Contralateral renal change in a unilateral ureteral obstruction rat model using intravoxel incoherent motion diffusion-weighted imaging.

OBJECTIVES: Most functional magnetic resonance research has primarily examined alterations in the affected kidney, often neglecting the contralateral kidney. Our study aims to investigate whether imaging parameters accurately depict changes in both the renal cortex and medulla in a unilateral ureteral obstruction rat model, thereby showcasing the utility of intravoxel incoherent motion (IVIM) in evaluating contralateral renal changes. METHODS: Six rats underwent MR scans and were subsequently sacrificed for baseline histological examination. Following the induction of left ureteral obstruction, 48 rats were scanned, and the histopathological examinations were conducted on days 3, 7, 10, 14, 21, 28, 35, and 42. The apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudodiffusion (D*), and perfusion fraction (f) values were measured using IVIM. RESULTS: On the 10th day of obstruction, both cortical and medullary ADC values differed significantly between the UUO10 group and the sham group (p < 0.01). The cortical D values showed statistically significant differences between UUO3 group and sham group (p < 0.01) but not among UUO groups at other time point. Additionally, the cortical and medullary f values were statistically significant between the UUO21 group and the sham group (p < 0.01). Especially, the cortical f values exhibited significant differences between the UUO21 group and the UUO groups with shorter obstruction time (at time point of 3, 7, 10, 14 day) (p < 0.01). CONCLUSIONS: Significant hemodynamic alterations were observed in the contralateral kidney following renal obstruction. IVIM accurately captures changes in the unobstructed kidney. Particularly, the cortical f value exhibits the highest potential for assessing contralateral renal modifications.

Nanoimprint-induced strain engineering of two-dimensional materials.

The high stretchability of two-dimensional (2D) materials has facilitated the possibility of using external strain to manipulate their properties. Hence, strain engineering has emerged as a promising technique for tailoring the performance of 2D materials by controlling the applied elastic strain field. Although various types of strain engineering methods have been proposed, deterministic and controllable generation of the strain in 2D materials remains a challenging task. Here, we report a nanoimprint-induced strain engineering (NISE) strategy for introducing controllable periodic strain profiles on 2D materials. A three-dimensional (3D) tunable strain is generated in a molybdenum disulfide (MoS2) sheet by pressing and conforming to the topography of an imprint mold. Different strain profiles generated in MoS2 are demonstrated and verified by Raman and photoluminescence (PL) spectroscopy. The strain modulation capability of NISE is investigated by changing the imprint pressure and the patterns of the imprint molds, which enables precise control of the strain magnitudes and distributions in MoS2. Furthermore, a finite element model is developed to simulate the NISE process and reveal the straining behavior of MoS2. This deterministic and effective strain engineering technique can be easily extended to other materials and is also compatible with common semiconductor fabrication processes; therefore, it provides prospects for advances in broad nanoelectronic and optoelectronic devices.

Genome-wide transcriptome profiling of mulberry (Morus alba) response to boron deficiency and toxicity reveal candidate genes associated with boron tolerance in leaves.

Mulberry (Morus alba) is an essential plant with countless economic benefits; however, its growth and metabolic processes are hampered by boron (B) stresses. Very little research has been performed to elucidate boron tolerance and detoxification mechanisms in this species. The M. alba cultivar, Yu-711, was exposed to five different concentrations of boric acid (H3BO3), including deficient (T1; 0 mM) moderate B deficiency (T2; 0.02 mM), sufficient (CK; 0.1 mM) and toxic (T3 and T4; 0.5 and 1 mM) levels for 18 days of growth in pots experiment. Transcriptome analysis of B deficiency and toxicity treatments was performed on mulberry leaves. The transcriptome data reveal that a total of 6114 genes were differentially expressed (DEGs), of which 3830 were up-regulated and 2284 were down-regulated. A comparative analysis between treatment groups CK-vs-T1 (deficiency) and CK-vs-T4 (toxicity) indicates that 590 and 1383 genes were down-regulated in both deficiency and B toxicity, respectively. The results show that 206 genes were differentially expressed in all treatments. B deficiency and toxicity significantly altered the expression of the key aquaporins (PIP2-1, PIP2-7, PIP2-4 and NIP3-1) and high-affinity boron transporter genes (BOR1 and BOR7). In addition, boron stress also altered the expression of antioxidants and photosynthesis-related genes. B stresses were found to alter several transcription factors including ERF1B, which is associated with the regulation of boron uptake and the synthesis and signaling of phytohormones. Unravelling the mechanisms of B tolerance and detoxification is important and would give us further insight into how B stresses affect mulberry plants.

