Masked cross-domain self-supervised deep learning framework for photoacoustic computed tomography reconstruction.

Accurate image reconstruction is crucial for photoacoustic (PA) computed tomography (PACT). Recently, deep learning has been used to reconstruct PA images with a supervised scheme, which requires high-quality images as ground truth labels. However, practical implementations encounter inevitable trade-offs between cost and performance due to the expensive nature of employing additional channels for accessing more measurements. Here, we propose a masked cross-domain self-supervised (CDSS) reconstruction strategy to overcome the lack of ground truth labels from limited PA measurements. We implement the self-supervised reconstruction in a model-based form. Simultaneously, we take advantage of self-supervision to enforce the consistency of measurements and images across three partitions of the measured PA data, achieved by randomly masking different channels. Our findings indicate that dynamically masking a substantial proportion of channels, such as 80%, yields meaningful self-supervisors in both the image and signal domains. Consequently, this approach reduces the multiplicity of pseudo solutions and enables efficient image reconstruction using fewer PA measurements, ultimately minimizing reconstruction error. Experimental results on in-vivo PACT dataset of mice demonstrate the potential of our self-supervised framework. Moreover, our method exhibits impressive performance, achieving a structural similarity index (SSIM) of 0.87 in an extreme sparse case utilizing only 13 channels, which outperforms the performance of the supervised scheme with 16 channels (0.77 SSIM). Adding to its advantages, our method can be deployed on different trainable models in an end-to-end manner, further enhancing its versatility and applicability.

Efficient Microbubble Trajectory Tracking in Ultrasound Localization Microscopy Using a Gated Recurrent Unit-Based Multitasking Temporal Neural Network.

Ultrasound Localization Microscopy (ULM), an emerging medical imaging technique, effectively resolves the classical trade-off between resolution and penetration inherent in traditional ultrasound imaging, opening up new avenues for noninvasive observation of the microvascular system. However, traditional microbubble tracking methods encounter various practical challenges. These methods typically entail multiple processing stages, including intricate steps like pairwise correlation and trajectory optimization, rendering real-time applications unfeasible. Furthermore, existing deep learning-based tracking techniques neglect the temporal aspects of microbubble motion, leading to ineffective modeling of their dynamic behavior. To address these limitations, this study introduces a novel approach called the Gated Recurrent Unit (GRU)-based Multitasking Temporal Neural Network (GRU-MT). GRU-MT is designed to simultaneously handle microbubble trajectory tracking and trajectory optimization tasks. Additionally, we enhance the nonlinear motion model initially proposed by Piepenbrock et al. to better encapsulate the nonlinear motion characteristics of microbubbles, thereby improving trajectory tracking accuracy. In this study, we perform a series of experiments involving network layer substitutions to systematically evaluate the performance of various temporal neural networks, including Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), GRU, Transformer, and its bidirectional counterparts, on the microbubble trajectory tracking task. Concurrently, the proposed method undergoes qualitative and quantitative comparisons with traditional microbubble tracking techniques. The experimental results demonstrate that GRU-MT exhibits superior nonlinear modeling capabilities and robustness, both in simulation and in vivo dataset. Additionally, it achieves reduced trajectory tracking errors in shorter time intervals, underscoring its potential for efficient microbubble trajectory tracking. Model code is open-sourced at https://github.com/zyt-Lib/GRU-MT.

Knowledge fused latent representation from lung ultrasound examination for COVID-19 pneumonia severity assessment.

COVID-19 pneumonia severity assessment is of great clinical importance, and lung ultrasound (LUS) plays a crucial role in aiding the severity assessment of COVID-19 pneumonia due to its safety and portability. However, its reliance on qualitative and subjective observations by clinicians is a limitation. Moreover, LUS images often exhibit significant heterogeneity, emphasizing the need for more quantitative assessment methods. In this paper, we propose a knowledge fused latent representation framework tailored for COVID-19 pneumonia severity assessment using LUS examinations. The framework transforms the LUS examination into latent representation and extracts knowledge from regions labeled by clinicians to improve accuracy. To fuse the knowledge into the latent representation, we employ a knowledge fusion with latent representation (KFLR) model. This model significantly reduces errors compared to approaches that lack prior knowledge integration. Experimental results demonstrate the effectiveness of our method, achieving high accuracy of 96.4 % and 87.4 % for binary-level and four-level COVID-19 pneumonia severity assessments, respectively. It is worth noting that only a limited number of studies have reported accuracy for clinically valuable exam level assessments, and our method surpass existing methods in this context. These findings highlight the potential of the proposed framework for monitoring disease progression and patient stratification in COVID-19 pneumonia cases.

