SeFilter-DIA: Squeeze-and-Excitation Network for Filtering High-Confidence Peptides of Data-Independent Acquisition Proteomics.

Mass spectrometry is crucial in proteomics analysis, particularly using Data Independent Acquisition (DIA) for reliable and reproducible mass spectrometry data acquisition, enabling broad mass-to-charge ratio coverage and high throughput. DIA-NN, a prominent deep learning software in DIA proteome analysis, generates peptide results but may include low-confidence peptides. Conventionally, biologists have to manually screen peptide fragment ion chromatogram peaks (XIC) for identifying high-confidence peptides, a time-consuming and subjective process prone to variability. In this study, we introduce SeFilter-DIA, a deep learning algorithm, aiming at automating the identification of high-confidence peptides. Leveraging compressed excitation neural network and residual network models, SeFilter-DIA extracts XIC features and effectively discerns between high and low-confidence peptides. Evaluation of the benchmark datasets demonstrates SeFilter-DIA achieving 99.6% AUC on the test set and 97% for other performance indicators. Furthermore, SeFilter-DIA is applicable for screening peptides with phosphorylation modifications. These results demonstrate the potential of SeFilter-DIA to replace manual screening, providing an efficient and objective approach for high-confidence peptide identification while mitigating associated limitations.

A noval pulmonary function evaluation method based on ResNet50 + SVR model and cough.

Traditionally, the clinical evaluation of respiratory diseases was pulmonary function testing, which can be used for the detection of severity and prognosis through pulmonary function parameters. However, this method is limited by the complex process, which is impossible for patients to monitor daily. In order to evaluate pulmonary function parameters conveniently with less time and location restrictions, cough sound is the substitute parameter. In this paper, 371 cough sounds segments from 150 individuals were separated into 309 and 62 as the training and test samples. Short-time Fourier transform (STFT) was applied to transform cough sound into spectrogram, and ResNet50 model was used to extract 2048-dimensional features. Through support vector regression (SVR) model with biological attributes, the data were regressed with pulmonary function parameters, FEV1, FEV1%, FEV1/FVC, FVC, FVC%, and the performance of this models was evaluated with fivefold cross-validation. Combines with deep learning and machine learning technologies, the better results in the case of small samples were achieved. Using the coefficient of determination (R2), the ResNet50 + SVR model shows best performance in five basic pulmonary function parameters evaluation as FEV1(0.94), FEV1%(0.84), FEV1/FVC(0.68), FVC(0.92), and FVC%(0.72). This ResNet50 + SVR hybrid model shows excellent evaluation of pulmonary function parameters during coughing, making it possible to realize a simple and rapid evaluation for pneumonia patients. The technology implemented in this paper is beneficial in judge the patient's condition, realize early screening of respiratory diseases, evaluate postoperative disease changes and detect respiratory infectious diseases without time and location restrictions.

MRI advances in the imaging diagnosis of tuberculous meningitis: opportunities and innovations.

Tuberculous meningitis (TBM) is not only one of the most fatal forms of tuberculosis, but also a major public health concern worldwide, presenting grave clinical challenges due to its nonspecific symptoms and the urgent need for timely intervention. The severity and the rapid progression of TBM underscore the necessity of early and accurate diagnosis to prevent irreversible neurological deficits and reduce mortality rates. Traditional diagnostic methods, reliant primarily on clinical findings and cerebrospinal fluid analysis, often falter in delivering timely and conclusive results. Moreover, such methods struggle to distinguish TBM from other forms of neuroinfections, making it critical to seek advanced diagnostic solutions. Against this backdrop, magnetic resonance imaging (MRI) has emerged as an indispensable modality in diagnostics, owing to its unique advantages. This review provides an overview of the advancements in MRI technology, specifically emphasizing its crucial applications in the early detection and identification of complex pathological changes in TBM. The integration of artificial intelligence (AI) has further enhanced the transformative impact of MRI on TBM diagnostic imaging. When these cutting-edge technologies synergize with deep learning algorithms, they substantially improve diagnostic precision and efficiency. Currently, the field of TBM imaging diagnosis is undergoing a phase of technological amalgamation. The melding of MRI and AI technologies unquestionably signals new opportunities in this specialized area.

The diagnosis of tuberculous meningitis: advancements in new technologies and machine learning algorithms.

