The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest.

Much of the complexity within cells arises from functional and regulatory interactions among proteins. The core of these interactions is increasingly known, but novel interactions continue to be discovered, and the information remains scattered across different database resources, experimental modalities and levels of mechanistic detail. The STRING database (https://string-db.org/) systematically collects and integrates protein-protein interactions-both physical interactions as well as functional associations. The data originate from a number of sources: automated text mining of the scientific literature, computational interaction predictions from co-expression, conserved genomic context, databases of interaction experiments and known complexes/pathways from curated sources. All of these interactions are critically assessed, scored, and subsequently automatically transferred to less well-studied organisms using hierarchical orthology information. The data can be accessed via the website, but also programmatically and via bulk downloads. The most recent developments in STRING (version 12.0) are: (i) it is now possible to create, browse and analyze a full interaction network for any novel genome of interest, by submitting its complement of encoded proteins, (ii) the co-expression channel now uses variational auto-encoders to predict interactions, and it covers two new sources, single-cell RNA-seq and experimental proteomics data and (iii) the confidence in each experimentally derived interaction is now estimated based on the detection method used, and communicated to the user in the web-interface. Furthermore, STRING continues to enhance its facilities for functional enrichment analysis, which are now fully available also for user-submitted genomes.

Interfacial Electron Engineering of PdSn-NbN/C for Highly Efficient Cleavage of the C-C Bonds in Alkaline Ethanol Electrooxidation.

The splitting of the C-C bonds of ethanol remains a key issue to be addressed, despite tremendous efforts made over the past several decades. This study highlights the enhancement mechanism of inexpensive NbN-modified Pd1 Sn3 -NbN/C towards the C-C bonds cleavage for alkaline ethanol oxidation reaction (EOR). The optimal Pd1 Sn3 -NbN/C delivers a catalytic activity up to 43.5 times higher than that of commercial Pd/C and high carbonate selectivity (20.5%) toward alkaline EOR. Most impressively, the Pd1 Sn3 -NbN/C presents good durability even after 25 200 s of chronoamperometric testing. The enhanced catalytic performance is mainly due to the interfacial interaction between PdSn and NbN, demonstrated by multiple structural characterization results. In addition, in situ ATR-SEIRAS (Attenuated total reflection-surface enhanced infrared absorption spectroscopy) results suggest that NbN facilitates the C-C bonds cleavage towards the alkaline EOR, followed by the enhanced OH adsorption to promote the subsequent oxidation of C1 intermediates after doping Sn. DFT (density functional theory) calculations indicate that the activation barriers of the C-H bond cleavage in CH3 CH2 OH, CH3 CHOH, CH3 CHO, CH3 CO, CH2 CO, and the C-C bond cleavage in CH3 CO, CH2 CO, CHCO are evidently reduced and the removal of adsorbed CH3 CO and CO becomes easier on the PdSn-NbN/C catalyst surface.

Quantitative Analysis of Photochemical Reactions in Pentacene Precursor Films.

On-surface reactions are rapidly gaining attention as a chemical technique for synthesizing organic functional materials, such as graphene nanoribbons and molecular semiconductors. Quantitative analysis of such reactions is essential for fabricating high-quality film structures, but until our recent work using p-polarized multiple-angle incidence resolution spectrometry (pMAIRS), no analytical technique is available to quantify the reaction rate. In the present study, the pMAIRS technique is employed to analyze the photochemical reaction from 6,13-dihydro-6,13-ethanopentacene-15,16-dione to pentacene in thin films. The spectral analysis on a pMAIRS principle readily reveals the photoconversion rate accurately without other complicated calculations. Thus, this study underlines that the pMAIRS technique is a powerful tool for quantitative analysis of on-surface reactions, as well as molecular orientation.

A New Powerful Magnetic Dark Catalyst Based on rGO/Fe3O4/CdSe Nanocomposite for Ultrafast Degradation of Methylene Blue Dye.

