Retrofit and application of pulverized coal burners with LNG and oxygen ignition in utility boiler under ultra-low load operation.

An oxygen-rich and low NOx burner integrated with liquefied natural gas (LNG) was proposed to address unstable combustion and high NOx emissions from a 330 MW subcritical boiler under ultra-low load operation in China. To assess the effectiveness of the retrofit, Chemkin and Fluent softwares were utilized to construct a new NOx model and calculate NOx generation, based on the combustion of pulverized coal gas and LNG. Further, an eddy dissipation concept (EDC) model, which can reflect detailed chemical reactions, was applied to calculate gas-phase reactions in the furnace. The results showed that when performing the deep peak shaving after the retrofit, the combustion in the furnace was stable under 50% or more load, and NOx emission level at the furnace outlet was lower than 350 mg/m3 (6% O2 content, dry basis). Under 25% load, the oxygen-rich burner integrated with LNG was applied, and the pulverized coal flow entered the furnace in a state of high-intensity combustion, which effectively promoted the stability of combustion in the furnace. The reductive combustion state with reductive free radicals generated by LNG decomposition inhibited NOx formation. Consequently, NOx emissions from the furnace outlet decreased from 380 mg/m3 to 316 mg/m3.

Developing a machine learning model for accurate nucleoside hydrogels prediction based on descriptors.

Supramolecular hydrogels derived from nucleosides have been gaining significant attention in the biomedical field due to their unique properties and excellent biocompatibility. However, a major challenge in this field is that there is no model for predicting whether nucleoside derivative will form a hydrogel. Here, we successfully develop a machine learning model to predict the hydrogel-forming ability of nucleoside derivatives. The optimal model with a 71% (95% Confidence Interval, 0.69-0.73) accuracy is established based on a dataset of 71 reported nucleoside derivatives. 24 molecules are selected via the optimal model external application and the hydrogel-forming ability is experimentally verified. Among these, two rarely reported cation-independent nucleoside hydrogels are found. Based on their self-assemble mechanisms, the cation-independent hydrogel is found to have potential applications in rapid visual detection of Ag+ and cysteine. Here, we show the machine learning model may provide a tool to predict nucleoside derivatives with hydrogel-forming ability.

A Self-Assembled 3D Model Demonstrates How Stiffness Educates Tumor Cell Phenotypes and Therapy Resistance in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense and stiff extracellular matrix (ECM) associated with tumor progression and therapy resistance. To further the understanding of how stiffening of the tumor microenvironment (TME) contributes to aggressiveness, a three-dimensional (3D) self-assembling hydrogel disease model is developed based on peptide amphiphiles (PAs, PA-E3Y) designed to tailor stiffness. The model displays nanofibrous architectures reminiscent of native TME and enables the study of the invasive behavior of PDAC cells. Enhanced tuneability of stiffness is demonstrated by interacting thermally annealed aqueous solutions of PA-E3Y (PA-E3Yh) with divalent cations to create hydrogels with mechanical properties and ultrastructure similar to native tumor ECM. It is shown that stiffening of PA-E3Yh hydrogels to levels found in PDAC induces ECM deposition, promotes epithelial-to-mesenchymal transition (EMT), enriches CD133+/CXCR4+ cancer stem cells (CSCs), and subsequently enhances drug resistance. The findings reveal how a stiff 3D environment renders PDAC cells more aggressive and therefore more faithfully recapitulates in vivo tumors.

Frequency and time dependent viscoelastic characterization of pediatric porcine brain tissue in compression.

Understanding the viscoelastic behavior of pediatric brain tissue is critical to interpret how external mechanical forces affect head injury in children. However, knowledge of the viscoelastic properties of pediatric brain tissue is limited, and this reduces the biofidelity of developed numeric simulations of the pediatric head in analysis of brain injury. Thus, it is essential to characterize the viscoelastic behavior of pediatric brain tissue in various loading conditions and to identify constitutive models. In this study, the pediatric porcine brain tissue was investigated in compression with determine the viscoelasticity under small and large strain, respectively. A range of frequencies between 0.1 and 40 Hz was applied to determine frequency-dependent viscoelastic behavior via dynamic mechanical analysis, while brain samples were divided into three strain rate groups of 0.01/s, 1/s and 10/s for compression up to 0.3 strain level and stress relaxation to obtain time-dependent viscoelastic properties. At frequencies above 20 Hz, the storage modulus did not increase, while the loss modulus increased continuously. With strain rate increasing from 0.01/s to 10/s, the mean stress at 0.1, 0.2 and 0.3 strain increased to approximate 6.8, 5.6 and 4.4 times, respectively. The brain compressive response was sensitive to strain rate and frequency. The characterization of brain tissue will be valuable for development of head protection systems and prediction of brain injury.

