Expanding carbon neutrality strategies: Incorporating out-of-boundary emissions in city-level frameworks

Cities are increasingly vital in global carbon mitigation efforts, yet few have specifically tailored carbon neutrality pathways. Furthermore, out-of-boundary indirect greenhouse gas (GHG) emissions, aside from those related to electricity and heat imports, are often overlooked in existing pathways, despite their significance in comprehensive carbon mitigation strategies. Addressing this gap, here we introduce an integrated analysis framework focusing on both production and consumption-related GHG emissions. Applied to Wuyishan, a service-oriented city in Southern China, this framework provides a holistic view of a city's carbon neutrality pathway, from a full-scope GHG emission perspective. The findings reveal the equal importance of carbon reduction within and outside the city's boundaries, with out-of-boundary emissions accounting for 42% of Wuyishan's present total GHG emissions. This insight highlights the necessity of including these external factors in GHG accounting and mitigation strategy development. This framework serves as a practical tool for cities, particularly in developing countries, to craft effective carbon neutrality roadmaps that encompass the full spectrum of GHG emissions.

Evaluation Method of Fatigue Life for Asphalt Pavement on the Steel Bridge Deck Based on the Inhomogeneous Poisson Stochastic Process

The paving layer on the steel box girder bridge deck is widely used when constructing pavements for steel bridges. Owing to the orthotropic feature of steel decks, a transverse clapboard and rib can lead to a concentration of stress. Consequently, fatigue cracks are often identified in asphalt concrete pavement layers due to re-compaction caused by heavy vehicles. This study aims to derive an evaluation method of fatigue life for asphalt pavement based on the inhomogeneous Poisson stochastic process in view of the highly random and uncertain working conditions of layered composite structures. According to the inhomogeneous Poisson stochastic process, along with Miner's fatigue damage accumulation theory and the linear elastic fracture mechanics theory, the fatigue life formula could be deduced. Meanwhile, fatigue experiments for asphalt concrete are designed to investigate the correlation between the theoretical formula and the actual fatigue damage life of the material. Compared with the test, the accuracy error is within 10%, which is better than other traditional methods. Therefore, the fatigue life prediction model could better reflect the loading order effect and the interaction between loads, providing a new path for the fatigue reliability design of steel bridge deck asphalt pavement.

Examination of the role of the rotating nursing department in the training of nursing staff based on SWOT analysis

BACKGROUND

The implementation of the rotation system in the Chinese medical industry has achieved significant results.

OBJECTIVES

The present study aims to 1) explore the strengths, weaknesses, opportunities and challenges of rotational nursing department implementation and 2) provide references for developing nursing staff's competencies in leadership, performance evaluation, quality of care, communication in relationships and human resources.

METHODS

A total of 16 rotational nursing department staff members from a tertiary tuberculosis specialist hospital in Beijing were interviewed, and the interview data were analysed using a strengths, weaknesses, opportunities and threats analysis and class analysis.

RESULTS

The advantages of the rotational nursing department included: (1) stimulating the nursing staff's enthusiasm and creativity; (2) strengthening the communication and collaboration between departments; (3) improving the detailed management of nursing quality; and (4) enhancing the nursing staff's comprehensive abilities. The disadvantages included: (1) the design of the rotation programme focusing on practice; (2) a lack of personalisation; and (3) imperfect performance assessment of the rotating staff. Opportunities included: (1) deepening the connotation of nursing job management and (2) developing the construction of nursing discipline and the need for personal career development and value realisation. Threats included the lack of a sound rotation management model to draw on.

CONCLUSION

A rotational nursing department is conducive to enhancing the competence of nursing staff in management positions and providing new ideas for hospitals to select and train nursing management talents. By taking full advantage of the benefits of vertical nursing management, designing personalised rotation training programmes, building a diversified learning and training platform and developing a positive performance incentive mechanism is recommended to fully engage the role of rotation in nursing management talent training.

Fear-Neuro-Inspired Reinforcement Learning for Safe Autonomous Driving

Ensuring safety and achieving human-level driving performance remain challenges for autonomous vehicles, especially in safety-critical situations. As a key component of artificial intelligence, reinforcement learning is promising and has shown great potential in many complex tasks; however, its lack of safety guarantees limits its real-world applicability. Hence, further advancing reinforcement learning, especially from the safety perspective, is of great importance for autonomous driving. As revealed by cognitive neuroscientists, the amygdala of the brain can elicit defensive responses against threats or hazards, which is crucial for survival in and adaptation to risky environments. Drawing inspiration from this scientific discovery, we present a fear-neuro-inspired reinforcement learning framework to realize safe autonomous driving through modeling the amygdala functionality. This new technique facilitates an agent to learn defensive behaviors and achieve safe decision making with fewer safety violations. Through experimental tests, we show that the proposed approach enables the autonomous driving agent to attain state-of-the-art performance compared to the baseline agents and perform comparably to 30 certified human drivers, across various safety-critical scenarios. The results demonstrate the feasibility and effectiveness of our framework while also shedding light on the crucial role of simulating the amygdala function in the application of reinforcement learning to safety-critical autonomous driving domains.

Lipid peroxidation and antioxidant responses of Microcoleus vaginatus with the aid of attapulgite-based nanocomposite to wind stress

Wind erosion is one of the reasons for the formation of desertification in arid and semiarid areas. Many measures are used to achieve sustainable land management. Microcoleus vaginatus can influence and offer limited protection to soils from wind erosion through its impact on controlling threshold friction velocity. Therefore, the study aims to explore the effectiveness and anti-wind erosion ability of Microcoleus vaginatus with the aid of attapulgite-based nanocomposite and to find a method that can act as bioindicators for investigating wind erosion in arid and semiarid areas in the future, for offering a method to prevent desertification and provide a valuable measure for the sustainable development of the environment. In this study, the effects of wind stress on reactive oxygen species (ROS), malondialdehyde (MDA), superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), glutathione (GSH) and the surface character of the soil were analysed. The results showed that increased ROS and MDA, decreased GSH, changed SOD, POD and CAT, and enhanced soil structure in Microcoleus vaginatus with the aid of attapulgite-based nanocomposites were influenced by 3 and 5 m·s-1 wind erosion. Further analysis demonstrated that increased SOD, POD and CAT and decreased GSH eliminated ROS and MDA through the antioxidant defense response of Microcoleus vaginatus with the aid of attapulgite-based nanocomposites. The results revealed that Microcoleus vaginatus with the aid of attapulgite-based nanocomposite had an important physiological adaptation for the elimination of ROS and lipid peroxidation induced by wind stress and could play a role in alleviating wind erosion.

Survey and analysis of willingness to use mobile medical services and influencing factors of TB patients treated at home

INTRODUCTION

The objective of this study was to investigate the willingness of patients with tuberculosis (TB) to use mobile medical services (mHealth) and its influencing factors, so as to provide theoretical guidance for optimizing the TB mobile medical platform and improve the willingness of patients to use mHealth.

METHODOLOGY

In this cross-sectional study, convenience sampling method was used to investigate patients with TB from the outpatient clinics of two TB specialized hospitals (Beijing Thoracic Tumor and Tuberculosis Hospital and Tuberculosis Prevention and Treatment Hospital of Shaanxi Province) from January to June 2021 using a self-designed questionnaire.

RESULTS

Out of 231 patients, only 90 (38.96%) were aware of mHealth services, and 63 (27.27%) had used mHealth services. Among the 63 patients who had used mHealth services, the proportion of mobile medical forms based on WeChat platform was 74.89%. Patients' willingness to use mHealth was scored (11.49 ± 2.53). Univariate analysis showed that the scores of patients' willingness to use mHealth differed by gender and the different ways of affording healthcare (p < 0.05). Regression analysis showed that the influencing factors of willingness to use mHealth in patients with TB included attitude towards use (0.750), health beliefs (0.091) and social impact (0.169) (adjusted R2 = 0.781, p < 0.001).

CONCLUSIONS

Patients' awareness of the advantages of the new medical model needs to be improved. Optimized design can improve the willingness of patients to use mHealth services and improve the role of mHealth in patient management.

