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Background: The unilateral biportal endoscopic (UBE) technique has garnered significant attention for its little paraspinal iatrogenic damage, expedited recovery, and low complication rates. This method is also applicable to open transforaminal lumbar interbody fusion (TLIF). Therefore, this study aimed to conduct a comparative analysis of the outcomes associated with unilateral biportal endoscopic transforaminal lumbar interbody fusion (UBE-TLIF), minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF), and TLIF for Meyerding grade I lumbar spondylolisthesis. Methods: The study examined the outcomes of 79 patients with Meyerding grade I lumbar spondylolisthesis who underwent single-level intervertebral fusion. Clinical assessments included the measurement of pain levels using the Visual Analogue Scale (VAS) for low back and leg pain, the Oswestry Disability Index (ODI), surgical data, and demographic information. Imaging techniques were utilized to evaluate the fusion rate. Results: The VAS-Back demonstrated a statistically significant improvement in Group UBE-TLIF compared to the other groups at the one-week postoperative evaluation (p <.05). Additionally, the UBE-TLIF group exhibited a significantly longer total operative time compared to the other groups (p <.05). However, it was noted that the Postop Hemovac drain were significantly greater in the MIS-TLIF and TLIF groups compared to the UBE-TLIF group (p <.05). Conclusions: The present research demonstrated the effectiveness of UBE-TLIF, MIS-TLIF, and TLIF as surgical approaches for treating Meyerding grade I lumbar spondylolisthesis. Among these methods, UBE-TLIF demonstrated a reduction in Postop Hemovac drain, and an increase in operative duration. [ABSTRACT FROM AUTHOR]

Mobile crowdsensing (MCS) is a combination of crowdsourcing ideas and mobile sensing devices, designed to enable rational allocation of resources at scale. However, the MCS platform is highly vulnerable to injection attacks from malicious participants and fake tasks that interfere with platform service capabilities and sensing activities. To this end, the participant and task submission process is modeled as a multivariate time series, and a detection model for malicious participants and fake tasks (MP-FTD) with a Gaussian prior on the attentional mechanism and a two-stage adversarial training process is proposed. The attention mechanism was corrected using Gaussian bias, and then the corrected attention mechanism was used to obtain the correlation discrepancies between the data. Using the adversarial training method of Generative Adversarial Networks (GAN), the output of the correlation discrepancy reconstruction phase is transformed into a focus score, to amplify the reconstruction error in the output of the focus score reconstruction phase, and to improve the differentiation between the injected data and normal data of malicious attackers. The detection of these malicious attackers will effectively improve the robustness of the sensing platform. Experiments on six real-world datasets showed that the average F1-score reached 93.44%, outperforming the current baseline method, and resulting in an average 12.07% improvement in participant assignment accuracy and an average 12.25% improvement in task assignment accuracy in task assignment experiments. [ABSTRACT FROM AUTHOR]

Mobile Crowd Sensing is a human-based data collection model, and the approach taken to recommend data collection tasks to users in order to maximize task acceptance rates is an important part of this research. Existing task recommendation methods are based only on intuitive data for unconscious analysis and decision-making, and lack the embodiment of cognitive intelligence. To address the above problem, a conscious task recommendation based on cognitive reasoning computing in Mobile Crowd Sensing has been proposed, using knowledge from cognitive science to simulate the human thinking process in order to achieve warm learning and conscious recommendation of sensing tasks. First, the task attributes are segmented into positive and negative attributes using a Kernel Density Estimation method based on bandwidth self-selection. Then, the user's attribute preferences are diagnosed by the Cognitive Diagnostic Method to obtain the user's preference vector. Finally, get the overall preference trend of users based on the Drift Diffusion Model, and make decisions according to whether the current task drift direction is consistent with the user preference trend. Simulation experiments were conducted using the Taobao dataset, MTurk dataset, and synthetic dataset, it was ultimately proven that conscious task recommendation combined with user cognitive ability effectively reduced RMSE and improved task acceptance rate. RMSE was 10.5%∼70.8% lower than other methods, and the task acceptance rate was basically over 80%, with most of the results being over 90%. [ABSTRACT FROM AUTHOR]

As an emerging wireless communication technology, narrowband Internet of Things is widely used in various scenarios, but it also brings new security problems, especially the group authentication between terminal devices and servers. In narrowband Internet of Things, terminal devices are often deployed in unattended environments, which are vulnerable to various attacks and controlled by adversaries, resulting in identity information leakage. Secondly, a large number of terminal devices send authentication request information to the server at the same time, which is easy to cause network signaling congestion, and the centralized calculation mode of the server will cause a large delay in the authentication process. To solve these problems, we propose an edge-assisted group authentication scheme for narrowband Internet of Things. Firstly, a lightweight encryption algorithm LCHAOSAES was used to encrypt the terminal device identity to prevent the terminal device identity information leakage. Then, the edge computing method was used to add an edge network layer to the NB-IoT system architecture to assist in completing the group authentication of massive terminal devices, and the edge assistance could realize decentralization and reduce the load of centralized processing of the server. The Burrows Abadi Needham logic verification, informal security analysis and performance analysis show that the proposed scheme is robust under malicious attacks such as replay attack, man-in-the-middle attack and insider attack, and has less signaling overhead and delay. [ABSTRACT FROM AUTHOR]

