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The physical power infrastructure is moving from the centralized structure to the distributed structure for enabling integration of distributed energy resources. Due to the large number of distributed energy resources, optimal resource allocation is an important and challenging problem. To solve this problem, a distributed and fast economic dispatch algorithm is provided to share the power generation task in an optimized fashion among a set of distributed energy resources, which can address both generation-demand equality and generation capacity inequality constraints. Different from most existing economic dispatch algorithms, the finite-time convergence to the optimal value is achieved, which makes more sense in real applications. Several case studies are discussed and tested to validate the proposed methods. [ABSTRACT FROM PUBLISHER]

Osseointegration is significantly impeded in osteoporotic conditions due to the elevated levels of reactive oxygen species (ROS) and inflammation at the site of injury. To enhance bone regeneration in osteoporotic conditions, a modified polyether ether ketone (PEEK) implants was prepared, denoted as PEEK-PDA-Sr. The implants consisted of mussel adhesion layer with the conjugation of strontium (Sr) ions, which can constantly release Sr ions for up to 3 weeks. PEEK-PDA-Sr demonstrated excellent biocompatibility and effectively regulated intracellular ROS levels and macrophage differentiation. In addition, the PEEK-PDA-Sr facilitated the osteogenesis of bone marrow stromal cells (BMSCs). In the ovariectomized (OVX) rat model of osteoporosis, the PEEK-PDA-Sr exhibited raised osseointegration in the femoral bone defects. The PEEK-PDA-Sr can be used as an immunoregulator with enhanced osseointegration and osteogenesis both in vivo and in vitro, which provides an available approach to treat osteoporotic bone defects., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Osteoarthritis (OA) is a frequent chronic illness in orthopedics that poses a major hazard to patient health. In situ cell therapy is emerging as a therapeutic option, but its efficacy is influenced by both the inflammatory milieu and the amount of stem cells, limiting its use. In this study, we designed a novel injectable porous microsphere (PM) based on microfluidic technology that can support in situ mesenchymal stem cells (MSCs) therapy by combining polylactic-glycolic acid copolymer, kartogenin, polydopamine, stromal cell-derived factor-1, and copper-doped bioactive glass (CuBG). The ex vivo tests demonstrated that PMs@CuBG microspheres were biocompatible and facilitated the transformation of synovial macrophages from pro-inflammatory M1 to anti-inflammatory M2 phenotypes by releasing CuBG to reduce joint inflammation. At the same time, the microspheres are able to recruit MSCs into the joint cavity and encourage their differentiation into chondrocytes, thereby treating articular cartilage injury. The in vivo rat experimental results show that intra-articular injection of PMs@CuBG in rats with OA improves OARSI scores, aggrecan content and the ratio of col-2α-positive cells, indicating a reparative effect on damaged cartilage within the joint. As a result, PMs@CuBG microspheres are predicted to provide a novel and successful approach to in situ cell therapy for OA., (© The Author(s) 2024. Published by Oxford University Press.)

