A facile fluorescence-coupling approach to visualizing leonurine uptake and distribution in living cells and Caenorhabditis elegans.

BACKGROUND: Caenorhabditis elegans (C. elegans) has been recognized for being a useful model organism in small-molecule drug screens and drug efficacy investigation. However, there remain bottlenecks in evaluating such processes as drug uptake and distribution due to a lack of appropriate chemical tools. PURPOSE: This study aims to prepare fluorescence-labeled leonurine as an example to monitor drug uptake and distribution of small molecule in C. elegans and living cells. METHODS: FITC-conjugated leonurine (leonurine-P) was synthesized and characterized by LC/MS, NMR, UV absorption and fluorescence intensity. Leonurine-P was used to stain C. elegans and various mammalian cell lines. Different concentrations of leonurine were tested in conjunction with a competing parent molecule to determine whether leonurine-P and leonurine shared the same biological targets. Drug distribution was analyzed by imaging. Fluorometry in microplates and flow cytometry were performed for quantitative measurements of drug uptake. RESULTS: The UV absorption peak of leonurine-P was 490∼495 nm and emission peak was 520 nm. Leonurine-P specifically bound to endogenous protein targets in C. elegans and mammalian cells, which was competitively blocked by leonurine. The highest enrichment levels of leonurine-P were observed around 72 h following exposure in C. elegans. Leonurine-P can be used in a variety of cells to observe drug distribution dynamics. Flow cytometry of stained cells can be facilely carried out to quantitatively detect probe signals. CONCLUSIONS: The strategy of fluorescein-labeled drugs reported herein allows quantification of drug enrichment and visualization of drug distribution, thus illustrates a convenient approach to study phytodrugs in pharmacological contexts.

Active substance and mechanisms of Actinidia chinensis Planch for the treatment of breast cancer was explored based on network pharmacology and in silico study.

In this paper, our objective was to investigate the potential mechanisms of Actinidia chinensis Planch (ACP) for breast cancer treatment with the application of network pharmacology, molecular docking, and molecular dynamics. "Mihoutaogen" was used as a key word to query the Traditional Chinese Medicine Systems Pharmacology database for putative ingredients of ACP and its related targets. DrugBank, GeneCards, Online Mendelian Inheritance in Man, and therapeutic target databases were used to search for genes associated with "breast cancer." Using Cytoscape 3.9.0 we then constructed the protein-protein interaction and drug-ingredient-target-disease networks. An enrichment analysis of Kyoto encyclopedia of genes and genomes pathway and gene ontology were performed to exploration of the signaling pathways associated with ACP for breast cancer treatment. Discovery Studio software was applied to molecular docking. Finally, the ligand-receptor complex was subjected to a 50-ns molecular dynamics simulation using the Desmond_2020.4 tools. Six main active ingredients and 176 targets of ACP and 2243 targets of breast cancer were screened. There were 118 intersections of targets for both active ingredients and diseases. Tumor protein P53 (TP53), AKT serine/threonine kinase 1 (AKT1), estrogen receptor 1 (ESR1), Erb-B2 receptor tyrosine kinase 2 (ERBB2), epidermal growth factor receptor (EGFR), Jun Proto-Oncogene (JUN), and Heat Shock Protein 90 Alpha Family Class A Member 1 (HSP90AA1) selected as the most important genes were used for verification by molecular docking and molecular dynamics simulation. The primary active compounds of ACP against breast cancer were predicted preliminarily, and its mechanism was studied, thereby providing a theoretical basis for future clinical studies.

Optimizing cell voltage dependence on size of carbon nanotube-based electrodes in Na-ion and K-ion batteries.