Subarachnoid hemorrhage (SAH) is a devastating disease associated with a high mortality and morbidity. Exosomes have been considered as a potential therapeutic target for SAH. However, the effect of exosomes in SAH remains to be elucidated. In this study, we focused on investigating the effect of plasma exosomal lncRNA TM7SF3-AU1 in white matter injury after SAH. The SAH model was established by means of endovascular perforation. Exosomes were extracted from rat plasma samples. The expression of RNAs in the exosomes was detected by the transcriptomic microarray. Differentially expressed circRNA, lncRNA, and mRNA were obtained. The ceRNA network showed that the lncRNA TM7SF3-AU1 and miR-702-3p were closely associated with SARM1. Knocking down TM7SF3-AU1 promoted the expression of miR-702-3p and suppressed the expression of SARM1, and knocking down TM7SF3-AU1 also attenuated white matter injury after SAH. In addition, knocking down TM7SF3-AU1 improved the neurological deficits in locomotion, anxiety, learning, memory, and electrophysiological activity after SAH. Mechanistically, TM7SF3-AU1 was able to absorb miR-702-3p, which directly bind the SARM1 mRNA. Furthermore, the white matter injury attenuated by knockdown of TM7SF3-AU1 was partially reversed by the miR-702-3p antagomir in SAH rats. Taken together, this study showed that TM7SF3-AU1 acts as a sponge for miR-702-3p, reducing the inhibitory effect of miR-702-3p on SARM1, resulting in increased SARM1 expression and thus leading to white matter injury after SAH. Our study provides new insights into exosome-associated white matter injury. It also highlights TM7SF3-AU1 as a potential therapeutic target for white matter injury after SAH. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to explore the impact of sarcopenia on clinical outcomes after percutaneous kyphoplasty (PKP) for osteoporotic vertebral compression fracture (OVCF). Methods: We retrospectively analyzed the medical records of patients with single-segment OVCF who underwent percutaneous kyphoplasty (PKP) between September 2021 and August 2022. Patients were categorized into a sarcopenia group (43 patients) and a non-sarcopenia group (125 patients) based on their Advanced Skeletal Muscle Index (ASMI). Clinical and radiological data were collected and analyzed. Results: There were no significant differences between the sarcopenia and non-sarcopenia groups in age, sex, bone mineral density (BMD), body mass index (BMI), fractured segment, fracture type, surgical approach, bone cement volume, bone cement distribution, comorbidities, preoperative and immediate postoperative VAS and ODI scores (P >.05). However, the time to ambulation, hospital stays, VAS and ODI scores at follow-up, excellent/good rate, and the incidence of residual pain and re-fractures in the non-sarcopenia group were significantly better than those in the sarcopenia group (P <.05). Meanwhile, radiological outcomes, including regional kyphosis and vertebral height loss rate, were significantly better in the non-sarcopenia group than in the sarcopenia group at 6 and 12 month follow-ups (P <.05). Conclusion: Clinical outcomes after PKP in patients with OVCF could be negatively affected by sarcopenia. Therefore, prevention and treatment of sarcopenia should be actively considered in the management of patients with OVCF. [ABSTRACT FROM AUTHOR]

The rapid recombination of photogenerated charge carriers seriously impedes the photocatalytic activity of BiVO4. We propose an effective strategy to overcome this by constructing heterostructured BiVO4-{010}/Ag plasmonic photocatalysts by the multi-object synchronous optimization of the microstructure of the BiVO4 matrix including the optimization of the active facets, morphology, and surface defects. A solvothermal method was employed to realize the optimization of BiVO4. The influence of BiVO4 with different microstructures on the construction and photocatalytic performance of BiVO4/Ag were studied. In terms of construction, the degree of exposure of the {010} facet of BiVO4 is a key factor in the thermodynamic process determining the formation of the {010} facet–Ag heterojunction, whereas the degree of exposure of the active facets, morphology, and surface defects of BiVO4 are crucial factors in the dynamic processes. The pseudo-first-order kinetic constant (k) of the photocatalytic degradation of Rhodamine B (RhB) for FS-BVO {010} under visible light irradiation is 8.8 and 4.8 times that of SS-BVO {010} and SS-BVO, respectively, and 2.8 and 3.8 times that of SS-BVO {010}/Ag and SS-BVO/Ag, respectively. FS-BVO {010} exhibited the second highest photocatalytic performance, primarily attributed to the promotion of the separation and migration of the photogenerated charge, the increased lifetime of the charge carriers, and more active sites. This depended on the multi-object synchronous optimization of the microstructure, including the preferentially exposed {010} facet, the four-star-like morphology with a stair-stepping hierarchical structure, and the {010} facet defect structure. This suggests that the photocatalytic performance of BiVO4 can be improved further by optimizing the microstructure of the BiVO4 matrix than by constructing BiVO4/Ag based on conventional BiVO4. Furthermore, the k value for FS-BVO {010}/Ag is 4.2 times that of FS-BVO {010}. This enhanced photocatalytic performance may be mainly due to the synergistic effect between the optimized microstructure and the {010} facet–Ag Schottky junction, and the surface plasmon resonance effect of the Ag nanoparticles, which can further extend the absorption of light, suppress the recombination of the photogenerated charge, and prolong the lifetime of the charge carriers. ˙O2− and h+ are the dominant active species in the photodegradation of RhB over FS-BVO {010}/Ag and a possible photocatalytic mechanism is proposed. This work provides new insights into constructing efficient photocatalysts based on matched surfaces/interfaces by optimizing the microstructure of a pure semiconductor for utilization in the field of environmental treatment. [ABSTRACT FROM AUTHOR]

