Behind the Non-Uniform Breakup of Bubble Slug in Y-Shaped Microchannel: Dynamics and Mechanisms.

Bubble flow in confined geometries is a problem of fundamental and technological significance. Among all the forms, bubble breakup in bifurcated microchannels is one of the most commonly encountered scenarios, where an in-depth understanding is necessary for better leveraging the process. This study numerically investigates the non-uniform breakup of a bubble slug in Y-shaped microchannels under different flow ratios, Reynolds numbers, and initial bubble volumes. Overall, the bubble can either breakup or non-breakup when passing through the bifurcation and shows different forms depending on flow regimes. The flow ratio-Reynolds number phase diagrams indicate a power-law transition line of breakup and non-breakup. The bubble takes longer to break up with rising flow ratios yet breaks earlier with higher Reynolds numbers and volumes. Non-breakup takes less time than the breakup patterns. Flow ratio is the origin of non-uniform breakup. Both the Reynolds number and initial volume influence the bubble states when reaching the bifurcation and thus affect subsequent processes. Bubble neck dynamics are analyzed to describe the breakup further. The volume distribution after breaking up is found to have a quadratic relation with the flow ratio. Our study is hoped to provide insights for practical applications related to non-uniform bubble breakups.

PMSNet: Multiscale Partial-Discharge Signal Feature Recognition Model via a Spatial Interaction Attention Mechanism.

Partial discharge (PD) is a localized discharge phenomenon in the insulator of electrical equipment resulting from the electric field strength exceeding the local dielectric breakdown electric field. Partial-discharge signal identification is an important means of assessing the insulation status of electrical equipment and critical to the safe operation of electrical equipment. The identification effect of traditional methods is not ideal because the PD signal collected is subject to strong noise interference. To overcome noise interference, quickly and accurately identify PD signals, and eliminate potential safety hazards, this study proposes a PD signal identification method based on multiscale feature fusion. The method improves identification efficiency through the multiscale feature fusion and feature aggregation of phase-resolved partial-discharge (PRPD) diagrams by using PMSNet. The whole network consists of three parts: a CNN backbone composed of a multiscale feature fusion pyramid, a down-sampling feature enhancement (DSFB) module for each layer of the pyramid to acquire features from different layers, a Transformer encoder module dominated by a spatial interaction-attention mechanism to enhance subspace feature interactions, a final categorized feature recognition method for the PRPD maps and a final classification feature generation module (F-Collect). PMSNet improves recognition accuracy by 10% compared with traditional high-frequency current detection methods and current pulse detection methods. On the PRPD dataset, the validation accuracy of PMSNet is above 80%, the validation loss is about 0.3%, and the training accuracy exceeds 85%. Experimental results show that the use of PMSNet can greatly improve the recognition accuracy and robustness of PD signals and has good practicality and application prospects.

Discovery of anti-melanogenic components in persimmon (Diospyros kaki) leaf using LC-MS/MS-MN, AlphaFold2-enabled virtual screening and biological validation.

Persimmon (Diospyros kaki) leaf is widely used as a tea substitute in East Asia, offering potential health benefits. Although studies have highlighted their effects on hyperpigmentation disorders, the active components remain unidentified. This study introduces a novel approach combining LC-MS/MS-based molecular networking with AlphaFold2-enabled virtual screening to expedite the identification of bioactive components in persimmon leaf. A total of 105 compounds were identified by MS/MS analysis. Further, virtual screening identified five flavonoids with potential anti-melanogenic properties. Bioassays confirmed myricetin, quercetin, and kaempferol inhibited melanogenesis in human melanocytes in a dose-dependent manner. Biolayer interferometry assays revealed strong binding affinity between these flavonols and hsTYR, with KD values of 23.26 ± 11.77 for myricetin, 12.43 ± 0.37 for quercetin, and 14.99 ± 3.80 µM for kaempferol. Molecular dynamics simulations provided insights into the binding interactions of these flavonols with hsTYR, particularly highlighting the essential role of the 3-OH group on the C-ring. This study elucidates the bioactive components responsible for the anti-melanogenic effects of persimmon leaf, supporting their use in product development.

DeepMulticut: Deep Learning of Multicut Problem for Neuron Segmentation from Electron Microscopy Volume.

