Prediction of dose distributions for non-small cell lung cancer patients using MHA-ResUNet.

BACKGROUND: The current level of automation in the production of radiotherapy plans for lung cancer patients is relatively low. With the development of artificial intelligence, it has become a reality to use neural networks to predict dose distributions and provide assistance for radiation therapy planning. However, due to the significant individual variability in the distribution of non-small cell lung cancer (NSCLC) planning target volume (PTV) and the complex spatial relationships between the PTV and organs at risk (OARs), there is still a lack of a high-precision dose prediction network tailored to the characteristics of NSCLC. PURPOSE: To assist in the development of volumetric modulated arc therapy (VMAT) plans for non-small cell lung cancer patients, a deep neural network is proposed to predict high-precision dose distribution. METHODS: This study has developed a network called MHA-ResUNet, which combines a large-kernel dilated convolution module and multi-head attention (MHA) modules. The network was trained based on 80 VMAT plans of NSCLC patients. CT images, PTV, and OARs were fed into the independent input channel. The dose distribution was taken as the output to train the model. The performance of this network was compared with that of several commonly used networks, and the networks' performance was evaluated based on the voxel-level mean absolute error (MAE) within the PTV and OARs, as well as the error in clinical dose-volume metrics. RESULTS: The MAE between the predicted dose distribution and the manually planned dose distribution within the PTV is 1.43 Gy, and the D95 error is less than 1 Gy. Compared with the other three commonly used networks, the dose error of the MHA-ResUNet is the smallest in PTV and OARs. CONCLUSIONS: The proposed MHA-ResUNet network improves the receptive field and filters the shallow features to learn the relative spatial relation between the PTV and the OARs, enabling accurate prediction of dose distributions in NSCLC patients undergoing VMAT radiotherapy.

A novel PGPR strain, Streptomyces lasalocidi JCM 3373T, alleviates salt stress and shapes root architecture in soybean by secreting indole-3-carboxaldehyde.

While soybean (Glycine max L.) provides the most important source of vegetable oil and protein, it is sensitive to salinity, which seriously endangers the yield and quality during soybean production. The application of Plant Growth-Promoting Rhizobacteria (PGPR) to improve salt tolerance for plant is currently gaining increasing attention. Streptomycetes are a major group of PGPR. However, to date, few streptomycetes has been successfully developed and applied to promote salt tolerance in soybean. Here, we discovered a novel PGPR strain, Streptomyces lasalocidi JCM 3373T, from 36 strains of streptomycetes via assays of their capacity to alleviate salt stress in soybean. Microscopic observation showed that S. lasalocidi JCM 3373T does not colonise soybean roots. Chemical analysis confirmed that S. lasalocidi JCM 3373T secretes indole-3-carboxaldehyde (ICA1d). Importantly, IAC1d inoculation alleviates salt stress in soybean and modulates its root architecture by regulating the expression of stress-responsive genes GmVSP, GmPHD2 and GmWRKY54 and root growth-related genes GmPIN1a, GmPIN2a, GmYUCCA5 and GmYUCCA6. Taken together, the novel PGPR strain, S. lasalocidi JCM 3373T, alleviates salt stress and improves root architecture in soybean by secreting ICA1d. Our findings provide novel clues for the development of new microbial inoculant and the improvement of crop productivity under salt stress.

Cobalt etched graphite felt electrode for enhanced removal of organic pollutant in aqueous solution with a solid polymer electrolyte.

In this study, cobalt etched graphite felt electrodes were produced using a simple etching technique. It was used in combination with a solid polymer electrolyte (SPE) for the degradation of the target contaminant Orange II by Electro-Fenton (EF) technique in low conductivity water. In this method, 94% of Orange II in low conductivity water was removed in 90 min. The characterization analysis substantiates the hypothesis that the electrodes produced exhibit a three-dimensional porous structure, augmented defect concentration, and enhanced electron transfer capability. In addition, the potential reaction mechanism was inferred from the radical quenching experiments, and hydroxyl radicals (·OH) were deemed the main reactive substances. The combination of cobalt etched graphite felt electrodes with SPE demonstrates remarkable efficacy in the treatment of organic wastewater characterized by low electrical conductivity.

Lateral epitaxial growth of two-dimensional organic heterostructures.

