A triphenylamine-benzofuran-derived fluorescent probe for monitoring sulfite in Chinese medicinal materials and bioimaging.

In this work, a triphenylamine-benzofuran-derived fluorescent probe TBSF was developed for monitoring the sulfite level in Chinese medicinal materials and imaging in living cells. In the testing system, under 445 nm excitation, TBSF responded to sulfite steadily with a 540 nm fluorescence reporting signal. The testing system showed advantages including high sensitivity, rapid response, and high selectivity. In particular, TBSF achieved the sulfite detection in the water decoction of Chinese medicinal materials from both addition and excessive fumigation. It also realized the intracellular imaging of both exogenous and endogenous sulfite in living HepG2 cells. The imaging in water decoction-treated cells inferred the potential for the interdisciplinary detection.

Insights into the cause of the Oroville dam spillway failure, 2017, California.

Earth internal seepage erosion in weathered bedrock under infrequently used hydraulic structures is often overlooked, which causes some solid particles to break away from the solid skeleton, degrading the earth's strength, and even causing unanticipated hydraulic engineering failures. The flood on the Oroville dam spillway in California in 2017 was caused by disturbed water flow due to a crack in the spillway chute caused by internal erosion in poorly weathered bedrock. The abnormal water flow of the spillway in the early stage and subsequent investigation revealed that the main reason for the accident was the insufficient weathered bedrock under the spillway chute. In this study, we formulated a coupled hydro-mechanical mechanism for internal erosion in weathered bedrock during the early stages. Using this model, we conducted an internal erosion numerical simulation at early stage, and the results showed that the physical characteristics of the weathered bedrock were degraded. Our results show the coupling analysis of quantitative computation during the early stage of internal erosion in weathered bedrock, which can provide an early warning method for the occurrence of internal erosion to avoid hydraulic disasters.

Coumarins from Jinhua Finger Citron: Separation by Liquid-Liquid Chromatography and Potential Antitumor Activity.

In this paper, liquid-liquid chromatography was introduced for the first time for the separation of fingered citron (Citrus medica L. var. sarcodactylis Swingle). The fingered citron cultivated in Jinhua is of significant industrial and medicinal value, with several major coumarin compounds detected in its extract. Therefore, further separation for higher purity was of necessity. A preparative liquid-liquid chromatographic method was developed by combining two elution modes (isocratic and step-gradient) with selection according to different polarities of the target sample. Five coumarin derivatives-5,7-dimethoxycoumarin (52.6 mg, 99.6%), phellopterin (4.9 mg, 97.1%), 5-prenyloxy-7-methoxycoumarin (6.7 mg, 98.7%), 6-hydroxy-7-methoxycoumarin (7.1 mg, 82.2%), and byakangelicol (10.5 mg, 90.1%)-with similar structures and properties were isolated on a large scale from 100 mg of petroleum ether (PE) extract and 100 mg of ethyl acetate (EA) extract in Jinhua fingered citron. The productivity was much improved. The anti-growth activity of the isolated coumarins was evaluated against three cancer cell lines (HeLa, A549, and MCF7) with an MTT assay. The coumarins demonstrated potential anti-tumor activity on the HeLa cell line, with 5,7-dimethoxycoumarin in particular exhibiting the best anti-growth activity (IC50 = 10.57 ± 0.24 µM) by inhibiting proliferation. It inhibited colony formation and reduced the size of the tumor sphere in a concentration-dependent manner. The main mechanism was confirmed as inducing apoptosis. This work was informative for further studies aimed at exploring new natural-product-based antitumor agents.

Neural Maximum a Posteriori Estimation on Unpaired Data for Motion Deblurring.

Real-world dynamic scene deblurring has long been a challenging task since paired blurry-sharp training data is unavailable. Conventional Maximum A Posteriori estimation and deep learning-based deblurring methods are restricted by handcrafted priors and synthetic blurry-sharp training pairs respectively, thereby failing to generalize to real dynamic blurriness. To this end, we propose a Neural Maximum A Posteriori (NeurMAP) estimation framework for training neural networks to recover blind motion information and sharp content from unpaired data. The proposed NeruMAP consists of a motion estimation network and a deblurring network which are trained jointly to model the (re)blurring process (i.e. likelihood function). Meanwhile, the motion estimation network is trained to explore the motion information in images by applying implicit dynamic motion prior, and in return enforces the deblurring network training (i.e. providing sharp image prior). The proposed NeurMAP is an orthogonal approach to existing deblurring neural networks, and is the first framework that enables training image deblurring networks on unpaired datasets. Experiments demonstrate our superiority on both quantitative metrics and visual quality over State-of-the-art methods.

