The most recent Intergovernmental Panel on Climate Change report sets out sobering scenarios about the future for our young people and appeals for \'deep, rapid, and sustained reductions in greenhouse gas emissions\'. Although technological responses are essential to achieve these reductions, technocratic solutions alone will not solve the environmental emergency; a widespread societal transformation is needed. Education can play a profound role in this transformation as it is fundamental to building a society with knowledge, skills and motivation to tackle climate change so as to regenerate ecological and social systems. This commentary reflects on multiple dimensions of education\'s role, focusing particularly on schools and the important contribution that all subjects can make towards developing interdisciplinary, complex understandings of the environmental emergency and living more sustainably. Drawing from a recent nationwide survey of teachers in England carried out by the UCL Centre for Climate Change and Sustainability Education, we highlight a troubling lack of engagement in formal professional development related to climate change and sustainability, even amongst a \'climate change engaged\' cohort of teachers, and the imperative for comprehensive professional learning for teachers from across all subjects and year levels.

Antibiotic resistance (AR) is considered one of the greatest global threats in the current century, which can only be overcome if all interconnected areas of humans, animals and the environment are taken into account as part of the One Health concept proposed by the World Health Organization (WHO). Water and wastewater are among the most important environmental media of AR sources, where the phenomena are generally non-linear. Therefore, the aim of this study was to investigate the application of machine learning-based methods (MLMs) to solve AR-induced problems in water and wastewater. For this purpose, most relevant databases were searched in the period between 1987 and 2023 to systematically analyze and categorize the applications. Accordingly, the results showed that out of 12 applications, 11 (91.6%) were for shallow learning and 1 (8.3%) for deep learning. In shallow learning category, n = 6, 50% of the applications were regression and n = 4, 33.3% were classification, mainly using artificial neural networks, decision trees and Bayesian methods for the following objectives: Predicting the survival of antibiotic-resistant bacteria (ARB), determining the order of influencing parameters on AR-based scores, and identifying the major sources of antibiotic resistance genes (ARGs). In addition, only one study (8.3%) was found for clustering and no study for association. Surprisingly, deep learning had been used in only one study (8.3%) to predict ARGs sequences. Therefore, working on the knowledge gaps of AR, especially using clustering, association and deep learning methods, would be a promising option to analyze more aspects of the related problems. However, there is still a long way to go to consider and apply MLMs as unique approaches to study different aspects of AR in water and wastewater.

Informal settlements are home to over 1 billion people worldwide and are characterised by high population densities and poor environmental conditions. The authors identify the impact of COVID-19 on existing water and sanitation practices and potential pathways for the transmission of COVID-19 in informal settlements in India and Indonesia. In the short term, there is an urgent need for mobile and contactless hand washing, washing/bathing facilities and toilets. In the long term, COVID-19 provides an opportunity to invest in centralised water and sanitation networked solutions appropriate for high-density settings to integrate those settlements into cities and improve environmental conditions and health in these cities.

The Pelagonian stratigraphy of the Internal Hellenides consists of a Permo-Triassic basement and an Upper Triassic and Jurassic carbonate platform formation that has been overthrust by the Eohellenic ophiolite sheet during the Early Cretaceous. Intensive erosion, during the Cretaceous, removed most of the ophiolite and parts of the Jurassic formation. It is hypothesised that uplift and erosion of eastern Pelagonia was triggered by the break-off of the subducted oceanic leading edge of the Pelagonian plate. An investigation of the rocks that succeed the erosional unconformity shows that they constitute a shear-zone that is tectonically overlain by Cretaceous platform carbonates. Geochemical analyses of the shear-zone rocks substantiate that they are of mid-oceanic ridge and island arc provenience. Eastern Pelagonia collided with a Cretaceous carbonate platform, probably the Paikon forearc basin, as the Almopias ocean crust subducted beneath that island-arc complex. The Cretaceous platform, together with a substrate of sheared-off ocean floor mélange, overthrust eastern Pelagonia as subduction continued, and the substrate was dynamically metamorphosed into cataclastic rocks, mylonite, phyllonite and interpreted pseudotachylite. This complex of Cretaceous platform rocks and a brittle-ductile shear-zone-substrate constitute the here named Paikon-Palouki nappe, which was emplaced during Early Palaeocene. The Paikon-Palouki nappe did not reach Evvoia. Seismic tomographic models of the Aegean region apparently depict images of two broken-off ocean-plate-slabs, interpreted as Almopias-lithosphere-slabs. It is concluded that the western Almopias slab began to sink during the Early Cretaceous, while the eastern Almopias slab broke off and sank after the Paikon-Palouki nappe was emplaced in the Early Palaeocene.

