Browse Articles

Experimental study of spontaneous imbibition from coal based on nuclear magnetic resonance relaxation spectroscopy

A new plentiful solutions for nanosolitons of ionic (NSIW) waves spread the length of microtubules in (MLC) living cells

Episodic and associative memory from spatial scaffolds in the hippocampus

Knowledge attitude and practice of patients with allergic conjunctivitis towards their disease

The German adaptation of the Amputee Body Image Scale and the importance of psychosocial adjustment to prosthesis use

Abstract Negative cognitions related to one’s own body, here referred to as body image disturbances (BID), are common after lower limb amputation and correlate with weak psychological functioning. The Amputee Body Image Scale (ABIS) is internationally used to assess BID in persons with lower limb amputation. However, there is no psychometrically evaluated German adaptation available. Including a sample of 191 individuals with lower limb amputation, the present study developed and psychometrically evaluated the German ABIS. Results suggest high reliability in terms of internal consistency and stability of the measure over two years. Meaningful and significant relationships to sex, amputation level, post-amputation pain, mobility, and psychopathology indicate validity of the instrument. Multivariate analyses emphasize a specific and inverse relationship between BID and psychosocial adaptation to the prosthesis including its embodiment. Focussing on ABIS items that are independent of the type of amputation or rehabilitation experiences resulted in an ABIS short form with psychometric properties comparable to the long form. This instrument could be prospectively used in diverse limb loss populations, such as individuals with upper limb amputation or persons not using a prosthesis. The present results thus crucially contribute to the repertoire of patient-reported outcome measures in the context of post-amputation rehabilitation.

Effects of acute pro-inflammatory stimulation and 25-hydroxycholesterol on hippocampal plasticity and learning involve NLRP3 inflammasome and cellular stress responses

In vivo and in silico studies on the potential role of garden cress oil in attenuating methotrexate-induced inflammation and apoptosis in liver

Abstract Methotrexate (MTX) has been used in high doses for cancer therapy and low doses for autoimmune diseases. It is proven that methotrexate-induced hepatotoxicity occurs even at relatively low doses. It is known that garden cress has anti-inflammatory, antioxidant, and hepatoprotective properties. This study investigates the potential alleviating effect of garden cress oil (GCO) against MTX-induced hepatotoxicity in rats. The chemical composition of GCO was assessed using GC/MS analysis. Liver damage was studied using hepatotoxicity biomarkers, molecular, and histological analysis. Also, the effects of GCO on TNF-α and caspase-3 proteins were evaluated through molecular docking studies. The results demonstrated that MTX caused liver damage, as seen by elevated levels of the liver enzymes ALT, AST, and ALP. Likewise, MTX showed clear signs of apoptosis, such as increased mRNA expression levels of BAX, Caspase-3, and P53, and increased liver inflammation indicated by higher levels of TNF-α expression. MTX exhibited significant liver damage, as demonstrated by histological examination. Treatment with GCO effectively alleviated the apoptotic effects of MTX, provided protection against inflammation, and restored histological alterations. GC/MS metabolite profiling of garden cress oil revealed the presence of several phytoconstituents, including tocopherols, erucic acid, sesamolin, linoleic acid, vaccenic acid, oleic acid, stearic acid, and palmitic acid, that showed strong binding affinities toward TNF-α and caspase-3 proteins in molecular docking studies, which could explain the anti-apoptotic and anti-inflammatory potential of GCO.

Efficacy of contrast versus non-contrast CT surveillance among patients surviving two years without recurrence after surgery for stage I lung cancer

Author Correction: Augmenting cybersecurity through attention based stacked autoencoder with optimization algorithm for detection and mitigation of attacks on IoT assisted networks

Autoactive CNGC15 enhances root endosymbiosis in legume and wheat

Abstract Nutrient acquisition is crucial for sustaining life. Plants develop beneficial intracellular partnerships with arbuscular mycorrhiza (AM) and nitrogen-fixing bacteria to surmount the scarcity of soil nutrients and tap into atmospheric dinitrogen, respectively1,2. Initiation of these root endosymbioses requires symbiont-induced oscillations in nuclear calcium (Ca2+) concentrations in root cells3. How the nuclear-localized ion channels, cyclic nucleotide-gated channel (CNGC) 15 and DOESN’T MAKE INFECTIONS1 (DMI1)4 are coordinated to specify symbiotic-induced nuclear Ca2+ oscillations remains unknown. Here we discovered an autoactive CNGC15 mutant that generates spontaneous low-frequency Ca2+ oscillations. While CNGC15 produces nuclear Ca2+ oscillations via a gating mechanism involving its helix 1, DMI1 acts as a pacemaker to specify the frequency of the oscillations. We demonstrate that the specificity of symbiotic-induced nuclear Ca2+ oscillations is encoded in its frequency. A high frequency activates endosymbiosis programmes, whereas a low frequency modulates phenylpropanoid pathways. Consequently, the autoactive cngc15 mutant, which is capable of generating both frequencies, has increased flavonoids that enhance AM, root nodule symbiosis and nutrient acquisition. We transferred this trait to wheat, resulting in field-grown wheat with increased AM colonization and nutrient acquisition. Our findings reveal a new strategy to boost endosymbiosis in the field and reduce inorganic fertilizer use while sustaining plant growth.

