Search Results (263)

Marine sources contain compounds that act on a wide variety of systems, including ligand-gated ion channels. This review will focus on the effectors of nicotinic acetylcholine receptors (nAChRs), for which the diversity of ligands and modulators from marine sources is determined mainly by neurotoxic peptides (α-conotoxins) from mollusks of the Conus genus. These are very selective compounds that allow the study of the role of different nAChR subtypes in the cancer cells. They have analgesic or anti-inflammatory activities associated with cholinergic transmission and have shown analgesic effect in case of chemotherapy-induced neuropathic pain. Another class of marine compounds targeting nAChRs for which cytotoxicity for cancer cells was shown is represented by low molecular organic substances found mostly in dinoflagellates and marine sponges. Some of the compounds discussed in this review show promise for developing drugs that suppress cancer growth. Full article

Probable Maximum Storms (PMS) are synthetic design storms represented by idealized hyetographs. They play a critical role in assessing extreme rainfall events over extended durations and are widely applied in the hydraulic design of infrastructure such as dams, culverts, and bridges. PMS provide essential input for estimating Probable Maximum Floods (PMF), vital for analyzing worst-case flood scenarios with the potential to cause catastrophic loss of life and property. Despite their importance, the estimation of design storms at ungauged locations, particularly across synoptic scales, remains a major scientific and engineering challenge. This study addresses this gap by utilizing the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) dataset, which provides near-global estimated precipitation coverage. IMERG’s 24 h design storm hyetographs (expressed as cumulative percentage of precipitation throughout a 24 h period) were modeled and compared with similar reference data from NOAA Atlas 14 across twenty-eight regions and seven larger zones covering most of the conterminous United States (CONUS). Across the regions, the average root mean square error (RMSE) was 3.7%, with a mean relative bias (RB) of 1.4%. The mean normalized storm loading index (NSLI) from NOAA Atlas 14 was −7.7%, indicating that 57.7% of the total precipitation was received during the first 12 h of the storm, whereas IMERG storms exhibited a mean NSLI of −4.1%, suggesting they are also frontloaded but to a lesser extent. Across the broader zones, the mean RMSE was 4.8% and the mean RB was 1.1%. The mean NSLI values were −9.7% for NOAA Atlas 14 and −5.7% for IMERG, again indicating that IMERG storms are less frontloaded. When design storm families were estimated corresponding with different degrees of frontloading (corresponding to the 10, 20, …, 90% deciles of NSLI), the 40th to 60th percentile range exhibited the strongest agreement between IMERG and NOAA Atlas 14 hyetographs. Full article

The Golgi of goblet cells represents a specialized machine for mucin glycosylation. This process occurs in a specialized form of the secretory pathway, which remains poorly examined. Here, using high-resolution three-dimensional electron microscopy (EM), EM tomography, serial block face scanning EM (SBF-SEM) and immune EM we analyzed the secretory pathway in goblet cells and revealed that COPII-coated buds on the endoplasmic reticulum (ER) are extremely rare. The ERES vesicles with dimensions typical for the COPII-dependent vesicles were not found. The Golgi is formed by a single cisterna organized in a spiral with characteristics of the cycloid surface. This ribbon has a shape of a cup with irregular perforations. The Golgi cup is filled with secretory granules (SGs) containing glycosylated mucins. Their diameter is close to 1 µm. The cup is connected with ER exit sites (ERESs) with temporal bead-like connections, which are observed mostly near the craters observed at the externally located cis surface of the cup. The craters represent conus-like cavities formed by aligned holes of gradually decreasing diameters through the first three Golgi cisternae. These craters are localized directly opposite the ERES. Clusters of the 52 nm vesicles are visible between Golgi cisternae and between SGs. The accumulation of mucin, started in the fourth cisternal layer, induces distensions of the cisternal lumen. The thickness of these distensions gradually increases in size through the next cisternal layers. The spherical distensions are observed at the edges of the Golgi cup, where they fuse with SGs and detach from the cisternae. After the fusion of SGs located just below the apical plasma membrane (APM) with APM, mucus is secreted. The content of this SG becomes less osmiophilic and the excessive surface area of the APM is formed. This membrane is eliminated through the detachment of bubbles filled with another SG and surrounded with a double membrane or by collapse of the empty SG and transformation of the double membrane lacking a visible lumen into multilayered organelles, which move to the cell basis and are secreted into the intercellular space where the processes of dendritic cells are localized. These data are evaluated from the point of view of existing models of intracellular transport. Full article

