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Adipose-derived stem cells (ADSCs) comprise a promising therapy for osteoarthritis (OA). The therapeutic potential of ELIXCYTE®, an allogeneic human ADSC (hADSC) product, was demonstrated in a phase I/II OA clinical trial. However, the exact mechanism underlying such effects is not clear. Moreover, studies suggest that interleukin-11 (IL-11) has anti-inflammatory, tissue-regenerative, and immune-regulatory functions. Our aim was to unravel the mechanism associated with the therapeutic effects of ELIXCYTE® on OA and its relationship with IL-11. We cocultured ELIXCYTE® with normal human articular chondrocytes (NHACs) in synovial fluid obtained from individuals with OA (OA-SF) to investigate its effect on chondrocyte matrix synthesis and degradation and inflammation by assessing gene expression and cytokine levels. NHACs exposed to OA-SF exhibited increased MMP13 expression. However, coculturing ELIXCYTE® with chondrocytes in OA-SF reduced MMP13 expression in chondrocytes and downregulated PTGS2 and FGF2 expression in ELIXCYTE®. ELIXCYTE® treatment elevated anti-inflammatory cytokine (IL-1RA, IL-10, and IL-13) levels, and the reduction in MMP13 was positively correlated with IL-11 concentrations in OA-SF. These findings indicate that IL-11 in OA-SF might serve as a predictive biomarker for the ELIXCYTE® treatment response in OA, emphasizing the therapeutic potential of ELIXCYTE® to mitigate OA progression and provide insights into its immunomodulatory effects.

This study proposed an improved full-scale aggregated MobileUNet (FA-MobileUNet) model to achieve more complete detection results of oil spill areas using synthetic aperture radar (SAR) images. The convolutional block attention module (CBAM) in the FA-MobileUNet was modified based on morphological concepts. By introducing the morphological attention module (MAM), the improved FA-MobileUNet model can reduce the fragments and holes in the detection results, providing complete oil spill areas which were more suitable for describing the location and scope of oil pollution incidents. In addition, to overcome the inherent category imbalance of the dataset, label smoothing was applied in model training to reduce the model’s overconfidence in majority class samples while improving the model’s generalization ability. The detection performance of the improved FA-MobileUNet model reached an mIoU (mean intersection over union) of 84.55%, which was 17.15% higher than that of the original U-Net model. The effectiveness of the proposed model was then verified using the oil pollution incidents that significantly impacted Taiwan’s marine environment. Experimental results showed that the extent of the detected oil spill was consistent with the oil pollution area recorded in the incident reports.

This study conducted adsorption experiments using Europium (Eu(III)) on geological materials collected from Taiwan. Batch tests on argillite, basalt, granite, and biotite showed that argillite and basalt exhibited strong adsorption reactions with Eu. X-ray diffraction (XRD) analysis also clearly indicated differences before and after adsorption. By combining X-ray absorption near-edge structure (XANES), extended X-ray absorption fine structure (EXAFS), and wavelet transform (WT) analyses, we observed that the Fe2O3 content significantly affects the Eu-Fe distance in the inner-sphere layer during the Eu adsorption process. The wavelet transform analysis for two-dimensional information helps differentiate two distances of Eu-O, which are difficult to analyze, with hydrated outer-sphere Eu-O distances ranging from 2.42 to 2.52 Å and inner-sphere Eu-O distances from 2.27 to 2.32 Å. The EXAFS results for Fe2O3 and SiO2 in argillite and basalt reveal different adsorption mechanisms. Fe2O3 exhibits inner-sphere surface complexation in the order of basalt, argillite, and granite, while SiO2 forms outer-sphere ion exchange with basalt and argillite. Wavelet transform analysis also highlights the differences among these materials.

