An efficient visual servo tracker for herd monitoring by UAV.

It is a challenging and meaningful task to carry out UAV-based livestock monitoring in high-altitude (more than 4500 m on average) and cold regions (annual average - 4 °C) on the Qinghai Tibet Plateau. The purpose of artificial intelligence (AI) is to execute automated tasks and to solve practical problems in actual applications by combining the software technology with the hardware carrier to create integrated advanced devices. Only in this way, the maximum value of AI could be realized. In this paper, a real-time tracking system with dynamic target tracking ability is proposed. It is developed based on the tracking-by-detection architecture using YOLOv7 and Deep SORT algorithms for target detection and tracking, respectively. In response to the problems encountered in the tracking process of complex and dense scenes, our work (1) Uses optical flow to compensate the Kalman filter, to solve the problem of mismatch between the target bounding box predicted by the Kalman filter (KF) and the input when the target detection in the current frame is complex, thereby improving the prediction accuracy; (2) Using a low confidence trajectory filtering method to reduce false positive trajectories generated by Deep SORT, thereby mitigating the impact of unreliable detection on target tracking. (3) A visual servo controller has been designed for the Unmanned Aerial Vehicle (UAV) to reduce the impact of rapid movement on tracking and ensure that the target is always within the field of view of the UAV camera, thereby achieving automatic tracking tasks. Finally, the system was tested using Tibetan yaks on the Qinghai Tibet Plateau as tracking targets, and the results showed that the system has real-time multi tracking ability and ideal visual servo effect in complex and dense scenes.

Analysis of cartilage loading and injury correlation in knee varus deformity.

Knee varus (KV) deformity leads to abnormal forces in the different compartments of the joint cavity and abnormal mechanical loading thus leading to knee osteoarthritis (KOA). This study used computer-aided design to create 3-dimensional simulation models of KOA with varying varus angles to analyze stress distribution within the knee joint cavity using finite element analysis for different varus KOA models and to compare intra-articular loads among these models. Additionally, we developed a cartilage loading model of static KV deformity to correlate with dynamic clinical cases of cartilage injury. Different KV angle models were accurately simulated with computer-aided design, and the KV angles were divided into (0°, 3°, 6°, 9°, 12°, 15°, and 18°) 7 knee models, and then processed with finite element software, and the Von-Mises stress distribution and peak values of the cartilage of the femoral condyles, medial tibial plateau, and lateral plateau were obtained by simulating the human body weight in axial loading while performing the static extension position. Finally, intraoperative endoscopy visualization of cartilage injuries in clinical cases corresponding to KV deformity subgroups was combined to find cartilage loading and injury correlations. With increasing varus angle, there was a significant increase in lower limb mechanical axial inward excursion and peak Von-Mises stress in the medial interstitial compartment. Analysis of patients' clinical data demonstrated a significant correlation between varus deformity angle and cartilage damage in the knee, medial plateau, and patellofemoral intercompartment. Larger varus deformity angles could be associated with higher medial cartilage stress loads and increased cartilage damage in the corresponding peak stress area. When the varus angle exceeds 6°, there is an increased risk of cartilage damage, emphasizing the importance of early surgical correction to prevent further deformity and restore knee function.

High-precision tracking and positioning for monitoring Holstein cattle.

Enhanced animal welfare has emerged as a pivotal element in contemporary precision animal husbandry, with bovine monitoring constituting a significant facet of precision agriculture. The evolution of intelligent agriculture in recent years has significantly facilitated the integration of drone flight monitoring tools and innovative systems, leveraging deep learning to interpret bovine behavior. Smart drones, outfitted with monitoring systems, have evolved into viable solutions for wildlife protection and monitoring as well as animal husbandry. Nevertheless, challenges arise under actual and multifaceted ranch conditions, where scale alterations, unpredictable movements, and occlusions invariably influence the accurate tracking of unmanned aerial vehicles (UAVs). To address these challenges, this manuscript proposes a tracking algorithm based on deep learning, adhering to the Joint Detection Tracking (JDT) paradigm established by the CenterTrack algorithm. This algorithm is designed to satisfy the requirements of multi-objective tracking in intricate practical scenarios. In comparison with several preeminent tracking algorithms, the proposed Multi-Object Tracking (MOT) algorithm demonstrates superior performance in Multiple Object Tracking Accuracy (MOTA), Multiple Object Tracking Precision (MOTP), and IDF1. Additionally, it exhibits enhanced efficiency in managing Identity Switches (ID), False Positives (FP), and False Negatives (FN). This algorithm proficiently mitigates the inherent challenges of MOT in complex, livestock-dense scenarios.

