[Application of microwave vacuum drying with process management in extract drying of personalized traditional Chinese medicine preparations].

Extracts are important intermediates in the production of traditional Chinese medicines preparations. The drying effect of extracts will directly affect the subsequent production process and the quality of the preparation. To meet the requirements of high drug loading, short time consumption, and simple production process of personalized traditional Chinese medicine preparations, this study explored the application of multi-program microwave vacuum drying process in the extract drying of personalized traditional Chinese medicine preparations. The influencing factors of microwave vacuum drying process were investigated for 5 excipients and 40 prescriptions. Taking the feasibility of drying, drying rate, drying time, and dried extract status as indicators, this study investigated the feeding requirements of microwave vacuum drying. With the dried extract status as the evaluation indicator, the three drying programs(A, B, and C) were compared to obtain the optimal drying condition. The experimental results showed that the optimal feeding conditions for microwave vacuum drying were material layer thickness of 2 cm and C program(a total of 7 drying processes), which solved the problem of easy scorching in microwave drying with process management. Furthermore, the preset moisture content of the dried extract in microwave drying should be 4%-5%, so that the dried extract of traditional Chinese medicine preparation had uniform quality, complete drying, and no scorching. This study lays a foundation for the application of microwave drying in the production of traditional Chinese medicine preparations, promoting the high-quality development of personalized traditional Chinese medicine preparations.

A variable speed limit control approach for freeway tunnels based on the model-based reinforcement learning framework with safety perception.

To improve the traffic safety and efficiency of freeway tunnels, this study proposes a novel variable speed limit (VSL) control strategy based on the model-based reinforcement learning framework (MBRL) with safety perception. The MBRL framework is designed by developing a multi-lane cell transmission model for freeway tunnels as an environment model, which is built so that agents can interact with the environment model while interacting with the real environment to improve the sampling efficiency of reinforcement learning. Based on a real-time crash risk prediction model for freeway tunnels that uses random deep and cross networks, the safety perception function inside the MBRL framework is developed. The reinforcement learning components fully account for most current tunnels' application conditions, and the VSL control agent is trained using a deep dyna-Q method. The control process uses a safety trigger mechanism to reduce the likelihood of crashes caused by frequent changes in speed. The efficacy of the proposed VSL strategies is validated through simulation experiments. The results show that the proposed VSL strategies significantly increase traffic safety performance by between 16.00% and 20.00% and traffic efficiency by between 3.00% and 6.50% compared to a fixed speed limit approach. Notably, the proposed strategies outperform traditional VSL strategy based on the traffic flow prediction model in terms of traffic safety and efficiency improvement, and they also outperform the VSL strategy based on model-free reinforcement learning framework when sampling efficiency is considered together. In addition, the proposed strategies with safety triggers are safer than those without safety triggers. These findings demonstrate the potential for MBRL-based VSL strategies to improve traffic safety and efficiency within freeway tunnels.

MSLTE: multiple self-supervised learning tasks for enhancing EEG emotion recognition.

Objective. The instability of the EEG acquisition devices may lead to information loss in the channels or frequency bands of the collected EEG. This phenomenon may be ignored in available models, which leads to the overfitting and low generalization of the model.Approach. Multiple self-supervised learning tasks are introduced in the proposed model to enhance the generalization of EEG emotion recognition and reduce the overfitting problem to some extent. Firstly, channel masking and frequency masking are introduced to simulate the information loss in certain channels and frequency bands resulting from the instability of EEG, and two self-supervised learning-based feature reconstruction tasks combining masked graph autoencoders (GAE) are constructed to enhance the generalization of the shared encoder. Secondly, to take full advantage of the complementary information contained in these two self-supervised learning tasks to ensure the reliability of feature reconstruction, a weight sharing (WS) mechanism is introduced between the two graph decoders. Thirdly, an adaptive weight multi-task loss (AWML) strategy based on homoscedastic uncertainty is adopted to combine the supervised learning loss and the two self-supervised learning losses to enhance the performance further.Main results. Experimental results on SEED, SEED-V, and DEAP datasets demonstrate that: (i) Generally, the proposed model achieves higher averaged emotion classification accuracy than various baselines included in both subject-dependent and subject-independent scenarios. (ii) Each key module contributes to the performance enhancement of the proposed model. (iii) It achieves higher training efficiency, and significantly lower model size and computational complexity than the state-of-the-art (SOTA) multi-task-based model. (iv) The performances of the proposed model are less influenced by the key parameters.Significance. The introduction of the self-supervised learning task helps to enhance the generalization of the EEG emotion recognition model and eliminate overfitting to some extent, which can be modified to be applied in other EEG-based classification tasks.

