Breast milk flora plays an important role in infantile eczema: cohort study in Northeast China

AIMS

Infantile eczema, usually coupled with a range of hypersensitive phenotypes, has come into notice with its rising prevalence and unclear pathogenesis. Recent studies show close ties between eczema and an infant's intestinal flora. To gain a further understanding of the interactions between microbiota and eczema, we studied the breast milk flora as a new factor and present the links among breast milk flora, infant intestinal flora and infantile eczema through a cohort study in Northeast China.

METHODS AND RESULTS

Fifty-two families were recruited with either an eczema or healthy infant younger than 6 months. Analysis and predictions using amplicon sequencing of microbiota found that Bifidobacterium and Bacteroidetes were enriched in healthy and eczema infant stools, respectively, consistent with previous reports. For breast milk flora, more 'positive' bacteria such as Akkermansia were enriched in breast milk from healthy infants' mothers. Further, higher bacterial delivery efficiencies were found in pairs of breast milk flora and infants' stool flora of families with eczema infants compared with families with healthy infants. Bacteroidetes, a widely known indicator of eczema, was found delivered more in eczema pairs. Further metagenomic predictions revealed that the breast milk microbiota participated significantly less in metabolism and immune system pathways, particularly in antigen processing and presentation and in Th17 cell-related pathways.

CONCLUSIONS

In conclusion, as with other components of breast milk, the breast milk microbiota closely associates with infants' health via mother-infant bacterial delivery and metabolic functions.

SIGNIFICANCE AND IMPACT OF THE STUDY

Our research aimed to fill the gap between the eczema and breast milk flora and describe the connections among breast milk and intestinal flora and eczema.

High-Throughput Functional Characterization of Visceral Afferents by Optical Recordings From Thoracolumbar and Lumbosacral Dorsal Root Ganglia

Functional understanding of visceral afferents is important for developing the new treatment to visceral hypersensitivity and pain. The sparse distribution of visceral afferents in dorsal root ganglia (DRGs) has challenged conventional electrophysiological recordings. Alternatively, Ca²⁺ indicators like GCaMP6f allow functional characterization by optical recordings. Here we report a turnkey microscopy system that enables simultaneous Ca²⁺ imaging at two parallel focal planes from intact DRG. By using consumer-grade optical components, the microscopy system is cost-effective and can be made broadly available without loss of capacity. It records low-intensity fluorescent signals at a wide field of view (1.9 × 1.3 mm) to cover a whole mouse DRG, with a high pixel resolution of 0.7 micron/pixel, a fast frame rate of 50 frames/sec, and the capability of remote focusing without perturbing the sample. The wide scanning range (100 mm) of the motorized sample stage allows convenient recordings of multiple DRGs in thoracic, lumbar, and sacral vertebrae. As a demonstration, we characterized mechanical neural encoding of visceral afferents innervating distal colon and rectum (colorectum) in GCaMP6f mice driven by VGLUT2 promotor. A post-processing routine is developed for conducting unsupervised detection of visceral afferent responses from GCaMP6f recordings, which also compensates the motion artifacts caused by mechanical stimulation of the colorectum. The reported system offers a cost-effective solution for high-throughput recordings of visceral afferent activities from a large volume of DRG tissues. We anticipate a wide application of this microscopy system to expedite our functional understanding of visceral innervations.

Neural network model assisted Fourier ptychography with Zernike aberration recovery and total variation constraint

SIGNIFICANCE

Fourier ptychography (FP) is a computational imaging approach that achieves high-resolution reconstruction. Inspired by neural networks, many deep-learning-based methods are proposed to solve FP problems. However, the performance of FP still suffers from optical aberration, which needs to be considered.

AIM

We present a neural network model for FP reconstructions that can make proper estimation toward aberration and achieve artifact-free reconstruction.

