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Abstract We consider two related tasks: (a) estimating a parameterisation of a given Gibbs state and expectation values of Lipschitz observables on this state; (b) learning the expectation values of local observables within a thermal or quantum phase of matter. In both cases, we present sample-efficient ways to learn these properties to high precision. For the first task, we develop techniques to learn parameterisations of classes of systems, including quantum Gibbs states for classes of non-commuting Hamiltonians. We then give methods to sample-efficiently infer expectation values of extensive properties of the state, including quasi-local observables and entropies. For the second task, we exploit the locality of Hamiltonians to show that M local observables can be learned with probability 1 − δ and precision ε using $$N={\mathcal{O}}\left(\log \left(\frac{M}{\delta }\right){e}^{{\rm{polylog}}({\varepsilon }^{-1})}\right)$$ N = O log M δ e polylog ( ε − 1 ) samples — exponentially improving previous bounds. Our results apply to both families of ground states of Hamiltonians displaying local topological quantum order, and thermal phases of matter with exponentially decaying correlations.

Abstract Background Non-specific low back pain is a common and costly global issue. Many people with low back pain live for years with ongoing symptom recurrence and disability, making it crucial to find effective prevention strategies. Motivational interviewing (MI) is an evidence-based patient-centred counselling style that helps motivate individuals to change their behaviours. In combination, MI and cognitive-behavioural therapy (MI-CBT) has the potential to yield long term improvements in pain and disability and reduce incidence of recurrence. Method This is a two-arm superiority randomised controlled trial comparing MI-CBT and Education (n = 83) with Education only (n = 83). Participants that have recovered from a recent episode of non-specific low back pain (7th consecutive day with pain ≤ 2 on a 0–10 numeric pain rating scale) will be eligible for inclusion into the study. Both groups will receive five 30-min sessions over a 10-week period as well as the Navigating Pain booklet, homework book and a standardised exercise programme. In the intervention group, MI-CBT techniques will be used to provide individualised support, identify beliefs, and increase engagement with the resources provided. Outcomes measures include pain (current and in the last 7 days) as rated on the numeric pain rating scale. This will be used to determine recurrence (number of participants who report back pain ≥ 3 out of 10 on the numeric pain rating scale). Furthermore, self-reported (1) pain intensity; (2) pain catastrophizing; (3) fear-avoidance beliefs; (4) pain self-efficacy; (5) depression and anxiety; (6) disability will be measured. All outcomes will be measured at baseline, and again at 3-, 6-, and 12-months post allocation. Discussion The effective delivery of self-management strategies to prevent recurrence of low back pain is an important aspect that requires urgent attention. This study will provide new information on the effectiveness of using an MI-CBT approach to facilitate self-management through education and exercise to improve low back pain outcomes. Evidence emerging from this trial has the potential to inform clinical practice and healthcare management of non-specific low back pain. Trial registration Prospectively registered with Australian New Zealand Clinical Trials Registry: ACTRN12623000746639 (10/07/2023).

Abstract We present the evolution of the electronic structure of CrSBr from its antiferromagnetic ground state to the paramagnetic phase above T N = 132 K, in both experiment and theory. Low-temperature angle-resolved photoemission spectroscopy (ARPES) results are obtained using a novel method to overcome sample charging issues, revealing quasi-2D valence bands in the ground state. The results are very well reproduced by our $${\rm{QSG}}\hat{{\rm{W}}}$$ QSG W ̂ calculations, which further identify certain bands at the X points to be exchange-split pairs of states with mainly Br and S character. By tracing band positions as a function of temperature, we show the splitting disappears above T N . The energy splitting is interpreted as an effective exchange splitting in individual layers in which the Cr moments all align, within the so-called A-type antiferromagnetic arrangement. Our results lay firm foundations for the interpretation of the many other intriguing physical and optical properties of CrSBr.

Abstract Background In 2020, a novel neurologic disease was observed in juvenile Quarter Horses (QHs) in North America. It was unknown if this was an aberrant manifestation of another previously described neurological disorder in foals, such as equine neuroaxonal dystrophy/equine degenerative myeloencephalopathy (eNAD/EDM). Hypothesis/Objectives To describe the clinical findings, outcomes, and postmortem changes with Equine Juvenile Spinocerebellar Ataxia (EJSCA), differentiate the disease from other similar neurological disorders, and determine a mode of inheritance. Animals Twelve neurologically affected QH foals and the dams. Methods Genomic DNA was isolated and pedigrees were manually constructed. Results All foals (n = 12/12) had a history of acute onset of neurological deficits with no history of trauma. Neurological deficits were characterized by asymmetrical spinal ataxia, with pelvic limbs more severely affected than thoracic limbs. Clinicopathological abnormalities included high serum activity of gamma‐glutamyl transferase and hyperglycemia. All foals became recumbent (median, 3 days: [0–18 days]), which necessitated humane euthanasia (n = 11/12, 92%; the remaining case was found dead). Histological evaluation at postmortem revealed dilated myelin sheaths and digestion chambers within the spinal cord, most prominently in the dorsal spinocerebellar tracts. Pedigree analysis revealed a likely autosomal recessive mode of inheritance. Conclusions and Clinical Importance EJSCA is a uniformly fatal, rapidly progressive, likely autosomal recessive neurological disease of QHs

