GAPS: a geometric attention-based network for peptide binding site identification by the transfer learning approach.

Protein-peptide interactions (PPepIs) are vital to understanding cellular functions, which can facilitate the design of novel drugs. As an essential component in forming a PPepI, protein-peptide binding sites are the basis for understanding the mechanisms involved in PPepIs. Therefore, accurately identifying protein-peptide binding sites becomes a critical task. The traditional experimental methods for researching these binding sites are labor-intensive and time-consuming, and some computational tools have been invented to supplement it. However, these computational tools have limitations in generality or accuracy due to the need for ligand information, complex feature construction, or their reliance on modeling based on amino acid residues. To deal with the drawbacks of these computational algorithms, we describe a geometric attention-based network for peptide binding site identification (GAPS) in this work. The proposed model utilizes geometric feature engineering to construct atom representations and incorporates multiple attention mechanisms to update relevant biological features. In addition, the transfer learning strategy is implemented for leveraging the protein-protein binding sites information to enhance the protein-peptide binding sites recognition capability, taking into account the common structure and biological bias between proteins and peptides. Consequently, GAPS demonstrates the state-of-the-art performance and excellent robustness in this task. Moreover, our model exhibits exceptional performance across several extended experiments including predicting the apo protein-peptide, protein-cyclic peptide and the AlphaFold-predicted protein-peptide binding sites. These results confirm that the GAPS model is a powerful, versatile, stable method suitable for diverse binding site predictions.

Research on Monitoring Assistive Devices for Rehabilitation of Movement Disorders through Multi-Sensor Analysis Combined with Deep Learning.

This study aims to integrate a convolutional neural network (CNN) and the Random Forest Model into a rehabilitation assessment device to provide a comprehensive gait analysis in the evaluation of movement disorders to help physicians evaluate rehabilitation progress by distinguishing gait characteristics under different walking modes. Equipped with accelerometers and six-axis force sensors, the device monitors body symmetry and upper limb strength during rehabilitation. Data were collected from normal and abnormal walking groups. A knee joint limiter was applied to subjects to simulate different levels of movement disorders. Features were extracted from the collected data and analyzed using a CNN. The overall performance was scored with Random Forest Model weights. Significant differences in average acceleration values between the moderately abnormal (MA) and severely abnormal (SA) groups (without vehicle assistance) were observed (p < 0.05), whereas no significant differences were found between the MA with vehicle assistance (MA-V) and SA with vehicle assistance (SA-V) groups (p > 0.05). Force sensor data showed good concentration in the normal walking group and more scatter in the SA-V group. The CNN and Random Forest Model accurately recognized gait conditions, achieving average accuracies of 88.4% and 92.3%, respectively, proving that the method mentioned above provides more accurate gait evaluations for patients with movement disorders.

Wafer-Scale Fabrication of Wearable All-Carbon Nanotube Photodetector Arrays.

With electronic devices evolving toward portable and high-performance wearables, the constraints of complex and wet processing technologies become apparent. This study presents a scalable photolithography/chemical-free method for crafting wearable all-carbon nanotube (CNT) photodetector device arrays. Laser-assisted patterning and dry deposition techniques directly assemble gas-phase CNTs into flexible devices without any lithography or lift-off processes. The resulting wafer-scale all-CNT photodetector arrays showcase excellent uniformity, wearability, environmental stability, and notable broadband photoresponse, boasting a high responsivity of 44 AW-1 and a simultaneous detectivity of 1.9 × 109 Jones. This research provides an efficient, versatile, and scalable strategy for manufacturing wearable all-CNT device arrays, allowing widespread adoption in wearable optoelectronics and multifunctional sensors.

Single-Atom Verification of the Optimal Trade-Off between Speed and Cost in Shortcuts to Adiabaticity.

The approach of shortcuts to adiabaticity enables the effective execution of adiabatic dynamics in quantum information processing with enhanced speed. Owing to the inherent trade-off between dynamical speed and the cost associated with the transitionless driving field, executing arbitrarily fast operations becomes impractical. To understand the accurate interplay between speed and energetic cost in this process, we propose theoretically and verify experimentally a new trade-off, which is characterized by a tightly optimized bound within s-parametrized phase spaces. Our experiment is carried out in a single ultracold ^{40}Ca^{+} ion trapped in a harmonic potential. By exactly operating the quantum states of the ion, we execute the Landau-Zener model as an example, where the quantum speed limit as well as the cost are governed by the spectral gap. We witness that our proposed trade-off is indeed tight in scenarios involving both initially eigenstates and initially thermal equilibrium states. Our work helps understanding the fundamental constraints in shortcuts to adiabaticity and illuminates the potential of underutilized phase spaces that have been traditionally overlooked.