Human-Guided Reinforcement Learning With Sim-to-Real Transfer for Autonomous Navigation

Reinforcement learning (RL) is a promising approach in unmanned ground vehicles (UGVs) applications, but limited computing resource makes it challenging to deploy a well-behaved RL strategy with sophisticated neural networks. Meanwhile, the training of RL on navigation tasks is difficult, which requires a carefully-designed reward function and a large number of interactions, yet RL navigation can still fail due to many corner cases. This shows the limited intelligence of current RL methods, thereby prompting us to rethink combining RL with human intelligence. In this paper, a human-guided RL framework is proposed to improve RL performance both during learning in the simulator and deployment in the real world. The framework allows humans to intervene in RL's control progress and provide demonstrations as needed, thereby improving RL's capabilities. An innovative human-guided RL algorithm is proposed that utilizes a series of mechanisms to improve the effectiveness of human guidance, including human-guided learning objective, prioritized human experience replay, and human intervention-based reward shaping. Our RL method is trained in simulation and then transferred to the real world, and we develop a denoised representation for domain adaptation to mitigate the simulation-to-real gap. Our method is validated through simulations and real-world experiments to navigate UGVs in diverse and dynamic environments based only on tiny neural networks and image inputs. Our method performs better in goal-reaching and safety than existing learning- and model-based navigation approaches and is robust to changes in input features and ego kinetics. Furthermore, our method allows small-scale human demonstrations to be used to improve the trained RL agent and learn expected behaviors online.

A fully human monoclonal antibody targeting Semaphorin 5A alleviates the progression of rheumatoid arthritis

Rheumatoid arthritis (RA) is the most common chronic autoimmune disease worldwide. Although progress has been made in RA treatment in recent decades, remission cannot be effectively achieved for a considerable proportion of RA patients. Thus, novel potential targets for therapeutic strategies are needed. Semaphorin 5A (SEMA5A) plays a pivotal role in RA progression by facilitating pannus formation, and it is a promising therapeutic target. In this study, we sought to develop an antibody treatment strategy targeting SEMA5A and evaluate its therapeutic effect using a collagen-induced arthritis (CIA) model. We generated SYD12-12, a fully human SEMA5A blocking antibody, through phage display technology. SYD12-12 intervention effectively inhibited angiogenesis and aggressive phenotypes of RA synoviocytes in vitro and dose-dependently inhibited synovial hyperplasia, pannus formation, bone destruction in CIA mice. Notably, SYD12-12 also improved the Treg/Th17 imbalance in CIA mice. We confirmed through immunofluorescence and molecular docking that SYD12-12 integrated with the unique TSP-1 domain of SEMA5A. In conclusion, we developed and characterized a fully human SEMA5A-blocking antibody for the first time. SYD12-12 effectively alleviated disease progression in CIA mice by inhibiting pannus formation and improving the Treg/Th17 imbalance, demonstrating its potential for the RA treatment.

Smart-seq2 Technology Reveals a Novel Mechanism That Zearalenone Inhibits the In Vitro Maturation of Ovine Oocytes by Influencing TNFAIP6 Expression

Zearalenone (ZEN), a non-steroidal estrogenic fungal toxin widely present in forage, food, and their ingredients, poses a serious threat to animal and human reproductive health. ZEN also threatens ovine, a major source of human food and breeding stock. However, the mechanisms underlying the impact of ZEN on the in vitro maturation (IVM) of ovine oocytes remain unclear. This study aimed to elucidate these mechanisms using the Smart-seq2 technology. A total of 146 differentially expressed genes were obtained, using Smart-seq2, from sheep oocytes cultured in vitro after ZEN treatment. ZEN treatment inhibited RUNX2 and SPP1 expression in the PI3K signaling pathway, leading to the downregulation of THBS1 and ultimately the downregulation of TNFAIP6; ZEN can also decrease TNFAIP6 by reducing PTPRC and ITGAM. Both inhibit in vitro maturation of ovine oocytes and proliferation of cumulus cells by downregulating TNFAIP6. These findings provide data and a theoretical basis for elucidating ZEN's toxicity mechanisms, screening therapeutic drugs, and reducing ZEN-related losses in the ovine industry.

LncRNA TYMSOS is a novel prognostic biomarker associated with immune infiltration in prostate cancer

The long noncoding RNA thymidylate synthetase opposite strand (lncRNA TYMSOS) plays an important role in cancers; however, its impact on prostate cancer (PCa) is still unclear. By analyzing the online data, we found that lncRNA TYMSOS was highly expressed in PCa and associated with T stage, Gleason score, age, and primary therapy outcome. The results of the ROC curve showed that lncRNA TYMSOS has a significant diagnostic ability. Furthermore, Kaplan-Meier analyses suggested that lncRNA TYMSOS plays an important role in progression-free survival (PFS). Increased lncRNA TYMSOS expression was an independent risk factor correlated with PFS in PCa patients. GSEA and GSVA indicated that the lncRNA TYMSOS was involved in the cell cycle, neurodegenerative diseases, oxidative phosphorylation, spliceosomes, and adaptive immune system pathways. Additionally, lncRNA TYMSOS expression was also associated with immune cell infiltrates and tumor mutational burden in PCa. Functional experiments were further conducted, and we verified that lncRNA TYMSOS played an oncogenic role in regulating PCa aggressiveness. Specifically, silencing of lncRNA TYMSOS suppressed cell proliferation, division and epithelial-mesenchymal transition (EMT) but promoted cell apoptosis in PCa cells, and conversely, lncRNA TYMSOS overexpression had the opposite effects. In summary, our study revealed that the lncRNA TYMSOS could be a biomarker and therapeutic target in PCa and participate in tumor-immune cell infiltration.

Sampling Efficient Deep Reinforcement Learning Through Preference-Guided Stochastic Exploration

Stochastic exploration is the key to the success of the deep Q -network (DQN) algorithm. However, most existing stochastic exploration approaches either explore actions heuristically regardless of their Q values or couple the sampling with Q values, which inevitably introduce bias into the learning process. In this article, we propose a novel preference-guided ϵ -greedy exploration algorithm that can efficiently facilitate exploration for DQN without introducing additional bias. Specifically, we design a dual architecture consisting of two branches, one of which is a copy of DQN, namely, the Q branch. The other branch, which we call the preference branch, learns the action preference that the DQN implicitly follows. We theoretically prove that the policy improvement theorem holds for the preference-guided ϵ -greedy policy and experimentally show that the inferred action preference distribution aligns with the landscape of corresponding Q values. Intuitively, the preference-guided ϵ -greedy exploration motivates the DQN agent to take diverse actions, so that actions with larger Q values can be sampled more frequently, and those with smaller Q values still have a chance to be explored, thus encouraging the exploration. We comprehensively evaluate the proposed method by benchmarking it with well-known DQN variants in nine different environments. Extensive results confirm the superiority of our proposed method in terms of performance and convergence speed.

Efficient Deep Reinforcement Learning With Imitative Expert Priors for Autonomous Driving

Deep reinforcement learning (DRL) is a promising way to achieve human-like autonomous driving. However, the low sample efficiency and difficulty of designing reward functions for DRL would hinder its applications in practice. In light of this, this article proposes a novel framework to incorporate human prior knowledge in DRL, in order to improve the sample efficiency and save the effort of designing sophisticated reward functions. Our framework consists of three ingredients, namely, expert demonstration, policy derivation, and RL. In the expert demonstration step, a human expert demonstrates their execution of the task, and their behaviors are stored as state-action pairs. In the policy derivation step, the imitative expert policy is derived using behavioral cloning and uncertainty estimation relying on the demonstration data. In the RL step, the imitative expert policy is utilized to guide the learning of the DRL agent by regularizing the KL divergence between the DRL agent's policy and the imitative expert policy. To validate the proposed method in autonomous driving applications, two simulated urban driving scenarios (unprotected left turn and roundabout) are designed. The strengths of our proposed method are manifested by the training results as our method can not only achieve the best performance but also significantly improve the sample efficiency in comparison with the baseline algorithms (particularly 60% improvement compared with soft actor-critic). In testing conditions, the agent trained by our method obtains the highest success rate and shows diverse and human-like driving behaviors as demonstrated by the human expert. We also find that using the imitative expert policy trained with the ensemble method that estimates both policy and model uncertainties, as well as increasing the training sample size, can result in better training and testing performance, especially for more difficult tasks. As a result, the proposed method has shown its potential to facilitate the applications of DRL-enabled human-like autonomous driving systems in practice. The code and supplementary videos are also provided. [https://mczhi.github.io/Expert-Prior-RL/].