We present a model that integrates the mapping of the phenology and climatic suitability for the spotted lanternfly (SLF), Lycorma delicatula (White, 1845) (Hemiptera: Fulgoridae), to provide guidance on when and where to conduct surveillance and management of this highly invasive pest. The model was designed for use in the Degree-Day, Establishment Risk, and Phenological Event Maps (DDRP) platform, which is an open-source decision support tool to help to detect, monitor, and manage invasive threats. We validated the model using presence records and phenological observations derived from monitoring studies and the iNaturalist database. The model performed well, with more than >99.9% of the presence records included in the potential distribution for North America, a large proportion of the iNaturalist observations correctly predicted, and a low error rate for dates of the first appearance of adults. Cold and heat stresses were insufficient to exclude the SLF from most areas of the conterminous United States (CONUS), but an inability for the pest to complete its life cycle in cold areas may hinder establishment. The appearance of adults occurred several months earlier in warmer regions of North America and Europe, which suggests that host plants in these areas may experience stronger feeding pressure. The near-real-time forecasts produced by the model are available at USPest.org and the USA National Phenology Network to support decision making for the CONUS. Forecasts of egg hatch and the appearance of adults are particularly relevant for surveillance to prevent new establishments and for managing existing populations. Full article

Late Pleistocene coastal deposits on the southeastern coast of Formentera (Es Ram–Es Estufadors) provide a high-resolution record of sea-level and climatic fluctuations associated with Marine Isotope Stage (MIS) 5. Three distinct beach levels (Sef-1, Sef-2, Sef-3) were identified, corresponding to substages MIS 5e, 5c, and possibly 5a, based on sedimentological features, fossil assemblages, and Optically Stimulated Luminescence (OSL) dating. The oldest beach level (Sef-1) is attributed to MIS 5e (ca. 128–116 ka) and is characterised by the widespread presence of thermophilic Senegalese fauna—including Thetystrombus latus, Conus ermineus, and Linatella caudata—which mark the onset of this interglacial phase and are associated with two peaks in relative sea-level highstand. A subsequent cooling event during MIS 5d is recorded by the development of thin palaeosols and the disappearance of these warm-water taxa. The second beach level (Sef-2) reflects renewed sea-level rise and warmer conditions during MIS 5c, with abundant macrofauna and red algae. The transition to MIS 5b (~97 ka) is marked by a significant sea-level drop (down to –60 m), cooler climate, and enhanced colluvial sedimentation linked to increased runoff and erosion. In total, 54 macrofaunal species were identified—16 from Sef-1 and 46 from Sef-2—highlighting ecological shifts across substages. These results improve our understanding of coastal response to sea-level oscillations and paleoenvironmental dynamics in the western Mediterranean during the Late Pleistocene. Full article

Forest drought monitoring tools are crucial for managing tree water stress and enhancing ecosystem resilience. The Forest Drought Response Index (ForDRI) was developed to monitor drought conditions in forested areas across the contiguous United States (CONUS), integrating vegetation health, climate data, groundwater, and soil moisture content. This study evaluated ForDRI using Pearson correlations with the Bowen Ratio (BR) at 24 AmeriFlux sites and Spearman correlations with the Tree-Ring Growth Index (TRSGI) at 135 sites, along with feedback from 58 stakeholders. CONUS was divided into four forest subgroups: (1) the West/Pacific Northwest, (2) Rocky Mountains/Southwest, (3) East/Northeast, and (4) South/Central/Southeast Forest regions. Strong positive ForDRI-TRSGI correlations (ρ > 0.7, p < 0.05) were observed in the western regions, where drought significantly impacts growth, while moderate alignment with BR (R = 0.35–0.65, p < 0.05) was noted. In contrast, correlations in Eastern and Southern forests were weak to moderate (ρ = 0.4–0.6 for TRSGI and R = 0.1–0.3 for BR). Stakeholders’ feedback indicated that ForDRI realistically maps historical drought years and recent trends, though suggestions for improvements, including trend maps and enhanced visualizations, were made. ForDRI is a valuable complementary tool for monitoring forest droughts and informing management decisions. Full article

