Bispecific antibodies promote natural killer cell-mediated elimination of HIV-1 reservoir cells.

The persistence of CD4+ T cells carrying latent human immunodeficiency virus-1 (HIV-1) proviruses is the main barrier to a cure. New therapeutics to enhance HIV-1-specific immune responses and clear infected cells will probably be necessary to achieve reduction of the latent reservoir. In the present study, we report two single-chain diabodies (scDbs) that target the HIV-1 envelope protein (Env) and the human type III Fcγ receptor (CD16). We show that the scDbs promoted robust and HIV-1-specific natural killer (NK) cell activation and NK cell-mediated lysis of infected cells. Cocultures of CD4+ T cells from people with HIV-1 on antiretroviral therapy (ART) with autologous NK cells and the scDbs resulted in marked elimination of reservoir cells that was dependent on latency reversal. Treatment of human interleukin-15 transgenic NSG mice with one of the scDbs after ART initiation enhanced NK cell activity and reduced reservoir size. Thus, HIV-1-specific scDbs merit further evaluation as potential therapeutics for clearance of the latent reservoir.

NFTest: automated testing of Nextflow pipelines.

MOTIVATION: The ongoing expansion in the volume of biomedical data has contributed to a growing complexity in the tools and technologies used in research with an increased reliance on complex workflows written in orchestration languages such as Nextflow to integrate algorithms into processing pipelines. The growing use of workflows involving various tools and algorithms has led to increased scrutiny of software development practices to avoid errors in individual tools and in the connections between them. RESULTS: To facilitate test-driven development of Nextflow pipelines, we created NFTest, a framework for automated pipeline testing and validation with customizability options for Nextflow features. It is open-source, easy to initialize and use, and customizable to allow for testing of complex workflows with test success configurable through a broad range of assertions. NFTest simplifies the testing burden on developers by automating tests once defined and providing a flexible interface for running tests to validate workflows. This reduces the barrier to rigorous biomedical workflow testing and paves the way toward reducing computational errors in biomedicine. AVAILABILITY AND IMPLEMENTATION: NFTest is an open-source Python framework under the GPLv2 license and is freely available at https://github.com/uclahs-cds/tool-NFTest. The call-sSNV Nextflow pipeline is available at: https://github.com/uclahs-cds/pipeline-call-sSNV.

Restricted Growth of Vinylene-Linked Covalent Organic Frameworks along Two-Dimensional Plane Using Heterogeneous Catalysis.

The vinylene-linked covalent organic frameworks (viCOFs) have been generally synthesized in the presence of homogeneous catalysts such as KOH or trifluoroacetic acid. However, highly ordered viCOFs cannot always be obtained due to the uncommitted growth of viCOF layers in the homogeneous system with ubiquitous catalysts. Here, we propose a scalable protocol to restrict the growth of viCOFs along the two-dimensional (2D) plane by introducing a heterogeneous catalyst, polyoxometalates (POMs). With the unique Brønsted alkalinity and catalytic surface, POMs induce the growth of 2D viCOF layers along the surface of the catalytic substrate and restrain the generation of out-of-plane branches. Based on this protocol, six typical 2D viCOFs with high crystallinity and porosity were synthesized within a shorter reaction time as compared with the reported works using the common homogeneous catalysts for viCOF synthesis. On the basis of the density functional theory calculations and experimental results, a bottom intercalation growth pattern of viCOFs was revealed during the heterogeneous reaction. The unique growth pattern greatly promotes the orderly assembly of monomers, thus shortening the reaction time and improving the crystallinity of viCOFs. Furthermore, this heterogeneous catalysis strategy is suitable for the gram-scale preparation of 2D viCOFs. These results provide a novel avenue for the synthesis of high-quality viCOFs and may bring new insights into the synthetic methodology of COFs.

[Risk factors for embolism in children with refractory Mycoplasmapneumoniae pneumonia and construction of a nomogram model for prediction of embolism]. / éš¾æ²»æ€§è‚ºç‚Žæ”¯åŽŸä½“è‚ºç‚Žæ‚£å„¿åˆå¹¶æ “å¡žçš„å±é™©å› ç´ åˆ†æžåŠåˆ—çº¿å›¾é¢„æµ‹æ¨¡åž‹çš„æž„å»º.

