Laser solid-phase synthesis of graphene shell-encapsulated high-entropy alloy nanoparticles.

Rapid synthesis of high-entropy alloy nanoparticles (HEA NPs) offers new opportunities to develop functional materials in widespread applications. Although some methods have successfully produced HEA NPs, these methods generally require rigorous conditions such as high pressure, high temperature, restricted atmosphere, and limited substrates, which impede practical viability. In this work, we report laser solid-phase synthesis of CrMnFeCoNi nanoparticles by laser irradiation of mixed metal precursors on a laser-induced graphene (LIG) support with a 3D porous structure. The CrMnFeCoNi nanoparticles are embraced by several graphene layers, forming graphene shell-encapsulated HEA nanoparticles. The mechanisms of the laser solid-phase synthesis of HEA NPs on LIG supports are investigated through theoretical simulation and experimental observations, in consideration of mixed metal precursor adsorption, thermal decomposition, reduction through electrons from laser-induced thermionic emission, and liquid beads splitting. The production rate reaches up to 30 g/h under the current laser setup. The laser-synthesized graphene shell-encapsulated CrMnFeCoNi NPs loaded on LIG-coated carbon paper are used directly as 3D binder-free integrated electrodes and exhibited excellent electrocatalytic activity towards oxygen evolution reaction with an overpotential of 293 mV at the current density of 10 mA/cm2 and exceptional stability over 428 h in alkaline media, outperforming the commercial RuO2 catalyst and the relevant catalysts reported by other methods. This work also demonstrates the versatility of this technique through the successful synthesis of CrMnFeCoNi oxide, sulfide, and phosphide nanoparticles.

Comparative Review of Standardized Incidence Ratio of Nonlymphoid, De Novo Malignancies After Liver Transplant Versus After Kidney Transplant.

OBJECTIVES: De novo malignancies are the most common cause of death after solid-organ transplant. Here, we aimed to summarize standard incidence ratios of de novo malignancies after liver and kidney transplant within the same geographical locations, compare these ratios among differenttypes of de novo malignancies after liver and kidney transplant, and elucidate differences in de novo malignancies between liver and kidney transplant recipients. MATERIALS AND METHODS: We performed a systematic review to identify studies on standard incidence ratios of de novo malignancies after liver and kidney transplant in the United Kingdom, Sweden, South Korea, and Taiwan. RESULTS: Four articles reported standard incidence ratios of de novo malignancies in 14 016 liver transplant recipients (mean follow-up 4.3 ± 0.7 y) and 48179 kidney transplant recipients (mean follow-up 6.1 ± 2.1 y). Mean ratios of oropharyngeal, pulmonary, colorectal, renal, and breast malignancies were 5.3, 1.6, 1.9, 1.8, and 1.1,respectively, after liver transplant and 3.2, 1.7, 1.5, 17.0, and 1.3, respectively, after kidney transplant. Mean ratios of bladder, cervixuterus, and stomach de novo malignancies were 1.8, 2.0, and 2.9, respectively, after liver transplant and 13.0, 1.9, and 1.9,respectively, after kidney transplant. Mean ratios of prostatic and esophageal malignancies were 1.6 and 1.8 after liver transplant and 1.2 and 1.1 after kidney transplant. Mean ratio of ovarian cancer was 1.2 and 2.9, respectively, after liver and kidney transplant. CONCLUSIONS: Low-frequency and lower standard incidence ratios were observed for testicular, ovarian and central nervous system malignancies after kidney and liver transplant. Standard incidence ratios of oropharyngeal and hepatic malignancies were higher after liver transplant compared with kidney transplant. After kidney transplant, standardized ration for renal malignancy were 9.4 times and bladder malignancies were 7.2 times higher compared with liver transplant recipients.

ß-Cyclodextrin metal-organic framework as a green carrier to improve the dissolution, bioavailability, and liver protective effect of luteolin.

