Ultrathin quantum light source with van der Waals NbOCl2 crystal.

Interlayer electronic coupling in two-dimensional materials enables tunable and emergent properties by stacking engineering. However, it also results in significant evolution of electronic structures and attenuation of excitonic effects in two-dimensional semiconductors as exemplified by quickly degrading excitonic photoluminescence and optical nonlinearities in transition metal dichalcogenides when monolayers are stacked into van der Waals structures. Here we report a van der Waals crystal, niobium oxide dichloride (NbOCl2), featuring vanishing interlayer electronic coupling and monolayer-like excitonic behaviour in the bulk form, along with a scalable second-harmonic generation intensity of up to three orders higher than that in monolayer WS2. Notably, the strong second-order nonlinearity enables correlated parametric photon pair generation, through a spontaneous parametric down-conversion (SPDC) process, in flakes as thin as about 46 nm. To our knowledge, this is the first SPDC source unambiguously demonstrated in two-dimensional layered materials, and the thinnest SPDC source ever reported. Our work opens an avenue towards developing van der Waals material-based ultracompact on-chip SPDC sources as well as high-performance photon modulators in both classical and quantum optical technologies1-4.

Efficient models of cortical activity via local dynamic equilibria and coarse-grained interactions.

Biologically detailed models of brain circuitry are challenging to build and simulate due to the large number of neurons, their complex interactions, and the many unknown physiological parameters. Simplified mathematical models are more tractable, but harder to evaluate when too far removed from neuroanatomy/physiology. We propose that a multiscale model, coarse-grained (CG) while preserving local biological details, offers the best balance between biological realism and computability. This paper presents such a model. Generally, CG models focus on the interaction between groups of neurons-here termed "pixels"-rather than individual cells. In our case, dynamics are alternately updated at intra- and interpixel scales, with one informing the other, until convergence to equilibrium is achieved on both scales. An innovation is how we exploit the underlying biology: Taking advantage of the similarity in local anatomical structures across large regions of the cortex, we model intrapixel dynamics as a single dynamical system driven by "external" inputs. These inputs vary with events external to the pixel, but their ranges can be estimated a priori. Precomputing and tabulating all potential local responses speed up the updating procedure significantly compared to direct multiscale simulation. We illustrate our methodology using a model of the primate visual cortex. Except for local neuron-to-neuron variability (necessarily lost in any CG approximation) our model reproduces various features of large-scale network models at a tiny fraction of the computational cost. These include neuronal responses as a consequence of their orientation selectivity, a primary function of visual neurons.

Learning spiking neuronal networks with artificial neural networks: neural oscillations.

First-principles-based modelings have been extremely successful in providing crucial insights and predictions for complex biological functions and phenomena. However, they can be hard to build and expensive to simulate for complex living systems. On the other hand, modern data-driven methods thrive at modeling many types of high-dimensional and noisy data. Still, the training and interpretation of these data-driven models remain challenging. Here, we combine the two types of methods to model stochastic neuronal network oscillations. Specifically, we develop a class of artificial neural networks to provide faithful surrogates to the high-dimensional, nonlinear oscillatory dynamics produced by a spiking neuronal network model. Furthermore, when the training data set is enlarged within a range of parameter choices, the artificial neural networks become generalizable to these parameters, covering cases in distinctly different dynamical regimes. In all, our work opens a new avenue for modeling complex neuronal network dynamics with artificial neural networks.

Relationship between cognitive function and weight-adjusted waist index in people ≥ 60 years old in NHANES 2011-2014.