Recently, point cloud domain adaptation (DA) practices have been implemented to improve the generalization ability of deep learning models on point cloud data. However, variations across domains often result in decreased performance of models trained on different distributed data sources. Previous studies have focused on output-level domain alignment to address this challenge. But this approach may increase the amount of errors experienced when aligning different domains, particularly for targets that would otherwise be predicted incorrectly. Therefore, in this study, we propose an input-level discretization-based matching to enhance the generalization ability of DA. Specifically, an efficient geometric deformation depth decoupling network (3DeNet) is implemented to learn the knowledge from the source domain and embed it into an implicit feature space, which facilitates the effective constraint of unsupervised predictions for downstream tasks. Secondly, we demonstrate that the sparsity within the implicit feature space varies between domains, rendering domain differences difficult to support. Consequently, we match sets of neighboring points with different densities and biases by differentiating the adaptive densities. Finally, inter-domain differences are aligned by constraining the loss originating from and between the target domains. We conduct experiments on point cloud DA datasets PointDA-10 and PointSegDA, achieving advanced results (over 1.2% and 1% on average)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Osteoarthritis (OA) is characterized primarily by the degeneration of articular cartilage, with a high prevalence and disability rate. The functional phenotype of chondrocytes, as the sole cell type within cartilage, is vital for OA progression. Due to the avascular nature of cartilage and its limited regenerative capacity, repair following injury poses significant challenges. Various cellular stressors, including hypoxia, nutrient deprivation, oxidative stress, and collagen mutations, can lead to the accumulation of misfolded proteins in the endoplasmic reticulum (ER), resulting in ER stress (ERS). In response to restore ER homeostasis as well as cellular vitality and function, a series of adaptive mechanisms are triggered, including the unfolded protein response, ER-associated degradation, and ER-phagy. Prolonged or severe ERS may exceed the adaptive capacity of cells, leading to dysregulation in apoptosis and autophagy-key pathogenic factors contributing to chondrocyte damage and OA progression. This review examines the relationship between ERS in OA chondrocytes and both apoptosis and autophagy in order to identify potential therapeutic targets and strategies for prevention and treatment of OA., Competing Interests: Declarations of interest The authors declare that there is no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Passive sensing through smartphone keyboard data can be used to identify and monitor symptoms of mood disorders with low participant burden. Behavioral phenotyping based on mobile keystroke data can aid in clinical decision-making and provide insights into the individual symptoms of mood disorders., Objective: This study aims to derive digital phenotypes based on smartphone keyboard backspace use among 128 community adults across 2948 observations using a Bayesian mixture model., Methods: Eligible study participants completed a virtual screening visit where all eligible participants were instructed to download the custom-built BiAffect smartphone keyboard (University of Illinois). The BiAffect keyboard unobtrusively captures keystroke dynamics. All eligible and consenting participants were instructed to use this keyboard exclusively for up to 4 weeks of the study in real life, and participants' compliance was checked at the 2 follow-up visits at week 2 and week 4. As part of the research protocol, every study participant underwent evaluations by a study psychiatrist during each visit., Results: We found that derived phenotypes were associated with not only the diagnoses and severity of depression and mania but also specific individual symptoms. Using a linear mixed-effects model with random intercepts accounting for the nested data structure from daily data, the backspace rates on the continuous scale did not differ between participants in the healthy control and in the mood disorders groups (P=.11). The 3-class model had mean backspace rates of 0.112, 0.180, and 0.268, respectively, with a SD of 0.048. In total, 3 classes, respectively, were estimated to comprise 37.5% (n=47), 54.4% (n=72), and 8.1% (n=9) of the sample. We grouped individuals into Low, Medium, and High backspace rate groups. Individuals with unipolar mood disorder were predominantly in the Medium group (n=54), with some in the Low group (n=27) and a few in the High group (n=6). The Medium group, compared with the Low group, had significantly higher ratings of depression (b=2.32, P=.008). The High group was not associated with ratings of depression with (P=.88) or without (P=.27) adjustment for medication and diagnoses. The High group, compared with the Low group, was associated with both nonzero ratings (b=1.91, P=.02) and higher ratings of mania (b=1.46, P<.001). The High group, compared with the Low group, showed significantly higher odds of elevated mood (P=.03), motor activity (P=.04), and irritability (P<.05)., Conclusions: This study demonstrates the promise of mobile typing kinematics in mood disorder research and practice. Monitoring a single mobile typing kinematic feature, that is, backspace rates, through passive sensing imposes a low burden on the participants. Based on real-life keystroke data, our derived digital phenotypes from this single feature can be useful for researchers and practitioners to distinguish between individuals with and those without mood disorder symptoms., (©Qimin Liu, Emma Ning, Mindy K Ross, Andrea Cladek, Sarah Kabir, Amruta Barve, Ellyn Kennelly, Faraz Hussain, Jennifer Duffecy, Scott A Langenecker, Theresa M Nguyen, Theja Tulabandhula, John Zulueta, Alexander P Demos, Alex Leow, Olusola Ajilore. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 29.10.2024.)

This study aims to develop machine learning (ML)-assisted models for analyzing datasets related to Gleason scores in prostate cancer, conducting statistical analyses on the datasets, and identifying meaningful features. We retrospectively collected data from 717 hormone-sensitive prostate cancer (HSPC) patients at Yunnan Cancer Hospital. Of these, data from 526 patients were used for modeling. Seven auxiliary models were established using Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), Extreme gradient boosting tree (XGBoost), Adaptive Boosting (Adaboost), and artificial neural network (ANN) based on 21 clinical biochemical indicators and features. Evaluation metrics included accuracy (ACC), precision (PRE), specificity (SPE), sensitivity (SEN) or regression rate(Recall), and f1 score. Evaluation metrics for the models primarily included ACC, PRE, SPE, SEN or Recall, f1 score, and area under the curve(AUC). Evaluation metrics were visualized using confusion matrices and ROC curves. Among the ensemble learning methods, RF, XGBoost, and Adaboost performed the best. RF achieved a training dataset score of 0.769 (95% CI: 0.759-0.835) and a testing dataset score of 0.755 (95% CI: 0.660-0.760) (AUC: 0.786, 95%CI: 0.722-0.803), while XGBoost achieved a training dataset score of 0.755 (95% CI: 95%CI: 0.711-0.809) and a testing dataset score of 0.745 (95% CI: 0.660-0.764) (AUC: 0.777, 95% CI: 0.726-0.798). Adaboost scored 0.789 on the training dataset (95% CI: 0.782-0.857) and 0.774 on the testing dataset (95% CI: 0.651-0.774) (AUC: 0.799, 95% CI: 0.703-0.802). In terms of feature importance (FI) in ensemble learning, Bone metastases at first visit, prostatic volume, age, and T1-T2 have significant proportions in RF's FI. fPSA, TPSA, and tumor burden have significant proportions in Adaboost's FI, while f/TPSA, LDH, and testosterone have the highest proportions in XGBoost. Our findings indicate that ensemble learning methods demonstrate good performance in classifying HSPC patient data, with TNM staging and fPSA being important classification indicators. These discoveries provide valuable references for distinguishing different Gleason scores, facilitating more accurate patient assessments and personalized treatment plans., (© 2024. The Author(s).)

