Sub-Nyquist sampling-based high-frequency photoacoustic computed tomography.

High-frequency (greater than 30 MHz) photoacoustic computed tomography (PACT) provides the opportunity to reveal finer details of biological tissues with high spatial resolution. To record photoacoustic signals above 30 MHz, sampling rates higher than 60 MHz are required according to the Nyquist sampling criterion. However, the highest sampling rates supported by existing PACT systems are typically within the range of 40-60 MHz. Herein, we propose a novel PACT imaging method based on sub-Nyquist sampling. The results of numerical simulation, phantom experiment, and in vivo experiment demonstrate that the proposed imaging method can achieve high-frequency PACT imaging with a relatively low sampling rate. An axial resolution of 22 µm is achieved with a 30-MHz transducer and a 41.67-MHz sampling rate. To the best of our knowledge, this is the highest axial resolution ever achieved in PACT based on a sampling rate of not greater than 60 MHz. This work is expected to provide a practical way for high-frequency PACT imaging with limited sampling rates.

Teacher-student guided knowledge distillation for unsupervised convolutional neural network-based speckle tracking in ultrasound strain elastography.

Accurate and efficient motion estimation is a crucial component of real-time ultrasound elastography (USE). However, obtaining radiofrequency ultrasound (RF) data in clinical practice can be challenging. In contrast, although B-mode (BM) data is readily available, elastographic data derived from BM data results in sub-optimal elastographic images. Furthermore, existing conventional ultrasound devices (e.g., portable devices) cannot provide elastography modes, which has become a significant obstacle to the widespread use of traditional ultrasound devices. To address the challenges above, we developed a teacher-student guided knowledge distillation for an unsupervised convolutional neural network (TSGUPWC-Net) to improve the accuracy of BM motion estimation by employing a well-established convolutional neural network (CNN) named modified pyramid warping and cost volume network (MPWC-Net). A pre-trained teacher model based on RF is utilized to guide the training of a student model using BM data. Innovations outlined below include employing spatial attention transfer at intermediate layers to enhance the guidance effect of the model. The loss function consists of smoothness of the displacement field, knowledge distillation loss, and intermediate layer loss. We evaluated our method on simulated data, phantoms, and in vivo ultrasound data. The results indicate that our method has higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) values in axial strain estimation than the model trained on BM. The model is unsupervised and requires no ground truth labels during training, making it highly promising for motion estimation applications.

Effects of different types of Ringer's solution on patients with traumatic haemorrhagic shock: a prospective cohort study.

OBJECTIVE: To compare the fluid resuscitation effect of sodium acetate Ringer's solution and sodium bicarbonate Ringer's solution on patients with traumatic haemorrhagic shock. METHOD: We conducted a prospective cohort study in our emergency department on a total of 71 patients with traumatic haemorrhagic shock admitted between 1 December 2020 and 28 February 2022. Based on the time of admission, patients were randomly divided into a sodium bicarbonate Ringer's solution group and sodium acetate Ringer's solution group, and a limited rehydration resuscitation strategy was adopted in both groups. General data were collected separately, and the patients' vital signs (body temperature, respiration, blood pressure and mean arterial pressure (MAP)), blood gas indices (pH, calculated bicarbonate (cHCO3-), partial pressure of oxygen (PaO2), partial pressure of carbon dioxide (pCO2) and clearance of lactate (CLac)), shock indices, peripheral platelet counts, prothrombin times and plasma fibrinogen levels were measured and compared before and 1 h after resuscitation. RESULTS: The post-resuscitation heart rate of the sodium bicarbonate Ringer's solution group was significantly lower than that of the sodium acetate Ringer's solution group (p < 0.05), and the MAP was also significantly lower (p < 0.05). The patients in the sodium bicarbonate Ringer's solution group had significantly higher pH, cHCO3- and PaO2 values and lower pCO2 and CLac values (p < 0.05) than those in the sodium acetate Ringer's solution group, and the post-resuscitation peripheral platelet counts and fibrinogen levels were significantly higher, with shorter plasma prothrombin times and smaller shock indices (p < 0.001). CONCLUSION: Sodium bicarbonate Ringer's solution is beneficial for maintaining MAP at a low level after resuscitation. The use of sodium bicarbonate Ringer's solution in limited fluid resuscitation has positive results and is of high clinical value.

Blind multi-Poissonian image deconvolution with sparse log-step gradient prior.

