Root-to-shoot signaling positively mediates source-sink relation in late growth stages in diploid and tetraploid wheat.

Non-hydraulic root source signaling (nHRS) is a unique positive response to soil drying in the regulation of plant growth and development. However, it is unclear how the nHRS mediates the tradeoff between source and sink at the late growth stages and its adaptive mechanisms in primitive wheat. To address this issue, a root-splitting design was made by inserting solid partition in the middle of the pot culture to induce the occurrence of nHRS using four wheat cultivars (MO1 and MO4, diploid; DM22 and DM31, tetraploid) as materials. Three water treatments were designed as 1) both halves watered (CK), 2) holistic root system watered then droughted (FS), 3) one-half of the root system watered and half droughted (PS). FS and PS were designed to compare the role of the full root system and split root system to induce nHRS. Leaves samples were collected during booting and anthesis to compare the role of nHRS at both growth stages. The data indicated that under PS treatment, ABA concentration was significantly higher than FS and CK, demonstrating the induction of nHRS in split root design and nHRS decreased cytokinin (ZR) levels, particularly in the PS treatment. Soluble sugar and proline accumulation were higher in the anthesis stage as compared to the booting stage. POD activity was higher at anthesis, while CAT was higher at the booting stage. Increased ABA (nHRS) correlated with source-sink relationships and metabolic rate (i.e., leaf) connecting other stress signals. Biomass density showed superior resource acquisition and utilization capabilities in both FS and PS treatment as compared to CK in all plants. Our findings indicate that nHRS-induced alterations in phytohormones and their effect on source-sink relations were allied with the growth stages in primitive wheat.

Flexible terahertz phase shifter for optically controlled polydimethylsiloxane-vanadium dioxide composite film.

In the terahertz (THz) band, modulation research has become a focal point, with precise control of the phase shift of THz waves playing a pivotal role. In this study, we investigate the optical control of THz phase shift modulation in a polydimethylsiloxane (PDMS)-vanadium dioxide (VO2) flexible material using THz time-domain spectroscopy. Under the influence of an 808-nm continuous wave (CW) laser with power densities ranging from 0 to 2.74 W/cm2, the PDMS-VO2 flexible material exhibits significant phase shift modulation in the frequency range of 0.2 to 1.0 THz. The maximum optical-pumping phase shift reaches 0.27π rad at 1.0 THz in a composite material with a VO2 mass fraction of 5% and a thickness of 360 µm, and the amplitude transmittance from 0.2 THz to 1.0 THz exceeds 70%. Furthermore, the composite material exhibits good stability under at least 640 switching cycle times, as confirmed through repeatability tests. The proposed composite devices offer a new approach for more flexible phase shift modulation owing to the flexibility of the composite material and the non-contact and precise modulation of light control. Additionally, the stress-adjustable characteristics of flexible materials make them highly suitable for use in wearable THz modulators, highlighting their significant application potential.

Aircraft Engine Fault Diagnosis Model Based on 1DCNN-BiLSTM with CBAM.

As the operational status of aircraft engines evolves, their fault modes also undergo changes. In response to the operational degradation trend of aircraft engines, this paper proposes an aircraft engine fault diagnosis model based on 1DCNN-BiLSTM with CBAM. The model can be directly applied to raw monitoring data without the need for additional algorithms to extract fault degradation features. It fully leverages the advantages of 1DCNN in extracting local features along the spatial dimension and incorporates CBAM, a channel and spatial attention mechanism. CBAM could assign higher weights to features relevant to fault categories and make the model pay more attention to them. Subsequently, it utilizes BiLSTM to handle nonlinear time feature sequences and bidirectional contextual feature information. Finally, experimental validation is conducted on the publicly available CMAPSS dataset from NASA, categorizing fault modes into three types: faultless, HPC fault (the single fault), and HPC&Fan fault (the mixed fault). Comparative analysis with other models reveals that the proposed model has a higher classification accuracy, which is of practical significance in improving the reliability of aircraft engine operations and for Remaining Useful Life (RUL) prediction.

