Emission characteristics of biogenic volatile organic compounds in a subtropical pristine forest of southern China.

Emission characteristics of biogenic volatile organic compounds (BVOCs) from dominant tree species in the subtropical pristine forests of China are extremely limited. Here we conducted in situ field measurements of BVOCs emissions from representative mature evergreen trees by using dynamic branch enclosures at four altitude gradients (600-1690 m a.s.l.) in the Nanling Mountains of southern China. Composition characteristics as well as seasonal and altitudinal variations were analyzed. Standardized emission rates and canopy-scale emission factors were then calculated. Results showed that BVOCs emission intensities in the wet season were generally higher than those in the dry season. Monoterpenes were the dominant BVOCs emitted from most broad-leaved trees, accounting for over 70% of the total. Schima superba, Yushania basihirsuta and Altingia chinensis had relatively high emission intensities and secondary pollutant formation potentials. The localized emission factors of isoprene were comparable to the defaults in the Model of Emissions of Gases and Aerosols from Nature (MEGAN), while emission factors of monoterpenes and sesquiterpenes were 2 to 58 times of those in the model. Our results can be used to update the current BVOCs emission inventory in MEGAN, thereby reducing the uncertainties of BVOCs emission estimations in forested regions of southern China.

Effects of different pretreatment methods on the degree of substitution, structure, and physicochemical properties of synthesized malic acid sweet potato starch ester.

BACKGROUND: The preparation of malic acid starch ester (MSE) is mostly carried out using a high temperature method, but there are problems such as high energy consumption, long preparation time, and uneven heating. Microwave technology can be used to overcome these limitations. The semi-crystalline structure of starch granules hinders the modifier's access to the matrix, thus limiting the esterification reaction. Physical techniques can act on the interior of the starch to create a number of active sites, thereby facilitating the reaction of the starch with esterification reagents. Therefore, this study investigated the effect of starch pretreatment by microwave, heat-moisture, and ultrasonic techniques on the degree of substitution (DS), structure, and physicochemical properties of MSE synthesized by the microwave method. RESULTS: The DS of MSE was increased after pretreatments. The modified starch obtained by different pretreatment methods did not show new characteristic peaks, while the MSE synthesized showed new absorption peaks near 1735 cm-1. The granular structure and morphology of the modified starch obtained by microwave and heat-moisture pretreatment were gelatinized and aggregated, while some of the starch particles of the modified starch obtained by ultrasonic pretreatment appeared pore-sized. The relative crystallinity and gelatinization enthalpy of the MSE were reduced, but the crystallization pattern remained as A-type. CONCLUSION: Overall, the results suggest that various pretreatment methods can enhance the DS of MSE by disrupting the structure of starch. The findings of this study provide theoretical support for improving the DS of esterified starch. © 2024 Society of Chemical Industry.

miR-708-3p targetedly regulates LSD1 to promote osteoblast differentiation of hPDLSCs in periodontitis.

Periodontitis (PD) is a multifactorial inflammatory disease associated with periodontopathic bacteria. Lysine-specific demethylase 1 (LSD1), a type of histone demethylase, has been implicated in the modulation of the inflammatory response process in oral diseases by binding to miRNA targets. This study investigates the molecular mechanisms by which miRNA binds to LSD1 and its subsequent effect on osteogenic differentiation. First, human periodontal ligament stem cells (hPDLSCs) were isolated, cultured, and characterized. These cells were then subjected to lipopolysaccharide (LPS) treatment to induce inflammation, after which osteogenic differentiation was initiated. qPCR and western blot were employed to monitor changes in LSD1 expression. Subsequently, LSD1 was silenced in hPDLSCs to evaluate its impact on osteogenic differentiation. Through bioinformatics and dual luciferase reporter assay, miR-708-3p was predicted and confirmed as a target miRNA of LSD1. Subsequently, miR-708-3p expression was assessed, and its role in hPDLSCs in PD was evaluated through overexpression. Using chromatin immunoprecipitation (ChIP) and western blot assay, we explored the potential regulation of osterix (OSX) transcription by miR-708-3p and LSD1 via di-methylated H3K4 (H3K4me2). Finally, we investigated the role of OSX in hPDLSCs. Following LPS treatment of hPDLSCs, the expression of LSD1 increased, but this trend was reversed upon the induction of osteogenic differentiation. Silencing LSD1 strengthened the osteogenic differentiation of hPDLSCs. miR-708-3p was found to directly bind to and negatively regulate LSD1, leading to the repression of OSX transcription through demethylation of H3K4me2. Moreover, overexpression of miR-708-3p was found to promote hPDLSCs osteogenic differentiation in inflammatory microenvironment. However, the protective effect was partially attenuated by reduced expression of OSX. Our findings indicate that miR-708-3p targetedly regulates LSD1 to enhance OSX transcription via H3K4me2 methylation, ultimately promoting hPDLSCs osteogenic differentiation.

