Smooth-Guided Implicit Data Augmentation for Domain Generalization.

The training process of a domain generalization (DG) model involves utilizing one or more interrelated source domains to attain optimal performance on an unseen target domain. Existing DG methods often use auxiliary networks or require high computational costs to improve the model's generalization ability by incorporating a diverse set of source domains. In contrast, this work proposes a method called Smooth-Guided Implicit Data Augmentation (SGIDA) that operates in the feature space to capture the diversity of source domains. To amplify the model's generalization capacity, a distance metric learning (DML) loss function is incorporated. Additionally, rather than depending on deep features, the suggested approach employs logits produced from cross entropy (CE) losses with infinite augmentations. A theoretical analysis shows that logits are effective in estimating distances defined on original features, and the proposed approach is thoroughly analyzed to provide a better understanding of why logits are beneficial for DG. Moreover, to increase the diversity of the source domain, a sampling-based method called smooth is introduced to obtain semantic directions from interclass relations. The effectiveness of the proposed approach is demonstrated through extensive experiments on widely used DG, object detection, and remote sensing datasets, where it achieves significant improvements over existing state-of-the-art methods across various backbone networks.

Risk factors and early prediction of cardiorenal syndrome type 3 among acute kidney injury patients: a cohort study.

BACKGROUND: Type 3 cardiorenal syndrome (CRS type 3) triggers acute cardiac injury from acute kidney injury (AKI), raising mortality in AKI patients. We aimed to identify risk factors for CRS type 3 and develop a predictive nomogram. METHODS: In this retrospective study, 805 AKI patients admitted at the Department of Nephrology, Second Hospital of Shanxi Medical University from 1 January 2017, to 31 December 2021, were categorized into a study cohort (406 patients from 2017.1.1-2021.6.30, with 63 CRS type 3 cases) and a validation cohort (126 patients from 1 July 2021 to 31 Dec 2021, with 22 CRS type 3 cases). Risk factors for CRS type 3, identified by logistic regression, informed the construction of a predictive nomogram. Its performance and accuracy were evaluated by the area under the curve (AUC), calibration curve and decision curve analysis, with further validation through a validation cohort. RESULTS: The nomogram included 6 risk factors: age (OR = 1.03; 95%CI = 1.009-1.052; p = 0.006), cardiovascular disease (CVD) history (OR = 2.802; 95%CI = 1.193-6.582; p = 0.018), mean artery pressure (MAP) (OR = 1.033; 95%CI = 1.012-1.054; p = 0.002), hemoglobin (OR = 0.973; 95%CI = 0.96--0.987; p < 0.001), homocysteine (OR = 1.05; 95%CI = 1.03-1.069; p < 0.001), AKI stage [(stage 1: reference), (stage 2: OR = 5.427; 95%CI = 1.781-16.534; p = 0.003), (stage 3: OR = 5.554; 95%CI = 2.234-13.805; p < 0.001)]. The nomogram exhibited excellent predictive performance with an AUC of 0.907 in the study cohort and 0.892 in the validation cohort. Calibration and decision curve analyses upheld its accuracy and clinical utility. CONCLUSIONS: We developed a nomogram predicting CRS type 3 in AKI patients, incorporating 6 risk factors: age, CVD history, MAP, hemoglobin, homocysteine, and AKI stage, enhancing early risk identification and patient management.

HCL: A Hierarchical Contrastive Learning Framework for Zero-Shot Relation Extraction.

Zero-shot relation extraction (ZSRE) is shown to become more significant in the current information extraction system, which aims at predicting relation classes that lack annotations or have just never appeared during training. Previous works focus on projecting sentences with their corresponding relation descriptions to an intermediate semantic space and searching the nearest semantic for predicting unseen classes. Though these methods can achieve sound performance, they only obtain inferior semantic information via a trivial distance metric and neglect the interaction in the instance representations. We are thus motivated to tackle these issues and propose a hierarchical contrastive learning (HCL) framework for ZSRE including projection-level and instance-level modules. Specifically, the projection-level component replaces the distance score function by contrastive loss to connect the input sentence with the relation semantic space. And the instance-level component integrates the external knowledge from sentence entities to establish new contrastive pairs for efficiently learning representations from mutual information. The experimental results on three well-known datasets demonstrate that our model surpasses the existing SOTA by at most 18.97% improvement on the F1 score when unseen classes are 15 . Moreover, our model can achieve more competitive performance alone with the increasing number of unseen classes.