APPROACH

Inspired by the iterative reconstruction of FP, we design a neural network model that mimics the forward imaging process of FP via TensorFlow. The sample and aberration are considered as learnable weights and optimized through back-propagation. Especially, we employ the Zernike terms instead of aberration to decrease the optimization freedom of pupil recovery and perform a high-accuracy estimation. Owing to the auto-differentiation capabilities of the neural network, we additionally utilize total variation regularization to improve the visual quality.

RESULTS

We validate the performance of the reported method via both simulation and experiment. Our method exhibits higher robustness against sophisticated optical aberrations and achieves better image quality by reducing artifacts.

CONCLUSIONS

The forward neural network model can jointly recover the high-resolution sample and optical aberration in iterative FP reconstruction. We hope our method that can provide a neural-network perspective to solve iterative-based coherent or incoherent imaging problems.

Paeonol derivative-6 attenuates inflammation by activating ZEB2 in acute liver injury

Paeonol is a natural phenolic compound and isolated as an active ingredient from Moutan Cortex. Paeonol derivative-6 (DPF-6) is a derivative of paeonol improved in water solubility and bioavailability. Previous studies have reported that paeonol possesses a variety of pharmacological activities, such as antioxidant and anti-inflammatory properties. Moreover, we have previously verified that DPF-6 has anti-inflammatory effects. However, the role and fundamental mechanism of DPF-6 in acute liver injury (ALI) was still unclear. In this study, we indicated that DPF-6 inhibited inflammation and the expression of TNF-α, IL-6 and IL-1β in liver tissues and LPS-mediated L-02 cells, concomitant with the upregulated expression of ZEB2. More importantly, it was demonstrated that overexpression of ZEB2 inhibited the expression level of TNF-α, IL-6 and IL-1β in LPS-mediated L-02 cells. In contrast, knockdown of ZEB2 increased the expression level of TNF-α, IL-6 and IL-1β in LPS-mediated L-02 cells. Further studies showed that ZEB2 inhibited the inflammation cytokine secretion via JNK signaling pathway in L-02 cells. Taken together, all the above results indicate that DPF-6 increased the expression of ZEB2, consequently inhibited inflammation cytokine secretion through JNK signaling pathway, which may be utilized as a potential anti-inflammation monomeric compound in the treatment of ALI.

2D monochromatic x-ray imaging for beam monitoring of an x-ray free electron laser and a high-power femtosecond laser

In pump-probe experiments with an X-ray Free Electron Laser (XFEL) and a high-power optical laser, spatial overlap of the two beams must be ensured to probe a pumped area with the x-ray beam. A beam monitoring diagnostic is particularly important in short-pulse laser experiments where a tightly focused beam is required to achieve a relativistic laser intensity for generation of energetic particles. Here, we report the demonstration of on-shot beam pointing measurements of an XFEL and a terawatt class femtosecond laser using 2D monochromatic Kα imaging at the Matter in Extreme Conditions end-station of the Linac Coherent Light Source. A thin solid titanium foil was irradiated by a 25-TW laser for fast electron isochoric heating, while a 7.0 keV XFEL beam was used to probe the laser-heated region. Using a spherical crystal imager (SCI), the beam overlap was examined by measuring 4.51 keV Kα x rays produced by laser-accelerated fast electrons and the x-ray beam. Measurements were made for XFEL-only at various focus lens positions, laser-only, and two-beam shots. Successful beam overlapping was observed on ∼58% of all two-beam shots for 10 μm thick samples. It is found that large spatial offsets of laser-induced Kα spots are attributed to imprecise target positioning rather than shot-to-shot laser pointing variations. By applying the Kα measurements to x-ray Thomson scattering measurements, we found an optimum x-ray beam spot size that maximizes scattering signals. Monochromatic x-ray imaging with the SCI could be used as an on-shot beam pointing monitor for XFEL-laser or multiple short-pulse laser experiments.

Comparison of Three Frailty Scales for Prediction of Adverse Outcomes among Older Adults: A Prospective Cohort Study

OBJECTIVES

To compare the ability of Frailty Phenotype (FP), FRAIL and Frailty Index (FI) to predict adverse outcomes.

DESIGN

A prospective cohort study.