Identification of the toxin components of Rhizoctonia solani AG1-IA and its destructive effect on plant cell membrane structure.

Rice sheath blight is a fungal disease caused mainly by Rhizoctonia solani AG1-IA. Toxins are a major pathogenic factor of R. solani, and some studies have reported their toxin components; however, there is no unified conclusion. In this study, we reported the toxin components and their targets that play a role in R. solani AG1-IA. First, toxins produced by R. solani AG1-IA were examined. Several important phytotoxins, including benzoic acid (BZA), 5-hydroxymethyl-2-furanic aid (HFA), and catechol (CAT), were identified by comparative analysis of secondary metabolites from AG1-IA, AG1-IB, and healthy rice. Follow-up studies have shown that the toxin components of this fungus can rapidly disintegrate the biofilm structure while maintaining the content of host plant membrane components, thereby affecting the organelles, which may also explain the lack of varieties highly resistant to sheath blight.

Potential of lncRNAs to regulate cuproptosis in hepatocellular carcinoma: Establishment and validation of a novel risk model.

Cuproptosis, a distinct form of programmed cell death, is an emerging field in oncology with promising implications. This novel mode of cell death has the potential to become a regulatory target for tumor therapy, thus expanding the currently limited treatment options available for patients with cancer. Our research team focused on investigating the role of functional long non-coding RNA (lncRNAs) in hepatocellular carcinoma (HCC). We were particularly intrigued by the potential implications of HCC-lncRNAs on cuproptosis. Through a comprehensive analysis, we identified three cuproptosis-related lncRNAs (CRLs): AC018690.1, AL050341.2, and LINC02038. These lncRNAs were found to influence the sensitivity of HCC to cuproptosis. Based on our results, we constructed a risk model represented by the equation: risk score = 0.82 * AC018690.1 + 0.65 * AL050341.2 + 0.61 * LINC02038. Notably, significant disparities were observed in clinical features, such as the response rate to immunotherapy and targeted therapy, as well as in cellular characteristics, including the composition of the tumor immune microenvironment (TIME), when comparing the high- and low-risk groups. Most importantly, knockdown of these CRLs was confirmed to significantly weaken the resistance to cuproptosis in HCC. This effect resulted from the accelerated accumulation of lipoacylated-DLAT and lipoacylated-DLST. In summary, we identified three CRLs in HCC and established a novel risk model with potential clinical applications. Additionally, we proposed a potential therapeutic method consisting of sorafenib-copper ionophores-immunotherapy.

The clinical implication and translational research of OSCC differentiation.

BACKGROUND: The clinical value and molecular characteristics of tumor differentiation in oral squamous cell carcinoma (OSCC) remain unclear. There is a lack of a related molecular classification prediction system based on pathological images for precision medicine. METHODS: Integration of epidemiology, genomics, experiments, and deep learning to clarify the clinical value and molecular characteristics, and develop a novel OSCC molecular classification prediction system. RESULTS: Large-scale epidemiology data (n = 118,817) demonstrated OSCC differentiation was a significant prognosis indicator (p < 0.001), and well-differentiated OSCC was more chemo-resistant than poorly differentiated OSCC. These results were confirmed in the TCGA database and in vitro. Furthermore, we found chemo-resistant related pathways and cell cycle-related pathways were up-regulated in well- and poorly differentiated OSCC, respectively. Based on the characteristics of OSCC differentiation, a molecular grade of OSCC was obtained and combined with pathological images to establish a novel prediction system through deep learning, named ShuffleNetV2-based Molecular Grade of OSCC (SMGO). Importantly, our independent multi-center cohort of OSCC (n = 340) confirmed the high accuracy of SMGO. CONCLUSIONS: OSCC differentiation was a significant indicator of prognosis and chemotherapy selection. Importantly, SMGO could be an indispensable reference for OSCC differentiation and assist the decision-making of chemotherapy.