Tumour microenvironment programming by an RNA-RNA-binding protein complex creates a druggable vulnerability in IDH-wild-type glioblastoma.

Patients with IDH-wild-type glioblastomas have a poor five-year survival rate along with limited treatment efficacy due to immune cell (glioma-associated microglia and macrophages) infiltration promoting tumour growth and resistance. To enhance therapeutic options, our study investigated the unique RNA-RNA-binding protein complex LOC-DHX15. This complex plays a crucial role in driving immune cell infiltration and tumour growth by establishing a feedback loop between cancer and immune cells, intensifying cancer aggressiveness. Targeting this complex with blood-brain barrier-permeable small molecules improved treatment efficacy, disrupting cell communication and impeding cancer cell survival and stem-like properties. Focusing on RNA-RNA-binding protein interactions emerges as a promising approach not only for glioblastomas without the IDH mutation but also for potential applications beyond cancer, offering new avenues for developing therapies that address intricate cellular relationships in the body.

Synthetic minority over-sampling technique-enhanced machine learning models for predicting recurrence of postoperative chronic subdural hematoma.

Objective: Chronic subdural hematoma (CSDH) is a neurological condition with high recurrence rates, primarily observed in the elderly population. Although several risk factors have been identified, predicting CSDH recurrence remains a challenge. Given the potential of machine learning (ML) to extract meaningful insights from complex data sets, our study aims to develop and validate ML models capable of accurately predicting postoperative CSDH recurrence. Methods: Data from 447 CSDH patients treated with consecutive burr-hole irrigations at Wenzhou Medical University's First Affiliated Hospital (December 2014-April 2019) were studied. 312 patients formed the development cohort, while 135 comprised the test cohort. The Least Absolute Shrinkage and Selection Operator (LASSO) method was employed to select crucial features associated with recurrence. Eight machine learning algorithms were used to construct prediction models for hematoma recurrence, using demographic, laboratory, and radiological features. The Border-line Synthetic Minority Over-sampling Technique (SMOTE) was applied to address data imbalance, and Shapley Additive Explanation (SHAP) analysis was utilized to improve model visualization and interpretability. Model performance was assessed using metrics such as AUROC, sensitivity, specificity, F1 score, calibration plots, and decision curve analysis (DCA). Results: Our optimized ML models exhibited prediction accuracies ranging from 61.0% to 86.2% for hematoma recurrence in the validation set. Notably, the Random Forest (RF) model surpassed other algorithms, achieving an accuracy of 86.2%. SHAP analysis confirmed these results, highlighting key clinical predictors for CSDH recurrence risk, including age, alanine aminotransferase level, fibrinogen level, thrombin time, and maximum hematoma diameter. The RF model yielded an accuracy of 92.6% with an AUC value of 0.834 in the test dataset. Conclusion: Our findings underscore the efficacy of machine learning algorithms, notably the integration of the RF model with SMOTE, in forecasting the recurrence of postoperative chronic subdural hematoma. Leveraging the RF model, we devised an online calculator that may serve as a pivotal instrument in tailoring therapeutic strategies and implementing timely preventive interventions for high-risk patients.

BCAR4 facilitates trastuzumab resistance and EMT in breast cancer via sponging miR-665 and interacting with YAP1.

Breast cancer antiestrogen resistance 4 (BCAR4) has been suggested that can modulate cell behavior, resulting in tumorigenesis and chemoresistance. However, the underlying mechanisms of BCAR4 in trastuzumab resistance (TR) is still elusive. Here, we explored the function and the underlying mechanism of BCAR4 involving in TR. We found that BCAR4 is significantly upregulated in trastuzumab-resistant BC cells. Knockdown of BCAR4 could sensitize the BC cells to trastuzumab and suppress epithelial-mesenchymal transition (EMT). Mechanically, BCAR4 promotes yes-associated protein 1 (YAP1) expression by competitively sponging miR-665, to activated TGF-ß signaling. Reciprocally, YAP1 could occupy the BCAR4 promoter to enhance its transcription, suggesting that there exists a positive feedback regulation between YAP1 and BCAR4. Targeting the BCAR4/miR-665/YAP1 axis may provide a novel insight of therapeutic approaches for TR in BC.

