Forests
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2022
·Vol. 13
·期 2
·253
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IF 3.282
Xuan Li,Huijuan Bo,Jialei Zhu,Jiwei Zhang,Jun Hu,Fuyong Mu,Lishui Nie
This study aimed to explore the effects of different additives on tending shreds ofPlatycladus orientalis(L.) Franco. Two different additives (priming 0.2% and common compost 0.2%) combined with C, N, and P adjustment of raw material treatments were tested on the temperature, moisture, EC, pH, lignocellulose degradation rate, nutrient content, and toxicity of compost. Priming made the compost temperature rise rapidly, and the peak temperature of the composting group with priming reached 51 °C. At the end of composting, the moisture in each treatment from high to low was in the order: common compost > priming > C/N, C/P adjustment only > control group. The increase of EC in the treatments with additives was great, and the peak value of EC in the treatment of priming was 1.30 ms·cm−1, which was 3.9 times higher than that of the control group. At the end of composting, the decomposition rate of cellulose in priming compost was 1.7 times higher than that in the control group, and the hemicellulose decomposition rate in the common compost group was 3.2 times higher than that in the control group. By the end of composting, the pH value of the composts in additive treatments was above 7.0, and the pH value of the priming treatment was the highest (7.5). The highest content of organic matter was found in the priming treatment, which was 52%, 1.7 times higher than that in the control group. The total nutrient content (TN + K2O + P2O5) of additive treatments was higher than 5.0%, and the priming treatment was 2.7% higher than that of the control group. By the end of composting, the germination rate and germination index ranged from 88% to 91% and 60% to 81%. Except for the control group, the C/N ratio of other treatments decreased to below 25. Additives can accelerate the decomposition of raw materials, shorten the composting cycle, and improve the quality of composts, and the effect of adding priming is the most significant.Keywords:Platycladus orientalis(L.) Franco;compost;forest stand;Huairou District;nutrient cycling
研究领域:
林业学
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生态学
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DOI
高影响因子
ANALYTICAL CHEMISTRY
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2022
·
IF 8.008
Han Lun Lu,Zhan Min Su,Lei Li,Xuan Li
Detection methods for microbiological aerosols based on single particle mass spectrometry (SPAMS) and a fluorescent aerosol particle sizer (FLAPS) have been developed progressively. However, they encounter interference and inefficiency issues. By merging FLAPS and SPAMS technologies, the majority of inorganic ambient aerosols may be eliminated by the FLAPS, thus resolving SPAMS’ large data volume. SPAMS, on the other hand, may eliminate the secondary fluorescence interference that plagues the FLAPS. With the addition of the enhanced machine learning classifier, it is possible to extract microbial aerosol signals more precisely. In this work, a FLAPS–SPAMS instrument and a Random Forest classifier based on Kendall’s correlation expansion training set approach were built. In addition to analyzing the outdoor microbial proportions, the interference components of non-microbial fluorescent particles were also examined. Results indicate that the fraction of outdoor microbial aerosols in fluorescent particles is 25.72% or roughly 2.57% of total particles. Traditional ART-2A algorithm and semi-empirical feature clustering approaches were used to identify the interference categories of abiotic fluorescent particles, which were mostly constituted of EC/OC, LPG/LNG exhaust, heavy metal organics, nicotine, vinylpyridine, polycyclic aromatic hydrocarbons (PAHs), and polymers, accounting for 68.51% of fluorescent particles.
研究领域:
环境科学
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生物技术
·
分析化学
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DOI
PubMed
高影响因子
CHEMICAL ENGINEERING JOURNAL
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2024
·
IF 13.3
Dechan Lu,Yanping Chen,Longfeng Ke,Zufang Huang,Yudong Lu,Jing Wang
DNA methylation is a promising biomarker for early cancer detection; however, traditional detection methods require bisulfite treatment and nucleic acid amplification, which are costly and impractical for point-of-care use. We propose a facile method that leverages immunoassays and surface-enhanced Raman scattering (SERS) readouts for the multiplex, sensitive, and portable detection of lung cancer-related DNA methylation biomarkers. This approach employs 5-methylcytosine antibody-modified magnetic probes to enrich methylated DNA sequences and uses core–shell nanoparticles with Probe DNA as SERS nanotags for multiplex detection, eliminating the need for bisulfite treatment and nucleic acid amplification. The multiplex SERS immunoassay detects synthetic methylated SHOX2 and RASSF1A with detection limits of 0.52 pM and 0.66 pM, respectively. It shows a strong correlation with quantitative PCR results in analyzing methylated SHOX2 and RASSF1A from cell lines and formalin-fixed paraffin-embedded tissue samples (n = 35). Additionally, the random forest analysis based on methylated SHOX2 and RASSF1A expression distinguishes lung cancer from benign lung diseases with a clinical sensitivity of 96 %, specificity of 90 %, and an AUC value of 0.972. This method offers a significant advancement for DNA methylation research and clinical applications.
