Search

To assess the impact of a deep learning (DL) denoising reconstruction algorithm applied to identical patient scans acquired with two different voxel dimensions, representing distinct spatial resolutions, this IRB-approved prospective study was conducted at a tertiary pediatric center in compliance with the Health Insurance Portability and Accountability Act. A General Electric Signa Premier unit (GE Medical Systems, Milwaukee, WI) was employed to acquire two DTI (diffusion tensor imaging) sequences of the left knee on each child at 3T: an in-plane 2.0 × 2.0 mm2 with section thickness of 3.0 mm and a 2 mm3 isovolumetric voxel; neither had an intersection gap. For image acquisition, a multi-band DTI with a fat-suppressed single-shot spin-echo echo-planar sequence (20 non-collinear directions; b-values of 0 and 600 s/mm2) was utilized. The MR vendor-provided a commercially available DL model which was applied with 75% noise reduction settings to the same subject DTI sequences at different spatial resolutions. We compared DTI tract metrics from both DL-reconstructed scans and non-denoised scans for the femur and tibia at each spatial resolution. Differences were evaluated using Wilcoxon-signed ranked test and Bland–Altman plots. When comparing DL versus non-denoised diffusion metrics in femur and tibia using the 2 mm × 2 mm × 3 mm voxel dimension, there were no significant differences between tract count (p = 0.1, p = 0.14) tract volume (p = 0.1, p = 0.29) or tibial tract length (p = 0.16); femur tract length exhibited a significant difference (p < 0.01). All diffusion metrics (tract count, volume, length, and fractional anisotropy (FA)) derived from the DL-reconstructed scans, were significantly different from the non-denoised scan DTI metrics in both the femur and tibial physes using the 2 mm3 voxel size (p < 0.001). DL reconstruction resulted in a significant decrease in femorotibial FA for both voxel dimensions (p < 0.01). Leveraging denoising algorithms could address the drawbacks of lower signal-to-noise ratios (SNRs) associated with smaller voxel volumes and capitalize on their better spatial resolutions, allowing for more accurate quantification of diffusion metrics.

Brown rice germination increases γ-aminobutyric acid (GABA) levels and enhances its antioxidant activity. In this study, Kaohsiung 145 brown rice was used as the raw material, and soaked in various solutions for 6 h before being processed with either high-pressure processing (HPP) or ultrasonic treatment to increase the GABA content. The GABA and antioxidant components of brown rice were analyzed after 42 h of germination and subsequent air-drying to obtain a moisture content of 14%. The results showed that non-germinated brown rice had GABA at 7.10 mg/100 g and treatment with various soaking solutions (0.1% CaCl2, 0.1% Glu, 0.2% CaCl2, and 0.2% Glu) increased GABA contents. Specifically, 0.1% CaCl2 and 0.1% Glu exhibited higher GABA content, at 42.51 and 44.64 mg/100 g. Furthermore, the GABA content increased synergistically when combined with HPP (100 MPa, 10 min) and ultrasonic (20 min) treatments after soaking. The results showed that the GABA contents in germinated rice were the greatest after ultrasonic treatment, followed by HPP treatment, and the least with only soaking treatment. The treatments with 0.1% CaCl2 and 0.2% Glu combined with ultrasonic processing for 20 min resulted in the highest GABA content at 102.38 and 110.88 mg/100 g, respectively. Finally, 0.1% CaCl2 with ultrasonic treatment for 20 min was chosen, as it demonstrated a considerable improvement in total polyphenols content and DPPH scavenging abilities, as seen by improved scores in subsequent taste evaluations.

Perovskite solar cells (PSCs) are currently among the most promising solar cell technologies. A key component influencing their efficiency and stability is the electron transport layer (ETL). This study examined the carrier transport properties of various ETL materials, including TiO2, SnO2, and TiO2/SnO2 bilayer ETLs, to understand their effects on PSC performance. The study proposed a hypothesis that the bilayer design, integrating TiO2 and SnO2, enhances performance, and it used experimental results to substantiate this. Through analysis and discussion of the ETLs, the interface between perovskite (PVSK) and ETLs, and other PSC components, we gained insights into the carrier transport dynamics in PSCs with different ETL configurations. Our findings indicate that the TiO2/SnO2 bilayer ETL structure can significantly improve PSC performance by reducing current leakage, improving carrier transport, and minimizing carrier recombination. This enhancement is quantified by the increase in efficiency from 13.58% with a single-layer TiO2 ETL to 20.49% with the bilayer ETL.

