Hydrothermal Synthesis of Zinc-Doped Silica Nanospheres Simultaneously Featuring Stable Fluorescence and Long-Lived Room-Temperature Phosphorescence.

Fluorescence and phosphorescence are known as two kinds of fundamental optical signals, which have been used for myriad applications. To date, simultaneous activation of stable fluorescence and long-lived room-temperature phosphorescence (RTP) emission in the aqueous phase remains a big challenge. We prepare zinc-doped silica nanospheres (Zn@SiNSs) with fluorescence and RTP properties using a facile hydrothermal synthetic strategy. For the as-prepared Zn@SiNSs, the recombination of electrons and holes in defects and defect-stabilized excitons derived from oxygen vacancy/C=N bonds lead to the production of stable fluorescence and long-lived RTP (emission lasting for ≈9 s, quantum yield (QY): ≈33.6 %, RTP lifetime: ≈236 ms). The internal Si-O bonded networks and hydrophilic surface in Zn@SiNSs can reduce nonradiative decay to form self-protective RTP, and also provide high water solubility, excellent pH- and photostability.

Multifunctional Silicon-Carbon Nanohybrids Simultaneously Featuring Bright Fluorescence, High Antibacterial and Wound Healing Activity.

In this work, a class of multifunctional silicon-carbon nanohybrids (designated as SiCNs), which simultaneously possess aqueous dispersibility, bright fluorescence (photoluminescence quantum yield [PLQY]: ≈28%), as well as high antibacterial and wound healing activity, is presented. Taking advantage of these unique merits, cell distribution and pharmacological behavior of the SiCNs is first investigated through tracking their strong and stable fluorescence. The high bacteria inhibition ability (≈82.9% killing rate toward S. aureus) and hemostatic effects (shorten the bleeding time from ≈60 to ≈15 s) of the resultant SiCNs are then demonstrated. Moreover, the wound closure promotion activity (10% lead in wound contraction) is systematically demonstrated in vivo, which is especially suitable for wound healing applications. The results suggest the SiCNs as a new kind of high-performance multifunctional nanoagents suitable for various biological and biomedical utilizations.

Role of four-dimensional echocardiography with high-definition flow imaging and spatiotemporal image correlation in detecting fetal pulmonary veins.

BACKGROUND: Prenatal diagnosis of fetal total anomalous pulmonary vein connection (TAPVC) remains challenging for most screening sonographers. The purpose of this study was to evaluate the use of four-dimensional echocardiography with high-definition flow imaging and spatiotemporal image correlation (4D-HDFI) in identifying pulmonary veins in normal and TAPVC fetuses. MATERIAL & METHODS: We retrospectively reviewed and performed 4D-HDFI in 204 normal and 12 fetuses with confirmed diagnosis of TAPVC. Cardiac volumes were available for postanalysis to obtain 4D-rendered images of the pulmonary veins. For the normal fetuses, two other traditional modalities including color Doppler and HDFI were used to detect the number of pulmonary veins and comparisons were made between each of these traditional methods and 4D-HDFI. RESULTS: For conventional echocardiography, HDFI modality was superior to color Doppler in detecting more pulmonary veins in normal fetuses throughout the gestational period. 4D-HDFI was the best method during the second trimester of pregnancy in identifying normal fetal pulmonary veins. 4D-HDFI images vividly depicted the figure, course, and drainage of pulmonary veins in both normal and TAPVC fetuses. CONCLUSION: HDFI and the advanced 4D-HDFI technique could facilitate identification of the anatomical features of pulmonary veins in both normal and TAPVC fetuses; 4D-HDFI therefore provides additional and more precise information than conventional echocardiography techniques.

Evaluation of fetal cardiac valve anomalies by four-dimensional echocardiography with spatiotemporal image correlation (4DSTIC).

