ITPRIPL1 binds CD3ε to impede T cell activation and enable tumor immune evasion.

Cancer immunotherapy has transformed treatment possibilities, but its effectiveness differs significantly among patients, indicating the presence of alternative pathways for immune evasion. Here, we show that ITPRIPL1 functions as an inhibitory ligand of CD3ε, and its expression inhibits T cells in the tumor microenvironment. The binding of ITPRIPL1 extracellular domain to CD3ε on T cells significantly decreased calcium influx and ZAP70 phosphorylation, impeding initial T cell activation. Treatment with a neutralizing antibody against ITPRIPL1 restrained tumor growth and promoted T cell infiltration in mouse models across various solid tumor types. The antibody targeting canine ITPRIPL1 exhibited notable therapeutic efficacy against naturally occurring tumors in pet clinics. These findings highlight the role of ITPRIPL1 (or CD3L1, CD3ε ligand 1) in impeding T cell activation during the critical "signal one" phase. This discovery positions ITPRIPL1 as a promising therapeutic target against multiple tumor types.

Legionella effectors SidC/SdcA ubiquitinate multiple small GTPases and SNARE proteins to promote phagosomal maturation.

Protein ubiquitination is one of the most important posttranslational modifications (PTMs) in eukaryotes and is involved in the regulation of almost all cellular signaling pathways. The intracellular bacterial pathogen Legionella pneumophila translocates at least 26 effectors to hijack host ubiquitination signaling via distinct mechanisms. Among these effectors, SidC/SdcA are novel E3 ubiquitin ligases with the adoption of a Cys-His-Asp catalytic triad. SidC/SdcA are critical for the recruitment of endoplasmic reticulum (ER)-derived vesicles to the Legionella-containing vacuole (LCV). However, the ubiquitination targets of SidC/SdcA are largely unknown, which restricts our understanding of the mechanisms used by these effectors to hijack the vesicle trafficking pathway. Here, we demonstrated that multiple Rab small GTPases and target soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNARE) proteins are bona fide ubiquitination substrates of SidC/SdcA. SidC/SdcA-mediated ubiquitination of syntaxin 3 and syntaxin 4 promotes their unconventional pairing with the vesicle-SNARE protein Sec22b, thereby contributing to the membrane fusion of ER-derived vesicles with the phagosome. In addition, our data reveal that ubiquitination of Rab7 by SidC/SdcA is critical for its association with the LCV membrane. Rab7 ubiquitination could impair its binding with the downstream effector Rab-interacting lysosomal protein (RILP), which partially explains why LCVs avoid fusion with lysosomes despite the acquisition of Rab7. Taken together, our study reveals the biological mechanisms employed by SidC/SdcA to promote the maturation of the LCVs.

Ultrasound had high accuracy in measuring hip joint capsule thickness.

BACKGROUND: The hip joint capsule is an essential component of hip joint function and stability, and its thickness is closely associated with certain medical conditions, surgical outcomes, and rehabilitation treatments. Currently, in clinical practice, hip joint capsule thickness is predominantly measured using magnetic resonance imaging (MRI), with limited utilization of ultrasound examinations for this purpose. METHODS: We retrospectively evaluated patients who visited our Sports Medicine Department between February 2017 and March 2023 and underwent both hip joint MRI and ultrasound imaging on the same side. All patients had undergone preoperative hip joint MRI and ultrasound examinations, with the time gap between the two examinations not exceeding three months. Measurements of hip joint capsule thickness were taken on both MRI and ultrasound images for the same patients to analyze their consistency. Additionally, we measured the alpha angle, lateral center-edge angle, acetabular anteversion angle, and femoral anteversion angle of the patients' hip joints and analyzed their correlation with hip joint capsule thickness measure by ultrasound. RESULTS: A total of 307 patients were included in this study, with hip joint capsule thickness measured by MRI and ultrasound being 5.0 ± 1.2 mm and 5.0 ± 1.5 mm, respectively. The Bland-Altman analysis demonstrates good agreement or consistency. The paired t-test resulted in a p-value of 0.708, indicating no significant statistical difference between the two methods. The correlation analysis between acetabular anteversion angle and ultrasound-measured capsule thickness yielded a p-value of 0.043, indicating acetabular anteversion angle and capsular thickness may have negative correlation. CONCLUSIONS: The measurements of joint capsule thickness obtained through ultrasound and MRI showed good consistency, suggesting that ultrasound can be used in clinical practice as a replacement for MRI in measuring hip joint capsule thickness. There was a significant correlation between acetabular anteversion angle and hip joint capsule thickness, indicating potential for further research in this area.

