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Candidate Denisovan fossils identified through gene regulatory phenotyping

Denisovans are an extinct group of humans whose morphology is mostly unknown. The scarcity of verified Denisovan fossils makes it challenging to study their anatomy, and how well they were adapted to their environment. We previously developed a genetic phenotyping approach to gain insight into Denisovan anatomy by detecting gene regulatory changes that likely altered Denisovan skeletal morphology. Here, we scan the Middle Pleistocene fossil record for crania matching the predicted Denisovan morphology and might therefore be related to Denisovans. We developed quantitative measures to assess both the proportion and extent of matches. These analyses revealed that the East Asian specimens of Harbin and Dali show an exceptionally high concordance with the Denisovan profile, surpassing all other examined Middle Pleistocene hominin specimens, including Neanderthals. Specifically, 15 out of 18 of Dali ’s features and 16 out of 18 of Harbin ’s matched Denisovan predictions. These findings are robust to overall skull size and to correlations between phenotypes. We also found that Kabwe 1 shows a strong affinity to the Denisovan–Neanderthal clade and might be placed near its root. Our results show that gene regulatory phenotyping may assist in classifying poorly understood specimens.

A rapid tectonic plate reorganization event driven by changes at subduction locations in a mantle convection model

Research on the impact of coupling and coordination of rural consumption power system on the consumption of rural residents in China

The harmonious operation of social consumption power system can stimulate residents’ higher-level consumption demands, thereby driving overall consumption growth. Based on the panel data of 30 Chinese provinces (excluding Hong Kong, Macao, Taiwan, and Tibet) from 2002 to 2022, this study integrates multiple determinants of rural residents’ consumption into the conceptual framework of social consumption power. Employing a systematic approach, we construct a spatial Durbin model to empirically examine how the coupling coordination level of the rural consumption power system influences rural residents’ consumption behavior. The findings reveal that the coupling coordination level of rural consumption power system exerts a statistically significant positive effect on rural residents’ consumption not only within a given province but also in neighboring provinces, indicating spatial spillover effects. These spillover effects are particularly pronounced in the eastern and central regions. Therefore, in order to release the huge consumption potential in rural areas, it’s vital to make good use of the coupling and coordinating role of the three subsystems of consumption subject, consumption object and consumption environment and achieve the fit and coordination between supply-side structural reform and demand-side structural reform. The research findings not only provide factual evidences and theoretical support for transforming the government’s strategy of expanding rural residents’ consumption but also propose practical instructions for further releasing rural residents’ consumption potential in the new era.

Logging disrupts the ecology of molecules in headwater streams

Global demand for wood products is increasing forest harvest. One understudied consequence of logging is that it accelerates mobilization of dissolved organic matter (DOM) from soils to aquatic ecosystems where it is more easily rereleased to the atmosphere. Here, we tested how logging changed DOM in headwaters of hardwood-dominated catchments in northern Ontario, Canada. We applied a before-after-control-impact experiment across four catchments for 3 y and measured DOM monthly during ice-free seasons. DOM concentration in streams from logged catchments quadrupled, on average, only for the first 2 mo postharvest, but resulting changes to the molecular composition of DOM persisted for at least 2 y. Ultrahigh-resolution mass spectrometry revealed that DOM composition within logged streams became more available for microbial use and chemically diverse than in controls, with novel highly unsaturated polyphenols, carboxylic-rich alicyclic, and nitrogen-containing formulae. The molecular composition of stream DOM measured fortnightly postharvest was most similar to the DOM composition of surrounding soils, likely due to increased hydrological connectivity. Alongside carbon being more likely to be released into the atmosphere, we estimate that selective logging increased the total flux of dissolved organic carbon in streams by 6.4% of the carbon extracted as timber. Although these estimates are short-lived, they should affect the millions of hectares that are logged annually. Carbon accounting of forestry, including as a natural climate solution, must now consider the transport and fate of DOM from land into water.

