While a growing number of studies have shown positive effects of perturbation-based balance training on balance recovery after tripping, this training has employed specialized equipment that may pose a barrier for wider adoption. To address this, the purpose of this pilot trial was to evaluate the feasibility and preliminary efficacy of a novel, low-resource (i.e., not requiring specialized equipment) version of perturbation-based balance training referred to here as task-specific step training. Thirty community-dwelling older adults (mean (SD) age: 71.8 (4.4) years) were recruited and allocated to either step training (n = 10), traditional treadmill perturbation-based balance training (n = 10), or a control group involving no training (n = 10). Participants were then exposed to two overground laboratory-induced trips while walking on a walkway. Results showed the step training group exhibited an initial recovery step that was 9.0% body height longer (p < 0.001) and 0.25 m/s faster (p = 0.011) than the control group.The step training group also exhibited a 4.8% body height longer recovery step, and a fall rate that was 39% lower (p = 0.037) when compared to the treadmill training group after lab-induced trips. While promising, these results should be interpreted with caution give the modest sample size and a potential bias between groups with respect to safety harness usage during laboratory-induced trips. A future trial with adequate statistical power to better evaluate efficacy and effectiveness of this step training on real-world trip and fall risk appears warranted. The study was registered on clinicaltrials.gov (NCT05734443).
Remote patient monitoring (RPM) expanded dramatically during the COVID-19 pandemic and continues to be implemented. However, no standardized method for classifying them exists which has implications for comparative evaluations. Our goal was to design and develop a disease-agnostic RPM typology tool as a first step towards a standardized approach for understanding and implementing RPM programs for different clinical use-cases. Guided by the Knowledge-To-Action framework, we conducted a rapid review of RPM programs from Canada, the United States, Europe, the United Kingdom, and Australia that were used to manage diabetes, chronic obstructive pulmonary disease, congestive heart failure, hypertension, and COVID-19. We identified 87 articles to define common characteristics of real-world RPM interventions to enable comparison across different programs through pattern recognition, information mapping, and sensemaking. We extracted data with a macros-enabled Excel template. Design sessions with key stakeholders (researchers, clinical advisors, provincial RPM managers, and patient partners) provided iterative feedback on the typology and we defined a glossary of characteristics. The 12 most reported characteristics of RPM programs (including size, resources, monitoring team, data flow, alert protocol, workflow, and equity considerations) were clustered into four domains. Integration and equity domains were recognised as ideal aspirations of all RPM programs. Technology and touch domains were considered to exist on a spectrum from low-to-high- neither inherently superior to the other. 16 distinct RPM typologies were expressed through a 4x4 matrix (i.e., high or low on each of the four domains). Using this tool can inform insights on program maturity, implementation, and continued investments in RPM. We anticipate this typology will help new initiatives have greater potential to be robustly evaluated and sustained to scale. Future directions include further validity testing and exploring feasibility to systematically categorise real-world RPM programs with this tool.
Worldwide, 451 million people and up to 156 million children are infected with hookworm, causing an estimated 3.2 million disability-adjusted life-years annually. We conducted a two-year longitudinal cohort study of hookworm infection with a random selection of 274 school-age children (4-16 yrs) in rural Ghana to identify nutritional and environmental exposures impacting hookworm infection and response to treatment. Every six months (baseline Jan 2013) we collected anthropometric measurements, pre- and post-treatment fecal samples, and blood samples. Household surveys and multiple-pass twenty-four-hour recalls were conducted at baseline and 18 months. Seventy-eight participants (28.5%) were absent from at least 1 time point. Of the 196 that were screened at all five time points, 87 (44.4%) were hookworm-infected>1 time. Assessment of albendazole treatment response was conducted on 83 participants. Sixty (72.3%) were cleared of hookworm infections while 23 (27.5%) remained infected post-treatment (ERR: 0-99%). Treatment efficacy was more likely among children aged over 9.66 years (HR: 1.55; 95% CI: 1.18, 2.04) and those from food-insecure households (HR: 2.26; 95% CI: 1.06, 4.81). Hookworm infection status and albendazole treatment outcome at baseline and 18 months were the dominant influences on infections at 6 and 24 months, respectively. Future risk of infection at both 6 and 24 months had significant environmental and nutritional predictors, although the variables differed. Global school-based deworming has been associated with reduced rates of hookworm infection among schoolchildren in Africa; however, additional strategies will be necessary for long-term, sustainable control. This study reports on an innovative two-year longitudinal study of school age children with repeated cycles of testing and treatment. We modelled hookworm infection as a function of predictors that were measured six months prior, thereby strengthening the assessment of causal relationships between environmental, infection and nutritional risk factors.