Periodontitis and the risk of all-cause and cause-specific mortality among US adults with diabetes: A population-based cohort study.

AIM: To evaluate the association between periodontitis, all-cause and cause-specific mortality, and its prognostic utility among adults with diabetes. MATERIALS AND METHODS: Periodontal health records were retrieved from the NHANES database for 4297 participants with diabetes aged >30 years at baseline during 1988-1994, 1999-2004 and 2009-2014. Multivariable Cox proportional hazards regression model was applied to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) for moderate/severe periodontitis with all-cause and cause-specific mortality in participants with diabetes. Area under the curve (AUC) was used to assess predictive value. RESULTS: During a median follow-up of 15.41 years, 1701 deaths occurred. After multivariate adjustments, moderate/severe periodontitis was significantly associated with increased risk of all-cause (HR: 1.27; 95% CI: 1.07-1.50; p = .005) and cardiovascular disease (CVD)-related (HR: 1.35, 95% CI: 1.03-1.76, p = .031) mortality in participants with diabetes. The absolute risk difference based on the cumulative incidence information was 0.022 (5-year, 95% CI: 0.021-0.023) and 0.044 (10-year, 95% CI: 0.041-0.048). Periodontitis improved the prediction of all-cause (AUC: 0.652; 95% CI: 0.627-0.676) and CVD-related (AUC: 0.649; 95% CI: 0.624-0.676) mortality over standard risk factors (all-cause: AUC: 0.631; 95% CI: 0.606-0.656; CVD-related: AUC: 0.629; 95% CI: 0.604-0.655). CONCLUSIONS: Moderate/severe periodontitis is associated with an increased risk of all-cause and CVD-related mortality in adults with diabetes. Periodontitis might represent a marker for residual risk.

Association between periodontitis and mortality of patients with cardiovascular diseases: A cohort study based on NHANES.

BACKGROUND: The association between periodontitis and cardiovascular disease (CVD) has been widely explored, but little is known about the effect of periodontitis on the mortality of CVD patients. This study aims to clarify the effect of periodontitis on all-cause and cause-specific mortality of CVD patients. METHODS: We included 2,135 individuals with CVD from the National Health and Nutrition Examination Survey. Mortality data were ascertained by linkage to National Death Index records through 31 December 2019. We used Cox proportional hazards models for all-cause mortality and competing risk models for CVD and cancer mortality to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Further covariate adjustments, stratification analyses, and a variety of sensitivity analyses were conducted to test the reliability and robustness of the results. RESULTS: The all-cause mortality in CVD patients with moderate/severe periodontitis was significantly higher than in those with no/mild periodontitis (HR: 1.25; 95% CI: 1.02-1.52; P = 0.03). The all-cause mortality in participants with severe clinical attachment loss was significantly higher (HR: 1.07; 95% CI: 1.01-1.14; P = 0.01). However, no discrepancy in CVD or cancer mortality was observed between CVD patients with different periodontal status. CONCLUSIONS: Our findings from a longitudinal study with a large sample indicated significant but slightly higher all-cause mortality in CVD patients with moderate/severe periodontitis than in those with no/mild periodontitis.

Co3X8 (X = Cl and Br): multiple phases and magnetic properties of the Kagome lattice.

The unique magnetic properties of two-dimensional (2D) materials have demonstrated huge potential for applications in nanodevices and spintronics. In this work, we propose a new Kagome lattice, Co3X8 (X = Cl and Br), based on density functional theory (DFT) calculation. We find that Co/X in Co3X8 has spontaneous movement in the lattice, resulting in 156- and 12-phases of Co3X8 and diverse magnetic and electronic properties. We show that the magnetic and electronic properties of Co3X8 can be engineered by strain, and the magnetic properties of Co3X8 are highly related to the spontaneous movement of X. Moreover, the transmission property of 12-Co3X8 shows clear angle-dependent features due to the symmetry breaking as caused by the spontaneous movement of X. Our findings may provide not only a possible Kagome lattice with unique properties, but also a strategy for designing nanodevices and for spintronics.