BACKGROUND: Prenatal diagnosis of cardiac valve anomalies challenged most screening sonographers. The purpose of the study was to evaluate the use of four-dimensional echocardiography with spatiotemporal image correlation (4DSTIC) in detecting normal and abnormal fetal cardiac valves. METHODS: Forty-three cases of confirmed cardiac valve anomalies identified by two-dimensional echocardiography (2DE) were retrospectively reviewed in this study. Additional 121 confirmed normal fetuses were included as controls. Four-dimensional volumes were acquired from each fetus using a transverse sweep. Four-dimensional rendered images were retrieved from the volumes for each of the cardiac valves for the normal fetuses and for the intended valves for fetuses with valve malformations. RESULTS: The visualization rates of cardiac valves retrieved from 4D volumes in the normal fetuses ranged from 72.5% to 97.5% before 33 gestational weeks and from 46.3% to 80.5% in late pregnancy. Furthermore, 4D rendered images were successfully obtained in 38 of 43 (88.4%) fetuses with cardiac valve lesions. CONCLUSIONS: The 4D images and cine loops displayed the valves anatomy vividly in both normal and abnormal fetuses, including some subtle malformations which were not identified by traditional 2DE. The standardized protocol we propose herein was important in obtaining the 4D images from the volumes. The 4D modality allows a better visualization of fetal cardiac valves and should be considered a valuable addition to traditional 2DE imaging.

Validation of dual-energy CT-based composition analysis using fresh animal tissues and composition-optimized tissue equivalent samples.

Objective.Proton therapy allows for highly conformal dose deposition, but is sensitive to range uncertainties. Several approaches currently under development measure composition-dependent secondary radiation to monitor the delivered proton rangein-vivo. To fully utilize these methods, an estimate of the elemental composition of the patient's tissue is often needed.Approach.A published dual-energy computed tomography (DECT)-based composition-extraction algorithm was validated against reference compositions obtained with two independent methods. For this purpose, a set of phantoms containing either fresh porcine tissue or tissue-mimicking samples with known, realistic compositions were imaged with a CT scanner at two different energies. Then, the prompt gamma-ray (PG) signal during proton irradiation was measured with a PG detector prototype. The PG workflow used pre-calculated Monte Carlo simulations to obtain an optimized estimate of the sample's carbon and oxygen contents. The compositions were also assessed with chemical combustion analysis (CCA), and the stopping-power ratio (SPR) was measured with a multi-layer ionization chamber. The DECT images were used to calculate SPR-, density- and elemental composition maps, and to assign voxel-wise compositions from a selection of human tissues. For a more comprehensive set of reference compositions, the original selection was extended by 135 additional tissues, corresponding to spongiosa, high-density bones and low-density tissues.Results.The root-mean-square error for the soft tissue carbon and oxygen content was 8.5 wt% and 9.5 wt% relative to the CCA result and 2.1 wt% and 10.3 wt% relative to the PG result. The phosphorous and calcium content were predicted within 0.4 wt% and 1.1 wt% of the CCA results, respectively. The largest discrepancies were encountered in samples whose composition deviated the most from tabulated compositions or that were more inhomogeneous.Significance.Overall, DECT-based composition estimations of relevant elements were in equal or better agreement with the ground truth than the established SECT-approach and could contribute toin-vivodose verification measurements.

A direct comparison of multi-energy x-ray and proton CT for imaging and relative stopping power estimation of plastic andex-vivophantoms.