O-GlcNAcylated RALY Contributes to Hepatocellular Carcinoma Cells Proliferation by Regulating USP22 mRNA Nuclear Export.

Hepatocellular carcinoma (HCC) is one of the most prevalent and deadly tumors; however, its pathogenic mechanism remains largely elusive. In-depth researches are needed to reveal the expression regulatory mechanisms and functions of the RNA-binding protein RALY in HCC. Here, we identify RALY as a highly expressed oncogenic factor that affects HCC cells proliferation both in vitro and in vivo. O-GlcNAcylation of RALY at Ser176 enhances its stability by protecting RALY from TRIM27-mediated ubiquitination, thus maintaining hyper-expression of the RALY protein. Mechanistically, RALY interacts with USP22 messenger RNA, as revealed by RNA immunoprecipitation, to increase their cytoplasmic localization and protein expression, thereby promoting the proliferation of HCC cells. Furthermore, we develop a novel RALY protein degrader based on peptide proteolysis-targeting chimeras, named RALY-PROTAC, which we chemically synthesize by linking a RALY-targeting peptide with the E3 ubiquitin ligase recruitment ligand pomalidomide. In conclusion, our findings demonstrate a novel mechanism by which O-GlcNAcylation/RALY/USP22 mRNA axis aggravates HCC cells proliferation. RALY-PROTACs as degraders of the RALY protein exhibit potential as therapeutic drugs for RALY-overexpressing HCC.

Tailored Supramolecular Interactions in Host-Guest Complexation for Efficient and Stable Perovskite Solar Cells and Modules.

Host-guest complexation offers a promising approach for mitigating surface defects in perovskite solar cells (PSCs). Crown ethers are the most widely used macrocyclic hosts for complexing perovskite surfaces, yet their supramolecular interactions and functional implications require further understanding. Here we show that the dipole moment of crown ethers serves as an indicator of supramolecular interactions with both perovskites and precursor salts. A larger dipole moment, achieved through the substitution of heteroatoms, correlates with enhanced coordination with lead cations. Perovskite films incorporating aza-crown ethers as additives exhibited improved morphology, reduced defect densities, and better energy-level alignment compared to those using native crown ethers. We report power-conversion efficiencies (PCEs) exceeding 25% for PSCs, which show enhanced long-term stability, and a record PCE of 21.5% for host-guest complexation-based perovskite solar modules with an active area of 14.0 cm2.

Neighbor effect on conformational spaces of alanine residue in azapeptides.

