Discovery of Bimetallic Hexagonal MBene Mo2ErB3T2.5 (T = O, F, and Cl).

Exfoliation from quaternary hexagonal MAB (h-MAB) phases has been suggested as a method for producing 2D in-plane ordered MBenes (i-MBenes) with the general formula (M'2/3M″1/3)2AB2. However, experimental realization of defect-free i-MBenes has not been achieved yet due to the absence of a suitable parent quaternary h-MAB phase. In this study, a machine learning (ML) model is used to predict the stability of 15771 quaternary h-MAB phases generated by considering 33 transition metals for the M site and 16 p-block elements for the A site. Out of these compounds, only 195 are identified as potentially stable. Subsequent high-precision first-principles calculations confirm that 47 of them exhibit both thermodynamic and dynamic stability. Their potential for exfoliation into bimetallic i-MBenes is investigated by bonding analysis. Leveraging these theoretical insights, a bimetallic i-MBene is successfully synthesized, namely 2D Mo2ErB3T2.5 (T = F, Cl and O). Further experimental scrutiny reveals its excellent performance for the hydrogen evolution reaction (HER), highlighting the application potential of bimetallic i-MBenes.

A new nuclear phylogeny of the tea family (Theaceae) unravels rapid radiations in genus Camellia.

Molecular analyses of rapidly radiating groups often reveal incongruence between gene trees. This mainly results from incomplete lineage sorting, introgression, and gene tree estimation error, which complicate the estimation of phylogenetic relationships. In this study, we reconstruct the phylogeny of Theaceae using 348 nuclear loci from 68 individuals and two outgroup taxa. Sequence data were obtained by target enrichment using the recently released Angiosperm 353 universal probe set applied to herbarium specimens. The robustness of the topologies to variation in data quality was established under a range of different filtering schemes, using both coalescent and concatenation approaches. Our results confirmed most of the previously hypothesized relationships among tribes and genera, while clarifying additional interspecific relationships within the rapidly radiating genus Camellia. We recovered a remarkably high degree of gene tree heterogeneity indicative of rapid radiation in the group and observed cytonuclear conflicts, especially within Camellia. This was especially pronounced around short branches, which we primarily associate with gene tree estimation error. Our analysis also indicates that incomplete lineage sorting (ILS) contributed to gene-tree conflicts and accounted for approximately 14 % of the explained variation, whereas inferred introgression levels were low. Our study advances the understanding of the evolution of this important plant family and provides guidance on the application of target capture methods and the evaluation of key processes that influence phylogenetic discordances.

Machine Learning-Accelerated Discovery of A2BC2 Ternary Electrides with Diverse Anionic Electron Densities.

This study combines machine learning (ML) and high-throughput calculations to uncover new ternary electrides in the A2BC2 family of compounds with the P4/mbm space group. Starting from a library of 214 known A2BC2 phases, density functional theory calculations were used to compute the maximum value of the electron localization function, indicating that 42 are potential electrides. A model was then trained on this data set and used to predict the electride behavior of 14,437 hypothetical compounds generated by structural prototyping. Then, the stability and electride features of the 1254 electride candidates predicted by the model were carefully checked by high-throughput calculations. Through this tiered approach, 41 stable and 104 metastable new A2BC2 electrides were predicted. Interestingly, all three kinds of electrides, i.e., electron-deficient, electron-neutral, and electron-rich electrides, are present in the set of predicted compounds. Three of the most promising new electrides (two electron-rich, Nd2ScSi2 and La2YbGe2, and one electron-deficient Y2LiSi2) were then successfully synthesized and characterized experimentally. Furthermore, the synthesized electrides were found to exhibit high catalytic activities for NH3 synthesis under mild conditions when Ru-loaded. The electron-deficient Y2LiSi2, in particular, was seen to exhibit a good balance of catalytic activity and chemical stability, suggesting its future application in catalysis.

Phytogeographic History of the Tea Family Inferred Through High-Resolution Phylogeny and Fossils.