OBJECTIVES: To study the risk factors for embolism in children with refractory Mycoplasma pneumoniae pneumonia (RMPP) and to construct a nomogram model for prediction of embolism. METHODS: This retrospective study included 175 children diagnosed with RMPP at Children's Hospital Affiliated toZhengzhou University from January 2019 to October 2023. They were divided into two groups based on the presence of embolism: the embolism group (n=62) and the non-embolism group (n=113). Multivariate logistic regression analysis was used to screen for risk factors of embolism in children with RMPP, and the R software was applied to construct the nomogram model for prediction of embolism. RESULTS: Multivariate logistic regression analysis indicated that higher levels of D-dimer, interleukin-6 (IL-6) and neutrophil to lymphocyte ratio (NLR), lung necrosis, and pleural effusion were risk factors for embolism in children with RMPP (P<0.05). The area under the curve of the nomogram model for prediction of embolism constructed based on the aforementioned risk factors was 0.912 (95%CI: 0.871-0.952, P<0.05). The Hosmer-Lemeshow goodness-of-fit test showed that the model had a good fit with the actual situation (P<0.05). Calibration and decision curve analysis indicated that the model had high predictive efficacy and clinical applicability. CONCLUSIONS: Higher levels of D-dimer, IL-6 and NLR, lung necrosis, and pleural effusion are risk factors for embolism in children with RMPP. The nomogram model based on these risk factors has high clinical value for predicting embolism in children with RMPP.

Predictive Value of Preoperative Peripheral Blood Inflammatory Markers for Surgical Site Infection in Laparoscopic Radical Gastrectomy for Gastric Cancer.

Background: To investigate the predictive value of preoperative peripheral blood inflammatory markers for surgical site infection (SSI) in laparoscopic radical gastrectomy for gastric cancer. Methods: A retrospective analysis was conducted on patients undergoing laparoscopic radical gastrectomy for gastric cancer, categorized into SSI and non-SSI groups based on postoperative SSI occurrences. Patient demographics, surgical details, laboratory results, and SSI incidence data were extracted. Differences in indicators, including neutrophil-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and platelet-lymphocyte ratio (PLR), were assessed between the two groups. Multivariate logistic regression was utilized to determine the independent association of each indicator with SSI. Receiver operating characteristics (ROC) curve analysis was utilized to evaluate the predictive value of parameters. Results: Of 169 patients, 36 (21.30%) experienced SSI postoperatively. The SSI group exhibited higher preoperative NLR and SII (p < 0.05). After adjusting for variables, preoperative NLR (OR = 1.691, 95% CI: 1.211-2.417, p = 0.003) and SII (OR = 1.001, 95% CI: 1.000-1.002, p = 0.006) were identified as independent risk factors for SSI. Both NLR (AUC = 0.758, 95% CI: 0.666-0.850) and SII (AUC = 0.753, 95% CI: 0.660-0.850) demonstrated favorable diagnostic performance for predicting postoperative SSI. Conclusion: Preoperative NLR and SII significantly associate with postoperative SSI in laparoscopic radical gastrectomy for gastric cancer, making them valuable indicators for early prediction of SSI.