Tuberculous meningitis (TBM) poses a diagnostic challenge, particularly impacting vulnerable populations such as infants and those with untreated HIV. Given the diagnostic intricacies of TBM, there's a pressing need for rapid and reliable diagnostic tools. This review scrutinizes the efficacy of up-and-coming technologies like machine learning in transforming TBM diagnostics and management. Advanced diagnostic technologies like targeted gene sequencing, real-time polymerase chain reaction (RT-PCR), miRNA assays, and metagenomic next-generation sequencing (mNGS) offer promising avenues for early TBM detection. The capabilities of these technologies are further augmented when paired with mass spectrometry, metabolomics, and proteomics, enriching the pool of disease-specific biomarkers. Machine learning algorithms, adept at sifting through voluminous datasets like medical imaging, genomic profiles, and patient histories, are increasingly revealing nuanced disease pathways, thereby elevating diagnostic accuracy and guiding treatment strategies. While these burgeoning technologies offer hope for more precise TBM diagnosis, hurdles remain in terms of their clinical implementation. Future endeavors should zero in on the validation of these tools through prospective studies, critically evaluating their limitations, and outlining protocols for seamless incorporation into established healthcare frameworks. Through this review, we aim to present an exhaustive snapshot of emerging diagnostic modalities in TBM, the current standing of machine learning in meningitis diagnostics, and the challenges and future prospects of converging these domains.

Anthocyanins Profiling Analysis and RNA-Seq Revealed the Dominating Pigments and Coloring Mechanism in Cyclamen Flowers.

Pigments in cyclamen (Cyclamen purpurascens) endows flowers with great ornamental and medicinal values. However, little is known about the biosynthetic pathways of pigments, especially anthocyanins, in cyclamen flowers. Herein, anthocyanins profiling and RNA-Seq were used to decipher the molecular events using cyclamen genotypes of red (HXK) or white (BXK) flowers. We found that red cyclamen petals are rich in cyanidin-3-O-rutinoside, cyanidin-3-O-glucoside, delphinidin-3-O-glucoside, malvidin-3-O-glucoside, peonidin-3-O-rutinoside, quercetin-3-O-glucoside, and ruti. In addition, our transcriptomics data revealed 3589 up-regulated genes and 2788 down-regulated genes comparing the BXK to HXK. Our rich dataset also identified eight putative key genes for anthocyanin synthesis, including four chalcone synthase (CHS, g13809_i0, g12097_i0, g18851_i0, g36714_i0), one chalcone isomerase (CHI, g26337_i0), two flavonoid 3-hydroxylase (F3'H, g14710_i0 and g15005_i0), and one anthocyanidin synthase (ANS, g18981_i0). Importantly, we found a 2.5 order of magnitude higher expression of anthocyanin 3-O-glucosyltransferase (g8206_i0), which encodes a key gene in glycosylation of anthocyanins, in HXK compared to BXK. Taken together, our multiomics approach demonstrated massive changes in gene regulatory networks and anthocyanin metabolism in controlling cyclamen flower color.

A forced cough sound based pulmonary function assessment method by using machine learning.

Pulmonary function testing (PFT) has important clinical value for the early detection of lung diseases, assessment of the disease severity, causes identification of dyspnea, and monitoring of critical patients. However, traditional PFT can only be carried out in a hospital environment, and it is challenging to meet the needs for daily and frequent evaluation of chronic respiratory diseases. In this study, we propose a novel method for accurately assessing pulmonary function by analyzing recorded forced cough sounds by mobile device without time and location restrictions. In the experiment, 309 clips of cough sound segments were separated from 133 patients who underwent PFT by using Audacity software. There are 247 clips of training samples and 62 clips of testing samples. Totally 52 features were extracted from the dataset, and principal component analysis (PCA) was used for feature reduction. Combined with biological attributes, the normalized features were regressed by using machine learning models with pulmonary function parameters (i.e., FEV1, FVC, FEV1/FVC, FEV1%, and FVC%). And a 5-fold cross-validation was applied to evaluate the performance of the regression models. As described in the experimental result, the result of coefficient of determination (R2) indicates that the support vector regression (SVR) model performed best in assessing FVC (0.84), FEV1% (0.61), and FVC% (0.62) among these models. The gradient boosting regression (GBR) model performs best in evaluating FEV1 (0.86) and FEV1/FVC (0.54). The result confirmed that the proposed method was capable of accurately assessing pulmonary function with forced cough sound. Besides, the cough sound sampling by a smartphone made it possible to conduct sampling and assess pulmonary function frequently in the home environment.