Cyp6g2 is the major P450 epoxidase responsible for juvenile hormone biosynthesis in Drosophila melanogaster.

BACKGROUND: Juvenile hormones (JH) play crucial role in regulating development and reproduction in insects. The most common form of JH is JH III, derived from MF through epoxidation by CYP15 enzymes. However, in the higher dipterans, such as the fruitfly, Drosophila melanogaster, a bis-epoxide form of JHB3, accounted most of the JH detected. Moreover, these higher dipterans have lost the CYP15 gene from their genomes. As a result, the identity of the P450 epoxidase in the JH biosynthesis pathway in higher dipterans remains unknown. RESULTS: In this study, we show that Cyp6g2 serves as the major JH epoxidase responsible for the biosynthesis of JHB3 and JH III in D. melanogaster. The Cyp6g2 is predominantly expressed in the corpus allatum (CA), concurring with the expression pattern of jhamt, another well-studied gene that is crucial in the last steps of JH biosynthesis. Mutation in Cyp6g2 leads to severe disruptions in larval-pupal metamorphosis and exhibits reproductive deficiencies, exceeding those seen in jhamt mutants. Notably, Cyp6g2-/-::jhamt2 double mutants all died at the pupal stage but could be rescued through the topical application of JH analogs. JH titer analyses revealed that both Cyp6g2-/- mutant and jhamt2 mutant lacking JHB3 and JH III, while overexpression of Cyp6g2 or jhamt caused a significant increase in JHB3 and JH III titer. CONCLUSIONS: These findings collectively established that Cyp6g2 as the major JH epoxidase in the higher dipterans and laid the groundwork for the further understanding of JH biosynthesis. Moreover, these findings pave the way for developing specific Cyp6g2 inhibitors as insect growth regulators or insecticides.

Biomaterials-based Technologies in Skeletal Muscle Tissue Engineering.

For many clinically prevalent severe injuries, the inherent regenerative capacity of skeletal muscle remains inadequate. Skeletal muscle tissue engineering (SMTE) seeks to meet this clinical demand. With continuous progress in biomedicine and related technologies including micro/nanotechnology and 3D printing, numerous studies have uncovered various intrinsic mechanisms regulating skeletal muscle regeneration and developed tailored biomaterial systems based on these understandings. Here, we discussed the skeletal muscle structure and regeneration process and explored in detail the diverse biomaterial systems derived from various technologies. Biomaterials serve not merely as local niches for cell growth, but also as scaffolds endowed with structural or physicochemical properties that provide tissue regenerative cues such as topographical, electrical, and mechanical signals. They can also act as delivery systems for stem cells and bioactive molecules that have been shown as key participants in endogenous repair cascades. To achieve bench-to-bedside translation, we have also summarized the typical effect enabled by biomaterial systems and the potential underlying molecular mechanisms. We hope to provide insights into the roles of biomaterials in SMTE from cellular and molecular perspectives. Finally, we provided perspectives on the advancement of SMTE, for which gene therapy, exosomes, and hybrid biomaterials may hold promise to make important contributions. This article is protected by copyright. All rights reserved.

Hydrochemical fingerprints of karst underground river systems impacted by urbanization in Guiyang, Southwest China.

