Fraxini cortex: Progresses in phytochemistry, pharmacology and ethnomedicinal uses.

ETHNOPHARMACOLOGICAL RELEVANCE: Fraxini cortex, which has been widely used as a traditional Chinese medicine for 2000 years, is made from the dried bark of four plant species: Fraxinus chinensis subsp. rhynchophylla (Hance) A.E.Murray, Fraxinus chinensis Roxb., Fraxinus chinensis subsp. chinensis and Fraxinus stylosa Lingelsh.. In Chinese traditional medicine, it possesses the properties of heat-clearing and dampness-drying, asthma relief and cough suppression, as well as vision improvement. It is utilized for treating bacterial disorders, enteritis, leukorrhea, chronic bronitis, painful red eyes with swelling, lacrimation due to windward exposure, psoriasis, and other diseases or related symptoms. AIM OF THE STUDY: Fraxini cortex is abundant in chemical constituents and has garnered significant attention from plant chemists, particularly regarding coumarins, as evidenced by the recently identified three coumarin compounds. Considering the current dearth of systematic reporting on studies pertaining to Fraxini cortex, herein we provide a comprehensive summary of the advancements in phytochemistry, pharmacology, detection methods, and ethnomedicinal applications of Fraxini cortex. MATERIALS AND METHODS: We conducted a comprehensive search across online data sources (Web of Science, Public Medicine (PubMed), China National Knowledge Infrastructure (CNKI), as well as Chinese dissertations) and traditional Chinese medicine classics to gather the necessary literature resources for this review. RESULTS: Briefly, The Fraxini cortex yielded a total of 132 phytochemicals, including coumarins, lignans, secoiridoids, phenylethanol glycosides, flavonoids, triterpenoids, and other compounds. Among them, the main active ingredients are coumarins which possess a diverse range of pharmacological activities such as anti-inflammatory effects, anti-tumor properties, prevention of tissue fibrosis and oxidation damage as well as cardioprotective effects. CONCLUSIONS: All types of research conducted on Fraxini cortex, particularly in the field of ethnopharmacology, phytochemistry, and pharmacology, have been thoroughly reviewed. However, certain traditional applications and pharmacological activities of Fraxini cortex lack scientific evaluation or convincing evidence due to incomplete methodologies and ambiguous results, as well as a lack of clinical data. To validate its pharmacological activity, clinical efficacy, and safety profile, a systematic and comprehensive research evaluation is imperative. As an important traditional Chinese medicine, Fraxini cortex should be further explored to facilitate the development of novel drugs and therapeutics for various diseases. Greater attention should be given to how it can be better utilized.

Coupled Ferroelectric-Photonic Memory in a Retinomorphic Hardware for In-Sensor Computing.

The development of all-in-one devices for artificial visual systems offers an attractive solution in terms of energy efficiency and real-time processing speed. In recent years, the proliferation of smart sensors in the growth of Internet-of-Things (IoT) has led to the increasing importance of in-sensor computing technology, which places computational power at the edge of the data-flow architecture. In this study, a prototype visual sensor inspired by the human retina is proposed, which integrates ferroelectricity and photosensitivity in two-dimensional (2D) α-In2Se3 material. This device mimics the functions of photoreceptors and amacrine cells in the retina, performing optical reception and memory computation functions through the use of electrical switching polarization in the channel. The gate-tunable linearity of excitatory and inhibitory functions in photon-induced short-term plasticity enables to encode and classify 12 000 images in the Mixed National Institute of Standards and Technology (MNIST) dataset with remarkable accuracy, achieving ≈94%. Additionally, in-sensor convolution image processing through a network of phototransistors, with five convolutional kernels electrically pre-programmed into the transistors is demonstrated. The convoluted photocurrent matrices undergo straightforward arithmetic calculations to produce edge and feature-enhanced scenarios. The findings demonstrate the potential of ferroelectric α-In2Se3 for highly compact and efficient retinomorphic hardware implementation, regardless of ambipolar transport in the channel.

