The integration of artificial intelligence (AI) and natural language processing (NLP) has gained significant attention in the education sector, particularly for enhancing adaptive learning and personalized instruction. Sentiment analysis, a key application of NLP, has shown promise in various domains, but its application to Chinese educational texts remains under-explored. This study proposes a Transformer-based multi-granularity sentiment analysis framework specifically designed for Chinese educational texts. The model processes sentiment at three levels, sentence, paragraph, and document, allowing for the extraction of nuanced emotional features that improve sentiment classification and academic performance prediction. By integrating sentiment analysis with student behavioral data, the study introduces a hybrid model that combines BERT, BiLSTM, and FNN architectures. This model significantly outperforms traditional machine learning and deep learning models, including the state-of-the-art knowledge-enhanced model, SentiLARE. Our experimental results also demonstrate the robustness of the model across different educational domains and its ability to generalize well to new, unseen data. These findings highlight the potential of NLP techniques to optimize personalized learning experiences and contribute to the development of intelligent tutoring systems.

[ Abstract ] Purpose This retrospective study aimed to identify risk factors for severe Mycoplasma pneumoniae pneumonia (SMPP) and plastic bronchitis (PB) in children, and to evaluate the predictive value of relevant biomarkers through receiver operating characteristic (ROC) curve analysis. Methods A total of 145 children with SMPP who underwent fiberoptic bronchoscopy at Dongguan People’s Hospital from April 2023 to April 2024 were enrolled, including 40 PB cases. A control group of 50 children with mild MPP was included. Clinical data, laboratory parameters were analyzed. Results 1.The univariate analysis revealed that age ≥6 years, fever duration ≥7 days, oxygen saturation <95%, and elevated IL-6 levels were significant risk factors for SMPP (P<0.05). 2. Multivariate logistic regression confirmed age >6 years and elevated serum IL-6 levels as independent risk factors for SMPP. 3. Compared to the SMPP group, the SMPP+PB group showed significantly higher rates of lung consolidation >50% on radiographs (P<0.05), longer fever duration (P<0.05), increased need for glucocorticoid/immunoglobulin therapy (P<0.05), and more frequent bronchoscopic interventions (P<0.05). However, no significant difference was observed in long-term outcomes (P>0.05). 4. The SMPP+PB group exhibited significantly higher serum IL-6, TNF-α, IFN-γ, and D-dimer levels compared to the SMPP group (P<0.05), whereas comparable MP genomic copy numbers were found in bronchoalveolar lavage fluid (BALF) (P>0.05). 5 The ROC analysis demonstrated that IL-6 had strong discriminatory power for disease severity (AUC=0.1),TNF-α, IFN-γ, and D-dimer effectively predicted PB (AUC=0.849, AUC=0.853, AUC=0.872, respectively). Conclusion Serum IL-6, TNF-α, IFN-γ, and D-dimer levels correlate with disease severity in pediatric MP infections, reflecting their roles in lung injury pathophysiology.

Communication of cells among themselves and with other organelles is one of the crucial functions of connexins. It has been well-known for years that disease is associated with structural and functional alterations in connexin proteins. Connexin 43 is the highly expressed subtype amongst the rest of the connexins. There is emerging evidence that connexin 43 is critically necessary for physiological development. In this review, we examine the current understanding of connexin 43 across various systems, including the cardiovascular, nervous, and musculoskeletal systems, as well as its implications in retinal, dermatological, renal and cancer-related conditions, along with pleiotropic syndromes like oculodentodigital dysplasia. The discussion delves into the fundamental aspects of connexin structure and function while providing insight into the techniques utilized for their detection. Furthermore, we explored the effects of both the upregulation and downregulation of connexin 43, in addition to the phosphorylation of connexin 43 in the aforementioned disorders. Our understanding of connexin 43 biology can aid in diagnosing and treating multiple diseases.

Title: Refractory Seizures in Lupus Cerebritis: Diagnostic Complexity, Immunosuppressive Challenges, and the Emerging Role of TWEAK Biomarker - A Case Report

This project explores how walking in nature can help students feel less stressed and improve their focus. We compared two groups of students: one group walked in a natural place like a park, and the other walked on a busy city street. Before and after the walk, we asked them to fill out a short stress survey and take a simple test that measured their concentration. The results showed that the students who walked in nature felt more relaxed and did better on the concentration test than those who walked in the city. This shows that spending even a short amount of time in nature can have a positive effect on students' mental health and thinking skills.  