Blind image deconvolution plays a very important role in the fields such as astronomical observation and fluorescence microscopy imaging, in which the noise follows Poisson distribution. However, due to the ill-posedness, it is a very challenging task to reach a satisfactory result from a single blurred image especially when the power of the Poisson noise is at a high level. Therefore, in this paper, we try to achieve high-quality restoration results with multi-blurred images which are contaminated by Poisson noise. Firstly, we design a novel sparse log-step gradient prior which adopts a mixture of logarithm and step functions to regularize the image gradients and combine it with the Poisson distribution to formulate the blind multi-image deconvolution problem. Secondly, we incorporate the methods of variable splitting and Lagrange multiplier to convert the original problem into sub-problems, then we alternately solve them to achieve the estimation of all the blur kernels of corresponding blurred images. Besides, we also design a non-blind multi-image deconvolution algorithm which is based on the log-step gradient prior to reach the final restored image. Experimental results on both synthetic and real-world blurred images show that the proposed prior is very capable of suppressing negative artifacts caused by ill-posedness. The algorithm can achieve restored image of very high quality which is competitive with some state-of-the-art methods.

Changes of uterocervical angle and cervical length in early and mid-pregnancy and their value in predicting spontaneous preterm birth.

Objective: To explore the feasibility of transvaginal ultrasound measurement of uterocervical angle (UCA) and cervical length (CL) in early and mid-pregnancy and evaluate their combined prediction of spontaneous preterm birth (sPTB) in singleton pregnancies. Patients and Methods: This retrospective study comprised 274 pregnant women who underwent transvaginal ultrasound measurement of CL in mid-pregnancy (15-23+6 weeks); in 75 among them, CL also had been measured in early-pregnancy (<14 weeks). These 274 pregnant women were further divided into a preterm group (n = 149, <37 weeks gestation) and a control group (n = 125, >37 weeks gestation) according to delivery before or after 37 weeks, respectively. In the preterm group, 35 patients delivered before 34 weeks and the remaining 114 delivered between 34 and 37 weeks. Results: The optimal threshold of CL to predict preterm birth risk in women with <37 weeks gestation was 3.38 cm, and the optimal threshold of the UCA to predict preterm birth risk in the same group of women was 96°. The optimal threshold of CL to predict preterm birth risk in women with <34 weeks gestation was 2.54 cm, while that of the UCA in the same group of patients was 106°. The area under the curve for predicting preterm birth by combining the UCA and CL measurements was greater than that by using the UCA or CL alone (p < 0.01). The sensitivity and specificity for predicting preterm birth at <34 weeks gestation was 71.7% and 86.4%, respectively; and the sensitivity and specificity for predicting preterm birth at <37 weeks gestation was 87.6% and 80.6%, respectively. The difference between the two groups in CL and UCA were not significant in early pregnancy (p > 0.01), but only in mid-pregnancy (p < 0.01). There was a negative correlation between UCA and gestational week at delivery (r = -0.361, p < 0.001) and a positive correlation between CL and gestational week at delivery (r = 0.346, p < 0.001) in mid-pregnancy. The proportion of deliveries at <34 weeks was highest when the UCA was >105°, and the proportion of deliveries between 35 and 37 weeks was highest when the UCA was between 95° and 105°. The proportion of deliveries at <34 weeks was highest when the CL was <2.5 cm. Conclusion: The combination of UCA and CL has a better ability to predict preterm birth than either measurement alone. A more obtuse UCA or a shorter CL is associated with an earlier spontaneous preterm birth. The UCA increases from early to mid-pregnancy, while the CL decreases from early to mid-pregnancy.

Development of a colloidal gold immunochromatographic strip for rapid detection of avian coronavirus infectious bronchitis virus.