Primary renal osteosarcoma is an exceedingly rare subtype of renal malignancy, noted for its aggressive nature and often fatal outcome. The scarcity and severity of this condition have resulted in a dearth of reliable methods for early diagnosis and effective treatment. The present article contributes to the existing body of knowledge by presenting a comprehensive clinical case of a 46-year-old male patient with primary renal osteosarcoma. The detailed analysis of the clinical features, imaging characteristics, treatment approaches and prognosis of the patient in the present case aimed to enhance the understanding of renal osteosarcoma and inform clinical decision-making. The patient initially presented with painless hematuria, and further diagnostic work-up, including imaging and pathology, confirmed the diagnosis of primary renal osteosarcoma., Competing Interests: The authors declare that they have no competing interests., (Copyright: © 2024 Zhang et al.)

Osteoarthritis (OA) is a prevalent cause of joint algesia, loss of function, and disability in adults, with cartilage injury being its core pathological manifestation. Since cartilage damage is non-renewable, the treatment outcome in the middle and late stages of OA is unsatisfactory, which can be minimized by changing lifestyle and other treatment modalities if diagnosed and managed in the early stages, indicating the importance of early diagnosis and monitoring of cartilage injury. Ultrasound technology has been used for timely diagnosis and even cartilage injury treatment, which is convenient and safe for the patient owing to no radiation exposure. Studies have demonstrated the effectiveness of ultrasound and its various quantitative ultrasound parameters, like ultrasound roughness index (URI), reflection coefficient (R), apparent integrated backscatter (AIB), thickness, and ultrasound elastography, in the early and accurate assessment of OA cartilage pathological changes, including surface and internal tissue, hardness, and thickness. Although many challenges are faced in the clinical application of this technology in diagnosis, ultrasound and ultrasound-assisted techniques offer a lot of promise for detecting early cartilage damage in OA. In this review, we have discussed the evaluation of ultrasonic cartilage quantitative parameters for early pathological cartilage changes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhang, Ning, Lu, Zhou, Shao, Yang and Hao.)

Introduction: Artemisia argyi Folium (AAF) is a traditional medicinal herb and edible plant. Analyzing the differential metabolites that affect the efficacy of AAF with different aging years is necessary., Objective: The aim of the study was to investigate the changing trend and differential markers of volatile and nonvolatile metabolites of AAF from different aging years, which are necessary for application in clinical medicine., Methodology: Metabolites were analyzed using a widely targeted metabolomic approach based on ultrahigh-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and gas chromatography tandem mass spectrometry (GC-MS)., Results: A total of 153 volatile metabolites and 159 nonvolatile metabolites were identified. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) could clearly distinguish AAF aged for 1 year (AF-1), 3 years (AF-3), and 5 years (AF-5). Seven flavonoids and nine terpenoids were identified as biomarkers for tracking the aging years., Conclusions: The metabolomic method provided an effective strategy for tracking and identifying biomarkers of AAF from different aging years. This study laid the foundation for analysis of the biological activity of Artemisia argyi with different aging years., (© 2024 John Wiley & Sons Ltd.)

Osteoarthritis (OA) is a chronic disease due to the deterioration of cartilage structure and function, involving the progressive degradation of the cartilage extracellular matrix. Cathepsins, lysosomal cysteine proteases, play pivotal roles in various biological and pathological processes, particularly in protein degradation. Excess cathepsins levels are reported to contribute to the development of OA. However, the causal relationship between the cathepsin family and knee and hip OA remains uncertain. Therefore, this study utilized bidirectional Mendelian Randomization (MR) analyses to explore this causal association. Our results indicated that elevated serum levels of cathepsin O increase the overall risk of knee OA, while increased serum levels of cathepsin H enhance the risk of hip OA. Conversely, the reverse MR analyses did not reveal a reverse causal relationship between them. In summary, OA in different anatomical locations may genetically result from pathological elevations in different serum cathepsin isoforms, which could be utilized as diagnostic and therapeutic targets in clinical practice., (© 2024. The Author(s).)

Impulsivity can be a risk factor for serious complications for those with mood disorders. To understand intra-individual impulsivity variability, we analyzed longitudinal data of a novel gamified digital Go/No-Go (GNG) task in a clinical sample (n=43 mood disorder participants, n=17 healthy controls) and an open-science sample (n=121, self-reported diagnoses). With repeated measurements within-subject, we disentangled two aspects of GNG: reaction time and accuracy in response inhibition (i.e., incorrect No-Go trials) with respect to diurnal and potential learning effects. Mixed-effects models showed diurnal effects in reaction time but not accuracy, with a significant effect of hour on reaction time in the clinical sample and the open-science sample. Moreover, subjects improved on their response inhibition but not reaction time. Additionally, significant interactions emerged between depression symptom severity and time-of-day in both samples, supporting that repeated administration of our GNG task can yield mood-dependent circadian rhythm-aware biomarkers of neurocognitive function.