The rapid advancement of quantum computing poses both transformative opportunities and profound challenges for modern cybersecurity and cryptography. Unlike classical computers, quantum systems leverage the principles of quantum mechanics-superposition, entanglement, and quantum tunneling-to process information in fundamentally new ways, enabling exponentially faster computation for certain problems. This paradigm shift threatens to render many of today's widely adopted cryptographic algorithms obsolete, particularly those relying on the hardness of integer factorization (e.g., RSA) and discrete logarithms (e.g., ECC and DSA). Quantum algorithms, such as Shor's algorithm, have the potential to break these cryptosystems in polynomial time, exposing sensitive data to unprecedented levels of vulnerability. Additionally, Grover's algorithm accelerates brute-force attacks on symmetric encryption schemes, reducing their effective security strength by half. This paper explores the implications of quantum computing on current cryptographic infrastructures, highlighting the urgency for transitioning to quantum-resistant or postquantum cryptographic algorithms. It examines emerging standards from bodies such as NIST, which are fostering the development and evaluation of lattice-based, codebased, multivariate polynomial, and hash-based cryptographic solutions. Furthermore, the study delves into the dual-edged nature of quantum computing in cybersecuritydiscussing its potential not only as a threat but also as a powerful tool for enhancing security through quantum key distribution (QKD), quantum random number generation, and other quantum-enhanced protocols. The work concludes by evaluating the readiness of current systems for the "quantum threat," identifying gaps in awareness, infrastructure, and policy, and proposing a strategic roadmap for a secure transition into the post-quantum era. As the quantum revolution accelerates, understanding and preparing for its cybersecurity ramifications is not merely a technical necessity but a cornerstone of global digital resilience.

What is science? Whose knowledge do you value and why? Is there room for spirituality in science? These are core questions in the third-year biology course officially titled Common Ground: Learning from the Land (BIOL3201) offered at Mt Royal University. Commonly referred to as ”Harley’s Course”, this course was co-developed with Piikani Knowledge Holder Harley Bastien. The purpose of the course is to expose students to comparative scientific perspectives - the Indigenous perspective based on relationships with creation and respect for the natural order of life, with the Western perspective based on maximizing land productivity and management. It encourages students to challenge their beliefs about what science is, who is a scientist, what it means to ‘think scientifically’, how to listen and observe, and the validity of the immeasurable. The opportunity to experience relational land-based learning, and to have the flexibility and freedom to discuss and reflect on perspectives different from the dominant Western perspective has a remarkable impact on the students. This paper includes lessons learned from the first three cohorts of students who participated in ‘Harley’s Course’ and shares some of the challenges inherent in decolonizing the Western post-secondary science curriculum.

Species that have complex courtship behaviors are some of the most evolutionarily diverse lineages observed in nature. Divergent, pre-mating calls are effective in both generating and maintaining reproductive isolation. Complex courtship displays provide numerous traits in which a small change can reinforce or lead to reproductive isolation. And display traits often evolve interactively, multiplicatively increasing the potential phenotype variants. Because many traits can be quantified and used to document variation among species, organisms that use complex courtship behaviors provide model systems for testing the influence of ecology on lineage diversification and trait evolution. Here, we quantify differences in the courtship behavior, morphology, and genetic trait change of male Photeros annecohenae over an intermediate range of geographic distances along reef habitats of the Mesoamerican barrier reef of Belize. Differences in bioluminescent ostracod behavior, morphology, and genetics have been documented across large geographic distances (500-1000 km) and at smaller geographic scales (~12km) but intermediate spatial scales have not previously been evaluated. We found significant differences in observed behavioral, morphological, and genetic traits across isolated populations of P. annecohenae resulting from both isolation by distance (IBD) and isolation by barrier (IBB). Furthermore, we describe a newly discovered downward displaying behavioral variant population of P. annecohenae nested within the upward displaying populations. The morphological, behavioral, and genetic variability documented for P. annecohenae across the 196 km seagrass mosaic of the Mesoamerican reef system offers novel insight toward our understanding of the speciation continuum and the role of complex behavioral courtship in promoting divergence within taxa.