Causal effects of life course adiposity on temporomandibular disorders: A Mendelian randomization study.

BACKGROUND: Previous studies investigated the associations between obesity and temporomandibular disorders (TMDs), but the evidence for the causal inferences was unclear. OBJECTIVE: We aimed to investigate the causal link between life course adiposity and TMDs. METHODS: Mendelian randomization (MR) studies were performed using genetic instruments for birth weight (BW) (N = 261 932), childhood body mass index (BMI) (N = 39 620), childhood body size (N = 454 718), adult BMI (N = 99 998), body fat percentage (N = 454 633) and TMDs (N = 211 023). We assessed the overall effect of each life course adiposity factor via inverse-variance weighted (IVW), weighted median, and MR-Egger methods and performed extensive sensitivity analyses. Additionally, multivariable MR was conducted to evaluate the direct and indirect effects of childhood BMI on TMDs while accounting for BW and adult BMI, and vice versa. RESULTS: Univariable MR analyses revealed a causal effect of low childhood adiposity on an increased risk of TMDs (childhood BMI: IVW OR: 0.65, 95% CI: 0.54-0.78, p < .001; childhood body size: IVW OR: 0.56, 95% CI: 0.43-0.73, p < .001). No causal association existed between genetically predicted BW, adult BMI, or body fat percentage and TMDs. In the multivariable MR analyses, the effects of childhood BMI on TMDs occurrence remained significant and direct, even after adjusting for BW and adult BMI (multivariable IVW OR: 0.78, 95% CI: 0.61-0.99, p = .048). No pleiotropy and heterogeneity were detected (p > .05). CONCLUSION: Low childhood BMI might causally increase the risk of TMDs through a direct pathway.

Causal effects of educational attainment on temporomandibular disorders and the mediating pathways: A Mendelian randomization study.

BACKGROUND: As one of the most important indicators of socioeconomic status, educational attainment (EA) exhibits a strong association with temporomandibular disorders (TMDs). Despite this link, there is a lack of evidence regarding the causal role of EA in either facilitating or preventing TMDs. OBJECTIVE: This study aimed to investigate the causal effect of education on TMDs and explore potential mediating pathways. METHODS: Utilizing summary statistics from genome-wide association studies on years of schooling (N = 766 345) and TMDs (N = 211 023), we conducted Mendelian randomization (MR) to assess the overall effect of education. Additionally, a two-step MR approach was employed to evaluate 30 potential mediators and calculate the mediation proportions in the association. Comprehensive sensitivity analyses were used to verify the robustness, heterogeneity, and pleiotropy. RESULTS: Univariable MR analyses revealed a causal effect of lower EA on an increased risk of TMDs (OR: 0.53, 95% CI: 0.43-0.66, p < .001). Five out of 30 modifiable factors were identified as causal mediators in the associations of EA with TMDs, including feeling nervous (mediation proportion: 11.6%), feeling tense (10.2%), depression (9.6%), feeling worry (7.6%) and daily smoking (8.9%). Meanwhile, no pleiotropy was detected in the analyses (p > .05). CONCLUSION: Our findings supported that higher EA has a protective effect on the onset of TMDs, with partial mediation by psychological disorders and daily smoking. Interventions on these factors thus have the potential of substantially reducing the burden of TMDs attributed to low education.

Causal relationship between hypothyroidism and temporomandibular disorders: evidence from complementary genetic methods.