Quantitative imaging for predicting hematoma expansion in intracerebral hemorrhage: A multimodel comparison.

BACKGROUND: Several studies report that radiomics provides additional information for predicting hematoma expansion in intracerebral hemorrhage (ICH). However, the comparison of diagnostic performance of radiomics for predicting revised hematoma expansion (RHE) remains unclear. METHODS: The cohort comprised 312 consecutive patients with ICH. A total of 1106 radiomics features from seven categories were extracted using Python software. Support vector machines achieved the best performance in both the training and validation datasets. Clinical factors models were constructed to predict RHE. Receiver operating characteristic curve analysis was used to assess the abilities of non-contrast computed tomography (NCCT) signs, radiomics features, and combined models to predict RHE. RESULTS: We finally selected the top 21 features for predicting RHE. After univariate analysis, 4 clinical factors and 5 NCCT signs were selected for inclusion in the prediction models. In the training and validation dataset, radiomics features had a higher predictive value for RHE (AUC = 0.83) than a single NCCT sign and expansion-prone hematoma. The combined prediction model including radiomics features, clinical factors, and NCCT signs achieved higher predictive performances for RHE (AUC = 0.88) than other combined models. CONCLUSIONS: NCCT radiomics features have a good degree of discrimination for predicting RHE in ICH patients. Combined prediction models that include quantitative imaging significantly improve the prediction of RHE, which may assist in the risk stratification of ICH patients for anti-expansion treatments.

Set stabilization of logical control networks: A minimum node control approach.

In network systems, control using minimum nodes or pinning control can be effectively used for stabilization problems to cut down the cost of control. In this paper, we investigate the set stabilization problem of logical control networks. In particular, we study the set stabilization problem of probabilistic Boolean networks (PBNs) and probabilistic Boolean control networks (PBCNs) via controlling minimal nodes. Firstly, an algorithm is given to search for the minimum index set of pinning nodes. Then, based on the analysis of its high computational complexity, we present optimized algorithms with lower computational complexity to ascertain the network control using minimum node sets. Moreover, some sufficient and necessary conditions are proposed to ensure the feasibility and effectiveness of the proposed algorithms. Furthermore, a theorem is presented for PBCNs to devise all state-feedback controllers corresponding to the set of pinning nodes. Finally, two models of gene regulatory networks are considered to show the efficacy of obtained results.

Hip Rotation and Femoral Anteversion and Its Influence on Traction Force of the Pulled Limb in Hip Arthroscopy.

Background: Several variables may affect the traction force during hip arthroscopy. Specifically, the degree of hip joint rotation may influence the magnitude of traction force during hip arthroscopy. However, there is currently limited research available on this particular issue. Purpose: To quantify the traction force applied to the pulled limb in various traction states and rotational positions. Additionally, the study aimed to investigate potential correlations between femoral anteversion, BMI, anesthesia methods, and the traction force required for hip dislocation. Hypothesis: It was hypothesized that traction force in different traction states and rotational positions would be different and that femoral anteversion, body mass index (BMI), and anesthesia methods may influence the traction force needed. Study Design: Cross-sectional study; Level of evidence, 4. Methods: Patients who attended the sports medicine clinic of our department and underwent arthroscopic surgery for the diagnosis of femoroacetabular impingement between June and December 2022 were retrospectively evaluated. The traction force at the following 6 key timepoints was measured-initial traction, traction to the operable width, after joint puncture, after capsulotomy, at 20 minutes after capsulotomy, and at 40 minutes after capsulotomy. In each state, the hip was rotated to the internal rotational position, external rotational position, and neutral position. The traction force at different states and positions was recorded and analyzed. The differences in traction force between the different joint capsular physical states and rotational positions were tested by analysis of variance and the Tukey method. The Pearson test was used to analyze the correlation between BMI and femoral anteversion in different groups. Results: A total of 41 patients were included in this study. The traction force increased after reaching the operable width and decreased significantly after capsulotomy (P < .05). Thereafter, the traction force decreased gradually over time (P < .05). Traction force in the external and internal rotational positions was significantly greater than that in the neutral position, across all states of traction (P < .05). Furthermore, the difference in traction force between the internal and neutral positions, as well as the difference in traction force between the external and neutral positions, was found to be significantly greater than the difference in traction force between the internal and external rotational positions in all traction states (P < .05). The difference between the traction forces in different rotational positions of the hip joint exhibited a negative correlation with femoral anteversion (Pearson correlation coefficient of neutral-internal in states 3, 4, and 5 was -0.33, -0.31, -0.31, respectively; P < .05) and a positive correlation with BMI (Pearson correlation coefficient of external-neutral in states 4 and 6 was 0.33 and 0.36, respectively; P < .05). Conclusion: Our findings show that the traction force decreased after joint puncture and capsulotomy and decreased over time during surgery. External or internal rotation increased the traction force. Patients with higher femoral anteversion or lower BMI may need lower traction force. These data may help in minimizing traction forces to help prevent complications due to traction during hip arthroscopy.