Although the Japanese encephalitis virus (JEV) infects various cell types, its receptor molecules are still not clearly understood. In our laboratory’s prior research, Rab4b was identified as a potential host factor that facilitates JEV infection in PK15 cells, utilizing a genome-wide CRISPR/Cas9 knockout library (PK-15-GeCKO). To further explore the effect of Rab4b on JEV replication, we used the Rab4b knockout PK15 cell line using the CRISPR/Cas9 technology and overexpressing the Rab4b PK15 cell line, with IFA, RT–qPCR, and Western blot to study the effect of Rab4b on viral replication in the whole life cycle of the JEV. The results show that the knockout of Rab4b inhibited the replication of the JEV in PK15 cells, and the overexpression of Rab4b promoted the replication of the JEV in PK15 cell lines. Furthermore, we demonstrated for the first time that host factor Rab4b facilitates the adsorption, internalization, assembly, and release of the JEV, thereby promoting JEV replication. This study enriches the regulatory network between the JEV and host factors and lays the experimental foundation for further understanding of the function of the Rab4b protein.

This research introduces a novel approach using silver (Ag) nanostructures generated through electrochemical deposition and photo-reduction of Ag on fluorine-doped tin oxide glass substrates (denoted as X-Ag-AgyFTO, where ‘X’ and ‘y’ represent the type of light source and number of deposited cycles, respectively) for surface-enhanced Raman spectroscopy (SERS). This study used malachite green (MG) as a Raman probe to evaluate the enhancement factors (EFs) in SERS-active substrates under varied fabrication conditions. For the substrates produced via electrochemical deposition, we determined a Raman EF of 6.15 × 104 for the Ag2FTO substrate. In photo-reduction, the impact of reductant concentration, light source, and light exposure duration were examined on X-Ag nanoparticle formation to achieve superior Raman EFs. Under optimal conditions (9.0 mM sodium citrate, 460 nm blue-LED at 10 W for 90 min), the combination of blue-LED-reduced Ag (B-Ag) and an Ag2FTO substrate (denoted as B-Ag-Ag2FTO) exhibited the best Raman EF of 2.79 × 105. This substrate enabled MG detection within a linear range of 0.1 to 1.0 µM (R2 = 0.98) and a detection limit of 0.02 µM. Additionally, the spiked recoveries in aquaculture water samples were between 90.0% and 110.0%, with relative standard deviations between 3.9% and 6.3%, indicating the substrate’s potential for fungicide detection in aquaculture.

Oil spills are a major threat to marine and coastal environments. Their unique radar backscatter intensity can be captured by synthetic aperture radar (SAR), resulting in dark regions in the images. However, many marine phenomena can lead to erroneous detections of oil spills. In addition, SAR images of the ocean include multiple targets, such as sea surface, land, ships, and oil spills and their look-alikes. The training of a multi-category classifier will encounter significant challenges due to the inherent class imbalance. Addressing this issue requires extracting target features more effectively. In this study, a lightweight U-Net-based model, Full-Scale Aggregated MobileUNet (FA-MobileUNet), was proposed to improve the detection performance for oil spills using SAR images. First, a lightweight MobileNetv3 model was used as the backbone of the U-Net encoder for feature extraction. Next, atrous spatial pyramid pooling (ASPP) and a convolutional block attention module (CBAM) were used to improve the capacity of the network to extract multi-scale features and to increase the speed of module calculation. Finally, full-scale features from the encoder were aggregated to enhance the network’s competence in extracting features. The proposed modified network enhanced the extraction and integration of features at different scales to improve the accuracy of detecting diverse marine targets. The experimental results showed that the mean intersection over union (mIoU) of the proposed model reached more than 80% for the detection of five types of marine targets including sea surface, land, ships, and oil spills and their look-alikes. In addition, the IoU of the proposed model reached 75.85 and 72.67% for oil spill and look-alike detection, which was 18.94% and 25.55% higher than that of the original U-Net model, respectively. Compared with other segmentation models, the proposed network can more accurately classify the black regions in SAR images into oil spills and their look-alikes. Furthermore, the detection performance and computational efficiency of the proposed model were also validated against other semantic segmentation models.