Objective.Proton therapy administers a highly conformal dose to the tumour region, necessitating accurate prediction of the patient's 3D map of proton relative stopping power (RSP) compared to water. This remains challenging due to inaccuracies inherent in single-energy computed tomography (SECT) calibration. Recent advancements in spectral x-ray CT (xCT) and proton CT (pCT) have shown improved RSP estimation compared to traditional SECT methods. This study aims to provide the first comparison of the imaging and RSP estimation performance among dual-energy CT (DECT) and photon-counting CT (PCCT) scanners, and a pCT system prototype.Approach.Two phantoms were scanned with the three systems for their performance characterisation: a plastic phantom, filled with water and containing four plastic inserts and a wood insert, and a heterogeneous biological phantom, containing a formalin-stabilised bovine specimen. RSP maps were generated by converting CT numbers to RSP using a calibration based on low- and high-energy xCT images, while pCT utilised a distance-driven filtered back projection algorithm for RSP reconstruction. Spatial resolution, noise, and RSP accuracy were compared across the resulting images.Main results.All three systems exhibited similar spatial resolution of around 0.54 lp/mm for the plastic phantom. The PCCT images were less noisy than the DECT images at the same dose level. The lowest mean absolute percentage error (MAPE) of RSP,(0.28±0.07)%, was obtained with the pCT system, compared to MAPE values of(0.51±0.08)%and(0.80±0.08)%for the DECT- and PCCT-based methods, respectively. For the biological phantom, the xCT-based methods resulted in higher RSP values in most of the voxels compared to pCT.Significance.The pCT system yielded the most accurate estimation of RSP values for the plastic materials, and was thus used to benchmark the xCT calibration performance on the biological phantom. This study underlined the potential benefits and constraints of utilising such a novelex-vivophantom for inter-centre surveys in future.

MonkeyTrail: A scalable video-based method for tracking macaque movement trajectory in daily living cages.

Behavioral analysis of macaques provides important experimental evidence in the field of neuroscience. In recent years, video-based automatic animal behavior analysis has received widespread attention. However, methods capable of extracting and analyzing daily movement trajectories of macaques in their daily living cages remain underdeveloped, with previous approaches usually requiring specific environments to reduce interference from occlusion or environmental change. Here, we introduce a novel method, called MonkeyTrail, which satisfies the above requirements by frequently generating virtual empty backgrounds and using background subtraction to accurately obtain the foreground of moving animals. The empty background is generated by combining the frame difference method (FDM) and deep learning-based model (YOLOv5). The entire setup can be operated with low-cost hardware and can be applied to the daily living environments of individually caged macaques. To test MonkeyTrail performance, we labeled a dataset containing >8 000 video frames with the bounding boxes of macaques under various conditions as ground-truth. Results showed that the tracking accuracy and stability of MonkeyTrail exceeded that of two deep learning-based methods (YOLOv5 and Single-Shot MultiBox Detector), traditional frame difference method, and naïve background subtraction method. Using MonkeyTrail to analyze long-term surveillance video recordings, we successfully assessed changes in animal behavior in terms of movement amount and spatial preference. Thus, these findings demonstrate that MonkeyTrail enables low-cost, large-scale daily behavioral analysis of macaques.

Assessment of quantitative information for radiation therapy at a first-generation clinical photon-counting computed tomography scanner.

As one of the latest developments in X-ray computed tomography (CT), photon-counting technology allows spectral detection, demonstrating considerable advantages as compared to conventional CT. In this study, we investigated the use of a first-generation clinical photon-counting computed tomography (PCCT) scanner and estimated proton relative (to water) stopping power (RSP) of tissue-equivalent materials from virtual monoenergetic reconstructions provided by the scanner. A set of calibration and evaluation tissue-equivalent inserts were scanned at 120 kVp. Maps of relative electron density (RED) and effective atomic number (EAN) were estimated from the reconstructed virtual monoenergetic images (VMI) using an approach previously applied to a spectral CT scanner with dual-layer detector technology, which allows direct calculation of RSP using the Bethe-Bloch formula. The accuracy of RED, EAN, and RSP was evaluated by root-mean-square errors (RMSE) averaged over the phantom inserts. The reference RSP values were obtained experimentally using a water column in an ion beam. For RED and EAN, the reference values were calculated based on the mass density and the chemical composition of the inserts. Different combinations of low- and high-energy VMIs were investigated in this study, ranging from 40 to 190 keV. The overall lowest error was achieved using VMIs at 60 and 180 keV, with an RSP accuracy of 1.27% and 0.71% for the calibration and the evaluation phantom, respectively.