Background: Both Unilateral Biportal Endoscopic Discectomy (UBED) and Percutaneous Endoscopic Interlaminar Discectomy (PEID) have resulted in favorable clinical outcomes in the management of LDH. The aim of this study is to comprehensively compare the efficacy of UBED and PEID in treating migrated LDH in the lower lumbar spine, with a specific focus on high-grade migrated LDH. Methods: 96 patients who underwent UBED (31 cases) and PEID (65 cases) procedures were enrolled in the study. All patients received a minimum follow-up period of 6 months. Clinical outcomes of the patients were assessed with incision length, operation time, total hemoglobin loss, hospital stay, intraoperative fluoroscopy times, visual analogue scale (VAS) for lower back and leg pain, Oswestry disability index (ODI), modified MacNab criteria, complications, area of lamina loss and increased intervertebral height. Results: The VAS scores for lower back and leg pain and ODI significantly decreased in both groups after the operation. Preoperatively, at 1 day, 1 month, and 6 months after the procedure, the VAS and ODI scores exhibited no significant differences between the two groups. There was no significant difference in terms of modified MacNab criteria, area of lamina loss, and increased intervertebral height. The UBED group had a longer incision length, operation time and postoperative hospital stay, and fewer intraoperative fluoroscopy times than to the PEID group. Complications were noted in both groups throughout the follow-up period, but there was no significant difference in the rate of complications. Moreover, there were no notable differences in clinical outcomes between the two groups in the high-grade migrated LDH. Conclusions: Both UBED and PEID could achieve favorable clinical outcomes for treating migrated LDH at the lower lumbar spine. Despite the longer operative time and postoperative hospital stay associated with the UBED group, UBED remains safe and innovative for treating migrated LDH at the lower lumbar spine. [ABSTRACT FROM AUTHOR]

A self-evolving reasoning method for task-user relationships based on the autonomic knowledge graph is proposed for the problem of existing task assignment methods, which cannot cope with dynamic environment changes in mobile crowd sensing. In particular, with the idea of "self-reflection," "self-configuration," and "self-adjustment" from autonomic computing, the concept of the autonomic knowledge graph is proposed for the first time. We apply it to build the complete cycle of the knowledge graph, which ensures the dynamic mapping between the task-user relationships in the mobile crowdsensing system. "Self-reflection" generates real-time responses to changes in the internal and external environment of the system. "Self-configuration" selects high-quality sensing users and filters the mobile crowd sensing knowledge graph paths to ensure the reliability of sensing users. Based on the filtered paths, "self-adjustment" computes the neighbor weight matrix of nodes to update node embeddings and exploit potential connections between task-user nodes. Finally, link prediction between task-user nodes achieves accurate and effective task recommendations. This self-evolving reasoning method of nodal relationships we designed combines autonomic computing with the knowledge graph. It forms a continuously operating loop that the next moment of sensing quality is assured and enhanced in the mobile crowd sensing system. Experiments based on the real-world Gollowa dataset, the public Last-FM dataset, and the Amazon-book dataset show that the proposed method can effectively improve sensing data quality and the accuracy of task recommendations. [ABSTRACT FROM AUTHOR]

With the increasingly prominent problem of data security in Narrowband Internet of Things (NB-IoT) terminal transmission, the existing cryptographic algorithms still have problems that cannot meet the security requirements of Narrowband Internet of Things terminal data and the low degree of lightweight. A lightweight block cryptographic algorithm SPNRX based on variant And-Rotate-XOR (ARX) structure and Substitute Permutation Network (SPN) structure is proposed. The proposed algorithm takes into account the unique security requirements of the NB-IoT terminal, such as simplifying the encryption process as far as possible, not too long encrypted data and high-security level, and reducing the number of encryption rounds. It overcomes the shortcoming that half of the block information of the ARX structure does not change during one round of encryption, to improve the diffusion speed. In addition, considering the security of keys and the cost of hardware implementation, a key schedule based on matrix transformation and P-box permutation is proposed. The security analysis of the SPNRX shows that the SPNRX is resistant to differential analysis, linear analysis, etc. Finally, the hardware and software performance of the SPNRX is tested. The experimental results show that the hardware implementation cost of the proposed algorithm is low; only 1357 GEs based on a 0.13 micron ASIC process are required. And the software implementation of the proposed algorithm performs well. Encryption and decryption of the proposed algorithm on the 64-bit processor take about 0.7748 ms and 0.7957 ms. And it requires 35.98 MB of memory resources. In addition, the algorithm's security strength and encryption effect are tested through key sensitivity, information entropy, etc. The results show that the proposed algorithm has high enough security. [ABSTRACT FROM AUTHOR]

High-quality perception data is the basis of the operation of mobile crowdsensing platform. False data has a negative impact on the perception platform to draw wrong conclusions and cannot provide valuable help to service requesters. In order to solve this problem, we propose a trusted user selection framework based on generative adversarial network to select perceived users from the perspective of providing data, named PnGAN. The framework requires users to provide evaluation opinions on the current environment when uploading data, the evaluation opinion can not only reflect the current situation of the perceived environment, it can also be used as one of the data for user credibility evaluation. The analysis module in the framework processes the data uploaded by users, and apply the trust matrix to calculate the reputation value, determine user credibility based on reputation value. Experiments show that, compared with other algorithms for selecting trusted users, the average error rate of our method decreased by 30.62%, and the data quality improved by 15.32%. [ABSTRACT FROM AUTHOR]

The sample data of the existing intrusion detection models of the Internet of Things has defects such as class imbalance and insufficient feature extraction, which leads to low accuracy. Therefore, an intrusion detection model based on Gated Recurrent Unit (GRU) and Residual Network (ResNet) is proposed. Firstly, the deep convolutional generative adversarial network is used to generate a few sample data in the class imbalance data to make the sample data reach balance. Then, GRU is used to learn the data features, extract time series features of the sample data, classify the sample data features with the ResNet, and finally normalize the classification results with the softmax function. The proposed model is verified on NSL-KDD dataset, simulation experiments on NSL-KDD dataset show that the accuracy and detection rate of the proposed intrusion detection model reach 96.12% and 97.85% respectively, which are 1.86% and 2.59% higher than those of LSTM-ResNet method. And compared with GRU, LSTM and SVM, the validity of the model was verified. [ABSTRACT FROM AUTHOR]

