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The postsynaptic density (PSD) consists of a lattice-like array of interacting proteins that organizes and stabilizes synaptic receptors, ion channels, structural proteins, and signaling molecules required for normal synaptic transmission and synaptic function. The scaffolding and hub protein postsynaptic density protein-95 (PSD-95) is a major element of central chemical synapses and interacts with glutamate receptors, cell adhesion molecules, and cytoskeletal elements. In fact, PSD-95 can regulate basal synaptic stability as well as the activity-dependent structural plasticity of the PSD and, therefore, of the excitatory chemical synapse. Several studies have shown that PSD-95 is highly enriched at excitatory synapses and have identified multiple protein structural domains and protein-protein interactions that mediate PSD-95 function and trafficking to the postsynaptic region. PSD-95 is also a target of several signaling pathways that induce posttranslational modifications, including palmitoylation, phosphorylation, ubiquitination, nitrosylation, and neddylation; these modifications determine the synaptic stability and function of PSD-95 and thus regulate the fates of individual dendritic spines in the nervous system. In the present work, we review the posttranslational modifications that regulate the synaptic localization of PSD-95 and describe their functional consequences. We also explore the signaling pathways that induce such changes.

Synapses are complex structures that allow communication between neurons in the central nervous system. Studies conducted in vertebrate and invertebrate models have contributed to the knowledge of the function of synaptic proteins. The functional synapse requires numerous protein complexes with specialized functions that are regulated in space and time to allow synaptic plasticity. However, their interplay during neuronal development, learning, and memory is poorly understood. Accumulating evidence links synapse proteins to neurodevelopmental, neuropsychiatric, and neurodegenerative diseases. In this review, we describe the way in which several proteins that participate in cell adhesion, scaffolding, exocytosis, and neurotransmitter reception from presynaptic and postsynaptic compartments, mainly from excitatory synapses, have been associated with several synaptopathies, and we relate their functions to the disease phenotype.

Background/Objectives: Cancer is the second leading cause of death in Puerto Rico, its impact worsened by an aging population. Many survivors experience long-term effects that reduce health-related quality of life (HRQoL). Chronic comorbidities are common in Puerto Rico, yet cancer survivors remain underrepresented in HRQoL research, raising concern about their impact on survivorship. This study examined whether comorbidity burden was associated with HRQoL and if patient navigation services or perceived social support moderated this association. Methods: This cross-sectional analysis included 643 cancer survivors from the START-PR study (November 2023–August 2025). HRQoL was measured using the Functional Assessment of Cancer Therapy—General (FACT-G) and dichotomized at the sample median (≤71 = poor; >71 = non-poor). Comorbidity burden was grouped as 0, 1, or ≥2 conditions. Patient navigation was assessed by self-reported service use in the past year. Perceived social support was measured using an adapted Multidimensional Scale of Perceived Social Support and dichotomized at the sample median (≤40 = low; >40 = high). Logistic regression estimated odds ratios (OR; 95% CI), adjusting for covariates. Interaction terms tested effect modification. Results: Participants with one (OR = 1.85; 95% CI: 1.15–2.97) or ≥2 comorbidities (OR = 2.95; 95% CI: 1.88–4.61) had significantly higher odds of poor HRQoL than those without comorbidities. Hypertension, depression, diabetes, arthritis, and asthma were more common among participants with poor HRQoL. Neither patient navigation nor perceived social support significantly moderated the comorbidity burden-HRQoL association. Conclusions: Greater comorbidity burden was associated with poor HRQoL. These findings underscore the need for survivorship care models that integrate chronic disease management, including mental health, to improve outcomes in underserved populations.

Potato cyst nematodes (PCN) from the genus Globodera spp. cause major losses in the potato ( Solanum tuberosum) industry worldwide. Despite their importance, at present little is known about the status of this plant pathogen in cultivated potatoes in Colombia. In this study, a total of 589 samples collected from 75 geographic localities in nine potato producing regions of Colombia (Cundinamarca, Boyacá, Antioquia, Nariño, Santander, Norte de Santander, Tolima, Caldas and Cauca) were assayed for the presence of potato cyst nematodes. Fifty-seven percent of samples tested positive for PCN. Based on phylogenetic analysis of the internal transcribed spacer region (ITS1-5.8S-ITS2) of the rRNA gene and D2-D3 expansion segments of the 28S rRNA gene, all populations but one were identified as Globodera pallida . Sequences of G . pallida from Colombia formed a monophyletic group closely related to Peruvian populations, with the lowest average number of nucleotide substitutions per site ( Dxy = 0.002) and net nucleotide substitutions per site ( Da = 0.001), when compared to G . pallida populations from Europe, South and North America. A single sample formed a well-supported subclade along with G . rostochiensis and G . tabacum from Japan, USA and Argentina. To our knowledge this is the first comprehensive survey of Globodera populations from Colombia that includes genetic data. Our findings on species diversity and phylogenetic relationships of Globodera populations from Colombia may help elucidate the status and distribution of Globodera species, and lead to the development of accurate management strategies for the potato cyst nematodes.