In organisms that use reduced sulfur compounds as alternative or additional electron donors to organic compounds, transcriptional regulation of genes for enzymes involved in sulfur oxidation is needed to adjust metabolic flux to environmental conditions. However, little is known about the sensing and response to inorganic sulfur compounds such as thiosulfate in sulfur-oxidizing bacteria. In the Alphaproteobacterium Hyphomicrobium denitrificans, one strategy is the use of the ArsR–SmtB-type transcriptional regulator SoxR. We show that this homodimeric repressor senses sulfane sulfur and that it is crucial for the expression not only of sox genes encoding the components of a truncated periplasmic thiosulfate-oxidizing enzyme system but also of several other sets of genes for enzymes of sulfur oxidation. DNA binding and transcriptional regulatory activity of SoxR are controlled by polysulfide-dependent cysteine modification. The repressor uses the formation of a sulfur bridge between two conserved cysteines as a trigger to bind and release DNA and can also form a vicinal disulfide bond to orchestrate a response to oxidizing conditions. The importance of the sulfur bridge forming cysteines was confirmed by site-directed mutagenesis, mass spectrometry, and gel shift assays. In vivo, SoxR interacts directly or indirectly with a second closely related repressor, sHdrR.

In order to save manpower on rail track inspection, computer vision-based methodologies are developed. We propose utilizing the YOLOv4-Tiny neural network to identify track defects in real time. There are ten defects covering fasteners, rail surfaces, and sleepers from the upward and six defects about the rail waist from the sideward. The proposed real-time inspection system includes a high-performance notebook, two sports cameras, and three parallel processes. The hardware is mounted on a flat cart running at 30 km/h. The inspection results about the abnormal track components could be queried by defective type, time, and the rail hectometer stake. In the experiments, data augmentation by a Cycle Generative Adversarial Network (GAN) is used to increase the dataset. The number of images is 3800 on the upward and 967 on the sideward. Five object detection neural network models—YOLOv4, YOLOv4-Tiny, YOLOX-Tiny, SSD512, and SSD300—were tested. The YOLOv4-Tiny model with 150 FPS is selected as the recognition kernel, as it achieved 91.7%, 92%, and 91% for the mAP, precision, and recall of the defective track components from the upward, respectively. The mAP, precision, and recall of the defective track components from the sideward are 99.16%, 96%, and 94%, respectively.

This investigation aimed to explore deep learning (DL) models’ potential for diagnosing Pseudomonas keratitis using external eye images. In the retrospective research, the images of bacterial keratitis (BK, n = 929), classified as Pseudomonas (n = 618) and non-Pseudomonas (n = 311) keratitis, were collected. Eight DL algorithms, including ResNet50, DenseNet121, ResNeXt50, SE-ResNet50, and EfficientNets B0 to B3, were adopted as backbone models to train and obtain the best ensemble 2-, 3-, 4-, and 5-DL models. Five-fold cross-validation was used to determine the ability of single and ensemble models to diagnose Pseudomonas keratitis. The EfficientNet B2 model had the highest accuracy (71.2%) of the eight single-DL models, while the best ensemble 4-DL model showed the highest accuracy (72.1%) among the ensemble models. However, no statistical difference was shown in the area under the receiver operating characteristic curve and diagnostic accuracy among these single-DL models and among the four best ensemble models. As a proof of concept, the DL approach, via external eye photos, could assist in identifying Pseudomonas keratitis from BK patients. All the best ensemble models can enhance the performance of constituent DL models in diagnosing Pseudomonas keratitis, but the enhancement effect appears to be limited.

