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Objective To investigate the differences of cytokine profiles between patients with novel COVID-19 and bacterial pneumonia, unravel the immunopathological mechanism of COVID-19, and provide evidence for new therapeutic targets in COVID-19. Methods In this study, 15 serum samples were collected from mild COVID-19 patients （COVID-19 group）, bacterial pneumonia patients （bacterial pneumonia group）, and healthy controls （healthy control group）, respectively. The expression profile of 48 cytokines was determined to clarify the differences among three groups. The expression levels of 48 cytokines at different time points were measured in serum samples from 10 patients with COVID-19 to analyze their correlation with clinical features and disease progression. Results In the comparation between the COVID-19 group and the bacterial pneumonia group, the expression levels of MIF, GROα, GM-CSF and TNF-β were upregulated in COVID-19 patients（all P < 0.05）, whereas those of IL-10, IL-18, IL-2Rα and MIG were upregulated in patients with bacterial pneumonia（all P < 0.05）. The expression level of M-CSF was significantly downregulated in COVID-19 patients at the second week of hospitalization. The changes in the expression level of MCP-1 were consistent with the nucleic acid test results of COVID-19 patients. Conclusions The cytokine profiles differ between patients with COVID-19 and bacterial pneumonia. In addition, M-CSF and MCP-1 play critical roles in the progression of COVID-19.

Background The association between different phenotypes and genotypes of circulating tumor cells (CTCs) and efficacy of neoadjuvant chemotherapy (NAC) remains uncertain. This study was conducted to evaluate the relationship of FTH1 gene-associated CTCs (F-CTC) with/without epithelial-mesenchymal transition (EMT) markers, or their dynamic changes with the efficacy of NAC in patients with non-metastatic breast cancer. Patients and Methods This study enrolled 120 patients with non-metastatic breast cancer who planned to undergo NAC. The FTH1 gene and EMT markers in CTCs were detected before NAC (T0), after 2 cycles of chemotherapy (T1), and before surgery (T2). The associations of these different types of CTCs with rates of pathological complete response (pCR) and breast-conserving surgery (BCS) were evaluated using the binary logistic regression analysis. Results F-CTC in peripheral blood ≥1 at T0 was an independent factor for pCR rate in patients with HER2-positive (odds ratio [OR]=0.08, 95% confidence interval [CI], 0.01-0.98, P =.048). The reduction in the number of F-CTC at T2 was an independent factor for BCS rate (OR = 4.54, 95% CI, 1.14-18.08, P =.03). Conclusions The number of F-CTC prior to NAC was related to poor response to NAC. Monitoring of F-CTC may help clinicians formulate personalized NAC regimens and implement BCS for patients with non-metastatic breast cancer. [ABSTRACT FROM AUTHOR]

Background/Aim: Abstracts of randomized controlled trials (RCTs) provide a summary of the entire trial report. Their transparent, detailed, and accurate reporting is essential for clinical decision‐making and evidence‐based dental practice. The aim of this study was to assess the reporting quality and prevalence of spin in abstracts of RCTs in the field of dentofacial trauma. Materials and Methods: The PubMed database was searched to identify RCT reports published between 2017 and 2021 in the field of dentofacial trauma. The reporting quality of abstracts was assessed according to the 16‐item CONSORT for Abstracts checklist and measured with an overall quality score (OQS, range: 0–16). Linear regression analyses were used to identify factors associated with reporting quality. Among the included RCTs, parallel‐group RCTs with non‐significant primary outcomes were selected for spin assessment using predefined spin strategies. Results: One hundred and twelve eligible abstracts were identified and included. The mean OQS was 4.51 (SD, 1.35; 95% CI, 4.26–4.76). Abstracts with more than 250 words (p =.004) and a structured format (p =.032) had significantly better reporting quality. Of the 30 abstracts that were eligible for spin assessment, spin was identified in 23 (76.7%). Among these, spin was observed in the Conclusions sections of 22 abstracts (73.3%) and the Results sections of 9 abstracts (30.0%). Conclusions: Among RCT abstracts in the field of dentofacial trauma, the reporting quality was sub‐optimal and the prevalence of spin was relatively high. Strict adherence to the CONSORT for Abstracts guidelines is needed to ensure complete and transparent reporting. Relevant stakeholders need to make concerted efforts to avoid spin. [ABSTRACT FROM AUTHOR]