The incidence of acetaminophen-induced liver injury has increased, but effective prevention methods are limited. Although luteolin has hepatoprotective activity, its low solubility and bioavailability limit its applications. Cyclodextrin metal-organic frameworks (CD-MOFs) possess 3D-network structures and large inner cavities, which make them excellent carriers of poorly soluble drugs. In this study, we used CD-MOFs as carriers to improve the dissolution of luteolin and assessed their antioxidant activity, bioavailability, and hepatoprotective effects. Luteolin was loaded into ß-CD-MOF, γ-CD-MOF, ß-CD, and γ-CD, and characterized by powder X-ray diffractometry (PXRD) and thermogravimetric analysis (TGA). Our results showed that luteolin-ß-CD-MOF was the most stable. The main driving forces were hydrogen bonds and van der Waals forces, as determined by molecular simulation. The loading capacity of luteolin-ß-CD-MOF was 14.67 wt%. Compared to raw luteolin, luteolin-ß-CD-MOF exhibited a 4.50-fold increase in dissolution and increased antioxidant activity in vitro. Luteolin-ß-CD-MOF increased the bioavailability of luteolin by approximately 4.04- and 11.07-fold in healthy rats and liver injured rats induced by acetaminophen in vivo, respectively. As determined by biochemical analysis, luteolin-ß-CD-MOF exhibited a better hepatoprotective effect than raw luteolin in rats with acetaminophen-induced liver injury. This study provides a new approach for preventing acetaminophen-mediated liver damage.

Coupling enzymatic activity and gating in an ancient TRPM chanzyme and its molecular evolution.

Channel enzymes represent a class of ion channels with enzymatic activity directly or indirectly linked to their channel function. We investigated a TRPM2 chanzyme from choanoflagellates that integrates two seemingly incompatible functions into a single peptide: a channel module activated by ADP-ribose with high open probability and an enzyme module (NUDT9-H domain) consuming ADP-ribose at a remarkably slow rate. Using time-resolved cryogenic-electron microscopy, we captured a complete series of structural snapshots of gating and catalytic cycles, revealing the coupling mechanism between channel gating and enzymatic activity. The slow kinetics of the NUDT9-H enzyme module confers a self-regulatory mechanism: ADPR binding triggers NUDT9-H tetramerization, promoting channel opening, while subsequent hydrolysis reduces local ADPR, inducing channel closure. We further demonstrated how the NUDT9-H domain has evolved from a structurally semi-independent ADP-ribose hydrolase module in early species to a fully integrated component of a gating ring essential for channel activation in advanced species.

Polysaccharides from Phellinus linteus attenuate type 2 diabetes mellitus in rats via modulation of gut microbiota and bile acid metabolism.

Type 2 diabetes mellitus (T2DM) is the most prevalent metabolic disorder. Polysaccharides from Phellinus linteus (PLP) have been found to have anti-diabetes effects, but the mechanism has not been elucidated. The purpose of this study was to investigate the mechanism of PLP on T2DM through the gut microbiota and bile acids metabolism. The T2DM rat model was induced by a high-fat high-carbohydrate (HFHC) diet and streptozocin (30 mg/kg). We found that PLP ameliorated diabetes symptoms. Besides, PLP intervention increased the abundance of g_Bacteroides, g_Parabacteroides, and g_Alistioes, which are associated with the biosynthesis of short-chain fatty acids (SCFAs) and bile acids (BAs) metabolism. Meanwhile, untargeted and targeted metabolomics indicated that PLP could regulate the composition of BAs and increase the levels of SCFAs. Real-time quantitative PCR (RT-qPCR) and enzyme-linked immunosorbent assay (ELISA) were performed to analyze the expression levels of BAs metabolism enzymes in the liver. Finally, the results of correlation analysis and Glucagon-like peptide-1 (GLP-1) showed that PLP stimulated the release of GLP-1 by regulating SCFAs and BAs. In conclusion, this study demonstrated that PLP can regulate gut microbiota and BAs metabolism to promote GLP-1 secretion, thereby increasing insulin release, decreasing blood glucose and attenuating T2DM.