Retraction Note: Investigation of laser factors influence on strength of laser spot welding of 316 stainless steel using the designing experiments method

Transplacental transfer of maternal SARS-CoV-2 antibodies in dichorionic and monochorionic twin pregnancies

Background Maternal immunization relies on active transplacental transfer of immunoglobulin G. However, very little is known about the efficacy of maternal immunization in the setting of multiple gestation. We aimed to investigate transplacental transfer of maternal antibody in pregnancies with multiple gestation including mono- and dichorionic pregnancies by evaluating anti-Spike antibody transfer at delivery. Methods We conducted a cohort study among individuals with singleton or twin pregnancies who received ≥ 2 doses of an mRNA COVID-19 vaccine before delivery. We tested paired maternal and cord blood samples for anti-Spike antibody levels via Roche Elecsys® immunoassays and used linear regression to evaluate associations between pregnancy type and anti-Spike antibody levels. We included as covariates gestational age at birth, timing of last vaccine dose, number of vaccine doses, and small for gestational age birth weight. Results Between 2021−2023, we tested paired maternal and cord samples for anti-Spike antibody from 362 singleton pregnancies and 36 twin pregnancies, of which 12 and 24 were monochorionic and dichorionic, respectively. After adjusting for covariates, maternal and cord anti-Spike antibody concentrations were significantly lower in twin pregnancies compared to singleton pregnancies (beta:-0.91, 95% Confidence Interval [CI]: −1.62,-0.19; p = 0.01. beta −1.20, 95% CI: −2.36,-0.04; p = 0.04), however there was no difference in cord:maternal antibody ratios. After adjusting for covariates, there was no difference in maternal and cord antibody concentrations between dichorionic and monochorionic pregnancies, however, cord:maternal antibody ratios remained significantly lower in monochorionic compared to dichorionic pregnancies (beta:-0.49; 95% CI: −0.86,-0.13; p = 0.01). Conclusions Twin and singleton infants have similar cord:maternal maternally derived SARS-CoV-2 antibody ratios after maternal COVID-19 vaccine although maternal and cord antibody concentrations are lower in infants from twin pregnancies and specifically antibody transfer is less efficient in monochorionic pregnancies. Further research is needed to investigate impaired transplacental IgG transfer in high-risk pregnancies.

Multistep catalytic abiotic CO ₂ conversion to sugars through C ₁ intermediates

Carbon dioxide (CO 2 ) to multicarbon (C n ) upgrading for commodity chemicals, fuel production, or artificial food synthesis using renewable energy input is a golden target for researchers in sustainable carbon emission reduction. Here, we explore and analyze a flexible modular roadmap for the task, utilizing sequential electro-, photo-, and organocatalysis to develop a strategy for CO 2 conversion using the key and elusive formaldehyde precursor of interest for sugar generation. We study the electrochemical carbon dioxide reduction reaction to methanol in a flow cell and its discontinuous photooxidation to formaldehyde (PMOR) with excellent selectivity. Utilizing a highly active N- heterocyclic carbene catalyst enables tunable generation of C 4 –C 6 aldoses without undesirable byproducts, with carbon conversion yield reaching 60 to 80% for desired pentose, tetrose, and triose product mixtures and over 20% for hexose. This approach presents a roadmap for CO 2 valorization, aiming to bridge carbon waste streams with sustainable sugar synthesis and opening broad avenues for green chemical production.

Displacement-encoded MRI reveals biomechanical stiffening in rheumatoid arthritis wrists: a case control study

Persistent inpatient delirium associated with increased length of stay and mortality

