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Melaleuca quinquenervia is widely grown in tropical areas worldwide. Studies have demonstrated that extracts of its buds, leaves, and branches obtained through hydrodistillation, steam distillation, or solvent extraction exhibit physiological activities, including anti-melanogenic, antibacterial, and antioxidant properties; nevertheless, such extracts are mostly not effectively collected or adequately utilized. Accordingly, this study applied a rapid, effective, and easy-to-operate microwave-assisted water extraction (MAWE) technique for the first time to prepare M. quinquenervia leaf extract (MLE) with improved physiological activities. The results indicated that the optimal irradiation time and liquid/solid ratio for the production of the MLE were 180 s and 20 mL/g, respectively. Under optimal conditions, the freeze-dried MLE achieved a high yield (6.28% ± 0.08%) and highly effective broad-spectrum physiological activities. The MLE exhibited strong antioxidant, antiaging, and anti-inflammatory activities and excellent antityrosinase and antimicrobial activities. Additionally, the MLE was noncytotoxic at concentrations of ≤300 mg/L, at which it exhibited pharmacological activity. The results also indicated that the MLE comprised a total of 24 chemical compounds and 17 phenolic compounds. Among these compounds, luteolin contributed to antityrosinase activity. The extract’s antiaging activity was attributed to ellagic acid and quercetin, its anti-inflammatory activity resulted from ellagic acid and kaempferol, and its antimicrobial activity resulted from quercetin and 3-O-methylellagic acid. In conclusion, the MAWE-derived MLE may be useful as a functional ingredient in cosmetic products, health foods, and botanical drugs.

Background: Serum malondialdehyde-oxidized low-density lipoprotein (MDA-oxLDL) is associated with atherosclerosis and increased risk of cardiovascular disease (CVD). Vascular calcification frequently occurs with arterial stiffness in patients on peritoneal dialysis (PD). This cross-sectional study aimed to elucidate the correlation between aortic stiffness and MDA-oxLDL levels in patients on PD. Methods: Overall, 92 patients on PD were included. The carotid–femoral pulse wave velocity (cfPWV) was evaluated using cuff-based volumetric displacement, and blood samples were obtained from all patients. Aortic stiffness was classified based on cfPWV values (>10 m/s indicating aortic stiffness). Serum MDA-ox-LDL levels were quantified using commercial enzyme-linked immunosorbent assay kits. Results: In total, 33 (35.9%) patients were classified into the aortic stiffness group. Factors, including systolic blood pressure (SBP), serum triglyceride levels, C-reactive protein levels, age, weight, body mass index (BMI), waist circumference, MDA-oxLDL levels, and diabetes mellitus (DM) prevalence, were significantly higher in the aortic stiffness group. Multivariable logistic regression analysis revealed significant associations between aortic stiffness and MDA-oxLDL levels, BMI, and SBP. Furthermore, multivariable forward stepwise linear regression analysis revealed serum MDA-oxLDL levels as a significant independent predictor of cfPWV values. Conclusions: Serum MDA-oxLDL levels correlate positively with cfPWV values and may predict aortic stiffness among PD patients, highlighting its potential role in assessing CVD risk in this population.

Activation of neutrophil leukocytes is tightly regulated, and it is important to understand the molecular mechanisms of their response to physiological and pathological stimuli. Here authors show that the adhesion molecule G protein-coupled receptor 97 and its interaction partners play pivotal roles in neutrophil leukocyte activation both in anti-microbial response and in inflammatory diseases.