First Report of Bacterial Leaf Streak of Rice Caused by Pantoea ananatis in Guangdong Province, China.

Rice (Oryza sativa L.) is a crucial staple crop worldwide, and bacterial diseases are among the primary factors affecting rice yield. In late October 2022, bacterial leaf streak disease was observed on the leaves of the rice variety Meixiangzhan 2 across multiple fields (approximately 130 hm2) in Leizhou City, Guangdong Province, China. The incidence rate was up to 30% in each field. Infected rice leaves exhibited distinctive symptoms at the boundary between diseased and healthy tissue, featuring dark green to yellow-brown streaks, while most of the leaf margin exhibited symptoms of either leaf edge or sheath rot. Disease progression from the leaf tip inwards revealed gray-white or dehydrated lesions with a bluish-gray color. Some leaves exhibited wrinkling at the edges, and severe symptoms at the leaf tip resembled those of bacterial leaf blight in rice. Ten leaves were collected from 10 infected rice plants in three distinct fields, and leaf pieces at the border of diseased and healthy areas were surface disinfected with 75% anhydrous ethanol for 60 seconds, rinsed three times with sterile water, and then soaked in sterile water for 8 hours. The obtained bacterial suspension was diluted at a ratio of 1: 106, and 100 µL of the diluted samples were plated on Potato Dextrose Agar (PDA) plates. After incubation at 28°C for 48 hours, the yellow bacterial colonies that appeared, were purified on PDA plates. To confirm the bacterial species, the amplification of genes gyrB, leuS, rpoB, and 16S rDNA was performed on six randomly selected isolates from the three different fields using the primers 27F/1492R, gyrB-F/R, leuS-F/R and rpoB-F/R, as reported by Yu et al (2022), respectively. PCR products were sequenced. All six isolates had identical sequences for all genes sequenced.The gene sequences of 16S rDNA (960 bp), gyrB (953 bp), leuS (733 bp), and rpoB (877 bp) for LZ1, were deposited in the NCBI database under accession numbers PP048830 , PP068625 , PP068626, and PP068627, respectively. These sequences were subsequently compared using BLASTn tool against the NCBI nr/nt database. The 16S rDNA, gyrB, leuS, and rpoB of LZ1 showed similarities of 99.90%, 99.16%, 99.73%, and 99.89%, with the corresponding sequences of P. ananatis TZ39 (GenBank accession numbers MZ800600.1 for 16S rDNA, and CP081342.1 for gyrB, leuS and rpoB ). MLSA analysis using concatenated sequences of gyrB, leuS, and rpoB genes indicated that the isolated strain LZ1 belongs to P. ananatis. In the tillering stage of rice varieties Meixiangzhan 2 and Huahangyuzhan, P. ananatis LZ1 was inoculated at a concentration of 108 CFU/mL using the leaf-cutting method, with sterile water used as a control (Toh et al., 2019). After 14 days of bacterial inoculation, the inoculated leaves gradually became necrotic, changing from light green to brown showing identical symptoms as those in the field, while the control plants remained symptom-free. Subsequent 16S rDNA, gyrB, leuS and rpoB gene sequencing results further confirmed the identity of the pathogen as P. ananatis, thereby fulfilling Koch's postulates. Previous reports have already identified P. ananatis as the pathogen causing rice bacterial leaf streak (Kini et al., 2017; Arayaskul et al., 2019; Yu et al., 2022; Lu et al., 2022; Luna et al., 2023; Yuan et al., 2023). This is the first report of rice bacterial leaf streak caused by P. ananatis in Guangdong Province, China, laying the foundation for future research to establish strategies for the prevention and control of this disease.

Differentiation of confluent hepatic fibrosis and infiltrative hepatocellular carcinoma on MR imaging.