The tea family (Theaceae) has a highly unusual amphi-Pacific disjunct distribution: most extant species in the family are restricted to subtropical evergreen broadleaf forests in East Asia, while a handful of species occur exclusively in the subtropical and tropical Americas. Here, we used an approach that integrates the rich fossil evidence of this group with phylogenies in biogeographic analysis to study the processes behind this distribution pattern. We first combined genome-skimming sequencing with existing molecular data to build a robust species-level phylogeny for c.130 Theaceae species, resolving most important unclarified relationships. We then developed an empirical Bayesian method to incorporate distribution evidence from fossil specimens into historical biogeographic analyses and used this method to account for the spatiotemporal history of Theaceae fossils. We compared our method with an alternative Bayesian approach and show that it provides consistent results while significantly reduces computational demands which allows analyses of much larger data sets. Our analyses revealed a circumboreal distribution of the family from the early Cenozoic to the Miocene and inferred repeated expansions and retractions of the modeled distribution in the Northern Hemisphere, suggesting that the current Theaceae distribution could be the remnant of a larger continuous distribution associated with the boreotropical forest that has been hypothesized to occupy most of the northern latitudes in the early Cenozoic. These results contradict with studies that only considered current species distributions and showcase the necessity of integrating fossil and molecular data in phylogeny-based parametric biogeographic models to improve the reliability of inferred biogeographical events. [Biogeography; genome skimming; phylogenomics; plastid genome; Theaceae.].

The diagnostic performance of ultrasound computer-aided diagnosis system for distinguishing breast masses: a prospective multicenter study.

OBJECTIVES: To evaluate the diagnostic value of computer-aided diagnosis (CAD) software on ultrasound in distinguishing benign and malignant breast masses and avoiding unnecessary biopsy. METHODS: This prospective, multicenter study included patients who were scheduled for pathological diagnosis of breast masses between April 2019 and November 2020. Ultrasound images, videos, CAD analysis, and BI-RADS were obtained. The AUC, accuracy, sensitivity, specificity, PPV, and NPV were calculated and compared with radiologists. RESULTS: Overall, 901 breast masses in 901 patients were enrolled in this study. The accuracy, sensitivity, specificity, PPV and NPV of CAD software were 89.6%, 94.2%, 87.0%, 80.4%, and 96.3, respectively, in the long-axis section; 89.0%, 91.4%, 87.7%, 80.8%, and 94.7%, respectively, in the short-axis section. With BI-RADS 4a as the cut-off value, CAD software has a higher AUC (0.906 vs 0.734 vs 0.696, all p < 0.001) than both experienced and less experienced radiologists. With BI-RADS 4b as the cut-off value, CAD software showed better AUC than less experienced radiologists (0.906 vs 0.874, p < 0.001), but not superior to experienced radiologists (0.906 vs 0.883, p = 0.057). After the application of CAD software, the unnecessary biopsy rate of BI-RADS categories 4 and 5 was significantly decreased (33.0% vs 11.9%, 37.8% vs 14.5%), and the malignant rate of biopsy in category 4a was significantly increased (11.6% vs 40.7%, 7.4% vs 34.9%, all p < 0.001). CONCLUSIONS: CAD software on ultrasound can be used as an effective auxiliary diagnostic tool for differential diagnosis of benign and malignant breast masses and reducing unnecessary biopsy. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov (NCT03887598) KEY POINTS: • Prospective multicenter study showed that computer-aided diagnosis software provides greater diagnostic confidence for differentiating benign and malignant breast masses. • Computer-aided diagnosis software can help radiologists reduce unnecessary biopsy. • The management of patients with breast masses becomes more appropriate.

The Added Value of a Computer-Aided Diagnosis System in Differential Diagnosis of Breast Lesions by Radiologists With Different Experience.

OBJECTIVES: To evaluate the value of the computer-aided diagnosis system, S-Detect (based on deep learning algorithm), in distinguishing benign and malignant breast masses and reducing unnecessary biopsy based on the experience of radiologists. METHODS: From February 2018 to March 2019, 266 breast masses in 192 women were included in our study. Ultrasound (US) examination, including S-Detect technique, was performed by the radiologist with about 10 years of clinical experience in breast US imaging. US images were analyzed by four other radiologists with different experience in breast imaging (radiologists 1, 2, 3, and 4 with 1, 4, 9, and 20 years, respectively) according to their clinical experience (with and without the results of S-Detect). Diagnostic capabilities and unnecessary biopsy of radiologists and radiologists combined with S-Detect were compared and analyzed. RESULTS: After referring to the results of S-Detect, the changes made by less experienced radiologists were greater than experienced radiologists (benign or malignant, 44 vs 22 vs 14 vs 2; unnecessary biopsy, 34 vs 25 vs 10 vs 5). When combined with S-Detect, less experienced radiologists showed significant improvement in accuracy, specificity, positive predictive value, negative predictive value, and area under curve (P < .05), but not for experienced radiologists (P > .05). Similarly, the unnecessary biopsy rate of less experienced radiologists decreased significantly (44.4% vs 32.7%, P = .006; 36.8% vs 28.2%, P = .033), but not for experienced radiologists (P > .05). CONCLUSIONS: Less experienced radiologists rely more on S-Detect software. And S-Detect can be an effective decision-making tool for breast US, especially for less experienced radiologists.

