miR-200 deficiency promotes lung cancer metastasis by activating Notch signaling in cancer-associated fibroblasts.

Lung adenocarcinoma, the most prevalent lung cancer subtype, is characterized by its high propensity to metastasize. Despite the importance of metastasis in lung cancer mortality, its underlying cellular and molecular mechanisms remain largely elusive. Here, we identified miR-200 miRNAs as potent suppressors for lung adenocarcinoma metastasis. miR-200 expression is specifically repressed in mouse metastatic lung adenocarcinomas, and miR-200 decrease strongly correlates with poor patient survival. Consistently, deletion of mir-200c/141 in the KrasLSL-G12D/+ ; Trp53flox/flox lung adenocarcinoma mouse model significantly promoted metastasis, generating a desmoplastic tumor stroma highly reminiscent of metastatic human lung cancer. miR-200 deficiency in lung cancer cells promotes the proliferation and activation of adjacent cancer-associated fibroblasts (CAFs), which in turn elevates the metastatic potential of cancer cells. miR-200 regulates the functional interaction between cancer cells and CAFs, at least in part, by targeting Notch ligand Jagged1 and Jagged2 in cancer cells and inducing Notch activation in adjacent CAFs. Hence, the interaction between cancer cells and CAFs constitutes an essential mechanism to promote metastatic potential.

Development of a Novel Hierarchically Biofabricated Blood Vessel Mimic Decorated with Three Vascular Cell Populations for the Reconstruction of Small-Diameter Arteries.

The availability of grafts to replace small-diameter arteries remains an unmet clinical need. Here, the validated methodology is reported for a novel hybrid tissue-engineered vascular graft that aims to match the natural structure of small-size arteries. The blood vessel mimic (BVM) comprises an internal conduit of co-electrospun gelatin and polycaprolactone (PCL) nanofibers (corresponding to the tunica intima of an artery), reinforced by an additional layer of PCL aligned fibers (the internal elastic membrane). Endothelial cells are deposited onto the luminal surface using a rotative bioreactor. A bioprinting system extrudes two concentric cell-laden hydrogel layers containing respectively vascular smooth muscle cells and pericytes to create the tunica media and adventitia. The semi-automated cellularization process reduces the production and maturation time to 6 days. After the evaluation of mechanical properties, cellular viability, hemocompatibility, and suturability, the BVM is successfully implanted in the left pulmonary artery of swine. Here, the BVM showed good hemostatic properties, capability to withstand blood pressure, and patency at 5 weeks post-implantation. These promising data open a new avenue to developing an artery-like product for reconstructing small-diameter blood vessels.

Bacterial Surface Appendages Modulate the Antimicrobial Activity Induced by Nanoflake Surfaces on Titanium.

Bioinspired nanotopography is a promising approach to generate antimicrobial surfaces to combat implant-associated infection. Despite efforts to develop bactericidal 1D structures, the antibacterial capacity of 2D structures and their mechanism of action remains uncertain. Here, hydrothermal synthesis is utilized to generate two 2D nanoflake surfaces on titanium (Ti) substrates and investigate the physiological effects of nanoflakes on bacteria. The nanoflakes impair the attachment and growth of Escherichia coli and trigger the accumulation of intracellular reactive oxygen species (ROS), potentially contributing to the killing of adherent bacteria. E. coli surface appendages type-1 fimbriae and flagella are not implicated in the nanoflake-mediated modulation of bacterial attachment but do influence the bactericidal effects of nanoflakes. An E. coli ΔfimA mutant lacking type-1 fimbriae is more susceptible to the bactericidal effects of nanoflakes than the parent strain, while E. coli cells lacking flagella (ΔfliC) are more resistant. The results suggest that type-1 fimbriae confer a cushioning effect that protects bacteria upon initial contact with the nanoflake surface, while flagella-mediated motility can lead to elevated membrane abrasion. This finding offers a better understanding of the antibacterial properties of nanoflake structures that can be applied to the design of antimicrobial surfaces for future medical applications.