Comparative Secretome Analyses of Mycoplasma bovis Virulent and Attenuated Strains Revealed MbovP0145 as a Promising Diagnostic Biomarker.

Mycoplasmas are successful pathogens both in humans as well as in animals. In cattle, Mycoplasma bovis (M. bovis) is known to be responsible for serious health complications, including pneumonia, mastitis, and arthritis. However, M. bovis pathogenesis remains unclear. Secreted proteins of M. bovis could influence infection and modify host defense signaling pathways after they enter their extracellular space in the host micro-environment. Therefore, this study was aimed to compare the secretomes of M. bovis HB0801 virulent (P1) and attenuated (P150) strains and identify potential pathogenesis-related secreted proteins and biomarkers. The cells of P1 and P150 strains were grown in pleuropneumonia-like organism medium to log phase and then transferred to phosphate-buffered saline for 2 h. Then, the supernatant was analyzed by using label-free quantitative proteomics, and 477 potential secreted proteins were identified. Combined with the bioinformatics prediction, we found that 178 proteins were commonly secreted by the P1 and P150 strains, and 49 of them were encoded by mycoplasmal core genes. Additionally, 79 proteins were found to have a different abundance between the P1 and P150 strains. Among these proteins, 34 were more abundant and uniquely expressed in P1, indicating a possible association with the virulence of M. bovis. Three differentially secreted proteins, MbovP0145, MbovP0725, and MbovP0174, as well as one equally secreted protein, MbovP0481, as positive control and one protein of inner membrane, MbovP0310, as negative control were, respectively, cloned, expressed, and evaluated for antigenicity, subcellular location, and the secretion nature with their mouse antisera by western blotting and colony immunoblotting assay. Among them, MbovP0145 was confirmed to be more secreted by P1 than P150 strain, highly reactive with the antisera from naturally infected and P1 experimentally infected cattle but not with the P150 vaccinated calves, indicating its potential as a diagnostic antigen. In conclusion, these findings may represent the most extensive compilation of potentially secreted proteins in mycoplasma species and the largest number of differentially secreted proteins between the virulent and attenuated M. bovis strains to date and provide new insights into M. bovis pathogenesis and diagnosis.

Multi-Scale Expressions of One Optimal State Regulated by Dopamine in the Prefrontal Cortex.

The prefrontal cortex (PFC), which plays key roles in many higher cognitive processes, is a hierarchical system consisting of multi-scale organizations. Optimizing the working state at each scale is essential for PFC's information processing. Typical optimal working states at different scales have been separately reported, including the dopamine-mediated inverted-U profile of the working memory (WM) at the system level, critical dynamics at the network level, and detailed balance of excitatory and inhibitory currents (E/I balance) at the cellular level. However, it remains unclear whether these states are scale-specific expressions of the same optimal state and, if so, what is the underlying mechanism for its regulation traversing across scales. Here, by studying a neural network model, we show that the optimal performance of WM co-occurs with the critical dynamics at the network level and the E/I balance at the level of individual neurons, suggesting the existence of a unified, multi-scale optimal state for the PFC. Importantly, such a state could be modulated by dopamine at the synaptic level through a series of U or inverted-U profiles. These results suggest that seemingly different optimal states for specific scales are multi-scale expressions of one condition regulated by dopamine. Our work suggests a cross-scale perspective to understand the PFC function and its modulation.

Fluorescent Silicon Nanorods-Based Nanotheranostic Agents for Multimodal Imaging-Guided Photothermal Therapy.