Most cancer‐related deaths are a result of metastasis. The development of small molecular inhibitors reversing cancer metastasis represents a promising therapeutic opportunity for cancer patients. This pan‐cancer analysis identifies oncogenic roles of membrane‐associated phosphatidylinositol transfer protein 3 (PITPNM3), which is crucial for cancer metastasis. Small molecules targeting PITPNM3 must be explored further. Here, PITPNM3‐selective small molecular inhibitors are reported. These compounds exhibit target‐specific inhibition of PITPNM3 signaling, thereby reducing metastasis of breast cancer cells. Besides, by using nanoparticle‐based delivery systems, these PITPNM3‐selective compounds loaded nanoparticles significantly repress metastasis of breast cancer in mouse xenograft models and organoid models. Notably, the results establish an important metastatic‐promoting role for PITPNM3 and offer PITPNM3 inhibition as a therapeutic strategy in metastatic breast cancer. [ABSTRACT FROM AUTHOR]

Industrial Internet of Things (IIoT) has attracted increasing attention for improving the efficiency of manufacturing. Plenty of computation-intensive and latency-sensitive applications are required by IIoT networks, which pose significant challenges for the computation capacities of IIoT networks. To address these challenges, Edge-enabled Industrial Internet of Things (E-IIoT) emerges. Edge devices located at the edge of IIoT networks enlarge computation capacities of IIoT networks and improve their efficiency accordingly. How to schedule computation resources wisely is a major problem in E-IIoT networks. Since IIoT devices in an E-IIoT network monitor the industrial site collaboratively, tasks for processing sensory data collected by them are correlated accordingly. That means, scheduling highly correlated tasks to be processed at the same device can improve computation efficiency. Inspired by this fact, we propose a correlation aware scheduling (CAS) algorithm for E-IIoT networks in this article. In specific, computation model decision and processing order decision are made by considering computation resources of devices and correlations among tasks in the algorithm to minimize latency of E-IIoT networks. The NP-hardness of correlation aware latency minimization scheduling problem in E-IIoT networks is first proved. Theoretical analysis on approximation ratio of the CAS algorithm is provided, and simulation results demonstrate the effectiveness of the proposed algorithm in reducing latency. [ABSTRACT FROM AUTHOR]

This paper studies the problem of learning the conditional distribution of a high-dimensional output given an input, where the output and input may belong to two different domains, e.g., the output is a photo image and the input is a sketch image. We solve this problem by cooperative training of a fast thinking initializer and slow thinking solver. The initializer generates the output directly by a non-linear transformation of the input as well as a noise vector that accounts for latent variability in the output. The slow thinking solver learns an objective function in the form of a conditional energy function, so that the output can be generated by optimizing the objective function, or more rigorously by sampling from the conditional energy-based model. We propose to learn the two models jointly, where the fast thinking initializer serves to initialize the sampling of the slow thinking solver, and the solver refines the initial output by an iterative algorithm. The solver learns from the difference between the refined output and the observed output, while the initializer learns from how the solver refines its initial output. We demonstrate the effectiveness of the proposed method on various conditional learning tasks, e.g., class-to-image generation, image-to-image translation, and image recovery. The advantage of our method over GAN-based methods is that our method is equipped with a slow thinking process that refines the solution guided by a learned objective function. [ABSTRACT FROM AUTHOR]

Background and Purpose: Arsenic exposure can lead to skin lesions and multiple organ damage, which are not easily reversible and for which there is no effective therapeutics. Identification of reliable epigenetic markers is essential for early recognition of arsenic poisoning risk. Anomalous DNA methylation of immune homeostasis regulator FOXP3 is a critical mechanism for triggering arsenic poisoning. This study aims to explore the value of FOXP3 methylation in the identification of arsenic poisoning risk. Methods: 88 arsenic poisoning subjects and 41 references were recruited. Urinary arsenic contents and FOXP3 methylation in PBLCs was measured by ICP-MS and pyrosequencing, respectively. Results: The results showed that the elevated FOXP3 methylation in PBLCs were associated with the increased levels of urinary arsenic and were positively associated with the increased risk of arsenic poisoning and its progression. The result of mediation analysis revealed that 24.3% of the effect of arsenic exposure on the risk of arsenic poisoning was mediated by increased FOXP3 methylation. Additionally, we constructed a nomogram model with FOXP3 methylation as an epigenetic predictor to assess the probability of individual arsenic poisoning. The model showed a robust ability in the discrimination of arsenic poisoning risk, with an area under receiver operating characteristics curve of 0.897(0.845–0.949) and more than 70% accuracy. The calibration curves and the Harrell concordance index showed that the consistency rate between the probability predicted by the nomogram model and the actual probability is 89.7%. Conclusions: Taken together, we found the great potential of FOXP3 methylation for the identification of arsenic poisoning risk and provided a new approach to the application of epigenetic markers in accurately quantifying the risk of adverse outcomes. [ABSTRACT FROM AUTHOR]