Two-dimensional organic lateral heterostructures (2D OLHs) are attractive for the fabrication of functional materials. However, it is difficult to control the nucleation, growth and orientation of two distinct components. Here we report the combination of two methods-liquid-phase growth and vapour-phase growth-to synthesize 2D OLHs from perylene and a perylenecarboxaldehyde derivative, with a lateral size of ~20 µm and a tunable thickness ranging from 20 to 400 nm. The screw dislocation growth behaviour of the 2D crystals shows the spiral arrangement of atoms within the crystal lattice, which avoids volume expansion and contraction of OLH, thereby minimizing lateral connection defects. Selective control of the nucleation and sequential growth of 2D crystals leads to structural inversion of the 2D OLHs by the vapour-phase growth method. The resulting OLHs show good light-transport capabilities and tunable spatial exciton conversion, useful for photonic applications. This synthetic strategy can be extended to other families of organic polycyclic aromatic hydrocarbons, as demonstrated with other pyrene and perylene derivatives.

A Novel Prediction Method of Transfer-Assisted Action Oriented to Individual Differences for the Excretion Care Robot.

The excretion care robot's (ECR) accurate recognition of transfer-assisted actions is crucial during its usage. However, transfer action recognition is a challenging task, especially since the differentiation of actions seriously affects its recognition speed, robustness, and generalization ability. We propose a novel approach for transfer action recognition assisted by a bidirectional long- and short-term memory (Bi-LSTM) network combined with a multi-head attention mechanism. Firstly, we utilize posture sensors to detect human movements and establish a lightweight three-dimensional (3D) model of the lower limbs. In particular, we adopt a discrete extended Kalman filter (DEKF) to improve the accuracy and foresight of pose solving. Then, we construct an action prediction model that incorporates a fused Bi-LSTM with Multi-head attention (MHA Bi-LSTM). The MHA extracts key information related to differentiated movements from different dimensions and assigns varying weights. Utilizing the Bi-LSTM network effectively combines past and future information to enhance the prediction results of differentiated actions. Finally, comparisons were made by three subjects in the proposed method and with two other time series based neural network models. The reliability of the MHA Bi-LSTM method was verified. These experimental results show that the introduced MHA Bi-LSTM model has a higher accuracy in predicting posture sensor-based excretory care actions. Our method provides a promising approach for handling transfer-assisted action individual differentiation in excretion care tasks.

Thickness-variation-insensitive near-infrared quantum dot LEDs.

In terms of tunable luminescence and high quantum efficiency, colloidal quantum dots (CQDs) are promising semiconductors for constructing near-infrared light-emitting diodes (NIR-LEDs). However, currently available NIR-LEDs are susceptible to variations in the emission layer thickness (EMLT), the highest external quantum efficiency (EQE) decreases to below 50% (relative to peak EQE) when the EMLT varies out of a narrow range of (±30 nm). This is due to the thickness-dependent carrier recombination rate and current density variation, resulting in batch-to-batch EQE fluctuations that limit LED reproducibility. Here we report efficient NIR-LEDs that exhibit EQE variations of less than 15% (relative to the champion EQE) over an EMLT range of 40-220 nm; the highest achievable EQE of ∼11.5% was obtained by encapsulating a 212 nm-thick CQD within a type-I inorganic shell to enhance the radiative recombination in the dots, resulting in a high photoluminescence quantum yield of 80%, and by post-treating the films with a bifunctional linking agent to improve and balance the hole and electron mobilities in the entire film (electron mobility: 8.23 × 10-3 cm2 V-1 s-1; hole mobility: 7.0 × 10-3 cm2 V-1 s-1). This work presents the first NIR-LEDs that exhibit EMLT-invariant EQE over an EMLT range of 40-220 nm, which represents the highest EQE among reported CQD NIR-LEDs with a QD thickness exceeding 100 nm.

Three-Dimensional Printed Poly (Lactic-co-Glycolic Acid)-Magnesium Composite Scaffolds for the Promotion of Osteogenesis Through Immunoregulation.