To better leverage opportunities arising out of sustainable and inclusive management of sanitation services there is a need for robust and comprehensive evidence of the wide-ranging benefits that sanitation can deliver. The Sustainable Development Goals (SDGs) provide a comprehensive framework for sustainable development broken down into 169 interconnected Targets which are articulated under 17 Goals. Based on a methodology developed at University College London (UCL), this study identifies linkages between sanitation and the 169 Targets corroborated by published evidence. We show that there are synergies between sanitation and all 17 Goals and 130 (77%) of the Targets, and trade-offs for 28 (17%) of the Targets. We identified 83 Targets (49%) that call for action in the sanitation sector. The results demonstrate the far-reaching benefits that can be unlocked from investment in sanitation, which extend beyond health and spread across sectors. The evidence base for the 17 Goals establishes links that can inform cross-sectoral action, collaborations and investment across governance levels for integrated sanitation solutions. The research provides different stakeholders with a framework that can be applied to context-specific cases and projects. We propose a range of recommendations to policy makers, practitioners and researchers who seek to take this study further to help achieve the SDGs.

The superfamily Alveolinoidea is a member of the Order Miliolida, and comprises three main families, the Alveolinidae, the Fabulariidae and the Rhapydioninidae. They are examples of Larger benthic foraminifera (LBF), which are single-celled organisms with specific characteristic endoskeletons. Alveolinoids are found globally from the Cretaceous to the present day, and are important biostratigraphic index fossils in shallow-marine carbonates. They are often associated with hydrocarbon reservoirs, and exhibit provincialism with characteristic genera often confined to one of the American, Tethyan or Indo-Pacific provinces. Previously, the systematic study of the global interrelationship between the various alveolinoid lineages has not been possible because of the absence of biostratigraphic correlation between the geographically scattered assemblages, and the scarcity of described material from the Indo-Pacific province. Here we use the literature and new material from the Americas, the French Alps, Iran, Tibet, India and South East Asia, coupled with the use of the planktonic foraminiferal zonal (PZ) correlation scheme to propose a comprehensive, global, systematic analysis of the biostratigraphic, phylogenetic and paleogeographic evolution of the alveolinoids. The alveolinoids originated in the Cretaceous in the Tethyan province. During a global sea-level low stand, a westward migration of some alveolinoids species to the Americas occurred, a behaviour previously reported in contemporaneous orbitolinid LBF. After the Cretaceous/Palaeogene (K-P) event, which saw the extinction of all Cretaceous alveolinoids, rare new forms of alveolinoids evolved again, first in the Americas and later independently in Tethys. As was found in previous studies of rotalid LBF, sea-level low stands in the Paleocene also allowed some alveolinoid forms to migrate, but this time in an eastward direction from the Americas to Tethys, and from Tethys on to the Indo-Pacific province. Alveolinoids still exist today (Borelis and Alveolinella), the former of which is cosmopolitan, while the latter is restricted to the Indo-Pacific province. Throughout their phylogenetic history, alveolinoids characteristically exhibit convergent evolution, with the repeated re-occurrence of certain morphological features. Understanding this propensity to homoplasy is essential in understanding and constructing the phylogenetic relationships within the alveolinoid superfamily.

