This research showed that the iron nanoparticles (FeNPs) formulated with Ocimum basilicum aqueous extract having potent antioxidant and anti-human glioma activities in vitro condition. For determinate the properties of the FeNPs that were produced from the reaction between iron chloride solution with aqueous Ocimum basilicum extract, we used UV–Visible Spectroscopy (UV-Vis), Field Emission Scanning Electron Microscopy (FE‐SEM), and Fourier Transformed Infrared Spectroscopy (FT‐IR). To survey the cytotoxicity and anti-human glioma effects of FeNPs, MTT assay was used on the SW1088, LN-229, U-87 and A-172 cell lines. For investigating the antioxidant properties of FeNPs, the DPPH test was used in the presence of butylated hydroxytoluene as the positive control. Iron nanoparticles had very low cell viability and anti-human glioma properties dose-dependently against SW1088, LN-229, U-87 and A-172 cell lines without any cytotoxicity on the normal cell line. The IC50 of the iron nanoparticles were 101, 75, 97, and 54 µg/ml against SW1088, LN-229, U-87 and A-172 cell lines. DPPH test revealed similar antioxidant potentials for FeNPs and butylated hydroxytoluene. It seems that the anti-human glioma effects of recent nanoparticles is due to their antioxidant properties.

We recount the life, work, and legacy of the theoretical physicist Roy Glauber (1925-2018). Admitted to Harvard at age sixteen, called upon to participate in the Manhattan Project at age eighteen, and appointed to the Harvard Physics faculty at age twenty-nine, Glauber is credited with seminal contributions to three separate fields of physics: nuclear scattering, statistical physics, and foundational work in quantum optics, which earned him the 2005 Nobel Prize in Physics. Over decades, Glauber was also a dedicated teacher of high-school, college, and graduate students. His pedagogical gifts are reflected in his lucid papers that read as if they were written yesterday.

The design of Inductance–capacitor–inductance (LCL) grid-connected inverter based on linear quadratic regulation (LQR) has been studied widely, while the performance of the controller is not analyzed in these designs. In this paper, a new design method of LCL is discussed in detail. Different from the existing method parameter of the LQR controller is obtained according to the pole assignment. Besides, parameters of LCL-type filter are designed in term of the characteristics of the new closed-loop system. Further, the robustness of the system is analyzed separately. At last, various performances of the new design system are verified by simulation. The suppression ability of the system for switching harmonics is verified in the rated state and in the case of power change. The performance including better robustness and better resistance to weak grid comparison of the traditional design is also shown in this paper.

Objective: To investigate the effects of anlotinib combined with second-line chemotherapy on the levels of immune cells and inflammatory factors and the curative effects in patients with advanced non-small cell lung cancer. Methods: A total of 106 patients with advanced non-small cell lung cancer were selected from November 2020 to March 2022 for clinical and hospital treatment as the research subjects. The patients were divided into a control group (n = 53) and an observation group (n = 53). The control group was treated with second-line single-agent chemotherapy regimens, and the observation group was treated with second-line combination chemotherapy including anlotinib. The prognostic effect, adverse reactions, levels of immune cells and inflammatory factors before and after treatment were observed and compared between the two groups. Results: There were no statistically significant differences in sex, age, lesion diameter, BMI or other general data between the two groups (P > 0.05), indicating comparability. The clinical efficacy of the observation group was significantly higher than that of the control group, and the difference was statistically significant (P<0.05). Before treatment, the levels of CD4+ and CD4+/CD8+ in the observation group were significantly higher than those in the control group, and the differences were statistically significant (P < 0.05). . After treatment, the levels of IL-6, IL-8, IL-10 and TNF-α in the observation group were lower than those in the control group, and the difference was statistically significant (P < 0.05). There were no significant differences in the incidence of nausea and vomiting, liver function damage, alopecia or leukopenia between the 2 groups (P > 0.05). Conclusion: Anlotinib combined with second-line chemotherapy has positive effects on the levels of immune cells and inflammatory factors in patients with advanced non-small cell lung cancer, which can reduce immunosuppression and benefit prognosis

With advancements in automation and high-throughput techniques, complex materials discovery with multiple conflicting objectives can now be tackled in experimental labs. Given that physical experimentation is greatly limited by evaluation budget, maximizing efficiency of optimization becomes crucial. We discuss the limitations of using hypervolume as a performance indicator for desired optimality across the entire multi-objective optimization run and propose new metrics specific to experimentation: ability to perform well for complex high-dimensional problems, minimizing wastage of evaluations, consistency/robustness of optimization, and ability to scale well to high throughputs. With these metrics, we perform a comparison of two conceptually different and state-of-the-art algorithms (Bayesian and Evolutionary) on synthetic and real-world datasets. We discuss the merits of both approaches with respect to exploration and exploitation, where fully resolving the Pareto Front could be the main aim for greater scientific value in understanding materials space, and thus provide a perspective for materials scientists to implement optimization in their platforms.