A p38 MAP kinase inhibitor suppresses osteoclastogenesis and alleviates ovariectomy-induced bone loss through the inhibition of bone turnover.

Inhibition of excessive osteoclastic activity is an efficient therapeutic strategy for many bone diseases induced by increased bone resorption, such as osteoporosis. BMS-582949, a clinical p38α inhibitor, is a promising drug in Phase II studies for treating rheumatoid arthritis. However, its function on bone resorption is largely unknown. In this study, we find that BMS-582949 represses RANKL-induced osteoclast differentiation in a dose-dependent manner. Moreover, BMS-582949 inhibits osteoclastic F-actin ring formation and osteoclast-specific gene expression. Mechanically, BMS-582949 treatment attenuates RANKL-mediated osteoclastogenesis through mitogen-activated protein kinases (MAPKs) and protein kinase B (AKT) signaling pathways without disturbing nuclear factor-κB (NF-κB) signaling. Interestingly, BMS-582949 impairs osteoclastic mitochondrial biogenesis and functions, such as oxidative phosphorylation (OXPHOS). Furthermore, BMS-582949 administration prevents bone loss in ovariectomized mouse mode by inhibiting both bone resorption and bone formation in vivo. Taken together, these findings indicate that BMS-582949 may be a potential and effective drug for the therapy of osteolytic diseases.

Discriminating atypical parotid carcinoma and pleomorphic adenoma utilizing extracellular volume fraction and arterial enhancement fraction derived from contrast-enhanced CT imaging: A multicenter study.

OBJECTIVES: To investigate the added value of extracellular volume fraction (ECV) and arterial enhancement fraction (AEF) derived from enhanced CT to conventional image and clinical features for differentiating between pleomorphic adenoma (PA) and atypical parotid adenocarcinoma (PCA) pre-operation. METHODS: From January 2010 to October 2023, a total of 187 cases of parotid tumors were recruited, and divided into training cohort (102 PAs and 51 PCAs) and testing cohort (24 PAs and 10 atypical PCAs). Clinical and CT image features of tumor were assessed. Both enhanced CT-derived ECV and AEF were calculated. Univariate analysis identified variables with statistically significant differences between the two subgroups in the training cohort. Multivariate logistic regression analysis with the forward variable selection method was used to build four models (clinical model, clinical model+ECV, clinical model+AEF, and combined model). Diagnostic performances were evaluated using receiver operating characteristic (ROC) curve analyses. Delong's test compared model differences, and calibration curve and decision curve analysis (DCA) assessed calibration and clinical application. RESULTS: Age and boundary were chosen to build clinical model, and to construct its ROC curve. Amalgamating the clinical model, ECV, and AEF to establish a combined model demonstrated superior diagnostic effectiveness compared to the clinical model in both the training and test cohorts (AUC = 0.888, 0.867). There was a significant statistical difference between the combined model and the clinical model in the training cohort (p = 0.0145). CONCLUSIONS: ECV and AEF are helpful in differentiating PA and atypical PCA, and integrating clinical and CT image features can further improve the diagnostic performance.

How liquids charge the superhydrophobic surfaces.

Liquid-solid contact electrification (CE) is essential to diverse applications. Exploiting its full implementation requires an in-depth understanding and fine-grained control of charge carriers (electrons and/or ions) during CE. Here, we decouple the electrons and ions during liquid-solid CE by designing binary superhydrophobic surfaces that eliminate liquid and ion residues on the surfaces and simultaneously enable us to regulate surface properties, namely work function, to control electron transfers. We find the existence of a linear relationship between the work function of superhydrophobic surfaces and the as-generated charges in liquids, implying that liquid-solid CE arises from electron transfer due to the work function difference between two contacting surfaces. We also rule out the possibility of ion transfer during CE occurring on superhydrophobic surfaces by proving the absence of ions on superhydrophobic surfaces after contact with ion-enriched acidic, alkaline, and salt liquids. Our findings stand in contrast to existing liquid-solid CE studies, and the new insights learned offer the potential to explore more applications.

