Search Results (120)

This study performed a phylogenomic analysis of the C2H2 gene family across 30 Basidiomycota species, identifying 1032 genes distributed across six evolutionary clades (Groups I–VI). Functional diversification and lineage-specific expansions were observed: Group II (37.1%) formed a conserved core, while wood decayers (e.g., Schizophyllum commune) and edible fungi (e.g., Pleurotus ostreatus) exhibited clade-specific expansions in Groups III and V, respectively. Physicochemical profiling revealed an acidic bias in Agaricomycotina proteins (pI 4.3–5.8) compared to alkaline trends in pathogens (Ustilaginomycotina/Pucciniomycotina; pI 8.3–8.6). Comparative genomics indicated that saprotrophs retained long genes (12.4 kb) with abundant introns (mean = 6.2/gene), whereas pathogens exhibited genomic streamlining (introns ≤ 2). Synteny network analysis revealed high ancestral conservation in core clusters (Cluster_1–2: 58% homologs) under strong purifying selection (Ka/Ks = 0.18–0.22), while peripheral clusters (Cluster_Mini) approached neutral evolution (Ka/Ks = 0.73). This study reveals stage-specific expression dynamics of 17 C2H2 zinc finger genes in Sarcomyxa edulis, highlighting their roles in coordinating developmental transitions (e.g., SeC2H2_1 in low-temperature adaptation, SeC2H2_7/12 in primordia initiation, and SeC2H2_8/9/13 in fruiting body maturation) through temporally partitioned regulatory programs, providing insights into fungal morphogenesis and stress-responsive adaptation. These findings underscore the dual role of C2H2 genes in sustaining conserved regulatory networks and facilitating ecological adaptation, providing new insights into fungal genome evolution. Full article

To address the core challenges in multi-robot path planning (MRPP) within large-scale, complex environments—namely path conflicts, suboptimal task allocation, and computational inefficiency—this paper introduces a Hybrid Clustering-Enhanced Brain Storm Optimization (HC-BSO) algorithm designed to improve both path quality and computational efficiency significantly. For optimizing initial task assignment, the conventional K-Means clustering method is supplanted by a hybrid clustering methodology that integrates Mini-Batch K-Means with Density-Based Spatial Clustering of Applications with Noise (DBSCAN), facilitating an efficient and robust partitioning of task points. Concurrently, we incorporate a two-stage exploration–perturbation evolutionary strategy. This strategy effectively balances global exploration with local exploitation, thereby enhancing solution diversity and search depth. Comparative analyses against the standard Brain Storm Optimization (BSO) and other prominent swarm intelligence algorithms reveal that HC-BSO exhibits significant advantages in terms of total path length, computational time, and path conflict avoidance. Notably, in large-scale, multi-task scenarios, HC-BSO consistently generates high-quality, conflict-free paths, demonstrating superior stability, convergence, and scalability. Full article

Large-language models (LLMs) show promise for automating evidence synthesis, yet head-to-head evaluations remain scarce. We benchmarked five state-of-the-art LLMs—openai/o1-mini, x-ai/grok-2-1212, meta-llama/Llama-3.3-70B-Instruct, google/Gemini-Flash-1.5-8B, and deepseek/DeepSeek-R1-70B-Distill—on extracting protocol details from transcranial direct-current stimulation (tDCS) trials enrolling older adults. A multi-LLM ensemble pipeline ingested ClinicalTrials.gov records, applied a structured JSON schema, and generated comparable outputs from unstructured text. The pipeline retrieved 83 aging-related tDCS trials—roughly double the yield of a conventional keyword search. Across models, agreement was almost perfect for the binary field brain stimulation used (Fleiss κ ≈ 0.92) and substantial for the categorical primary target (κ ≈ 0.71). Numeric parameters such as stimulation intensity and session duration showed excellent consistency when explicitly reported (ICC 0.95–0.96); secondary targets and free-text duration phrases remained challenging (κ ≈ 0.61; ICC ≈ 0.35). An ensemble consensus (majority vote or averaging) resolved most disagreements and delivered near-perfect reliability on core stimulation attributes (κ = 0.94). These results demonstrate that multi-LLM ensembles can markedly expand trial coverage and reach expert-level accuracy on well-defined fields while still requiring human oversight for nuanced or sparsely reported details. The benchmark and open-source workflow set a solid baseline for future advances in prompt engineering, model specialization, and ensemble strategies aimed at fully automated evidence synthesis in neurostimulation research involving aging populations. Overall, the five-model multi-LLM ensemble doubled the number of eligible aging-related tDCS trials retrieved versus keyword searching and achieved near-perfect agreement on core stimulation parameters (κ ≈ 0.94), demonstrating expert-level extraction accuracy. Full article