This paper presents a novel approach to scientific discovery using an artificial intelligence (AI) environment known as ChatGPT, developed by OpenAI. This is the first paper entirely generated with outputs from ChatGPT. We demonstrate how ChatGPT can be instructed through a gamification environment to define and benchmark hypothetical physical theories. Through this environment, ChatGPT successfully simulates the creation of a new improved model, called GPT4, which combines the concepts of GPT in AI (generative pretrained transformer) and GPT in physics (generalized probabilistic theory). We show that GPT4 can use its built-in mathematical and statistical capabilities to simulate and analyze physical laws and phenomena. As a demonstration of its language capabilities, GPT4 also generates a limerick about itself. Overall, our results demonstrate the promising potential for human-AI collaboration in scientific discovery, as well as the importance of designing systems that effectively integrate AI's capabilities with human intelligence.

We show the global dynamics of spatial cross-correlation of Pc2 wave activity can track the evolution of the 2015 St. Patrick’s Day geomagnetic storm for an 8 hour time window around onset. The global spatially coherent response is tracked by forming a dynamical network from 1 second data using the full set of 100+ ground-based magnetometer stations collated by SuperMAG and Intermagnet. The pattern of spatial coherence is then captured by a few network parameters which in turn track the evolution of the storm. At onset IMF B_z>0 and Pc2 power increases, we find a global response with stations being correlated over both local and global distances. Following onset, whilst B_z>0, the network response is confined to the day-side. When IMF B_z<0, there is a strong local response at high latitudes, consistent with the onset of polar cap convection driven by day-side reconnection. The spatially coherent response as revealed by the network grows and is maximal when both SME and SMR peak, consistent with an active electrojet and ring-current. Throughout the storm there is a coherent response both in stations located along lines of constant geomagnetic longitude, between hemispheres, and across magnetic local time. The network does not simply track the average Pc2 wave power, however is characterized by network parameters which track the evolution of the storm. This is a first study to parameterize global Pc2 wave correlation and offers the possibility of statistical studies across multiple events to detailed comparison with, and validation of, space weather models.

A document by Nora Loose. Click on the document to view its contents.

Because strong absorption of infrared radiation by greenhouse gases is more significant than the cloud longwave (LW) scattering effect, most climate models neglect cloud LW scattering to save computational costs. However, ignoring cloud LW scattering directly overestimates the outgoing longwave radiation (OLR). A recent study performed slab-ocean model simulations in the Community Earth System Model and showed that such radiative flux changes due to ice cloud LW scattering can affect the polar surface climate more than other climate zones. In this study, we included the same ice cloud LW scattering treatment in the Exascale Energy Earth System Model (E3SM) version 2 and ran fully-coupled simulations to assess the impact of ice cloud LW scattering on global climate simulation. Including ice cloud LW scattering leads to ~2 W m^-2 instantaneous OLR reduction in the tropics, more than the OLR reduction in other climate zones. Strong surface warming occurs in the Arctic, which is dominantly caused by the polar amplification resulting from the radiative forcing caused by ice cloud LW scattering. In the tropics, when the ice cloud LW scattering effect is included, more liquid clouds form in the middle troposphere, high clouds in the convection zone are lifted, anvil clouds retreat, and stratiform low cloud fraction increases. Most of these effects are similar to the cloud response to the increase of well-mixed greenhouse gases. The present study suggests that the ice cloud LW scattering effect must be incorporated into climate simulations.

A document by Brendan McCormick Kilbride. Click on the document to view its contents.