Abstract Spin-orbit coupling in noncentrosymmetric crystals leads to spin-momentum locking – a directional relationship between an electron’s spin angular momentum and its linear momentum. Isotropic orthogonal Rashba spin-momentum locking has been studied for decades, while its counterpart, isotropic parallel Weyl spin-momentum locking has remained elusive in experiments. Theory predicts that Weyl spin-momentum locking can only be realized in structurally chiral cubic crystals in the vicinity of Kramers-Weyl or multifold fermions. Here, we use spin- and angle-resolved photoemission spectroscopy to evidence Weyl spin-momentum locking of multifold fermions in the chiral topological semimetal PtGa. We find that the electron spin of the Fermi arc surface states is orthogonal to their Fermi surface contour for momenta close to the projection of the bulk multifold fermion at the Γ point, which is consistent with Weyl spin-momentum locking of the latter. The direct measurement of the bulk spin texture of the multifold fermion at the R point also displays Weyl spin-momentum locking. The discovery of Weyl spin-momentum locking may lead to energy-efficient memory devices and Josephson diodes based on chiral topological semimetals.

Abstract Background Placental management strategies such as umbilical cord milking and delayed cord clamping may provide a range of benefits for the newborn. The aim of this review was to assess the effectiveness of umbilical cord milking and delayed cord clamping for the prevention of neonatal hypoglycaemia. Methods Three databases and five clinical trial registries were systematically reviewed to identify randomised controlled trials comparing umbilical cord milking or delayed cord clamping with control in term and preterm infants. The primary outcome was neonatal hypoglycaemia (study defined). Two independent reviewers conducted screening, data extraction and quality assessment. Quality of the included studies was assessed using the Cochrane Risk of Bias tool (RoB-2). Certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. Meta-analysis using a random effect model was done using Review Manager 5.4. The review was registered prospectively on PROSPERO (CRD42022356553). Results Data from 71 studies and 14 268 infants were included in this review; 22 (2 537 infants) compared umbilical cord milking with control, and 50 studies (11 731 infants) compared delayed with early cord clamping. For umbilical cord milking there were no data on neonatal hypoglycaemia, and no differences between groups for any of the secondary outcomes. We found no evidence that delayed cord clamping reduced the incidence of hypoglycaemia (6 studies, 444 infants, RR = 0.87, CI: 0.58 to 1.30, p = 0.49, I2 = 0%). Delayed cord clamping was associated with a 27% reduction in neonatal mortality (15 studies, 3 041 infants, RR = 0.73, CI: 0.55 to 0.98, p = 0.03, I2 = 0%). We found no evidence for the effect of delayed cord clamping for any of the other outcomes. The certainty of evidence was low for all outcomes. Conclusion We found no data for the effectiveness of umbilical cord milking on neonatal hypoglycaemia, and no evidence that delayed cord clamping reduced the incidence of hypoglycaemia, but the certainty of the evidence was low.

Abstract Ships brighten low marine clouds from emissions of sulfur and aerosols, resulting in visible “ship tracks”. In 2020, new shipping regulations mandated an ∼80% reduction in the allowed fuel sulfur content. Recent observations indicate that visible ship tracks have decreased. Model simulations indicate that since 2020 shipping regulations have induced a net radiative forcing of +0.12 Wm−2. Analysis of recent temperature anomalies indicates Northern Hemisphere surface temperature anomalies in 2022–2023 are correlated with observed cloud radiative forcing and the cloud radiative forcing is spatially correlated with the simulated radiative forcing from the 2020 shipping emission changes. Shipping emissions changes could be accelerating global warming. To better constrain these estimates, better access to ship position data and understanding of ship aerosol emissions are needed. Understanding the risks and benefits of emissions reductions and the difficultly in robust attribution highlights the large uncertainty in attributing proposed deliberate climate intervention.

The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood, and uncertainty in climate model results persists, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. We synthesize current challenges and emphasize opportunities for advancing our understanding of the interactions between atmospheric composition, air quality, and climate change, as well as for quantifying model diversity. Our perspective is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specializations across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation–response paradigm through multi-model ensembles of Earth system models of varying complexity. We discuss the challenges of gaining insights from Earth system models that face computational and process representation limits and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible and machine learning approaches where they are needed, e.g., for faster and better subgrid-scale parameterizations and pattern recognition in big data. New model constraints can arise from augmented observational products that leverage multiple datasets with machine learning approaches. Future MIPs can develop smart experiment protocols that strive towards an optimal trade-off between the resolution, complexity, and number of simulations and their length and, thereby, help to advance the understanding of climate change and its impacts.