Mating-Type Genes Play an Important Role in Fruiting Body Development in Morchella sextelata.

True morels (Morchella spp.) are edible mushrooms that are commercially important worldwide due to their rich nutrition and unique appearance. In recent years, outdoor cultivation has been achieved and expanded on a large scale in China. However, the mechanisms of fruiting body development in morels are poorly understood. In this study, the role of mating-type genes in fruiting body development was researched. Fruiting bodies cultivated with different mating-type strains showed no difference in appearance, but the ascus and ascospores were slightly malformed in fruiting bodies obtained from the MAT1-1 strains. The transcript levels of mating-type genes and their target genes revealed that the regulatory mechanisms were conserved in ascomycetes fungi. The silencing of mat1-2-1 by RNA interference verified the direct regulatory effect of mat1-2-1 on its target genes at the asexual stage. When cultivated with the spawn of single mating-type strains of MAT1-1 or MAT1-2, only one corresponding mating-type gene was detected in the mycelial and conidial samples, but both mat1-1-1 and mat1-2-1 were detected in the samples of primordium, pileus, and stipe. An understanding of the mating-type genes' role in fruiting body development in M. sextelata may help to understand the life cycle and facilitate artificial cultivation.

Comparative transcriptome analysis of cells from different areas reveals ROS responsive mechanism at sclerotial initiation stage in Morchella importuna.

Morels are some of the most highly prized edible and medicinal mushrooms, with great economic and scientific value. Outdoor cultivation has been achieved and expanded on a large scale in China in recent years. Sclerotial formation is one of the most important phases during the morel life cycle, and previous reports indicated that reactive oxygen species (ROS) play an important role. However, ROS response mechanisms at sclerotial initiation (SI) stage are poorly understood. In this study, comparative transcriptome analyses were performed with sclerotial and hyphal cells at different areas in the same plate at SI stage. Gene expression was significantly different at SI stage between sclerotial formation and mycelia growth areas. GO and KEGG analyses indicated more vigorous metabolic characteristics in the hyphae area, while transcription process, DNA repair, and protein processing were enriched in sclerotial cells. Gene expression related to H2O2 production was high in the hyphae area, while expression of H2O2-scavenging genes was high in sclerotial cells, leading to a higher H2O2 concentration in the hyphal region than in the sclerotium. Minor differences were observed in gene expression of H2O2-induced signaling pathway in sclerotial and hyphal cells; however, expression levels of the target genes of transcription factor MSN2, important in the H2O2-induced signaling pathways, were significantly different. MSN2 enhanced stress response regulation in sclerotia by regulating these target genes. Small molecular HSPs were also found upregulated in sclerotial cells. This study indicated that sclerotial cells are more resistant to ROS stress than hyphal cells through transcriptional regulation of related genes.

Toxic effects of heavy metal Cd and Zn on chlorophyll, carotenoid metabolism and photosynthetic function in tobacco leaves revealed by physiological and proteomics analysis.

