Browse Articles

Outcome comparison of rotational ankle fractures: Supination external rotation versus pronation external rotation

Background Ankle fractures are among the most common types of fractures in the orthopaedic field, and the Lauge-Hansen classification is commonly used to categorize rotational ankle fractures. This study evaluated and compared the clinical and radiological outcomes of surgically treated supination external rotation (SER) and pronation external rotation (PER) injuries of grades III or IV. Methods We retrospectively reviewed and enrolled 104 patients who underwent open reduction and internal fixation for SER or PER injuries classified as Grades III or IV between January 2016 and December 2021, all performed at a single center. Of these, 72 belonged to the SER group and 32 to the PER group. The average postoperative follow-up durations were 31.3 months (range, 24 to 74) for the SER group and 32.1 months (range, 24 to 71) for the PER group. Clinical and radiological outcomes were assessed 24 months after surgery and compared between the two groups. Details of concomitant surgical procedures performed and postoperative complications were also evaluated. Results All clinical outcome variables, including the Foot and Ankle Outcome Score, Visual Analog Scale for pain, and ankle range of motion, were comparable between the two groups. Similarly, no statistically significant differences were observed in the development of post-traumatic arthritis or in the frequency of syndesmotic widening 24 months postoperatively. However, the time required for fibular union was significantly longer in the PER group, taking 5.6 ± 2.2 months compared to 3.4 ± 1.3 months in the SER group on average (p < 0.001). Conclusions Our study demonstrated that both types of rotational ankle fractures can achieve equivalent clinical and radiological outcomes with surgical treatment. Given the prolonged time to fibular union in the PER group, careful monitoring during postoperative follow-up is required.

Polar mesospheric ozone loss initiates downward coupling of solar signal in the Northern Hemisphere

Abstract Solar driven energetic particle precipitation (EPP) is an important factor in polar atmospheric ozone balance and has been linked to ground-level regional climate variability. However, the linking mechanism has remained ambiguous. The observed and simulated ground-level changes start well before the processes from the main candidate, the so-called EPP-indirect effect, would start. Here we show that initial reduction of polar mesospheric ozone and the resulting change in atmospheric heating rapidly couples to dynamics, transferring the signal downwards, shifting the tropospheric jet polewards. This pathway is not constrained to the polar vortex. Rather, a subtropical route initiated by a changing wind shear plays a key role. Our results show that the signal propagates downwards in timescales consistent with observed tropospheric level climatic changes linked to EPP. This pathway, from mesospheric ozone to regional climate, is independent of the EPP-indirect effect, and solves the long-standing mechanism problem for EPP effects on climate.

CooccurrenceAffinity: An R package for computing a novel metric of affinity in co-occurrence data that corrects for pervasive errors in traditional indices

1. Analysis of co-occurrence data with traditional indices has led to many problems such as sensitivity of the indices to prevalence and the same value representing either a strong positive or strong negative association across different datasets. In our recent study (Mainali et al 2022), we revealed the source of the problems that make the traditional indices fundamentally flawed and unreliable–namely that the indices in common use have no target of estimation quantifying degree of association in the non-null case–and we further developed a novel parameter of association, alpha, with complete formulation of the null distribution for estimating the mechanism of affinity. We also developed the maximum likelihood estimate (MLE) of alpha in our previous study. 2. Here, we introduce the CooccurrenceAffinity R package that computes the MLE for alpha. We provide functions to perform the analysis based on a 2×2 contingency table of occurrence/co-occurrence counts as well as a m×n presence-absence matrix (e.g., species by site matrix). The flexibility of the function allows a user to compute the alpha MLE for entity pairs on matrix columns based on presence-absence states recorded in the matrix rows, or for entity pairs on matrix rows based on presence-absence recorded in columns. We also provide functions for plotting the computed indices. 3. As novel components of this software paper not reported in the original study, we present theoretical discussion of a median interval and of four types of confidence intervals. We further develop functions (a) to compute those intervals, (b) to evaluate their true coverage probability of enclosing the population parameter, and (c) to generate figures. 4. CooccurrenceAffinity is a practical and efficient R package with user-friendly functions for end-to-end analysis and plotting of co-occurrence data in various formats, making it possible to compute the recently developed metric of alpha MLE as well as its median and confidence intervals introduced in this paper. The package supplements its main output of the novel metric of association with the three most common traditional indices of association in co-occurrence data: Jaccard, Sørensen–Dice, and Simpson.