Osteoarthritis (OA) is distinguished by pathological alterations in the synovial membrane, articular cartilage, and subchondral bone, resulting in physical symptoms such as pain, deformity, and impaired mobility. Numerous research studies have validated the effectiveness of low-intensity pulsed ultrasound (LIPUS) in OA treatment. The periodic mechanical waves generated by LIPUS can mitigate cellular ischemia and hypoxia, induce vibration and collision, produce notable thermal and non-thermal effects, alter cellular metabolism, expedite tissue repair, improve nutrient delivery, and accelerate the healing process of damaged tissues. The efficacy and specific mechanism of LIPUS is currently under investigation. This review provides an overview of LIPUS's potential role in the treatment of OA, considering various perspectives such as the synovial membrane, cartilage, subchondral bone, and tissue engineering. It aims to facilitate interdisciplinary scientific research and further exploration of LIPUS as a complementary technique to existing methods or surgery. Ongoing research is focused on determining the optimal dosage, frequency, timing, and treatment strategy of LIPUS for OA. Additional research is required to clarify the precise mechanism of action and potential impacts on cellular, animal, and human systems prior to its integration into therapeutic applications., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhou, Ning, Lu, Zhang, Yang and Hao.)

Neutrophil (PMN) tissue accumulation is an established feature of ulcerative colitis (UC) lesions and colorectal cancer (CRC). To assess the PMN phenotypic and functional diversification during the transition from inflammatory ulceration to CRC we analyzed the transcriptomic landscape of blood and tissue PMNs. Transcriptional programs effectively separated PMNs based on their proximity to peripheral blood, inflamed colon, and tumors. In silico pathway overrepresentation analysis, protein-network mapping, gene signature identification, and gene-ontology scoring revealed unique enrichment of angiogenic and vasculature development pathways in tumor-associated neutrophils (TANs). Functional studies utilizing ex vivo cultures, colitis-induced murine CRC, and patient-derived xenograft models demonstrated a critical role for TANs in promoting tumor vascularization. Spp1 (OPN) and Mmp14 (MT1-MMP) were identified by unbiased -omics and mechanistic studies to be highly induced in TANs, acting to critically regulate endothelial cell chemotaxis and branching. TCGA data set and clinical specimens confirmed enrichment of SPP1 and MMP14 in high-grade CRC but not in patients with UC. Pharmacological inhibition of TAN trafficking or MMP14 activity effectively reduced tumor vascular density, leading to CRC regression. Our findings demonstrate a niche-directed PMN functional specialization and identify TAN contributions to tumor vascularization, delineating what we believe to be a new therapeutic framework for CRC treatment focused on TAN angiogenic properties.

While digital phenotyping provides opportunities for unobtrusive, real-time mental health assessments, the integration of its modalities is not trivial due to high dimensionalities and discrepancies in sampling frequencies. We provide an integrated pipeline that solves these issues by transforming all modalities to the same time unit, applying temporal independent component analysis (ICA) to high-dimensional modalities, and fusing the modalities with linear mixed-effects models. We applied our approach to integrate high-quality, daily self-report data with BiAffect keyboard dynamics derived from a clinical suicidality sample of mental health outpatients. Applying the ICA to the self-report data (104 participants, 5712 days of data) revealed components related to well-being, anhedonia, and irritability and social dysfunction. Mixed-effects models (55 participants, 1794 days) showed that less phone movement while typing was associated with more anhedonia (β = -0.12, p = 0.00030). We consider this method to be widely applicable to dense, longitudinal digital phenotyping data., (© 2024. The Author(s).)

The real-time and accurate monitoring of severe weather is the key to reducing traffic accidents on highways. Currently, rainy day monitoring based on video images focuses on removing the impact of rain. This article aims to build a monitoring model for rainy days and rainfall intensity to achieve precise monitoring of rainy days on highways. This paper introduces an algorithm that combines the frequency domain and spatial domain, thresholding, and morphology. It incorporates high-pass filtering, full-domain value segmentation, the OTSU method (the maximum inter-class difference method), mask processing, and morphological opening for denoising. The algorithm is designed to build the rain coefficient model P rain coefficient and determine the intensity of rainfall based on the value of P rain coefficient . To validate the model, data from sunny, cloudy, and rainy days in different sections and time periods of the Jinan Bypass G2001 line were used. The aim is to raise awareness about driving safety on highways. The main findings are: the rain coefficient model P rain coefficient can accurately identify cloudy and rainy days and assess the intensity of rainfall. This method is not only suitable for highways but also for ordinary road sections. The model's accuracy has been verified, and the algorithm in this study has the highest accuracy. This research is crucial for road traffic safety, particularly during bad weather such as rain., (© 2024. The Author(s).)