Zn-induced formation of polymetallic carbonate hydroxide cathodes with high mass loading for high performance aqueous alkaline Zn-based batteries.

Developing high mass loading cathodes with high capacity and durable life cycles is greatly worthwhile and challenging for alkaline aqueous rechargeable Zn-based batteries (AAZBs). Herein, we demonstrate an efficient zinc-induced strategy to rationally develop Zn-Ni-Co carbonate hydroxides/hydroxides heterostructure nanosheet array with an extremely high mass loading of 9.2 mg cm-2 on Ni foam (ZNC/NF) as such a superior cathode for AAZBs. It is discovered that Ni-Co hydroxide nanowires can be transformed into Zn-Ni-Co carbonate hydroxides/hydroxides heterostructure nanosheet with rich defect structures after the introduction of Zn during the synthetic process. The formed heterostructures and rich defect structures can enhance ion and electron transfer efficiency, thus ensuring the excellent electrochemical performance under high loading condition. Consequently, the ZNC/NF//Zn battery shows an outstanding areal capacity of 2.1 mAh cm-2 at 5 mA cm-2, with an ultrahigh energy density of 3.6 mWh cm-2. Moreover, the battery can still retain a high capacity of 0.42 mAh cm-2 after 5000 cycles at 50 mA cm-2, suggesting strong long-term cycling stability. This research enables pave the way for the rational design and manufacture of advanced electrode materials with large mass loadings.

Automatic Chinese Food recognition based on a stacking fusion model.

With commercialization of deep learning models, daily precision dietary record based on images from smartphones becomes possible. This study took advantage of Deep-learning techniques on visual recognition tasks and proposed a big-data-driven Deep-learning model regressing from food images. We established the largest data set of Chinese dishes to date, named CNFOOD-241. It contained more than 190,000 images with 241 categories, covering Staple food, meat, vegetarian diet, mixed meat and vegetables, soups, dessert category. This study also compares the prediction results of three popular deep learning models on this dataset, ResNeXt101_32x32d achieving up to 82.05% for top-1 accuracy and 97.13% for top-5 accuracy. Besides, this paper uses a multi-model fusion method based on stacking in the field of food recognition for the first time. We built a meta-learner after the base model to integrate the three base models of different architectures to improve robustness. The accuracy achieves 82.88% for top-1 accuracy.Clinical Relevance-This study proves that the application of artificial intelligence technology in the identification of Chinese dishes is feasible, which can play a positive role in people who need to control their diet, such as diabetes and obesity.

The search for a maximum of the D-π-A paradigm for second order nonlinear optical molecular materials.

Push-pull π-conjugated molecules are one of the paradigms of second order nonlinear optical (NLO) materials and have been extensively explored. However, high-performance second order NLO materials with an optimum electron donor (D), π-bridge (π) and acceptor (A) under this paradigm are still the most sought-after. In the present work, D-π-A molecules with optimal D, π and A combination for strong second order NLO properties are proposed based on molecular orbital theories. The optimal D-π-A push-pull molecule achieves an unprecedentedly strong NLO response under the D-π-A paradigm, i.e., the static first hyperpolarizability reaches -453.92 × 10-30 esu per heavy atom using azulene as part of the π-bridge and acceptor to synergistically reinforce the strength of the acceptor. The protocols of D-π-A NLO molecule design through frontier molecular orbital matching of D, π and A with optimal combination of electron donating and accepting strengths shed light on future molecular NLO materials exploration. The simulated two-dimensional second order spectra provide useful information (e.g., sum frequency generation) on the applications of those D-π-A push-pull molecules in nonlinear optics.

Narrative Review: The FDA's Perfunctory Approach of Dietary Supplement Regulations Giving Rise to Copious Reports of Adverse Events.