Sorghum (Sorghum bicolor) exhibits drought resistance and environmental adaptability, making it a crucial cereal crop for semi-arid regions. It has a wide range of uses, including as food, feed, brooms, alcohol production, and bioethanol. In particular, Taiwan imports nearly 50,000 tons of sorghum annually, primarily for the production of sorghum liquor. However, the ideal raw material for high-quality sorghum liquor is waxy sorghum, and not all sorghum varieties imported or promoted in Taiwan are of this waxy type. Consequently, there is a shortage of sufficient waxy sorghum raw materials to meet the demands of the Taiwan market. The occurrence of waxy sorghum (wx) is caused by the mutation of granule-bound starch synthase I (GBBS I), and there are currently several known types of mutants, carrying different wxa, wxb, and wxc waxy alleles. Among them, wxc is a novel mutation type, and in native sorghum in Taiwan, individuals with the waxy allele wxc have been found. The three-line method is a commonly used breeding strategy, which simplifies the process of emasculation to obtain hybrid F1 offspring. In this study, imported sorghum variety Liangnuo No.1 (with male sterility), native glutinous sorghum variety SB6 from Taiwan (carrying the wxc waxy allele), and sorghum reference genome variety BTx623 were used as research materials. The goal was to use the three-line method to produce waxy sorghums, including the male sterile line (A-line), male sterile maintenance line (B-line), and fertility-restoring line (R-line). The breeding results showed that by using backcross breeding, molecular-assisted selection, and traditional field selection methods, high-quality three-line materials (A-, B-, R-lines, named CNA1, CNB1 CNR1, respectively) and F1 hybrid (CNH1) with favorable agronomic traits and yield quality were successfully obtained.

Abstract Background Exposure to traffic-related air pollution (TRAP) during development and/or in adulthood has been associated in many human studies with both neurodevelopmental and neurodegenerative diseases, such as autism spectrum disorder (ASD) and Alzheimer’s disease (AD) or Parkinson’s disease (PD). Methods In the present study, C57BL/6 J mice were exposed to environmentally relevant levels (250+/−50 μg/m3) of diesel exhaust (DE) or filtered air (FA) during development (E0 to PND21). The expression of several transcription factors relevant for CNS development was assessed on PND3. To address possible mechanistic underpinnings of previously observed behavioral effects of DE exposure, adult neurogenesis in the hippocampus and laminar organization of neurons in the somatosensory cortex were analyzed on PND60. Results were analyzed separately for male and female mice. Results Developmental DE exposure caused a male-specific upregulation of Pax6, Tbr1, Tbr2, Sp1, and Creb1 on PND3. In contrast, in both males and females, Tbr2+ intermediate progenitor cells in the PND60 hippocampal dentate gyrus were decreased, as an indication of reduced adult neurogenesis. In the somatosensory region of the cerebral cortex, laminar distribution of Trb1, calbindin, and parvalbumin (but not of Ctip2 or Cux1) was altered by developmental DE exposure. Conclusions These results provide additional evidence to previous findings indicating the ability of developmental DE exposure to cause biochemical/molecular and behavioral alterations that may be involved in neurodevelopmental disorders such as ASD.

Chenopodium formosanum Koidz (CF) is an indigenous cereal plant of Taiwan. Its high content of secondary metabolites and nutrients has attracted attention for its use in skin care products and functional foods. However, most studies have focused on the extract of CF seeds, which are relatively expensive, and none have investigated the effects of combining extraction and fermentation. In this study, we evaluated the utility of using extracts of different parts of CF, i.e., the leaves, stems, and unhulled and hulled seeds. We first made aqueous, ethanolic, methanolic, and ethyl acetate extracts of the four parts. After assessing their biological activities, we selected only unfermented and fermented CF leaf methanolic extracts for subsequent analysis. None of the concentrations of fermented CF leaf extract (≤400 mg/L) were cytotoxic, and all exhibited antioxidative, anti-inflammatory, antimicrobial, skin-whitening, moisturizing, and antiaging activities. The concentrations of protocatechuic acid, epicatechin, gallic acid, and quercetin increased the most after fermentation. Therefore, they were subjected to a molecular docking analysis, which revealed that quercetin and epicatechin may contribute the most to skin-whitening and antiaging properties, respectively. In conclusion, fermented CF leaf methanolic extracts can be useful as a functional ingredient in health foods, botanical drugs, and cosmetic products.