Assembly and succession of the phyllosphere microbiome and nutrient-cycling genes during plant community development in a glacier foreland.

The phyllosphere, particularly the leaf surface of plants, harbors a diverse range of microbiomes that play a vital role in the functioning of terrestrial ecosystems. However, our understanding of microbial successions and their impact on functional genes during plant community development is limited. In this study, considering core and satellite microbial taxa, we characterized the phyllosphere microbiome and functional genes in various microhabitats (i.e., leaf litter, moss and plant leaves) across the succession of a plant community in a low-altitude glacier foreland. Our findings indicate that phyllosphere microbiomes and associated ecosystem stability increase during the succession of the plant community. The abundance of core taxa increased with plant community succession and was primarily governed by deterministic processes. In contrast, satellite taxa abundance decreased during plant community succession and was mainly governed by stochastic processes. The abundance of microbial functional genes (such as C, N, and P hydrolysis and fixation) in plant leaves generally increased during the plant community succession. However, in leaf litter and moss leaves, only a subset of functional genes (e.g., C fixation and degradation, and P mineralization) showed a tendency to increase with plant community succession. Ultimately, the community of both core and satellite taxa collaboratively influenced the characteristics of phyllosphere nutrient-cycling genes, leading to the diverse profiles and fluctuating abundance of various functional genes during plant community succession. These findings offer valuable insights into the phyllosphere microbiome and plant-microbe interactions during plant community development, advancing our understanding of the succession and functional significance of the phyllosphere microbial community.

Interaction of tetracycline and copper co-intake in inducing antibiotic resistance genes and potential pathogens in mouse gut.

The widespread use of copper and tetracycline as growth promoters in the breeding industry poses a potential threat to environmental health. Nevertheless, to the best of our knowledge, the potential adverse effects of copper and tetracycline on the gut microbiota remain unknown. Herein, mice were fed different concentrations of copper and/or tetracycline for 6 weeks to simulate real life-like exposure in the breeding industry. Following the exposure, antibiotic resistance genes (ARGs), potential pathogens, and other pathogenic factors were analyzed in mouse feces. The co-exposure of copper with tetracycline significantly increased the abundance of ARGs and enriched more potential pathogens in the gut of the co-treated mice. Copper and/or tetracycline exposure increased the abundance of bacteria carrying either ARGs, metal resistance genes, or virulence factors, contributing to the widespread dissemination of potentially harmful genes posing a severe risk to public health. Our study provides insights into the effects of copper and tetracycline exposure on the gut resistome and potential pathogens, and our findings can help reduce the risks associated with antibiotic resistance under the One Health framework.

A One-Stone-Two-Birds Strategy of Targeting Microbubbles with "Dual" Anti-Inflammatory and Blood-Brain Barrier "Switch" Function for Ischemic Stroke Treatment.

Inflammation is considered to be the main target of the development of new stroke therapies. There are three key issues in the treatment of stroke inflammation: the first one is how to overcome the blood-brain barrier (BBB) to achieve drug delivery, the second one is how to select drugs to treat stroke inflammation, and the third one is how to achieve targeted drug delivery. In this study, we constructed hydrocortisone-phosphatidylserine microbubbles and combined them with ultrasound (US)-targeted microbubble destruction technology to successfully open the BBB to achieve targeted drug delivery. Phosphatidylserine on the microbubbles was used for its "eat me" effect to increase the targeting of the microvesicles. In addition, we found that hydrocortisone can accelerate the closure of the BBB, achieving efficient drug delivery while reducing the entry of peripheral toxins into the brain. In the treatment of stroke inflammation, it was found that hydrocortisone itself has anti-inflammatory effects and can also change the polarization of microglia from the harmful pro-inflammatory M1 phenotype to the beneficial anti-inflammatory M2 phenotype, thus achieving dual anti-inflammatory effects and enhancing the anti-inflammatory effects in ischemic areas after stroke, well reducing the cerebellar infarction volume by inhibiting the inflammatory response after cerebral ischemia. A confocal microendoscope was used to directly observe the polarization of microglial cells in living animal models for dynamic microscopic visualization detection showing the advantage of being closer to clinical work. Taken together, this study constructed a multifunctional targeted US contrast agent with the function of "one-stone-two-birds", which can not only "on-off" the BBB but also have "two" anti-inflammatory functions, providing a new strategy of integrated anti-inflammatory targeted delivery and imaging monitoring for ischemic stroke treatment.