[Research on quality difference of standard decoction of raw and fried Paeoniae Radix Alba based on fingerprint and multicomponent determination].

The extract rates, multicomponent content and fingerprint were determined in this study to investigate the quality diffe-rence between standard decoction of raw Paeoniae Radix Alba and fried Paeoniae Radix Alba. UPLC fingerprint was established for 17 batches of standard decoction of raw and fried Paeoniae Radix Alba, and the contents of gallic acid, catechin, albiflorin, paeoniflorin and benzoyl paeoniflorin were determined. The peak areas of standard decoction were analyzed by the independent t-test and orthogonal partial least squares discriminant analysis. There was no significant difference in extract rates between the standard decoction of raw and fried Paeoniae Radix Alba. After fried processing, the content of albiflorin increased by 0.26%, while the contents of gallic acid, catechin, paeoniflorin and benzoyl paeoniflorin decreased by 13.04%, 27.97%, 10.30% and 18.79% respectively. There were 14 common peaks in the fingerprint of standard decoction of raw Paeoniae Radix Alba, and 16 common peaks in the fried Paeoniae Radix Alba. Peak 1 and peak 3 were new ones after processing, among which the peak 3 was 5-hydroxymethylfurfural. The results showed that peak 1, peak 3, peak 11 and peak 15 were the key compounds to distinguish standard decoction of raw and fried Paeoniae Radix Alba. In conclusion, this method is stable and can be used for the study of quantity transfer and quality control in the preparation process of standard decoction, granules and other dosage forms for raw and fried Paeoniae Radix Alba, providing reference for the identification of raw and fried Paeoniae Radix Alba and related preparations.

Triptolide induces mitochondria-mediated apoptosis of Burkitt's lymphoma cell via deacetylation of GSK-3ß by increased SIRT3 expression.

Burkitt's lymphoma (BL) is a highly aggressive B-cell non-Hodgkin lymphoma with rapid growth and dissemination propensity. Triptolide (TP), an active component extracted from Chinese herb Tripterygium wilfordii Hook f., has broad-spectrum anti-tumor activities. This study aimed to explore the in vitro and in vivo anti-cancer effects of TP on BL and the potential molecular mechanisms. In this study, the in vitro anti-tumor activity of TP was determined by CCK-8 and flow cytometry assays in Raji, NAMALWA and Daudi cells. The expression of SIRT3, phosphorylation and acetylation of glycogen synthase kinase-3ß (GSK-3ß) were analyzed by Western blot assay. Moreover, we examined the mitochondrial membrane potential by JC-1 method and measured apoptosis related protein using Western blot assay. BL xenograft model in NOD/SCID mice were established to evaluate the in vivo anti-cancer effect of TP. We discovered that TP inhibited BL cell growth and induced apoptosis in a dose-dependent manner. Loss of SIRT3 provides growth advances for BL cells. However, TP could up-regulate SIRT3 expression, which resulted in suppression of BL cells proliferation. GSK-3ß was activated by SIRT3-mediated deacetylation, which subsequently induced mitochondrial translocation and accumulation of Bax and decrease of mitochondrial membrane potential. Anti-tumor studies in vivo showed that TP (0.36 mg/kg) inhibited the growth of BL xenografts in NOD/SCID mice with an inhibitory rate of 73.13%. Our data revealed that TP triggered mitochondrial apoptotic pathway in BL by increasing SIRT3 expression and activating SIRT3/GSK-3ß/Bax pathway. This study indicated that TP is a potential anti-cancer Chinese herbal medicine against BL.

Metabolic effects of Hedyotis diffusa on rats bearing Walker 256 tumor revealed by NMR-based metabolomics.