A proposed method, Enhancement, integration, and Expansion, aims to activate the representation of detailed features for occluded person re-identification. Region and context are two important and complementary features, and integrating them in an occluded environment can effectively improve the robustness of the model. Firstly, a self-enhancement module is designed. Based on the constructed multi-stream architecture, rich and meaningful feature interference is introduced in the feature extraction stage to enhance the model's ability to perceive noise. Next, a collaborative integration module similar to cascading cross-attention is proposed. By studying the intrinsic interaction patterns of regional and contextual features, it adaptively fuses features across streams and enhances the diverse and complete representation of internal information. The module is not only robust to complex occlusions, but also mitigates the feature interference problem due to similar appearances or scenes. Finally, a matching expansion module that enhances feature discriminability and completeness is proposed. Providing more stable and accurate features for recognition. Compared with state-of-the-art methods on two occluded and holistic datasets, the proposed method is proved to be advanced and the effectiveness of the module is proved by extensive ablation studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

While digital phenotyping provides opportunities for unobtrusive, real-time mental health assessments, the integration of its modalities is not trivial due to high dimensionalities and discrepancies in sampling frequencies. We provide an integrated pipeline that solves these issues by transforming all modalities to the same time unit, applying temporal independent component analysis (ICA) to high-dimensional modalities, and fusing the modalities with linear mixed-effects models. We applied our approach to integrate high-quality, daily self-report data with BiAffect keyboard dynamics derived from a clinical suicidality sample of mental health outpatients. Applying the ICA to the self-report data (104 participants, 5712 days of data) revealed components related to well-being, anhedonia, and irritability and social dysfunction. Mixed-effects models (55 participants, 1794 days) showed that less phone movement while typing was associated with more anhedonia (β = -0.12, p = 0.00030). We consider this method to be widely applicable to dense, longitudinal digital phenotyping data.

In this study, a validated quality evaluation method with peony flower fingerprint chromatogram combined with simultaneous determination of sixteen bioactive constituents was established using UPLC-DAD-MS/MS. The results demonstrated that the method was stable, reliable, and accurate. The UPLC chemical fingerprints of 12 different varieties of peonies were established and comprehensively evaluated by similarity evaluation (SE), hierarchical cluster analysis (HCA), principal component analysis (PCA), and quantification analysis. The results of SE indicated that similar chemical components were present in these samples regardless of variety, but there were significant differences in the content of chemical components and material basis characteristics. The results of HCA and PCA showed that 12 varieties of samples were divided into two groups. Four flavonoids (11, 12, 13, and 16), five monoterpenes and their glycosides (3, 4, 6, 14, and 15), three tannins (7, 9, and 10), three phenolic acids (1, 2, and 5), and one aromatic acid (8) were identified from sixteen common peaks by standards and liquid chromatography-mass spectrometry (LC-MS). The simultaneous quantification of six types of components was conducted with the 12 samples, it was found that the sum contents of analytes varied obviously for peony flower samples from different varieties. The content of flavonoids, tannins, and monoterpenes (≥19.34 mg/g) was the highest, accounting for more than 78.45% of the total compounds. The results showed that the flavonoids, tannins, and monoterpenes were considered to be the key indexes in the classification and quality assessment of peony flower. The UPLC-DAD-MS/MS method coupled with multiple compounds determination and fingerprint analysis can be effectively applied as a feature distinguishing method to evaluate the compounds in peony flower raw material for product quality assurance in the food, pharmaceutical, and cosmetic industries. Moreover, this study provides ideas for future research and the improvement of products by these industries.

A high-accuracy gridding vehicle emission inventory is not only the foundation for developing refined emission control strategies but a necessary input to air quality model as well. An accurate approach to the spatiotemporal disaggregation is the key step to improving the accuracy of gridding emission inventories. The existing spatial disaggregation method considers relatively fewer impact factors, lacking adequate correlation analysis among impact factors. Additionally, the existing temporal disaggregation method does not correspond with the actual travel behavior of residents. This paper proposes a multi-factor spatial disaggregation model by principal component analysis (PCAM), based on a correlation analysis of the main impact factors. Further, a new temporal disaggregation model is proposed based on the congestion delay index combined with the traffic flow fundamental model (CDITF). The results from a case study in Jinan show that the square of correlation coefficients (RSQ) between the model- disaggregated NO 2 emissions based on PCAM and the monitored NO 2 concentration increased by 34.4% compared to the traditional disaggregation model based on the standard road length, and the RSQ for CO increased by 13%; the NMD and NME of the simulation results based on CMAQ model compared to standard road length model decrease by approximately 33.7% and 35.5%, respectively. The trend of the monthly, daily, and hourly variations of NO 2 and CO emissions disaggregated by the proposed temporal disaggregation model is quite consistent with that of the monitored concentration data. The PCAM method and the CDITF proposed in this paper are more in line with the actual situation using the cumulative emissions on road sections. The vehicle emissions in Jinan are found to be concentrated in the center of each district and county and near high-grade roads. The disaggregation results in areas with large road slopes are more realistic for considering road slope factors. The trend of the monthly, daily, and hourly variations of NO 2 and CO emissions disaggregated by the proposed temporal disaggregation model is quite consistent with that of the monitored concentration data, however, the monitored concentration data presents a certain degree of time lag. The proposed spatiotemporal disaggregation model in this paper improves the accuracy of gridding vehicle emission inventory, which is of a great significance for developing precise control strategies of vehicle emissions and improving the urban air quality in general., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Camelina [ Camelina sativa (L.) Crantz] seed has long been consumed as a source of food in Canada. But limited information is available concerning the systematical evaluation of the composition, content, and antioxidant activity of Camelina seed polyphenol extract (CSPE). Therefore, the aim of this study was to identify, quantify and evaluate the antioxidant activity of CSPE. The result showed that eight compositions were identified and determined by the UPLC-DAD-ESI-MS 2 analysis. CSPE has potent free radical scavenging capacity. CSPE treatment significantly increased the activities of the antioxidant enzymes (superoxide dismutase and catalase) and glutathione content in a dose-dependent manner in RAW264.7 cells with oxidative injury and also reduced malondialdehyde content (P < 0.01). It may be concluded that CSPE has a strong antioxidant activity as depicted by the in vitro experiments and thus possesses the potential to be developed as food antioxidants or as an ingredient in functional foods.