Recent Advances in Electrochemical Sensors for Formaldehyde.

Formaldehyde, a ubiquitous indoor air pollutant, plays a significant role in various biological processes, posing both environmental and health challenges. This comprehensive review delves into the latest advancements in electrochemical methods for detecting formaldehyde, a compound of growing concern due to its widespread use and potential health hazards. This review underscores the inherent advantages of electrochemical techniques, such as high sensitivity, selectivity, and capability for real-time analysis, making them highly effective for formaldehyde monitoring. We explore the fundamental principles, mechanisms, and diverse methodologies employed in electrochemical formaldehyde detection, highlighting the role of innovative sensing materials and electrodes. Special attention is given to recent developments in nanotechnology and sensor design, which significantly enhance the sensitivity and selectivity of these detection systems. Moreover, this review identifies current challenges and discusses future research directions. Our aim is to encourage ongoing research and innovation in this field, ultimately leading to the development of advanced, practical solutions for formaldehyde detection in various environmental and biological contexts.

PVT1 promotes proliferation and macrophage immunosuppressive polarization through STAT1 and CX3CL1 regulation in glioblastoma multiforme.

AIMS: This study aimed to investigate the role of plasmacytoma variant translocation 1 (PVT1), a long non-coding RNA, in glioblastoma multiforme (GBM) and its impact on the tumor microenvironment (TME). METHODS: We assessed aberrant PVT1 expression in glioma tissues and its impact on GBM cell growth in vitro and in vivo. Additionally, we investigated PVT1's role in influencing glioma-associated macrophages. To understand PVT1's role in cell growth and the immunosuppressive TME, we performed a series of comprehensive experiments. RESULTS: PVT1 was overexpressed in GBM due to copy number amplification, correlating with poor prognosis. Elevated PVT1 promoted GBM cell proliferation, while its downregulation inhibited growth in vitro and in vivo. PVT1 inhibited type I interferon-stimulated genes (ISGs), with STAT1 as the central hub. PVT1 correlated with macrophage enrichment and regulated CX3CL1 expression, promoting recruitment and M2 phenotype polarization of macrophages. PVT1 localized to the cell nucleus and bound to DHX9, enriching at the promoter regions of STAT1 and CX3CL1, modulating ISGs and CX3CL1 expression. CONCLUSION: PVT1 plays a significant role in GBM, correlating with poor prognosis, promoting cell growth, and shaping an immunosuppressive TME via STAT1 and CX3CL1 regulation. Targeting PVT1 may hold therapeutic promise for GBM patients.

circRNADisease v2.0: an updated resource for high-quality experimentally supported circRNA-disease associations.

circRNADisease v2.0 is an enhanced and reliable database that offers experimentally verified relationships between circular RNAs (circRNAs) and various diseases. It is accessible at http://cgga.org.cn/circRNADisease/ or http://cgga.org.cn:9091/circRNADisease/. The database currently includes 6998 circRNA-disease entries across multiple species, representing a remarkable 19.77-fold increase compared to the previous version. This expansion consists of a substantial rise in the number of circRNAs (from 330 to 4246), types of diseases (from 48 to 330) and covered species (from human only to 12 species). Furthermore, a new section has been introduced in the database, which collects information on circRNA-associated factors (genes, proteins and microRNAs), molecular mechanisms (molecular pathways), biological functions (proliferation, migration, invasion, etc.), tumor and/or cell line and/or patient-derived xenograft (PDX) details, and prognostic evidence in diseases. In addition, we identified 7 159 865 relationships between mutations and circRNAs among 30 TCGA cancer types. Due to notable enhancements and extensive data expansions, the circRNADisease 2.0 database has become an invaluable asset for both clinical practice and fundamental research. It enables researchers to develop a more comprehensive understanding of how circRNAs impact complex diseases.