In the existing Mobile Crowd Sensing, the task allocation method based on sensing user trajectory only considers the sensing user's moving position, but ignores the user's other information, such as moving speed, environmental noise, and so on. To solve this problem, a task allocation method based on multimodal trajectory data fusion is proposed in this paper. Firstly, the characteristics of users' trajectory data in Mobile Crowd Sensing are analyzed, the effects of moving speed and environmental noise on users' acquisition intention are judged, and the speed grayscale image and sound grayscale image are established. Then, the velocity gray image and the sound grayscale image are fused to form the track grayscale image by using the Tow-Branch Convolution Neural Network. Finally, the sensing user selection is based on the grayscale image coverage similarity, to maximize the coverage. Compared with other methods, the results show that the method proposed in this paper is significantly better than other comparison methods in improving coverage. [ABSTRACT FROM AUTHOR]

For the following problems: information loss in the original pool layer of CNN and the gradient disappearance in the processing of long sequence data by RNN, an intrusion detection system for the Internet of things based on improved CNN and RNN is proposed. Firstly, the time series is imaged by Gram angle field imaging method as the input of the intrusion detection model, and then SoftPool layer replaces the original pooling layer. Finally, the multi-head structure from multi-head self-attention mechanism is applied to RNN, and Bi-GRU which is one kind of RNN is chosen because of its fewer parameters. The TON-IoT data set from the Internet of things is used as the benchmark data set for the simulation. The simulation part includes the selection of imaging modes, the pooling layer combinations and the number of heads of multi-head Bi-GRU. The results show the model with Gram angle summation field, the pooling layer combination of Soft-Pool+SoftPool and the three-head structure has finer accuracy, precision, F1-score and false-positive rate, and precision, detection rate, F1-score and false-positive rate are at least 0.14,0.09,0.13 and 0.08 better than the existing models. [ABSTRACT FROM AUTHOR]

Mobile crowd sensing is a data collection model that combines crowdsourcing ideas and mobile device sensing abilities. In the decision-making process of mobile crowd sensing perception behavior, a single type of historical behavior is used to predict the user's single preference tag, so the generalization ability of the model is weak, and the recommendation efficiency is not high. Aiming at the perception problem that the information overload of mobile crowd sensing leads to a significant increase in participants' decision-making costs, this paper proposes an innovative MUDBP prediction method based on Multi-view and social network group behavior to improve the task recommendation in mobile crowd sensing model. Specifically, this method starts from the multi-time behavior sequence, adopts an attention mechanism, sets different weights for different individual behaviors of various users according to the social influence of different users, and calculates the aggregation representation of group user behaviors at additional time granularity. Then, the multi-scale behavior sequence characteristics of a single user are fused with the multi-scale behavior sequence characteristics of a group of users in a social network, and the multi-view embedded behavior sequence characteristics of a single user are extracted. Finally, through multi-label prediction, the preference probability of users to various task types is obtained. Experimental results based on real data sets show that compared with other baseline methods, the proposed method can effectively improve the accuracy of task recommendation and reduce the perceived cost. At the same time, it can effectively deal with the cold start problem. [ABSTRACT FROM AUTHOR]

With the large-scale popularization of mobile terminals, crowd sensing technology has gradually replaced the existing static sensors with its efficient and low-cost advantages as an emerging data collection method. How to quickly allocate the sensing task to the optimal execution user under the premise of ensuring the perceived quality and reducing the cost is the focus of the research. In this regard, this paper proposes a Crowd sensing Sparrow Search Algorithm (CSSA) collaborative optimization recommendation method that combines fitness priority, collaboration, and intelligent optimization algorithms, and uses it for task allocation problems. Firstly, the concept of fitness is proposed to calculate the location, power, equipment and reputation of the perceived user, and analyze the matching degree of the user to the task. Secondly, according to the different fitness, the user is divided into explorers and followers, and the two cooperate to complete the perception task. Thirdly, in the process of solving the optimal task allocation scheme, CSSA intelligent optimization algorithm is used to simulate the process of users completing tasks, and the selected user results can be obtained after limited iterations. Through the comparative experiments of the proposed algorithm and other optimization algorithms in the same environment, the results show that it has higher performance in solving the task allocation problem. [ABSTRACT FROM AUTHOR]

While promoting the development of the Internet of Things, cloud-fog hybrid computing faces severe information security risks. The intrusion detection system deployed in the fog node has lower latency but needs to be more lightweight. In response to the abovementioned problems, this paper proposes a lightweight intrusion detection model based on ConvNeXt-Sf. First, the two-dimensional structure of the latest computer vision model ConvNeXt is reduced to a one-dimensional sequence. Then, the design criteria of the lightweight computer vision model ShuffleNet V2 are used to improve ConvNeXt to make the latter more lightweight. Finally, the max-min normalization and label encoder are built into the data preprocessing model to convert the network traffic into a form conducive to ConvNeXt learning. The proposed model is evaluated on the TON-IoT and BoT-IoT datasets. The params of ConvNeXt-Sf are only 1.25% of that of ConvNeXt. Compared with the ConvNeXt, the ConvNeXt-Sf shortens the training time and prediction time by 82.63% and 56.48%, respectively, without reducing the learning capability and detection capability. Compared with the traditional models, the accuracy of the proposed model is increased by 6.18%, and the FAR is decreased by 4.49%. Compared with other lightweight models, the ShuffleNet V2 is better at making ConvNeXt lightweight. [ABSTRACT FROM AUTHOR]