Accurate crop yield prediction is essential for stabilizing food supply chains and reducing the uncertainties in financial risks related to agricultural production. Yet, it is even more essential to understand how crop yield models make predictions depending on their relationship to Earth Observation (EO) indicators. This study presents a state-of-the-art explainable artificial intelligence (XAI) method to estimate corn yield prediction over the Corn Belt in the continental United States (CONUS). We utilize the recently introduced Kolmogorov–Arnold Network (KAN) architecture, which offers an interpretable alternative to the traditional Multi-Layer Perceptron (MLP) approach by utilizing learnable spline-based activation functions instead of fixed ones. By including a KAN in our crop yield prediction framework, we are able to achieve high prediction accuracy and identify the temporal drivers behind crop yield variability. We create a multi-source dataset that includes biophysical parameters along the crop phenology, as well as meteorological, topographic, and soil parameters to perform end-of-season and in-season predictions of county-level corn yields between 2016–2023. The performance of the KAN model is compared with the commonly used traditional machine learning (ML) models and its architecture-wise equivalent MLP. The KAN-based crop yield model outperforms the other models, achieving an R² of 0.85, an RMSE of 0.84 t/ha, and an MAE of 0.62 t/ha (compared to MLP: R² = 0.81, RMSE = 0.95 t/ha, and MAE = 0.71 t/ha). In addition to end-of-season predictions, the KAN model also proves effective for in-season yield forecasting. Notably, even three months prior to harvest, the KAN model demonstrates strong performance in in-season yield forecasting, achieving an R² of 0.82, an MAE of 0.74 t/ha, and an RMSE of 0.98 t/ha. These results indicate that the model maintains a high level of explanatory power relative to its final performance. Overall, these findings highlight the potential of the KAN model as a reliable tool for early yield estimation, offering valuable insights for agricultural planning and decision-making. Full article

A large majority of cone snails (a species in the genus Conus) are vermivorous (worm-hunting), but the diversity and bioactivity of their venom peptides remain largely unexplored. In this study, we report the first venom gland transcriptomes from two species in the Rhizoconus clade, Conus capitaneus and Conus mustelinus, and a new Conus miles transcriptome from a specimen collected in the Philippines. From the set of assembled sequences, a total of 225 C. capitaneus, 121 C. miles, and 168 C. mustelinus putative peptide toxin transcripts were identified, which were assigned to 27 canonical gene superfamilies in C. capitaneus and 24 in C. miles and in C. mustelinus. Most of these venom peptides are novel, and some exhibit new cysteine patterns. Clustering also revealed 12 putative novel gene superfamilies, highlighting the diversity of uncharacterized venom peptides in this group. The O1-, M-, O2-, and con-ikot-ikot superfamilies were the most abundant, while gene superfamilies such as D and G2 were highly expressed. Several hormone-like conopeptides were also identified in this study, revealing the vast diversity of conopeptides from the Rhizoconus species. Full article

Accurate and spatially detailed soil moisture (SM) data are essential for hydrological research, precision agriculture, and ecosystem monitoring. The NASA’s Soil Moisture Active Passive (SMAP) product offers unprecedented information on global soil moisture. To provide more detailed information about the cropland SM data for the Contiguous United States (CONUS), a 1-km SMAP product has been produced using the THySM model in support of USDA NASS operations. However, the current 1-km product contains substantial data gaps, which poses challenges for applications that require continuous daily data. Data Interpolation Empirical Orthogonal Functions (DINEOF+) is an interpolation technique that uses singular value decomposition (SVD) to address missing data problems. Previous studies have applied DINEOF+ to reconstruct the 1-km daily SM dataset but without further analysis of the reconstruction errors. In this study, we perform a comprehensive validation of DINEOF+ reconstructed SM by using both the original SMAP data and in situ measurements across the CONUS. Our results show that the reconstructed SM closely aligns with the original SM with R² > 0.65 and bias ranging from 0.01 to 0.02 m³/m³. When compared to in situ SM, the mean absolute error (MAE) ranges between 0.01 and 0.04 m³/m³ and the time series correlation coefficient ranges from 0.6 to 0.8. Our findings suggest that DINEOF+ effectively recovers missing data and improves the temporal resolution of SM time series. However, we also note that the accuracy of the reconstructed SM is dependent on the quality of the original SMAP data, emphasizing the need for continued improvements in SM retrievals by satellite. Full article

