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Airflow significantly affects crop growth, and providing adequate and uniform airflow is essential to improve crop yield and quality. This paper used computational fluid dynamics software to optimize multifunctional fan-coil unit (FCU) installation factors at different crop heights. Fan pressure jump coefficient got optimized further, and the percentage of disturbance velocity was proposed as an index to evaluate the improvement of turbulence characteristics in airflow fields. The simulation results showed that the FCU system's optimal tilt angle, swing angle, and height above the ground were 20°, 45°, and 2.9 m, respectively. The optimum spacing is related to crop height. For lower tomatoes, the optimal spacing was 4.2 m and 4.5 m for higher tomatoes. The velocity coefficients of variation (Cv-v) for different height crops before optimization were 0.58 and 0.66. The Cv-v after optimization decreased to 0.37 and 0.41, and the uniformity was improved by 36.21 % and 37.88 %; the porous medium amounts percentage in the optimum air velocity range were increased to 64.70 % and 23.50 %. Simultaneously, the homogeneous airflow distribution improved the temperature field uniformity by 46.5 % and 23.95 %. This paper can provide theoretical guidance for the design and installation of FCU systems.

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system primarily mediated by CD4+ T helper cells. This study investigated the dynamic changes of natural killer (NK) cells and follicular T helper (Tfh) cells and their associations in relapsing-remitting MS patients. The findings revealed inverse relationships between NK cells and CD4+ T cells or Tfh cells. Specifically, CD56dim NK cells, not CD56bright NK cells, were negatively correlated with CD4+ T cells and Tfh cells. However, no significant correlations were found between NK cells and sNfL levels or EDSS scores. The ratio of CD56dim NK cells to circulating Tfh (cTfh) cells demonstrated superior discriminatory ability in distinguishing relapsing MS patients from healthy controls (HCs) and remitting patients, as determined by receiver operating characteristic (ROC) analysis. Following treatment with immunosuppressants or disease-modifying therapies (DMTs), a significant increase in the CD56dim NK/cTfh ratio was observed. These findings suggest that the CD56dim NK/cTfh ratio holds promise as a prognostic indicator for clinical relapse and treatment response in MS.

Abstract In view of its high mechanical performance, outstanding aesthetic qualities, and biological stability, zirconia has been widely used in the fields of dentistry. Due to its potential to produce suitable advanced configurations and structures for a number of medical applications, especially personalized created devices, ceramic additive manufacturing (AM) has been attracting a great deal of attention in recent years. AM zirconia hews out infinite possibilities that are otherwise barely possible with traditional processes thanks to its freedom and efficiency. In the review, AM zirconia’s physical and adhesive characteristics, accuracy, biocompatibility, as well as their clinical applications have been reviewed. Here, we highlight the accuracy and biocompatibility of 3D printed zirconia. Also, current obstacles and a forecast of AM zirconia for its development and improvement have been covered. In summary, this review offers a description of the basic characteristics of AM zirconia materials intended for oral medicine. Furthermore, it provides a generally novel and fundamental basis for the utilization of 3D printed zirconia in dentistry.

The benzofuran core inhibitors HCV-796, BMS-929075, MK-8876, compound 2, and compound 9B exhibit good pan-genotypic activity against various genotypes of NS5B polymerase. To elucidate their mechanism of action, multiple molecular simulation methods were used to investigate the complex systems of these inhibitors binding to GT1a, 1b, 2a, and 2b NS5B polymerases. The calculation results indicated that these five inhibitors can not only interact with the residues in the palm II subdomain of NS5B polymerase, but also with the residues in the palm I subdomain or the palm I/III overlap region. Interestingly, the binding of inhibitors with longer substituents at the C5 position (BMS-929075, MK-8876, compound 2, and compound 9B) to the GT1a and 2b NS5B polymerases exhibits different binding patterns compared to the binding to the GT1b and 2a NS5B polymerases. The interactions between the para-fluorophenyl groups at the C2 positions of the inhibitors and the residues at the binding pockets, together with the interactions between the substituents at the C5 positions and the residues at the reverse β-fold (residues 441–456), play a key role in recognition and the induction of the binding. The relevant studies could provide valuable information for further research and development of novel anti-HCV benzofuran core pan-genotypic inhibitors.