BACKGROUND: The role of thyroid health in temporomandibular disorders (TMDs) has been emphasized in observational studies. However, whether the causation exists is unclear, and controversy remains about which specific disorder, such as hypothyroidism or hyperthyroidism, is destructive in TMDs. This study aims to investigate the overall and specific causal effects of various thyroid conditions on TMDs. METHODS: Mendelian randomization (MR) studies were performed using genetic instruments for thyrotropin (TSH, N = 119,715), free thyroxine (fT4, N = 49,269), hypothyroidism (N = 410,141), hyperthyroidism (N = 460,499), and TMDs (N = 211,023). We assessed the overall effect of each thyroid factor via inverse-variance weighted (IVW), weighted median, and MR-Egger methods, and performed extensive sensitivity analyses. Additionally, multivariable MR was conducted to evaluate the direct or indirect effects of hypothyroidism on TMDs whilst accounting for TSH, fT4 and hyperthyroidism, and vice versa. RESULTS: Univariable MR analyses revealed a causal effect of hypothyroidism on an increased risk of TMDs (IVW OR: 1.12, 95% CI: 1.05-1.20, p = 0.001). No significant association between genetically predicted hyperthyroidism, TSH, or fT4 and TMDs. In the multivariable MR analyses, the effects of hypothyroidism on TMDs occurrence remained significant even after adjSusting for TSH, fT4 and hyperthyroidism (multivariable IVW OR: 1.10, 95% CI: 1.03-1.17, p = 0.006). No pleiotropy and heterogeneity were detected in the analyses (p > 0.05). CONCLUSIONS: Hypothyroidism might causally increase the risk of TMDs through a direct pathway, highlighting the critical role of managing thyroid health in the prevention of TMDs. Clinicians should give heightened attention to patients with hypothyroidism when seeking medical advice for temporomandibular discomfort. However, caution is warranted due to the potential confounders, pleiotropy, and selection bias in the MR study.

Sirt6 enhances macrophage lipophagy and improves lipid metabolism disorder by regulating the Wnt1/ß-catenin pathway in atherosclerosis.

Lipid metabolism disorders are considerably involved in the pathology of atherosclerosis; nevertheless, the fundamental mechanism is still largely unclear. This research sought to examine the function of lipophagy in lipid metabolism disorder-induced atherosclerosis and its fundamental mechanisms. Previously, Sirt6 has been reported to stimulate plaque stability by promoting macrophage autophagy. However, its role in macrophage lipophagy and its relationship with Wnt1 remains to be established. In this study, ApoE-/-: Sirt6-/- and ApoE-/-: Sirt6Tg mice were used and lipid droplets were analysed via transmission electron microscopy and Bodipy 493/503 staining in vitro. Atherosclerotic plaques in ApoE-/-: Sirt6-/- mice showed greater necrotic cores and lower stability score. Reconstitution of Sirt6 in atherosclerotic mice improved lipid metabolism disorder and prevented the progression of atherosclerosis. Furthermore, macrophages with Ac-LDL intervention showed more lipid droplets and increased expression of adipophilin and PLIN2. Reconstitution of Sirt6 recruited using SNF2H suppressed Wnt1 expression and improved lipid metabolism disorder by promoting lipophagy. In addition, downregulation of Sirt6 expression in Ac-LDL-treated macrophages inhibited lipid droplet degradation and stimulated foam cell formation. Innovative discoveries in the research revealed that atherosclerosis is caused by lipid metabolism disorders due to downregulated Sirt6 expression. Thus, modulating Sirt6's function in lipid metabolism might be a useful therapeutic approach for treating atherosclerosis.

Causal association between body mass index and temporomandibular disorders: a bidirectional two-sample Mendelian randomization analysis.

BACKGROUND: Observational studies have shown that body mass index (BMI) is highly correlated with the occurrence of temporomandibular disorders (TMDs). However, these studies failed to present a causal relationship. Thus, we aimed to performed a Mendelian randomization (MR) study to investigate causality between BMI and TMDs. METHODS: We performed a two-sample bidirectional MR analysis using large-scale genome-wide association studies (GWAS). Data were obtained from a large-scale BMI dataset (N = 322,154), TMDs dataset (N = 134,280). The causal effects were estimated with inverse-variance weighted (IVW) method, MR Egger, weighted median. Sensitivity analyses were implemented with Cochran's Q test, MR-Egger intercept test, MR-PRESSO, leave-one-out analysis and the funnel plot. RESULTS: In the forward MR analysis, a genetic prediction of low BMI was causally associated with a higher risk of TMDs (IVW OR: 0.575, 95% CI: 0.415-0.798, p: 0.001). Similar results were obtained using other complementary methods (MR Egger OR: 0.270, 95% CI: 0.104-0.698, p: 0.009; weighted median OR: 0.496, 95% CI: 0.298-0.826, p: 0.007). In the reverse MR results, TMDs was shown to have no significant effect on BMI (all p > 0.05). No pleiotropy and heterogeneity were detected in the bidirectional analysis (p > 0.05). CONCLUSION: A lower BMI might be causally associated with increased risk of TMDs, supporting the importance of weight control for the prevention of TMDs. Clinicians should pay more attention to the low-BMI patients among those seeking medical advice due to temporomandibular joint discomfort.