The conformational properties of Alanine (Ala) residue have been investigated to understand protein folding and develop force fields. In this work, we examined the neighbor effect on the conformational spaces of Ala residue using model azapeptides, Ac-Ala-azaGly-NHMe (3, AaG), and Ac-azaGly-Ala-NHMe (4, aGA1). Ramachandran energy maps were generated by scanning (φ, ψ) dihedral angles of the Ala residues in models with the fixed dihedral angles (φ = ±90°, ψ = ±0° or ±180°) of azaGly residue using LCgau-BOP and LCgau-BOP + LRD functionals in the gas and water phases. The integral-equation-formalism polarizable continuum model (IEF-PCM) and a solvation model density (SMD) were employed to mimic the solvation effect. The most favorable conformation of Ala residue in azapeptide models is found as the polyproline II (ßP), inverse γ-turn (γ'), ß-sheet (ßS), right-handed helix (αR), or left-handed helix (αL) depending on the conformation of neighbor azaGly residue in isolated form. Solvation methods exhibit that the Ala residue favors the ßP, δR, and αR conformations regardless of its position in azapeptides 3 and 4 in water. Azapeptide 5, Ac-azaGly-Ala-NH2 (aGA2), was synthesized to evaluate the theoretical results. The X-ray structure showed that azaGly residue adopts the polyproline II (ßP) and Ala residue adopts the right-handed helical (αR) structure in aGA2. The conformational preferences of aGA2 and the dimer structure of aGA2 based on the X-ray structure were examined to assess the performance of DFT functionals. In addition, the local minima of azapeptide 6, Ac-Phe-azaGly-NH2 (FaG), were compared with the previous experimental results. SMD/LCgau-BOP + LRD methods agreed well with the reported experimental results. The results suggest the importance of weak dispersion interactions, neighbor effect, and solvent influence in the conformational preferences of Ala residue in model azapeptides.

Real-time evolution characteristics and potential reactions of contaminants in commuter bus cabin air.

Despite the increasing use of motor vehicles, the impact of airborne pollutants and their health risks inside public transportation, such as commuter buses, is not well understood. This study assessed air quality inside an urban commuter bus by continuously monitoring PM10, PM2.5, and CO concentrations during both driving and parking periods. Our findings revealed that the ventilation system of the bus significantly reduced the infiltration of outdoor particulate matter and water vapor. However, CO concentrations were considerably higher inside the bus than outside, primarily due to vehicular self-emission. The ineffection of the ventilation system to remove CO potentially increases long-term exposure risks for passengers. The study identified ozone as a key oxidant in the cabin. Besides vehicle emissions, C3-C10 saturated aldehydes and carbonyl compounds were detected, including acetone, propanal, and hexanal. The presence of 6-MHO, an oxidation product of squalene, suggests that passengers contribute to VOCs load through direct emissions or skin surface reactions. Additionally, human respiration was found to significantly contribute to isoprene levels, estimated at 81.7 %. This research underscores the need for further investigation into the cumulative effects of stable compounds in cabin air and provides insights for developing healthier public transportation systems.

Multi-branch CNN and grouping cascade attention for medical image classification.

Visual Transformers(ViT) have made remarkable achievements in the field of medical image analysis. However, ViT-based methods have poor classification results on some small-scale medical image classification datasets. Meanwhile, many ViT-based models sacrifice computational cost for superior performance, which is a great challenge in practical clinical applications. In this paper, we propose an efficient medical image classification network based on an alternating mixture of CNN and Transformer tandem, which is called Eff-CTNet. Specifically, the existing ViT-based method still mainly relies on multi-head self-attention (MHSA). Among them, the attention maps of MHSA are highly similar, which leads to computational redundancy. Therefore, we propose a group cascade attention (GCA) module to split the feature maps, which are provided to different attention heads to further improves the diversity of attention and reduce the computational cost. In addition, we propose an efficient CNN (EC) module to enhance the ability of the model and extract the local detail information in medical images. Finally, we connect them and design an efficient hybrid medical image classification network, namely Eff-CTNet. Extensive experimental results show that our Eff-CTNet achieves advanced classification performance with less computational cost on three public medical image classification datasets.

GSK2334470 attenuates high salt-exacerbated rheumatoid arthritis progression by restoring Th17/Treg homeostasis.