Numerous studies have considered galectin-3 or Glycogen synthase kinase 3 beta (GSK3B) as a potential prognosis marker for various cancers. However, the correlation between the protein expression of galectin-3/GSK3B and the clinical parameters of astrocytoma has not been reported. This study aims to validate the correlation between the clinical outcomes and protein expression of galectin-3/GSK3B in astrocytoma. Immunohistochemistry staining was performed to detect galectin-3/GSK3B protein expression in patients with astrocytoma. The Chi-square test, Kaplan−Meier evaluation, and Cox regression analysis were used to determine the correlation between clinical parameters and galectin-3/GSK3B expression. Cell proliferation, invasion, and migration were compared between a non-siRNA group and a galectin-3/GSK3B siRNA group. Protein expression in galectin-3 or GSK3B siRNA-treated cells was evaluated using western blotting. Galectin-3 and GSK3B protein expression were significantly positively correlated with the World Health Organization (WHO) astrocytoma grade and overall survival time. Multivariate analysis revealed that WHO grade, galectin-3 expression, and GSK3B expression were independent prognostic factors for astrocytoma. Galectin-3 or GSK3B downregulation induced apoptosis and decreased cell numbers, migration, and invasion. siRNA-mediated gene silencing of galectin-3 resulted in the downregulation of Ki-67, cyclin D1, VEGF, GSK3B, p-GSK3B Ser9 (p-GSK3B S9), and β-catenin. In contrast, GSK3B knockdown only decreased Ki-67, VEGF, p-GSK3B S9, and β-catenin protein expression but did not affect cyclin D1 and galectin-3 protein expression. The siRNA results indicated that GSK3B is downstream of the galectin-3 gene. These data support that galectin-3 mediated tumor progression by upregulating GSK3B and β-catenin protein expression in glioblastoma. Therefore, galectin-3 and GSK3B are potential prognostic markers, and their genes may be considered to be anticancer targets for astrocytoma therapy.

Vitiligo, a psychologically distressing pigmentary disorder characterized by white depigmented patches due to melanocyte loss, necessitates non-invasive tools for early detection and treatment response monitoring. High-cellular-resolution full-field optical coherence tomography (CRFF-OCT) is emerging in pigmentary disorder assessment, but its applicability in vitiligo repigmentation after tissue grafting remains unexplored. To investigate the feasibility of CRFF-OCT for evaluating vitiligo lesions following tissue grafting, our investigation involved ten vitiligo patients who underwent suction blister epidermal grafting and laser ablation at a tertiary center between 2021 and 2022. Over a six-month period, clinical features, dermoscopy, and photography data were recorded. Utilizing CRFF-OCT along with artificial intelligence (AI) applications, repigmentation features were captured and analyzed. The CRFF-OCT analysis revealed a distinct dark band in vitiligo lesion skin, indicating melanin loss. Grafted areas exhibited melanocytes with dendrites around the epidermal-dermal junction and hair follicles. CRFF-OCT demonstrated its efficacy in the early detection of melanocyte recovery and accurate melanin quantification. This study introduces CRFF-OCT as a real-time, non-invasive, and in vivo evaluation tool for assessing vitiligo repigmentation, offering valuable insights into pigmentary disorders and treatment responses.

Although the expression of p53 and epidermal growth factor receptor (EGFR) is associated with therapeutic resistance and patient outcomes in many malignancies, the relationship in astrocytomas is unclear. This study aims to correlate p53 and EGFR expression in brain astrocytomas with overall patient survival. Eighty-two patients with astrocytomas were enrolled in the study. Semi-quantitative p53 and EGFR immunohistochemical staining was measured in tumor specimens. The mean follow-up after astrocytoma surgery was 18.46 months. The overall survival rate was 83%. Survival was reduced in EGFR-positive patients compared with survival in EGFR-negative patients (p < 0.05). However, no significant differences in survival were detected between patients with high and low p53 expression. In patients with low p53 expression, positive EGFR staining was associated with significantly worse survival compared with patients with negative EGFR staining (log-rank test: p < 0.001). Survival rates in positive and negative EGFR groups with high p53 protein expression were similar (log-rank test: p = 0.919). The IC50 of an EGFR inhibitor was higher in GBM cells with high p53 protein expression compared with the IC50 in cells with low p53 expression. Combined EGFR and p53 expression may have prognostic significance in astrocytomas.