Transition in plant-plant facilitation in response to soil water and phosphorus availability in a legume-cereal intercropping system.

BACKGROUND: The tradeoff between negative and positive interactions of facilitated species and facilitators may depend on the degree of resource availability in agroecosystems. However, the rhizospheric mechanisms driving trade-offs that occur along phosphorus (P) and water availability gradients have not yet been systematically clarified. We established three types of root isolation conditions (no barrier, nylon barrier and solid barrier) at different P and water addition levels to address the above issue in a maize-grass pea intercropping system. RESULTS: The total yield and biomass net effect (NE) and the relative interaction index (RII) were significantly higher than 0 under all environmental conditions, demonstrating that plant-plant interactions generated positive effects in the intercropping system. The maize yield and biomass RII were 0.029-0.095 and 0.018-0.066, respectively, which indicated that maize growth was constantly facilitated. However, the RII for grass pea yield and biomass exhibited a different trend in comparison with maize. It was higher than 0 (as the facilitated species) under low soil P and moisture conditions and transitioned to values lower than 0 (facilitator species) under high P and moisture conditions, which showed that the type and intensity of plant-plant interactions steadily shifted with the applied stressors. Direct interactions decreased the maize rhizospheric soil pH by 1.5% and 1.9% under Low-P conditions. Notably, the rhizospheric soil acid and alkaline phosphatase secretions of maize and grass pea increased by 17.4-27.4% and 15.3-27.7%, respectively, in P-deficient soils. These results show that plant-plant interactions can effectively relieve P stress by mineralizing organophosphorus in P-deficient soils. Furthermore, the above tendency became more pronounced under drought-stressed conditions. The nylon barrier partially restricted the exchange and utilization of available nutrients and decreased the total yield and biomass by 1.8-7.8% and 1.1-7.8%, respectively. The presence of a solid barrier completely restricted interspecific rhizospheric interactions and decreased the total yield and biomass by 2.1-13.8% and 1.6-15.7%, respectively. Phytate and KH2PO4 addition intensified asymmetric interspecific competition, and grass pea was consistently subjected to competitive pressures. CONCLUSION: Briefly, the tradeoff between facilitation and competition was driven by rhizospheric interactions, and the transition in the intensity and type of interaction was highly dependent on resource availability in a biologically diverse system.

Genome-wide association study of SARS-CoV-2 infection in Chinese population.

Coronavirus disease 2019 (COVID-19) is a global public health concern. The purpose of this study was to investigate the association between genetic variants and SARS-CoV-2 infection and the COVID-19 severity in Chinese population. A total of 256 individuals including 87 symptomatic patients (tested positive for SARS-CoV-2), 84 asymptomatic cases, and 85 close contacts of confirmed patients (tested negative for SARS-CoV-2) were recruited from February 2020 to May 2020. We carried out the whole exome genome sequencing between the individuals and conducted a genetic association study for SARS-CoV-2 infection and the COVID-19 severity. In total, we analyzed more than 100,000 single-nucleotide polymorphisms. The genome-wide association study suggested potential correlation between genetic variability in POLR2A, ANKRD27, MAN1A2, and ERAP1 genes and SARS-CoV-2 infection susceptibility. The most significant gene locus associated with SARS-CoV-2 infection was located in POLR2A (p = 5.71 × 10-6). Furthermore, genetic variants in PCNX2, CD200R1L, ZMAT3, PLCL2, NEIL3, and LINC00700 genes (p < 1 × 10-5) were closely associated with the COVID-19 severity in Chinese population. Our study confirmed that new genetic variant loci had significant association with SARS-CoV-2 infection and the COVID-19 severity in Chinese population, which provided new clues for the studies on the susceptibility of SARS-CoV-2 infection and the COVID-19 severity. These findings may give a better understanding on the molecular pathogenesis of COVID-19 and genetic basis of heterogeneous susceptibility, with potential impact on new therapeutic options.

