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Newly copied sister chromatids are tethered together by the cohesin complex, but how sister chromatid cohesion is coordinated with DNA replication is poorly understood. Prevailing models suggest cohesin complexes, bound to DNA before replication, remain behind the advancing replication fork to keep sister chromatids together. By visualizing single replication forks colliding with pre-loaded cohesin complexes, we find that the replisome instead pushes cohesin to where a converging replisome is met. While the converging replisomes are removed during DNA replication termination, cohesin remains on nascent DNA and provides cohesion. Additionally, we show that CMG disassembly during replication termination is vital for proper cohesion in budding yeast. Together, our results support a new model where sister chromatid cohesion is established during DNA replication termination.
\n \n\n \n \nEukaryotic genomes are organized by loop extrusion and sister chromatid cohesion, both mediated by the multimeric cohesin protein complex. Understanding how cohesin holds sister DNAs together, and how loss of cohesion causes age-related infertility in females, requires knowledge as to cohesin's stoichiometry in vivo. Using quantitative super-resolution imaging, we identified two discrete populations of chromatin-bound cohesin in postreplicative human cells. Whereas most complexes appear dimeric, cohesin that localized to sites of sister chromatid cohesion and associated with sororin was exclusively monomeric. The monomeric stoichiometry of sororin:cohesin complexes demonstrates that sister chromatid cohesion is conferred by individual cohesin rings, a key prediction of the proposal that cohesion arises from the co-entrapment of sister DNAs.
\n \n\n \n \nBACKGROUND: The Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) total score is a widely used measure of functional status in Amyotrophic Lateral Sclerosis/Motor Neuron Disease (ALS), but recent evidence has raised doubts about its validity. The objective was to examine the measurement properties of the ALSFRS-R, aiming to produce valid measurement from all 12 scale items. METHOD: Longitudinal ALSFRS-R data were collected between 2013-2020 from 1120 people with ALS recruited from 35 centers, together with other scales in the Trajectories of Outcomes in Neurological Conditions-ALS (TONiC-ALS) study. The ALSFRS-R was analyzed by confirmatory factor analysis (CFA), Rasch Analysis (RA) and Mokken scaling. RESULTS: No definite factor structure of the ALSFRS-R was confirmed by CFA. RA revealed the raw score total to be invalid even at the ordinal level because of multidimensionality; valid interval level subscale measures could be found for the Bulbar, Fine-Motor and Gross-Motor domains but the Respiratory domain was only valid at an ordinal level. All four domains resolved into a single valid, interval level measure by using a bifactor RA. The smallest detectable difference was 10.4% of the range of the interval scale. CONCLUSION: A total ALSFRS-R ordinal raw score can lead to inferential bias in clinical trial results due to its non-linear nature. On the interval level transformation, more than 5 points difference is required before a statistically significant detectable difference can be observed. Transformation to interval level data should be mandatory in clinical trials.
\n \n\n \n \nBACKGROUND: Artificial intelligence (AI) for ultrasound scanning in regional anaesthesia is a rapidly developing interdisciplinary field. There is a risk that work could be undertaken in parallel by different elements of the community but with a lack of knowledge transfer between disciplines, leading to repetition and diverging methodologies. This scoping review aimed to identify and map the available literature on the accuracy and utility of AI systems for ultrasound scanning in regional anaesthesia. METHODS: A literature search was conducted using Medline, Embase, CINAHL, IEEE Xplore, and ACM Digital Library. Clinical trial registries, a registry of doctoral theses, regulatory authority databases, and websites of learned societies in the field were searched. Online commercial sources were also reviewed. RESULTS: In total, 13,014 sources were identified; 116 were included for full-text review. A marked change in AI techniques was noted in 2016-17, from which point on the predominant technique used was deep learning. Methods of evaluating accuracy are variable, meaning it is impossible to compare the performance of one model with another. Evaluations of utility are more comparable, but predominantly gained from the simulation setting with limited clinical data on efficacy or safety. Study methodology and reporting lack standardisation. CONCLUSIONS: There is a lack of structure to the evaluation of accuracy and utility of AI for ultrasound scanning in regional anaesthesia, which hinders rigorous appraisal and clinical uptake. A framework for consistent evaluation is needed to inform model evaluation, allow comparison between approaches/models, and facilitate appropriate clinical adoption.
