genome editing. These transgenic pigs exhibited normal health with continuous expression of the CRISPR-Cas-gRNA system, and a subset displayed latent viral replication and delayed infection. However, the CRISPR-Cas9-engineered pigs did not exhibit a survival advantage upon exposure to ASFV. To our knowledge, this study represents the first instance of a living organism engineered via germline editing to assess resistance to ASFV infection using a CRISPR-Cas system. Our findings contribute valuable insights to guide the future design of enhanced viral immunity strategies. IMPORTANCE: ASFV is currently a devastating disease with no effective vaccine or treatment available. Our study introduces a multiplexed CRISPR-Cas system targeting nine specific loci in the ASFV genome. This innovative approach successfully inhibits ASFV replication in vitro, and we have successfully engineered pig strains to express this anti-ASFV CRISPR-Cas system constitutively. Despite not observing survival advantages in these transgenic pigs upon ASFV challenges, we did note a delay in infection in some cases. To the best of our knowledge, this study constitutes the first example of a germline-edited animal with an anti-virus CRISPR-Cas system. These findings contribute to the advancement of future anti-viral strategies and the optimization of viral immunity technologies.

Catalpol attenuates ischemic stroke by promoting neurogenesis and angiogenesis via the SDF-1α/CXCR4 pathway.

BACKGROUND: Stroke is a leading cause of disability and death worldwide. Currently, there is a lack of clinically effective treatments for the brain damage following ischemic stroke. Catalpol is a bioactive compound derived from the traditional Chinese medicine Rehmannia glutinosa and shown to be protective in various neurological diseases. However, the potential roles of catalpol against ischemic stroke are still not completely clear. PURPOSE: This study aimed to further elucidate the protective effects of catalpol against ischemic stroke. METHODS: A rat permanent middle cerebral artery occlusion (pMCAO) and oxygen-glucose deprivation (OGD) model was established to assess the effect of catalpol in vivo and in vitro, respectively. Behavioral tests were used to examine the effects of catalpol on neurological function of ischemic rats. Immunostaining was performed to evaluate the proliferation, migration and differentiation of neural stem cells (NSCs) as well as the angiogenesis in each group. The protein level of related molecules was detected by western-blot. The effects of catalpol on cultured NSCs as well as brain microvascular endothelial cells (BMECs) subjected to OGD in vitro were also examined by similar methods. RESULTS: Catalpol attenuated the neurological deficits and improved neurological function of ischemic rats. It stimulated the proliferation of NSCs in the subventricular zone (SVZ), promoted their migration to the ischemic cortex and differentiation into neurons or glial cells. At the same time, catalpol increased the cerebral vessels density and the number of proliferating cerebrovascular endothelial cells in the infracted cortex of ischemic rats. The level of SDF-1α and CXCR4 in the ischemic cortex was found to be enhanced by catalpol treatment. Catalpol was also shown to promote the proliferation and migration of cultured NSCs as well as the proliferation of BMECs subjected to OGD insult in vitro. Interestingly, the impact of catalpol on cultured cells was inhibited by CXCR4 inhibitor AMD3100. Moreover, the culture medium of BMECs containing catalpol promoted the proliferation of NSCs, which was also suppressed by AMD3100. CONCLUSION: Our data demonstrate that catalpol exerts neuroprotective effects by promoting neurogenesis and angiogenesis via the SDF-1α/CXCR4 pathway, suggesting the therapeutic potential of catalpol in treating cerebral ischemia.

Advancements in Uric Acid Stone Detection: Integrating Deep Learning with CT Imaging and Clinical Assessments in the Upper Urinary Tract.

INTRODUCTION: Among upper urinary tract stones, a significant proportion comprises uric acid stones. The aim of this study was to use machine learning techniques to analyze CT scans and blood and urine test data, with the aim of establishing multiple predictive models that can accurately identify uric acid stones. METHODS: We divided 276 patients with upper urinary tract stones into two groups: 48 with uric acid stones and 228 with other types, identified using Fourier-transform infrared spectroscopy. To distinguish the stone types, we created three types of deep learning models and extensively compared their classification performance. RESULTS: Among the three major types of models, considering accuracy, sensitivity, and recall, CLNC-LR, IMG-support vector machine (SVM), and FUS-SVM perform the best. The accuracy and F1 score for the three models were as follows: CLNC-LR (82.14%, 0.7813), IMG-SVM (89.29%, 0.89), and FUS-SVM (29.29%, 0.8818). The area under the curves for classes CLNC-LR, IMG-SVM, and FUS-SVM were 0.97, 0.96, and 0.99, respectively. CONCLUSION: This study shows the feasibility of utilizing deep learning to assess whether urinary tract stones are uric acid stones through CT scans, blood, and urine tests. It can serve as a supplementary tool for traditional stone composition analysis, offering decision support for urologists and enhancing the effectiveness of diagnosis and treatment.

