Search

Abstract Multilayer ceramic capacitor as a vital core-component for various applications is always in the spotlight. Next-generation electrical and electronic systems elaborate further requirements of multilayer ceramic capacitors in terms of higher energy storage capabilities, better stabilities, environmental-friendly lead-free, etc., where these major obstacles may restrict each other. An effective strategy for energy storage performance global optimization is put up here by constructing local polymorphic polarization configuration integrated with prototype device manufacturing. A large energy density of 20.0 J·cm−3 along with a high efficiency of 86.5%, and remarkable high-temperature stability, are achieved in lead-free multilayer ceramic capacitors. The strategy provides a feasible routine from nano, micro to macro regions in manipulating local polarizations, domain-switching barriers and breakdown strength, illustrating its great potential to be generally applicable in the design of high-performance energy storage multilayer ceramic capacitors.

Summary: Glioblastoma represents one of the most aggressive cancers, characterized by severely limited therapeutic options. Despite extensive investigations into this brain malignancy, cellular and molecular components governing its immunosuppressive microenvironment remain incompletely understood. Here, we identify a distinct neutrophil subpopulation, termed disease-specific suppressive granulocytes (DSSGs), present in human glioblastoma and lower-grade gliomas. DSSGs exhibit the concurrent expression of multiple immunosuppressive and immunomodulatory signals, and their abundance strongly correlates with glioma grades and poor clinical outcomes. Genetic disruption of neutrophil recruitment in immunocompetent mouse models of gliomas, achieved through Cxcl1 knockout in glioma cells or host-specific Cxcr2 deletion or diphtheria toxin A-mediated neutrophil depletion, can significantly enhance antitumor immunity and prolong survival. Further, we reveal that the skull bone marrow and meninges can be the primary sources of neutrophils and DSSGs in human and mouse glioma tumors. These findings demonstrate a critical mechanism underlying the establishment of the immunosuppressive microenvironment in gliomas.

BackgroundWe queried ChatGPT (OpenAI) and Google Assistant about amblyopia and compared their answers with the keywords found on the American Association for Pediatric Ophthalmology and Strabismus (AAPOS) website, specifically the section on amblyopia. Out of the 26 keywords chosen from the website, ChatGPT included 11 (42%) in its responses, while Google included 8 (31%). ObjectiveOur study investigated the adherence of ChatGPT-3.5 and Google Assistant to the guidelines of the AAPOS for patient education on amblyopia. MethodsChatGPT-3.5 was used. The four questions taken from the AAPOS website, specifically its glossary section for amblyopia, are as follows: (1) What is amblyopia? (2) What causes amblyopia? (3) How is amblyopia treated? (4) What happens if amblyopia is untreated? Approved and selected by ophthalmologists (GW and DL), the keywords from AAPOS were words or phrases that deemed significant for the education of patients with amblyopia. The “Flesch-Kincaid Grade Level” formula, approved by the US Department of Education, was used to evaluate the reading comprehension level for the responses from ChatGPT, Google Assistant, and AAPOS. ResultsIn their responses, ChatGPT did not mention the term “ophthalmologist,” whereas Google Assistant and AAPOS both mentioned the term once and twice, respectively. ChatGPT did, however, use the term “eye doctors” once. According to the Flesch-Kincaid test, the average reading level of AAPOS was 11.4 (SD 2.1; the lowest level) while that of Google was 13.1 (SD 4.8; the highest required reading level), also showing the greatest variation in grade level in its responses. ChatGPT’s answers, on average, scored 12.4 (SD 1.1) grade level. They were all similar in terms of difficulty level in reading. For the keywords, out of the 4 responses, ChatGPT used 42% (11/26) of the keywords, whereas Google Assistant used 31% (8/26). ConclusionsChatGPT trains on texts and phrases and generates new sentences, while Google Assistant automatically copies website links. As ophthalmologists, we should consider including “see an ophthalmologist” on our websites and journals. While ChatGPT is here to stay, we, as physicians, need to monitor its answers.