研究领域:
癌症生物学
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分子诊断学
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纳米技术
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生物化学
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产品关联
DOI
高影响因子
Analytical Methods
·
2025
·
IF 2.6
Suxuan Li,Ningyang Mao,Cong Chen,Hui Zhao,Xiaoyu Chen,Liusheng Wang,Fuyun Cui,Wenning Feng,Zhiyong Wu
This study employed headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) technology combined with multivariate statistical analysis methods to analyze the flavor compounds in flue-cured tobacco from five different regions in China: Henan, Hunan, Yunnan, Chongqing, and Fujian. A total of 98 volatile aroma compounds were identified through HS-GC-IMS analysis, including esters, ketones, aldehydes, acids, alcohols, heterocyclic compounds, sulfur-containing compounds, other types of compounds, and 8 uncharacterized compounds. Principal Component Analysis (PCA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) were utilized to conduct dimensionality reduction and distinguish the samples, effectively recognizing differences in volatile compounds among tobacco leaves from various origins. A Random Forest (RF) classification model was constructed, and its reliability was validated through ROC (Receiver Operating Characteristic) analysis, achieving an AUC (Area Under the Curve) value of 0.980, which demonstrates exceptional predictive performance. PCA revealed distinct separations of tobacco leaf samples from different regions on the PCA score plot, and OPLS-DA analysis further validated these differences and confirmed the model's validity through permutation testing. Twenty key aroma compounds with VIP > 1.0 were screened by integrating OPLS-DA with the Random Forest classification model. These compounds showed significant differences in content among different samples, suggesting their potential as chemical markers for distinguishing the origin of flue-cured tobacco. This study not only provides a new method for identifying volatile compounds in tobacco but also offers novel insights into the geographical identification of flue-cured tobacco.
研究领域:
分析化学
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食品科学
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植物学
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化学计量学
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农业科学
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产品关联
DOI
PubMed
高影响因子
SENSORS AND ACTUATORS B-CHEMICAL
·
2025
·
IF 7.7
Sheng Huang,Xiangyi Bai,Zhenyu Xu,Li Meng,Shasha Gao,Lei Zhu,Qiuchen Yu,Man-Kay Law
To address the limitations of traditional blood glucose monitoring in industrial environments, this study presents a charge transfer-enhanced glucose sensor based on organic electrochemical transistor, utilizing a carboxymethyl cellulose-modified PEDOT:PSS with aminated multi-walled carbon nanotubes/gold nanoparticles composite film. The sensor is integrated with superabsorbent polymer composites for non-invasive breath analysis. Molecular electrostatic potential calculations reveal that hydrogen-bond networks between carboxymethyl cellulose carboxyl groups and glucose hydroxyl moieties, together with π-π interactions of glucose molecules at the composite surface, enhance interfacial charge transfer efficiency by 2.5 % (0.236e→0.242e). Structural characterization confirms a honeycomb-like porous architecture (0.5–2 μm pore size) formed via carboxymethyl cellulose-mediated hydrogen bonding, accelerating glucose diffusion while suppressing interferent adsorption (response<1 %). The composite's three-dimensional conductive network combines PEDOT:PSS (p-type pathways), carbon nanotubes (surface area expansion) and gold nanoparticles (catalytic sites), achieving a linear detection range of 2–22 μmol·L⁻¹ (extendable up to 9 mM) in exhaled breath condensate with 56.656 μA·(mmol·L⁻¹·cm²)⁻¹ sensitivity, 0.2 μmol·L⁻¹ detection limit (S/N = 23.8), and < 4.8 s response time. The sensor-integrated facemask platform uses superabsorbent polymer to maintain 100 % relative humidity, stabilizing the electrolyte layer for real-time monitoring. Machine learning (random forest classifier processing 18 time-frequency features from transistor outputs) achieves 87.5 % accuracy in resolving glucose fluctuations. This work demonstrates the integration of hierarchical materials, interfacial charge control, and algorithmic processing for wearable biosensors in health monitoring.
研究领域:
生物传感器
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有机电子学
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纳米技术
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分析化学
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可穿戴设备
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生物医学工程
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高分子科学
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机器学习
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健康监测
✓ 已验证
产品关联
DOI
高影响因子
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