Single-Cell Transcriptomic Analysis Reveals Myocardial Fibrosis Mechanism of Doxorubicin-Induced Cardiotoxicity.

Myocardial fibrosis is a pathological feature of doxorubicin-induced chronic cardiotoxicity that severely affects the prognosis of oncology patients. However, the specific cellular and molecular mediators driving doxorubicin-induced cardiac fibrosis, and the relative impact of different cell populations on cardiac fibrosis, remain unclear.This study aimed to explore the mechanism of doxorubicin-induced cardiotoxicity and myocardial fibrosis and to find potential therapeutic targets. Single-cell RNA sequencing was used to analyze the transcriptome of non-cardiomyocytes from normal and doxorubicin-induced chronic cardiotoxicity in mouse model heart tissue.We established a mouse model of doxorubicin-induced cardiotoxicity with a well-defined fibrotic phenotype. Analysis of single-cell sequencing results showed that fibroblasts were the major origin of extracellular matrix in doxorubicin-induced myocardial fibrosis. Further resolution of fibroblast subclusters showed that resting fibroblasts were converted to matrifibrocytes and then to myofibroblasts to participate in the myocardial remodeling process in response to doxorubicin treatment. Ctsb expression was significantly upregulated in fibroblasts after doxorubicin-induced.This study provides a comprehensive map of the non-cardiomyocyte landscape at high resolution, reveals multiple cell populations contributing to pathological remodeling of the cardiac extracellular matrix, and identifies major cellular sources of myofibroblasts and dynamic gene-expression changes in fibroblast activation. Finally, we used this strategy to detect potential therapeutic targets and identified Ctsb as a specific target for fibroblasts in doxorubicin-induced myocardial fibrosis.

Effect of Retrogression with Different Cooling Ways on the Microstructure and Properties of T'/η' Strengthened Al-Zn-Mg-Cu Alloys.

Retrogression and re-aging (RRA) treatment has been proven to effectively overcome the trade-off between strength and corrosion resistance. Current research focuses on the heating rate, temperature, and holding time of retrogression treatment while ignoring the retrogression cooling ways. In this paper, the effects of RRA treatment with different retrogression cooling ways on the microstructure and properties of newly developed T'/η' strengthened Al-Zn-Mg-Cu alloys were investigated by performing tests on mechanical properties, intergranular corrosion (IGC) resistance, and electrochemical corrosion behavior. The results show that the mechanical properties of samples subject to RRA treatment with water-quenching retrogression (ultimate tensile strength, yield strength, and elongation of 419.2 MPa, 370.2 MPa, and 15.9, respectively) are better than those of air-cooled and furnace-cooled samples. The corrosion resistance of water-quenching (IGC depth of 162.2 µm, corrosion current density of 0.833 × 10-5 A/cm2) and furnace-cooled samples (IGC depth of 123.7 µm, corrosion current density of 0.712 × 10-5 A/cm2) is better than that of air-cooled samples. Microstructure characterization reveals that the effect of the retrogression cooling rate on mechanical properties is related to the size of T'/η' precipitates with grains as well as the proportion of T' and η', while the difference in corrosion resistance depends on the continuity of grain boundary precipitates (GBPs). With mechanical properties, corrosion resistance, and time cost taken into consideration, it is appropriate to select water quenching for retrogression. These findings offer valuable insights for further design to achieve superior performance in various applications.

A Two-Step Regional Ionospheric Modeling Approach for PPP-RTK.

In the precise point positioning/real-time kinematic (PPP-RTK) technique, high-precision ionospheric delay correction information is an important prerequisite for rapid PPP convergence. The commonly used ionospheric modeling approaches in the PPP-RTKs only take the trend term of the ionospheric total electron content (TEC) variations into account. As a result, the residual ionospheric delay still affects the positioning solutions. In this study, we propose a two-step regional ionospheric modeling approach that involves combining a polynomial fitting model (PFM) and a Kriging interpolation (KI) model. In the first step, a polynomial fitting method is used to model the trend term of the ionospheric TEC variations. In the second step, a KI method is used to compensate for the residual term of the ionospheric TEC variations. Datasets collected from continuously operating reference stations (CORSs) in Hunan Province, China, are used to validate the PFM/KI method by comparing with a single PFM method and a combined PFM and inverse distance weighting interpolation (IDWI) method. The experimental results show that the two-step PFM/KI modeled ionospheric delay achieves an average root mean square (RMS) error of 1.8 cm, which is improved by about 48% and 23% when compared with the PFM and PFM/IDWI methods, respectively. Regarding the positioning performance, the PPP-RTK with the PFM/KI method takes an average of 1.8 min or 4.0 min to converge to a positioning accuracy of 1.3 cm or 2.5 cm in the horizontal and vertical directions, respectively. The convergence times are decreased by about 18% and 14% in the horizontal direction and 9% and 5% in the vertical direction over the PFM and the PFM/IDWI methods, respectively.