Evaluation and comparison of efficacy and safety of tirzepatide and semaglutide in patients with type 2 diabetes mellitus: A Bayesian network meta-analysis.

BACKGROUND: As new antidiabetic drugs, tirzepatide (Tir) and semaglutide (Sem) are progressively applied in clinical practice. However, their efficacy and safety profiles have not been comprehensively assessed. Therefore, a Bayesian network meta-analysis was used to evaluate and compare the efficacy and safety of Tir and Sem in treating type 2 diabetes mellitus (T2DM). METHODS: PubMed, EMBASE, Web of Science, Cochrane Library and ClinicalTrials.gov were systematically searched from inception to April 3rd, 2023. Randomized clinical trials (RCTs) comparing the efficacy and safety of Tir and Sem with placebo or the other antidiabetic drugs in treating T2DM were included. The efficacy outcomes included changes in glycated hemoglobin (HbA1c), body weight (BW), body mass index (BMI), and the proportion of participants with HbA1c< 7 %. The safety outcome was the proportion of participants experiencing gastrointestinal adverse events (GIAEs). RESULTS: A total of 38 studies involving 34,166 participants were included. Compared to 1 mg of subcutaneous Sem (Sem SC), 5 mg, 10 mg and 15 mg of Tir demonstrated superior efficacy in reducing HbA1c (mean difference (MD), [95 % CI], -0.22 [-0.40, -0.03] %, -0.42 [-0.60, -0.24] % and -0.53 [-0.71, -0.35] %, respectively) and BW (MD [95 % CI], -1.48 [-2.53, -0.43] kg, -4.00 [-5.05, -2.95] kg and -5.71 [-6.73, -4.68] kg, respectively). Conversely, 7 mg and 14 mg of oral Sem (Sem PO) displayed inferior efficacy in reducing HbA1c (MD [95 % CI], 0.47 [0.26, 0.68] % and 0.35 [0.16, 0.54] %, respectively) and BW (MD [95 % CI], 2.36 [1.24, 3.48] kg and 1.11 [0.10, 2.13] kg). However, 20 mg and 40 mg of Sem PO were non-inferior in reducing HbA1c (MD [95 % CI], 0.13 [-0.29, 0.55] % and 0.01 [-0.38, 0.40] %, respectively) and BW (MD [95 % CI], -0.41 [-2.71, 1.90] kg and -1.32 [-3.58, 0.92] kg). In terms of safety, compared to 1 mg of Sem SC, 5 mg, 10 mg and 15 mg of Tir did not significantly increase the incidence of GIAEs (odd ratio (OR) [95 % CI], 0.70 [0.42, 1.10], 0.87 [0.52, 1.36] and 0.99 [0.60, 1.54], respectively), while 7 mg of Sem PO showed a lower incidence of GIAEs (OR [95 % CI], 0.48 [0.25, 0.83]). Compared to insulin, 0.5 mg of Sem SC, 1 mg of Sem SC, 5 mg of Tir, 10 mg of Tir and 15 mg of Tir displayed better efficacy in lowering HbA1c (MD [95 % CI], -0.40 [-0.63, -0.18] %, -0.69 [-0.90, -0.48] %, -0.91 [-1.10, -0.72] %, -1.11 [-1.30, -0.92] % and -1.22 [-1.41, -1.03] %, respectively) and BW (MD [95 % CI], -5.34[-6.60, -4.09] kg, -6.70 [-7.90,-5.51] kg, -8.18 [-9.27, -7.10] kg, -10.70 [-11.79, -9.61] kg and -12.41 [-13.49,-11.33] kg, respectively). According to the surface under the cumulative ranking curve (SUCRA) value, among all the included interventions, 15 mg of Tir exhibited the most potent effect in reducing HbA1c (99.81 %) and BW (99.98 %), followed by 10 mg of Tir (96.83 % and 95.72 %), 5 mg of Tir (92.88 % and 86.04 %), 1 mg of Sem SC (85.85 % and 74.97 %), 40 mg of Sem PO (83.66 % and 84.31 %), 20 mg of Sem PO (76.98 % and 77.12 %), 300 mg of Can (49.93 % and 60.89 %), insulin (36.38 % and 0.22 %) and 100 mg of Sit (12.28 % and 18.51 %) respectively. Meanwhile, 5 mg, 10 mg, and 15 mg of Tir (48.32 %, 30.96 %, and 21.07 %, respectively), 0.5 mg and 1 mg of Sem SC (33.54 % and 24.77 %, respectively) significantly increased the incidence of GIAEs. CONCLUSION: Both Tir and Sem demonstrated favorable antidiabetic effects and were particularly suitable for T2DM patients who were obese or overweight. Despite a high incidence of GIAEs, their safety profile was deemed acceptable. Tir was the best option among all the included interventions.