Image registration for in situ X-ray nano-imaging of a composite battery cathode with deformation.

The structural and chemical evolution of battery electrodes at the nanoscale plays an important role in affecting the cell performance. Nano-resolution X-ray microscopy has been demonstrated as a powerful technique for characterizing the evolution of battery electrodes under operating conditions with sensitivity to their morphology, compositional distribution and redox heterogeneity. In real-world batteries, the electrode could deform upon battery operation, causing challenges for the image registration which is necessary for several experimental modalities, e.g. XANES imaging. To address this challenge, this work develops a deep-learning-based method for automatic particle identification and tracking. This approach was not only able to facilitate image registration with good robustness but also allowed quantification of the degree of sample deformation. The effectiveness of the method was first demonstrated using synthetic datasets with known ground truth. The method was then applied to an experimental dataset collected on an operating lithium battery cell, revealing a high degree of intra- and interparticle chemical complexity in operating batteries.

Comparative studies of AlphaFold, RoseTTAFold and Modeller: a case study involving the use of G-protein-coupled receptors.

Neural network (NN)-based protein modeling methods have improved significantly in recent years. Although the overall accuracy of the two non-homology-based modeling methods, AlphaFold and RoseTTAFold, is outstanding, their performance for specific protein families has remained unexamined. G-protein-coupled receptor (GPCR) proteins are particularly interesting since they are involved in numerous pathways. This work directly compares the performance of these novel deep learning-based protein modeling methods for GPCRs with the most widely used template-based software-Modeller. We collected the experimentally determined structures of 73 GPCRs from the Protein Data Bank. The official AlphaFold repository and RoseTTAFold web service were used with default settings to predict five structures of each protein sequence. The predicted models were then aligned with the experimentally solved structures and evaluated by the root-mean-square deviation (RMSD) metric. If only looking at each program's top-scored structure, Modeller had the smallest average modeling RMSD of 2.17 Å, which is better than AlphaFold's 5.53 Å and RoseTTAFold's 6.28 Å, probably since Modeller already included many known structures as templates. However, the NN-based methods (AlphaFold and RoseTTAFold) outperformed Modeller in 21 and 15 out of the 73 cases with the top-scored model, respectively, where no good templates were available for Modeller. The larger RMSD values generated by the NN-based methods were primarily due to the differences in loop prediction compared to the crystal structures.

Ensemble modeling with machine learning and deep learning to provide interpretable generalized rules for classifying CNS drugs with high prediction power.

The trade-off between a machine learning (ML) and deep learning (DL) model's predictability and its interpretability has been a rising concern in central nervous system-related quantitative structure-activity relationship (CNS-QSAR) analysis. Many state-of-the-art predictive modeling failed to provide structural insights due to their black box-like nature. Lack of interpretability and further to provide easy simple rules would be challenging for CNS-QSAR models. To address these issues, we develop a protocol to combine the power of ML and DL to generate a set of simple rules that are easy to interpret with high prediction power. A data set of 940 market drugs (315 CNS-active, 625 CNS-inactive) with support vector machine and graph convolutional network algorithms were used. Individual ML/DL modeling methods were also constructed for comparison. The performance of these models was evaluated using an additional external dataset of 117 market drugs (42 CNS-active, 75 CNS-inactive). Fingerprint-split validation was adopted to ensure model stringency and generalizability. The resulting novel hybrid ensemble model outperformed other constituent traditional QSAR models with an accuracy of 0.96 and an F1 score of 0.95. With the power of the interpretability provided with this protocol, our model laid down a set of simple physicochemical rules to determine whether a compound can be a CNS drug using six sub-structural features. These rules displayed higher classification ability than classical guidelines, with higher specificity and more mechanistic insights than just for blood-brain barrier permeability. This hybrid protocol can potentially be used for other drug property predictions.

Highly integrated automatic injection terahertz microfluidic biosensor based on metasurface and LT-GaAs photoconductive antenna.

