Search Results (96)

The development of planar structures such as wings or leaves is a common feature among organisms and serves as a mechanism to increase surface to volume ratios. We wished to explore whether the recurrent and independent development of similar adaptive planar morphologies is the result of an activation of common genetic modules or toolkits. To test this, we focused on the developmental gene networks that are proposed to define leaf polarity in eudicots in phylloclades, leaf-like organs derived from branch primordia, in the monocot Ruscus aculeatus. Since branch primordia normally have a radial shape, this approach allowed us to examine the genetic changes required for the transformation from a round to a planar (flat) form. In our transcriptome analysis of phylloclade and stem tissue, we detected 76,085 annotated ORFs of which 87.2% were identified as complete out of 2026 BUSCO groups. Expression patterns clearly identify differentiation between phylloclade and stem tissues consistent with an enhanced photosynthetic function in the phylloclades. However, except for the AS1/AS2 and possibly STM module, we see little evidence that canonical leaf adaxial and abaxial modules are activated in the sampled phylloclades compared with the stems. Our results show that the unifacial nature of phylloclades is consistent with the observed lack of strong adaxial/abaxial molecular signatures. We propose that in R. aculeatus and plants with similar unifacial laminar leaves, adaxial/abaxial molecular identity may not be required for planar growth, and that lateral expansion of organ primordia and acropetal and intercalary cell division may be sufficient to generate planar versus radial organ shapes. Full article

Telomerase is known as a very specific marker of embryonic cells. It is responsible for telomere elongation (bypassing the end-replication problem) and thus supports normal cell division during tissue and organ development. But it is generally absent or very low in most normal adult somatic cells. However, its overexpression in adulthood (due to secondary expression and activity restoration) is commonly known to be associated with cancer. Apart from its canonical function (associated with telomere length restoration), it also carries out various other roles. Its non-canonical activity covers mitochondrial and epigenetic processes. Consequently, it contributes to the cell response to stress and chemotherapeutic drug treatment. A more detailed understanding of these phenomena offers the opportunity to identify new pathways and targets that may serve as critical factors in breast cancer diagnostics and therapy. In this article, we summarize the latest reports on the discovery of telomerase’s nature, including its canonical and non-canonical roles. The manuscript highlights how these mechanisms contribute to tumorigenesis, therapy resistance, and the survival of cancer cells. Understanding these multifaceted mechanisms behind hTERT’s role in (breast) cancer progression and therapy resistance is crucial for developing more effective therapeutic strategies. Full article

This paper proposes an enhanced hierarchical fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) integrated with the Analytic Network Process (ANP) for solving multi-criteria decision-making (MCDM) problems under uncertainty. Conventional fuzzy TOPSIS models often face significant challenges, such as restrictions to specific fuzzy number formats, difficulties in normalization when zero or very small values appear, and limited capacity to capture hierarchical interdependencies among criteria. To address these limitations, we develop a generalized fuzzy geometric mean approach for deriving weights from pairwise comparisons that can accommodate multiple fuzzy number types. Moreover, a novel normalization function is introduced, which ensures mathematically valid outcomes within the [0, 1] interval while avoiding division-by-zero and inconsistency issues. The proposed method is validated through both a numerical building selection problem and a practical supplier selection case study. Comparative analyses against established fuzzy MCDM models demonstrate the improved robustness, flexibility, and accuracy of the approach. Additionally, a sensitivity analysis confirms the stability of results with respect to variations in criteria weights, fuzzy number formats, and normalization techniques. These findings highlight the potential of the proposed fuzzy hierarchical TOPSIS-ANP framework as a reliable and practical decision support tool for complex real-world applications, including supply chain management and resource allocation under uncertainty. Full article

We propose a dual-groove few-mode fiber surface plasmon resonance sensor that exploits the LP₁₁ mode for enhanced plasmonic sensing. The device incorporates two physically separated grooves with distinct metallic coatings, enabling dual-channel operation via wavelength-division multiplexing. Finite element method simulations show that the optimized design achieves a maximum sensitivity of 14,800 nm/RIU within the RI range of 1.33–1.40. The introduction of a TiO₂–Au bilayer enhances mode coupling and ensures complete spectral separation, thereby improving stability and reducing environmental interference. Biosensing simulations at 37 °C further confirm the practicality of the proposed architecture. Channel 1, filled with ethanol as a temperature-sensitive medium, provides temperature monitoring, while Channel 2 successfully distinguishes between normal and tumor cells, reaching a sensitivity of up to 9428.57 nm/RIU for Jurkat cells. Overall, the TiO₂-enhanced dual-channel FMF-SPR sensor combines ultra-high sensitivity, spectral independence, and biosensing capability, demonstrating strong potential for next-generation fiber-optic sensing and biomedical applications. Full article