Scaffolds play an important role in bone tissue engineering. The ideal engineered scaffold needs to be biocompatible, bioactive, and able to regulate immune cells to enhance bone regeneration. In this study, magnesium (Mg)-contained poly(lactic-co-glycolic acid) (PLGA) scaffolds (hereinafter, referred to as PLGA-2Mg) were fabricated by 3-dimensional printing using a mixture of PLGA and MgSO 4 powder. Poly(lactic-co-glycolic acid) scaffolds (hereinafter, referred to as PLGA) were also fabricated by 3-dimensional printing and were used as control. The biocompatibility, immunoregulatory ability, and osteogenic properties of PLGA-2Mg were analyzed and compared with those of PLGA. The results indicate that the incorporation of Mg increased the Young modulus and surface roughness of the scaffold, but did not affect its degradation. The PLGA-2Mg further promoted the adhesion and proliferation of MC3T3-E1 cells compared with PLGA, which indicates its improved biocompatibility and bioactivity. In addition, PLGA-2Mg inhibited the polarization of RAW 264.7 cells toward the M1 phenotype by down-regulating the IL-1ß , IL-6 , and iNOs gene expression when challenged with lipopolysaccharide stimulation. In contrast, it promoted the polarization of RAW 264.7 cells toward the M2 phenotype by up-regulating the TGF-ß , IL-10 , and Arg-1 gene expression without lipopolysaccharide stimulation. Finally, MC3T3-E1 cells were cocultured with RAW 264.7 cells and scaffolds using a transwell system. It was found that the expression level of osteogenic-related genes ( ALP , COL-1 , BMP2 , and BSP ) was significantly upregulated in the PLGA-2Mg group compared with that in the PLGA group. Consequently, PLGA-2Mg with increased biocompatibility and bioactivity can promote osteogenesis through immunoregulation and has the potential to be used as a novel scaffold in bone tissue engineering.

Applying a novel two-step deep learning network to improve the automatic delineation of esophagus in non-small cell lung cancer radiotherapy.

Purpose: To introduce a model for automatic segmentation of thoracic organs at risk (OARs), especially the esophagus, in non-small cell lung cancer radiotherapy, using a novel two-step deep learning network. Materials and methods: A total of 59 lung cancer patients' CT images were enrolled, of which 39 patients were randomly selected as the training set, 8 patients as the validation set, and 12 patients as the testing set. The automatic segmentations of the six OARs including the esophagus were carried out. In addition, two sets of treatment plans were made on the basis of the manually delineated tumor and OARs (Plan1) as well as the manually delineated tumor and the automatically delineated OARs (Plan2). The Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and average surface distance (ASD) of the proposed model were compared with those of U-Net as a benchmark. Next, two groups of plans were also compared according to the dose-volume histogram parameters. Results: The DSC, HD95, and ASD of the proposed model were better than those of U-Net, while the two groups of plans were almost the same. The highest mean DSC of the proposed method was 0.94 for the left lung, and the lowest HD95 and ASD were 3.78 and 1.16 mm for the trachea, respectively. Moreover, the DSC reached 0.73 for the esophagus. Conclusions: The two-step segmentation method can accurately segment the OARs of lung cancer. The mean DSC of the esophagus realized preliminary clinical significance (>0.70). Choosing different deep learning networks based on different characteristics of organs offers a new option for automatic segmentation in radiotherapy.

Advances in Solution-Processed Blue Quantum Dot Light-Emitting Diodes.

Quantum dot light-emitting diodes (QLEDs) have been identified as a next-generation display technology owing to their low-cost manufacturing, wide color gamut, and electrically driven self-emission properties. However, the efficiency and stability of blue QLEDs still pose a significant challenge, limiting their production and potential application. This review aims to analyse the factors leading to the failure of blue QLEDs and presents a roadmap to accelerate their development based on the progress made in the synthesis of II-VI (CdSe, ZnSe) quantum dots (QDs), III-V (InP) QDs, carbon dots, and perovskite QDs. The proposed analysis will include discussions on material synthesis, core-shell structures, ligand interactions, and device fabrication, providing a comprehensive overview of these materials and their development.

Efficient Near-Infrared Electroluminescence from Lanthanide-Doped Perovskite Quantum Cutters.

Perovskite nanocrystals (PeNCs) deliver size- and composition-tunable luminescence of high efficiency and color purity in the visible range. However, attaining efficient electroluminescence (EL) in the near-infrared (NIR) region from PeNCs is challenging, limiting their potential applications. Here we demonstrate a highly efficient NIR light-emitting diode (LED) by doping ytterbium ions into a PeNCs host (Yb3+ : PeNCs), extending the EL wavelengths toward 1000 nm, which is achieved through a direct sensitization of Yb3+ ions by the PeNC host. Efficient quantum-cutting processes enable high photoluminescence quantum yields (PLQYs) of up to 126 % from the Yb3+ : PeNCs. Through halide-composition engineering and surface passivation to improve both PLQY and charge-transport balance, we demonstrate an efficient NIR LED with a peak external quantum efficiency of 7.7 % at a central wavelength of 990 nm, representing the most efficient perovskite-based LEDs with emission wavelengths beyond 850 nm.