In this paper, a highly integrated terahertz (THz) biosensor is proposed and implemented, which pioneered the preparation of low-temperature gallium arsenide (LT-GaAs) thin film photoconductive antenna (PCA) on the sensor for direct generation and detection of THz waves, simplifying complex terahertz time-domain spectroscopy (THz-TDS) systems. A latch type metasurface is deposited in the detection region to produce a resonance absorption peak at 0.6 THz that is independent of polarisation. Microfluidics is utilised and automatic injection is incorporated to mitigate the experimental effects of hydrogen bond absorption of THz waves in aqueous-based environment. Additionally, cell damage is minimised by regulating the cell flow rate. The biosensor was utilised to detect the concentration of three distinct sizes of bacteria with successful results. The assay was executed as a proof of concept to detect two distinct types of breast cancer cells. Based on the experimental findings, it has been observed that the amplitude and blueshift of the resonance absorption peaks have the ability to identify and differentiate various cancer cell types. The findings of this study introduce a novel approach for developing microfluidic THz metasurface biosensors that possess exceptional levels of integration, sensitivity, and rapid label-free detection capabilities.

PROTAC EZH2 degrader-1 overcomes the resistance of podophyllotoxin derivatives in refractory small cell lung cancer with leptomeningeal metastasis.

BACKGROUND: Leptomeningeal metastasis (LM) of small cell lung cancer (SCLC) is a highly detrimental occurrence associated with severe neurological disorders, lacking effective treatment currently. Proteolysis-targeting chimeric molecules (PROTACs) may provide new therapeutic avenues for treatment of podophyllotoxin derivatives-resistant SCLC with LM, warranting further exploration. METHODS: The SCLC cell line H128 expressing luciferase were mutated by MNNG to generate H128-Mut cell line. After subcutaneous inoculation of H128-Mut into nude mice, H128-LM and H128-BPM (brain parenchymal metastasis) cell lines were primarily cultured from LM and BPM tissues individually, and employed to in vitro drug testing. The SCLC-LM mouse model was established by inoculating H128-LM into nude mice via carotid artery and subjected to in vivo drug testing. RNA-seq and immunoblotting were conducted to uncover the molecular targets for LM. RESULTS: The SCLC-LM mouse model was successfully established, confirmed by in vivo live imaging and histological examination. The upregulated genes included EZH2, SLC44A4, VEGFA, etc. in both BPM and LM cells, while SLC44A4 was particularly upregulated in LM cells. When combined with PROTAC EZH2 degrader-1, the drug sensitivity of cisplatin, etoposide (VP16), and teniposide (VM26) for H128-LM was significantly increased in vitro. The in vivo drug trials with SCLC-LM mouse model demonstrated that PROTAC EZH2 degrader-1 plus VM26 or cisplatin/ VP16 inhibited H128-LM tumour significantly compared to VM26 or cisplatin/ VP16 alone (P < 0.01). CONCLUSION: The SCLC-LM model effectively simulates the pathophysiological process of SCLC metastasis to the leptomeninges. PROTAC EZH2 degrader-1 overcomes chemoresistance in SCLC, suggesting its potential therapeutic value for SCLC LM.

Transformation to small cell lung cancer is irrespective of EGFR and accelerated by SMAD4-mediated ASCL1 transcription independently of RB1 in non-small cell lung cancer.

