Prediction of small intracranial aneurysm rupture status based on combined Clinical-Radiomics model.

Background: Accumulating small unruptured intracranial aneurysms are detected due to the improved quality and higher frequency of cranial imaging, but treatment remains controversial. While surgery or endovascular treatment is effective for small aneurysms with a high risk of rupture, such interventions are unnecessary for aneurysms with a low risk of rupture. Consequently, it is imperative to accurately identify small aneurysms with a low risk of rupture. The purpose of this study was to develop a clinically practical model to predict small aneurysm ruptures based on a radiomics signature and clinical risk factors. Methods: A total of 293 patients having an aneurysm with a diameter of less than 5 mm, including 199 patients (67.9 %) with a ruptured aneurysm and 94 patients (32.1 %) without a ruptured aneurysm, were included in this study. Digital subtraction angiography or surgical treatment was required in all cases. Data on the clinical risk factors and the features on computed tomography angiography images associated with the aneurysm rupture status were collected simultaneously. We developed a clinical-radiomics model to predict aneurysm rupture status using multivariate logistic regression analysis. The combined clinical-radiomics model was constructed by nomogram analysis. The diagnostic performance, clinical utility, and model calibration were evaluated by operating characteristic curve analysis, decision curve analysis, and calibration analysis. Results: A combined clinical-radiomics model (Area Under Curve [AUC], 0.85; 95 % confidence interval [CI], 0.757-0.947) showed effective performance in the operating characteristic curve analysis. In the validation cohort, the performance of the combined model was better than that of the radiomics model (AUC, 0.75; 95 % CI, 0.645-0.865; Delong's test p-value = 0.01) and the clinical model (AUC, 0.74; 95 % CI, 0.625-0.851; Delong's test p-value <0.01) alone. The results of the decision curve, nomogram, and calibration analyses demonstrated the clinical utility and good fitness of the combined model. Conclusion: Our study demonstrated the effectiveness of a clinical-radiomics model for predicting rupture status in small aneurysms.

Crosstalk between T lymphocyte and extracellular matrix in tumor microenvironment.

The extracellular matrix (ECM) is a complex three-dimensional structure composed of proteins, glycans, and proteoglycans, constituting a critical component of the tumor microenvironment. Complex interactions among immune cells, extracellular matrix, and tumor cells promote tumor development and metastasis, consequently influencing therapeutic efficacy. Hence, elucidating these interaction mechanisms is pivotal for precision cancer therapy. T lymphocytes are an important component of the immune system, exerting direct anti-tumor effects by attacking tumor cells or releasing lymphokines to enhance immune effects. The ECM significantly influences T cells function and infiltration within the tumor microenvironment, thereby impacting the behavior and biological characteristics of tumor cells. T cells are involved in regulating the synthesis, degradation, and remodeling of the extracellular matrix through the secretion of cytokines and enzymes. As a result, it affects the proliferation and invasive ability of tumor cells as well as the efficacy of immunotherapy. This review discusses the mechanisms underlying T lymphocyte-ECM interactions in the tumor immune microenvironment and their potential application in immunotherapy. It provides novel insights for the development of innovative tumor therapeutic strategies and drug.

Localized Phonon Transport Study of GaN/SiO2 Core/shell Nanowires under Thermal-Stress Coupling.

In order to comprehensively explore the intricate mechanisms of thermo-mechanical interactions, this study employs the molecular dynamics method to investigate the influence of heat flux density, shell thickness and length, as well as stress on the radial interface phonon transport in GaN/SiO2 core/shell nanowire. Additionally, the surface eigenmode decomposition method is employed to analyze the interface phonon dispersion curves. The investigation reveals that with increasing heat flux density, internal thermal stresses intensify, leading to a complex distribution of thermal stresses within the system. Under the influence of thermal stress, the nonlinear acoustic properties interact with phonon scattering, resulting in the pronounced localization of interface phonons. Compressive stress causes an upshift in low-frequency phonons, while tensile stress induces a downward shift in the high-frequency optical branches at the interface. The localized phonon vibrations at the SiO2/GaN interface under nonuniform stress are identified as the primary cause for the abundant presence of nondispersive phonon modes at the radial interface. By elucidating the subtle interplay between lattice vibrations and stress fields, this study offers a novel and profound understanding of thermo-mechanical coupling effects, thereby providing innovative theoretical foundations for the design and performance management of thermoelectric devices.