Introduction Delirium is associated with an increased risk of post-hospitalization mortality. However, the impact of persistent delirium on mortality is not well defined. Methods We conducted a retrospective cohort study on the association of non-persistent or persistent delirium and mortality. We included patients aged > 65 years admitted to the Owensboro Health Regional Hospital between August 2021 and August 2022. Delirium was determined based on a score of ≥ 2 on the Nurse Delirium Screening Scale (NuDESC) recorded on all admitted patients three times a day during nursing shift change. Multivariate logistic regression models were used to evaluate the association between non-persistent or persistent delirium and 30-day, 60-day, 90-day, 180-day, and 360-day mortality after adjusting for covariates. Sensitivity analysis was performed to compare different definitions of delirium as ≥ 2, ≥ 3, or ≥ 4 days of delirium occurring consecutively or non-consecutively. Results 4560 hospitalized patients were included in this study. Of these, 634 (13.9%) were identified as having delirium (persistent or non-persistent) and 3926 (86.1%) as without delirium. Patients with delirium were slightly older than those without (77 ± 7.9 vs. 79.5 ± 8.5 years old). The patients in each group were relatively comparable in terms of sex, race, smoking status, Medicare user status, and comorbidities. After adjusting for comorbidities, delirium was associated with an increase of mortality at 30 days for patients with persistent delirium of 2 days (aOR 4.88, 95% CI 3.63–6.54), 3 days (aOR 5.64, 95% CI 3.95–7.98), 4 days (aOR 7.21, 95% CI 4.74–10.8). Persistent delirium was associated with higher 60-day, 90-day, 180-day, and 360-day mortality rates, with an incremental increase in the risk of mortality for each additional day of delirium. Conclusion Persistent delirium is consistently associated with increased mortality, with an increased risk of mortality for each additional day of delirium, underscoring the need for early identification and treatment.

Color-neutral and reversible tissue transparency enables longitudinal deep-tissue imaging in live mice

Light scattering in biological tissue presents a significant challenge for deep in vivo imaging. Our previous work demonstrated the ability to achieve optical transparency in live mice using intensely absorbing dye molecules, which created transparency in the red spectrum while blocking shorter-wavelength photons. In this paper, we extend this capability to achieve optical transparency across the entire visible spectrum by employing molecules with strong absorption in the ultraviolet spectrum and sharp absorption edges that rapidly decline upon entering the visible spectrum. This color-neutral and reversible tissue transparency method enables optical transparency for imaging commonly used fluorophores in the green and yellow spectra. Notably, this approach facilitates tissue transparency for structural and functional imaging of the live mouse brain labeled with yellow fluorescent protein and GCaMP through the scalp and skull. We show that this method enables longitudinal imaging of the same brain regions in awake mice over multiple days during development. Histological analyses of the skin and systemic toxicology studies indicate minimal acute or chronic damage to the skin or body using this approach. This color-neutral and reversible tissue transparency technique opens opportunities for noninvasive deep-tissue optical imaging, enabling long-term visualization of cellular structures and dynamic activity with high spatiotemporal resolution and chronic tracking capabilities.

Updated reference intervals for serum cystatin C and creatinine based on age and sex variations

Using protection motivation theory to support patient adherence in healthcare settings: A scoping review

Background Protection motivation theory (PMT) shows promise as a basis for motivating healthy behaviours in healthcare settings. There has been no systematic overview of how PMT has been translated into clinical practice and which translation strategies effectively improve outcomes. Objectives This scoping review aimed to systematically map and synthesise existing literature on PMT-based interventions targeting health behaviours in healthcare contexts. Methods Medline, PsycINFO, and EMBASE were searched for studies applying PMT within healthcare contexts. Eligible populations had a clinical condition. To be eligible, studies had to report a healthcare-delivered PMT intervention with adherence outcomes directly benefiting participants. Two reviewers extracted data on study features, intervention characteristics including behaviour change techniques employed, PMT constructs addressed, results, and research recommendations. Findings were summarised narratively and tabulated. Results Thirteen studies published between 1998 and 2023 met the eligibility criteria, including 12 randomised trials. Studies addressed acute and chronic conditions across primary, secondary, and non-clinical settings. Half significantly improved behaviour outcomes in intervention groups. All targeted coping-self-efficacy and perceived threat-severity PMT constructs to some degree. Combinations of behaviour change techniques did not clearly differentiate successful outcomes. Studies recommended longer follow-up, clarifying effective PMT component combinations, and drawing on multiple behaviour theories. Discussion Despite heterogeneity in how PMT interventions were operationalised, they show potential benefits for motivating adherence to healthy behaviours. To enable optimisation and dissemination, consistent nonadherence detection and reporting methods are critical. Further research should include translation of PMT to other healthcare settings, refining methodology and implementing well-powered effectiveness trials in routine care.