Association between the composite dietary antioxidant index and metabolic dysfunction-associated steatotic liver disease in adults: a cross-sectional study from NHANES 2017-2020.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as a predominant liver disease worldwide, lacking approved drugs for clinical intervention at present. The composite dietary antioxidant index (CDAI) is used to assess the anti-inflammatory properties of diets, with higher CDAI indicating greater exposure to antioxidants. Therefore, our study aimed to explore the relationship between CDAI and MASLD in order to identify potential therapeutic approaches. We collected data from 12,286 participants in the National Health and Nutrition Examination Survey (NHANES) database from 2017 to 2020 for analysis. The correlation between CDAI and MASLD status, controlled attenuation parameter (CAP), and liver stiffness measurement (LSM) was evaluated by adjusting for confounding variables using weighted binary logistic regression model, linear regression model, and restricted cubic spline (RCS) regression. The median CDAI in this study was - 0.3055 (interquartile range [IQR], - 2.299 to 2.290). The CDAI was higher in the population characterized by being young, female, higher income, absence of diabetes, and non-MASLD. After multivariable adjustment, the results of the weighted linear regression model suggested that higher CDAI may be associated with a decrease in CAP values; the results of the RCS regression model indicated significant non-linear relationships between MASLD status, CAP, LSM, and CDAI. The CDAI corresponding to the inflection points of the relationship curves between MASLD status, CAP, LSM, and CDAI were 0.349, 0.699, and 0.174, respectively. After further stratification by gender, we found that the relationship between MASLD status, CAP, and CDAI was significantly linear for females, whereas for males, it was non-linear, and the CDAI values corresponding to the inflection points in the curves for males were 1.325 and 0.985, respectively. We found that higher CDAI may be associated with decreased CAP values, particularly significant in females, suggesting that the intake of complex dietary antioxidants may ameliorate hepatic steatosis and reduce the occurrence of MASLD. Therefore, promoting dietary patterns rich in antioxidants may be an appropriate strategy to reduce the incidence of MASLD.

Does vegetation greening have a positive effect on global vegetation carbon and water use efficiency?

Terrestrial ecosystems have undergone significant changes as a result of climate change, profoundly affecting global carbon and water cycling processes. Notably, the synergistic changes in vegetation carbon use efficiency (CUE) and water use efficiency (WUE) and their response to patterns of climate change over the last 40 years are unknown. Therefore, in this study, global vegetation WUE and CUE were inverted using Gross primary productivity (GPP), Net primary productivity (NPP) and total evaporation (ET) data from 1981 to 2019 to reveal their temporal and spatial patterns of change through trend analysis and stability analysis. A stepwise regression algorithm was used to reveal the potential driving law of environmental factors on vegetation WUE and CUE. The results shows that (1) From 1981 to 2019, the global vegetation WUE and CUE showed in a relatively stable state, and the trends of WUE and CUE were -0.00004/year and 0.006 g C m-2 mm-1/year, respectively; (2) the greening of vegetation was the most important cause of the changes in WUE and CUE, and the driving force of rain and heat conditions on the CUE of vegetation was smaller than that of solar radiation and soil water, the regions where CO2 is the dominant factor affecting CUE and WUE are mainly in the north temperate zone; (3) the region of synergistic growth of WUE and CUE accounts for about 31.38 % of the global terrestrial area, and this pattern of change suggests that the global vegetation carbon sink potential is huge, and the popularization of vegetation planting patterns under the synergistic growth of CUE and WUE should be strengthened. The research has shown that vegetation greening is a key factor influencing changes in the WUE and CUE of vegetation, therefore, the implementation of ecological engineering will be an important step in combating climate change.

Sustainable remediation of Cr(VI)-contaminated soil by soil washing and subsequent recovery of washing agents using biochar supported nanoscale zero-valent iron.

Soil contamination by Cr(VI) has attracted widespread attention globally in recent years, but it remains a significant challenge in developing an environmentally friendly and eco-sustainable technique for the disposal of Cr(VI)-contaminated soil. Herein, a sustainable cyclic soil washing system for Cr(VI)-polluted soil remediation and the recovery of washing agents using biochar supported nanoscale zero-valent iron (nZVI-BC) was established. Citric acid (CA) was initially screened to desorb Cr(VI) from contaminated soil, mobilizing Cr from the highly bioaccessible fractions. The nZVI-BC exhibited superior properties for Cr(VI) and Cr(total) removal from spent effluent, allowing effective recovery of the washing agents. The elimination mechanism of Cr(total) by nZVI-BC involved the coordinated actions of electrostatic adsorption, reduction, and co-precipitation. The contributions to Cr(VI) reduction by Fe0, surface-bound Fe(II), and soluble Fe(II) were 0.6 %, 39.8 %, and 59.6 %, respectively. Meanwhile, CA favored the activity of surface-bound Fe(II) and Fe0 in nZVI-BC, enhancing the production of soluble Fe(II) to strengthen Cr(VI) removal. Finally, the recovered washing agent was proven to be reused three times. This study showcases that the combined soil washing using biodegradable chelant CA and effluent treatment by nZVI-BC could be a sustainable and promising strategy for Cr(VI)-contaminated soil remediation.