The stimulator of interferon genes (STING) plays a significant role in immune defense and protection against tumor proliferation. Many cyclic dinucleotide (CDN) analogues have been reported to regulate its activity, but the dynamic process involved when the ligands activate STING remains unclear. In this work, all-atom molecular dynamics simulations were performed to explore the binding mode between human STING (hSTING) and four cyclic adenosine–inosine monophosphate analogs (cAIMPs), as well as 2′,3′-cGMP-AMP (2′,3′-cGAMP). The results indicate that these cAIMPs adopt a U-shaped configuration within the binding pocket, forming extensive non-covalent interaction networks with hSTING. These interactions play a significant role in augmenting the binding, particularly in interactions with Tyr167, Arg238, Thr263, and Thr267. Additionally, the presence of hydrophobic interactions between the ligand and the receptor further contributes to the overall stability of the binding. In this work, the conformational changes in hSTING upon binding these cAIMPs were also studied and a significant tendency for hSTING to shift from open to closed state was observed after binding some of the cAIMP ligands.

Objective: This study aims to evaluate the short-term safety of inactivated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines in Chinese patients with central nervous system inflammatory demyelinating diseases (CNS IDDs). Methods: A web-based survey was conducted among patients with CNS IDDs from April 15 to 19, 2022 in China. In total, 645 patients with CNS IDDs were identified, including 425 patients with multiple sclerosis (MS), 194 with neuromyelitis optica spectrum disorder (NMOSD), and 26 with other CNS IDDs. The questionnaire consisted of demographic data, clinical records, history of SARS-CoV-2 vaccination, and vaccination-related symptoms within one month after vaccination. The demographic data, clinical information, and relapse rates between vaccinated and non-vaccinated patients were compared. Results: Among 645 patients with CNS IDDs, 78 were vaccinated and 567 were non-vaccinated with the vaccination rate of 12.1 %. Compared to non-vaccinated group, a lower percentage of patients on DMDs therapy (41.0 % vs. 71.8 %, P

Abstract Background Mutations in the signal transducers and activators of transcription 3 (STAT3) gene result in hyper-IgE syndrome(HIES), a rare immunodeficiency that causes abnormalities in immune system, bones and teeth. However, the role of Stat3 in development of dental hard tissues was yet to investigate. Methods In this study, a transgenic mouse of conditional knockout of Stat3 in dental mesenchymal cells (Osx-Cre; Stat3 fl/fl , Stat3 CKO) was made. The differences of postnatal tooth development between control and Stat3 CKO mice were compared by histology, µCT and scanning electron microscopy. Result Compared with the control, Stat3 CKO mice were presented with remarkable abnormal tooth phenotypes characterized by short root and thin dentin in molars and incisors. The enamel defects were also found on mandibular incisors. showed that Ki67-positive cells significantly decreased in dental mesenchymal of Stat3 CKO mice. In addition, β-catenin signaling was reduced in Hertwig's epithelial root sheath (HERS) and odontoblasts of Stat3 CKO mice. Conclusions Our results suggested that Stat3 played an important role in dental hard tissues development, and Stat3 may regulate dentin and tooth root development through the β-catenin signaling pathway.

ObjectiveTo address a novel lower-dose rituximab (RTX) therapy strategy based on our clinical experience and assess its efficacy and safety in neuromyelitis optica spectrum disorder (NMOSD).MethodsA multicenter, open-label, self-controlled, prospective follow-up study. Totally, 108 NMOSD patients were enrolled and a lower-dose RTX strategy was applied including 100 mg weekly for 3 weeks and then reinfusions every 6 months. Annualized relapse rate (ARR), the expanded disability status scale (EDSS) score and length of spinal cord lesions were included to evaluate the efficacy. Side effects were recorded to assess the safety profile.ResultsOf 108 patients, 80 (74.1%) initiated low-dose RTX therapy immediately after acute attack treatment and 33 (30.6%) initiated it after the first attack. During a median treatment period of 35.5 (22.0–48.8) months, significant decreases were observed in median ARR (1.1 [0.8–2.0] versus 0 [0–0.2], p < 0.001), EDSS score (3.5 [2.5–4.0] versus 2.0 [1.0–3.0], p < 0.001) and spinal cord lesion segments (5.0 [4.0–8.0] versus 3.0 [1.0–6.0], p < 0.001). The cumulative risk of relapses significantly decreased during the post- versus pre-RTX period (HR 0.238, 95%CI 0.160–0.356, p < 0.001) and on early therapy initiated within 24 months after disease onset versus delayed therapy (HR 0.506, 95%CI 0.258–0.994, p = 0.041). No serious side effects were recorded and all the subjects did not discontinue treatment due to RTX-related side effects.ConclusionOur research provided evidence supporting the lower-dose RTX strategy in treating NMOSD and reopened the issues of optimal dosage and therapy initiation timing.