Hedyotis diffusa, a traditional Chinese herbal medicine, is widely used for oncotherapy and shows a positive effect in the clinical treatment. But its mechanism of anticancer activities is complicated and unclear. This study was undertaken to assess the therapeutic effects and reveal detailed mechanisms of H. diffusa for oncotherapy. A Walker 256 tumor-bearing rat model was established, and metabolomic profiles of plasma and urine were obtained from 1 H NMR technique. Multivariate statistical analysis methods were used to characterize the discriminating metabolites between control (C), Walker 256 tumor-bearing rats model (M), and H. diffusa treatment (H) groups. Finally, 13 and 10 metabolomic biomarkers in urine and plasma samples were further identified as characteristic metabolites in M group, whereas H group showed a partial metabolic balance recovered, such as ornithine, N-acetyl-l-aspartate, l-aspartate, and creatinine in urine samples, and acetate, lactate, choline, l-glutamine, and 3-hydroxybutyrate in plasma samples. On the basis of the methods above, we hypothesized H. diffusa treatment reduced the injury caused by Walker 256 tumor and maintained a metabolic balance. Our study demonstrated that this method provided new insights into metabolic alterations in tumor-bearing biosystems and researching on the effects of H. diffusa on the endogenous metabolism in tumor-bearing rats.

A rising Layered Boride Family for Energy and Catalysis Applications: Novel Hexagonal MAB phases and MBenes.

Over the past decade, conventional MAX phases and MXenes have garnered significant interest, primarily limited to carbides and/or nitrides. However, in 2019, the hexagonal ternary boride Ti2InB2 was successfully synthesized, sparking extensive research into hexagonal MAB (h-MAB) phases and their derived MBenes (h-MBenes). In recent years, h-MAB and h-MBenes have become focal points in the fields of physics, chemistry, and materials science. The unique properties and promising performances of h-MBenes in catalysis, energy storage, spintronics, and electrical devices underscore their considerable potential. Nonetheless, the exploration of h-MAB and h-MBenes is still in its nascent stages, with many anticipated properties and potentials yet to be fully explored. This article introduces the general concepts, crystal structure, and exfoliation properties of h-MAB phases, while also highlighting advancements in the synthesis and applications of h-MBenes. Finally, we discuss future challenges and prospects for the study of h-MAB and h-MBenes.

Dibenzothiophene S, S-Dioxide-Containing Dipolar Molecules As Efficient Hole-Transport Materials for p-i-n Perovskite Solar Cells.

Organic-inorganic hybrid perovskite solar cells (OIH-PSCs) have developed rapidly in the past decade, and the commercialization of OIH-PSCs demands low-cost hole-transport materials (HTMs) with high performance and stability. The present study synthesized two organic HTMs containing dibenzothiophene S-dioxide as the acceptor unit and triphenylamine as the donor (denoted by TPAF-SO2 and TPA-SO2). In TPAF-SO2, the methoxy group and adjacent fluorine atom were introduced to decrease the highest occupied molecular orbital energy level. In TPA-SO2, the methyl sulfide group is the end group that can passivate the lead ion. TPAF-SO2 and TPA-SO2 exhibit hole-transport mobilities as high as 1.12 × 10-3 and 2.31 × 10-3 cm2 v-1 s-1, respectively, and strongly passivate Pb vacancies. Compared with TPAF-SO2, TPA-SO2 is more suitable for the growth of perovskite crystals. The perovskite grown on the latter has a lower trap density and higher carrier mobility; thus, both the nonradiative recombination and the charge-transport loss are decreased. The OIH-PSC based on TPA-SO2 as the HTM achieved a power conversion efficiency (PCE) as high as 22.08%, whereas the device based on TPAF-SO2 achieved a PCE of only 18.42%. In addition, the unencapsulated device based on TPA-SO2 can maintain 85% of the initial PCE after being stored in N2 for 1200 h, whereas the device based on TPAF-SO2 decayed rapidly to zero in 800 h under the same conditions.

Correlation of cytotoxic effect of transmembrane and secretory TNF-α to cell cycle.