Hypervirulent Klebsiella pneumoniae (hvKp) has emerged as a significant public health concern, yet rare sublineages remain poorly characterized. Here, we described a K30-ST198 hvKp sublineage identified in four isolates from two patients, including three sequential strains (K30B1, K30B2, K30B3) recovered over eight months from recurrent liver abscesses and one strain (K30-HUMV1) from a urinary tract infection. All isolates exhibited a yYpermucoviscous phenotype and resistance restricted to ampicillin and amoxicillin. Screening with the eazyplex hvKp assay detected ybt and rmpA in all strains, yielding a virulence score of 1. Biofilm production was strong in K30B1, K30B2, moderate in K30-HUMV1, but weak in K30B3. In the Galleria mellonella infection model, K30B1 showed higher virulence than the other isolates. Whole-genome sequencing identified the ICEKp1 carrying hypervirulence-associated genes (ybt, pagO, rmpAC, iroBCDN) together with additional virulence factors (fim, mrkD, uge, ureA, wabG, wcaJ, mliC), while antibiotic resistance genes were limited to fosA and blaSHV-77. Protein structures and their functional domains were predicted using AlphaFold v3.0.1 and ColabFold v1.5.5, based on pLDDT scores, providing further insights into gene functionality. This work represents one of the first detailed characterizations of K30-ST198 hvKp, underscoring the need for integrated genomic, phenotypic, and structural approaches in hvKp surveillance.

Potato virus S (PVS) is a prevalent virus in potato fields in Colombia and the rest of the world. PVS has been classified into two separate lineages, PVSO (Ordinary) and PVSA (An- dean), which are genetically distinct. In this study, the com- plete genome sequence of a new PVS isolate (PVS_Antioquia) was obtained using High-throughput sequencing (Illumina HiSeq-2000) from tuber sprouts of Solanum phureja (var. Criolla Colombia). The PVS_Antioquia genome comprises 8,483 nt that code for six ORFs: RdRp (223 kDa), TGBp1-3 (25kDa, 12kDa, 7kDa) CP (32.3 kDa) and NABP (11 kDa) and share a high sequence identity with respect to the PVS_RVC (>95%) from Colombia, in contrast to 81 to 82% identity with respect to the PVSA and PVSO isolates from around the world. This genome information was used to design RT-qPCR primers that are specific for the Colombian PVS strains (RVC and Antioquia) which were validated in S. phureja leaf and tuber samples. These primers detected PVS in 80 and 60% of a set of fifteen leaf and tuber samples, respectively, suggesting a high incidence of this virus in the potato crops of Antioquia.

Potato cyst nematodes (PCN) from the genus Globodera spp. cause major losses in the potato (Solanum tuberosum) industry worldwide. Despite their importance, at present little is known about the status of this plant pathogen in cultivated potatoes in Colombia. In this study, a total of 589 samples collected from 75 geographic localities in nine potato producing regions of Colombia (Cundinamarca, Boyacá, Antioquia, Nariño, Santander, Norte de Santander, Tolima, Caldas and Cauca) were assayed for the presence of potato cyst nematodes. Fifty-seven percent of samples tested positive for PCN. Based on phylogenetic analysis of the internal transcribed spacer region (ITS1-5.8S-ITS2) of the rRNA gene and D2-D3 expansion segments of the 28S rRNA gene, all populations but one were identified as Globodera pallida. Sequences of G. pallida from Colombia formed a monophyletic group closely related to Peruvian populations, with the lowest average number of nucleotide substitutions per site (Dxy = 0.002) and net nucleotide substitutions per site (Da = 0.001), when compared to G. pallida populations from Europe, South and North America. A single sample formed a well-supported subclade along with G. rostochiensis and G. tabacum from Japan, USA and Argentina. To our knowledge this is the first comprehensive survey of Globodera populations from Colombia that includes genetic data. Our findings on species diversity and phylogenetic relationships of Globodera populations from Colombia may help elucidate the status and distribution of Globodera species, and lead to the development of accurate management strategies for the potato cyst nematodes.