BACKGROUND: Widespread attention has been given to the detrimental effects of obesity on cognitive function. However, there is no evidence on the connection between low cognitive performance and the WWI (weight-adjusted waist index). This study looked into the connection between poor cognitive performance and the WWI in senior Americans. METHODS: A cross-sectional research study was carried out with information from the NHANES 2011-2014. With multivariate linear regression models, the pertinence between the WWI and low cognitive function in persons older than 60 years was examined. The nonlinear link was described using threshold effect analyses and fitted smoothed curves. Interaction tests and subgroup analysis were also conducted. RESULTS: The study had 2762 individuals in all, and subjects with higher WWI values were at greater risk for low cognitive function. In the completely adjusted model, the WWI was positively connected with low cognitive performance assessed by CERAD W-L (OR = 1.22, 95% CI 1.03-1.45, p = 0.0239), AFT (OR = 1.30, 95% CI 1.09-1.54, p = 0.0029), and DSST (OR = 1.59, 95% CI 1.30-1.94, p < 0.0001). The effect of each subgroup on the positive correlation between the WWI and low cognitive performance was not significant. The WWI and low cognitive performance as determined by CERAD W-L and AFT had a nonlinear connection (log-likelihood ratio < 0.05). CONCLUSION: Among older adults in the United States, the risk of low cognitive performance may be positively related to the WWI.

Identification of key genes in sepsis by WGCNA.

When the body damages its own tissues in response to an infection, sepsis develops. Medical treatments are limited. It's important to understand the molecular mechanism behind sepsis pathogenesis and identify potential molecular treatment targets. We made two modules based on how genes work together by using WGCNA analysis. The light-green GSE131761 module and the blue GSE137342 module had the strongest links to sepsis. A gene ontology (GO) analysis showed that most of the genes in the lightgreen module were involved in the inflammatory response, specific granule, and immune receptor activity. Most of the genes in the blue module were significantly more likely to have the GO terms proteasomal protein catabolic process, ubiquitin ligase complex, and ubiquitin-like protein transferase activity. The KEGG analysis showed that the genes in module lightgreen were mostly involved in the TNF signaling pathway, while the genes in module blue were mostly involved in the Prion disease pathway. There were two hub genes that were found. In the end, ANKRD22 and VNN1 were singled out as crucial genes. This study used WGCNA to investigate sepsis-associated susceptibility modules and genes. Our study identified two modules and two key genes as essential components in sepsis etiology, which may improve our understanding of its molecular mechanisms.

Rapid and Selective Uptake of Radioactive Cesium from Water by a Microporous Zeolitic-like Sulfide.

The fast and efficient removal of 137Cs+ ions from water is of great significance for the further treatment and disposal of highly active nuclear waste. Hitherto, although many layered metal sulfides have been proven to be very effective in capturing aqueous cesium, three-dimensional (3D) microporous examples have rarely been explored, especially compounds that are systematically used to study cesium ion exchange behaviors. In this paper, we present detailed Cs+ ion exchange properties of a 3D, microporous, zeolitic-like sulfide, namely K@GaSnS-1, in different conditions. Isotherm studies indicate that K@GaSnS-1 has a high cesium saturation capacity of 249.3 mg/g. In addition, it exhibits rapid sorption kinetics, with an equilibrium time of only 2 min. Further studies show that K@GaSnS-1 also displays a strong preference and good selectivity for cesium, with the highest distribution coefficient Kd value up to 3.53 × 104 mL/g. Also noteworthy is that the excellent cesium ion exchange properties are well-maintained despite acidic, basic, and competitive multiple-component environments. More importantly, the Cs+-exchanged products can be easily eluted and regenerated by a low-cost and eco-friendly method. These merits demonstrated by K@GaSnS-1 render it very promising in the effective and efficient separation of radioactive cesium from nuclear waste.

Effects of new hypoglycemic drugs on cardiac remodeling: a systematic review and network meta-analysis.