Catalysts with Trimetallic Sites on Graphene-like C2N for Electrocatalytic Nitrogen Reduction Reaction: A Theoretical Investigation.

Electrocatalytic nitrogen reduction reaction (NRR) is a green and highly efficient way to replace the industrial Haber-Bosch process. Herein, clusters consisting of three transition metal atoms loaded on C2N as NRR electrocatalysts are investigated using density functional theory (DFT). Meanwhile, Ca was introduced as a promoter and the role of Ca in NRR was investigated. It was found that Ca anchored to the catalyst can act as an electron donor and effectively promote the activation of N2 on M3. In both M3@C2N and M3Ca@C2N (M = Fe, Co, Ni), the limiting potential (UL) is less negative than that of the Ru(0001) surface and has the ability to suppress the competitive hydrogen evolution reaction (HER). Among them, Fe3@C2N is suggested to be the most promising candidate for NRR with high thermal stability, strong N2 adsorption ability, low limiting potential, and good NRR selectivity. The concepts of trimetallic sites and alkaline earth metal promoters in this work provide theoretical guidance for the rational design of atomically active sites in electrocatalytic NRR.

Chemokines and Their Receptors: Predictors of Therapeutic Potential in Tumor Microenvironment on Esophageal Cancer.

Esophageal carcinoma (ESCA) is an aggressive solid tumor. The 5-year survival rate for patients with ESCA is estimated to be less than 20%, mainly due to tumor invasion and metastasis. Therefore, it is urgent to improve early diagnostic tools and effective treatments for ESCA patients. Tumor microenvironment (TME) enhances the ability of tumor cells to proliferate, migrate, and escape from the immune system, thus promoting the occurrence and development of tumor. TME contains chemokines. Chemokines consist of four major families, which are mainly composed of CC and CXC families. The main purpose of this review is to understand the CC and CXC chemokines and their receptors in ESCA, to improve the understanding of tumorigenesis of ESCA and determine new biomarkers for the diagnosis and prognosis of ESCA. We reviewed the literature on CC and CXC chemokines and their receptors in ESCA identified by PubMed database. This article introduces the general structures and functions of CC, CXC chemokines and their receptors in TME, as well as their roles in the progress of ESCA. Chemokines are involved in the development of ESCA, such as cancer cell invasion, metastasis, angiogenesis, and radioresistance, and are key determinants of disease progression, which have a great impact on patient prognosis and treatment response. In addition, a full understanding of their mechanism of action is essential to further verify that these chemokines and their receptors may serve as biomarkers or therapeutic targets of ESCA.

Exenatide reduces atrial fibrillation susceptibility by inhibiting hKv1.5 and hNav1.5 channels.

Exenatide, a promising cardioprotective agent, protects against cardiac structural remodeling and diastolic dysfunction. Combined blockade of sodium and potassium channels is valuable for managing atrial fibrillation (AF). Here, we explored whether exenatide displayed anti-AF effects by inhibiting human Kv1.5 and Nav1.5 channels. We used the whole-cell patch-clamp technique to investigate the effects of exenatide on hKv1.5 and hNav1.5 channels expressed in human embryonic kidney 293 cells and studied the effects of exenatide on action potential (AP) and other cardiac ionic currents in rat atrial myocytes. Additionally, an electrical mapping system was used to explore the effects of exenatide on electrical properties and AF activity in isolated rat hearts. Finally, a rat AF model, established using acetylcholine and calcium chloride, was employed to evaluate the anti-AF potential of exenatide in rats. Exenatide reversibly suppressed IKv1.5 with IC50 of 3.08 µM, preferentially blocked hKv1.5 channel in its closed state, and positively shifted the voltage-dependent activation curve. Exenatide also reversibly inhibited INav1.5 with IC50 of 3.30 µM, negatively shifted the voltage-dependent inactivation curve, and slowed its recovery from inactivation with significant use-dependency at 5 and 10 Hz. Furthermore, exenatide prolonged AP duration and suppressed the sustained K+ current (Iss) and transient outward K+ current (Ito), but without inhibition of L-type Ca2+ current (ICa,L) in rat atrial myocytes. Exenatide prevented AF incidence and duration in rat hearts and rats. These findings demonstrate that exenatide inhibits IKv1.5 and INav1.5in vitro and reduces AF susceptibility in isolated rat hearts and rats.

