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Analysis on the potential of Pennisetum hydridum for phytoremediation of Cd-polluted soil fertilized by worm castings

Soil heavy metal pollution including Cd, is the main factor that causes the decline of ecological environment quality, the excessive content in crops and the harm to human health. Phytoremediation is one of the important ways to control heavy metals, which has both ecological and economic benefits. However, most plant species have limited remediation ability and cannot achieve good heavy metal removal effect. In contrast, P. hydridum, easy to cultivate, has large biomass and short growth cycle, shows strong restoration ability in the treatment of heavy metal polluted soil. In order to explore its phytoremediation in Cd-polluted soils under appropriate agronomic measures, this experiment adopts the field random block experiment design to study the control effect and application safety of the application of organic fertilizers (warm castings and biogas slurry) to plant it in the Cd-polluted farmland. The results showed the Cd in the soil after P. hydridum harvesting was 0.53–0.56 mg/kg, and the partial Cd in the shoot was 0.21–0.28 mg/kg (fresh weight), and the enrichment coefficients were all greater than 1, and the extraction amount and efficiency of Cd were 7.17–9.43 mg/m2 and 5.71%–7.01%, respectively. All those data express a decrease in Cd under various treatment conditions, indicating that, P. hydridum can grow under high concentration and it has a certain enrichment effect on Cd, especially in the application of organic fertilizers, which could not only improve the growth performance of the plant, but also improve the soil, much better than that of other Cd hyper-accumulators. Moreover, the positive correlation between the biomass allocation rate and Cd in the soil reflects that the biomass allocation of the plant behaved in different ways with the increase of Cd oil. It is also feasible in terms of application safety due to a long and gradual process to enrich Cd in soil. This study made a proof that it would be a green and environmentally friendly treatment method by making good use of its high biomass to adsorb and remove heavy metals from soil, which would have a good application prospect and development value.

Mechanistic insights into the P-coumaric acid protection against bisphenol A-induced hepatotoxicity in in vivo and in silico models

Evaluation of statistical methods applied in theses and dissertations in an Open, Distance and e-Learning University

The appropriate application of research methods and statistical analyses used in the studies directly affects the quality of scientific studies. Due to the possibility of employing an incorrect statistical technique, it is crucial to choose a statistical method based on the study’s data and research objectives. This study aimed to evaluate whether statistical techniques applied in the theses and dissertations were appropriate for planning surveys or experiments and analyzing data, and to identify common mistakes that master’s and doctoral students made when using statistical techniques for the intended goals. The study reviewed 139 master’s theses and doctoral dissertations submitted to seven agricultural and environmental sciences disciplines at a leading Open, Distance and e-learning university in Africa between 2015 and 2020. These dissertations and theses used mixed and quantitative research methods. The analysis of variance test was the most often used statistical test, according to the results, followed by the student t-test and the Chi-square test. At least one blatant methodological error was found in 41.0% of theses and dissertations, either in the data collection process or in the data analysis. Examples of these errors include the use of a simple random sampling technique despite the heterogeneous population units, the conversion of count responses to binary responses and percentages for fitting logistic and general binomial regression models, and the incorrect modeling of correlated data using generalized linear models. The results of this study will create greater awareness of the common errors that postgraduate students make when using statistical methods to design experiments or sample surveys and analyse data. In addition, the findings inform the university management to plan for specific training in statistical methods appropriate for a range of academic fields.

Ultrasound-based incidence of coarctation of the aorta in true and false positive fetuses

Editorial Note: Prolonged immune alteration following resolution of acute inflammation in humans

Paired proteomic analysis reveals protein alterations in sun-exposed skin of professional drivers