Lysine-specific demethylase 1 (LSD1/KDM1A) has emerged as a promising therapeutic target for treating various cancers (such as breast cancer, liver cancer, etc.) and other diseases (blood diseases, cardiovascular diseases, etc.), owing to its observed overexpression, thereby presenting significant opportunities in drug development. Since its discovery in 2004, extensive research has been conducted on LSD1 inhibitors, with notable contributions from computational approaches. This review systematically summarizes LSD1 inhibitors investigated through computer-aided drug design (CADD) technologies since 2010, showcasing a diverse range of chemical scaffolds, including phenelzine derivatives, tranylcypromine (abbreviated as TCP or 2-PCPA) derivatives, nitrogen-containing heterocyclic (pyridine, pyrimidine, azole, thieno[3,2-b]pyrrole, indole, quinoline and benzoxazole) derivatives, natural products (including sanguinarine, phenolic compounds and resveratrol derivatives, flavonoids and other natural products) and others (including thiourea compounds, Fenoldopam and Raloxifene, (4-cyanophenyl)glycine derivatives, propargylamine and benzohydrazide derivatives and inhibitors discovered through AI techniques). Computational techniques, such as virtual screening, molecular docking and 3D-QSAR models, have played a pivotal role in elucidating the interactions between these inhibitors and LSD1. Moreover, the integration of cutting-edge technologies such as artificial intelligence holds promise in facilitating the discovery of novel LSD1 inhibitors. The comprehensive insights presented in this review aim to provide valuable information for advancing further research on LSD1 inhibitors.

Abstract Background and purpose To summarize the clinical characteristics of patients with muscle-specific kinase antibody-associated myasthenia gravis (MuSK-MG) and to evaluate the therapeutic responses to different treatment regimes. Methods Eighteen MuSK-MG patients admitted in our department between October 2017 and September 2020 were included. Clinical parameters were collected and the responses to different immunosuppressive drugs were assessed by MGFA Postintervention Status (MGFA-PIS). Meanwhile, the correlation between QMG scores and MuSK antibody titers were analyzed and MuSK antibody (MuSK-ab) titers were compared before and after therapy based on different immunosuppressive treatment regimes. Results Female predominance (ratio of females to males, 15:3) was evident in the study population, with the average onset age of (40.28 ± 18.57) years and the median disease course of 30.50 months (interquartile range [IQR], 17.50–44.75 months). Ocular manifestation was the most common onset symptom (11/18; 61.11%), and mild symmetrical ptosis was most frequent. Bulbar symptoms had the highest incidence of 88.89% over the entire disease course. Abnormal responses to RNS test were recorded most frequently on the musculus deltoideus (83.33%). All patients were treated with prednisone (Pred) alone or plus azathioprine (AZA), tacrolimus (TAC) or low-dose rituximab (RTX), and 17 (94.44%) of them achieved a favorable outcome defined as minimal manifestation (MM) or better. In general, an obvious positive correlation between QMG score and MuSK-ab titer (r = 0.710, P