Karst groundwater plays an irreplaceable role in the formation and development of urban areas, and land-use and land-cover change (LUCC) and the input of pollutants during the urbanization process would pose potential environmental risks to underground rivers. We analysed the relationship between urbanization processes and underground river hydrochemistry over nearly 35 years in Guiyang city, southwest of China, it was found that concentrations of various cations and anions, as well as total dissolved solids (TDS), gradually increased with the urbanization process, with significant fluctuations during the rapid urbanization periods. The Hydrochemical Facies Evolution Diagram (HFED) clearly showed the influence of urbanization on the hydrochemistry of the underground rivers. The ion ratios of γMg2+/γCa2+-γHCO3-, γNa+/γCl-, Ca2+/Mg2+-Ca2+ or Mg2+/Σ cations, HCO3-/SO42--HCO3- or SO42-/Σ anions revealed two distinct phases in the hydrochemical evolution of the underground river system, highly consistent with the urbanization process. Before the rapid urbanization, acid deposition and agricultural activities affected the hydrochemistry, with HCO3-Ca·Mg and HCO3·SO4-Ca·Mg as the dominant types controlled by limestone and dolomite dissolution in water-rock interactions. As acid deposition diminished, the input of SO42- from urban sewage compensated for the reduced impact, but the increased impermeable surfaces reduced the infiltration of atmospheric precipitation, leading to a reduced dissolution of dolomite minerals in water-rock interactions, resulting in a decrease in Mg2+ and a change in the hydrochemical type. The hydrochemical type evolved from a single HCO3·SO4-Ca·Mg type and HCO3-Ca·Mg type to multiple types, such as HCO3·Cl-Ca, HCO3·SO4-Ca, HCO3-Ca, and HCO3·SO4-Ca·Mg, and was highly unstable. With changes in land use, the proportions of various cations and anions in the hydrochemistry changed, especially NH4+, NO3-, SO42-, Na+, and Cl-, which were more sensitive to human activities. This study indicated the impact of urbanization on the hydrochemistry of the underground river system, with the input of SO42- from human activities and the increase in paved surfaces due to urbanization collectively altering the hydrochemical types of the underground river system. The rapid response of karst underground river system hydrochemistry indicates a potential impact on groundwater system by urbanization that should not be ignored.

Effect of hydrothermal-acid pretreatment on methane yield and microbial community in anaerobic digestion of rice straw.

Hydrothermal pretreatment has been proposed to enhance straw methane yield during anaerobic digestion recently. However, the combined effect of hydrothermal and organic acid pretreatment (HTOAP) needs further investigation. This study identified optimal pretreatment at 120 °C with 3 % acetic acid for 24 h by orthogonal design method. The HTOAP increased the reducing sugar content by destroying the lignocellulosic structure. A 79 % increment of methane production after HTOAP was observed compared to the untreated group. Microbial analysis showed that HTOAP enriched the relative abundance of lignocellulose-degraders, such as W5053, Thermanaerovibrio, Caldicoprobacter, as well as the syntrophic acetate oxidizing bacteria Syntrophaceticus. Moreover, Methanobacterium conducted hydrogenotrophic methanogenesis dominantly. Furthermore, the potential function analysis showed that HTOAP stimulated the expression of key enzymes in the hydrogenotrophic pathway, including carbon-monoxide dehydrogenase (EC 1.2.7.4) and coenzyme F420 hydrogenase (EC 1.12.98.1). This investigation illustrated the potential of HTOAP of rice straw to facilitate methane production.

Formation and toxicity alteration of halonitromethanes from Chlorella vulgaris during UV/chloramination process involving bromide ion.

Frequent algal blooms cause algal cells and their algal organic matter (AOM) to become critical precursors of disinfection by-products (DBPs) during water treatment. The presence of bromide ion (Br-) in water has been demonstrated to affect the formation laws and species distribution of DBPs. However, few researchers have addressed the formation and toxicity alteration of halonitromethanes (HNMs) from algae during disinfection in the presence of Br-. Therefore, in this work, Chlorella vulgaris was selected as a representative algal precursor to investigate the formation and toxicity alteration of HNMs during UV/chloramination involving Br-. The results showed that the formation concentration of HNMs increased and then decreased during UV/chloramination. The intracellular organic matter of Chlorella vulgaris was more susceptible to form HNMs than the extracellular organic matter. When the Br-: Cl2 mass ratio was raised from 0.004 to 0.08, the peak of HNMs total concentration increased 33.99%, and the cytotoxicity index and genotoxicity index of HNMs increased 67.94% and 22.80%. Besides, the formation concentration and toxicity of HNMs increased with increasing Chlorella vulgaris concentration but decreased with increasing solution pH. Possible formation pathways of HNMs from Chlorella vulgaris during UV/chloramination involving Br- were proposed based on the alteration of nitrogen species and fluorescence spectrum analysis. Furthermore, the formation laws of HNMs from Chlorella vulgaris in real water samples were similar to those in deionized water samples. This study contributes to a better comprehension of HNMs formation from Chlorella vulgaris and provides valuable information for water managers to reduce hazards associated with the formation of HNMs.