Avian infectious bronchitis virus (IBV) still causes serious economic losses in the poultry industry. Currently, there are multiple prevalent genotypes and serotypes of IBVs. It is imperative to develop a new diagnosis method that is fast, sensitive, specific, simple, and broad-spectrum. A monoclonal hybridoma cell, N2D5, against the IBV N protein was obtained after fusion of myeloma SP2/0 cells with spleen cells isolated from the immunized Balb/c mice. The N2D5 monoclonal antibody (mAb) and the previously prepared mouse polyclonal antibody against the IBV N protein were used to target IBV as a colloidal gold-mAb conjugate and a captured antibody, respectively, in order to develop an immunochromatographic strip. The optimal pH and minimum antibody concentration in the reaction system for colloidal gold-mAb N2D5 conjugation were pH 6.5 and 30 µg/mL, respectively. Common avian pathogens were tested to evaluate the specificity of the strip and no cross-reaction was observed. The sensitivity of the strip for detecting IBV was 10-1.4522 EID50/mL. The strip showed a broad-spectrum cross-reactive capacity for detecting IBV antigens, including multiple IBV genotypes in China and all of the seven serotypes of IBV that are currently prevalent in southern China. Additionally, the result can be observed within 2 min without any equipment. The throat and cloacal swab samples of chickens that were artificially infected with three IBV strains were tested using the developed strip and the qPCR method; the strip test demonstrated a high consistency in detecting IBV via qPCR gene detection. In conclusion, the immunochromatographic strip that was established is rapid, sensitive, specific, simple, practical, and broad-spectrum; additionally, it has the potential to serve as an on-site rapid detection method of IBV and can facilitate the surveillance and control of the disease, especially in resource-limited areas.

Fibroblasts/three-dimensional scaffolds complexes promote wound healing in rats with skin defects.

We aim to construct a three-dimensional nano-skin scaffold material in vitro and study its promoting effect on wound healing in vivo. In this study, hybrid constructs of three-dimensional (3D) scaffolds were successfully fabricated by combination of type I collagen (COL-1) and polylactic-glycolic acid (PLGA). Fibroblasts and human umbilical cord mesenchymal stem cells (hUCMSCs) were used to implanted into 3D scaffolds and constructed into SD skin scaffolds in vitro. Finally, the fibroblasts/scaffolds complexes were inoculated on the surface of rat wound skin to study the promoting effect of the complex on wound healing. In our study, we successfully built a 3D scaffold, which had a certain porosity. Meanwhile, the content of COL-1 in the cell supernatant of fibroblast/scaffold complexes was increased. Furthermore, the expression of F-actin, CD105, integrin ß, VEGF, and COL-1 was up-regulated in hUCMSC/scaffold complexes compared with the control group. In vivo, fibroblast/scaffold complexes promoted wound healing in rats. Our data suggested that the collagen Ⅳ and vimentin were elevated and collagen fibers were neatly arranged in the fibroblast/scaffold complex group was significantly higher than that in the scaffold group. Taken together, fibroblast/scaffold complexes were expected to be novel materials for treating skin defects.

Elaboration and validation of a novelty nomogram for the prognostication of anxiety susceptibility in individuals suffering from low back pain.

Low back pain (LBP) constitutes a distressing emotional ordeal and serves as a potent catalyst for adverse emotional states, notably anxiety. We dedicated to discerning methodologies for identifying patients who are predisposed to heightened levels of anxiety and pain. A self-assessment questionnaire was administered to patients afflicted with LBP. The pain scores were subjected to analysis in conjunction with anxiety scores, and a clustering procedure was executed using the scientific k-means methodology. Subsequently, six machine learning algorithms, including Logistics Regression (LR), K-Nearest Neighbor (KNN), Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGB), were employed. Next, five pertinent variables were identified, namely Age, Course, Body Mass Index (BMI), Education, and Marital status. Furthermore, a LR model was utilized to construct a nomogram, which was subsequently subjected to assessment for discrimination, calibration, and evaluation of its clinical utility. As a result, 599 questionnaires were valid (effective rate: 99 %). The correlation analysis revealed a significant association between anxiety and pain scores (r = 0.31, P < 0.001). LBP patients could be divided into two clusters, Cluster1 had higher pain scores (P < 0.05) and SAS scores (P < 0.001). The proposed nomogram demonstrated an area under the receiver operating characteristics curve (ROC) of 0.841 (95 %CI: 0.804-0.878) and 0.800 (95 %CI: 0.733-0.867) in the training and test groups, respectively. Briefly, the established nomogram has demonstrated remarkable proficiency in discerning individuals afflicted with LBP who are at a heightened risk of experiencing anxiety.

Influences of shallow groundwater depth on N2O diffusion along the soil profile of summer maize fields in North China Plain.