The use of low-resolution analog-to-digital converters (ADCs) in receivers has emerged as an effective solution for reducing power consumption in millimeter-wave (mmWave) massive multiple-input–multiple-output (MIMO) systems. However, low-resolution ADCs also pose significant challenges for channel estimation. To address this issue, we propose a joint uplink/downlink (UL/DL) channel estimation algorithm that utilizes the spatial reciprocity of frequency division duplex (FDD) to improve the estimation of quantized UL channels. Quantified UL/DL channels are concentrated at the BS for joint estimation. This estimation problem is regarded as a compressed sensing problem with finite bits, which has led to the development of expectation-maximization-based quantitative generalized approximate messaging (EM-QGAMP) algorithms. In the expected step, QGAMP is used for posterior estimation of sparse channel coefficients, and the block maximization minimization (MM) algorithm is introduced in the maximization step to improve the estimation accuracy. Finally, simulation results verified the robustness of the proposed EM-QGAMP algorithm, and the proposed algorithm’s NMSE (normalized mean squared error) outperforms traditional methods by over 90% and recent state-of-the-art techniques by 30%. Full article

Background and Objectives: Vision uses about half of the pathways within the brain, and these anatomical structures are susceptible to injury in concussion. Authors have suggested that subconcussive head impacts, common in soccer, may disrupt visual function. The following study aimed to explore and compare quantitative pupillometry and Vestibular Ocular Motor Screening (VOMS) in female soccer athletes. Materials and Methods: Twenty-six Division 1 female soccer athletes (20.46 ± 2.36 years) received baseline quantitative pupillometry and VOMS measurements. Results: Of the 26 tested athletes, 3 (11.5%) had clinically significant pupillometry findings at baseline. The mean Neurological Pupil Index or NPi, a composite generated from pupillometry, did not vary: 3.9 ± 0.4 (right eye) and 4.0 ± 0.4 (left eye). No difference in NPi was observed compared to the VOMS score (p > 0.05). Kruskal–Wallis H tests were significant in the right eye for constriction percentage (χ²(2) = 17.843, p < 0.001, E² = 0.69) and minimum pupil size (χ²(2) = 7.976, p = 0.019, E² = 0.31). A post hoc Dunn test showed significant differences in constriction percentage and minimum pupil size between low NPi and high NPi groups (p < 0.05). One athlete sustained a concussion. NPi was measured within 24 h and was normal, but VOMS was not (total score = 4). Conclusions: The components of pupillometry need more investigation, and there is a need for agreement on concussion-specific cutoffs for quantitative pupillometry for concussion assessment. The lack of a relationship between quantitative pupillometry and VOMS suggests that these tools evaluate different constructs. Athletes with an NPi < 3.8 had significantly less constriction percentage and larger minimum pupil size than athletes with higher NPi scores. More research should be carried out to determine the usefulness of the NPi score, and perhaps researchers should consider individual pupillometry components. Full article

Epigeal cotyledons with excised embryonic axes are often used as a model system to study the processes of cell division and expansion. These processes are regulated by diverse phytohormones and signaling molecules. Phytohormones modulate antioxidant defense systems and interact with reactive oxygen species (ROS) to synchronize normal plant cell growth. This study provides new information concerning alterations in enzymatic antioxidants linked to the production and scavenging of ROS in excised epigeal cotyledons of zucchini grown on solutions of methyl jasmonate (MeJA) and cytokinins (CKs)—N⁶-benzyl adenine and N₁-(2-chloropyridin-4-yl)-N₂-phenylurea—in the presence or absence of light under laboratory conditions. The cotyledon material was used to determine the dynamics of selected biochemical parameters starting from the 2nd to the 6th day of incubation. In general, our results revealed that exogenous MeJA caused a reduction in the content of hydrogen peroxide (H₂O₂) and free proline, as well as in the activity of superoxide dismutase (SOD), guaiacol peroxidase (POX) and catalase (CAT) in dark-grown cotyledons. Applied alone, both cytokinins increased most of the parameters studied, except proline and protein levels. However, when MeJA was combined with CKs, it acted in a diverse manner, ranging from antagonistic to synergistic depending on the cytokinin type, parameter measured and light regime. Similar alterations were also found in the levels of leaf pigments in the cotyledons grown under light conditions. In general, the changes in the antioxidant enzyme activities due to light were more intense than those observed in dark-grown cotyledons. The data obtained show, for the first time, the involvement of the hormonal interplay between MeJA and CKs on the biochemical changes in antioxidant defense during cotyledon growth under different light conditions. Full article