Tunable effective diffusion of CO ₂ in aqueous foam

Aqueous foams are solid materials composed of gases and liquids, exhibiting a large gas/liquid surface area and enabling dynamic exchanges between their fluid components. The structure of binary-gas foams, whose bubbles consist of a mixture of two gases having different affinities with the liquid, thus offers real potential for the dynamic separation of these gases at low cost. In single-gas foams, the structure evolves under the effect of gas flow induced by Laplace pressure differences, arising from heterogeneities in bubble size. This leads to the well-documented Ostwald ripening. In addition to these capillary effects, the structure of binary-gas foams can evolve under the effect of gas flow induced by partial pressure differences, arising from heterogeneities in bubble composition. We experimentally investigate the shrinking of CO 2 -laden 2D foams exposed to air, observing a crust of tiny bubbles at the front. We derive a nonlinear diffusion model for the gas in the foam and propose a description of the whole foam as an effective, homogeneous medium, the key parameter being the gas permeability ratio across the foam’s soap films (≠1 for CO 2 /air). The effective diffusivity of the gas in the foam emerges from the coupling between foam structure and gas transport across soap films. We extrapolate it for various permeability ratios and show that it can vary continuously between the diffusivity of the gas in the liquid and that of the gas in the atmosphere, enabling tunable gas retention and release by controlling the composition of the atmosphere.

Epidemiology and co-infection patterns of community-acquired pneumonia among children from 2015 to 2023 in Henan Province, China: longitudinal surveillance study

Prediction of the ectasia screening index from raw Casia2 volume data for keratoconus identification by using convolutional neural networks

Purpose Prediction of the ectasia screening index, an estimator provided by the Casia2 instrument for identifying keratoconus, from raw optical coherence tomography data using convolutional neural networks. Methods Three convolutional neural networks models (ResNet18, DenseNet121 and EfficientNetB0) were employed to predict the ectasia screening index. Mean absolute error was used as the performance metric for predicting the ectasia screening index by the adapted convolutional neural network models on the test set. Scans with an ectasia screening index value higher than a certain threshold were classified as Keratoconus, while the remaining scans were classified as Not Keratoconus. The architectures’ performance was evaluated using metrics such as accuracy, sensitivity, specificity, positive predictive value and F1 score on data collected from patients examined at the eye clinic of the Homburg University Hospital. The raw data from the Casia2 instrument, in 3dv format, was converted into 16 images per examination of one eye. For the training, validation and testing phases, 3689, 1050 and 1078 scans (3dv files) were selected, respectively. Results In the prediction of the ectasia screening index, the mean absolute error values for the adapted ResNet18, the adapted DenseNet121 and the adapted EfficientNetB0, rounded to two decimal places, were 7.15, 6.64 and 5.86, respectively. In the classification task, the three networks yielded an accuracy of 94.80%, 95.27% and 95.83%, respectively; a sensitivity of 92.07%, 94.64% and 94.17%, respectively; a specificity of 96.61%, 95.69% and 96.92%, respectively; a positive predictive value of 94.72%, 93.55% and 95.28%, respectively; and a F1 score of 93.38%, 94.09% and 94.72%, respectively. Conclusions Our results show that the prediction of keratoconus based on the ectasia screening index values estimated from raw data outperforms previous approaches using processed data. adapted EfficientNetB0 outperformed both the other adapted models and those in state-of-the-art studies, with the highest accuracy and F1 score.