The latest research indicates that Large Vision-Language Models (VLMs) have a wide range of applications in the field of remote sensing. However, the vast amount of image data in this field presents a challenge in selecting high-quality multimodal data, which are essential for saving computational resources and time. Therefore, we propose an adaptive fine-tuning algorithm for multimodal large models. The core steps of this algorithm involve two stages of data truncation. First, the vast dataset is projected into a semantic vector space, where the MiniBatchKMeans algorithm is used for automated clustering. This classification ensures that the data within each cluster exhibit high semantic similarity. Next, the data within each cluster are processed by calculating the translational difference between the original and perturbed data in the multimodal large model’s vector space. This difference serves as a generalization metric for the data. Based on this metric, we select data with high generalization potential for training. We apply this algorithm to train the InternLM-XComposer2-VL-7B model on two 3090 GPUs, using one-third of the GeoChat multimodal remote sensing dataset. The results demonstrate that our algorithm outperforms state-of-the-art baselines. The model trained on our optimally chosen one-third dataset, as validated through experiments, showed only a 1% reduction in performance across various remote sensing metrics compared to the model trained on the full dataset. This approach significantly preserved general-purpose capabilities while reducing training time by 68.2%. Furthermore, the model achieved scores of 89.86 and 77.19 on the UCMerced and AID evaluation datasets, respectively, surpassing the GeoChat dataset by 5.43 and 5.16 points. It only showed a 0.91-point average decrease on the LRBEN evaluation dataset. Full article

An understanding of the textures (grain size, grain shape, porosity, etc.), composition (mineralogy), and distribution of constituent components of geological materials such as carbonate and siliciclastic sedimentary rocks is essential in their classification, interpretation, and significance in terms of their geomechanical strength and liquid/gas storage potential. In terms of scanning electron microscopy (SEM), this is limited to relatively flat areas of selected rough surfaces, or the analysis of polished thin sections. Here, we illustrate a new technique that can image large areas of the external surface of mini-cores (approximately 10 mm or smaller in diameter) drilled from carbonate and siliciclastic rock samples. The technique utilises a specially developed horizontal rotation stage within an SEM and allows the collection of high-resolution images that can be reconstructed into realistic surface representations of the mini-core surfaces. Elemental data (representative of mineralogy) can also be added using a combined backscattered electron and X-ray (BEX) detector. Currently, these reconstructions can be used as a useful tool for the analysis of both carbonate and siliciclastic geological materials. Further work may allow such reconstructions to aid in the improvement of resolution in micro-CT scans and the direct identification of mineral phases within such scans. Full article

Recent studies show that patients with Alzheimer’s disease (AD) harbor specific methylation marks in the brain that, if accessible, could be used as epigenetic biomarkers. Liquid biopsy enables the study of circulating cell-free DNA (cfDNA) fragments originated from dead cells, including neurons affected by neurodegenerative processes. Here, we isolated and epigenetically characterized plasma cfDNA from 35 patients with AD and 35 cognitively healthy controls by using the Infinium^® MethylationEPIC BeadChip array. Bioinformatics analysis was performed to identify differential methylation positions (DMPs) and regions (DMRs), including APOE ε4 genotype stratified analysis. Plasma pTau181 (Simoa) and cerebrospinal fluid (CSF) core biomarkers (Fujirebio) were also measured and correlated with differential methylation marks. Validation was performed with bisulfite pyrosequencing and bisulfite cloning sequencing. Epigenome-wide cfDNA analysis identified 102 DMPs associated with AD status. Most DMPs correlated with clinical cognitive and functional tests including 60% for Mini-Mental State Examination (MMSE) and 80% for Global Deterioration Scale (GDS), and with AD blood and CSF biomarkers. In silico functional analysis connected 30 DMPs to neurological processes, identifying key regulators such as SPTBN4 and APOE genes. Several DMRs were annotated to genes previously reported to harbor epigenetic brain changes in AD (HKR1, ZNF154, HOXA5, TRIM40, ATG16L2, ADAMST2) and were linked to APOE ε4 genotypes. Notably, a DMR in the HKR1 gene, previously shown to be hypermethylated in the AD hippocampus, was validated in cfDNA from an orthogonal perspective. These results support the feasibility of studying cfDNA to identify potential epigenetic biomarkers in AD. Thus, liquid biopsy could improve non-invasive AD diagnosis and aid personalized medicine by detecting epigenetic brain markers in blood. Full article