LncRNA TARID induces cell proliferation through cell cycle pathway associated with coronary artery disease.

BACKGROUND/AIM: Long non-coding RNA TARID (lncRNA TARID) can activate the tumor suppressor TCF21 in tumorigenesis by inducing promoter demethylation. However, the impact on lncRNA TARID and its variants of coronary artery disease (CAD) are poorly understood. METHODS: We performed a case-control study enrolling 949 cases and 892 controls to assess genotype. Five variants were genotyped by TaqMan assay. 20 cases and 20 controls were used to evaluate the expression of lncRNA TARID. The cell proliferation rate was evaluated by CCK-8. The RT-qPCR and cell cycle analysis were applied to examine cell proliferation-related mRNA and cell distribution. RESULTS: This study indicated that rs2327433 GG genotype was associated with CAD risk adjusting for traditional risk factors (OR = 2.74, 95%CI: 1.10-6.83, P = 0.03). Our results analyses revealed that the genotype of rs2327433 was related to the proportion of CAD patients with left anterior descending artery disease and left circumflex artery disease (P = 0.025 and P = 0.025, respectively). The results showed that the minor allele frequency of rs2327433 was significantly correlated with the severity of the disease (P = 0.029). The eQTL analysis showed that rs2327433 may affect the transcription factors TCF21 regulated by lncRNA TARID. We found that TARID silencing regulated cell proliferation and altered cell cycle progression by induced upregulation of CDK1 and PCNA. CONCLUSIONS: SNP rs2327433 in lncRNA TARID was associated with CAD risk and the severity of CAD in the Chinese Han population. Furthermore, SNP rs2327433 may affect the expression of atherosclerosis-related transcription factor TCF21 regulated by lncRNA TARID. Finally, our study provided a new lncRNA-dictated regulatory mechanism participating in cell proliferation.

Building quantum mechanics quality force fields of proteins with the generalized energy-based fragmentation approach and machine learning.

We combined our generalized energy-based fragmentation (GEBF) approach and machine learning (ML) technique to construct quantum mechanics (QM) quality force fields for proteins. In our scheme, the training sets for a protein are only constructed from its small subsystems, which capture all short-range interactions in the target system. The energy of a given protein is expressed as the summation of atomic contributions from QM calculations of various subsystems, corrected by long-range Coulomb and van der Waals interactions. With the Gaussian approximation potential (GAP) method, our protocol can automatically generate training sets with high efficiency. To facilitate the construction of training sets for proteins, we store all trained subsystem data in a library. If subsystems in the library are detected in a new protein, corresponding datasets can be directly reused as a part of the training set on this new protein. With two polypeptides, 4ZNN and 1XQ8 segment, as examples, the energies and forces predicted by GEBF-GAP are in good agreement with those from conventional QM calculations, and dihedral angle distributions from GEBF-GAP molecular dynamics (MD) simulations can also well reproduce those from ab initio MD simulations. In addition, with the training set generated from GEBF-GAP, we also demonstrate that GEBF-ML force fields constructed by neural network (NN) methods can also show QM quality. Therefore, the present work provides an efficient and systematic way to build QM quality force fields for biological systems.

Combined fragment-based machine learning force field with classical force field and its application in the NMR calculations of macromolecules in solutions.