High salt (HS) consumption is a risk factor for multiple autoimmune disorders via disturbing immune homeostasis. Nevertheless, the exact mechanisms by which HS exacerbates rheumatoid arthritis (RA) pathogenesis remain poorly defined. Herein, we found that heightened phosphorylation of PDPK1 and SGK1 upon HS exposure attenuated FoxO1 expression to enhance the glycolytic capacity of CD4 T cells, resulting in strengthened Th17 but compromised Treg program. GSK2334470 (GSK), a dual PDPK1/SGK1 inhibitor, effectively mitigated the HS-induced enhancement in glycolytic capacity and the overproduction of IL-17A. Therefore, administration of GSK markedly alleviated HS-exacerbated RA progression in collagen-induced arthritis (CIA) model. Collectively, our data indicate that HS consumption subverts Th17/Treg homeostasis through the PDPK1-SGK1-FoxO1 signaling, while GSK could be a viable drug against RA progression in clinical settings.

Fermented Ginsenosides Alleviate Acute Liver Injury Induced by CCl4 in Mice by Regulating the AKT/mTOR Signaling Pathway.

This study investigated the alleviating effect of fermented ginsenosides obtained through yeast strain fermentation transformation on acute liver injury (ALI) induced by CCl4. Strains were screened for their ability to produce ß-glucosidase, the transformation ability of the strain was verified by high-performance liquid chromatography, and the Saccharomyces cerevisiae strain F6 was obtained by 26S rRNA sequencing. After fermentation by F6 strain, it was found that the content of ginsenosides Re, Rb1, and Rb2 was significantly decreased (P < 0.05), and rare ginsenosides were detected, with the content of Rh4 and Rg5 reaching 2.65 mg·g-1 and 2.56 mg·g-1. We also explored the preventive effect of fermented ginsenoside extract (FGE) on ALI. Mice were evenly divided into 9 groups as follows: control group, ALI model group, positive drug bifendate group, and treatment group, which included 3 ginsenoside extract (GE) groups and 3 FGE groups (dosage of 150, 300, and 450 mg·kg-1 b.w.). The results showed that compared with the ALI model group, FGE significantly increased the levels of glutathione peroxidase, hydroperoxidase, and superoxide dismutase and also decreased the malondialdehyde level. The levels of alanine aminotransferase, aspartate aminotransferase, and total bilirubin markers were significantly reduced, and the levels of inflammatory cytokines TNF-α, IL-6, and IL-1ß were significantly decreased. Bioinformatics analysis combined with Western blot validation explored the molecular mechanism of the effect of FGE. It was found that FGE could downregulate the expression of the p-AKT/AKT and the p-mTOR/mTOR ratios. These results suggested that FGE played an alleviative role in ALI by promoting autophagy to inhibit the AKT/mTOR signaling pathway.

PDIA3 orchestrates effector T cell program by serving as a chaperone to facilitate the non-canonical nuclear import of STAT1 and PKM2.

Dysregulated T cell activation underpins the immunopathology of rheumatoid arthritis (RA), yet the machineries that orchestrate T cell effector program remain incompletely understood. Herein, we leveraged bulk and single-cell RNA sequencing data from RA patients and validated protein disulfide isomerase family A member 3 (PDIA3) as a potential therapeutic target. PDIA3 is remarkably upregulated in pathogenic CD4 T cells derived from RA patients and positively correlates with C-reactive protein level and disease activity score 28. Pharmacological inhibition or genetic ablation of PDIA3 alleviates RA-associated articular pathology and autoimmune responses. Mechanistically, T cell receptor signaling triggers intracellular calcium flux to activate NFAT1, a process that is further potentiated by Wnt5a under RA settings. Activated NFAT1 then directly binds to the Pdia3 promoter to enhance the expression of PDIA3, which complexes with STAT1 or PKM2 to facilitate their nuclear import for transcribing T helper 1 (Th1) and Th17 lineage-related genes, respectively. This non-canonical regulatory mechanism likely occurs under pathological conditions, as PDIA3 could only be highly induced following aberrant external stimuli. Together, our data support that targeting PDIA3 is a vital strategy to mitigate autoimmune diseases, such as RA, in clinical settings.

The Trend of Smoking-Related Cognition and Its Association with Smoking Behaviors Among Junior High School Students - China, 2013-2021.