Inhibition characteristics research of aluminum alloy polishing dust explosion through addition of ultrafine Al(OH)3 inerting agent

Investigations into the deactivation of explosion sensitivity and reduction of flame propagation for aluminium alloy polishing wastes were carried out by the addition of ultrafine Al(OH)3 inerting agent. Meanwhile, high-purity aluminium powders with similar mean diameters were also used as a comparative study. The explosion propagation characteristics of high-purity aluminium dust and aluminium alloy polishing waste dust under different inerting ratios (ε ) were tested and investigated using a standardised Hartmann tester and a developed experimental platform. The results show that the minimum ignition energy of high-purity aluminium powder is between 40 and 45 mJ, and the minimum ignition energy of aluminium alloy polishing waste is between 500 and 550 mJ, which is one order of magnitude higher than that of high-purity aluminium powder. The lower explosion limit concentration of aluminium alloy polishing waste dust is 150 g/m3, which is 53.33% of that of high-purity aluminium powder. According to the analysis of the SEM image, the main reason is that the spherical particles of high-purity aluminium dust have a folded surface and good dispersion. Compared with the smooth fibre surface of aluminium alloy polishing waste dust, the former is easier to contact with air and the contact area is larger. Therefore, in engineering practice, it is not appropriate to use high-purity aluminium dust-related explosion parameters as the basis for the risk assessment of combustion and explosion at aluminium alloy polishing work sites. In addition, as the dust concentration decreases, the combustion intensity of high-purity aluminium dust and aluminium alloy polishing waste dust also decreases, and the flame propagation appears to be a discontinuous phenomenon. The peak flame propagation velocity of aluminium alloy polishing waste is 7.368 m/s at a concentration of 300 g/m3, which is 56.85% of that of high-purity aluminium powder. As the inerting ratio increases, the propagation velocity of the explosion flame slows down. When the inerting ratio reaches 30%, the minimum ignition energy of aluminium alloy polishing waste is inerted to 1 J, and self-sustained flame propagation cannot be formed. The results show that the ultra-fine Al(OH)3 powder has a significant inerting effect and is a realistic possibility in the production of aluminium alloy polishing.

FPattNet: A Multi-Scale Feature Fusion Network with Occlusion Awareness for Depth Estimation of Light Field Images

A light field camera can capture light information from various directions within a scene, allowing for the reconstruction of the scene. The light field image inherently contains the depth information of the scene, and depth estimations of light field images have become a popular research topic. This paper proposes a depth estimation network of light field images with occlusion awareness. Since light field images contain many views from different viewpoints, identifying the combinations that contribute the most to the depth estimation of the center view is critical to improving the depth estimation accuracy. Current methods typically rely on a fixed set of views, such as vertical, horizontal, and diagonal, which may not be optimal for all scenes. To address this limitation, we propose a novel approach that considers all available views during depth estimation while leveraging an attention mechanism to assign weights to each view dynamically. By inputting all views into the network and employing the attention mechanism, we enable the model to adaptively determine the most informative views for each scene, thus achieving more accurate depth estimation. Furthermore, we introduce a multi-scale feature fusion strategy that amalgamates contextual information and expands the receptive field to enhance the network's performance in handling challenging scenarios, such as textureless and occluded regions.

Randomized phase II adjuvant trial to compare two treatment durations of icotinib (2 years versus 1 year) for stage II-IIIA EGFR-positive lung adenocarcinoma patients (ICOMPARE study)

BACKGROUND

Despite the prolonged median disease-free survival (DFS) by adjuvant targeted therapy in non-small-cell lung cancer patients with epidermal growth factor receptor (EGFR) mutations, the relationship between the treatment duration and the survival benefits in patients remains unknown.

PATIENTS AND METHODS

In this multicenter, randomized, open-label, phase II trial, eligible patients aged 18-75 years with EGFR-mutant, stage II-IIIA lung adenocarcinoma and who had not received adjuvant chemotherapy after complete tumor resection were enrolled from eight centers in China. Patients were randomly assigned (1 : 1) to receive either 1-year or 2-year icotinib (125 mg thrice daily). The primary endpoint was DFS assessed by investigator. The secondary endpoints were overall survival (OS) and safety. This study was registered at ClinicalTrials.gov (NCT01929200).

RESULTS

Between September 2013 and October 2018, 109 patients were enrolled (1-year group, n = 55; 2-year group, n = 54). Median DFS was 48.9 months [95% confidence interval (CI) 33.1-70.1 months] in the 2-year group and 32.9 months (95% CI 26.6-44.8 months) in the 1-year group [hazard ratio (HR) 0.51; 95% CI 0.28-0.94; P = 0.0290]. Median OS for patients was 75.8 months [95% CI 64.4 months-not evaluable (NE)] in the 2-year group and NE (95% CI 66.3 months-NE) in the 1-year group (HR 0.34; 95% CI 0.13-0.95; P = 0.0317). Treatment-related adverse events (TRAEs) were observed in 41 of 55 (75%) patients in the 1-year group and in 36 of 54 (67%) patients in the 2-year group. Grade 3-4 TRAEs occurred in 4 of 55 (7%) patients in the 1-year group and in 3 of 54 (6%) patients in the 2-year group. No treatment-related deaths or interstitial lung disease was reported.

CONCLUSIONS

Two-year adjuvant icotinib was shown to significantly improve DFS and provide an OS benefit in EGFR-mutant, stage II-IIIA lung adenocarcinoma patients compared with 1-year treatment in this exploratory phase II study.

Differentiable Integrated Motion Prediction and Planning With Learnable Cost Function for Autonomous Driving

Predicting the future states of surrounding traffic participants and planning a safe, smooth, and socially compliant trajectory accordingly are crucial for autonomous vehicles (AVs). There are two major issues with the current autonomous driving system: the prediction module is often separated from the planning module, and the cost function for planning is hard to specify and tune. To tackle these issues, we propose a differentiable integrated prediction and planning (DIPP) framework that can also learn the cost function from data. Specifically, our framework uses a differentiable nonlinear optimizer as the motion planner, which takes as input the predicted trajectories of surrounding agents given by the neural network and optimizes the trajectory for the AV, enabling all operations to be differentiable, including the cost function weights. The proposed framework is trained on a large-scale real-world driving dataset to imitate human driving trajectories in the entire driving scene and validated in both open-loop and closed-loop manners. The open-loop testing results reveal that the proposed method outperforms the baseline methods across a variety of metrics and delivers planning-centric prediction results, allowing the planning module to output trajectories close to those of human drivers. In closed-loop testing, the proposed method outperforms various baseline methods, showing the ability to handle complex urban driving scenarios and robustness against the distributional shift. Importantly, we find that joint training of planning and prediction modules achieves better performance than planning with a separate trained prediction module in both open-loop and closed-loop tests. Moreover, the ablation study indicates that the learnable components in the framework are essential to ensure planning stability and performance. Code and Supplementary Videos are available at https://mczhi.github.io/DIPP/.

