Scientific Reports
<p><em>Scientific Reports</em> publishes original research in all areas of the natural and clinical sciences. We believe that if your research is scientifically valid and technically sound then it deserves to be published and made accessible to the research community.</p> <p>By publishing with us, your research will get the coverage and attention it deserves. Open access and continuous online publication means your work will be published swiftly, ready to be accessed by anyone, anywhere, at any time. Article Level Metrics allow you to follow the conversations your work has started.</p>
Scientific Reports - Publisher Correction: Inter-reader agreement for diagnosing thymic cysts on chest MRI in two tertiary referral centers
Scientific Reports - Publisher Correction: Investigating the modulatory effects of lactoferrin on depressed rats through 16S rDNA gene sequencing and LC–MS metabolomics analysis
Scientific Reports - Publisher Correction: Scattering of Sculpted Light in Intact Brain Tissue, with implications for Optogenetics
Scientific Reports - Publisher Correction: First principles design of multifunctional spintronic devices based on super narrow borophene nanoribbons
Scientific Reports - Author Correction: Comparative analysis of amino acid sequence level in plant GATA transcription factors
Scientific Reports - Author Correction: Energy optimization and plant comfort management in smart greenhouses using the artificial bee colony algorithm
Scientific Reports - Publisher Correction: Decreased PD-L1 contributes to preeclampsia by suppressing GM-CSF via the JAK2/STAT5 signal pathway
Scientific Reports - Publisher Correction: Molecular diversity and genetic potential of new maize inbred lines across varying sowing conditions in arid environment
Heavy metal ions are a major source of pollution in the environment since they are nondegradable and accumulate in human bodies, creating serious threats to human health and the ecosystem. Conventional heavy metal ion detection techniques are not generally suitable for onsite or rapid detection, as they frequently require highly sophisticated and costly equipment, expert operation, laborious sample preparation, restricted testing conditions, and professional operators. As a result, they are not well suited for real-time and quick detection in the field. Advances in chemical sensing and electronic communication have resulted in the invention of wireless chemical sensors. Smartphones are widely used along with sensors, including test strips, sensor chips, and portable detectors, for biochemical detection owing to their versatility and affordability. The development of chemical sensor technologies will lead to the fabrication of more compact, lightweight, affordable, adaptable, and long-lasting devices. Considering these shortcomings, we propose that chemical sensor systems that are coupled with wireless technology and smartphones represent an important component of the sensor Internet of Things. In this context, the easy-to-synthesize ligand 2-(2-(pyridin-2-yl)hydrazono)-1 H-indene-1,3(2 H)-dione (PHID) has been explored for sensing divalent Hg2+ and Cu2+.
This paper presents the design of a circularly polarized millimeter-wave (mm-wave) metasurface (MTS) antenna. The Characteristics Modes Analysis (CMA) is employed to examine various modes within the unit-cell design of the proposed metasurface. Based on a thorough analysis, two orthogonal TM modes with a broadside radiation pattern were identified. These modes were then simultaneously excited on a single substrate using simple coplanar waveguide (CPW) magnetic dipoles resulting in circular polarization (CP). Further, it has been demonstrated that the sense of polarization can be easily reconfigured for realizing multiple-input-multiple-output (MIMO) antenna with polarization diversity. Both the single MTS antenna and the MIMO design are characterized numerically and experimentally. The simulated and measured results show that impedance bandwidth (S11 ≤ − 10 dB) of the antenna is from 25 to 30.8 GHz. The axial ratio (AR) below 3 dB is from 26 to 31 GHz with a stable broadside radiation pattern. The proposed design features a low profile and simple geometry which is extremely appropriate for applications in the mm-wave band.
Hypoparathyroidism is the inability of parathyroid hormone (PTH) to maintain calcium homeostasis. Patients with post-surgical hypoparathyroidism may have an increased risk of mortality; there is clinical and molecular evidence of the effects of this condition on the cardiovascular system. The aim of this study was to evaluate arterial stiffness by measuring the carotid-femoral pulse wave velocity (PWV) in post-surgical hypoparathyroidism patients. A cross-sectional study was conducted with 30 post-surgical hypoparathyroidism patients and 25 volunteers from the Endocrinology Outpatient Clinic of the Medical School. The SphygmoCor system was used to evaluate arterial stiffness by analyzing the PWV. The mean ages of the hypoparathyroidism (50.4 years) and control individuals (49.6 years) were similar. The mean PWVs were 8.7 and 7.5 m/s in the Hypoparathyroidism and Control groups, respectively (p-value = 0.084). Considering only normotensive patients, PWV was statistically higher in the Hypoparathyroidism Group (7.6 versus 6.5 m/s; p-value = 0.039). For this group, serum ionized calcium, phosphorus, and the calcium x phosphorus product levels were positively associated to PWV. Hypoparathyroidism increases arterial stiffness as assessed by PWV. Serum ionized calcium, phosphorus, and the calcium x phosphorus product are affected. A more effective investigative and therapeutic approach for patients with hypoparathyroidism can help control cardiovascular risk.
