Experimental validation of an advanced impedance pneumography for monitoring ventilation volume during programmed cycling exercise.

Objective.Impedance pneumography (IP) has provided static assessments of subjects' breathing patterns in previous studies. Evaluating the feasibility and limitation of ambulatory IP based respiratory monitoring needs further investigation on clinically relevant exercise designs. The aim of this study was to evaluate the capacity of an advanced IP in ambulatory respiratory monitoring, and its predictive value in independent ventilatory capacity quantification during cardiopulmonary exercise testing (CPET).Approach.35 volunteers were examined with the same calibration methodology and CPET exercise protocol comprising phases of rest, unloaded, incremental load, maximum load, recovery and further-recovery. In 3 or 4 deep breaths of calibration stage, thoracic impedance and criterion spirometric volume were simultaneously recorded to produce phase-specific prior calibration coefficients (CCs). The IP measurement during exercise protocol was converted by prior CCs to volume estimation curve and thus calculate minute ventilation (VE) independent from the spirometry approach.Main results.Across all measurements, the relative error of IP-derived VE (VER) and flowrate-derived VE (VEf) was less than 13.8%. In Bland-Altman plots, the aggregate VE estimation bias was statistically insignificant for all 3 phases with pedaling exercise and the discrepancy between VERand VEffell within the 95% limits of agreement (95% LoA) for 34 or all subjects in each of all CPET phases.Significance.This work reinforces the independent use of IP as an accurate and robust alternative to flowmeter for applications in cycle ergometry CPET, which could significantly encourage the clinical use of IP and improve the convenience and comfort of CPET.

Melatonin as an immunomodulator in CD19-targeting CAR-T cell therapy: managing cytokine release syndrome.

BACKGROUND: Chimeric antigen receptor CAR-T cell therapies have ushered in a new era of treatment for specific blood cancers, offering unparalleled efficacy in cases of treatment resistance or relapse. However, the emergence of cytokine release syndrome (CRS) as a side effect poses a challenge to the widespread application of CAR-T cell therapies. Melatonin, a natural hormone produced by the pineal gland known for its antioxidant and anti-inflammatory properties, has been explored for its potential immunomodulatory effects. Despite this, its specific role in mitigating CAR-T cell-induced CRS remains poorly understood. METHODS: In this study, our aim was to investigate the potential of melatonin as an immunomodulatory agent in the context of CD19-targeting CAR-T cell therapy and its impact on associated side effects. Using a mouse model, we evaluated the effects of melatonin on CAR-T cell-induced CRS and overall survival. Additionally, we assessed whether melatonin administration had any detrimental effects on the antitumor efficacy and persistence of CD19 CAR-T cells. RESULTS: Our findings demonstrate that melatonin effectively mitigated the severity of CAR-T cell-induced CRS in the mouse model, leading to improved overall survival outcomes. Remarkably, melatonin administration did not compromise the antitumor effectiveness or persistence of CD19 CAR-T cells, indicating its compatibility with therapeutic goals. These results suggest melatonin's potential as an immunomodulatory compound to alleviate CRS without compromising the therapeutic benefits of CAR-T cell therapy. CONCLUSION: The study's outcomes shed light on melatonin's promise as a valuable addition to the existing treatment protocols for CAR-T cell therapies. By attenuating CAR-T cell-induced CRS while preserving the therapeutic impact of CAR-T cells, melatonin offers a potential strategy for optimizing and refining the safety and efficacy profile of CAR-T cell therapy. This research contributes to the evolving understanding of how to harness immunomodulatory agents to enhance the clinical application of innovative cancer treatments.

Dynamic Characteristics and Effective Stiffness Properties of Sandwich Panels with Hierarchical Hexagonal Honeycomb.

The dynamic characteristics of sandwich panels with a hierarchical hexagonal honeycomb (SP-HHHs) show significant improvements due to their distinct hierarchy configurations. However, this also increases the complexity of structural analysis. To address this issue, the variational asymptotic method was utilized to homogenize the unit cell of the SP-HHH and obtain the equivalent stiffness, establishing a two-dimensional equivalent plate model (2D-EPM). The accuracy and effectiveness of the 2D-EPM were then verified through comparisons with the results from a detailed 3D FE model in terms of the free vibration and frequency- and time-domain forced vibration, as well as through local field recovery analysis at peak and trough times. Furthermore, the tailorability of the typical unit cell was utilized to perform a parametric analysis of the effects of the length and thickness ratios of the first-order hierarchy on the dynamic characteristics of the SP-HHH under periodic loading. The results reveal that the vertices serve as weak points in the SP-HHH, while the vertex cell pattern significantly influences the specific stiffness and stiffness characteristics of the panel. The SP-HHH with hexagonal vertex cells has superior specific stiffness compared to panels with circular and rectangular vertex cells, resulting in a more lightweight design and enhanced stiffness.

Design of nanobody-based bispecific constructs by in silico affinity maturation and umbrella sampling simulations.