BACKGROUND: To identify reliable magnetic resonance imaging (MRI) features that can differentiate confluent fibrosis (CF) from infiltrative hepatocellular carcinoma (HCC). METHODS: A retrospective analysis was conducted on Twenty CF patients and 28 infiltrative HCC patients who underwent upper abdomen MRI scans. The imaging features of lesions were analyzed, and the apparent diffusion coefficient (ADC) of lesions were measured. Accuracy, sensitivity and specificity for the diagnosis of CF were calculated for each category individually and combined. RESULTS: Compared to infiltrative HCC, hepatic capsular retraction at the site of lesion, hepatic volume loss at the site of lesion and "nodular surround sign" were more common in patients with CF (all P < 0.001). Hepatic volume loss at the site of lesion, no or mild enhancement in arterial phase, and hyper-enhancing in delayed phase to the background parenchyma showed superior diagnostic accuracy (83.3%, 85.4%, 97.9%, respectively). When the lesion exhibited hepatic volume loss at the site of lesion or no or mild enhancement in arterial phase or hyper-enhancing in delayed phase, a sensitivity of 100.0% for the diagnosis of CF was achieved. When the lesion was positive for any two of three categories, or positive for all three categories, a specificity of 100.0% was achieved. The ADC values of CF were higher than those of infiltrative HCC (P < 0.001). CONCLUSION: The combination of the hepatic volume loss at the site of lesion, no or mild enhancement in arterial phase, and hyper-enhancing in delayed phase to the background parenchyma can be considered reliable MR features for the diagnosis of CF, as they allow differentiation from infiltrative HCC.

Stabilization of all-natural water-in-oil high internal phase pickering emulsion by using diosgenin/soybean phosphatidylethanolamine complex: Characterization and application in 3D printing.

This study aimed to prepare an all-natural water-in-oil high internal phase Pickering emulsion (W/O-HIPPE) using diosgenin/soybean phosphatidylethanolamine complex (DGSP) and investigate the 3D printing performance. Results suggested that the self-assembly of diosgenin crystal was modified by SP in DGSP (diosgenin-SP ratios at 3:1 and 1:1), revealing a variation from large-size outward radiating needle-like to small-size granular-like shape, which facilitated closely packing at the interface. Hydrophilicity of DGSP was also increased (contact angle varying from 133.3 o to 106.4 o), ensuring more adequate interfacial adsorption to reduce interfacial tension more largely (6.5 mN/m). Thus, the W/O-HIPPE made by DGSP with diosgenin-SP = 1:1, exhibited smaller droplets and better freeze/thawing stability. The W/O-HIPPE was also measured improved rheological properties for 3D printing: satisfied shear-thinning behavior, higher recovery and self-supporting (viscoelasticity and deformation resistance). Consequently, the W/O-HIPPE allowed for printing more delicate patterns. This work provided guidance to prepare W/O-HIPPE for 3D printing.

Iron Oxide Nanoparticles Engineered Macrophage-Derived Exosomes for Targeted Pathological Angiogenesis Therapy.

Engineering exosomes with nanomaterials usually leads to the damage of exosomal membrane and bioactive molecules. Here, pathological angiogenesis targeting exosomes with magnetic imaging, ferroptosis inducing, and immunotherapeutic properties is fabricated using a simple coincubation method with macrophages being the bioreactor. Extremely small iron oxide nanoparticle (ESIONPs) incorporated exosomes (ESIONPs@EXO) are acquired by sorting the secreted exosomes from M1-polarized macrophages induced by ESIONPs. ESIONPs@EXO suppress pathological angiogenesis in vitro and in vivo without toxicity. Furthermore, ESIONPs@EXO target pathological angiogenesis and exhibit an excellent T1-weighted contrast property for magnetic resonance imaging. Mechanistically, ESIONPs@EXO induce ferroptosis and exhibit immunotherapeutic ability toward pathological angiogenesis. These findings demonstrate that a pure biological method engineered ESIONPs@EXO using macrophages shows potential for targeted pathological angiogenesis therapy.