Robust antibacterial activity of rare-earth ions on planktonic and biofilm bacteria.

Bacterial infections pose a serious threat to human health, with emerging antibiotic resistance, necessitating the development of new antibacterial agents. Cu2+and Ag+are widely recognized antibacterial agents with a low propensity for inducing bacterial resistance; however, their considerable cytotoxicity constrains their clinical applications. Rare-earth ions, owing to their unique electronic layer structure, hold promise as promising alternatives. However, their antibacterial efficacy and biocompatibility relative to conventional antibacterial agents remain underexplored, and the variations in activity across different rare-earth ions remain unclear. Here, we systematically evaluate the antibacterial activity of five rare-earth ions (Yb3+, Gd3+, Sm3+, Tb3+, and La3+) againstStaphylococcus aureusandPseudomonas aeruginosa, benchmarked against well-established antibacterial agents (Cu2+, Ag+) and the antibiotic norfloxacin. Cytotoxicity is also assessed via live/dead staining of fibroblasts after 24 h rare-earth ion exposure. Our findings reveal that rare-earth ions require higher concentrations to match the antibacterial effects of traditional agents but offer the advantage of significantly lower cytotoxicity. In particular, Gd3+demonstrates potent bactericidal efficacy against both planktonic and biofilm bacteria, while maintaining the lowest cytotoxicity toward mammalian cells. Moreover, the tested rare-earth ions also exhibited excellent antifungal activity againstCandida albicans. This study provides a critical empirical framework to guide the selection of rare-earth ions for biomedical applications, offering a strategic direction for the development of novel antimicrobial agents.

Pulse Compression Shape-Based ADC/DAC Chain Synchronization Measurement Algorithm with Sub-Sampling Resolution.

In this article, we address the problem of synchronizing multiple analog-to-digital converter (ADC) and digital-to-analog converter (DAC) chains in a multi-channel system, which is constrained by the sampling frequency and inconsistencies among the components during system integration. To evaluate and compensate for the synchronization differences, we propose a pulse compression shape-based algorithm to measure the entire delay parameter of the ADC/DAC chain, which achieves sub-sampling resolution by mapping the shape of the discrete pulse compression peak to the signal propagation delay. Moreover, owing to the matched filtering in the pulse compression process, the algorithm exhibits good noise performance and is suitable for wireless scenarios. Experiments verified that the algorithm can achieve precise measurements with sub-sampling resolution in scenarios where the signal-to-noise ratio (SNR) is greater than -10 dB.

Heterogeneous Sensor-Carrier Microswarms for Collaborative Precise Drug Delivery toward Unknown Targets with Localized Acidosis.

Micro/nanorobots hold the potential to revolutionize biomedicine by executing diverse tasks in hard-to-reach biological environments. Nevertheless, achieving precise drug delivery to unknown disease sites using swarming micro/nanorobots remains a significant challenge. Here we develop a heterogeneous swarm comprising sensing microrobots (sensor-bots) and drug-carrying microrobots (carrier-bots) with collaborative tasking capabilities for precise drug delivery toward unknown sites. Leveraging robust interspecific hydrodynamic interactions, the sensor-bots and carrier-bots spontaneously synchronize and self-organize into stable heterogeneous microswarms. Given that the sensor-bots can create real-time pH maps employing pH-responsive structural-color changes and the doxorubicin-loaded carrier-bots exhibit selective adhesion to acidic targets via pH-responsive charge reversal, the sensor-carrier microswarm, when exploring unknown environments, can detect and localize uncharted acidic targets, guide itself to cover the area, and finally deploy therapeutic carrier-bots precisely there. This versatile platform holds promise for treating diseases with localized acidosis and inspires future theranostic microsystems with expandability, task flexibility, and high efficiency.

Identification of a risk score model based on tertiary lymphoid structure-related genes for predicting immunotherapy efficacy in non-small cell lung cancer.