For over 6 months, the 2014–2015 effusive eruption at Holuhraun, Iceland, injected considerable amounts of sulfur dioxide (SO2) into the lower troposphere with a daily rate of up to one-third of the global emission rate, causing extensive air pollution across Europe. The large injection of SO2, which oxidises to form sulfate aerosol (SO42-), provides a natural experiment offering an ideal opportunity to scrutinise state-of-the-art general circulation models' (GCMs) representation of aerosol–cloud interactions (ACIs). Here we present Part 1 of a two-part model inter-comparison using the Holuhraun eruption as a framework to analyse ACIs. We use SO2 retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) instrument and ground-based measurements of SO2 and SO42- mass concentrations across Europe, in conjunction with a trajectory analysis using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, to assess the spatial and chemical evolution of the volcanic plume as simulated by five GCMs and a chemical transport model (CTM). IASI retrievals of plume altitude and SO2 column load reveal that the volcanic perturbation is largely contained within the lower troposphere. Compared to the satellite observations, the models capture the spatial evolution and vertical variability of the plume reasonably well, although the models often overestimate the plume altitude. HYSPLIT trajectories are used to attribute to Holuhraun emissions 111 instances of elevated sulfurous surface mass concentrations recorded at European Monitoring and Evaluation Programme (EMEP) stations during September and October 2014. Comparisons with the simulated concentrations show that the modelled ratio of SO2 to SO42- during these pollution episodes is often underestimated and overestimated for the young and mature plume, respectively. Models with finer vertical resolutions near the surface are found to better capture these elevated sulfurous ground-level concentrations. Using an exponential function to describe the decay of observed surface mass concentration ratios of SO2 to SO42- with plume age, the in-plume oxidation rate constant is estimated as 0.032 ± 0.002 h−1 (1.30 ± 0.08 d e-folding time), with a near-vent ratio of 25 ± 5 (µg m−3 of SO2 / µg m−3 of SO42-). The majority of the corresponding derived modelled oxidation rate constants are lower than the observed estimate. This suggests that the representation of the oxidation pathway/s in the simulated plumes is too slow. Overall, despite their coarse spatial resolutions, the six models show reasonable skill in capturing the spatial and chemical evolution of the Holuhraun plume. This capable representation of the underlying aerosol perturbation is essential to enable the investigation of the eruption's impact on ACIs in the second part of this study.

Abstract In continuation of research into RuCl3 and RuBr3 as potential quantum spin liquids, a phase with unique magnetic order characterised by long-range quantum entanglement and fractionalised excitations, the compound RuI3 has been recently synthesised. Here, we show RuI3 is a moderately correlated metal with two bands crossing the Fermi level, implying the absence of any quantum spin liquids phase. We find that the Fermi surface as measured or calculated for a 2D (k x, k y) slice at any k z lacks mirror symmetry, i.e. is pseudochiral. We link this phenomenon to the ABC stacking in the R $$\bar{3}$$ 3 ¯ space group of α-RuI3, which is achiral but lacks any mirror or glide symmetries. We further provide a formal framework for understanding when such a pseudochiral electronic structure may be observed.

Background: Secondary mitral regurgitation (MR) is common in heart failure with reduced ejection fraction (HFrEF) and is associated with poor outcomes. However, there is little evidence regarding secondary MR in advanced HFrEF. Poor outcomes for MR intervention suggest a need for further risk stratification. Methods: Patients were assessed with echocardiography, right heart catheterization (RHC), and cardiopulmonary exercise testing. Ventricular-secondary MR was identified by echocardiography and categorized as mild, moderate, or severe according to guidelines. RV ability to compensate for pulmonary pressure rise was assessed by RV-pulmonary artery (PA) coupling, calculated as ratio of tricuspid annular plane systolic excursion (TAPSE), and systolic pulmonary artery pressure (SPAP) (echocardiography for TAPSE and RHC for SPAP). Primary end-point was a composite of all-cause mortality, urgent heart transplantation, or mechanical circulatory support. Results: Four hundred and fifty-six patients with ventricular-secondary MR were followed up for a median of 2.39 years, with 237 reaching a primary end-point. Severe MR conferred a worse prognosis than mild or moderate ((hazard ratio) HR 2.6, p

Abstract Iron-chalcogenide superconductors display rich phenomena caused by orbital-dependent band shifts and electronic correlations. Additionally, they are potential candidates for topological superconductivity due to the band inversion between the Fe d bands and the chalcogen p z band. Here we present a detailed study of the electronic structure of the nematic superconductors FeSe1−x Te x (0