Background: No prominent advancements in osteosarcoma (OS) treatment have been made in the past 20 years. Although photodynamic therapy (PDT) is an emerging technique for cancer therapy, the lack of targeted photosensitizers for OS treatment severely limits its applications. Results: In this study, we constructed a potential theranostic nanoplatform by using (poly (lactic-co-glycolic) acid (PLGA) nanoparticles (NPs) encapsulating IR780 into the shell (PLGA-IR780 NPs), which were further camouflaged with human OS cell membranes from the HOS cell line (MH-PLGA-IR780 NPs). These constructed NPs showed the capacity for homologous targeting with excellent photoacoustic (PA)/fluorescence (FL) imaging ability. Benefitting from their homologous targeting capacity, MH-PLGA-IR780 NPs obviously promoted cell endocytosis in vitro and tumor accumulation in vivo, which could further improve PDT performance under near-infrared (NIR) irradiation. In addition, to their homologous targeting and PA/FL dual-mode imaging ability, MH-PLGA-IR780 NPs had advantages in penetrating deeper into tumor tissues and in real-time dynamic distribution monitoring in vivo, which laid a foundation for further clinical applications in OS. Moreover, we demonstrated that PDT guided by the constructed NPs could significantly induce HOS cells apoptosis and ferroptosis via excessive accumulation of reactive oxygen species (ROS), and further determined that the potential anticancer molecular mechanism of apoptosis was triggered by the release of cytochrome c-activated mitochondrial apoptosis (endogenous apoptosis), and that ferroptosis caused the activation of nuclear receptor coactivator 4 (NCOA4)-mediated ferritinophagy and the inactivation of glutathione peroxidase 4 (GPX4), synergistically leading to excessive accumulation of Lipid-ROS and Lipid peroxides (LPOs). Concurrently, MH-PLGA-IR780 NPs-guided PDT also showed an obvious inhibitory effect on tumor growth in vivo. Conclusion: These results suggest that this homologous targeting-based theranostic nanoplatform provides an effective method to improve PDT performance in OS and contributes a new and promising approach for OS therapy. [ABSTRACT FROM AUTHOR]

B Relative viability (%) of HOS cells after coincubation with MH-PLGA-IR780 NPs (PLGA: 0.2 mg/mL) at prolonged time points. Reference 1 Wang Y, Zhang L, Zhao G, Zhang Y, Zhan F, Chen Z. Homologous targeting nanoparticles for enhanced PDT against osteosarcoma HOS cells and the related molecular mechanisms. [Extracted from the article]

Background: No prominent advancements in osteosarcoma (OS) treatment have been made in the past 20 years. Although photodynamic therapy (PDT) is an emerging technique for cancer therapy, the lack of targeted photosensitizers for OS treatment severely limits its applications. Results: In this study, we constructed a potential theranostic nanoplatform by using (poly (lactic-co-glycolic) acid (PLGA) nanoparticles (NPs) encapsulating IR780 into the shell (PLGA-IR780 NPs), which were further camouflaged with human OS cell membranes from the HOS cell line (MH-PLGA-IR780 NPs). These constructed NPs showed the capacity for homologous targeting with excellent photoacoustic (PA)/fluorescence (FL) imaging ability. Benefitting from their homologous targeting capacity, MH-PLGA-IR780 NPs obviously promoted cell endocytosis in vitro and tumor accumulation in vivo, which could further improve PDT performance under near-infrared (NIR) irradiation. In addition, to their homologous targeting and PA/FL dual-mode imaging ability, MH-PLGA-IR780 NPs had advantages in penetrating deeper into tumor tissues and in real-time dynamic distribution monitoring in vivo, which laid a foundation for further clinical applications in OS. Moreover, we demonstrated that PDT guided by the constructed NPs could significantly induce HOS cells apoptosis and ferroptosis via excessive accumulation of reactive oxygen species (ROS), and further determined that the potential anticancer molecular mechanism of apoptosis was triggered by the release of cytochrome c-activated mitochondrial apoptosis (endogenous apoptosis), and that ferroptosis caused the activation of nuclear receptor coactivator 4 (NCOA4)-mediated ferritinophagy and the inactivation of glutathione peroxidase 4 (GPX4), synergistically leading to excessive accumulation of Lipid-ROS and Lipid peroxides (LPOs). Concurrently, MH-PLGA-IR780 NPs-guided PDT also showed an obvious inhibitory effect on tumor growth in vivo. Conclusion: These results suggest that this homologous targeting-based theranostic nanoplatform provides an effective method to improve PDT performance in OS and contributes a new and promising approach for OS therapy. [ABSTRACT FROM AUTHOR]

Background: No prominent advancements in osteosarcoma (OS) treatment have been made in the past 20 years. Although photodynamic therapy (PDT) is an emerging technique for cancer therapy, the lack of targeted photosensitizers for OS treatment severely limits its applications. Results: In this study, we constructed a potential theranostic nanoplatform by using (poly (lactic-co-glycolic) acid (PLGA) nanoparticles (NPs) encapsulating IR780 into the shell (PLGA-IR780 NPs), which were further camouflaged with human OS cell membranes from the HOS cell line (MH-PLGA-IR780 NPs). These constructed NPs showed the capacity for homologous targeting with excellent photoacoustic (PA)/fluorescence (FL) imaging ability. Benefitting from their homologous targeting capacity, MH-PLGA-IR780 NPs obviously promoted cell endocytosis in vitro and tumor accumulation in vivo, which could further improve PDT performance under near-infrared (NIR) irradiation. In addition, to their homologous targeting and PA/FL dual-mode imaging ability, MH-PLGA-IR780 NPs had advantages in penetrating deeper into tumor tissues and in real-time dynamic distribution monitoring in vivo, which laid a foundation for further clinical applications in OS. Moreover, we demonstrated that PDT guided by the constructed NPs could significantly induce HOS cells apoptosis and ferroptosis via excessive accumulation of reactive oxygen species (ROS), and further determined that the potential anticancer molecular mechanism of apoptosis was triggered by the release of cytochrome c-activated mitochondrial apoptosis (endogenous apoptosis), and that ferroptosis caused the activation of nuclear receptor coactivator 4 (NCOA4)-mediated ferritinophagy and the inactivation of glutathione peroxidase 4 (GPX4), synergistically leading to excessive accumulation of Lipid-ROS and Lipid peroxides (LPOs). Concurrently, MH-PLGA-IR780 NPs-guided PDT also showed an obvious inhibitory effect on tumor growth in vivo. Conclusion: These results suggest that this homologous targeting-based theranostic nanoplatform provides an effective method to improve PDT performance in OS and contributes a new and promising approach for OS therapy. [ABSTRACT FROM AUTHOR]