Automated detection of cerebral microbleeds on MR images using knowledge distillation framework.

Introduction: Cerebral microbleeds (CMBs) are associated with white matter damage, and various neurodegenerative and cerebrovascular diseases. CMBs occur as small, circular hypointense lesions on T2*-weighted gradient recalled echo (GRE) and susceptibility-weighted imaging (SWI) images, and hyperintense on quantitative susceptibility mapping (QSM) images due to their paramagnetic nature. Accurate automated detection of CMBs would help to determine quantitative imaging biomarkers (e.g., CMB count) on large datasets. In this work, we propose a fully automated, deep learning-based, 3-step algorithm, using structural and anatomical properties of CMBs from any single input image modality (e.g., GRE/SWI/QSM) for their accurate detections. Methods: In our method, the first step consists of an initial candidate detection step that detects CMBs with high sensitivity. In the second step, candidate discrimination step is performed using a knowledge distillation framework, with a multi-tasking teacher network that guides the student network to classify CMB and non-CMB instances in an offline manner. Finally, a morphological clean-up step further reduces false positives using anatomical constraints. We used four datasets consisting of different modalities specified above, acquired using various protocols and with a variety of pathological and demographic characteristics. Results: On cross-validation within datasets, our method achieved a cluster-wise true positive rate (TPR) of over 90% with an average of <2 false positives per subject. The knowledge distillation framework improves the cluster-wise TPR of the student model by 15%. Our method is flexible in terms of the input modality and provides comparable cluster-wise TPR and better cluster-wise precision compared to existing state-of-the-art methods. When evaluating across different datasets, our method showed good generalizability with a cluster-wise TPR >80 % with different modalities. The python implementation of the proposed method is openly available.

Comparative transcriptome profiling of Eimeria tenella in various developmental stages and functional analysis of an ApiAP2 transcription factor exclusively expressed during sporogony.

BACKGROUND: The apicomplexan parasites Eimeria spp. are the causative agents of coccidiosis, a disease with a significant global impact on the poultry industry. The complex life cycle of Eimeria spp. involves exogenous (sporogony) and endogenous (schizogony and gametogony) stages. Unfortunately, the genetic regulation of these highly dynamic processes, particularly for genes involved in specific developmental phases, is not well understood. METHODS: In this study, we used RNA sequencing (RNA-Seq) analysis to identify expressed genes and differentially expressed genes (DEGs) at seven time points representing different developmental stages of Eimeria tenella. We then performed K-means clustering along with co-expression analysis to identify functionally enriched gene clusters. Additionally, we predicted apicomplexan AP2 transcription factors in E. tenella using bioinformatics methods. Finally, we generated overexpression and knockout strains of ETH2_0411800 to observe its impact on E. tenella development. RESULTS: In total, we identified 7329 genes that are expressed during various developmental stages, with 3342 genes exhibiting differential expression during development. Using K-means clustering along with co-expression analysis, we identified clusters functionally enriched for oocyte meiosis, cell cycle, and signaling pathway. Among the 53 predicted ApiAP2 transcription factors, ETH2_0411800 was found to be exclusively expressed during sporogony. The ETH2_0411800 overexpression and knockout strains did not exhibit significant differences in oocyst size or output compared to the parental strain, while the resulting ETH2_0411800 knockout parasite showed a relatively small oocyst output. CONCLUSIONS: The findings of our research suggest that ETH2_0411800 is not essential for the growth and development of E. tenella. Our study provides insights into the gene expression dynamics and is a valuable resource for exploring the roles of transcription factor genes in regulating the development of Eimeria parasites.

A selective fluorescent probe for hydrogen sulfide from a series of flavone derivatives and intracellular imaging.