Abstract Background Plasmodium vivax has been more resistant to various control measures than Plasmodium falciparum malaria because of its greater transmissibility and ability to produce latent parasite forms. Therefore, developing P. vivax vaccines and therapeutic monoclonal antibodies (humAbs) remains a high priority. The Duffy antigen receptor for chemokines (DARC) expressed on erythrocytes is central to P. vivax invasion of reticulocytes. P. vivax expresses a Duffy binding protein (PvDBP) on merozoites, a DARC ligand, and the DARC: PvDBP interaction is critical for P. vivax blood stage malaria. Therefore, PvDBP is a leading vaccine candidate for P. vivax and a target for therapeutic human monoclonal antibodies (humAbs). Methods Here, the functional activity of humAbs derived from naturally exposed and vaccinated individuals are compared for the first time using easily cultured Plasmodium knowlesi (P. knowlesi) that had been genetically modified to replace its endogenous PkDBP orthologue with PvDBP to create a transgenic parasite, PkPvDBPOR. This transgenic parasite requires DARC to invade human erythrocytes but is not reticulocyte restricted. This model was used to evaluate the invasion inhibition potential of 12 humAbs (9 naturally acquired; 3 vaccine-induced) targeting PvDBP individually and in combinations using growth inhibition assays (GIAs). Results The PvDBP-specific humAbs demonstrated 70–100% inhibition of PkPvDBPOR invasion with the IC50 values ranging from 51 to 338 µg/mL for the 9 naturally acquired (NA) humAbs and 33 to 99 µg/ml for the 3 vaccine-induced (VI) humAbs. To evaluate antagonistic, additive, or synergistic effects, six pairwise combinations were performed using select humAbs. Of these combinations tested, one NA/NA (099100/094083) combination demonstrated relatively strong additive inhibition between 10 and 100 µg/mL; all combinations of NA and VI humAbs showed additive inhibition at concentrations below 25 µg/mL and antagonism at higher concentrations. None of the humAb combinations showed synergy. Invasion inhibition efficacy by some mAbs shown with PkPvDBPOR was closely replicated using P. vivax clinical isolates. Conclusion The PkPvDBPOR transgenic model is a robust surrogate of P. vivax to assess invasion and growth inhibition of human monoclonal Abs recognizing PvDBP individually and in combination. There was no synergistic interaction for growth inhibition with the humAbs tested here that target different epitopes or subdomains of PvDBP, suggesting little benefit in clinical trials using combinations of these humAbs.

Salmonella infection causes epidemic death in wild songbirds, with potential to spread to humans. In February 2021, public health officials in Oregon and Washington, USA, isolated a strain of Salmonella enterica serovar Typhimurium from humans and a wild songbird. Investigation by public health partners ultimately identified 30 illnesses in 12 states linked to an epidemic of Salmonella Typhimurium in songbirds. We report a multistate outbreak of human salmonellosis associated with songbirds, resulting from direct handling of sick and dead birds or indirect contact with contaminated birdfeeders. Companion animals might have contributed to the spread of Salmonella between songbirds and patients; the outbreak strain was detected in 1 ill dog, and a cat became ill after contact with a wild bird. This outbreak highlights a One Health issue where actions like regular cleaning of birdfeeders might reduce the health risk to wildlife, companion animals, and humans.

Abstract In half-metallic systems, electronic conduction is mediated by a single spin species, offering enormous potential for spintronic devices. Here, using microscopic-area angle-resolved photoemission, we show that a spin-polarised two-dimensional hole gas is naturally realised in the polar magnetic semiconductor AgCrSe2 by an intrinsic self-doping at its CrSe2-terminated surface. Through comparison with first-principles calculations, we unveil a striking role of spin-orbit coupling for the surface hole gas, unlocked by both bulk and surface inversion symmetry breaking, suggesting routes for stabilising complex magnetic textures in the surface layer of AgCrSe2.

Human aerosol emissions change cloud properties by providing additional cloud condensation nuclei. This increases cloud droplet numbers, which in turn affects other cloud properties like liquid-water content and ultimately cloud albedo. These adjustments are poorly constrained, making aerosol effects the most uncertain part of anthropogenic climate forcing. Here we show that cloud droplet number and water content react differently to changing emission amounts in shipping exhausts. We use information about ship positions and modeled emission amounts together with reanalysis winds and satellite retrievals of cloud properties. The analysis reveals that cloud droplet numbers respond linearly to emission amount over a large range (1–10 kg h−1) before the response saturates. Liquid water increases in raining clouds, and the anomalies are constant over the emission ranges observed. There is evidence that this independence of emissions is due to compensating effects under drier and more humid conditions, consistent with suppression of rain by enhanced aerosol. This has implications for our understanding of cloud processes and may improve the way clouds are represented in climate models, in particular by changing parameterizations of liquid-water responses to aerosol.

Background: Esophageal cancer [esophagogastric adenocarcinoma (OGA)] shows heterogeneity at the molecular level, leading to lower efficacy rates and highlighting the need for personalized treatment strategies. We have developed a computational model that uses both mechanistic and statistical approaches to integrate a patient’s genomic aberrations, revealing signaling pathway dysregulation and variable drug response. The model output, Therapy Response Index (TRI), has been used to predict therapeutic outcomes in this study. Design: TRI’s ability to predict patient outcomes was retrospectively evaluated in a prospectively collected cohort of patients with operable OGA from the UK Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) consortium receiving neoadjuvant chemotherapy. Stratified random sampling was used to split the data into training and validation subsets. Multivariate Cox proportional hazard and proportional odds models were used to predict survival and pathological response as a function of TRI and clinical thresholds compared with clinical factors. Results: A total of 270 patients with OGA were selected who had 50× whole genome sequencing carried out on tissue derived from either biopsy or resection. Patients were treated with chemotherapy drugs or regimens according to UK clinical guidelines. The association of TRI with overall survival (OS) was significant above and beyond standard clinical factors (P = 0.0012). A significant association was also observed with disease-free survival (DFS; P = 0.0288). A TRI optimized for tumor regression grade also displayed a significant association (P = 0.0011). Conclusions: TRI was predictive of OS and DFS beyond clinical factors. These positive results suggest the potential utility of personalized biosimulation-informed therapy selection and that further assessment in prospective clinical studies is warranted.