We have developed a combined fragment-based machine learning (ML) force field and molecular mechanics (MM) force field for simulating the structures of macromolecules in solutions, and then compute its NMR chemical shifts with the generalized energy-based fragmentation (GEBF) approach at the level of density functional theory (DFT). In this work, we first construct Gaussian approximation potential based on GEBF subsystems of macromolecules for MD simulations and then a GEBF-based neural network (GEBF-NN) with deep potential model for the studied macromolecule. Then, we develop a GEBF-NN/MM force field for macromolecules in solutions by combining the GEBF-NN force field for the solute molecule and ff14SB force field for solvent molecules. Using the GEBF-NN/MM MD simulation to generate snapshot structures of solute/solvent clusters, we then perform the NMR calculations with the GEBF approach at the DFT level to calculate NMR chemical shifts of the solute molecule. Taking a heptamer of oligopyridine-dicarboxamides in chloroform solution as an example, our results show that the GEBF-NN force field is quite accurate for this heptamer by comparing with the reference DFT results. For this heptamer in chloroform solution, both the GEBF-NN/MM and classical MD simulations could lead to helical structures from the same initial extended structure. The GEBF-DFT NMR results indicate that the GEBF-NN/MM force field could lead to more accurate NMR chemical shifts on hydrogen atoms by comparing with the experimental NMR results. Therefore, the GEBF-NN/MM force field could be employed for predicting more accurate dynamical behaviors than the classical force field for complex systems in solutions.

Clinical Value of Metagenomic Next-Generation Sequencing in Immunocompromised Patients with Sepsis.

BACKGROUND Sepsis is a serious threat to human life, particularly in immunocompromised patients; hence, early diagnosis and targeted treatment are important. Metagenomic next-generation sequencing (NGS) has significant advantages over traditional diagnostic methods. This study investigated the clinical value of NGS for pathogen identification in immunocompromised patients with sepsis. MATERIAL AND METHODS From July 2020 to September 2021, 90 consecutive patients with sepsis were enrolled in this prospective study. The patients were divided into 2 groups: an immunocompromised group (n=30) and an immunocompetent group (n=60). The pathogens causing sepsis were concurrently identified using NGS and traditional diagnostic methods. The pathogen detection rates and the spectrum of pathogens identified were compared according to the method of detection and between the immunocompromised and immunocompetent groups. RESULTS Of the 90 patients, 77 (86%) were positive for 1 or more pathogens using NGS, and 50 (56%) were positive using traditional detection methods. The positivity rate of sputum and bronchoalveolar lavage fluid was higher than that of blood samples. Pneumocystis jirovecii and cytomegalovirus infections were more common in the immunocompromised group than in the immunocompetent group. CONCLUSIONS The performance of NGS in identifying pathogens for patients with sepsis is better than that of traditional detection methods, especially in immunocompromised patients. Pneumocystis jirovecii and cytomegalovirus infections are more common in immunocompromised patients.

Evaluation of potential cardiotoxicity of ammonia: l-selenomethionine inhibits ammonia-induced cardiac autophagy by activating the PI3K/AKT/mTOR signaling pathway.

Ammonia is a major harmful gas in the environment of livestock and poultry. Studies have shown that excessive ammonia inhalation has adverse effects in pig heart. However, the mechanism of ammonia-induced cardiac toxicity in pigs has not been reported. L-selenomethionine is a kind of organic selenium (Se) which is easily absorbed by the body. Therefore, in this study, twenty-four 125-day-old pigs were randomly divided into 4 groups: C (control) group, A (ammonia) group, Se group (Se content: 0.5 mg kg-1), and A (ammonia) + Se group. The mechanism of ammonia-induced cardiotoxicity and the alleviating effect of L-selenomethionine were examined. The results in the A group showed as follows: a large number of myocardial fiber edema and cytoplasmic bleakness were observed in the heart; a large number of mitochondrial autophagy were observed; ATP content, ATPase activities and hematological parameters decreased significantly; Endoplasmic reticulum stress (ERS) markers (GRP78, IRE1α, ATF4, ATF6, and CHOP) were significantly induced in the mRNA and protein levels; PI3K/AKT/mTOR signaling pathway was activated; and autophagy key genes and proteins (Beclin-1, LC3, ATG3, and ATG5) were significantly up-regulated. The results of comparison between the A + Se group and the A group were as follows: the degree of edema of cardiac muscle fiber in the A + Se group was somewhat relieved; the level of mitochondrial autophagy decreased; ATP content and ATPase activities increased significantly; the mRNA and protein levels of ERS markers were significantly down-regulated; the expression level of PI3K/AKT/mTOR signaling pathway was decreased; and the mRNA and protein levels of key autophagy genes were decreased. However, the changes of these indexes in the A + Se group were still significantly different from those in the C group. Our results indicated that L-selenomethionine supplementation inhibited ammonia-induced cardiac autophagy by activating the PI3K/AKT/mTOR signaling pathway, which confirmed that L-selenomethionine could alleviate the cardiac injury caused by excessive ammonia inhalation to a certain extent. This study aims to enrich the toxicological mechanism of ammonia and provide valuable reference for future intervention of ammonia toxicity.

