Is epinephrine still the drug of choice during cardiac arrest in the emergency department of the hospital? A meta-analysis

Epinephrine is the first-line emergency drug for cardiac arrest and anaphylactic reactions but is reported to be associated with many challenges resulting in its under- or improper utilization. Therefore, in this meta-analysis, the efficacy and safety of epinephrine as a first-line cardiac emergency drug for both out-of-hospital and in-hospital patients was assessed. Pertinent articles were searched in central databases like PubMed, Scopus, and Web of Science, using appropriate keywords as per the PRISMA guidelines. Retrospective and prospective studies were included according to the predefined PICOS criteria. RevMan and MedCalc software were used and statistical parameters such as odds ratio and risk ratio were calculated. Twelve clinical trials with a total of 208,690 cardiac arrest patients from 2000 to 2022 were included, in accordance with the chosen inclusion criteria. In the present meta-analysis, a high odds ratio (OR) value of 3.67 (95 % CI 2.32–5.81) with a tau2 value of 0.64, a chi2 value of 12,446.86, df value of 11, I2 value of 100 %, Z-value 5.53, and a p-value < 0.00001 were reported. Similarly, the risk ratio of 1.89 (95 % CI 1.47–2.43) with a tau2 value of 0.19, chi2 value of 11,530.67, df value of 11, I2 value of 100 %, Z-value of 4.95, and p-value < 0.000001. The present meta-analysis strongly prefers epinephrine injection as the first cardiac emergency drug for both out-of-hospital and in-hospital patients during cardiac arrest

A Pilot Trial Assessing Urinary Gene Expression Profiling with an mRNA Array for Diabetic Nephropathy

BACKGROUND: The initiation and progression of diabetic nephropathy (DN) is complex. Quantification of mRNA expression in urinary sediment has emerged as a novel strategy for studying renal diseases. Considering the numerous molecules involved in DN development, a high-throughput platform with parallel detection of multiple mRNAs is needed. In this study, we constructed a self-assembling mRNA array to analyze urinary mRNAs in DN patients with aims to reveal its potential in searching novel biomarkers. METHODS: mRNA array containing 88 genes were fabricated and its performance was evaluated. A pilot study with 9 subjects including 6 DN patients and 3 normal controls were studied with the array. DN patients were assigned into two groups according to their estimate glomerular rate (eGFR): DNI group (eGFR>60 ml/min/1.73 m(2), n = 3) and DNII group (eGFR<60 ml/min/1.73 m(2), n = 3). Urinary cell pellet was collected from each study participant. Relative abundance of these target mRNAs from urinary pellet was quantified with the array. RESULTS: The array we fabricated displayed high sensitivity and specificity. Moreover, the Cts of Positive PCR Controls in our experiments were 24±0.5 which indicated high repeatability of the array. A total of 29 mRNAs were significantly increased in DN patients compared with controls (p<0.05). Among these genes, α-actinin4, CDH2, ACE, FAT1, synaptopodin, COL4α, twist, NOTCH3 mRNA expression were 15-fold higher than those in normal controls. In contrast, urinary TIMP-1 mRNA was significantly decreased in DN patients (p<0.05). It was shown that CTGF, MCP-1, PAI-1, ACE, CDH1, CDH2 mRNA varied significantly among the 3 study groups, and their mRNA levels increased with DN progression (p<0.05). CONCLUSION: Our pilot study demonstrated that mRNA array might serve as a high-throughput and sensitive tool for detecting mRNA expression in urinary sediment. Thus, this primary study indicated that mRNA array probably could be a useful tool for searching new biomarkers for DN

A new tool for in vitro culture of porcine eggs

Mineral oil is usually used to cover the microdrops of medium in oocytes or embryos culture system here designated as oil method. A large number of oocytes are needed for the production of porcine embryos for in vitro fertilization or somatic cell nuclear transfer (SCNT). The oil method not only wastes a lot of mineral oil, but needs tedious steps in the transferring of embryos. Here we designed a new method called nest dish, which need not mineral oil, to replace the oil method and improve the development rates of porcine eggs in vitro. The oocyte maturation rate with the mTCM199 (83.2%) was significantly higher than with the NCSU23 (75.5%, P﹤ 0.05), although the parthenogenetic cleavage rates with two media were not significantly different (77.7 and 72.4%, P﹤ 0.05 ). Chosing mTCM199 as base medium, the rate of maturation with concave dish (90.1%) was significantly higher than with the flat dish (82.6%, P﹥ 0.05) in nest method, although no significant differences in the oocyte maturation were found between flat dish (82.6%) in nest method and oil method (80.0%). Parthenogenetic cleavage from nest method (80.1% for concave dish, 78.0% for flat dish) did not show any decrease compared to oil method (76.2%), but the developmental rate to blastocysts in the nest groups(17.9 and 19.5%) were significantly higher than the oil method (12.3%, P﹤ 0.05). These results showed that mTCM199 presented higher maturation rate than that NCSU-23 did, and the nest method with concave dish significantly improved the maturation rate of porcine oocytes in vitro and can replace the conventional oil method.Keywords: Porcine oocytes, in vitro maturation (IVM), microdrop method, nest dish metho

Lattice marginal reconstruction enabled high ambient-tolerance Perovskite Quantum Dots phototransistors