Background: The Food and Drug Administration (FDA) originated from the passage of the 1906 Pure Food and Drugs act aimed to rein in the long-standing abuse in the consumer product marketplace. The act was passed to prohibit interstate commerce of misbranded and adulterated foods, drinks, drugs. Thus, promoting the FDA's mission to protect the public health by regulating human and veterinary drugs, biological products, medical devices, food supply, cosmetics, and tobacco to ensure safety, efficacy, and security. Progressing further in 1994, the Dietary Supplement Health and Education Act (DSHEA) was established designating specific label requirements, providing regulatory framework, and authorizing the FDA to promulgate good manufacturing practices for dietary supplements. This act defined and classified "dietary supplements" and "dietary ingredients" as food requiring all over the counter products (OTC) products to consist of labeling that is easy to understand and meets the FDA quality, effectiveness, and safety standards. However, under the umbrella of OTC products, the FDA fell short in its regulation of the expansive dietary supplement market. The objective of this study is to discern how the lack of efficacy in the FDA's regulations of OTC dietary supplements inevitably inspired more harm than benefit. Methods: This review comprised of case studies including young adolescents and adult consumers who experienced adverse events from the use of dietary supplements. Products which showed highest prevalence in adverse event reports through the Food and Drug Administration CFSAN Adverse Event Reporting System (CAERS) included but not limited to; Vitamin E (vitamin derivative), Beta-sitosterol (plant sterol) Yohimbine, Kava Kava Kratom, Garcinia Cambogia, (herbal products) and OxyElite Pro (marketed weight loss product). The primary endpoint was evaluating the FDA's regulations on dietary supplement safety protocols. The secondary endpoint was assessing the actions of the FDA in response to these case events. Results: Overall, between 2004 to 2021, a total of 79,071 adverse events related to the use of dietary supplements were reported to the Center for Food Safety and Applied Nutrition. Vitamin E products for example, marketed for decades for their antioxidant benefits in turn have shown significant evidence of toxicity and an increased risk of bleeding outweighing its potential benefit. The FDA's response was simply implementing a label guideline update, yet this update had evidence of minimal effect as the number of cases gradually continued to increase. Likewise, herbal products such as Kava Kava, Yohimbine, Kratom, and Garcinia Cambogia, in addition to weight regulating products, such as OxyElite Pro and HydroxyCut, have been linked to organ failure, hepatic, renal, cardiac toxicity, and death respectively. The FDA merely responded through instating public consumer warnings of their effects with consumption and limited recalls of certain products. Conclusion: With the easy accessibility of these products, the general public is more inclined to its use without proper guidance and monitoring from their healthcare team, posing as a major concern for possible interactions, contraindications and unfavorable outcomes. With proper implementation of stringent regulations post findings from increased studies on efficacy and safety, cases of adverse events could have been reduced significantly or averted completely. The FDA's minimalistic efforts consisting of only post-marketing monitoring and retrospective actions of label modifying have time and time again shown flaws as seen in the growing series of reports. By emending the over-the-counter supplement review process to reflect that of prescription medication, the magnitude of adverse events can be diminished. The process should include preclinical research in addition to clinical research, FDA thorough examination of data prior approval and post marketing surveillance.

Biomechanical effects of osteoporosis severity on the occurrence of proximal junctional kyphosis following long-segment posterior thoracolumbar fusion.

BACKGROUND: Proximal junctional kyphosis is a common long-term complication in adult spinal deformity surgery that involves long-segment posterior spinal fusion. However, the underlying biomechanical mechanisms of the impact of osteoporosis on proximal junctional kyphosis remain unclear. The present study was to evaluate adjacent segment degeneration and spine mechanical instability in osteoporotic patients who underwent long-segment posterior thoracolumbar fusion. METHODS: Finite element models of the thoracolumbar spine T1-L5 with posterior long-segment T8-L5 fusion under different degrees of osteoporosis were constructed to analyze intervertebral disc stress characterization, vertebrae mechanical transfer, and pedicle screw system loads during various motions. FINDINGS: Compared with normal bone mass, the maximum von Mises stresses of T7 and T8 were increased by 20.32%, 22.38%, 44.69%, 4.49% and 29.48%, 17.84%, 40.95%, 3.20% during flexion, extension, lateral bending, and axial rotation in the mild osteoporosis model, and by 21.21%, 18.32%, 88.28%, 2.94% and 37.76%, 15.09%, 61.47%, -0.04% in severe osteoporosis model. The peak stresses among T6/T7, T7/T8, and T8/T9 discs were 14.77 MPa, 11.55 MPa, and 2.39 MPa under lateral bending conditions for the severe osteoporosis model, respectively. As the severity of osteoporosis increased, stress levels on SCR8 and SCR9 intensified during various movements. INTERPRETATION: Osteoporosis had an adverse effect on proximal junctional kyphosis. The stress levels in cortical bone, intervertebral discs and screws were increased with bone mass loss, which can easily lead to intervertebral disc degeneration, bone destruction as well as screw pullout. These factors have significantly affected or accelerated the occurrence of proximal junctional kyphosis.