In the present study, Rgo/Fe3O4/CdSe as a dark catalyst material was synthesized by a refluxing method. The synthesized magnetic nanocomposites were studied by various analyses such as Fourier transform infrared (FTIR), energy-dispersive X-ray spectroscopy (EDS), field emission scanning electron microscopy (FESEM), X-ray diffractometer (XRD), Raman, Zeta and vibrating sample magnetometer (VSM). Characterization of structural analysis showed that the nanocomposites were successfully synthesized. The absorption spectrum was used to determine the dark catalyst activity of rGO/Fe3O4/CdSe nanocomposite. Analysis of the absorption spectrum showed that the prepared nanocomposites degrade the MB organic dye completely (100%) after 2 min of stirring in the dark, also experimenting with different pH showed that the best performance for the degradation of MB occurs in neutral and alkaline media. The Raman spectrum analysis showed that the Fe3O4/CdSe quantum dots (QDs) were correctly incorporated on the reduced graphene oxide (rGO) nanosheets. Zeta potential analysis showed that rGO/Fe3O4/CdSe has a large amount of negative charge on its surface and the surface charge increased by about 16 mV compared to the Fe3O4/CdSe compound. BET and BJH techniques were used to determine the effective surface area and pore size diameter, BET results to determine the effective surface area showed that by adding graphene to the compound, the specific surface area increased from 42.877 m2g-1 to 54.1896 m2g-1. The radical scavenger experiment showed that electrons play an essential role in the degradation process. VSM analysis showed that the prepared nanocomposites have excellent superparamagnetic behavior, this advantage enables the easy collection of nanocatalysts by magnets from wastewater after dye degradation.

Octamer-binding transcription factor 4-positive circulating tumor cell predicts worse treatment response and survival in advanced cholangiocarcinoma patients who receive immune checkpoint inhibitors treatment.

BACKGROUND: Octamer-binding transcription factor 4-positive circulating tumor cell (OCT4+CTC) exhibits high stemness and invasive potential, which may influence the efficacy of immune checkpoint inhibitors (ICI). This study aimed to assess the prognostic role of OCT4+CTC in advanced cholangiocarcinoma (CCA) patients who received ICI treatment. METHODS: In total, 40 advanced CCA patients who received ICI treatment were included, and CTC and OCT4 counts were detected via a Canpatrol system and an RNA in situ hybridization method before ICI treatment. Patients were subsequently divided into none CTC, OCT4-CTC, and OCT4+CTC groups. Patients were followed up for a median of 10.4 months. RESULTS: The percentages of patients in none CTC, OCT4-CTC, and OCT4+CTC groups were 25.0%, 30.0%, and 45.0%, respectively. The proportion of patients with lymph node metastasis was highest in OCT4+CTC group, followed by none CTC group, and lowest in OCT4-CTC group (P = 0.025). The objective response rate (ORR) was lowest in OCT4+CTC group, moderate in OCT4-CTC group, and highest in none CTC group (P = 0.009), while disease control rate was not different among three groups (P = 0.293). In addition, progression-free survival (PFS) (P < 0.001) and overall survival (OS) (P = 0.001) were shorter in the OCT4+CTC group than in none CTC & OCT4-CTC group. Moreover, OCT4+CTC (versus none CTC) was independently linked with poorer PFS [hazard ratio (HR) = 6.752, P = 0.001] and OS (HR = 6.674, P = 0.003) in advanced CCA patients. CONCLUSION: OCT4+CTC relates to lymph node metastasis and shows a good predictive value for poor treatment response and survival in advanced CCA patients who receive ICI treatment.

Neoadjuvant PD-(L)1 blockade plus platinum-based chemotherapy for potentially resectable oncogene-positive non-small cell lung cancer.