Abstract Professional drivers represent an ideal cohort for investigating the effects of solar radiation on skin due to their unique, asymmetric exposure to sun, a consequence of vehicle window orientations. Consequently, one side of the face is naturally subjected to more solar radiation, resulting in uneven sunlight exposure. This scenario supports a paired experimental design for precise within-individual comparisons, crucial for assessing sun exposure’s impact on skin health, including signs of aging. Leveraging this approach, our study reveals sun-induced overexpression of proteins linked to photoaging through paired proteomic analysis, providing novel insights into the skin’s adaptive responses to chronic solar exposure. Initially, our research focused on a dataset from ten male professional drivers, identifying a set upregulated proteins in sun-exposed skin compared to the less exposed side of the face. To validate these findings, we extended our investigation to a new cohort of seven female bus drivers. Our motivation in switching genders and utilizing different mass spectrometry equipment and sample preparation techniques was for assessing the robustness of our initial findings, encompassing not just sex differences but also methodological variations, and also for understanding the broader implications of our results for photodermatology. To enable this detailed analysis, we developed specialized software that allows precise paired proteomic analysis, significantly enhancing the robustness and clarity of our findings. Our results shortlisted keratins, S100A14, and F-box proteins—by remaining consistently overexpressed in sun-exposed skin—and hemoglobin subunit beta as downregulated across both cohorts. Our findings underscore the potential of proteomic techniques in advancing our understanding of the molecular dynamics of photoaging and highlight the value of selecting cohorts with specific exposure characteristics.

Ictal cardiovascular autonomic dysfunction during focal seizures induced by direct electrical stimulation: An observational study research protocol

Introduction Autonomic symptoms, such as changes in heart rate, blood pressure, or respiration often accompany epileptic seizures and, in some cases, may be life threatening or even contribute to sudden death. However, autonomic changes during seizures with onset from certain brain areas are insufficiently understood. Intracranial direct electrical stimulation during stereoelectroencephalographic (SEEG) monitoring in surgical candidates allows researchers to investigate autonomic responses to induced seizures in conscious patients with known precise location of the electrodes. We aimed to identify the epileptogenic focus locations or brain structures associated with ictal cardiovascular autonomic dysfunction during focal seizures induced by direct electrical stimulation. Methods and analysis This is an observational study. In focal epilepsy patients undergoing presurgical evaluation with implanted intracranial SEEG electrodes, we will record heart rate (HR), beat-to-beat blood pressure (BP), and respiratory rate during the SEEG monitoring and stimulation conducted in accordance with the clinical needs. Tachycardia (HR > 100 bpm), bradycardia (HR < 60 bpm), hypertension (systolic or diastolic BP ≥ 140/90 mmHg), and hypotension (systolic or diastolic BP < 90/60 mmHg) during the first minute of induced clinical seizures will be considered as ictal cardiovascular autonomic dysfunction. We will use the chi-squared test to compare percentage of dysautonomia-associated seizures in the total number of induced seizures between cortical areas related to or interconnected with the central autonomic network and other cortical areas. Significance will be assumed for p-values < 0.05. At the time of submission, this study has enrolled thirteen patients and still on-going.

Miniaturization limits of ceramic UHF RFID tags

Cytomegalovirus host receptor expression in the human fetal inner ear

Fetal infection with human cytomegalovirus (hCMV) can cause sensorineural hearing loss and vestibular impairment, yet its pathogenesis remains unclear. This study aims to identify potential target cell types of hCMV in the human fetal inner ear. Viral particles use several envelope glycoproteins to enter target cells, including the pentameric complex, the trimeric complex and glycoprotein B. Platelet-derived growth factor receptor alpha (PDGFRA) serves as the receptor in fibroblasts, neuropilin-2 (NRP2) in epithelial, endothelial and dendritic cells as well as in leukocytes. Upon binding of these glycoproteins, glycoprotein B initiates membrane fusion which is proposed to be mediated by EGFR. When and where these proteins are expressed in the fetal inner ear during development is unknown. To address this, expression patterns of PDGFRA, NRP2 and EGFR were investigated in human fetal inner ear tissue using single-nucleus RNA sequencing data (first trimester: N = 2) and immunohistochemistry (first trimester: N = 6, second trimester: N = 5). PDGFRA gene and protein expression was detected in mesenchymal cells, NRP2 protein expression in epithelial cells and endothelial cells, and EGFR gene and protein expression in both epithelial cells and mesenchymal cells. Notably, all three receptors were present in tissue from the first and second trimesters. In conclusion, hCMV host receptors PDGFRA, NRP2 and EGFR are expressed in mesenchymal, epithelial and endothelial cells within the cochlea and vestibular organs during the first and second trimesters. These cell types may serve as targets for hCMV infection of the fetal inner ear.