Case Report: Rapid and progressive left ventricular endocardial calcification in an infant with Williams syndrome.

Williams syndrome (WS) is characterized by a range of clinical features, including cardiovascular disease, distinctive facial traits, neurobehavioral disorders, and a condition known as transient infantile hypercalcemia. Among these, endocardial calcification represents a non-specific response to severe, etiologically diverse myocardial injuries. In this report, we document a unique case involving an infant with WS who exhibited rapidly progressive arterial stenosis and left ventricular endocardial calcification, associated with a novel heterozygous deletion. While arterial stenosis is the most frequently observed cardiovascular issue in WS, instances of endocardial calcification during infancy are exceedingly rare and have not previously been reported in the context of WS.

A novel method for precise implantation of tracheal Y-shaped stent.

The tracheal Y-shaped stent is mainly used for the treatment of critical patients with airway stenosis or esophagotracheal fistula near carina. A novel method for precise implantation of Y-shaped tracheal stents was developed using double-lumen endotracheal intubation and flexible bronchoscopy. This approach aims to address the limitations associated with X-ray or rigid bronchoscopy guidance, such as operational difficulties and the risk of inaccurate stent placement leading to implantation failure or suffocation. With this new technique, 13 tracheal Y-shaped stents were successfully implanted. This method shows promise in reducing the complexity of stent implantation and facilitating timely treatment for patients in need. Additionally, it has the potential to update current operating standards and guidelines for this procedure.

[Computer-aided prediction and molecular mechanism investigation of active components in compound Kushen injection inhibiting p21-activated kinase 1].

Targeting p21-activated kinase 1 (PAK1) is a novel strategy for pancreatic cancer treatment. Compound Kushen injection contains many anti-pancreatic cancer components, but the specific targets are unknown. In this study, 14α-hydroxymatrine, an active component of Kushen injection, was found to possess high binding free energy with the allosteric site of PAK1 by molecular docking based virtual screening. Molecular dynamics simulations suggested that 14α-hydroxymatrine caused the α1 and α2 helices of the allosteric site of PAK1 to extend outward to form a deep allosteric regulatory pocket. Meanwhile, 14α-hydroxymatrine induced the ß-folding region at the adenosine triphosphate (ATP)-binding pocket of PAK1 to close inward, resulting in the ATP-binding pocket in a "semi-closed" state which caused the inactivation of PAK1. After removal of 14α-hydroxymatrine, PAK1 showed a tendency to change from the inactive conformation to the active conformation. We supposed that 14α-hydroxymatrine of compound Kushen injection might be a reversible allosteric inhibitor of PAK1. This study used modern technologies and methods to study the active components of traditional Chinese medicine, which laid a foundation for the development and utilization of natural products and the search for new treatments for pancreatic cancer.

Norfloxacin adsorption by urban green waste biochar: characterization, kinetics, and mechanisms.

Biochar, as a potential adsorbent, has been widely employed to remove pollutants from sewage. In this study, a lignin-based biochar (CB-800) was prepared by a simple high-temperature pyrolysis using urban green waste (Cinnamomum camphora leaves) as a feedstock to remove norfloxacin (NOR) from water. Batch adsorption test results indicated that CB-800 had a strong removal capacity for NOR at a wide range of pH values. The maximum adsorption achieved in the study was 50.90 ± 0.64 mg/g at 298 K. The pseudo-first and second-order kinetic models and the Dubinin-Radushkevich isotherm fitted the experimental data well, indicating that NOR adsorption by CB-800 was a complex process involving both physi-sorption and chemi-sorption. The physical properties of CB-800 were characterized by SEM and BET. The mesoporous structures were formed hierarchically on the surface of CB-800 (with an average pore size of 2.760 nm), and the spatial structure of NOR molecules was more easily adsorbed by mesoporous structures. Combined with Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) analysis, it was showed that the main NOR adsorption mechanisms by CB-800 included ion exchange, π-electron coordination, hydrogen bonding, and electrostatic adsorption. Meanwhile, the reduction of C = O and pyridine nitrogen, and the presence of C-F2, also indicated the occurrence of substitution, addition, and redox. This study not only determined the reaction mechanism between biochar and NOR, but also provides guidance to waste managers for the removal of NOR from water by biochar. It is envisaged that the results will broaden the utilization of urban green waste.

