Online rumors during the COVID-19 pandemic: co-evolution of themes and emotions.

Introduction: During public health emergencies, online rumors spread widely on social media, causing public information anxiety and emotional fluctuations. Analyzing the co-evolution patterns of online rumor themes and emotions is essential for implementing proactive and precise governance of online rumors during such events. Methods: Rumor texts from mainstream fact-checking platforms during the COVID-19 pandemic were collected and analyzed in phases based on the crisis lifecycle theory. The LDA topic model was applied to analyze the distribution of rumor themes at different stages. The Baidu AI Sentiment Analysis API was used to study the emotional tendencies of rumors at different stages. Line graphs were utilized to analyze the co-evolution characteristics of rumor themes and emotions. Results: During the COVID-19 pandemic, the themes of online rumors can be categorized into five types: epidemic prevention and control, panic-inducing, production and livelihood, virus dissemination, and social figures. These themes exhibited repetition and fluctuation at different stages of the pandemic. The emotions embedded in pandemic-related online rumors evolved with the progression of the pandemic. Panic-inducing rumors co-evolved with negative emotions, while epidemic prevention and control rumors co-evolved with positive emotions. Conclusion: The study results help to understand the public's focus and emotional tendencies at different stages of the COVID-19 pandemic, thereby enabling targeted public opinion guidance and crisis management.

DrugFlow: An AI-Driven One-Stop Platform for Innovative Drug Discovery.

Artificial intelligence (AI)-aided drug design has demonstrated unprecedented effects on modern drug discovery, but there is still an urgent need for user-friendly interfaces that bridge the gap between these sophisticated tools and scientists, particularly those who are less computer savvy. Herein, we present DrugFlow, an AI-driven one-stop platform that offers a clean, convenient, and cloud-based interface to streamline early drug discovery workflows. By seamlessly integrating a range of innovative AI algorithms, covering molecular docking, quantitative structure-activity relationship modeling, molecular generation, ADMET (absorption, distribution, metabolism, excretion and toxicity) prediction, and virtual screening, DrugFlow can offer effective AI solutions for almost all crucial stages in early drug discovery, including hit identification and hit/lead optimization. We hope that the platform can provide sufficiently valuable guidance to aid real-word drug design and discovery. The platform is available at https://drugflow.com.

Mechanistic Insights into Tanshinone IIA in the Amelioration of Post-Thyroidectomy Hypoparathyroidism.

BACKGROUND: Thyroidectomy causes impaired blood supply to the parathyroid glands, which leads to hypoparathyroidism. Tanshinone IIA (Tan IIA) is helpful in blood activation and cardiovascular protection. Therefore, the efficacy of Tan IIA in improving hypoparathyroidism was explored in this study. METHODS: New Zealand white rabbits were utilized to establish a unilateral parathyroid gland ischemia injury model. The model was created by selectively ligating the main blood supply vessel of one parathyroid gland, and the rabbits were then divided into three groups receiving 1, 5, and 10 mg/kg of Tan IIA. Serum calcium and parathyroid hormone (PTH) levels were measured using specialized assay kits. Immunohistochemistry was used to assess the microvessel density (MVD) in parathyroid glands. Western blotting (WB) was used to analyze protein expression related to the PI3K/AKT signaling pathway and the pathway-associated HIF-1α and VEGF. Moreover, MMP-2 and MMP-9 involved in angiogenesis were detected by WB. RESULTS: Tan IIA treatment effectively restored serum calcium and PTH levels in a dose-dependent manner. Notably, MVD in the parathyroid glands increased significantly, especially at higher doses. The Tan IIA treatment also elevated the p-PI3K/PI3K and p-AKT/AKT ratios, indicating that the PI3K/AKT pathway was reactivated. Moreover, Tan IIA significantly restored the decreased expression levels of VEGF and HIF-1α caused by parathyroid surgery. Additionally, Tan IIA increased MMP-2 and MMP-9 levels. CONCLUSION: Tan IIA activates the PI3K/AKT pathway, promotes angiogenesis by modulating VEGF, HIF-1α, MMP-2, and MMP-9, thereby further enhancing MVD within the parathyroid glands. This study demonstrates that Tan IIA improved post-thyroidectomy hypoparathyroidism.