Neuroprotective Effects of Bifidobacterium animalis subsp. lactis NJ241 in a Mouse Model of Parkinson's Disease: Implications for Gut Microbiota and PGC-1α.

Intestinal dysbiosis plays a critical role in the pathogenesis of Parkinson's disease (PD), and probiotics have emerged as potential modulators of central nervous system function through the microbiota-gut-brain axis. This study aimed to elucidate the anti-inflammatory effects and underlying mechanisms of the probiotic strain Bifidobacterium animalis subsp. lactis NJ241 (NJ241) in a mouse model of PD induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). The impact of NJ241 was comprehensively assessed in PD mice through behavioral tests, immunofluorescence, Western blotting, enzyme-linked immunosorbent assay (ELISA), 16S rRNA sequencing, and short-chain fatty acid (SCFA) detection. NJ241 exhibited notable efficacy in mitigating MPTP-induced weight loss, gastrointestinal dysfunction, and behavioral deficits in mice. Furthermore, it demonstrated protected against MPTP-induced dopaminergic neuron death and inhibited the activation of glial cells in the substantia nigra (SN). NJ241 demonstrated the ability to normalized dysbiosis in the intestinal microbiota and elevate SCFA levels in PD mice. Additionally, NJ241 reversed MPTP-induced reductions in colonic GLP-1 levels and the expression of GLP-1R and PGC-1α in the SN. Notably, GLP-1R antagonists partially reversed the inhibitory effects of NJ241 on the activation of glial cells in the SN. In summary, NJ241 exerts a neuroprotective effect against MPTP-induced neuroinflammation by enhancing intestinal GLP-1 levels and activating nigral PGC-1α signaling. These findings provide a rationale for the exploration and development of probiotic-based therapeutic strategies for PD.

A chromatographic method for determining the interaction between a drug and two target proteins by fabricating a dual-heterogeneous surface.

Characterization of the drug-target interactions is pivotal throughout the whole procedure of drug development. Most of the current assays, particularly, chromatographic methods lack the capacity to reveal drug adsorption on the muti-target surface. To this end, we derived a reliable and workable mathematical equation for revealing drug bindings to dual targets on the heterogeneous surface starting from the mass balance equation. The derivatization relied on the correlation of drug injection amounts with their retention factors. Experimental validation was performed by determining the binding parameters of three canonical drugs on a heterogeneous surface, which was fabricated by fusing angiotensin receptor type I and type II receptors (AT1R and AT2R) at the terminuses of circularly permuted HaloTag (cpHaloTag) and immobilizing the whole fusion protein onto 6-bromohexanoic acid modified silica gel. We proved that immobilized AT1R-cpHalo-AT2R maintained the original ligand- and antibody-binding activities of the two receptors in three weeks. The association constants of valsartan, candesartan, and telmisartan to AT1R were (6.26±0.14) × 105, (9.66±0.71) × 105, and (3.17±0.03) × 105 L/mol. In the same column, their association constants to AT2R were (1.25±0.04) × 104, (2.30±0.08) × 104, and (8.51±0.06) × 103 L/mol. The patterns of the association constants to AT1R/AT2R (candesartan>valsartan>telmisartan) were in good line with the data by performing nonlinear chromatography on control columns containing immobilized AT1R or AT2R alone. This provided proof of the fact that the derivatization allowed the determination of drug bindings on the heterogeneous surface with the utilization of a single series of injections and linear regression. We reasoned that is simple enough to model the bindings of drug adsorption on commercially available adsorbents in fundamental or industrial fields, thus having the potential to become a universal method for analyzing the bindings of a drug to the heterogeneous surface containing multiple targets.

Light-Induced TaHY5-7A and TaBBX-3B Physically Interact to Promote PURPLE PERICARP-MYB 1 Expression in Purple-Grained Wheat.