Copper oxide nanoparticles suppress retinal angiogenesis via inducing endothelial cell cuproptosis.

Background: Copper oxide nanoparticles (CuO NPs) exhibit antitumor activity; however, their potential as an antiangiogenesis agent is unknown. Materials & methods: The antiangiogenesis properties of CuO NPs were evaluated in vitro and in vivo and the underlying mechanism was examined using RNA sequencing and metabolomic analyses. Results: CuO NPs inhibited endothelial cell function in vitro. They also mitigated retinal vasculature development and alleviated pathological retinal angiogenesis in vivo. RNA sequencing and metabolomic analyses revealed that CuO NPs disrupt the tricarboxylic acid cycle and induce cuproptosis, which was further supported by evaluating cuproptosis-related metabolites and proteins. Conclusion: CuO NPs may be an effective antiangiogenic agent for the treatment of retinal angiogenesis.

A novel MRI-based diagnostic model for predicting placenta accreta spectrum.

Objective To develop and evaluate a diagnostic model based on MRI signs for predicting placenta accreta spectrum. Materials and Methods A total of 155 pregnant women were included in this study, randomly divided into 104 cases in the training set and 51 cases in the validation set. There were 93 Non-PAS cases, and 62 cases in the PAS group. The training set included 62 Non-PAS cases and 42 PAS cases. Clinical factors and MRI signs were collected for univariate analysis. Then, binary logistic regression analysis was used to develop independent diagnostic models with clinical relevant risk factors or MRI signs, as well as those combining clinical risk factors and MRI signs. The ROC curve analysis was used to evaluate the diagnostic performance of each diagnostic model. Finally, the validation was performed with the validation set. Results In the training set, four clinical factors (gestity, parity, uterine surgery history, placental position) and 11 MRI features (T2-dark bands, placental bulge, T2 hypointense interface loss, myometrial thinning, bladder wall interruption, focal exophytic mass, abnormal placental bed vascularization, placental heterogeneity, asymmetric placental thickening/shape, placental ischemic infarction, abnormal intraplacental vascularity) were considered as risk factors for PAS. The AUC of the clinical diagnostic model, MRI diagnostic model, and clinical + MRI model of PAS were 0.779, 0.854, and 0.874, respectively. In the validation set, the AUC of the clinical diagnostic model, MRI diagnostic model, and clinical + MRI model of PAS were 0.655, 0.728, and 0.735, respectively. Conclusion Diagnosis model based on MRI features in this study can well predict placenta accreta spectrum.

Noninvasive glucose monitoring using portable GOx-Based biosensing system.

Wearable biosensors have gained huge interest due to their potential for real-time physiological information. The development of a non-invasive blood glucose device is of great interests for health monitoring in reducing the diabetes incidence. Here, we report a sandwich-structured biosensor that is designed for glucose levels detection by using sweat as the means of monitoring. The Prussian blue nanoparticles (PBNPs) and carboxylated carbon nanotubes (MWCNT-COOH) were self-assembled on the electrode to improve the electrochemical performance and as the sensor unit, glucose oxidase (GOx) was immobilized by chitosan (CS) as the reaction catalysis unit, and finally encapsulated with Nafion to ensure a stable performance. As a result, the GOx/PBNPs/MWCNT-COOH sensor displays a low detection limit (7.0 µM), high sensitivity (11.87 µA mM-1 cm-2), and excellent interference resistance for a full sweat glucose application range (0.0-1.0 mM) for both healthy individuals and diabetic patients. Additionally, the glucose sensor exhibits stable stability for two weeks and can be successfully applied to screen-printed carbon electrodes (SPCE), demonstrating its great potential for personalized medical detection and chronic disease management.

Inter-Class and Inter-Domain Semantic Augmentation for Domain Generalization.