The Main Ethiopian Rift (MER) is accompanied by extensive volcanism and the formation of geothermal systems, both having an imminent impact on lives of millions of local inhabitants. Although previous studies from the region found evidence that asthenospheric upwelling and associated decompression melting provide melt to magmatic mush systems that feed the tectono-volcanic segments in the rift valley, no geophysical model imaged these regional and local scale transcrustal structures within a single comprehensive 3-D model. To fill this gap, we combined regional and local magnetotelluric data sets to obtain the first multi-scale 3-D electrical conductivity model of the central MER. The model clearly images a magma ponding zone with up to 7 vol.% melt at the base of the crust in the western part of the rift, its connection to Aluto volcano via a tectonically controlled transcrustal magmatic mush system and how the melt, stored at shallow crustal depths, supplies heat for Aluto’s geothermal system. Our model provides evidence that different volcano-tectonic lineaments in the rift valley share a common melt source, which has been debated in the past. The presented multi-scale model provides new constraints as well as geologic insights into the melt distribution below the rift and will facilitate future geothermal developments and volcanic hazard assessments in the MER.

The estimation of the slope (b-value) of the frequency magnitude distribution of earthquakes is usually based on a formula derived decades ago under the hypothesis of continuous exponential distribution of magnitudes. However, as the magnitude is provided with a limited resolution (one decimal digit usually), its distribution is not continuous but discrete. In the literature this problem is solved mostly by applying an empirical correction to the minimum magnitude of the dataset depending on the binning size, but a recent paper recalled that this solution is only approximate and proposed an exact formula. The same paper further showed that the b-value can be estimated also by considering the positive magnitude differences (which are proven to follow an exponential discrete Laplace distribution) and that in this case the estimator is more resilient to the incompleteness of the magnitude dataset. In this work we provide the complete theoretical formulation including the derivation of i) the means and standard deviations of the discrete exponential and Laplace distributions; ii) the estimators of the decay parameter of the discrete exponential and trimmed Laplace distributions by the methods of the mean as well as of the maximum likelihood; and iii) the corresponding formulas for the parameter b. We further deduce iv) the standard confidence limits for the estimated b. Moreover, we are able v) to quantify the error associated with the formula including the Utsu minimum-magnitude correction. We tested such formulas on simulated synthetic datasets including cases with a certain amount of incompleteness.

RATIONALE: Diagnosis and differentiation of Alzheimer’s disease (AD) from other tauopathies is challenging, especially at the early stages. In this aim, analytical methods are essential to identify and to confirm new biomarkers. Antibody-dependent approaches may not capture all the diversity of proteoforms when dealing with complex proteins such as tau. METHODS: We adapted and evaluated the single-pot solid-phase-enhanced sample-preparation (SP3) protocol for antibody-free extraction of tau-protein in diluted human serum or human brain, following perchloric acid precipitation. A total of 13 non-modified peptides were quantified by high-resolution mass spectrometry (HRMS) after digestion of tau by trypsin. RESULTS: We significantly improved the basic SP3 protocol by carefully optimizing the organic solvents and incubation time for tau binding, as well as the digestion step for the release directly from the beads of the 13 tau peptides. These optimizations proved to be primarily beneficial for the most hydrophilic tau peptides, increasing the sequence coverage. Mean recovery of the 13 non-modified peptides quantified by LC-HRMS was of 53%, with LODs ranging from 0.75 to 10ng/mL. CONCLUSIONS: Finally, we tested the optimized SP3 protocol on pathological tau extracted from the soluble fraction from an AD brain sample (middle frontal gyrus). We could successfully identify and quantify several biologically relevant tau peptides, including representative peptides of two isoforms and two phospho-peptides (p-Tau217 and p-Tau181).

Minirhizotron technique (MR), an image-based root phenotyping technology, has expanded our understanding of in situ root responses to changing environmental conditions. However, the conventional manual approaches to capturing and analyzing images are time-consuming, thus constraining the size and frequency of sampling and interpretation. To address this bottleneck, an automated MR system was developed, which worked in a fully automatic manner according to the pre-set schedule. Users can remotely control the system and download images. This system was tested in a net house by imaging bell pepper roots on a daily basis, which shows superior performance over commercial manual MR systems in terms of image resolution and sampling frequency. Besides, an image analysis model was built on convolutional neural networks to estimate root length from MR images directly without segmentation in the training process. This model was trained on a dataset of ~18,000 tomato root images taken by a manual MR camera and was used for estimating root length on 832 bell pepper root images taken by the automated MR camera. The high correlation coefficient (R 2 = 0.854) between the model estimation and manual measurement proved that this model generalizes well over different crop roots and camera types. Therefore, high-frequency in situ root phenotyping can be achieved by the automated Minirhizotron image acquisition and analysis tools proposed here.

Lung transplantation is an option for end-stage lung disease in Kartagener's syndrome patients. We describe a case of successful pregnancy in a patient with Kartagener's syndrome who had been offered an indication for lung transplantation before conception, despite aggravation of the lung disease during pregnancy.