Abstract Potato cyst nematodes (PCN) from the genus Globodera spp. cause major losses in potato (Solanum tuberosum) industry worldwide. Despite their importance, at present little is known about the status of this plant pathogen in cultivated potatoes in Colombia. In this study, a total of 589 samples collected from 75 geographic localities from nine potato producing departments of Colombia were assayed for the presence of potato cyst nematodes. Fifty-seven percent of samples tested positive for PCN. All populations but one were identified as Globodera pallida, with conspicuous morphometric variation found among populations. Based on phylogenetic analysis of the internal transcribed spacer region (ITS1-5.8S-ITS2) of the rRNA gene and D2-D3 expansion segments of the 28S rRNA gene, G. pallida from Colombia formed a monophyletic group closely related to Peruvian populations, with the lowest average number of nucleotide substitutions per site (Dxy= 0.002) and net nucleotide substitutions per site (Da= 0.001), when compared to G. pallida populations from South, North America and Europe. A single sample formed a well-supported subclade along with G. rostochiensis and G. tabacum from Japan, USA and Argentina. To our knowledge this is the first comprehensive survey of Globodera populations from Colombia that includes morphological and genetic data. Our findings on species diversity and phylogenetic relationships of Globodera populations from Colombia may help elucidate the status and distribution of Globodera species, and lead to the development of accurate management strategies for the potato cyst nematodes.

Background Columnaris disease (CD) is an emerging problem for the rainbow trout aquaculture industry in the US. The objectives of this study were to: (1) identify common genomic regions that explain a large proportion of the additive genetic variance for resistance to CD in two rainbow trout ( Oncorhynchus mykiss ) populations; and (2) estimate the gains in prediction accuracy when genomic information is used to evaluate the genetic potential of survival to columnaris infection in each population. Methods Two aquaculture populations were investigated: the National Center for Cool and Cold Water Aquaculture (NCCCWA) odd-year line and the Troutlodge, Inc., May odd-year (TLUM) nucleus breeding population. Fish that survived to 21 days post-immersion challenge were recorded as resistant. Single nucleotide polymorphism (SNP) genotypes were available for 1185 and 1137 fish from NCCCWA and TLUM, respectively. SNP effects and variances were estimated using the weighted single-step genomic best linear unbiased prediction (BLUP) for genome-wide association. Genomic regions that explained more than 1% of the additive genetic variance were considered to be associated with resistance to CD. Predictive ability was calculated in a fivefold cross-validation scheme and using a linear regression method. Results Validation on adjusted phenotypes provided a prediction accuracy close to zero, due to the binary nature of the trait. Using breeding values computed from the complete data as benchmark improved prediction accuracy of genomic models by about 40% compared to the pedigree-based BLUP. Fourteen windows located on six chromosomes were associated with resistance to CD in the NCCCWA population, of which two windows on chromosome Omy 17 jointly explained more than 10% of the additive genetic variance. Twenty-six windows located on 13 chromosomes were associated with resistance to CD in the TLUM population. Only four associated genomic regions overlapped with quantitative trait loci (QTL) between both populations. Conclusions Our results suggest that genome-wide selection for resistance to CD in rainbow trout has greater potential than selection for a few target genomic regions that were found to be associated to resistance to CD due to the polygenic architecture of this trait, and because the QTL associated with resistance to CD are not sufficiently informative for selection decisions across populations.

Recently, the use of small UAVs for monitoring agricultural land areas has been increasingly used by agricultural producers in order to improve crop yields. However, correctly interpreting the collected imagery data is still a challenging task. In this study, an automated pipeline for monitoring C. Annuum crops based on a deep learning model is implemented. The system is capable of performing inferences on the health status of individual plants, and to determine their locations and shapes in a georeferenced orthomosaic. Accuracy achieved on the classification task was 94.5. AP values among classes were in the range of [63,100] for plant location boxes, and in [40,80] for foliar area predictions. The methodology requires only RGB images, and so, it can be replicated for the monitoring of other types of crops by only employing consumer-grade UAVs. A comparison with random forest and large-scale mean shift segmentation methods which use predetermined features is presented. NDVI results obtained with multispectral equipment are also included.