Neurodegenerative diseases, including Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD), are progressive disorders with limited therapeutic options. Centella asiatica (C. asiatica), a medicinal and edible plant, has been reported to exert neuroprotective and anti-neuroinflammatory properties. Yet, the mechanisms underlying its effects against neurodegenerative diseases remain largely unclear. We employed an integrative strategy combining network pharmacology, transcriptomic analyses, machine learning and molecular docking to prioritize disease-associated molecular networks and candidate compound-target relationships in AD, PD and HD. Sixteen candidate constituents of C. asiatica met the predefined drug-likeness, gastrointestinal absorption and blood-brain barrier permeability criteria, yielding 370 unique predicted targets. Disease-gene mining identified 983 AD-associated genes, 1,103 PD-associated genes, and 3,316 HD-associated genes. Integration of compound targets, disease-associated genes, and transcriptomic profiles prioritized five hub genes in PD (CCKAR, MAPK8, PSEN2, SLC6A3, and TH), four in AD (APP, PGK1, PIK3CA, and TTR), and four in HD (CHRND, HSP90AA1, PRKCQ, and TH). Enrichment analyses highlighted disease-relevant processes involving neurotransmitter signalling, cAMP and calcium pathways, MAPK-related responses and inflammatory regulation. ROC analyses provided additional support for the discriminatory performance of the prioritized genes in independent datasets, whereas molecular docking identified favourable predicted Vina docking scores and structurally plausible interactions between selected compounds and hub targets. This integrative computational analysis prioritizes candidate C. asiatica constituents, putative disease-associated targets, and molecular pathways in AD, PD, and HD. The findings provide a foundation for subsequent biochemical, cellular, and in vivo validation.
Arthropod-borne viruses (arboviruses) such as dengue virus pose a significant and growing threat to human health worldwide. Maintained in a transmission cycle between arthropod vectors and vertebrate hosts, arboviruses experience strong bottlenecks during transmission which can drastically alter virus population composition and fitness. In vectors, severe population bottlenecks occur at the initial site of infection, the midgut, yet the specific factors driving this process remain unclear. To investigate these mechanisms, we need a better understanding of early infection events; however, traditional detection methods lack the necessary sensitivity. Recent advances in molecular signal amplification-based methods now make it possible to study these early stages in detail. In this study, we examined early dengue virus 2 (DENV-2) infection of Ae. aegypti midguts using multiple hybridization chain reaction techniques. We demonstrate that these techniques are much more sensitive than the traditional immunofluorescence assay and can reliably detect DENV-2 in mosquito midguts as early as 6 hours post infection. Further, we observed significant bottlenecks as only a handful of virions initiate infection of the midgut. The application of signal amplification strategies now enables critical assessment of the cellular and molecular interactions governing early infection events which could inform the development of novel interventions.
Human gnathostomiasis is a foodborne zoonotic nematode infection caused by the larval stage of Gnathostoma species. Although historically reported predominantly from Asia and America, cases are increasingly identified in previously non-endemic regions. The heterogeneous clinical presentation and diagnostic challenges likely contribute to underrecognition of the global disease burden. Current evidence is largely derived from case reports and case series, with a notable lack of prospective studies. To better delineate the epidemiological distribution and clinical characteristics of human gnathostomiasis, we systematically reviewed and analyzed the available literature. Most cases are reported from Asia and the Americas, with Thailand, Japan, and Mexico accounting for the highest numbers. Clinical manifestations are predominantly larva migrans syndromes, including cutaneous involvement (83.6% of cases), followed by neurological (7.7%), ocular (3.5%), and visceral (2.3%) presentations. Long-term sequelae are uncommon overall but occur frequently in ocular (51.8%) and neurological (32.2%) disease, the latter also being associated with a substantial case-fatality rate (33.9%). Diagnosis is based on exposure risk, most commonly consumption of raw fish (70.7%), as well as laboratory findings such as eosinophilia, positive serology, and, when feasible, histopathological confirmation. Treatment primarily relies on anthelmintic treatment with albendazole and/or ivermectin and, if feasible, surgical removal of larvae. Treatment success is highest with albendazole plus ivermectin combination therapy (86.7%) compared to monotherapy with albendazole (73.5%) or ivermectin (56.7%).