Recent Advances in Flexible CNC-Based Chiral Nematic Film Materials.

Cellulose nanocrystal (CNC) is a renewable resource derived from lignocellulosic materials, known for its optical permeability, biocompatibility, and unique self-assembly properties. Recent years have seen great progresses in cellulose nanocrystal-based chiral photonic materials. However, due to its inherent brittleness, cellulose nanocrystal shows limitations in the fields of flexible materials, optical sensors and food freshness testing. In order to solve the above limitations, attempts have been made to improve the flexibility of cellulose nanocrystal materials without destroying their structural color. Despite these progresses, a systematic review on them is lacking. This review aims to fill this gap by providing an overview of the main strategies and the latest research findings on the flexibilization of cellulose nanocrystal-based chiral nematic film materials (FCNM). Specifically, typical substances and methods used for their preparation are summarized. Moreover, different kinds of cellulose nanocrystal-based composites are compared in terms of flexibility. Finally, potential applications and future challenges of flexible cellulose nanocrystal-based chiral nematic materials are discussed, inspiring further research in this field.

Ultrafast power Doppler imaging for ischemic encephalopathy: A case report.

BACKGROUND: Severely elevated intracranial pressure due to various reasons, such as decreased cerebral perfusion, can lead to devastating neurological outcomes, such as brain herniation. Decompression craniectomy is a life-saving procedure that is commonly performed for such a critical situation, but the changes in cerebral microvessels after brain herniation and decompression are unclear. Ultrafast power Doppler imaging (uPDI) is a new microvascular imaging technology that utilizes high frame rate plane/diverging wave transmission and advanced clutter filters. uPDI significantly improves Doppler sensitivity and can detect microvessels, which are usually invisible using traditional ultrasound Doppler imaging. CASE SUMMARY: In this report, uPDI was used for the first time to observe the brain blood flow of a hypoperfusion area in a 4-year-old girl who underwent decompression craniectomy due to refractory intracranial hypertension (ICP) after malignant brain tumor surgery. B-mode imaging was used to verify the increased densities of the cerebral cortex and basal ganglia that were observed by computed tomography. CONCLUSION: uPDI showed the local blood supplies and anatomical structures of the patient after decompressive craniectomy. uPDI is potentially a more intuitive and noninvasive method for evaluating the effects of severe ICP on cerebral microvessels.

Improved Ultrafast Power Doppler Imaging Using United Spatial-Angular Adaptive Scaling Wiener Postfilter.

Ultrafast power Doppler imaging (uPDI) using high-frame-rate plane-wave transmission is a new microvascular imaging modality that offers high Doppler sensitivity. However, due to the unfocused transmission of plane waves, the echo signal is subject to interference from noise and clutter, resulting in a low signal-to-noise ratio (SNR) and poor image quality. Adaptive beamforming techniques are effective in suppressing noise and clutter for improved image quality. In this study, an adaptive beamformer based on a united spatial-angular adaptive scaling Wiener (uSA-ASW) postfilter is proposed to improve the resolution and contrast of uPDI. In the proposed method, the signal power and noise power of the Wiener postfilter are estimated by uniting spatial and angular signals, and a united generalized coherence factor (uGCF) is introduced to dynamically adjust the noise power estimation and enhance the robustness of the method. Simulation and in vivo data were used to verify the effectiveness of the proposed method. The results show that the uSA-ASW can achieve higher resolution and significant improvements in image contrast and background noise suppression compared with conventional delay-and-sum (DAS), coherence factor (CF), spatial-angular CF (SACF), and adaptive scaling Wiener (ASW) postfilter methods. In the simulations, uSA-ASW improves contrast-to-noise ratio (CNR) by 34.7 dB (117.3%) compared with DAS, while reducing background noise power (BNP) by 52 dB (221.4%). The uSA-ASW method provides full-width at half-maximum (FWHM) reductions of [Formula: see text] (59.5%) and [Formula: see text] (56.9%), CNR improvements of 25.6 dB (199.9%) and 42 dB (253%), and BNP reductions of 46.1 dB (319.3%) and 12.9 dB (289.1%) over DAS in the experiments of contrast-free human neonatal brain and contrast-free human liver, respectively. In the contrast-free experiments, uSA-ASW effectively balances the performance of noise and clutter suppression and enhanced microvascular visualization. Overall, the proposed method has the potential to become a reliable microvascular imaging technique for aiding in more accurate diagnosis and detection of vascular-related diseases in clinical contexts.

