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Flexible surface acoustic wave technology has garnered significant attention for wearable electronics and sensing applications. However, the mechanical strains induced by random deformation of these flexible SAWs during sensing often significantly alter the specific sensing signals, causing critical issues such as inconsistency of the sensing results on a curved/flexible surface. To address this challenge, we first developed high-performance AlScN piezoelectric film-based flexible SAW sensors, investigated their response characteristics both theoretically and experimentally under various bending strains and UV illumination conditions, and achieved a high UV sensitivity of 1.71 KHz/(mW/cm²). To ensure reliable and consistent UV detection and eliminate the interference of bending strain on SAW sensors, we proposed using key features within the response signals of a single flexible SAW device to establish a regression model based on machine learning algorithms for precise UV detection under dynamic strain disturbances, successfully decoupling the interference of bending strain from target UV detection. The results indicate that under strain interferences from 0 to 1160 με the model based on the extreme gradient boosting algorithm exhibits optimal UV prediction performance. As a demonstration for practical applications, flexible SAW sensors were adhered to four different locations on spacecraft model surfaces, including flat and three curved surfaces with radii of curvature of 14.5, 11.5, and 5.8 cm. These flexible SAW sensors demonstrated high reliability and consistency in terms of UV sensing performance under random bending conditions, with results consistent with those on a flat surface. [ABSTRACT FROM AUTHOR]

Objective: Portal hypertension leads to hepatic artery dilatation and a higher risk of bleeding. We tried to identify the bleeding risk after gastroesophageal varices (GOV) treatment using hepatic artery diameter of contrast-enhanced CT. Methods: Retrospective retrieval of 258 patients with cirrhosis who underwent contrast-enhanced CT from January 2022 to May 2023 and endoscopy within one month thereafter at Hainan Affiliated Hospital of Hainan Medical University. Cirrhotic patients before GOV treatment were used as the test cohort (n = 199), and cirrhotic patients after GOV treatment were used as the validation cohort (n = 59). The grading and bleeding risk was classified according to the endoscopic findings. Arterial-phase images of contrast-enhanced CT were used for coronal reconstruction, and the midpoint diameter of the hepatic artery was measured on coronal images. The optimal cutoff value for identifying bleeding risk was analyzed and calculated in the test cohort, and its diagnostic performance was evaluated in the validation cohort. Results: In the test cohort, hepatic artery diameters were significantly higher in high-risk GOV than in low-risk GOV [4.69 (4.31, 5.56) vs. 3.10 (2.59, 3.77), P < 0.001]. With a hepatic artery diameter cutoff value of 4.06 mm, the optimal area under the operating characteristic curve was 0.940 (95% confidence interval: 0.908–0.972), with a sensitivity of 0.887, a specificity of 0.892, a positive predictive value of 0.904, and a negative predictive value of 0.874 for identifying bleeding risk in the test cohort, while in the validation cohort, the sensitivity was 0.885, specificity was 0.939, positive predictive value was 0.920, and negative predictive value was 0.912. Conclusion: Hepatic artery diameter has high diagnostic performance in identifying bleeding risk after GOV treatment. [ABSTRACT FROM AUTHOR]

Reconfigurable devices can be used to achieve multiple logic operation and intelligent optical sensing with low power consumption, which is promising candidates for new generation electronic and optoelectronic integrated circuits. However, the versatility is still limited and need to be extended by the device architectures design. Here, we report an asymmetrically gate two-dimensional (2D) van der Waals heterostructure with hybrid dielectric layer SiO2/hexagonal boron nitride (h-BN), which enable rich function including reconfigurable logic operation and in-sensor information encryption enabled by both volatile and nonvolatile optoelectrical modulation. When the partial gate is grounded, the non-volatile light assisted electrostatic doping endowed partially reconfigurable doping between n-type and p-type, which allow the switching of logic XOR and not implication (NIMP). When the global gate is grounded, additionally taking the optical signal as another input signal, logic AND and OR is realized by combined regulation of the light and localized gate voltage. Depending on the high on/off current ratio approaching 105 and reliable & switchable logic gate, in-sensor information encryption and decryption is demonstrated by manipulating the logic output. Hence, these results provide strong extension for current reconfigurable electronic and optoelectronic devices. [ABSTRACT FROM AUTHOR]

Background: Abnormal white matter has been reported in patients with end-stage renal disease (ESRD). However, few studies have investigated the relationship between specific damage segments and cognition in ESRD. This study aimed to delineate white matter alterations in ESRD and its relationship with cognition. Methods: A total of 36 patients undergoing hemodialysis and 25 healthy controls underwent diffusion tensor imaging (DTI) and a series of neuropsychiatric tests. Automated fiber quantification was used to extract distinct DTI indices, and the relationship between the specific segment of the white matter and clinical properties was investigated. Furthermore, a support vector machine was applied to differentiate patients with ESRD from healthy controls. Results: Fractional anisotropy values decreased in multiple fiber bundles, including bilateral thalamic radiata, cingulum cingulate, inferior fronto-occipital fasciculus (IFOF), uncinate, Callosum_Forceps_Major/Callosum_Forceps_Minor (CFMaj/CFMin), and left uncinate from the tract level in patients with ESRD. Specific damaged segments were detected in 8 fiber bundles, including bilateral thalamic radiation, cingulum cingulate, IFOF, CFMin, and left corticospinal tract. Few alterations in these fiber bundles were correlated with cognition impairment and hemoglobin levels. The tract profiles of the left thalamic radiata and left cingulum cingulate could be used to differentiate hemodialysis patients from healthy controls, with an accuracy of 76.9% and 67.6%, respectively. Conclusions: This study revealed white matter damage in hemodialysis patients. This damage occurred in specific segments of the tract, especially in the left thalamic radiata and left cingulum cingulate, which might become a new biomarker for patients with ESRD and cognition impairment. [ABSTRACT FROM AUTHOR]