Impact of home blood pressure monitors on self-monitoring and control of blood pressure in vulnerable adults.

To evaluate associations between home blood pressure monitoring (HBPM) and blood pressure (BP) in vulnerable adults during the COVID-19 pandemic, when access to in-person care was restricted. A retrospective cohort study was conducted in adults with hypertension or elevated BP given a home BP monitor vs. usual care. Change in BP from baseline to follow-up was compared between groups, controlling for potential confounders. Subgroup analyses of BP outcomes were also assessed in patients age >50 years. There was no difference in SBP reduction between n = 82 HBPM patients (-11.7/-2.9 mmHg) and n = 280 usual care patients (-12.5/-5.8 mmHg; P > 0.05). Results were similar in multivariable analysis controlling for potential confounders [coefficient 0.44, 95% confidence interval (CI) -3.98 to 4.87]. However, in the subgroup of patients aged>50 years, there was a significant association between SBP reduction and HBPM in the multivariable analyses (coefficient -7.2, 95% CI -13.8 to -0.62, P = 0.032). HBPM use was not associated with BP reduction in vulnerable adults overall during high telehealth use. An association between SBP reduction and HBPM was observed in those aged>50 years. Targeting limited HBPM resources to those aged >50 years old may have the most impact on BP.

Causal relationship of gut microbiota and metabolites on cognitive performance: A mendelian randomization analysis.

Emerging evidence has indicated that the alterations in gut microbiota and metabolites are associated with cognitive performance. However, whether these associations imply a causal relationship remains to be definitively established. Here, we conducted two-sample mendelian randomization (MR) studies to explore the causal effects of gut microbiota and metabolites on cognitive performance, using large-scale genome-wide association studies (GWASs). We identified seven positive causalities between host genetic-driven gut microbiota and cognitive performance, including Class Clostridia (p = 0.0002), Order Clostridiales (p = 8.12E-05), Family Rhodospirillaceae (p = 0.042) and Ruminococcustorquesgroup (p = 0.030), Dialister (p = 0.027), Paraprevotella (p = 0.037) and RuminococcaceaeUCG003 (p = 0.007) at the genus level. Additionally, a total of four higher abundance of gut microbiota traits were identified to be negatively related to cognitive performance, including genus Blautia (p = 0.013), LachnospiraceaeFCS020group (p = 0.035), LachnospiraceaeNK4A136group (p = 0.034) and Roseburia (p = 0.00016). In terms of plasma metabolites, we discovered eight positive and six negative relationships between genetic liability in metabolites and cognitive performance (all p < 0.05). No evidence was detected across a series of sensitivity analyses, including pleiotropy and heterogeneity. Collectively, our MR analyses revealed that gut microbiota and metabolites were causally connected with cognitive performance, which holds significant potential for shedding light on the early detection and diagnosis of cognitive impairment, offering valuable insights into this area of research.

Future time perspective and study engagement among middle school students: A moderated mediation model.

To examine the effect of future time perspective on middle school students' study engagement and explore the mediating role of motivation internalization and the moderating role of grit, we conducted a study in several middle schools. Six hundred sixty-four middle school students completed our measures. Results indicated that future time perspective positively predicted study engagement, and motivation internalization mediated the relationship between future time perspective and study engagement. It is also indicated that grit played a significant moderating role between motivation internalization and study engagement, with the effect of motivation internalization being stronger for low-grit students compared to high-grit students. These findings shed light on how to increase study engagement among middle school students.