Background: Despite advances in the management of coronary disease, the incidence of sudden cardiac death (SCD) in the context of coronary artery disease (CAD) remains significant and unpredictable. We investigated the patient and angiographic characteristics, and predictors of long-term outcomes, of patients presenting with cardiac arrest in the context of acute coronary occlusion, to elucidate possible mechanisms of ventricular arrhythmia. Methods: A total of 127 consecutive patients presenting to a tertiary cardiac centre with pulseless ventricular tachycardia or ventricular fibrillation during acute myocardial infarction (AMI) were compared to 100 patients with uncomplicated AMI (Cohort A). We also compared a separate group comprising 20 patients with acute RCA occlusion complicated by cardiac arrest and 24 patients with uncomplicated inferior STEMI (Cohort B). Results: In Cohort A, there was a higher incidence of proximal lesions in the arrest group (55% vs. 41%, p < 0.05). There was an almost equivalent incidence of both LAD and non-LAD (RCA/Cx) infarcts presenting with cardiac arrest. In the non-LAD arrest patients, sinoatrial nodal artery (SANa) involvement was seen in 77%, compared with 33% in non-arrest patients (p < 0.005). In Cohort B, involvement of the SANa or conus artery (CA) was found in 74% of arrest versus 21% of non-arrest patients (p < 0.005). Cohort A patients were followed up for 3.8 to 8.7 years, and at the end of this period, 22% of arrest patients and 16% of non-arrest patients were deceased. Mortality <30 days was highest in the arrest group (43% vs. 7%, p < 0.05). Beyond 30 days, there were no differences in all-cause mortality between arrest and non-arrest patients. There were more cardiac causes of death in the arrest group (54% vs. 20%, p < 0.05). Conclusions: VT/VF arrest due to acute coronary occlusion was more common in those with proximal disease and there was an increased incidence of SANa and/or CA involvement in non-LAD infarcts. Short-term mortality was higher in patients with cardiac arrest post-AMI, but beyond 30 days there was no significant difference. Full article

The conopeptide αD-FrXXA was previously isolated by our team from the venom of the vermivorous snail Conus fergusoni. This toxin is composed of two chains of 47 amino acids and inhibits neuronal and muscular subtypes of nAChR. In this study, we explored its effects on voltage-gated potassium channels heterologously expressed in Xenopus laevis oocytes using the two-electrode voltage-clamp technique (TEVC). At a concentration of 15 μM, αD-FrXXA was able to inhibit by 50% or more the currents of four subtypes of the Kv1 subfamily and slightly inhibit (<20%) two subtypes of the EAG subfamily. The conopeptide αD-FrXXA inhibits in a concentration-dependent manner the subtypes Kv1.3 (IC₅₀ 0.38 ± 0.06 μM) and Kv1.6 (IC₅₀ 0.52 ± 0.14 μM). The results reported here are noteworthy because this α-conopeptide behaves similarly to the α/κJ-PlXIVA conopeptide that inhibits nAChR and Kv channels. Full article

Neural crest cells (NCCs) play a significant role in the development of ventricular outflow tracts (OFTs), and cardiac neural crest cells (cNCCs) are involved in the development of the embryonic conus, suggesting that these cell lineages may be a teratogenic target for the development of cardiopathies in offspring conceived under a hyperglycemic environment. We evaluate the effect of the hyperglycemic intrauterine environment on the morphological and anatomical changes in the conal ridges along with the alterations in the spatiotemporal expression of AP2α in offspring hearts at 13, 15, and 17 DPC. The anatomical and histological analysis of the hearts in the experimental group presented smaller dimensions compared to the control group in the offspring at the three ages studied. Consequently, this resulted in a hyperglycemic environment that altered the immunostaining of AP2α in the hearts of the offspring at the three ages studied. Thus, the hyperglycemic intrauterine environment in offspring caused important morphological alterations in the development of conal ridges and promoted the generation of conotruncal heart defects in which the double outlet of the right ventricle, the atrioventricular (AV) canal, predominated. Therefore, knowing that exposing the offspring to more glucose potentially can lead to complications during organogenesis of the circulatory and central nervous systems. Full article