Carbon dot based dressing for therapy of chemically-induced cutaneous burns

Development of label-free cell tracking for discrimination of the heterogeneous mesenchymal migration

Image-based cell phenotyping is fundamental in both cell biology and medicine. As cells are dynamic systems, phenotyping based on static data is complemented by dynamic data extracted from time-dependent cell characteristics. We developed a label-free automatic tracking method for phase contrast images. We examined the possibility of using cell motility-based discrimination to identify different types of mesenchymal migration in invasive malignant cancer and non-cancer cells. These cells were cultured in plastic tissue culture vessels, using motility parameters from cell trajectories extracted with label-free tracking. Correlation analysis with these motility parameters identified characteristic parameters for cancer HT1080 fibrosarcoma and non-cancer 3T3-Swiss fibroblast cell lines. The parameter “sum of turn angles,” combined with the “frequency of turns” at shallow angles and “migration speed,” proved effective in highlighting the migration characteristics of these cells. It revealed differences in their mechanisms for generating effective propulsive forces. The requirements to characterize these differences included the spatiotemporal resolution of segmentation and tracking, capable of detecting polarity changes associated with cell morphological alterations and cell body displacement. With the segmentation and tracking method proposed here, a discrimination curve computed using quadratic discrimination analysis from the “sum of turn angles” and “frequency of turns below 30°” gave the best performance with a 94% sensitivity. Cell migration is a process related not only to cancer but also to tissue healing and growth. The proposed methodology is easy to use, enabling anyone without professional skills in image analysis, large training datasets, or special devices. It has the potential for application not only in cancer cell discrimination but also in a broad range of applications and basic research. Validating the expandability of this method to characterize cell migration, including the scheme of propulsive force generation, is an important consideration for future study.

Prediction of acoustic tinnitus suppression using resting-state EEG via explainable AI approach

Abstract Tinnitus is defined as the perception of sound without an external source. Its perceptual suppression or on/off states remain poorly understood. This study investigates neural traits linked to brief acoustic tinnitus suppression (BATS) using naive resting-state EEG (closed eyes) from 102 individuals. A set of EEG features (band power, entropy, aperiodic slope and offset of the EEG spectrum, and connectivity) and standard classifiers were applied achieving consistent high accuracy across data splits: 98% for sensor and 86% for source models. The Random Forest model outperformed other classifiers by excelling in robustness and reduction of overfitting. It identified several key EEG features, most prominently alpha and gamma frequency band power. Gamma power was stronger in the left auditory network, while alpha power dominated the right hemisphere. Aperiodic features were normalized in individuals with BATS. Additionally, hyperconnected auditory-limbic networks in BATS suggest sensory gating may aid suppression. These findings demonstrate robust classification of BATS status, revealing distinct neural traits between tinnitus subpopulations. Our work emphasizes the role of neural mechanisms in predicting and managing tinnitus suppression. Moreover, it advances the understanding of effective feature selection, model choice, and validation strategies for analyzing clinical neurophysiological data in general.

Measuring metabolic energy expenditure with short duration walking tests for individuals with lower limb amputation

Introduction Metabolic assessment of prosthetic gait is useful when comparing devices, interventions, or populations. However, the standard requirement to walk continuously for six minutes or more to reach steady state (SS) is difficult for many individuals with lower limb amputation. Our goal was to assess the concurrent validity of metabolic outcomes from shorter duration walking tests with those from the standard six-minute walk, in persons with transfemoral or transtibial amputation. Methods Thirty participants (amputation: 10 transfemoral, 10 transtibial, 10 none) performed three walking tests while data were collected with a wearable metabolic system: 1) two-minute treadmill walk plus 10-minute recovery, 2) six-minute treadmill walk, and 3) overground two-minute walk test (2MWT). Three different analyses were performed to correlate SS metabolic outcomes from minutes 5-6 of the six-minute treadmill walk with: 1) total oxygen uptake from the two-minute treadmill walk, incorporating excess post-exercise oxygen consumption (EPOC), 2) minute interval outcomes from minutes 1-4 of the six-minute treadmill walk, and 3) outcomes during minutes 1 and 2 of the 2MWT. Results Strong correlations were found between total oxygen uptake of the two-minute treadmill walk plus EPOC and SS oxygen uptake (Pearson r 0.86 to 0.94). Likewise, there were strong correlations between minute interval outcomes of minutes 2, 3, and 4 of the six-minute treadmill walk and SS outcomes (Pearson r 0.82 to > 0.99). Fewer significant correlations were observed when comparing 2MWT outcomes with SS outcomes (Pearson r 0.41 to 0.78). Conclusion Strong correlations between metabolic outcomes of shorter duration walking tests with SS outcomes suggest that treadmill walking tests as short as two minutes may be acceptable to compare energy expenditure between conditions in individuals with lower limb amputation for circumstances where longer duration tests would not be possible. Additionally, these shorter tests would be more similar to real-life activities and more accessible for those with lower limb amputation.

