Advances in gut-brain organ chips.

The brain and gut are sensory organs responsible for sensing, transmitting, integrating, and responding to signals from the internal and external environment. In-depth analysis of brain-gut axis interactions is important for human health and disease prevention. Current research on the brain-gut axis primarily relies on animal models. However, animal models make it difficult to study disease mechanisms due to inherent species differences, and the reproducibility of experiments is poor because of individual animal variations, which leads to a significant limitation of real-time sensory responses. Organ-on-a-chip platforms provide an innovative approach for disease treatment and personalized research by replicating brain and gut ecosystems in vitro. This enables a precise understanding of their biological functions and physiological responses. In this article, we examine the history and most current developments in brain, gut, and gut-brain chips. The importance of these systems for understanding pathophysiology and developing new drugs is emphasized throughout the review. This article also addresses future directions and present issues with the advancement and application of gut-brain-on-a-chip technologies.

Progress in SARS-CoV-2, diagnostic and clinical treatment of COVID-19.

Background: Corona Virus Disease 2019(COVID-19)is a global pandemic novel coronavirus infection disease caused by Severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2). Although rapid, large-scale testing plays an important role in patient management and slowing the spread of the disease. However, there has been no good and widely used drug treatment for infection and transmission of SARS-CoV-2. Key findings: Therefore, this review updates the body of knowledge on viral structure, infection routes, detection methods, and clinical treatment, with the aim of responding to the large-section caused by SARS-CoV-2. This paper focuses on the structure of SARS-CoV-2 viral protease, RNA polymerase, serine protease and main proteinase-like protease as well as targeted antiviral drugs. Conclusion: In vitro or clinical trials have been carried out to provide deeper thinking for the pathogenesis, clinical diagnosis, vaccine development and treatment of SARS-CoV-2.

Intrafractional motion and dosimetric analysis in prostate stereotactic body radiation therapy with auto beam hold technique.

Objective: To summarize our institutional prostate stereotactic body radiation therapy (SBRT) experience using auto beam hold (ABH) technique for intrafractional prostate motion and assess ABH tolerance of 10-millimeter (mm) diameter.Approach: Thirty-two patients (160 fractions) treated using ABH technique between 01/2018 and 03/2021 were analyzed. During treatment, kV images were acquired every 20-degree gantry rotation to visualize 3-4 gold fiducials within prostate to track target motion. If the fiducial center fell outside the tolerance circle (diameter = 10 mm), beam was automatically turned off for reimaging and repositioning. Number of beam holds and couch translational movement magnitudes were recorded. Dosimetric differences from intrafractional motion were calculated by shifting planned isocenter.Main Results: Couch movement magnitude (mean ± SD) in vertical, longitudinal and lateral directions were -0.7 ± 2.5, 1.4 ± 2.9 and -0.1 ± 0.9 mm, respectively. For most fractions (77.5%), no correction was necessary. Number of fractions requiring one, two, or three corrections were 15.6%, 5.6% and 1.3%, respectively. Of the 49 corrections, couch shifts greater than 3 mm were seen primarily in the vertical (31%) and longitudinal (39%) directions; corresponding couch shifts greater than 5 mm occurred in 2% and 6% of cases. Dosimetrically, 100% coverage decreased less than 2% for clinical target volume (CTV) (-1 ± 2%) and less than 10% for PTV (-10 ± 6%). Dose to bladder, bowel and urethra tended to increase (Bladder: ΔD10%:184 ± 466 cGy, ΔD40%:139 ± 241 cGy, Bowel: ΔD1 cm3:54 ± 129 cGy; ΔD5 cm3:44 ± 116 cGy, Urethra: ΔD0.03 cm3:1 ± 1%). Doses to the rectum tended to decrease (Rectum: ΔD1 cm3:-206 ± 564 cGy, ΔD10%:-97 ± 426 cGy; ΔD20%:-50 ± 251 cGy).Significance: With the transition from conventionally fractionated intensity modulated radiation therapy to SBRT for localized prostate cancer treatment, it is imperative to ensure that dose delivery is spatially accurate for appropriate coverage to target volumes and limiting dose to surrounding organs. Intrafractional motion monitoring can be achieved using triggered imaging to image fiducial markers and ABH to allow for reimaging and repositioning for excessive motion.

Regioselective Propargylic Suzuki-Miyaura Coupling by SciPROP-Iron Catalyst.