Response coupling with an auxiliary neural signal for enhancing brain signal detection

Abstract Brain-computer interfaces (BCIs) offer an implicit, non-linguistic communication channel between users and machines. Despite their potential, BCIs are far from becoming a mainstream communication modality like text and speech. While non-invasive BCIs, such as Electroencephalography, are favored for their ease of use, their broader adoption is limited by challenges related to signal noise, artifacts, and variability across users. In this paper, we propose a novel method called response coupling, aimed at enhancing brain signal detection and reliability by pairing a brain signal with an artificially induced auxiliary signal and leveraging their interaction. Specifically, we use error-related potentials (ErrPs) as the primary signal and steady-state visual evoked potentials (SSVEPs) as the auxiliary signal. SSVEPs, known for their phase-locked responses to rhythmic stimuli, are selected because rhythmic neural activity plays a critical role in sensory and cognitive processes, with evidence suggesting that reinforcing these oscillations can improve neural performance. By exploring the interaction between these two signals, we demonstrate that response coupling significantly improves the detection accuracy of ErrPs, especially in the parietal and occipital regions. This method introduces a new paradigm for enhancing BCI performance, where the interaction between a primary and an auxiliary signal is harnessed to enhance the detection performance. Additionally, the phase-locking properties of SSVEPs allow for unsupervised rejection of suboptimal data, further increasing BCI reliability.

Design of tomato picking robot detection and localization system based on deep learning neural networks algorithm of Yolov5

Association of dietary carbohydrate ratio, caloric restriction, and genetic factors with breast cancer risk in a cohort study

Dual-functional probe for sensitive detection of MCF-7 cells and mendelian randomization analysis of MUC1 association with multiple cancers

Exploring the early drivers of pain in Parkinson’s disease

Streamlining whole genome sequencing for clinical diagnostics with ONT technology

Investigating practices and difficulties in communicating with patients about COVID-19 vaccination among healthcare workers in Italy

Abstract The aims of this cross-sectional study were to understand the healthcare workers’ (HCWs) practices and difficulties in communicating with patients about COVID-19 vaccinations, to investigate the factors associated, and to identify targets to improve the efficacy of the COVID-19 immunization strategy. Questionnaires were administered between November 2021 and March 2022 in three immunization centers in Italy. More than half of HCWs (56.8%) reported to always recommend COVID-19 vaccination to their patients, and the recommendations for other vaccinations were provided by 50.4% of the participants. Physicians/medical residents, males, and those who recommended other vaccinations to their patients were more likely to always recommend COVID-19 vaccination. The participants’ perception of difficulties in communicating with patients about COVID-19 vaccination and the impact of sources of information on patients’ knowledge about vaccination, explored using a ten-point Likert-type scale, resulted in a mean value of 6.3 and 7.9, respectively. A higher level of perception regarding difficulties in communicating with patients was more likely to be found among nurses/midwives and younger HCWs. It is important to reduce HCWs’ perceived gap regarding difficulties in communicating with patients, supporting them through health policy to recommend vaccinations, and engaging them in increasing uptake rates.

Prolonged persistence of mutagenic DNA lesions in somatic cells

Abstract DNA is subject to continual damage, leaving each cell with thousands of individual DNA lesions at any given moment 1–3 . The efficiency of DNA repair means that most known classes of lesion have a half-life of minutes to hours 3,4 , but the extent to which DNA damage can persist for longer durations remains unknown. Here, using high-resolution phylogenetic trees from 89 donors, we identified mutations arising from 818 DNA lesions that persisted across multiple cell cycles in normal human stem cells from blood, liver and bronchial epithelium 5–12 . Persistent DNA lesions occurred at increased rates, with distinctive mutational signatures, in donors exposed to tobacco or chemotherapy, suggesting that they can arise from exogenous mutagens. In haematopoietic stem cells, persistent DNA lesions, probably from endogenous sources, generated the characteristic mutational signature SBS19 13 ; occurred steadily throughout life, including in utero; and endured for 2.2 years on average, with 15–25% of lesions lasting at least 3 years. We estimate that on average, a haematopoietic stem cell has approximately eight such lesions at any moment in time, half of which will generate a mutation with each cell cycle. Overall, 16% of mutations in blood cells are attributable to SBS19, and similar proportions of driver mutations in blood cancers exhibit this signature. These data indicate the existence of a family of DNA lesions that arise from endogenous and exogenous mutagens, are present in low numbers per genome, persist for months to years, and can generate a substantial fraction of the mutation burden of somatic cells.

Chemical modification and antioxidant activity of Wendan peel polysaccharide

Predicting three-dimensional chaotic systems with four qubit quantum systems

Abstract Reservoir computing (RC) is among the most promising approaches for AI-based prediction models of complex systems. It combines superior prediction performance with very low CPU-needs for training. Recent results demonstrated that quantum systems are also well-suited as reservoirs in RC. Due to the exponential growth of the Hilbert space dimension obtained by increasing the number of quantum elements small quantum systems are already sufficient for time series prediction. Here, we demonstrate that three-dimensional systems can already well be predicted by quantum reservoir computing with a quantum reservoir consisting of the minimal number of qubits necessary for this task, namely four. This is achieved by optimizing the encoding of the data, using spatial and temporal multiplexing and recently developed read-out-schemes that also involve higher exponents of the reservoir response. We outline, test and validate our approach using eight prototypical three-dimensional chaotic systems. Both, the short-term prediction and the reproduction of the long-term system behavior (the system’s “climate”) are feasible with the same setup of optimized hyperparameters. Our results may be a further step towards the realization of a dedicated small quantum computer for prediction tasks in the NISQ-era.