Singularity index and multifractal analysis of magnitude magnetic transforms: a new methodology to explore Au mineralization with application to Esh El Mallaha, Egypt

Abstract The primary objective of mineral exploration is to discover new mineral-rich zones within targeted regions. The fractal concentration area (C-A) and the magnetic maps are now extensively used in mineral prospecting. Unfortunately, the calculation of the reduced-to-pole (RTP) maps suffers from several drawbacks. It requires a prior knowledge of the inclination and declination of the source magnetization. It can be complicated to determine the direction of the source magnetization vector in certain conditions because of the large and significant remanent magnetization of the source if present. Furthermore, at low magnetic latitudes, the RTP computation is unstable. However, a new class of transforms known as magnitude magnetic transforms (MMTs) overcome these drawbacks. Such transforms have nonnegative distributions and exhibit significantly higher centricity with regard to the observed anomalous field. Their anomaly patterns are much less influenced by the direction of the magnetization vector than the observed total magnetic intensity. Due to these benefits, in this work, these transforms are used instead of RTP transform as a base for fractal/multifractal analysis of the magnetic signal from the Esh El Mallaha area, Eastern desert to delineate gold mineralization and hydrothermally altered and potential zones. Moreover, are used for the singularity analysis S-A in a novel integrated workflow. The results of this study show a promising approach that can be utilized globally for mineralization detection strategies.

Advancing methods for comparative urban research: A city-centric protocol and longitudinal dataset for US metropolitan statistical areas

Comparative urban research in the USA has an unacknowledged data and methodological problem at the metropolitan scale, rooted in geographic and definitional boundary changes of urban areas across time. In this article, we introduce a new spatial dataset, decision criteria, and methodological protocol for longitudinal and comparative research with US metropolitan statistical areas (MSAs)—known as ‘metros’—in a way that centers a ‘city-centric’ approach to comparison while significantly reducing spatial error and bias. First, we review gaps and limitations of existing approaches and identify three major but previously unacknowledged sources of error, including a new source of bias we call ‘spanning error.’ Next, we explain our methodological protocol and decision criteria, which are guided by the twin aims of reducing spatial bias and ensuring metropolitan consistency over time. We then introduce our improved dataset, which covers the 50 largest MSAs from 1980-2020. We argue that by centering the urban area as the fundamental unit of analysis—a city-centric approach—our methodology and dataset provides robust and dynamic metropolitan definitions that advance comparative urban studies while improving precision and accuracy in urban data analysis across different time scales. We discuss broader applications of our methodology and identify advantages and limitations over existing techniques, including potential applications of this work in policy, planning, and future research.

Presence of gluten and soy derived excipients in medicinal products and their implications on allergen safety and labeling

Abstract Gluten and soy allergies are significant health concerns, particularly in individuals with celiac disease or soy sensitivity. While dietary sources of these allergens are well-studied, their presence in medicinal products remains under-explored. This study assessed the prevalence of gluten and soy-derived excipients in 308 medicinal products authorized for marketing in Portugal. A systematic search of the Summary of Product Characteristics (SmPC) database was conducted for 108 analgesics and antipyretics containing paracetamol, 85 NSAIDs containing ibuprofen, and 115 antiasthmatic and bronchodilator medicinal products. The study found significant associations between pharmacotherapeutic groups and the presence of these allergens (p < 0.001). Gluten was more prevalent in the group of analgesics and antipyretics (44.4%) than in NSAIDs (8.2%), whereas soy-derived excipients were more frequent in NSAIDs (14%) than in analgesics and antipyretics (6.5%). No excipients containing gluten or soy were identified in antiasthmatic and bronchodilator medicinal products. In analgesics and antipyretics, 51.2% of solid oral dosage forms and 40% of liquid oral formulations contained gluten. Within the NSAIDs group, gluten was mainly present in liquid oral dosage forms (26.7%). Soy-derived excipients were found in 30% of liquid oral formulations and in 33.3% of rectal dosage forms of analgesics and antipyretics. In the NSAIDs group, soy was more prevalent in liquid oral formulations (26.7%). These findings highlight the need for clearer labeling of allergens in medicinal products and underscore the importance of vigilance for patients with gluten or soy allergies. Further research is required to address gaps in allergen disclosure by pharmaceutical manufacturers and to promote safer medicinal product use for sensitive populations. Enhanced awareness among healthcare providers and patients is essential to mitigate the risk of allergic reactions associated with hidden excipients in medicinal products.