Abstract Background Signal transducer and activator of transcription 3 (Stat3) is a cytoplasmic transcription factor that participates in various biologic processes. Loss of Stat3 causes hyperimmunoglobulin E syndrome, presenting with skeletal disorders including osteoporosis, recurrent fractures, scoliosis, and craniosynostosis. The objective of this study is to explore the effect and mechanism of Stat3 on osteogenesis of mesenchymal progenitors. Methods Stat3 was conditionally knockout (CKO) in mesenchymal progenitors by crossing the pair-related homeobox gene 1-cre (Prx1-Cre) with Stat3-floxed strain mice. Whole-mount-skeletal staining, histology, and micro-CT were used to assess the differences between Stat3 CKO and control mice. Further, in vitro experiments were conducted to evaluate the osteogenesis potential of primary isolated bone marrow mesenchymal stem cells (BMSCs) from both control and Stat3 CKO mice. After osteogenic induction for 14d, alizarin red staining was used to show the calcium deposit, while the western blotting was applied to detect the expression of osteogenic markers. Results Compared with the control, Stat3 CKO mice were present with shortened limbs, multiple fractures of long bone, and open calvarial fontanels. The abnormal growth plate structure and reduced collagen fiber were found in Stat3 CKO limbs. According to micro-CT analysis, the reduced cortical bone thickness and bone volume were found on Stat3 CKO mice. The in vitro osteogenic differentiation of BMSCs was inhibited in Stat3 CKO samples. After osteogenic induction for 14d, the significantly diminished calcium deposits were found in Stat3 CKO BMSCs. The decreased expression of osteogenic markers (OPN and COL1A1) was observed in Stat3 CKO BMSCs, compared with the control. Conclusions Stat3 played a critical role in bone development and osteogenesis. Loss of Stat3 impaired the osteogenesis of mesenchymal progenitors in vivo and in vitro.

The hybrid heating system consisting of loop heat pipe solar collector (LHPSC) and ground source heat pump (GSHP) is proposed to control greenhouse temperature in Harbin (the coldest provincial capital of China) in this paper. The combined thermal resistance network and energy balance model is developed to predict transient greenhouse temperature corresponding to the energy supplied by GSHP. The influence of ambient temperature on the thermal performance of greenhouse heating system is analyzed. The results show that the greenhouse temperature fluctuates in the range of 17–24 °C corresponding to the energy of 200 kW intermittently supplied by GSHP, which is reasonable for predicting greenhouse temperature in severely cold regions. As ambient temperature varies from −24 °C to −13 °C, heat loss of maintenance structure, ground, ventilation and water storage tank change in the range of 51.9–73.2 kW, 2.45–3.45 kW, 11.1–15.5 kW and 5.87–6.91 kW, respectively. The maximum thermal efficiency of loop heat pipe solar collector is higher (76.38%) than that of evacuated tube solar collectors (45%–50%), which will be promising for greenhouse heating due to higher thermal efficiency and better environmental adaptability. The results presented in this study will provide further valuable guidelines for designing greenhouse heating system.

Considering small diameter pipes, special pipes conveying corrosive, and flammable medium, a two-mass impact pipeline robot driven by a non-circular gear is proposed to study the walking dynamics of the robot in a dry piping environment. The mechanism principle of the two-mass impact pipeline robot is given to illustrate the walking mechanism of the robot under the combined action of the internal force and the external isotropic coulomb friction force. A dynamic model of a two-mass impact pipeline robot driven by non-circular gear is established. The dynamic response of the robot calculated by the numerical method reveals the walking characteristics of the pipe-impact robot under nonharmonic inertial force. The results show that the moving speed of the robot fluctuating rises with the increase of the input speed. The moving speed of the robot can be effectively improved by increasing the eccentricity of the non-circular gear or setting a certain amount of compression of the spring which is between the internal oscillator and the housing.

The present work reported the intrinsic mechanical behavior of vanadium dioxide (VO2) thin film deposited on a SiO2 substrate using a combination of nanoindentation tests and a theoretical model. The effect of phase transition on mechanical parameters was studied by adjusting the test temperature. A new model that can simultaneously extract the elastic modulus and hardness was derived by introducing a dimensional analysis. The results showed that the thin film exhibits a hardness of 9.43 GPa and a Young’s modulus of about 138.5 GPa at room temperature, compared with the values of 5.71 GPa and 126.9 GPa at a high temperature, respectively. It can be seen that the intrinsic mechanical parameters decrease to a certain extent after a phase transition. Finally, the numerical simulation results were consistent with those of the experiments, which verified the effectiveness of the new method. In addition, this study also provided useful guidance for mechanical tests on other ultra-thin films.

