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Evaluate the relationship between body mass index (BMI), overweight status (OW), or obesity (OB) and ambulatory status in a predominantly Hispanic population of children with spinal dysraphism (SD). Retrospective data were extracted from records of 272 children and youth aged 0-24 years with a diagnosis of SD. Body mass index (BMI) and OW / OB rates were calculated for children 0-3 years, 4-11 years, and adolescents older than 11. Ethnicity was predominantly Hispanic (65.4%). No difference in mean BMI or OW / OB rate was found between ambulation groups (p = .20; p = .72). Mean BMI and OW / OB rate increased with increasing age in all groups (p < .001; p = .02). Forty-four percent of patients were OW / OB, which was greater among Hispanics (48.2%) compared with non-Hispanics [(35.2%), p = .03]. Female gender was a risk factor for increased BMI among Hispanics (p = .00). Despite no difference in ambulatory status, increasing BMI and OW / OB are associated with Hispanic ethnicity and increasing age.

In this article we undertake a systematic mapping of 649 cases of resistance movements to both fossil fuel (FF) and low carbon energy (LCE) projects, providing the most comprehensive overview of such place-based energy-related mobilizations to date. We find that (1) Place-based resistance movements are succeeding in curbing both fossil-fuel and low-carbon energy projects. Over a quarter of projects encountering social resistance have been cancelled, suspended or delayed. (2) The evidence highlights that low carbon, renewable energy and mitigation projects are as conflictive as FF projects, and that both disproportionately impact vulnerable groups such as rural communities and Indigenous peoples. Amongst LCE projects, hydropower was found to have the highest number of conflicts with concerns over social and environmental damages. (3) Repression and violence against protesters and land defenders was rife in almost all activities, with 10% of all cases analysed involving assassination of activists. Violence was particularly common in relation to hydropower, biomass, pipelines and coal extraction. Wind, solar and other renewables were the least conflictive and entailed lower levels of repression than other projects. The results caution that decarbonization of the economy is by no means inherently environmentally innocuous or socially inclusive. We find that conflicts and collective action are driven by multiple concerns through which community mobilization seeks to reshape the energy regime and its impacts. These include claims for localization, democratic participation, shorter energy chains, anti-racism, climate-justice-focused governance, and Indigenous leadership. Climate and energy policymakers need to pay closer attention to the demands and preferences of these collective movements pointing to transformative pathways to decarbonization.

Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment and accelerate research, helping scientists to generate hypotheses, design experiments, collect and interpret large datasets, and gain insights that might not have been possible using traditional scientific methods alone. Here we examine breakthroughs over the past decade that include self-supervised learning, which allows models to be trained on vast amounts of unlabelled data, and geometric deep learning, which leverages knowledge about the structure of scientific data to enhance model accuracy and efficiency. Generative AI methods can create designs, such as small-molecule drugs and proteins, by analysing diverse data modalities, including images and sequences. We discuss how these methods can help scientists throughout the scientific process and the central issues that remain despite such advances. Both developers and users of AI tools need a better understanding of when such approaches need improvement, and challenges posed by poor data quality and stewardship remain. These issues cut across scientific disciplines and require developing foundational algorithmic approaches that can contribute to scientific understanding or acquire it autonomously, making them critical areas of focus for AI innovation. The advances in artificial intelligence over the past decade are examined, with a discussion on how artificial intelligence systems can aid the scientific process and the central issues that remain despite advances.

Lamins (A/C and B) are major constituents of the nuclear lamina (NL). Structurally conserved lamina-associated domains (LADs) are formed by genomic regions that contact the NL. Lamins are also found in the nucleoplasm, with a yet unknown function. Here we map the genome-wide localization of lamin B1 in an euchromatin-enriched fraction of the mouse genome and follow its dynamics during the epithelial-to-mesenchymal transition (EMT). Lamin B1 associates with actively expressed and open euchromatin regions, forming dynamic euchromatin lamin B1-associated domains (eLADs) of about 0.3 Mb. Hi-C data link eLADs to the 3D organization of the mouse genome during EMT and correlate lamin B1 enrichment at topologically associating domain (TAD) borders with increased border strength. Having reduced levels of lamin B1 alters the EMT transcriptional signature and compromises the acquisition of mesenchymal traits. Thus, during EMT, the process of genome reorganization in mouse involves dynamic changes in eLADs. Lamina-associated domains (LADs) contact lamins in the nuclear lamina, and lamin B1 was thought to bind heterochromatic regions at the nuclear envelope. Here, the authors show lamin B1 associates with actively expressed euchromatin regions, creating dynamic euchromatin lamina-associated domains (eLADs) during epithelial-to-mesenchymal transition.