Immunogenicity and Safety of a SARS-CoV-2 Inactivated Vaccine KCONVAC in Chinese Children: Randomized, Double-blind, Placebo-controlled Phase 1 and 2 Trials.

BACKGROUND: It is important to extend the indication of severe acute respiratory syndrome coronavirus 2 vaccine to children to improve the vaccine intake rate and reduce infection in this population. METHODS: In 2 phase 1 and phase 2 randomized, double-blind and placebo-controlled trials, 84 and 480 Chinese healthy children 3 to 17 years old were enrolled, respectively, and randomized in 3:1 ratio to receive 2 doses of a severe acute respiratory syndrome coronavirus 2 inactivated vaccine, KCONVAC or placebo. The 2 doses were given 28 days apart. Adverse events (AEs) were recorded through Day 28 after each dosing. Live virus neutralizing antibody and receptor binding domain antibody (RBD-IgG) were tested before vaccination and after the second dose. RESULTS: Two doses of the vaccine, KCONVAC, elicited geometric mean titers of 142-150 for neutralizing antibody and 4154-4253 for RBD-IgG 28 days after the second dose. Seroconversion rates were 100% after 2 doses for both antibodies in both trials. The predominant AEs were injection-site pain, cough and fever. Most AEs were grade 1 or 2 in intensity. Five participants reported 6 vaccination-unrelated serious AEs in the phase 2 trial. CONCLUSIONS: Two doses of this study vaccine, KCONVAC, were well tolerated and immunogenic in children 3 to 17 years of age.

Associations of periodontitis with risk of all-cause and cause-specific mortality among us adults with chronic kidney disease.

OBJECTIVES: To investigate the associations of periodontitis with risk of all-cause and cause-specific mortality in a nationally representative sample of adults with chronic kidney disease (CKD) in the United States. METHODS: This prospective cohort study included 4,271 individuals aged ≥30 years at baseline with CKD participants in the National Health and Nutrition Examination Survey (NHANES) during 1988-1994, 1999-2004, and 2009-2014. CKD was defined as an estimated glomerular filtration rate (eGFR) <60 ml/min/1.73m2 and/or urinary albumin/creatinine ratio (uACR) ≥30 mg/g. Multivariate cox proportional hazards regression models were used to estimate the hazard ratios (HRs) and 95 % confidence intervals (CIs) of all-cause and cause-specific mortality in participants with CKD according to periodontitis. The associations of the quartiles of mean clinical attachment loss (CAL) and mean periodontal probing depth (PPD) levels with mortality were examined using the first quartile as the reference group. RESULTS: During a median of 8.67 years of follow-up, 2,146 deaths were documented. After multivariate adjustments, moderate/severe periodontitis was significantly associated with all-cause (HR:1.28; 95 % CI:1.11-1.47; P = 0.001) and cardiovascular disease (CVD)-related mortality (HR:1.44; 95 % CI:1.14-1.81; P = 0.002) in participants with CKD. Compared with the reference group of mean CAL and mean PPD levels, all-cause (CAL: HR, 1.58; 95 % CI, 1.32-1.89, P <0.001; PPD: HR, 1.35, 95 % CI, 1.09-1.67, P = 0.011) and CVD-related mortality (CAL: HR, 1.70, 95 % CI, 1.21-2.40, P = 0.001) were increased for participants in the highest quartile. CONCLUSIONS: This study suggests that moderate/severe periodontitis and high levels of mean CAL and mean PPD are associated with an increased risk of all-cause mortality, and moderate/severe periodontitis and mean CAL associated with CVD-related mortality among adults with CKD in the US. CLINICAL SIGNIFICANCE: This study details the association between periodontitis and the increased risk of all-cause mortality and CVD-related mortality in a large, representative sample of adults with CKD.