In this study, we aim to explore the soliton phenomena in fully nonlinear complex perturbed Gerdjikov–Ivanov equation (PGIE). This model concerns with optical pulse transmission pursuant to perturbation impacts encompassing significant uses in optical fibers, especially, photonic crystal fibers. We employ the Riccati modified extended simple equation method, which has never been employed for this model previously, to acquire novel and distinct optical soliton solutions. To visually evaluate the dynamics of derived optical soliton solutions, several 3D, 2D, and contour graphics are incorporated. These visuals reveal a range of quasi-periodic type optical soliton phenomena, that include internal envelope, hump, cnoidal, periodic, and fractal solitons. In addition to including additional soliton dynamics into the model, the results show how these dynamics interact to affect the system’s overall behavior.
Retroperitoneal soft tissue sarcoma (RSTS) is a rare type of cancer with limited treatment options. Achieving complete resection with negative margins is one of the most significant prognostic factors for RSTS survival. The UltraProbe is a handheld point probe Raman spectroscopy system that significantly decreases the imaging time compared to the probe systems currently used. This study aims to determine the performance of the UltraProbe in detecting STS in an in vivo environment during their resection. Thirty patients were recruited at Maisonneuve-Rosemont Hospital, Montreal, Canada. Raman spectra were acquired during STS resection using the instrument. A machine learning random forest classification algorithm was developed to predict the diagnosis associated with new Raman spectra: STS or healthy tissue. The classification of Raman spectra as well-differentiated liposarcomas or normal adipose tissue was performed with a sensitivity of 94%, specificity of 95%, and accuracy of 94%. The classification of spectra as well-differentiated and dedifferentiated liposarcomas or normal adipose tissue was performed with a sensitivity of 90%, specificity of 93%, and accuracy of 90%. The classification of spectra as non-liposarcoma STS or protein-rich non-adipose tissue was performed with a sensitivity of 87%, specificity of 81%, and accuracy of 87%.
Field test kits are indispensable tools for strengthening community-based water quality monitoring and surveillance programs. However, the reliability of field test kits is important, as these kits are being used to test large number of water sources in developing countries due to insufficient laboratory resources. A field test kit validation protocol is essentially needed to strengthen the quality control mechanism during the kit production and procurement stages. The technical efficiency of a kit is the most important criterion for assessing its sensitivity and specificity to accurately detect the parameter of interest. The adequacy, safety and information to users are also very significant aspects to ensure effective and safe usage of kits. In the present study, arsenic field test kits were evaluated in the laboratory as well as at field by performing in situ testing. Statistical weight was assigned to each parameter, such as technical efficiency, adequacy, safety and information, to estimate the ‘individual parameter weight’, and then an importance factor was applied to estimate the cumulative parameter weight to assess the effectiveness of the field test kits. The overall arsenic testing efficiency, in the case of the most effective kit when used in the field, was estimated at 55.0% when compared with accurate testing results in the ± 5% range and 90.0% when kit findings were compared with accurate testing results in the ± 10% range. Considering variable and dynamic field conditions, variation tolerance between kit results in the field and accurate laboratory results in the ± 10% range seems to be appropriate. This study provides inputs for the development of a protocol for the reliability assessment of field test kits.
Recent environmental changes due to land-use and climate change threaten biodiversity and the ecosystem services it provides. Understanding the true scope of these changes is complicated by the lack of historical baselines for many of the interactions underpinning ecosystem services, such as pollination, or disservices, such as disease spreading. To assess changes in such services, it is vital to find ways of comparing past and current interactions between species. Here, we focus on interactions between honey bees – one of the world’s most important agricultural pollinators, the plants they visit, and the microbes they encounter in the environment. DNA in honey offers insights into the contemporary interactions of honey bees. Old honey samples could serve to describe honey bees’ interactions in previous decades, providing a baseline against which to assess changes in interactions over time. By identifying the taxonomic origin of plant, bacterial and fungal DNA in fifty-year-old honey samples, we show that plant DNA can reveal which plants honey bees visited in the past. Likewise, microbe DNA records the microbes, including pollinator and plant pathogens, honey bees encountered and possibly spread. However, some differences in the DNA recovered between old and new honey suggest that differences in DNA degradation of different microbes could bias naive comparisons between samples. Like other types of ancient samples, old honey may be most useful for identifying interactions that historically occurred and should not be taken as proof that an interaction did not occur. Keeping these limits of the data in mind, time series of honey may offer unique information about how honey bees’ associations with flowers and microbes have changed during decades of environmental change.
Online participant recruitment is a cornerstone of modern psychology research. While this offers clear benefits for studying individual differences in cognitive abilities, test performance can vary across lab-based and web-based settings. Here we assess the stability of normative test scores across popular online recruitment platforms and in-person testing, for three standard measures of face identity processing ability: the GFMT2, CFMT+ , and MFMT. Participants recruited via Amazon Mechanical Turk (MTurk) scored approximately 10 percentage points lower in all tests compared to those recruited through Prolific and university students tested in the lab. Applying stricter exclusion criteria based on attention checks resulted in notably higher exclusion rates for the MTurk group (~ 62%) compared to the Prolific group (~ 22%), yet even after exclusion, some test scores remained lower for MTurk participants. Given that the GFMT2 subtests were developed using MTurk participants, we provide updated normative scores for all subtests (GFMT2-Short, GFMT2-Low, GFMT2-High) and further recommendations for their use. We also confirm the robust psychometric properties of the GFMT2-Short and GFMT2-High, demonstrating strong test–retest reliability, convergent validity with other established tests, and high diagnostic value in identifying super-recognisers. The GFMT2 subtests are freely available for use in both online and in-person research via www.gfmt2.org .