Accurate prediction of the Normalized Difference Vegetation Index (NDVI) is crucial for regional ecological management and precision decision-making. Existing methodologies often rely on smoothed NDVI data as ground truth, overlooking uncertainties inherent in data acquisition and processing. Fuzzy time series (FTS) prediction models based on the Fuzzy C-Means (FCM) clustering algorithm address some of these uncertainties by enabling soft partitioning through membership functions. However, the method remains limited by its reliance on expert experience in setting fuzzy parameters, which introduces uncertainty in the definition of fuzzy intervals and negatively affects prediction performance. To overcome these limitations, this study enhances the interval type-2 fuzzy clustering time series (IT2-FCM-FTS) model by developing a pixel-level time series forecasting framework, optimizing fuzzy interval divisions, and extending the model from unidimensional to spatial time series forecasting. Experimental results from 2021 to 2023 demonstrate that the proposed model outperforms both the Autoregressive Integrated Moving Average (ARIMA) and conventional FCM-FTS models, achieving the lowest RMSE (0.0624), MAE (0.0437), and SEM (0.000209) in 2021. Predictive analysis indicates a general ecological improvement in the Aksu region (Xinjiang, China), with persistent growth areas comprising 61.12% of the total and persistent decline areas accounting for 2.6%. In conclusion, this study presents an improved fuzzy model for NDVI time series prediction, providing valuable insights into regional desertification prevention and ecological strategy formulation. Full article

Variations in terrain elevation cause images acquired under different imaging modalities to deviate from a linear mapping relationship. This effect is particularly pronounced between optical and SAR images, where the range-based imaging mechanism of SAR sensors leads to significant local geometric distortions, such as perspective shrinkage and occlusion. As a result, it becomes difficult to represent the spatial correspondence between optical and SAR images using a single geometric model. To address this challenge, we propose a global optical-SAR image registration method that leverages local distortion characteristics. Specifically, we introduce a Superpixel-based Local Distortion Division (SLDD) method, which defines superpixel region features and segments the image into local distortion and normal regions by computing the Mahalanobis distance between superpixel features. We further design a Multi-Feature Fusion Capsule Network (MFFCN) that integrates shallow salient features with deep structural details, reconstructing the dimensions of digital capsules to generate feature descriptors encompassing texture, phase, structure, and amplitude information. This design effectively mitigates the information loss and feature degradation problems caused by pooling operations in conventional convolutional neural networks (CNNs). Additionally, a hard negative mining loss is incorporated to further enhance feature discriminability. Feature descriptors are extracted separately from regions with different distortion levels, and corresponding transformation models are built for local registration. Finally, the local registration results are fused to generate a globally aligned image. Experimental results on public datasets demonstrate that the proposed method achieves superior performance over state-of-the-art (SOTA) approaches in terms of Root Mean Squared Error (RMSE), Correct Match Number (CMN), Distribution of Matched Points (Scat), Edge Fidelity (EF), and overall visual quality. Full article

Air pollution poses a pressing global challenge, particularly in rapidly industrializing nations like China where deteriorating air quality critically endangers public health and sustainable development. To address the heterogeneous patterns of air pollution across diverse geographical and climatic regions, this study proposes a novel CNN-LSTM-KAN hybrid deep learning framework for high-precision Air Quality Index (AQI) time-series prediction. Through systematic analysis of multi-city AQI datasets encompassing five representative Chinese metropolises—strategically selected to cover diverse climate zones (subtropical to temperate), geographical gradients (coastal to inland), and topographical variations (plains to mountains)—we established three principal methodological advancements. First, Shapiro–Wilk normality testing (p < 0.05) revealed non-Gaussian distribution characteristics in the observational data, providing statistical justification for implementing Gaussian filtering-based noise suppression. Second, our multi-regional validation framework extended beyond conventional single-city approaches, demonstrating model generalizability across distinct environmental contexts. Third, we innovatively integrated Kolmogorov–Arnold Networks (KANs) with attention mechanisms to replace traditional fully connected layers, achieving enhanced feature weighting capacity. Comparative experiments demonstrated superior performance with a 23.6–59.6% reduction in Root-Mean-Square Error (RMSE) relative to baseline LSTM models, along with consistent outperformance over CNN-LSTM hybrids. Cross-regional correlation analyses identified PM2.5/PM10 as dominant predictive factors. The developed model exhibited robust generalization capabilities across geographical divisions (R² = 0.92–0.99), establishing a reliable decision-support platform for regionally adaptive air quality early-warning systems. This methodological framework provides valuable insights for addressing spatial heterogeneity in environmental modeling applications. Full article