Sodium-ion batteries (NIBs) and potassium-ion batteries (KIBs) are gaining extensive attention as promising alternatives to lithium-ion batteries owing to their superior energy density and cost-effectiveness. However, the larger ionic radius of Na+ and K+ ions in comparison to Li+ ions poses a challenge in designing anode materials characterized by enduring structures and elevated voltage to facilitate the efficacy of high-performance NIBs and KIBs. Carbon nanomaterials, particularly carbon nanotubes (CNTs), have emerged as a potential candidate in anode materials. Herein, we used density functional theory calculations to study the cell voltage of CNTs in relation to Na-ion and K-ion storage as a function of CNT size. The adsorption energy profiles of both Na+@CNT and K+@CNT systems exhibit a descending trend concomitant with the increase in the CNT diameter, where Na+/K+ ion primarily prefers to adsorb in the interior wall of CNT. Conversely, the cell voltage for the Na and K system gradually increases with the increasing diameter of CNT, which can be attributed to the stronger electrostatic interaction validated by energy decomposition calculation. The voltage of Na-ion adsorbed on the inter wall of (10,10) CNT attains 1.29 V, close to the previously theoretical voltage of Li-ion on the same CNT (1.35 V), while the much lower voltage pertaining to K-ion adsorption on the inter wall of (10,10) CNT just stands at 0.59 V, suggesting the viability of CNT-based electrode for NIBs but not for KIBs. These findings lay a solid foundation for delineating the interrelationship between the voltage properties of CNT as prospective anode material and their structural characteristics, thereby expanding the application of CNT-based optoelectronic devices.

Comprehensive in silico characterization of NAC transcription factor family of Pinellia ternata and functional analysis of PtNAC66 under high-temperature tolerance in transgenic Arabidopsis thaliana.

Pinellia ternata, a valuable Chinese herb, suffers yield reduction due to "sprout tumble" under high temperatures. However, the mechanisms underlying its high-temperature stress remain poorly understood. NAM, ATAF1/2, and CUC2 (NAC) transcription factors regulate plant tissue growth and abiotic stress. Hence, there has been no comprehensive research conducted on NAC transcription factors in P. ternata. We identified 98 PtNAC genes unevenly distributed across 13 chromosomes, grouped into 15 families via phylogenetic analysis. Gene expression analysis revealed diverse expression patterns of PtNAC genes in different tissue types. Further studies revealed that PtNAC5/7/17/35/43/47/57/66/86 genes were highly expressed in various tissues of P. ternata and induced by heat stress, among which PtNAC66 was up-regulated at the highest folds induced by heat temperature. PtNAC66 is a nuclear protein that can selectively bind to the cis-responsive region NACRS but lacks the ability to activate transcription in yeast. For further research, PtNAC66 was cloned and transgenic Arabidopsis was obtained. PtNAC66 overexpression increased high-temperature tolerance compared to wild-type plants. Transcriptome profiling demonstrated that overexpression of PtNAC66 led to significant modification of genes responsible for regulating binding, catalytic activity, transcription regulator activity and transporter activity response genes. Additionally, PtNAC66 was found to bind the promoters of CYP707A3, MYB102 and NAC055, respectively, and inhibited their expression, affecting the high-temperature stress response in Arabidopsis. Our research established the foundation for functional studies of PtNAC genes in response to high-temperature forcing by characterizing the P. ternata NAC gene family and examining the biological role of PtNAC66 in plant high-temperature tolerance.

Development of hypertension models for lung cancer screening cohorts using clinical and thoracic aorta imaging factors.

This study aims to develop and validate nomogram models utilizing clinical and thoracic aorta imaging factors to assess the risk of hypertension for lung cancer screening cohorts. We included 804 patients and collected baseline clinical data, biochemical indicators, coexisting conditions, and thoracic aorta factors. Patients were randomly divided into a training set (70%) and a validation set (30%). In the training set, variance, t-test/Mann-Whitney U-test and standard least absolute shrinkage and selection operator were used to select thoracic aorta imaging features for constructing the AIScore. Multivariate logistic backward stepwise regression was utilized to analyze the influencing factors of hypertension. Five prediction models (named AIMeasure model, BasicClinical model, TotalClinical model, AIBasicClinical model, AITotalClinical model) were constructed for practical clinical use, tailored to different data scenarios. Additionally, the performance of the models was evaluated using receiver operating characteristic (ROC) curves, calibration curves and decision curve analyses (DCA). The areas under the ROC curve for the five models were 0.73, 0.77, 0.83, 0.78, 0.84 in the training set, and 0.77, 0.78, 0.81, 0.78, 0.82 in the validation set, respectively. Furthermore, the calibration curves and DCAs of both sets performed well on accuracy and clinical practicality. The nomogram models for hypertension risk prediction demonstrate good predictive capability and clinical utility. These models can serve as effective tools for assessing hypertension risk, enabling timely non-pharmacological interventions to preempt or delay the future onset of hypertension.

Transient Neonatal Myasthenia Gravis Born to a Mother with Asymptomatic MG: A Case Report.