Multiparametric MRI subregion radiomics for preoperative assessment of high-risk subregions in microsatellite instability of rectal cancer patients: A multicenter study.

BACKGROUND: Microsatellite instability (MSI) is associated with treatment response and prognosis in patients with rectal cancer (RC). However, intratumoral heterogeneity limits MSI testing in patients with RC. We developed a subregion radiomics model based on multiparametric magnetic resonance imaging (MRI) to preoperatively assess high-risk subregions with MSI and predict the MSI status of patients with RC. METHODS: This retrospective study included 475 patients (training cohort, 382; external test cohort, 93) with RC from two participating hospitals between April 2017 and June 2023. In the training cohort, subregion radiomic features were extracted from multiparametric MRI, which included T2-weighted, T1-weighted, diffusion-weighted, and contrast-enhanced T1-weighted imaging. MSI-related subregion radiomic features, classical radiomic features, and clinicoradiological variables were gathered to build five predictive models using logistic regression. Kaplan-Meier survival analysis was conducted to explore the prognostic information. RESULTS: Among the 475 patients (median age, 64 years [interquartile range, IQR: 55-70 years];304 men and 171 women), the prevalence of MSI was 11.16% (53/475). The subregion radiomics model outperformed the classical radiomics and clinicoradiological models in both training (area under the curve [AUC]=0.86, 0.72, and 0.59, respectively) and external test cohorts (AUC=0.83, 0.73, and 0.62, respectively). The subregion-clinicoradiological model combining clinicoradiological variables and subregion radiomic features performed the optimal, with AUCs of 0.87 and 0.85 in the training and external test cohorts, respectively. The 3-year disease-free survival rate of MSI groups predicted based on the model was higher than that of the predicted microsatellite stability (MSS) groups in both patient cohorts (training, P=0.032; external test, P=0.046). CONCLUSIONS: We developed and validated a model based on subregion radiomic features of multiparametric MRI to evaluate high-risk subregions with MSI and predict the MSI status of RC preoperatively, which may assist in individualized treatment decisions and positioning for biopsy.

Evaluation of a new dynamic real-time visualization 25 kHz swept-source optical coherence tomography based biometer.

BACKGROUND: To evaluate the intraobserver repeatability and interobserver reproducibility of a newly developed dynamic real-time visualization 25 kHz swept-source optical coherence tomography (SS-OCT) based biometer (ZW-30, TowardPi Medical Technology Ltd, China) and compare its agreement with another SS-OCT based biometer (IOLMaster 700, Carl Zeiss Meditec AG, Jena, Germany). METHODS: Eighty-two healthy right eyes were enrolled in this prospective observational study. Measurements were repeated for three times using the ZW-30 and IOLMaster 700 in a random order. Obtained parameters included axial length (AL), central corneal thickness (CCT), aqueous depth (AQD), anterior chamber depth (ACD), lens thickness (LT), mean keratometry (Km), astigmatism magnitude (AST), vector J0, vector J45, and corneal diameter (CD). The within-subject standard deviation (Sw), test-retest (TRT) variability, coefficient of variation (CoV), and intraclass correlation coefficient (ICC) were adopted to assess the intraobserver repeatability and interobserver reproducibility. The double-angle plot was also used to display the distribution of AST. To estimate agreement, Bland-Altman plots were used. RESULTS: For the intraobserver repeatability and interobserver reproducibility, the Sw, TRT and CoV for all parameters were low. Meanwhile, the ICC values were all close to 1.000, except for the J45 (ICC = 0.887 for the intraobserver repeatability). The double-angle plot showed that the distribution of AST measured by these two devices was similar. For agreement, the Bland-Altman plots showed narrow 95% limits of agreements (LoAs) for AL, CCT, AQD, ACD, LT, Km AST, J0, J45, and CD (- 0.02 mm to 0.02 mm, - 7.49 µm to 8.08 µm, - 0.07 mm to 0.04 mm, - 0.07 mm to 0.04 mm, - 0.07 mm to 0.08 mm, - 0.16 D to 0.30 D, - 0.30 D to 0.29 D, - 0.16 D to 0.16 D, - 0.23 D to 0.13 D, and - 0.39 mm to 0.10 mm, respectively). CONCLUSIONS: The newly dynamic real-time visualization biometer exhibited excellent intraobserver repeatability and interobserver reproducibility. The two devices both based on the SS-OCT principle had similar ocular parameters measurement values and can be interchanged in clinical practice.