Despite recurring episodes of fire exacerbated by climate change, post-fire dynamics in trees remain to be fully understood. In a mixed forest in northern Mexico that experiences frequent fires, we aimed to determine how tree growth responds to surface fire by examining earlywood (EW) and latewood (LW) responsiveness, as well as their connection with canopy activity, using UAV-acquired NDVI data. We compared EW and LW growth from mini cores of burned and unburned trees (n = 100) across four species, correlating this with NDVI data from 33 UAV monthly flights at the individual tree level from 2021 to 2023. Our results identified Quercus durifolia Seemen as the species that presented the highest growth following exposure to surface fire. Arbutus arizonica (A. Gray) Sarg. was the species most affected by fire in terms of EW production immediately after burning but showed benefits in subsequent summers. Juniperus deppeana Steud. demonstrated adaptive plasticity by responding more quickly to fire, with notable growth in EW. Pinus engelmannii Carrière responded in 2023, and its NDVI was associated to the least extent with seasonal growth. Thus, there is an evident seasonal response in trees subjected to low-intensity fire, which can act to shape the stand habitat. However, there is a divergence in response between broadleaf and evergreen species that could be attributed to fire-adaptive traits and hydraulic strategies. Although combining the tree-ring data with the NDVI served to improve our understanding of the effects of fire, further research is required. Full article

Background/Objectives: Metastatic prostate cancer remains a major clinical challenge, with limited therapeutic options. Doxycycline, a tetracycline antibiotic with anti-inflammatory properties, has shown potential as an adjunctive therapy. This study aimed to evaluate its efficacy in reducing prostate-specific antigen (PSA) levels and improving quality of life in patients receiving standard treatment for metastatic prostate cancer. Methods: This phase II, double-blind, randomized controlled trial included 45 participants (aged 57–81 years) assigned to doxycycline (100 mg daily) or a placebo for six months. The primary outcome was the percentage change in PSA levels at 3 and 6 months. Secondary outcomes included quality of life (EQ-5D-5L), cognitive function (Mini-Mental State Examination), and glucose levels. Additionally, a structure–activity relationship (SAR) analysis was performed through an extensive bibliographic review to identify pharmacophores responsible for doxycycline’s biological activity, particularly its tetracyclic core. The SAR analysis included tetracyclines and derivatives, androgen-targeting agents, and other pharmacologically relevant molecules used in prostate cancer therapy. Statistical analysis was conducted using multivariate logistic regression. Results: At six months, the doxycycline group showed a median PSA reduction of 60% compared to 10% in the placebo group (p = 0.043). A ≥50% reduction in PSA levels was observed in 71.4% of patients receiving doxycycline versus 20.8% in the placebo group (p = 0.001), with an adjusted relative risk of 10.309 (95% CI: 2.359–45.055, p = 0.002). Quality of life improved, with 7.1% of doxycycline-treated patients reporting poor quality of life compared to 42.9% in the placebo group (p = 0.028). A slight improvement in cognitive function was also noted (p = 0.037). SAR analysis suggested that the tetracyclic ring of doxycycline may play a crucial role in its observed biological effects. Conclusions: Doxycycline demonstrates potential as an adjunctive therapy in metastatic prostate cancer by reducing PSA levels and improving quality of life. The SAR analysis supports the hypothesis that its tetracyclic structure may be responsible for its therapeutic effects. Further large-scale trials are warranted to confirm these findings. Full article