The Brazilian Cerrado has high diversity of species with non-timber potential. Hymenaea stigonocarpa, commonly known as Jatobá-do-cerrado, is among them. This species stands out for its high economic potential, since its fruits are used in the food and pharmaceutical sectors. It is important knowing this species representatives’ yield potential to improve their fruit management practices by analyzing their morphometry in association with their competitive environment. The aim of the present study is to build a probabilistic model for H. stigonocarpa fruit yield based on dendrometric variables and competition indices. In order to do so, 60 individuals belonging to this species were sampled in a Cerrado region in Minas Gerais State. Diameter at breast height (1.30 m - dbh), total height and competition indices at distances of 3, 6 and 9m were calculated. These variables were related to fruit yield and a model was adjusted to estimate the species’ yield probability. The quality of the sampled individuals was checked and each inventoried tree was classified based on stem quality, and on crown quality and lighting. Variable DBH helped estimating the species fruits’ yield probability based on the trend of fruit yield decrease due to individuals’ DBH increase. Likewise, the semi-dependent competition index, at 3m radius, helped estimating fruit yield. Yet, the increased competition has reduced the fruit yield probability. Smaller individuals were less competitive, but they were more likely to achieve higher fruit yield probability than the bigger ones.

The DNS systems serves an important role in accessing and managing domain names. Despite its importance, DNS is vulnerable to numerous network-based attacks such as Distributed Denial-of-Service DDoS attacks. Unfortunately, no comprehensive solution has been discovered to combat such attacks. In this paper, we proposed an approach to enhance DNS security by adopting RAID technology and data coding. This approach relies on multiple independent DNS servers holding distinct coded DNS records instead of relying on a single DNS server. Our proposed solution shows efficient results in overcoming data loss and disruption of DNS server operation. This solution lies on the fact that if one server is attacked or damaged, the other servers will continue working to resolve IP addresses without disruption. The results obtained indicate that the time taken to process multiple DNS requests may slightly increase compared to single DNS operation. However, the time required for DNS recovery from DDoS attack is significantly larger when only a single server is being used, which may take hours or even days

Metabolic dysfunction-associated steatotic liver disease (MASLD) affects around 25% of the global population. It is expected to be the primary cause of end-stage liver disease and liver transplantation. Obesity is regarded as a major risk factor for MASLD. Still, there is a subset of MASLD patients who do not exhibit obesity-related traits, and this group is frequently neglected in clinical workups. It cannot be detected and treated immediately. More and more research has shown that MASLD is a multi-systemic disease that is linked not only to type-2 diabetes but also to end-stage liver disorders like cirrhosis, liver failure, hepatocellular carcinoma, cardiovascular disease, and chronic kidney disease. Furthermore, lean MASLD patients may be more likely to develop liver fibrosis and end-stage liver disease, as well as a higher risk of cardiovascular disease and mortality.

1. Identifying and characterizing stressor interactions is central to multiple-stressor research. Such interactions refer to stronger (synergism) or weaker (antagonism) joint effects of co-occurring stressors on biological entities, when compared to the predictions of a theoretical null model. Various null models have been developed and selection of the most appropriate null model for a specific research question is ideally based on assumptions on co-tolerance patterns in communities, and mechanisms of stressor effects. 2. Statistical models are commonly used to evaluate the statistical significance of interaction terms. However, they introduce constraints by imposing a specific null hypothesis on stressor combinations that cannot be flexibly changed. This can introduce a mismatch between the null model that the analyst wants to test, and the one imposed by the statistical model. 3. Here, we show under which conditions the statistical null hypothesis for interaction terms misaligns with a multiple-stressor null model and propose to resolve such misalignments using post-estimation inference. Null-model specific interaction estimates can be calculated from adjusted predictions of a fitted regression model, and associated standard errors are derived using the delta method, posterior simulations or bootstrapping. We illustrate the suggested approach with three case studies and validate statistical conclusions through data simulations. 4. Post-estimation inference has the potential to advance hypothesis-driven research on stressor interactions by flexibly testing any a priori defined null model independent from regression model structure.