Purple-grained wheat (Triticum aestivum L.) is an important germplasm source in crop breeding. Anthocyanin biosynthesis in the pericarps of purple-grained wheat is largely light-dependent; however, the regulatory mechanisms underlying light-induced anthocyanin accumulation in the wheat pericarp remain unknown. Here we determined that anthocyanins rapidly accumulate in the pericarps of the purple-grained wheat cultivar Heixiaomai 76 (H76) at 16 days after pollination under light treatment. Using transcriptome sequencing, differential gene expression analysis, and phylogenetic analysis, we identified two key genes involved in light signaling in wheat: ELONGATED HYPOCOTYL 5-7A (TaHY5-7A) and B-BOX-3B (TaBBX-3B). TaHY5-7A and TaBBX-3B were highly expressed in purple-grained wheat pericarps. The heterologous expression of TaHY5-7A partially restored the phenotype of the Arabidopsis (Arabidopsis thaliana) hy5 mutant, resulting in increased anthocyanin accumulation and a shortened hypocotyl. The heterologous expression of TaBBX-3B in wild-type Arabidopsis had similar effects. TaHY5-7A and TaBBX-3B were nucleus-localized, consistent with a function in transcription regulation. However, TaHY5-7A, which lacks a transactivation domain, was not sufficient to activate the expression of PURPLE PERICARP-MYB 1 (TaPpm1), the key anthocyanin biosynthesis regulator in purple pericarps of wheat. TaHY5-7A physically interacted with TaBBX-3B in yeast two-hybrid and bimolecular fluorescence complementation assays. Additionally, TaHY5-7A, together with TaBBX-3B, greatly enhanced the promoter activity of TaPpm1 in a dual luciferase assay. Overall, our results suggest that TaHY5-7A and TaBBX-3B collaboratively activate TaPpm1 expression to promote light-induced anthocyanin biosynthesis in purple-pericarp wheat.

Metallo-ß-lactamase SMB-1 evolves into a more efficient hydrolase under the selective pressure of meropenem.

Metallo-ß-lactamases (MßLs) are the primary mechanism of resistance to carbapenem antibiotics. To elucidate how MßLs have evolved with the introduction and use of antibiotics, the mutation and evolution of SMB-1 from Serratia marcescens were investigated in microbial evolution plates containing discontinuous meropenem (MEM) concentration gradients. The results revealed 2-point mutations, A242G and S257R; 1 double-site mutation, C240G/E258G; and 3 frameshift mutations, M5, M12, and M13, which are all missense mutations situated at the C-terminus. Compared with that of the wild-type (WT), the minimum inhibitory concentrations (MICs) of MEM for A242G, C240G/E258G, M5, M12, and M13 increased at least 120-fold, and that of S257R increased 8-fold. The catalytic efficiency kcat/Km increased by 365% and 647%, respectively. Concerning the structural changes, the structure at the active site changed from an ordered structure to an unordered conformation. Simultaneously, the flexibility of loop 1 was enhanced. These changes increased the volume of the active site cavity; thus, this was more conducive to exposing the Zn2+ site, facilitating substrate binding and conversion to products. In A242G, structural changes in Gly-242 can be transmitted to the active region via a network of interactions between the side chains of Gly-242 and the amino acid side chains near the active pocket. Together, these results pointed to the process of persistent drug tolerance and resistance, the SMB-1 enzyme evolved into a more exquisite structure with increased flexibility and stability, and stronger hydrolysis activity via genetic mutations and structural changes.

SFXN3 is Associated with Poor Clinical Outcomes and Sensitivity to the Hypomethylating Therapy in Non-M3 Acute Myeloid Leukemia Patients.