Gastrointestinal stromal tumors (GIST) are the most common gastrointestinal soft tissue sarcoma. Tyrosine kinase inhibitors are guideline-recommended therapy; however, resistance often occurs, requiring subsequent therapy. Regorafenib is a multikinase inhibitor approved for third-line therapy. Real-world data surrounding regorafenib's use and place in therapy are limited. To understand real-world regorafenib utilization and patient characteristics among US patients with advanced GIST. This retrospective cohort claims analysis used data from Merative™ MarketScan® research databases and included patients with ≥1 pharmacy claim for regorafenib during the identification period (10/2015-5/2023) and ≥1 GIST diagnoses any time prior to/on index date (first regorafenib prescription claim). Primary outcomes included duration of therapy (DOT) and time to next therapy (TTNT). Outcomes were stratified based on prior GIST treatment during the baseline period (BL) and initial regorafenib dose (i.e., low dose [LD] or regorafenib standard dose [RSD]) as of the index date. Nearly half (45.2%) of patients received imatinib and sunitinib prior to regorafenib initiation, and 73.5% received RSD. Patients who received prior imatinib or sunitinib alone before regorafenib had a numerically longer median DOT with regorafenib than those who received both in the BL before regorafenib (142.5 days [IQR: 87-257.5] vs 95 days [IQR: 53-192]). Patients receiving LD and RSD demonstrated similar median DOT (103.0 days [IQR: 41.5, 210.5] vs 94.5 days [IQR: (35.0, 171.0]) and TTNT (143 days [IQR: 70-293] vs 141 days [IQR: 77-191]). Patients on LD and RSD had similar DOT and TTNT. Acknowledging the limitations from this real-world data, patients with prior imatinib or sunitinib alone appeared to have longer DOT on regorafenib than those who received both. Further research is warranted to explore the clinical benefits of these differences.
Plastic consumption has become pervasive in modern society, with over 300 million metric tonnes produced annually worldwide, contributing significantly to municipal waste. In Bangladesh, where annual per capita plastic use has risen to 22 kg as of 2022, innovative solutions for managing plastic waste are urgently needed. This research introduces a novel approach to the pyrolysis of various plastics (PET, PVC, PP, HDPE) within a temperature range of 300 °C to 550 °C to produce pyrolytic bio-oil and biochar. We established optimal conditions for each plastic type-500 °C for PET, PVC, and HDPE, and 450 °C for PP-resulting in maximized yields of high-quality liquid oils (61.3% for PP and 47.23% for HDPE). Unique to this study, we innovatively adjust the pyrolysis process parameters to enhance the yield and quality of the derived bio-oils, tailored specifically to the types of plastics treated. The liquid products were characterized as predominantly consisting of C6-C16 hydrocarbons, aligning them closely with naphtha, gasoline, and diesel specifications, suitable for use as renewable fuels. Furthermore, our research applies FTIR and GC-MS analyses in a novel way to provide a detailed examination of these bio-oils, revealing significant quantities of paraffinic hydrocarbons in PP and olefins and naphthenes in HDPE, contributing to their potential fuel applications. The solid char byproducts were also comprehensively characterized using SEM and XRD, providing insights into their suitability for various industrial applications. This study not only demonstrates the potential of pyrolysis to transform waste plastics into valuable renewable energy resources but also advances the technological framework for sustainable waste management practices, marking a significant leap forward in the efficiency and application of plastic waste conversion technologies.