Climate change is reshaping freshwater ecosystems by warming waters and modifying nutrient dynamics. These combined environmental changes exert novel gradients of selection on phytoplankton populations and communities. Temperature and phosphorus availability are individually critical determinants of growth in phytoplankton, and can have interactive impacts on population and community dynamics. While we understand how interspecific variation in thermal and resource-use traits of phytoplankton can affect community composition in response to changing environments, the extent of intraspecific variation in these responses remains poorly understood. In this study, we examined the intraspecific variation in the temperature- and phosphorus-dependences of growth in the freshwater diatom Fragilaria crotonensis. We predict that the growth of this diatom is locally adapted to the environmental conditions of the lakes of origin. To test this, we isolated strains from eight Swiss lakes (one strain per lake) with distinct historical temperatures and nutrient status. We estimated the growth rate of each strain under combined gradients of temperature and phosphorus availability. We fitted Monod curves to the growth rate data, and we quantified the minimal phosphorus requirements (P*), half-saturation constants (Ks) and maximum growth rates (μmax) for each strain as a function of temperature. We also fitted thermal performance curves and quantified activation energies (Ea) and cumulative performance across the thermal gradient as a function of phosphorus availability. We observed large intraspecific variation on the dependency of P* on experimental temperature, with strains from phosphorus-rich lakes showing stronger increases in phosphorus requirements with warming. These patterns imply local adaptation to phosphorus availability. Our findings highlight a potentially critical role for intraspecific diversity and local adaptation in shaping phytoplankton responses to global change and call for a greater recognition of this trait variation in making predictions of community-level responses to future climate.

Salt and drought represent major threats to global agricultural productivity and food security, but plants have developed a suite of adaptive responses conferring short-or longer-term survival to this stress. A new transcription factor HgMYB60 in H. glomeratus was explored to coordinate these responses. We cloned the full-length sequence of HgMYB60, determined the expressions and functions of HgMYB60, and explored the HgMYB60 assayed proteins related to sodium and potassium transport. The expression levels of HgMYB60 were increased in Arabidopsis mutants under salt and drought stress, and HgMYB60-overexpressing Arabidopsis mutants showed enhanced survival to salt and drought stress. In addition, HgMYB60 mediated sodium ion efflux and potassium ion absorption at the cellular level. HgMYB60 was localized to the nucleus, and these results are thus consistent with a major role for Na + transport in the signaling systems that respond to salt and drought stress.

CYP2D6 catalyses the metabolism of around 25% of all clinically used drugs. In Caucasians, 5-10% are homozygous carriers of variant alleles encoding no CYP2D6 enzyme activity and classified as poor metabolizers (PMs). Increased risk of supra-therapeutic concentrations and adverse effects of CYP2D6 substrates have been reported in PMs during standard recommended dosing. Recently, semi-quantitative measurements of the potato-containing compound solanidine and its CYP2D6-dependent metabolite 4-hydroxysolanidine have been shown to predict CYP2D6 PMs with excellent accuracy. We have therefore implemented these measurements as part of our routine therapeutic drug monitoring practice to provide a recommendation for genotyping in subjects using a CYP2D6 substrate. Here we report a case where solanidine and 4-hydroxysolanidine signals in a therapeutic drug monitoring (TDM) sample indicated CYP2D6 PM status in a patient who had previously been genotyped as CYP2D6 *1/*1 and interpreted as a normal metaboliser. The patients had a history of side effects during use of the CYP2D6 substrates perphenazine and aripiprazole at standard doses. Upon reanalysis with an extended genotyping panel, a rare CYP2D6 genotype (CYP2D6*7/*7) encoding PM status was revealed. The report shows the clinical value and feasibility of analysing solanidine and 4-hydroxysolanidine as part of routine TDM to identify patients predicted to be CYP2D6 PMs and who should be selected for genotyping, including patients with rare variants not included in standard genotyping panels. Solanidine and 4-hydroxysolanidine semi-quantification can be used as a complementary tool to genotyping and substantially reduce the number-needed-to-genotype for identification of CYP2D6 PMs in clinical practice.