This study was aimed to examine the correlation of the cytotoxic effects induced by two types of TNF-α to cell cycle. Hoechst 33342 and PI were used to detect the morphological changes in the cell death induced by the two types of TNF-α. TdT and PI co-staining was performed to determine the phase of cell cycle of apoptotic cells. L929 cells in different phases of cell cycle were further synchronized and their sensitivity to the two types of TNF-α was observed. Our results showed that the apoptosis of HepG2 cells triggered by tm-TNF-α mainly occurred in G(1) phase while in HL-60, Raji and K562 cell lines it mainly took place in S phase. The apoptosis of L929 cells induced by tm-TNF-α mainly occurred in S phase while the apoptosis induced by s-TNF-α mainly appeared in G(1) phase. L929 cells were sensitive to s-TNF-α when synchronized in G(1) phase (cytotoxicity 49.8%) while their sensitivity to tm-TNF-α was highest in S phase (45.7%) and G(1)/S phase (cytotoxicity 40.6%). It was concluded that tm-TNF-α-induced apoptosis of different target cells took place in different phases of cell cycle. The apoptosis of the specific cell line induced by the two types of TNF-α occurred in different phases of cell cycle. The sensitivity of the specific cell line to the two types of TNF-α was correlated with the phase of cell cycle.

Deep Learning Based on ACR TI-RADS Can Improve the Differential Diagnosis of Thyroid Nodules.

OBJECTIVE: The purpose of this study was to improve the differentiation between malignant and benign thyroid nodules using deep learning (DL) in category 4 and 5 based on the Thyroid Imaging Reporting and Data System (TI-RADS, TR) from the American College of Radiology (ACR). DESIGN AND METHODS: From June 2, 2017 to April 23, 2019, 2082 thyroid ultrasound images from 1396 consecutive patients with confirmed pathology were retrospectively collected, of which 1289 nodules were category 4 (TR4) and 793 nodules were category 5 (TR5). Ninety percent of the B-mode ultrasound images were applied for training and validation, and the residual 10% and an independent external dataset for testing purpose by three different deep learning algorithms. RESULTS: In the independent test set, the DL algorithm of best performance got an AUC of 0.904, 0.845, 0.829 in TR4, TR5, and TR4&5, respectively. The sensitivity and specificity of the optimal model was 0.829, 0.831 on TR4, 0.846, 0.778 on TR5, 0.790, 0.779 on TR4&5, versus the radiologists of 0.686 (P=0.108), 0.766 (P=0.101), 0.677 (P=0.211), 0.750 (P=0.128), and 0.680 (P=0.023), 0.761 (P=0.530), respectively. CONCLUSIONS: The study demonstrated that DL could improve the differentiation of malignant from benign thyroid nodules and had significant potential for clinical application on TR4 and TR5.

Added Value of a New Strain Elastography Technique in Conventional Ultrasound for the Diagnosis of Breast Masses: A Prospective Multicenter Study.

OBJECTIVE: This study aimed to explore the value of elasticity score (ES) and strain ratio (SR) combined with conventional ultrasound in distinguishing benign and malignant breast masses and reducing biopsy of BI-RADS (Breast Imaging Reporting and Data System) 4a lesions. METHODS: This prospective, multicenter study included 910 patients from nine different hospitals. The acquisition and analysis of conventional ultrasound and strain elastography (SE) were obtained by radiologists with more than 5 years of experience in breast ultrasound imaging. The diagnostic sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under curve (AUC) of conventional ultrasound alone and combined tests with ES and/or SR were calculated and compared. RESULTS: The optimal cutoff value of SR for differentiating benign from malignant masses was 2.27, with a sensitivity of 60.2% and a specificity of 84.8%. When combined with ES and SR, the AUC of the new BI-RADS classification increased from 0.733 to 0.824 (p < 0.001); the specificity increased from 48.1% to 68.5% (p < 0.001) without a decrease in the sensitivity (98.5% vs. 96.4%, p = 0.065); and the PPV increased from 52.2% to 63.7% (p < 0.001) without a loss in the NPV (98.2% vs. 97.1%, p = 0.327). All three combinations of conventional ultrasound, ES, and SR could reduce the biopsy rate of category 4a lesions without reducing the malignant rate of biopsy (from 100% to 68.3%, 34.9%, and 50.4%, respectively, all p < 0.001). CONCLUSIONS: SE can be used as a useful and non-invasive additional method to improve the diagnostic performance of conventional ultrasound by increasing AUC and specificity and reducing the unnecessary biopsy of BI-RADS 4a lesions.

RIP mutated ITS genes in populations of Ophiocordyceps sinensis and their implications for molecular systematics.