We examine the feasibility of using accelerometer data exclusively collected during typing on a custom smartphone keyboard to study whether typing dynamics are associated with daily variations in mood and cognition. As part of an ongoing digital mental health study involving mood disorders, we collected data from a well-characterized clinical sample (N = 85) and classified accelerometer data per typing session into orientation (upright vs. not) and motion (active vs. not). The mood disorder group showed lower cognitive performance despite mild symptoms (depression/mania). There were also diurnal pattern differences with respect to cognitive performance: individuals with higher cognitive performance typed faster and were less sensitive to time of day. They also exhibited more well-defined diurnal patterns in smartphone keyboard usage: they engaged with the keyboard more during the day and tapered their usage more at night compared to those with lower cognitive performance, suggesting a healthier usage of their phone.

Objectives: We investigated the protective effect of Rehmannia glutinosa oligosaccharides (RGO) on lipopolysaccharide (LPS)-induced intestinal inflammation and barrier injury among mice., Methods: RGO is prepared from fresh rehmannia glutinosa by water extraction, active carbon decolorization, ion exchange resin impurity removal, macroporous adsorption resin purification, and decompression drying. LPS could establish the model for intestinal inflammation and barrier injury in mice. Three different doses of RGO were administered for three consecutive weeks. Then the weight, feces, and health status of the mice were recorded. After sacrificing the mice, their colon length and immune organ index were determined. The morphological changes of the ileum and colon were observed using Hematoxylin-eosin (H&E) staining, followed by measuring the villus length and recess depth. RT-qPCR was utilized to detect the relative mRNA expression of intestinal zonula occludens-1 (ZO-1) and occludin . The expression of inflammatory factors and oxidation markers within ileum and colon tissues and the digestive enzyme activities in the ileum contents were detected using ELISA. The content of short-chain fatty acids (SCFAs) in the colon was determined with GC. The gut microbial composition and diversity changes were determined with 16S-rRNA high-throughput sequencing. The association between intestinal microorganisms and SCFAs, occludins, digestive enzymes, inflammatory factor contents, and antioxidant indexes was also analyzed., Results: RGO significantly increased the weight, pancreatic index, thymus index, and colon length of mice compared with the model group. Moreover, it also improved the intestinal tissue structure and increased the expression of intestinal barrier-related junction proteins ZO-1 and Occludin. The contents of IL-6, IL-17, IL-1β, and TNF-α in the intestinal tissues of mice were significantly reduced. Additionally, the activities of superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT) were elevated. In contrast, the malondialdehyde (MDA) content decreased. Trypsin and pancreatic lipase activities in the ileum enhanced, and the SCFA contents such as acetic acid, propionic acid, and butyric acid in the colon increased. The study on intestinal flora revealed that RGO could enhance the abundance of intestinal flora and improve the flora structure. After RGO intervention, the relative abundance of Firmicutes, Lactobacillus , and Akkermania bacteria in the intestinal tract of mice increased compared with the model group, while that of Actinomycetes decreased. The intestinal microbiota structure changed to the case, with probiotics playing a dominant role. The correlation analysis indicated that Lactobacillus and Ackermann bacteria in the intestinal tract of mice were positively associated with SCFAs, Occludin, ZO-1 , pancreatic amylase, SOD, and CAT activities. Moreover, they were negatively correlated with inflammatory factors IL-6, IL-17, IL-1β, and TNF-α., Conclusions: RGO can decrease LPS-induced intestinal inflammation and intestinal barrier injury in mice and protect their intestinal function. RGO can ameliorate intestinal inflammation and maintain the intestinal barrier by regulating intestinal flora., Competing Interests: XL, XuefW, EN, LZ, LC, LY, JZ, ZhL, LW, WW, ZiL, and YW were employed by Henan Natural Products Biotechnology Co., Ltd. YF was employed by Henan High Tech Industry Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Li, Gui, Wang, Ning, Zhang, Fan, Chen, Yu, Zhu, Li, Wei, Wang, Li, Wei and Wang.)