\n \n\n \n \nCancer metabolism produces large fluxes of lactate and H+, which are extruded by membrane transporters. However, H+ production and extrusion must be coupled by diffusion, facilitated by mobile buffers. Yan et\u00a0al. propose that carnosine, generated by CARNS2, provides this mobile buffering and enables lysosomal functions that block T\u00a0cell surveillance.
\n \n\n \n \nINTRODUCTION: There is growing evidence that sleep is disrupted after stroke, with worse sleep relating to poorer motor outcomes. It is also widely acknowledged that consolidation of motor learning, a critical component of poststroke recovery, is sleep-dependent. However, whether the relationship between disrupted sleep and poor outcomes after stroke is related to direct interference of sleep-dependent motor consolidation processes, is currently unknown. Therefore, the aim of the present study is to understand whether measures of motor consolidation mediate the relationship between sleep and clinical motor outcomes post stroke. METHODS AND ANALYSIS: We will conduct a longitudinal observational study of up to 150 participants diagnosed with stroke affecting the upper limb. Participants will be recruited and assessed within 7\u2009days of their stroke and followed up at approximately 1 and 6 months. The primary objective of the study is to determine whether sleep in the subacute phase of recovery explains the variability in upper limb motor outcomes after stroke (over and above predicted recovery potential from the Predict Recovery Potential algorithm) and whether this relationship is dependent on consolidation of motor learning. We will also test whether motor consolidation mediates the relationship between sleep and whole-body clinical motor outcomes, whether motor consolidation is associated with specific electrophysiological sleep signals and sleep alterations during subacute recovery. ETHICS AND DISSEMINATION: This trial has received both Health Research Authority, Health and Care Research Wales and National Research Ethics Service approval (IRAS: 304135; REC: 22/LO/0353). The results of this trial will help to enhance our understanding of the role of sleep in recovery of motor function after stroke and will be disseminated via presentations at scientific conferences, peer-reviewed publication, public engagement events, stakeholder organisations and other forms of media where appropriate. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov: NCT05746260, registered on 27 February 2023.
\n \n\n \n \nTerrestrial CAM plants typically occur in hot semiarid regions, yet can show high crop productivity under favorable conditions. To achieve a more mechanistic understanding of CAM plant productivity, a biochemical model of diel metabolism was developed and integrated with 3-D shoot morphology to predict the energetics of light interception and photosynthetic carbon assimilation. Using Agave tequilana as an example, this biochemical model faithfully simulated the four diel phases of CO2 and metabolite dynamics during the CAM rhythm. After capturing the 3-D form over an 8-yr production cycle, a ray-tracing method allowed the prediction of the light microclimate across all photosynthetic surfaces. Integration with the biochemical model thereby enabled the simulation of plant and stand carbon uptake over daily and annual courses. The theoretical maximum energy conversion efficiency of Agave spp. is calculated at 0.045-0.049, up to 7% higher than for C3 photosynthesis. Actual light interception, and biochemical and anatomical limitations, reduced this to 0.0069, or 15.6\u2009Mg\u2009ha-1 \u2009yr-1 dry mass annualized over an 8-yr cropping cycle, consistent with observation. This is comparable to the productivity of many C3 crops, demonstrating the potential of CAM plants in climates where little else may be grown while indicating strategies that could raise their productivity.