Social networks have increasingly become important and popular in modern times. Moreover, the influence of social networks plays a vital role in various organizations, including government organizations, academic research organizations and corporate organizations. Therefore, strategizing the optimal propagation strategy in social networks has also become more important. Increasing the precision of evaluating the propagation probability of social networks can indirectly influence the investment of cost, manpower and time for information propagation to achieve the best return. This study proposes a new algorithm, which includes a scale-free network, Barabási–Albert model, binary-addition tree (BAT) algorithm, PageRank algorithm, Personalized PageRank algorithm and a new BAT algorithm to calculate the propagation probability of social networks. The results obtained after implementing the simulation experiment of social network models show that the studied model and the proposed algorithm provide an effective method to increase the efficiency of information propagation in social networks. In this way, the maximum propagation efficiency is achieved with the minimum investment.

Biofilm formation is an important virulence factor for the opportunistic microorganisms that elicit skin infections. The recalcitrant feature of biofilms and their antibiotic tolerance impose a great challenge on the use of conventional therapies. Most antibacterial agents have difficulty penetrating the matrix produced by a biofilm. One novel approach to address these concerns is to prevent or inhibit the formation of biofilms using nanoparticles. The advantages of using nanosystems for antibiofilm applications include high drug loading efficiency, sustained or prolonged drug release, increased drug stability, improved bioavailability, close contact with bacteria, and enhanced accumulation or targeting to biomasses. Topically applied nanoparticles can act as a strategy for enhancing antibiotic delivery into the skin. Various types of nanoparticles, including metal oxide nanoparticles, polymeric nanoparticles, liposomes, and lipid-based nanoparticles, have been employed for topical delivery to treat biofilm infections on the skin. Moreover, nanoparticles can be designed to combine with external stimuli to produce magnetic, photothermal, or photodynamic effects to ablate the biofilm matrix. This study focuses on advanced antibiofilm approaches based on nanomedicine for treating skin infections. We provide in-depth descriptions on how the nanoparticles could effectively eliminate biofilms and any pathogens inside them. We then describe cases of using nanoparticles for antibiofilm treatment of the skin. Most of the studies included in this review were supported by in vivo animal infection models. This article offers an overview of the benefits of nanosystems for treating biofilms grown on the skin.

Polysaccharides isolated from fungus Cordyceps militaris display multi-biofunctions, such as immunostimulation, down-regulation of hyperlipidemia, and anti-cancer function. The occurrence of obesity and metabolic syndrome is related to the imbalance of gut microbiota. In this study, the effects of C. militaris and its fractions on modifying metabolic syndrome in mice were evaluated. Mice were fed a high-fat/high-sucrose diet (HFSD) for 14 weeks to induce body weight increase and hyperlipidemia symptoms in mice, and then the mice were simultaneously given a HFSD and C. militaris samples for a further 8 weeks. The results indicated that the fruit body, polysaccharides, and cordycepin obtained from C. militaris had different efficacies on regulating metabolic syndrome and gut microbiota in HFSD-treated mice. Polysaccharides derived from C. militaris decreased the levels of blood sugar and serum lipids in mice fed HFSD. In addition, C. militaris-polysaccharide treatment obviously improved intestinal dysbiosis through promoting the population of next generation probiotic Akkermansia muciniphila in the gut of mice fed HFSD. In conclusion, polysaccharides derived from C. militaris have the potential to act as dietary supplements and health food products for modifying the gut microbiota to improve the metabolic syndrome.