Visualization of Cytoskeleton Organization and Dynamics in Elongating Cotton Fibers by Live-Cell Imaging.

Cotton fibers are extremely elongated single cells and have long been regarded as an ideal model to investigate polarized plant cell elongation. Actin filaments (F-actin), as well as the cortical microtubules (CMTs), play vital roles in polarized cell growth and morphogenesis. We have generated stable transgenic cotton plants expressing fluorescent markers for the actin and microtubule cytoskeletons. Further live-cell imaging identified dynamic features of the F-actin and cortical microtubule (CMT) architectures and discovered that cotton fibers elongate in a unique tip-biased diffuse growth mode. Here, we describe methods for preparing growing cotton fiber samples, as well as the visualization of cytoskeletal organization and dynamics by live-cell imaging. Combined with comprehensive image analyses, these methods can be used to identify how cytoskeleton organization and dynamics determine cell morphogenesis in highly polarized cotton fibers.

Verticillium dahliae Asp1 regulates the transition from vegetative growth to asexual reproduction by modulating microtubule dynamic organization.

Verticillium dahliae is a devastating pathogenic fungus that causes severe vascular wilts in more than 400 dicotyledonous plants. The conidiation of V. dahliae in plant vascular tissues is the key strategy for its adaptation to the nutrient-poor environment and is required for its pathogenicity. However, it remains unclear about the regulatory mechanism of conidium production of V. dahliae in vascular tissues. Here, we found that VdAsp1, encoding an inositol polyphosphate kinase, is indispensable for the pathogenicity of V. dahliae. Loss of VdAsp1 function does not affect the invasion of the host, but it impairs the colonization and proliferation in vascular tissues. The ΔVdAsp1 mutant shows defective initiation of conidiophore formation and reduced expression of genes associated with the central developmental pathway. By live-cell imaging, we observed that some of ΔVdAsp1 mutant hyphae are swollen, and microtubule arrangements at the apical region of these hyphae are disorganized. These results indicate that VdAsp1 regulates the transition from vegetative growth to asexual reproduction by modulating microtubule dynamic organization, which is essential for V. dahliae to colonize and proliferate in vascular tissues. These findings provided a potential new direction in the control of vascular wilt pathogen by targeting conidium production in vascular tissues.

Brassinosteroid signals cooperate with katanin-mediated microtubule severing to control stamen filament elongation.

Proper stamen filament elongation is essential for pollination and plant reproduction. Plant hormones are extensively involved in every stage of stamen development; however, the cellular mechanisms by which phytohormone signals couple with microtubule dynamics to control filament elongation remain unclear. Here, we screened a series of Arabidopsis thaliana mutants showing different microtubule defects and revealed that only those unable to sever microtubules, lue1 and ktn80.1234, displayed differential floral organ elongation with less elongated stamen filaments. Prompted by short stamen filaments and severe decrease in KTN1 and KTN80s expression in qui-2 lacking five BZR1-family transcription factors (BFTFs), we investigated the crosstalk between microtubule severing and brassinosteroid (BR) signaling. The BFTFs transcriptionally activate katanin-encoding genes, and the microtubule-severing frequency was severely reduced in qui-2. Taken together, our findings reveal how BRs can regulate cytoskeletal dynamics to coordinate the proper development of reproductive organs.

A legume kinesin controls vacuole morphogenesis for rhizobia endosymbiosis.