Super typhoons can lead to post-traumatic stress disorder (PTSD), which can adversely affect a person's mental health after a disaster. Neuroimaging studies suggest that patients with PTSD may have post-exposure abnormalities of the white matter. However, little is known about these defects, if they are localized to specific regions of the white matter fibers, or whether they may be potential biomarkers for PTSD. Typhoon survivors with PTSD (n = 27), trauma-exposed controls (TEC) (n = 33), and healthy controls (HCs) (n = 30) were enrolled. We used automated fiber quantification (AFQ) to process the participants' DTI and compared diffusion metrics among the three groups. To evaluate diagnostic value, we used support vector machine (SVM) and a random forest (RF) classifier to build a machine learning model. White matter fiber segmentation between the three groups was found to be statistically significant for the fractional anisotropy (FA) value of the right anterior thalamic radiation (ATR) (26—50 nodes) and right uncinate fasciculus (UF) (60—72 nodes) (FDR correction, p < 0.05). By analyzing the characteristics of the machine learning model, the two most important variables were the right ATR and right UF for differentiating PTSD and trauma-exposed controls (TEC) from the healthy controls (HC). In addition, the left cingulum cingulate and left UF were the most critical variables in the differentiation of PTSD and TEC. AFQ with machine learning can localize abnormalities in specific regions of white matter fibers. These regions may be used as a diagnostic biomarker for PTSD. [ABSTRACT FROM AUTHOR]

Purpose: To build an automatic computer-aided diagnosis (CAD) pipeline based on multiparametric magnetic resonance imaging (mpMRI) and explore the role of different imaging features in the classification of breast cancer. Materials and methods: A total of 222 histopathology-confirmed breast lesions, together with their BI-RADS scores, were included in the analysis. The cohort was randomly split into training (159) and test (63) cohorts, and another 50 lesions were collected as an external cohort. An nnUNet-based lesion segmentation model was trained to automatically segment lesion ROI, from which radiomics features were extracted for diffusion-weighted imaging (DWI), T2-weighted imaging (T2WI), and contrast-enhanced (DCE) pharmacokinetic parametric maps. Models based on combinations of sequences were built using support vector machine (SVM) and logistic regression (LR). Also, the performance of these sequence combinations and BI-RADS scores were compared. The Dice coefficient and AUC were calculated to evaluate the segmentation and classification results. Decision curve analysis (DCA) was used to assess clinical utility. Results: The segmentation model achieved a Dice coefficient of 0.831 in the test cohort. The radiomics model used only three features from diffusion coefficient (ADC) images, T2WI, and DCE-derived kinetic mapping, and achieved an AUC of 0.946 [0.883–0.990], AUC of 0.842 [0.6856–0.998] in the external cohort, which was higher than the BI-RADS score with an AUC of 0.872 [0.752–0.975]. The joint model using both radiomics score and BI-RADS score achieved the highest test AUC of 0.975 [0.935–1.000], with a sensitivity of 0.920 and a specificity of 0.923. Conclusion: Three radiomics features can be used to construct an automatic radiomics-based pipeline to improve the diagnosis of breast lesions and reduce unnecessary biopsies, especially when using jointly with BI-RADS scores. [ABSTRACT FROM AUTHOR]

Surface acoustic wave (SAW) technology has been widely developed for ultraviolet (UV) detection due to its advantages of miniaturization, portability, potential to be integrated with microelectronics, and passive/wireless capabilities. To enhance UV sensitivity, nanowires (NWs), such as ZnO, are often applied to enhance SAW-based UV detection due to their highly porous and interconnected 3D network structures and good UV sensitivity. However, ZnO NWs are normally hydrophilic, and thus, changes in environmental parameters such as humidity will significantly influence the detection precision and sensitivity of SAW-based UV sensors. To solve this issue, in this work, we proposed a new strategy using ZnO NWs wrapped with hydrophobic silica nanoparticles as the effective sensing layer. Analysis of the distribution and chemical bonds of these hydrophobic silica nanoparticles showed that numerous C-F bonds (which are hydrophobic) were found on the surface of the sensitive layer, which effectively blocked the adsorption of water molecules onto the ZnO NWs. This new sensing layer design minimizes the influence of humidity on the ZnO NW-based UV sensor within the relative humidity range of 10–70%. The sensor showed a UV sensitivity of 9.53 ppm (mW/cm2)−1, with high linearity (R2 value of 0.99904), small hysteresis (<1.65%) and good repeatability. This work solves the long-term dilemma of ZnO NW-based sensors, which are often sensitive to humidity changes. [ABSTRACT FROM AUTHOR]