Modulation format recognition in a UVLC system based on an ultra-lightweight model with communication-informed knowledge distillation.

Modulation format recognition (MFR) is a key technology for adaptive optical systems, but it faces significant challenges in underwater visible light communication (UVLC) due to the complex channel environment. Recent advances in deep learning have enabled remarkable achievements in image recognition, owing to the powerful feature extraction of neural networks (NN). However, the high computational complexity of NN limits their practicality in UVLC systems. This paper proposes a communication-informed knowledge distillation (CIKD) method that achieves high-precision and low-latency MFR with an ultra-lightweight student model. The student model consists of only one linear dense layer under a communication-informed auxiliary system and is trained under the guidance of a high-complexity and high-precision teacher model. The MFR task involves eight modulation formats: PAM4, QPSK, 8QAM-CIR, 8QAM-DIA, 16QAM, 16APSK, 32QAM, and 32APSK. Experimental results show that the student model based on CIKD can achieve comparable accuracy to the teacher model. After knowledge transfer, the prediction accuracy of the student model can be increased by up to 87%. Besides, it is worth noting that CIKD's inference accuracy can reach up to 100%. Moreover, the parameters constituting the student model in CIKD correspond to merely 18% of the parameters found in the teacher model, which facilitates the hardware deployment and online data processing of MFR algorithms in UVLC systems.

Additive manufacturing of an ultrastrong, deformable Al alloy with nanoscale intermetallics.

Light-weight, high-strength, aluminum (Al) alloys have widespread industrial applications. However, most commercially available high-strength Al alloys, like AA 7075, are not suitable for additive manufacturing due to their high susceptibility to solidification cracking. In this work, a custom Al alloy Al92Ti2Fe2Co2Ni2 is fabricated by selective laser melting. Heterogeneous nanoscale medium-entropy intermetallic lamella form in the as-printed Al alloy. Macroscale compression tests reveal a combination of high strength, over 700 MPa, and prominent plastic deformability. Micropillar compression tests display significant back stress in all regions, and certain regions have flow stresses exceeding 900 MPa. Post-deformation analyses reveal that, in addition to abundant dislocation activities in Al matrix, complex dislocation structures and stacking faults form in monoclinic Al9Co2 type brittle intermetallics. This study shows that proper introduction of heterogeneous microstructures and nanoscale medium entropy intermetallics offer an alternative solution to the design of ultrastrong, deformable Al alloys via additive manufacturing.

The effect of LNCRNA SHANK3 on the malignant development of gastric cancer cells by regulating the miR-4530/MNX1.

Gastric cancer (GC) has become the first malignant tumor with highest incidence rate and mortality of cancer in China, finding therapeutic targets for gastric cancer is of great significant for improving the survival rate of patients with GC. Recently, many of studies have shown that LncRNAs is involved in multiple biological progresses in the development of GC. This study, we screened for abnormally high expression of LncSHANK3 in GC through the TCGA database, and found that LncSHANK3 sponge adsorbs miR-4530, further competing with MNX1 and binding to miR-4530. We demonstrated the interaction between LncSHANK3 and miR-4530 through luciferase reporting analysis, with miR-4530 negatively regulating MNX1.Through CCK8, colony formation, transwell, and wound healing assays, it was found that LncSHANK3 affects the occurrence of GC through cell proliferation, migration and invasion. In conclusion, LncSHANK3/miR-4530/MNX1 axis is a potential mechanism for the treatment of GC.

Prognostic predictive modeling of non-small cell lung cancer associated with cadmium-related pathogenic genes.