During the past two decades, an increasing number of patients with very-late-onset myasthenia gravis (v-LOMG) with an onset age of 65 years or older have been identified. However, few studies explore the predictors of secondary generalization in patients with v-LOMG with pure ocular onset. In this retrospective cohort study, 69 patients with v-LOMG were divided into ocular MG (OMG) and generalized MG (GMG), and the clinical characteristics and outcomes were compared. Cox regression analysis was performed to explore the predictors of generalization. The average onset age of the study population was 73.1 ± 4.2 years and the median disease duration was 48.0 months (interquartile range, 32.5–64.5 months). Serum acetylcholine receptor (AChR) antibody was detected in up to 86% of patients and concomitant diseases in approximately half of the patients. Male predominance was seen in OMG group while female predominance in GMG group (p = 0.043). Patients with OMG showed a lower positive rate of repetitive nerve stimulation (RNS) than those with GMG (p = 0.014), and favorable outcomes were obtained in more patients with OMG than those with GMG (p < 0.001). Of the 51 patients with pure ocular onset, 25 (49.0%) underwent secondary generalization. A higher probability of generalization was found in patients with positive RNS results and without immunotherapy (p = 0.018 and

Abstract Background and Aim Guillain–Barré syndrome (GBS) is one of the most common causes of acute flaccid paralysis. A timely assessment of this disease condition and its treatments are of vital importance to patients diagnosed with GBS. The purpose of this study is to investigate the variation trend of neutrophils along with disease courses and assess the prognostic value of serum low‐density neutrophils (LDNs) in the acute‐onset and recurrence of GBS. Methods A total of 176 GBS patients were recruited. Patients were evaluated with Medical Research Council (MRC) sum score and the Hughes Functional Grading Scale score upon admission. Peripheral blood samples were collected for routine testing. Flow cytometry analysis was performed to identify LDNs. All patients were followed up to collect disease condition data. Results The total neutrophil ratios and counts were significantly higher in patients with acute‐onset GBS compared to healthy controls (HCs). These counts/ratios decreased during remission and re‐elevated in recurrent GBS patients. However, no correlation was observed between the total neutrophil counts/ratios and the MRC sum score. The LDNs collected from different GBS courses were identified using flow cytometry. The counts and ratios were significantly higher in acute‐onset GBS and recurrent GBS compared to HCs and patients in remission. The LDN counts/ratios displayed a negative correlation with the MRC sum scores in acute‐onset GBS and recurrent GBS. Conclusion Our findings suggest that LDN counts/ratios are positively correlated with the acute‐onset and recurrence of GBS and its severity. Therefore, LDNs might serve as an accessible prognostic indicator for disease progression monitoring.

Supplying homogenous and suitable airflow schemes were explored in Chinese solar greenhouses, which had a positive impact on the crop yield and quality. This paper provided a multifunctional fan–coil unit system (FCU) to assist in circulating air. This system could collect the surplus heat of daytime air and release it to heat the greenhouse at nighttime. However, the main problem to be faced was the nonuniform airflow distributions. Thus, this paper aimed to optimize and analyze the placement strategy of the FCU system for a Chinese solar greenhouse using the numerical methodology. The computational fluid dynamics model was constructed to evaluate the effect of the FCU system on the airflow field and to uphold its validation. The complex structure of the FCU system was simplified to a fan model by fitting the pressure jump and the air velocity to enhance the practicality of the simulation model. Finally, the coefficient of variation was used to optimize four parameters: the tilt angle, swing angle, height above the ground, and shape of the outlet baffle. The effective disturbance velocity percentage was proposed as the evaluation index to improve the turbulence characteristics. The mean absolute error (MAE) between the measured and simulated values of the air velocity for the two planes was 0.06 m/s and 0.09 m/s, and the root mean square error (RMSE) was 0.08 m/s and 0.11 m/s. The simulated results showed that the coefficient of variation before optimization was 0.76, and the effective disturbance velocity percentages of the planes at 0.7 m and 1.0 m from the ground were 42.73% and 41.02%, respectively. After optimization, the coefficient of variation was reduced to 0.33, and the effective disturbance velocity percentages of the two planes increased to 58.68% and 43.73%, respectively. These results significantly improved the uniformity of the interior airflow field. This paper provides a reference for the design and installation of the FCU system.