Seizing the fate of lymph nodes in immunotherapy: To preserve or not?

Lymph node dissection has been a long-standing diagnostic and therapeutic strategy for metastatic cancers. However, questions over myriad related complications and survival outcomes are continuously debated. Immunotherapy, particularly neoadjuvant immunotherapy, has revolutionized the conventional paradigm of cancer treatment, yet has benefited only a fraction of patients. Emerging evidence has unveiled the role of lymph nodes as pivotal responders to immunotherapy, whose absence may contribute to drastic impairment in treatment efficacy, again posing challenges over excessive lymph node dissection. Hence, centering around this theme, we concentrate on the mechanisms of immune activation in lymph nodes and provide an overview of minimally invasive lymph node metastasis diagnosis, current best practices for activating lymph nodes, and the prognostic outcomes of omitting lymph node dissection. In particular, we discuss the potential for future comprehensive cancer treatment with effective activation of immunotherapy driven by lymph node preservation and highlight the challenges ahead to achieve this goal.

Pore size distribution and Al oxide content significantly regulated the effects of humic acid on perfluorooctanoic acid transport in natural soils.

The ubiquity of dissolved organic matter (DOM) makes it encounter the released perfluorooctanoic acid (PFOA) in subsurface environment. However, the effect of DOM (e.g., humic acid, HA) on PFOA transport in soils and the critical influencing factors and mechanisms remain obscure. Column experiments were conducted to explore PFOA transport with the presence of different concentrations of HA in three types of soils and two types of Al oxide coated sand. Results revealed soil properties significantly regulate the effects of HA on PFOA transport, for which pore size distribution, minerals content (e.g., Al oxide) and pH were critical influencing soil-properties. For soil with large mesopore volume, pore blockage caused by HA controlled the effect of HA on PFOA transport. Large mesopore volume significantly alleviated pore blockage of HA, and led to insignificant effects of HA on PFOA transport. For soil exhibited minimum mesopore volume, Al oxide content and pH dominated the effect of HA on PFOA transport. Results from Al oxide coated sand (low mesopore volume) columns further proved that higher Al oxide content and lower pH caused more significant facilitating effect of HA on PFOA transport via site competition. Results highlighted the importance of considering pore size distribution and Al oxide content when assessing PFOA mobility capacity with co-transport with DOM in soils.

Assessing progression limits in different grades of keratoconus from a novel perspective: precision of measurements of the corneal epithelium.

BACKGROUND: To assess repeatability and reproducibility of corneal epithelium thickness (ET) measured by a spectral-domain optical coherence tomographer (SD-OCT)/Placido topographer (MS-39, CSO, Florence, Italy) in keratoconus (KC) population at different stages, as well as to determine the progression limits for evaluating KC progression. METHODS: A total of 149 eyes were enrolled in this study, with 29 eyes in the forme fruste keratoconus (FFKC) group, 34 eyes in the mild KC group, 40 eyes in the moderate KC group, and 46 eyes in the severe KC group. Employing the within-subject standard deviation (Sw), test-retest variability (TRT), coefficient of variation (CoV), and intraclass correlation coefficient (ICC) to evaluate intraoperator repeatability and interoperator reproducibility. RESULTS: The repeatability and reproducibility of MS-39 in patients with KC were acceptable, according to ICC values ranging from 0.732 to 0.954. However, patients with more severe KC and progressive peripheralization of the measurement points had higher TRTs but a thinning trend. The current study tended to set the cut-off values of mild KC, moderate KC, and severe KC to 4.9 µm, 5.2 µm, and 7.4 µm for thinnest epithelium thickness (TET). When differences between follow-ups are higher than those values, progression of the disease is possible. As for center epithelium thickness (CET), cut-off values for mild KC, moderate KC, and severe KC should be 2.8 µm, 4.4 µm, and 5.3 µm. This might be useful in the follow-up and diagnosis of keratoconus. CONCLUSIONS: This study demonstrated that the precision of MS-39 was reduced in measuring more severe KC patients and more peripheral corneal points. In determining disease progression, values should be differentiated between disease-related real changes and measurement inaccuracies. Due to the large difference in ET measured by MS-39 between various stages of disease progression, it is necessary to accurately grade KC patients to avoid errors in KC clinical decision-making.