Despite speech emotion recognition(SER) makes a significant contribution to artificial intelligence, there exists a heterogeneity gap between different modalities. Moreover, most cross-corpus SER only use audio modality. There are few studies on cross-corpus bimodal SER. Motivated by these problems, in this work, we address these issues at the same time. We design YouTube dataset as a source data and interactive emotional dyadic motion capture database (IEMOCAP) as a target data. In both source data and target data, we use CNN and bidirectional long short term memory network (Bi-LSTM) to extract speech features and use Bidirectional Encoder Representation from Transformers (BERT)+ Bi-LSTM to extract text features , then we design modality-invariance loss to form a common representation space of two modalities. To deal with the problem of cross-corpus SER, we learn a common subspace of source data and target data by optimizing Linear Discriminant analysis(LDA), Maximum Mean Discrepancy (MMD) and Graph Embedding (GE) jointly. To preserve emotion-discriminative features, we add emotion-aware center loss .We use SVM classifier as final emotion classification.The experiment results on IEMOCAP demonstrate that our method is superior to other state-of-art cross-corpus and bimodal SER.

BACKGROUND AND PURPOSE: The updates in the definition of absence status epilepticus raise questions about the pathophysiological aspects of absence status. Here, we propose an animal model of absence status epilepticus, induced by specific alpha 2a adrenergic receptor (α2AR) activation. EXPERIMENTAL APPROACH: An α2AR agonist, dexmedetomidine was injected intracerebroventricularly into the adult rats with genetic absence epilepsy and the electroencephalography (EEG) from animals was recorded. The total duration, number and mean duration of each spike-and-wave discharges (SWDs) were evaluated. The blocks of absence status events were classified as first and second set of absence statuses. Ethosuximide was given as a pre-treatment to another group of animals, later injected with 2.5 μg dexmedetomidine. Power spectral characteristics and coherence analysis for the absence status events and sleep were performed on the EEG. KEY RESULTS: The 2.5 µg dose of dexmedetomidine increased the total SWD duration and induced continuous SWDs up to 26 min. Following a first absence status event, sleep is induced and it was followed by the second set of absence status events. Ethosuximide pre-treatment blocked the occurrence of these events. Power spectral density analyses revealed that dexmedetomidine injection-induced absence seizures and the absence seizures following sleep had lower spectral power than typical SWDs in the frequency bands. CONCLUSIONS AND IMPLICATIONS: This study presents that activation of α2AR may induce absence status epilepticus and this can be an animal model to study the pathophysiological role of absence status. Our results strengthen the significant role of α2AR in SWD generation or termination. **This article has been reviewed and published at Epilepsia open with doi number:   https://doi.org/10.1002/epi4.12879

Sleep spindles are major oscillatory components of Non-Rapid Eye Movement (NREM) sleep, reflecting hyperpolarization-rebound sequences of thalamocortical neurons. Reports suggest a link between sleep spindles and several forms of high frequency oscillations which are considered as expressions of pathological off-line neural plasticity in the central nervous system. Here we investigated the relationship between thalamic sleep spindles and ripples in the anterior and mediodorsal nuclei (ANT and MD) of epilepsy patients. Whole-night LFP from the ANT and MD were co-registered with scalp EEG/polysomnography by using externalized leads in 15 epilepsy patients undergoing a Deep Brain Stimulation protocol. Slow (~12 Hz) and fast (~14 Hz) sleep spindles were present in the human ANT and MD and roughly, 20 % of them were associated with ripples. Ripple-associated thalamic sleep spindles were characterized by longer duration and exceeded pure spindles in terms of 100–200 Hz thalamic, but not cortical activity as indicated by time-frequency analysis. Furthermore, ripple amplitude was modulated by the phase of sleep spindles within both thalamic nuclei. No signs of pathological processes were correlated with measures of ripple and spindle association, furthermore, the density of ripple-associated sleep spindles in the ANT and MD showed a positive correlation with general intelligence. Our findings indicate the complex and multifaceted role of the human thalamus in sleep spindle-related physiological and pathological processes.