The emissions of nitrous oxide (N2O) from agricultural fields are a significant contribution to global warming. Understanding the mechanisms of N2O emissions from agricultural fields is essential for the development of N2O emission mitigation strategies. Currently, there are extensive studies on N2O emissions on the surface of agricultural soils, while studies on N2O fluxes at the interface between the saturated and unsaturated zones (ISU) are limited. Uncertainties exist regarding N2O emissions from the soil-shallow groundwater systems in agricultural fields. In this study, a three-year lysimeter experiment (2019-2020, 2022) was conducted to simulate the soil-shallow groundwater systems under four controlled shallow groundwater depth (SGD) (i.e., SGD = 40, 70, 110, and 150 cm) conditions in North China Plain (NCP). Weekly continuous monitoring of N2O emissions from soil surface, N2O concentration in the shallow groundwater and the upper 10 cm of pores at the ISU, and nitrogen cycling-related parameters in the soil and groundwater was conducted. The results showed that soil surface N2O emissions increased with decreased shallow groundwater depth, and the highest emissions of 96.44 kg ha-1 and 104.32 kg ha-1 were observed at G2 (SGD = 40 cm) in 2020 and 2022. During the observation period of one maize growing season, shallow groundwater acted as a sink for the unsaturated zone when the groundwater depth was 40 cm, 70 cm, and 110 cm. However, when SGD was 150 cm, shallow groundwater became a source for the unsaturated zone. After fertilization, the groundwater in all treatment plots behaved as a sink for the unsaturated zone, and the diffusion intensity decreased with increasing SGD. The results would provide a theoretical basis for cropland water management to reduce N2O emissions.

Genome-wide association study identifies new loci associated with OCD.

To date, four genome-wide association studies (GWAS) of obsessive-compulsive disorder (OCD) have been published, reporting a high single-nucleotide polymorphism (SNP)-heritability of 28% but finding only one significant SNP. A substantial increase in sample size will likely lead to further identification of SNPs, genes, and biological pathways mediating the susceptibility to OCD. We conducted a GWAS meta-analysis with a 2-3-fold increase in case sample size (OCD cases: N = 37,015, controls: N = 948,616) compared to the last OCD GWAS, including six previously published cohorts (OCGAS, IOCDF-GC, IOCDF-GC-trio, NORDiC-nor, NORDiC-swe, and iPSYCH) and unpublished self-report data from 23andMe Inc. We explored the genetic architecture of OCD by conducting gene-based tests, tissue and celltype enrichment analyses, and estimating heritability and genetic correlations with 74 phenotypes. To examine a potential heterogeneity in our data, we conducted multivariable GWASs with MTAG. We found support for 15 independent genome-wide significant loci (14 new) and 79 protein-coding genes. Tissue enrichment analyses implicate multiple cortical regions, the amygdala, and hypothalamus, while cell type analyses yielded 12 cell types linked to OCD (all neurons). The SNP-based heritability of OCD was estimated to be 0.08. Using MTAG we found evidence for specific genetic underpinnings characteristic of different cohort-ascertainment and identified additional significant SNPs. OCD was genetically correlated with 40 disorders or traits-positively with all psychiatric disorders and negatively with BMI, age at first birth and multiple autoimmune diseases. The GWAS meta-analysis identified several biologically informative genes as important contributors to the aetiology of OCD. Overall, we have begun laying the groundwork through which the biology of OCD will be understood and described.

On the imaging depth limit of photoacoustic tomography in the visible and first near-infrared windows.

It is well known that photoacoustic tomography (PAT) can circumvent the photon scattering problem in optical imaging and achieve high-contrast and high-resolution imaging at centimeter depths. However, after two decades of development, the long-standing question of the imaging depth limit of PAT in biological tissues remains unclear. Here we propose a numerical framework for evaluating the imaging depth limit of PAT in the visible and the first near-infrared windows. The established framework simulates the physical process of PAT and consists of seven modules, including tissue modelling, photon transportation, photon to ultrasound conversion, sound field propagation, signal reception, image reconstruction, and imaging depth evaluation. The framework can simulate the imaging depth limits in general tissues, such as the human breast, the human abdomen-liver tissues, and the rodent whole body and provide accurate evaluation results. The study elucidates the fundamental imaging depth limit of PAT in biological tissues and can provide useful guidance for practical experiments.

Decreased plasma miR-140-3p is associated with coronary artery disease.