Mitochondrial segmentation and function prediction in live-cell images with deep learning

Trends in the prevalence of obesity and estimation of the direct health costs attributable to child and adolescent obesity in Brazil from 2013 to 2022

Introduction Childhood obesity is a major global public health issue globally and in Brazil. The impacts of childhood obesity include higher risk of disease during childhood and of obesity and non-communicable diseases in adulthood and represent an important epidemiological and economic burden to countries. This study aims to analyze the trends and to estimate the direct healthcare costs of childhood and adolescent obesity to the National Health System from 2013 to 2022. Methods We used Prais-Winsten regressions for determining the trends in the prevalence of obesity and modeled the attributable to childhood and adolescent obesity in the Brazilian National Health System using previous meta-analysis of studies. Results The hospitalizations of children and adolescents with obesity as a primary cause totaled Int$2.6 million to the Brazilian National Health System from 2013 to 2022, demonstrating that obesity is rarely considered as a cause of hospitalization especially among children and adolescents. The additional costs of hospitalizations attributable to childhood obesity totaled Int$101.5 million during the same period. The additional non-hospital, outpatient and medication cost attributable to childhood obesity in Brazil were estimated at Int$6.0 million, so the total estimated healthcare costs were of approximately Int$107.5 million in the last decade. Conclusion This study highlights that childhood and adolescent obesity are increasing for most age-groups and that its costs are not limited to the economic impacts on adult health and represent a relevant economic burden to the Brazilian National Health System and to families because of additional costs during childhood and adolescence. Therefore, the prevention and control of childhood and adolescent obesity must be public health priorities.

Rational engineering of DNA-nanoparticle motor with high speed and processivity comparable to motor proteins

A machine learning based variable selection algorithm for binary classification of perinatal mortality

The identification of significant predictors with higher model performance is the key objective in classification domain. A machine learning-based variable selection technique termed as CARS-Logistic model is proposed by coupling competitive adaptive re-weighted sampling(CARS) and logistic regression for binary classification. Based on five assessment criteria, the proposed method is found to be more efficient than Forward selection logistic regression model. The CARS-Logistic model is executed to determine the significant factors of perinatal mortality in Pakistan. The identified hazards communicated social, cultural, financial, and health-related characteristics which contain key information about perinatal mortality in Pakistan for policymakers.

Control of water for high-yield and low-cost sustainable electrochemical synthesis of uniform monolayer graphene oxide

Abstract With the rapid development of graphene industry, low-cost sustainable synthesis of monolayer graphene oxide (GO) has become more and more important for many applications such as water desalination, thermal management, energy storage and functional composites. Compared to the conventional chemical oxidation methods, water electrolytic oxidation of graphite-intercalation-compound (GIC) shows significant advantages in environmental-friendliness, safety and efficiency, but suffers from non-uniform oxidation, typically ~50 wt.% yield with ~50% monolayers. Here, we show that water-induced deintercalation of GIC is responsible for the non-uniform oxidation of the water electrolytic oxidation method. Using in-situ experiments, the control principles of water diffusion governing electrochemical oxidation and deintercalation of GIC are revealed. Based on these principles, a liquid membrane electrolysis method was developed to precisely control the water diffusion to achieve a dynamic equilibrium between oxidation and deintercalation, enabling industrial sustainable synthesis of uniform monolayer GO with a high yield (~180 wt.%) and a very low cost (~1/7 of Hummers’ methods). Moreover, this method allows precise control on the structure of GO and the synthesis of GO by using pure water. This work provides new insights into the role of water in electrochemical reaction of graphite and paves the way for the industrial applications of GO.

RORγt inverse agonists demonstrating a margin between inhibition of IL-17A and thymocyte apoptosis

Multiple genetic associations suggest a causative relationship between Th17-related genes coding for proteins, such as IL-17A, IL-23 and STAT3, and psoriasis. Further support for this link comes from the findings that neutralizing antibodies directed against IL-17A, IL-17RA and IL-23 are efficacious in diseases like psoriasis, psoriatic arthritis and ankylosing spondylitis. RORγt is a centrally positioned transcription factor driving Th17 polarization and cytokine secretion and modulation of RORγt may thus provide additional benefit to patients. However, RORγt also plays a role in the normal development of T cells in the thymus and genetic disruption of RORγt in the mouse leads to the development of lymphoma originating in the thymus. Whilst it is not established that down-regulation of RORγt activity would lead to the same consequence in humans, further understanding of the thymus effects is desirable to support progress of this target as a potential treatment of Th17-driven disease. Herein we present the characterisation of recently disclosed RORγt inverse agonists demonstrating target engagement and efficacy in vitro and in vivo against Th17 endpoints but requiring higher concentrations in vitro to affect thymocyte apoptosis.