Predictive value of acoustic radiation force impulse imaging in breast cancer after neoadjuvant chemotherapy

To investigate the predictive value of acoustic radiation force impulse imaging for neoadjuvant chemotherapy in breast cancer. Seventy-eight breast cancer patients treated in our hospital from March 2019 to March 2022 were recruited. They received neoadjuvant chemotherapy and were examined by conventional ultrasound and acoustic radiation force impulse imaging before chemotherapy and after two cycles of chemotherapy. The lesion diameter, intralesional blood flow pulsatility index (PI), resistance index (RI), shear wave velocity (SWV), and change rate (Δlesion diameter, ΔPI, ΔRI, ΔSWV) were compared between the two groups before and after chemotherapy. The receiver operating characteristic curve was drawn to evaluate the predictive power of related parameters on the efficacy of neoadjuvant chemotherapy in breast cancer. After two cycles of neoadjuvant chemotherapy, according to the Miller-Payne grading, 57 cases (73.08%) with significant neoadjuvant chemotherapy response were classified as the response group, and 21 cases (26.92%) with non-significant response were classified as the non-response group. Before and after chemotherapy, the difference in lesion diameter, PI, RI, SWV, and change rate (Δlesion diameter, ΔPI, ΔRI, and ΔSWV) was statistically significant between the two groups (P < 0.05). The area under the curve of ΔSWV in predicting the efficacy of neoadjuvant chemotherapy 0.876 (95%CI 0.781 ~ 0.939) was significantly higher than that of Δlesion diameter 0.652 (95%CI 0.535 ~ 0.756), that of ΔPI 0.712 (95%CI 0.599 ~ 0.809), and that of ΔRI 0.678 (95%CI 0.563 ~ 0.780) (P < 0.05). The change rate of tissue stiffness has a relatively high predictive value for the effect of neoadjuvant chemotherapy in breast cancer.

BML-111 inhibits osteoclast differentiation by suppressing the MAPK and NF-κB pathways, alleviating deterioration of the knee joints in a CIA rat model

Irreversible destruction of joints is the hallmark of rheumatoid arthritis (RA). Osteoclasts are the only bone-resorbing cells and play an important role in joint rebuilding. BML-111 (5(S),6(R),7-trihydroxyheptanoic acid methyl ester, C₈ H₁₆ O₅ ) is a synthetic lipoxin A4 agonist with antioxidant and anti-inflammatory properties. The present study aimed to investigate the effect of BML-111 on osteoclasts in vivo and in vitro, to investigate its therapeutic effect on joint destruction in RA. Cell Counting Kit-8 assay and flow cytometry were used to exclude cytotoxic effects of BML-111 to bone marrow-derived macrophages (BMMs). Then, osteoclasts were differentiated in vitro from BMMs by used macrophage colony-stimulating factor and receptor activator of nuclear factor-κB ligand, and osteoclasts were observed following tartrate-resistant acid phosphatase staining with or without BML-111 treatment. Meanwhile, absorption pit assay and immunofluorescence staining of the fibrous actin ring were used to observe osteoclast function. Moreover, we examined mitogen-activated protein kinase (MAPK) and nuclear factor-κB (NF-κB) activation. We established collagen-induced arthritis in a rat model and, after treatment with BML-111, joint swelling was measured and the knee joints were processed for histology. We also examined serum and tissue for osteoclastogenesis-related markers. BML-111 inhibited osteoclast formation and differentiation in a time- and concentration-dependent manner, and downregulated the expression levels of MAPK and NF-κB in vitro. Meanwhile, BML-111 effectively alleviated joint structural damage and inhibited osteoclast formation in vivo. BML-111 inhibited osteoclast formation and differentiation in vitro and in vivo, and delayed the progression of joint destruction.

Large tunneling magnetoresistance in van der Waals magnetic tunnel junctions based on FeCl2 films with interlayer antiferromagnetic couplings

Antiferromagnets (AFMs) are some of the most promising candidates for next-generation magnetic memory technology owing to their advantages over conventional ferromagnets (FMs), such as zero stray field and THz-range magnetic resonance frequency. Motivated by the recent synthesis of FeCl₂ films with interlayer AFM and intralayer FM couplings, we investigated the magnetic properties of few-layer FeCl₂ and the spin-dependent transmissions of graphite/bilayer FeCl₂/graphite and Au/n-layer FeCl₂/Au magnetic tunnel junctions (MTJs) using first-principles calculations combined with the nonequilibrium Green's function. The interlayer AFM coupling of FeCl₂ is certified to be stable and independent of the stacking orders and relative displacement between layers. Furthermore, based on the Au electrode with better conductive performance than the graphite electrode and monolayer 1T-FeCl₂ with complete spin polarization, high Curie temperature and large magnetic anisotropic energy, a high tunnel magnetoresistance (TMR) ratio of 2.7 × 10³% is achieved in Au/bilayer FeCl₂/Au MTJs at zero bias and it increases with different layers of FeCl₂ (n = 2-10). These excellent spin transport properties of Au/n-layer FeCl₂/Au MTJs based on two-dimensional (2D) AFM barriers with out-of-plane magnetization directions suggest their great potential for application in high-reliability, high-speed and high-density spintronic devices.

Cold Acclimation and Supercooling Capacity of Agasicles hygrophila Adults

Agasicles hygrophila Selman and Vogt is used in the biological control of the invasive weed Alternanthera philoxeroides (Mart.) Griseb. However, with the northward establishment of A. philoxeroides in China, the weak adaptivity of A. hygrophila to cold weather has resulted in the ineffective control of A. philoxeroides in northern China. Cold acclimation can significantly enhance insect cold tolerance, enabling them to cope with more frequent climate fluctuations. To improve the biological control efficacy of A. hygrophila in cold climates, we compared the effects of rapid cold hardening and acclimation on A. hygrophila under laboratory conditions. On initially transferring adults from 26 to -10 °C for 2 h, mortality reached 80%. However, when pre-exposed to 0 °C for 2 h and then transferred to -10 °C for 2 h, adult mortality was reduced to 36.67%. These findings indicate that cold acclimation can enhance the cold tolerance of A. hygrophila under laboratory conditions. However, the beneficial cold acclimation effects waned after more than 15 min of recovery at 26 °C. Exposure to 15 °C for 24 h or gradual cooling from 0 to -10 °C at 1 °C·min^-1 also induced cold acclimation, indicating that long-term cold and fluctuating cold acclimation are also potentially effective strategies for enhancing low-temperature tolerance.

Mapping carbon emissions of China's domestic air passenger transport: From individual cities to intercity networks

As a significant carbon emission source with high growth potential, the air transport sector plays a crucial role in China's decarbonisation efforts. However, the spatial pattern and evolutionary dynamics of aviation carbon emissions in China have not been thoroughly studied. This study proposed a framework to reveal the spatial characteristics and influencing factors of aviation carbon emissions at the city level. Using data from 2019 to construct the aviation carbon emissions network of China (ACENC), the novelty of the study lies in the subdivision of carbon emissions of air passenger transport into cities and intercity lines in China, which helps to reveal the spatial characteristics of individual cities in the intercity network. Beijing, Shanghai, Shenzhen, Chengdu, and Guangzhou were the cities with the highest carbon emissions, and the routes between these cities caused a significant amount of carbon emissions. >80 % of the total carbon emissions can be attributed to two communities in the network, owing to their large size and strong connections. Correlation analysis indicates that a city's carbon emissions are significantly related to its demographic and economic attributes as well as its connection with other cities, while a city's carbon emission intensity may be influenced by its centrality in the whole network and the structure of the community to which it belongs. Overall, the presented results provide directions for stakeholders and policymakers to regulate carbon emissions from air transportation.

A Structure Constraint Matrix Factorization Framework for Human Behavior Segmentation

This article presents a structure constraint matrix factorization framework for different behavior segmentation of the human behavior sequential data. This framework is based on the structural information of the behavior continuity and the high similarity between neighboring frames. Due to the high similarity and high dimensionality of human behavior data, the high-precision segmentation of human behavior is hard to achieve from the perspective of application and academia. By making the behavior continuity hypothesis, first, the effective constraint regular terms are constructed. Subsequently, the clustering framework based on constrained non-negative matrix factorization is established. Finally, the segmentation result can be obtained by using the spectral clustering and graph segmentation algorithm. For illustration, the proposed framework is applied to the Weiz dataset, Keck dataset, mo_86 dataset, and mo_86_9 dataset. Empirical experiments on several public human behavior datasets demonstrate that the structure constraint matrix factorization framework can automatically segment human behavior sequences. Compared to the classical algorithm, the proposed framework can ensure consistent segmentation of sequential points within behavior actions and provide better performance in accuracy.