Symbioses between legumes and rhizobia require establishment of the plant-derived symbiosome membrane, which surrounds the rhizobia and accommodates the symbionts by providing an interface for nutrient and signal exchange. The host cytoskeleton and endomembrane trafficking systems play central roles in the formation of a functional symbiotic interface for rhizobia endosymbiosis; however, the underlying mechanisms remain largely unknown. Here we demonstrate that the nodulation-specific kinesin-like calmodulin-binding protein (nKCBP), a plant-specific microtubule-based kinesin motor, controls central vacuole morphogenesis in symbiotic cells in Medicago truncatula. Phylogenetic analysis further indicated that nKCBP duplication occurs solely in legumes of the clade that form symbiosomes. Knockout of nKCBP results in central vacuole deficiency, defective symbiosomes and abolished nitrogen fixation. nKCBP decorates linear particles along microtubules, and crosslinks microtubules with the actin cytoskeleton, to control central vacuole formation by modulating vacuolar vesicle fusion in symbiotic cells. Together, our findings reveal that rhizobia co-opted nKCBP to achieve symbiotic interface formation by regulating cytoskeletal assembly and central vacuole morphogenesis during nodule development.

Distribution of Diatoms in the Navigable Sections of Beijing-Hangzhou Grand Canal.

OBJECTIVES: To establish a diatom database by analyzing the quatity, species distribution and differences of diatom in water samples of the whole navigable sections of the Beijing-Hangzhou Grand Canal, to provide a reference for the inference of the drowning site. METHODS: Water samples were collected at 22 sites in the navigable sections of the Beijing-Hangzhou Grand Canal (Jining section to Yangzhou Section), and the diatoms at each site were qualitatively and quantitatively analyzed by using graphite digestion-scanning electron microscopy. RESULTS: Sampling site T (Laohuaijiang River Line, Gaoyou City, Yangzhou City, Jiangsu Province) had the highest number of diatoms, while sampling site O (Siyang County, Suqian City, Jiangsu Province) had the lowest number of diatoms, with a large gap of 68 times. At sampling site Q (Jiangpu District, Huaian city, Jiangsu Province), there were 19 species of diatoms. The sampling site O had the least diatoms, with 7 species. There were no significant differences in species evenness and species diversity at each sampling site (P>0.05). Some sampling sites have characterized diatoms, such as Caloneis at station A (Taibai Lake, Weishan County, Shandong Province), Rhoicosphenia at station B (Nanyang Town, Weishan County, Shandong Province), Amphora at station I (Taierzhuang District, Zaozhuang City, Shandong Province) and Epithemia at station J (Pizhou 310 national highway, Xuzhou City, Jiangsu Province). CONCLUSIONS: The species richness of diatoms gradually increased from north to south. Diatom species richness and species diversity might be higher in areas with complex environments and large population flow. Climate type has a certain influence on the distribution of diatoms.

Elucidating the origin mechanism of a morphology-dependent layered double hydroxide catalyst toward organic contaminant oxidation via persulfate activation.

Understanding how the morphology of a layered double hydroxide (LDH)-based catalyst alters its catalytic activity provides an available strategy for the rational design and fabrication of high-efficiency catalysts at a micro-scale. Herein, three nickel-iron layered double hydroxide (NiFe-LDH) catalysts including 2D-plate-like hexagon (P-NiFe-LDH), 2D/3D-flower-like solid sphere (FS-NiFe-LDH), and 2D/3D-flower-like hollow sphere (FH-NiFe-LDH) with regulable oxygen vacancies (OVs) were fabricated via a morphological regulation method of Ostwald ripening. The experimental results demonstrated that the three types of NiFe-LDH exhibited different abilities to activate persulfate (PS) for the abatement of acid orange 7 (AO7) with a sequence of FH-NiFe-LDH > FS-NiFe-LDH > P-NiFe-LDH. Particularly, the FH-NiFe-LDH with a hollow structure exhibited the most considerable activity with the first-order rate constant up to k = 0.02639 min-1, benefiting from the highly accessible surface areas, higher intrinsic activity of the exposed crystal planes, and abundant OVs. Characterizations further confirmed that these properties could profoundly allow for more exposure of active sites and enhance the reactivity of OV-connected Ni or Fe to facilitate electron transfer and generate more reactive radicals, therefore elucidating the morphologic origin of catalytic performance. Based on the quenching experiments, sulfate radicals (SO4·-), hydroxyl radicals (·OH), and oxygen radicals (O2·-) were identified to be involved in the decomposition process. Furthermore, the continuous redox cycle of Ni(II)/Ni(III)/Ni(II) and Fe(II)/Fe(III)/Fe(II) was responsible for the generation of active radicals via activating PS.

Geometric and Dosimetric Evaluation of the Automatic Delineation of Organs at Risk (OARs) in Non-Small-Cell Lung Cancer Radiotherapy Based on a Modified DenseNet Deep Learning Network.