Abstract As the fourth largest CO2 emitter, Russia's constituent entities collectively contribute with vast territory and regional heterogeneity. Existing studies only present production‐based inventories; state‐level consumption‐based emissions patterns and driving forces remain rare. Here, we built the Russia state‐level Multi‐regional input‐output table to ascertain heterogeneity in consumption‐based emissions and track carbon flows in the inter‐state. We found that 60% of consumption‐based emissions coming from affluent areas (top 20% of the GRP), including Moscow (139.1 Mt) and St. Petersburg (50.5 Mt). Energy‐intensive regions also had huge consumption‐based emissions (31.6 Mt in Khanty‐Mansi Autonomous Okrug and 29.4 Mt in Republic of Tatarstan). Household consumption emissions accounted for 41%–73% of consumption‐based emissions in the 83 regions, except for Tula and Lipetsk, where fixed capital formation dominated. In addition, the major contributor of embodied emissions in households were power and services sectors, which contributed about 8%–61% (0.03 Mt–12.7 Mt) and 12%–40% (0.1 Mt–20.1 Mt). In Russia's low carbon transition, policymakers should not only focus on a local mitigation policy in developed states (such as Moscow and St. Petersburg), but on key sectors to curb the consumption. Regions with high carbon intensity should switch to renewable energy and implement cleaner production techniques in high‐emission industries.

Abstract The immense potential of lead-free dielectric capacitors in advanced electronic components and cutting-edge pulsed power systems has driven enormous investigations and evolutions heretofore. One of the significant challenges in lead-free dielectric ceramics for energy-storage applications is to optimize their comprehensive characteristics synergistically. Herein, guided by phase-field simulations along with rational composition-structure design, we conceive and fabricate lead-free Bi0.5Na0.5TiO3-Bi0.5K0.5TiO3-Sr(Sc0.5Nb0.5)O3 ternary solid-solution ceramics to establish an equitable system considering energy-storage performance, working temperature performance, and structural evolution. A giant W rec of 9.22 J cm−3 and an ultra-high ƞ ~ 96.3% are realized in the BNKT-20SSN ceramic by the adopted repeated rolling processing method. The state-of-the-art temperature (W rec ≈ 8.46 ± 0.35 J cm−3, ƞ ≈ 96.4 ± 1.4%, 25–160 °C) and frequency stability performances at 500 kV cm−1 are simultaneously achieved. This work demonstrates remarkable advances in the overall energy storage performance of lead-free bulk ceramics and inspires further attempts to achieve high-temperature energy storage properties.

Objectives “Floaters,” a common complaint among patients of all ages, was used as a query term because it affects 30% of all people searching for eye care. The American Academy of Ophthalmology website's “floaters” section was used as a source for questions and answers ( www.aao.org ). Floaters is a visual obstruction that moves with the movement of the eye. They can be associated with retinal detachment, which can lead to vision loss. With the advent of large language model (LLM) chatbots ChatGPT, Bard versus virtual assistants (VA), Google Assistant, and Alexa, we analyzed their responses to “floaters.” Methods Using AAO.org, “Public & Patients,” and its related subsection, “EyeHealth A-Z”: Floaters and Flashes link, we asked four questions: (1) What are floaters? (2) What are flashes? (3) Flashes and Migraines? (4) Floaters and Flashes Treatment? to ChatGPT, Bard, Google Assistant, and Alexa. The American Academy of Ophthalmology (AAO) keywords were identified if they were highlighted. The “Flesch-Kincaid Grade Level” formula approved by the U.S. Department of Education, was used to evaluate the reading comprehension level for the responses. Results Of the chatbots and virtual assistants, Google Assistant is the only one that uses the term “ophthalmologist.” There is no mention of the urgency or emergency nature of floaters. AAO.org shows a lower reading level vs the LLMs and VA ( p = .11). The reading comprehension levels of ChatGPT, Bard, Google Assistant, and Alexa are higher (12.3, 9.7, 13.1, 8.1 grade) vs the AAO.org (7.3 grade). There is a higher word count for LLMs vs VA ( p

Summary: Successful genome editing in primary human islets could reveal features of the genetic regulatory landscape underlying β cell function and diabetes risk. Here, we describe a CRISPR-based strategy to interrogate functions of predicted regulatory DNA elements using electroporation of a complex of Cas9 ribonucleoprotein (Cas9 RNP) and guide RNAs into primary human islet cells. We successfully targeted coding regions including the PDX1 exon 1, and non-coding DNA linked to diabetes susceptibility. CRISPR-Cas9 RNP approaches revealed genetic targets of regulation by DNA elements containing candidate diabetes risk SNPs, including an in vivo enhancer of the MPHOSPH9 gene. CRISPR-Cas9 RNP multiplexed targeting of two cis-regulatory elements linked to diabetes risk in PCSK1, which encodes an endoprotease crucial for Insulin processing, also demonstrated efficient simultaneous editing of PCSK1 regulatory elements, resulting in impaired β cell PCSK1 regulation and Insulin secretion. Multiplex CRISPR-Cas9 RNP provides powerful approaches to investigate and elucidate human islet cell gene regulation in health and diabetes.