Cation-induced Ti3C2Tx MXene@melamine sponge aerogels with large layer spacing and high strength for high-performance supercapacitors.

The self-assembled aerogels are considered as an efficient strategy to address the aggregation and restacking of Ti3C2Tx MXene nanosheets for high-performance supercapacitors. However, the low mechanical strength of the MXene aerogel results in the structural collapse of the self-standing supercapacitor electrode materials. Herein, a low-cost melamine sponge (MS) absorbed different cations (H+, K+, Mg2+, Fe2+, Co2+, Ni2+ and Al3+), serves as a carrier and crosslinker for loading MXene hydrogel induced by the absorbed cations on the skeleton surface and the pores of MS, resulting in the high loading mass MXene aerogels with high mechanical strength. The experimental results show that the Mg-Ti3C2Tx@MS aerogel exhibits the maximum area capacitance of 702.22 mF cm-2 at 3 mA cm-2, and the area capacitance is still 603.12 mF cm-2 even at 100 mA cm-2, indicating the high rate capability with a capacitance retention of 85.89 %. It is worth noting that the constructed asymmetric supercapacitor with activated carbon achieves high energy densities of 104.53 µWh cm-2 and 93.87 µWh cm-2 at 800 µW cm-2 and 7999 µW cm-2, respectively. Furthermore, the asymmetric supercapacitor shows the high cycling stability with 90.2 % capacity retention after 10,000 cycles. This work provides a feasible strategy to prepare Ti3C2Tx MXene aerogels with large layer spacing and high strength for high-performance supercapacitors.

Increased gene dosage of RFWD2 causes autistic-like behaviors and aberrant synaptic formation and function in mice.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social interactions, communication deficits and repetitive behaviors. A study of autistic human subjects has identified RFWD2 as a susceptibility gene for autism, and autistic patients have 3 copies of the RFWD2 gene. The role of RFWD2 as an E3 ligase in neuronal functions, and its contribution to the pathophysiology of ASD, remain unknown. We generated RFWD2 knockin mice to model the human autistic condition of high gene dosage of RFWD2. We found that heterozygous knockin (Rfwd2+/-) male mice exhibited the core symptoms of autism. Rfwd2+/- male mice showed deficits in social interaction and communication, increased repetitive and anxiety-like behavior, and spatial memory deficits, whereas Rfwd2+/- female mice showed subtle deficits in social communication and spatial memory but were normal in anxiety-like, repetitive, and social behaviors. These autistic-like behaviors in males were accompanied by a reduction in dendritic spine density and abnormal synaptic function on layer II/III pyramidal neurons in the prelimbic area of the medial prefrontal cortex (mPFC), as well as decreased expression of synaptic proteins. Impaired social behaviors in Rfwd2+/- male mice were rescued by the expression of ETV5, one of the major substrates of RFWD2, in the mPFC. These findings indicate an important role of RFWD2 in the pathogenesis of autism.

Identifying the Key Role of Plutella xylostella General Odorant Binding Protein 2 in Perceiving a Larval Attractant, (E,E)-2,6-Farnesol.

There is currently a lack of effective olfaction-based techniques to control diamondback moth (DBM) larvae. Identifying behaviorally active odorants for DBM larvae and exploring their recognition mechanisms can provide insights into olfaction-based larval control strategies. Through the two-choice assay, (E,E)-2,6-farnesol (farnesol) was identified as a compound exhibiting significant attractant activity toward DBM larvae, achieving an attraction index of 0.48 ± 0.13. PxylGOBP1 and PxylGOBP2, highly expressed in the antennae of DBM larvae, both showed high affinity toward farnesol. RNAi technology was used to knock down PxylGOBP1 and PxylGOBP2, revealing that the attraction of DBM larvae to farnesol nearly vanished following the knockdown of PxylGOBP2, indicating its critical role in recognizing farnesol. Further investigation into the PxylGOBP2-farnesol interaction revealed the importance of residues like Thr9, Trp37, and Phe118 in PxylGOBP2's binding to farnesol. This research is significant for unveiling the olfactory mechanisms of DBM larvae and developing larval behavior regulation techniques.