UFM: Unified feature matching pre-training with multi-modal image assistants

Image feature matching, a foundational task in computer vision, remains challenging for multimodal image applications, often necessitating intricate training on specific datasets. In this paper, we introduce a Unified Feature Matching pre-trained model (UFM) designed to address feature matching challenges across a wide spectrum of modal images. We present Multimodal Image Assistant (MIA) transformers, finely tunable structures adept at handling diverse feature matching problems. UFM exhibits versatility in addressing both feature matching tasks within the same modal and those across different modals. Additionally, we propose a data augmentation algorithm and a staged pre-training strategy to effectively tackle challenges arising from sparse data in specific modals and imbalanced modal datasets. Experimental results demonstrate that UFM excels in generalization and performance across various feature matching tasks. The code will be released at: https://github.com/LiaoYun0x0/UFM.

Factors affecting prognosis in patients with locally advanced and advanced esophageal cancer receiving definitive radiotherapy in plateau regions

Aerobic exercise and brain structure among military service members and Veterans with varying histories of mild traumatic brain injury: A LIMBIC-CENC exploratory investigation

Objectives To explore associations of recent moderate-to-vigorous aerobic exercise (MVAE) participation and lifetime mild traumatic brain injury (mTBI) history with measures of brain gray matter volumes among military service members and Veterans (SMVs). Methods Participants (n = 1,340; aged 41.3 ± 10.3 years; 13% female) were SMV’s who participated in the Long-term Impact of Military-relevant Brain Injury Consortium-Chronic Effects of Neurotrauma Consortium Prospective Longitudinal Study (LIMBIC-CENC PLS). MVAE participation was self-reported via the Behavioral Risk Factor Surveillance System and categorized according to current MVAE recommendations (Inactive, Insufficiently Active, Active, and Highly Active). Lifetime mTBI history was queried via validated structured interview and categorized as 0 mTBI, 1-2 mTBIs, 3 + mTBIs. Structural MRI (T1- and T2-weighted images) were used to measure gray matter volumetrics: ventricle-to-brain ratio (VBR); bilateral volumes of the frontal, parietal, temporal, occipital, cingulate, hippocampus, amygdala, and thalamus regions. Multivariable linear regression models were fit to test associations of MVAE participation, mTBI history, and their interaction on each of the volumetric outcomes while controlling for age, sex, education attainment, and PTSD symptoms. Effects were considered statistically significant if the corresponding unstandardized beta (B) and 95% CI did not include 0. Results Regarding main effects, participants in the Inactive MVAE group had significantly larger VBR values (worse outcome) than those in the Insufficiently Active group (B[95%CI] = -0.137[-0.260, -0.014]). Interaction effects showed participants with no lifetime mTBIs in the Highly Active group had larger VBR values (worse outcome) when compared to those in the Inactive and Insufficiently Active groups. SMVs with 3 + lifetime mTBIs who were Highly Active also had smaller VBR values (better outcome) when compared to Highly Active SMVs with fewer lifetime mTBIs. There were no other statistically significant differences for MVAE participation, mTBI history, or their interactions. Conclusions History of one or more lifetime mTBIs was not associated with measures of brain gray matter volumes, suggesting that declines in structural brain health are not expected for the most SMVs with mTBI(s). Although MVAE may benefit brain health, a positive association between self-reported MVAE participation and gray matter volumes was not observed.

Efficacy and safety of azvudine versus nirmatrelvir/ritonavir in cancer patients with COVID-19