Clinical and imaging predictors for hemorrhagic transformation of acute ischemic stroke after endovascular thrombectomy.

BACKGROUND AND PURPOSE: Hemorrhagic transformation (HT) is a common complication of endovascular thrombectomy (EVT) in patients with acute ischemic stroke (AIS). Our study aims to investigate the clinical and imaging predictors of HT and symptomatic intracranial hemorrhage (sICH) in patients who underwent EVT. METHODS: A retrospective analysis of 118 patients undergoing EVT for acute anterior circulation stroke was performed. Potential clinical and imaging predictors of all patients were collected and multivariate logistic regression was performed. The risk prediction system was constructed according to the multivariate logistic regression results. RESULTS: The incidence of HT and sICH after EVT were 46.6% and 15.3%, respectively. The multivariate logistic regression results showed that Alberta Stroke Program Early CT Score (ASPECTS) (p = .001, odds ratio [OR] = 0.367, 95% [confidence interval] CI, 0.201-0.670), collateral status (p<.001, OR = 0.117, 95% CI, 0.042-0.325), relative cerebral blood flow (CBF) ratio (p = .025, OR = 0.943, 95% CI, 0.895-0.993), and blood glucose on admission (p = .012, OR = 1.258, 95% CI, 1.053-1.504) were associated with HT. While for sICH, collateral circulation (p = .007, OR = 0.148, 95% CI, 0.037-0.589), ASPECTS (p = .033, OR = 0.510, 95% CI, 0.274-0.946), and blood glucose (p = .005, OR = 1.304, 95% CI, 1.082-1.573) were independent factors. The predictive model for HT after EVT was established, and the sensitivity and specificity of it were 90.9% and 79.4%, respectively, with the area under the curve of 90.0% (84.5%-95.4%). CONCLUSION: Collateral status, ASPECTS, relative CBF ratio, and blood glucose on admission were predictors for HT in AIS patients, while collateral status, ASPECTS, and blood glucose on admission were also predictors for sICH. In addition, the established predictive model showed good diagnostic value for prediction of HT after EVT.

The Competing Endogenous RNAs Regulatory Genes Network Mediates Leaf Shape Variation and Main Effector Gene Function in Mulberry Plant (Morus alba).

Mulberry plants (Morus alba) have leaf shapes, ranging from unlobed to lobed, which are crucial for yield, growth, and adaptability, indicating their ability to adapt to their environment. Competing endogenous RNAs (ceRNAs) constitute a web of RNAs within the organism's transcriptional regulatory system, including protein-coding genes (mRNAs), microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and others. In this study, samples for ceRNA sequencing were categorized into two groups: whole leaves and lobed leaves, each group with three replicates. In addition, we isolated, cloned, and characterized the precursor miRNA (miR156x) from the leaves of M. alba. miR156x precursor had a length of 107 base pairs and a minimum folding free energy of 50.27 kcal/mol. We constructed a pCAMBIA-35S-GUS-miR156x dual overexpression vector and established a transient transformation system for mulberry. At an optimal transformation solution (OD600 = 0.7), the GUS gene showed a higher expression in the leaves of transiently transformed mulberry with miR156x overexpression, four days after transformation, while the target genes of miR156x had decreased expression in the same leaves. Investigations into the transgenic mulberry plants uncovered various modifications to physio-chemical parameters including POD, SOD, PRO, MDA, soluble proteins and sugars, and chlorophyl content. miRNAs in the plants were found to act as negative regulators of gene expression in response to changes in leaf shape regulation, which was confirmed in vitro using dual-luciferase reporter assays. Subsequently, we cloned Maspl3 in vitro and conducted GST-Pull down assays, obtaining multiple proteins that interacted with the Maspl3 gene. This indicates that the miR156x/Maspl3/MSTRG.25812.1 regulatory module contributes to the differences in mulberry leaf shape.

Multi-Level Optimization for Data-Driven Camera-LiDAR Calibration in Data Collection Vehicles.

Accurately calibrating camera-LiDAR systems is crucial for achieving effective data fusion, particularly in data collection vehicles. Data-driven calibration methods have gained prominence over target-based methods due to their superior adaptability to diverse environments. However, current data-driven calibration methods are susceptible to suboptimal initialization parameters, which can significantly impact the accuracy and efficiency of the calibration process. In response to these challenges, this paper proposes a novel general model for the camera-LiDAR calibration that abstracts away the technical details in existing methods, introduces an improved objective function that effectively mitigates the issue of suboptimal parameter initialization, and develops a multi-level parameter optimization algorithm that strikes a balance between accuracy and efficiency during iterative optimization. The experimental results demonstrate that the proposed method effectively mitigates the effects of suboptimal initial calibration parameters, achieving highly accurate and efficient calibration results. The suggested technique exhibits versatility and adaptability to accommodate various sensor configurations, making it a notable advancement in the field of camera-LiDAR calibration, with potential applications in diverse fields including autonomous driving, robotics, and computer vision.