Mentha species are widely cultivated aromatic plants valued for their essential oils and antimicrobial properties. However, despite their agricultural and pharmacological significance, limited information is available on how different Mentha species influence rhizosphere microbial communities and their relationships with soil physicochemical parameters and essential oil composition. In this study, we examined the rhizosphere microbiota of three closely related taxa - Mentha × villosa B10, M. spicata B17, and M. suaveolens J17 - cultivated under uniform field conditions. Rhizosphere and bulk soils were analyzed for physicochemical properties, microbial composition (16S rRNA, ITS sequencing), essential oils (gas chromatography-mass spectrometry), and arbuscular mycorrhizal colonization. Bacterial communities were dominated by the phyla Actinomycetota, Pseudomonadota, Acidobacteriota, Bacillota, and Chloroflexota, while fungal communities were primarily composed of Ascomycota, Mortierellomycota, Basidiomycota, and Rozellomycota. Rhizosphere soils exhibited higher fungal diversity than bulk soils, with Glomeromycota detected exclusively in rhizosphere. Microbial community composition differed significantly among Mentha taxa: M. spicata B17 displayed the lowest bacterial diversity, the most distinct microbial assemblages, and the highest arbuscular mycorrhiza colonization. Soil properties - particularly humus content, phosphorus, potassium, and sodium - were strongly correlated with bacterial diversity, while fungal communities showed weaker associations. Integration of essential oil data revealed genotype-dependent chemical profiles: Mentha × villosa B10 and M. spicata B17 were characterized by high proportions of L-carvone and limonene, whereas M. suaveolens J17 was dominated by cis-piperitone epoxide and piperitenone oxide. Together, these findings demonstrate that even closely related Mentha cultivars can harbor distinct rhizosphere microbiota, associated with both plant chemical traits and soil characteristics. This study highlights the complex interactions between aromatic plants, soil chemistry, and microbial communities, offering novel insights into plant-soil-microbe interactions in medicinal and aromatic crop systems.
Slow, endogenous brain rhythms in the auditory cortex are hypothesized to track acoustic amplitude modulations during speech comprehension. Temporal predictions from the motor system are thought to enhance this tracking. However, direct evidence for the involvement of endogenous auditory and motor brain rhythms is lacking. Combining magnetoencephalographic recordings with behavioral data, we here show that endogenous peak frequencies of individuals' resting-state theta rhythm in superior temporal gyrus predict speech tracking during comprehension. Importantly, endogenous rates of speech motor areas predicted auditory-cortical speech tracking only in individuals with high auditory-motor synchronization profiles. Higher rates in the supplementary motor area and lower rates in inferior frontal gyrus predicted stronger tracking. These findings provide support for oscillatory accounts of auditory-motor interactions during speech perception. Behaviorally, higher auditory-motor synchronization was related to higher comprehension, with effects of the spontaneous speech motor production rate only in high synchronizers. Working memory capacity predicted speech comprehension performance only in individuals with low auditory-motor synchronization profiles. No significant relationship between the neural data and behavioral readouts was observed. The findings highlight differential speech processing preferences across individuals, with an auditory-motor route related to enhanced comprehension performance.
Podocyte injury is a central driver of progressive glomerular diseases, yet the temporal organization of podocyte-intrinsic responses remains incompletely defined. In this study, we performed an integrated re-analysis of two publicly available mouse transcriptomic datasets (GSE108629 and GSE151869) to identify conserved molecular responses to LMB2-induced podocyte injury across comparable post-injury time points. Differential expression analysis was conducted independently at Day 4 and Day 7 in each dataset, followed by cross-dataset integration at each time point by identifying shared differentially expressed genes (DEGs) with consistent directionality. The resulting Day 4 and Day 7 shared gene sets were subsequently combined to define a final pooled shared DEG set. Functional enrichment, network analysis, upstream regulator prediction, and gene set enrichment analysis (GSEA) were used to characterize conserved biological processes and regulatory features. We identified 1,418 and 1,401 shared DEGs at Day 4 and Day 7, respectively, with 725 genes defining the final pooled shared DEGs set. At Day 4, the transcriptional response was characterized by inflammatory signaling and adaptive stress-related pathways, including endoplasmic reticulum stress. By Day 7, this response expanded to include extracellular matrix remodeling, focal adhesion reorganization, sustained inflammatory signaling, and downregulation of autophagy-lysosome pathways, together with disruption of ER-to-Golgi trafficking. Network analysis highlighted RELA-centered regulatory modules alongside epigenetic- and kinase-associated regulators. Collectively, these findings support a conserved, cross-dataset biphasic transcriptional response to podocyte injury, characterized by an early adaptive inflammatory phase followed by a later maladaptive state involving extracellular remodeling and impaired proteostasis. This framework provides a reproducible, temporally organized injury signature and is consistent with stage-specific pathways as potential targets for future mechanistic and therapeutic studies.