Background Infant medulloblastoma (iMBL) are predominantly desmoplastic nodular (DN) or Medulloblastoma with Extensive Nodularity (MBEN) histology, Sonic Hedgehog (SHH) driven. Intensified chemotherapy (intraventricular chemotherapy or high-dose chemotherapy with autologous stem cell rescue) is recommended to compensate the omission of radiation. This study aims to analyse the outcomes of iMBL treated without treatment intensification. Methods This retrospective study was done on 28 patients with iMBL (children with medulloblastoma <3 years at diagnosis or 3-4 years with DN/MBEN) treated between January 2004- April 2024 in a tertiary care institute in Southern India. Results The median age at diagnosis and duration of symptoms were 24.5 months and 1 month, respectively. Vomiting (82%) and ataxia (71.4%) were the common presentations. Ventriculoperitoneal shunt or endoscopic 3 rd ventriculostomy was done in 57% patients. Twenty-four patients (~86%) underwent gross/near total resection. The most common surgical complication was cerebellar mutism (n=6, 21%). Half of the cohort had non-metastatic disease. Sixteen patients had DN/MBEN histology. Only 68%(n=19) opted to continue adjuvant therapy. Chemotherapy protocols used were Baby SFOP, HIT SKK and modified Packers. One fourth (n=7) received radiation (DN/MBEN=3, other histology=4) after 3 years of age. There was no treatment related mortality. The 5-year EFS of patients who received adjuvant treatment, DN/MBEN, non-DN/MBEN histology were 70%, 82.5% and 35.7%, respectively. Conclusions Managing medulloblastoma in infants is challenging in LMIC as significant proportion of families opt against adjuvant treatment. Although traditionally iMBL considered high risk, good outcomes can be achieved with non-intensified therapy in DN/MBEN subgroup.

Background: Evidence indicates that beta-2 microglobulin (β2M) plays a prognostic role in patients with diffuse large B-cell lymphoma (DLBCL). Aim: However, due to controversies among previous studies, this meta-analysis was conducted to evaluate the prognostic role of β2M in DLBCL patients. Materials and Methods: Relevant studies were identified through a systematic search using specific keywords in PubMed/Medline, Scopus, and Web of Science databases. Studies that provided complete information on the Hazard ratio with a 95% confidence interval for β2M with respect to overall survival (OS) and progression-free survival (PFS) in multivariate models were included in the meta-analysis. Results: A total of 30 studies, encompassing 25,128 patients, were included in this meta-analysis. The pooled analysis demonstrated a significant association between elevated β2M levels and poor OS in DLBCL patients (HR Pooled: 1.65, 95% CI: 1.45–1.88, P < 0.01). Similarly, increased β2M levels were significantly associated with lower PFS in DLBCL patients (HR Pooled: 1.54, 95% CI: 1.39–1.70, P < 0.01). Conclusion: The available evidence suggests that β2M serves as an independent prognostic marker with significant effects on OS and PFS in DLBCL patients. Elevated serum β2M levels are associated with poor prognosis and worse OS and PFS outcomes in DLBCL patients.

Myopericytoma is a relatively rare benign tumor that arises from perivascular myoid cells, these tumors typically occur in the skin, superficial soft tissues, or rarely in deeper tissues such as muscle. These are slow-growing and non-aggressive, but they can vary in size and may present as solitary nodules or masses.We describe a case of a 36-year-old male who presented with knee pain and swelling, the MRI of the knee was suggestive of soft tissue lesion in the intraarticular region. The lesion was excised, and diagnosed as Myopericytoma on histopathology.Clinically, Myopericytoma are characterized by their firm texture and well-circumscribed but unencapsulated borders. They are usually painless unless they compress nearby structures. Diagnosis often involves a biopsy for histological examination to confirm the presence of perivascular myoid cells and to rule out mimics such as solitary fibrous tumor, myofibroma and glomus tumor. Treatment typically involves surgical excision, and the prognosis is generally good with low rates of recurrence after complete removal.