In this work, through the orthogonal design of two fluorophores and two recognition groups, a series of fluorescent probes were developed from the flavone derivatives for hydrogen sulfide (H2S). The probe FlaN-DN stood out from the primarily screening on the selectivity and response intensities. It could respond to H2S with both the chromogenic and fluorescent signals. Among the recent reported probes for the H2S detection, FlaN-DN indicated the most highlighted advantages including the rapid response (within 200 s) and the high response multiplication (over 100 folds). FlaN-DN was sensitive to the pH condition, thus could be applied to distinguish the cancer micro-environment. Moreover, FlaN-DN suggested practical capabilities including a wide linear range (0-400 µM), a relatively high sensitivity (limit of detection 0.13 µM), and high selectivity towards H2S. As a low cytotoxic probe, FlaN-DN achieved the imaging in living HeLa cells. FlaN-DN could detect the endogenous generation H2S and visualize the dose-dependent responses to the exogenous H2S level. This work provided a typical case of natural-sourced derivatives as functional implements, which might inspire the future investigations.

Association of gout with brain reserve and vulnerability to neurodegenerative disease.

Studies of neurodegenerative disease risk in gout are contradictory. Relationships with neuroimaging markers of brain structure, which may offer insights, are uncertain. Here we investigated associations between gout, brain structure, and neurodegenerative disease incidence. Gout patients had smaller global and regional brain volumes and markers of higher brain iron, using both observational and genetic approaches. Participants with gout also had higher incidence of all-cause dementia, Parkinson's disease, and probable essential tremor. Risks were strongly time dependent, whereby associations with incident dementia were highest in the first 3 years after gout diagnosis. These findings suggest gout is causally related to several measures of brain structure. Lower brain reserve amongst gout patients may explain their higher vulnerability to multiple neurodegenerative diseases. Motor and cognitive impairments may affect gout patients, particularly in early years after diagnosis.

Recent Advances for Quantum Neural Networks in Generative Learning.

Quantum computers are next-generation devices that hold promise to perform calculations beyond the reach of classical computers. A leading method towards achieving this goal is through quantum machine learning, especially quantum generative learning. Due to the intrinsic probabilistic nature of quantum mechanics, it is reasonable to postulate that quantum generative learning models (QGLMs) may surpass their classical counterparts. As such, QGLMs are receiving growing attention from the quantum physics and computer science communities, where various QGLMs that can be efficiently implemented on near-term quantum machines with potential computational advantages are proposed. In this paper, we review the current progress of QGLMs from the perspective of machine learning. Particularly, we interpret these QGLMs, covering quantum circuit Born machines, quantum generative adversarial networks, quantum Boltzmann machines, and quantum variational autoencoders, as the quantum extension of classical generative learning models. In this context, we explore their intrinsic relations and their fundamental differences. We further summarize the potential applications of QGLMs in both conventional machine learning tasks and quantum physics. Last, we discuss the challenges and further research directions for QGLMs.

Transcriptome profile of halofuginone resistant and sensitive strains of Eimeria tenella.

The antiparasitic drug halofuginone is important for controlling apicomplexan parasites. However, the occurrence of halofuginone resistance is a major obstacle for it to the treatment of apicomplexan parasites. Current studies have identified the molecular marker and drug resistance mechanisms of halofuginone in Plasmodium falciparum. In this study, we tried to use transcriptomic data to explore resistance mechanisms of halofuginone in apicomplexan parasites of the genus Eimeria (Apicomplexa: Eimeriidae). After halofuginone treatment of E. tenella parasites, transcriptome analysis was performed using samples derived from both resistant and sensitive strains. In the sensitive group, DEGs associated with enzymes were significantly downregulated, whereas the DNA damaging process was upregulated after halofuginone treatment, revealing the mechanism of halofuginone-induced parasite death. In addition, 1,325 differentially expressed genes (DEGs) were detected between halofuginone resistant and sensitive strains, and the DEGs related to translation were significantly downregulated after halofuginone induction. Overall, our results provide a gene expression profile for further studies on the mechanism of halofuginone resistance in E. tenella.

EtcPRS Mut as a molecular marker of halofuginone resistance in Eimeria tenella and Toxoplasma gondii.