Despite the salient feature of cloud computing, the cloud provider still suffers from electricity bill, which in part comes from 1) the power consumption of running physical machines (PMs) to guarantee the resource/time requirements of virtual machines (VMs), and 2) the dynamically varying electricity price offered by smart grids. In the literature, there exist viable solutions adaptive to electricity price variation to reduce the electricity bill. However, they are not applicable to serving time-sensitive VM requests. In serving time-sensitive VM requests, it is potential for the cloud provider to apply proper consolidation strategies to further reduce the electricity bill. Few prior works have provided theoretical solutions of VM consolidation strategies that are adaptive to electricity price variations in serving time-sensitive VM requests. In this work, to address this challenge, we develop electricity-price-aware consolidation algorithms for both the offline and online scenarios. For the offline scenario, we first develop a consolidation algorithm with constant approximation, which always approaches the optimal solution within a constant factor of 5. For the online scenario, we propose an $O(\log (\frac{L_{max}}{L_{min}}))$ O (log (L m a x L m i n )) -competitive algorithm that is able to approach the optimal offline solution within a logarithmic factor, where $\frac{L_{max}}{L_{min}}$ L m a x L m i n is the ratio of the longest length of the processing time requirement of VMs to the shortest one. Our trace-driven simulation results further demonstrate that the average performance of the proposed algorithms produce near-optimal electricity bill. [ABSTRACT FROM AUTHOR]

Objectives To identify the presence and characteristics of spin (using reporting strategies to distort study results and mislead readers) within randomized controlled trial (RCT) abstracts published in orthodontic journals, and to explore the association between spin and potentially related factors. Methods A manual search was conducted to identify abstracts of RCTs with statistically non-significant primary outcomes published in five leading orthodontic journals between 2015 and 2020. Spin in the Results and Conclusions sections of each included abstract was evaluated and categorized according to pre-determined spin strategies. Logistic regression analyses were employed to explore the association between spin and relevant factors. Results A total of 111 RCT abstracts were included, of which 69 (62.2 per cent) were identified with spin. In the Results section, 47 (42.3 per cent) abstracts had spin, and 'focusing on significant within-group comparison for primary outcomes' was the most frequent spin strategy. In the Conclusions section, 57 (51.4 per cent) abstracts presented spin, with the most common strategy being 'claiming equivalence or non-inferiority for statistically nonsignificant results'. According to multivariable logistic regression analysis, a significantly lower presence of spin was found in studies with international collaboration (odds ratio [OR]: 0.331, 95 per cent confidence interval [CI]: 0.120–0.912, P = 0.033) and trial registration (OR: 0.336, 95 per cent CI: 0.117–0.962, P = 0.042). Conclusion The prevalence of spin is high among RCT abstracts in orthodontics. Clinicians need to be aware of the definition and presence of spin. Concerted efforts are needed from researchers and other stakeholders to address this issue. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the presence and characteristics of spin (a distorted interpretation to make research findings seem favourable) in abstracts of randomized controlled trials (RCTs) in periodontology and oral implantology, and to explore its associated factors and influence on the subsequent literature. Materials and methods: PubMed was searched to identify recent RCTs in periodontology and oral implantology, whose primary outcome was non‐significant. Spin in abstracts was assessed and categorized according to pre‐determined spin strategies. The associations between study characteristics and the presence/severity of spin were analysed using multivariable logistic regressions. Results: 196 abstracts were included, 137 (69.9%) of which had spin. 57 (29.1%) abstracts had spin in the Results section, and 126 (64.3%) had spin in the Conclusion section. The main spin strategies in the Results and Conclusion sections were focusing on secondary outcomes (16.3%) and focusing on within‐group comparisons (28.6%), respectively. The presence of spin was associated with number of centres (OR = 0.28, 95% CI: 0.11–0.73; p =.009), while its severity was associated with topic (OR = 0.24, 95% CI: 0.08–0.70; p =.009). Conclusions: The frequency of spin is relatively high among published RCT abstracts in periodontology and oral implantology. Findings reported in these abstracts need to be interpreted with caution. [ABSTRACT FROM AUTHOR]