Nomogram model for predicting invasive placenta in patients with placenta previa: integrating MRI findings and clinical characteristics.

This study aims to validate a nomogram model that predicts invasive placenta in patients with placenta previa, utilizing MRI findings and clinical characteristics. A retrospective analysis was conducted on a training cohort of 269 patients from the Second Affiliated Hospital of Fujian Medical University and a validation cohort of 41 patients from Quanzhou Children's Hospital. Patients were classified into noninvasive and invasive placenta groups based on pathological reports and intraoperative findings. Three clinical characteristics and eight MRI signs were collected and analyzed to identify risk factors and develop the nomogram model. The mode's performance was evaluated in terms of its discrimination, calibration, and clinical utility. Independent risk factors incorporated into the nomogram included the number of previous cesarean sections ≥ 2 (odds ratio [OR] 3.32; 95% confidence interval [CI] 1.28-8.59), type-II placental bulge (OR 17.54; 95% CI 3.53-87.17), placenta covering the scar (OR 2.92; CI 1.23-6.96), and placental protrusion sign (OR 4.01; CI 1.06-15.18). The area under the curve (AUC) was 0.908 for the training cohort and 0.803 for external validation. The study successfully developed a highly accurate nomogram model for predicting invasive placenta in placenta previa cases, based on MRI signs and clinical characteristics.

Surgical Treatment of Brucellar Cervical Epidural Abscess.

OBJECTIVES: Brucellar cervical epidural abscess (CEA) is a rare condition with potentially permanent neurological damage if left untreated. This study aims to define the clinical presentation of brucellar CEA and evaluate the outcome of surgical treatment, specifically decompression and fusion surgery. The findings will contribute to understanding whether all patients with brucellar CEA could benefit from this surgical intervention. METHODS: A retrospective study on brucellar spondylitis was conducted at the First Hospital of Jilin University from August 2018 to August 2022. During this period, a total of 37 patients were diagnosed with brucellar spondylitis at the hospital. Out of the 37 cases, six patients (16.2%) were confirmed to have CEA through cervical magnetic resonance imaging examination and serology test results.. RESULTS: Six patients were diagnosed with brucellar CEA (16.2%), of whom 5 successfully underwent anterior cervical decompression and fusion surgery. One patient had a large prevertebral abscess that could only be drained. In combination with effective antibiotic therapy, the clinical performance of the 5 patients who underwent surgery improved after the surgery. The remaining one patient required delayed surgery due to instability of the cervical spine. The follow-up period of all the 6 patients was 6 months. CONCLUSIONS: Brucellosis should be considered as a potential cause of CEA, especially in endemic areas. Timely detection and effective management of this condition are crucial in order to minimize the associated morbidity and mortality. For patients with detectable brucellar CEA, we recommend decompression and fusion surgery.

Research on automatic recognition radiomics algorithm for early sacroiliac arthritis based on sacroiliac MRI imaging.

OBJECTIVE: To create an automated machine learning model using sacroiliac joint MRI imaging for early sacroiliac arthritis detection, aiming to enhance diagnostic accuracy. METHODS: We conducted a retrospective analysis involving 71 patients with early sacroiliac arthritis and 85 patients with normal sacroiliac joint MRI scans. Transverse T1WI and T2WI sequences were collected and subjected to radiomics analysis by two physicians. Patients were randomly divided into training and test groups at a 7:3 ratio. Initially, we extracted the region of interest on the sacroiliac joint surface using ITK-SNAP 3.6.0 software and extracted radiomic features. We retained features with an Intraclass Correlation Coefficient > 0.80, followed by filtering using max-relevance and min-redundancy (mRMR) and LASSO algorithms to establish an automatic identification model for sacroiliac joint surface injury. Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC) was calculated. Model performance was assessed by accuracy, sensitivity, and specificity. RESULTS: We evaluated model performance, achieving an AUC of 0.943 for the SVM-T1WI training group, with accuracy, sensitivity, and specificity values of 0.878, 0.836, and 0.943, respectively. The SVM-T1WI test group exhibited an AUC of 0.875, with corresponding accuracy, sensitivity, and specificity values of 0.909, 0.929, and 0.875, respectively. For the SVM-T2WI training group, the AUC was 0.975, with accuracy, sensitivity, and specificity values of 0.933, 0.889, and 0.750. The SVM-T2WI test group produced an AUC of 0.902, with accuracy, sensitivity, and specificity values of 0.864, 0.889, and 0.800. In the SVM-bimodal training group, we achieved an AUC of 0.974, with accuracy, sensitivity, and specificity values of 0.921, 0.889, and 0.971, respectively. The SVM-bimodal test group exhibited an AUC of 0.964, with accuracy, sensitivity, and specificity values of 0.955, 1.000, and 0.875, respectively. CONCLUSION: The radiomics-based detection model demonstrates excellent automatic identification performance for early sacroiliitis.