BACKGROUND: Whether programmed cell death-1/ligand-1 (PD-1/PD-L1) blockade-based neoadjuvant treatment may benefit locally advanced oncogene-mutant non-small cell lung cancer (NSCLC) patients remains controversial. This retrospective study was designed to observe the efficacy and safety of neoadjuvant PD-1/PD-L1 blockade plus chemotherapy versus chemotherapy and corresponding tyrosine kinase inhibitors (TKIs) in patients with resectable oncogene-positive NSCLC. METHODS: Patients with potential resectable NSCLC harbouring oncogene alterations who had received neoadjuvant treatment were retrospectively recruited, and an oncogene-negative cohort of patients who received neoadjuvant PD-(L)1 blockade-based neoadjuvant treatment was reviewed for comparison during the same period. The primary aim was to observe the treatment efficacy and event-free survival (EFS) of these agents. Safety profile, molecular target, and immunologic factor data, including PD-L1 expression and tumour mutational burden (TMB), were also obtained. RESULTS: A total of 46 patients were recruited. Thirty-one of them harboured oncogene alterations, including EGFR, KRAS, ERBB2, ROS1, MET, RET, ALK, and FGFR3 alterations. Among the oncogene-positive patients, 18 patients received neoadjuvant PD-(L)1 blockade immunotherapy plus chemotherapy (oncogene-positive IO group), 13 patients were treated with neoadjuvant chemotherapy and/or corresponding TKIs or TKIs alone (oncogene-positive chemo/TKIs group), and the other 15 patients were oncogene negative and received neoadjuvant PD-(L)1 blockade plus chemotherapy (oncogene-negative IO group). The pathological complete response (pCR) and major pathological response (MPR) rates were 22.2% (4 of 18) and 44.4% (8 of 18) in the oncogene-positive IO group, 0% (P = 0.120) and 23.1% (3 of 13) (P = 0.276) in the oncogene-positive chemo/TKIs group, and 46.7% (7 of 15) (P = 0.163) and 80.0% (12 of 15) (P = 0.072) in the oncogene-negative IO group, respectively. By the last follow-up, the median EFS time had not reached in the oncogene-positive IO group, and was 29.5 months in the oncogene-positive chemo/TKIs group and 38.4 months in the oncogene-negative IO group. CONCLUSION: Compared with chemotherapy/TKIs treatment, neoadjuvant treatment with PD-(L)1 blockade plus platinum-based chemotherapy was associated with higher pCR/MPR rates in patients with partially resectable oncogene-mutant NSCLC, while the pCR/MPR rates were lower than their oncogene-negative counterparts treated with PD-(L)1 blockade-based treatment. Specifically, oncogene alteration types and other predictors of response to immunotherapy should be taken into account in clinical practice.

Cellular and gene expression patterns associated with root bifurcation in Selaginella.

The roots of lycophytes branch through dichotomy or bifurcation, during which the root apex splits into two daughter roots. This is morphologically distinct from lateral root (LR) branching in the extant euphyllophytes, with LRs developing along the root axis at different distances from the apex. Although the process of root bifurcation is poorly understood, such knowledge can be important, because it may represent an evolutionarily ancient strategy that roots recruited to form new stem cells or meristems. In this study, we examined root bifurcation in the lycophyte Selaginella moellendorffii. We characterized an in vitro developmental time frame based on repetitive apex bifurcations, allowing us to sample different stages of dichotomous root branching and analyze the root meristem and root branching in S. moellendorffii at the microscopic and transcriptomic level. Our results showed that, in contrast to previous assumptions, initial cells (ICs) in the root meristem are mostly not tetrahedral but rather show an irregular shape. Tracking down the early stages of root branching argues for the occurrence of a symmetric division of the single IC, resulting in two apical stem cells that initiate root meristem bifurcation. Moreover, we generated a S. moellendorffii root branching transcriptome that resulted in the delineation of a subset of core meristem genes. The occurrence of multiple putative orthologs of meristem genes in this dataset suggests the presence of conserved pathways in the control of meristem and root stem cell establishment or maintenance.