Bile acids metabolism involved in the beneficial effects of Danggui Shaoyao San via gut microbiota in the treatment of CCl4 induced hepatic fibrosis.

ETHNOPHARMACOLOGICAL RELEVANCE: Danggui Shaoyao San (DSS) is a traditional Chinese medicine (TCM) first recorded in the Synopsis of the Golden Chamber. DSS has proven efficacy in treating hepatic fibrosis (HF). However, the effects and mechanisms of DSS on HF are not clear. AIM OF THE STUDY: To investigate the effect of DSS on HF via gut microbiota and its metabolites (SCFAs, BAs). MATERIALS AND METHODS: HF rats were induced with CCl4 and treated with DSS. Firstly, the therapeutic efficacy of DSS in HF rats and the protection of gut barrier were assessed. Then, 16S rRNA gene sequencing and untargeted fecal metabolomics preliminarily explored the mechanism of DSS in treating HF, and identified different microbiota and metabolic pathways. Finally, targeted metabolomics and RT-qPCR were used to further validate the mechanism of DSS for HF based on the metabolism of SCFAs and BAs. RESULTS: After 8 weeks of administration, DSS significantly reduced the degree of HF. In addition, DSS alleviated inflammation in the ileum and reduced the levels of LPS and D-lactate. Furthermore, DSS altered the structure of gut microbiota, especially Veillonella, Romboutsia, Monoglobus, Parabacteroides, norank_f_Coriobacteriales_Incertae_Sedis. These bacteria have been linked to the production of SCFAs and the metabolism of BAs. Untargeted metabolomics suggested that DSS may play a role via BAs metabolism. Subsequently, targeted metabolomics and RT-qPCR further confirmed the key role of DSS in increasing SCFAs levels and regulating BAs metabolism. CONCLUSIONS: DSS can alleviate CCl4-induced HF and protect the gut barrier. DSS may exert its beneficial effects on HF by affecting the gut microbiota and its metabolites (SCFAs, BAs).

Dispersive solid phase extraction based on cross-linked hydroxypropyl ß-cyclodextrin polymers for simultaneous enantiomeric determination of three chiral triazole fungicides in water.

An efficient method is presented for simultaneous enantioselective determination of three chiral triazole fungicides (namely paclobutrazol, hexaconazole, and diniconazole) in water samples by DSPE-HPLC-UV. The perfect chiral separation of the enantiomers was achieved on a Chiralpak IH column within 15 min. In order to adsorb and enrich the analytes from water matrices, a cross-linked hydroxypropyl ß-cyclodextrin polymer was synthesized. The prepared material exhibited good adsorption capacity, which was assessed by adsorption kinetic and adsorption thermodynamic experiments. One-variable-at-a-time and the response surface methodology were used to optimize the extraction parameters. Under the optimum sample preparation conditions, good linearity (2.0 ~ 800 µg L-1, R2 ≥ 0.9978), detection limits (0.6 to 1.0 µg L-1), quantitation limits (2.0 to 3.2 µg L-1), recoveries (86.7 ~ 105.8%), and the relative standard deviation (intra-day RSD ≤ 3.7%, inter-day RSD ≤ 5.1%) were obtained, satisfying the requirements of pesticides residues determination. These results demonstrated that the proposed method was applicable for routine determination of chiral triazole fungicide residues in water samples.

Ethanol extract of Pueraria lobata improve acute myocardial infarction in rats via regulating gut microbiota and bile acid metabolism.