Glucosamine delays the progression of osteoporosis in senile mice by promoting osteoblast autophagy

Background

Senile osteoporosis (SOP) is one of the most prevalent diseases that afflict the elderly population, which characterized by decreased osteogenic ability. Glucosamine (GlcN) is an over-the-counter dietary supplement. Our previous study reported that GlcN promotes osteoblast proliferation by activating autophagy in vitro. The purpose of this study is to determine the effects and mechanisms of GlcN on senile osteoporosis and osteogenic differentiation in vivo.

Methods

Aging was induced by subcutaneous injection of d-Galactose (d-Gal), and treated with GlcN or vehicle. The anti-senile-osteoporosis effect of GlcN was explored by examining changes in micro-CT, serum indicators, body weight, protein and gene expression of aging and apoptosis. Additionally, the effects of GlcN on protein and gene expression of osteogenesis and autophagy were observed by inhibiting autophagy with 3-methyladenine (3-MA).

Results

GlcN significantly improved bone mineral density (BMD) and bone micro-architecture, decreased skeletal senescence and apoptosis and increased osteogenesis in d-Gal induced osteoporotic mice. While all effect was reversed with 3-MA.

Conclusion

GlcN effectively delayed the progression of osteoporosis in senile osteoporotic mice by promoting osteoblast autophagy. This study suggested that GlcN may be a prospective candidate drug for the treatment of SOP.

Investigation on the evolution of hydrothermal biochar

The objective of this study was to visualize trends and current research status of hydrothermal biochar research through a bibliometric analysis by using CiteSpace software. The original article data were collected from the Web of Science core database published between 2009 and 2020. A visual analysis network of national co-authored, institutional co-authored and author co-authored articles was created, countries, institutions and authors were classified accordingly. By visualizing the cited literature and journal co-citation networks, the main subject distribution and core journals were identified respectively. By visualizing journal co-citations, the main research content was identified. Further the cluster analysis revealed the key research directions of knowledge structure. Keyword co-occurrence analysis and key occurrence analysis demonstrate current research hotspots and new research frontiers. Through the above analysis, the cooperation and contributions of hydrothermal biochar research at different levels, from researchers to institutions to countries to macro levels, were explored, the disciplinary areas of knowledge and major knowledge sources of hydrothermal biochar were discovered, and the development lineage, current status, hotspots and trends of hydrothermal biochar were clarified. The results obtained from the study can provide a reference for scholars to gain a deeper understanding of hydrothermal biochar.

miRNA-150_R-1 mediates the HIF-1/ErbB signaling pathway to regulate the adhesion of endometrial epithelial cells in cows experiencing retained placenta

Retained placenta (RP) refers to reproductive disorders caused by the failure of fetal membranes to be expelled 12 h after delivery in dairy cows. Postpartum adhesion of the fetal membranes to the uterus causes diseases such as mastitis or endometritis, which threatening the profitability of the dairy industry. Emerging evidence suggests that micro RNAs (miRNAs) play crucial roles in various processes, such as the occurrence and progression of fetal membranes discharge. However, the molecular mechanisms of miRNAs in RP remain unknown. In this study, we performed RNA-sequencing to characterize the expression profiles of mRNAs and miRNAs in caudal vein blood samples of postpartum Holstein cows whose fetal membranes were discharged normally or retained to identify RP-related genes and evaluate their molecular mechanisms. We identified 44 differentially expressed miRNAs (19 upregulated and 25 downregulated) and 706 differentially expressed mRNAs (325 upregulated and 381 downregulated) in the RP group compared to the normal fetal membranes discharge group. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis revealed that differentially expressed mRNAs were mainly enriched in the extracellular matrix, cell adhesion, and autoimmunity-related biological processes or pathways. Further analyses using RNA-sequencing, a dual luciferase reporter system, quantitative reverse transcription-PCR, immunofluorescence, and western blotting verified that endothelial PAS domain protein 1 (EPAS1) is regulated by miR-150_R-1 in endometrial epithelial cells. We demonstrated the relationship between EPAS1 and RP and confirmed that EPAS1 is upregulated in the blood and placenta of cows that experience RP. Further, we proposed a model of the miRNA-mRNA negative regulatory network mediated by the HIF-1/ErbB signaling pathway to show its regulatory role in RP.

An Integrated Framework for Multi-State Driver Monitoring Using Heterogeneous Loss and Attention-Based Feature Decoupling

Multi-state driver monitoring is a key technique in building human-centric intelligent driving systems. This paper presents an integrated visual-based multi-state driver monitoring framework that incorporates head rotation, gaze, blinking, and yawning. To solve the challenge of head pose and gaze estimation, this paper proposes a unified network architecture that tackles these estimations as soft classification tasks. A feature decoupling module was developed to decouple the extracted features from different axis domains. Furthermore, a cascade cross-entropy was designed to restrict large deviations during the training phase, which was combined with the other features to form a heterogeneous loss function. In addition, gaze consistency was used to optimize its estimation, which also informed the model architecture design of the gaze estimation task. Finally, the proposed method was verified on several widely used benchmark datasets. Comprehensive experiments were conducted to evaluate the proposed method and the experimental results showed that the proposed method could achieve a state-of-the-art performance compared to other methods.

A systematic assessment of city-level climate change mitigation and air quality improvement in China

China is facing dual challenges of air pollution and climate change. By using city-level data, we comprehensively assessed air quality and CO₂ emission changes from 2015 to 2019 for 335 Chinese cities. We selected important regions for air pollution control and categorized all cities into different classes according to their development levels. Our novel approach revealed new insights on different patterns of changes of PM_2.5, O₃, and CO₂ by region and city class. We found that PM_2.5 concentrations decreased remarkably due to mandatory city-level reduction targets, especially in the Beijing-Tianjin-Hebei (-27%) region. Nonetheless, O₃ concentrations and CO₂ emissions increased in 91% and 69% of Chinese cities, respectively. Observed CO₂ emission reductions in more developed cities were mainly due to prominent energy intensity reduction and energy structure improvement. Our study indicates a lack of synergy in air pollution control and CO₂ mitigation under current policies in China. To address both challenges holistically, we suggest setting mandatory city-level CO₂ emission reduction targets and reinforcing clean energy and energy efficiency measures.

Connective tissue growth factor-targeting DNA aptamer suppresses pannus formation as diagnostics and therapeutics for rheumatoid arthritis

Connective tissue growth factor (CTGF) has been recently acknowledged as an ideal biomarker in the early disease course, participating in the pathogenesis of pannus formation in rheumatoid arthritis (RA). However, existing approaches for the detection of or antagonist targeting CTGF are either lacking or unsatisfactory in the diagnosis and treatment of RA. To address this, we synthesized and screened high-affinity single-stranded DNA aptamers targeting CTGF through a protein-based SELEX procedure. The structurally optimized variant AptW2-1-39-PEG was characterized thoroughly for its high-affinity (KD 7.86 nM), sensitivity (minimum protein binding concentration, 2 ng), specificity (negative binding to other biomarkers of RA), and stability (viability-maintaining duration in human serum, 48 h) properties using various biochemical and biophysical assays. Importantly, we showed the antiproliferative and antiangiogenic activities of the aptamers obtained using functional experiments and further verified the therapeutic effect of the aptamers on joint injury and inflammatory response in collagen-induced arthritis (CIA) mice, thus advancing this study into actual therapeutic application. Furthermore, we revealed that the binding within AptW2-1-39-PEG/CTGF was mediated by the thrombospondin 1 (TSP1) domain of CTGF using robust bioinformatics tools together with immunofluorescence. In conclusion, our results revealed a novel aptamer that holds promise as an additive or alternative approach for CTGF-targeting diagnostics and therapeutics for RA.