Accurate generation and measurement of entangled states, such as the Bell state |Φ⁺⟩, are crucial benchmarks for assessing the capabilities and variability of Noisy Intermediate-Scale Quantum (NISQ) hardware. This work benchmarks the fidelity of preparing the |Φ⁺⟩ = (|00⟩ + |11⟩)/√2 state on different qubit pairs ([2, 3] and [7, 8]) of the ibm_kyiv quantum processor over multiple runs (N=5) and employs the deviation from perfect correlation as a quantitative analogy for the probability of unexpected decoupling in systems expected to exhibit strong correlation, such as linked economic indicators. Implementing the standard Hadamard and CNOT gate sequence for 4096 shots per run using the qiskit-ibm-runtime SamplerV2 primitive, we characterized the state preparation and measurement fidelity and applied mthree-based readout error mitigation. Experimental raw results revealed significant variability between layouts, yielding mean anti-correlated outcome probabilities P(Anti) = P(01) + P(10) of approximately 1.6% (±0.3%) for layout [2, 3] and 9.2% (±0.8%) for layout [7, 8]. This performance difference strongly correlated with reported hardware calibration metrics, particularly average readout error rates. Readout error mitigation successfully reduced P(Anti) to near-zero values (≤0.1%) for both layouts, achieving corrected correlated outcome probabilities P(Corr) = P(00) + P(11) of ~99.9-100.0%. Within our conceptual framework, the range of raw P(Anti) serves as a quantitative analogue for the likelihood of 'unexpected decoupling' under different inherent noise conditions, while the mitigated results suggest the potential to isolate underlying system dynamics from measurement noise. This research provides concrete multi-run fidelity benchmarks for ibm_kyiv, demonstrates the effectiveness of error mitigation, highlights performance variability linked to calibration data, and quantifies a range for the proposed economic uncertainty analogy.

YAP1-MAML2 Fusion in Young Children with Pediatric High Grade Glioma: A Case ReportNina Thomson1, Emily Jewels1, Samuel Bergeron-Gravel2, Simon Lagacé2, Lili-Naz Hazrati3, Stephen Saikali4, Christopher Dunham5, Sylvia Cheng1Division of Hematology, Oncology & BMT, BC Children’s Hospital, University of British Columbia, Vancouver, British Columbia, CanadaDepartment of Radiation Oncology, CHU de Québec, Université Laval, Québec, Québec, CanadaDepartment of Pathology, Faculty of Medicine and Health Sciences, McGill University, Québec, Québec, CanadaDepartment of Pathology, CHU de Québec, Université Laval, Québec, Québec, CanadaDivision of Anatomical Pathology, BC Children’s Hospital and Women’s Hospital and Health Center, Vancouver, British Columbia, Canada

Background: Mitophagy is a crucial mitochondrial quality control mechanism that removes dysfunctional mitochondria via lysosomal degradation, maintaining cellular homeostasis. Cancer cells exploit this process to sustain mitochondrial function, promote tumor renewal, and enhance therapy resistance. While mitophagy has been extensively studied in solid tumors, its role in Acute Myeloid Leukemia (AML), particularly in pediatric cases, remains largely unexplored. Therefore, this study investigated the prognostic value of pivotal mitophagy-related genes, PINK1, FUNDC1, and BNIP3, contributing to the flagging and recognition of damaged mitochondria. Methodology: Expression of PINK1, FUNDC1, and BNIP3 was analyzed using qRT-PCR in bone marrow samples from 90 pediatric AML patients and 30 controls. Kaplan-Meier survival analysis was performed to evaluate their association with overall survival (OS) and relapse-free survival (RFS) based on quartile expression. Pathway enrichment analysis was conducted using bioinformatics tools. Results: PINK1 (fold-change ~2.5, p = 0.0180) and FUNDC1 (fold-change ~4.0, p = 0.0335) were significantly upregulated in AML samples, with lower quartile expression of PINK1 strongly correlating with poor overall survival (OS) [Hazard Ratio (HR) = 3.636; 95% Confidence Interval (CI): 1.723–7.671; p = 0.0001]. Similarly, the lower quartile expression of FUNDC1 was associated with poor OS (HR = 2.027; 95% CI: 0.9474–4.339; p = 0.0384). Notably, BNIP3 expression did not differ significantly between pediatric AML and control samples (p = 0.769); however, higher quartile expression of BNIP3 was associated with poorer OS (HR = 3.238; 95% CI: 1.500–6.989; p = 0.0001). We did not observe the association of mitophagy-related genes with RFS. Pathway enrichment analysis revealed that PINK1 and FUNDC1 play key roles in mitophagy and hypoxia adaptation, while BNIP3 is primarily involved in apoptosis and cellular stress signaling. Conclusion: Overall, PINK1 and FUNDC1 may be potential prognostic biomarkers for OS in pediatric AML, emphasizing their role in mitochondrial homeostasis and leukemia progression. However, BNIP3 could also be used as prognostic markers; further validation on a large sample size is still required. This study will open a new AML diagnosis, prognosis, and therapy frontier.