SETTING

A senior community in Beijing, China.

PARTICIPANTS

A total of 188 older adults aged 65 years or older (mean age 84.0 ± 4.4 years, 58.5% female).

MEASUREMENTS

Frailty was evaluated by FP, FRAIL and FI. The agreement between scales was assessed by Cohen kappa coefficient. The predictive value of the three scales for adverse outcomes during one-year follow-up period were analyzed using decision curve analysis(DCA) and receiver operating characteristic curve (ROC) analysis.

RESULTS

Frailty ranged from 25% (FRAIL) to 42.6% (FI). The agreement between scales was moderate to good (Cohen's kappa coefficient 0.44~0.61). DCA showed though the curves of the scales overlapped across all relevant risk thresholds, clinical treating had a higher net benefit than "treat all" and "treat none" when risk of unplanned hospital visits ≥30%, risk of functional decline or falls ≥15%. The three scales had similar predictive value for unplanned hospital visits (area under ROC, AUC 0.63, 0.64 and 0.69). FRAIL and FI had similar predictive value for functional decline (AUC 0.63,0.65). FI had predictive value for falls (AUC 0.65).

CONCLUSIONS

All three scales showed clinical utility but FRAIL may be best in practice because it is simple. Multidimensional measures of frailty are better than unidimensional for prediction of adverse outcomes among older adults.

Structure and thermal properties of beeswax-based oleogels with different types of vegetable oil

Beeswax-based oleogels with different types of vegetable oil, including camellia oil (CO), soybean oil (SO), sunflower oil (SFO), or flaxseed oil (FO), were prepared and their structure and thermal properties were evaluated. The critical concentration of oleogel obtained from each of CO, SO, and SFO at 25 °C was 3% (w/w), and that from FO was 4%. Thermal measurements revealed similar thermodynamic curves for oleogels in different lipid phases. X-Ray diffraction showed orthorhombic perpendicular subcell packing and characteristic peaks of the β’ form. Furthermore, a morphology analysis of the crystals showed that they were needle shaped. Fourier transform-infrared spectra revealed that beeswax-based oleogels were formed via non-covalent bonds and may be stabilized with physical entanglements. The oleogels showed oil type-dependent oxidative abilities, but they were all stable and showed no obvious changes in peroxide value during 90 days of storage at 5 °C.

Physiological effects of transport duration on stress biomarkers and meat quality of medium-growing Yellow broiler chickens

Pre-slaughter transport exerts negative effects on broilers' welfare, meat yield, and meat quality, but little is known about the effect of transport on medium-growing broiler chickens. This study aimed at evaluating the effects of different durations of transport (0, 0.5, 1, 2, and 3h) on stress biomarkers and meat quality of medium-growing Yellow-feathered broiler chickens. One hundred and eighty Chinese Yellow-feathered broilers aged 75days (marketing age), of 2.02kg average BW, were allotted into five groups; each group contained six replicates (six birds/replicate (crate)). Each crate with dimensions 74×55×27cm (length × width × height) was loaded with six birds, that is, 30kg live BW/m² crate. The tested transport durations increased BW loss (linear, P<0.01), plasma concentrations of ACTH (linear, P<0.10), cortisol and corticosterone (quadratic, P<0.05), and activity of glutathione peroxidase (linear, P<0.05), whereas plasma glucose was not affected. In breast muscle, contents of glycogen, lactic acid, malondialdehyde, and reduced glutathione were not affected (P>0.05), but total antioxidant capacity decreased (linear, P<0.01). The drip loss of breast muscle increased (linear, P<0.01), whereas shear force, pH at 24h postmortem, and breast meat color lightness (L*), redness (a*), and yellowness (b*) scores were not affected. In conclusion, the tested transport durations (from 0.5 to 3h) increased BW loss and some plasma stress biomarkers in 75-day-old Yellow-feathered broiler chickens, but the effect on meat quality attributes was minor.