OBJECTIVES: Histological transformation to small cell lung cancer (SCLC) has been identified as a mechanism of TKIs resistance in EGFR-mutant non-small cell lung cancer (NSCLC). We aim to explore the prevalence of transformation in EGFR-wildtype NSCLC and the mechanism of SCLC transformation, which are rarely understood. METHODS: We reviewed 1474 NSCLC patients to investigate the NSCLC-to-SCLC transformed cases and the basic clinical characteristics, driver gene status and disease course of them. To explore the potential functional genes in SCLC transformation, we obtained pre- and post-transformation specimens and subjected them to a multigene NGS panel involving 416 cancer-related genes. To validate the putative gene function, we established knocked-out models by CRISPR-Cas 9 in HCC827 and A549-TP53-/- cells and investigated the effects on tumor growth, drug sensitivity and neuroendocrine phenotype in vitro and in vivo. We also detected the expression level of protein and mRNA to explore the molecular mechanism involved. RESULTS: We firstly reported an incidence rate of 9.73% (11/113) of SCLC transformation in EGFR-wildtype NSCLC and demonstrated that SCLC transformation is irrespective of EGFR mutation status (P = 0.16). We sequenced 8 paired tumors and identified a series of mutant genes specially in transformed SCLC such as SMAD4, RICTOR and RET. We firstly demonstrated that SMAD4 deficiency can accelerate SCLC transition by inducing neuroendocrine phenotype regardless of RB1 status in TP53-deficient NSCLC cells. Further mechanical experiments identified the SMAD4 can regulate ASCL1 transcription competitively with Myc in NSCLC cells and Myc inhibitor acts as a potential subsequent treatment agent. CONCLUSIONS: Transformation to SCLC is irrespective of EFGR status and can be accelerated by SMAD4 in non-small cell lung cancer. Myc inhibitor acts as a potential therapeutic drug for SMAD4-mediated resistant lung cancer. Video Abstract.

Development and validation of a nomogram for screening patients with type 2 diabetic ketoacidosis.

OBJECTIVE AND BACKGROUND: The early detection of diabetic ketoacidosis (DKA) in patients with type 2 diabetes (T2D) plays a crucial role in enhancing outcomes. We developed a nomogram prediction model for screening DKA in T2D patients. At the same time, the input variables were adjusted to reduce misdiagnosis. METHODS: We obtained data on T2D patients from Mimic-IV V0.4 and Mimic-III V1.4 databases. A nomogram model was developed using the training data set, internally validated, subjected to sensitivity analysis, and further externally validated with data from T2D patients in Aviation General Hospital. RESULTS: Based on the established model, we analyzed 1885 type 2 diabetes patients, among whom 614 with DKA. We further additionally identified risk factors for DKA based on literature reports and multivariate analysis. We identified age, glucose, chloride, calcium, and urea nitrogen as predictors in our model. The logistic regression model demonstrated an area under the curve (AUC) of 0.86 (95%CI: 0.85-0.90]. To validate the model, we collected data from 91 T2D patients, including 15 with DKA, at our hospital. The external validation of the model yielded an AUC of 0.68 (95%CI: 0.67-0.70). The calibration plot confirmed that our model was adequate for predicting patients with DKA. The decision-curve analysis revealed that our model offered net benefits for clinical use. CONCLUSIONS: Our model offers a convenient and accurate tool for predicting whether DKA is present. Excluding input variables that may potentially hinder patient compliance increases the practical application significance of our model.

Schizophrenia in the genetic era: a review from development history, clinical features and genomic research approaches to insights of susceptibility genes.

Schizophrenia is a devastating neuropsychiatric disorder affecting 1% of the world population and ranks as one of the disorders providing the most severe burden for society. Schizophrenia etiology remains obscure involving multi-risk factors, such as genetic, environmental, nutritional, and developmental factors. Complex interactions of genetic and environmental factors have been implicated in the etiology of schizophrenia. This review provides an overview of the historical origins, pathophysiological mechanisms, diagnosis, clinical symptoms and corresponding treatment of schizophrenia. In addition, as schizophrenia is a polygenic, genetic disorder caused by the combined action of multiple micro-effective genes, we further detail several approaches, such as candidate gene association study (CGAS) and genome-wide association study (GWAS), which are commonly used in schizophrenia genomics studies. A number of GWASs about schizophrenia have been performed with the hope to identify novel, consistent and influential risk genetic factors. Finally, some schizophrenia susceptibility genes have been identified and reported in recent years and their biological functions are also listed. This review may serve as a summary of past research on schizophrenia genomics and susceptibility genes (NRG1, DISC1, RELN, BDNF, MSI2), which may point the way to future schizophrenia genetics research. In addition, depending on the above discovery of susceptibility genes and their exact function, the development and application of antipsychotic drugs will be promoted in the future.