The use of selenomethionine to reduce ammonia toxicity in porcine spleen by inhibiting endoplasmic reticulum stress and autophagy mediated by oxidative stress.

Ammonia (NH3) is a typical pollutant in the atmosphere and is well known for its harmful effects on plants, animals as well as human health. Previous studies have shown that NH3 exposure can cause damage to immune organs and impaired immune function in animals. Selenomethionine is a kind of organic selenium, which can not only promote the growth and development of the body, but also inhibit the generation of intracellular reactive oxygen species (ROS), and effectively improve the immune function of the body. Therefore, this study evaluated the toxic effect of NH3 exposure on spleen from a new perspective and investigated the protective effect of selenomethionine on ammonia-induced immunotoxicity. Twenty-four Large White*Duroc*Min pigs were randomly assigned to 4 groups: control group, NH3 group, selenium group, and NH3 + selenium group. Our results showed that NH3 inhalation caused autophagy in the pig spleen, a decrease in lymphocytes, and an increase in autophagic vesicles. Also, NH3 exposure led to a decrease in the activity of some antioxidant enzymes (decreased by about 50%) and a significant increase in the expression of genes related to oxidative stress and endoplasmic reticulum stress (ERS). Our results indicated that selenomethionine mitigated ammonia toxicity in pigs (alleviated about 20-55%). In summary, our findings should be of value in providing a theoretical basis for revealing the toxicity of the high-risk gas NH3, and providing a new perspective on the mechanism of Se against toxic substances.

Chiral Photonic Liquid Crystal Films Derived from Cellulose Nanocrystals.

As a nanoscale renewable resource derived from lignocellulosic materials, cellulose nanocrystals (CNCs) have the features of high purity, high crystallinity, high aspect ratio, high Young's modulus, and large specific surface area. The most interesting trait is that they can form the entire films with bright structural colors through the evaporation-induced self-assembly (EISA) process under certain conditions. Structural color originates from micro-nano structure of CNCs matrixes via the interaction of nanoparticles with light, rather than the absorption and reflection of light from the pigment. CNCs are the new generation of photonic liquid crystal materials of choice due to their simple and convenient preparation processes, environmentally friendly fabrication approaches, and intrinsic chiral nematic structure. Therefore, understanding the forming mechanism of CNCs in nanoarchitectonics is crucial to multiple fields of physics, chemistry, materials science, and engineering application. Herein, a timely summary of the chiral photonic liquid crystal films derived from CNCs is systematically presented. The relationship of CNC, structural color, chiral nematic structure, film performance, and applications of chiral photonic liquid crystal films is discussed. The review article also summarizes the most recent achievements in the field of CNCs-based photonic functional materials along with the faced challenges.

Transferable Multilevel Attention Neural Network for Accurate Prediction of Quantum Chemistry Properties via Multitask Learning.