The interactions between cells and nanomaterials at the nanoscale play a pivotal role in controlling cellular behavior and ample evidence links cell intercommunication to nanomaterial size. However, little is known about the effect of nanomaterial geometry on cell behavior. To elucidate this and to extend the application in cancer theranostics, we have engineered core–shell cobalt–gold nanoparticles with spherical (Co@Au NPs) and elliptical morphology (Co@Au NEs). Our results show that owing to superparamagnetism, Co@Au NPs can generate hyperthermia upon magnetic field stimulation. In contrast, due to the geometric difference, Co@Au NEs can be optically excited to generate hyperthermia upon photostimulation and elevate the medium temperature to 45 °C. Both nanomaterial geometries can be employed as prospective contrast agents; however, at identical concentration, Co@Au NPs exhibited 4-fold higher cytotoxicity to L929 fibroblasts as compared to Co@Au NEs, confirming the effect of nanomaterial geometry on cell fate. Furthermore, photostimulation-generated hyperthermia prompted detachment of anti-cancer drug, Methotrexate (MTX), from Co@Au NEs-MTX complex and which triggered 90% decrease in SW620 colon carcinoma cell viability, confirming their application in cancer theranostics. The geometry-based perturbation of cell fate can have a profound impact on our understanding of interactions at nano-bio interface which can be exploited for engineering materials with optimized geometries for superior theranostic applications.

Curcumin is a known anti-adipogenic agent for alleviating obesity and related disorders. Comprehensive comparisons of the anti-adipogenic activity of curcumin with other curcuminoids is minimal. This study compared adipogenesis inhibition with curcumin, demethoxycurcumin (DMC), and bisdemethoxycurcumin (BDMC), and their underlying mechanisms. We differentiated 3T3-L1 cells in the presence of curcuminoids, to determine lipid accumulation and triglyceride (TG) production. The expression of adipogenic transcription factors and lipogenic proteins was analyzed by Western blot. A significant reduction in Oil red O (ORO) staining was observed in the cells treated with curcuminoids at 20 μM. Inhibition was increased in the order of curcumin < DMC < BDMC. A similar trend was observed in the detection of intracellular TG. Curcuminoids suppressed differentiation by downregulating the expression of peroxisome proliferator-activated receptor γ (PPARγ) and CCAAT/enhancer-binding protein α (C/EBPα), leading to the downregulation of the lipogenic enzymes acetyl-CoA carboxylase (ACC) and fatty acid synthase (FAS). AMP-activated protein kinase α (AMPKα) phosphorylation was also activated by BDMC. Curcuminoids reduced the release of proinflammatory cytokines and leptin in 3T3-L1 cells in a dose-dependent manner, with BDMC showing the greatest potency. BDMC at 20 μM significantly decreased leptin by 72% compared with differentiated controls. Molecular docking computation indicated that curcuminoids, despite having structural similarity, had different interaction positions to PPARγ, C/EBPα, and ACC. The docking profiles suggested a possible interaction of curcuminoids with C/EBPα and ACC, to directly inhibit their expression.

Diabetes mellitus is a well-known chronic metabolic disease that poses a long-term threat to human health and is characterized by a relative or absolute lack of insulin, resulting in hyperglycemia. Type 2 diabetes mellitus (T2DM) typically affects many metabolic pathways, resulting in β-cell dysfunction, insulin resistance, abnormal blood glucose levels, inflammatory processes, excessive oxidative reactions, and impaired lipid metabolism. It also leads to diabetes-related complications in many organ systems. Antidiabetic drugs have been approved for the treatment of hyperglycemia in T2DM; these are beneficial for glucose metabolism and promote weight loss, but have the risk of side effects, such as nausea or an upset stomach. A wide range of active components, derived from medicinal plants, such as alkaloids, flavonoids, polyphenol, quinones, and terpenoids may act as alternative sources of antidiabetic agents. They are usually attributed to improvements in pancreatic function by increasing insulin secretions or by reducing the intestinal absorption of glucose. Ease of availability, low cost, least undesirable side effects, and powerful pharmacological actions make plant-based preparations the key player of all available treatments. Based on the study of therapeutic reagents in the pathogenesis of humans, we use the appropriate animal models of T2DM to evaluate medicinal plant treatments. Many of the rat models have characteristics similar to those in humans and have the advantages of ease of genetic manipulation, a short breeding span, and access to physiological and invasive testing. In this review, we summarize the pathophysiological status of T2DM rat models and focus on several bioactive compounds from herbal medicine with different functional groups that exhibit therapeutic potential in the T2DM rat models, in turn, may guide future approach in treating diabetes with natural drugs.