Different hypotheses have been proposed to interpret the observed unusual ITS (internal transcribed spacer) sequences in Ophiocordyceps sinensis. The coexistence of diverged ITS paralogs in a single genome was previously shown by amplifying the ITS region from mono-ascospore isolates using specific primers designed for different ITS paralog groups. Among those paralogs, are AT-biased ITS sequences which were hypothesized to result from repeat-induced point mutation (RIP). This is a process that detects and mutates repetitive DNA and frequently leads to epigenetic silencing, and these mutations have been interpreted as pseudogenes. Here we investigate the occurrence and frequency of ITS pseudogenes in populations of O. sinensis using large-scale sampling, and discusses the implications of ITS pseudogenes for fungal phylogenetic and evolutionary studies. Our results demonstrate a wide distribution of ITS pseudogenes amongst different geographic populations, and indicate how ITS pseudogenes can contribute to the reconstruction of the evolutionary history of the species.

The value of S-Detect in improving the diagnostic performance of radiologists for the differential diagnosis of thyroid nodules.

AIMS: To compare the diagnostic value of S-Detect (a computer aided diagnosis system using deep learning) in differentiating thyroid nodules in radiologists with different experience and to assess if S-Detect can improve the diagnostic performance of radiologists. MATERIALS AND METHODS: Between February 2018 and October 2019, 204 thyroid nodules in 181 patients were included. An experienced radiologist performed ultrasound for thyroid nodules and obtained the result of S-Detect. Four radiologists with different experience on thyroid ultrasound (Radiologist 1, 2, 3, 4 with 1, 4, 9, 20 years, respectively) analyzed the conventional ultrasound images of each thyroid nodule and made a diagnosis of "benign" or "malignant" based on the TI-RADS category. After referring to S-Detect results, they re-evaluated the diagnoses. The diagnostic performance of radiologists was analyzed before and after referring to the results of S-Detect. RESULTS: The accuracy, sensitivity, specificity, positive predictive value and negative predictive value of S-Detect were 77.0, 91.3, 65.2, 68.3 and 90.1%, respectively. In comparison with the less experienced radiologists (radiologist 1 and 2), S-Detect had a higher area under receiver operating characteristic curve (AUC), accuracy and specificity (p <0.05). In comparison with the most experienced radiologist, the diagnostic accuracy and AUC were lower (p<0.05). In the less experienced radiologists, the diagnostic accuracy, specificity and AUC were significantly improved when combined with S-Detect (p<0.05), but not for experienced radiologists (radiologist 3 and 4) (p>0.05). CONCLUSIONS: S-Detect may become an additional diagnostic method for the diagnosis of thyroid nodules and improve the diagnostic performance of less experienced radiologists.

The effects of jolkinolide B on HepG2 cells as revealed by 1H-NMR-based metabolic profiling.

Jolkinolide B (JB), which is isolated from the dried root of Euphorbia fischeriana Steud., has been reported to possess various therapeutic effects, such as treatment of edema and abdominal distention and protection against acute lung injury, and it has also been reported to have anti-inflammatory even antitumor properties. Thus, JB has always been considered a promising anticancer drug candidate. In the current work, a cellular metabolomics evaluation based on the nuclear magnetic resonance (NMR) approach was applied to investigate the mechanism of JB in HepG2 cells. In addition, biological assays such as the MTT assay, DAPI staining and the Annexin V-FITC/PI assay were implemented to evaluate cell viability and apoptosis in JB-treated cells. Subsequently, we used multivariate statistical analyses, such as principal component analysis (PCA) and orthogonal projection to latent structure with discriminant analysis (OPLS-DA) to identify metabolic biomarkers. In total, 36 metabolites in the cell extract samples and 30 metabolites in the cell culture media samples were clearly identified to be altered after the treatment. Variations in the specific metabolites suggested that HepG2 cells that were exposed to JB displayed the disordered effects in multiple metabolic pathways, such as the tricarboxylic acid cycle, amino acid metabolism, GSH synthesis and pyruvate metabolism. NMR-based cell metabolomics provided a holistic method for the identification of JB's antitumor mechanisms and the exploration of its potential applications in preclinical and clinical studies.

Preclinical safety evaluation of chimeric antigen receptor-modified T cells against CD19 in NSG mice.