The iron-catalyzed Suzuki-Miyaura cross-coupling of secondary propargyl electrophiles with lithium organoborates has been established. A propyl-bridged bulky bisphosphine ligand, SciPROP-TB, cooperated with the bulky TIPS substituent at the alkyne terminal position to achieve the cross-coupling reaction with exclusive propargylic selectivity. The reaction features high functional group compatibility, regioselectivity, and yield with a broad substrate scope. The reaction of an optically active chiral propargyl bromide proceeds with complete racemization, supporting a mechanism involving propargyl radical formation.

Exploring Dual-Energy CT Spectral Information for Machine Learning-Driven Lesion Diagnosis in Pre-Log Domain.

In this study, we proposed a computer-aided diagnosis (CADx) framework under dual-energy spectral CT (DECT), which operates directly on the transmission data in the pre-log domain, called CADxDE, to explore the spectral information for lesion diagnosis. The CADxDE includes material identification and machine learning (ML) based CADx. Benefits from DECT's capability of performing virtual monoenergetic imaging with the identified materials, the responses of different tissue types (e.g., muscle, water, and fat) in lesions at each energy can be explored by ML for CADx. Without losing essential factors in the DECT scan, a pre-log domain model-based iterative reconstruction is adopted to obtain decomposed material images, which are then used to generate the virtual monoenergetic images (VMIs) at selected n energies. While these VMIs have the same anatomy, their contrast distribution patterns contain rich information along with the n energies for tissue characterization. Thus, a corresponding ML-based CADx is developed to exploit the energy-enhanced tissue features for differentiating malignant from benign lesions. Specifically, an original image-driven multi-channel three-dimensional convolutional neural network (CNN) and extracted lesion feature-based ML CADx methods are developed to show the feasibility of CADxDE. Results from three pathologically proven clinical datasets showed 4.01% to 14.25% higher AUC (area under the receiver operating characteristic curve) scores than the scores of both the conventional DECT data (high and low energy spectrum separately) and the conventional CT data. The mean gain >9.13% in AUC scores indicated that the energy spectral-enhanced tissue features from CADxDE have great potential to improve lesion diagnosis performance.

A Joint-Parameter Estimation and Bayesian Reconstruction Approach to Low-Dose CT.

Most penalized maximum likelihood methods for tomographic image reconstruction based on Bayes' law include a freely adjustable hyperparameter to balance the data fidelity term and the prior/penalty term for a specific noise-resolution tradeoff. The hyperparameter is determined empirically via a trial-and-error fashion in many applications, which then selects the optimal result from multiple iterative reconstructions. These penalized methods are not only time-consuming by their iterative nature, but also require manual adjustment. This study aims to investigate a theory-based strategy for Bayesian image reconstruction without a freely adjustable hyperparameter, to substantially save time and computational resources. The Bayesian image reconstruction problem is formulated by two probability density functions (PDFs), one for the data fidelity term and the other for the prior term. When formulating these PDFs, we introduce two parameters. While these two parameters ensure the PDFs completely describe the data and prior terms, they cannot be determined by the acquired data; thus, they are called complete but unobservable parameters. Estimating these two parameters becomes possible under the conditional expectation and maximization for the image reconstruction, given the acquired data and the PDFs. This leads to an iterative algorithm, which jointly estimates the two parameters and computes the to-be reconstructed image by maximizing a posteriori probability, denoted as joint-parameter-Bayes. In addition to the theoretical formulation, comprehensive simulation experiments are performed to analyze the stopping criterion of the iterative joint-parameter-Bayes method. Finally, given the data, an optimal reconstruction is obtained without any freely adjustable hyperparameter by satisfying the PDF condition for both the data likelihood and the prior probability, and by satisfying the stopping criterion. Moreover, the stability of joint-parameter-Bayes is investigated through factors such as initialization, the PDF specification, and renormalization in an iterative manner. Both phantom simulation and clinical patient data results show that joint-parameter-Bayes can provide comparable reconstructed image quality compared to the conventional methods, but with much less reconstruction time. To see the response of the algorithm to different types of noise, three common noise models are introduced to the simulation data, including white Gaussian noise to post-log sinogram data, Poisson-like signal-dependent noise to post-log sinogram data and Poisson noise to the pre-log transmission data. The experimental outcomes of the white Gaussian noise reveal that the two parameters estimated by the joint-parameter-Bayes method agree well with simulations. It is observed that the parameter introduced to satisfy the prior's PDF is more sensitive to stopping the iteration process for all three noise models. A stability investigation showed that the initial image by filtered back projection is very robust. Clinical patient data demonstrated the effectiveness of the proposed joint-parameter-Bayes and stopping criterion.