(1) Background: This study aimed to investigate the changes in core temperature of Cyan-shank partridge chickens with continuously increased ambient temperature at different relative humidity (RH) levels. (2) Methods: Thirty birds were selected at the age of 35 days and randomly divided and housed in three artificial climate chambers. Each chamber was set at one of three different RH levels (50%, 65%, and 80%), and the ambient temperature was increased by 1.0 °C per 0.5 h from 24.0 to 34.0 °C. The core temperature was tested at 1.0 h intervals, and the ambient temperature in the chambers was recorded using mini temperature data loggers. Data were collected continuously for three days at the ages of 35, 42, and 49 days. The broken-line model (BLM) was used to calculate the inflection point temperature (IPT) and basal core temperature (constant). (3) Results: Both RH and age had no significant influence on the IPT. With increasing ambient temperature, the average IPT values of birds measured at the three ages were 26.52, 27.02, and 26.71 °C at the RH levels of 50%, 65%, and 80%, respectively. A significant downward trend in basal core temperature was observed as the birds aged from 35 to 42 days (p < 0.05). (4) Conclusions: the core temperature of the chicken gradually decreased as the age increased. During the hot summer months, it is better to keep the ambient temperature less than 26.5 °C to avoid the excessive increase in core temperature in Cyan-shank partridge chicken at the ages from 35 to 49 days. Full article

Coleoptile is a sheath-like structure unique to monocots and is easily observed in sorghum. Colored coleoptiles have been shown to protect plants against abiotic and biotic stresses. The purpose of this study was to identify factors controlling coleoptile color in sorghum. We phenotyped the sorghum mini core accessions for coleoptile color in two environments, determined the anthocyanin content of each color of selected accessions, carried out a genome-wide association analysis and identified a candidate gene. The phenotypic analysis showed that 95 (40% of 235) accessions were green, 28 (12%) were purple and 42 (18%) were red in both 2022 and 2023. About 12% of the accessions changed from green to red due to environmental conditions. The anthocyanin content analysis showed a positive correlation between intensity of coleoptile color and anthocyanin levels. A genome-wide association analysis identified two candidate genes, Sobic.006G175700 and Sobic.006G175500, mapped to this trait in a single locus on chromosome 6. An orthologous comparison, together with mapping, sequence analysis and qPCR, identified Sobic.006G175700 as Rs1, the gene determining the sorghum coleoptile color. The haplotype analysis with SNPs from both coding and upstream regions of Sobic.006G175700 indicates that the predominant haplotypes can differentiate between green and colored coleoptile colors. This information can be used for marker-assisted selection of desired coleoptile colors in sorghum. Full article

Background/Objectives: The Agenesis of maxillary lateral incisors occurs with a variable prevalence in different ethnic groups, and there is a need for a temporary replacement until maturity has been reached in patients for whom the replacement solution has been chosen. This study aims to analyze the scientific evidence available to date concerning the use of mini-screw implant (MSI)-supported pontics for the transitional management of permanent maxillary lateral incisors’ agenesis in developmental age subjects. Methods: Electronic research was conducted using four databases: PubMed, Clarivate Analytics/Web of Science Core Collection, Scopus, and the Wiley/Cochrane Library. Six studies were included in the final review. Data were extracted based on the first and second author, year of publication, study design, sample characteristics, mini-screw implant (MSI) characteristics, MSI insertion and loading protocol, characteristics of the prosthetic component, and outcomes during the follow-up time. Results: Clinical outcomes were proven positive in all studies. In only one study did MSIs show mobility and consequent failure after one month. Discoloration of the prosthetic part proved to be the main complication. Conclusions: The comparison with conventional removable prostheses and fixed dental prostheses revealed that MSI-supported pontics are a viable alternative and a promising temporary solution until the end of growth. Further studies to standardize protocols and assess long-term outcomes are needed. Full article

Background/Objectives: Cognitive impairment represents a core and prodromal clinical feature of cerebral amyloid angiopathy (CAA). We sought to assess specific cognitive domains which are mainly affected among patients with CAA and to investigate probable associations with neuroimaging markers and Cerebrospinal Fluid (CSF) biomarkers. Methods: Thirty-five patients fulfilling the Boston Criteria v1.5 or v2.0 for the diagnosis of probable/possible CAA were enrolled in this prospective cohort study. Brain Magnetic Resonance Imaging and CSF biomarker data were collected. Every eligible participant underwent a comprehensive neurocognitive assessment. Spearman’s rank correlation tests were used to identify possible relationships between the Addenbrooke’s Cognitive Examination—Revised (ACE-R) sub-scores and other neurocognitive test scores and the CSF biomarker and neuroimaging parameters among CAA patients. Moreover, linear regression analyses were used to investigate the effects of CSF biomarkers on the ACE-R total score and Mini-Mental State Examination (MMSE) score, based on the outcomes of univariate analyses. Results: Cognitive impairment was detected in 80% of patients, and 60% had a coexistent Alzheimer’s disease (AD) pathology based on CSF biomarker profiles. Notable correlations were identified between increased levels of total tau (t-tau) and phosphorylated tau (p-tau) and diminished performance in terms of overall cognitive function, especially memory. In contrast, neuroimaging indicators, including lobar cerebral microbleeds and superficial siderosis, had no significant associations with cognitive scores. Among the CAA patients, those without AD had superior neurocognitive test performance, with significant differences observed in their ACE-R total scores and memory sub-scores. Conclusions: The significance of tauopathy in cognitive impairment associated with CAA may be greater than previously imagined, underscoring the necessity for additional exploration of the non-hemorrhagic facets of the disease and new neuroimaging markers. Full article