BACKGROUND: DNA hypermethylation plays a critical role in the occurrence and progression of acute myeloid leukemia (AML). The mitochondrial serine transporter, SFXN3, is vital for onecarbon metabolism and DNA methylation. However, the impact of SFXN3 on the occurrence and progression of AML has not been reported yet. OBJECTIVE: In this study, we hypothesized that SFXN3 indicates a poor prognosis and suggested tailored treatment for AML patients. METHODS: We used GEPIA and TCGA repository data to analyze the expression of SFXN3 and its correlation with survival in AML patients. RT-qPCR was used to detect the SFXN3 level in our enrolled AML patients and volunteers. Additionally, Whole Genome Bisulfite Sequencing (WGBS) was used to detect the genomic methylation level in individuals. RESULTS: Through the TCGA and GEPIA databases, we found that SFXN3 was enriched in AML patients, predicting shorter survival. Furthermore, we confirmed that SFXN3 was primarily overexpressed in AML patients, especially non-M3 patients, and that high SFXN3 in non-M3 AML patients was found to be associated with poor outcomes and frequent blast cells. Interestingly, non-M3 AML patients with high SFXN3 levels who received hypomethylating therapy showed a higher CR ratio. Finally, we found that SFXN3 could promote DNA methylation at transcription start sites (TSS) in non-M3 AML patients. These sites were found to be clustered in multiple vital cell functions and frequently accompanied by mutations in DNMT3A and NPM1. CONCLUSION: In conclusion, SXFN3 plays an important role in the progression and hypermethylation in non-M3 AML patients and could be a potential biomarker for indicating a high CR rate for hypomethylating therapy.

Genome-wide analysis of Hsp40 and Hsp70 gene family in four cotton species provides insights into their involvement in response to Verticillium dahliae and abiotic stress.

Introduction: Cotton is an important economic crop to provide natural fibers as raw materials to textile industry, and is significantly affected by biotic and abiotic stress during the whole growth stage, in which Verticillium wilt (VW) caused by Verticillium dahliae is one of the most destructive disease to lead to a significant yield reduction. Heat shock proteins (Hsps) are important molecular chaperones, and play crucial roles in plant growth, development, resistance to biotic and abiotic stress. Hsp40 and Hsp70 are two key Hsps in cell chaperone network, however, the function and regulatory mechanism of Hsp40 and Hsp70 members in VW resistance and abiotic stress in cotton are largely unknown. Methods and Results: Herein, a systematic and comprehensive analysis of Hsp40s and Hsp70s in four cotton species of Gossypium arboretum, G. raimondii, G. hirsutum, and G. barbadense were performed. A total of 291 Hsp40s and 171 Hsp70s identified in four Gossypium species. Sequence analysis revealed that all Hsp40 proteins contained J domain that provides the binding sites to Hsp70. Protein-protein interaction prediction analysis displayed that GhHsp40-55 might interact with GhHsp70-2 and GhHsp70-13, suggesting their potential function as protein complex. Promoter cis-acting element analysis demonstrated that multiple cis-elements related to disease and stress response consists in GhHsp40 and GhHsp70 promoters. Further expression analysis showed that eight GhHsp40s (Hsp40-2,4,8,11,20,23,53,55) and seven GhHsp70s (Hsp70-2,3,6,8,13,19,22) were up-regulated after V. dahliae infection. In addition, five GhHsp40s (Hsp40-2,8,11,53,55) and four GhHsp70s (Hsp70-3,6,8,13) were up-regulated after salt treatment, six GhHsp40s (Hsp40-4,11,20,23) and three GhHsp70s (Hsp70-2,8,19) were up-regulated after drought treatment, four GhHsp40s (Hsp40-2,11,20,23) and four GhHsp70s (Hsp70-3,6,19,22) were up-regulated after temperature treatment, suggesting these Hsps have possible important function in the process of abiotic stress response. Discussion: Our results lay a foundation for understanding the function of Hsp40 and Hsp70 in the resistance against V. dahliae and abiotic stress, and elucidating the regulatory mechanism of the protein complex, evolution and molecular mechanism under stress.

An Efficient Hybrid Linear Clustering Superpixel Decomposition Framework for Traffic Scene Semantic Segmentation.

Superpixel decomposition could reconstruct an image through meaningful fragments to extract regional features, thus boosting the performance of advanced computer vision tasks. To further optimize the computational efficiency as well as segmentation quality, a novel framework is proposed to generate superpixels from the perspective of hybridizing two existing linear clustering frameworks. Instead of conventional grid sampling seeds for region clustering, a fast convergence strategy is first introduced to center the final superpixel clusters, which is based on an accelerated convergence strategy. Superpixels are then generated from a center-fixed online average clustering, which adopts region growing to label all pixels in an efficient one-pass manner. The experiments verify that the integration of this two-step implementation could generate a synergistic effect and that it becomes more well-rounded than each single method. Compared with other state-of-the-art superpixel algorithms, the proposed framework achieves a comparable overall performance in terms of segmentation accuracy, spatial compactness and running efficiency; moreover, an application on image segmentation verifies its facilitation for traffic scene analysis.