Transcatheter arterial chemoembolization (TACE) is the preferred treatment for patients with advanced hepatocellular carcinoma (HCC), but it lacks safe and effective embolic agents. 5-Fluorouracil (5-FU) is a broad-spectrum anticancer drug, but its clinical application is limited due to drug resistance and toxic side effects. Therefore, in this study, we developed a new liquid embolic agent with 5-FU as the model drug. We found that this liquid embolic agent possesses good gelling properties and embolic effects. An in vitro drug release model of the agent conformed to the Weibull model. Cumulative release of the drug over 7 d was ∼90%, consisting of an initial burst followed by sustained release. Cytotoxicity testing showed that each liquid embolic composition is cytocompatible and only mildly cytotoxic. Pharmacokinetic experiments showed that the formulation significantly prolongs the t1/2 of 5-FU (approximately five times that of 5-FU solution) and 5-FU residence time in the body (approximately three times that of 5-FU solution). These results indicate that the liquid embolic agent has embolic capacity and could be used as a potential therapeutic method for TACE. [ABSTRACT FROM AUTHOR]

Transmission is crucial for big data analysis and learning in industrial Internet of Things (IoT) systems. To transmit data with limited energy is a challenge. This paper studies the problem of data transmission in energy harvesting systems with capacitor to supply energy where the energy receiving rate varies over time. The energy receiving rate is slower when the capacitor receives more energy. Based on this characteristic, we study the problem of how to transmit more data when the energy receiving time is not continuous. Given many packets that arrive at different time instances, there is a tradeoff between transmitting the packet right now or saving the energy to transmit the future arriving packets. We formalize two types of problems. The first one is how to minimize the total completion time when there is enough energy to transmit all the packets. The second one is how to transmit as many packets as possible when the energy is not enough to transmit all the packets. For the first problem, we give a $1+\alpha$ approximation offline algorithm when all the information of the packets and the energy receiving periods is known in advance, and a $\max \lbrace 2,\beta \rbrace$ competitive ratio online algorithm where the information is not known in advance. For the second problem, we study three cases and give a $6+\lceil \frac{h}{b/R} \rceil$ approximation offline algorithm for the general situation. We also prove that there does not exit a constant competitive ratio online algorithm. [ABSTRACT FROM AUTHOR]

Abstract: Recently, an increasing number of studies have focused on the key function of long noncoding RNAs (lncRNAs) in biological activity. Abnormal lncRNA expression was found to relate to the development and pathogenesis of multiple cancers. LncRNA LINC00152 served as an oncogene in multiple cancers; however, its role in ovarian cancer remains unknown. In our research study, LINC00152 was upregulated in ovarian cancer tissues and cell lines. An increasing LINC00152 level was positively correlated with the histological grade, clinical stage, and poor prognosis of ovarian cancer patients. In addition, knockdown of LINC00152 reduced cell growth, induced cell apoptosis, and suppressed tumor growth. Moreover, we revealed that LINC00152 and Myeloid cell leukemia‐1 (MCL‐1) were targeted by miR‐125b and had the same miR‐125b combining site. The miR‐125b level was negatively correlated with the expression of LINC00152, while MCL‐1 was positively related to the LINC00152 level. MiR‐125b could affect LINC00152 levels as evaluated by qRT‐PCR. Finally, we affirmed that LINC00152 mediated cell proliferation by affecting MCL‐1 expression and MCL‐1‐mediated mitochondrial apoptosis pathways and by working as a competitive endogenous RNA (ceRNA) of miR‐125b. In summary, based on ceRNA theory, the combined research on miR‐125b and MCL‐1, and taking LINC00152 as a new study point, we provide new insight into the molecular mechanism of reversing cell proliferation in ovarian cancer. [ABSTRACT FROM AUTHOR]