Chimeric Porcine Parvovirus VP2 Virus-like Particles with Epitopes of South African Serotype 2 Foot-and-Mouth Disease Virus Elicits Specific Humoral and Cellular Responses in Mice.

Southern Africa Territories 2 (SAT2) foot-and-mouth disease (FMD) has crossed long-standing regional boundaries in recent years and entered the Middle East. However, the existing vaccines offer poor cross-protection against the circulating strains in the field. Therefore, there is an urgent need for an alternative design approach for vaccines in anticipation of a pandemic of SAT2 Foot-and-mouth disease virus (FMDV). The porcine parvovirus (PPV) VP2 protein can embed exogenous epitopes into the four loops on its surface, assemble into virus-like particles (VLPs), and induce antibodies and cytokines to PPV and the exogenous epitope. In this study, chimeric porcine parvovirus VP2 VLPs (chimeric PPV-SAT2-VLPs) expressing the T-and/or B-cell epitopes of the structural protein VP1 of FMDV SAT2 were produced using the recombinant pFastBac™ Dual vector of baculoviruses in Sf9 and HF cells We used the Bac-to-Bac system to construct the recombinant baculoviruses. The VP2-VLP--SAT2 chimeras displayed chimeric T-cell epitope (amino acids 21-40 of VP1) and/or the B-cell epitope (amino acids 135-174) of SAT FMDV VP1 by substitution of the corresponding regions at the N terminus (amino acids 2-23) and/or loop 2 and/or loop 4 of the PPV VP2 protein, respectively. In mice, the chimeric PPV-SAT2-VLPs induced specific antibodies against PPV and the VP1 protein of SAT2 FMDV. The VP2-VLP-SAT2 chimeras induced specific antibodies to PPV and the VP1 protein specific epitopes of FMDV SAT2. In this study, as a proof-of-concept, successfully generated chimeric PPV-VP2 VLPs expressing epitopes of the structural protein VP1 of FMDV SAT2 that has a potential to prevent FMDV SAT2 and PPV infection in pigs.

Development of Serum Lactate Level-Based Nomograms for Predicting Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients.

Purpose: To establish nomograms integrating serum lactate levels and traditional risk factors for predicting diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients. Patients and methods: A total of 570 T2DM patients and 100 healthy subjects were enrolled. T2DM patients were categorized into normal and high lactate groups. Univariate and multivariate logistic regression analyses were employed to identify independent predictors for DKD. Then, nomograms for predicting DKD were established, and the model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration, and decision curve analysis (DCA). Results: T2DM patients exhibited higher lactate levels compared to those in healthy subjects. Glucose, platelet, uric acid, creatinine, and hypertension were independent factors for DKD in T2DM patients with normal lactate levels, while diabetes duration, creatinine, total cholesterol, and hypertension were indicators in high lactate levels group (P<0.05). The AUC values were 0.834 (95% CI, 0.776 to 0.891) and 0.741 (95% CI, 0.688 to 0.795) for nomograms in both normal lactate and high lactate groups, respectively. The calibration curve demonstrated excellent agreement of fit. Furthermore, the DCA revealed that the threshold probability and highest Net Yield were 17-99% and 0.36, and 24-99% and 0.24 for the models in normal lactate and high lactate groups, respectively. Conclusion: The serum lactate level-based nomogram models, combined with traditional risk factors, offer an effective tool for predicting DKD probability in T2DM patients. This approach holds promise for early risk assessment and tailored intervention strategies.