Treatment of COVID-19 by monoclonal antibodies and the traditional Chinese medicine.

The mortality rate of the recent global pandemic corona virus disease 2019 (COVID-19) is currently as high as 7%. The SARS-CoV-2 virus is the culprit behind COVID-19. SARS-CoV-2 is an enveloped single-stranded RNA virus, the genome encodes four types of the structural proteins: S protein, E protein (envelope protein), M protein (matrix protein) and N protein (nucleocapsid protein). In COVID-19, monoclonal antibodies have played a significant role in diagnosis and treatment. This article briefly introduced the development of monoclonal antibodies targeting on S protein and N protein, which represents the main direction of monoclonal antibody drugs used in the diagnosis and treatment of COVID-19. Meanwhile, the traditional Chinese medicine also plays important role in the fight against COVID-19 by regulating human immunity. The article introduced the use of traditional Chinese medicine in fighting against COVID-19.

Molecular Design, Supramolecular Assembly, and Excellent Dye Adsorption Capacity of Natural Rigid Dehydroabietic Acid-Tailored Amide Organogelators.

It is very appealing to synthesize functional soft materials from natural and abundant plant diterpenes because they have conformationally rigid and chiral properties. Herein, dehydroabietic-based monoamide (DA-1) and diamide (DA-2) were designed by introducing device interactions, π-π stacking and hydrogen bonding, with an aromatic group, C═O, and N-H. DA-1 and DA-2 can be gelled in a mixed solvent and a single solvent, respectively. Several novel supramolecular organic gels including highly entangled three-dimensional networks composed of rods or fibers were constructed. Interestingly, DA-2 forms a helical structure that is right-handed under the cooperative control of the solvent and the rigid structure of rosin. Gel formation was primarily driven by hydrogen bonding, π-π stacking, and van der Waals force. Combined with Gaussian calculation and X-ray diffraction (XRD), we established pack patterns for each system, revealing the roles played by rosin and amide groups. Moreover, the carbon tetrachloride gel of DA-2 can effectively remove Congo red in an aqueous solution, and the removal rate can reach 98.4%. This research explores an efficient organic gel for adsorbing Congo red dye with the secretions of pine trees.

Liraglutide Regulates Mitochondrial Quality Control System Through PGC-1α in a Mouse Model of Parkinson's Disease.

Parkinson's disease (PD) is a multifactorial disorder, and there is strong evidence that mitochondria play an essential role in the disorder. Factors that regulate the mechanism of the mitochondrial quality control system have been drawing more and more attention. PGC-1α (peroxisome proliferator-activated receptor-γ coactivator-1α) is a powerful transcription factor involved in regulation of mitochondrial function. Glucagon-like peptide 1 (GLP-1), a brain-gut peptide, can enter the central nervous system through the blood-brain barrier and play neuroprotective role. However, whether the GLP-1R agonist liraglutide regulates mitochondrial quality control system through PGC-1α is still unclear. We administered different doses of liraglutide to intervene MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine)-induced PD model, and then immunofluorescence, Western blot, and stereotactic injection of lentivirus to downregulate PGC-1α were used to explore the mechanisms underlying the protective effect of liraglutide in PD. The results showed that MPTP lead to decreased mitochondrial biogenesis, disrupted mitochondrial dynamics, inhibited mitochondrial autophagy, and promoted cell apoptosis. While liraglutide effectively attenuated the neurotoxicity of MPTP, including reversing the dyskinesia caused by MPTP and preserving the expression of GLP-1R, TH, and PGC-1α in the substantia nigra (SN), further experiments showed that downregulation of PGC-1α expression via stereotactic injection PGC-1α lentivirus into the SN reversed the liraglutide protective effects. By PGC-1α downregulation, we found that PGC-1α can not only regulate mitochondria biogenesis, mitochondria dynamics, and autophagy, but also regulate cell apoptosis. In summary, liraglutide has a neuroprotective effect in the PD model induced by MPTP. This protective effect is accomplished by activating PGC-1α, which regulates the mitochondrial quality control system.