Trans-electrode pressure of gas-diffusion electrodes significantly influencing the electrochemical hydrogen peroxide production.

Hydrogen peroxide (H2O2) synthesis by electrochemical two-electron oxygen reduction has garnered increasing interest as a wide range of potential applications. Gas diffusion electrodes (GDEs) can effectively promote the H2O2 production efficiency by overcoming the oxygen mass transfer limitations but strongly influenced by the electrowetting process along the long-term operation. In this study, the effect of trans-electrode pressure (TEP) of GDE cathode on the electrowetting process was further elucidated. We controlled the TEP values of four types of GDEs: two Ni-based GDEs and two carbon cloth GDEs prepared by hot-pressing or brushing carbon black. SBA-15 was further used to regulate the microstructure of one Ni-based GDE. It was found that an optimal range of TEP occurred for all tested GDEs in terms of the max. concentration, the yield efficiency, the energy consumption, and the stability because TEP may change the triple-phase interface and influence the anti-electrowetting effect. The porosity of hot-pressed Ni GDE can maintain the TEP window and thus enhance the production of H2O2, likely via creating oxygen-containing functional groups and a bimodal pore structure on the electrode, revealed with several characterization techniques including SEM, CA, XPS, Raman spectra, CV and EIS. The porous Ni GDE presented an efficient and stable production of H2O2 for 10 cycles: yielding H2O2 at 4393.2-4602.2 mmol m-2 h-1 with current efficiencies of 94.2-98.7%. The best accumulated H2O2 concentration can reach up to 3.58 ωt% H2O2 at 10 h. The results provide an important reference for the industrial scaleup of electro-production of H2O2 with GDEs.

Deep learning-assisted diagnosis of large vessel occlusion in acute ischemic stroke based on four-dimensional computed tomography angiography.

Purpose: To develop deep learning models based on four-dimensional computed tomography angiography (4D-CTA) images for automatic detection of large vessel occlusion (LVO) in the anterior circulation that cause acute ischemic stroke. Methods: This retrospective study included 104 LVO patients and 105 non-LVO patients for deep learning models development. Another 30 LVO patients and 31 non-LVO patients formed the time-independent validation set. Four phases of 4D-CTA (arterial phase P1, arterial-venous phase P2, venous phase P3 and late venous phase P4) were arranged and combined and two input methods was used: combined input and superimposed input. Totally 26 models were constructed using a modified HRNet network. Assessment metrics included the areas under the curve (AUC), accuracy, sensitivity, specificity and F1 score. Kappa analysis was performed to assess inter-rater agreement between the best model and radiologists of different seniority. Results: The P1 + P2 model (combined input) had the best diagnostic performance. In the internal validation set, the AUC was 0.975 (95%CI: 0.878-0.999), accuracy was 0.911, sensitivity was 0.889, specificity was 0.944, and the F1 score was 0.909. In the time-independent validation set, the model demonstrated consistently high performance with an AUC of 0.942 (95%CI: 0.851-0.986), accuracy of 0.902, sensitivity of 0.867, specificity of 0.935, and an F1 score of 0.901. The best model showed strong consistency with the diagnostic efficacy of three radiologists of different seniority (k = 0.84, 0.80, 0.70, respectively). Conclusion: The deep learning model, using combined arterial and arterial-venous phase, was highly effective in detecting LVO, alerting radiologists to speed up the diagnosis.

Discovery of galectin-8 as an LILRB4 ligand driving M-MDSCs defines a class of antibodies to fight solid tumors.