Population pharmacokinetics of Amisulpride in Chinese patients with schizophrenia with external validation: the impact of renal function.

Introduction: Amisulpride is primarily eliminated via the kidneys. Given the clear influence of renal clearance on plasma concentration, we aimed to explicitly examine the impact of renal function on amisulpride pharmacokinetics (PK) via population PK modelling and Monte Carlo simulations. Method: Plasma concentrations from 921 patients (776 in development and 145 in validation) were utilized. Results: Amisulpride PK could be described by a one-compartment model with linear elimination where estimated glomerular filtration rate, eGFR, had a significant influence on clearance. All PK parameters (estimate, RSE%) were precisely estimated: apparent volume of distribution (645 L, 18%), apparent clearance (60.5 L/h, 2%), absorption rate constant (0.106 h-1, 12%) and coefficient of renal function on clearance (0.817, 10%). No other significant covariate was found. The predictive performance of the model was externally validated. Covariate analysis showed an inverse relationship between eGFR and exposure, where subjects with eGFR= 30 mL/min/1.73 m2 had more than 2-fold increase in AUC, trough and peak concentration. Simulation results further illustrated that, given a dose of 800 mg, plasma concentrations of all patients with renal impairment would exceed 640 ng/mL. Discussion: Our work demonstrated the importance of renal function in amisulpride dose adjustment and provided a quantitative framework to guide individualized dosing for Chinese patients with schizophrenia.

Combining temporal and spatial attention for seizure prediction.

Purpose: Approximately 1% of the world population is currently suffering from epilepsy. Successful seizure prediction is necessary for those patients. Influenced by neurons in their own and surrounding locations, the electroencephalogram (EEG) signals collected by scalp electrodes carry information of spatiotemporal interactions. Therefore, it is a great challenge to exploit the spatiotemporal information of EEG signals fully. Methods: In this paper, a new seizure prediction model called Gatformer is proposed by fusing the graph attention network (GAT) and the Transformer. The temporal and spatial attention are combined to extract EEG information from the perspective of spatiotemporal interactions. The model aims to explore the temporal dependence of single-channel EEG signals and the spatial correlations among multi-channel EEG signals. It can automatically identify the most noteworthy interaction in brain regions and achieve accurate seizure prediction. Results: Compared with the baseline models, the performance of our model is significantly improved. The false prediction rate (FPR) on the private dataset is 0.0064/h. The average accuracy, specificity and sensitivity are 98.25%, 99.36% and 97.65%. Conclusion: The proposed model is comparable to the state of the arts. Experiments on different datasets show that it has good robustness and generalization performance. The high sensitivity and low FPR prove that this model has great potential to realize clinical assistance for diagnosis and treatment.

Establishment and Evaluation of a Parametric Population Pharmacokinetic Model Repository for Ganciclovir and Valganciclovir.

BACKGROUND: Ganciclovir and valganciclovir are used for prophylaxis and treatment of cytomegalovirus infection. However, there is great interindividual variability in ganciclovir's pharmacokinetics (PK), highlighting the importance of individualized dosing. To facilitate model-informed precision dosing (MIPD), this study aimed to establish a parametric model repository of ganciclovir and valganciclovir by summarizing existing population pharmacokinetic information and analyzing the sources of variability. (2) Methods: A total of four databases were searched for published population PK models. We replicated these models, evaluated the impact of covariates on clearance, calculated the probability of target attainment for each model based on a predetermined dosing regimen, and developed an area under the concentration-time curve (AUC) calculator using maximum a posteriori Bayesian estimation. (3) Results: A total of 16 models, one- or two-compartment models, were included. The most significant covariates were body size (weight and body surface area) and renal function. The results show that 5 mg/kg/12 h of ganciclovir could make the AUC0-24h within 40-80 mg·h/L for 50.03% pediatrics but cause AUC0-24h exceeding the exposure thresholds for toxicity (120 mg·h/L) in 51.24% adults. (4) Conclusions: Dosing regimens of ganciclovir and valganciclovir should be adjusted according to body size and renal function. This model repository has a broad range of potential applications in MIPD.