The control of coccidiosis, causing huge economic losses in the poultry industry, is facing the stagnation of the development of new drugs and the emergence of drug resistance. Thus, the priority for coccidiosis control is to decipher the effect mechanisms and resistance mechanisms of anticoccidial drugs. In this study, we mined and validated a molecular marker for halofuginone resistance in Eimeria tenella through forward and reverse genetic approaches. We screened whole-genome sequencing data and detected point mutations in the ETH2_1020900 gene (encoding prolyl-tRNA synthetase, PRS). Then, we introduced this mutated gene into E. tenella and Toxoplasma gondii and validated that overexpression of this mutated gene confers resistance to halofuginone in vivo and in vitro. These results together show that mutations A1852G and A1854G on the ETH2_1020900 gene are pivotal to halofuginone resistance in E. tenella, encouraging the exploration of mechanisms of drug resistance against other anticoccidial drugs in eimerian parasites.

Telomere length and brain imaging phenotypes in UK Biobank.

Telomeres form protective caps at the ends of chromosomes, and their attrition is a marker of biological aging. Short telomeres are associated with an increased risk of neurological and psychiatric disorders including dementia. The mechanism underlying this risk is unclear, and may involve brain structure and function. However, the relationship between telomere length and neuroimaging markers is poorly characterized. Here we show that leucocyte telomere length (LTL) is associated with multi-modal MRI phenotypes in 31,661 UK Biobank participants. Longer LTL is associated with: i) larger global and subcortical grey matter volumes including the hippocampus, ii) lower T1-weighted grey-white tissue contrast in sensory cortices, iii) white-matter microstructure measures in corpus callosum and association fibres, iv) lower volume of white matter hyperintensities, and v) lower basal ganglia iron. Longer LTL was protective against certain related clinical manifestations, namely all-cause dementia (HR 0.93, 95% CI: 0.91-0.96), but not stroke or Parkinson's disease. LTL is associated with multiple MRI endophenotypes of neurodegenerative disease, suggesting a pathway by which longer LTL may confer protective against dementia.

The Gut-Eye Axis: Correlation Between the Gut Microbiota and Autoimmune Dry Eye in Individuals With Sjögren Syndrome.

ABSTRACT: The impact of gut microbiota on human health, autoimmunity, and disease occurrence has long been recognized since the advancement of metagenomic sequencing technology has enabled a new level of perspective on the human microbiome. Emerging findings also suggest the existence of a gut-eye axis, wherein gut dysbiosis may be a crucial factor affecting the onset and progression of multiple ocular diseases. Sjögren syndrome (SS) is a chronic autoimmune disease mainly affecting the exocrine glands, primarily the lacrimal gland in the eye, resulting in severe dry eye. Although there are currently various treatments for environmental dry eye, the efficacy for SS-related autoimmune dry eye is limited, and new and more effective therapies still need to be explored. The latest studies have demonstrated that the gut microbiota plays a key role in the pathogenesis of autoimmune dry eye. This review describes the effect of gut microbiota on the ocular surface of autoimmune dry eye; introduces the presumable pathways forming the "gut dysbiosis-ocular surface-lacrimal gland axis"; discusses the advantages of restoring intestinal microecology to treat dry eye by fecal microbiota transplantation or probiotics, which are expected to provide perspectives into the correlation between the gut microbiome and dry eye; enhance our understanding of the pathogenesis in autoimmune dry eye; and be useful in the development of future interventions of dry eye by regulating the gut microbiota.

Evidence of high-efficiency cross fertilization in Eimeria acervulina revealed using two lines of transgenic parasites.

Eimeria species are apicomplexan parasites with a direct life cycle consisting of a replicative phase involving multiple rounds of asexual replication in the intestine or other organs including kidneys, liver, and gallbladder, depending on the species, followed by a sexual phase or gamogony involving the development and fertilization of gametes, an essential process for Eimeria transmission. Recent advances in the genetic manipulation of these parasites made it possible to conduct genetic crosses combined with genomic approaches to elucidate the genetic determinants of Eimeria development, virulence, drug resistance, and immune evasion. Here, we employed genetic techniques to generate two transgenic Eimeria acervulina lines, EaGAM56 and EaHAP2, each expressing two unique fluorescent proteins, with one controlled by a constitutive promotor for cross-efficiency analysis and the other by a male or female gametocyte stage-specific promoter to observe sexual development. The expression of fluorescent proteins in the transgenic lines was analyzed in different developmental stages of the E. acervulina life cycle by immunoblotting and by examination of frozen sections using fluorescence microscopy. The effect of infective doses on cross-fertilization was further investigated by conducting several genetic crosses between the two transgenic lines at different doses and ratios. Two transgenic lines expressing constitutive and gametocyte-specific fluorescence proteins were generated and characterized. These transgenic parasites display synchronous development in chickens, comparable with that of the wild type. Genetic crosses between the two transgenic parasites showed that a high rate of oocysts co-expressing the two reporters could be achieved following inoculation with high doses of infective oocysts. We further showed that the proportion of co-transfected oocysts can be modulated by altering the ratio of the transgenic parental lines. Higher infective doses and similar numbers of functional gametocytes from the parents increase the rate of cross-fertilization. Our data highlight the usefulness of genetic manipulation and fluorescently-labeled transgenic gametocytes as tools to study Eimeria development and to elucidate the factors that modulate sexual development. This work sets the stage for the implementation of novel approaches to investigate other aspects of Eimeria pathogenesis, virulence, and drug susceptibility and resistance.