PurposeOur study investigates ChatGPT and its ability to communicate with glaucoma patients.MethodsWe inputted eight glaucoma-related questions/topics found on the American Academy of Ophthalmology (AAO)’s website into ChatGPT. We used the Flesch–Kincaid test, Gunning Fog Index, SMOG Index, and Dale–Chall readability formula to evaluate the comprehensibility of its responses for patients. ChatGPT’s answers were compared with those found on the AAO’s website.ResultsChatGPT’s responses required reading comprehension of a higher grade level (average = grade 12.5 ± 1.6) than that of the text on the AAO’s website (average = 9.4 grade ± 3.5), (0.0384). For the eight responses, the key ophthalmic terms appeared 34 out of 86 times in the ChatGPT responses vs. 86 out of 86 times in the text on the AAO’s website. The term “eye doctor” appeared once in the ChatGPT text, but the formal term “ophthalmologist” did not appear. The term “ophthalmologist” appears 26 times on the AAO’s website. The word counts of the answers produced by ChatGPT and those on the AAO’s website were similar (p = 0.571), with phrases of a homogenous length.ConclusionChatGPT trains on the texts, phrases, and algorithms inputted by software engineers. As ophthalmologists, through our websites and journals, we should consider encoding the phrase “see an ophthalmologist”. Our medical assistants should sit with patients during their appointments to ensure that the text is accurate and that they fully comprehend its meaning. ChatGPT is effective for providing general information such as definitions or potential treatment options for glaucoma. However, ChatGPT has a tendency toward repetitive answers and, due to their elevated readability scores, these could be too difficult for a patient to read.

Based on the metal elements contained in crude zinc, the evaporation kinetic experiments of the Cd-Zn, Bi-Zn and Bi-Sn-Zn systems in vacuum distillation were carried out. The Langmuir formula was used for theoretical prediction of evaporation rate. The results are in good agreement with the experimental data. It indicates that the method of evaporation rate calculation is applicable. The condensation coefficients of zinc in the alloys were calculated. The relationship between the interaction and the evaporation rate of components in the alloys was discussed. It will be helpful to the separation and purification of crude zinc and the optimization of experimental equipmentby vacuum distillation.

Abstract Improved models of experimental diabetes are needed to develop cell therapies for diabetes. Here, we introduce the B6 RIP-DTR mouse, a model of experimental diabetes in fully immunocompetent animals. These inbred mice harbor the H2b major histocompatibility complex (MHC), selectively express high affinity human diphtheria toxin receptor (DTR) in islet β-cells, and are homozygous for the Ptprc a (CD45.1) allele rather than wild-type Ptprc b (CD45.2). 100% of B6 RIP-DTR mice rapidly became diabetic after a single dose of diphtheria toxin, and this was reversed indefinitely after transplantation with islets from congenic C57BL/6 mice. By contrast, MHC-mismatched islets were rapidly rejected, and this allotransplant response was readily monitored via blood glucose and graft histology. In peripheral blood of B6 RIP-DTR with mixed hematopoietic chimerism, CD45.2 BALB/c donor blood immune cells were readily distinguished from host CD45.1 cells by flow cytometry. Reliable diabetes induction and other properties in B6 RIP-DTR mice provide an important new tool to advance transplant-based studies of islet replacement and immunomodulation to treat diabetes.

Nanotechnology emerges as an important way to safeguard global food security amid the escalating challenges posed by the expansion of the global population and the impacts of climate change. The perfect fusion of this breakthrough technology with traditional agriculture promises to revolutionize the way agriculture is traditionally practiced and provide effective solutions to the myriad of challenges in agriculture. Particularly noteworthy are the applications of nano-fertilizers and pesticides in agriculture, which have become milestones in sustainable agriculture and offer lasting alternatives to traditional methods. This review meticulously explores the key role of nano-fertilizers and pesticides in advancing sustainable agriculture. By focusing on the dynamic development of nanotechnology in the field of sustainable agriculture and its ability to address the overarching issue of global food security, this review aims to shed light on the transformative potential of nanotechnology to pave the way for a more resilient and sustainable future for agriculture.