Superpixel aggregation is a powerful tool for automated neuron segmentation from electron microscopy (EM) volume. However, existing graph partitioning methods for superpixel aggregation still involve two separate stages-model estimation and model solving, and therefore model error is inherent. To address this issue, we integrate the two stages and propose an end-to-end aggregation framework based on deep learning of the minimum cost multicut problem called DeepMulticut. The core challenge lies in differentiating the NPhard multicut problem, whose constraint number is exponential in the problem size. With this in mind, we resort to relaxing the combinatorial solver-the greedy additive edge contraction (GAEC)-to a continuous Soft-GAEC algorithm, whose limit is shown to be the vanilla GAEC. Such relaxation thus allows the DeepMulticut to integrate edge cost estimators, Edge-CNNs, into a differentiable multicut optimization system and allows a decision-oriented loss to feed decision quality back to the Edge-CNNs for adaptive discriminative feature learning. Hence, the model estimators, Edge-CNNs, can be trained to improve partitioning decisions directly while beyond the NP-hardness. Also, we explain the rationale behind the DeepMulticut framework from the perspective of bi-level optimization. Extensive experiments on three public EM datasets demonstrate the effectiveness of the proposed DeepMulticut.

A robust transformer-based pipeline of 3D cell alignment, denoise and instance segmentation on electron microscopy sequence images.

Germline cells are critical for transmitting genetic information to subsequent generations in biological organisms. While their differentiation from somatic cells during embryonic development is well-documented in most animals, the regulatory mechanisms initiating plant germline cells are not well understood. To thoroughly investigate the complex morphological transformations of their ultrastructure over developmental time, nanoscale 3D reconstruction of entire plant tissues is necessary, achievable exclusively through electron microscopy imaging. This paper presents a full-process framework designed for reconstructing large-volume plant tissue from serial electron microscopy images. The framework ensures end-to-end direct output of reconstruction results, including topological networks and morphological analysis. The proposed 3D cell alignment, denoise, and instance segmentation pipeline (3DCADS) leverages deep learning to provide a cell instance segmentation workflow for electron microscopy image series, ensuring accurate and robust 3D cell reconstructions with high computational efficiency. The pipeline involves five stages: the registration of electron microscopy serial images; image enhancement and denoising; semantic segmentation using a Transformer-based neural network; instance segmentation through a supervoxel-based clustering algorithm; and an automated analysis and statistical assessment of the reconstruction results, with the mapping of topological connections. The 3DCADS model's precision was validated on a plant tissue ground-truth dataset, outperforming traditional baseline models and deep learning baselines in overall accuracy. The framework was applied to the reconstruction of early meiosis stages in the anthers of Arabidopsis thaliana, resulting in a topological connectivity network and analysis of morphological parameters and characteristics of cell distribution. The experiment underscores the 3DCADS model's potential for biological tissue identification and its significance in quantitative analysis of plant cell development, crucial for examining samples across different genetic phenotypes and mutations in plant development. Additionally, the paper discusses the regulatory mechanisms of Arabidopsis thaliana's germline cells and the development of stamen cells before meiosis, offering new insights into the transition from somatic to germline cell fate in plants.

Cevanine-type alkaloids from the bulbs of Fritillaria unibracteata var. wabuensis and their antifibrotic activities in vitro.

Steroidal alkaloids are the main bioactive components of the bulbs of Fritillaria, which have been used as traditional Chinese medicine, known as "Beimu", for the treatment of cough for thousands of years in China. Cough and dyspnea are the most common symptoms observed in patients with pulmonary fibrosis. However, the antifibrotic activity of steroidal alkaloids has not been reported yet. In this study, two previously unreported cevanine-type steroidal alkaloids (1 and 2), four previously undescribed cevanine-type alkaloid glycosides (3-6), and 19 known steroidal alkaloids (7-25) were isolated from the bulbs of Fritillaria unibracteata var. wabuensis. The structures of these compounds were elucidated by comprehensive HRESIMS and NMR spectroscopic data analysis, as well as DP4+ NMR calculations. The biological evaluation showed that compounds 2, 7-10, 14, 15, and 17 downregulated fibrotic markers induced by transforming growth factor-ß (TGF-ß) in MRC-5 cells. Moreover, compounds 14 and 17 dose dependently inhibited TGF-ß-induced epithelial-mesenchymal transition in A549 cells, alleviated TGF-ß-induced migration and proliferation of fibroblasts, and decreased the expression of fibrotic markers, fibronectin, and N-cadherin in TGF-ß-induced MRC-5 cells. The research showed the potential of cevanine-type alkaloids as a class of natural antifibrotic agents.