Summary: Anaplastic thyroid carcinoma is arguably the most lethal human malignancy. It often co-occurs with differentiated thyroid cancers, yet the molecular origins of its aggressivity are unknown. We sequenced tumor DNA from 329 regions of thyroid cancer, including 213 from patients with primary anaplastic thyroid carcinomas. We also whole genome sequenced 9 patients using multi-region sequencing of both differentiated and anaplastic thyroid cancer components. Using these data, we demonstrate thatanaplastic thyroid carcinomas have a higher burden of mutations than other thyroid cancers, with distinct mutational signatures and molecular subtypes. Further, different cancer driver genes are mutated in anaplastic and differentiated thyroid carcinomas, even those arising in a single patient. Finally, we unambiguously demonstrate that anaplastic thyroid carcinomas share a genomic origin with co-occurring differentiated carcinomas and emerge from a common malignant field through acquisition of characteristic clonal driver mutations.

Aerosol radiative forcing uncertainty affects estimates of climate sensitivity and limits model skill in terms of making climate projections. Efforts to improve the representations of physical processes in climate models, including extensive comparisons with observations, have not significantly constrained the range of possible aerosol forcing values. A far stronger constraint, in particular for the lower (most-negative) bound, can be achieved using global mean energy balance arguments based on observed changes in historical temperature. Here, we show that structural deficiencies in a climate model, revealed as inconsistencies among observationally constrained cloud properties in the model, limit the effectiveness of observational constraint of the uncertain physical processes. We sample the uncertainty in 37 model parameters related to aerosols, clouds, and radiation in a perturbed parameter ensemble of the UK Earth System Model and evaluate 1 million model variants (different parameter settings from Gaussian process emulators) against satellite-derived observations over several cloudy regions. Our analysis of a very large set of model variants exposes model internal inconsistencies that would not be apparent in a small set of model simulations, of an order that may be evaluated during model-tuning efforts. Incorporating observations associated with these inconsistencies weakens any forcing constraint because they require a wider range of parameter values to accommodate conflicting information. We show that, by neglecting variables associated with these inconsistencies, it is possible to reduce the parametric uncertainty in global mean aerosol forcing by more than 50 %, constraining it to a range (around −1.3 to −0.1 W m−2) in close agreement with energy balance constraints. Our estimated aerosol forcing range is the maximum feasible constraint using our structurally imperfect model and the chosen observations. Structural model developments targeted at the identified inconsistencies would enable a larger set of observations to be used for constraint, which would then very likely narrow the uncertainty further and possibly alter the central estimate. Such an approach provides a rigorous pathway to improved model realism and reduced uncertainty that has so far not been achieved through the normal model development approach.

Abstract The currently established electronic phase diagram of cuprates is based on a study of single- and double-layered compounds. These CuO2 planes, however, are directly contacted with dopant layers, thus inevitably disordered with an inhomogeneous electronic state. Here, we solve this issue by investigating a 6-layered Ba2Ca5Cu6O12(F,O)2 with inner CuO2 layers, which are clean with the extremely low disorder, by angle-resolved photoemission spectroscopy (ARPES) and quantum oscillation measurements. We find a tiny Fermi pocket with a doping level less than 1% to exhibit well-defined quasiparticle peaks which surprisingly lack the polaronic feature. This provides the first evidence that the slightest amount of carriers is enough to turn a Mott insulating state into a metallic state with long-lived quasiparticles. By tuning hole carriers, we also find an unexpected phase transition from the superconducting to metallic states at 4%. Our results are distinct from the nodal liquid state with polaronic features proposed as an anomaly of the heavily underdoped cuprates.

Abstract Charge Density Waves (CDW) are commonly associated with the presence of near-Fermi level states which are separated from others, or “nested", by a wavector of q. Here we use Angle-Resolved Photo Emission Spectroscopy (ARPES) on the CDW material Ta2NiSe7 and identify a total absence of any plausible nesting of states at the primary CDW wavevector q. Nevertheless we observe spectral intensity on replicas of the hole-like valence bands, shifted by a wavevector of q, which appears with the CDW transition. In contrast, we find that there is a possible nesting at 2q, and associate the characters of these bands with the reported atomic modulations at 2q. Our comprehensive electronic structure perspective shows that the CDW-like transition of Ta2NiSe7 is unique, with the primary wavevector q being unrelated to any low-energy states, but suggests that the reported modulation at 2q, which would plausibly connect low-energy states, might be more important for the overall energetics of the problem.