To explore the mechanisms underlying the action of the heavy metals Cd and Zn on the photosynthetic function of plant leaves, the effects of 100 µmol L-1 Cd and 200 µmol L-1 Zn stress (the exposure concentrations of Cd and Zn in the culture medium were 2.24 mg kg-1 and 5.36 mg kg-1) on the chlorophyll and carotenoid contents as well as the photosynthetic function of tobacco leaves (Long Jiang 911) were studied. The key proteins in these physiological processes were quantitatively analyzed using a TMT-based proteomics approach. Cd stress was found to inhibit the expression of key enzymes during chlorophyll synthesis in leaves, resulting in a decrease of the Chl content. However, Zn stress did not significantly influence the chlorophyll content. Leaves adapted to Zn stress by upregulating CAO expression and increase the Chl b content. Although the Car content in leaves did not significantly change under either Cd or Zn stress, the expressions of ZE and VDE during Car metabolism decreased significantly under Cd stress. This was accompanied by damages to the xanthophyll cycle and the NPQ-dependent energy dissipation mechanism. In contrast, under Zn stress, leaves adapted to Zn stress by increasing the expression of VDE, thus improving NPQ. Under Cd stress, the expressions of three sets of proteins were significantly down-regulated, including PSII donor-side proteins (PPD3, PPD6, OEE1, OEE2-1, OEE2-2, OEE2-3, and OEE3-2), receptor-side proteins (D1, D2, CP43, CP47, Cyt b559α, Cyt b559ß, PsbL, PsbQ, PsbR, Psb27-H1, and Psb28), and core proteins of the PSI reaction center (psaA, psaB, psaC, psaD, psaE-A, PsaE-B, psaF, psaG, psaH-1, psaK, psaL, psaN, and psaOL). In comparison, only eight of the above proteins (PPD6, OEE3-2, PsbL, PsbQ, Psb27-H1, psaL, and psaOL) were significantly down-regulated by Zn stress. Under Cd stress, both the donor side and the receptor side of PSII were damaged, and PSII and PSI experienced severe photoinhibition. However, Zn stress did not decrease either PSII or PSI activities in tobacco leaves. In addition, the expression of electron transport-related proteins (cytb6/f complex, PC, Fd, and FNR), ATPase subunits, Rubisco subunits, and RCA decreased significantly in leaves under Cd stress. However, no significant changes were observed in any of these proteins under Zn stress. Although Cd stress was found to up-regulate the expressions of PGRL1A and PGRL1B and induce an increase of PGR5/PGRL1-CEF in tobacco leaves, NDH-CEF was significantly inhibited. Under Zn stress, the expressions of ndhH and PGRL1A in leaves were significantly up-regulated, but there were no significant changes in either NDH-CEF or PGR5/PGRL-CEF. Under Cd stress, the expressions of proteins related to Fd-dependent nitrogen metabolism and reactive oxygen species (ROS) scavenging processes (e.g., FTR, Fd-NiR, and Fd-GOGAT) were significantly down-regulated in leaves. However, no significant changes of any of the above proteins were identified under Zn stress. In summary, Cd stress could inhibit the synthesis of chlorophyll in tobacco leaves, significantly down-regulate the expressions of photosynthesis-related proteins or subunits, and suppress both the xanthophyll cycle and NDH-CEF process. The expressions of proteins related to the Fd-dependent nitrogen metabolism and ROS scavenging were also significantly down-regulated, which blocked the photosynthetic electron transport, thus resulting in severe photoinhibition of both PSII and PSI. However, Zn stress had little effect on the photosynthetic function of tobacco leaves.

PEO-LITFSI-SiO2-SN System Promotes the Application of Polymer Electrolytes in All-Solid-State Lithium-ion Batteries.

All-solid-state polymer lithium-ion batteries are ideal choice for the next generation of rechargeable lithium-ion batteries due to their high energy, safety and flexibility. Among all polymer electrolytes, PEO-based polymer electrolytes have attracted extensive attention because they can dissolve various lithium salts. However, the ionic conductivity of pure PEO-based polymer electrolytes is limited due to high crystallinity and poor segment motion. An inorganic filler SiO2 nanospheres and a plasticizer Succinonitrile (SN) are introduced into the PEO matrix to improve the crystallization of PEO, promote the formation of amorphous region, and thus improve the movement of PEO chain segment. Herein, a PEO18-LiTFSI-5 %SiO2-5 %SN composite solid polymer electrolyte (CSPE) was prepared by solution-casting. The high ionic conductivity of the electrolyte was demonstrated at 60 °C up to 3.3×10-4 S cm-1. Meanwhile, the electrochemical performance of LiFePO4/CSPE/Li all-solid-state battery was tested, with discharge capacity of 157.5 mAh g-1 at 0.5 C, and capacity retention rate of 99 % after 100 cycles at 60 °C. This system provides a feasible strategy for the development of efficient all-solid-state lithium-ion batteries.

Overexpression of Trx CDSP32 gene promotes chlorophyll synthesis and photosynthetic electron transfer and alleviates cadmium-induced photoinhibition of PSII and PSI in tobacco leaves.