TRAF2 decrease promotes the TGF-ß-mTORC1 signal in MAFLD-HCC through enhancing AXIN1-mediated Smad7 degradation.

According to recent research, metabolic-associated fatty liver disease (MAFLD) has emerged as an important underlying etiology of hepatocellular carcinoma (HCC). However, the molecular mechanism of MAFLD-HCC is still unclear. Tumor necrosis factor receptor-associated factor 2 (TRAF2) is the key molecule to mediate the signal of inflammatory NF-κB pathway. This study aims to investigate the potential dysregulation of TRAF2 and its biological function in MAFLD-HCC. Huh7 TRAF2-/- demonstrated increased tumor formation ability compared to huh7 TRAF2+/+ when stimulated with transforming growth factor-ß (TGF-ß). The decisive role of TGF-ß in the development of MAFLD-HCC was confirmed through the specific depletion of TGF-ß receptor II gene in the hepatocytes (Tgfbr2ΔHep) of mice. In TRAF2-/- cells treated with TGF-ß, both the glycolysis rate and lipid synthesis were enhanced. We proved the signal of the mechanistic target of rapamycin complex 1 (mTORC1) could be activated in the presence of TGF-ß, and was enhanced in TRAF2-/- cells. The coimmunoprecipitation (co-IP) experiments revealed that TRAF2 fortified the Smurf2-mediated ubiquitination degradation of AXIN1. Hence, TRAF2 depletion resulted in increased Smad7 degradation induced by AXIN1, thus promoting the TGF-ß signal. We also discovered that PLX-4720 could bind with AXIN1 and restrained the tumor proliferation of TRAF2-/- in mice fed with high-fat diet (HFD). Our findings indicate that TRAF2 plays a significant role in the pathogenesis of MAFLD-HCC. The reduction of TRAF2 expression leads to the enhancement of the TGF-ß-mTORC1 pathway by facilitating AXIN1-mediated Smad7 degradation.

In silico drug repurposing carvedilol and its metabolites against SARS-CoV-2 infection using molecular docking and molecular dynamic simulation approaches.

The pandemic of coronavirus disease 2019 (COVID-19) caused by the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a significant impact on the economy and public health worldwide. Therapeutic options such as drugs and vaccines for this newly emerged disease are eagerly desired due to the high mortality. Using the U.S. Food and Drug Administration (FDA) approved drugs to treat a new disease or entirely different diseases, in terms of drug repurposing, minimizes the time and cost of drug development compared to the de novo design of a new drug. Drug repurposing also has some other advantages such as reducing safety evaluation to accelerate drug application on time. Carvedilol, a non-selective beta-adrenergic blocker originally designed to treat high blood pressure and manage heart disease, has been shown to impact SARS-CoV-2 infection in clinical observation and basic studies. Here, we applied computer-aided approaches to investigate the possibility of repurposing carvedilol to combat SARS-CoV-2 infection. The molecular mechanisms and potential molecular targets of carvedilol were identified by evaluating the interactions of carvedilol with viral proteins. Additionally, the binding affinities of in vivo metabolites of carvedilol with selected targets were evaluated. The docking scores for carvedilol and its metabolites with RdRp were - 10.0 kcal/mol, - 9.8 kcal/mol (1-hydroxyl carvedilol), - 9.7 kcal/mol (3-hydroxyl carvedilol), - 9.8 kcal/mol (4-hydroxyl carvedilol), - 9.7 kcal/mol (5-hydroxyl carvedilol), - 10.0 kcal/mol (8-hydroxyl carvedilol), and - 10.1 kcal/mol (O-desmethyl carvedilol), respectively. Using the molecular dynamics simulation (100 ns) method, we further confirmed the stability of formed complexes of RNA-dependent RNA polymerase (RdRp) and carvedilol or its metabolites. Finally, the drug-target interaction mechanisms that contribute to the complex were investigated. Overall, this study provides the molecular targets and mechanisms of carvedilol and its metabolites as repurposed drugs to fight against SARS-CoV-2 infection.