A novel assay platform consisting of a microfluidic sliding double-track paper-based chip and a hand-held Raspberry Pi detection system is proposed for determining the albumin-to-creatine ratio (ACR) in human urine. It is a clinically important parameter and can be used for the early detection of related diseases, such as renal insufficiency. In the proposed method, the sliding layer of the microchip is applied and the sample diffuses through two parallel filtration channels to the reaction/detection areas of the microchip to complete the detection reaction, which is a simple method well suited for self-diagnosis of ACR index in human urine. The RGB (red, green, and blue) value intensity signals of the reaction complexes in these two reaction zones are analyzed by a Raspberry Pi computer to derive the ACR value (ALB and CRE concentrations). It is shown that the G + B value intensity signal is linearly related to the ALB and CRE concentrations with the correlation coefficients of R2 = 0.9919 and R2 = 0.9923, respectively. It is additionally shown that the ALB and CRE concentration results determined using the proposed method for 23 urine samples were collected from real suffering chronic kidney disease (CKD) patients are in fine agreement with those acquired operating a traditional high-reliability macroscale method. Overall, for point-of-care (POC) CKD diagnosis and monitoring in clinical applications, the results prove that the proposed method offers a convenient, real time, reliable, and low-spending solution for POC CKD diagnosis.

p-Cresyl sulfate (PCS) is a uremic toxin that causes cardiovascular injury and progression in patients with chronic kidney disease (CKD). Peripheral arterial stiffness (PAS) as measured using the brachial-ankle pulse wave velocity (baPWV) is considered a valuable predictor of cardiovascular event risk in the general population. The study investigated the correlation between serum PCS levels and PAS (baPWV > 18.0 m/s) in 160 patients with stage 3–5 CKD. Liquid chromatography–mass spectrometry was used to assay serum PCS levels. PAS was detected in 54 patients (33.8%), and it was linked to older age, a higher prevalence of hypertension, higher systolic and diastolic blood pressure, higher serum calcium–phosphorus product and PCS levels, and lower height and body weight. Multivariable logistic regression analysis for independent factors associated with PAS illustrated that, in addition to age and diastolic blood pressure, serum PCS levels exhibited an odds ratio (OR) of 1.098 (95% confidence interval = 1.029–1.171, p = 0.005). These findings demonstrated that serum PCS levels were associated with PAS among patients with stage 3–5 CKD.

Abstract Background Sclerostin is known to be a canonical Wnt/β-catenin signaling pathway inhibitor, while the Wnt/β-catenin signaling pathway is proposed to be involved in the development of arterial stiffness. This study aims to investigate the relationship between serum sclerostin levels and carotid–femoral pulse wave velocity (cfPWV) among hypertensive patients. Methods Fasting blood samples were obtained from 105 hypertensive patients. Patients with cfPWV values of > 10 m/s were classified in the high arterial stiffness group, whereas those with cfPWV values of ≤10 m/s were assigned to the low arterial stiffness group. Serum sclerostin and Dickkopf-1 (DKK1) levels were quantified using commercially available enzyme-linked immunosorbent assays. Results Thirty-six hypertensive patients (34.3%) who belonged to the high arterial stiffness group were generally older (p

Abstract We assembled the sequences from deep RNA sequencing experiments by the Genotype-Tissue Expression (GTEx) project, to create a new catalog of human genes and transcripts, called CHESS. The new database contains 42,611 genes, of which 20,352 are potentially protein-coding and 22,259 are noncoding, and a total of 323,258 transcripts. These include 224 novel protein-coding genes and 116,156 novel transcripts. We detected over 30 million additional transcripts at more than 650,000 genomic loci, nearly all of which are likely nonfunctional, revealing a heretofore unappreciated amount of transcriptional noise in human cells. The CHESS database is available at http://ccb.jhu.edu/chess.

Abstract Background Escalating prevalence of autism spectrum disorders (ASD) in recent decades has triggered increasing efforts in understanding roles played by environmental risk factors as a way to address this widespread public health concern. Several epidemiological studies show associations between developmental exposure to traffic-related air pollution and increased ASD risk. In rodent models, a limited number of studies have shown that developmental exposure to ambient ultrafine particulates or diesel exhaust (DE) can result in behavioral phenotypes consistent with mild ASD. We performed a series of experiments to determine whether developmental DE exposure induces ASD-related behaviors in mice. Results C57Bl/6J mice were exposed from embryonic day 0 to postnatal day 21 to 250–300 μg/m3 DE or filtered air (FA) as control. Mice exposed developmentally to DE exhibited deficits in all three of the hallmark categories of ASD behavior: reduced social interaction in the reciprocal interaction and social preference tests, increased repetitive behavior in the T-maze and marble-burying test, and reduced or altered communication as assessed by measuring isolation-induced ultrasonic vocalizations and responses to social odors. Conclusions These findings demonstrate that exposure to traffic-related air pollution, in particular that associated with diesel-fuel combustion, can cause ASD-related behavioral changes in mice, and raise concern about air pollution as a contributor to the onset of ASD in humans.