Gut Microbiota Control the Bioavailability and Metabolism of Organoarsenicals of Seaweeds in Mice after Oral Ingestion.

Edible seaweed consumption is an essential route of human exposure to complex organoarsenicals, including arsenosugars and arsenosugar phospholipids. However, the effects of gut microbiota on the metabolism and bioavailability of arsenosugars in vivo are unknown. Herein, two nori and two kelp samples with phosphate arsenosugar and sulfonate arsenosugar, respectively, as the predominant arsenic species, were administered to normal mice and gut microbiota-disrupted mice treated with the broad-spectrum antibiotic cefoperazone for 4 weeks. Following exposure, the community structures of the gut microbiota, total arsenic concentrations, and arsenic species in excreta and tissues were analyzed. Total arsenic excreted in feces and urine did not differ significantly between normal and antibiotic-treated mice fed with kelp samples. However, the total urinary arsenic of normal mice fed with nori samples was significantly higher (p < 0.05) (urinary arsenic excretion factor, 34-38 vs 5-7%), and the fecal total arsenic was significantly lower than in antibiotic-treated mice. Arsenic speciation analysis revealed that most phosphate arsenosugars in nori were converted to arsenobetaine (53.5-74.5%) when passing through the gastrointestinal tract, whereas a large portion of sulfonate arsenosugar in kelp was resistant to speciation changes and was excreted in feces intact (64.1-64.5%). Normal mice exhibited greater oral bioavailability of phosphate arsenosugar from nori than sulfonate arsenosugar from kelp (34-38 vs 6-9%). Our work provides insights into organoarsenical metabolism and their bioavailability in the mammalian gut.

Evaluation of Early Diabetic Kidney Disease Using Ultrasound Localization Microscopy: A Feasibility Study.

OBJECTIVE: The purpose of this study is to detect the hemodynamic changes of microvessels in the early stage of diabetic kidney disease (DKD) and to test the feasibility of ultrasound localization microscopy (ULM) in early diagnosis of DKD. METHODS: In this study, streptozotocin (STZ) induced DKD rat model was used. Normal rats served as the control group. Conventional ultrasound, contrast-enhanced ultrasound (CEUS), and ULM data were collected and analyzed. The kidney cortex was divided into four segments, which are 0.25-0.5 mm (Segment 1), 0.5-0.75 mm (Segment 2), 0.75-1 mm (Segment 3), and 1-1.25 mm (Segment 4) away from the renal capsule, respectively. The mean blood flow velocities of arteries and veins in each segment were separately calculated, and also the velocity gradients and overall mean velocities of arteries and veins. Mann-Whitney U test was used for comparison of the data. RESULTS: Quantitative results of microvessel velocity obtained by ULM show that the arterial velocity of Segments 2, 3, and 4, and the overall mean arterial velocity of the four segments in the DKD group are significantly lower than those in the normal group. The venous velocity of Segment 3 and the overall mean venous velocity of the four segments in the DKD group are higher than those in the normal group. The arterial velocity gradient in the DKD group is lower than that in the normal group. CONCLUSION: ULM can visualize and quantify the blood flow and may be used for early diagnosis of DKD.

High-Quality Ultrafast Power Doppler Imaging Based on Spatial Angular Coherence Factor.

