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.

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.

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.

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.

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.

Amidoxime Functionalization of Algal/Polyethyleneimine Beads for the Sorption of Sr(II) from Aqueous Solutions.

There is a need for developing new sorbents that incorporate renewable resources for the treatment of metal-containing solutions. Algal-polyethyleneimine beads (APEI) (reinforced with alginate) are functionalized by grafting amidoxime groups (AO-APEI). Physicochemical characteristics of the new material are characterized using FTIR, XPS, TGA, SEM, SEM-EDX, and BET. AO-APEI beads are tested for the recovery of Sr(II) from synthetic solutions after pH optimization (≈ pH 6). Uptake kinetics is fast (equilibrium ≈ 60-90 min). Sorption isotherm (fitted by the Langmuir equation) shows remarkable sorption capacity (≈ 189 mg Sr g-1). Sr(II) is desorbed using 0.2 M HCl/0.5 M CaCl2 solution; sorbent recycling over five cycles shows high stability in terms of sorption/desorption performances. The presence of competitor cations is studied in relation to the pH; the selectivity for Sr(II) is correlated to the softness parameter. Finally, the recovery of Sr(II) is carried out in complex solutions (seawater samples): AO-APEI is remarkably selective over highly concentrated metal cations such as Na(I), K(I), Mg(II), and Ca(II), with weaker selectivity over B(I) and As(V). AO-APEI appears to be a promising material for selective recovery of strontium from complex solutions (including seawater).

Tumor-on-a-chip platforms for assessing nanoparticle-based cancer therapy.

Cancer has become the most prevalent cause of deaths, placing a huge economic and healthcare burden worldwide. Nanoparticles (NPs), as a key component of nanomedicine, provide alternative options for promoting the efficacy of cancer therapy. Current conventional cancer models have limitations in predicting the effects of various cancer treatments. To overcome these limitations, biomimetic and novel 'tumor-on-a-chip' platforms have emerged with other innovative biomedical engineering methods that enable the evaluation of NP-based cancer therapy. In this review, we first describe cancer models for evaluation of NP-based cancer therapy techniques, and then present the latest advances in 'tumor-on-a-chip' platforms that can potentially facilitate clinical translation of NP-based cancer therapies.

Interactions between interleukin-6 and myeloid-derived suppressor cells drive the chemoresistant phenotype of hepatocellular cancer.

Emerging evidence implicates an important role for myeloid-derived suppressor cells (MDSCs) in tumor growth, angiogenesis and metastasis. However, limited knowledge is known about the function of MDSCs in response to chemotherapies. In this study, we find that drug-resistant hepatocellular cancer (HCC) cells-derived conditioned medium significantly enhances the expansion and immunosuppressive function of MDSCs compared to their parental sensitive cells, which is demonstrated by increased level of arginase, nitric oxide (NO), and reactive oxygen species (ROS). Next, we reveal that drug-resistant HCC cells-derived IL-6 activated MDSCs, which is demonstrated by using an anti-IL-6 neutralizing antibody that caused a reduced MDSC immunosuppressive activity. More importantly, the depletion of MDSC via the administration of anti-Gr-1 antibody or the blockade of IL-6 signaling sensitized 5-FU-resistant H22 hepatoma to chemotherapy in the immunocompetent C57BL/6N mice. In primary human HCC, IL-6 expression levels strongly correlate with an MDSC phenotype and chemotherapy response in HCC patients. In conclusion, these results describe a role of IL-6 in the drug resistance in HCC chemotherapy and suggest that MDSC-targeting treatments may be potential therapeutic strategy for HCC chemoresistance.

Nanomaterial-based biosensors for measurement of lipids and lipoproteins towards point-of-care of cardiovascular disease.

Cardiovascular disease (CVD) has become the primary cause of global deaths and inflicts an enormous healthcare burden on both developed and developing countries. Frequent monitoring of CVD-associated risk factors such as the level of lipids (e.g., triglyceride (TG) and total cholesterol (TC)) and lipoproteins (e.g., low-density lipoprotein (LDL) and high-density lipoprotein (HDL)) can effectively help prevent disease progression and improve clinical outcomes. However, measurement of these risk factors is generally integrated into an automated analyzer, which is prohibitively expensive and highly instrument-dependent for routine testing in primary care settings. As such, a variety of rapid, simple and portable nanomaterial-based biosensors have been developed for measuring the level of lipids (TG and TC) and lipoproteins (LDL and HDL) towards the management of CVD at the point-of-care (POC). In this review, we first summarize traditional methods for measurement of lipids and lipoproteins, and then present the latest advances in developing nanomaterial-based biosensors that can potentially monitor the risk factors of CVD at the POC.

Tuning of AcurosXB source size setting for small intracranial targets.

This study details a method to evaluate the source size selection for small field intracranial stereotactic radiosurgery (SRS) deliveries in Eclipse treatment planning system (TPS) for AcurosXB dose calculation algorithm. Our method uses end-to-end dosimetric data to evaluate a total of five source size selections (0.50 mm, 0.75 mm, 1.00 mm, 1.25 mm, and 1.50 mm). The dosimetric leaf gap (DLG) was varied in this analysis (three DLG values were tested for each scenario). We also tested two MLC leaf designs (standard and high-definition MLC) and two delivery types for intracranial SRS (volumetric modulated arc therapy [VMAT] and dynamic conformal arc [DCA]). Thus, a total of 10 VMAT plans and 10 DCA plans were tested for each machine type (TrueBeam [standard MLC] and Edge [high-definition MLC]). Each plan was mapped to a solid water phantom and dose was calculated with each iteration of source size and DLG value (15 total dose calculations for each plan). To measure the dose, Gafchromic film was placed in the coronal plane of the solid water phantom at isocenter. The phantom was localized via on-board CBCT and the plans were delivered at planned gantry, collimator, and couch angles. The planned and measured film dose was compared using Gamma (3.0%, 0.3 mm) criteria. The vendor-recommended 1.00 mm source size was suitable for TrueBeam planning (both VMAT and DCA planning) and Edge DCA planning. However, for Edge VMAT planning, the 0.50 mm source size yielded the highest passing rates. The difference in dose calculation among the source size variations manifested primarily in two regions of the dose calculation: (1) the shoulder of the high-dose region, and (2) for small targets (volume ≤ 0.30 cc), in the central portion of the high-dose region. Selection of a larger than optimal source size can result in increased blurring of the shoulder for all target volume sizes tested, and can result in central axis dose discrepancies in excess of 10% for target volumes sizes ≤ 0.30 cc. Our results indicate a need for evaluation of the source size when AcurosXB is used to model intracranial SRS delivery, and our methods represent a feasible process for many clinics to perform tuning of the AcurosXB source size parameter.

Residential Mobility within Guangzhou City, China, 1990-2010: Local Residents Versus Migrants.

Drawing on residential history data from two household surveys conducted in Guangzhou in 2005 and 2010, this paper compares the pattern of intra-city residential moves of local residents and that of migrants. The findings show different trajectories of residential moves for the two groups. While migrants showed increasing mobility over time, residential moves of locals first rose until the early 2000s, then declined steadily afterward. Moreover, the determinants of residential moves of migrants differ from those of the local population. Also, whereas residential moves for the local population are subject to changing factors over time, drivers of relocation for migrants remain more or less stable.

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.

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.

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.

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.

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.

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.

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.