Aiming at the problems of low data quality and high incentive costs caused by the low enthusiasm of participants in mobile crowd sensing, a new task recommendation framework is proposed in this paper. First, the participants' historical behaviors are analyzed, assuming that user behaviors can be quantified as the user's willingness to participate, and the cosine similarity theorem is used to calculate the similarity between participants, thereby constructing a user-hybrid model. Secondly, probabilistic matrix factorization is developed to predict the willingness of participants, and a ranking model is obtained through learn-to-rank algorithm. Finally, a task recommendation list is generated according to the ranking model, which serves as the target participant's preferred task list for sensing task recommendation. The experiment in this paper is carried out on the MATLAB platform based on two real check-in datasets, Gowalla and Brightkite. The results show that the average allocation precision rate can reach 96%, and the sensing user participation rate is about 97%. Meantime, the user's mobile cost is reduced, and the overall goal of maximizing accuracy and minimizing perceived cost is achieved. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the mobile crowdsensing (MCS) system relies on a specific platform with a large user group presupposed, this paper proposes a sensing user diffusion analysis and incentive method based on knowledge graph reasoning. We consider motivating users to participate under the constraint of limited budget so that the platform and users can get the most benefits. In this paper, we focus on socially aware users represented by self-organizing social networks, combine the knowledge graph to establish a knowledge graph for the crowdsensing system, use rules to derive user influence, and optimize user contributions. With the goal of maximizing social welfare, we propose a social awareness reverse auction (SARA) mechanism, in which the total contribution of users is the key to select winners, and the winners are paid based on critical prices. Through experimental simulations, we verify that SARA is close to the optimal social welfare under budget constraints. [ABSTRACT FROM AUTHOR]

Background: Immunotherapy is a vital component in cancer treatment. However, due to the complex genetic bases of cancer, a clear prediction index for efficacy has not been established. Tumor mutation burden (TMB) is one of the essential factors that affect immunotherapeutic efficacies, but it has not been determined whether the mutation is associated with the survival of Skin Cutaneous Melanoma (SKCM) patients. This study aimed at evaluating the correlation between TMB and immune infiltration.Methods: Somatic mutation profiles (n = 467), transcriptome data (n = 471), and their clinical information (n = 447) of all SKCM samples were downloaded from The Cancer Genome Atlas (TCGA) database. For each sample, TMB was calculated as the number of variants per megabase. Based on K-M survival analysis, they were allocated into the high-TMB and low-TMB groups (the optimal cutoff was determined by the 'surv_cutpoint' algorithm of survival R package). Then, Gene ontology (GO) and Gene Set Enrichment Analyses (GSEA) were performed, with immune-associated biological pathways found to be significantly enriched in the low-TMB group. Therefore, immune genes that were differentially expressed between the two groups were evaluated in Cox regression to determine their prognostic values, and a four-gene TMB immune prognostic model (TMB-IP) was constructed.Results: Elevated TMB levels were associated with better survival outcomes in SKCM patients. Based on the cutoff value in OS analysis, they were divided into high-TMB and low-TMB groups. GSEA revealed that the low-TMB group was associated with immunity while intersection analysis revealed that there were 38 differentially expressed immune-related genes between the two groups. Four TMB-associated immune genes were used to construct a TMB-IP model. The AUC of the ROC curve of this model reached a maximum of 0.75 (95%CI, 0.66-0.85) for OS outcomes. Validation in each clinical subgroup confirmed the efficacy of the model to distinguish between high and low TMB-IP score patients.Conclusions: In SKCM patients, low TMB was associated with worse survival outcomes and enriched immune-associated pathways. The four TMB-associated immune genes model can effectively distinguish between high and low-risk patients. [ABSTRACT FROM AUTHOR]

Aiming at the dynamic uncertainty and prediction accuracy of security situation prediction in complex cloud network environment, a prediction model of cloud security situation based on evolutionary functional network is proposed. Firstly, the evolutionary functional network model is constructed by combining the evolutionary algorithm with the functional network, which solves the problem of basis function selection and basis function coefficient correction of the prediction model. Secondly, the stochastic approximation algorithm is used to process and comprehend the cloud security situation elements, and the computational complexity of the prediction model is reduced by the dimensionality reduction method. Finally, by constructing the credibility matrix of the uncertain influence relationship of security situation elements, we use the multivariate non-linear regression algorithm to predict the cloud security situation. The simulation results show that compared with BP model and RAN-RBF model, the prediction accuracy of the proposed model is improved by 8.2% and 6.9% respectively, and the convergence efficiency is improved by 12.3% and 10.8% respectively. [ABSTRACT FROM AUTHOR]