Perovskite quantum dots (PeQDs) have been developed rapidly as photoactive materials in hybrid phototransistors because of their strong light absorption, broad bandgap customizability, and defect-tolerance in charge-transport properties. The solvent treatment has been well recognized as a practical approach for improving the charge transport of PeQDs and the photoresponsivity of PeQD phototransistors. However, there is a lack of fundamental understanding of the origin of its impacts on the material’s ambient stability as well as phototransistor’s operational lifetime. Especially, the relationship between surface ligands dissociation and their microstructural reconstruction has not been fully elucidated so far. Herein, we report that a simultaneous enhancement of photoresponsivity and ambient tolerance for PeQD-based hybrid phototransistors can be realized via medium-polarity-solvent treatment on solid-state PeQDs. Our comprehensive optoelectronic characterization and electron microscopic study reveals that the crystal morphology, instead of surface ligands, is the dominating factor that results in the PeQD’s stability enhancement associated with the preservation of optical property and quantum confinement. Besides, we unveil a marginal reconstruction process occurred during solvent treatment, which opens up a new route for facets-oriented attachment of PeQDs along the zone axis to suppress the damage from water molecules penetration. Our study yields a new understanding of the solvent impact on PeQD microstructures reconstruction and suggests new routes for perovskite materials and corresponding device operational stability enhancement

Effects of acidification on nitrification and associated nitrous oxide emission in estuarine and coastal waters

In the context of an increasing atmospheric carbon dioxide (CO2) level, acidification of estuarine and coastal waters is greatly exacerbated by land-derived nutrient inputs, coastal upwelling, and complex biogeochemical processes. A deeper understanding of how nitrifiers respond to intensifying acidification is thus crucial to predict the response of estuarine and coastal ecosystems and their contribution to global climate change. Here, we show that acidification can significantly decrease nitrification rate but stimulate generation of byproduct nitrous oxide (N2O) in estuarine and coastal waters. By varying CO2 concentration and pH independently, an expected beneficial effect of elevated CO2 on activity of nitrifiers (“CO2-fertilization” effect) is excluded under acidification. Metatranscriptome data further demonstrate that nitrifiers could significantly up-regulate gene expressions associated with intracellular pH homeostasis to cope with acidification stress. This study highlights the molecular underpinnings of acidification effects on nitrification and associated greenhouse gas N2O emission, and helps predict the response and evolution of estuarine and coastal ecosystems under climate change and human activities.publishedVersio

Toward a high-precision mass–energy test of the equivalence principle with atom interferometers

The equivalence principle (EP) is a basic assumption of the general relativity. The quantum test of the equivalence principle with atoms is an important way to examine the applicable scope of the current physical framework so as to discover new physics. Recently, we extended the traditional pure mass or energy tests of the equivalence principle to the joint test of mass–energy by atom interferometry (Zhou et al.,Phys.Rev.A 104,022822). The violation parameter of mass is constrained to η0 = (−0.8 ± 1.4) × 10–10 and that of internal energy to ηE = (0.0 ± 0.4) × 10–10 per reduced energy ratio. Here, we first briefly outline the joint test idea and experimental results, and then, we analyze and discuss how to improve the test accuracy. Finally, we report the latest experimental progress toward a high-precision mass–energy test of the equivalence principle. We realize atom interference fringes of 2T = 2.6 s in the 10-m long-baseline atom interferometer. This free evolution time T, to the best of our knowledge, is the longest duration realized in the laboratory, and the corresponding resolution of gravity measurement is 4.5 × 10−11 g per shot

A Survey of Large Language Models

Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for comprehending and grasping a language. As a major approach, language modeling has been widely studied for language understanding and generation in the past two decades, evolving from statistical language models to neural language models. Recently, pre-trained language models (PLMs) have been proposed by pre-training Transformer models over large-scale corpora, showing strong capabilities in solving various NLP tasks. Since researchers have found that model scaling can lead to performance improvement, they further study the scaling effect by increasing the model size to an even larger size. Interestingly, when the parameter scale exceeds a certain level, these enlarged language models not only achieve a significant performance improvement but also show some special abilities that are not present in small-scale language models. To discriminate the difference in parameter scale, the research community has coined the term large language models (LLM) for the PLMs of significant size. Recently, the research on LLMs has been largely advanced by both academia and industry, and a remarkable progress is the launch of ChatGPT, which has attracted widespread attention from society. The technical evolution of LLMs has been making an important impact on the entire AI community, which would revolutionize the way how we develop and use AI algorithms. In this survey, we review the recent advances of LLMs by introducing the background, key findings, and mainstream techniques. In particular, we focus on four major aspects of LLMs, namely pre-training, adaptation tuning, utilization, and capacity evaluation. Besides, we also summarize the available resources for developing LLMs and discuss the remaining issues for future directions.Comment: ongoing work; 51 page

Biological Bone Micro Grinding Temperature Field under Nanoparticle Jet Mist Cooling

Clinical neurosurgeons used micro grinding to remove bone tissues, and drip irrigation-type normal saline (NS) is used with low cooling efficiency. Osteonecrosis and irreversible thermal neural injury caused by excessively high grinding temperature are bottleneck problems in neurosurgery and have severely restricted the application of micro grinding in surgical procedures. Therefore, a nanoparticle jet mist cooling (NJMC) bio-bone micro grinding process is put forward in this chapter. The nanofluid convective heat transfer mechanism in the micro grinding zone is investigated, and heat transfer enhancement mechanism of solid nanoparticles and heat distribution mechanism in the micro grinding zone are revealed. On this basis, a temperature field model of NJMC bio-bone micro grinding is established. An experimental platform of NJMC bio-bone micro grinding is constructed, and bone micro grinding force and temperatures at different measuring points on the bone surface are measured. The results indicated that the model error of temperature field is 6.7%, theoretical analysis basically accorded with experimental results, thus certifying the correctness of the dynamic temperature field in NJMC bio-bone micro grinding