Miniaturized optical spectrometers providing broadband operation and fine resolution have an immense potential for applications in remote sensing, non-invasive medical diagnostics and astronomy. Indeed, optical spectrometers working in the mid-infrared spectral range have garnered a great interest for their singular capability to monitor the main absorption fingerprints of a wide range of chemical and biological substances. Fourier-transform spectrometers (FTS) are a particularly interesting solution for the on-chip integration due to their superior robustness against fabrication imperfections. However, the performance of current on-chip FTS implementations is limited by tradeoffs in bandwidth and resolution. Here, we propose a new FTS approach that gathers the advantages of spatial heterodyning and optical path tuning by thermo-optic effect to overcome this tradeoff. The high resolution is provided by spatial multiplexing among different interferometers with increasing imbalance length, while the broadband operation is enabled by fine tuning of the optical path delay in each interferometer harnessing the thermo-optic effect. Capitalizing on this concept, we experimentally demonstrate a mid-infrared SiGe FTS, with a resolution better than 15 cm −1 and a bandwidth of 603 cm −1 near 7.7  μ m wavelength with a 10 MZI array. This is a resolution comparable to state-of-the-art on-chip mid-infrared spectrometers with a 4-fold bandwidth increase with a footprint divided by a factor two.

Germanium (Ge) has played a key role in silicon photonics as an enabling material for datacom applications. Indeed, the unique properties of Ge have been leveraged to develop high performance integrated photodectors, which are now mature devices. Ge is also very useful for the achievement of compact modulators and monolithically integrated laser sources on silicon. Interestingly, research efforts in these domains also put forward the current revolution of mid-IR photonics. Ge and Ge-based alloys also present strong advantages for mid-infrared photonic platform such as the extension of the transparency window for these materials, which can operate at wavelengths beyond 8 μm. Different platforms have been proposed to take benefit from the broad transparency of Ge up to 15 μm, and the main passive building blocks are now being developed. In this review, we will present the most relevant Ge-based platforms reported so far that have led to the demonstration of several passive and active building blocks for mid-IR photonics. Seminal works on mid-IR optical sensing using integrated platforms will also be reviewed.

Soft magnetic Fe65Ni28Mn7 (at. %) alloy was successfully synthesized by mechanical alloying and spark plasma sintering (SPS) and, in parallel, the same composition was prepared by arc melting (AM) for comparison. Several SPS conditions were tested. X-ray diffraction and scanning electron microscopy were used to investigate the structure, phase composition, and morphology of the samples. It was found that mechanical alloying produced BCC and FCC supersaturated solid solution after 130 h of milling, with a fine microstructure (i.e., crystallite size of 10 nm). Spark plasma sintering performed at 750 °C and 1000 °C under two pressures of 50 MPa and 75 MPa revealed stable FCC phases. A single FCC phase was observed after the arc melting synthesis. The magnetic properties of milled powders and solids obtained by AM and SPS were investigated. The specimen consolidated by SPS at 1000 °C under the pressure of 50 MPa exhibits soft magnetic behavior (coercivity 0.07 Oe), whereas the mechanically alloyed sample revealed hard magnetic behavior. The specimen consolidated at 750 °C under a pressure of 75 MPa showed a higher compressive strength of 1700 MPa and a Vickers hardness of 425 ± 18 HV. As a result, sintering at 750 °C/75 MPa can be utilized to enhance the mechanical properties, while those sintered at 1000 °C/50 MPa increase magnetic softness.