The domain generalization approach seeks to develop a universal model that performs well on unknown target domains with the aid of diverse source domains. Data augmentation has proven to be an effective method to enhance domain generalization in computer vision. Recently, semantic-level based data augmentation has yielded remarkable results. However, these methods focus on sampling semantic directions on feature space from intra-class and intra-domain, limiting the diversity of the source domain. To address this issue, we propose a novel approach called Inter-Class and Inter-Domain Semantic Augmentation (CDSA) for domain generalization. We first introduce a sampling-based method called CrossSmooth to obtain semantic directions from inter-class. Then, CrossVariance obtains the styles of different domains by sampling semantic directions. Our experiments on four well-known domain generalization benchmark datasets (Digits-DG, PACS, Office-Home, and DomainNet) demonstrate the effectiveness of our approach. We also validate our approach on commonly-used semantic segmentation datasets, namely GTAV, SYNTHIA, Cityscapes, Mapillary, and BDDS which also show significant improvements.

Circularly Polarized Organic Ultralong Room-Temperature Phosphorescence with A High Dissymmetry Factor in Chiral Helical Superstructures.

Long-lived room-temperature phosphorescence (RTP) of organic materials holds a significant potential for optical information. Circularly polarized organic ultralong room-temperature phosphorescence (CP-OURTP) with extremely high dissymmetry factor (glum ) values is even highly demanded and considerably challenging. Here, an effective strategy is introduced to realize CP-OURTP with an emission decay time of 735 ms and a glum value up to 1.49, which exceeds two orders of magnitude larger than previous records, through a system composed of RTP polymers and chiral helical superstructures. The system exhibits excellent stability under multiple cycles of photoirradiation and thermal treatment, and is further employed for information encryption based on optical multiplexing. The results are anticipated to lay the foundation for the development of CP-OURTP materials in advanced photonic applications.

Discrimination between human epidermal growth factor receptor 2 (HER2)-low-expressing and HER2-overexpressing breast cancers: a comparative study of four MRI diffusion models.

OBJECTIVES: To determine the value of conventional DWI, continuous-time random walk (CTRW), fractional order calculus (FROC), and stretched exponential model (SEM) in discriminating human epidermal growth factor receptor 2 (HER2) status of breast cancer (BC). METHODS: This prospective study included 158 women who underwent DWI, CTRW, FROC, and SEM and were pathologically categorized into the HER2-zero-expressing group (n = 10), HER2-low-expressing group (n = 86), and HER2-overexpressing group (n = 62). Nine diffusion parameters, namely ADC, αCTRW, ßCTRW, DCTRW, ßFROC, DFROC, µFROC, αSEM, and DDCSEM of the primary tumor, were derived from four diffusion models. These diffusion metrics and clinicopathologic features were compared between groups. Logistic regression was used to determine the optimal diffusion metrics and clinicopathologic variables for classifying the HER2-expressing statuses. Receiver operating characteristic (ROC) curves were used to evaluate their discriminative ability. RESULTS: The estrogen receptor (ER) status, progesterone receptor (PR) status, and tumor size differed between HER2-low-expressing and HER2-overexpressing groups (p < 0.001 to p = 0.009). The αCTRW, DCTRW, ßFROC, DFROC, µFROC, αSEM, and DDCSEM were significantly lower in HER2-low-expressing BCs than those in HER2-overexpressing BCs (p < 0.001 to p = 0.01). Further multivariable logistic regression analysis showed that the αCTRW was the single best discriminative metric, with an area under the curve (AUC) being higher than that of ADC (0.802 vs. 0.610, p < 0.05); the addition of ER status, PR status, and tumor size to the αCTRW improved the AUC to 0.877. CONCLUSIONS: The αCTRW could help discriminate the HER2-low-expressing and HER2-overexpressing BCs. CLINICAL RELEVANCE STATEMENT: Human epidermal growth factor receptor 2 (HER2)-low-expressing breast cancer (BC) might also benefit from the HER2-targeted therapy. Prediction of HER2-low-expressing BC or HER2-overexpressing BC is crucial for appropriate management. Advanced continuous-time random walk diffusion MRI offers a solution to this clinical issue. KEY POINTS: • Human epidermal receptor 2 (HER2)-low-expressing BC had lower αCTRW, DCTRW, ßFROC, DFROC, µFROC, αSEM, and DDCSEM values compared with HER2-overexpressing breast cancer. • The αCTRW was the single best diffusion metric (AUC = 0.802) for discrimination between the HER2-low-expressing and HER2-overexpressing breast cancers. • The addition of αCTRW to the clinicopathologic features (estrogen receptor status, progesterone receptor status, and tumor size) further improved the discriminative ability.