Background: Although many circulating miRNAs (c-miRNAs) are associated with coronary artery disease (CAD), they are far from being the biomarker for CAD diagnosis or risk prediction. Therefore, novel c-miRNAs discovery and validation are still required, especially evaluating their prediction capacity. Objectives: Identify novel CAD-related c-miRNAs and evaluate its risk prediction capacity for CAD. Methods: miRNAs associated with CAD were preliminarily investigated in three paired samples representing pre-CAD stage and CAD stage of three female individuals using the Applied Biosystems miRNA TaqMan® Low-Density Array (TLDA). Then, the candidate miRNAs were further verified in an independent case-control study including 129 CAD patients and 76 controls, and their potential practical value in prediction for CAD was evaluated using a machine learning (ML) algorithm. The accuracy of classification and prediction was assessed with the area under the receiver operating characteristic curve (AUC). Results: TLDA analysis shows that miR-140-3p decreased significantly in CAD-stage (FC = -3.01, P = 0.007). Further study shows that miR-140-3p was significantly lower in CAD group [1.26 (0.68, 2.01)] than in control group [2.07 (1.19, 3.21)] (P < 0.001) and independently associated with CAD (P < 0.001). The addition of miR-140-3p to the variables including smoking history, HDL-c, and APOA1 improved the accuracy of classification by logistic regression and of prediction for CAD by ML models. The ML models built with miR-140-3p and HDL-c, respectively, had a similar prediction accuracy. The feature importance of miR-140-3p and HDL-c in the ML models was also similar. Decision curve analysis showed that miR-140-3p and HDL-c had almost identical net benefits. Conclusion: Reduced levels of miR-140-3p is linked to CAD, and it is possible to use the plasma level of miR-140-3p as a means of evaluating the risk of CAD.

[Efficiency Characteristics and Evolution Patterns of Urban Carbon Metabolism of Production-Living-Ecological Space in Beijing-Tianjin-Hebei Region].

This study explored the carbon metabolism efficiency of a production-living-ecological space system, which is of great significance for regional factor integration and spatial optimization. In this study, the material flow analysis method was introduced to establish a framework for evaluating the carbon metabolism efficiency of the production-living-ecological space system, and the super-efficiency DEA model and Malmquist index were used to empirically analyze the spatio-temporal distribution, dynamic change, and evolution patterns of the carbon metabolism efficiency of production-living-ecological space in the Beijing-Tianjin-Hebei Region, China, from 2000 to 2020 on the basis of the urban metabolic perspective. The results showed that:① the carbon metabolism efficiency of the production-living-ecological space showed a fluctuating growth trend, indicating the significant spatial differentiation of carbon metabolism efficiency in each city. There was a low overall carbon metabolism efficiency level, with a distribution pattern of being high in the middle and low in the north and south. ② The Malmquist index showed that the Total Factor Productivity (TFP) of carbon metabolism efficiency was greater than 1, and both the Technical Change (TC) and Pure Efficiency Change (PEC) were less than 1, in which the TFP showed an increasing trend, whereas there was no significant contribution of technological progress or pure technical efficiency to carbon metabolism efficiency. The total factor productivity of more than 50% of the cities showed an improving trend, only 38.46% of which made technological progress in improving carbon metabolism efficiency, and more than half of the urban pure technical efficiency showed a decreasing trend, in which the technical efficiency change and scale efficiency change were greater than 1 in most cities. ③ There were different types of carbon efficiency characteristics in each city, and according to the movement rules of the corresponding points in the quartile map, the evolution patterns of tourism industry efficiency were classified into stable, reciprocating, progressive, and abrupt. Therefore, local governments should adopt differentiated strategies to reasonably allocate spatial resources of production-living-ecological space and improve the technical level and scale efficiency, so as to improve the efficiency of urban carbon metabolism.

A co-assembly platform engaging macrophage scavenger receptor A for lysosome-targeting protein degradation.

Targeted degradation of proteins has emerged as a powerful method for modulating protein homeostasis. Identification of suitable degraders is essential for achieving effective protein degradation. Here, we present a non-covalent degrader construction strategy, based on a modular supramolecular co-assembly system consisting of two self-assembling peptide ligands that bind cell membrane receptors and the protein of interest simultaneously, resulting in targeted protein degradation. The developed lysosome-targeting co-assemblies (LYTACAs) can induce lysosomal degradation of extracellular protein IL-17A and membrane protein PD-L1 in several scavenger receptor A-expressing cell lines. The IL-17A-degrading co-assembly has been applied in an imiquimod-induced psoriasis mouse model, where it decreases IL-17A levels in the skin lesion and alleviates psoriasis-like inflammation. Extending to asialoglycoprotein receptor-related protein degradation, LYTACAs have demonstrated the versatility and potential in streamlining degraders for extracellular and membrane proteins.