Accumulative evidence suggests metabolic disorders correlate with prostate cancer. Metabolic profiling of urine allows the measurement of numerous metabolites simultaneously. This study set up a metabolomic platform consisting of UPLC-FTMS and UPLC-ion trap MSn for urine metabolome analysis. The platform improved retention time, mass accuracy, and signal stability. Additionally, the product ion spectrum obtained from ion trap MSn facilitated structure elucidation of candidate metabolites, especially when authentic standards were not available. Urine samples from six hernia patients and six BPH patients were used for the initial establishment of the analytic platform. This platform was further employed to analyze the urine samples of 27 PCa and 49 BPH patients. Choosing the upper and lower 16% of metabolites, 258 metabolite candidates were selected. Twenty-four of them with AUC values larger than 0.65 were further selected. Eighteen of the twenty-four features can be matched in METLIN and HMDB. Eleven of the eighteen features can be interpreted by MSn experiments. They were used for the combination achieving the best differential power. Finally, four metabolites were combined to reach the AUC value of 0.842 (CI 95, 0.7559 to 0.9279). This study demonstrates the urinary metabolomic analysis of prostate cancer and sheds light on future research.

5-FU-based chemoradiotherapy (CRT) and oxaliplatin-based CRT are commonly used therapies for advanced colorectal cancer (CRC). However, patients with a high expression of ERCC1 have a worse prognosis than those with a low expression. In this study, we investigated the effect of XPF–ERCC1 blockers on chemotherapy and 5-FU-based CRT and oxaliplatin (OXA)-based CRT in colorectal cancer cell lines. We investigated the half-maximal inhibitory concentration (IC50) of 5-FU, OXA, XPF–ERCC1 blocker, and XPF–ERCC1 blocker, and 5-FU or OXA combined and analyzed the effect of XPF–ERCC1 blocker on 5-FU-based CRT and oxaliplatin-based CRT. Furthermore, the expression of XPF and γ-H2AX in colorectal cells was analyzed. In animal models, we combined the XPF–ERCC1 blocker with 5-FU and OXA to investigate the effects of RC and finally combined the XPF–ERCC1 blocker with 5-FU- and oxaliplatin-based CRT. In the IC50 analysis of each compound, the cytotoxicity of the XPF–ERCC1 blocker was lower than that of 5-FU and OXA. In addition, the XPF–ERCC1 blocker combined with 5-FU or OXA enhanced the cytotoxicity of the chemotherapy drugs in colorectal cells. Furthermore, the XPF–ERCC1 blocker also increased the cytotoxicity of 5-FU-based CRT and OXA -based CRT by inhibiting the XPF product DNA locus. In vivo, the XPF–ERCC1 blocker was confirmed to enhance the therapeutic efficacy of 5-FU, OXA, 5-FU-based CRT, and OXA CRT. These findings show that XPF–ERCC1 blockers not only increase the toxicity of chemotherapy drugs but also increase the efficacy of combined chemoradiotherapy. In the future, the XPF–ERCC1 blocker may be used to improve the efficacy of 5-FU- and oxaliplatin-based CRT.

Since the fall was often occurred in elders daily, this paper focused on gait analysis with fall detection to develop a wearable device. To ensure that the mobile application, APP, could be used in different platform of mobile phone, such Android or iOS, the designed wearable device also could be used in cross-platform in mobile phone. Therefore, a cross-platform gait analysis and fall detection wearable device (CPGAFDWD) was proposed. Since CPGAFDWD APP was used in web browser without limiting to platform, it could be used for different platforms of mobile phone. The gait analysis could be detected at home. The fall detection also could be executed in any place immediately. The patients and medical staff all could query the status of rehabilitation in any place and any time via the Internet. The experimental results showed that the correct rate of gait analysis and fall detection could be up to 90% in cross-platform of mobile phone. In the future, CPGAFDWD will be planned to be verified by Institutional Review Board, IRB, for clinical treatment.