BACKGROUND: With the increase of chimeric antigen receptor-modified T (CAR-T) cell therapy, serious complications initiated by CAR-T cells have garnered wide attention. We have previously developed a 4-1BB/CD3-ζ-costimulated CAR-T cells against CD19 (CART19) for adult acute lymphoblastic leukemia (ALL). In this study, a preclinical safety assessment of CART19 was performed on NSG mice, to evaluate the preclinical toxicity along with its efficacy and tissue distribution. METHODS: A total of 120 NSG mice were used for a combined pharmacodynamics and toxicity study for 56 days. Ninety-six mice of which were single dosed with Raji-Luc (5×105 per animal, i.p.) and different concentrations of CART19 (0.2×107, 0.6×107 and 1.8×107 per animal, i.v.), while the rest were assigned to the Untreated group. Optical intensity of Raji-Luc in mice, clinical symptoms, body mass, hematological analysis, humanized cytokine, lymphocyte subset counting, necropsy and histopathological examinations were performed. In addition, a single dose of 0.6×107 CART19 was intravenously administered to 48 NSG mice, and the distribution of CART19 in different tissues was analyzed using quantitative PCR. RESULTS: CART19 is widely distributed in organs well-perfused with blood, including the lungs, blood, bone marrow, liver and spleen. Significant proliferation of CART19 was also found in the blood by through recognition using humanized CD3+ for T lymphocytes. The survival rate and leukemia related clinical symptoms in mice administered CART19 were markedly ameliorated, and the proliferation of Raji cells in mice was effectively inhibited. However, CART19 had no obvious effects on either the mean body mass or the blood cell counts, and no cytokine release syndrome and graft versus host disease were observed. CONCLUSIONS: NSG mice given CART19 treatment demonstrated a longer survival period without significant immunotoxicity, suggesting encouraging clinical prospects for CART19 in patients with R/R ALL. Our study shed light on evaluation and supervision strategies for CAR-T products for the treatment of hematological diseases or leukemia.

NMR-based Metabolomic Techniques Identify the Toxicity of Emodin in HepG2 Cells.

Emodin is a natural anthraquinone derivative that is present in various herbal preparations. The pharmacological effects of emodin include anticancer, hepatoprotective, anti-inflammatory, antioxidant and even antimicrobial activities. However, emodin also has been reported to induce hepatotoxicity, nephrotoxicity, genotoxicity and reproductive toxicity. The mechanism of emodin's adverse effects is complicated and currently not well understood. This study aimed to establish a cell metabonomic method to investigate the toxicity of emodin and explore its potential mechanism and relevant targets. In the present study, metabonomic profiles of cell extracts and cell culture media obtained using the 1H NMR technique were used to assess emodin toxicity in HepG2 cells. Multivariate statistical analyses such as partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were used to characterize the metabolites that differed between the control and emodin groups. The results indicated that emodin resulted in differences in 33 metabolites, including acetate, arginine, aspartate, creatine, isoleucine, leucine and histidine in the cell extract samples and 23 metabolites, including alanine, formate, glutamate, succinate and isoleucine, in the cell culture media samples. Approximately 8 pathways associated with these metabolites were disrupted in the emodin groups. These results demonstrated the potential for using cell metabonomics approaches to clarify the toxicological effects of emodin, the underlying mechanisms and potential biomarkers. Our findings may help with the development of novel strategies to discover targets for drug toxicity, elucidate the changes in regulatory signal networks and explore its potential mechanism of action.

Transmembrane TNF-alpha promotes chemoresistance in breast cancer cells.

Chemoresistance remains a major obstacle to successful treatment of breast cancer. Although soluble tumor necrosis factor-α (sTNF-α) has been implicated in mediating drug-resistance in human cancers, whether transmembrane tumor necrosis factor-α (tmTNF-α) plays a role in chemoresistance remains unclear. Here we found that over 50% of studied patients expressed tmTNF-α at high levels in breast cancer tissues and tmTNF-α expression positively correlated with resistance to anthracycline chemotherapy. Alteration of tmTNF-α expression changed the sensitivity of primary human breast cancer cells and breast cancer cell lines to doxorubicin (DOX). Overexpression of N-terminal fragment (NTF) of tmTNF-α, a mutant form with intact intracellular domain of tmTNF-α to transmit reverse signals, induced DOX-resistance. Mechanistically, the tmTNF-α/NTF-ERK-GST-π axis and tmTNF-α/NTF-NF-κB-mediated anti-apoptotic functions were required for tmTNF-α-induced DOX-resistance. In a xenograft mouse model, the combination of tmTNF-α suppression with chemotherapy significantly enhanced the efficacy of DOX. Our data indicate that tmTNF-α mediates DOX-resistance through reverse signaling and targeting tmTNF-α may be beneficial for the treatment of DOX-resistant breast cancer.