Seepage-erosion-induced water inrush in karst cavities is a typical form of water-inrush disaster in karst tunnels. It is governed not only by the spatial distribution of karst cavities and hydraulic recharge conditions, but also by the particle-size gradation and composition of the cavity fill. During seepage erosion, fill particles are progressively transported by flowing water, which may trigger a sudden water-inrush catastrophe. To reveal the catastrophe mechanism and establish early-warning indicators, this study employs the Smoothed Particle Hydrodynamics (SPH) method to simulate the evolution of seepage-erosion-induced water inrush under different particle-size gradations, cavity confining stresses, and seepage velocities. The inflection point of the cumulative particle loss rate is used as an indicator of catastrophic transition. The relationships among particle-size gradation, confining stress, seepage velocity, and particle loss rate at the transition point are then analyzed to determine early-warning thresholds. The results show that fill-particle loss is positively correlated with both seepage velocity and confining stress. When the content of fine particles, such as rock cuttings and fine sand, exceeds 60%, the inflection point corresponds to a seepage velocity of 1.6 m/s and a confining stress of 2.6 MPa, with an early-warning particle-loss range of 8%-15%. When the content of coarse particles, such as coarse sand and gravel, exceeds 40%, the inflection point corresponds to a seepage velocity of 3.0 m/s and a confining stress of 4.5 MPa, with an early-warning particle-loss threshold of approximately 45%.
Typhoid is a significant global health challenge due to its high pathogenicity and antimicrobial resistance. Salmonella typhi (S.typhi) can switch its lifestyles between biofilm and planktonic phase which allows it to evade host defenses and develop resistance to antibiotics. Salmonella sp. harbors multiple genes encoding efflux-pumps systems whose up-regulation contributes to multi-drug resistance (MDR) and extensive drug-resistance (XDR). To overcome the battle against resistant S. typhi strains, novel non-antibiotics inhibitors are required for inhibitory application. This study assesses the inhibitory effect of lignans against drug resistance of S. typhi. Clinical resistant and sensitive strains of S. typhi were obtained and characterized. The inhibitory effect of lignans, specifically Schisandrin A and B, purified from the plant Schisandra chinensis, are found to be effective non-antibiotic inhibitors were evaluated through standard microbiological techniques like growth curve and time-kill assays. Impact on bacterial morphology was analyzed using scanning electron microscopy (SEM). Our study explores two approaches, such as efflux pumps (EPs) inhibition and antibiofilm assays. Using colony-forming unit (CFU) assays, growth curve analysis, and SEM imaging, we observed significant bacteriostatic effects, with Schisandrin B causing notable membrane disruption. Schisandrin B also showed remarkable biofilm inhibition (90.33%) and strong efflux pumps inhibition. This study offers a strong basis for future research on addressing antibiotic resistance in clinically relevant pathogens.
In scientific studies of human-AI interaction dynamics, researchers often need to present participants with opportunities to interact with live large-language models (LLMs). However, technical and practical challenges (from survey platform limitations and logging chat data to manipulating AI behaviors for experimental designs) often inhibit survey-based deployment of AI stimuli. We developed DiSCoKit-an open-source toolkit for deploying live LLM experiences (e.g., ones based on models delivered through Microsoft Azure portal) through JavaScript-enabled survey platforms (e.g., Qualtrics). We describe the toolkit's scientific motivation, architecture, and operation. We also offer an example of toolkit deployment and customization, along with discussing its possibilities and limitations. Altogether, DiSCoKit gives researchers a flexible, secure, scalable solution for deploying naturalistic LLM stimulus experiences through online surveys.