Ageing is a complex and unavoidable physiological process which, in simple terms, consists of a progressive deterioration in the functionality of cells, tissues and organs, culminating in an increased risk of developing chronic pathologies. Telomeres, the repetitive nucleotide structures at the end of chromosomes, ensure genomic integrity and modulate cellular senescence. The progressive shortening of telomere length with each cell division directly correlates with an increased susceptibility to developing chronic pathologies. However, this shortening, normally physiological and inevitable, can be markedly accelerated in the presence of chronic infections, such as HIV-1 infection, by sustained and continuous activation of the immune system, chronic inflammation, generation of oxidative stress, or direct alterations produced by viral proteins. Thus, in this narrative review, we discuss the 12 hallmarks of ageing in the context of HIV-1 infection, as understanding the molecular changes induced by HIV-1 through these well-established pillars could provide a holistic approach to the management of HIV-positive patients. At the same time, considering that telomeres are at the centre of all these changes, an assessment of the impact of antiretroviral therapy on telomere length is necessary to guide clinical decisions. The ultimate goal of this research is to develop personalised therapies to increase the quality of life and health outcomes of HIV patients. Full article

Ganglioside-induced differentiation-associated protein 2 (GDAP2) is a gene involved in hereditary cerebellar ataxia. At present, little is known about the function of GDAP2 in insects. In this study, BmGDAP2 was detected to be highly expressed in the head, epidermis, midgut, and anterior silk glands of silkworms. We generated a knockout mutant, BmGDAP2 (BmGDAP2^KO), using the CRISPR/Cas9 system. Compared with that of the wild-type, the growth cycle of BmGDAP2^KO larvae was significantly prolonged, while their body size was reduced. Furthermore, we found 149 differentially expressed genes (DEGs) between BmGDAP2^KO and the wild-type, including 106 upregulated and 43 downregulated genes. GO annotation analysis indicated that BmGDAP2 primarily influences structural and molecular activities, as well as catalytic and binding functions. KEGG pathway analysis revealed that the differentially expressed genes were mainly enriched in pathways related to peroxidase activity, hormone synthesis, apoptosis, and longevity regulation. Further investigation focused on candidate genes related to these pathways. We found that the expression levels of MAD2L1, which can inhibit cell proliferation and promote apoptosis, and Aurka-b, which plays a crucial role in cell cycle regulation, were significantly reduced in BmGDAP2^KO silkworms. These changes may interfere with the normal functions of cell division, leading to the prolonged developmental cycle observed in BmGDAP2^KO larvae. Our findings demonstrate that knockout of BmGDAP2 significantly prolongs the life cycle of Bombyx mori by affecting genes related to autophagy, apoptosis, and hormone regulation. Full article