Interphylum dissemination of NDM-5-positive plasmids in hospital wastewater from Fuzhou, China: a single-centre, culture-independent, plasmid transmission study.

BACKGROUND: The global spread of plasmid-borne carbapenem resistance is an ongoing public health challenge; however, the nature of such horizontal gene transfer events among complex bacterial communities remains poorly understood. We examined the in-situ transfer of the globally dominant New Delhi metallo-ß-lactamase (NDM)-5-positive IncX3 plasmid (denoted pX3_NDM-5) in hospital wastewater to simulate a real-world, One Health antimicrobial resistance context. METHODS: For this transmission study, we tagged pX3_NDM-5 with the green fluorescent protein gene, gfp, using a CRISPR-based method and transferred the plasmid to a donor Escherichia coli strain. Bacteria were extracted from a hospital wastewater treatment plant (Fujian Provincial Maternity and Children's Hospital, Fuzhou, China) as the bacterial recipient community. We mixed this recipient community with the E coli donor strain carrying the gfp-tagged plasmid, both with and without sodium hypochlorite (NaClO) as an environmental stressor, and conducted several culture-based and culture-independent conjugation assays. The conjugation events were observed microscopically and quantified by fluorescence-activated cell sorting. We analysed the taxonomic composition of the sorted transconjugal pool by 16S rRNA gene amplicon sequencing and assessed the stability of the plasmid in the isolated transconjugants and its ability to transfer back to E coli. FINDINGS: We show that the plasmid pX3_NDM-5 has a broad host range and can transfer across various bacterial phyla, including between Gram-negative and Gram-positive bacteria. Although environmental stress with NaClO did not affect the overall plasmid transfer frequency, it reduced the breadth of the transconjugant pool. The taxonomic composition of the transconjugal pool was distinct from that of the recipient communities, and environmental stress modulated the permissiveness of some operational taxonomic units towards the acquisition of pX3_NDM-5. Notably, pX3_NDM-5 transconjugants included the Gram-positive pathogen Enterococcus faecalis, and the plasmid could subsequently be reconjugated back to E coli. These findings suggest that E faecalis could act as a natural shuttle vector for the wide dissemination of pX3_NDM-5 plasmids. INTERPRETATION: Our culture-independent conjugation model simulates natural environmental conditions and challenges the established theory that Gram-negative and Gram-positive bacteria rarely exchange clinically important plasmids. The data show that plasmids disseminate more widely across genera and phyla than previously thought. These findings have substantial implications when considering the spread of antimicrobial resistance across One Health sectors. FUNDING: The Laboratory of Lingnan Modern Agriculture Project, the National Natural Science Foundation of China, the Natural Science Foundation of Fujian Province of China, and the Outstanding Young Research Talents Program of Fujian Agriculture and Forestry University.

Interfacial adsorption of soybean phosphatidylethanolamine in different oil phase and the stability of water-in-oil emulsion.

Water-in-oil (W/O) emulsion holds great potential in designing fat-reduced foods. However, due to the lack of W/O-type surfactant, formation of all-natural W/O emulsion is challenged. This study aimed to investigate the effect of oil phase on interfacial adsorption of soybean phosphatidylethanolamine (SP) and stability of W/O emulsion. Five oils, including medium chain triglycerides oil (MO), coconut oil (CO), palm kernel oil (PKO), sunflower oil (SO) and rapeseed oil (RO), were selected. Results showed that diffusion rate of SP to the interface ranked as MO > CO > PKO > SO ≈ RO, increasing interfacial adsorption from 50.2 % to 85.3 %. Higher interfacial adsorption improved the deformation resistance of interfacial layer, causing more significant decrease in interfacial tension (3.54 mN/m). So, the largest water fraction (65 %) was stabilized by SP with MO and CO, and exhibited smaller droplet sizes and better stability. Consequently, shorter-chain oil was more suitable for preparing W/O emulsions.