Random mutagenesis is the natural opportunity for proteins to evolve and biotechnologically it has been exploited to create diversity and identify variants with improved characteristics in the mutant pools. Rational mutagenesis based on biophysical assumptions and supported by computational power has been proposed as a faster and more predictable strategy to reach the same aim. In this work we confirm that substantial improvements in terms of both affinity and stability of nanobodies can be obtained by using combinations of algorithms, even for binders with already high affinity and elevated thermal stability. Furthermore, in silico approaches allowed the development of an optimized bispecific construct able to bind simultaneously the two clinically relevant antigens TNF-α and IL-23 and, by means of its enhanced avidity, to inhibit effectively the apoptosis of TNF-α-sensitive L929 cells. The results revealed that salt bridges, hydrogen bonds, aromatic-aromatic and cation-pi interactions had a critical role in increasing affinity. We provided a platform for the construction of high-affinity bispecific constructs based on nanobodies that can have relevant applications for the control of all those biological mechanisms in which more than a single antigen must be targeted to increase the treatment effectiveness and avoid resistance mechanisms.

VHH212 nanobody targeting the hypoxia-inducible factor 1α suppresses angiogenesis and potentiates gemcitabine therapy in pancreatic cancer in vivo.

OBJECTIVE: We aimed to develop a novel anti-HIF-1α intrabody to decrease gemcitabine resistance in pancreatic cancer patients. METHODS: Surface plasmon resonance and glutathione S-transferase pull-down assays were conducted to identify the binding affinity and specificity of anti-HIF-1α VHH212 [a single-domain antibody (nanobody)]. Molecular dynamics simulation was used to determine the protein-protein interactions between hypoxia-inducible factor-1α (HIF-1α) and VHH212. The real-time polymerase chain reaction (PCR) and Western blot analyses were performed to identify the expressions of HIF-1α and VEGF-A in pancreatic ductal adenocarcinoma cell lines. The efficiency of the VHH212 nanobody in inhibiting the HIF-1 signaling pathway was measured using a dual-luciferase reporter assay. Finally, a PANC-1 xenograft model was developed to evaluate the anti-tumor efficiency of combined treatment. Immunohistochemistry analysis was conducted to detect the expressions of HIF-1α and VEGF-A in tumor tissues. RESULTS: VHH212 was stably expressed in tumor cells with low cytotoxicity, high affinity, specific subcellular localization, and neutralization of HIF-1α in the cytoplasm or nucleus. The binding affinity between VHH212 and the HIF-1α PAS-B domain was 42.7 nM. Intrabody competitive inhibition of the HIF-1α heterodimer with an aryl hydrocarbon receptor nuclear translocator was used to inhibit the HIF-1/VEGF pathway in vitro. Compared with single agent gemcitabine, co-treatment with gemcitabine and a VHH212-encoding adenovirus significantly suppressed tumor growth in the xenograft model with 80.44% tumor inhibition. CONCLUSIONS: We developed an anti-HIF-1α nanobody and showed the function of VHH212 in a preclinical murine model of PANC-1 pancreatic cancer. The combination of VHH212 and gemcitabine significantly inhibited tumor development. These results suggested that combined use of anti-HIF-1α nanobodies with first-line treatment may in the future be an effective treatment for pancreatic cancer.

LiDAR-Camera Calibration Using Line Correspondences.

In this paper, we introduce a novel approach to estimate the extrinsic parameters between a LiDAR and a camera. Our method is based on line correspondences between the LiDAR point clouds and camera images. We solve the rotation matrix with 3D-2D infinity point pairs extracted from parallel lines. Then, the translation vector can be solved based on the point-on-line constraint. Different from other target-based methods, this method can be performed simply without preparing specific calibration objects because parallel lines are commonly presented in the environment. We validate our algorithm on both simulated and real data. Error analysis shows that our method can perform well in terms of robustness and accuracy.

In vitro affinity maturation to improve the efficacy of a hypoxia-inducible factor 1α single-domain intrabody.

Affinity is an important property of therapeutic antibodies, so improving affinity is critical to the biological activity and clinical efficacy. An anti-HIF-1α nanobody, VHH212, was screened via a native ribosome display library with a 26.6 nM of KD value was used as the parent. In this paper, a Venn-intersection of multi-algorithms screening (VIMAS) strategy for computer-aided binding affinity prediction was designed. Homology modeling and protein docking methods were used to substitute the need for a crystal structure. Finally, a mutant with a 17.5-fold enhancement in binding affinity (1.52 nM) was obtained by using the VIMAS strategy. Furthermore, the biological activity of mutants was verified at the cellular level. Targeting HIF-1α can sensitize PDAC (pancreatic ductal adenocarcinoma) tumors to gemcitabine, which is a potential co-treatment method for pancreatic cancer patients. Our results showed that the cytotoxicity of gemcitabine on pancreatic cancer cell lines increased with the enhanced-affinity of an intrabody under combined treatment.