Conus venoms are both highly powerful and complex, exhibiting a remarkably intriguing molecular variability. The biologic reasons behind such astonishing molecular diversity are yet to be fully understood. We hypothesized that the current knowledge has been hampered by a lack of studies targeting the whole Conus genus backed by a feeding habit analysis, as opposed to the abundant studies focused on single species or at the individual level. We aim to enlighten the understanding of the remarkable venom variability in cone snails while pushing to deliver novel peptides for biomedical applications through a broad transcriptomics approach. Here, we assessed 76 publicly available venom-related and unrelated transcriptomes from a total of 20 different Conus species. The shared transcriptomic repertoire revealed several gene variations in accordance with predatory diets (e.g., gene loss in piscivorous species), indicating that feeding habit largely influences venom evolution. Furthermore, evidences of ubiquitous symbiotic relationships within the venom organs were depicted, as biological processes alien to Conus species (e.g., Sorocarp morphogenesis) were found in all analyzed transcriptomes. Moreover, 88 potential anti-microbial peptides were bioinformatically detected, including one showing similarity with the human ACE2 receptor. Our study highlights the importance of in-depth comparative transcriptomic analyses, fostering cross-field synergic assessments by relying on informatic, biologic, and pharmacologic resources. Full article

Groundwater depletion has emerged as a pressing global challenge, yet the low spatial resolution (0.25°) of Gravity Recovery and Climate Experiment (GRACE) satellite data limits its application in regional groundwater monitoring. In this study, based on 0.25° spatial resolution groundwater storage anomalies (GWSAs) data derived from GRACE satellite observations and GLDAS hydrological model outputs, supplemented with hydrological data, humanities data, and other geographic parameters, we constructed a Stacking-based ensemble machine learning model that achieved a 1 km spatial resolution of GWSAs distribution data across the contiguous United States (CONUS) from 2010 to 2020. The ensemble model integrates eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Categorical Boosting (CatBoost) models using an Attention-Based Dynamic Weight Allocation (ADWA) approach, along with a ridge regression model. The results indicate that our ensemble model outperforms individual machine learning (ML) models, achieving a coefficient of determination (R²) of 0.929, root mean square error (RMSE) of 25.232 mm, mean absolute error (MAE) of 19.125 mm, and Nash–Sutcliffe efficiency (NSE) of 0.936, validated by 10-fold cross-validation. In situ measurements indicate that, compared with the original data, approximately 61.7% of the monitoring wells (266 out of 431) exhibit a higher correlation after downscaling, with the overall correlation coefficient increasing by about 18.7%, which suggests that the downscaled product exhibits an appreciable improvement in accuracy. The ensemble model proposed in this study, by integrating the advantages of various ML algorithms, is better able to address the complexity and uncertainty of groundwater storage variations, thus providing scientific support for the sustainable management of groundwater resources. Full article

The marine environment is a rich source of new biotechnologies and products. Bottom trawling for shrimp species such as Xiphopenaeus kroyeri and Farfantepenaeus brasiliensis leads to the unintentional capture of non-target species, known as bycatch, which includes a variety of marine life that are often discarded without economic value. A common bycatch species on the southeast coast of Brazil is Olivancillaria urceus (O. urceus), a carnivorous gastropod that feeds mainly on bivalves. Despite its abundance, this species is still little studied, especially for biotechnological applications. Other gastropods such as Conus are known for their diverse and potent toxins, which offer great potential for pharmacological discoveries. In this study, an omics approach, including transcriptomics and proteopeptidomics, was applied to explore O. urceus at the molecular level. The transcriptome of the muscle foot/mantle led to the annotation of 19,097 genes via Gene Ontology, identifying 20 toxin-like transcripts identified considering the Gastropod class. The proteome fraction confirmed 2179 transcripts, including sequences with toxin activity, such as conotoxin precursors, Conodipine-P3, and BPTI/Kunitz domain-containing proteins. In addition, 9663 peptides of 1484 precursor proteins were detected in the peptide fraction, including 2 sequences representing neurotoxins. The identification of these sequences could lead to the discovery of new molecules with therapeutic potential. Full article