Lysine-specific demethylase 1 (LSD1) is a histone-modifying enzyme, which is a significant target for anticancer drug research. In this work, 40 reported tetrahydroquinoline-derivative inhibitors targeting LSD1 were studied to establish the three-dimensional quantitative structure–activity relationship (3D-QSAR). The established models CoMFA (Comparative Molecular Field Analysis (q2 = 0.778, Rpred2 = 0.709)) and CoMSIA (Comparative Molecular Similarity Index Analysis (q2 = 0.764, Rpred2 = 0.713)) yielded good statistical and predictive properties. Based on the corresponding contour maps, seven novel tetrahydroquinoline derivatives were designed. For more information, three of the compounds (D1, D4, and Z17) and the template molecule 18x were explored with molecular dynamics simulations, binding free energy calculations by MM/PBSA method as well as the ADME (absorption, distribution, metabolism, and excretion) prediction. The results suggested that D1, D4, and Z17 performed better than template molecule 18x due to the introduction of the amino and hydrophobic groups, especially for the D1 and D4, which will provide guidance for the design of LSD1 inhibitors.

The buckling, de-lamination, and cracking of the thin film/substrate system caused by thermal stress is the main obstacle for functional failure. Moreover, the thermal stress of vanadium dioxide (VO2) thin film may be more complicated due to the stress re-distribution caused by phase transition. Therefore, the thermal stress of VO2 thin films deposited on four substrates with different materials (fused silica, silicon slice, sapphire, and glass) has been studied by finite element method in the present work. The influences of external temperature, substrate, and interlayer on thermal stress were analyzed. It was found that the substrates can greatly affect the thermal stresses, which were mainly caused by the mismatch of coefficient of thermal expansion (CTE). The thermal stress had a linear relationship with the external temperature, but this tendency would be redistributed or even change direction when phase transition occurred. The simulated results were in tandem with the analytical method. Meanwhile, the radial stress and shear stress distribution under the influence of phase transition were calculated. In addition, the reduction of thermal stress and shear stress showed that the appropriate interlayer can enhance the adhesive strength effectively.

DenseNet has strong expressiveness in many computer vision tasks, but the complexity of its model makes it difficult to deploy to devices with limited computing resources. In this paper, we propose S-DenseNet, a compact model of DenseNet which makes the extracting features of DenseNet more comprehensively and reduces the parameter redundancy at the same time. Firstly, we investigate the parameter redundancy of DenseNet and show the possibility of compressing DenseNet. For example, we reduced its parameters by 10% as keeping in the same accuracy. Secondly, we propose an algorithm based on the Skyline method for converting standard convolution into group convolution automatically. It can choose the filter weights automatically and restore the standard convolution filter with a high sparsity one called S-Conv. Finally, we combine S-Conv with dense connections and formed a more effective network architecture, that is S-DenseNet. Experiments show that in Cifar10, Cifar100 and SVHN datasets, we use only 40% parameters and 20% FLOPs of DenseNet, and the accuracy is improved by 1%. Compared with the compression models of DenseNet and other CNNs, we use less complexity in the model and achieve higher or similar accuracy. On ImageNet dataset, compared with lightweight CNN models, traditional CNNs and their compression models, we achieve the higher or similar Top-1 accuracy with less complexity.

The identification of drug-target interaction (DTI) plays a key role in drug discovery and development. Benefitting from large-scale drug databases and verified DTI relationships, a lot of machine-learning methods have been developed to predict DTIs. However, due to the difficulty in extracting useful information from molecules, the performance of these methods is limited by the representation of drugs and target proteins. This study proposes a new model called EmbedDTI to enhance the representation of both drugs and target proteins, and improve the performance of DTI prediction. For protein sequences, we leverage language modeling for pretraining the feature embeddings of amino acids and feed them to a convolutional neural network model for further representation learning. For drugs, we build two levels of graphs to represent compound structural information, namely the atom graph and substructure graph, and adopt graph convolutional network with an attention module to learn the embedding vectors for the graphs. We compare EmbedDTI with the existing DTI predictors on two benchmark datasets. The experimental results show that EmbedDTI outperforms the state-of-the-art models, and the attention module can identify the components crucial for DTIs in compounds.