Neuroprotective effects of liraglutide against inflammation through the AMPK/NF-κB pathway in a mouse model of Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disease with increasing incidence in aged populations, second only to Alzheimer's disease. Increasing evidence has shown that inflammation plays an important role in the occurrence and development of Parkinson's disease. Growing evidence has shown that AMP-activated protein kinase (AMPK) and NF-κB are closely related to inflammation. Glucagon-like peptide 1 (GLP-1) is a hormone that is primarily secreted by intestinal endocrine L cells, and it has a variety of physiology through binding to GLP-1 receptor. GLP-1can be used for treatment of type 2 diabetes. In addition, GLP-1 also has anti-neuroinflammation activity. However, the exact mechanism behind how GLP-1 regulates neuroinflammation remains unclear. This study was designed to examine the effect of liraglutide on 1-methyl-4-phenyl-1,2,3,6- tetrahydropyridine (MPTP)-induced injury in mice and its potential mechanism of action. Results showed that liraglutide dose-dependently ameliorated mouse behavior including swimming time and locomotor activity, increased the number of tyrosine hydroxylase (TH)-positive neurons and protein level, and reduced Iba1 and GFAP expression in the substantia nigra (SN). Liraglutide treatment also increased p-AMPK expression and reduced NF-κB protein level. Applying the AMPK inhibitor Dorsomorphin (Compound C) reversed the effect of liraglutide-reducing p-AMPK and increasing NF-κB expression. Finally, GFAP protein level increased, along with a decrease in TH expression. In conclusion, these results suggest that liraglutide can suppress neuroinflammation. Moreover, this effect is mediated through the AMPK/NF-κB signaling pathway.

Boosting transparent electromagnetic interference shielding by multi-cavity resonances.

We propose a multi-cavity resonant architecture that is established by employing two opposing ultrathin silver-based films to form a Fabry-Pérot (F-P) cavity and inserting one or two metallic mesh layers in between. Compared with the single F-P cavity, the multi-cavity architecture with one metallic mesh layer experimentally exhibits a ∼37% improvement in the average shielding effectiveness and maintains a transmittance over 80% at 550 nm. A more significant improvement of ∼108% in shielding effectiveness (SE) can be achieved by inserting two metallic mesh layers. The proposed multi-cavity architecture provides a strategy for removal of the hindrance to transparent electromagnetic interference shielding.

Record-High Transparent Electromagnetic Interference Shielding Achieved by Simultaneous Microwave Fabry-Pérot Interference and Optical Antireflection.

As a potential risk to human and environmental health, radio frequency (RF) radiation should be studied due to the higher frequencies and larger bandwidths that may be employed. Electromagnetic interference (EMI) shielding materials can prevent exposure to RF radiation, but most of them are visibly opaque. In this work, we propose and fabricate visibly transparent EMI shielding materials using an ultrathin silver layer sandwiched by oxides (SLSO) as building blocks. The samples with a double-sided SLSO (D-SLSO) structure exhibit the highest EMI shielding effectiveness (SE) of 70 dB at 27.6 GHz (>62 dB on average at 4-40 GHz) and a transmittance close to 90% at a visible wavelength of 550 nm, which is comparable with those of polyethylene terephthalate (PET) and glass substrates. The D-SLSO structure plays a dual role: it suppresses optical reflections as antireflection coatings and enhances EMI shielding via Fabry-Pérot interference. In addition, we discuss the origin of the extraordinary frequency dependence of SE, which monotonically increases, contrary to that of conventional metallic mesh. This report describes SLSO-based transparent EMI shielding materials with record-high SE and visible transmittance that provide optoelectronic applications with robust safety and reliability under RF radiation with high and broad frequencies.

Draft Genome Sequence of a Selenite- and Tellurite-Reducing Marine Bacterium, Lysinibacillus sp. Strain ZYM-1.

Lysinibacillus sp. ZYM-1, a Gram-positive strain isolated from marine sediments, reduces selenite and tellurite efficiently. Meanwhile, it also exhibits high resistance to Zn2+ and Mn2+. Here, we report the draft genome sequence of strain ZYM-1, which contains genes related to selenite and tellurite reduction and also metal resistance.