Point spread function modeling for photoacoustic tomography - I: three-dimensional detection geometries.

Photoacoustic computed tomography (PACT) has been under intensive investigation as a promising noninvasive biomedical imaging modality. Various acoustic detector arrays have been developed to achieve enhanced imaging performance. In this paper, we study the effect of the detection geometry on image quality through point spread function (PSF) modeling based on back-projection image reconstruction. Three commonly-used three-dimensional detection geometries, namely, spherical, cylindrical, and planar detector arrays, are investigated. The effect of detector bandwidth and aperture on PSF in these detection geometries is also studied. This work provides a performance evaluation tool for acoustic detector arrays used in PACT and can be helpful in the design and selection of detector arrays in practical imaging applications.

Point spread function modeling for photoacoustic tomography - II: two-dimensional detection geometries.

Point spread function (PSF) modeling is important for the characterization of the imaging performance of a photoacoustic computed tomography (PACT) system. This work aims to study the degradation mechanism of PSF in PACT and investigate the impact of the shape of detection geometry on PSF. PSF modeling of three typical two-dimensional detection geometries, including circular, curved, and linear detector arrays, is presented. Based on the non-ideal detection geometries, the effect of detector bandwidth and detector aperture on PSF is also investigated. Moreover, PSFs of each geometry with typical detector bandwidths and typical detector aperture sizes are presented. Experiments are conducted to validate the results. The proposed PSF modeling approach and corresponding results can help predict and interpret the quality of photoacoustic images produced by a practical PACT system. It is beneficial for the design of detector arrays for enhanced imaging performance.

The Transcriptome Analysis of Circular RNAs between the Doxorubicin-Induced Cardiomyocytes and Bone Marrow Mesenchymal Stem Cells-Derived Exosomes Treated Ones.

AIM: To analyze the sequencing results of circular RNAs (circRNAs) in cardiomyocytes between the doxorubicin (DOX)-injured group and exosomes treatment group. Moreover, to offer potential circRNAs possibly secreted by exosomes mediating the therapeutic effect on DOXinduced cardiotoxicity for further study. MATERIALS & METHODS: The DOX-injured group (DOX group) of cardiomyocytes was treated with DOX, while an exosomes-treated group of injured cardiomyocytes were cocultured with bone marrow mesenchymal stem cells (BMSC)-derived exosomes (BEC group). The high-throughput sequencing of circRNAs was conducted after the extraction of RNA from cardiomyocytes. The differential expression of circRNA was analyzed after identifying the number, expression, and conservative of circRNAs. Then, the target genes of differentially expressed circRNAs were predicted based on the targetscan and Miranda database. Next, the GO and KEGG enrichment analyses of target genes of circRNAs were performed. The crucial signaling pathways participating in the therapeutic process were identified. Finally, a real-time quantitative polymerase chain reaction experiment was conducted to verify the results obtained by sequencing. RESULTS: Thirty-two circRNAs are differentially expressed between the two groups, of which twenty-three circRNAs were elevated in the exosomes-treated group (BEC group). The GO analysis shows that target genes of differentially expressed circRNAs are mainly enriched in the intracellular signalactivity, regulation of nucleic acid-templated transcription, Golgi-related activity, and GTPase activator activity. The KEGG analysis displays that they were involved in the autophagy biological process and NOD-like receptor signaling pathway. The verification experiment suggested that mmu_circ_0000425 (ID: 116324210) was both decreased in the DOX group and elevated in BEC group, which was consistent with the result of sequencing. CONCLUSION: mmu_circ_0000425 in exosomes derived from bone marrow mesenchymal stem cells (BMSC) may have a therapeutic role in alleviating doxorubicin-induced cardiotoxicity (DIC).

Identification of HSP90B1 in pan-cancer hallmarks to aid development of a potential therapeutic target.