There are great concerns for sensing using flexible acoustic wave sensors and lab-on-a-chip, as mechanical strains will dramatically change the sensing signals (e.g., frequency) when they are bent during measurements. These strain-induced signal changes cannot be easily separated from those of real sensing signals (e.g., humidity, ultraviolet, or gas/biological molecules). Herein, we proposed a new strategy to minimize/eliminate the effects of mechanical bending strains by optimizing off-axis angles between the direction of bending deformation and propagation of acoustic waves on curved surfaces of layered piezoelectric film/flexible glass structure. This strategy has theoretically been proved by optimization of bending designs of off-axis angles and acoustically elastic effect. Proof-of-concept for humidity and ultraviolet-light sensing using flexible SAW devices with negligible interferences are achieved within a wide range of bending strains. This work provides the best solution for achieving high-performance flexible acoustic wave sensors under deformed/bending conditions. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the capacity of ultrashort echo time (UTE) T1 mapping to non-invasively assess gadolinium deposition in cortical bone after gadolinium-based contrast agent (GBCA) administration. Methods: Twenty-eight New Zealand rabbits (male, 3.0–3.5 kg) were randomly allocated into control, macrocyclic, high-dose macrocyclic, and linear GBCA groups (n = 7 for each group), and respectively given daily doses of 0.9 ml/kg bodyweight saline, 0.3 mmol/kg bodyweight gadobutrol, 0.9 mmol/kg bodyweight gadobutrol, and 0.3 mmol/kg bodyweight gadopentetate dimeglumine for five consecutive days per week over a period of 4 weeks. After a subsequent 4 weeks of recovery, the rabbits were sacrificed and their tibiae harvested. T1 value of cortical bone was measured using a combination of UTE actual flip angle imaging and variable repetition time on a 7T animal scanner. Gadolinium concentration in cortical bone was measured using inductively coupled plasma mass spectrometry (ICP-MS). Pearson's correlation between R1 value (R1 = 1/T1) and gadolinium concentration in cortical bone was assessed. Results: Bone T1 values were significantly lower in the lower-dose macrocyclic (329.2 ± 21.0 ms, p < 0.05), higher-dose macrocyclic (316.8 ± 21.7 ms, p < 0.01), and linear (296.8 ± 24.1 ms, p < 0.001) GBCA groups compared with the control group (356.3 ± 19.4 ms). Gadolinium concentrations measured by ICP-MS in the control, lower-dose macrocyclic, higher-dose macrocyclic, and linear GBCA groups were 0.04 ± 0.02 μg/g, 2.60 ± 0.48 μg/g, 4.95 ± 1.17 μg/g, and 13.62 ± 1.55 μg/g, respectively. There was a strong positive correlation between R1 values and gadolinium concentrations in cortical bone (r = 0.73, p < 0.001). Conclusions: These results suggest that UTE T1 mapping has the potential to provide a non-invasive assessment of gadolinium deposition in cortical bone following GBCA administration. Key Points: • Changes in T1value related to gadolinium deposition were found in bone after both linear and macrocyclic GBCA administrations. • R1relaxometry correlates strongly with gadolinium concentration in cortical bone. • UTE T1mapping provides a potential tool for non-invasively monitoring gadolinium deposition in cortical bone. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the efficacy of quantitative susceptibility mapping (QSM) in the assessment of osteoporosis for postmenopausal women.Methods: Between May and September 2017, a total of 70 postmenopausal women who underwent MRI-based QSM and quantitative computed tomography (QCT) were consecutively enrolled in this prospective study. The measurement of QSM and QCT values was performed on the L3 vertebrae body. On the basis of QCT value, all individuals were divided into three groups (normal, osteopenia and osteoporosis).Results: On the basis of QCT, 18 individuals were normal (25.7%), 26 osteopenic (37.1%) and 26 osteoporotic (37.1%). The QSM value was age-related (p = 0.04) and significantly higher in the osteoporosis group than in either the normal or osteopenia group (for all, p < 0.001). In addition, the QSM value was highly correlated with QCT value (r = - 0.720, p < 0.001). For QSM, the area under the curve (AUC), sensitivity and specificity for differentiating osteopenia from non-osteopenia were 0.88, 86.5% and 77.8%, respectively, and for differentiating osteoporosis from non-osteoporosis they were 0.86, 80.8% and 77.3%, respectively.Conclusions: MRI-based QSM could be used for quantifying susceptibility in vertebrae and has the potential to be a new biomarker in the assessment of osteoporosis for postmenopausal women.Key Points: • Osteoporosis significantly increases risk of fracture for postmenopausal women. • QSM value was correlated with QCT value (r = - 0.72, p < 0.001). • QSM is feasible in the assessment of osteoporosis for postmenopausal women. • QSM offers the quantification of susceptibility within bone. [ABSTRACT FROM AUTHOR]