Quantitative 1H NMR with global spectral deconvolution approach for quality assessment of natural and cultured Cordyceps sinensis.

Cordyceps sinensis is a precious medicinal food which has been successfully cultivated indoors. It remains to be investigated for a simultaneous comparison on aqueous components of natural and cultivated samples. Herein, an approach of quantitative nuclear magnetic resonance (qNMR) analysis combined with global spectral deconvolution (GSD) was established for simultaneous quantification of 26 aqueous components in C. sinensis. Processed by GSD, the distorted baselines of 1H NMR spectra were greatly improved, and overlapped signals were also well separated so as to achieve accurate identification and quantitation of components in C. sinensis. Method validation by UHPLC-QTOF-MS and TOF-SIMS analysis revealed that qNMR combined with GSD is a reliable approach for simultaneous quantification of multiple components including characteristic markers of glutamine, GABA and trehalose in authentic and fake C. sinensis. The well-established qNMR approach can be used for quality assessment of natural and cultivated C. sinensis as well as differentiation from fake ones.

A new perspective on hippocampal synaptic plasticity and post-stroke depression.

Post-stroke depression, a common complication after stroke, severely affects the recovery and quality of life of patients with stroke. Owing to its complex mechanisms, post-stroke depression treatment remains highly challenging. Hippocampal synaptic plasticity is one of the key factors leading to post-stroke depression; however, the precise molecular mechanisms remain unclear. Numerous studies have found that neurotrophic factors, protein kinases and neurotransmitters influence depressive behaviour by modulating hippocampal synaptic plasticity. This review further elaborates on the role of hippocampal synaptic plasticity in post-stroke depression by summarizing recent research and analysing possible molecular mechanisms. Evidence for the correlation between hippocampal mechanisms and post-stroke depression helps to better understand the pathological process of post-stroke depression and improve its treatment.

Di- and Triterpenoids from the Rhizomes of Isodon amethystoides and Their Anti-inflammatory Activities.

Amethystoidesic acid (1), a triterpenoid with an unprecedented 5/6/6/6 tetracyclic skeleton, and six undescribed diterpenoids, amethystoidins A-F (2-7), were isolated from the rhizomes of Isodon amethystoides along with 31 known di- and triterpenoids (8-38). Their structures were fully elucidated via extensive spectroscopic analysis including 1D and 2D NMR, high-resolution electrospray ionization mass spectrometry (HRESIMS), and electronic circular dichroism (ECD) calculations. Compound 1 is the first example of a triterpenoid possessing a rare ring system (5/6/6/6) derived from a contracted A-ring and the 18,19-seco-E-ring of ursolic acid. Compounds 6, 16, 21, 22, 24, and 27 significantly inhibited nitric oxide (NO) production in lipopolysaccharide (LPS)-stimulated RAW264.7 cells, which could be partly mediated by the downregulation of LPS-induced inducible nitric oxide synthase (iNOS) protein expression.

Sirtuin4 impacts mitochondrial homeostasis in pancreatic cancer cells by reducing the stability of AlkB homolog 1 via deacetylation of the HRD1-SEL1L complex.

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant tumor with a poor prognosis. As a tumor inhibitor, the specific tumor suppressor mechanism of Sirtuin4(SIRT4) in PDAC remains elusive. In this study, SIRT4 was found to inhibit PDAC by impacting mitochondrial homeostasis. SIRT4 deacetylated lysine 547 of SEL1L and increased the protein level of an E3 ubiquitin ligase HRD1. As a central member of ER-associated protein degradation (ERAD), HRD1-SEL1L complex is recently reported to regulate the mitochondria, though the mechanism is not fully delineated. Here, we found the increase in SEL1L-HRD1 complex decreased the stability of a mitochondrial protein, ALKBH1. Downregulation of ALKBH1 subsequently blocked the transcription of mitochondrial DNA-coded genes, and resulted in mitochondrial damage. Lastly, a putative SIRT4 stimulator, Entinostat, was identified, which upregulated the expression of SIRT4 and effectively inhibited pancreatic cancer in vivo and in vitro.

Anti-Entry Activity of Natural Flavonoids against SARS-CoV-2 by Targeting Spike RBD.