Targeting progranulin alleviated silica particles-induced pulmonary inflammation and fibrosis via decreasing Il-6 and Tgf-ß1/Smad.

Long term exposure to silica particles leads to various diseases, among which silicosis is of great concern. Silicosis is an interstitial lung disease caused by inhalation of silica particles in production environments. However, the mechanisms underlying silicosis remains unclear. Our previous studies revealed that progranulin (Pgrn) promoted the expression of pro-inflammatory factors in alveolar macrophages treated with silica particles and the secretion of extracellular matrix of pulmonary fibroblasts. Nevertheless, the role of Pgrn in silica particles-induced silicosis in vivo was unknown. This study found that silica particles increased Pgrn expression in silicosis patients. Pgrn deficiency reduced lung inflammation and fibrosis in silica particles-induced silicosis mouse models. Subsequently, based on transcriptional sequencing and interleukin (Il) -6 knockout mouse models, results demonstrated that Pgrn deficiency might decrease silicosis inflammation by reducing the production of Il-6, thereby modulating pulmonary fibrosis in the early stage of silicosis mouse models. Furthermore, another mechanism through which Pgrn deficiency reduced fibrosis in silicosis mouse models was the regulation of the transforming growth factor (Tgf) -ß1/Smad signaling pathway. Conclusively, Pgrn contributed to silicosis inflammation and fibrosis induced by silica particles, indicating that Pgrn could be a promising therapeutic target.

Tumor Multiregional Mean Apparent Propagator (MAP) Features in Evaluating Gliomas-A Comparative Study With Diffusion Kurtosis Imaging (DKI).

BACKGROUND: Glioma classification affects treatment and prognosis. Reliable imaging methods for preoperatively evaluating gliomas are essential. PURPOSE: To evaluate tumor multiregional mean apparent propagator (MAP) features in glioma diagnosis and to compare those with diffusion-kurtosis imaging (DKI). STUDY TYPE: Retrospective study. SUBJECTS: 70 untreated glioma patients (31 LGGs (low-grade gliomas), 34 women; mean age, 47 ± 12 years, training (60%, n = 42) and testing cohorts (40%, n = 28)). FIELD STRENGTH/SEQUENCE: 3-T, diffusion-MRI using q-space Cartesian grid sampling with 11 different b-values. ASSESSMENT: Tumor multiregional MAP (mean squared displacement (MSD); q-space inverse variance (QIV); non-Gaussianity (NG); axial/radial non-Gaussianity (NGAx, NGRad); return-to-origin/axis/plane probability (RTOP, RTAP, and RTPP)); and DKI metrics (axial/mean/radial kurtosis (AK, MK, and RK)) on tumor parenchyma (TP) and peritumoral areas (PT) in histopathologically gliomas grading and genotyping were assessed. STATISTICAL TESTS: Mann-Whitney U; Kruskal-Wallis; Benjamini-Hochberg; Bonferroni-correction; receiver operating curve (ROC) and area under curve (AUC); DeLong's test; Random Forest (RF). P value<0.05 was considered statistically significant after multiple comparisons correction. RESULTS: Compared with LGGs, MSD, and QIV were significantly lower in TP, whereas NG, NGAx, NGRad, RTOP, RTAP, RTPP, and DKI metrics were significantly higher in HGGs (high-grade gliomas) (P ≤ 0.007), as well as in isocitrate-dehydrogenase (IDH)-mutated than IDH-wildtype gliomas (P ≤ 0.039). These trends were reversed for PT (tumor grades, P ≤ 0.011; IDH-mutation status, P ≤ 0.012). ROC analysis showed that, in TP, DKI metrics performed best in TP (AUC 0.83), whereas in PT, RTPP performed best (AUC 0.77) in glioma grading. AK performed best in TP (AUC 0.77), whereas MSD and RTPP performed best in PT (AUC 0.73) in IDH genotyping. Further RF analysis with DKI and MAP demonstrated good performance in grading (AUC 0.91, Accuracy 82%) and IDH genotyping (AUC 0.87, Accuracy 79%). DATA CONCLUSION: Tumor multiregional MAP features could effectively evaluate gliomas. The performance of MAP may be similar to DKI in TP, while in PT, MAP may outperform DKI. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

The guiding value of the cinematic volume rendering technique in the preoperative diagnosis of brachial plexus schwannoma.