Machine Learned Texture Prior From Full-Dose CT Database via Multi-Modality Feature Selection for Bayesian Reconstruction of Low-Dose CT.

In our earlier study, we proposed a regional Markov random field type tissue-specific texture prior from previous full-dose computed tomography (FdCT) scan for current low-dose CT (LdCT) imaging, which showed clinical benefits through task-based evaluation. Nevertheless, two assumptions were made for early study. One assumption is that the center pixel has a linear relationship with its nearby neighbors and the other is previous FdCT scans of the same subject are available. To eliminate the two assumptions, we proposed a database assisted end-to-end LdCT reconstruction framework which includes a deep learning texture prior model and a multi-modality feature based candidate selection model. A convolutional neural network-based texture prior is proposed to eliminate the linear relationship assumption. And for scenarios in which the concerned subject has no previous FdCT scans, we propose to select one proper prior candidate from the FdCT database using multi-modality features. Features from three modalities are used including the subjects' physiological factors, the CT scan protocol, and a novel feature named Lung Mark which is deliberately proposed to reflect the z-axial property of human anatomy. Moreover, a majority vote strategy is designed to overcome the noise effect from LdCT scans. Experimental results showed the effectiveness of Lung Mark. The selection model has accuracy of 84% testing on 1,470 images from 49 subjects. The learned texture prior from FdCT database provided reconstruction comparable to the subjects having corresponding FdCT. This study demonstrated the feasibility of bringing clinically relevant textures from available FdCT database to perform Bayesian reconstruction of any current LdCT scan.

The Influence of Air Nanobubbles on Controlling the Synthesis of Calcium Carbonate Crystals.

Numerous approaches have been developed to control the crystalline and morphology of calcium carbonate. In this paper, nanobubbles were studied as a novel aid for the structure transition from vaterite to calcite. The vaterite particles turned into calcite (100%) in deionized water containing nanobubbles generated by high-speed shearing after 4 h, in comparison to a mixture of vaterite (33.6%) and calcite (66.3%) by the reaction in the deionized water in the absence of nanobubbles. The nanobubbles can coagulate with calcite based on the potential energy calculated and confirmed by the extended DLVO (Derjaguin-Landau-Verwey-Overbeek) theory. According to the nanobubble bridging capillary force, nanobubbles were identified as the binder in strengthening the coagulation between calcite and vaterite and accelerated the transformation from vaterite to calcite.

Sacha Inchi Oil Press-Cake Protein Hydrolysates Exhibit Anti-Hyperuricemic Activity via Attenuating Renal Damage and Regulating Gut Microbiota.

The incidence of hyperuricemia has increased globally due to changes in dietary habits. The sacha inchi oil press-cake is generally discarded, resulting in the waste of resources and adverse environmental impact. For the purpose of developing sacha inchi oil press-cake and identifying natural components with anti-hyperuricemic activities, we systemically investigated the underlying mechanisms of sacha inchi oil press-cake protein hydrolysates (SISH) in the hyperuricemic rat model. SISH was obtained from sacha inchi oil press-cake proteins after trypsin treatment, and 24 peptides with small molecular weight (<1000 Da) were identified. The results of animal experiments showed that SISH significantly decreased the serum uric acid (UA) level by inhibiting the xanthine oxidase (XOD) activity and regulating the gene expression related to UA production and catabolism in hyperuricemia rats, such as Xdh and Hsh. In addition, SISH attenuated the renal damage and reduced the gene expression related to inflammation (Tlr4, Map3k8, Pik3cg, Pik3ap1, Ikbke, and Nlrp3), especially Tlr4, which has been considered a receptor of UA. Notably, SISH reversed high purine-induced gut microbiota dysbiosis, particularly by enhancing the relative abundance of butyric acid-producing bacteria (unidentified_Ruminococcaceae, Oscillibacter, Ruminiclostridium, Intestinimonas). This research provided new insights into the treatment of hyperuricemia.

New compound probiotic beverage protects against antibiotic-associated diarrhea in mice by modulating the microbiota.