BACKGROUND: Tertiary lymphoid structures (TLSs) affect the prognosis and efficacy of immunotherapy in patients with non-small cell lung cancer (NSCLC), but the underlying mechanisms are not well understood. METHODS: TLSs were identified and categorized online from the Cancer Digital Slide Archive (CDSA). Overall survival (OS) and disease-free survival (DFS) were analyzed. GSE111414 and GSE136961 datasets were downloaded from the GEO database. GSVA, GO and KEGG were used to explore the signaling pathways. Immune cell infiltration was analyzed by xCell, ssGSEA and MCP-counter. The analysis of WGCNA, Lasso and multivariate cox regression were conducted to develop a gene risk score model based on the SU2C-MARK cohort. RESULTS: TLS-positive was a protective factor for OS according to multivariate cox regression analysis (p = 0.029). Both the TLS-positive and TLS-mature groups exhibited genes enrichment in immune activation pathways. The TLS-mature group showed more activated dendritic cell infiltration than the TLS-immature group. We screened TLS-related genes using WGCNA. Lasso and multivariate cox regression analysis were used to construct a five-genes (RGS8, RUF4, HLA-DQB2, THEMIS, and TRBV12-5) risk score model, the progression free survival (PFS) and OS of patients in the low-risk group were markedly superior to those in the high-risk group (p < 0.0001; p = 0.0015, respectively). Calibration and ROC curves indicated that the combined model with gene risk score and clinical features could predict the PFS of patients who have received immunotherapy more accurately than a single clinical factor. CONCLUSIONS: Our data suggested a pivotal role of TLSs formation in survival outcome and immunotherapy response of NSCLC patients. Tumors with mature TLS formation showed more activated immune microenvironment. In addition, the model constructed by TLS-related genes could predict the response to immunotherapy and is meaningful for clinical decision-making.

Association analyses between the variants of SNAP25, SV2C and ST3GAL2 and the efficacy of botulinum toxin A in the treatment of the primary Meige syndrome.

Objective: Individual differences were observed in the clinical efficacy of Botulinum toxin A (BoNT-A) in the treatment of the primary Meige syndrome. Our study aimed to explore the potential associations between the clinical efficacy of BoNT-A in the treatment of the primary Meige syndrome and variants of SNAP25, SV2C and ST3GAL2, which are involving in the translocation of the BoNT-A in vivo. Methods: Patients with the primary Meige syndrome treated with BoNT-A were enrolled. Clinical efficacy was evaluated by the maximum improvement rate of motor symptoms and the duration of efficacy. Variants of SNAP25, SV2C and ST3GAL2 were obtained by Sanger sequencing. Another cohort diagnosed with primary cervical dystonia was also enrolled in the replication stage. Results: Among the 104 primary Meige syndrome patients, 80 patients (76.9%) had a good efficacy (the maximum improvement rate of motor symptoms ≥30%) and 24 (23. 1%) had a poor (the maximum improvement rate of motor symptoms <30%). As to the duration of efficacy, 52 patients (50.0%) had a long duration of efficacy (≥4 months), and 52 (50.0%) had a short (<4 months). In terms of primary Meige syndrome, SNAP25 rs6104571 was found associating with the maximum improvement rate of motor symptoms (Genotype: P = 0.02, OR = 0.26; Allele: P = 0.013, OR = 0.29), and SV2C rs31244 was found associating with the duration of efficacy (Genotype: P = 0.024, OR = 0.13; Allele: P = 0.012, OR = 0.13). Besides, we also conducted the association analyses between the variants and BoNT-A-related adverse reactions. Although, there was no statistical difference between the allele of SV2C rs31244 and BoNT-A-related adverse reactions, there was a trend (P = 0.077, OR = 2.56). In the replication stage, we included 39 patients with primary cervical dystonia to further expanding the samples' size. Among the 39 primary cervical dystonia patients, 25 patients (64.1%) had a good efficacy (the maximum improvement rate of motor symptoms ≥50%) and 14 (35.9%) had a poor (the maximum improvement rate of motor symptoms <50%). As to the duration of efficacy, 32 patients (82.1%) had a long duration of efficacy (≥6 months), and 7 (17.9%) had a short (<6 months). Integrating primary Meige syndrome and primary cervical dystonia, SV2C rs31244 was still found associating with the duration of efficacy (Genotype: P = 0.002, OR = 0. 23; Allele: P = 0.001, OR = 0. 25). Conclusion: In our study, SNAP25 rs6104571 was associated with the maximum improvement rate of motor symptoms in patients with primary Meige syndrome treated with BoNT-A, and patients carrying this variant had a lower improvement rate of motor symptoms. SV2C rs31244 was associated with duration of treatment in patients with primary Meige syndrome treated with BoNT-A and patients carrying this variant had a shorter duration of treatment. Patients with primary Meige syndrome carrying SV2C rs31244 G allele have an increase likelihood of BoNT-A-related adverse reactions. Involving 39 patients with primary cervical dystonia, the results further verify that SV2C rs31244 was associated with duration of treatment and patients carrying this variant had a shorter duration of treatment.