Cadmium stress causes a decrease in chlorophyll content and inhibits photosynthesis in tobacco leaves. The role of thioredoxin-like protein CDSP32 expressed in plant chloroplasts is to alleviates the reduced enzymes expression involved in chlorophyll synthesis of tobacco leaves due to Cd exposure, effectively preventing chlorophyll degradation and promoting increased tobacco biomass. Overexpression of Trx CDSP32 can protect the oxygen-evolving complex on the PSII donor side and promote electron transfer on the PSII acceptor side of tobacco leaves under Cd stress. Trx CDSP32 not only significantly increase the PSI activity of tobacco leaves, but also alleviate cadmium-induced PSI photoinhibition. Although Trx CDSP32 has no significant effect on the expression of PC and FNR proteins in tobacco leaves under Cd stress, it can alleviate the decreased expression of protein subunits involved in photosynthetic electron transfer such as Cyt b6/f complex subunits, Fd, and ATP synthase subunits. Trx CDSP32 can promote the synthesis of chlorophyll, stabilize the electron transfer chain, and promote ATP synthase activity to alleviate cadmium-induced photoinhibition of PSII and PSI in tobacco leaves.

3D hybrid of Co9S8 and N-doped carbon hollow spheres as effective hosts for Li-S batteries.

Lithium-sulfur (Li-S) batteries as a new generation of high energy batteries, with low cost and environmentally friendly, have a broad application prospects. While the poor conductivity of sulfur, the volume effect and 'shuttle effect' during charge and discharge, and slow redox kinetics of polysulfide intermediates still limit the practical application. To solve these problems, we synthesize a valid 3D hybrid material (Co9S8@N-CHS) of nanosized Co9S8 evenly distributed on N-doped carbon hollow spheres with strong chemical coupling by in situ carbonization of Co(NO3)2@resorcinol/formaldehyde and sulfidation. It presents a high electronic conductivity, absorbing chemical adsorption capability to polysulfides and can catalyze the sulfur redox processes. Compared with S/AC and S/N-CHS electrodes, S/Co9S8@N-CHS electrodes achieve an excellent initial discharge specific capacity of 1337 mAh g-1 at 0.1 C and a long cycle life with an ultralow capacity decay of 0.027% per cycle over 1000 cycles at 1.0 C and the coulombic efficiency is above 99%. Consequently, it is an effective sulfur host material for high performance Li-S batteries.

Six new species and two new records of Morchella in China using phylogenetic and morphological analyses.

In this paper, species of the genus Morchella are investigated in China. Based on morphological characteristics and molecular phylogenetic analyses of the nuc rDNA internal transcribed spacer region ITS1-5.8S-ITS2 (ITS) and the combined data set ITS + nuclear large subunit rDNA (28S) + the translation elongation factor 1-α (TEF1) gene + RNA polymerase II first largest subunit (RPB1) + RNA polymerase II second largest subunit (RPB2), six new phylogenetic species are illustrated and described: M. clivicola, M. confusa, M. odonnellii, M. owneri, M. yangii, and M. yishuica. Furthermore, two new record species, M. dunensis and M. palazonii, which were only known in Europe, are now reported for the first time from Asia. New species of morels will provide additional information on species diversity and genetic resource candidates for improving the cultivation of this economically important fungus.

Highly Reactive Metastable Intermixed Composites (MICs): Preparation and Characterization.

Highly reactive metastable intermixed composites (MICs) have attracted much attention in the past decades. The MIC family of materials mainly includes traditional metal-based nanothermites, novel core-shell-structured, 3D ordered macroporous-structured, and ternary nanocomposites. By applying special fabrication approaches, highly reactive MICs with uniformly dispersed reactants, "layer-by-layer" or "core-shell" structures, can be prepared. Thus, the combustion performance can be greatly improved, and the ignition characteristics and safety can be precisely controlled by using a certain preparation strategy. Here, the preparation and characterization of the MICs that have been developed during the past few decades are summarized. Traditional preparation methods for MICs generally include physical mixing, high-energy ball milling, sol-gel synthesis, and vapor deposition, while the novel methods include self-assembly, electrophoretic deposition, and electrospinning. Various preparation procedures and the ignition and combustion performance of different MIC reactive systems are compared and discussed. In particular, the advantages of novel structured MICs in terms of safety and combustion efficiency are clarified, based on which suggestions regarding the possible future research directions are proposed.

Regularized lattice Boltzmann model for immiscible two-phase flows with power-law rheology.