This paper studies the problem of maximizing the energy utilization for data transmission in sensors with periodical wireless charging process while taking into account the thermal effect. Two classes of problems are analyzed: one is the case that wireless charging can process for only a limited period of time, and the other is the case that wireless charging can process for a long enough time. Algorithms are proposed to solve the problems and analysis of these algorithms are also provided. For the first problem, three subproblems are studied, and, for the general problem, we give an algorithm that can derive a performance bound of (1−1/2m)(OPT−E) compared to an optimal solution. In addition, for the second problem, we provide an algorithm with 2m/2m−1OPT+1 performance bound for the general problem. Simulations confirm the analysis of the algorithms [ABSTRACT FROM AUTHOR]

Multicast is an important way to diffuse data in duty-cycled wireless sensor networks (WSNs), where nodes can receive data only in active state. The communication delay can be extremely large if inappropriate schedules are adopted. Unfortunately, most previous methods do not consider controlling multicast delay energy-efficiently. This paper studies the minimum active time slot augmentation for delay-bounded multicast (MAADM) problem in duty-cycled WSNs. The MAADM problem is proved to be NP-hard even under the node-exclusive interference model. An optimal algorithm is proposed for the MAADM problem when $K=2$ and a heuristic latency bounding algorithm is proposed for source-to-all communications, where $K$ denotes the number of the destination nodes. When $K>2$ , two ( $K$ −1)-approximation algorithms are designed for the MAADM problem. In addition, a low computation-complexity distributed algorithm is proposed. To the best of our knowledge, this is the first work that develops a series of efficient centralized and distributed algorithms for the MAADM problem in duty-cycled WSNs. The theoretical analysis and experimental results verify that all the proposed algorithms have high performance in terms of delivery delay and energy consumption. [ABSTRACT FROM PUBLISHER]

In crowdsourcing markets, a requester announces a task and calls for contribution from potential participants. With strategic participants, the requester needs to reward the participants to introduce the incentives of participation. However, it is natural to ask whether it is worth introducing incentives if the total payment for eliciting incentives is too high. This paper addresses such a fundamental concern by designing a frugal mechanism with minimum payment used to procure the total amount of service contributions demanded. We design two mechanisms to provide the incentives of participation while minimizing the payment used by the requester. We first propose a frugal auction-based mechanism, which stimulates participants to truthfully report their information. We theoretically prove that the payment used is not more than the optimal cost (with no incentive considered) plus a bounded additive. We then design a Stackelberg-game-based mechanism, in which the requester fixes a certain total payment at the very beginning so as to encourage the participants to compete for it and participate in the task. We verify the existence of a unique Nash equilibrium (NE) and develop a novel algorithm to find the NE, as well as the optimal payment to extract the NE. Our simulation results show that the payment used in these mechanisms is close to the optimal solution with no incentive considered, while the extra payment caused by introducing truthfulness in auction-based mechanism is about twice that of the NE in Stakelberg-game-based mechanism. [ABSTRACT FROM AUTHOR]

BACKGROUND An 8-hydroxyquinoline ( HQ)-type composite chelating material with high performance was designed and prepared. Monomer hydroxyethyl methacrylate ( HEMA) was first grafted onto silica gel particles via surface-initiated graft-polymerization, forming grafted particles PHEMA/ SiO2 with a high grafting degree. Subsequently, through the substitution reaction between 5-chloromethyl-8-hydroxyquinoline ( CHQ) and the grafted macromolecules PHEMA, HQ groups were bonded onto the grafted particles, obtaining the composite chelating material HQ-PHEMA/ SiO2. The chelating adsorption performance and mechanism of HQ-PHEMA/ SiO2 towards Cu2+ and Ni2+ ions was studied, and the adsorption thermodynamics was investigated. RESULTS The experimental results show that HQ-PHEMA/ SiO2 possesses a strong adsorption affinity for heavy metal ions owing to the high density of the HQ group, and for Cu2+ and Ni2+ ions, the adsorption capacities were up to 63.4 mg g−1 and 51.1 mg g−1, respectively. The adsorption behavior fits the Langmuir model, and the adsorption enthalpy change Δ H is positive, indicating endothermic chemisorption. The value of the entropy change Δ S is also positive, and the higher value of | TΔ S| suggests that the adsorption process is entropically driven. CONCLUSION HQ-PHEMA/SiO2 is a promising material for the effective removal of heavy metal ions from water. © 2013 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