Cancers of the urinary tract are one of the most common malignancies worldwide, causing high morbidity and mortality, and representing a social burden. Upper tract urothelial carcinoma (UTUC) accounts for 5–10% of urinary tract cancers, and its oncogenic mechanisms remain elusive. We postulated that cancers of the lower and the upper urinary tract may share some important oncogenic mechanisms. Therefore, the oncogenic mechanisms discovered in the lower urinary tract may guide the investigation of molecular mechanisms in the upper urinary tract. Based on this strategy, we revisited a high-quality transcriptome dataset of 510 patients with non-muscle invasive bladder cancer (NMIBC), and performed an innovative gene set enrichment analysis of the transcriptome. We discovered that the epigenetic regulation of polycomb repressive complex 2 (PRC2) is responsible for the recurrence and progression of lower-track urinary cancers. Additionally, a PRC2-related gene signature model was discovered to be effective in classifying bladder cancer patients with distinct susceptibility of subsequent recurrence and progression (log-rank p < 0.001 and = 0.001, respectively). We continued to discover that the same model can differentiate stage T3 UTUC patients from stage Ta/T1 patients (p = 0.026). Immunohistochemical staining revealed the presence of PRC2 components (EZH2, EED, and SUZ12) and methylated PRC2 substrates (H3K27me3) in the archived UTUC tissues. The H3K27me3 exhibited higher intensity and area intensity product in stage T3 UTUC tissues than in stage Ta/T1 tissues (p = 0.006 and 0.015, respectively), implicating stronger PRC2 activity in advanced UTUC. The relationship between H3K27 methylation and gene expression is examined using correlations. The H3K27me3 abundance is positively correlated with the expression levels of CDC26, RP11-2B6, MAPK1IP1L, SFR1, RP11-196B3, CDK5RAP2, ANXA5, STX11, PSMD5, and FGFRL1. It is also negatively correlated with CNPY2, KB-1208A12, RP11-175B9, ZNF692, RANP8, RP11-245C17, TMEM266, FBXW9, SUGT1P2, and PRH1. In conclusion, PRC2 and its epigenetic effects are major oncogenic mechanisms underlying both bladder cancer and UTUC. The epigenetically regulated genes of PRC2 in urothelial carcinoma were also elucidated using correlation statistics.

Climate change and global warming lead to changes in the sea level and shoreline, which pose a huge threat to island regions. Therefore, it is important to effectively detect the shoreline changes. Taiwan is a typical island, located at the junction of the East China Sea and the South China Sea in the Pacific Northwest, and is deeply affected by shoreline changes. In this research, Taiwan was selected as the study area. In this research, an efficient shoreline detection method was proposed based on the semantic segmentation U-Net model using the Sentinel-1 synthetic aperture radar (SAR) data of Taiwan island. In addition, the batch normalization (BN) module was added to the convolution layers in the U-Net architecture to further improve the generalization ability of U-Net and accelerate the training process. A self-built shoreline dataset was introduced to train the U-Net model and test its detection efficiency. The dataset consists of a total of 4029 SAR images covering all coastal areas of Taiwan. The training samples of the dataset were annotated by morphological processing and manual inspection. The segmentation results of U-Net were then processed by edge detection and morphological postprocessing to extract the shoreline. The experimental results showed that the proposed method could achieve a satisfactory detection performance compared with the related methods using the data provided by the Ministry of the Interior of Taiwan from 2016 to 2019 for different coastal landforms in Taiwan. Within a 5-pixel difference between the detected shoreline and the ground truth data, the F1-Meaure of the proposed method exceeded 80%. In addition, the potential of this method in shoreline change detection was validated with a sandbar located on the southwestern coast of Taiwan. Finally, the entire shoreline of Taiwan has been described by the proposed approach and the detected shoreline length was close to the actual length.

A cross-docking system is a kind of facility design for the purpose of enhancing the time efficiency of a distribution center. In this study, we attempt to consider a cross-docking system without temporary storage and obtain great system performance by addressing the scheduling problem of inbound and outbound trucks, in which the total operation time of trucks is minimized. In order to reduce computational efforts, three hybrid metaheuristic approaches based on particle swarm optimization, simulated annealing, and a variable neighborhood search are proposed. By the computational experiments, the three optimized approaches are analyzed and compared with each other. The experimental results show that all of these three approaches can obtain pretty good solutions, even in the large-scale examples. Moreover, one of these approaches—a hybrid metaheuristic with particle swarm optimization and a variable neighborhood search—can usually obtain the best solutions.