Textural and physical properties of breast fillets with myopathies (wooden breast, white striping, spaghetti meat) in Canadian fast-growing broiler chickens.

The combined effects of different severities of Wooden Breast (WB), White Striping (WS), and Spaghetti Meat (SM) were examined in 300 chicken breast fillets from 10 flocks. Severity (0 = absent, 1 = mild, noticeable upon close inspection, 2 = severe), noticeably altered from normal breast fillet (NB). Results showed that any combination of myopathies and severity resulted in significantly elevated compression force, pH and peak counts measured by the shear force test. With the exception of mild WB + mild WS, all combinations resulted in significantly higher drip loss, cooking loss and lightness value. Overall, the quality of fillets was affected the least by WS, while negatively affected the most by SM. There were limited effects on fillet quality from mild WB but major deleterious effects from severe WB.

Textural Restoration of Broiler Breast Fillets with Spaghetti Meat Myopathy, Using Two Alginate Gels Systems.

The effects of salt-sensitive alginate ("A") and a two-component salt-tolerant alginate system ("B") used at a 0.5% or 1.0% level were evaluated in normal breast (NB) chicken fillets and in spaghetti meat (SM) fillets. Minced raw and cooked SM samples showed higher cooking loss (p < 0.05) and lower penetration force compared to NB meat. Both alginate systems significantly raised the penetration force in raw samples and decreased cooking loss (p < 0.05). Adding 1% of "A" or 0.5% "B" to SM, without salt, resulted in a similar penetration force as the cooked NB meat, while 1% "B" with salt resulted in a higher penetration force. Excluding salt from SM samples while adding alginate "A" or "B" improved texture profiles, but not to the same level as using NB without additives. Overall, salt, together with alginate "B", improved the texture of SM to that of normal meat without myopathy.

An automated pipeline for extracting histological stain area fraction for voxelwise quantitative MRI-histology comparisons.

The acquisition of MRI and histology in the same post-mortem tissue sample enables direct correlation between MRI and histologically-derived parameters. However, there still lacks a standardised automated pipeline to process histology data, with most studies relying on manual intervention. Here, we introduce an automated pipeline to extract a quantitative histological measure for staining density (stain area fraction, SAF) from multiple immunohistochemical (IHC) stains. The pipeline is designed to directly address key IHC artefacts related to tissue staining and slide digitisation. Here, the pipeline was applied to post-mortem human brain data from multiple subjects, relating MRI parameters (FA, MD, RD, AD, R2*, R1) to IHC slides stained for myelin, neurofilaments, microglia and activated microglia. Utilising high-quality MRI-histology co-registrations, we then performed whole-slide voxelwise comparisons (simple correlations, partial correlations and multiple regression analyses) between multimodal MRI- and IHC-derived parameters. The pipeline was found to be reproducible, robust to artefacts and generalisable across multiple IHC stains. Our partial correlation results suggest that some simple MRI-SAF correlations should be interpreted with caution, due to the co-localisation of other tissue features (e.g., myelin and neurofilaments). Further, we find activated microglia-a generic biomarker of inflammation-to consistently be the strongest predictor of high DTI FA and low RD, which may suggest sensitivity of diffusion MRI to aspects of neuroinflammation related to microglial activation, even after accounting for other microstructural changes (demyelination, axonal loss and general microglia infiltration). Together, these results show the utility of this approach in carefully curating IHC data and performing multimodal analyses to better understand microstructural relationships with MRI.