COVID-19 is still a global public health concern, and the SARS-CoV-2 mutations require more effective antiviral agents. In this study, the antiviral entry activity of thirty-one flavonoids was systematically evaluated by a SARS-CoV-2 pseudovirus model. Twenty-four flavonoids exhibited antiviral entry activity with IC50 values ranging from 10.27 to 172.63 µM and SI values ranging from 2.33 to 48.69. The structure-activity relationship of these flavonoids as SARS-CoV-2 entry inhibitors was comprehensively summarized. A subsequent biolayer interferometry assay indicated that flavonoids bind to viral spike RBD to block viral interaction with ACE2 receptor, and a molecular docking study also revealed that flavonols could bind to Pocket 3, the non-mutant regions of SARS-CoV-2 variants, suggesting that flavonols might be also active against virus variants. These natural flavonoids showed very low cytotoxic effects on human normal cell lines. Our findings suggested that natural flavonoids might be potential antiviral entry agents against SARS-CoV-2 via inactivating the viral spike. It is hoped that our study will provide some encouraging evidence for the use of natural flavonoids as disinfectants to prevent viral infections.

Factors associated with gastrointestinal stromal tumor rupture and pathological risk: A single-center retrospective study.

BACKGROUND: Gastrointestinal stromal tumor (GIST) is a rare gastrointestinal mesenchymal tumor with potential malignancy. Once the tumor ruptures, regardless of tumor size and mitotic number, it can be identified into a high-risk group. It is of great significance for the diagnosis, treatment, and prognosis of GIST if non-invasive examination can be performed before surgery to accurately assess the risk of tumor. AIM: To identify the factors associated with GIST rupture and pathological risk. METHODS: A cohort of 50 patients with GISTs, as confirmed by postoperative pathology, was selected from our hospital. Clinicopathological and computed tomography data of the patients were collected. Logistic regression analysis was used to evaluate factors associated with GIST rupture and pathological risk grade. RESULTS: Pathological risk grade, tumor diameter, tumor morphology, internal necrosis, gas-liquid interface, and Ki-67 index exhibited significant associations with GIST rupture (P < 0.05). Gender, tumor diameter, tumor rupture, and Ki-67 index were found to be correlated with pathological risk grade of GIST (P < 0.05). Multifactorial logistic regression analysis revealed that male gender and tumor diameter ≥ 10 cm were independent predictors of a high pathological risk grade of GIST [odds ratio (OR) = 11.12, 95% confidence interval (95%CI): 1.81-68.52, P = 0.01; OR = 22.96, 95%CI: 2.19-240.93, P = 0.01]. Tumor diameter ≥ 10 cm, irregular shape, internal necrosis, gas-liquid interface, and Ki-67 index ≥ 10 were identified as independent predictors of a high risk of GIST rupture (OR = 9.67, 95%CI: 2.15-43.56, P = 0.01; OR = 35.44, 95%CI: 4.01-313.38, P < 0.01; OR = 18.75, 95%CI: 3.40-103.34, P < 0.01; OR = 27.00, 95%CI: 3.10-235.02, P < 0.01; OR = 4.43, 95%CI: 1.10-17.92, P = 0.04). CONCLUSION: Tumor diameter, tumor morphology, internal necrosis, gas-liquid, and Ki-67 index are associated with GIST rupture, while gender and tumor diameter are linked to the pathological risk of GIST. These findings contribute to our understanding of GIST and may inform non-invasive examination strategies and risk assessment for this condition.

The glucotoxicity protecting effect of honokiol in human hepatocytes via directly activating AMPK.

Introduction: Sustained hyperglycemia causes glucotoxicity, which has been regarded as a contributor to hepatocyte damage in type 2 diabetes (T2D) and its metabolic comorbidities. Honokiol is a natural biphenolic component derived from the dietary supplement Magnolia officinalis extract. This study aimed to investigate the effects of honokiol on glucose metabolism disorders and oxidative stress in hepatocytes and the underlying mechanisms. Methods: HepG2 cells were treated with glucosamines (18 mM) to induce glucotoxicity as a diabetic complication model in vitro. Results and discussion: Honokiol significantly increased glucose consumption, elevated 2-NBDG uptake, and promoted GLUT2 translocation to the plasma membrane in glucosamine-treated HepG2 cells, indicating that honokiol ameliorates glucose metabolism disorders. Furthermore, glucosamine-induced ROS accumulation and loss of mitochondrial membrane potential were markedly reduced by honokiol, suggesting that honokiol alleviated glucotoxicity-induced oxidative stress. These effects were largely abolished by compound C, an AMPK inhibitor, suggesting an AMPK activation-dependent manner of honokiol function in promoting glucose metabolism and mitigating oxidative stress. Molecular docking results revealed that honokiol could interact with the amino acid residues (His151, Arg152, Lys243, Arg70, Lys170, and His298) in the active site of AMPK. These findings provide new insights into the antidiabetic effect of honokiol, which may be a promising agent for the prevention and treatment of T2D and associated metabolic comorbidities.