Purpose: To introduce an end-to-end automatic segmentation model for organs at risk (OARs) in thoracic CT images based on modified DenseNet, and reduce the workload of radiation oncologists. Materials and Methods: The computed tomography (CT) images of 36 lung cancer patients were included in this study, of which 27 patients' images were randomly selected as the training set, 9 patients' as the testing set. The validation set was generated by cross validation and 6 patients' images were randomly selected from the training set during each epoch as the validation set. The autosegmentation task of the left and right lungs, spinal cord, heart, trachea and esophagus was implemented, and the whole training time was approximately 5 hours. Geometric evaluation metrics including the Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95) and average surface distance (ASD), were used to assess the autosegmentation performance of OARs based on the proposed model and were compared with those based on U-Net as benchmarks. Then, two sets of treatment plans were optimized based on the manually contoured targets and OARs (Plan1), as well as the manually contours targets and the automatically contoured OARs (Plan2). Dosimetric parameters, including Dmax, Dmean and Vx, of OARs were obtained and compared. Results: The DSC, HD95 and ASD of the proposed model were better than those of U-Net. The differences in the DSC of the spinal cord and esophagus, differences in the HD95 of the spinal cord, heart, trachea and esophagus, as well as differences in the ASD of the spinal cord were statistically significant between the two models (P<0.05). The differences in the dose-volume parameters of the two sets of plans were not statistically significant (P>0.05). Moreover, compared with manual segmentation, autosegmentation significantly reduced the contouring time by nearly 40.7% (P<0.05). Conclusions: The bilateral lungs, spinal cord, heart and trachea could be accurately delineated using the proposed model in this study; however, the automatic segmentation effect of the esophagus must still be further improved. The concept of feature map reuse provides a new idea for automatic medical image segmentation.

Full-Dimensional Grain Boundary Stress Release for Flexible Perovskite Indoor Photovoltaics.

Perovskite photovoltaics are strong potential candidates to drive low-power off-grid electronics for indoor applications. Compared with rigid devices, flexible perovskite devices can provide a more suitable surface for indoor small electronic devices, enabling them have a broader indoor application prospect. However, the mechanical stability of flexible perovskite photovoltaics is an urgent issue solved. Herein, a kind of 3D crosslinking agent named borax is selected to carry out grain boundary penetration treatment on perovskite film to realize full-dimensional stress release. This strategy improves the mechanical and phase stabilities of perovskite films subjected to external forces or large temperature changes. The fabricated perovskite photovoltaics deliver a champion power conversion efficiency (PCE) of 21.63% under AM 1.5G illumination, which is the highest one to date. The merit of low trap states under weak light makes the devices present a superior indoor PCE of 31.85% under 1062 lux (LED, 2956 K), which is currently the best flexible perovskite indoor photovoltaic device. This work provides a full-dimensional grain boundary stress release strategy for highly stable flexible perovskite indoor photovoltaics.

A Modified Actin (Gly65Val Substitution) Expressed in Cotton Disrupts Polymerization of Actin Filaments Leading to the Phenotype of Ligon Lintless-1 (Li1) Mutant.

Dynamic remodeling of the actin cytoskeleton plays a central role in the elongation of cotton fibers, which are the most important natural fibers in the global textile industry. Here, a high-resolution mapping approach combined with comparative sequencing and a transgenic method revealed that a G65V substitution in the cotton actin Gh_D04G0865 (GhACT17D in the wild-type) is responsible for the Gossypium hirsutum Ligon lintless-1 (Li1) mutant (GhACT17DM). In the mutant GhACT17DM from Li1 plant, Gly65 is substituted with valine on the lip of the nucleotide-binding domain of GhACT17D, which probably affects the polymerization of F-actin. Over-expression of GhACT17DM, but not GhACT17D, driven by either a CaMV35 promoter or a fiber-specific promoter in cotton produced a Li1-like phenotype. Compared with the wild-type control, actin filaments in Li1 fibers showed higher growth and shrinkage rates, decreased filament skewness and parallelness, and increased filament density. Taken together, our results indicate that the incorporation of GhACT17DM during actin polymerization disrupts the establishment and dynamics of the actin cytoskeleton, resulting in defective fiber elongation and the overall dwarf and twisted phenotype of the Li1 mutant.