Unraveling varying spatiotemporal patterns of dengue and associated exposure-response relationships with environmental variables in Southeast Asian countries before and during COVID-19.

The enforcement of COVID-19 interventions by diverse governmental bodies, coupled with the indirect impact of COVID-19 on short-term environmental changes (e.g. plant shutdowns lead to lower greenhouse gas emissions), influences the dengue vector. This provides a unique opportunity to investigate the impact of COVID-19 on dengue transmission and generate insights to guide more targeted prevention measures. We aim to compare dengue transmission patterns and the exposure-response relationship of environmental variables and dengue incidence in the pre- and during-COVID-19 to identify variations and assess the impact of COVID-19 on dengue transmission. We initially visualized the overall trend of dengue transmission from 2012-2022, then conducted two quantitative analyses to compare dengue transmission pre-COVID-19 (2017-2019) and during-COVID-19 (2020-2022). These analyses included time series analysis to assess dengue seasonality, and a Distributed Lag Non-linear Model (DLNM) to quantify the exposure-response relationship between environmental variables and dengue incidence. We observed that all subregions in Thailand exhibited remarkable synchrony with a similar annual trend except 2021. Cyclic and seasonal patterns of dengue remained consistent pre- and during-COVID-19. Monthly dengue incidence in three countries varied significantly. Singapore witnessed a notable surge during-COVID-19, particularly from May to August, with cases multiplying several times compared to pre-COVID-19, while seasonality of Malaysia weakened. Exposure-response relationships of dengue and environmental variables show varying degrees of change, notably in Northern Thailand, where the peak relative risk for the maximum temperature-dengue relationship rose from about 3 to 17, and the max RR of overall cumulative association 0-3 months of relative humidity increased from around 5 to 55. Our study is the first to compare dengue transmission patterns and their relationship with environmental variables before and during COVID-19, showing that COVID-19 has affected dengue transmission at both the national and regional level, and has altered the exposure-response relationship between dengue and the environment.

Rest to Promote Learning: A Brain Default Mode Network Perspective.

The brain often switches freely between focused attention and divergent thinking, and the Default Mode Network (DMN) is activated during brain rest. Since its discovery, the DMN, together with its function and characteristics, indicates that learning does not stop when the brain "rests". Therefore, DMN plays an important role in learning. Neural activities such as beta wave rhythm regulation, "subconscious" divergence thinking mode initiation, hippocampal function, and neural replay occur during default mode, all of which explains that "rest" promotes learning. This paper summarized the function and neural mechanism of DMN in learning and proposed that the DMN plays an essential role in learning, which is that it enables rest to promote learning.

Peroxiredoxin 1 promotes proliferation and inhibits differentiation of MC3T3-E1 cells via AKT1 / NF-κB signaling pathway.