Persistent exposure to low-dose of cadmium is strongly linked to both the development and prognosis of non-small cell lung cancer (NSCLC), yet the precise molecular mechanism behind this relationship remains uncertain. In this study, cadmium-related pathogenic genes (CRPGs) in NSCLC were identified via differential expression analysis. NSCLC patient clusters related to CRPGs were constructed through univariate Cox and K-means clustering algorithms. Multivariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were employed to determine the prognosis. Sixteen CRPGs showed a significant association with NSCLC. We found biological and prognostic differences between patients in clusters A and B. A predictive prognostic risk model for NSCLC revealed that FAM83H, MSMO1, and SNAI1 are central. Hence, the 3 hub genes were named. To further elucidate the role of CRPGs in NSCLC, A549 cells were exposed to CdCl2. The mRNA and protein expression levels of the 3 hub genes and cell invasion were detected. Moreover, 10 µM CdCl2 may increase the protein expression of 3 hub genes and enhance the invasive ability of A549 cells. This risk model may have established a theoretical foundation for investigating the mechanisms, treatment, and prognosis of NSCLC.

Wide field-of-view laser-based white light transmitter for visible light communications.

The advancement demands of high-speed wireless data link ask for higher requirements on visible light communication (VLC), where wide coverage stands as a critical criterion. Here, we present the design and implementation of a transmitter structure capable of emitting a high-power wide-coverage white light laser. This laser source exhibits excellent stability, with an irradiation range extending to a half-angle of 20°. Its high brightness satisfies the needs of indoor illumination while maintaining excellent communication performance. Utilizing bit-loading discrete multi-tone modulation, a peak data transmission rate of 3.24 Gbps has been achieved, spanning 1 to 5 m. Remarkably, the data rates exceed 2.5 Gbps within a 40° range at a distance of 5 m, enabling a long-distance, wide coverage, high-speed VLC link for future mobile network applications.

Study of equivalent circuit of GaN based laser chip and packaged laser.

High-speed GaN-based lasers play a pivotal role in visible light communication (VLC) systems; however, the causes of the limited modulation response of our fabricated laser diode (LD) are not fully understood. Accordingly, we constructed an equivalent circuit model for both the LD and its packaging. This model enabled us to analyze the series resistance and parallel capacitance of the LD at different injection currents. Experiments and simulations were performed to investigate the intrinsic responses of the LD. The series resistance and parallel capacitance are responsible for S21 roll-off at low frequencies. Determination of the packaging design parameters on the modulation response of a transistor outline (TO)-can packaged LD was investigated which is important to achieve the impedance match in the future. The value of each discrete component was determined by fitting the scattering parameters of the equivalent circuit model to the packaged LD. Reducing the series resistance and parallel capacitance improved the modulation response. Our study firstly illustrates the design and manufacture of violet-blue-green laser transmitters with a large modulation bandwidth for ultra-high-speed VLC from the point of the impedance influence.

Constructing a New Biomass-Based Bistatic Window for Solar Regulation.

Smart windows effectively respond to the ever-changing climatic conditions, offering a smart solution for low-carbon buildings. However, current smart windows derived from chromic materials often have inferior solar modulation ability, or showcase high haze that obstructs outdoor views. Here, instead of developing new chromic materials, a new bistatic window is proposed for ultra-high solar modulation and luminous transmission. The new developed window can reduce the indoor surface temperature for ≈11 °C, and reduce the building space cooling and heating energy consumption by 30% to 40%, providing significant energy-related advances over traditional smart windows. In detail, the bistatic window exhibits excellent solar modulation ability (ΔTsol = 61%), high visible transmittance in both bleached (Tlum,bleached = 91%) and colored (Tlum,colored = 56%) states, low haze (< 1%), rapid switching response (switching time < 1 min), high color rendering index (CRI > 80), and long-cyclic stability after 1000 cycles. With the advantages of facile fabrication and scalability, it is foreseen the developed bistatic window holds promising prospect for the next-generation low-carbon buildings, paving a new way for future advancements in the fields of smart windows.

Laser-Based Mobile Visible Light Communication System.