Myasthenia gravis (MG) is an autoimmune disease which can impact pregnancy. We describe a transient neonatal myasthenia gravis (TNMG) born to an asymptomatic mother aged 26. The newborn presented cyanosis and generalized muscular weakness quickly after birth. Nasal continuous positive airway pressure (nCPAP) ventilation was performed immediately. On day 3, detailed family history showed that the neonate's 50-year-old maternal grandmother was diagnosed as ocular MG at the age of 40. Ryanodine receptor calcium release channel antibody (RyR-Ab) and acetylcholine receptor antibody (AChR-Ab) tested on day 5 were positive. However, neostigmine tests were negative for the neonate. Intravenous immunoglobulin (IVIG) and oral pyridostigmine were administered. The infant was weaned from the ventilator on day 7. On day 10, the neonate's asymptomatic mother was confirmed to have positive AChR-Ab either. The neonate regained the capability of bottle feeding on day 17 and discharged on day 26. Asymptomatic pregnant women with MG family history can also deliver infants who develop TNMG. Testing AChR antibodies in pregnant women with a family history of MG should be necessary as TNMG was a life-threatening disease. With timely diagnosis and accurate treatment, TNMG can be effectively relieved.

MCPNET: Development of an interpretable deep learning model based on multiple conformations of the compound for predicting developmental toxicity.

The development of deep learning models for predicting toxicological endpoints has shown great promise, but one of the challenges in the field is the accuracy and interpretability of these models. The bioactive conformation of a compound plays a critical role for it to bind in the target. It is a big issue to figure out the bioactive conformation in deep learning without the co-crystal structure or highly precise molecular simulations. In this study, we developed a deep learning framework of Multi-Conformation Point Network (MCPNET) to construct classification and regression models, respectively, based on electrostatic potential distributions on vdW surfaces around multiple conformations of the compound using a dataset of compounds with developmental toxicity in zebrafish embryo. MCPNET applied 3D multi-conformational surface point cloud to extract the molecular features for model training, which may be critical for capturing the structural diversity of compounds. The models achieved an accuracy of 85 % on the classification task and R2 of 0.66 on the regression task, outperforming traditional machine learning models and other deep learning models. The key feature of our model is its interpretability with the component visualization to identify the factors contributing to the prediction and to understand the compound action mechanism. MCPNET may predict the conformation quietly close to the bioactive conformation of a compound by attention-based multi-conformation pooling mechanism. Our results demonstrated the potential of deep learning based on 3D molecular representations in accurately predicting developmental toxicity. The source code is publicly available at https://github.com/Superlit-CC/MCPNET.

Interventions to address parenting stress among caregivers of children with chronic diseases: An umbrella review.

BACKGROUND: Caregivers of children with chronic diseases suffer from great parenting pressure, which directly affects the treatment and rehabilitation of children, reduces the quality of life of caregivers and damages family functioning. Existing reviews have not systematically summarized and evaluated interventions for parenting stress in caregivers of children with chronic diseases. DATA SOURCES: Embase, PubMed, Web of Science, OVID, CNKI, CBM, Wan Fang and Cochrane Library were searched for eligible reviews in November 2021 and October 2022. METHODS: Two reviewers independently screened titles and abstracts, reviewed full texts of articles for eligibility, and appraised the quality of reviews using JBI. The quality of the evidence was assessed using GRADE. Findings are reported in accordance with PRISMA checklist. Narrative summaries grouped findings by intervention types. RESULTS: Out of 2632 records, we included 21 systematic reviews for a synthesis. Interventions for parenting stress in children with chronic diseases were divided into seven categories. Cognitive behavioural interventions, psychosocial interventions, child behavioural and/or developmental parent interventions and synthesized interventions have shown high-level evidence in reducing parenting stress for caregivers of children with chronic diseases. Furthermore, outcome measures and intervention protocols were highly heterogeneous across interventions. CONCLUSIONS: This umbrella review suggest that reducing the parenting stress of caregivers of children with chronic diseases can directly target caregivers' parenting stress through cognitive behavioural interventions/psychosocial interventions and/or provide guidance to parents on the behavioural and developmental problems of children with chronic diseases. A more standardized approach to outcome measures is essential to assess efficacy and compare interventions across studies. RELEVANCE TO CLINICAL PRACTICE: The findings provide information and evidence for reducing parenting stress among caregivers of children with chronic diseases to guide the development of comprehensive intervention strategies. PATIENT OR PUBLIC CONTRIBUTION: Patient or public contribution does not apply to this study.