Autofocusing technologies for whole slide imaging and automated microscopy

Whole slide imaging (WSI) has moved digital pathology closer to diagnostic practice in recent years. Due to the inherent tissue topography variability, accurate autofocusing remains a critical challenge for WSI and automated microscopy systems. The traditional focus map surveying method is limited in its ability to acquire a high degree of focus points while still maintaining high throughput. Real-time approaches decouple image acquisition from focusing, thus allowing for rapid scanning while maintaining continuous accurate focus. This work reviews the traditional focus map approach and discusses the choice of focus measure for focal plane determination. It also discusses various real-time autofocusing approaches including reflective-based triangulation, confocal pinhole detection, low-coherence interferometry, tilted sensor approach, independent dual sensor scanning, beam splitter array, phase detection, dual-LED illumination and deep-learning approaches. The technical concepts, merits and limitations of these methods are explained and compared to those of a traditional WSI system. This review may provide new insights for the development of high-throughput automated microscopy imaging systems that can be made broadly available and utilizable without loss of capacity.

Convolutional neural network based proton stopping-power-ratio estimation with dual-energy CT: a feasibility study

Dual-energy computed tomography (DECT) has shown a great potential for lowering range uncertainties, which is necessary for truly leveraging the Bragg peak in proton therapy. However, analytical stopping-power-ratio (SPR) estimation methods have limitations in resolving the influence from the beam-hardening artifact, i.e. CT number variation of the same object scanned under different imaging conditions, such as different patient size and location in the field-of-view (FOV). We present a convolutional neural network (CNN)-based framework to estimate proton SPR that accounts for patient geometry variation and addresses CT number variation. The proposed framework was tested on both prostate and head-and-neck (HN) patient datasets. Simulated CT images were used in order to have a well-defined ground-truth SPR for evaluation. Two training scenarios were evaluated: training with patient CT images (ideal scenario) and training with computational phantoms (realistic scenario). For the training in ideal scenario, computational phantoms were created based on 120 kVp patient CT images using a custom-defined density and material translation curve. Then, 80 kVp and 150 kVp Sn DECT image pairs were obtained using ray-tracing simulation, and their corresponding SPR was calculated from the known density and elemental compositions. For the training in realistic scenario, computational phantoms were created based on the geometry of calibration phantoms. For both scenarios, evaluation was performed on the phantoms created from patient CT images. Compared to a conventional parametric model, U-net trained with computational phantoms (realistic scenario) reduced the SPR estimation uncertainty (95th percentile) of the prostate patient from 1.10% to 0.71%, and HN patient from 2.11% to 1.20%. With the U-net trained with patient images (ideal scenario) uncertainty values were 0.32% and 0.42% for prostate and HN patients, respectively. These results suggest that CNN has great potential to improve the accuracy of SPR estimation in proton therapy by incorporating individual patient geometry information.

Predictors of plaque erosion in current smokers and non-current smokers presented with ST-segment elevation myocardial infarction: an optical coherence tomography study

Background

Plaque erosion with subsequent coronary thrombosis is considered as an important cause of ST-segment elevation myocardial infarction (STEMI). Smoking is a major risk factor for acute coronary thrombosis. However, the relationship between current smoking status and plaque erosion has not been systematically investigated.

Purpose

The present study aimed to investigate predictors of plaque erosion in current smokers and non-current smokers with STEMI by using optical coherence tomography (OCT).

Methods

Between January 2015 to December 2017, a total of 1313 STEMI patients underwent pre-intervention OCT of culprit lesion were enrolled and divided into two groups based on current smoking status: current smoking group (n=713) and non-current smoking group (n=600). Using established criteria, quantitative and qualitative underlying plaque characteristics were assessed by OCT. Clinical, angiographic and OCT characteristics of all enrolled patients were recorded. Univariable and multivariable logistic regression analyses were used to identify predictors of plaque erosion in two groups.