The morphological and hemodynamic changes of microvessels are demonstrated to be related to the diseased conditions in tissues. Ultrafast power Doppler imaging (uPDI) is a novel modality with a significantly increased Doppler sensitivity, benefiting from the ultrahigh frame rate plane-wave imaging (PWI) and advanced clutter filtering. However, unfocused plane-wave transmission often leads to a low imaging quality, which degrades the subsequent microvascular visualization in power Doppler imaging. Coherence factor (CF)-based adaptive beamformers have been widely studied in conventional B-mode imaging. In this study, we propose a spatial and angular coherence factor (SACF) beamformer for improved uPDI (SACF-uPDI) by calculating the spatial CF across apertures and the angular CF across transmit angles, respectively. To identify the superiority of SACF-uPDI, simulations, in vivo contrast-enhanced rat kidney, and in vivo contrast-free human neonatal brain studies were conducted. Results demonstrate that SACF-uPDI can effectively enhance contrast and resolution and suppress background noise simultaneously, compared with conventional uPDI methods based on delay-and-sum (DAS) (DAS-uPDI) and CF (CF-uPDI). In the simulations, SACF-uPDI can improve the lateral and axial resolutions compared with those of DAS-uPDI, from 176 to [Formula: see text] of lateral resolution, and from 111 to [Formula: see text] of axial resolution. In the in vivo contrast-enhanced experiments, SACF achieves 15.14- and 5.6-dB higher contrast-to-noise ratio (CNR), 15.25- and 3.68-dB lower noise power, and 240- and 15- [Formula: see text] narrower full-width at half-maximum (FWHM) than DAS-uPDI and CF-uPDI, respectively. In the in vivo contrast-free experiments, SACF achieves 6.11- and 1.09-dB higher CNR, 11.93- and 4.01-dB lower noise power, and 528- and 160- [Formula: see text] narrower FWHM than DAS-uPDI and CF-uPDI, respectively. In conclusion, the proposed SACF-uPDI method can efficiently improve the microvascular imaging quality and has the potential to facilitate clinical applications.

Unveiling the retrogradation mechanism of a novel high amylose content starch-Pouteria campechiana seed.

The research of starch retrogradation have been attracting interest. Thereby, the long-term retrogradation mechanism (0-21 days) of Pouteria campechiana seed starch (PCSS) was investigated. The results showed that crystal type was changed from A- to B + V-type during retrogradation. The retrogradation PCSS (RPCSS) exhibited faster retrogradation rate and more compact internal ultra-structure compared to rice, wheat and maize starch. Pearson correlation indicated that, as retrogradation days increased, values of α-1,4-glycosidic bond, A chains, double helix, V-type polymorphism, Mw, relative crystallinity (Rc) and short-range order gradually significantly increased, and B1 chains, B3 + chains values gradually significantly dropped (p < 0.05). These inferred an increasing peak temperature and compactness of morphology with increasing retrogradation days. Compared to native starch, RPCSS α-1.4-glycosidic bond was increased, which indicated that its quick molecules degradation including decreased Mw, B3 + chains, Rc, semicrystalline order, and ΔH. These might provide a theoretical direction for preparation of starch-basis food.

Development of chlorine dioxide sustained-release device using carboxymethyl cellulose-polyvinyl alcohol-ß-cyclodextrin ternary hydrogel and a new sustained-release kinetic model.

Owing to unique physiochemical and biological properties as well as the ability to be combined with a wide variety of materials for both biocompatibility and hydrophilia, carboxymethyl cellulose (CMC) is an excellent choice as a carrier. Loading Chlorine dioxide (ClO2) into biodegradable carrier for its good disinfection performance and high safety factors has attracted significantattention. Therefore, in this study, we used ClO2 as a model drug, and a sustained-ClO2-gas-release gel was developed from degradable materials, such as carboxymethyl cellulose (CMC), polyvinyl alcohol (PVA), and ß-cyclodextrin (ßCD), through a simple and benign crosslinking strategy. Notably, the gel had sustained-release property in a wide temperature range of 4-35 â„ƒ and released ClO2 gas effectively for more than 30 days. Furthermore, a loss factor was proposed based on the incomplete release of the drug in the sustained release process to a chieve a good fit with the gas diffusion process. A new diffusion model was designed based on the Korsmeyer-Peppas model, and an excellent fit was obtained. This sustained-ClO2-gas-release gel provides theoretical and technical guidance for the development of sustained-disinfectant-release agents for use in space and offers new insights into the sustained release model of skeleton-soluble hydrogels. Supplementary Information: The online version contains supplementary material available at 10.1007/s10570-023-05070-6.