In the industrial Internet of Things, the network time protocol (NTP) can be used for time synchronization, allowing machines to run in sync so that machines can take critical actions within 1 ms. However, the commonly used NTP mechanism does not take into account that the network packet travel time over a link is time-varying, which causes the NTP to make incorrect synchronization decisions. Therefore, this paper proposed a low-cost modification to NTP with clock skew compensation and adaptive clock adjustment, so that the clock difference between the NTP client and NTP server can be controlled within 1 ms in the wired network environment. The adaptive clock adjustment skips the clock offset calculation when the NTP packet run trip time (RTT) exceeds a certain threshold. The clock skew compensation addresses the inherent issue that different clocks (or oscillators) naturally drift away from each other. Both adaptive clock adjustment and clock skew compensation are environment dependent and device dependent. The measurement result in our experimental environment shows that the when the RTT threshold is set at 1.7 ms, the best synchronization accuracy is achieved.

Being one of the renal replacement therapies, peritoneal dialysis (PD) maintains around 15% of end-stage kidney disease patients’ lives; however, complications such as peritoneal fibrosis and ultrafiltration failure during long-term PD compromise its application. Previously, we established a sodium hypochlorite (NaClO)-induced peritoneal fibrosis porcine model, which helped to bridge the rodent model toward pre-clinical human peritoneal fibrosis research. In this study, the peritoneal equilibration test (PET) was established to evaluate instant functional changes in the peritoneum in the pig model. Similar to observations from long-term PD patients, increasing small solutes transport and loss of sodium sieving were observed. Mechanistic investigation from both in vivo and in vitro data suggested that disruption of cytoskeleton induced by excessive reactive oxygen species defected intracellular transport of aquaporin 1, this likely resulted in the disappearance of sodium sieving upon PET. Functional interference of aquaporin 1 on free water transport would result in PD failure in patients.

Acute lung injury (ALI) is a high mortality disease with acute inflammation. Corylin is a compound isolated from the whole plant of Psoralea corylifolia L. and has been reported to have anti-inflammatory activities. Herein, we investigated the therapeutic potential of corylin on lipopolysaccharides (LPS)-induced ALI, both in vitro and in vivo. The levels of proinflammatory cytokine secretions were analyzed by ELISA; the expressions of inflammation-associated proteins were detected using Western blot; and the number of immune cell infiltrations in the bronchial alveolar lavage fluid (BALF) were detected by multicolor flow cytometry and lung tissues by hematoxylin and eosin (HE) staining, respectively. Experimental results indicated that corylin attenuated LPS-induced IL-6 production in human bronchial epithelial cells (HBEC3-KT cells). In intratracheal LPS-induced ALI mice, corylin attenuated tissue damage, suppressed inflammatory cell infiltration, and decreased IL-6 and TNF-α secretions in the BALF and serum. Moreover, it further inhibited the phosphorylation of mitogen-activated protein kinases (MAPKs), including p-JNK, p-ERK, p-p38, and repressed the activation of signal transducer and activator of transcription 3 (STAT3) in lungs. Collectively, our results are the first to demonstrate the anti-inflammatory effects of corylin on LPS-induced ALI and suggest corylin has significant potential as a novel therapeutic agent for ALI.

The inflammatory cytokine interleukin-26 (IL-26) is highly expressed in the serum and synovial fluid of patients with inflammatory arthritis. The effect of IL-26 on human articular chondrocytes (HACs) remains unclear. Obesity is associated with disability of patients with rheumatoid arthritis and disease activity in those with ankylosing spondylitis. The saturated free fatty acid palmitate with IL-1β can synergistically induce catabolic effects in HACs. The aim of this study was to evaluate the effects of IL-26 and palmitate in HACs. In this study, palmitate markedly synergizes the IL-26-induced proinflammatory effects and matrix protease, including COX-2, IL-6, and MMP-1, in HACs via the toll-like receptor 4 (TLR4)-ERK1/2-c-Jun signal transduction pathway. The synergistic catabolic effects of palmitate and IL-26 were attenuated by inhibitors of TLR4 (TAK242), ERK1/2 (U0126), or c-Jun (SP600125) in HACs and cartilage matrix. In addition, metformin, a potential inhibitor of TLR4, also decreased expression of COX-2 and IL-6 induced by co-incubation with IL-26 and palmitate. IL-26 and palmitate synergistically induced expression of inflammatory and catabolic mediators, resulting in articular cartilage matrix breakdown. The present study also revealed a possible mechanism and therapeutic targets against articular cartilage degradation by increased saturated fatty acids in patients with inflammatory arthritis.