OBJECTIVES: Osteoporosis is the most common metabolic bone disease worldwide. The decrease in bone mass is primarily accompanied by a decrease in the number and activity of osteoblasts. Peroxiredoxins (PRDXs) are proteins that detect extremely low peroxide levels and act as sensors that regulate oxidation signals, thereby regulating various cellular functions. This study aimed to evaluate the effects of PRDX1 and estrogen on the biological behavior of osteoblasts, including their proliferation and differentiation. METHODS: Ovariectomized (OVX) mice were used to establish a model of osteoporosis and perform morphological and immunohistochemical analyses. Prdx1 gene knockout and overexpression were performed in mouse MC3T3-E1 pre-osteoblasts to assess proliferation and osteogenic differentiation using the cell counting kit-8, quantitative reverse transcription polymerase chain reaction, western blotting (WB), Alizarin Red S staining, etc. RESULTS: The OVX mice exhibited osteoporosis and PRDX1 expression increased. In vitro experiments showed that during the osteogenic differentiation of osteoblasts, PRDX1 expression decreased, while the expression of COL1 and RUNX2 increased. After Prdx1 knockout, the proliferation of osteoblasts decreased; expression of Runx2, ALP, and COL1 increased; and mineralization increased. However, after Prdx1 overexpression, osteoblast proliferation was enhanced, whereas osteogenic differentiation and mineralization were inhibited. Estrogen inhibits the H2O2-induced decrease in osteoblastic differentiation and increase in PRDX1 expression. WB revealed that when LY294002 inhibited the AKT signaling pathway, the levels of p-AKT1, p-P65, and PRDX1 protein in MC3T3-E1 cells decreased. However, when pyrrolidine dithiocarbamate (PDTC) inhibited the NF-κB signaling pathway, the expression of p-AKT1 and PRDX1 did not change except for a significant reduction of p-P65 expression. Furthermore, PDTC reversed the decreased expression of RUNX2, ALP, and COL1 caused by PRDX1 overexpression. CONCLUSIONS: PRDX1 promotes the proliferation of osteoblasts and inhibits osteogenic differentiation. Estrogen regulated osteoblastic differentiation by affecting the expression of PRDX1 in osteoblasts, and the effect is related to the AKT1/NF-κB signaling pathway.

Metabolic difference between patient-derived xenograft model of pancreatic ductal adenocarcinoma and corresponding primary tumor.

BACKGROUND: Patients-derived xenograft (PDX) model have been widely used for tumor biological and pathological studies. However, the metabolic similarity of PDX tumor to the primary cancer (PC) is still unknown. METHODS: In present study, we established PDX model by engrafting primary tumor of pancreatic ductal adenocarcinoma (PDAC), and then compared the tumor metabolomics of PC, the first generation of PDX tumor (PDXG1), and the third generation of PDX tumor (PDXG3) by using 1H NMR spectroscopy. Then, we assessed the differences in response to chemotherapy between PDXG1 and PDXG3 and corresponding metabolomic differences in drug-resistant tumor tissues. To evaluate the metabolomic similarity of PDX to PC, we also compared the metabolomic difference of cell-derived xenograft (CDX) vs. PC and PDX vs. PC. RESULTS: After engraftment, PDXG1 tumor had a low level of lactate, pyruvate, citrate and multiple amino acids (AAs) compared with PC. Metabolite sets enrichment and metabolic pathway analyses implied that glycolysis metabolisms were suppressed in PDXG1 tumor, and tricarboxylic acid cycle (TCA)-associated anaplerosis pathways, such as amino acids metabolisms, were enhanced. Then, after multiple passages of PDX, the altered glycolysis and TCA-associated anaplerosis pathways were partially recovered. Although no significant difference was observed in the response of PDXG1 and PDXG3 to chemotherapy, the difference in glycolysis and amino acids metabolism between PDXG1 and PDXG3 could still be maintained. In addition, the metabolomic difference between PC and CDX models were much larger than that of PDX model and PC, indicating that PDX model still retain more metabolic characteristics of primary tumor which is more suitable for tumor-associated metabolism research. CONCLUSIONS: Compared with primary tumor, PDX models have obvious difference in metabolomic level. These findings can help us design in vivo tumor metabolomics research legitimately and analyze the underlying mechanism of tumor metabolic biology thoughtfully.

Revealing the role of a bridging oxygen in a carbon shell coated Ni interface for enhanced alkaline hydrogen oxidation reaction.