Dengue virus (DENV) represents a growing global health challenge with billions of people at risk. Severe Dengue (SD), a complication of DENV infection that involves generalized hemorrhage, is driven, at least in part, by endothelial dysfunction. Endothelial dysfunction refers to increased permeability due to inflammation, mechanical injury and/or modification of the genetic program of endothelial cells. Previous work showed that exposure of endothelial cells to conditioned media from DENV-infected cells (CMDV) increased permeability and cellular stiffness, repressed endothelial markers and induced mesenchymal genes. However, the generality, extent, mechanism and ultimate impact of these events in the onset of SD remain elusive. Here, we integrate analysis from in vitro treatment of endothelial cells with media containing UV-inactivated DENV with computational modeling to investigate the key features of CMDV-induced endothelial alterations and their potential impact on endothelial dysfunction. We found that CMDV increased SNA1 and CDH2 expression, while suppressing endothelial genes OCLN and CDH5. Global transcriptomics analysis revealed that CMDV triggered a transient pro-inflammatory response, followed by induction of selected tissue repair genes and matrix remodeling. A non-directed asynchronous network model (NDAM-CMDV) identified IL6 and FN1 as central nodes of DENV-induced endothelial trans-differentiation, providing new molecular insights that predict the evolution of the disease and identify potential therapeutic targets.
Getah virus (GETV), a mosquito-borne alphavirus, poses an emerging threat to public health with its increasingly broad host spectrum. While glycosaminoglycans (GAGs) serve as critical attachment factors for many alphaviruses and the low-density lipoprotein receptor (LDLR) facilitates the cellular entry of several members, the precise viral determinants governing these interactions and their implications for viral virulence remain poorly defined. Here, we introduced an H86Y substitution, a potential adaptive mutation site, within the E2 glycoprotein of GETV using reverse genetics. The H86Y mutant replicated more efficiently in mosquito C6/36 cells but was consistently attenuated across several mammalian cell lines. In susceptible mouse models, H86Y infection led to reduced viral loads, milder histopathology, and lower inflammatory responses compared with the parental virus, yet still elicited robust protective immunity in adult mice. Mechanistically, a series of functional assays, including infection in GAG-deficient cells, decoy inhibition, co-immunoprecipitation, receptor overexpression and knockdown, and biolayer interferometry, demonstrated that the residue 86 in E2 glycoprotein is a critical determinant for GETV binding to both GAGs and LDLR. The H86Y mutation concurrently reduces these interactions, contributing the impairment of virus attachment and entry into mammalian cells. Furthermore, the GAG-binding site functionally overlaps with the LDLR interaction interface. In LDLR-deficient suckling mice, the impaired replication of H86Y persisted in examined tissues. However, pre-treatment with heparinase nearly completely eliminated this attenuation phenotype, further confirming that LDLR and GAG are the key host factors mediating attenuation phenotype for H86Y. In summary, the residue 86 of the GETV E2 glycoprotein represents a determinant of viral virulence, and an H86Y mutation attenuates GAGs and LDLR-dependent infection, providing mechanistic insights into alphavirus-host interactions and a potential target for antiviral and vaccine development.
Accurate prediction of Remaining Useful Life (RUL) is critical for predictive maintenance and minimizing downtime in industrial systems. This paper presents a cross-domain deep learning framework based on a hybrid Convolutional Neural Network-Bidirectional Long Short-Term Memory (CNN-BiLSTM) architecture. Unlike domain-specific models that require handcrafted features, the proposed framework extracts local degradation features through CNN layers and captures long-term dependencies via BiLSTM networks. The model is evaluated on three heterogeneous datasets: construction machinery, continuous casting machines, and lithium-ion batteries. Experimental results show that CNN-BiLSTM consistently outperforms baselines, achieving up to 22% lower RMSE compared to GRU and 30-50% lower RMSE compared to traditional models. On the construction dataset, it achieves an MAE of 48.2 hours and RMSE of 67.1 hours (R2 = 0.88), outperforming GRU by 20%. For the casting dataset, the model attains an MAE of 87.6 tons and RMSE of 113.9 tons (R2 = 0.87), surpassing Random Forest by over 35%. On the battery dataset, CNN-BiLSTM reduces the MAE to 49.6 cycles and RMSE to 72.8 cycles (R2 = 0.89), while also achieving the lowest Timeliness Score (27.5) and PHM08 Score (192.4). Cross-domain experiments are evaluated under two settings: zero-shot transfer, where the model is trained on one source domain and directly tested on a different target domain without using labeled target-domain samples, and fine-tuned transfer, where 20% of labeled target-domain samples are used to update only the fully connected layers while keeping the CNN and BiLSTM layers frozen. The zero-shot results reflect the effect of domain shift, while the fine-tuned results show that lightweight transfer adaptation reduces RMSE by 25-40% across domains. These findings indicate cross-domain adaptability under limited target-domain supervision rather than fully unsupervised cross-domain generalization. These results highlight the feasibility of a unified CNN-BiLSTM framework for scalable, cross-domain RUL estimation and its suitability for real-world prognostic applications.