Results

Plaque erosion were found in 30.9% (220/713) culprit lesions in current smoking group and 20.8% (125/600) of those in non-current smoking group detected by OCT. In multivariate regression analysis, the predictors that strongly related to plaque erosion in the current smoking group were nearby bifurcation (OR: 4.84; 95% CI:2.38–9.87; p&lt;0.001); the minimum fiber cap thickness (FCT, OR:1.05; 95% CI:1.03–1.08; p&lt;0.001); thin-cap fibroatheroma (TCFA, OR: 0.22; 95% CI: 0.07–0.67; p=0.007) and lipid core length (OR: 0.91; 95% CI: 0.84–0.97; p=0.007). The predictors in the non-current smoking group were nearby bifurcation (OR: 4.84; 95% CI: 2.38–9.87; p=0.006); the minimal FCT (OR: 1.09; 95% CI: 1.06–1.13; p&lt;0.001); multi-vessel disease (MVD, OR: 0.43; 95% CI: 0.19–0.97; p=0.042) and dyslipidemia (OR: 0.34; 95% CI: 0.14–0.84; p=0.020).

Conclusions

Predictors of plaque erosion causing STEMI onset are different between current smokers and non-current smoker, with nearby bifurcation and thicker minimal FCT both predicting plaque erosion in two groups of patients.

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): National Key Research and Development Program of China, National Natural Science Foundation of China.

Profiling the effects of physicochemical indexes on the microbial diversity and its aroma substances in pit mud

Microbial diversity of pit mud (PM) plays a significant role in Baijiu's flavour. Here we explored the microbial community structures and aroma substances of Wenwang Winery with high-throughput sequencing coupling with headspace solid-phase microextraction-gas chromatography-mass spectrometry. We discovered that the odorant was mainly derived from 14 aroma compounds because of their OAVs ≥ 1 (OAV, the ratio of substance concentration to aroma threshold; s, on behalf of the plural), such as ethyl hexanoate (2438), ethyl octanoate (975), caproic acid (52) and etc. Moreover we also revealed that Lactobacillaceae (97·08%) was the mainly bacterial microbial community in 2-year-old PM, companied by the primarily fungi including Aspergillaceae (55·45%), Unclassified Ascomycota (11·13%) and Dipodascaceae (5·72%). Compared with the 2-year-old PM, bacterial floras in 20-year-old PM and 30-year-old PM were more abundant (i.e. Dysgonomonadaceae, Clostridium and Synerggstaceas), while no fungi were detected. Besides, the physicochemical analysis showed that the content of Lactobacillaceae was inversely associated with moisture, pH and ammonia nitrogen. By further Spearman's correlation coefficient analysis, we verified that the content of Lactobacillaceae was positively correlated with ethyl hexanoate, while negatively correlated with ethyl octanoate and caproic acid. Meanwhile, ethyl octanoate and caproic acid were positively correlated with most flora including Ruminococcaceae, Dysgonomonadaceae and Clostridiacea, which were related to physicochemical indexes. This work demonstrates promise for adjusting the physicochemical indexes of PM to affect the micro-organisms and aroma, which may provide a reference for the production of high-quality Baijiu.

Virtual brightfield and fluorescence staining for Fourier ptychography via unsupervised deep learning

Fourier ptychographic microscopy (FPM) is a computational approach geared towards creating high-resolution and large field-of-view images without mechanical scanning. Acquiring color images of histology slides often requires sequential acquisitions with red, green, and blue illuminations. The color reconstructions often suffer from coherent artifacts that are not presented in regular incoherent microscopy images. As a result, it remains a challenge to employ FPM for digital pathology applications, where resolution and color accuracy are of critical importance. Here we report a deep learning approach for performing unsupervised image-to-image translation of FPM reconstructions. A cycle-consistent adversarial network with multiscale structure similarity loss is trained to perform virtual brightfield and fluorescence staining of the recovered FPM images. In the training stage, we feed the network with two sets of unpaired images: (1) monochromatic FPM recovery and (2) color or fluorescence images captured using a regular microscope. In the inference stage, the network takes the FPM input and outputs a virtually stained image with reduced coherent artifacts and improved image quality. We test the approach on various samples with different staining protocols. High-quality color and fluorescence reconstructions validate its effectiveness.