We study the power conservation and disseminating reliability problem in precision agriculture applications in this paper. Precision agriculture needs to accurately evaluate farming environment, and soil monitoring is an important part of this effort. Soil measurement requires soil sensors being buried deep enough so as to avoid plowing and other mechanical activities. Due to dielectric loss, reflection and many other reasons, radio communication underground is difficult. But existing work find that the communication between aboveground and underground (air-soil) is feasible, thus aboveground sensor nodes are employed to connect the underground nodes. In such air-soil sensor network, most transmissions are dependent on the aboveground sensor nodes, thus, the energy consumption of them is a critical concern. On the other hand, the reliability of data dissemination must also be well considered as a result of important packets forwarding, such as query commands disseminating, control information delivering and binary reprogramming over the air. Given the situation of limited power and unreliable wireless links, we propose the K-matching problem, which is to minimize the energy consumption by setting optimal transmitting power so that each node underground is connected to at least K aboveground nodes in the air. We prove that this problem is NP-complete and two centralized and one distributed approximation algorithm are provided to solve this problem. Theoretical analysis and experiment results demonstrate the effectiveness of the proposed algorithms [ABSTRACT FROM AUTHOR]

Simple Summary: Distant metastasis, especially bone metastasis, is the major cause of death in breast cancer patients. However, breast cancer patients with bone metastasis are frequently complicated by delayed intervention as clinically bone metastasis cannot be detected early enough. Here, we report that CTNND1 is downregulated in both primary tumors and metastatic bone lesions of patients with triple-negative breast cancer (TNBC). Decreased CTNND1 is a crucial intrinsic contributor to homing to the bones and the survival of the breast cancer cells in the bone microenvironment. Thus, CTNND1 may be a novel biomarker for early predicting bone metastasis of triple-negative breast cancer. Bone metastasis from triple-negative breast cancer (TNBC) frequently results in poorer prognosis than other types of breast cancer due to the delay in diagnosis and intervention, lack of effective treatments and more skeletal-related complications. In the present study, we identified CTNND1 as a most reduced molecule in metastatic bone lesion from TNBC by way of high throughput sequencing of TNBC samples. In vivo experiments revealed that knockdown of CTNND1 enhanced tumor cells metastasis to bones and also increased neutrophils infiltration in bones. In vitro, we demonstrated that knockdown of CTNND1 accelerated epithelial–mesenchymal transformation (EMT) of tumor cells and their recruitment to bones. The involvement by CTNND1 in EMT and bone homing was achieved by upregulating CXCR4 via activating the PI3K/AKT/HIF-1αpathway. Moreover, TNBC cells with reduced expression of CTNND1 elicited cytotoxic T-cells responses through accelerating neutrophils infiltration by secreting more GM-CSF and IL-8. Clinically, patients with triple-negative breast cancer and lower level of CTNND1 had shorter overall survival (OS) and distant metastasis-free survival (DMFS). It was concluded that downregulation of CTNND1 played a critical role in facilitating bone metastasis of TNBC and that CTNND1 might be a potential biomarker for predicting the risk of bone metastases in TNBC. [ABSTRACT FROM AUTHOR]

Phosphatidylinositol transfer protein membrane-associated 1 (PITPNM1) contains a highly conserved phosphatidylinositol transfer domain which is involved in phosphoinositide trafficking and signaling transduction under physiological conditions. However, the functional role of PITPNM1 in cancer progression remains unknown. Here, by integrating datasets of The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer (METABRIC), we found that the expression of PITPNM1 is much higher in breast cancer tissues than in normal breast tissues, and a high expression of PITPNM1 predicts a poor prognosis for breast cancer patients. Through gene set variation analysis (GSEA) and gene ontology (GO) analysis, we found PITPNM1 is mainly associated with carcinogenesis and cell-to-cell signaling ontology. Silencing of PITPNM1, in vitro, significantly abrogates proliferation and colony formation of breast cancer cells. Collectively, PITPNM1 is an important prognostic indicator and a potential therapeutic target for breast cancer. [ABSTRACT FROM AUTHOR]

Since the discovery of the first microRNA (miRNA), the exploration of miRNA biology has come to a new era in recent decades. Monumental studies have proven that miRNAs can be dysregulated in different types of cancers and the roles of miRNAs turn out to function to either tumor promoters or tumor suppressors. The interplay between miRNAs and the development of cancers has grabbed attention of miRNAs as novel tools and targets for therapeutic attempts. Moreover, the development of miRNA delivery system accelerates miRNA preclinical implications. In this review, we depict recent advances of miRNAs in cancer and discuss the potential diagnostic or therapeutic approaches of miRNAs. [ABSTRACT FROM AUTHOR]