\n \n\n \n \nBACKGROUND AND AIMS: CAM photosynthesis is hypothesized to have evolved in atmospheres of low CO2 concentration in recent geological time because of its ability to concentrate CO2 around Rubisco and boost water use efficiency relative to C3 photosynthesis. We assess this hypothesis by compiling estimates of when CAM clades arose using phylogenetic chronograms for 73 CAM clades. We further consider evidence of how atmospheric CO2 affects CAM relative to C3 photosynthesis. RESULTS: Where CAM origins can be inferred, strong CAM is estimated to have appeared in the past 30 million years in 46 of 48 examined clades, after atmospheric CO2 had declined from high (near 800 ppm) to lower (<450 ppm) values. In turn, 21 of 25 clades containing CAM species (but where CAM origins are less certain) also arose in the past 30 million years. In these clades, CAM is probably younger than the clade origin. We found evidence for repeated weak CAM evolution during the higher CO2 conditions before 30 million years ago, and possible strong CAM origins in the Crassulaceae during the Cretaceous period prior to atmospheric CO2 decline. Most CAM-specific clades arose in the past 15 million years, in a similar pattern observed for origins of C4 clades. CONCLUSIONS: The evidence indicates strong CAM repeatedly evolved in reduced CO2 conditions of the past 30 million years. Weaker CAM can pre-date low CO2 and, in the Crassulaceae, strong CAM may also have arisen in water-limited microsites under relatively high CO2. Experimental evidence from extant CAM species demonstrates that elevated CO2 reduces the importance of nocturnal CO2 fixation by increasing the contribution of C3 photosynthesis to daily carbon gain. Thus, the advantage of strong CAM would be reduced in high CO2, such that its evolution appears less likely and restricted to more extreme environments than possible in low CO2.
\n \n\n \n \nBACKGROUND AND SCOPE: The growth of experimental studies of crassulacean acid metabolism (CAM) in diverse plant clades, coupled with recent advances in molecular systematics, presents an opportunity to re-assess the phylogenetic distribution and diversity of species capable of CAM. It has been more than two decades since the last comprehensive lists of CAM taxa were published, and an updated survey of the occurrence and distribution of CAM taxa is needed to facilitate and guide future CAM research. We aimed to survey the phylogenetic distribution of these taxa, their diverse morphology, physiology and ecology, and the likely number of evolutionary origins of CAM based on currently known lineages. RESULTS AND CONCLUSIONS: We found direct evidence (in the form of experimental or field observations of gas exchange, day-night fluctuations in organic acids, carbon isotope ratios and enzymatic activity) for CAM in 370 genera of vascular plants, representing 38 families. Further assumptions about the frequency of CAM species in CAM clades and the distribution of CAM in the Cactaceae and Crassulaceae bring the currently estimated number of CAM-capable species to nearly 7 % of all vascular plants. The phylogenetic distribution of these taxa suggests a minimum of 66 independent origins of CAM in vascular plants, possibly with dozens more. To achieve further insight into CAM origins, there is a need for more extensive and systematic surveys of previously unstudied lineages, particularly in living material to identify low-level CAM activity, and for denser sampling to increase phylogenetic resolution in CAM-evolving clades. This should allow further progress in understanding the functional significance of this pathway by integration with studies on the evolution and genomics of CAM in its many forms.
\n \n\n \n \nGlobally, we are facing an emerging climate crisis, with impacts to be notably felt in semiarid regions across the world. Cultivation of drought-adapted succulent plants has been suggested as a nature-based solution that could: (i) reduce land degradation, (ii) increase agricultural diversification and provide both economic and environmentally sustainable income through derived bioproducts and bioenergy, (iii) help mitigate atmospheric CO2 emissions and (iv) increase soil sequestration of CO2. Identifying where succulents can grow and thrive is an important prerequisite for the advent of a sustainable alternative \u2018bioeconomy\u2019. Here, we first explore the viability of succulent cultivation in Africa under future climate projections to 2100 using species distribution modelling to identify climatic parameters of greatest importance and regions of environmental suitability. Minimum temperatures and temperature variability are shown to be key controls in defining the theoretical distribution of three succulent species explored, and under both current and future SSP5 8.5 projections, the conditions required for the growth of at least one of the species are met in most parts of sub-Saharan Africa. These results are supplemented with an analysis of potentially available land for alternative succulent crop cultivation. In total, up to 1.5 billion ha could be considered ecophysiologically suitable and available for succulent cultivation due to projected declines in rangeland biomass and yields of traditional crops. These findings may serve to highlight new opportunities for farmers, governments and key stakeholders in the agriculture and energy sectors to invest in sustainable bioeconomic alternatives that deliver on environmental, social and economic goals.