Mobile visible light communication (VLC) is key for integrating lighting and communication applications in the 6G era, yet there exists a notable gap in experimental research on mobile VLC. In this study, we introduce a mobile VLC system and investigate the impact of mobility speed on communication performance. Leveraging a laser-based light transmitter with a wide coverage, we enable a light fidelity (LiFi) system with a mobile receiving end. The system is capable of supporting distances from 1 m to 4 m without a lens and could maintain a transmission rate of 500 Mbps. The transmission is stable at distances of 1 m and 2 m, but an increase in distance and speed introduces interference to the system, leading to a rise in the Bit Error Rate (BER). The mobile VLC experimental system provides a viable solution to the issue of mobile access in the integration of lighting and communication applications, establishing a solid practical foundation for future research.

PARP inhibition leads to synthetic lethality with key splicing-factor mutations in myelodysplastic syndromes.

BACKGROUND: Splicing factors are frequently mutated in patients with myelodysplastic syndromes and acute myeloid leukaemia. Recent studies have revealed convergent molecular defects caused by splicing factor mutations, among which R-loop dysregulation and resultant genome instability are suggested as contributing factors to disease progression. On the other hand, understanding how mutant cells survive upon aberrant R-loop formation and genome instability is essential for developing novel therapeutics. METHODS: The immunoprecipitation was performed to identify R-loops in association with PARP1/poly-ADP-ribosylation. The western blot, immunofluorescence, and flow cytometry assays were used to test the cell viability, cell cycle arrest, apoptosis, and ATM activation in mutant cells following the treatment of the PARP inhibitor. The Srsf2(P95H) knock-in murine hematopoietic cells and MLL-AF9 transformed leukaemia model were generated to investigate the potential of the PARP inhibitor as a therapy for haematological malignancies. RESULTS: The disease-causing mutations in SRSF2 activate PARP and elevate the overall poly-ADP-ribosylation levels of proteins in response to R-loop dysregulation. In accordance, mutant cells are more vulnerable to the PARP inhibitors in comparison to the wild-type counterpart. Notably, the synthetic lethality was further validated in the Srsf2(P95H) knock-in murine hematopoietic cell and MLL-AF9 leukaemia model. CONCLUSIONS: Our findings suggest that mutant cells antagonise the genome threat caused by R-loop disruption by PARP activation, thus making PARP targeting a promising therapeutic strategy for myeloid cancers with mutations in SRSF2.

Advancing Ligand Docking through Deep Learning: Challenges and Prospects in Virtual Screening.

Molecular docking, also termed ligand docking (LD), is a pivotal element of structure-based virtual screening (SBVS) used to predict the binding conformations and affinities of protein-ligand complexes. Traditional LD methodologies rely on a search and scoring framework, utilizing heuristic algorithms to explore binding conformations and scoring functions to evaluate binding strengths. However, to meet the efficiency demands of SBVS, these algorithms and functions are often simplified, prioritizing speed over accuracy.The emergence of deep learning (DL) has exerted a profound impact on diverse fields, ranging from natural language processing to computer vision and drug discovery. DeepMind's AlphaFold2 has impressively exhibited its ability to accurately predict protein structures solely from amino acid sequences, highlighting the remarkable potential of DL in conformation prediction. This groundbreaking advancement circumvents the traditional search-scoring frameworks in LD, enhancing both accuracy and processing speed and thereby catalyzing a broader adoption of DL algorithms in binding pose prediction. Nevertheless, a consensus on certain aspects remains elusive.In this Account, we delineate the current status of employing DL to augment LD within the VS paradigm, highlighting our contributions to this domain. Furthermore, we discuss the challenges and future prospects, drawing insights from our scholarly investigations. Initially, we present an overview of VS and LD, followed by an introduction to DL paradigms, which deviate significantly from traditional search-scoring frameworks. Subsequently, we delve into the challenges associated with the development of DL-based LD (DLLD), encompassing evaluation metrics, application scenarios, and physical plausibility of the predicted conformations. In the evaluation of LD algorithms, it is essential to recognize the multifaceted nature of the metrics. While the accuracy of binding pose prediction, often measured by the success rate, is a pivotal aspect, the scoring/screening power and computational speed of these algorithms are equally important given the pivotal role of LD tools in VS. Regarding application scenarios, early methods focused on blind docking, where the binding site is unknown. However, recent studies suggest a shift toward identifying binding sites rather than solely predicting binding poses within these models. In contrast, LD with a known pocket in VS has been shown to be more practical. Physical plausibility poses another significant challenge. Although DLLD models often achieve higher success rates compared to traditional methods, they may generate poses with implausible local structures, such as incorrect bond angles or lengths, which are disadvantageous for postprocessing tasks like visualization. Finally, we discuss the future perspectives for DLLD, emphasizing the need to improve generalization ability, strike a balance between speed and accuracy, account for protein conformation flexibility, and enhance physical plausibility. Additionally, we delve into the comparison between generative and regression algorithms in this context, exploring their respective strengths and potential.