Piplartine (or Piperlongumine) is a natural alkaloid isolated from Piper longum L., which has been proposed to exhibit various biological properties such as anti-inflammatory effects; however, the effect of piplartine on sepsis has not been examined. This study was performed to examine the anti-inflammatory activities of piplartine in vitro, ex vivo and in vivo using murine J774A.1 macrophage cell line, peritoneal macrophages, bone marrow-derived macrophages and an animal sepsis model. The results demonstrated that piplartine suppresses iNOS and COX-2 expression, reduces PGE2, TNF-α and IL-6 production, decreases the phosphorylation of MAPKs and NF-κB and attenuates NF-κB activity by LPS-activated macrophages. Piplartine also inhibits IL-1β production and suppresses NLRP3 inflammasome activation by LPS/ATP- and LPS/nigericin-activated macrophages. Moreover, piplartine reduces the production of nitric oxide (NO) and TNF-α, IL-6 and IL-1β, decreases LPS-induced tissue damage, attenuates infiltration of inflammatory cells and enhances the survival rate. Collectively, these results demonstrate piplartine exhibits anti-inflammatory activities in LPS-induced inflammation and sepsis and suggest that piplartine might have benefits for sepsis treatment.

This study proposed a feature-based decision method for the mapping of rice cultivation by using the time-series C-band synthetic aperture radar (SAR) data provided by Sentinel-1A. In this study, a model related to crop growth was first established. The model was developed based on a cubic polynomial function which was fitted by the complete time-series SAR backscatters during the rice growing season. From the developed model, five rice growth-related features were introduced, including backscatter difference (BD), time interval (TI) between vegetative growth and maturity stages, backscatter variation rate (BVR), average normalized backscatter (ANB) and maximum backscatter (MB). Then, a decision method based on the combination of the five extracted features was proposed to improve the rice detection accuracy. In order to verify the detection performance of the proposed method, the test data set of this study consisted of 50,000 rice and non-rice fields which were randomly sampled from a research area in Taiwan for simulation verification. From the experimental results, the proposed method can improve overall accuracy in rice detection by 6% compared with the method using feature BD. Furthermore, the rice detection efficiency of the proposed method was compared with other four classifiers, including decision tree (DT), support vector machine (SVM), K-nearest neighbor (KNN) and quadratic discriminant analysis (QDA). The experimental results show that the proposed method has better rice detection accuracy than the other four classifiers, with an overall accuracy of 91.9%. This accuracy is 3% higher than fine SVM, which performs best among the other four classifiers. In addition, the consistency and effectiveness of the proposed method in rice detection have been verified for different years and studied regions.

Background: Sepsis is a leading cause of mortality in intensive care units (ICUs). Cell-free hemoglobin (CFH) released during sepsis interacts with lysosomal enzymes from neutrophils and macrophages. This study aims to examine the association of LVV-hemorphin-7 (LVV-H7), cathepsin D, and cathepsin G with sepsis and shock in ICU patients. Methods: A prospective observational cohort study was conducted in the medical ICU of a tertiary referral hospital in Taiwan. The patients with an acute increasing sequential organ failure assessment (SOFA) score ≥ 2 between 2022 and 2023. Blood samples from 40 healthy controls were obtained from the hospital biobank. CFH metabolites, including LVV-H7 and lysosomal enzyme cathepsin D and cathepsin G, were compared between the sepsis (definite and probable) and non-sepsis (possible sepsis) groups. Multivariate logistic regression analyzed factors associated with sepsis and shock. Results: Among 120 patients, 75 were classified as septic and 45 as non-septic. Significant differences were observed in CFH, cathepsin D, cathepsin G, and LVV-H7 levels between sepsis and non-sepsis groups. LVV-H7 was a significant predictor for sepsis (adjusted OR [aOR] 1.009, 95% CI 1.005–1.013; p < 0.001) and shock (aOR 1.005, 95% CI 1.002–1.008; p < 0.05). Cathepsin G predicted non-shock (aOR 0.917, 95% CI 0.848–0.991; p < 0.05), while cathepsin D predicted septic shock (aOR 1.001, 95% CI 1.000–1.002; p < 0.05). Conclusions: LVV-H7, cathepsin D, and cathepsin G are associated with the classification of sepsis and shock episodes in critically ill patients with elevated SOFA scores.