Colossal anisotropic absorption of spin currents induced by chirality.

The chiral induced spin selectivity (CISS) effect, in which the structural chirality of a material determines the preference for the transmission of electrons with one spin orientation over that of the other, is emerging as a design principle for creating next-generation spintronic devices. CISS implies that the spin preference of chiral structures persists upon injection of pure spin currents and can act as a spin analyzer without the need for a ferromagnet. Here, we report an anomalous spin current absorption in chiral metal oxides that manifests a colossal anisotropic nonlocal Gilbert damping with a maximum-to-minimum ratio of up to 1000%. A twofold symmetry of the damping is shown to result from differential spin transmission and backscattering that arise from chirality-induced spin splitting along the chiral axis. These studies reveal the rich interplay of chirality and spin dynamics and identify how chiral materials can be implemented to direct the transport of spin current.

Antisymmetric planar Hall effect in rutile oxide films induced by the Lorentz force.

The conventional Hall effect is linearly proportional to the field component or magnetization component perpendicular to a film. Despite the increasing theoretical proposals on the Hall effect to the in-plane field or magnetization in various special systems induced by the Berry curvature, such an unconventional Hall effect has only been experimentally reported in Weyl semimetals and in a heterodimensional superlattice. Here, we report an unambiguous experimental observation of the antisymmetric planar Hall effect (APHE) with respect to the in-plane magnetic field in centrosymmetric rutile RuO2 and IrO2 single-crystal films. The measured Hall resistivity is found to be linearly proportional to the component of the applied in-plane magnetic field along a particular crystal axis and to be independent of the current direction or temperature. Both the experimental observations and theoretical calculations confirm that the APHE in rutile oxide films is induced by the Lorentz force. Our findings can be generalized to ferromagnetic materials for the discovery of anomalous Hall effects and quantum anomalous Hall effects induced by in-plane magnetization. In addition to significantly expanding knowledge of the Hall effect, this work opens the door to explore new members in the Hall effect family.

Kinetically Controlled Synthesis of Metallic Glass Nanoparticles with Expanded Composition Space.

Nanoscale metallic glasses offer opportunities for investigating fundamental properties of amorphous solids and technological applications in biomedicine, microengineering, and catalysis. However, their top-down fabrication is limited by bulk counterpart availability, and bottom-up synthesis remains underexplored due to strict formation conditions. Here, a kinetically controlled flash carbothermic reaction is developed, featuring ultrafast heating (>105 K s-1) and cooling rates (>104 K s-1), for synthesizing metallic glass nanoparticles within milliseconds. Nine compositional permutations of noble metals, base metals, and metalloid (M1─M2─P, M1 = Pt/Pd, M2 = Cu/Ni/Fe/Co/Sn) are synthesized with widely tunable particle sizes and substrates. Through combinatorial development, a substantially expanded composition space for nanoscale metallic glass is discovered compared to bulk counterpart, revealing that the nanosize effect enhances glass forming ability. Leveraging this, several nanoscale metallic glasses are synthesized with composition that have never, to the knowledge, been synthesized in bulk. The metallic glass nanoparticles exhibit high activity in heterogeneous catalysis, outperforming crystalline metal alloy nanoparticles.