Scientific Reports - Author Correction: Fault correcting adder design for low power applications
Scientific Reports - Author Correction: The anticancer activity of fucoidan coated selenium nanoparticles and curcumin nanoparticles against colorectal cancer lines
Scientific Reports - Author Correction: Protective effect of low-dose lactulose in dextran sulfate sodium induced ulcerative colitis model of rats
Scientific Reports - Author Correction: Characterisation of a cyclic peptide that binds to the RAS binding domain of phosphoinositide 3-kinase p110α
Scientific Reports - Author Correction: Partner relationships, hopelessness, and health status strongly predict maternal well-being: an approach using light gradient boosting machine
Scientific Reports - Author Correction: Alzheimer’s disease may develop from changes in the immune system, cell cycle, and protein processing following alterations in ribosome function
Scientific Reports - Author Correction: Universal conditional networks (UniCoN) for multi-age embryonic cartilage segmentation with sparsely annotated data
Adolescent idiopathic scoliosis (AIS) is a three-dimensional lateral and torsional deformity of the spine, affecting up to 5% of the population. Traditional scoliosis screening methods exhibit limited accuracy, leading to unnecessary referrals and exposure to ionizing radiation from x-ray examinations. The 3D markerless surface topography (ST) technique quantifies trunk asymmetry and can be a potential scoliosis screening tool. However, differences in trunk asymmetry between individuals with scoliosis and those with a typically developing spine have yet to be thoroughly studied. Using the ST method, this study aims to distinguish adolescents with AIS from those with typically a developing spine. Participants aged 10 to 18 years, comprising of 285 individuals with confirmed AIS and 273 with typically developing spines, were included in the study (total scans including follow-ups: 693 for the AIS group and 298 for the control group). The positive for AIS group was identified through radiographic exams, specifically with curves ranging from 10° to 45°, while the negative (control) group qualified if their scoliometer test measured less than 7° and they had no known scoliosis diagnosis. The dataset comprised of surface torso scans captured either using stationary Minolta cameras or with the Structure sensor. ST analysis involved the reflection of the 3D geometry of the torso, aligning it with the original torso by minimizing the distance between corresponding points. Deviations between the original and reflected torso over the back surface and torso surface depth were mapped onto 102 × 102 grids. A convolutional neural network (CNN) was developed using deviations and depth (distance between the back surface and frontal plane) maps as inputs to classify the torso surface of typically developing adolescents and those with AIS. 10-fold cross-validation was applied during model development. 20% of the data was used as a holdout for final testing. Classification results of the proposed model were compared to the ground truth. The average training and validation accuracy across the ten folds was 100% and 94%, respectively. The classifications from the testing sets using the best performing model from the 10-fold cross-validation obtained accuracy, sensitivity, and specificity of 95%, 97%, and 90%, respectively. The positive likelihood ratio (PLR) of the testing set was 9.7. Likewise, a negative likelihood ratio (NLR) of 0.032 was also attained. The model sensitivity for detecting curves with Cobb greater than 25° was 99%. The sensitivity for detecting mild cases (Cobb < 25°) was 96%. The proposed CNN predictive model to detect AIS using ST showed excellent classification results. Markerless surface topography can serve as a dependable and non-invasive method for screening AIS.
Emerging evidence has been linking changes in the early-life gut microbiome and neurodevelopmental outcomes. The founder bacteria that first colonize the infant’s gut determine the microbial succession that signals host tissues and impact development including the brain. Here we investigated the association between the meconium microbiome and neurobehavior. To this end, we surveyed the 16S rRNA gene on meconium samples and assessed behavioral outcomes at six-months of age by the Denver Developmental Screening Test II (DDST-II). Among the four behavioral domains investigated, the personal-social domain was associated with significant differences in meconium bacterial beta diversity (unweighted UniFrac; R2 0.078, p = 0.021) and reduced alpha diversity (β = −2.290, 95% CI = −4.212; CI = −0.368), after adjustment for gestational antibiotics, preterm delivery, and delivery mode. Besides, this altered neurobehavior (failing to meet the milestone) was associated with overrepresented Ruminococcaceae, Christensenellaceae, and Eubacterium, Treponema, Senegalimassilia, Ruminiclostridium, Roseburia, Romboutsia, Prevotella, and Veillonella seminalis. Predicted functional genes showed reduced abundance in association with altered neurobehavior (all q < 0.15). Fine and gross motor skills presented no associations with the microbiome. This pilot study shows associations between the first gut microbiome and behavioral outcomes that deserve further studies in different neonate populations.