Mercury ion selective membrane (Hg-ISM) coated extended gate Field Effect transistors (ISM-FET) were used to manifest a novel methodology for ion-selective sensors based on FET’s, creating ultra-high sensitivity (−36 mV/log [Hg2+]) and outweighing ideal Nernst sensitivity limit (−29.58 mV/log [Hg2+]) for mercury ion. This highly enhanced sensitivity compared with the ion-selective electrode (ISE) (10−7 M) has reduced the limit of detection (10−13 M) of Hg2+ concentration’s magnitude to considerable orders irrespective of the pH of the test solution. Systematical investigation was carried out by modulating sensor design and bias voltage, revealing that higher sensitivity and a lower detection limit can be attained in an adequately stronger electric field. Our sensor has a limit of detection of 10−13 M which is two orders lower than Inductively Coupled Plasma Mass Spectrometry (ICP-MS), having a limit of detection of 10−11 M. The sensitivity and detection limit do not have axiomatic changes under the presence of high concentrations of interfering ions. The technology offers economic and consumer friendly water quality monitoring options intended for homes, offices and industries.

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments.

MALDI-TOF MS provides rapid and sensitive analyses of larger biomolecules. However, MS analyses of polysaccharide have been reported to have lower sensitivity compared to peptides and proteins. Here, we investigated some polysaccharides chemically derivatized by permethylation and ortho-phenylene diamine (OPD) tagging. Methylated glycan is obviously able to improve the sensitivity for mass spectrometry detection. Oxidative condensation by UV-activation tagging to saccharides by OPD and peptide-OPD also improve the sensitivity of MALDI-TOF MS analyses. Polysaccharides including dextran, glucomannan, arabinoxylan, arabinogalactan and beta-1,3-glucan, isolated from nutritional supplements of Ganoderma lucidum and Saccharomyces pastorianus were measured using MALDI-TOF MS with 2,5-dihydroxybenzoic acid (2,5-DHB) as the matrix. These glycans were also derivatized to methylated and benzimidazole-tagged glycans by chemical transformation for molecular weight analysis. The derivatized polysaccharides showed excellent MALDI-TOF MS signal enhancement in the molecular weight range from 1 to 5 kDa. Here, we demonstrate an efficient method to give glycan-benzimidazole (glycan-BIM) derivatives for polysaccharide determination in MALDI-TOF MS. Therefore, permethylated or benzimidazole-derivatized polysaccharides provide a new option for polysaccharide analysis using MALDI-TOF MS.

Metal nanoparticles are extensively studied due to their unique chemical and physical properties, which differ from the properties of their respective bulk materials. Likewise, the properties of heterogeneous bimetallic structures are far more attractive than those of single-component nanoparticles. For example, the incorporation of a second metal into a nanoparticle structure influences and can potentially enhance the optical/plasmonic and magnetic properties of the material. This review focuses on the enhanced optical/plasmonic and magnetic properties offered by bimetallic nanoparticles and their corresponding impact on biological applications. In this review, we summarize the predominant structures of bimetallic nanoparticles, outline their synthesis methods, and highlight their use in biological applications, both diagnostic and therapeutic, which are dictated by their various optical/plasmonic and magnetic properties.

Magnetic particles are widely used as signal labels in a variety of biological sensing applications, such as molecular detection and related strategies that rely on ligand-receptor binding. In this review, we explore the fundamental concepts involved in designing magnetic particles for biosensing applications and the techniques used to detect them. First, we briefly describe the magnetic properties that are important for bio-sensing applications and highlight the associated key parameters (such as the starting materials, size, functionalization methods, and bio-conjugation strategies). Subsequently, we focus on magnetic sensing applications that utilize several types of magnetic detection techniques: spintronic sensors, nuclear magnetic resonance (NMR) sensors, superconducting quantum interference devices (SQUIDs), sensors based on the atomic magnetometer (AM), and others. From the studies reported, we note that the size of the MPs is one of the most important factors in choosing a sensing technique.