BACKGROUND AND AIM: Acute myocardial infarction (AMI) is a multifactorial disease with high mortality rate worldwide. Ethanol extract of Pueraria lobata (EEPL) has been widely used in treating cardiovascular diseases in China. This study aimed to explore the underlying therapeutic mechanism of EEPL in AMI rats. EXPERIMENTAL PROCEDURE: We first evaluated the anti-AMI efficacy of EEPL through immunohistochemistry staining and biochemical indexes. Then, UPLC-MS/MS, 16S rDNA, and shotgun metagenomic sequencing were used to analyze the alterations in bile acid metabolism and intestinal flora. Finally, the influence of EEPL on ilem bile acid metabolism, related enzymes expression, and transporter proteins expression in rats were verified by mass spectrometry image and ELISA. KEY RESULTS: The results showed that EEPL can reduce cardiac impairment in AMI rats. Besides, EEPL effectively increased bile acid levels and regulated gut microbiota disturbance in AMI rats via increasing CYP7A1 expression and restoring intestinal microbiota diversity, separately. Moreover, it can increase bile acids reabsorption and fecal excretion through inhibiting FXR-FGF15 signaling pathway and increasing OST-α expression, which associated with Lachnoclostridium. CONCLUSIONS AND IMPLICATIONS: Our findings demonstrated that EEPL alleviated AMI partially by remediating intestinal dysbiosis and promoting bile acid biosynthesis, which provided new targets for AMI treatment.

Coupling enzymatic activity and gating in an ancient TRPM chanzyme and its molecular evolution.

The canonical ion channels gated by chemical ligands use the free energy of agonist binding to open the channel pore, returning to a closed state upon agonist departure. A unique class of ion channels, known as channel-enzymes (chanzymes), possess additional enzymatic activity that is directly or indirectly linked to their channel function. Here we investigated a TRPM2 chanzyme from choanoflagellates, an evolutionary ancestor of all metazoan TRPM channels, which integrates two seemingly incompatible functions into a single peptide: a channel module activated by ADP ribose (ADPR) with high open probability and an enzyme module (NUDT9-H domain) consuming ADPR at a remarkably slow rate. Using time-resolved cryo- electron microscopy (cryo-EM), we captured a complete series of structural snapshots of the gating and catalytic cycles, revealing the coupling mechanism between channel gating and enzymatic activity. Our results showed that the slow kinetics of the NUDT9-H enzyme module confers a novel self-regulatory mechanism, whereby the enzyme module modulates channel gating in a binary manner. Binding of ADPR to NUDT9-H first triggers tetramerization of the enzyme modules, promoting channel opening, while the subsequent hydrolysis reaction reduces local ADPR availability, inducing channel closure. This coupling enables the ion-conducting pore to alternate rapidly between open and closed states, avoiding Mg 2+ and Ca 2+ overload. We further demonstrated how the NUDT9-H domain has evolved from a structurally semi-independent ADPR hydrolase module in early species TRPM2 to a fully integrated component of a gating ring essential for channel activation in advanced species TRPM2. Our study demonstrated an example of how organisms can adapt to their environments at the molecular level.

Profiling of intracellular and extracellular antibiotic resistance genes in municipal wastewater treatment plant and their effluent-receiving river.

The presence of antibiotic resistance genes (ARGs) and heavy metal resistance genes (MRGs) in extracellular and intracellular DNA (eDNA and iDNA) has received considerable attention in recent years owing to the potential threat to human health and the ecosystem. As a result, we investigated six ARGs, three MRGs, and two mobile genetic elements (MGEs) in the municipal wastewater treatment plant (MWWTP) and its adjacent environments. Results revealed that the absolute abundances of eARGs and eMRGs were lower than iARGs and iMRGs in MWWTP. By contrast, eARGs and eMRGs were higher in river sediments. Among ARGs, aminoglycoside resistance genes (aadA) was the most abundant gene (3.13 × 102 to 2.31 × 106 copies/mL in iDNA; 1.27 × 103 to 7.23 × 105 copies/mL in eDNA) in MWWTP, while zntA gene (9.4 × 102 to 3.97 × 106 copies/mL in iDNA; 3.2 × 103 to 6 × 105 copies/mL in eDNA) was amongst the MRGs. Notably, intI1 was enriched and positively correlated with iDNA (tetA, sul1, blaCTX-M, ermB, and merA) and eDNA (blaCTX-M, ermB, and merA), demonstrating its function in the proliferation of resistance genes. This widespread distribution of ARGs, MRGs, and MGEs in MWWTP and its adjacent river sediments will help clarify the transmission routes within these environments and provide a theoretical basis for better monitoring and mitigation of such dissemination.

