Aquatic environments under anthropogenic pressure serve as critical hotspots for the rapid development of microbial populations, including the growth of antibiotic-resistant bacteria (ARB). This study evaluates the efficiency of natural lagooning wastewater treatment systems at two sites in Settat and Ouled Said, Morocco, focusing on physicochemical characteristics and ARB prevalence in treated effluents. A substantial reduction in total bacterial counts, including coliforms, Enterococcus spp., and Pseudomonas spp., was observed following treatment, demonstrating overall system performance. However, a considerable proportion of resistant strains persisted, with coliforms demonstrating resistance rates of 27.5% to ampicillin and 45.98% to ciprofloxacin. A total of 535 bacterial isolates were detected, demonstrating the presence of human pathogenic species such as Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa. These isolates revealed substantial resistance to numerous antibiotics, including ceftazidime and imipenem. Correlation analyses revealed significant associations between physicochemical parameters and antibiotic resistance patterns, with dissolved oxygen and pH showing strong negative correlations with resistant bacterial populations. Low dissolved oxygen levels and high organic load were associated with increased resistance rates. Factor analysis indicated four major components explaining 90.53% of the overall variance, underlining the pivotal importance of temperature, nitrate, and chemical oxygen demand for water quality and ARB dynamics. Spatial and seasonal variations further affected ARB prevalence, with higher resistance rates seen during colder months and in downstream regions. Effluents from wastewater treatment and urban runoff largely contribute to the emergence and spread of ARB. This study provides valuable insights into ARB dynamics in treated wastewater, underlining the necessity for advanced wastewater treatment strategies.
Metatranscriptomic analysis of Wyeomyia confusa mosquitoes collected in the Atlantic Forest (Pindamonhangaba, São Paulo, Brazil) led to the identification of a previously uncharacterized virus, designated Wyeomyia confusa Lispivirus (WcLispV-SP), classified within the family Lispiviridae, genus Canmovirus. The viral genome consists of a negative-sense single-stranded RNA (ssRNA−) of 12,698 nucleotides, encoding six open reading frames (ORFs): nucleoprotein (N), two hypothetical proteins (HP/1 and HP/2), glycoprotein (G), ORFan protein, and RNA-dependent RNA polymerase (RdRp-L). Phylogenetic analysis supports the classification of WcLispV-SP as a distinct species within the genus Canmovirus. Structural analysis of the RdRp revealed conserved domains and catalytic motifs characteristic of members of the order Mononegavirales, supporting its functional integrity. These findings expand the known diversity of the Lispiviridae family and highlight the utility of metagenomic approaches for the discovery and characterization of RNA viruses associated with Neotropical sylvatic mosquitoes.
Establishing a rapid method to obtain pure and intact RNA molecules has revolutionized the field of RNA biology, enabling laboratories to routinely perform RNA analysis such as Northern blot, reverse transcriptase quantitative PCR, and RNA sequencing. Here, we describe an application of the effective single-step method of RNA extraction (or guanidinium thiocyanate-phenol-chloroform extraction) applied to Leptospira species. This method is based on the powerful ability of guanidinium thiocyanate to inactivate RNases and on the different solubilities of RNA and DNA in acidic phenol. This method allows one to reproducibly obtain total RNAs with high yield and integrity, as determined by capillary electrophoresis, suitable for the RNA sequencing technology.
With the advent of whole-genome sequencing (WGS), comparative analysis has led to the use of core genome MLST (cgMLST) schemes for the high-resolution reproducible typing of bacterial isolates. In cgMLST, hundreds of loci are used for gene-by-gene comparisons of assembled genomes for studying the genetic diversity of clinically important pathogens. Combination of the cgMLST data and metadata of the isolates is useful for epidemiological investigations.Here we present a cgMLST scheme for the high-resolution typing of isolates from the whole Leptospira genus, enabling identification at the level of species, clades, clonal groups, and sequence types. We show several examples how the cgMLST Leptospira database, which is a publicly available web-based database, can be used for the analyses of WGS data of Leptospira isolates. This effort was undertaken in order to facilitate international collaborations and support the global surveillance of leptospirosis.
Multimaterial 3D printing enables the fabrication of functionally graded components, but optimizing their spatial material distribution alongside structural topology remains a formidable challenge due to high-dimensional design spaces and complex constitutive modeling. This paper presents an end-to-end computational framework integrating sparsified physics-augmented neural networks with finite-element-based topology optimization. By extracting closed-form, composition-aware hyperelastic constitutive laws from experimental data, this approach facilitates exact symbolic differentiation via the adjoint state method implemented with FEniCSx, efficiently circumventing the bottlenecks of applying neural network constitutive models. This pipeline is deployed on soft robotic gripper applications, demonstrating continuous composition optimization for highly anisotropic contact responses, and the concurrent optimization of macroscopic topology and material distribution under non-failure stretch constraints. This methodology could replace laborious empirical prototyping, establishing interpretable machine-learning models as practical, robust design primitives for advanced multimaterial additive manufacturing.