Probiotics and their products are the classic way to treat and prevent gastrointestinal diseases. In this study, the authors designed new combinations and doses of probiotic beverages for antibiotic-associated diarrhea. Group S1 was different from the other groups, including Lactobacillus rhamnosus HN001, Lactobacillus acidophilus NCFM and Bifidobacterium lactis BI-07. Its inulin content was higher than those of the other groups. Mice were induced with a 16-day administration of triple antibiotics in advance for 2 weeks prior to antibiotic treatment. In the experiment, the treatment group returned to normal more quickly than the placebo group. In group S1, the relative abundance of the phylum Firmicutes and genus Lactobacillus increased, and the structure of the microbiota was the closest to normal among all groups. In conclusion, the combinations of probiotic beverages effectively caused structural recovery of the gut and fecal microbiota against antibiotic-associated diarrhea, and the S1 formula showed the best efficacy.

Supplementation of Bacillus sp. DU-106 Alleviates Antibiotic-Associated Diarrhea in Association with the Regulation of Intestinal Microbiota in Mice.

Bacillus sp. DU-106, a potential probiotic, has been proved to activate innate immunity, reduce hypercholesterolemia, and regulate the gut microbiota of mice. In the present study, we investigated the therapeutic effect of strain DU-106 in antibiotic-associated diarrhea (AAD) via analyzing the changes in gut microbial composition in mice. The results indicated that supplementation of strain DU-106 alleviated gastrointestinal symptoms, improved gut barrier integrity and immunoglobulin-A level of mice with AAD. A 16S rRNA sequencing showed that antibiotics decreased bacterial diversity and the abundances of Alistipes, Roseburia, Hungatella, Eubacterium-xylanophilum, Lachnospiraceae-UCG-001, Intestinimonas, and Lachnospiraceae-NK4A136, but increased the abundance of Klebsiella, Bacteroidota, and Verrucomicrobiota. However, strain DU-106 treatment reversed these alternations in mice with AAD. In conclusion, strain DU-106 could alleviate AAD in association with the regulation of intestinal microbiota and could be used as an alternative treatment for AAD.

Methods of Respiratory Virus Detection: Advances towards Point-of-Care for Early Intervention.

Respiratory viral infections threaten human life and inflict an enormous healthcare burden worldwide. Frequent monitoring of viral antibodies and viral load can effectively help to control the spread of the virus and make timely interventions. However, current methods for detecting viral load require dedicated personnel and are time-consuming. Additionally, COVID-19 detection is generally relied on an automated PCR analyzer, which is highly instrument-dependent and expensive. As such, emerging technologies in the development of respiratory viral load assays for point-of-care (POC) testing are urgently needed for viral screening. Recent advances in loop-mediated isothermal amplification (LAMP), biosensors, nanotechnology-based paper strips and microfluidics offer new strategies to develop a rapid, low-cost, and user-friendly respiratory viral monitoring platform. In this review, we summarized the traditional methods in respiratory virus detection and present the state-of-art technologies in the monitoring of respiratory virus at POC.

Leaching of indium and tin from waste LCD by a time-efficient method assisted planetary high energy ball milling.

The phenomenon of the long leaching time and low leaching rate is presented in the acid leaching process under the conventional conditions of low reaction temperature and acid concentration. In order to promote leaching rates of indium and tin in waste liquid crystal display, an optimized process combining rapid milling and acid leaching has been proposed, which is more time and energy-efficient, environmentally sound compared with the traditional acid leaching process. Leaching mechanism analysis was conducted to uncover the different leaching behavior of indium and tin. And the external factors affecting the leaching rates of indium and tin were studied to optimize. In this process, the fine powder with a weight ratio of 97.6%, which particle size less than 0.075 mm, was obtained with the optimal milling time of 30 min by rapid grinding in the planetary high energy ball milling. About -0.003 l/s of grinding rate constant was performed in the grinding size fraction from 3 mm to 0.075 mm. The research results indicated that the particle size less than 0.035 mm was agglomerated, and the addition of H2O2 reduced the leaching rate for the particle size less than 0.075 mm. Moreover, 86.3% and 76.1% of indium and tin were leached in a short leaching time of 10 min by using 3 M H2SO4 at 85 °C for particle size range from 0.075 to 0.035 mm, while 96.9% and 85.6%, respectively in 90 min.

Associations between hematological parameters and disease severity in patients with SARS-CoV-2 infection.