STAGE: A compact and versatile TnpB-based genome editing toolkit for <i>Streptomyces</i>

Streptomyces are naturally endowed with the capacity to produce a wide array of natural products with biomedical and biotechnological value. They have garnered great interest in synthetic biology applications given the abundance of uncharacterized biosynthetic gene clusters (BGCs). However, progress has been hindered by the limited availability of genetic tools for manipulating these bacteria. Several representative CRISPR-Cas systems have been established in Streptomyces to streamline experimental workflows and improve editing efficiency. Nevertheless, their broader applicability has been constrained by issues such as nuclease activity-related cytotoxicity and the large size of effector proteins. To address these challenges, we present Streptomyces -compatible TnpB-assisted genome editing (STAGE), a genetic toolkit based on ISDra2 TnpB, which is approximately one-third the size of Cas9 and enables precise, site-specific gene editing. We demonstrated that STAGE introduces genetic mutations with high efficiency and minimal off-target effects in two industrially important Streptomyces strains. Building on this platform, we developed STAGE-cBEST and STAGE-McBEST, enabling single and multiplexed C·G-to-T·A base editing, respectively, with editing efficiencies exceeding 75%. To further enhance performance, we engineered the ISDra2 TnpB system using an AI-assisted protein engineering framework, resulting in two variants that achieve nearly 100% genome editing efficiency. Additionally, through sequence homology analysis, we identified a TnpB ortholog from the same biological origin of ISDra2 TnpB, which also functions effectively as a gene editing tool. Our study establishes STAGE as a highly precise, programmable, and versatile genome editing platform for Streptomyces , paving the way for advanced genetic manipulation and synthetic biology applications in these industrially important bacteria.

Impact of cone system compatibility on single cone bioceramic obturation in canals prepared with variable taper NiTi rotary files

Cancer disparities: Projection, COVID-19, and scenario-based diagnosis delay impact

There has been limited research on how disparities in cancer mortality may evolve in the future, although relevant socio-economic and regional disparities in cancer risk are well-documented. We studied future trends in breast cancer (BC) and lung cancer (LC) mortality up to 2036 across affluent and deprived communities in nine regions of England, motivated by the distinct socio-economic patterns and burden of these cancer types. We used cancer death registrations from the Office for National Statistics on population and deaths in nine regions of England by underlying cause of death from 2001 to 2018, stratified by sex, 5-year age group, and income deprivation. We applied a gender- and cause-specific Bayesian hierarchical model to obtain robust estimates of cancer mortality by age group, gender, deprivation quintile, and region, up to 2036. In these models, we also used a data-driven proxy for age-at-diagnosis as an additional risk factor, and non-smoker prevalence rates as a proxy for smoking. We found that if pre-COVID conditions and trends remained the same, socio-economic disparities in LC would persist during our projection period. LC mortality rates for women in 2036 were found to be around 60% lower in the least deprived areas of London, as compared to the most deprived in the same region, with the disparities being even higher in northern regions and among men. Using data from the period 2011-2018, our model estimated 2% fewer LC deaths than those registered during the pandemic years (2020-2022) across England (and 4% fewer for men). Scenarios linked to delays in LC diagnosis led to stark differences in future excess mortality – significantly higher excesses in the northern regions compared to the southern regions, and in the most deprived areas compared to the least deprived areas. Additionally, our findings show that if pre-COVID conditions and trends remained unchanged, BC mortality would continue to decline up to 2036, with comparable rates in the regions of England. During the pandemic years, BC deaths were estimated to decline by 1% across England compared to the pre-pandemic trends (2001-2018). However, our analysis shows 10% to 13% increase in BC deaths for women aged 80+ in the same years. Cancer disparities are predicted to persist in the future unless targeted interventions are implemented. Our results underscore the notable impact of delays in cancer diagnosis on cancer mortality and related inequalities. Future research that models different causes of death while adjusting model outputs for competing risk factors might be beneficial. Further models with individual-level socio-economic risk factors would also be useful.