Soil mineralized carbon drives more carbon stock in coniferous-broadleaf mixed plantations compared to pure plantations

Forest soil carbon (C) sequestration has an important effect on global C dynamics and is regulated by various environmental factors. Mixed and pure plantations are common afforestation choices in north China, but how forest type and environmental factors interact to affect soil C stock remains unclear. We hypothesize that forest type changes soil physicochemical properties and surface biological factors, and further contributes to soil active C components, which together affect soil C sequestration capacity and C dynamic processes. Three 46-year-old 25 m × 25 m pure Pinus tabulaeformis forests (PF) and three 47-year-old 25 m × 25 m mixed coniferous-broadleaf (Pinus tabulaeformis-Quercus liaotungensis) forests (MF) were selected as the two treatments and sampled in August 2016. In 2017, soil temperature (ST) at 10 cm were measured every 30 min for the entire vegetation season. Across 0-50 cm (five soil layers, 10 cm per layer), we also measured C components and environmental factors which may affect soil C sequestration, including soil organic carbon (SOC), soil total nitrogen (STN), dissolved organic carbon (DOC), microbial biomass carbon (MBC), soil moisture (SM) and soil pH. We then incubated samples for 56 days at 25 °C to monitor the C loss through CO₂ release, characterized as cumulative mineralization carbon (CMC) and mineralized carbon (MC). Our results indicate that ST, pH, SM and litter thickness were affected by forest type. Average SOC stock in MF was 20% higher than in PF (MF: 11.29 kg m^-2; PF: 13.52 kg m^-2). Higher CMC under PF caused more soil C lost, and CMC increased 14.5% in PF (4.67 g kg^-1 soil) compared to MF (4.04 g kg^-1 soil) plots over the two-month incubation period. SOC stock was significantly positively correlated with SM (p < 0.001, R² = 0.43), DOC (p < 0.001, R² = 0.47) and CMC (p < 0.001, R² = 0.33), and significantly negatively correlated with pH (p < 0.001, R² = -0.37) and MC (p < 0.001, R² = -0.32). SOC stock and litter thickness may have contributed to more DOC leaching in MF, which may also provide more C source for microbial decomposition. Conversely, lower SM and pH in MF may inhibit microbial activity, which ultimately makes higher MC and lower CMC under MF and promotes C accumulation. Soil mineralized C drives more C stock in coniferous-broadleaf mixed plantations compared to pure plantations, and CMC and MC should be considered when soil C balance is assessed.

Prioritized Experience-Based Reinforcement Learning With Human Guidance for Autonomous Driving

Reinforcement learning (RL) requires skillful definition and remarkable computational efforts to solve optimization and control problems, which could impair its prospect. Introducing human guidance into RL is a promising way to improve learning performance. In this article, a comprehensive human guidance-based RL framework is established. A novel prioritized experience replay mechanism that adapts to human guidance in the RL process is proposed to boost the efficiency and performance of the RL algorithm. To relieve the heavy workload on human participants, a behavior model is established based on an incremental online learning method to mimic human actions. We design two challenging autonomous driving tasks for evaluating the proposed algorithm. Experiments are conducted to access the training and testing performance and learning mechanism of the proposed algorithm. Comparative results against the state-of-the-art methods suggest the advantages of our algorithm in terms of learning efficiency, performance, and robustness.

Nonlinear Predictive Motion Control for Autonomous Mobile Robots Considering Active Fault-Tolerant Control and Regenerative Braking

To further advance the performance and safety of autonomous mobile robots (AMRs), an integrated chassis control framework is proposed. In the longitudinal motion control module, a velocity-tracking controller was designed with the integrated feedforward and feedback control algorithm. Besides, the nonlinear model predictive control (NMPC) method was applied to the four-wheel steering (4WS) path-tracking controller design. To deal with the failure of key actuators, an active fault-tolerant control (AFTC) algorithm was designed by reallocating the driving or braking torques of the remaining normal actuators, and the weighted least squares (WLS) method was used for torque reallocation. The simulation results show that AMRs can advance driving stability and braking safety in the braking failure condition with the utilization of AFTC and recapture the braking energy during decelerations.

Leader’s Implicit Followership and Employees’ Innovative Behavior: Chain Mediation Effect of Leader–Member Exchange and Psychological Empowerment

In the Chinese society, where power distance is high, leaders’ attitudes and behavior toward employees determine their career development as well as affect the entire team’s performance. Therefore, exploring the kind of employees that leaders expect in China is essential. Based on implicit followership theory perspective, this study considers leaders’ positive implicit followership (LPIF) as the main research variable and examines its influence on employees’ innovative behavior (EIB). Moreover, it explores the multiple mediation effect of the leader–member exchange (LMX) relationship and psychological empowerment (PE) in this influence mechanism. The study sample comprised 389 leaders and their direct employees at 45 large- and medium-sized enterprises in Shandong, Beijing, Hebei, Shanghai, Shanxi, Zhejiang, and other regions of China. We used the leader–employee 1:1 matching questionnaire, and the longitudinal research design was adopted to avoid homology variance, making the study results more realistic and reliable. This study used the SPSS 26.0 and AMOS 26.0 statistical software to verify the hypotheses. Our findings show that LPIF has a significant positive effect on EIB, and LMX and PE have multiple mediation effects on the relationship between LPIF and EIB. When the level of LPIF is high, LMX and PE are also enhanced, which in turn promotes the increase in EIB. This study provides a new perspective for subsequent research on the psychological mechanism of employees and suggests an important method for understanding leadership and following processes in an organization. It plays a guiding role for the management practice of an enterprise, selection of leaders, and training of employees.

A Topical Emollient Mitigates the Progression of Cognitive Impairment in the Elderly: A Randomized, Open-Label Pilot Trial

BACKGROUND

Cognitive impairment is common in the elderly. Prior studies suggest a link between chronic inflammation and cognitive dysfunction, while aging-associated epidermal dysfunction has been connected to elevations in circulating cytokines.

OBJECTIVE

We assessed here whether improvements in epidermal function can mitigate the progression of cognitive impairment.

METHODS

This randomized, open-label pilot trial was carried out in two cities in northern China. A total of 200 participants aged ≥65 years were randomly assigned to the emollient-treated and untreated groups at 1:1 ratio. Participants in the treated group were treated topically with Atopalm cream® twice-daily from November to the following May each year for three consecutive years, while the untreated subjects served as controls. The Global Deterioration Scale (GDS) was used to assess the severity of cognitive impairment, while epidermal biophysical properties were measured on the forearms and the shins in parallel.

RESULTS

Over the three-year trial, GDS significantly increased from baseline (p<0.0001) in the controls, while in the treated group, GDS stabilized. While stratum corneum hydration on the forearms did not change significantly in the controls, transepidermal water loss rates (TEWL), significantly increased by the end of the trial compared to baselines in the controls (p<0.0001). On the forearms of the treated group, stratum corneum hydration increased (p<0.0001) while skin surface pH decreased from baseline (p<0.0001).

CONCLUSIONS

These results suggest that improvements in epidermal function with topical emollient can mitigate the progression of cognitive impairment. However, the sample size was relatively small, and trials in a larger cohort are needed to validate the present results.

The Status of Iodine Nutrition after Removing Iodized Salt in High Water Iodine Regions: a Cross-sectional Study in China

Currently, the removal of iodized salt is carried out in high water iodine regions. The present situation of iodine nutrition and the prevalence of thyroid diseases in such regions have not been clearly elucidated. This study aimed to figure out these problems to help render effective measures for cases of abnormal iodine nutrition status. A cross-sectional study was carried out in four areas of Jining and Heze, Shandong Province, China, with different water iodine concentrations (WIC). In total, 1344 adults were enrolled in this study, and data related to their iodine nutrition, thyroid function, and thyroid ultrasonography were collected. Subjects were grouped according to WIC, urine iodine concentration (UIC), serum iodine concentration (SIC), and combined UIC and SIC for analysis. Iodine levels were in excess in the 100 μg/L ≤ WIC < 300 μg/L and WIC ≥ 300 μg/L areas. Compared with the control WIC group (10-100 μg/L), the WIC ≥ 300 μg/L group had a higher prevalence of thyroid autoimmunity (TAI, 21.25% vs. 13.19%, P <0.05), subclinical hypothyroidism (SH, 20.20% vs. 11.96%, P < 0.05), thyroid nodules (TN, 31.75% vs. 18.71%, P < 0.05), and thyroid dysfunction (23.62% vs. 12.26%, P < 0.05). Compared with the UIC control group (100-300 μg/L), high UIC group (≥ 800 μg/L) had a higher prevalence of TN (33.75% vs. 21.14%, P < 0.05) and thyroid dysfunction (25% vs. 14.47%, P < 0.05). Next, compared with the control SIC group (50-110 μg/L), high SIC group (≥ 110 μg/L) had a higher prevalence of TAI (33.80% vs. 14.47%, P < 0.05), SH (23.94% vs. 14.30%, P < 0.05), and thyroid dysfunction (33.80% vs. 15.29%, P < 0.05). Finally, subjects with the highest UIC and the highest SIC also had a higher prevalence of TAI (25.92% vs. 10.97%, P < 0.05), SH (23.45% vs. 10.97%, P < 0.05), TN (34.56% vs. 15.85%, P < 0.05), and thyroid dysfunction (27.16% vs. 13.41%, P < 0.05) than subjects with middle iodine levels. The iodine nutrition of subjects in the WIC ≥ 300 μg/L areas was still in excess after removing iodized salt from their diets. High levels of iodine also increased the prevalence of TAI, SH, TN, and thyroid dysfunction in those areas. Simply removing iodized salt may not be sufficient for high water iodine regions.