Left atrial strain parameters to predicting elevated left atrial pressure in patients with atrial fibrillation.

OBJECTIVES: To assess the ability of left atrial (LA) strain parameters to discriminate patients with elevated left atrial pressure (LAP) from patients with atrial fibrillation (AF). METHODS AND RESULTS: A total of 142 patients with non-valvular AF who underwent first catheter ablation (CA) between November 2022 and November 2023 were enrolled in the study. Conventional and speckle-tracking echocardiography (STE) were performed in all patients within 24 h before CA, and LAP was invasively measured during the ablation procedure. According to mean LAP, the study population was classified into two groups of normal LAP (LAP < 15 mmHg, n = 101) and elevated LAP (LAP ≥ 15 mmHg, n = 41). Compared with the normal LAP group, elevated LAP group showed significantly reduced LA reservoir strain (LASr) [9.14 (7.97-11.80) vs. 20 (13.59-26.96), p < .001], and increased LA filling index [9.60 (7.15-12.20) vs. 3.72 (2.17-5.82), p < .001], LA stiffness index [1.13 (.82-1.46) vs. .47 (.30-.70), p < .001]. LASr, LA filling index and LA stiffness index were independent predictors of elevated LAP after adjusted by the type of AF, EDT, E/e', mitral E, and peak acceleration rate of mitral E velocity. The receiver-operating characteristic curve (ROC) analysis showed LA strain parameters (area under curve [AUC] .794-.819) could provide similar or greater diagnostic accuracy for elevated LAP, as compared to conventional echocardiographic parameters. Furthermore, the novel algorithms built by LASr, LA stiffness index, LA filling index, and left atrial emptying fraction (LAEF), was used to discriminate elevated LAP in AF with good accuracy (AUC .880, accuracy of 81.69%, sensitivity of 80.49%, and specificity of 82.18%), and much better than 2016 ASE/EACVI algorithms in AF. CONCLUSION: In patients with AF, LA strain parameters could be useful to predict elevated LAP and non-inferior to conventional echocardiographic parameters. Besides, the novel algorithm built by LA strain parameters combined with conventional parameters would improve the diagnostic efficiency.

Diallyl disulfide antagonizes DJ-1 mediated proliferation, epithelial-mesenchymal transition, and chemoresistance in gastric cancer cells.

Diallyl disulfide (DADS), an organic component of allicin abstracted from garlic, possesses multi-target antitumor activity. DJ-1 performs a vital function in promoting AKT aberrant activation via down-regulating phosphatase and tensin homologue (PTEN) in tumors. It is unknown the involvement of DJ-1 in epithelial-mesenchymal transition (EMT) of gastric cancer (GC) cells. The purpose of this study is to investigate whether diallyl disulfide (DADS) intervenes in the role of DJ-1 in GC. Based on the identification that the correlation between high DJ-1 and low PTEN expression in GC was implicated in clinical progression, we illuminated that down-regulation of DJ-1 by DADS aided in an increase in PTEN expression and a decrease in phosphorylated AKT levels, which was in line with the results manifested in the DJ-1 knockdown and overexpressed cells, concurrently inhibiting proliferation, EMT, migration, and invasion. Furthermore, the antagonistic effects of DADS on DJ-1 were observed in in vivo experiments. Additionally, DADS mitigated the DJ-1-associated drug resistance. The current study revealed that DJ-1 is one of potential targets for DADS, which hopefully provides a promising strategy for prevention and adjuvant chemotherapy of GC.

Integration of land ecological consolidation and ecosystem product value realization: A case from the Yangtze riverside industrial park in Changzhou, China.