Clonal Propagation and Assessment of Biomass Production and Saponin Content of Elite Accessions of Wild Paris polyphylla var. yunnanensis.

Paris polyphylla var. yunnanensis is an endangered medicinal plant endemic to China with great economic importance for the pharmaceutical industry. Two significant barriers to its commercial development are the long duration of its seed germination and the frequency of interspecific hybridization. We developed a method for clonal propagation of Paris polyphylla var. yunnanensis and successfully applied it to selected elite wild plants, which could become cultivar candidates based on their biomass production and saponin content. In comparison to the traditional method, somatic embryogenesis produced an average of 63 somatic embryos per gram of callus in just six weeks, saving 12 to 15 months in plantlet production. The produced in vitro plantlets were strong and healthy and 94% survived transplanting to soil. Using this method, four candidate cultivars with diverse morphologies and geographic origins were clonally reproduced from selected elite wild accessions. In comparison to those obtained with the traditional P. polyphylla propagation technique, they accumulated higher biomass and polyphyllin levels in rhizomes plus adventitious roots during a five-year period. In conclusion, somatic embryogenesis-based methods offer an alternate approach for the rapid and scaled-up production of P. polyphylla, as well as opening up species conservation options.

Strain-dependent magnetic ordering switching in 2D AFM ternary V-based chalcogenide monolayers.

The lack of macroscopic magnetic moments makes antiferromagnetic materials promising candidates for high-speed spintronic devices. The 2D ternary V-based chalcogenides (VXYSe4; X, Y = Al, Ga) monolayers are investigated based on the density-functional theory and Monte Carlo simulations. The results reveal that the Néel temperature of the VGa2Se4 monolayer is 18 K with zigzag2-antiferromagnetic (AFM) spin ordering. Also, the magnetic ordering of V ions in VAl2Se4 and VAlGaSe4 monolayers prefer zigzag1-AFM coupling with Néel temperature of 47 K and 33 K, respectively. The magnetic anisotropy calculations demonstrate that the easy magnetization axis of the VXYSe4 monolayers is parallel to the y axis. In addition, the VXYSe4 monolayers can be adjusted from the AFM state to the ferromagnetic (FM) state under biaxial stretching, which can be attributed to the competition between d-p-d superexchange and d-d direct exchange caused by the variation of bond length. The transition temperature of VXYSe4 monolayers can be elevated above room temperature with the help of compression strain. In particular, the in-plane magnetic anisotropy is a robust characteristic regardless of the magnitude of the applied biaxial strain. These explorations not only enrich the family of AFM monolayers with excellent stability but also provide distinctive ideas for the performance control of AFM materials and their applications in nanodevices.

Humoral immune disorders affect clinical outcomes of oral lichen planus.

OBJECTIVES: The molecular characteristics of oral lichen planus (OLP) are still unclear, and it is not possible to distinguish the clinical outcome of OLP patients in a short period of time for follow-up. Here, we investigate the molecular characteristics of lesions in patients with stable lichen planus (SOLP) and recalcitrant erosive oral lichen planus (REOLP). METHODS: Our clinical follow-up cohort was split into SOLP and REOLP groups based on the follow-up clinical data. The core modules associated with the clinical information were identified by weighted gene co-expression network analysis (WGCNA). The OLP cohort samples were divided into two groups by molecular typing, and a prediction model for OLP was created by training neural networks with the neuralnet package. RESULTS: We screened 546 genes in five modules. After doing a molecular type of OLP, it was determined that B cells might have a significant impact on the clinical outcome of OLP. In addition, by means of machine learning, a prediction model was developed to predict the clinical regression of OLP with greater accuracy than the existing clinical diagnostic. CONCLUSIONS: Our study revealed humoral immune disorders may make an important contribution to the clinical outcome of OLP.