Abstract Epidemiologic data suggest that the prevalence of hypertension in patients with diabetes mellitus is ∼1.5–2.0 times greater than in matched non-diabetic patients. This co-existent disease burden exacerbates cardiac and vascular injury, leading to structural and functional changes to the myocardium, impaired cardiac function and heart failure. Oxidative stress and persistent low-grade inflammation underlie both conditions, and are identified as major contributors to pathological cardiac remodelling. There is an urgent need for effective therapies that specifically target oxidative stress and inflammation to protect against cardiac remodelling. Animal models are a valuable tool for testing emerging therapeutics, however, there is a notable lack of appropriate animal models of co-morbid diabetes and hypertension. In this study, we describe a novel preclinical mouse model combining diabetes and hypertension to investigate cardiac and vascular pathology of co-morbid disease. Type 1 diabetes was induced in spontaneously hypertensive, 8-week old, male Schlager (BPH/2) mice via 5 consecutive, daily injections of streptozotocin (55 mg/kg in citrate buffer; i.p.). Non-diabetic mice received citrate buffer only. After 10 weeks of diabetes induction, cardiac function was assessed by echocardiography prior to post-mortem evaluation of cardiomyocyte hypertrophy, interstitial fibrosis and inflammation by histology, RT-PCR and flow cytometry. We focussed on the oxidative and inflammatory stress pathways that contribute to cardiovascular remodelling. In particular, we demonstrate that markers of inflammation (monocyte chemoattractant protein; MCP-1), oxidative stress (urinary 8-isoprostanes) and fibrosis (connective tissue growth factor; CTGF) are significantly increased, whilst diastolic dysfunction, as indicated by prolonged isovolumic relaxation time (IVRT), is elevated in this diabetic and hypertensive mouse model. In summary, this pre-clinical mouse model provides researchers with a tool to test therapeutic strategies unique to co-morbid diabetes and hypertension, thereby facilitating the emergence of novel therapeutics to combat the cardiovascular consequences of these debilitating co-morbidities.

Asset-based Community Development (ABCD) approaches in higher education have the potential to benefit a diversity of higher education settings and partners, but they can also present challenges and opportunities for growth in higher education institutions. Co- curricular community engagement and academic service-learning programs may struggle to balance the broader political and logistical constraints imposed by the university with equitable, long-term, community-guided relationships that reflect a genuine commitment to ABCD. Extension programs may face difficulty engaging community members and maintaining their commitment to the long-term nature of ABCD in an environment where ABCD is not universally utilised. Although these challenges may seem daunting, partners in all three contexts can draw on a wealth of ABCD tools and resources, including case studies like those anchoring this discussion, in order to answer the question: How can ABCD approaches be utilised most effectively in higher education contexts to address challenges and improve outcomes? Specifically, can an asset-based orientation help position community participants as peer ‘experts’ alongside their academic partners, share power and authority in the collaboration? If so, how? If not, why not? The authors explore these questions using a case study methodology, allowing for nuanced portraits of three different contexts depicting interactions among community and university partners seeking to ground their collaborations in the mobilisation of assets, gifts and strengths. This article also seeks to identify key lessons learned in each setting of the three participating United States universities – the public, four-year research institution, the private religious university and the land-grant college/cooperative extension in order to make recommendations on using ABCD to build and nurture academic-community partnerships that are generalisable across other contexts.

The study’s aim was to examine alcohol consumption patterns and predictors of consumption across time among Hispanics with traumatic brain injury (TBI) in the U.S. within ten years post-injury. This longitudinal cohort study included 1342 Hispanic individuals (77.6% males) from the multi-site, longitudinal TBI Model Systems (TBIMS) database. The main outcome measures were consumption information, demographic, and injury characteristics. Across the full sample, alcohol consumption variables generally demonstrated quadratic movement characterized by an initial increase followed by a plateau or slight decrease over the ten years post-injury. The predictors of higher consumption were being men, single, with a history of excessive alcohol use, with a nonviolent mechanism of injury, shorter duration of PTA, and higher levels of education. Participants had a greater number of 5+ drinks/episode occurrences in the past month if they were men and had had a greater number of 5+ drinks/episode occurrences in the month before injury. There was no differential change in alcohol consumption over time as a function of these predictors. This study identified a profile of at-risk Hispanics with TBI for increased alcohol consumption. These individuals should be identified and targeted for early evidence-based alcohol intervention after TBI when results might be most favorable.

Renormalisation group methods serve for finding analytic solutions, critical points and computing phase diagrams of many-body systems. Here the authors demonstrate that renormalisation group schemes can be constructed for undecidable many-body systems, giving rise to the types of renormalisation group flow which are strictly more unpredictable than chaotic flows.