Hydrothermal carbonization (HTC) has been proved to be a promising technology for swine manure (SM) treatment. Currently, there is a lack of systematic understanding of the transformation characteristics of nutrient speciation in the HTC of SM. In this study, the speciation of the main nutrients (N/P/K) in SM-derived hydrochar produced at different reaction temperatures (200–280 °C) was investigated. The recovery of P (61.0–67.1%) in hydrochars was significantly higher than that of N (23.0–39.8%) and K (25.5–30.0%), and the increase in reaction temperature promoted the recovery of P and reduced the recovery of N. After the HTC treatment, the percentage of soluble/available P was reduced from 61.6% in raw SM to 4.0–23.9% in hydrochars, while that of moderately labile/slow-release P was improved from 29.2% in raw SM feedstock to 65.5–82.7%. An obvious reduction was also found in the amounts of available N (from 51.3% in raw SM feedstock to 33.0–40.5% in hydrochars). The percentages of slow-release N and residual N in hydrochars produced at 240 °C reached the maximum and minimum values (46.4% and 18.9%), respectively. A total of 49.5–58.3% of K retained in hydrochars was residual (invalid) potassium. From the perspective of the mobility and availability of N, P and K only, it was suggested that the HTC of SM should be carried out at 220–240 °C. Compared with the original SM, it is safer and more effective to use the SM-derived hydrochar as an organic fertilizer. [ABSTRACT FROM AUTHOR]

Stem cells from apical papilla (SCAPs) are desirable sources of dentin regeneration. Epigallocatechin-3-gallate (EGCG), a natural component of green tea, shows potential in promoting the osteogenic differentiation of bone mesenchymal stem cells. However, whether EGCG regulates the odontogenic differentiation of SCAPs and how this occurs remain unknown. SCAPs from immature human third molars (16–20 years, n = 5) were treated with a medium containing different concentrations of EGCG or bone morphogenic protein 2 (BMP2), with or without LDN193189 (an inhibitor of the canonical BMP pathway). Cell proliferation and migration were analyzed using a CCK-8 assay and wound-healing assay, respectively. Osteo-/odontogenic differentiation was evaluated via alkaline phosphatase staining, alizarin red S staining, and the expression of osteo-/odontogenic markers using qPCR and Western blotting. We found that EGCG (1 or 10 μM) promoted the proliferation of SCAPs, increased alkaline phosphatase activity and mineral deposition, and upregulated the expression of osteo-/odontogenic markers including dentin sialophosphoprotein (Dspp), dentin matrix protein-1 (Dmp-1), bone sialoprotein (Bsp), and Type I collagen (Col1), along with the elevated expression of BMP2 and phosphorylation level of Smad1/5/9 (p < 0.01). EGCG at concentrations below 10 μM had no significant influence on cell migration. Moreover, EGCG-induced osteo-/odontogenic differentiation was significantly attenuated via LDN193189 treatment (p < 0.01). Furthermore, EGCG showed the ability to promote mineralization comparable with that of recombinant BMP2. Our study demonstrated that EGCG promotes the osteo-/odontogenic differentiation of SCAPs through the BMP–Smad signaling pathway. [ABSTRACT FROM AUTHOR]

Security is a critical concern in low-power IoT (Internet of Things) wireless sensors because these resource constrained devices are easy to attack and meanwhile the energy constraint sensors will consume a lot of energy to run algorithms for security purposes. We study the energy efficiency data transmission problem in IoT sensors that use capacitors to harvest wireless energy while considering the energy cost for running security algorithms. Energy harvesting with capacitors has the characteristic that the energy harvesting rate varies over time, and it is getting slower and slower as the capacitor gets more and more wireless energy. This observation will result in a trade-off for data transmission in two ways: (1) dividing data into more number of packets, thus the sensors can receive wireless energy at a higher harvesting rate, but it will result in extra energy consumption; (2) dividing data into less numbers of packets—in this way, the sensor cannot utilize the high harvesting rate, but the extra energy cost is less. We studied two sets of this problem where the low-power sensors can harvest enough wireless energy or not, and give algorithms to transmit all the data or as much data as possible, respectively, while taking into account extra cost. The theoretical performance of the proposed algorithms is also analyzed. Both theoretical analysis and extensive simulations show that the proposed algorithms have good performance. [ABSTRACT FROM AUTHOR]