It is estimated that 40–70%, 80–90% and 50–90% of the conventional macronutrients N, P and K applied to the soil are lost, respectively, resulting in considerable loss of resources. Compared to conventional fertilizers, nanofertilizers have the advantages of controlled release, high nutrient utilization, low cost and relatively low environmental pollution due to their small size (1–100 nm) and high specific surface area. The application of nanofertilizers is an up-and-coming field of agricultural research and is an attractive and economical substitute for common fertilizers which can boost global food productivity sustainably. Foliar fertilization is a popular way to satisfy the needs of higher plants. Because of its small application dose, faster nutrient uptake than soil application and relatively less environmental pollution, foliar fertilization is more popular among plants. It can be seen that nanofertilizers and foliar fertilization are the hotspots of attention at present and that current research on the foliar application of nanofertilizers is not as extensive as that on soil application. Based on this background, this paper provides an overview of various applications of foliar spraying of nanofertilizers in agriculture, including applications in improving crop yield and quality as well as mitigating heavy metal stress, salt stress and drought stress.

This article presents a method for extracting neural signal features to identify the imagination of left- and right-hand grasping movements. A functional magnetic resonance imaging (fMRI) experiment is employed to identify four brain regions with significant activations during motor imagery (MI) and the effective connections between these regions of interest (ROIs) were calculated using Dynamic Window-level Granger Causality (DWGC). Then, a real-time fMRI (rt-fMRI) classification system for left- and right-hand MI is developed using the Open-NFT platform. We conducted data acquisition and processing on three subjects, and all of whom were recruited from a local college. As a result, the maximum accuracy of using Support Vector Machine (SVM) classifier on real-time three-class classification (rest, left hand, and right hand) with effective connections is 69.3%. And it is 3% higher than that of traditional multivoxel pattern classification analysis on average. Moreover, it significantly improves classification accuracy during the initial stage of MI tasks while reducing the latency effects in real-time decoding. The study suggests that the effective connections obtained through the DWGC method serve as valuable features for real-time decoding of MI using fMRI. Moreover, they exhibit higher sensitivity to changes in brain states. This research offers theoretical support and technical guidance for extracting neural signal features in the context of fMRI-based studies.

Measurement(s) carbon dioxide emission Technology Type(s) digital curation Factor Type(s) sub-national constituent entity • year Sample Characteristic - Environment climate system Sample Characteristic - Location Russia Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14798694

The editing of primary human islets could provide insight into diabetes pathogenesis. Here the authors use CRISPR-Cas9 to target regulatory elements associated with T2D susceptibility.

To ensure food safety, the current agricultural development has put forward requirements for improving nutritional quality and reducing the harmful accumulation of agricultural chemicals. Nano-enabled sustainable agriculture and food security have been increasingly explored as a new research frontier. Nano-fertilizers show the potential to be more efficient than traditional fertilizers, reducing the amount used while ensuring plant uptake, supplying the inorganic nutrients needed by plants, and improving the process by which plants produce organic nutrients. Other agricultural uses of nanotechnology affect crop productivity and nutrient quality in addition to nano-fertilizers. This article will review the research progress of using nanomaterials to improve nutritional quality in recent years and point out the focus of future research.

Glucose concentration is an important physiological index, therefore methods for sensitive detection of glucose are important. In this study, Au foam was prepared by electrodeposition with a dynamic gas template on an Au nanoparticle/Si substrate. The Au foam showed ultrasensitivity, high selectivity, and long-term stability in the quantitative detection of glucose. The foam was used as an electrode, and the amperometric response indicated excellent catalytic activity in glucose oxidation, with a linear response across the concentration range 0.5 μM to 12 mM, and a limit of detection of 0.14 μM. High selectivity for interfering molecules at six times the normal level and long-term stability for 30 days were obtained. The results for electrochemical detection with Au foam of glucose in human serum were consistent with those obtained with a sensor based on surface-enhanced Raman spectroscopy and a commercial sensor. This proves that this method can be used with real samples. These results show that Au foam has great potential for use as a non-enzymatic glucose sensor.