Minor envelope proteins from GP2a to GP4 contribute to the spread pattern and yield of type 2 PRRSV in MARC-145 cells.

In China, porcine reproductive and respiratory syndrome virus (PRRSV) vaccines are widely used. These vaccines, which contain inactivated and live attenuated vaccines (LAVs), are produced by MARC-145 cells derived from the monkey kidney cell line. However, some PRRSV strains in MARC-145 cells have a low yield. Here, we used two type 2 PRRSV strains (CH-1R and HuN4) to identify the genes responsible for virus yield in MARC-145 cells. Our findings indicate that the two viruses have different spread patterns, which ultimately determine their yield. By replacing the viral envelope genes with a reverse genetics system, we discovered that the minor envelope proteins, from GP2a to GP4, play a crucial role in determining the spread pattern and yield of type 2 PRRSV in MARC-145 cells. The cell-free transmission pattern of type 2 PRRSV appears to be more efficient than the cell-to-cell transmission pattern. Overall, these findings suggest that GP2a to GP4 contributes to the spread pattern and yield of type 2 PRRSV.

The value of CT-based radiomics in predicting hemorrhagic transformation in acute ischemic stroke patients without recanalization therapy.

Objective: The aim of this study is to investigate the clinical value of radiomics based on non-enhanced head CT in the prediction of hemorrhage transformation in acute ischemic stroke (AIS). Materials and methods: A total of 140 patients diagnosed with AIS from January 2015 to August 2022 were enrolled. Radiomic features from infarcted areas on non-enhanced CT images were extracted using ITK-SNAP. The max-relevance and min-redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) were used to select features. The radiomics signature was then constructed by multiple logistic regressions. The clinicoradiomics nomogram was constructed by combining radiomics signature and clinical characteristics. All predictive models were constructed in the training group, and these were verified in the validation group. All models were evaluated with the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results: Of the 140 patients, 59 experienced hemorrhagic transformation, while 81 remained stable. The radiomics signature was constructed by 10 radiomics features. The clinicoradiomics nomogram was constructed by combining radiomics signature and atrial fibrillation. The area under the ROC curve (AUCs) of the clinical model, radiomics signature, and clinicoradiomics nomogram for predicting hemorrhagic transformation in the training group were 0.64, 0.86, and 0.86, respectively. The AUCs of the clinical model, radiomics signature, and clinicoradiomics nomogram for predicting hemorrhagic transformation in the validation group were 0.63, 0.90, and 0.90, respectively. The DCA curves showed that the radiomics signature performed well as well as the clinicoradiomics nomogram. The DCA curve showed that the clinical application value of the radiomics signature is similar to that of the clinicoradiomics nomogram. Conclusion: The radiomics signature, constructed without incorporating clinical characteristics, can independently and effectively predict hemorrhagic transformation in AIS patients.

MARCH8 inhibits pseudorabies virus replication by trapping the viral cell-to-cell fusion complex in the trans-Golgi network.

The membrane-associated RING-CH 8 protein (MARCH8), a member of the E3 ubiquitin ligase family, has broad-spectrum antiviral activity. However, some viruses hijack MARCH8 to promote virus replication, highlighting its dual role in the viral lifecycle. Most studies on MARCH8 have focused on RNA viruses, leaving its role in DNA viruses largely unexplored. Pseudorabies virus (PRV) is a large DNA virus that poses a potential threat to humans. In this study, we found that MARCH8 inhibited PRV replication at the cell-to-cell fusion stage. Interestingly, our findings proved that MARCH8 blocks gB cleavage by recruiting furin but this activity does not inhibit viral infection in vitro. Furthermore, we confirmed that MARCH8 inhibits cell-to-cell fusion independent of its E3 ubiquitin ligase activity but dependent on the interaction with the cell-to-cell fusion complex (gB, gD, gH, and gL). Finally, we discovered that the distribution of the cell-to-cell fusion complex is significantly altered and trapped within the trans-Golgi network. Overall, our results indicate that human MARCH8 acts as a potent antiviral host factor against PRV via trapping the cell-to-cell fusion complex in the trans-Golgi network.

MARCH1 and MARCH2 inhibit pseudorabies virus replication by trapping the viral cell-to-cell fusion complex in trans-Golgi network.