In this work, a regularized lattice Boltzmann color-gradient model is developed for the simulation of immiscible two-phase flows with power-law rheology. This model is as simple as the Bhatnagar-Gross-Krook (BGK) color-gradient model except that an additional regularization step is introduced prior to the collision step. In the regularization step, the pseudo-inverse method is adopted as an alternative solution for the nonequilibrium part of the total distribution function, and it can be easily extended to other discrete velocity models no matter whether a forcing term is considered or not. The obtained expressions for the nonequilibrium part are merely related to macroscopic variables and velocity gradients that can be evaluated locally. Several numerical examples, including the single-phase and two-phase layered power-law fluid flows between two parallel plates, and the droplet deformation and breakup in a simple shear flow, are conducted to test the capability and accuracy of the proposed color-gradient model. Results show that the present model is more stable and accurate than the BGK color-gradient model for power-law fluids with a wide range of power-law indices. Compared to its multiple-relaxation-time counterpart, the present model can increase the computing efficiency by around 15%, while keeping the same accuracy and stability. Also, the present model is found to be capable of reasonably predicting the critical capillary number of droplet breakup.

Ab Initio Calculations of the N-N Bond Dissociation for the Gas-phase RDX and HMX.

NO2 fission is a vital factor for 1,3,5-Trinitroperhydro-1,3,5-triazine (RDX) and octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) decomposition. In this study, the geometry of the gas-phase RDX and HMX molecules was optimized, and the bond order and the bond dissociation energy of the N-N bonds were examined. Moreover, the rate constants of the gas-phase RDX and HMX conformers, concerning the N-N bond dissociation, were evaluated using the microcanonical variational transition state theory (µVT). The calculation results have shown that HMX is more stable than RDX in terms of the N-N bond dissociation, and the conformers stability parameters were as follows: RDXaaa < RDXaae < HMX I < HMX II. In addition, for the RDX conformers, the N-N bond of the pseudo-equatorial positioning of the nitro group was more stable than the N-N bond of the axial positioning of the nitro group, while the results were opposite in the case of the HMX conformers. Moreover, it has been shown that the dissociation rate constant of the N-N bond is influenced by the temperature significantly, thus the rate constants were much lower (<10-10 s-1) when the temperature was less than 1000 K.

Ion-exchange-assisted synthesis of Pt-VC nanoparticles loaded on graphitized carbon: a high-performance nanocomposite electrocatalyst for oxygen-reduction reactions.

Carbide-based electrocatalysts are superior to traditional carbon-based electrocatalysts, such as the commercial Pt/C electrocatalysts, in terms of their mass activity and stability. Herein, we report a general approach for the preparation of a nanocomposite electrocatalyst of platinum and vanadium carbide nanoparticles that are loaded onto graphitized carbon. The nanocomposite, which was prepared in a localized and controlled fashion by using an ion-exchange process, was an effective electrocatalyst for the oxygen-reduction reaction (ORR). Both the stability and the durability of the Pt-VC/GC nanocomposite catalyst could be enhanced compared with the state-of-the-art Pt/C. This approach can be extended to the synthesis of other metal-carbide-based nanocatalysts. Moreover, this straightforward synthesis of high-performance composite nanocatalysts can be scaled up to meet the requirements for mass production.

[Effects of exogenous CaCl2 on the functions of flue-cured tobacco seedlings leaf photosystem II under drought stress].

Taking chlorophyll a fluorescence transient OJIP as the probe, this paper studied the effects of foliar spraying 10 mmol x L(-1) of CaCl2 on the functions of photosystem II (PS II) in tobacco seedling leaves under drought stress. Drought stress decreased the conversion efficiency of PS II primary light energy (F(v)/F(m)) and electron transport rate (ETR), and inhibited the primal process of photosynthesis, resulting in an obvious photoinhibition. After the spraying of CaCl2, the decrement of quantum yield for electron transport (phiE(o)) under drought stress was obviously lower, and the increment of electron transport efficiency of per reaction center (ET(o)/RC) was obviously higher, compared with those after the spraying of water. Foliar spraying CaCl2 increased the amount of PS II -captured light energy used for photosynthesis electron transport, the efficiency of surplus active reaction center, as well as the energy transport in electron transport chain, making the PS II remain relatively high activity under drought stress, and accordingly, the drought resistance of the tobacco seedlings was improved.