Truffles are an iconic food that have long held high regard. Here we explore the seasonality and eco-physiological interactions affecting truffle quality and quantity across time and space. Collaborating with professional truffle hunters working eight different locations, detailed metrics of 3180 recovered truffles from 236 hunt events and spanning a full fruiting period, were recorded. Contrary to expectations, truffle weight showed no correlation with climate variables, suggesting a limited influence of environmental factors such as temperature and precipitation on truffle size. We also found that truffle maturity and damage from mycophagy were strongly linked, with deeper truffles being more mature but also more susceptible to damage. Finally, we observe that scent-dog behaviour significantly impacts the quantity and quality of recovered truffles, and we address the necessity of considering this in truffle ecophysiology studies. Alongside advances in our biological understanding, we make recommendations of how training methods can be improved to lead to greater detection and quality targeting with immediate socioeconomic impact. These findings highlight the complex interplay between truffle physiology, environmental factors, and human and animal behaviours, emphasizing the need for further considered research to enhance our understanding of truffle biology and to improve truffle cultivation practices.
During plastic deformation of metals and alloys, dislocations self-organise in cells, which subsequently continuously decrease in size. How and when these processes take place has remained elusive, because observations of the structural dynamics in the bulk have not been feasible. We here present X-ray diffraction microscopy sequences of the structural evolution during tensile deformation of a mm-sized aluminium (111) single crystal. The formation and subsequent development of 40,000 cells are visualised. The cells form in a stochastic, isotropic and uncorrelated manner already at 1% strain. We reveal that the cell size and dislocation density distributions are log-normal and bi-modal distributions, respectively, exhibiting scaling and maintaining a fixed volume ratio between cell interior and cell boundary. This insight leads to an interpretation of the formation and evolution steps in terms of universal stochastic multiplicative processes. This work will guide dislocation dynamics modelling, as it provides unique dynamic data and understanding.
Recent advancements in deep learning have significantly enhanced the segmentation of high-resolution microcomputed tomography (µCT) bone scans. In this paper, we present the dual-branch attention-based hybrid network (DBAHNet), a deep learning architecture designed for automatically segmenting the cortical and trabecular compartments in 3D µCT scans of mouse tibiae. DBAHNet’s hierarchical structure combines transformers and convolutional neural networks to capture long-range dependencies and local features for improved contextual representation. We trained DBAHNet on a limited dataset of 3D µCT scans of mouse tibiae and evaluated its performance on a diverse dataset collected from seven different research studies. This evaluation covered variations in resolutions, ages, mouse strains, drug treatments, surgical procedures, and mechanical loading. DBAHNet demonstrated excellent performance, achieving high accuracy, particularly in challenging scenarios with significantly altered bone morphology. The model’s robustness and generalization capabilities were rigorously tested under diverse and unseen conditions, confirming its effectiveness in the automated segmentation of high-resolution µCT mouse tibia scans. Our findings highlight DBAHNet’s potential to provide reliable and accurate 3D µCT mouse tibia segmentation, thereby enhancing and accelerating preclinical bone studies in drug development. The model and code are available at https://github.com/bigfahma/DBAHNet .
We retrospectively analyzed the degree of stenosis in patients with acute cerebral infarction (CI) to investigate the correlation between C-reactive protein (CRP)/ albumin ratio and intracranial atherosclerotic stenosis (ICAS). Meanwhile, the differentially expressed genes (DEGs) in CI were identified through two Microarray profile GSE202518 and GSE180470. The receiver operating characteristics (ROC) curve analysis were performed to evaluate the sensitivity and specificity of CRP/ albumin ratio for the diagnosis of ICAS. Binary logistic regression models were used to examine the relationship between these biomarkers and the degree of ICAS, adjusting for potential confounders. The level of CRP/ albumin ratio in high group was significantly higher than that in low group. The area under the curve (AUC) of CRP/ albumin ratio for the diagnosis of ICAS was 0.6526 (95% CI, 0.5737 to 0.7316) in serum. TMTC1 was found to be highly expressed in high group, and the AUC of TMTC1 for the diagnosis of ICAS was 0.6853 (95% CI, 0.6085 to 0.7622) in serum. Moreover, the combination of CRP/ albumin ratio and TMTC1 enhanced the diagnosis of ICAS with AUC of 0.708 (95% CI, 0.633 to 0.783). High levels of CRP/ albumin ratio and TMTC1 expression were associated with the degree of ICAS, and may be potential diagnostic and prognostic markers for the ICAS.
18F-SPAL-T-06 and 18F-C05-05 are two novel positron emission tomography (PET) radioligands targeting α-synuclein fibrils. Our study aimed to evaluate the biodistribution, safety, and radiation dosimetry of each tracer in humans. Biodistribution and radiation dosimetry studies were carried out with two healthy volunteers for each tracer, 18F-SPAL-T-06 (one female and one male volunteer, both aged 63 years) and 18F-C05-05 (one female and one male volunteer, aged 63 and 73 years, respectively). After injection of either tracer, dynamic PET images were acquired from head to upper thigh. Effective dose of each tracer was estimated using OLINDA/EXM Version 2.2. Injection of either of the tracers caused no adverse effects. Greatest uptake of both tracers was observed in the liver and small intestine. The estimated absorbed doses were highest in the biliary tract, followed by the lower large intestinal wall. Effective doses were 35.9 µSv/MBq for 18F-SPAL-T-06 and 30.5 µSv/MBq for 18F-C05-05. 18F-SPAL-T-06 and 18F-C05-05 are safe for in vivo PET imaging of humans. Their mean effective doses were 6.6 mSv for 18F-SPAL-T-06 and 5.6 mSv for 18F-C05-05 when 185 MBq of either tracer was given to a subject, and they were comparable to other amyloid and tau PET tracers labelled with 18F. Trial registration Trial registration number: jRCTs031210180, Registered date: 2nd July 2021 (18F-SPAL-T-06) https://jrct.niph.go.jp/en-latest-detail/jRCTs031210180 and Trial registration number: jRCTs031220123, Registered date: 9th June 2022 (18F-C05-05) https://jrct.niph.go.jp/en-latest-detail/jRCTs031220123 .