Predicting COVID-19 Re-Positive Cases in Malnourished Older Adults: A Clinical Model Development and Validation.

Purpose: Building and validating a clinical prediction model for novel coronavirus (COVID-19) re-positive cases in malnourished older adults. Patients and Methods: Malnourished older adults from January to May 2023 were retrospectively collected from the Department of Geriatrics of the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine. They were divided into a "non-re-positive" group and a "re-positive" group based on the number of COVID-19 infections, and into a training set and a validation set at a 7:3 ratio. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to identify predictive factors for COVID-19 re-positivity in malnourished older adults, and a nomogram was constructed. Independent influencing factors were screened by multivariate logistic regression. The model's goodness-of-fit, discrimination, calibration, and clinical impact were assessed by Hosmer-Lemeshow test, area under the curve (AUC), calibration curve, decision curve analysis (DCA), and clinical impact curve analysis (CIC), respectively. Results: We included 347 cases, 243 in the training set, and 104 in the validation set. We screened 10 variables as factors influencing the outcome. By multivariate logistic regression analysis, preliminary identified protective factors, risk factors, and independent influencing factors that affect the re-positive outcome. We constructed a clinical prediction model for COVID-19 re-positivity in malnourished older adults. The Hosmer-Lemeshow test yielded χ2 =5.916, P =0.657; the AUC was 0.881; when the threshold probability was >8%, using this model to predict whether malnourished older adults were re-positive for COVID-19 was more beneficial than implementing intervention programs for all patients; when the threshold was >80%, the positive estimated value was closer to the actual number of cases. Conclusion: This model can help identify the risk of COVID-19 re-positivity in malnourished older adults early, facilitate early clinical decision-making and intervention, and have important implications for improving patient outcomes. We also expect more large-scale, multicenter studies to further validate, refine, and update this model.

8-shogaol derived from dietary ginger alleviated acute and inflammatory pain by targeting TRPV1.

Ginger, a well-known spice plant, has been used widely in medicinal preparations for pain relief. However, little is known about its analgesic components and the underlying mechanism. Here, we ascertained, the efficacy of ginger ingredient 8-Shogaol (8S), on inflammatory pain and tolerance induced by morphine, and probed the role of TRPV1 in its analgesic action using genetic and electrophysiology approaches. Results showed that 8S effectively reduced nociceptive behaviors of mice elicited by chemical stimuli, noxious heat as well as inflammation, and antagonized morphine analgesic tolerance independent on opioid receptor function. Genetic deletion of TRPV1 significantly abolished 8S' analgesia action. Further calcium imaging and patch-clamp recording showed that 8S could specifically activate TRPV1 in TRPV1-expressing HEK293T cells and dorsal root ganglion (DRG) neurons. The increase of [Ca2+]i in DRG was primarily mediated through TRPV1. Mutational and computation studies revealed the key binding sites for the interactions between 8S and TRPV1 included Leu515, Leu670, Ile573, Phe587, Tyr511, and Phe591. Further studies showed that TRPV1 activation evoked by 8S resulted in channel desensitization both in vitro and in vivo, as may be attributed to TRPV1 degradation or TRPV1 withdrawal from the cell surface. Collectively, this work provides the first evidence for the attractive analgesia of 8S in inflammatory pain and morphine analgesic tolerance mediated by targeting pain-sensing TRPV1 channel. 8S from dietary ginger has potential as a candidate drug for the treatment of inflammatory pain.

Association between perceived neighborhood environment and depression among residents living in mega-communities in Guiyang, China: a cross-sectional study.