Glucosamine suppresses oxidative stress and induces protective autophagy in osteoblasts by blocking the ROS/Akt/mTOR signaling pathway

Oxidative stress are the crucial pathogenic factors in osteoporosis. Cell autophagy, a major form of self-digestion, plays critical functions in different forms of stress by devouring harmful cytosolic proteins or organelles for the renewal of organelles and to maintain cellular homeostasis. Glucosamine (GlcN) has been widely utilized in treatments for patients with osteoarthritis-related joint pain. It has potential antioxidant effects and its pharmacological effect in osteoblasts remain unclear. The present study aimed to investigate whether autophagy participates the protective effects of GlcN in osteoblasts under oxidative stress and the possible mechanism. First of all, MC3T3-E1 cells were treated with hydrogen peroxide (H2O2) to induce oxidative stress, as assessed by viability assays, apoptosis, the intracellular ROS production. GlcN was capable of inducing autophagy and protected osteoblasts from those cytotoxic effects. Moreover, it significantly attenuated H2O2-induced oxidative stress as measured by malondialdehyde (MDA), glutathione (GSH), nitrite and superoxide dismutase (SOD) level. Importantly, the autophagy level increased in osteoblasts treated with GlcN as represented by an increased in both Beclin1 expression and the LC3 II/I ratio. Immunofluorescence analysis of autophagosomes also confirmed the above results. In addition, GlcN decreased the mammalian target of rapamycin (mTOR) and protein kinase B (Akt). However, the Akt activator (SC79) suppressed the autophagy level induced by GlcN in osteoblasts. Consequently, the antioxidant effects of GlcN were mediated, at least in part, by enhancing autophagy through the Akt/mTOR pathway. These results suggested that GlcN might be a promising candidate for osteoporosis treatment. This article is protected by copyright. All rights reserved.

Conversion effects of farmland to Zanthoxylum bungeanum plantations on soil organic carbon mineralization in the arid valley of the upper reaches of Yangtze River, China

Farmland conversion to forest is considered to be one of the effective measures to mitigate climate change. However, the impact of farmland conversion to forest land or grassland on soil CO₂ emission in arid areas is unclear due to the lack of comparative information on soil organic carbon (SOC) mineralization of different conversion types. The SOC mineralization in 0–100 cm soil layer in farmland (FL), abandoned land (AL) and different ages (including 8, 15, 20 and 28 years) of Zanthoxylum bungeanum plantations were measured by laboratory incubation. The size and decomposition rate of fast pool (C_f) and slow pool (C_s) in different land-use types and soil layers were estimated by double exponential model. The results showed that: 1) Farmland conversion increased the cumulative CO₂-C release (C_min) and SOC mineralization efficiency, and those indexes in AL were higher than that in Z. bungeanum plantations. The C_min and SOC mineralization efficiency of 0–100 cm soil increased with the ages of Z. bungeanum plantation. Both C_min and SOC mineralization efficiency decreased with the increase of soil depth; 2) Both soil C_f and C_s increased after farmland converted to Z. bungeanum plantations and AL. The C_s in the same soil layer increased with the ages of Z. bungeanum plantation, and the C_f showed a “V” type with the increased ages of Z. bungeanum plantation. The C_f and C_s decreased with the increase of soil depth in all land-use types; 3) Farmland conversion increased the decomposition rate of C_f (k₁) in all soil layer by 0.008–0.143 d⁻¹ and 0.082–0.148 d⁻¹ in Z. bungeanum plantations and AL, respectively. The k₁ was obviously higher in the 0−20 cm soil layer than that in other soil layers, while the decomposition rate of C_s (k₂) was not affected by FL conversion and soil depth; and 4) The initial soil chemical properties and enzyme activity affected SOC mineralization, especially the concentrations of total organic nitrogen (TON), SOC, easily oxidizable organic carbon (EOC) and microbial biomass carbon (MBC). It indicated that the conversion of farmland to Z. bungeanum plantations and AL increases SOC mineralization, especially in deeper soils, and it increased with the ages. The conversion of farmland to Z. bungeanum plantation is the optimal measure when the potential C sequestration of plant-soil system were taken in consideration.

Regulatory role of melatonin on epidermal growth factor receptor, Type I collagen α1 chain, and caveolin 1 in granulosa cells of sheep antral follicles

We investigated the expression of epidermal growth factor receptor (EGFR), Type I collagen α1 chain (COL1A1), and caveolin 1 (CAV1) during follicular development and examined the regulatory role of melatonin (MLT) on EGFR, COL1A1, and CAV1 in sheep antral ovaries. The expression was detected in granulosa and theca cells by immunohistochemistry. Quantitative real-time polymerase chain reaction and Western blotting were used to examine the expression levels of EGFR, COL1A1, and CAV1 in small (≤2 mm), medium (2-5 mm), and large (≥5 mm) follicles. The mRNA and protein levels of EGFR, COL1A1, and CAV1 were found to be the highest in large follicles. Furthermore, cultured granulosa cells were treated with MLT (10^-7 -10^-11  M), luzindole (nonselective MT1 and MT2 receptor antagonist, 10^-7  M), and 4-phenyl-2-propanamide tetraldehyde (4P-PDOT, MT2 selective antagonist, 10^-7  M) to detect the regulatory role of MLT on EGFR, COL1A1, and CAV1. Results indicated COL1A1 and CAV1 were at least partially regulated by MLT through MT1 and MT2 pathways, whereas EGFR was not. This study provided a reference for further studies on MLT regulatory role on EGFR, COL1A1, and CAV1 during sheep follicular development and elucidated the physiological mechanism of MLT regulator production.

The Identification of Non-Driving Activities with Associated Implication on the Take-Over Process

In conditionally automated driving, the engagement of non-driving activities (NDAs) can be regarded as the main factor that affects the driver’s take-over performance, the investigation of which is of great importance to the design of an intelligent human–machine interface for a safe and smooth control transition. This paper introduces a 3D convolutional neural network-based system to recognize six types of driver behaviour (four types of NDAs and two types of driving activities) through two video feeds based on head and hand movement. Based on the interaction of driver and object, the selected NDAs are divided into active mode and passive mode. The proposed recognition system achieves 85.87% accuracy for the classification of six activities. The impact of NDAs on the perspective of the driver’s situation awareness and take-over quality in terms of both activity type and interaction mode is further investigated. The results show that at a similar level of achieved maximum lateral error, the engagement of NDAs demands more time for drivers to accomplish the control transition, especially for the active mode NDAs engagement, which is more mentally demanding and reduces drivers’ sensitiveness to the driving situation change. Moreover, the haptic feedback torque from the steering wheel could help to reduce the time of the transition process, which can be regarded as a productive assistance system for the take-over process.

TSP1 is the essential domain of SEMA5A involved in pannus formation in rheumatoid arthritis

OBJECTIVE

In this study, we explored the effect of semaphorin5A (SEMA5A) on RA pathogenesis and its specific TSP1 domain on pannus formation.