Determination of the components of danyikangtai powder into the plasma and its pharmacodynamic study.

Danyikangtai powder has a definite therapeutic effect on pancreatitis. However, the internal mechanism is unclear. The purpose of this experiment is to quickly identify the blood components of danyikangtai powder and evaluate its efficacy. 25 blood components were identified by comparing the components with the same mass spectrometry information from in vivo and in vitro samples. The AR42J cells of the pancreatitis model were treated with drug-containing plasma, and the drug efficacy was evaluated by investigating the amylase release rate. This study provides a scientific reference for its pharmacological research and rational clinical application.

Predicting Protein-Ligand Docking Structure with Graph Neural Network.

Modern day drug discovery is extremely expensive and time consuming. Although computational approaches help accelerate and decrease the cost of drug discovery, existing computational software packages for docking-based drug discovery suffer from both low accuracy and high latency. A few recent machine learning-based approaches have been proposed for virtual screening by improving the ability to evaluate protein-ligand binding affinity, but such methods rely heavily on conventional docking software to sample docking poses, which results in excessive execution latencies. Here, we propose and evaluate a novel graph neural network (GNN)-based framework, MedusaGraph, which includes both pose-prediction (sampling) and pose-selection (scoring) models. Unlike the previous machine learning-centric studies, MedusaGraph generates the docking poses directly and achieves from 10 to 100 times speedup compared to state-of-the-art approaches, while having a slightly better docking accuracy.

AFSE: towards improving model generalization of deep graph learning of ligand bioactivities targeting GPCR proteins.

Ligand molecules naturally constitute a graph structure. Recently, many excellent deep graph learning (DGL) methods have been proposed and used to model ligand bioactivities, which is critical for the virtual screening of drug hits from compound databases in interest. However, pharmacists can find that these well-trained DGL models usually are hard to achieve satisfying performance in real scenarios for virtual screening of drug candidates. The main challenges involve that the datasets for training models were small-sized and biased, and the inner active cliff cases would worsen model performance. These challenges would cause predictors to overfit the training data and have poor generalization in real virtual screening scenarios. Thus, we proposed a novel algorithm named adversarial feature subspace enhancement (AFSE). AFSE dynamically generates abundant representations in new feature subspace via bi-directional adversarial learning, and then minimizes the maximum loss of molecular divergence and bioactivity to ensure local smoothness of model outputs and significantly enhance the generalization of DGL models in predicting ligand bioactivities. Benchmark tests were implemented on seven state-of-the-art open-source DGL models with the potential of modeling ligand bioactivities, and precisely evaluated by multiple criteria. The results indicate that, on almost all 33 GPCRs datasets and seven DGL models, AFSE greatly improved their enhancement factor (top-10%, 20% and 30%), which is the most important evaluation in virtual screening of hits from compound databases, while ensuring the superior performance on RMSE and $r^2$. The web server of AFSE is freely available at http://noveldelta.com/AFSE for academic purposes.

Utilization of machine learning methods for predicting surgical outcomes after total knee arthroplasty.