\n \n\n \n \nHealth-related behaviours have been related to brain structural features. In developing settings, such as Latin America, high social inequality has been inversely associated with several health-related behaviours affecting brain development. Understanding the relationship between health behaviours and brain structure in such settings is particularly important during adolescence when critical habits are acquired and ingrained. In this cross-sectional study, we carry out a multimodal analysis identifying a brain region associated with health-related behaviours (i.e., adiposity, fitness, sleep problems and others) and cognitive/academic performance, independent of socioeconomic status in a large sample of Chilean adolescents. Our findings suggest that the relationship between health behaviours and cognitive/academic performance involves a particular brain phenotype that could play a mediator role. These findings fill a significant gap in the literature, which has largely focused on developed countries and raise the possibility of promoting healthy behaviours in adolescence as a means to influence brain structure and thereby cognitive/academic achievement, independently of socioeconomic factors. By highlighting the potential impact on brain structure and cognitive/academic achievement, policymakers could design interventions that are more effective in reducing health disparities in developing countries.
\n \n\n \n \nOBJECTIVES: To develop a clinical prediction model to risk stratify children admitted to PICUs in locations with limited resources, and compare performance of the model to nine existing pediatric severity scores. DESIGN: Retrospective, single-center, cohort study. SETTING: PICU of a pediatric hospital in Siem Reap, northern Cambodia. PATIENTS: Children between 28 days and 16 years old admitted nonelectively to the PICU. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Clinical and laboratory data recorded at the time of PICU admission were collected. The primary outcome was death during PICU admission. One thousand five hundred fifty consecutive nonelective PICU admissions were included, of which 97 died (6.3%). Most existing severity scores achieved comparable discrimination (area under the receiver operating characteristic curves [AUCs], 0.71-0.76) but only three scores demonstrated moderate diagnostic utility for triaging admissions into high- and low-risk groups (positive likelihood ratios [PLRs], 2.65-2.97 and negative likelihood ratios [NLRs], 0.40-0.46). The newly derived model outperformed all existing severity scores (AUC, 0.84; 95% CI, 0.80-0.88; p < 0.001). Using one particular threshold, the model classified 13.0% of admissions as high risk, among which probability of mortality was almost ten-fold greater than admissions triaged as low-risk (PLR, 5.75; 95% CI, 4.57-7.23 and NLR, 0.47; 95% CI, 0.37-0.59). Decision curve analyses indicated that the model would be superior to all existing severity scores and could provide utility across the range of clinically plausible decision thresholds. CONCLUSIONS: Existing pediatric severity scores have limited potential as risk stratification tools in resource-constrained PICUs. If validated, our prediction model would be a readily implementable mechanism to support triage of critically ill children at admission to PICU and could provide value across a variety of contexts where resource prioritization is important.
\n \n\n \n \nPrevious work has shown that motor skill learning stimulates and requires generation of myelinating oligodendrocytes (OLs) from their precursor cells (OLPs) in the brains of adult mice. In the present study we ask whether OL production is also required for non-motor learning and cognition, using T-maze and radial-arm-maze tasks that tax spatial working memory. We find that maze training stimulates OLP proliferation and OL production in the medial prefrontal cortex (mPFC), anterior corpus callosum (genu), dorsal thalamus and hippocampal formation of adult male mice; myelin sheath formation is also stimulated in the genu. Genetic blockade of OL differentiation and neo-myelination in Myrf conditional-knockout mice strongly impairs training-induced improvements in maze performance. We find a strong positive correlation between the performance of individual wild type mice and the scale of OLP proliferation and OL generation during training, but not with the number or intensity of c-Fos+ neurons in their mPFC, underscoring the important role played by OL lineage cells in cognitive processing.
\n \n\n \n \nCooperative interactions between the amygdala and hippocampus are widely regarded as critical for overnight emotional processing of waking experiences, but direct support from the human brain for such a dialog is absent. Using overnight intracranial recordings in 4 presurgical epilepsy patients (3 female), we discovered ripples within human amygdala during nonrapid eye movement (NREM) sleep, a brain state known to contribute to affective processing. Like hippocampal ripples, amygdala ripples are associated with sharp waves, linked to sleep spindles, and tend to co-occur with their hippocampal counterparts. Moreover, sharp waves and ripples are temporally linked across the 2 brain structures, with amygdala ripples occurring during hippocampal sharp waves and vice versa. Combined with further evidence of interregional sharp-wave and spindle synchronization, these findings offer a potential physiological substrate for the NREM-sleep-dependent consolidation and regulation of emotional experiences.