Metformin associated lactic acidosis (MALA) and severe acute kidney injury (AKI) is a life-threatening condition, often requiring renal replacement therapy. However, the optimal renal replacement therapy regimen in this setting remains unclear. Furthermore, limited data exist on the use of regional citrate anticoagulation, as severe hyperlactatemia is associated with increased risk of citrate accumulation. We retrospectively analyzed the medical records of all patients with MALA and severe AKI requiring renal replacement therapy at our hospital between June 2011 and December 2021. All patients were treated with high dose CVVHDF. Anticoagulation was achieved using either heparin or regional citrate anticoagulation. A total of 27 patients with MALA and AKI requiring renal replacement therapy were identified. In all patients, CVVHDF was started within one hour of the diagnosis. Four deaths were recorded, resulting in an overall mortality rate of 14.8%. In the remaining 23 patients (85.2%), we observed the correction of the metabolic disorder and the recovery of renal function that allowed for the discontinuation of dialysis. Mean lactatemia at diagnosis was 12.9 mmol/l (range 7.0–24.0) and mean pH 6.99 (range 6.50–7.22). CVVHDF mean effluent rate was as high as 52.1 ml/kg/h. In thirteen patients regional citrate anticoagulation was safely employed. In our experience, CVVHDF prescribed at the appropriate dose have yielded favorable results, in terms both of patient survival and metabolic control of the disease. Regional citrate anticoagulation can be safely used in selected cases.
Scientific Reports - Publisher Correction: Enhancing black mulberry storage with sodium caseinate and gum tragacanth edible films
The development of efficient parallelization strategies for numerical simulation methods of fluid, gas and plasma mechanics remains one of the key technology challenges in modern scientific computing. The numerical models of gas and plasma dynamics based on the Navier-Stokes and electrodynamics equations require enormous computational efforts. For such cases, the use of parallel and distributed computing proved to be effective. The Grid computing environment could provide virtually unlimited computational resources and data storage, convenient task launch and monitoring tools, graphical user interfaces such as web portals and visualization systems. However, the deployment of traditional CFD solvers in the Grid environment remains very limited because basically it requires the cluster computing architecture. This study explores the applicability of distributed computing and Grid technologies for solving the weak-coupled problems of fluid, gas and plasma mechanics, including techniques of flow separation control like using plasma actuators to influence boundary layer structure. The adaptation techniques for the algorithms of coupled computational fluid dynamics and electrodynamics problems for distributed computations on grid and cloud infrastructure are presented. A parallel solver suitable for the Grid infrastructure has been developed and the test calculations in the distributed computing environment are performed. The simulation results for partially ionized separated flow behind the circular cylinder are analysed. Discussion includes some performance metrics and parallelization effectiveness estimation. The potential of the Grid infrastructure to provide a powerful and flexible computing environment for fast and efficient solution of weak-coupled problems of fluid, gas and plasma mechanics has been shown.
Seismic rupture in carbonate rocks influences fault friction behavior through thermal evolution and mineral reactions. Focusing on the 1959 Mw 7.2 Hebgen Lake event in western Yellowstone, Montana, the largest earthquake on a normal fault in the United States, we analyze fault rock microstructures and mineralogical changes to constrain frictional heating on the fault plane. We combine thermal maturity of organic matter, magnetic fabric, and thermomagnetic methods with scanning electron microscopy to unravel variations in peak frictional temperature along the fault slip surface. The mineral changes caused by coseismic heating (e.g., nanocalcite formation or goethite to hematite reaction) occur in patches along the fault mirror, hence reflecting considerable differences in frictional heat. While coseismic thermal heterogeneities have been reported in other rock types, this is the first time they are documented and quantified specifically in carbonates. Furthermore, these results provide new mineralogical criteria to quantify coseismic frictional heat in natural faults at temperatures lower than that of decarbonation and highlight the need to consider coseismic friction processes at a scale larger than most deformation experiments. For example, we document the critical role played by fault plane attitude (dip) at the scale of a few tens of centimeters in production of frictional heat. Our results emphasize that while coseismic decarbonation dynamically weakens carbonate-hosted faults, it may generally not occur along an entire fault plane.