BACKGROUND: Predictive models could help clinicians identify risk factors that cause adverse events after total knee arthroplasty (TKA), allowing for appropriate preoperative preventive interventions and allocation of resources. METHODS: The National Inpatient Sample datasets from 2010-2014 were used to build Logistic Regression (LR), Gradient Boosting Method (GBM), Random Forest (RF), and Artificial Neural Network (ANN) predictive models for three clinically relevant outcomes after TKA-disposition at discharge, any post-surgical complications, and blood transfusion. Model performance was evaluated using the Brier scores as calibration measures, and area under the ROC curve (AUC) and F1 scores as discrimination measures. RESULTS: GBM-based predictive models were observed to have better calibration and discrimination than the other models; thus, indicating comparatively better overall performance. The Brier scores for GBM models predicting the outcomes under investigation ranged from 0.09-0.14, AUCs ranged from 79-87%, and F1-scores ranged from 41-73%. Variable importance analysis for GBM models revealed that admission month, patient location, and patient's income level were significant predictors for all the outcomes. Additionally, any post-surgical complications and blood transfusions were significantly predicted by deficiency anemias, and discharge disposition by length of stay and age groups. Notably, any post-surgical complications were also significantly predicted by the patient undergoing blood transfusion. CONCLUSIONS: The predictive abilities of the ML models were successfully demonstrated using data from the National Inpatient Sample (NIS), indicating a wide range of clinical applications for obtaining accurate prognoses of complications following orthopedic surgical procedures.

A randomized control trial of a multiplex gastrointestinal PCR panel versus usual testing to assess antibiotics use for patients with infectious diarrhea in the emergency department.

OBJECTIVE: This study analyzed physician treating behavior through the use of a multiplex gastrointestinal polymerase chain reaction (GI PCR) test compared with usual testing in emergency department (ED) patients with suspected acute infectious diarrhea to assess differences in antibiotic management. METHODS: A prospective, single-center, randomized control trial was designed to investigate antibiotic use in ED patients with moderate to severe suspected infectious diarrhea, comparing those who received GI PCR to those who received usual testing. ED patients with signs of dehydration, inflammation, or persistent symptoms were randomized to either the experimental arm (GI PCR) or the control arm (usual testing or no testing). RESULTS: A total of 74 patients met study criteria and were randomized to either the experimental GI PCR arm (n = 38) or to the control arm (n = 36). Participants in the GI PCR arm received antibiotics in 87% of bacterial or protozoal diarrheal infections (13/15) whereas those in the control arm received antibiotics in 46% of bacterial or protozoal infections (6/13) (P value 0.042) with 2-proportion difference 0.41 (95% confidence interval 0.07 and 0.68). CONCLUSIONS: ED use of multiplex GI PCR led to an increase in antibiotic use for bacterial and protozoal causes of infectious diarrhea compared to usual testing. This increase in antibiotics appears to be appropriate given patients' moderate to severe symptoms and a definitive identification of a likely bacterial or protozoal cause of symptoms. Results should be interpreted with caution because of the small sample size.

Characteristics of nano-plastics in bottled drinking water.

Plastic pollution in water is threatening the environment and human health. Previous relevant studies mainly focus on macro and micro plastic pollutions and their characteristics. Little is known about the extent and characteristics of nano-scale plastics in our drinking water systems, mainly due to difficulties in their isolation and analysis. These nano-plastics may pose higher risk to human health than micro-plastics. Here we report the collection and analysis of organic nanoparticles from commercial bottled water of two brands. Novel nano-plastic particle imaging and molecular structure analysis techniques have been applied. The findings show the existence of organic nanoparticles, and a likely source has been identified to be the degradation of plastic water bottles.

Assessing Margin-Wide Rupture Behaviors Along the Cascadia Megathrust With 3-D Dynamic Rupture Simulations.