Exploring new catechin derivatives as SARS-CoV-2 Mpro inhibitors from tea by molecular networking, surface plasma resonance, enzyme inhibition, induced fit docking, and metadynamics simulations.

SARS-CoV-2 Mpro (Mpro) is the critical cysteine protease in coronavirus viral replication. Tea polyphenols are effective Mpro inhibitors. Therefore, we aim to isolate and synthesize more novel tea polyphenols from Zhenghedabai (ZHDB) white tea methanol-water (MW) extracts that might inhibit COVID-19. Through molecular networking, 33 compounds were identified and divided into 5 clusters. Further, natural products molecular network (MN) analysis showed that MN1 has new phenylpropanoid-substituted ester-catechin (PSEC), and MN5 has the important basic compound type hydroxycinnamoylcatechins (HCCs). Thus, a new PSEC (1, PSEC636) was isolated, which can be further detected in 14 green tea samples. A series of HCCs were synthesized (2-6), including three new acetylated HCCs (3-5). Then we used surface plasmon resonance (SPR) to analyze the equilibrium dissociation constants (KD) for the interaction of 12 catechins and Mpro. The KD values of PSEC636 (1), EGC-C (2), and EC-CDA (3) were 2.25, 2.81, and 2.44 µM, respectively. Moreover, compounds 1, 2, and 3 showed the potential Mpro inhibition with IC50 5.95 ± 0.17, 9.09 ± 0.22, and 23.10 ± 0.69 µM, respectively. Further, we used induced fit docking (IFD), binding pose metadynamics (BPMD), and molecular dynamics (MD) to explore the stable binding pose of Mpro-1, showing that 1 could tightly bond with the amino acid residues THR26, HIS41, CYS44, TYR54, GLU166, and ASP187. The computer modeling studies reveal that the ester, acetyl, and pyrogallol groups could improve inhibitory activity. Our research suggests that these catechins are effective Mpro inhibitors, and might be developed as therapeutics against COVID-19.

Joint reconstruction of neuron and ultrastructure via connectivity consensus in electron microscope volumes.

BACKGROUND: Nanoscale connectomics, which aims to map the fine connections between neurons with synaptic-level detail, has attracted increasing attention in recent years. Currently, the automated reconstruction algorithms in electron microscope volumes are in great demand. Most existing reconstruction methodologies for cellular and subcellular structures are independent, and exploring the inter-relationships between structures will contribute to image analysis. The primary goal of this research is to construct a joint optimization framework to improve the accuracy and efficiency of neural structure reconstruction algorithms. RESULTS: In this investigation, we introduce the concept of connectivity consensus between cellular and subcellular structures based on biological domain knowledge for neural structure agglomeration problems. We propose a joint graph partitioning model for solving ultrastructural and neuronal connections to overcome the limitations of connectivity cues at different levels. The advantage of the optimization model is the simultaneous reconstruction of multiple structures in one optimization step. The experimental results on several public datasets demonstrate that the joint optimization model outperforms existing hierarchical agglomeration algorithms. CONCLUSIONS: We present a joint optimization model by connectivity consensus to solve the neural structure agglomeration problem and demonstrate its superiority to existing methods. The intention of introducing connectivity consensus between different structures is to build a suitable optimization model that makes the reconstruction goals more consistent with biological plausible and domain knowledge. This idea can inspire other researchers to optimize existing reconstruction algorithms and other areas of biological data analysis.

Integrated network pharmacology analysis, molecular docking, LC-MS analysis and bioassays revealed the potential active ingredients and underlying mechanism of Scutellariae radix for COVID-19.