BACKGROUND: Little was known about the relationship between perceived neighborhood environment and depression among residents living in mega-communities. Furthermore, the mediating effects of physical activity (PA) and anxiety in this relationship have not been investigated. Thus, this study aimed to comprehensively examine the association between perceived neighborhood environment and depression among residents living in mega-communities, and test whether PA and anxiety mediated the association. METHODS: A cross-sectional study on perceived neighborhood environment and depression was conducted among individuals who lived in mega-communities (n = 665) in Guiyang, China from July to August 2022. Perceived neighborhood environment was assessed from the following six aspects: traffic, building quality, accessibility, neighborhood, indoor, and pollution. Depression was measured by the Patients Health Questionnaire-9. Structural equation model was used to evaluate the association between perceived neighborhood environment and depression, and test the mediating effect of PA and anxiety in this association. RESULTS: We found that neighborhood (ß = -0.144, p = 0.002) and PA (ß = -0.074, p < 0.001) were both negatively associated with depression, while anxiety was positively associated with depression (ß = 0.447, p < 0.001). Married residents were less likely to experience depression than residents of other marital status. PA played a mediator role in the relationship between accessibility and depression (ß = 0.014, p = 0.033). PA mediated the relationship between neighborhood and depression (ß = -0.032, p = 0.015). The mediating effect of anxiety in the relationship between perceived neighborhood environment and depression was not significant. CONCLUSIONS: This study demonstrated that neighborhood, which was assessed by satisfaction with safety, hygiene, parking, greening, lighting, and building shape, was negatively associated with depression, and PA mediated the relationship.

Nonequilibrium electron-phonon coupling across the interfaces between Al nanofilm and GaN.

The metal Al is commonly attached to external circuits as the source and drain in GaN-based field effect transistors, so profound comprehension of the energy transfer between electrons and phonons in Al/GaN is crucial for nanofabrication and thermal management of electronic devices. Time-domain thermoreflectance (TDTR) is an effective technique for measuring the strength of non-equilibrium electron-phonon (e-ph) coupling. The two-temperature model (TTM) is widely employed in conjunction with TDTR methods to determine e-ph coupling factors. However, TTM is a gray method and cannot take into account interactions between electrons and different phonon modes. Therefore, in this work, we use the TDTR technique to analyze the non-equilibrium transport properties of pure Al and the thickness dependence of the e-ph coupling with Al nanofilms, and the coupling strengths of high-energy electrons excited by femtosecond lasers with different modes of phonons are obtained in conjunction with MTM. The results show that the e-ph coupling coefficients of Al nanofilms on GaN substrates are larger than those of pure Al. In conjunction with the TTM, we determined the coupling strength between high-energy electrons excited by femtosecond laser pulses and various phonon modes. Compared to the transverse acoustic branch-1 (TA1) and transverse acoustic branch-2 (TA2) modes, the longitudinal acoustic (LA) phonon mode of Al exhibits a higher e-ph coupling factor. This suggests that the LA mode predominates in the electron relaxation process after ultrafast femtosecond laser excitation. This study provides experimental and theoretical guidance for laser processing and electronic device design.

Uncovering brain functional connectivity disruption patterns of lung cancer-related pain.

Pain is a pervasive symptom in lung cancer patients during the onset of the disease. This study aims to investigate the connectivity disruption patterns of the whole-brain functional network in lung cancer patients with cancer pain (CP+). We constructed individual whole-brain, region of interest (ROI)-level functional connectivity (FC) networks for 50 CP+ patients, 34 lung cancer patients without pain-related complaints (CP-), and 31 matched healthy controls (HC). Then, a ROI-based FC analysis was used to determine the disruptions of FC among the three groups. The relationships between aberrant FCs and clinical parameters were also characterized. The ROI-based FC analysis demonstrated that hypo-connectivity was present both in CP+ and CP- patients compared to HC, which were particularly clustered in the somatomotor and ventral attention, frontoparietal control, and default mode modules. Notably, compared to CP- patients, CP+ patients had hyper-connectivity in several brain regions mainly distributed in the somatomotor and visual modules, suggesting these abnormal FC patterns may be significant for cancer pain. Moreover, CP+ patients also showed increased intramodular and intermodular connectivity strength of the functional network, which could be replicated in cancer stage IV and lung adenocarcinoma. Finally, abnormal FCs within the prefrontal cortex and somatomotor cortex were positively correlated with pain intensity and pain duration, respectively. These findings suggested that lung cancer patients with cancer pain had disrupted connectivity in the intrinsic brain functional network, which may be the underlying neuroimaging mechanisms.