Dl-3-n-Butylphthalide Protects against Memory Deficits in Vascular Dementia Rats by Attenuating Pyroptosis via TLR-4/NF-κB Signaling Pathway.

INTRODUCTION: Inflammation is closely associated with the pathogenesis of vascular dementia (VD). Dl-3-n-butylphthalide (NBP) is a small molecule compound extracted from the seeds of Chinese celery, which have anti-inflammatory properties in animal models of acute ischemia and patients with stroke. In this experiment, we studied the protective effects of NBP in a rat model of VD induced by permanent bilateral occlusion of the common carotid arteries and investigated the role of the TLR-4/NF-κB inflammatory signaling pathway in the pathology of VD. METHODS: The Morris water maze test was used to evaluate cognitive deficits in the VD rats. Western blot, immunohistochemistry, and PCR analyses were used to analyze the molecular basis of the inflammatory response. RESULTS: NBP significantly improved the learning and memory ability of VD rats. With regard to the protective mechanism, the results showed that NBP significantly downregulated the relative expression of Cleaved Cas-1/Cas-1 and Cleaved GSDMD/GSDMD. Moreover, NBP decreased the levels of the TLR-4 and NF-κB (P65) protein and phosphorylation of P65 in the hippocampus of VD rats via the TLR-4/NF-κB signaling pathway. CONCLUSION: These findings demonstrate that NBP protects against memory deficits in permanent bilateral common carotid artery occlusion-induced VD rats by attenuating pyroptosis via the TLR-4/NF-κB signaling pathway.

Magnetic induction heating and drug release properties of magnetic carbon nanotubes.

AIM: The use of magnetic carbon nanotubes for multi-modal cancer treatment, incorporating both hyperthermia and drug delivery functions, has drawn substantial interest. Yet, the present method of regulating hyperthermia temperature involves manually adjusting the magnetic field intensity, adding to the complexity and difficulty of clinical applications. This study seeks to design novel magnetic carbon nanotubes capable of self-temperature regulation, and investigate their drug loading and release characteristics. METHODS: Using the co-precipitation method, we synthesized magnetic carbon nanotubes with a Curie temperature of 43 °C. A comprehensive investigation was conducted to analyze their morphology, crystal structure, and magnetic characteristics. To enhance their functionality, chitosan and sodium alginate modifications were introduced, enabling the loading of the antitumor drug doxorubicin hydrochloride (DOX) into these magnetic carbon nanotubes. Subsequently, the loading and release properties of DOX were investigated within the modified magnetic nanotubes. RESULTS: Under alternating magnetic field, magnetic carbon nanotubes exhibit self-regulating properties by undergoing a magnetic phase transition, maintaining temperatures around 43 °C as required for hyperthermia. On the other hand, during magnetic induction heating, the release percentage of DOX reached 23.5% within 2 h and 71.7% within 70 h at tumor pH conditions, indicating their potential for sustained drug release. CONCLUSIONS: The prepared magnetic carbon nanotubes can effectively regulate the temperature during hyperthermia treatment while ensuring controlled drug release, which presents a promising method for preparing nanomaterials that synergistically enhance magnetic hyperthermia and chemotherapy drugs.

Predicting the structures and vibrational spectra of molecular crystals containing large molecules with the generalized energy-based fragmentation approach.