Using a cyclocarbon additive as a cyclone separator to achieve fast lithiation and delithiation without dendrite growth in lithium-ion batteries.

Carbon materials are widely used for reversible lithium uptake in the anode of lithium-ion batteries. Nevertheless, the challenge of uncontrollable dendrite deposition during fast charge-discharge cycles remains a grand hurdle. Various strategies have been explored to prevent detrimental heterogeneous dendrite metal deposits, such as interface engineering and electrolyte modification, but they often compromise the reverse diffusion freedom of Li+ ions during discharging and are incompatible with the most mainstream use of graphite as an anode material. Here, we propose the incorporation of a novel carbon allotrope of cyclocarbon as a potential additive in the anode. In contrast to conventional carbon materials, density functional theory calculations reveal that cyclocarbon has a much higher affinity for Li atoms than Li+ ions, even surpassing the inherent cohesion of Li atoms, due to the charge transfer from the 2s orbital of Li atoms to the unique in-plane π orbital of cyclocarbon. Furthermore, ab initio molecular dynamics simulations show that Li+ ions can shuttle freely back and forth across cyclocarbon, whereas the lithiation process for Li atoms occurs rapidly within picoseconds. The delithiation of Li atoms within cyclocarbon follows a voltage-gated mechanism that is effectively controlled by an external electric field of 3 V nm-1. Remarkably, cyclocarbon exhibits potential compatibility with commercialized graphite electrodes via the π-π interaction and also can be extended to sodium-ion and potassium-ion batteries. These distinct compatibility, scalability and electrochemical properties of cyclocarbon provide a new avenue to realize both safety and ultrafast rechargeable performance of ion batteries.

EpCAM-targeting CAR-T cell immunotherapy is safe and efficacious for epithelial tumors.

The efficacy of CAR-T cells for solid tumors is unsatisfactory. EpCAM is a biomarker of epithelial tumors, but the clinical feasibility of CAR-T therapy targeting EpCAM is lacking. Here, we report pre- and clinical investigations of EpCAM-CAR-T cells for solid tumors. We demonstrated that EpCAM-CAR-T cells costimulated by Dectin-1 exhibited robust antitumor activity without adverse effects in xenograft mouse models and EpCAM-humanized mice. Notably, in clinical trials for epithelial tumors (NCT02915445), 6 (50%) of the 12 enrolled patients experienced self-remitted grade 1/2 toxicities, 1 patient (8.3%) experienced reversible grade 3 leukopenia, and no higher-grade toxicity reported. Efficacy analysis determined two patients as partial response. Three patients showed >23 months of progression-free survival, among whom one patient experienced 2-year progress-free survival with detectable CAR-T cells 200 days after infusion. These data demonstrate the feasibility and tolerability of EpCAM-CAR-T therapy.

Quantitative assessment of airway wall thickness in COPD patients with interstitial lung abnormalities.

Background: Whether the airway is involved in the pathogenesis of interstitial lung abnormalities (ILA) is not well understood. Also the impact of ILA on lung function in COPD patients remains controversial. We aimed to assess the quantitative CT measurements of airway wall thickness (AWT) and lung function according to ILA status in COPD patients. Methods: 157 COPD patients discharged from our hospital from August 1, 2019 through August 31, 2022 who underwent chest CT imagings and pulmonary function tests were retrospectively enrolled. Linear regression analysis and multiple models were used to analyze associations between quantitative assessment of airway wall changes and the presence of ILA. Results: In 157 COPD patients, 23 patients (14.6%) had equivocal ILA, 42 patients (26.8%) had definite ILA. The definite ILA group had the highest measurements of Pi10 (square root of theoretical airway wall area with a lumen perimeter of 10 mm), segmental AWT and segmental WA% (percentage of wall area), whereas the no ILA group had the lowest measurements of Pi10, segmental AWT and segmental WA%. In the adjusted analyses (adjusted by age, sex, body mass index, smoking intensity, COPD GOLD stage, lung function, slice thickness and scanner type), compared to COPD patients without ILA, the measurements of Pi10, segmental AWT and segmental WA% were higher in definite ILA group with differences of 0.225 mm (p = 0.012), 0.152 mm (p < 0.001), 4.8% (p < 0.001) respectively. COPD patients with definite ILA tended to have higher FEV1% predicted, FVC% predicted and lower MMEF75/25% predicted, but there were no statistically differences among the three groups. Conclusion: Our study demonstrates the higher AWT measures in COPD patients with ILA compared to the patients without ILA. These findings suggest that the airway may be involved in the pathogenesis of ILA.