To mitigate the emissions of greenhouse gases (GHGs) from fossil fuels, the use of biodiesel and its sustainable production have been receiving more attention over the past decade, especially for the reuse of waste cooking oils and non-edible oils as starting feedstocks. For the biodiesel production process, the suitability of a green catalyst is a core function in the transesterification reaction. Heterogeneous (solid-state) catalysts are generally superior to homogeneous (liquid-state) catalysts due to several significant advantages such as no saponification products formed, recyclability, and less equipment corrosion. Recent studies also revealed that heterogeneous solid base catalysts were widely used for the production of biodiesel. Furthermore, the use of biomass-based ash derived from herbaceous and agricultural biomass is increasing rapidly because of its environmental sustainability, high biodiesel yield, and low catalyst cost. To highlight alternative catalysts from biomass residues, this mini-review paper thus focused on a summary of various heterogeneous potassium-rich ash materials, which were used as green catalysts for the sustainable production of biodiesel. Due to the abundant quantity and chemical compositions, it was found that ash derived from cocoa pod husk may be the most commonly used solid base catalyst for producing biodiesel in the literature. Finally, future perspectives on biodiesel production by adopting emerging technologies and using high-potassium (K) biomass ash as a green catalyst were also addressed. Full article

The human mitochondrial proteome comprises approximately 1500 proteins, with only 13 being encoded by mitochondrial DNA. The remainder are encoded by the nuclear genome, translated by cytosolic ribosomes, and subsequently imported into and sorted within mitochondria. The process of mitochondria-destined protein import is mediated by several intricate protein complexes distributed among the four mitochondrial compartments. The focus of this mini-review is the translocase of the inner membrane 23 (TIM23) complex that assists in the import of ~60% of the mitochondrial proteome, which includes the majority of matrix proteins as well as some inner membrane and intermembrane space proteins. To date, numerous pathogenic mutations have been reported in the genes encoding various components of the TIM23 complex. These diseases exhibit mostly developmental and neurological defects at an early age. Interestingly, accumulating evidence supports the possibility that the gene for Tim50 represents a hotspot for disease-causing mutations among core TIM23 complex components, while genes for the mitochondrial Hsp70 protein (mortalin) and its J domain regulators represent hotspots for mutations affecting presequence translocase-associated motor (PAM) subunits. The potential mechanistic implications of the discovery of disease-causing mutations on the function of the TIM23 complex, in particular Tim50, are discussed. Full article

Recently, Marigo et al, identified a kink in the initial-final mass relation around initial masses of $M_{ini}\approx 1.65-2.10$$M_{\odot }$, based on Gaia DR2 and EDR3 data for white dwarfs in open clusters aged 1.5–2.5 Gyr. Notably, the white dwarfs associated with this kink, all from NGC 7789, exhibit masses of ∼0.70–0.74 M_⊙, usually associated with stars of $M_{ini}\sim$ 3–4 $M_{\odot }$. This kink in the M_ini mass range coincides with the theoretically accepted solar metallicity lowest-mass stars evolving into carbon stars during the AGB phase. According to Marigo et al., these carbon stars likely experienced shallow third dredge-up events, resulting in low photospheric C/O ratios and, consequently, middle stellar winds. Under such conditions, the AGB phase is prolonged, allowing for further core mass growth beyond typical predictions. If this occurs, it might provoke other anomalies, such as a non-standard surface chemical composition. We have conducted a chemical analysis of several carbon stars belonging to open clusters within the above cluster ages. Our chemical analysis reveals that the carbon stars found within the kink exhibit C/O ratios only slightly above the unity and the typical chemical composition expected for carbon stars of near solar metallicity, partially validating the above theoretical predictions. We also show that this kink in the IMFR strongly depends on the method used to derived the distances (luminosity) of these carbon stars. Full article