Parkinson’s disease is a neurodegenerative disorder that is associated with aging, leading to the progressive deterioration of certain regions of the brain. Accurate and timely diagnosis plays a crucial role in facilitating optimal therapy and improving patient outcomes. This study presents an innovative approach to identify Parkinson’s disease (PD) through the examination of audio waves using Feature Based - Deep Neural Network (FB-DNN) techniques. Autoencoder, a specific form of Artificial Neural Network (ANN) that is designed to excel in the task of feature extraction, is utilized in our study to effectively capture complex patterns present in audio data. Deep Neural Networks (DNNs) are utilized in the task of classification, using the capabilities of deep learning (DL) to differentiate between audio samples that exhibit Parkinson’s disease (PD) and those that do not. The deep neural network (DNN) model is trained using the retrieved data, allowing it to effectively distinguish minor variations in voice characteristics that are linked to Parkinson’s disease. The suggested methodology not only enhances the precision of diagnosis but also enables prompt identification, perhaps resulting in more efficacious treatment methodologies. The present study introduces a potentially effective approach for the automated and non-intrusive identification of Parkinson’s disease through the analysis of audio data. The integration of Autoencoder-based feature extraction with Deep Neural Networks (DNN) presents a dependable and easily accessible solution for the early detection and continuous monitoring of Parkinson’s disease. This approach has promise for significantly improving the quality of life for persons affected by this condition. The implementation in Python was conducted as part of our experimentation. Upon analyzing the accuracy, it became apparent that the Feature-Based Deep Neural Network (FB-DNN) exhibited superior performance compared to the other models. Notably, the FB-DNN achieved the highest accuracy score of 96.15%.
The growing demand for clean energy has highlighted plant biomass as a valuable alternative, supporting sustainable development goals. Elephant grass (EG) is a promising feedstock due to its adaptability to diverse soils and climates, high dry matter production, and substantial energy yield. This study aimed to evaluate and characterize six selected EG genotypes (BRS Capiaçu, T_23.1, T_23.2, T_41.2, T_47.1, and T_51.5) based on their broth productivity and energy yield. Analysis of the broth’s yield and physicochemical properties revealed that the by-product extracted from the biomass had a high residual energy value. Additionally, extracting the broth reduces the grass’s biomass moisture content, enhancing its calorific value and improving the bagasse quality for combustion in boilers, thus optimizing energy production. This study demonstrates that the promising EG genotypes T_47.1, T_41.2, and T_23.1 presented relevant energy values ranging from 4248.12 to 4304.06 kcal kg− 1 of bagasse and thus are suitable for energy production through direct combustion. The extracted broth is a valuable residual energy source that can be utilized industrially after anaerobic digestion. Future research should focus on the environmental and economic effectiveness of EG broth as an energy source from waste and its potential for biogas production.
This study investigates the complex relationships between globalization, economic growth, urbanization, and ecological footprint in the context of advancing the United Nations Sustainable Development Goals (SDGs). Employing a club convergence framework, we evaluate global SDG Index from 2000 to 2023 for 149 countries with 3212 observations, identifying five converging clubs and one non-converging group. Our analysis demonstrates that higher GDP per capita and various dimensions of globalization positively impact SDG outcomes, whereas rapid urbanization and expansive ecological footprints exert negative influences. This research highlights the critical need for tailored policy interventions that address the distinct challenges encountered by different country clusters to bolster sustainable development efforts. Our findings reveal the multifaceted nature of sustainable development, indicating that economic growth and globalization can support SDG advancement if their detrimental effects are effectively mitigated. The study offers valuable insights for crafting national and global strategies to expedite progress towards the SDGs, emphasizing the importance of harmonizing economic, social, and environmental priorities.
Chronic exposure to nicotine is related to low activity in the prefrontal cortex and insular hyperactivity in smokers. Therefore, addiction has been the target of experimental studies in aerobic exercise (AE) and transcranial direct current stimulation (tDCS). Thus, the objective of this study was to verify the effect of AE and anodal tDCS at F4 and cathodal at T3 on craving, motivation to change smoking behaviour (MCSB) and brain reactivity (BR) in smokers. The sample consisted of 41 chronic smokers distributed into four groups: tDCS (G1), AE (G2), tDCS combined with AE (G3) and sham tDCS combined with AE (G4). All volunteers underwent 5 consecutive sessions of the intended intervention. Before starting the intervention protocol and after the last intervention session, the volunteers answered questionnaires and underwent an electroencephalogram exam, to evaluate the variables investigated. The results demonstrated that AE, when associated with active tDCS, was effective in promoting a reduction in craving (p < 0,05), cigarette consumption (p < 0,05), and BR (p < 0,05) during exposure to smoking cues, in addition to increasing MCSB (p < 0,05). Therefore, only when associated with AE, tDCS was able to modulate positive effects on smoking.
Cholangiocarcinoma (CCA) is a highly lethal hepatobiliary malignancy, with prognosis is influenced by anatomical subtypes and etiological factors. This study successfully established three CCA cell lines: KKU-097, KKU-466, and KKU-610, from the primary tumors of patients in liver fluke-endemic areas. These cells represent the perihilar CCA (pCCA) and intrahepatic CCA (iCCA) subtypes. Comprehensive analyses, including histopathology, molecular profiling, biomarkers, cancer phenotype characterization, and drug sensitivity testing with standard chemotherapeutics, were conducted. Whole-exome sequencing was performed to explore genetic alterations. All three cell lines exhibited adherent growth with an epithelial morphology and positive expression of the bile duct epithelial markers CK-7 and CK-19. Cytogenetic analysis revealed highly complex hypertriploid karyotypes with multiple chromosomal aberrations. Among the cell lines, KKU-610 demonstrated higher growth and invasion rates, whereas KKU-466 and KKU-097 cells exhibited less aggressive phenotypes. Drug sensitivity testing demonstrated relative resistance to gemcitabine as a monotherapy and in combination with cisplatin in all three cells. Genomic profiling identified targetable mutations, highlighting these new cell lines as valuable models for investigating the pathogenesis of CCA and evaluating therapeutic strategies.