Abstract Reducing the thickness of a material to its two-dimensional (2D) limit can have dramatic consequences for its collective electronic states, including magnetism, superconductivity, and charge and spin ordering. An extreme case is TiTe2, where a charge density wave (CDW) emerges in the single-layer, which is absent for the bulk compound, and whose origin is still poorly understood. Here, we investigate the electronic band structure evolution across this CDW transition using temperature-dependent angle-resolved photoemission spectroscopy. Our study reveals an orbital-selective band hybridisation between the backfolded conduction and valence bands occurring at the CDW phase transition, which in turn leads to a significant electronic energy gain, underpinning the CDW transition. For the bulk compound, we show how this energy gain is almost completely suppressed due to the three-dimensionality of the electronic band structure, including via a k z -dependent band inversion which switches the orbital character of the valence states. Our study thus sheds new light on how control of the electronic dimensionality can be used to trigger the emergence of new collective states in 2D materials.

The semi-permanent stratocumulus clouds over the south-eastern Atlantic Ocean (SEA) can act as an “air conditioner” to the regional and global climate system. The interaction of aerosols and clouds becomes important in this region and can lead to negative radiative effects, partially offsetting the positive radiative forcing of greenhouse gases. A key pathway by which aerosols affect cloud properties is by acting as cloud condensation nuclei (CCN). In this paper, we use the United Kingdom Earth System Model (UKESM1) to investigate the sources of CCN (from emissions and atmospheric processes) in the SEA as well as the response of the cloud droplet number concentration (CDNC), the cloud liquid water path (LWP), and radiative forcing to these sources during 2016 and 2017. Overall, free and upper troposphere nucleated aerosols are the dominant source of the boundary layer CCN concentration at 0.2 % supersaturation (CCN0.2 %), contributing an annual average of ∼ 41 % as they subside and entrain into the marine boundary layer, which is consistent with observations highlighting the important role of nucleation in the boundary layer CCN concentration. In terms of emission sources, anthropogenic emissions (from energy, industry, agriculture, etc.) contribute the most to the annual average CCN0.2 % in the marine boundary layer (∼ 26 %), followed by biomass burning (BB, ∼ 17 %). In the cloud layer, BB contributes about 34 % of the annual CCN0.2 %, midway between the contributions from aerosol nucleation (36 %) and anthropogenic sources (31 %). The contribution of aerosols from different sources to the CDNC is consistent with their contribution to CCN0.2 % within the marine boundary layer, with free and upper troposphere aerosol nucleation being the most important source of the CDNC overall. In terms of emission sources, anthropogenic sources are also the largest contributors to the annual average CDNC, closely followed by BB. However, during the BB season, BB and free and upper troposphere aerosol nucleation are equally the most important sources of the CDNC. The contribution of BB to the CDNC is more significant than its increase to CCN0.2 %, mainly because BB aerosols are mostly located directly above the inversion layer in the model; thus, they can increase the in-cloud CDNC by enhancing the supersaturation through the dynamical feedback due to short-wave absorption. An aerosol source that shows an increase in the CDNC also shows an increase in the LWP resulting from a reduction in autoconversion. Due to the absorption effect, BB aerosol can enhance existing temperature inversions and reduce the entrainment of sub-saturated air, leading to a further increase in the LWP. As a result, the contribution of BB to the LWP is second only to aerosol nucleation on annual averages. These findings demonstrate that BB is not the dominant source of CCN within the marine boundary layer from an emission source perspective. However, as most BB aerosols are located directly above the inversion layer, their effect on clouds increases due to their absorption effect (about the same as anthropogenic sources for the CDNC and more than anthropogenic sources for the LWP), highlighting the crucial role of their radiative effect on clouds. The results on the radiative effects of aerosols show that BB aerosol exhibits an overall positive RFari (radiative forcing associated with aerosol–radiation interactions), but its net effective radiative forcing remains negative due to its effect on clouds (mainly due to its absorbing effect). By quantifying aerosol and cloud properties affected by different sources, this paper provides a framework for understanding the effects of aerosol sources on marine stratocumulus clouds and radiation in the SEA.

Abstract Atherosclerosis and its complications are major causes of cardiovascular morbidity and death. Apart from risk factors such as hypercholesterolemia and inflammation, the causal molecular mechanisms are unknown. One proposed causal mechanism involves elevated levels of reactive oxygen species (ROS). Indeed, early expression of the ROS forming NADPH oxidase type 5 (Nox5) in vascular endothelial cells correlates with atherosclerosis and aortic aneurysm. Here we test the pro-atherogenic Nox5 hypothesis using mouse models. Because Nox5 is missing from the mouse genome, a knock-in mouse model expressing human Nox5 in its physiological location of endothelial cells (eNOX5ki/ki) was tested as a possible new humanised mouse atherosclerosis model. However, whether just on a high cholesterol diet or by crossing in aortic atherosclerosis-prone ApoE −/− mice with and without induction of diabetes, Nox5 neither induced on its own nor aggravated aortic atherosclerosis. Surprisingly, however, diabetic ApoE−/− x eNOX5ki/ki mice developed aortic aneurysms more than twice as often correlating with lower vascular collagens, as assessed by trichrome staining, without changes in inflammatory gene expression, suggesting that endothelial Nox5 directly affects extracellular matrix remodelling associated with aneurysm formation in diabetes. Thus Nox5-derived reactive oxygen species are not a new independent mechanism of atherosclerosis but may enhance the frequency of abdominal aortic aneurysms in the context of diabetes. Together with similar clinical findings, our preclinical target validation opens up a first-in-class mechanism-based approach to treat or even prevent abdominal aortic aneurysms.