Restoring Functionalities in Chicken Breast Fillets with Spaghetti Meat Myopathy by Using Dairy Proteins Gels.

The use of caseinate, whole milk powder, and two whey protein preparations (WP; 2% w/w) was studied in minced meat made with normal breast (NB), and ones showing spaghetti meat (SM). SM is an emerging myopathy known for muscle fiber separation and lower protein content, costing $100s of millions to the industry. Using SM without dairy proteins resulted in a higher cooking loss (SM: 3.75%, NB: 2.29%; p < 0.05), and lower hardness (SM: 29.83 N, NB: 34.98 N), and chewiness (SM: 1.29, NB: 1.56) compared to NB. Using dairy proteins, except WP concentrate and WP isolate, significantly improved yield and increased hardness. Adding WP isolate to SM resulted in a similar texture profile as NB samples without dairy proteins (34 and 35 N hardness; 0.22 and 0.24 springiness; 1.57 and 1.59 chewiness values, respectively). Adding caseinate and whole milk to SM showed a more substantial effect of improving water-holding capacity, increasing hardness, gumminess, and chewiness compared to adding WP; i.e., adding caseinate and milk powder resulted in higher values for those parameters compared to NB without additives. Overall, it is shown that dairy proteins can be added to SM to produce minced poultry meat products with similar or higher yield and texture profiles compared to using normal breast fillets.

Reliability of multi-site UK Biobank MRI brain phenotypes for the assessment of neuropsychiatric complications of SARS-CoV-2 infection: The COVID-CNS travelling heads study.

INTRODUCTION: Magnetic resonance imaging (MRI) of the brain could be a key diagnostic and research tool for understanding the neuropsychiatric complications of COVID-19. For maximum impact, multi-modal MRI protocols will be needed to measure the effects of SARS-CoV-2 infection on the brain by diverse potentially pathogenic mechanisms, and with high reliability across multiple sites and scanner manufacturers. Here we describe the development of such a protocol, based upon the UK Biobank, and its validation with a travelling heads study. A multi-modal brain MRI protocol comprising sequences for T1-weighted MRI, T2-FLAIR, diffusion MRI (dMRI), resting-state functional MRI (fMRI), susceptibility-weighted imaging (swMRI), and arterial spin labelling (ASL), was defined in close approximation to prior UK Biobank (UKB) and C-MORE protocols for Siemens 3T systems. We iteratively defined a comparable set of sequences for General Electric (GE) 3T systems. To assess multi-site feasibility and between-site variability of this protocol, N = 8 healthy participants were each scanned at 4 UK sites: 3 using Siemens PRISMA scanners (Cambridge, Liverpool, Oxford) and 1 using a GE scanner (King's College London). Over 2,000 Imaging Derived Phenotypes (IDPs), measuring both data quality and regional image properties of interest, were automatically estimated by customised UKB image processing pipelines (S2 File). Components of variance and intra-class correlations (ICCs) were estimated for each IDP by linear mixed effects models and benchmarked by comparison to repeated measurements of the same IDPs from UKB participants. Intra-class correlations for many IDPs indicated good-to-excellent between-site reliability. Considering only data from the Siemens sites, between-site reliability generally matched the high levels of test-retest reliability of the same IDPs estimated in repeated, within-site, within-subject scans from UK Biobank. Inclusion of the GE site resulted in good-to-excellent reliability for many IDPs, although there were significant between-site differences in mean and scaling, and reduced ICCs, for some classes of IDP, especially T1 contrast and some dMRI-derived measures. We also identified high reliability of quantitative susceptibility mapping (QSM) IDPs derived from swMRI images, multi-network ICA-based IDPs from resting-state fMRI, and olfactory bulb structure IDPs from T1, T2-FLAIR and dMRI data. CONCLUSION: These results give confidence that large, multi-site MRI datasets can be collected reliably at different sites across the diverse range of MRI modalities and IDPs that could be mechanistically informative in COVID brain research. We discuss limitations of the study and strategies for further harmonisation of data collected from sites using scanners supplied by different manufacturers. These acquisition and analysis protocols are now in use for MRI assessments of post-COVID patients (N = 700) as part of the ongoing COVID-CNS study.