The impact of boron nutrient supply in mulberry (Morus alba) response to metabolomics, enzyme activities, and physiological parameters.

Boron (B) is essential for normal and healthy plant growth. Therefore, Boron stress is a common abiotic stress that limits plant growth and productivity. However, how mulberry copes with boron stress remains unclear. In this study, seedlings of the Morus alba cultivar, Yu-711, were treated with five different concentrations of boric acid (H3BO3), including deficient (0 and 0.02 mM), sufficient (0.1 mM) and toxic (0.5 and 1 mM) levels. Physiological parameters, enzymatic activities and non-targeted liquid chromatography-mass spectrometry (LC-MS) technique were employed to evaluate the effects of boron stress on the net photosynthetic rate (Pn), chlorophyll content, stomatal conductance (Gs), transpiration rate (Tr), intercellular CO2 concentration (Ci) and metabolome signatures. Physiological analysis revealed that Boron deficiency and toxicity induced a decline in Pn, Ci, Gs, Tr, and chlorophyll content. Also, enzymatic activities, including catalase (CAT) and superoxide dismutase (SOD), decreased, while POD activity increased in response to Boron stress. Osmotic substances such as soluble sugars, soluble proteins, and proline (PRO) presented elevated levels under all Boron concentrations. Metabolome analysis indicated that differential metabolites, including amino acids, secondary metabolites, carbohydrates, and lipids, played a key role in Yu-711's response to Boron stress. These metabolites were mainly involved in amino acid metabolism, biosynthesis of other secondary metabolites, lipid metabolism, metabolism of cofactors and vitamins, and metabolism of other amino acids pathways. Our findings reveal the various metabolites pathways in mulberry response to boron nutrient supply and may serve as fundamental knowledge in breeding resistance mulberry plants, so that it can cope with climate changes.

A molecular atlas reveals the tri-sectional spinning mechanism of spider dragline silk.

The process of natural silk production in the spider major ampullate (Ma) gland endows dragline silk with extraordinary mechanical properties and the potential for biomimetic applications. However, the precise genetic roles of the Ma gland during this process remain unknown. Here, we performed a systematic molecular atlas of dragline silk production through a high-quality genome assembly for the golden orb-weaving spider Trichonephila clavata and a multiomics approach to defining the Ma gland tri-sectional architecture: Tail, Sac, and Duct. We uncovered a hierarchical biosynthesis of spidroins, organic acids, lipids, and chitin in the sectionalized Ma gland dedicated to fine silk constitution. The ordered secretion of spidroins was achieved by the synergetic regulation of epigenetic and ceRNA signatures for genomic group-distributed spidroin genes. Single-cellular and spatial RNA profiling identified ten cell types with partitioned functional division determining the tri-sectional organization of the Ma gland. Convergence analysis and genetic manipulation further validated that this tri-sectional architecture of the silk gland was analogous across Arthropoda and inextricably linked with silk formation. Collectively, our study provides multidimensional data that significantly expand the knowledge of spider dragline silk generation and ultimately benefit innovation in spider-inspired fibers.

Spatial modulation of nanopattern dimensions by combining interference lithography and grayscale-patterned secondary exposure.

Functional nanostructures are exploited for a variety of cutting-edge fields including plasmonics, metasurfaces, and biosensors, just to name a few. Some applications require nanostructures with uniform feature sizes while others rely on spatially varying morphologies. However, fine manipulation of the feature size over a large area remains a substantial challenge because mainstream approaches to precise nanopatterning are based on low-throughput pixel-by-pixel processing, such as those utilizing focused beams of photons, electrons, or ions. In this work, we provide a solution toward wafer-scale, arbitrary modulation of feature size distribution by introducing a lithographic portfolio combining interference lithography (IL) and grayscale-patterned secondary exposure (SE). Employed after the high-throughput IL, a SE with patterned intensity distribution spatially modulates the dimensions of photoresist nanostructures. Based on this approach, we successfully fabricated 4-inch wafer-scale nanogratings with uniform linewidths of <5% variation, using grayscale-patterned SE to compensate for the linewidth difference caused by the Gaussian distribution of the laser beams in the IL. Besides, we also demonstrated a wafer-scale structural color painting by spatially modulating the filling ratio to achieve gradient grayscale color using SE.