One-carbon metabolism, including the folate cycle, has a crucial role in fetal development though its molecular function is complex and unclear. The hypomorphic Mtrrgt allele is known to disrupt one-carbon metabolism, and thus methyl group availability, leading to several developmental phenotypes (e.g., neural tube closure defects, fetal growth anomalies). Remarkably, previous studies showed that some of the phenotypes were transgenerationally inherited. Here, we explored the genome-wide epigenetic impact of one-carbon metabolism in placentas associated with fetal growth phenotypes and determined whether specific DNA methylation changes were inherited. Firstly, methylome analysis of Mtrrgt/gt homozygous placentas revealed genome-wide epigenetic instability. Several differentially methylated regions (DMRs) were identified including at the Cxcl1 gene promoter and at the En2 gene locus, which may have phenotypic implications. Importantly, we discovered hypomethylation and ectopic expression of a subset of ERV elements throughout the genome of Mtrrgt/gt placentas with broad implications for genomic stability. Next, we determined that known spermatozoan DMRs in Mtrrgt/gt males were reprogrammed in the placenta with little evidence of direct or transgenerational germline DMR inheritance. However, some spermatozoan DMRs were associated with placental gene misexpression despite normalisation of DNA methylation, suggesting the inheritance of an alternative epigenetic mechanism. Integration of published wildtype histone ChIP-seq datasets with Mtrrgt/gt spermatozoan methylome and placental transcriptome datasets point towards H3K4me3 deposition at key loci. These data suggest that histone modifications might play a role in epigenetic inheritance in this context. Overall, this study sheds light on the mechanistic complexities of one-carbon metabolism in development and epigenetic inheritance.

Abstract Chalcogen and tetrel intermolecular bonding interactions formed between carbonyl sulfide and halide anions have been studied utilizing a combined experimental and theoretical approach. In particular, high‐level CCSD(T) energetics and experimental anion photoelectron spectroscopy have been used in order to assign the dominant binding motif exhibited in these complexes. Halide anions solvated by multiple carbonyl sulfide molecules have also been investigated in order to ascertain the effect that additional binding partners has on the strength of the noncovalent interactions. The experimental and computational results support the main binding motif of carbonyl sulfide molecules with halide anions being chalcogen bonding, both in dimer complexes and larger solvated complexes. In addition, comparison between the noncovalent interactions formed by halides with carbon disulfide, carbonyl sulfide, and carbon dioxide allows a deeper understanding of noncovalent binding strength in relation to isoelectronic species. Key points Spectroscopic and ab initio characterization of halide–carbonyl sulfide van der Waals complexes bound through chalcogen and tetrel bonding. Detailed insight into chalcogen and tetrel bond strength in the context of changing chemical environments. Effect of increasing solvation on noncovalent binding strength.

While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios. In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008–2009 and 2014–2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, O3, BC, and SO42-), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs. Of the SLCFs in our study, model biases were smallest for CH4 and greatest for OA. For most SLCFs, model biases skewed from positive to negative with increasing latitude. Our analysis suggests that vertical mixing, long-range transport, deposition, and wildfires remain highly uncertain processes. These processes need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment. As model development proceeds in these areas, we highly recommend that the vertical and 3-D distribution of SLCFs be evaluated, as that information is critical to improving the uncertain processes in models.

IntroductionThis study aimed to determine whether the COVID-19 pandemic had an impact on essential primary healthcare services at public primary healthcare facilities.MethodsThe number of weekly consultations for antenatal care (ANC), outpatient (OPD), immunisations (EPI), family planning (FP) and HIV services, between January 2018 and December 2020, were collected from 25 facilities in Masaka district, Uganda, 21 in Goma, and 29 in Kambia district, Sierra Leone. Negative binomial regression models accounting for clustering and season were used to analyse changes in activity levels between 2018, 2019 and 2020.ResultsIn Goma, we found no change in OPD, EPI or ANC consultations, FP was 17% lower in March-July 2020 compared to 2019, but this recovered by December 2020. New diagnoses of HIV were 34% lower throughout 2020 compared to 2019. In Sierra Leone, compared to the same periods in 2019, facilities had 18-29% fewer OPD consultations throughout 2020, and 27% fewer DTP3 doses in March-July 2020. There was no evidence of differences in other services. In Uganda there were 20-35% fewer under-5 OPD consultations, 21-66% fewer MCV1 doses, and 48-51% fewer new diagnoses of HIV throughout 2020, compared to 2019. There was no difference in the number of HPV doses delivered.ConclusionsThe level of disruption varied across the different settings and qualitatively appeared to correlate with the strength of lockdown measures and reported attitudes towards the risk posed by COVID-19. Mitigation strategies such as health communications campaigns and outreach services may be important to limit the impact of lockdowns on primary healthcare services.