The membrane-associated RING-CH (MARCH) family of proteins are members of the E3 ubiquitin ligase family and are essential for a variety of biological functions. Currently, MARCH proteins are discovered to execute antiviral functions by directly triggering viral protein degradation or blocking the furin cleavage of viral class I fusion proteins. Here, we report a novel antiviral mechanism of MARCH1 and MARCH2 (MARCH1/2) in the replication of Pseudorabies virus (PRV), a member of the Herpesviridae family. We discovered MARCH1/2 restrict PRV replication at the cell-to-cell fusion step. Furthermore, MARCH1/2 block gB cleavage, and this is dependent on their E3 ligase activity. Interestingly, the blocking of gB cleavage by MARCH1/2 does not contribute to their antiviral activity in vitro. We discovered that MARCH1/2 are associated with the cell-to-cell fusion complex of gB, gD, gH, and gL and trap these viral proteins in the trans-Golgi network (TGN) rather than degrading them. Overall, we conclude that MARCH1/2 inhibit PRV by trapping the viral cell-to-cell fusion complex in TGN.

Radiographic features of congenital thumb duplication type C2 of Wu et al. classification: new subtypes and surgical strategies.

Objective: This study aimed (i) to evaluate the radiographic characteristics of patients with congenital thumb duplication (CTD) type C2 according to the classification of Wu et al., (ii) to describe the various subtypes of type C2 CTD, and (iii) to propose a classification system that allows the identification of different surgical strategies based on the radiographic anatomy of this specific subtype of duplication. Methods: We retrospectively reviewed 92 patients (92 thumbs) with type C2 CTD according to the Wu et al. classification in our institution between August 2015 and April 2021. All CTDs were classified according to the interphalangeal joint alignment of the main thumb at the posteroanterior radiograph of the thumb before operation: type I (no deviation), type II (ulnar deviation), and type III (radial deviation). Results: All CTDs (n = 92) could be classified according to the proposed classification system: 76 (82.6%) were type I, 10 (10.9%) were type II, and six were type III (6.5%). According to the Kim system of subtype classification, there were 55 (59.8%) type 1, 24 (26.1%) type 2, and 13 (14.1%) type 3 cases. Conclusions: The suggested classification completes the Wu et al. system and has the potential to guide surgical treatment in children with type C2 CTD. Level of evidence: III.

Computer-Aided Diagnosis of Laryngeal Cancer Based on Deep Learning with Laryngoscopic Images.

Laryngeal cancer poses a significant global health burden, with late-stage diagnoses contributing to reduced survival rates. This study explores the application of deep convolutional neural networks (DCNNs), specifically the Densenet201 architecture, in the computer-aided diagnosis of laryngeal cancer using laryngoscopic images. Our dataset comprised images from two medical centers, including benign and malignant cases, and was divided into training, internal validation, and external validation groups. We compared the performance of Densenet201 with other commonly used DCNN models and clinical assessments by experienced clinicians. Densenet201 exhibited outstanding performance, with an accuracy of 98.5% in the training cohort, 92.0% in the internal validation cohort, and 86.3% in the external validation cohort. The area under the curve (AUC) values consistently exceeded 92%, signifying robust discriminatory ability. Remarkably, Densenet201 achieved high sensitivity (98.9%) and specificity (98.2%) in the training cohort, ensuring accurate detection of both positive and negative cases. In contrast, other DCNN models displayed varying degrees of performance degradation in the external validation cohort, indicating the superiority of Densenet201. Moreover, Densenet201's performance was comparable to that of an experienced clinician (Clinician A) and outperformed another clinician (Clinician B), particularly in the external validation cohort. Statistical analysis, including the DeLong test, confirmed the significance of these performance differences. Our study demonstrates that Densenet201 is a highly accurate and reliable tool for the computer-aided diagnosis of laryngeal cancer based on laryngoscopic images. The findings underscore the potential of deep learning as a complementary tool for clinicians and the importance of incorporating advanced technology in improving diagnostic accuracy and patient care in laryngeal cancer diagnosis. Future work will involve expanding the dataset and further optimizing the deep learning model.