A deep-learning-based framework for identifying and localizing multiple abnormalities and assessing cardiomegaly in chest X-ray.

Accurate identification and localization of multiple abnormalities are crucial steps in the interpretation of chest X-rays (CXRs); however, the lack of a large CXR dataset with bounding boxes severely constrains accurate localization research based on deep learning. We created a large CXR dataset named CXR-AL14, containing 165,988 CXRs and 253,844 bounding boxes. On the basis of this dataset, a deep-learning-based framework was developed to identify and localize 14 common abnormalities and calculate the cardiothoracic ratio (CTR) simultaneously. The mean average precision values obtained by the model for 14 abnormalities reached 0.572-0.631 with an intersection-over-union threshold of 0.5, and the intraclass correlation coefficient of the CTR algorithm exceeded 0.95 on the held-out, multicentre and prospective test datasets. This framework shows an excellent performance, good generalization ability and strong clinical applicability, which is superior to senior radiologists and suitable for routine clinical settings.

Clinical Application of MRI in Coronavirus Disease 2019: A Bibliometric Analysis.

BACKGROUND: Currently, coronavirus disease 2019 (COVID-19) continues to remain in the pandemic stage, leading to severe challenges in the global public healthcare system. Magnetic resonance imaging (MRI) methods have played an important role in the diagnosis of COVID-19 and the structural evaluation of the affected organs. Reviewing and summarizing the application of MRI has significant clinical implications for COVID-19. OBJECTIVE: The study aimed to analyze literature related to the application of MRI in COVID-19 using bibliometric tools, to explore the research status, hotspots, and developmental trends in this field, and to provide a reference for the application of MRI in the clinical diagnosis and evaluation of COVID-19. METHODS: We used the Web of Science Core Collection database to search and collect relevant literature on the use of MRI in COVID-19. The authors, institutes, countries, journals, and keyword modules of the bibliometric analysis software CiteSpace and VOSviewer were used to analyze and plot the network map. RESULTS: A total of 1506 relevant articles were shortlisted through the search; the earliest study was published in 2019, showing an overall upward trend every year. The research was mainly presented as published articles. Clinical neurology was found to be the primary discipline. The United States had the highest publication volume and influence in this field. Countries around the world cooperated more closely. The Cureus Journal of Medical Science was the main periodical to publish articles. Institutes, such as Harvard Medical School, Mayo Clinic, and Massachusetts General Hospital, have published a large number of papers. Some of the high-frequency keywords were "COVID-19", "SARS-CoV-2", "magnetic resonance", "myocarditis", and "cardiac magnetic resonance imaging". The keyword clustering study showed that the current research mainly focuses on five "hot" directions. CONCLUSION: There is a need to strengthen cross-teamwork and multidisciplinary collaboration in the future to completely explore the positive role of MRI in COVID-19 and to discover breakthroughs for the challenges in the clinical diagnosis and treatment of COVID-19.

Identifying virulence factors using graph transformer autoencoder with ESMFold-predicted structures.

With the increasing resistance of bacterial pathogens to conventional antibiotics, antivirulence strategies targeting virulence factors (VFs) have become an effective new therapy for the treatment of pathogenic bacterial infections. Therefore, the identification and prediction of VFs can provide ideal candidate targets for the implementation of antivirulence strategies in treating infections caused by pathogenic bacteria. Currently, the existing computational models predominantly rely on the amino acid sequences of virulence proteins while overlooking structural information. Here, we propose a novel graph transformer autoencoder for VF identification (GTAE-VF), which utilizes ESMFold-predicted 3D structures and converts the VF identification problem into a graph-level prediction task. In an encoder-decoder framework, GTAE-VF adaptively learns both local and global information by integrating a graph convolutional network and a transformer to implement all-pair message passing, which can better capture long-range correlations and potential relationships. Extensive experiments on an independent test dataset demonstrate that GTAE-VF achieves reliable and robust prediction accuracy with an AUC of 0.963, which is consistently better than that of other structure-based and sequence-based approaches. We believe that GTAE-VF has the potential to emerge as a valuable tool for assessing VFs and devising antivirulence strategies.