This study examined the number of contractions required for an isometric plantar flexion familiarization. Twenty-six males were separated into two independent Groups: Group A: where five contractions were initiated on the dominant limb (right) followed by the contralateral limb; and Group B, initiated by the non-dominant limb (left) followed by the dominant limb. Participants carried out a 5-s maximum voluntary contraction (MVC), with an interpolated twitch administered to the tibial nerve. In Group A, both the dominant and non-dominant limbs required two contractions for familiarization, whereas in Group B, the dominant limb required two contractions, and the non-dominant limb required three (p < 0.05). A strong relationship between MVC and voluntary activation (VA) was observed in Group A for the D (r = 0.91, p < 0.05) and in Group B for the ND limb (r = 0.99, p < 0.05). The results demonstrated evidence of cross-limb transfer from the dominant to the non-dominant limb (p < 0.05). This phenomenon implicates central involvement, substantiated by VA responses that mirror the changes in MVC. Practitioners and researchers should consider the impact of cross-limb transfer during a single familiarization session when assessing strength to avoid overestimation of the gains. Future cross-education/cross-limb transfer studies could investigate the central mechanisms involved during familiarization.
Extensive exposure to specific kinds of imagery tunes visual perception, enhancing recognition and interpretation abilities relevant to those stimuli (e.g. radiologists can rapidly extract important information from medical scans). For the first time, we tested whether specific visual expertise induced by professional training also affords domain-general perceptual advantages. Experts in medical image interpretation (n = 44; reporting radiographers, trainee radiologists, and certified radiologists) and a control group consisting of psychology and medical students (n = 107) responded to the Ebbinghaus, Ponzo, Müller-Lyer, and Shepard Tabletops visual illusions in forced-choice tasks. Our results show that medical image experts were significantly less susceptible to all illusions except for the Shepard Tabletops, demonstrating superior perceptual accuracy. These findings could possibly be attributed to a stronger local processing bias, a by-product of learning to focus on specific areas of interest by disregarding irrelevant context in their domain of expertise.
Scientific Reports - Publisher Correction: HDL-ACO hybrid deep learning and ant colony optimization for ocular optical coherence tomography image classification
One of the most established approaches to navigate pedicle screws is the planning and alignment (PA) method. Thereby a trajectory and associated entry point (EP) is planned and navigated after referencing to patient anatomy. However, deviations from the planned EP potentially lead to an altered screw position. The aim of this study was to investigate the influence of these EP deviations and to examine possible alternative methods. The merits of two new points of reference (screw tip point STP and midpoint MP) were therefore analyzed. STP represents the point on the optimal screw tip, MP the point at the center/midportion of the pedicle at its narrowest portion. The adapted screw trajectory was defined as the directional vector from any chosen EP to the STP or MP. First, computer simulations were used to evaluate the performance of these new approaches. Subsequently, the navigation technique yielding more acceptable screws in case of an EP deviation was analyzed on phantom-sawbone models. Both new methods showed a significantly larger number of possible screw trajectories in the simulations (p < 0.01). Even with a deliberate deviation of 4.5 mm (IQR 3.3) from the optimal EP, a perforation-free screw diameter of 4.9 mm (IQR 5.7 mm) could be achieved using the new navigation techniques. The simulated perforations were mainly located laterally with a median of 8.45 mm (IQR 3.95) distance to the medial pedicle wall. The PA method seems to be susceptible to EP deviations. The STP and MP methods are possible improvement mechanisms to overcome this disadvantage.
Scientific Reports - Publisher Correction: Drug resistant Mycobacterium tuberculosis strains have altered cell envelope hydrophobicity that influences infection outcomes in human macrophages
Scientific Reports - Author Correction: Cep78 knockout causes sterility and oligoasthenoteratozoospermia in male mice
Scientific Reports - Retraction Note: Experimental and TDDFT materials simulation of thermal characteristics and entropy optimized of Williamson Cu-methanol and Al2O3-methanol nanofluid flowing...