HBV-miR-3 is closely related to HBV replication and strongly predictive of HBeAg seroconversion in PegIFN-α treated patients.

HBV-miR-3 is encoded by HBV and takes part in pathogenesis of HBV-related liver disease. Whether HBV-miR-3 has a relationship with HBV replication and is predictive of PegIFN-α treatment response is still unknown. HBV-miR-3 quantification is based on qRT-PCR. The relationship of HBV-miR-3 and HBV replication, and predictive value of HBV-miR-3 were evaluated in a cohort of 650 HBeAg positive patients from a multi-center, randomized phase III clinical trial for the study of PegIFN-a2b. HBV-miR-3 is significantly positively related to HBVDNA, HBVpgRNA, HBeAg and HBsAg at baseline and at all the different time points during PegIFN-α treatment. Both univariate regression analyses and multivariate logistic regression analyses showed HBV-miR-3 is a predictor of HBeAg seroconversion in the patients treated with PegIFN-α at weeks of 0, 12, and 24. 70.0% of patients with HBV-miR-3 < 3log at week 12 achieved HBeAg seroconversion, otherwise, with HBV-miR-3 > 6log at week 12 no patient obtained HBeAg seroconversion. Conbination of HBV-miR-3 and HBeAg is more strongly predictive of HBeAg seroconversion (83.64%) at week 12. HBV-miR-3 is new biomarker for HBV replication and positively correlated to HBV replication. HBV-miR-3 is also an early predictor of HBeAg seroconversion in the patients treated with PegIFN-α.

Multi_CycGT: A Deep Learning-Based Multimodal Model for Predicting the Membrane Permeability of Cyclic Peptides.

Cyclic peptides are gaining attention for their strong binding affinity, low toxicity, and ability to target "undruggable" proteins; however, their therapeutic potential against intracellular targets is constrained by their limited membrane permeability, and researchers need much time and money to test this property in the laboratory. Herein, we propose an innovative multimodal model called Multi_CycGT, which combines a graph convolutional network (GCN) and a transformer to extract one- and two-dimensional features for predicting cyclic peptide permeability. The extensive benchmarking experiments show that our Multi_CycGT model can attain state-of-the-art performance, with an average accuracy of 0.8206 and an area under the curve of 0.8650, and demonstrates satisfactory generalization ability on several external data sets. To the best of our knowledge, it is the first deep learning-based attempt to predict the membrane permeability of cyclic peptides, which is beneficial in accelerating the design of cyclic peptide active drugs in medicinal chemistry and chemical biology applications.

Imaging diagnosis and efficacy monitoring by [89Zr]Zr-DFO-KN035 immunoPET in patients with PD-L1-positive solid malignancies.