Human activity recognition without equipment plays a vital role in smart home applications, freeing humans from the shackles of wearable devices. In this paper, by using the channel state information (CSI) of the WiFi signal, semi-supervised transfer learning with dynamic associate domain adaptation is proposed for human activity recognition. In order to improve the CSI quality and denoising of CSI, we carried out missing packet filling, burst noise removal, background estimation, feature extraction, feature enhancement, and data augmentation in the data pre-processing stage. This paper considers the problem of environment-independent human activity recognition, also known as domain adaptation. The pre-trained model is trained from the source domain by collecting a complete labeled dataset of all of the CSI of human activity patterns. Then, the pre-trained model is transferred to the target environment through the semi-supervised transfer learning stage. Therefore, when humans move to different target domains, a partial labeled dataset of the target domain is required for fine-tuning. In this paper, we propose a dynamic associate domain adaptation called DADA. By modifying the existing associate domain adaptation algorithm, the target domain can provide a dynamic ratio of labeled dataset/unlabeled dataset, while the existing associate domain adaptation algorithm only allows target domains with the unlabeled dataset. The advantage of DADA is that it provides a dynamic strategy to eliminate different effects on different environments. In addition, we further designed an attention-based DenseNet model, or AD, as our training network, which is modified by an existing DenseNet by adding the attention function. The solution we proposed was simplified to DADA-AD throughout the paper. The experimental results show that for domain adaptation in different domains, the accuracy of human activity recognition of the DADA-AD scheme is 97.4%. It also shows that DADA-AD has advantages over existing semi-supervised learning schemes.

The use of a threshold-switching Ni/NbO2/Ni device with a memory-switching Pt/magnesium zirconate titanate/Al device on a flexible substrate was proposed to suppress undesired sneak currents. The proposed flexible one selector and one resistor (1S1R) memory device exhibits a low operation voltage, good ON/OFF ratio of 105, uniform current distribution, excellent flexibility, and stable I-V curve at 85 °C. The good selection and memory properties of the flexible 1S1R memory device are highly promising for high-density and low-power flexible electronic applications.

The technique of active ionospheric sounding by ionosondes requires sophisticated methods for the recovery of experimental data on ionograms. In this work, we applied an advanced algorithm of deep learning for the identification and classification of signals from different ionospheric layers. We collected a dataset of 6131 manually labeled ionograms acquired from low-latitude ionosondes in Taiwan. In the ionograms, we distinguished 11 different classes of the signals according to their ionospheric layers. We developed an artificial neural network, FC-DenseNet24, based on the FC-DenseNet convolutional neural network. We also developed a double-filtering algorithm to reduce incorrectly classified signals. That made it possible to successfully recover the sporadic E layer and the F2 layer from highly noise-contaminated ionograms whose mean signal-to-noise ratio was low, SNR = 1.43. The Intersection over Union (IoU) of the recovery of these two signal classes was greater than 0.6, which was higher than the previous models reported. We also identified three factors that can lower the recovery accuracy: (1) smaller statistics of samples; (2) mixing and overlapping of different signals; (3) the compact shape of signals.

In recent years, microfluidic lab-on-paper devices have emerged as a rapid and low-cost alternative to traditional laboratory tests. Additionally, they were widely considered as a promising solution for point-of-care testing (POCT) at home or regions that lack medical infrastructure and resources. This review describes important advances in microfluidic lab-on-paper diagnostics for human health monitoring and disease diagnosis over the past five years. The review commenced by explaining the choice of paper, fabrication methods, and detection techniques to realize microfluidic lab-on-paper devices. Then, the sample pretreatment procedure used to improve the detection performance of lab-on-paper devices was introduced. Furthermore, an in-depth review of lab-on-paper devices for disease measurement based on an analysis of urine samples was presented. The review concludes with the potential challenges that the future development of commercial microfluidic lab-on-paper platforms for human disease detection would face.