Shear localisation controls the dynamics of earthquakes

Abstract Earthquakes are produced by the propagation of rapid slip along tectonic faults. The propagation dynamics is governed by a balance between elastic stored energy in the surrounding rock, and dissipated energy at the propagating tip of the slipping patch. Energy dissipation is dictated by the mechanical behaviour of the fault, which is itself the result of feedbacks between thermo-hydro-mechanical processes acting at the mm to sub-mm scale. Here, we numerically simulate shear ruptures using a dual scale approach, allowing us to couple a sub-mm description of inner fault processes and km-scale elastodynamics, and show that the sudden localisation of shear strain within a shear zone leads to the emergence of classical cracks driven by a constant fracture energy. The fracture energy associated to strain localisation is substantially smaller than that predicted in theoretical and numerical models assuming uniform shearing within the shear zone. We show the existence of a unique scaling law between the localised shearing width and the rupture speed. Our results indicate that earthquakes are likely to be systematically associated to extreme strain localisation.

A co-produced mixed methods protocol: Exploring perceptions of oral health care and quality of life in people with mental health conditions

This planned mixed methods protocol is designed to explore oral health care for individuals living with serious mental health conditions (SMHC). It was co-produced by academics, people with lived experience of mental health conditions, and oral and mental health clinicians. The study seeks to explore oral health quality of life predictors and oral health care experiences of people diagnosed with serious mental health conditions (e.g. schizophrenia, bipolar disorder, major depression and general anxiety disorder) about their oral health care experiences. The research research will generate recommendations for creating positive oral healthcare experiences for people living with SMHC. Research co-production with people diagnosed with mental health conditions is a recommended strategy to improve the utility and relevance of health research, as well as empower a disenfranchised population.

Transducing chemical energy through catalysis by an artificial molecular motor

Abstract Cells display a range of mechanical activities generated by motor proteins powered through catalysis 1 . This raises the fundamental question of how the acceleration of a chemical reaction can enable the energy released from that reaction to be transduced (and, consequently, work to be done) by a molecular catalyst 2–7 . Here we demonstrate the molecular-level transduction of chemical energy to mechanical force 8 in the form of the powered contraction and powered re-expansion of a cross-linked polymer gel driven by the directional rotation of artificial catalysis-driven 9 molecular motors. Continuous 360° rotation of the rotor about the stator of the catalysis-driven motor-molecules incorporated in the polymeric framework of the gel twists the polymer chains of the cross-linked network around one another. This progressively increases writhe and tightens entanglements, causing a macroscopic contraction of the gel to approximately 70% of its original volume. The subsequent addition of the opposite enantiomer fuelling system powers the rotation of the motor-molecules in the reverse direction, unwinding the entanglements and causing the gel to re-expand. Continued powered twisting of the strands in the new direction causes the gel to re-contract. In addition to actuation, motor-molecule rotation in the gel produces other chemical and physical outcomes, including changes in the Young modulus and storage modulus—the latter is proportional to the increase in strand crossings resulting from motor rotation. The experimental demonstration of work against a load by a synthetic organocatalyst, and its mechanism of energy transduction 6 , informs both the debate 3,5,7 surrounding the mechanism of force generation by biological motors and the design principles 6,10–14 for artificial molecular nanotechnology.

Continuous photo-oxidation of methane to methanol at an atomically tailored reticular gas-solid interface

RETRACTED: Machine vision model for drip leakage detection of pipeline

The prevailing trend in industrial equipment development is integration, with pipelines as the lifeline connecting system components. Given the often harsh conditions of these industrial equipment pipelines, leakage is a common occurrence that can disrupt normal operations and, in severe cases, lead to safety accidents. Early detection of even minor drips at the onset of leakage can enable timely maintenance measures, preventing more significant leaks and halting the escalation of pipeline failures. In light of this, our study investigates a method for monitoring pipe drips in industrial equipment using machine vision technology. We propose a machine vision model specifically designed for pipe drip detection, aiming to facilitate monitoring of pipe system drips. The system designed to collect the image of the droplet side cross-section with a Charge charge-coupled device (CCD) industrial camera, is aided by the computer image processing system used to analyze and process the collected images. Image enhancement technology is applied to improve the visibility of the image and image filtering technology is applied to remove the noise of the image. With the help of image segmentation technology, target droplet identification and division are achieved. Morphological reconstruction and region-filling techniques are used to remove the noise caused by shooting in the side cross-section image, such as hollow, reflection, and irregular droplet edge, to upgrade the quality of the solution droplet edge. The mathematical model is established for boundary position points extracted from the droplet side cross-section image. Then, the fitting droplet image is drawn. The droplet volume is obtained by calculating the volume of the rotating body. The two-dimensional image of the target droplet is obtained dynamically through the camera capture technology. The droplet boundary extraction algorithm is proposed, and the three-dimensional model of the target droplet is established, so the volume calculation problem of the droplet is solved, which provides a way of thinking for drip leakage detection of the pipeline.