• Ca/P-PILP was synthesized at high Ca2+ concentration without precipitation. • Electron Probe Micro Analyzer was used to investigate element contents. • Artificial caries dentin lesion could be biomimetic remineralized by Ca/P-PILP. • Remineralization could improve the bond strength of artificial caries dentin lesion. To assess the ultrastructural change of demineralized dentin collagen during calcium phosphate polymer-induced liquid precursor (Ca/P-PILP) mediated remineralization process and to evaluate the biomimetic remineralization potential of high concentration Ca/P-PILP at demineralized artificial caries dentin lesion, additionally to investigate the bond interfacial integrity as well as the bonding strength of the biomimetic remineralized artificial caries dentin lesion. Demineralized dentin collagen of 5 μm thick was biomimetically remineralized with low, medium concentration Ca/P-PILP for 10 days and high concentration Ca/P-PILP for 10, 15, 20 days. Artificial caries dentin lesion at a thickness of 150 ± 50 μm was biomimetically remineralized with high concentration Ca/P-PILP for 20 days. The biomimetic remineralization of demineralized dentin collagen was observed by scanning electron microscopy (SEM). The biomimetic remineralization intensity and depth of artificial caries dentin lesion was assessed by Electron Probe Micro Analyzer (EPMA). The bonding interfacial integrity between remineralized artificial caries dentin and composite resin was observed by Swept-source optical coherence tomography (SS-OCT) and the bonding strength of remineralized artificial caries dentin was evaluated by micro-tensile bond strength analysis (μTBS). Solely PAA-PASP solution and solely saturated Ca/P solution can't achieve dentin collagen remineralization. Increased concentration of Ca/P-PILP and prolonged remineralization time can enhance the biomimetic remineralization intensity of demineralized dentin collagen. After treating with high concentration Ca/P-PILP, a 150 ± 50 μm thick layer of demineralized artificial caries dentin lesion was not fully remineralized, and the biomimetic remineralization intensity reached up to 88.0%. Furthermore, a better bonding interfacial integrity with less microgap and increased bond strength at both baseline level and aging level were observed when artificial caries dentin lesion was biomimetically remineralized with high concentration Ca/P-PILP. Biomimetic remineralization of demineralized caries dentin lesion promotes its clinical properties for resin composited adhesive restoration. [ABSTRACT FROM AUTHOR]

MicroRNA-196b (miR-196b) is frequently amplified and aberrantly overexpressed in acute leukemias. To investigate the role of miR-196b in acute leukemias, it has been observed that forced expression of this miRNA increases proliferation and inhibits apoptosis in human cell lines. More importantly, we show that this miRNA can significantly increase the colony-forming capacity of mouse normal bone marrow progenitor cells alone, as well as partially blocking the cells from differentiation. Taken together, our studies suggest that miRNA-196b may play an essential role in the development of MLL -associated leukemias through inhibiting cell differentiation and apoptosis, while promoting cell proliferation. [ABSTRACT FROM AUTHOR]

Camouflaged objects often blend in with their surroundings, making the perception of a camouflaged object a more complex procedure. However, most neural-network-based methods that simulate the visual information processing pathway of creatures only roughly define the general process, which deficiently reproduces the process of identifying camouflaged objects. How to make modeled neural networks perceive camouflaged objects as effectively as creatures is a significant topic that deserves further consideration. After meticulous analysis of biological visual information processing, we propose an end-to-end prudent and comprehensive neural network, termed IdeNet, to model the critical information processing. Specifically, IdeNet divides the entire perception process into five stages: information collection, information augmentation, information filtering, information localization, and information correction and object identification. In addition, we design tailored visual information processing mechanisms for each stage, including the information augmentation module (IAM), the information filtering module (IFM), the information localization module (ILM), and the information correction module (ICM), to model the critical visual information processing and establish the inextricable association of biological behavior and visual information processing. The extensive experiments show that IdeNet outperforms state-of-the-art methods in all benchmarks, demonstrating the effectiveness of the five-stage partitioning of visual information processing pathway and the tailored visual information processing mechanisms for camouflaged object detection. Our code is publicly available at: https://github.com/whyandbecause/IdeNet.