ß-catenin attenuation leads to up-regulation of activating NKG2D ligands and tumor regression in BrafV600E-driven thyroid cancer cells.

Introduction: BRAFV600E mutations frequently occur in papillary thyroid cancer (PTC). ß-catenin, encoded by CTNNB1, is a key downstream component of the canonical Wnt signaling pathway and is often overexpressed in PTC. BRAFV600E-driven PTC tumors rely on Wnt/ß-catenin signaling to sustain growth and progression. Methods: In the present study, we investigated the tumorigenicity of thyroid cancer cells derived from BRAFV600E PTC mice following Ctnnb1 ablation (BVE-Ctnnb1null). Results: Remarkably, the tumorigenic potential of BVE-Ctnnb1null tumor cells was lost in nude mice. Global gene expression analysis of BVE-Ctnnb1null tumor cells showed up-regulation of NKG2D receptor activating ligands (H60a, H60b, H60c, Raet1a, Raet1b, Raet1c, Raet1d, Raet1e, and Ulbp1) and down-regulation of inhibitory MHC class I molecules H-2L and H-2K2 in BVE-Ctnnb1null tumor cells. In vitro cytotoxicity assay demonstrated that BVE-Ctnnb1wt tumor cells were resistant to NK cell-mediated cytotoxicity, whereas BVE-Ctnnb1null tumor cells were sensitive to NK cell-mediated killing. Furthermore, the overexpression of any one of these NKG2D ligands in the BVE-Ctnnb1wt cell line resulted in a significant reduction of tumor growth in nude mice. Conclusions: Our results indicate that active ß-catenin signaling inhibits NK cell-mediated immune responses against thyroid cancer cells. Targeting the ß-catenin signaling pathway may have significant therapeutic benefits for BRAF-mutant thyroid cancer by not only inhibiting tumor growth but also enhancing host immune surveillance.

Application of physiologically based pharmacokinetics modeling in the research of small-molecule targeted anti-cancer drugs.

INTRODUCTION: Physiologically based pharmacokinetics (PBPK) models are increasingly used in the drug research and development, especially in anti-cancer drugs. Between 2001 and 2020, a total of 89 small-molecule targeted antitumor drugs were approved in China and the United States, some of which already included PBPK modeling in their application or approval packages. This article intended to review the prevalence and application of PBPK model in these drugs. METHOD: Article search was performed in the PubMed to collect English research articles on small-molecule targeted anti-cancer drugs using PBPK modeling. The selected articles were classified into nine categorizes according to the application areas and further analyzed. RESULT: From 2001 to 2020, more than 60% of small-molecule targeted anti-cancer drugs (54/89) were studied using PBPK model with a wide range of application. Ninety research articles were included, of which 48 involved enzyme-mediated drug-drug interaction (DDI). Of these retrieved articles, Simcyp, GastroPlus, and PK-Sim were the most widely model building platforms, which account for 63.8%, 15.2%, and 8.6%, respectively. CONCLUSION: PBPK modeling is commonly and widely used to research small-molecule targeted anti-cancer drugs.

Attack Resilient True Random Number Generators Using Ferroelectric-Enhanced Stochasticity in 2D Transistor.