Synergistic Effect of Asphaltene, Resin, and Wax Improving the Emulsification and Interfacial Properties of a High-Phase-Inversion Thin Oil.

Nowadays, high-phase-inversion in situ emulsification technology has shown great potential in enhancing oil recovery from high-water-cut thin-oil reservoirs. However, emulsification characteristics, interfacial properties, and the mechanism of high phase inversion have not been systematically described. In this study, an emulsification experiment was conducted to investigate the effects of shear time, shear rate, and temperature on the phase inversion of thin oil. Furthermore, the influence of resin and wax on the dispersion of asphaltene was studied through microscopic morphology analysis. Interfacial tension measurement and interfacial viscoelasticity analysis were carried out to determine the interaction characteristics of asphaltene, resin, and wax at the interface. The results showed that, at 50 °C, the phase-inversion point of thin oil reached as high as 75%, and even at 60 °C, it remained at 70%. The shear time and shear rate did not affect the phase-inversion point of thin oil, while an increase in temperature led to a decrease in the phase-inversion point. Moreover, compared to the 20% phase-inversion point of base oil, the phase-inversion point increased with different proportions of asphaltene, resin, and wax. Particularly, at the ratio of asphaltene/resin/wax = 1:5:9, the phase-inversion point reached as high as 80%, indicating the optimal state. In this proportion, asphaltene aggregates exhibited the smallest and most uniform size, best dispersion, lower interfacial tension, and higher interfacial modulus. These findings provide reference and guidance for further enhancing oil recovery in medium-to-high-water-cut thin-oil reservoirs.

Achieving room temperature plasticity in brittle ceramics through elevated temperature preloading.

Ceramic materials with high strength and chemical inertness are widely used as engineering materials. However, the brittle nature limits their applications as fracture occurs before the onset of plastic yielding. There has been limited success despite extensive efforts to enhance the deformability of ceramics. Here we report a method for enhancing the room temperature plastic deformability of ceramics by artificially introducing abundant defects into the materials via preloading at elevated temperatures. After the preloading treatment, single crystal (SC) TiO2 exhibited a substantial increase in deformability, achieving 10% strain at room temperature. SC α-Al2O3 also showed plastic deformability, 6 to 7.5% strain, by using the preloading strategy. These preinjected defects enabled the plastic deformation process of the ceramics at room temperature. These findings suggest a great potential for defect engineering in achieving plasticity in ceramics at room temperature.

Dry-processed technology for flexible and high-performance FeS2-based all-solid-state lithium batteries at low stack pressure.