Heat shock proteins play crucial roles in various biochemical processes, encompassing protein folding and translocation. HSP90B1, a conserved member of the heat shock protein family, growing evidences have demonstrated that it might be closely associated with cancer development. In the present study, we employed multi-omics analyses and cohort validations to explore the dynamic expression of HSP90B1 in pan-cancer and comprehensively evaluate HSP90B1 as a novel biomarker that hold promise for precision cancer diagnostics and therapeutics. The results suggest HSP90B1 was highly expressed in various kinds of tumors, often correlating with a poor prognosis. Notably, methylation of HSP90B1 emerged as a protective factor in several cancer types. In immune infiltration analysis, the expression of HSP90B1 in most tumors showed a negative association with CD8 + T cells. HSP90B1 expression was positively correlated with microsatellite instability and tumor mutational burden. HSP90B1 expression was also discovered to be positively correlated with tumor metabolism, cell cycle-related pathways and the expression of immune checkpoint genes. The expression of HSP90B1 was mainly negatively correlated with immunostimulatory genes and positively correlated with immunosuppressive genes, as well as strongly correlated with chemokines and their receptor genes. In addition, the HSP90B1 inhibitor PU-WS13 demonstrated significant efficacy in suppressing cancer cell proliferation in both leukemic and solid tumor cells, and remarkably reduced the expression of the cancer cell surface immune checkpoint PD-L1. The single-cell RNA sequencing analysis further highlighted that HSP90B1 was significantly higher in tumor cells compared to surrounding cells, revealing a potential target therapeutic window. Taken together, HSP90B1 emerges as a promising avenue for breakthroughs in cancer diagnosis, prognosis and therapy. This study provides a rationale for HSP90B1 targeted cancer diagnosis and therapy in future.

Non-negligible N2O emission hotspots: Rivers impacted by ion-adsorption rare earth mining.

Rare earth mining causes severe riverine nitrogen pollution, but its effect on nitrous oxide (N2O) emissions and the associated nitrogen transformation processes remain unclear. Here, we characterized N2O fluxes from China's largest ion-adsorption rare earth mining watershed and elucidated the mechanisms that drove N2O production and consumption using advanced isotope mapping and molecular biology techniques. Compared to the undisturbed river, the mining-affected river exhibited higher N2O fluxes (7.96 ± 10.18 mmol m-2d-1 vs. 2.88 ± 8.27 mmol m-2d-1, P = 0.002), confirming that mining-affected rivers are N2O emission hotspots. Flux variations scaled with high nitrogen supply (resulting from mining activities), and were mainly attributed to changes in water chemistry (i.e., pH, and metal concentrations), sediment property (i.e., particle size), and hydrogeomorphic factors (e.g., river order and slope). Coupled nitrification-denitrification and N2O reduction were the dominant processes controlling the N2O dynamics. Of these, the contribution of incomplete denitrification to N2O production was greater than that of nitrification, especially in the heavily mining-affected reaches. Co-occurrence network analysis identified Thiomonas and Rhodanobacter as the key genus closely associated with N2O production, suggesting their potential roles for denitrification. This is the first study to elucidate N2O emission and influential mechanisms in mining-affected rivers using combined isotopic and molecular techniques. The discovery of this study enhances our understanding of the distinctive processes driving N2O production and consumption in highly anthropogenically disturbed aquatic systems, and also provides the foundation for accurate assessment of N2O emissions from mining-affected rivers on regional and global scales.

Spatial and channel attention-based conditional Wasserstein GAN for direct and rapid image reconstruction in ultrasound computed tomography.

Ultrasound computed tomography (USCT) is an emerging technology that offers a noninvasive and radiation-free imaging approach with high sensitivity, making it promising for the early detection and diagnosis of breast cancer. The speed-of-sound (SOS) parameter plays a crucial role in distinguishing between benign masses and breast cancer. However, traditional SOS reconstruction methods face challenges in achieving a balance between resolution and computational efficiency, which hinders their clinical applications due to high computational complexity and long reconstruction times. In this paper, we propose a novel and efficient approach for direct SOS image reconstruction based on an improved conditional generative adversarial network. The generator directly reconstructs SOS images from time-of-flight information, eliminating the need for intermediate steps. Residual spatial-channel attention blocks are integrated into the generator to adaptively determine the relevance of arrival time from the transducer pair corresponding to each pixel in the SOS image. An ablation study verified the effectiveness of this module. Qualitative and quantitative evaluation results on breast phantom datasets demonstrate that this method is capable of rapidly reconstructing high-quality SOS images, achieving better generation results and image quality. Therefore, we believe that the proposed algorithm represents a new direction in the research area of USCT SOS reconstruction.