By harnessing the physically unclonable properties, true random number generators (TRNGs) offer significant promises to alleviate security concerns by generating random bitstreams that are cryptographically secured. However, fundamental challenges remain as conventional hardware often requires complex circuitry design, showing a predictable pattern that is susceptible to machine learning attacks. Here, a low-power self-corrected TRNG is presented by exploiting the stochastic ferroelectric switching and charge trapping in molybdenum disulfide (MoS2 ) ferroelectric field-effect transistors (Fe-FET) based on hafnium oxide complex. The proposed TRNG exhibits enhanced stochastic variability with near-ideal entropy of ≈1.0, Hamming distance of ≈50%, independent autocorrelation function, and reliable endurance cycle against temperature variations. Furthermore, its unpredictable feature is systematically examined by machine learning attacks, namely the predictive regression model and the long-short-term-memory (LSTM) approach, where nondeterministic predictions can be concluded. Moreover, the generated cryptographic keys from the circuitry successfully pass the National Institute of Standards and Technology (NIST) 800-20 statistical test suite. The potential of integrating ferroelectric and 2D materials is highlighted for advanced data encryption, offering a novel alternative to generate truly random numbers.

USP7- and PRMT5-dependent G3BP2 stabilization drives de novo lipogenesis and tumorigenesis of HNSC.

GTPase-activating protein-binding protein 2 (G3BP2) is a key stress granule-associated RNA-binding protein responsible for the formation of stress granules (SGs). Hyperactivation of G3BP2 is associated with various pathological conditions, especially cancers. Emerging evidence indicates that post-translational modifications (PTMs) play critical roles in gene transcription, integrate metabolism and immune surveillance. However, how PTMs directly regulate G3BP2 activity is lacking. Here, our analyses identify a novel mechanism that PRMT5-mediated G3BP2-R468me2 enhances the binding to deubiquitinase USP7, which ensures the deubiquitination and stabilization of G3BP2. Mechanistically, USP7- and PRMT5-dependent G3BP2 stabilization consequently guarantee robust ACLY activation, which thereby stimulating de novo lipogenesis and tumorigenesis. More importantly, USP7-induced G3BP2 deubiquitination is attenuated by PRMT5 depletion or inhibition. PRMT5-activity dependent methylation of G3BP2 is required for its deubiquitination and stabilization by USP7. Consistently, G3BP2, PRMT5 and G3BP2 R468me2 protein levels were found positively correlated in clinical patients and associated with poor prognosis. Altogether, these data suggest that PRMT5-USP7-G3BP2 regulatory axis serves as a lipid metabolism reprogramming mechanism in tumorigenesis, and unveil a promising therapeutic target in the metabolic treatment of head and neck squamous carcinoma.

Molecular Genetics of Diffuse Sclerosing Papillary Thyroid Cancer.

CONTEXT: Diffuse sclerosing papillary thyroid cancer (DSPTC) is rare, with limited data on its molecular genetics. OBJECTIVE: We studied the molecular genetics of a cohort of DSPTC. METHODS: DNA was isolated from paraffin blocks of 22 patients with DSPTC (15 females, 7 males, median age 18 years, range 8-81). We performed polymerase chain reaction-based Sanger sequencing and a next-generation sequencing (NGS) gene panel to characterize the genomic landscape of these tumors. We classified genetic alterations to definitely or probably pathogenic. Definitely pathogenic are genetic alterations that are well known to be associated with PTC (e.g., BRAFV600E). Probably pathogenic are other alterations in genes that were reported in The Cancer Genome Atlas or the poorly differentiated and anaplastic thyroid cancer datasets. RESULTS: Three tumors were tested only by Sanger sequencing and were negative for BRAFV600E, HRAS, KRAS, NRAS, TERT promoter, PTEN, and PIK3CA mutations. The other 19 tumors tested by NGS showed definitely pathogenic alterations in 10 patients (52.6%): 2/19 (10.5%) BRAFV600E, 5/19 (26.3%) CCDC6-RET (RET/PTC1), 1/19 (5.3%) NCOA4-RET (RET/PTC3), 1/19 (5.3%) STRN-ALK fusion, and 2/19 (10.6%) TP53 mutations. Probably pathogenic alterations occurred in 13/19 tumors (68.4%) and included variants in POLE (31.6%), CDKN2A (26%), NF1 (21%), BRCA2 (15.8%), SETD2 (5.3%), ATM (5.3%), FLT3 (5.3%), and ROS1 (5.3%). In 1 patient, the gene panel showed no alterations. No mutations were found in the RAS, PTEN, PIK3CA, or TERT promoter in all patients. There was no clear genotype/phenotype correlation. CONCLUSION: In DSPTC, fusion genes are common, BRAFV600E is rare, and other usual point mutations are absent. Pathogenic and likely pathogenic variants in POLE, NF1, CDKN2A, BRCA2, TP53, SETD2, ATM, FLT3, and ROS1 occur in about two-thirds of DTPTC.