The generalized energy-based fragmentation (GEBF) approach under periodic boundary conditions (PBCs) has been developed to facilitate calculations of molecular crystals containing large molecules. The PBC-GEBF approach can help predict structures and properties of molecular crystals at different theory levels by performing molecular quantum chemistry calculations on a series of non-periodic subsystems constructed from the studied systems. A more rigorous formula of the forces on translational vectors of molecular crystals was proposed and implemented, enabling more reliable predictions of crystal structures. Our benchmark results on several typical molecular crystals show that the PBC-GEBF approach could reproduce the forces on atoms and the translational vectors and the optimized crystal structures from the corresponding conventional periodic methods. The improved PBC-GEBF approach is then applied to predict the crystal structures and vibrational spectra of two molecular crystals containing large molecules. The PBC-GEBF approach can provide a satisfactory description on the crystal structure of a molecular crystal containing 312 atoms in a unit cell at density-fitting second-order Møller-Plesset perturbation theory and density functional theory (DFT) levels and the infrared vibrational spectra of another molecular crystal containing 864 atoms in a unit cell at the DFT level. The PBC-GEBF approach is expected to be a promising theoretical tool for electronic structure calculations on molecular crystals containing large molecules.

The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets.

Cellular life depends on a complex web of functional associations between biomolecules. Among these associations, protein-protein interactions are particularly important due to their versatility, specificity and adaptability. The STRING database aims to integrate all known and predicted associations between proteins, including both physical interactions as well as functional associations. To achieve this, STRING collects and scores evidence from a number of sources: (i) automated text mining of the scientific literature, (ii) databases of interaction experiments and annotated complexes/pathways, (iii) computational interaction predictions from co-expression and from conserved genomic context and (iv) systematic transfers of interaction evidence from one organism to another. STRING aims for wide coverage; the upcoming version 11.5 of the resource will contain more than 14 000 organisms. In this update paper, we describe changes to the text-mining system, a new scoring-mode for physical interactions, as well as extensive user interface features for customizing, extending and sharing protein networks. In addition, we describe how to query STRING with genome-wide, experimental data, including the automated detection of enriched functionalities and potential biases in the user's query data. The STRING resource is available online, at https://string-db.org/.

Prenatal phthalate exposure and birth size: a systematic review and meta-analysis.

Phthalates are common endocrine disruptors. The placental barrier can be crossed by phthalates and may have a negative impact on the health of the fetus. However, the association between prenatal exposure to phthalates and birth size is still debatable. Here, we performed this meta-analysis to assess the relationship between prenatal phthalates exposure and birth size. Eighteen studies were finally included by searching PubMed, Embase, Scopus, Ovid, and Web of Science databases and standardized regression coefficients and standard errors were used to pool effect size. Our results showed that prenatal exposure to MMP (=-0.04, 95%CI: -0.08, -0.01) and MEP (=-0.01, 95%CI: -0.01, -0.002) was significantly associated with birth weight. However, no significant associations were identified for phthalate exposure with birth length, head circumference and chest circumference. Because the limiting of studies, more high-quality case-control studies or cohort studies are urgently needed to draw the best conclusions.

Predicting miRNA-disease associations based on graph attention network with multi-source information.

BACKGROUND: There is a growing body of evidence from biological experiments suggesting that microRNAs (miRNAs) play a significant regulatory role in both diverse cellular activities and pathological processes. Exploring miRNA-disease associations not only can decipher pathogenic mechanisms but also provide treatment solutions for diseases. As it is inefficient to identify undiscovered relationships between diseases and miRNAs using biotechnology, an explosion of computational methods have been advanced. However, the prediction accuracy of existing models is hampered by the sparsity of known association network and single-category feature, which is hard to model the complicated relationships between diseases and miRNAs. RESULTS: In this study, we advance a new computational framework (GATMDA) to discover unknown miRNA-disease associations based on graph attention network with multi-source information, which effectively fuses linear and non-linear features. In our method, the linear features of diseases and miRNAs are constructed by disease-lncRNA correlation profiles and miRNA-lncRNA correlation profiles, respectively. Then, the graph attention network is employed to extract the non-linear features of diseases and miRNAs by aggregating information of each neighbor with different weights. Finally, the random forest algorithm is applied to infer the disease-miRNA correlation pairs through fusing linear and non-linear features of diseases and miRNAs. As a result, GATMDA achieves impressive performance: an average AUC of 0.9566 with five-fold cross validation, which is superior to other previous models. In addition, case studies conducted on breast cancer, colon cancer and lymphoma indicate that 50, 50 and 48 out of the top fifty prioritized candidates are verified by biological experiments. CONCLUSIONS: The extensive experimental results justify the accuracy and utility of GATMDA and we could anticipate that it may regard as a utility tool for identifying unobserved disease-miRNA relationships.