Abstract This paper describes the preparation of nanoarrays composed of silver nanoparticles (AgNPs: 20–50 nm) for use as surface-enhanced Raman scattering (SERS) substrates. The AgNPs were grown on porous anodic aluminum oxide (AAO) templates by electrochemical plating, and the inter-channel gap of AAO channels is between 10 and 20 nm. The size and interparticle gap of silver particles were adjusted in order to achieve optimal SERS signals and characterized by scanning electron microscopy, atomic force microscopy, and Raman spectroscopy. The fluctuation of SERS intensity is about 10–20% when measuring adenine solutions, showing a great reproducible SERS sensing. The nanoparticle arrays offer a large potential for practical applications as shown by the SERS-based quantitative detection and differentiation of adenine (A), thymine (T), cytosine (C), guanine (G), β-carotene, and malachite green. The respective detection limits are

In this research, the Taguchi method was used to optimize the detection accuracy and reproducibility of an immunodetection system used for a quantitative analysis of a rapid test. Furthermore, the standard deviation (SD) and coefficient of variation (CV) between the theoretical value and the measured value of the self-made simulated rapid test became smaller, and the linearity became higher. The results thus indicated that the immunodetection system became more reliable. In the present research, a camera was used to capture an image containing the control line (C line) and the test line (T line) in the self-made simulated rapid test. The captured image was then analyzed, and the grayscales of the C line and T line were calculated. The Taguchi method was used to adjust the light intensity of the light-emitting diode (LED) and the camera parameters in the immunodetection system to determine the optimal parameters by which to optimize the performance of the immunodetection system. The goal of the present research was to obtain a measurement with a minimum SD and CV between the detected grayscales and the grayscales of the self-made simulated rapid test, thus indicating successful development of a practical, stable, and accurate immunodetection system. To mimic the color expression in an actual rapid test, the ratio of the red, green, blue (RGB) components of the self-made simulated rapid test had to be adjusted to closely fit the color expression of the actual rapid test. After the RGB ratio was set, the Taguchi method was used to optimize the parameters for the purpose of detection. When the optimal parameters were found, the signal-to-noise ratio (S/N ratio) had been increased from −12.89 dB to −10.91 dB, which means the accuracy of the color detection had been improved. Compared to the original detection system, the quality loss had been reduced to 33.1%.

In this paper, a rapid test system with high sensitivity, linearity, and stability is presented for fecal occult blood (FOB) detection. The coloration results of the immune response are used as the basis for the determination of the detection target in combination with an immunochromatographic strip. The rapid test system can be used to detect and calculate the concentration of the sample, so detection of the immune coloration response is more accurate in a quantitative analysis. The system is composed of both hardware and software. The programs used for the analysis and programmed by Python include the main program, polarization calibration, QR Code decoding, Bluetooth transmission, and image processing. After verification of each part of the system, it was found that the rapid test system successfully detects from 0 ng/mL to 400 ng/mL of FOB with coefficients of variation (CV) below 3.7% and 1000 ng/mL with a CV only at 7.41%.

Coliform bacteria are indicators of water quality; however, most detection methods for coliform bacteria are time-consuming and nonspecific. Here, we developed a fluorescence in situ hybridization (FISH) approach to detect four types of coliform bacteria, including Escherichia coli, Klebsiella pneumoniae, Enterobacter aerogenes, and Citrobacter freundii, simultaneously in water samples using specific probes for 16S rRNA. This FISH method was applied to detect coliform bacteria in simulated water and domestic wastewater samples and compared with traditional detection methods (e.g., plate counting, multiple-tube fermentation (MTF) technique, and membrane filter (MF) technique). Optimal FISH conditions for detecting the four types of coliforms were found to be fixation in 3% paraformaldehyde at 4 °C for 2 h and hybridization at 50 °C for 1.5 h. By comparing FISH with plate counting, MTF, MF, and a commercial detection kit, we found that FISH had the shortest detection time and highest accuracy for the identification of coliform bacteria in simulated water and domestic wastewater samples. Moreover, the developed method could simultaneously detect individual species and concentrations of coliform bacteria. Overall, our findings indicated that FISH could be used as a rapid, accurate biosensor system for simultaneously detecting four types of coliform bacteria to ensure water safety.