The treatment of mood disorders, which can become a lifelong process, varies widely in efficacy between individuals. Most options to monitor mood rely on subjective self-reports and clinical visits, which can be burdensome and may not portray an accurate representation of what the individual is experiencing. A passive method to monitor mood could be a useful tool for those with these disorders. Some previously proposed models utilized sensors from smartphones and wearables, such as the accelerometer. This study examined a novel approach of processing accelerometer data collected from smartphones only while participants of the open-science branch of the BiAffect study were typing. The data were modeled by von Mises-Fisher distributions and weighted networks to identify clusters relating to different typing positions unique for each participant. Longitudinal features were derived from the clustered data and used in machine learning models to predict clinically relevant changes in depression from clinical and typing measures. Model accuracy was approximately 95%, with 97% area under the ROC curve (AUC). The accelerometer features outperformed the vast majority of clinical and typing features, which suggested that this new approach to analyzing accelerometer data could contribute towards unobtrusive detection of changes in depression severity without the need for clinical input.

Sarcoma represents one of the most common malignant tumors with poor treatment outcomes and prognosis. Docetaxel (DTX) is acknowledged as one of the most important chemotherapy agents. The aim of this study was to improve the efficacy of docetaxel by incorporation into the mPEG-PLA nanoparticle (DTX NP) for the treatment of sarcoma. The DTX NP was prepared by emulsion solvent diffusion method and the prescription and preparation process were optimized through a single factor experiment. The optimized DTX NP was characterized by drug loading, encapsulation efficiency, drug release, etc. Then, the pharmacokinetics was conducted on rats and tumor-bearing ICR mice. Finally, the anti-tumor efficacy of DTX NP with different dosages was evaluated on tumor-bearing ICR mice. The optimized DTX NP was characterized by around 100 nm sphere nanoparticles, sustained in vitro drug release with no obvious burst drug release. Compared with DTX injection, the AUC of DTX NP increased by 94.7- and 35.1-fold on the rats and tumor-bearing ICR mice models, respectively. Moreover, the intra-tumoral drug concentration increased by 5.40-fold. The tumor inhibition rate of DTX NP reached 94.66%, which was 1.24 times that of DTX injection (76.11%) at the same dosage, and the bodyweight increase rate was also higher than the DTX injection. The study provided a DTX NP, which could significantly improve the bioavailability and therapeutic efficacy of DTX as well as reduced its toxicity. It possessed a certain prospect of application for sarcoma treatment.

Terminal ligand exchange and framework linker exchange have been frequently practiced as powerful tools to functionalize reticular structures such as metal-organic frameworks (MOFs). Herein, we report the postsynthetic modification (PSM) of a 6-connected layered MOF ( hxl topology) to achieve a 12-connected fcu framework. In the PSM process, isometric linker exchange in the layers and linker installation between adjacent layers by the substitution of modulating ligands happen simultaneously. Snapshots of PSM at different time points reveal that the hxl domain is adaptively reorganized to create sites for new linker installation, and gradually the fcu domain dominates the crystal. Detailed kinetic analysis suggests that, although adaptive linker installation requires interlayer expansion of stackings in situ, it is kinetically faster than isometric linker exchange in the layers.

Traffic congestion and smog are hot topics in recent years. This study analyzes the impacts of road traffic characteristic parameters on urban air quality quantitatively based on aerosol optical thickness (AOD) and geographical weighted regression (GWR) models, including the road network density, road area occupancy, intersection number, and bus network density as main factors. There are some major research findings. Firstly, there exists a strong positive correlation between the peak congestion delay index (PCDI) and air quality, the correlation has R 2 values of up to 0.4962 (R 0.70). Secondly, GWR refines the local spatial changes in the AOD and the road parameters, and the correlation R 2 based GWR model all above 0.6. The correlation between AOD and the road area occupancy was the highest, and the correlations with the bus network density and the intersections number were higher than that with the road network density. Thus, bus route planning, bus emission reduction, road network planning, and signal timing (at intersections) have a greater impact on air quality than other policy, especially in areas with traffic jams. The results of this study could provide theoretical support for traffic planning and traffic control, and is promising in practice., (© 2021. The Author(s).)