BACKGROUND: The emergence and rapid spread of the deadly novel coronavirus disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a swiftly evolving public health crisis worldwide. SARS-CoV-2 infection is characterized by the development and progression of inflammatory responses. Hematological parameters, such as white blood cells (WBCs) and their subpopulations, red cell distribution width, platelet count, mean platelet volume, plateletcrit, and derived markers such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio, are established biomarkers of inflammatory responses. We aimed to investigate associations between hematological parameters and disease severity in patients with SARS-CoV-2 infection. METHODS: We retrospectively analyzed data from 68 patients with confirmed SARS-CoV-2 infection. Twenty-two patients had mild illness, and 46 had moderate or severe illness at the time of admission. Univariate and multivariate regression analyses were used to identify correlates of disease severity. The areas under receiver operating characteristic curves were calculated to estimate and compare the predictive values of different diagnostic markers. RESULTS: Mean lymphocyte and monocyte counts were lower while WBC counts, neutrophil counts, NLR, and PLR were higher in patients with severe disease compared with those with mild disease (all P < .01). Univariate analysis revealed that older age, high WBC counts, high neutrophil counts, high NLR, high PLR, low monocyte counts, and low lymphocyte counts were independent correlates of severe illness. Multivariate analysis identified high NLR as the only independent correlate of severe illness. Receiver operating characteristic curve analysis showed that NLR had the highest area under curve of all hematological parameters. CONCLUSION: Among hematological parameters, the NLR showed superior prediction of disease severity in patients with SARS-CoV-2 infection. Thus, the NLR could be a valuable parameter to complement conventional measures for identification of patients at high risk for severe disease.

Characterization of tissue-specific pre-log Bayesian CT reconstruction by texture-dose relationship.

PURPOSE: Tissue textures have been recognized as biomarkers for various clinical tasks. In computed tomography (CT) image reconstruction, it is important but challenging to preserve the texture when lowering x-ray exposure from full- toward low-/ultra-low dose level. Therefore, this paper aims to explore the texture-dose relationship within one tissue-specific pre-log Bayesian CT reconstruction algorithm. METHODS: To enhance the texture in ultra-low dose CT (ULdCT) reconstruction, this paper presents a Bayesian type algorithm. A shifted Poisson model is adapted to describe the statistical properties of pre-log data, and a tissue-specific Markov random field prior (MRFt) is used to incorporate tissue texture from previous full-dose CT, thus called SP-MRFt algorithm. Utilizing the SP-MRFt algorithm, we investigated tissue texture degradation as a function of x-ray dose levels from full dose (100 mAs/120 kVp) to ultralow dose (1 mAs/120 kVp) by using quantitative texture-based evaluation metrics. RESULTS: Experimental results show the SP-MRFt algorithm outperforms conventional filtered back projection (FBP) and post-log domain penalized weighted least square MRFt (PWLS-MRFt) in terms of noise suppression and texture preservation. Comparable results are also obtained with shifted Poisson model with 7 × 7 Huber MRF weights (SP-Huber7). The investigation on texture-dose relationship shows that the quantified texture measures drop monotonically as dose level decreases, and interestingly a turning point is observed on the texture-dose response curve. CONCLUSIONS: This important observation implies that there exists a minimum dose level, at which a given CT scanner (hardware configuration and image reconstruction software) can achieve without compromising clinical tasks. Moreover, the experiment results show that the variance of electronic noise has higher impact than the mean to the texture-dose relationship.

Novel NHC-coordinated ruthenium(II) arene complexes achieve synergistic efficacy as safe and effective anticancer therapeutics.

There is an urgent need for more effective, less toxic cancer therapy agents. Motivated by this need, we synthesized a small panel of N-heterocyclic carbene (NHC)-coordinated ruthenium(II) arene complexes Ru1-Ru6 with the formula [Ru(p-cymene)(L)Cl]PF6 (L = NHC ligand with varying substituents). Cell-based in vitro studies revealed that despite the structural similarity, Ru1-Ru6 exhibited distinct cytotoxic activities against cancer cells. In particular, Ru4 and Ru6, which bear n-octyl and pentamethylbenzyl motifs, respectively, were the most active at inducing apoptosis. In human ovarian A2780 cancer cells, Ru4 and Ru6 showed the highest cytotoxicities with IC50 values of 2.74 ± 0.15 µM and 1.98 ± 0.10 µM, respectively, and they were approximately 2-fold more potent than cisplatin (IC50 = 5.55 ± 0.37 µM). In addition to the cell killing capacity, inhibition of cell migration was validated by using these two optimized complexes. Mechanistic studies revealed that Ru4 and Ru6 complexes induced apoptosis in a caspase-dependent manner, primarily through intracellular reactive oxygen species (ROS) overproduction and cell cycle arrest at G1 phase. Furthermore, in a preclinical metastatic model of A2780 tumor xenograft, administration of Ru4 and Ru6 (20 µmol/kg) resulted in a marked inhibition of tumor progression and metastasis. Finally, a substantially alleviated systemic toxicity was observed for both complexes in comparison with cisplatin in animals. Overall, this study greatly increases our understanding of NHC-coordinated Ru(II) arene metallodrugs, aiding further investigation of their therapeutic potential in the treatment of metastatic cancers.