Chimeric Antigen Receptor-T Cell Therapy Decreases Distant Metastasis and Inhibits Local Recurrence Post-surgery in Mice.

Distant metastasis and primary tumor relapse are the two main hurdles to the success of surgical treatment for cancer patients. Circulating tumor cells (CTCs) and incomplete surgical resection are the primary cause of distant metastasis and local recurrence of tumors, respectively. Chimeric antigen receptor (CAR)-modified T cells target residual carcinomas and CTCs hold the potential to inhibit primary recurrence and reduce tumor metastasis, but the experimental evidence is lacking. Here, we developed a surgery-induced tumor metastasis model in immunocompetent mice to investigate the efficacy of CAR-T cells therapy in preventing metastasis and local recurrence. We observed that subcutaneous tumor resection has induced a large number of CTCs intravasated into circulation. EpCAM-specific CAR-T was effective in clearing CTCs following surgical removal of the tumor. This resulted in less pulmonary metastasis and longer survival in mice when compared to mice treated with surgery followed by Mock-T cells infusion. In addition, the local relapse was obviously inhibited at the surgical site followed by EpCAM-CAR-T cell treatment. This study demonstrated that CAR-T cell therapy can be an adjuvant treatment following surgery to prevent tumor metastasis and inhibit primary tumor relapse for cancer patients.

Transcriptome Analysis Reveals Long Non-Coding RNAs Involved in Shade-Induced Growth Promotion in Pinellia ternata.

BACKGROUND: High temperature and drought environments are important limiting factors for Pinellia ternata growth, whereas shading can promote growth by relieving these stresses. However, the mechanism of growth promotion by shading in P. ternata is unknown. Long non-coding RNAs (lncRNAs) play important roles in the plant's growth and environmental response, but few analyses of lncRNAs in P. ternata have been reported. METHODS: We performed lncRNAs analysis of P. ternata in response to shading using RNA-seq data from our previous studies. A total of 13,927 lncRNAs were identified, and 145 differentially expressed lncRNAs (DELs) were obtained from the comparisons of 5 days shade (D5S) vs. 5 days of natural light (D5CK), 20 days of shade (D20S) vs. 20 days of natural light (D20CK), D20S vs. D5S, and D20CK vs. D5CK. Of these, 119 DELs (82.07%) were generated from the D20S vs. D20CK comparison. RESULTS: Gene ontology (GO) analysis indicated that the reactive oxygen (ROS) metabolism and programmed cell death (PCD) processes might regulate shade-induced growth promotion. The "signal transduction" and "environmental adaptation" in the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used for lncRNA-mRNA regulatory network construction and showed that the lncRNAs might mediate P. ternata growth by regulating ROS accumulation and light signals. CONCLUSIONS: This study explores lncRNAs' functions and regulatory mechanisms related to P. ternata growth and lays a foundation for further research on P. ternata.

Fine-Tuning Electrolyte Concentration and Metal-Organic Framework Surface toward Actuating Fast Zn2+ Dehydration for Aqueous Zn-Ion Batteries.

Functional porous coating on zinc electrode is emerging as a powerful ionic sieve to suppress dendrite growth and side reactions, thereby improving highly reversible aqueous zinc ion batteries. However, the ultrafast charge rate is limited by the substantial cation transmission strongly associated with dehydration efficiency. Here, we unveil the entire dynamic process of solvated Zn2+ ions' continuous dehydration from electrolyte across the MOF-electrolyte interface into channels with the aid of molecular simulations, taking zeolitic imidazolate framework ZIF-7 as proof-of-concept. The moderate concentration of 2 M ZnSO4 electrolyte being advantageous over other concentrations possesses the homogeneous water-mediated ion pairing distribution, resulting in the lowest dehydration energy, which elucidates the molecular mechanism underlying such concentration adopted by numerous experimental studies. Furthermore, we show that modifying linkers on the ZIF-7 surface with hydrophilic groups such as -OH or -NH2 can weaken the solvation shell of Zn2+ ions to lower the dehydration free energy by approximately 1 eV, and may improve the electrical conductivity of MOF. These results shed light on the ions delivery mechanism and pave way to achieve long-term stable zinc anodes at high capacities through atomic-scale modification of functional porous materials.