In view of the problems involved in remote sensing monitoring of urban air quality, including low spatial resolution, only for a single pollutant, complex inversion algorithms, and difficultly obtaining parameter values, in this study, a new difference smog index (DSI) was developed, and then a comparison with the normal difference haze index, the difference index, and the MODIS aerosol optical depth products. The results show that the DSI model developed in this study has a higher accuracy and a better monitoring effect in urban areas, and it has a higher resolution (30 m), which greatly improves the degree of refinement of the remote sensing monitoring. The DSI model has a higher extensibility, and it is suitable for monitoring the AQI, PM 2.5 , NO 2 . The DSI model proposed in this paper is simple and easy to use, and thus, it has a high potential for application and deserves promotion in urban air quality monitoring., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Forsythoside A is the main active ingredient in the Chinese medicine Forsythia suspensa, which has antiviral, anti-inflammatory, antioxidation, and immunoregulatory effects. It is reported that Forsythoside A can significantly inhibit the replication of the avian infectious bronchitis virus(IBV) in cells, but there is no report in chickens. The present study aimed to investigate the effect of Forsythoside A on IBV-M41, experiments were designed using 120 chickens at 12 days of age. The chickens were randomly divided into eight groups: Forsythoside A high-, medium-, and low-dose prevention groups, Forsythoside A high-, medium-, and low-dose treatment groups, model control group and normal control group. All chickens, except the normal control group, were inoculated with 0.2 ml of IBV-M41 at 15 days of age.The antiviral effects were evaluated by clinical signs, weight, histopathology, T-,B-lymphocyte proliferation, T-lymphocyte subsets and cytokine levels.The results showed that the infection rate in each Forsythoside A prevention group was significantly lower than that in the treatment group and model control group (P < 0.05). The recovery rate in each Forsythoside A treatment group was significantly higher than that in the model control group (P < 0.05), and the recovery rate in high- and medium-dose treatment group was the highest, at up to 86.67%. Lymphocytic transformation ability significantly improved in the prevention and treatment groups. Forsythoside A significantly improved the CD3+, CD4+, and CD8+ T-lymphocyte of infected chickens. The cytokine level was able to maintain high concentrations of IL-2 and IFN-α for a long time and maintain a dynamic IL-4-concentration balance. A number of results showed that Forsythoside A had both preventive and therapeutic effects in IBV-M41-infected chickens, among which the high-dose (80 mg/kg/d) prevention group，the high- (80 mg/kg/d) and medium (40 mg/kg/d) -dose treatment group had significant effects., (Copyright © 2020. Published by Elsevier Ltd.)

In this work, the effects of the protozoan Neospora caninum on the bioenergetics, chemical composition, and elemental content of human brain microvascular endothelial cells (hBMECs) were investigated. We showed that N. caninum can impair cell mitochondrial (Mt) function and causes an arrest in host cell cycling at S and G2 phases. These adverse effects were also associated with altered expression of genes involved in Mt energy metabolism, suggesting Mt dysfunction caused by N. caninum infection. Fourier Transform Infrared (FTIR) spectroscopy analysis of hBMECs revealed alterations in the FTIR bands as a function of infection, where infected cells showed alterations in the absorption bands of lipid (2924 cm -1 ), amide I protein (1649 cm -1 ), amide II protein (1537 cm -1 ), nucleic acids and carbohydrates (1092 cm -1 , 1047 cm -1 , and 939 cm -1 ). By using quantitative synchrotron radiation X-ray fluorescence (μSR-XRF) imaging and quantification of the trace elements Zn, Cu and Fe, we detected an increase in the levels of Zn and Cu from 3 to 24 h post infection (hpi) in infected cells compared to control cells, but there were no changes in the level of Fe. We also used Affymetrix array technology to investigate the global alteration in gene expression of hBMECs and rat brain microvascular endothelial cells (rBMVECs) in response to N. caninum infection at 24 hpi. The result of transcriptome profiling identified differentially expressed genes involved mainly in immune response, lipid metabolism and apoptosis. These data further our understanding of the molecular events that shape the interaction between N. caninum and blood-brain-barrier endothelial cells.

Objective: To investigate the safety and therapeutic efficacy of adjuvant cytokine-induced killer (CIK) cells to minimally invasive therapies in unresectable hepatocellular carcinoma (u-HCC)., Materials and Methods: Hundred patients diagnosed with having u-HCC in our department from January 1, 2001, to July 31, 2018, were recruited. Forty-three patients received microwave ablation (MWA) and transcatheter arterial chemoembolization (TACE) together with autologous CIK cell treatment (TACE + MWA + CIK group), whereas 57 patients received TACE and MWA only (TACE + MWA group). Postprocedural complications and cumulative therapeutic effects were assessed in all patients. The disease control rate, median survival time (MST), and cumulative survival rate were compared between the cohorts using the Kaplan-Meier method and unpaired Student's t-tests., Results: The overall response (complete response [CR] + partial response [PR]) rate was 74.42% (32/43) and 77.19% (44/57) for TACE + MWA + CIK and TACE + MWA groups, respectively (P = 0.243). Those of the TACE + MWA + CIK group had better rates of disease control (CR + PR + stable disease) in contrast to the TACE + MWA group (87.72% vs. 79.07%, respectively) but this failed to achieve statistical significance (P = 0.748). Based on the Kaplan-Meier survival graphs, those of the TACE + MWA + CIK groups possessed markedly increased overall survival (41 months vs. 24 months, P = 0.002) and progression-free survival (17 months vs. 10 months, P = 0.023) rates in compared to the TACE + MWA group. Survival rates were raised also TACE + MWA + CIK group than in TACE + MWA group (P = 0.002), with a MST of 6.13 ± 0.83 months and 11.61 ± 1.59 months in the TACE + MWA + CIK and TACE + MWA groups, respectively. Patients in the TACE + MWA + CIK group were not reported to have any severe complications., Conclusion: CIK cell immunotherapy as an adjuvant to TACE and MWA enhanced long-term prognosis and improved quality of life in patients with u-HCC. This regimen may be recommended as a novel treatment regime in u-HCC patients., Competing Interests: None