The gut microbiome is shaped by diet and influences host metabolism; however, these links are complex and can be unique to each individual. We performed deep metagenomic sequencing of 1,203 gut microbiomes from 1,098 individuals enrolled in the Personalised Responses to Dietary Composition Trial (PREDICT 1) study, whose detailed long-term diet information, as well as hundreds of fasting and same-meal postprandial cardiometabolic blood marker measurements were available. We found many significant associations between microbes and specific nutrients, foods, food groups and general dietary indices, which were driven especially by the presence and diversity of healthy and plant-based foods. Microbial biomarkers of obesity were reproducible across external publicly available cohorts and in agreement with circulating blood metabolites that are indicators of cardiovascular disease risk. While some microbes, such as Prevotella copri and Blastocystis spp., were indicators of favorable postprandial glucose metabolism, overall microbiome composition was predictive for a large panel of cardiometabolic blood markers including fasting and postprandial glycemic, lipemic and inflammatory indices. The panel of intestinal species associated with healthy dietary habits overlapped with those associated with favorable cardiometabolic and postprandial markers, indicating that our large-scale resource can potentially stratify the gut microbiome into generalizable health levels in individuals without clinically manifest disease. Analyses from the gut microbiome of over 1,000 individuals from the PREDICT 1 study, for which detailed long-term diet information as well as hundreds of fasting and same-meal postprandial cardiometabolic blood marker measurements are available, unveil new associations between specific gut microbes, dietary habits and cardiometabolic health.

The nucleotide analogue azacitidine (AZA) is currently the best treatment option for patients with high-risk myelodysplastic syndromes (MDS). However, only half of treated patients respond and of these almost all eventually relapse. New treatment options are urgently needed to improve the clinical management of these patients. Here, we perform a loss-of-function shRNA screen and identify the histone acetyl transferase and transcriptional co-activator, CREB binding protein (CBP), as a major regulator of AZA sensitivity. Compounds inhibiting the activity of CBP and the closely related p300 synergistically reduce viability of MDS-derived AML cell lines when combined with AZA. Importantly, this effect is specific for the RNA-dependent functions of AZA and not observed with the related compound decitabine that is only incorporated into DNA. The identification of immediate target genes leads us to the unexpected finding that the effect of CBP/p300 inhibition is mediated by globally down regulating protein synthesis. Azacitidine (AZA) treatment is used for patients with myelodysplasias that cannot undergo bone marrow transplantation; however, AZA treatment is only partially effective. Here the authors show synergy of AZA with compounds inhibiting the chromatin regulators CBP and p300, which is mediated by the RNA-dependent functions of AZA affecting protein translation.

Indicator organisms and antibiotic resistance were used as a proxy to measure microbial water quality of ballast tanks of ships, and surface waters in a tropical harbor. The survival of marine bacteria in ballast tanks appeared to diminish over longer water retention time, with a reduction of cell viability observed after a week based on heterotrophic plate counts. Pyrosequencing of 16S rRNA genes showed distinct differences in microbial composition of ballast and harbor waters. The harbor waters had a higher abundance of operational taxonomic units (OTUs) assigned to Cyanobacteria (Synechococcus spp.) and α-proteobacteria (SAR11 members), while marine hydrocarbon degraders such as γ-proteobacteria (Ocenspirillaes spp., Thiotrchales spp.) and Bacteroidetes (Flavobacteriales spp.) dominated the ballast water samples. Screening of indicator organisms found Escherichia coli (E. coli), Enterococcus and Pseudomonas aeruginosa (P. aeruginosa) in two or more of the ballast and harbor water samples tested. Vibrio spp. and Salmonella spp. were detected exclusively in harbor water samples. Using quantitative PCR (qPCR), we screened for 13 antibiotic resistant gene (ARG) targets and found higher abundances of sul1 (4.13-3.44 x 102 copies/mL), dfrA (0.77-1.80 x10 copies/mL) and cfr (2.00-5.21 copies/mL) genes compared to the other ARG targets selected for this survey. These genes encode for resistance to sulfonamides, trimethoprim and chloramphenicol-florfenicol antibiotics, which are also known to persist in sediments of aquaculture farms and coastal environments. Among the ARGs screened, we found significant correlations (P<0.05) between ereA, ermG, cfr and tetO genes to one or more of the indicator organisms detected in this study, which may suggest that these members contribute to the environmental resistome. This study provides a baseline water quality survey, quantitatively assessing indicators of antibiotic resistance, potentially pathogenic organisms and a broad-brush description of difference in microbial composition and diversity between open oceans and tropical coastal environments through the use of next generation sequencing technology.