Maintaining the cathode pressure stable and avoiding oxygen starvation are crucial for the air supply of proton exchange membrane fuel cell (PEMFC). In most applications, the cathode pressure and oxygen excess ratio (OER) are unmeasurable parameters, which makes it difficult to precisely control the air supply system. This article proposes a fractional order PID (FOPID) controller based on an unknown input nonlinear observer for the fuel cell air supply system. The proposed nonlinear observer is able to estimate internal states including the cathode pressure of the PEMFC system. Then, the OER is obtained based on the observed system states. A fractional-order PID controller with a parameter optimization algorithm is developed to regulate as fast the OER and the cathode pressure to their desired values. Both the steady and transient performances of the proposed control method are simulated and experimentally validated compared with supertwisting sliding mode controller and traditional PID controller. [ABSTRACT FROM AUTHOR]

Background: The latest basic studies and clinical evidence have confirmed the safety and efficacy of intraoperative autologous blood cell transfusion in cardiac surgery and orthopaedics. However, in caesarean section, there are still concerns about the contamination of amniotic fluid and foetal components, and consequently the application of intraoperative autologous blood cell transfusion is not universal. Therefore, this study aimed to evaluate the clinical value of intraoperative autologous blood cell transfusion in obstetric surgery.Methods: A prospective, randomized, controlled, feasibility study was performed in women undergoing caesarean section. One hundred sixteen participants were randomly assigned at a 1:1 ratio into either the intraoperative cell salvage group or the control group. Allogeneic blood cells were transfused into patients with haemoglobin concentrations < 80 g/dL in both the intraoperative cell salvage group and the control group.Results: No significant differences were found between the two groups in age, weight, maternal parity, history of previous caesarean section, gestational weeks of delivery, etc. However, compared with the control group, patients in the intraoperative cell salvage group had a significantly lower amount of allogeneic blood cell transfusion, lower incidence of postoperative incision infection, delayed wound healing, perioperative allergy, adverse cardiovascular events, hypoproteinaemia and shorter hospital stay.Conclusion: The results of this study suggest that the use of autologous blood cell transfusion is safe and effective for patients with obstetric haemorrhage.Trial Registration: All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional and/or National Research Committee of Beijing Obstetrics and Gynecology Hospital, Capital Medical University (2016-XJS-003-01) as well as the 1964 Helsinki Declaration and its later amendments or other comparable ethical standards. The clinical trials were registered (ChiCTR-ICC-15,007,096) on September 28, 2015. [ABSTRACT FROM AUTHOR]

A simple and feasible hydrothermal method was employed to regulate the surface charge and growth degree of active facet of BiVO4 by varying the pH value of precursor. The prepared products were characterized by XRD, Raman spectra, SEM, N2 adsorption and desorption, zeta potential, and UV–Vis DRS. It is found that with increasing the pH value, not only do the phase composition, micro-morphology, specific surface area, and light absorption of BiVO4 products have obvious changes, but so do the surface charge and growth degree of {010} facet. A possible formation mechanism is proposed on the basis of the characterization results. The photocatalytic activities were evaluated by the degradation of rhodamine B solution under visible light irradiation. The results showed that monoclinic scheelite BiVO4 (m-BiVO4) particles prepared at pH 4 exhibit the maximum adsorption capacity and the best photocatalytic performance, which was mainly attributed to the negatively charged surface. On the contrary, the similar degradation rate and kinetic constant of the m-BiVO4 prepared at pH 3 could be ascribed to the preferential growth of {010} facets. [ABSTRACT FROM AUTHOR]

Objectives: The influence of commercial helium-oxygen saturation diving on divers' gut microbiotas was assessed to provide dietary suggestion.Methods: Faecal samples of 47 divers working offshore were collected before (T1), during (T2) and after (T3) saturation diving. Their living and excursion depths were 55-134 metres underwater with a saturation duration of 12-31 days and PaO2 of 38-65 kPa. The faecal samples were examined through 16S ribosomal DNA amplicon sequencing based on the Illumina sequencing platform to analyse changes in the bacteria composition in the divers' guts.Results: Although the α and β diversity of the gut microbiota did not change significantly, we found that living in a hyperbaric environment of helium-oxygen saturation decreased the abundance of the genus Bifidobacterium, an obligate anaerobe, from 2.43%±3.83% at T1 to 0.79%±1.23% at T2 and 0.59%±0.79% at T3. Additionally, the abundance of some short-chain fatty acid (SCFA)-producing bacteria, such as Fusicatenibacter, Faecalibacterium, rectale group and Anaerostipes, showed a decreased trend in the order of before, during and after diving. On the contrary, the abundance of species, such as Lactococcus garvieae, Actinomyces odontolyticus, Peptoclostridium difficile, Butyricimonas virosa, Streptococcus mutans, Porphyromonas asaccharolytica and A. graevenitzii, showed an increasing trend, but most of them were pathogens.Conclusions: Occupational exposure to high pressure in a helium-oxygen saturation environment decreased the abundance of Bifidobacterium and some SCFA-producing bacteria, and increased the risk of pathogenic bacterial infection. Supplementation of the diver diet with probiotics or prebiotics during saturation diving might prevent these undesirable changes. [ABSTRACT FROM AUTHOR]