Population pharmacokinetics of buprenorphine and naloxone sublingual combination in Chinese healthy volunteers and patients with opioid use disorder: Model-based dose optimization.

The sublingual combination of buprenorphine (BUP) and naloxone (NLX) is a new treatment option for opioid use disorder (OUD) and is effective in preventing drug abuse. This study aimed to explore rational dosing regimen for OUD patients in China via a model-based dose optimization approach. BUP, norbuprenorphine (norBUP), and NLX plasma concentrations of 34 healthy volunteers and 12 OUD subjects after single or repeated dosing were included. A parent-metabolite population pharmacokinetics (popPK) model with transit compartments for absorption was implemented to describe the pharmacokinetic profile of BUP-norBUP. In addition, NLX concentrations were well captured by a one-compartment popPK model. Covariate analysis showed that every additional swallow after the administration within the observed range (0-12) resulted in a 3.5% reduction in BUP bioavailability. This provides a possible reason for the less-than-dose proportionality of BUP. There were no differences in the pharmacokinetic characteristics between BUP or NLX in healthy volunteers and OUD subjects. Ethnic sensitivity analysis demonstrated that the dose-normalized peak concentration and area-under-the-curve of BUP in Chinese were about half of Puerto Ricans, which was consistent with a higher clearance observed in Chinese (166 L / h vs. 270 L / h ). Furthermore, Monte Carlo simulations showed that an 8 mg three-times daily dose was the optimized regimen for Chinese OUD subjects. This regimen ensured that opioid receptor occupancy remained at a maximum (70%) in more than 95% of subjects, at the same time, with NLX plasma concentrations below the withdrawal reaction threshold (4.6  n g / m L ).

In Outpatients Receiving Parenteral Vancomycin, Dosing Adjustments Produced by Area Under the Curve-Based and Trough-Based Monitoring Differ Only at the Extremes of the Therapeutic Trough Range.

Area under the curve (AUC)-based vancomycin dosing reduces nephrotoxicity but is burdensome. Reviewing 115 adults receiving ≥2 weeks of outpatient vancomycin, we found AUC-based and trough-based dose adjustments discordant only for troughs <12 or >16 mg/L. Selective versus universal outpatient AUC calculation would likely offer similar benefit with reduced workload.

Foretinib Is Effective against Triple-Negative Breast Cancer Cells MDA-MB-231 In Vitro and In Vivo by Down-Regulating p-MET/HGF Signaling.

This study investigated the antitumor effects of foretinib on triple-negative breast cancer cells MDA-MB-231 xenograft tumors in vivo underlying phosphorylated mesenchymal to epithelial transition (p-MET)/ hepatocyte growth factor (HGF)-related mechanism, as well as its pharmacokinetic characteristics. The MDA-MB-231 human breast cancer cell line was used for in vitro experiments, and the tumor xenograft model was established for in vivo experiments. MDA-MB-231 xenograft mice received oral foretinib (15 or 50 mg/kg/day) or vehicle for 18 days. The xenograft tumors were collected. Protein expressions of p-MET and HGF were examined with Western blotting and immunohistochemical staining. The mRNA expression of MET was examined with real-time PCR. Blood samples were collected from the mice treated with foretinib under different doses of 2, 10, and 50 mg/kg, and the pharmacokinetic profiles of foretinib were evaluated. We found that foretinib treatment caused a significant inhibition in tumor growth in a dose-dependent manner, whereas the continuous administration did not result in weight loss in treated nude mice. In both MDA-MB-231 cells and xenograft tumors, foretinib suppressed the expression of p-MET and HGF. These findings reveal that the decrease of p-MET and HGF may play an important role in the anti-breast cancer properties of foretinib.