What is already known about this topic?: In 2013, 31.61% of students perceived quitting smoking as difficult, 61.73% considered smoking less attractive, and 73.89% believed that secondhand smoke is definitely harmful to health. What is added by this report?: The percentage of students who perceived quitting smoking as difficult increased from 31.61% in 2013 to 38.83% in 2021, while the percentage of students who found smoking less attractive rose from 61.73% to 69.40%. Conversely, there was a decrease in the percentage of students who perceived secondhand smoke as harmful, from 73.89% to 68.46%. An increased awareness of the hazards of secondhand smoke was associated with a reduction in smoking behaviors. What are the implications for public health practice?: It is imperative to enhance health education efforts that aim to raise awareness of the hazards of secondhand smoke.

Cigarette Use and Secondhand Smoke Exposure Among Secondary School Students - China, 2023.

What is already known about this topic?: In 2021, the prevalence of experimental and current cigarette use among secondary school students in China stood at 16.7% and 4.7%, respectively. Additionally, 39.9% of these students were exposed to secondhand smoke at school. What is added by this report?: In comparison to 2021, the prevalence of current cigarette use remained unchanged at 4.2% in 2023, whereas experimental use declined to 13.7%. Notably, rates were significantly higher among vocational senior high school (VSHS) students relative to their peers in senior high school (SHS) and junior high school (JHS). Furthermore, exposure to secondhand smoke in schools decreased to 35.4% in 2023 from previously recorded levels, with more pronounced reductions observed in JHS and SHS populations and no notable change among VSHS students. What are the implications for public health practice?: Targeted tobacco control policies are imperative for secondary school students, including the establishment of smoke-free school environments. Additionally, it is crucial to pay close attention to the needs of VSHS students.

Alcohol Advertising Exposure and Drinking Habits Among Chinese Adolescents in 2021: A National Survey.

Objectives. To assess the exposure of Chinese adolescents to proalcohol advertising and explore its association with alcohol consumption. Methods. A nationally and regionally representative school-based survey was conducted in mainland China in 2021 among students in grades 7 through 12, aged 13 to 18 years. We assessed adolescent exposure to proalcohol advertising and its association with alcohol consumption. Results. A total of 57 336 students participated in the survey, and the exposure percentage of proalcohol advertising was 66.8%, with no difference between boys and girls or between urban and rural areas. The top 3 exposure channels were television (51.8%), the Internet (43.6%), and outdoor billboards (42.0%). The exposure was higher among students who had consumed alcohol in the past 30 days (80.1% vs 65.1%; adjusted odds ratio [AOR] = 1.29) and in the past 12 months (77.3% vs 61.7%; AOR = 1.30). However, no significant correlation was observed between advertising exposure and drunkenness. Conclusions. Approximately two thirds of Chinese adolescents have been exposed to proalcohol advertising in the past 30 days, with television, the Internet, and outdoor billboards being the most prevalent channels. Exposure to proalcohol advertising exhibits a positive correlation with drinking. (Am J Public Health. 2024;114(8):814-823. https://doi.org/10.2105/AJPH.2024.307680).

Disruption of bacterial biofilms by a green synthesized artemisinin nano-copper nanomaterial.

Bacterial biofilms are associated with antibiotic resistance and account for ∼80% of all bacterial infections. In this study, we explored novel nanomaterials for combating bacteria and their biofilms. Artemisinin nano-copper (ANC) was synthesized using a green synthesis strategy, and its shape, size, structure, elemental composition, chemical valence, zeta potential, and conductivity were characterized using transmission electron microscopy, X-ray diffractometer, X-ray photoelectron spectroscopy, zeta potential, and dynamic light scattering. The results showed that ANC was successfully synthesized utilizing a liquid phase chemical reduction method using chitosan as a modified protectant and l-ascorbic acid as a green reducing agent. The stability of ANC was evaluated using dynamic light scattering. The results showed that the particle size of ANC at different concentrations was comparable to that of the original solution after 7 days of storage, and there was no significant change in the polydispersity index (P > 0.05). The antibacterial effects of ANC on Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) were determined by disc diffusion and broth dilution methods. The results demonstrated that ANC inhibited and killed E. coli and S. aureus. The effect of ANC on bacterial biofilms was investigated using crystal violet staining, scanning electron microscopy, laser confocal microscopy, and quantitative polymerase chain reaction. The results showed that ANC treatment was able to destroy bacterial biofilms and downregulate biofilm- and virulence-related genes in E. coli (HlyA, gyrA, and F17) and S. aureus (cna, PVL, ClfA, and femB). Green-synthesized ANC possesses excellent antibiofilm properties and is expected to exhibit antibacterial and antibiofilm properties.