Cascades have emerged as a new paradigm in disaster studies. The high level of dependency of modern populations on critical infrastructure and networks allows the impact of disasters to propagate through socio-economic systems. Where vulnerabilities overlap and interact, escalation points are created that can create secondary effects with greater impact than the primary event. This article explains how complexity can be categorised and analysed in order to find those weak points in society that enable cascading impacts to develop. Scenarios can be used to identify critical dependencies and guide measures designed to increase resilience. Experience suggests that many potential impacts of cascading disasters remain uninvestigated, which provides ample scope for escalation of impacts into complex forms of crisis.

We conducted a molecular surveillance study for carbapenem-resistant Enterobacteriaceae (CRE) colonization in food-producing animals in China that included primarily swine and poultry for three consecutive years. A total of 2,771 samples from food-producing animals and their surrounding environments were collected from different regions in China from 2015 to 2017. Enrichment cultures supplemented with meropenem were used to isolate carbapenem non-susceptible isolates and these were subsequently identified by MALDI-TOF MS. Resistance phenotypes and genotypes were confirmed using antimicrobial susceptibility testing and molecular biological techniques. Genomic characteristics of the carbapenemase-producing isolates were investigated using whole genome sequencing (WGS) and bioinformatic analysis. In total, 88 NDM-positive Enterobacteriaceae were identified from 2,771 samples and 96.6% were Escherichia coli. The New Delhi metallo-β-lactamase (NDM)-positive E. coli displayed a diversity of sequence types (ST), and ST48 and ST165 were the most prevalent. Three variants of bla NDM (bla NDM-1, bla NDM-4, and bla NDM-5) were detected and WGS indicated that bla NDM-5 predominated and was carried primarily on IncX3 plasmids. All these isolates were also multiply-drug resistant. These results revealed that food-producing animals in China are an important reservoir for NDM-positive E. coli and pose a potential threat to public health.

UNASSIGNED: Carbapenems, colistin, and tigecycline are critically important antibiotics in clinics. After the global appearance of bla NDM and mcr mediating the resistance to carbapenems and colistin, respectively, tigecycline becomes the last-resort drug against severe human infections caused by multidrug-resistant bacteria. Recently, a mobile tigecycline resistance gene tet(X4) has been identified in Escherichia coli, Klebsiella pneumoniae, and Acinetobacter baumannii that causes high resistance to tigecycline and other tetracyclines. In this study, the prevalence of tet(X4) in E. coli isolates from duck and goose farms in Southeast China was identified and characterized.
UNASSIGNED: Feces, soil, sewage, and dust samples were collected from duck and goose farms along with the southeast coast provinces of China. Antimicrobial susceptibility testing and polymerase chain reaction screening were performed to investigate the phenotype and genotype of tigecycline resistance. Conjugation, S1 pulsed-field gel electrophoresis (PFGE), and whole-genome sequencing were used to determine the transferability, genetic location, and the genomic characteristics of tet(X4).
UNASSIGNED: In total, 1,716 samples were collected, and 16 isolates (0.9%) recovered from Guangdong, Shandong, and Jiangsu were positive for tet(X4) gene with tigecycline minimum inhibitory concentrations ≥16 mg/L. Notably, among these tet(X4)-positive E. coil isolates, seven of them were from the environment samples (soil and sewage). PFGE and multilocus sequence typing demonstrated that ST3997 was the most prevalent sequence type (eight isolates, 50%) in Jiangsu province. By conjugation assays, 11 isolates were able to transfer tet(X4) plasmid to E. coli C600 recipient, and these plasmids belonged to IncHI1 and IncX1 detected by sequence analysis. tet(X4) was found adjacent to an insertion sequence ISCR2 downstream and a catD gene upstream for all isolates. In addition, multiple-drug resistance to tigecycline, chlortetracycline, ampicillin, florfenicol, ciprofloxacin, gentamicin, trimethoprim/sulfamethoxazole, and fosfomycin was profiled in most of the tet(X4)-positive isolates.
UNASSIGNED: The identification of tet(X4) harboring E. coli strains in duck farms and their surrounding environment enlarges our knowledge of the variety and prevalence of tigecycline resistance. The prevalence of tet(X4) raises concern for the use of tetracyclines in animal farming, and the tet(X4) gene should be listed as primary gene for resistance surveillance.