High temperature is one of the major environmental stressors that severely affects plant growth. Paris polyphylla var. yunnanensis, a traditional Chinese herbal medicine, is sensitive to high temperature. However, the underlying mechanisms of its response to high temperature remain unclear. In this study, we investigated the physiological and proteomic change of P. polyphylla var. yunnanensis under different treatments (25°C, 30°C, 35°C, 40°C). Our results showed that high temperature directly impaired photosynthesis and disrupted metabolism, evidenced by reduced chlorophyll and photosynthetic rate, as well as accumulated proline and increased conductivity. A total of 893 differentially expressed proteins (DEPs) were identified, with significant changes in the expression levels of enzymes associated with protein processing and synthesis. Additionally, the expression levels of key proteins involved in the circadian pathway and the glutathione pathway were also notably upregulated. Dynamic changes in the endocytosis and autophagy-related proteins ATG3 and ATG8C were also observed, suggesting that these processes may play a significant protective role under high-temperature stress. Overall, this study provides an important starting point for improving the heat tolerance of P.polyphylla var. yunnanensis through genetic engineering.
1,5-Anhydrohexitol nucleic acid (HNA) is a promising xeno nucleic acid (XNA) for applications such as aptamers and catalysts, due to its favourable physico-chemical properties. Realizing this potential requires efficient and high-fidelity polymerases capable of processing HNA. A key component are HNA reverse transcriptases that convert HNA into DNA, an essential step in standard SELEX workflows. Although HNA reverse transcriptases have been generated by directed evolution, structural insight is essential to guide further enzyme engineering. Here, we report the 2.8 Å crystal structure of the engineered HNA reverse transcriptase KOD-H4, derived from the B-family DNA polymerase of Thermococcus kodakarensis, captured in a closed ternary complex with dATP, a 3'-terminated primer and a mixed HNA/DNA template. Compared to a previously reported open ternary KOD-H4 structure, the presented structure adopts a more closed conformation with increased finger and thumb domain closure and formation of a canonical Watson-Crick-Franklin base pair at the insertion site. Direct downstream nucleotides show more distorted base pairing and one HNA residue transits from the unusual 1C4 conformation it adopted in the open complex to the 4C1 hexitol sugar conformation. These findings demonstrate that KOD-H4 can form a closed, pre-catalytic complex resembling that of the wildtype enzyme with natural substrates, and reveal state-dependent conformational flexibility of HNA. Such flexibility should be considered in the design and optimization of enzymes that process HNA.
Early Support Hubs have recently become widespread in the UK and aim to provide community-based, easy access mental health support to young people aged 11-25, integrating a variety of forms of support. Evidence is needed on the role such services aim to fulfil in addressing young people's mental health needs, perceived good practice in their operations and challenges encountered in achieving this. In order to understand this, we conducted individual interviews with 24 staff members from eight Hubs across England; data was analysed using codebook thematic analysis. Several structural-, organisational- and individual-level factors were identified, including: Hubs' service model and role in care pathway; service culture; staff characteristics, and staff and young people interactions.  The Early Support Hub model was perceived to provide a valuable and distinctive contribution to mental health support for young people, including a youth-centred and holistic approach, easy accessibility (e.g. self-referrals, no minimum thresholds for access), non-clinical service settings, and a diverse and compassionate workforce. Several constraining factors were identified, including the challenge of providing early intervention support to all young people whilst also ensuring the needs of those with significant mental health difficulties are met; short-term funding affecting sustainability, and challenges in recruiting and retaining staff with the desired qualities and values. Research is needed to further understand the Hubs' role in the system as a whole, their overall impact on addressing the rising burden of young people's mental ill health, and how well-functioning local service systems that do not result in significant gaps in provision can be established.