Overview of AlphaFold2 and breakthroughs in overcoming its limitations.

Predicting three-dimensional (3D) protein structures has been challenging for decades. The emergence of AlphaFold2 (AF2), a deep learning-based machine learning method developed by DeepMind, became a game changer in the protein folding community. AF2 can predict a protein's three-dimensional structure with high confidence based on its amino acid sequence. Accurate prediction of protein structures can dramatically accelerate our understanding of biological mechanisms and provide a solid foundation for reliable drug design. Although AF2 breaks through the barriers in predicting protein structures, many rooms remain to be further studied. This review provides a brief historical overview of the development of protein structure prediction, covering template-based, template-free, and machine learning-based methods. In addition to reviewing the potential benefits (Pros) and considerations (Cons) of using AF2, this review summarizes the diverse applications, including protein structure predictions, dynamic changes, point mutation, integration of language model and experimental data, protein complex, and protein-peptide interaction. It underscores recent advancements in efficiency, reliability, and broad application of AF2. This comprehensive review offers valuable insights into the applications of AF2 and AF2-inspired AI methods in structural biology and its potential for clinically significant drug target discovery.

Influence of F-Containing Materials on Perovskite Solar Cells.

Perovskite solar cells (PSCs) are usually modified and passivated to improve their performance and stability. The interface modification and bulk doping are the two basic strategies. Fluorine (F)-containing materials are highly favored because of their unique hydrophobicity and coordination ability. This review discusses the basic characteristics of F, and the basic principles of improving the photovoltaic performance and stability of PSC devices using F-containing materials. We systematically summarized the latest progress in the application of F-containing materials to achieve efficient and stable PSCs on several key interface layers. It is believed that this work will afford significant understanding and inspirations toward the future application directions of F-containing materials in PSCs, and provide profound insights for the development of efficient and stable PSCs.

Nondestructive testing of runny salted egg yolk based on improved ConvNeXt-T.

Salted egg yolks from salted duck eggs are widely utilized in the domestic and international food industry as both raw materials and ingredients. When salted egg yolks are not fully cured and matured, they exist in a fluid state, with a mixture of solid and liquid internally. Due to this composition, they are susceptible to deterioration during storage and usage, necessitating their detection and classification. In this study, a dataset specifically for salted egg yolks was established, and the ConvNeXt-T model, employed as the benchmark model, underwent two notable improvements. First, a lightweight location-aware circular convolution (ParC) was introduced, utilizing a ParC-block to replace a portion of the original ConvNeXt-T block. This enhancement aimed to overcome the limitations of convolution in extracting global feature information while integrating the global sensing capability of vision transformer and the localization capability of convolution. Additionally, the activation function was modified through substitution. These improvements resulted in the final model. Experimental results indicate that the enhanced model exhibits faster convergence on the custom salted egg yolk dataset compared to the baseline model. Furthermore, a significant reduction of model parameters by a factor of 4 led to a 2.167 percentage point improvement in the accuracy of the test set. The ParC-ConvNeXt-SMU-T model achieved an accuracy of 96.833% with 26.8 million parameters. Notably, the improved model demonstrates exceptional effectiveness in recognizing salted egg yolks. PRACTICAL APPLICATION: This study can be widely applied in the process of salted egg yolk production and quality inspection, which can improve the actual sorting efficiency of salted egg yolks and reduce the labor cost at the same time. It can also be used for nondestructive testing of salted egg yolks by governmental enterprises and other regulatory authorities.