All-solid-state lithium batteries (ASSLBs) are considered promising energy storage systems due to their high energy density and inherent safety. However, scalable fabrication of ASSLBs based on transition metal sulfide cathodes through the conventional powder cold-pressing method with ultrahigh stacking pressure remains challenging. This article elucidates a dry process methodology for preparing flexible and high-performance FeS2-based ASSLBs under low stack pressure by utilizing polytetrafluoroethylene (PTFE) binder. In this design, fibrous PTFE interweaves Li6PS5Cl particles and FeS2 cathode components, forming flexible electrolyte and composite cathode membranes. Beneficial to the robust adhesion, the composite cathode and Li6PS5Cl membranes are tightly compacted under a low stacking pressure of 100 MPa which is a fifth of the conventional pressure. Moreover, the electrode/electrolyte interface can sustain adequate contact throughout electrochemical cycling. As expected, the FeS2-based ASSLBs exhibit outstanding rate performance and cyclic stability, contributing a reversible discharged capacity of 370.7 mAh g-1 at 0.3C after 200 cycles. More importantly, the meticulous dQ/dV analysis reveals that the three-dimensional PTFE binder effectively binds the discharge products with sluggish kinetics (Li2S and Fe) to the ion-electron conductive network in the composite cathode, thereby preventing the electrochemical inactivation of products and enhancing electrochemical performance. Furthermore, FeS2-based pouch-type cells are fabricated, demonstrating the potential of PTFE-based dry-process technology to scale up ASSLBs from laboratory-scale mold cells to factory-scale pouch cells. This feasible dry-processed technology provides valuable insights to advance the practical applications of ASSLBs.

Increased visceral fat area to skeletal muscle mass ratio is positively associated with the risk of metabolic dysfunction-associated steatotic liver disease in a Chinese population.

BACKGROUND: The diagnosis and comprehension of nonalcoholic fatty liver disease (NAFLD), recently redefined as metabolic dysfunction-associated steatotic liver disease (MASLD) are gaining a better understanding. In this study, we examined the association between visceral fat area and skeletal muscle mass ratio (VSR) and the prevalence of MASLD in a Chinese population. METHODS: A cross-sectional study was conducted involving 10,916 individuals who underwent bioelectrical impedance analysis, along with anthropometric and biochemical measurements, from January 2022 to June 2023. According to the VSR distribution, sex-specific quartiles of VSR within the study population were defined. Linear trend tests were performed for the categorized VSR variables. Logistic regression models were performed to estimate the odds ratio and 95% confidence intervals between VSR distribution and MASLD prevalence stratified by sex. RESULTS: The prevalence of MASLD was 37.94% in the overall population (56.34% male), and it gradually increased with higher VSR levels in both genders (P < 0.001). Logistic regression analysis demonstrated a significant association between VSR and MASLD prevalence after adjusting for confounders. The odds ratio (95% confidence interval) for MASLD, comparing the lowest to the highest VSR quartile, was 3.159 (2.671, 3.736) for men and 2.230 (1.764, 2.819) for women (all P < 0.001). Restricted cubic splines also indicated significant non-linear relationships between VSR and MASLD prevalence. CONCLUSIONS: VSR is positively associated with the prevalence of MASLD in this Chinese population, with a notably higher risk for men as VSR increases compared to women.

Computed tomography radiogenomics: A potential tool for prediction of molecular subtypes in gastric stromal tumor.