Traditional industries and industrialization have led to widespread environmental pollution and ecosystem degradation in major river basins globally. Strategies centered on ecological restoration and ecological economy are emerging as essential tools for effective environmental governance. This study aims to investigate how a multifaceted framework for land ecological consolidation, with various developmental goals, can effectively support ecological restoration and sustainability. Through quantitative analysis and in-depth interviews, we investigated the case of Yangtze riverside chemical industrial park in Changzhou. This park pursues ecological and economic sustainability through chemical industry transformation, ecological restoration and protection, ecological management, and ecological industry development. The results show that this practice established a multi-objective action framework rooted in urban renewal, land consolidation, ecological restoration, industrial transformation, and rural revitalization. Through multiplanning integration, integrated implementation and full-cycle profit distribution, the aim of ecological protection has been initially achieved, offering a crucial guarantee for sustainable development. A total of 96.47 ha ecological space expanded, which can generate ecological product worth CNY 7.283 billion, alongside a net economic benefit of CNY 978 million over three decades. The top-down ecological responsibilities, coupled with local developmental demands, have stimulated collaborations within a bottom-up endogenous network comprising government, enterprises, and residents.

Terahertz Spectra of Mannitol and Erythritol: A Joint Experimental and Computational Study.

Sugar substitutes, which generally refer to a class of food additives, mostly have vibration frequencies within the terahertz (THz) band. Therefore, THz technology can be used to analyze their molecular properties. To understand the characteristics of sugar substitutes, this study selected mannitol and erythritol as representatives. Firstly, PXRD and Raman techniques were used to determine the crystal structure and purity of mannitol and erythritol. Then, the THz time-domain spectroscopy (THz-TDS) system was employed to measure the spectral properties of the two sugar substitutes. Additionally, density functional theory (DFT) was utilized to simulate the crystal configurations of mannitol and erythritol. The experimental results showed good agreement with the simulation results. Finally, microfluidic chip technology was used to measure the THz spectroscopic properties of the two sugar substitutes in solution. A comparison was made between their solid state and aqueous solution state, revealing a strong correlation between the THz spectra of the two sugar substitutes in both states. Additionally, it was found that the THz spectrum of a substance in solution is related to its concentration. This study provides a reference for the analysis of sugar substitutes.

The influence of coiled-coil motif of serine recombinase toward the directionality regulation.

Serine integrases promote the recombination of two complementary DNA sequences, attP and attB, to create hybrid sequences, attL and attR. The reaction is unidirectional in the absence of an accessory protein called recombination directionality factor. We utilized tethered particle motion (TPM) experiments to investigate the reaction behaviors of two model serine integrases from Listeria innocua phage LI and Streptomyces coelicolor phage C31. Detailed kinetic analyses of wild-type and mutant proteins were carried out to verify the mechanisms of recombination directionality. In particular, we assessed the influence of a coiled-coil motif (CC) that is conserved in the C-terminal domain of serine integrases and is an important prerequisite for efficient recombination. Compared to wild type, we found that CC deletions in both serine integrases reduced the overall abundance of integrase (Int) att-site complexes and favored the formation of nonproductive complexes over recombination-competent complexes. Furthermore, the rate at which CC mutants formed productive synaptic complexes and disassembled aberrant nonproductive complexes was significantly reduced. It is notable that while the φC31 Int CC is essential for recombination, the LI Int CC plays an auxiliary role for recombination to stabilize protein-protein interactions and to control the directionality of the reaction.

Iridium-Catalyzed, Site-Selective Silylation of Secondary C(sp3)-H Bonds in Secondary Alcohols and Ketones.

We report the iridium-catalyzed, stereoselective conversion of secondary alcohols or ketones to anti-1,3-diols by the silylation of secondary C-H bonds γ to oxygen and oxidation of the resulting oxasilolane. The silylation of secondary C-H bonds in secondary silyl ethers derived from alcohols or ketones is enabled by a catalyst formed from a simple bisamidine ligand. The silylation occurs with high selectivity at a secondary C-H bond γ to oxygen over distal primary or proximal secondary C-H bonds. Initial mechanistic investigations suggest that the source of the newly achieved reactivity is a long catalyst lifetime resulting from the high binding constant of the strongly electron-donating bisamidine ligand.