LILRB4 is an immunosuppressive receptor, and its targeting drugs are undergoing multiple preclinical and clinical trials. Currently, the absence of a functional LILRB4 ligand in solid tumors not only limits the strategy of early antibody screening but also leads to the lack of companion diagnostic (CDx) criteria, which is critical to the objective response rate in early-stage clinical trials. Here, we show that galectin-8 (Gal-8) is a high-affinity functional ligand of LILRB4, and its ligation induces M-MDSC by activating STAT3 and inhibiting NF-κB. Significantly, Gal-8, but not APOE, can induce MDSC, and both ligands bind LILRB4 noncompetitively. Gal-8 expression promotes in vivo tumor growth in mice, and the knockout of LILRB4 attenuates tumor growth in this context. Antibodies capable of functionally blocking Gal-8 are able to suppress tumor growth in vivo. These results identify Gal-8 as an MDSC-driving ligand of LILRB4, and they redefine a class of antibodies for solid tumors.

A Novel 3D-Printed Negative-Stiffness Lattice Structure with Internal Resonance Characteristics and Tunable Bandgap Properties.

The bandgap tuning potential offered by negative-stiffness lattice structures, characterized by their unique mechanical properties, represents a promising and burgeoning field. The potential of large deformations in lattice structures to transition between stable configurations is explored in this study. This transformation offers a novel method for modifying the frequency range of elastic wave attenuation, simultaneously absorbing energy and effectively generating diverse bandgap ranges. In this paper, an enhanced lattice structure is introduced, building upon the foundation of the normal negative-stiffness lattice structures. The research examined the behavior of the suggested negative-stiffness lattice structures when subjected to uniaxial compression. This included analyzing the dispersion spectra and bandgaps across different states of deformation. It also delved into the effects of geometric parameter changes on bandgap properties. Furthermore, the findings highlight that the normal negative-stiffness lattice structure demonstrates restricted capabilities in attenuating vibrations. In contrast, notable performance improvements are displayed by the improved negative-stiffness lattice structure, featuring distinct energy band structures and variable bandgap ranges in response to differing deformation states. This highlights the feasibility of bandgap tuning through the deformation of negatively stiffened structures. Finally, the overall metamaterial structure is simulated using a unit cell finite element dynamic model, and its vibration transmission properties and frequency response patterns are analyzed. A fresh perspective on the research and design of negative-stiffness lattice structures, particularly focusing on their bandgap tuning capabilities, is offered in this study.

Effect of berberine on cognitive function and ß-amyloid precursor protein in Alzheimer's disease models: a systematic review and meta-analysis.

Introduction: Berberine is an isoquinoline alkaloid extracted from Berberis vulgaris, which possesses a variety of pharmacological activities. Alzheimer's disease (AD) is a complex disease with multiple pathologic factors, with cognitive decline being the main manifestation of AD. The neuroprotective effects of berberine in animal models of Alzheimer's disease (AD) have been widely reported, exhibiting protective effects against risk factors associated with AD. In this study, we summarize and evaluate the effects of berberine on cognitive function and ß-amyloid precursor protein in animal models of AD. Material and methods: Eligible studies were retrieved from PubMed, MEDLINE, EMBASE, Web of Science, and Cochrane Library databases up to 1 June 2023. Risk of bias was assessed by the Systematic Review Center for Laboratory Animal Experiments (SYRCLE). Statistical analyses were performed using STATA 14.0 and Review Manger 5.4 software to calculate weighted standardized mean difference (SMD) and 95% confidence intervals (CI), Morris water maze (MWM) test and ß-amyloid precursor protein as outcome measures. Heterogeneity was tested using the I2 test. Sensitivity analysis and publication bias were also assessed. Results: 19 studies involving 360 animals met the inclusion criteria, and the results of the meta-analysis showed that berberine decreased escape latency (SMD = -2.19, 95% CI: (-2.50, -1.88), p < 0.00001), increased the number of platform crossings (SMD = 4.27, 95% CI (3.38, 5.17), p < 0.00001), time in the target quadrant (SMD = 5.92, 95% CI (4.43, 7.41), p < 0.00001) and APP expression (SMD = 0.73, 95% CI: (0.25, 1.21), p = 0.003). Conclusion: Berberine can regulate APP expression and improve cognitive function in animal models of AD, and the mechanism may be related to the involvement of berberine in APP processing and influence the expression of its related factors. Systematic review registration: PROSPERO, CRD42023437445.