The utilization of diagnosis to guide/aid therapy procedures has shown great prospects in the era of personalized medicine along with the recognition of tumor heterogeneity and complexity. Herein, a kind of multifunctional silicon-based nanostructure, i.e., gold nanoparticles-decorated fluorescent silicon nanorods (Au@SiNRs), is fabricated and exploited for tumor-targeted multimodal imaging-guided photothermal therapy. In particular, the prepared Au@SiNRs feature high photothermal conversion efficiency (~ 43.9%) and strong photothermal stability (photothermal performance stays constant after five-cycle NIR laser irradiation), making them high-performance agents for simultaneously photoacoustic and infrared thermal imaging. The Au@SiNRs are readily modified with targeting peptide ligands, enabling an enhanced tumor accumulation with a high value of ~ 8.74% ID g-1. Taking advantages of these unique merits, the Au@SiNRs are superbly suitable for specifically ablating tumors in vivo without appreciable toxicity under the guidance of multimodal imaging. Typically, all the mice treated with the Au@SiNRs remain alive, and no distinct tumor recurrence is observed during 60-day investigation.

Calves Infected with Virulent and Attenuated Mycoplasma bovis Strains Have Upregulated Th17 Inflammatory and Th1 Protective Responses, Respectively.

Mycoplasma bovis is a critical bovine pathogen, but its pathogenesis remains poorly understood. Here, the virulent HB0801 (P1) and attenuated HB0801-P150 (P150) strains of M. bovis were used to explore the potential pathogenesis and effect of induced immunity from calves' differential transcriptomes post infection. Nine one-month-old male calves were infected with P1, P150, or mock-infected with medium and euthanized at 60 days post-infection. Calves in P1 group exhibited other clinical signs and pathological changes compared to the other two groups. Transcriptome profiles of peripheral blood mononuclear cells revealed seven and 10 hub differentially expressed genes (DEGs) in P1 and P150 groups compared with mock-infected group, respectively. Then, P1-induced pathogenesis was predicted to be associated with enhanced Th17, and P150-induced immunity with Th1 response and expression of ubiquitination-associated enzymes. Association analysis showed that 14 and 11 DEGs were positively and negatively correlated with pathological changes, respectively. Furthermore, up-regulated expression in molecules critical to differentiation of pathogenic Th17 cells in lung and peripheral blood mononuclear cells in P1 group was validated at RNA and protein levels. The results confirmed virulent and attenuated strains might be associated with biased differentiation of pro-inflammatory pathogenic Th17 and Th1 subsets respectively.

Effects of light-emitting diode supplementary lighting on the winter growth of greenhouse plants in the Yangtze River Delta of China.

BACKGROUND: The winter in the Yangtze River Delta area of China involves more than 1 month of continuous low temperature and poor light (CLTL) weather conditions, which impacts horticultural production in an unheated greenhouse; however, few greenhouses in this area are currently equipped with a heating device. The low-cost and long-living light-emitting diode (LED) was used as an artificial light source to explore the effects of supplementary lighting during the dark period in CLTL winter on the vegetative characteristics, early yield, and physiology of flowering for pepper plants grown in a greenhouse without heating. Two LED lighting sets were employed with different light source to provide 65 µmol m-2 s-1 at night: (1) LED-A: red LEDs (R, peak wavelength 660 nm) and blue LEDs (B, peak wavelength 460 nm) with an R:B ratio of 6:3; and (2) LED-B: R and B LEDs at an R:B ratio of 8:1. Plants growth parameters and chlorophyll fluorescence characteristics were compared between lighting treatments and the control group. RESULTS: Plants' yield and photosynthesis ability were improved by LED-A. Pepper grown under the LED-A1 strategy showed a 303.3 % greater fresh weight of fruits and a 501.3 % greater dry mass compared with the control group. Plant leaves under LED-A1 showed maximum efficiency of the light quantum yield of PSII, electron transfer rate, and the proportion of the open fraction of PSII centers, with values 113.70, 114.34, and 211.65 % higher than those of the control group, respectively, and showed the lowest rate constant of thermal energy dissipation of all groups. LED-B was beneficial to the plant height and stems diameter of the pepper plants more than LED-A. CONCLUSIONS: These results can serve as a guide for environment control and for realizing low energy consumption for products grown in a greenhouse in the winter in Southern China.