This study aimed to explore and compare the guiding value of Maximum Intensity Projection (MIP) and Cinematic Volume Rendering Technique (cVRT) in the preoperative diagnosis of brachial plexus schwannomas. We retrospectively analyzed the clinical and imaging data of 45 patients diagnosed with brachial plexus schwannomas at the First Affiliated Hospital of Zhengzhou University between January 2020 and December 2022. The enhanced three-dimensional short recovery time inversion-recovery fast spin-echo imaging (3D-STIR-SPACE) sequence served as source data for the reconstruction of MIP and cVRT. Two independent observers scored the image quality and evaluated the location of the tumor and the relationship between the tumor and the brachial plexus. The image quality scores of the two reconstruction methods were compared using the nonparametric Wilcoxon signed-rank test, and the consistency between the image and surgical results was assessed using the weighted kappa. Compared to MIP images, cVRT images had a better performance of overall image quality (p < 0.001), nerve and lump visualization (p < 0.001), spatial positional relationship conspicuity (p < 0.001), and diagnostic confidence (p < 0.001). Additionally, the consistency between the cVRT image results and surgical results (kappa =0.913, P<0.001) was higher than that of the MIP images (kappa =0.829, P<0.001). cVRT provides a high guiding value in the preoperative diagnosis of brachial plexus schwannomas and is an important basis for formulating surgical plans.

Design and synthesis of 1H-benzo[d]imidazole selective HDAC6 inhibitors with potential therapy for multiple myeloma.

Pan-HDAC inhibitors exhibit significant inhibitory activity against multiple myeloma, however, their clinical applications have been hampered by substantial toxic side effects. In contrast, selective HDAC6 inhibitors have demonstrated effectiveness in treating multiple myeloma. Compounds belonging to the class of 1H-benzo[d]imidazole hydroxamic acids have been identified as novel HDAC6 inhibitors, with the benzimidazole group serving as a specific linker for these inhibitors. Notably, compound 30 has exhibited outstanding HDAC6 inhibitory activity (IC50 = 4.63 nM) and superior antiproliferative effects against human multiple myeloma cells, specifically RPMI-8226. Moreover, it has been shown to induce cell cycle arrest in the G2 phase and promote apoptosis through the mitochondrial pathway. In a myeloma RPMI-8226 xenograft model, compound 30 has demonstrated significant in vivo antitumor efficacy (T/C = 34.8%) when administered as a standalone drug, with no observable cytotoxicity. These findings underscore the immense potential of compound 30 as a promising therapeutic agent for the treatment of multiple myeloma.

Highly Sensitive Flexible Sensors for Human Activity Monitoring and Personal Healthcare.

Flexible sensors are capable of converting multiple human physiological signals into electrical signals for various applications in clinical diagnostics, athletics, and human-machine interaction. High-performance flexible strain sensors are particularly desirable for sensitive, reliable, and long-term monitoring, but current applications are still constrained due to high response threshold, low recoverability properties, and complex preparation methods. In this study, we present a stable and flexible strain sensor by a cost-effective self-assemble approach that demonstrates remarkable sensitivity (2169), ultrafast response and recovery time (112 ms), and wide dynamic response range (0-50%), as confirmed in human pulse and human-computer interaction. These excellent performances can be attributed to the design of a Polydimethylsiloxane (PDMS) substrate integrated with multiwalled carbon nanotubes (MWCNT) and graphene nanosheets (GNFs), which results in high electrical conductivity. The MWCNT serves as a bridge, connecting the GNFs to create an efficient conductive path even under a strain of 50%. We also demonstrate the strain sensor's capability in weak physiological signal pulse measurement and excellent resistance to mechanical fatigue. Moreover, the sensor shows diverse sensitivities in various tensile states with different signal patterns, making it highly suitable for full-range human monitoring and flexible wearable systems.