Change of motifs in C. elegans reveals developmental principle of neural network.

Revealing the organizing principles of developing neural networks is a difficult but significant task in neuroscience. As a creature with a rather compact and well-studied neural network, C. elegans is an ideal subject for neuroscience study. However, the researches on its developing neural network remain challenging. The changes in specific properties of neural network across development may uncover part of its principles. Motif is a typical structure property that can be well applied to various complex networks. Here, we study the motif changes in C. elegans neural network across development. By counting the occurrence number of all three-node subgraph motif structures in its neural network at different stages of C. elegans development, along with those in corresponding random networks, we determine which of these structures are motifs for C. elegans, finding out the regular changes of motifs during its development. Combined with the potential function of these subgraph motifs and synaptic information, we gain insight into the organizing principle of neural network during development, which may increase our understanding of neuroscience and inspire the construction of artificial neural network.

Recent Progress in Phase Regulation, Functionalization, and Biosensing Applications of Polyphase MoS2.

The disulfide compounds of molybdenum (MoS2 ) are layered van der Waals materials that exhibit a rich array of polymorphic structures. MoS2 can be roughly divided into semiconductive phase and metallic phase according to the difference in electron filling state of the 4d orbital of Mo atom. The two phases show completely different properties, leading to their diverse applications in biosensors. But to some extent, they compensate for each other. This review first introduces the relationship between phase state and the chemical/physical structures and properties of MoS2 . Furthermore, the synthetic methods are summarized and the preparation strategies for metastable phases are highlighted. In addition, examples of electronic and chemical property designs of MoS2 by means of doping and surface modification are outlined. Finally, studies on biosensors based on MoS2 in recent years are presented and classified, and the roles of MoS2 with different phases are highlighted. This review offers references for the selection of materials to construct different types of biosensors based on MoS2 , and provides inspiration for sensing performance enhancement.

Assessment of network module identification across complex diseases.

Many bioinformatics methods have been proposed for reducing the complexity of large gene or protein networks into relevant subnetworks or modules. Yet, how such methods compare to each other in terms of their ability to identify disease-relevant modules in different types of network remains poorly understood. We launched the 'Disease Module Identification DREAM Challenge', an open competition to comprehensively assess module identification methods across diverse protein-protein interaction, signaling, gene co-expression, homology and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies. Our robust assessment of 75 module identification methods reveals top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets. This community challenge establishes biologically interpretable benchmarks, tools and guidelines for molecular network analysis to study human disease biology.

NLRC5 modulates phenotypic transition and inflammation of human venous smooth muscle cells by activating Wnt/ß-catenin pathway via TLR4 in varicose veins.

In varicose veins, abnormal phenotypic transition and inflammatory response is commonly found in venous smooth muscle cells (VSMCs). We aimed to explore the potential role and mechanism of NLRC5 exerted on VSMCs phenotypic transition and inflammation. NLRC5 expression was detected in varicose veins and platelet-derived growth factor (PDGF)-induced VSMCs by RT-qPCR and Western bolt assays. A loss-of-function assay was performed to evaluate the effects of NLRC5 knockdown on VSMC proliferation, migration, and phenotypic transition. ELISA was used to detect the contents of pro-inflammatory cytokines in the supernatant. The modulation of NLRC5 on TLR4 expression and Wnt/ß-catenin signaling was also evaluated. We found that the expressions of NLRC5 in varicose veins and PDGF-induced VSMCs were upregulated. NLRC5 knockdown inhibited VSMC proliferation and migration. Extracellular matrix transformation was blocked by downregulating NLRC5 with increasing SM-22α expression and MMP-1/TIMP-1 ratio, as well as decreasing OPN and collagen I expressions. Besides, NLRC5 silencing reduced the contents of inflammatory cytokines. Furthermore, we found that NLRC5 regulated TLR4 expression, as well as subsequently activation of Wnt/ß-catenin pathway and nuclear translocation of ß-catenin, which was involved in NLRC5-mediated phenotypic transition and inflammatory in VSMCs. In conclusion, silencing NLRC5 depressed VSMCs' phenotypic transition and inflammation by modulating Wnt/ß-catenin pathway via TLR4. This may provide a theoretical basis for treatment of varicose veins.