Effects of baohuoside-I on epithelial-mesenchymal transition and metastasis in nasopharyngeal carcinoma

To investigate the effect of baohuoside-I against nasopharyngeal carcinoma (NPC) and its underlying mechanism, baohuoside-I was employed to treat NPC cell lines CNE1 and CNE2 in vitro, followed by attachment and detachment assays to evalute the epithelial-mesenchymal transition (EMT) phenotype markers. Baohuoside-I was also administered to experimental mice to assess its effect on xenograft tumor growth and NPC cell metastasis. A microRNA (miRNA, miR) microarray was performed to screen for miRNA altered by baohuoside-I in NPC cells. Bioinformatic tools and luciferase activity assay was conducted to identify the downstream molecules mediating the anti-tumor property of baohuoside-I. Baohuoside-I inhibited EMT and metastasis and upregulated miR-370-3p in NPC cells, which was shown to directly recognize and inhibit expression of Hedgehog pathway component Smoothened (SMO). Baohuoside-I suppresses metastasis as well as EMT of NPC cells through targeting the Hedgehog pathway component SMO, and may serve as a potent anti-tumor agent in the clinical management of NPC.

Super-resolved multispectral lensless microscopy via angle-tilted, wavelength-multiplexed ptychographic modulation

We report an angle-tilted, wavelength-multiplexed ptychographic modulation approach for multispectral lensless on-chip microscopy. In this approach, we illuminate the specimen with lights at five wavelengths simultaneously. A prism is added at the illumination path for spectral dispersion. Thus, lightwaves at different wavelengths hit the specimen at slightly different incident angles, breaking the ambiguities in mixed-state ptychographic reconstruction. At the detection path, we place a thin diffuser between the specimen and the monochromatic image sensor for encoding the spectral information into 2D intensity measurements. By scanning the sample to different x-y positions, we acquire a sequence of monochromatic images for reconstructing the five complex object profiles at the five wavelengths. An up-sampling procedure is integrated into the recovery process to bypass the resolution limit imposed by the imager pixel size. We demonstrate a half-pitch resolution of 0.55 µm using an image sensor with 1.85 µm pixel size. We also demonstrate quantitative and high-quality multispectral reconstructions of stained tissue sections for digital pathology applications.

Wide-field, high-resolution lensless on-chip microscopy via near-field blind ptychographic modulation

We report a novel lensless on-chip microscopy platform based on near-field blind ptychographic modulation. In this platform, we place a thin diffuser in between the object and the image sensor for light wave modulation. By blindly scanning the unknown diffuser to different x-y positions, we acquire a sequence of modulated intensity images for quantitative object recovery. Different from previous ptychographic implementations, we employ a unit magnification configuration with a Fresnel number of ∼50 000, which is orders of magnitude higher than those of previous ptychographic setups. The unit magnification configuration allows us to have the entire sensor area, 6.4 mm by 4.6 mm, as the imaging field of view. The ultra-high Fresnel number enables us to directly recover the positional shift of the diffuser in the phase retrieval process, addressing the positioning accuracy issue plaguing regular ptychographic experiments. In our implementation, we use a low-cost, DIY scanning stage to perform blind diffuser modulation. Precise mechanical scanning that is critical in conventional ptychography experiments is no longer needed in our setup. We further employ an up-sampling phase retrieval scheme to bypass the resolution limit set by the imager pixel size and demonstrate a half-pitch resolution of 0.78 μm. We validate the imaging performance via in vitro cell cultures, transparent and stained tissue sections, and a thick biological sample. We show that the recovered quantitative phase map can be used to perform effective cell segmentation of a dense yeast culture. We also demonstrate 3D digital refocusing of the thick biological sample based on the recovered wavefront. The reported platform provides a cost-effective and turnkey solution for large field-of-view, high-resolution, and quantitative on-chip microscopy. It is adaptable for a wide range of point-of-care-, global-health-, and telemedicine-related applications.