\n \n\n \n \nAssociative memory enables the encoding and retrieval of relations between different stimuli. To better understand its neural basis, we investigated whether associative memory involves temporally correlated spiking of medial temporal lobe (MTL) neurons that exhibit stimulus-specific tuning. Using single-neuron recordings from patients with epilepsy performing an associative object-location memory task, we identified the object-specific and place-specific neurons that represented the separate elements of each memory. When patients encoded and retrieved particular memories, the relevant object-specific and place-specific neurons activated together during hippocampal ripples. This ripple-locked coactivity of stimulus-specific neurons emerged over time as the patients' associative learning progressed. Between encoding and retrieval, the ripple-locked timing of coactivity shifted, suggesting flexibility in the interaction between MTL neurons and hippocampal ripples according to behavioral demands. Our results are consistent with a cellular account of associative memory, in which hippocampal ripples coordinate the activity of specialized cellular populations to facilitate links between stimuli.
\n \n\n \n \nThe beneficial effect of sleep on memory consolidation relies on the precise interplay of slow oscillations and spindles. However, whether these rhythms are orchestrated by an underlying pacemaker has remained elusive. Here, we tested the relationship between respiration, which has been shown to impact brain rhythms and cognition during wake, sleep-related oscillations and memory reactivation in humans. We re-analysed an existing dataset, where scalp electroencephalography and respiration were recorded throughout an experiment in which participants (N\u2009=\u200920) acquired associative memories before taking a nap. Our results reveal that respiration modulates the emergence of sleep oscillations. Specifically, slow oscillations, spindles as well as their interplay (i.e., slow-oscillation_spindle complexes) systematically increase towards inhalation peaks. Moreover, the strength of respiration - slow-oscillation_spindle coupling is linked to the extent of memory reactivation (i.e., classifier evidence in favour of the previously learned stimulus category) during slow-oscillation_spindles. Our results identify a clear association between respiration and memory consolidation in humans and highlight the role of brain-body interactions during sleep.
\n \n\n \n \nStress may shift behavioural control from a goal-directed system that encodes action-outcome relationships to a habitual system that learns stimulus-response associations. Although this shift to habits is highly relevant for stress-related psychopathologies, limitations of existing behavioural paradigms hinder research from answering the fundamental question of whether the stress-induced bias to habits is due to reduced outcome processing or enhanced response processing at the time of stimulus presentation, or both. Here, we used EEG-based multivariate pattern analysis to decode neural outcome representations crucial for goal-directed control, as well as response representations during instrumental learning. We show that stress reduced outcome representations but enhanced response representations. Both were directly associated with a behavioural index of habitual responding. Furthermore, changes in outcome and response representations were uncorrelated, suggesting that these may reflect distinct processes. Our findings indicate that habitual behaviour under stress may be the result of both enhanced stimulus-response processing and diminished outcome processing.
\n \n\n \n \nR-loops are three-stranded structures that can pose threats to genome stability. RNase H1 precisely recognizes R-loops to drive their resolution within the genome, but the underlying mechanism is unclear. Here, we report that ARID1A recognizes R-loops with high affinity in an ATM-dependent manner. ARID1A recruits METTL3 and METTL14 to the R-loop, leading to the m6A methylation of R-loop RNA. This m6A modification facilitates the recruitment of RNase H1 to the R-loop, driving its resolution and promoting DNA end resection at DSBs, thereby ensuring genome stability. Depletion of ARID1A, METTL3, or METTL14 leads to R-loop accumulation and reduced cell survival upon exposure to cytotoxic agents. Therefore, ARID1A, METTL3, and METTL14 function in a coordinated, temporal order at DSB sites to recruit RNase H1 and to ensure efficient R-loop resolution. Given the association of high ARID1A levels with resistance to genotoxic therapies in patients, these findings open avenues for exploring potential therapeutic strategies for cancers with ARID1A abnormalities.
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