Rationale: Although programmed death-ligand 1 (PD-L1) inhibitors have achieved efficacy in cancer therapy, their response rate is low. Differences in the prognosis of patients with cancer under anti-PD-L1 treatment are related to the PD-L1 level in tumors. Accurate PD-L1 detection can optimize the accuracy of tumor immunotherapy and avoid ineffective clinical diagnosis and treatments. Methods: We investigated the imaging efficiency and therapy monitoring capacity of [89Zr]Zr-DFO-KN035 immunoPET for tumors. We labeled the monodomain anti-PD-L1 antibody KN035 with the radionuclide zirconium-89 and used this tracer for PET imaging. [89Zr]Zr-DFO-KN035 uptakes in patients with PD-L1-positive tumors, including primary and metastatic tumors, as well as in normal tissues, were comparatively assessed by using positron emission tomography/computed tomography imaging. Results: In PD-L1-positive patients, [89Zr]Zr-DFO-KN035 was sensitive in tumor-targeting imaging and could detect multiple metastatic foci, including multiple bone metastases (tumor-to-muscle ratios of 7.102 and 6.118 at 55 and 120 h, respectively) and lymph-node metastases (tumor-to-muscle ratios of 11.346 and 6.542 at 55 and 120 h, respectively). The needed radioactive dose of [89Zr]Zr-DFO-KN035 (55.5-92.5 MBq) used in this study was considerably lower than that of [18F]FDG (370-555 MBq). [89Zr]Zr-DFO-KN035 monitored and predicted the site of adverse reactions in antitumor immunotherapy. Moreover, after antitumor treatment, [89Zr]Zr-DFO-KN035 enabled observational imaging for therapeutic efficacy evaluation, which can help predict patient prognosis. Conclusion: [89Zr]Zr-DFO-KN035 can be used for the diagnosis and therapy monitoring of PD-L1-positive tumors and provide noninvasive and comprehensive observations for tumor diagnostic imaging, prognosis prediction, and efficacy evaluation.

High-permittivity Solvents Increase MXene Stability and Stacking Order Enabling Ultraefficient Terahertz Shielding.

2D transition metal carbides and nitrides (MXenes) suggest an uncommonly broad combination of important functionalities amongst 2D materials. Nevertheless, MXene suffers from facile oxidation and colloidal instability upon conventional water-based processing, thus limiting applicability. By experiments and theory, It is suggested that for stability and dispersibility, it is critical to select uncommonly high permittivity solvents such as N-methylformamide (NMF) and formamide (FA) (εr  = 171, 109), unlike the classical solvents characterized by high dipole moment and polarity index. They also allow high MXene stacking order within thin films on carbon nanotube (CNT) substrates, showing very high Terahertz (THz) shielding effectiveness (SE) of 40-60 dB at 0.3-1.6 THz in spite of the film thinness < 2 µm. The stacking order and mesoscopic porosity turn relevant for THz-shielding as characterized by small-angle X-ray scattering (SAXS). The mechanistic understanding of stability and structural order allows guidance for generic MXene applications, in particular in telecommunication, and more generally processing of 2D materials.

A multi-epitope subunit vaccine based on CU/ZN-SOD, OMP31 and BP26 against Brucella melitensis infection in BALB/C mice.

Brucellosis, a zoonosis caused by Brucella, is highly detrimental to both humans and animals. Most existing vaccines are live attenuated vaccines with safety flaws for people and animals. Therefore, it is advantageous to design a multi-epitope subunit vaccine (MEV) to prevent Brucella infection. To this end, we applied a reverse vaccinology approach. Six cytotoxic T cell (CTL) epitopes, seven T helper cell (HTL) epitopes, and four linear B cell epitopes from CU/ZN-SOD, Omp31, and BP26 were obtained. We linked the CTL, HTL, B-cell epitopes, the appropriate CTB molecular adjuvant, and the universal T helper lymphocyte epitope, PADRE, with linkers AAY, GPPGG, and KK, respectively. This yielded a 412-amino acid MEV construct, which we named MEVcob. The immunogenicity, stability, safety, and feasibility of the construct were evaluated by bioinformatics tools (including the AlphaFold2 prediction tool, the AlphaFold2 tool, NetMHC-I pan 4.0 server, IEDB MHC-I server, ABCpred service, and C-ImmSim server); the physicochemical properties, secondary and tertiary structures, and binding ability of MEVocb to toll-like receptor 4 (TLR4) was analyzed. Then, codon adaptation and computer cloning studies were performed. MEVocb is highly immunogenic in immunostimulation experiments, The proteins translated by these sequences were relatively stable, exhibiting a high antigenic index. Furthermore, mouse experiments confirmed that the MEVocb construct could raise IFN-γ, IgG, IgG2a, IgG1, IL-2, TNF-α levels in mice, indicating that induced a specific humoral and cellular immune response in BALB/c mice. This vaccine induced a statistically significant level of protection in BALB/c mice when challenged with Brucella melitensis 043 in Xinjiang. Briefly, we utilized immunoinformatic tools to design a novel multi-epitope subunit candidate vaccine against Brucella. This vaccine aims to induce host immune responses and confer specific protective effects. The study results offer a theoretical foundation for the development of a novel Brucella subunit vaccine.