METHODS

The expression of SEMA5A was detected in the synovium, the fibroblast-like synoviocytes (FLSs) and the SF of RA patients and healthy controls (HCs) by real-time quantitative PCR (q-PCR), immunohistochemistry staining, western blot and ELISA. SEMA5A-mAb intervention was performed to appraise the severity of joints in the CIA model. Transcriptome sequencing and bioinformatics analysis in SEMA5A-transfected FLSs from HCs were performed to screen differentially expressed genes after SEMA5A overexpression. An MTT assay in RA-FLSs, a chicken embryo allantoic membrane experiment and a tube formation experiment were used to clarify the influence of SEMA5A on cell proliferation and angiogenesis. Furthermore, a rescue experiment verified the function of the TSP1 domain of SEMA5A in the progress of RA with Sema5a-/- CIA mice.

RESULTS

The expression of SEMA5A increased in RA compared with that in HCs. Simultaneously, SEMA5A-mAbs significantly attenuated joint injury and the inflammatory response in CIA models. In addition, transcriptome sequencing and angiogenesis-related experiments verified the ability of SEMA5A to promote FLS proliferation and angiogenesis. Moreover, TSP1 was proved to be an essential domain in SEMA5A-induced angiogenesis in vitro. Additionally, rescue of TSP1-deleted SEMA5A failed to reduce the severity of arthritis in a CIA model constructed with Sema5a -/- mice.

CONCLUSION

In summary, upregulation of SEMA5A was first confirmed in pathological lesions of RA patients. Furthermore, treatment with SEMA5A-mAbs attenuated the progress of RA in the CIA model. Moreover, TSP1 was indicated as the key domain of SEMA5A in the promotion of pannus formation in RA.

Three Novel Structural Variations at MHC and IL12B Predisposing to Psoriasis

BACKGROUND

Structural variations (SVs, defined as DNA variants ≥50 bp) have been associated with various complex human diseases. However, research to screen the whole genome for SVs predisposing to psoriasis is still lacking.

OBJECTIVES

This study aimed to investigate the association of SVs and psoriasis.

METHODS

We performed a genome-wide screen on SVs using an imputation method on 5 independent cohorts with 45,386 subjects from the Chinese Han population. Fine mapping analysis, genetic interaction analysis and RNA expression analysis were conducted to explore the mechanism of SVs.

RESULTS

We obtained 4,535 SVs in total and identified 2 novel deletions (esv3608550, OR=2.73, P<2.00×10^-308 ; esv3608542, OR=0.47, P=7.40×10^-28 ) at 6q21.33 (MHC), 1 novel Alu element insertion (esv3607339, OR=1.22, P=1.18×10^-35 ) at 5q33.3 (IL12B), and confirmed 1 previously reported deletion (esv3587563, OR=1.30, P=9.52×10^-60 ) at 1q21.2 (LCE) for psoriasis. Fine mapping analysis including SNPs and small Insertions/Deletions (InDels) revealed that esv3608550 and esv3608542 were independently associated with psoriasis, and a novel independent SNP (rs9378188, OR=1.65, P=3.46×10^-38 ) was identified at 6q21.33. By genetic interaction analysis and RNA expression analysis, we speculate that the association of 2 deletions at 6q21.33 with psoriasis might relate to their influence on the expression of HLA-C.

CONCLUSIONS

Our study constructed the most comprehensive SV map for psoriasis thus far and enriched the genetic architecture and pathogenesis of psoriasis as well as highlighted the nonnegligible impact of SVs on complex diseases.

The effects of aerobic exercise on the intestinal tumors and flora of the ApcMin/+ mouse

INTRODUCTION

Intestinal tumor is one of the most common tumors that seriously threaten the health of residents all over the world. Studies suggest that the imbalance of intestinal flora is associated with tumorgenesis; meanwhile, long-term regular aerobic exercise can improve the occurrence and development of tumors. However, moderate aerobic exercise affecting the development of intestinal tumors and their related flora has not been explored. Thus, the purpose of our study is to explore the effects of aerobic exercise on intestinal tumor growth and flora changes in Apc^Min/+ mice, and try to answer whether there is a correlation between them after exercise intervention.

METHODS

In this study, 18 required Apc^Min/+ mice were randomly divided into Model group (n = 6), Exercise group (n = 6), and Aspirin group (positive control, n = 6), while C57BL/6 J wild-type mice were used as the blank control group. Each group is given corresponding intervention. Weight monitoring, tumor counts, hematoxylin-eosin staining, TdT-mediated dUTP nick-end labeling (TUNEL) fluorescence assay, immunohistochemistry (IHC), fecal sampling and grouping, and bacterial 16S rDNA gene analysis were completed after 12 weeks' intervention for each group of mice.

RESULTS

As a result, we were able to show significant improvements in mice' body weight changing rates (Exercise group 8.6% higher than Model control group), tumor numbers (Exercise group 4.33 ± 0.94 vs. Model control group 7.33 ± 2.49, Then put the slides into xylenewith tumor inhibition rate 40.93%), tumor pathological staging (Exercise group mainly low-grade tumorous adenomas vs. Model group mainly high-grade adenomas), and TUNEL staining (Exercise group 8.59% higher positive rate of apoptotic cells in tumors than Model group). The 16s rRNA sequencing analysis results showed that aerobic exercise could regulate the abundance of some genus (16/149, P < 0.01), and the number of intestinal tumors correlates with changes in the abundance of some bacteria in the intestinal flora (positive correlation with probiotics abundance and negative correlation with conditioned pathogens).

DISCUSSION

Changes in flora abundance may be one of the reasons for aerobic exercise to reduce the number of intestinal tumors, probably mediated by cell apoptosis. Future studies should focus on the potential mechanism of aerobic exercise in preventing intestinal tumorgenesis, especially the molecular mechanism through intestinal flora.

CONCLUSION

Aerobic exercise has a preventive effect on intestinal tumors in Apc^Min/+ mice, and can regulate the abundance of intestinal flora.

Human-Machine Shared Driving Control for Semi-Autonomous Vehicles Using Level of Cooperativeness

This paper proposes a new haptic shared control concept between the human driver and the automation for lane keeping in semi-autonomous vehicles. Based on the principle of human-machine interaction during lane keeping, the level of cooperativeness for completion of driving task is introduced. Using the proposed human-machine cooperative status along with the driver workload, the required level of haptic authority is determined according to the driver’s performance characteristics. Then, a time-varying assistance factor is developed to modulate the assistance torque, which is designed from an integrated driver-in-the-loop vehicle model taking into account the yaw-slip dynamics, the steering dynamics, and the human driver dynamics. To deal with the time-varying nature of both the assistance factor and the vehicle speed involved in the driver-in-the-loop vehicle model, a new ℓ∞ linear parameter varying control technique is proposed. The predefined specifications of the driver-vehicle system are guaranteed using Lyapunov stability theory. The proposed haptic shared control method is validated under various driving tests conducted with high-fidelity simulations. Extensive performance evaluations are performed to highlight the effectiveness of the new method in terms of driver-automation conflict management.

Enhanced production of seed oil with improved fatty acid composition by overexpressing NAD+ -dependent glycerol-3-phosphate dehydrogenase in soybean

There is growing interest in expanding the production of soybean oils (mainly triacylglycerol, or TAG) to meet rising feed demand and address global energy concerns. We report that a plastid-localized glycerol-3-phosphate dehydrogenase (GPDH), encoded by GmGPDHp1 gene, catalyzes the formation of glycerol-3-phosphate (G3P), an obligate substrate required for TAG biosynthesis. Overexpression of GmGPDHp1 increases soybean seed oil content with high levels of unsaturated fatty acids (FAs), especially oleic acid (C18:1), without detectably affecting growth or seed protein content or seed weight. Based on the lipidomic analyses, we found that the increase in G3P content led to an elevated diacylglycerol (DAG) pool, in which the Kennedy pathway-derived DAG was mostly increased, followed by PC-derived DAG, thereby promoting the synthesis of TAG containing relatively high proportion of C18:1. The increased G3P levels induced several transcriptional alterations of genes involved in the glycerolipid pathways. In particular, genes encoding the enzymes responsible for de novo glycerolipid synthesis were largely upregulated in the transgenic lines, in-line with the identified biochemical phenotype. These results reveal a key role for GmGPDHp1-mediated G3P metabolism in enhancing TAG synthesis and demonstrate a strategy to modify the FA compositions of soybean oils for improved nutrition and biofuel.