Scutellariae radix ("Huang-Qin" in Chinese) is a well-known traditional herbal medicine and popular dietary supplement in the world, extensively used in prescriptions of TCMs as adjuvant treatments for coronavirus pneumonia 2019 (COVID-19) patients in China. According to the differences in its appearance, Scutellariae radix can be classified into two kinds: ZiQin (1∼3 year-old Scutellariae baicalensis with hard roots) and KuQin (more than 3 year-old S. baicalensis with withered pithy roots). In accordance with the clinical theory of TCM, KuQin is superior to ZiQin in cooling down the heat in the lung. However, the potential active ingredients and underlying mechanisms of Scutellariae radix for the treatment of COVID-19 remain largely unexplored. It is still not clear whether there is a difference in the curative effect of ZiQin and KuQin for the treatment of COVID-19. In this research, network pharmacology, LC-MS based plant metabolomics, and in vitro bioassays were integrated to explore both the potential active components and mechanism of Scutellariae radix for the treatment of COVID-19. As the results, network pharmacology combined with molecular docking analysis indicated that Scutellariae radix primarily regulates the MAPK and NF-κB signaling pathways via active components such as baicalein and scutellarin, and blocks SARS-CoV-2 spike binding to human ACE2 receptors. In vitro bioassays showed that baicalein and scutellarein exhibited more potent anti-inflammatory and anti-infectious effects than baicalin, the component with the highest content in Scutellariae radix. Moreover, baicalein inhibited SARS-CoV-2's entry into Vero E6 cells with an IC50 value of 142.50 µM in a plaque formation assay. Taken together, baicalein was considered to be the most crucial active component of Scutellariae radix for the treatment of COVID-19 by integrative analysis. In addition, our bioassay study revealed that KuQin outperforms ZiQin in the treatment of COVID-19. Meanwhile, plant metabolomics revealed that baicalein was the compound with the most significant increase in KuQin compared to ZiQin, implying the primary reason for the superiority of KuQin over ZiQin in the treatment of COVID-19.

High Quality Pt-Pt Metal Bonding for High Temperature Packaging.

Platinum is an ideal material for high-temperature resistant device packaging due to its higher melting point and good electrical properties. In this paper, the thermocompression bonding of Pt-Pt metal electrodes was successfully realized through process exploration, and the package interconnection that meets the requirements was formed. A square bump with a side length of 160 µm and a sealing ring with a width of 80 µm were fabricated by magnetron sputtering. Different pressure parameters were selected for chip-level bonding; the bonding temperature was 350 °C for about 20 min. Analysis of the interface under a scanning electron microscope found that the metal Cr diffused into Pt. It was found that two chips sputtered with 300 nm metal Pt can achieve shear resistance up to 30 MPa by flip-chip bonding at 350 °C and 100 MPa temperature and pressure, respectively. The leakage rate of the sample is less than 2 × 10-3 Pa·cm3/s, the bonding interface is relatively smooth, and the hot-pressed metal bonding of Pt electrodes with good quality is realized. By comparing the failure rates at different temperatures and pressures, the process parameters for Pt-Pt bonding with higher success rates were obtained. We hope to provide new ideas and methods for the packaging of high-temperature resistant devices.

Structures, biomimetic synthesis, and anti-SARS-CoV-2 activity of two pairs of enantiomeric phenylpropanoid-conjugated protoberberine alkaloids from the rhizomes of Corydalis decumbens.

(±)-Decumicorine A (1) and (±)-epi-decumicorine A (2), two pairs of enantiomeric isoquinoline alkaloids featuring a novel phenylpropanoid-conjugated protoberberine skeleton, were isolated and purified from the rhizomes of Corydalis decumbens. The separation of (±)-1 and (±)-2 was achieved by chiral HPLC to produce four optically pure enantiomers. The structures and absolute configurations of compounds (-)-1, (+)-1, (-)-2, and (+)-2 were elucidated by spectroscopic analysis, ECD calculations, and X-ray crystallographic analyses. The two racemates were generated from a Diels-Alder [4 + 2] cycloaddition between jatrorrhizine and ferulic acid in the proposed biosynthetic pathways, which were fully verified by a biomimetic synthesis. Moreover, compound (+)-1 exhibited an antiviral entry effect on SARS-CoV-2 pseudovirus by blocking spike binding to the ACE2 receptor on HEK-293T-ACE2h host cells.