Hydroxyl-Bonded Ru on Metallic TiN Surface Catalyzing CO2 Reduction with H2O by Infrared Light.

Synchronized conversion of CO2 and H2O into hydrocarbons and oxygen via infrared-ignited photocatalysis remains a challenge. Herein, the hydroxyl-coordinated single-site Ru is anchored precisely on the metallic TiN surface by a NaBH4/NaOH reforming method to construct an infrared-responsive HO-Ru/TiN photocatalyst. Aberration-corrected high-angle annular dark-field scanning transmission electron microscopy (ac-HAADF-STEM) and X-ray absorption spectroscopy (XAS) confirm the atomic distribution of the Ru species. XAS and density functional theory (DFT) calculations unveil the formation of surface HO-RuN5-Ti Lewis pair sites, which achieves efficient CO2 polarization/activation via dual coordination with the C and O atoms of CO2 on HO-Ru/TiN. Also, implanting the Ru species on the TiN surface powerfully boosts the separation and transfer of photoinduced charges. Under infrared irradiation, the HO-Ru/TiN catalyst shows a superior CO2-to-CO transformation activity coupled with H2O oxidation to release O2, and the CO2 reduction rate can further be promoted by about 3-fold under simulated sunlight. With the key reaction intermediates determined by in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and predicted by DFT simulations, a possible photoredox mechanism of the CO2 reduction system is proposed.

Full-field hard X-ray nano-tomography at SSRF.

An in-house designed transmission X-ray microscopy (TXM) instrument has been developed and commissioned at beamline BL18B of the Shanghai Synchrotron Radiation Facility (SSRF). BL18B is a hard (5-14 keV) X-ray bending-magnet beamline recently built with sub-20 nm spatial resolution in TXM. There are two kinds of resolution mode: one based on using a high-resolution-based scintillator-lens-coupled camera, and the other on using a medium-resolution-based X-ray sCMOS camera. Here, a demonstration of full-field hard X-ray nano-tomography for high-Z material samples (e.g. Au particles, battery particles) and low-Z material samples (e.g. SiO2 powders) is presented for both resolution modes. Sub-50 nm to 100 nm resolution in three dimensions (3D) has been achieved. These results represent the ability of 3D non-destructive characterization with nano-scale spatial resolution for scientific applications in many research fields.

Current development of integrated web servers for preclinical safety and pharmacokinetics assessments in drug development.

In drug development, preclinical safety and pharmacokinetics assessments of candidate drugs to ensure the safety profile are a must. While in vivo and in vitro tests are traditionally used, experimental determinations have disadvantages, as they are usually time-consuming and costly. In silico predictions of these preclinical endpoints have each been developed in the past decades. However, only a few web-based tools have integrated different models to provide a simple one-step platform to help researchers thoroughly evaluate potential drug candidates. To efficiently achieve this approach, a platform for preclinical evaluation must not only predict key ADMET (absorption, distribution, metabolism, excretion and toxicity) properties but also provide some guidance on structural modifications to improve the undesired properties. In this review, we organized and compared several existing integrated web servers that can be adopted in preclinical drug development projects to evaluate the subject of interest. We also introduced our new web server, Virtual Rat, as an alternative choice to profile the properties of drug candidates. In Virtual Rat, we provide not only predictions of important ADMET properties but also possible reasons as to why the model made those structural predictions. Multiple models were implemented into Virtual Rat, including models for predicting human ether-a-go-go-related gene (hERG) inhibition, cytochrome P450 (CYP) inhibition, mutagenicity (Ames test), blood-brain barrier penetration, cytotoxicity and Caco-2 permeability. Virtual Rat is free and has been made publicly available at https://virtualrat.cmdm.tw/.