Global climate change has exacerbated drought stress episodes, which are emerging as a serious threat to plant growth and productivity worldwide. In this context, melatonin has emerged as a potential signaling molecule for improved drought tolerance in plants, primarily through enhanced antioxidant defenses. Here, physiological, transcriptome, and metabolome analyses were used to investigate the physiological and molecular mechanisms of melatonin in drought stress mitigation in A. mongolicum with both drought-tolerant and drought-sensitive genotypes. Physiological results suggest that melatonin improves drought tolerance in A. mongolicum primarily by enhancing the antioxidant enzyme system. Integrated transcriptomic and metabolomic analyses have demonstrated that the tryptophan metabolic pathway plays a crucial role in melatonin-mediated enhancement of drought resistance. Notably, we report on the drought-related gene AmASMT, which encodes a melatonin biosynthesis enzyme and contributes to drought stress tolerance in A. mongolicum. We found that the AmASMT overexpressing rice lines exhibited higher endogenous melatonin levels and increased tolerance to drought stress by promoting antioxidant systems. Our findings indicate that the AmASMT plays a crucial role in regulating melatonin biosynthesis A. mongolicum while facilitating protection against drought stress. These results provides a basis for exploiting melatonin-mediated mechanisms and genetic engineering approaches to enhance plant drought tolerance.

We present the methods and results of our protein complex and RNA structure predictions at CASP16. Our approach integrated multiple state-of-the-art deep learning models with a consensus-based scoring method. To enhance the depth of multiple sequence alignments (MSAs), we employed a large metagenomic sequence database. Model ranking was performed with a state-of-the-art consensus ranking method, to which we added more scoring terms. These predictions were further refined manually based on literature evidence. For RNA, we adopted an ensemble approach that incorporated multiple state-of-the-art methods, centered around our NuFold framework. As a result, our KiharaLab group ranked first in protein complex prediction and third in RNA structure prediction. A detailed analysis of targets that significantly differed from those of other groups highlighted both the strengths of our MSA and scoring strategies, as well as areas requiring further improvement.

The CASP16 experiment provided the first opportunity to benchmark AlphaFold3. In contrast to AlphaFold2, AlphaFold3 can predict the structure of non-protein molecules, and according to the benchmark presented by the developers, it should perform slightly better than AlphaFold2 for proteins. In this study, we assess the performance of AlphaFold3 using both automatic server submissions and manual predictions from the Elofsson group. All predictions were generated via the AlphaFold3 web server, with manual interventions applied to large targets and ligands. Compared to AlphaFold2-based methods, we found that AlphaFold3 performs slightly better for protein complexes. However, when massive sampling is applied to AlphaFold2, the difference disappears. It was also noted that in the official ranking from CASP, AlphaFold3 performs better than AlphaFold2 for easier targets, but not for harder targets. Further, the performance of the AlphaFold3 server is comparable to the best methods when taking the top-ranked predictions into account, but slightly behind when examining the best out of the five submitted models. Here, there exist targets where AlphaFold3 makes a good prediction and the top-ranked method failed, and vice-versa, indicating that a venue for progress could be to develop better strategies for identifying the best model. When using AlphaFold3 to predict the stoichiometry of larger protein complexes, the accuracy is limited, especially for heteromeric targets. When analyzing the predictions including nucleic acids, it was found that, in general, the accuracy is relatively low, but the AlphaFold3 performance was not far behind the top-ranked method. In summary, AlphaFold3 provides an easy-to-use method that offers close to state-of-the-art predictions in all categories of CASP.