Pregnancy entails a U-shaped trajectory in human brain structure linked to hormones and maternal attachment

Deep learning-based skin lesion analysis using hybrid ResUNet++ and modified AlexNet-Random Forest for enhanced segmentation and classification

Skin cancer is considered globally as the most fatal disease. Most likely all the patients who received wrong diagnosis and low-quality treatment die early. Though if it is detected in the early stages the patient has fairly good chance and the aforementioned diseases can be cured. Consequently, diagnostic identification and management of the patient at this level becomes a rather enormous task. This paper offers a cutting-edge hybrid deep learning approach of better segmentation and classification of skin lesions. The proposed method incorporates three key stages: preprocessing, segmentation of lesions, and classification of lesions. By the stage of preprocessing, a morphology-based technique takes out hair so as to enhance the segmentation precision to use the cleansed images for subsequent analysis. Segmentation cuts off the lesion from the surrounding skin, giving the classification phase a dedicated area of interest and the ability to clear the background noise that may affect classification rates. The isolation enables the model to better analyze anatomical lesion features in order to achieve accurate benign and malignant classifications. Using ResUNet++, the cutting-edge deep learning architecture, we achieved accurate lesion segmentation. Next, we will modify and use an AlexNet-Random Forest (AlexNet-RF) based classifier for robust lesion classification. The proposed hybrid deep learning model is intensively validated on the Ham10000 data set which is one of the most popular datasets for skin lesions analysis. The obtained results show that the utilized approach, compared to the previous ones, is more effective, giving better segmentation and classification results. This method takes advantage of ResUNet++ strong classification skill and modified AlexNet-Random Forest robustness for more accurate segmentation. There is a high probability that ResUNet++, which is highly proficient at medical image segmentation, can produce better segmentation of lesions than the simpler models. The composition of AlexNet’s extraction of features with Random Forest ability to reduce overfitting possibly may be more precise in the classification when compared to using only one model.

Spontaneous curvature in two-dimensional van der Waals heterostructures

Correction: Defending Against Advanced Persistent Threats Using Game-Theory

Developing an alternative medium for in-space biomanufacturing

Protective effects of Euphorbia heterophylla against testicular degeneration in streptozotocin-induced diabetic rats in relation to phytochemical profile

Background Diabetes mellitus (DM) poses a major risk to human health due to an array of implications, one of which is a detrimental effect on the testicular and reproductive functions. Euphorbia heterophylla is widely recognized for its medicinal properties worldwide. Methods and findings The objective of this study was to profile E. heterophylla ethanol extract (EH-EtOH) and elucidate its protective role in oxidative stress, relieving inflammatory action of hyperglycemia-induced testicular degeneration and restoring the normal histological structure with physiological properties of testicular tissue in streptozotocin (STZ)-induced DM. High-resolution ultra-performance liquid chromatography-mass spectrometry (UHPLC-ESI-Orbitrap-MS) analysis was employed to analyze the compounds present in EH-EtOH. The protective effect of EH-EtOH against testicular degeneration in the rat model of DM was evaluated by measuring improvements in blood glucose levels, body weight, testicular inflammation, oxidative damage, testicular microcirculation impairment, and apoptosis of testicular cells induced by STZ. The chemical profiling of EH-EtOH revealed the presence of 52 compounds, including phenolic acids, flavonoids, coumarins, phloroglucinols, and triterpenes. Notably, this study identified isovitexin-C-hexoside, isorhamnetin-O-hexoside, diosmetin, and halfordin for the first time in Euphorbia species. Treatment with EH-EtOH effectively mitigated the damage caused by STZ, as evidenced by restored testosterone (T4) levels and antioxidant capacity, reduced expression of pro-inflammatory cytokines, improved testicular microcirculation, and inhibition of apoptosis in the testes. Conclusions These results emphasize the potential therapeutic effect of E. heterophylla on DM related to male infertility and reproductive dysfunctions via its antioxidant/angiogenetic /anti-apoptotic effect.