Existing modified-Nix-Gao models have been developed to accurately describe the descending indentation size effect (ISE). This raises the question of whether the modified-Nix-Gao models can describe other types of ISE. In this paper, because Nix-Gao-Feng and Nix-Gao-Haušild models are exceptionally straightforward and user-friendly, the two modified-Nix-Gao models are chosen to make a systematic study. To our surprise, the parameters analysis indicates that the two modified-Nix-Gao models are able to describe the transition of descending to ascending ISE. The Nix-Gao-Feng is also capable of predicting a transition in hardness from hardening to softening at shallow indentation depth. However, the two modified-Nix-Gao models does not capture the ascending ISE. Further study reveals that the mechanism behind of this novel finding is attributed to the competition between the relative rate of change of k3 (k is the ratio of the effective radius to the contact radius) and indentation depth with indentation depth. However, two modified-Nix-Gao models gradually transition to a dislocation-dominated descending ISE as indentation depth increases, resulting in the inability of both models to reflect the ascending ISE. The evaluation indicates that the two modified-Nix-Gao models can successfully predict the transition of descending to ascending ISE of different materials, and the minimum determination coefficients (DCs) of both models are more than 0.8 for different materials. Although the DCs of both models are relatively high for some results of the ascending ISE, qualitative comparison and parameter analysis reveal that they fail to fully capture the ascending ISE. This implies that quantitative comparison alone is insufficient to reasonably reflect the predictive accuracy of the models.
Patients with multiple comorbidities and those undergoing complex cardiac surgery may experience extubation failure and reintubation. The aim of this study was to establish an extubation prediction model using explainable machine learning and identify the most important predictors of extubation failure in patients undergoing cardiac surgery. Data from 776 adult patients who underwent cardiac surgery and were intubated for more than 24 h were obtained from the Medical Information Mart for Intensive Care (MIMIC)-IV database. The primary endpoint was extubation failure according to the WIND criteria, with 205 patients experiencing extubation failure. The data was split into a training set (80%) and a test set (20%). The performance of the XGBoost algorithm was the highest (AUC 0.793, Mean Precision 0.700, Brier Score0.150), which was better than that of logistic regression (AUC 0.766, Mean Precision 0.553, Brier Score0.173) and random forest (AUC 0.791, Mean Precision 0.510, Brier Score 0.181). The most crucial predictor of extubation failure is the mean value of the anion gap in the 24 h before extubation. The other main features include ventilator parameters and blood gas indicators. By applying machine learning to large datasets, we developed a new method for predicting extubation failure after cardiac surgery in critically ill patients. Based on the predictive factors analyzed, internal environmental indicators and ventilation characteristics were important predictors of extubation failure. Therefore, these predictive factors should be considered when determining extubation readiness.
Transseptal puncture (TSP) is widely used in catheter-based cardiac interventions to gain left atrial (LA) access, but its workflow has remained largely unchanged and is still a source of serious complications. Pulsed field ablation (PFA) for pulmonary vein isolation (PVI) has been shown to be at least comparable with radiofrequency ablation (RFA) in terms of safety and efficacy. However, PFA catheter delivery to the LA typically requires a standard TSP and an over the wire sheath exchange which can limit workflow and lengthen procedure time—a shorter procedure time being a proposed advantage of PFA over RFA. This study aimed to evaluate a simplified workflow for direct TSP using the PFA sheath (Faradrive, Boston Scientific). We retrospectively analyzed 166 patients undergoing PVI with PFA in our center. TSP was performed by combining a 16.8F PFA sheath (Faradrive, Boston Scientific) and a RF-guidewire (Versacross, Boston Scientific) as a direct approach without the need over an over-the-wire exchange. The patient population had a mean age of 63.8 ± 11.3 years and was 72.3% male (n = 119/166). TSP was achieved in all patients (n = 166, 100%) without complication. The mean time from groin puncture to LA ablation catheter delivery was 16.2 ± 5.5 min with a mean fluoroscopy time of 15.7 ± 12.7 min. Dilator and sheath crossed the septum with no significant resistance in all cases (n = 168, 100%). The RF-guidewire allowed catheters to be tracked back up to the superior vena cava without exchange in cases where another dropdown was desired to locate a preferred puncture site. The stiffness of the wire provided adequate support to advance all sheaths to the left side regardless of outer diameter. This is the first case series on the use of a RF-guidewire combined with the PFA sheath for TSP. This study proved that an over a RF-powered guidewire TSP directly with 16.8F PFA sheath is feasible, reproducible, and safe. This very simplified workflow eliminates the need for both a rigid metal needle and an over the wire sheath exchange reducing procedure time and complexity, fluoroscopy time and potential related risks.
Diamond’s superior carrier transport properties and unparalleled radiation tolerance make it an ideal material for alpha/neutron detection. High performing diamond detectors are already commercially available. However, even high quality single crystal diamond can degrade after high doses of radiation, resulting in a reduction in carrier mean free path. It is well known that reducing the carrier collection distance, by decreasing the detector electrode spacing, makes radiation detectors more tolerant of mean free path reduction, and therefore more resilient to high radiation doses. One approach for thin device fabrication involves using thin diamond substrates, which can be fragile. In this work, a thin detector has been fabricated using a thick, highly resilient 300 μm diamond substrate by utilising a 3D network of laser-written nano-carbon network electrodes. An optimised femto-second laser write process, utilising specialised optical arrangements, is used to realise planar configured diamond detectors, comprising two Ti/Pt/Au spiral electrodes, connected to internal spiral nano-carbon network ’wall’ electrodes, which extend 20 μm below the surface and have a 50 μm separation. It was found that introducing the nano-carbon network electrodes greatly improved the detector resolution and Charge Collection Efficiency. With close to 100% charge collection efficiency and ns rise times demonstrated, achieving “thin” detector performance, in “thick”, structural substrates.
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