Nanosecond tunable laser for the all-optical switching network.

The optically switched network can offset the increasing gap between datacenter traffic growth and electrical switch capacity due to the slowdown of Moore's law. Ultra-high-speed wavelength tunable lasers are especially vital for the high integration and performance improvement of the all-optical switching system. In this paper, a fast tunable laser based on a laser array is realized. The 2×8 matrix structure of the laser array is fabricated by the reconstruction-equivalent-chirp (REC) technique. Aiming at the 2×8 array, a drive control system is designed to provide stable and fast switching, to achieve high-speed switching of the laser wavelength, and to keep the wavelength stable after switching. The simulation and experimental results show that the switching time between any two wavelength channels of the laser is less than 10 ns. The switching time of any two channels of the laser can be reduced by 2-3 ns after the pre-emphasis processing of the electrical signal.

Nanobody-based CAR T cells that target the tumor microenvironment inhibit the growth of solid tumors in immunocompetent mice.

Chimeric antigen receptor (CAR) T cell therapy has been successful in clinical trials against hematological cancers, but has experienced challenges in the treatment of solid tumors. One of the main difficulties lies in a paucity of tumor-specific targets that can serve as CAR recognition domains. We therefore focused on developing VHH-based, single-domain antibody (nanobody) CAR T cells that target aspects of the tumor microenvironment conserved across multiple cancer types. Many solid tumors evade immune recognition through expression of checkpoint molecules, such as PD-L1, that down-regulate the immune response. We therefore targeted CAR T cells to the tumor microenvironment via the checkpoint inhibitor PD-L1 and observed a reduction in tumor growth, resulting in improved survival. CAR T cells that target the tumor stroma and vasculature through the EIIIB+ fibronectin splice variant, which is expressed by multiple tumor types and on neovasculature, are likewise effective in delaying tumor growth. VHH-based CAR T cells can thus function as antitumor agents for multiple targets in syngeneic, immunocompetent animal models. Our results demonstrate the flexibility of VHH-based CAR T cells and the potential of CAR T cells to target the tumor microenvironment and treat solid tumors.

Movable Surface Rotation Angle Measurement System Using IMU.

In this paper, we describe a rotation angle measurement system (RAMS) based on an inertial measurement unit (IMU) developed to measure the rotation angle of a movable surface. The existing IMU-based attitude (tilt) sensor can only accurately measure the rotation angle when the rotation axis of the movable surface is perfectly aligned with the X axis or Y axis of the sensor, which is always not possible in real-world engineering. To overcome the difficulty of sensor installation and ensure measurement accuracy, first, we build a model to describe the relationship between the rotation axis and the IMU. Then, based on the built model, we propose a simple online method to estimate the direction of the rotation axis without using a complicated apparatus and a method to estimate the rotation angle using the known rotation axis based on the extended Kalman filter (EKF). Using the estimated rotation axis direction, we can effectively eliminate the influence of the mounting position on the measurement results. In addition, the zero-velocity detection (ZVD) technique is used to ensure the reliability of the rotation axis direction estimation and is used in combination with the EKF as the switching signal to adaptively adjust the noise covariance matrix. Finally, the experimental results show that the developed RAMS has a static measurement error of less than 0.05° and a dynamic measurement error of less than 1° in the range of ±180°.