Characterizing polyproline II conformational change of collagen superhelix unit on adsorption on gold surface.

The dynamic process of protein binding onto a metal surface is a frequent occurrence as gold nanoparticles are increasingly being used in biomedical applications, including wound treatment and drug transport. Collagen, as a major component of the extracellular matrix, has potentially advantageous biomedical applications, due to its excellent biocompatibility and elasticity properties. Therefore, a mechanistic comprehension of how and which species in collagen interact with gold nanoparticles is a prerequisite for collagen-gold complexes in clinical application. However, the dynamic behavior of collagen with the polyproline II (PPII) conformation on gold sheets at the molecular level is too complex to capture under current experimental conditions. Here, using molecular dynamics simulations, we investigate the adsorption process and conformational behavior of the tripeptide Gly-Pro-Hyp with the repetitive unit of the collagen superhelix on the gold surface as a function of number of repeating units from 1 to 10. The different numbers of repeating units all prefer to approach the gold surface and adsorb via charged residues at the C-terminal or N-terminal ends, tending to form arch structures on the gold surface. Compared with the various tripeptide units in solution still retaining the native PPII conformation, the presence of the gold surface affects the formation of hydrogen bonds between the protein and water molecules, thus disrupting the PPII conformation of collagen. Specifically, the interaction between the gold surface and HYP limits the rotation of the dihedral angle of collagen, resulting in a tendency for the PPII conformation of the gold surface to transform to the ß-sheet conformation. The results provide an indication of how to improve the interaction between the terminal groups and the gold surface for the design of a bioavailable protein-gold material for medicinal purposes.

Chimeric antigen receptor engineered natural killer cells for cancer therapy.

Natural killer (NK) cells, a unique component of the innate immune system, are inherent killers of stressed and transformed cells. Based on their potent capacity to kill cancer cells and good tolerance of healthy cells, NK cells have been successfully employed in adoptive cell therapy to treat cancer patients. In recent years, the clinical success of chimeric antigen receptor (CAR)-T cells has proven the vast potential of gene-manipulated immune cells as the main force to fight cancer. Following the lessons learned from mature gene-transfer technologies and advanced strategies in CAR-T therapy, NK cells have been rapidly explored as a promising candidate for CAR-based therapy. An exponentially growing number of studies have employed multiple sources of CAR-NK cells to target a wide range of cancer-related antigens, showing remarkable outcomes and encouraging safety profiles. Clinical trials of CAR-NK cells have also shown their impressive therapeutic efficacy in the treatment of hematological tumors, but CAR-NK cell therapy for solid tumors is still in the initial stages. In this review, we present the favorable profile of NK cells as a potential platform for CAR-based engineering and then summarize the outcomes and strategies of CAR-NK therapies in up-to-date preclinical and clinical investigations. Finally, we evaluate the challenges remaining in CAR-NK therapy and describe existing strategies that can assist us in devising future prospective solutions.

Co-infusion of CAR T cells with aAPCs expressing chemokines and costimulatory ligands enhances the anti-tumor efficacy in mice.

Chimeric antigen receptor-modified T (CAR-T) cell therapy has shown curable efficacy for treating hematological malignancies, while in solid tumors, the immunosuppressive microenvironment causes poor activation, expansion and survival of CAR-T cells, accounting mainly for the unsatisfactory efficacy. The artificial antigen-presenting cells (aAPCs) have been used for ex vivo expansion and manufacturing of CAR-T cells. Here, we constructed a K562 cell-based aAPCs expressing human epithelial cell adhesion molecule (EpCAM), chemokines (CCL19 and CCL21) and co-stimulatory molecular ligands (CD80 and 4-1BBL). Our data demonstrated that the novel aAPCs enhanced the expansion, and increased the immune memory phenotype and cytotoxicity of CAR-T cells recognizing EpCAM, in vitro. Of note, co-infusion CAR-T and aAPC enhances the infiltration of CAR-T cells in solid tumors, which has certain potential for the treatment of solid tumors Moreover, IL-2-9-21, a cytokine cocktail, prevents CAR-T cells from entering the state of exhaustion prematurely after continuous antigen engagement and boosts the anti-tumor activity of CAR-T cells co-infused with aAPCs. These data provide a new strategy to enhance the therapeutic potential of CAR-T cell therapy for the treatment of solid tumors.