Specificities of chemosensory receptors in the human gut microbiota

The human gut is rich in metabolites and harbors a complex microbial community, yet surprisingly little is known about the spectrum of chemical signals detected by the large variety of sensory receptors present in the gut microbiome. Here, we systematically mapped the ligand specificities of selected extracytoplasmic sensory domains from twenty members of the human gut microbiota, with a primary focus on the abundant and physiologically important class of Clostridia. Twenty-five metabolites from different chemical classes—including amino acids, nucleobase derivatives, amines, indole, and carboxylates—were identified as specific ligands for fifteen sensory domains from nine bacterial species, which represent all three major functional classes of transmembrane receptors: chemotaxis receptors, histidine kinases, and enzymatic sensors. We have further characterized the specificity and evolution of ligand binding to Cache superfamily sensors specific for lactate, dicarboxylic acids, and for uracil and short-chain fatty acids (SCFAs). Structural and biochemical analysis of the dCache sensor of uracil and SCFAs revealed that its two different ligand types bind at distinct sensory modules. Overall, combining experimental identification with computational analyses, we were able to assign ligands to approximately half of the Cache-type chemotaxis receptors found in the eleven gut commensal genomes from our set, with carboxylic acids representing the largest ligand class. Among these, the most commonly found ligand specificities were for lactate and formate, indicating a particular importance of these metabolites in the human gut microbiota and consistent with their observed growth-promoting effects on selected bacterial commensals.

Comparison of dental findings between dentists and pediatricians using intraoral scan-based teledentistry in children

Abstract Background Asynchronous transmission of health information via teledentistry offers the potential for remote diagnosis in pediatric dentistry. The aim of this study was to compare teledental findings obtained from intraoral scans (IOS) with those from conventional visual examinations (VIS) in children. Specifically, the study assessed the diagnostic accuracy of teledentistry using IOS in evaluating oral health and determining treatment needs focusing on comparisons between dentists and pediatricians. Methods Children (mean age 10.04 ± 2.90 years) underwent VIS during routine dental examinations. Two examiners performed the VIS, followed by digital IOS imaging of the oral cavity. Independent teledental evaluations based on the IOS data were then performed by a dentist (DEN) and a pediatrician (PED). Evaluation criteria included general dental status, presence of caries and molar incisor hypomineralization (MIH) (yes/no), restorations (yes/no; and type, if applicable), urgency of dental intervention, and treatment recommendations (no treatment, prophylaxis, follow-up, or immediate intervention). Agreement was analyzed using Gwet’s AC1, Cohen’s d, sensitivity, specificity, and area under the curve (AUC). Results Almost perfect agreement (AC1 ≥ 0.81) was found for all test criteria, with two exceptions showing substantial agreement (AC1 = 0.61–0.80). Agreement values of overall dental status were 0.953/0.962 (primary dentition/permanent dentition (pD/PD)) for DEN and 0.908/0.923 for PED. Caries detection (yes/no) showed an agreement of 0.965/0.995 for DEN vs. 0.930/0.979 for PED, while restorations agreement was 0.988/0.993 (DEN) vs. 0.950/0.946 (PED). MIH assessment showed agreement of 0.996 (DEN) vs. 0.987 (PED). Cohen’s d for the comparison between DEN and PED ranged from small for MIH (0.17), caries detection (0.23) and overall dental status (0.34/0.35) to large for restoration type (0.89). The clinically most relevant item “urgency of dental intervention” showed almost perfect agreement (0.903 for DEN vs. 0.878 for PED), and the final treatment recommendations showed an almost perfect to substantial agreement of 0.832 (DEN) vs. 0.775 (PED). Notably, both examiners showed similar accuracy in assessing the urgency of intervention. Conclusions This study demonstrates the potential of IOS-based teledentistry for pediatric dental assessments. The results indicate that pediatricians can effectively assess oral health and provide reliable treatment recommendations. This approach has the potential to increase access to dental care and to promote interdisciplinary collaboration in pediatric health care.