From California to British Columbia, the Pacific Northwest coast bears an omnipresent earthquake and tsunami hazard from the Cascadia subduction zone. Multiple lines of evidence suggests that magnitude eight and greater megathrust earthquakes have occurred - the most recent being 321 years ago (i.e., 1700 A.D.). Outstanding questions for the next great megathrust event include where it will initiate, what conditions are favorable for rupture to span the convergent margin, and how much slip may be expected. We develop the first 3-D fully dynamic rupture simulations for the Cascadia subduction zone that are driven by fault stress, strength and friction to address these questions. The initial dynamic stress drop distribution in our simulations is constrained by geodetic coupling models, with segment locations taken from geologic analyses. We document the sensitivity of nucleation location and stress drop to the final seismic moment and coseismic subsidence amplitudes. We find that the final earthquake size strongly depends on the amount of slip deficit in the central Cascadia region, which is inferred to be creeping interseismically, for a given initiation location in southern or northern Cascadia. Several simulations are also presented here that can closely approximate recorded coastal subsidence from the 1700 A.D. event without invoking localized high-stress asperities along the down-dip locked region of the megathrust. These results can be used to inform earthquake and tsunami hazards for not only Cascadia, but other subduction zones that have limited seismic observations but a wealth of geodetic inference.

Semi-supervised method for image texture classification of pituitary tumors via CycleGAN and optimized feature extraction.

BACKGROUND: Accurately determining the softness level of pituitary tumors preoperatively by using their image textures can provide a basis for surgical options and prognosis. Existing methods for this problem require manual intervention, which could hinder the efficiency and accuracy considerably. METHODS: We present an automatic method for diagnosing the texture of pituitary tumors using unbalanced sequence image data. Firstly, for the small sample problem in our pituitary tumor MRI image dataset where T1 and T2 sequence data are unbalanced (due to data missing) and under-sampled, our method uses a CycleGAN (Cycle-Consistent Adversarial Networks) model for domain conversion to obtain fully sampled MRI spatial sequence. Then, it uses a DenseNet (Densely Connected Convolutional Networks)-ResNet(Deep Residual Networks) based Autoencoder framework to optimize the feature extraction process for pituitary tumor image data. Finally, to take advantage of sequence data, it uses a CRNN (Convolutional Recurrent Neural Network) model to classify pituitary tumors based on their predicted softness levels. RESULTS: Experiments show that our method is the best in terms of efficiency and accuracy (91.78%) compared to other methods. CONCLUSIONS: We propose a semi-supervised method for grading pituitary tumor texture. This method can accurately determine the softness level of pituitary tumors, which provides convenience for surgical selection and prognosis, and improves the diagnostic efficiency of pituitary tumors.

Rapid growth of large area graphene on glass from olive oil by laser irradiation.

Although homogeneous, high quality graphene can be fabricated on a Cu or Ni sheet using the traditional chemical vapour deposition method at high temperatures (over 1000 °C) under specific atmospheric conditions, their transfer to another substrate is difficult. In this paper a novel method of rapidly (i.e. 3-6 s of laser irradiation) producing a large area (>3 cm2) graphene film from olive oil on a glass surface (pre-coated with a 5-28 nm thick Ni film) with defocused, large area continuous laser irradiation is described. The turbostratic graphene film (6 layers) grown in such a way has shown high electrical conductivity (sheet resistance of around 20 Ω sq-1) and an optical transmittance of 40-50%. With femtosecond laser patterning, 70% optical transparency was demonstrated. Continuous large area graphene was formed at relatively lower temperatures (<250 °C) and without the need for specific atmospheric conditions. The basic process characteristics and mechanisms involved are discussed.

A structural overview of the ion channels of the TRPM family.

The TRPM (transient receptor potential melastatin) family belongs to the superfamily of TRP cation channels. The TRPM subfamily is composed of eight members that are involved in diverse biological functions such as temperature sensing, inflammation, insulin secretion, and redox sensing. Since the first cloning of TRPM1 in 1998, tremendous progress has been made uncovering the function, structure, and pharmacology of this family. Complete structures of TRPM2, TRPM4, and TRPM8, as well as a partial structure of TRPM7, have been determined by cryo-EM, providing insights into their channel assembly, ion permeation, gating mechanisms, and structural pharmacology. Here we summarize the current knowledge about channel structure, emphasizing general features and principles of the structure of TRPM channels discovered since 2017. We also discuss some of the key unresolved issues in the field, including the molecular mechanisms underlying voltage and temperature dependence, as well as the functions of the TRPM channels' C-terminal domains.