The development of efficient models for predicting specific properties through machine learning is of great importance for the innovation of chemistry and material science. However, predicting global electronic structure properties like Frontier molecular orbital highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels and their HOMO-LUMO gaps from the small-sized molecule data to larger molecules remains a challenge. Here, we develop a multilevel attention neural network, named DeepMoleNet, to enable chemical interpretable insights being fused into multitask learning through (1) weighting contributions from various atoms and (2) taking the atom-centered symmetry functions (ACSFs) as the teacher descriptor. The efficient prediction of 12 properties including dipole moment, HOMO, and Gibbs free energy within chemical accuracy is achieved by using multiple benchmarks, both at the equilibrium and nonequilibrium geometries, including up to 110,000 records of data in QM9, 400,000 records in MD17, and 280,000 records in ANI-1ccx for random split evaluation. The good transferability for predicting larger molecules outside the training set is demonstrated in both equilibrium QM9 and Alchemy data sets at the density functional theory (DFT) level. Additional tests on nonequilibrium molecular conformations from DFT-based MD17 data set and ANI-1ccx data set with coupled cluster accuracy as well as the public test sets of singlet fission molecules, biomolecules, long oligomers, and protein with up to 140 atoms show reasonable predictions for thermodynamics and electronic structure properties. The proposed multilevel attention neural network is applicable to high-throughput screening of numerous chemical species in both equilibrium and nonequilibrium molecular spaces to accelerate rational designs of drug-like molecules, material candidates, and chemical reactions.

The Demand Supply Steady-State Process-Based Multi-Level Spare Parts Optimization.

Spare parts are one of the important components of the equipment comprehensive support system. Spare parts management plays a decisive role in achieving the desired availability with the minimum cost. With the equipment complexity increasing, the price of spare parts has risen sharply. The traditional spare parts management makes the contradiction between fund shortage and spare parts shortage increasingly prominent. Based on the analysis of the multi-echelon and multi-indenture spare parts support model VARI-METRIC (vary multi-echelon technology for recoverable item control, VARI-METRIC), which is widely used by troops and enterprises in various countries, the model is mainly used in high system availability scenarios. However, in the case of low equipment system availability, the accuracy and cost of model inventory prediction are not ideal. This paper proposed the multi-level spare parts optimization model, which is based on the demand-supply steady-state process. It is an analytical model, which is used to solve the low accuracy problem of the VARI-METRIC model in the low equipment system availability. The analytical model is based on the multi-level spare parts support process. The article deduces methods for solving demand rate, demand-supply rate, equipment system availability, and support system availability. The marginal analysis method is used in the model to analyze the spare parts inventory allocation strategy's current based cost and availability optimal value. Finally, a simulation model is established to evaluate and verify the model. Then, the simulation results show that, when the low availability of equipment systems are 0.4, 0.6, the relative errors of the analytical model are 3.54%, 3.86%, and its costs are 0.52, 1.795 million ¥ RMB. The experiment proves that the inventory prediction accuracy of the analytical model is significantly higher than that of the VARI-METRIC model in low equipment system availability. Finally, the conclusion and future research directions are discussed.

Source apportionment of pulping wastewater and application of mechanical vapor recompression: Environmental and economic analyses.

It is expected that low-energy and scientific zero discharge of chemical-mechanical pulping wastewater will be achieved by applying the mechanical vapor recompression (MVR) technology. In this paper, the equal-standard pollution load model was introduced into pulp and paper field to parse the pollution sources for the first time. The results from the source apportionment indicated that the screw press and concentrating were the major pollution unit operations, and their cumulative load ratio reached 92.92%. The further survey demonstrated that the dominating pollution factors in the traditional chemical-mechanical pulping process were Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD5), and Suspended Solids (SS), whose cumulative load ratio was 92.69%. The environmental analysis demonstrated the implementation of MVR technology significantly decreased the pollution load and reduce the pressure of subsequent wastewater treatment. In addition, a further economic performance indicated that the utilization of MVR technology possessed a smaller operating cost of 2.899 $/m3. The result of the given model provides a scientific gist and instruction for the future treatment of water pollutants in the chemical-mechanical pulping process. The MVR technology is conducive for wastewater treatment to minimize environmental effects and costs.