A MoS2 Hafnium Oxide Based Ferroelectric Encoder for Temporal-Efficient Spiking Neural Network.

Spiking neural network (SNN), where the information is evaluated recurrently through spikes, has manifested significant promises to minimize the energy expenditure in data-intensive machine learning and artificial intelligence. Among these applications, the artificial neural encoders are essential to convert the external stimuli to a spiking format that can be subsequently fed to the neural network. Here, a molybdenum disulfide (MoS2 ) hafnium oxide-based ferroelectric encoder is demonstrated for temporal-efficient information processing in SNN. The fast domain switching attribute associated with the polycrystalline nature of hafnium oxide-based ferroelectric material is exploited for spike encoding, rendering it suitable for realizing biomimetic encoders. Accordingly, a high-performance ferroelectric encoder is achieved, featuring a superior switching efficiency, negligible charge trapping effect, and robust ferroelectric response, which successfully enable a broad dynamic range. Furthermore, an SNN is simulated to verify the precision of the encoded information, in which an average inference accuracy of 95.14% can be achieved, using the Modified National Insitute of Standards and Technology (MNIST) dataset for digit classification. Moreover, this ferroelectric encoder manifests prominent resilience against noise injection with an overall prediction accuracy of 94.73% under various Gaussian noise levels, showing practical promises to reduce the computational load for the neural network.

A Spatiotemporal Graph Attention Network Based on Synchronization for Epileptic Seizure Prediction.

Accurate early prediction of epileptic seizures can provide timely treatment for patients. Previous studies have mainly focused on a single temporal or spatial dimension, making it difficult to take both relationships into account. Therefore, the effective properties of electroencephalograms (EEGs) may not be fully evaluated. To solve this problem, we propose a spatiotemporal graph attention network (STGAT) based on synchronization. The spatial and functional connectivity information between EEG channels was extracted by using the phase locking values (PLVs) first, which allowed multichannel EEG signals to be modeled as graph signals. Afterward, the STGAT model was used to dynamically learn the temporal correlation properties of EEG sequences and explore the spatial topological structure information of multiple channels. Experimental results demonstrated that the STGAT model was able to obtain spatiotemporal correlations and achieve good results on two benchmark datasets. The accuracy, specificity and sensitivity were 98.74%, 99.21% and 98.87%, respectively, on the CHB-MIT dataset. Moreover, all evaluation indices of the private dataset had reached more than 98.8%, with the area under the curve (AUC) reaching 99.96%. The proposed method is superior or comparable to the state-of-the-art models. Extensive experiments demonstrate that our end-to-end automatic seizure prediction model can be extended to design clinical assistant decision systems.

GARP: A family of glycine and alanine-rich proteins that helps spider mites feed on plants.

Spider mites (Tetranychidae) are destructive agricultural pests which have evolved strategies to overcome plant defenses, such as the ability to puncture the leaves of their hosts to feed. The expression of many genes with unknown functions is altered during feeding, but little is known about the role of these genes in plant-mite interactions. Here, we identified 3 novel gene families through analysis of genomic and transcriptomic data from 3 spider mite species. These GARP family genes encode glycine and alanine-rich proteins; they are present in mites (Acariformes) but absent in ticks (Parasitiformes) in the subclass Acari, indicating that these genes have undergone a significant expansion in spider mites and thus play important adaptive roles. Transcriptomic analysis revealed that the expression of GARP genes is strongly correlated with feeding and the transfer to new hosts. We used RNA interference to silence GARP1d in the two-spotted spider mite Tetranychus urticae, which inhibited feeding and egg laying and significantly increased mortality when the mites were transferred to soybean shoots; a similar effect was observed after TuVATPase was silenced. However, no changes in mite mortality were observed after TuGARP1d-silenced mites were placed on an artificial diet, which was different from the effect of TuVATPase silencing. Our results indicate that GARP family members play important roles in mite-plant interactions. Additional studies are needed to clarify the mechanisms underlying these interactions.