Microbial proteins have recently been found to have more benefits in clinical disease treatment because of their better-developed strategy and properties than traditional medicine. In this study, we investigated the effectiveness of a truncated peptide synthesized from the C-terminal sequence of pneumolysin, i.e., C70PLY4, in Streptococcus pneumoniae, in treating chronic inflammatory conditions. It has been shown that C70PLY4 significantly blocks the transendothelial migration of neutrophils and attenuates the formation of atherosclerotic plaque and the secretion of soluble forms of the intercellular adhesion molecule-1 (ICAM-1), the vascular cell adhesion molecule 1 (VCAM-1), and E-selectin in high-fat-diet/streptozotocin-induced inflammatory rats. The mechanism and the docking simulation analysis further indicated that C70PLY4 might serve as a Toll-like receptor 4 (TLR4) antagonist by competing for the binding site of MD2, an indispensable protein for lipopolysaccharide (LPS)–TLR4 interaction signaling, on the TLR4 structure. Moreover, compared to the full-length PLY, C70PLY4 seems to have no cytotoxicity in human vascular endothelial cells. Our study elucidated a possible therapeutic efficacy of C70PLY4 in reducing chronic inflammatory conditions and clarified the underlying mechanism. Thus, our findings identify a new drug candidate that, by blocking TLR4 activity, could be an effective treatment for patients with chronic inflammatory diseases.

Disrupting lung tumor growth via histone deacetylases (HDACs) inhibition is a strategy for cancer therapy or prevention. Targeting HDAC6 may disturb the maturation of heat shock protein 90 (Hsp90) mediated cell cycle regulation. In this study, we demonstrated the effects of semisynthesized NBM-T-BBX-OS01 (TBBX) from osthole on HDAC6-mediated growth arrest in lung cancer cells. The results exhibited that the anti-proliferative activity of TBBX in numerous lung cancer cells was more potent than suberoylanilide hydroxamic acid (SAHA), a clinically approved pan-HDAC inhibitor, and the growth inhibitory effect has been mediated through G1 growth arrest. Furthermore, the protein levels of cyclin D1, CDK2 and CDK4 were reduced while cyclin E and CDK inhibitor, p21Waf1/Cip1, were up-regulated in TBBX-treated H1299 cells. The results also displayed that TBBX inhibited HDAC6 activity via down-regulation HDAC6 protein expression. TBBX induced Hsp90 hyper-acetylation and led to the disruption of cyclin D1/Hsp90 and CDK4/Hsp90 association following the degradation of cyclin D1 and CDK4 proteins through proteasome. Ectopic expression of HDAC6 rescued TBBX-induced G1 arrest in H1299 cells. Conclusively, the data suggested that TBBX induced G1 growth arrest may mediate HDAC6-caused Hsp90 hyper-acetylation and consequently increased the degradation of cyclin D1 and CDK4.

A novel tetranorditerpenoid, sinubatin A (1) (having an unprecedented carbon skeleton), a new norditerpenoid, sinubatin B (2) (a 4,5-epoxycaryophyllene possessing an unusual methylfuran moiety side chain), and a known diterpenoid, gibberosin J (3) were isolated from soft coral Sinularia nanolobata. The structures of the new compounds were elucidated by extensive analysis of spectroscopic data.

Carbon-based nanomaterials serve as a type of smart material for photo-triggered disease theranostics. The inherent physicochemical properties of these nanomaterials facilitate their use for less invasive treatments. This review summarizes the properties and applications of materials including fullerene, nanotubes, nanohorns, nanodots and nanographenes for photodynamic nanomedicine in cancer and antimicrobial therapies. Carbon nanomaterials themselves do not usually act as photodynamic therapy (PDT) agents owing to the high hydrophobicity, however, when the surface is passivated or functionalized, these materials become great vehicles for PDT. Moreover, conjugation of carbonaceous nanomaterials with the photosensitizer (PS) and relevant targeting ligands enhances properties such as selectivity, stability, and high quantum yield, making them readily available for versatile biomedical applications.