In view of the location privacy problem of participants in mobile crowd sensing, this paper proposes a method to protect the location of participants based on local differential privacy preference. First of all, the map is discretized and mapped from two-dimensional space to one-dimensional space by means of MHC, which can guarantee the spatial correlation, and the map is segmented based on the density of participants using genetic algorithm; Then, according to the personal privacy needs of current location, two different local differential privacy perturbation methods, RAPPOR and k-RR, are chosen by participants; Next, the chosen local differential privacy is used to perturb the location of each participant in the region after segmentation, and the perturbed location data are sent to the data collection server to protect the participants' locations. Finally, the simulation experiments are carried out and show that map density segmentation can reduce the privacy cost, and the method proposed in this paper is superior to the method using k-anonymous and differential privacy and the method using Hilbert and differential privacy in terms of running time and average relative error, and prove that the execution time is lower and the data availability is improved. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to analyze the perinatal changes of plasma estradiol (E2) and angiotensin II (Ang II) in pregnant women with pulmonary arterial hypertension before and after cesarean section. Methods: Depending on pulmonary arterial pressure, the subjects were divided into two groups, moderate group, and severe group. Plasma concentrations of E2 and Ang II were determined at different time points using electrochemiluminescence immunoassay and ELISA, respectively. The correlation between E2 and Ang II concentrations was analyzed. Results: Intragroup comparison indicated that E2 levels at different time points after surgery decreased in the two groups than before, with a greater reduction in the severe group. Besides, both groups showed a reduction in Ang II concentrations after surgery. As indicated by intragroup comparison, there was a significant difference at each time point in the two groups. The reduction in Ang II concentrations was more conspicuous at 48 h and 72 h after surgery (cesarean section) than before for the two groups. Moreover, E2 concentrations were correlated positively with AngII concentrations. Conclusion: Plasma concentrations of E2 and Ang II decreased after delivery. The plasma concentrations of E2 and Ang II were correlated with each other. [ABSTRACT FROM AUTHOR]

Mesocrystals have attracted more attention owing to their unique structures and properties. Nevertheless, facile and green synthesis of well‐defined mesocrystals still remains a significant challenge. Herein, one‐dimensional (1D) rodlike monoclinic scheelite phase BiVO4 (mBiVO4) mesocrystals having superstructures orderly assembled by mBiVO4 nanoparticle building blocks, were created via a facile solvothermal method in the glycerol (Gly)/water mixed solvent without any additives. By adjusting the dosage of Gly and pH value of the reaction system, the microstructure of BiVO4 can be accurately regulated. The obtained samples were carefully characterized by XRD, SEM, TEM, HRTEM, BET, FTIR, PL and UV‐vis techniques. The lower pH value and the higher dosage of Gly were propitious to form rodlike mBiVO4 mesocrystals. Of course, the kind and concentration of reaction species in the system and the assembly force were affected by the dosage of Gly and pH value. The possible formation mechanism of the BiVO4 mesocrystals was proposed on the basis of these analyses. The optimized rodlike mBiVO4 mesocrystal prepared with 8 mL of Gly at pH 2 exhibited the highest photocatalytic degradation activity for methylene blue (MB) under simulated sunlight irradiation, which could be attributed to its phase composition, higher surface area, stronger light absorption and 1D rodlike morphology with short L/D ratio which may increase the separation efficiency of photogenerated electrons and holes. [ABSTRACT FROM AUTHOR]

Combining the principle of antibody concentration with the idea of biological evolution, this paper proposes an adaptive target detection algorithm for cloud service security based on Bio-Inspired Performance Evaluation Process Algebra (Bio-PEPA). The formal modelling of cloud services is formally modded by Bio-PEPA and the modules are transformed between cloud service internal structures and various components. Then, the security adaptive target detection algorithm of cloud service is divided into two processes, the short-term optimal action selection process which selects the current optimal detective action through the iterative operation of the expected function and the adaptive function, and the long-term detective strategy realized through the updates and eliminations of action planning table. The combination of the two processes reflects the self-adaptability of cloud service system to target detection. The simulating test detects three different kinds of security risks and then analyzes the relationship between the numbers of components with time in the service process. The performance of this method is compared with random detection method and three anomaly detection methods by the cloud service detection experiment. The detection time of this method is 50.1% of three kinds of detection methods and 86.3% of the random detection method. The service success rate is about 15% higher than that of random detection methods. The experimental results show that the algorithm has good time performance and high detection hit rate. [ABSTRACT FROM AUTHOR]

Nanostructured shuriken-like monoclinic scheelite phase BiVO4 (mBiVO4) with preferentially exposed {010} facets was synthesized by a solvothermal process in a glycerol (Gly)/water mixed solvent using ethylenediamine tetraacetic acid disodium (EDTA) as the structure-directing agent. EDTA competes with Gly to control the kind and concentration of reaction species in the system, and thereby the preferential growth of mBiVO4 nanocrystals along the {010} facets as well as formation of a shuriken-like morphology can take place at the same time. The formation mechanism of products with different microstructures is proposed. The optimized mBiVO4 photocatalyst obtained using 0.4 mmol EDTA exhibited highest photocatalytic activity for methylene blue (MB) degradation, which could be attributed to the highest exposure degree of the active {010} facets, as well as the shuriken-like nanostructure, which enhanced the separation of photogenerated electrons and holes. [ABSTRACT FROM AUTHOR]

Background: The combination of phytochemicals with chemotherapy drugs is an emerging new strategy for cancer therapy to increase antitumor responses. Methods: The present study investigates the effect of the combination of capsaicin (CAP) with cisplatin (DDP) and the potential underlying anticancer mechanisms in osteosarcoma (OS) cells in vitro and in vivo. Results: Cell viability assays and isobolographic analyses demonstrated that the combination of CAP and DDP showed synergistic cytotoxic effects on OS cells. We chose relatively low concentrations of CAP (100 μM) and DDP (16.7 μM) for subsequent experiments. Generally, the combination of CAP and DDP had significant effects on apoptosis induction, cell cycle arrest and cell invasion inhibition in OS cells compared with the individual-treatment groups and the control group. Moreover, cotreatment with CAP and DDP triggered prosurvival autophagy through reactive oxygen species (ROS)/JNK and p-AKT/mTOR signaling in OS cells. The combination regimen of CAP and DDP also inhibited tumor growth in an OS xenograft model. Conclusion: These results suggest that the combination of CAP and DDP has strong inhibitory effects on OS cells and identify CAP as a promising agent for supplementing standard chemotherapy and possible future targeted therapy in OS. [ABSTRACT FROM AUTHOR]