New Organometallic Ruthenium(II) Compounds Synergistically Show Cytotoxic, Antimetastatic and Antiangiogenic Activities for the Treatment of Metastatic Cancer.

In this study, we newly designed and synthesized a small library of ten structurally related C,N-cyclometalated ruthenium(II) complexes containing various pyridine-functionalized NHC ligand and chelating bipyridyl ligands (e.g., 2,2'-bipyridine, 5,5'-dimethyl-2,2'-bipyridine, and 1,10-phenanthroline (phen)). The complexes were well characterized by NMR, electrospray ionization-mass spectrometry, and single-crystal X-ray structure analyses. Among the new ruthenium(II) derivatives, we identified that the complex Ru8 bearing bulky moieties (i.e., phen and pentamethyl benzene) had the most potent cytotoxicity against all tested cancer cell lines, generating dose- and cell line-dependent IC50 values at the range of 3.3-15.0 µm. More significantly, Ru8 not only efficiently inhibited the metastasis process against invasion and migration of tumor cells but also exhibited potent antivascular effects by suppressing HUVEC cells migration and tube formation in vitro and blocking vessel generation in vivo (chicken chorioallantoic membrane model). In a metastatic A2780 tumor xenograft-bearing mouse model, administration of Ru8 outperformed antimetastatic agent NAMI-A and clinically approved cisplatin in terms of antitumor efficacy and inhibition of metastases to other organs. Overall, these data provided compelling evidence that the new cyclometalated ruthenium complex Ru8 is an attractive agent because of synergistically suppressing bulky tumors and metastasized tumor nudes. Therefore, the complex Ru8 deserves further investigations.

A bioartificial liver support system integrated with a DLM/GelMA-based bioengineered whole liver for prevention of hepatic encephalopathy via enhanced ammonia reduction.

Although bioartificial liver support systems (BLSSs) play an essential role in maintaining partial liver functions and detoxification for liver failure patients, hepatocytes are unanimously seeded in biomaterials, which lack the hierarchal structures and mechanical cues of native liver tissues. To address this challenge, we developed a new BLSS by combining a decellularized liver matrix (DLM)/GelMA-based bioengineered whole liver and a perfusion-based, oxygenated bioreactor. The novel bioengineered whole liver was fabricated by integrating photocrosslinkable gelatin (GelMA) and hepatocytes into a DLM. The combination of GelMA and the DLM not only provided a biomimetic extracellular microenvironment (ECM) for enhanced cell immobilization and growth with elevated hepatic functions (e.g., albumin secretion and CYP activities), but also provided biomechanical support to maintain the native structure of the liver. In addition, the perfusion-based, oxygenated bioreactor helped deliver oxygen to the interior tissues of the bioengineered liver, which was of importance for long-term culture. Most importantly, this new bioengineered whole liver decreased ammonia concentration by 45%, whereas direct seeding of hepatocytes in a naked DLM showed no significant reduction. Thus, the developed BLSS integrated with the DLM/GelMA-based bioengineered whole liver can potentially help elevate liver functions and prevent HE in liver failure patients while waiting for liver transplantation.

Regio- and stereoselective synthesis of 1,4-enynes by iron-catalysed Suzuki-Miyaura coupling of propargyl electrophiles under ligand-free conditions.

The first iron-catalysed cross coupling of propargyl electrophiles with lithium alkenylborates has been developed. Various propargyl electrophiles can be cross-coupled with lithium (E)- or (Z)-alkenylborates in a stereospecific manner to afford the corresponding 1,4-enynes in good to excellent yields. The reaction features high SN2-type regioselectivity and functional group compatibility.