Synthesis of 2,3-Fused Quinazolinones via the Radical Cascade Pathway and Reaction Mechanistic Studies by DFT Calculations.

An efficient radical cascade cyclization of unactivated alkenes toward the synthesis of a series of ring-fused quinazolinones has been developed in moderate to excellent yields using commercially available ethers, alkanes, and alcohols, respectively, under a base-free condition in a short time without a transition metal as catalyst. Notably, the transformations can be carried out with the advantages of a broad substrate scope and high atomic economy. Density functional theory calculations and wavefunction analyses were performed to elucidate the radical reaction mechanism.

Development of meso-Five-Membered Heterocycle BODIPY-Based AIE Fluorescent Probes for Dual-Organelle Viscosity Imaging.

Fluorescent rotors with aggregation-induced emission (AIE) and organelle-targeting properties have attracted great attention for sensing subcellular viscosity changes, which could help understand the relationships of abnormal fluctuations with many associated diseases. Despite the numerous efforts spent, it remains rare and urgent to explore the dual-organelle targeting probes and their structural relationships with viscosity-responsive and AIE properties. Therefore, in this work, we reported four meso-five-membered heterocycle-substituted BODIPY-based fluorescent probes, explored their viscosity-responsive and AIE properties, and further investigated their subcellular localization and viscosity-sensing applications in living cells. Interestingly, the meso-thiazole probe 1 showed both good viscosity-responsive and AIE (in pure water) properties and could successfully target both mitochondria and lysosomes, further imaging cellular viscosity changes by treating lipopolysaccharide and nystatin, attributing to the free rotation and potential dual-organelle targeting ability of the meso-thiazole group. The meso-benzothiophene probe 3 with a saturated sulfur only showed good viscosity-responsive properties in living cells with the aggregation-caused quenching effect and no subcellular localization. The meso-imidazole probe 2 showed the AIE phenomenon without an obvious viscosity-responsive property with a C═N bond, while the meso-benzopyrrole probe 4 displayed fluorescence quenching in polar solvents. Therefore, for the first time, we investigated the structure-property relationships of four meso-five-membered heterocycle-substituted BODIPY-based fluorescent rotors with viscosity-responsive and AIE properties, and among these, 1 with a C═N bond and a saturated sulfur on the meso-thiazole, potentially contributing to their corresponding AIE and viscosity-responsive properties, served as a sensitive AIE fluorescent rotor for imaging dual-organelle viscosity in both mitochondria and lysosomes.

Segment aorta and localize landmarks simultaneously on noncontrast CT using a multitask learning framework for patients without severe vascular disease.

BACKGROUND: Non-contrast chest CT is widely used for lung cancer screening, and its images carry potential information of the thoracic aorta. The morphological assessment of the thoracic aorta may have potential value in the presymptomatic detection of thoracic aortic-related diseases and the risk prediction of future adverse events. However, due to low vasculature contrast in such images, visual assessment of aortic morphology is challenging and highly depends on physicians' experience. PURPOSE: The main objective of this study is to propose a novel multi-task framework based on deep learning for simultaneous aortic segmentation and localization of key landmarks on unenhanced chest CT. The secondary objective is to use the algorithm to measure quantitative features of thoracic aorta morphology. METHODS: The proposed network is composed of two subnets to carry out segmentation and landmark detection, respectively. The segmentation subnet aims to demarcate the aortic sinuses of the Valsalva, aortic trunk and aortic branches, whereas the detection subnet is devised to locate five landmarks on the aorta to facilitate morphology measures. The networks share a common encoder and run decoders in parallel, taking full advantage of the synergy of the segmentation and landmark detection tasks. Furthermore, the volume of interest (VOI) module and the squeeze-and-excitation (SE) block with attention mechanisms are incorporated to further boost the capability of feature learning. RESULTS: Benefiting from the multitask framework, we achieved a mean Dice score of 0.95, average symmetric surface distance of 0.53 mm, Hausdorff distance of 2.13 mm for aortic segmentation, and mean square error (MSE) of 3.23 mm for landmark localization in 40 testing cases. CONCLUSION: We proposed a multitask learning framework which can perform segmentation of the thoracic aorta and localization of landmarks simultaneously and achieved good results. It can support quantitative measurement of aortic morphology for further analysis of aortic diseases, such as hypertension.