BACKGROUND: Preoperative knowledge of mutational status of gastrointestinal stromal tumors (GISTs) is essential to guide the individualized precision therapy. AIM: To develop a combined model that integrates clinical and contrast-enhanced computed tomography (CE-CT) features to predict gastric GISTs with specific genetic mutations, namely KIT exon 11 mutations or KIT exon 11 codons 557-558 deletions. METHODS: A total of 231 GIST patients with definitive genetic phenotypes were divided into a training dataset and a validation dataset in a 7:3 ratio. The models were constructed using selected clinical features, conventional CT features, and radiomics features extracted from abdominal CE-CT images. Three models were developed: ModelCT sign, modelCT sign + rad, and model CTsign + rad + clinic. The diagnostic performance of these models was evaluated using receiver operating characteristic (ROC) curve analysis and the Delong test. RESULTS: The ROC analyses revealed that in the training cohort, the area under the curve (AUC) values for modelCT sign, modelCT sign + rad, and modelCT sign + rad + clinic for predicting KIT exon 11 mutation were 0.743, 0.818, and 0.915, respectively. In the validation cohort, the AUC values for the same models were 0.670, 0.781, and 0.811, respectively. For predicting KIT exon 11 codons 557-558 deletions, the AUC values in the training cohort were 0.667, 0.842, and 0.720 for modelCT sign, modelCT sign + rad, and modelCT sign + rad + clinic, respectively. In the validation cohort, the AUC values for the same models were 0.610, 0.782, and 0.795, respectively. Based on the decision curve analysis, it was determined that the modelCT sign + rad + clinic had clinical significance and utility. CONCLUSION: Our findings demonstrate that the combined modelCT sign + rad + clinic effectively distinguishes GISTs with KIT exon 11 mutation and KIT exon 11 codons 557-558 deletions. This combined model has the potential to be valuable in assessing the genotype of GISTs.

Is RNA editing truly absent in the complex thalloid liverworts (Marchantiopsida)? Evidence of extensive RNA editing from Cyathodium cavernarum.

RNA editing is a crucial modification in plants' organellar transcripts that converts cytidine to uridine (C-to-U; and sometimes uridine to cytidine) in RNA molecules. This post-transcriptional process is controlled by the PLS-class protein with a DYW domain, which belongs to the pentatricopeptide repeat (PPR) protein family. RNA editing is widespread in land plants; however, complex thalloid liverworts (Marchantiopsida) are the only group reported to lack both RNA editing and DYW-PPR protein. The liverwort Cyathodium cavernarum (Marchantiopsida, Cyathodiaceae), typically found in cave habitats, was newly found to have 129 C-to-U RNA editing sites in its chloroplast and 172 sites in its mitochondria. The Cyathodium genus, specifically C. cavernarum, has a large number of PPR editing factor genes, including 251 DYW-type PPR proteins. These DYW-type PPR proteins may be responsible for C-to-U RNA editing in C. cavernarum. Cyathodium cavernarum possesses both PPR DYW proteins and RNA editing. Our analysis suggests that the remarkable RNA editing capability of C. cavernarum may have been acquired alongside the emergence of DYW-type PPR editing factors. These findings provide insight into the evolutionary pattern of RNA editing in land plants.

Molecular Phylogenetics and the Evolution of Morphological Complexity in Aytoniaceae (Marchantiophyta).

Aytoniaceae are one of the largest families of complex thalloid liverworts (Marchantiopsida), consisting of about 70 species, with most species being distributed in temperate areas. However, the phylogeny and evolution of the morphological character of Aytoniaceae are still poorly understood. Here, we employed two chloroplast loci, specifically, rbcL and trnL-F, along with a 26S nuclear ribosomal sequence to reconstruct the phylogeny and track the morphological evolution of Aytoniaceae. Our results reveal that Aytoniaceae are monophyletic, and five monophyletic clades were recovered (i.e., Asterellopsis-Cryptomitrium, Calasterella, Mannia, Reboulia-Plagiochasma, and Asterella). Asterella was divided into five clades (i.e., Asterella lindenbergiana, subg. Saccatae, subg. Phragmoblepharis, subg. Wallichianae, and subg. Asterella), except for Asterella palmeri, which is the sister of Asterellopsis grollei. Bayesian molecular clock dating indicates that the five primary clades within Aytoniaceae underwent divergence events in the Cretaceous period. Asterellopsis differentiated during the early Upper Cretaceous (c. 84.2 Ma), and Calasterella originated from the late Lower Cretaceous (c. 143.0 Ma). The ancestral Aytoniaceae plant is reconstructed as the absence of a pseudoperianth, lacking equatorial apertures, and having both male and female reproductive organs on the main thallus. At present, Asterellopsis consists of two species known in Asia and America with the new transfer of Asterella palmeri to Asterellopsis. A new subgenus, Asterella subg. Lindenbergianae, is proposed.