Background: Tomatoes are self-pollinating plants, and successful fruit set depends on the production of functional pollen within the same flower. Our previous studies have shown that the ‘Black Vernissage’ tomato variety exhibits greater resilience to heat stress in terms of pollen productivity compared to the ‘Micro-Tom’ variety. Pollen productivity is determined by meiotic activity during microsporogenesis and the development of free microspores during gametogenesis. This study focused on identifying heat stress (HS)-induced proteomes in pollen mother cells (PMCs) and microspores. Methods: Tomato plants were grown under two temperature conditions: 26 °C (non-heat-treated control) and 37 °C (heat-treated). Homogeneous cell samples of meiotic PMCs (prior to the tetrad stage) and free microspores were collected using laser capture microdissection (LCM). The heat-induced proteomes were identified using tandem mass tag (TMT)–quantitative proteomics analysis. Results: The enrichment of the meiotic cell cycle in PMCs and the pre-mitotic process in free microspores confirmed the correlation between proteome expression and developmental stage. Under HS, PMCs in both tomato varieties were enriched with heat shock proteins (HSPs). However, the ‘Black Vernissage’ variety exhibited a greater diversity of HSP species and a higher level of enrichment compared to the ‘Micro-Tom’ variety. Additionally, several proteins involved in gene expression and protein translation were downregulated in PMCs and microspores of both varieties. In the PMC proteomes, the relative abundance of proteins showed no significant differences between the two varieties under normal conditions, with very few exceptions. However, HS induced significant differential expression both within and between the varieties. More importantly, these heat-induced differentially abundant proteins (DAPs) in PMCs are directly involved in meiotic cell division, including the meiosis-specific protein ASY3 (Solyc01g079080), the cell division protein kinase 2 (Solyc11g070140), COP9 signalosome complex subunit 1 (Solyc01g091650), the kinetochore protein ndc80 (Solyc01g104570), MORC family CW-type zinc finger 3 (Solyc02g084700), and several HSPs that function in protecting the fidelity of the meiotic processes, including the DNAJ chaperone (Solyc04g009770, Solyc05g055160), chaperone protein htpG (Solyc04g081570), and class I and class II HSPs. In the microspores, most of the HS-induced DAPs were consistently observed across both varieties, with only a few proteins showing significant differences between them under heat stress. These HS-induced DAPs include proteases, antioxidant proteins, and proteins related to cell wall remodeling and the generation of pollen exine. Conclusions: HS induced more dynamic proteomic changes in meiotic PMCs compared to microspores, and the inter-varietal differences in the PMC proteomes align with the effects of HS on pollen productivity observed in the two varieties. This research highlights the importance of the cell-type-specific proteomics approach in identifying the molecular mechanisms that are critical for the pollen developmental process under elevated temperature conditions. Full article

Amniotic band syndrome is a constrictive phenomenon in fetal development that can provoke limb autoamputation, malformation, trunk division, and umbilical cord strangulation. The latter two complications will ultimately lead to fetal demise if left untreated. If detected early enough, select cases may benefit from prenatal resection of the amniotic bands, thus preventing amputation and fetal death. Yet, especially in the presence of complete chorioamniotic separation, these procedures are rare, technically difficult, and not without significant risk. Objectives: The purpose of this report is to present the surgical technique and outcome of a challenging percutaneous fetoscopic intervention in a human fetus with amniotic band constrictions of a fetal thigh, retroplacental hematoma, partial placental abruption, subtotal chorioamniotic separation, and multiple amniotic bands encircling the umbilical cord. Methods: Minimally invasive, fetoscopic surgery to salvage the fetal life and lower leg was performed at 22 + 2 weeks of gestation under general maternofetal anesthesia. Results: Total resection of all amniotic bands was achieved, notwithstanding the aforementioned challenges. No surgical complications were observed. Despite preterm delivery at 25 + 4 weeks of gestation, the postnatal experience for the infant was favorable and uncomplicated as it furthermore benefitted from neonatal intensive care. At almost three years of age, the child remains healthy and demonstrates normal function of the formerly constricted leg. Conclusions: Our case shows that the combination of tested percutaneous fetoscopic techniques, high-risk obstetrics, and modern neonatology can overcome multiple obstacles in order to save a fetal patient stuck in a near-hopeless situation. Full article

Linear spatial data are primarily used in Geographic Information Systems (GISs) to represent spatial data in the form of roads, rivers, railways, and utility lines. Linear spatial data are mostly composed of one-dimensional linear elements, incorporating geometric attributes such as location, direction, and length, as well as the interconnections of these elements. In the case of roads, this information is used to map and analyze traffic data, such as vehicle movements, on the road network. This study aims to propose an area-based spatial analysis method that allows for the flexible application of analysis scales using individual vehicle data, as opposed to node and link generation for linear road networks. The analysis focused on nine expressways, conducting a microscopic analysis of speed-homogeneous sections. The final analysis showed that out of 375 cells, 91 cells in the final 12 division cells did not meet the homogeneity criteria. This discrepancy was ascertained to be due to vehicles decelerating or accelerating when entering or exiting highways at ramps or interchanges, not due to directional speed differences but lane-specific speed variations. The final cells with large speed deviations were found to be influenced by connections to highway on-ramps or off-ramps. In contrast, sections with small speed variations within a cell were influenced by traffic factors such as connection points and traffic volume, which hindered normal driving. As a result, this study validated that traffic information from highways, typically provided as linear data, could be divided into cells based on real-time GPS speed data and presented on an area-based scale. While dividing regions based on fixed intervals does not pinpoint exact speed change points, this study found that reasonable segmentation is possible based on spatial size and speed-homogeneous sections. Full article