Aging can be caused by oxidative stress. Keap1-Nrf2/ARE signaling pathway is an antioxidant pathway. Ginsenoside Rg1 is one of the saponins found in ginseng having biological activity. It possesses anti-aging, anti-oxidant, and immune-strengthening properties. However, the molecular mechanism through which Rg1 affects brain aging is unknown. The purpose of this study was to investigate the effect of ginsenoside Rg1 in aging mice models and to decipher the molecular mechanisms underlying hippocampal aging and NSCs. D-gal was used to construct a mouse brain and NSCs aging model. Rg1 treatment improved brain function; decreased the structural damage of D-gal to hippocampal tissue and cells; decreased Ach neurotransmitter degradation; down-regulated the expression of the aging-related protein P53; alleviated oxidative stress damage: increased SOD and CAT activities, decreased MDA, 4-HNE and 8-OHdG content; down-regulated Keap1 protein expression and promoted Nrf2 dissociation from Keap1, and up-regulated Nrf2 and HO-1 protein expression, thus activating the Keap1-Nrf2/ARE pathway; Up-regulated expression of Nrf2/ARE pathway-related protective target genes (NQO1, GCLM, GSTM-1, and GCLC), reducing the aging process caused by D-gal-induced oxidative stress damage. Conclusion: Ginsenoside Rg1 can protect the hippocampus and NSCs of mice from oxidative damage and delay aging via the Keap1-Nrf2/ARE pathway.It advances our understanding of antioxidant therapy, serves as a critical reference for the prevention and treatment of aging-related disorders of the nervous system, and gives new scientific connotations to the Chinese medicine.

We describe the case of a patient with a diagnosis of rheumatoid arthritis experiencing a mucocutaneous delayed reaction to golimumab. Anyway, there is no consensus regarding the best management of delayed reactions to biologics. Excluding allergic cross-reactivity or sensitization, we finally tested adalimumab by a graded challenge.

Though rare, guidewire loss or fracture after percutaneous coronary intervention (PCI) can occur. Coronary perforations (CP) are rare complications of PCI and can be classified as type I (extraluminal crater), II (myocardial or pericardial blushing) and III (contrast streaming or cavity spilling).

Recently, studies have been incorporating larger datasets and a higher number of flow events. Consequently, automated methods have become an indispensable necessity. In this work, an automated procedure to improve hysteresis analysis is proposed. Two main aspects are targeted for methodological improvement:  The qualitative and quantitative analysis axes of hysteresis loops. The concept of Hysteresis Signature, a sequence of parameters that defines the parts forming a hysteresis loop (linear, clockwise, and anticlockwise parts), is introduced to classify hysteresis shapes. A new numeric analysis format is also introduced following the signature to characterize each part of the loop individually. It uses both normalized and real-scale metrics for a full hysteresis quantification. The procedure was extensively tested and validated using 1400+ events from real datasets. Results showed a significant methodological improvement in both the qualitative and quantitative analysis aspects of a given hydrological hysteresis response. The automated classification identified 51 different shapes, successfully confirming the increase of identifiable hysteresis loops. The new numeric analysis format, compared to hysteresis indices, gives a unique quantitative examination in combined forms (e.g., Figure of eight loops) which improves the accuracy of the acquired information. Real-scale quantification improved normalized metrics by reflecting the physical impact associated with the opening of the loop. Finally, the overall results of the method’s testing showed that the procedure is versatile and compatible with varying data types so that the method can be generalized to various hysteresis relationships. 

Animals encounter many novel and unpredictable challenges when moving into new areas including pathogen exposure. Because effective immune defenses against such threats can be costly, plastic immune responses could be particularly advantageous, as such defenses can be engaged only when context warrants activation. DNA methylation is a key regulator of plasticity via its effects on gene expression. In vertebrates, DNA methylation occurs exclusively at CpG dinucleotides, and typically, high DNA methylation decreases gene expression. The CpG content of gene regulatory regions may therefore represent one form of epigenetic potential (EP), a genomic means to capacitate gene expression. Non-native populations of house sparrows (Passer domesticus) - one of the world’s most cosmopolitan species – have high EP in the promoter of a key microbial surveillance gene, Toll-like receptor 4 (TLR4), compared to native populations. We previously hypothesized that high EP may enable sparrows to balance the costs and benefits of immune responses well, a trait critical to success in novel environments. In the present study, we found support for this hypothesis. House sparrows with high EP in TLR4 were better able to resist a pathogenic Salmonella enterica infection than sparrows with low EP. These results support the premise that high EP contributes to adaptation in novel environments.

During the COVID-19 pandemic, a 32-year-old front line health-worker tested positive for COVID-19 in RT-PCR and was admitted to the Japan East West Medical College Hospital in Bangladesh. In the ICU, the patient was in coma for 5 days. The Patient's condition was improved after taking fresh frozen plasma.