Encapsulating metal nanoparticles inside carbon layers is a promising approach to simultaneously improving the activity and stability of electrocatalysts. The role of carbon layer shells, however, is not fully understood. Herein, we report a study of boron doped carbon layers coated on nickel nanoparticles (Ni@BC), which were used as a model catalyst to understand the role of a bridging oxygen in a carbon shell coated Ni interface for the improvement of the hydrogen oxidation reaction (HOR) activity using an alkaline electrolyte. Combining experimental results and density functional theory (DFT) calculations, we find that the electronic structure of Ni can be precisely tailored by Ni-O-C and Ni-O-B coordinated environments, leading to a volcano type correlation between the binding ability of the OH* adsorbate and HOR activity. The obtained Ni@BC with a optimized d-band center displays a remarkable HOR performance with a mass activity of 34.91 mA mgNi-1, as well as superior stability and CO tolerance. The findings reported in this work not only highlight the role of the OH* binding strength in alkaline HOR but also provide guidelines for the rational design of advanced carbon layers used to coat metal electrocatalysts.

Risk factors and prediction model construction for peripherally inserted central catheter-related infections.

Objective: To establish a predictive modeling for the risk of bloodstream infection associated with peripherally inserted central catheter (PICC). Methods: Patients receiving PICC treatment in Shenzhen People's Hospital from June 2020 to December 2020 were retrospectively enrolled and divided into the infection group and the non-infection group according to the presence and absence of PICC-related infections. Then, relevant clinical information of patients was collected and the predictors of PICC-related infection were screened by the least absolute shrinkage and selection operator regression (LASSO) model. Besides, multivariate logistic regression was used to analyze the influencing factors of PICC-related infection, A nomogram was constructed based on the results of the multivariate analysis. Ultimately, a receiver operating characteristic (ROC) curve was plotted to analyze the application value of influencing factors to predict PICC-related infections. Results: A total of 505 patients were included, including 75 patients with PICC-related infections (14.85%). The main pathogen was gram-positive cocci. The predictors screened by LASSO included age >60 years, catheter movement, catheter maintenance cycle, insertion technique, immune function, complications, and body temperature ≥37.2 °C before PICC placement. Multivariate logistic regression analysis showed that independent risk factors of infections related to PICC included age >60 years [odds ratio (OR) = 1.722; 95% confidence interval (CI) = 1.312-3.579; P = 0.006], catheter movement (OR = 1.313; 95% CI = 1.119-3.240; P = 0.014), catheter maintenance cycle >7 days (OR = 2.199; 95% CI = 1.677-4.653; P = 0.000), direct insertion (OR = 1.036; 95% CI = 1.019-2.743; P = 0.000), poor immune function (OR = 2.322; 95% CI = 2.012-4.579; P = 0.000), complications (OR = 1.611; 95% CI = 1.133-3.454; P = 0.019), and body temperature ≥37.2 °C before PICC placement (OR = 1.713; 95% CI = 1.172-3.654; P = 0.012). Besides, the area under the ROC curve was 0.889. Conclusion: PICC-related infections are associated with factors such as age >60 years, catheter movement, catheter maintenance cycle, insertion technique, immune function, complications, and body temperature ≥37.2 °C before PICC placement. Additionally, the LASSO model is moderately predictive for predicting the occurrence of PICC-related infections.

Circadian rhythm response and its effect on photosynthetic characteristics of the Lhcb family genes in tea plant.

BACKGROUND: The circadian clock, also known as the circadian rhythm, is responsible for predicting daily and seasonal changes in the environment, and adjusting various physiological and developmental processes to the appropriate times during plant growth and development. The circadian clock controls the expression of the Lhcb gene, which encodes the chlorophyll a/b binding protein. However, the roles of the Lhcb gene in tea plant remain unclear. RESULTS: In this study, a total of 16 CsLhcb genes were identified based on the tea plant genome, which were distributed on 8 chromosomes of the tea plant. The promoter regions of CsLhcb genes have a variety of cis-acting elements including hormonal, abiotic stress responses and light response elements. The CsLhcb family genes are involved in the light response process in tea plant. The photosynthetic parameter of tea leaves showed rhythmic changes during the two photoperiod periods (48 h). Stomata are basically open during the day and closed at night. Real-time quantitative PCR results showed that most of the CsLhcb family genes were highly expressed during the day, but were less expressed at night. CONCLUSIONS: Results indicated that CsLhcb genes were involved in the circadian clock process of tea plant, it also provided potential references for further understanding of the function of CsLhcb gene family in tea plant.