BACKGROUND: In recent years, the incidence of diabetes mellitus has been increasing annually, and cardiovascular complications secondary to diabetes mellitus have become the leading cause of death in diabetic patients. Considering the high incidence of type 2 diabetes (T2DM) combined with cardiovascular disease (CVD), some new hypoglycemic agents with cardiovascular protective effects have attracted extensive attention. However, the specific role of these regimens in ventricular remodeling remains unknown. The purpose of this network meta-analysis was to compare the effects of sodium glucose cotransporter type 2 inhibitor (SGLT-2i), glucagon-like peptide 1 receptor agonist (GLP-1RA) and dipeptidyl peptidase-4 inhibitor (DPP-4i) on ventricular remodeling in patients with T2DM and/or CVD. METHODS: Articles published prior to 24 August 2022 were retrieved in four electronic databases: the Cochrane Library, Embase, PubMed, and Web of Science. This meta-analysis included randomized controlled trials (RCTs) and a small number of cohort studies. The differences in mean changes of left ventricular ultrasonic parameters between the treatment and control groups were compared. RESULTS: A total of 31 RCTs and 4 cohort studies involving 4322 patients were analyzed. GLP-1RA was more significantly associated with improvement in left ventricular end-systolic diameter (LVESD) [MD = -0.38 mm, 95% CI (-0.66, -0.10)] and LV mass index (LVMI) [MD = -1.07 g/m2, 95% CI (-1.71, -0.42)], but significantly decreased e' [MD = -0.43 cm/s 95% CI (-0.81, -0.04)]. DPP-4i was more strongly associated with improvement in e' [MD = 3.82 cm/s, 95% CI (2.92,4.7)] and E/e'[MD = -5.97 95% CI (-10.35, -1.59)], but significantly inhibited LV ejection fraction (LVEF) [MD = -0.89% 95% CI (-1.76, -0.03)]. SGLT-2i significantly improved LVMI [MD = -0.28 g/m2, 95% CI (-0.43, -0.12)] and LV end-diastolic diameter (LVEDD) [MD = -0.72 ml, 95% CI (-1.30, -0.14)] in the overall population, as well as E/e' and SBP in T2DM patients combined with CVD, without showing any negative effect on left ventricular function. CONCLUSION: The results of the network meta-analysis provided high certainty to suggest that SGLT-2i may be more effective in cardiac remodeling compared to GLP-1RA and DPP-4i. While GLP-1RA and DPP-4i may have a tendency to improve cardiac systolic and diastolic function respectively. SGLT-2i is the most recommended drug for reversing ventricular remodeling in this meta-analysis.

Multi-band oscillations emerge from a simple spiking network.

In the brain, coherent neuronal activities often appear simultaneously in multiple frequency bands, e.g., as combinations of alpha (8-12 Hz), beta (12.5-30 Hz), and gamma (30-120 Hz) oscillations, among others. These rhythms are believed to underlie information processing and cognitive functions and have been subjected to intense experimental and theoretical scrutiny. Computational modeling has provided a framework for the emergence of network-level oscillatory behavior from the interaction of spiking neurons. However, due to the strong nonlinear interactions between highly recurrent spiking populations, the interplay between cortical rhythms in multiple frequency bands has rarely been theoretically investigated. Many studies invoke multiple physiological timescales (e.g., various ion channels or multiple types of inhibitory neurons) or oscillatory inputs to produce rhythms in multi-bands. Here, we demonstrate the emergence of multi-band oscillations in a simple network consisting of one excitatory and one inhibitory neuronal population driven by constant input. First, we construct a data-driven, Poincaré section theory for robust numerical observations of single-frequency oscillations bifurcating into multiple bands. Then, we develop model reductions of the stochastic, nonlinear, high-dimensional neuronal network to capture the appearance of multi-band dynamics and the underlying bifurcations theoretically. Furthermore, when viewed within the reduced state space, our analysis reveals conserved geometrical features of the bifurcations on low-dimensional dynamical manifolds. These results suggest a simple geometric mechanism behind the emergence of multi-band oscillations without appealing to oscillatory inputs or multiple synaptic or neuronal timescales. Thus, our work points to unexplored regimes of stochastic competition between excitation and inhibition behind the generation of dynamic, patterned neuronal activities.

Near-Field Modulation of Differently Oriented Single Photon Emitters with A Plasmonic Probe.

Single photon emitters (SPEs) are critical components of photon-based quantum technology. Recently, the interaction between surface plasmons and emitters has attracted increasing attention because of its potential to improve the quality of single-photon sources through stronger light-matter interactions. In this work, we use a hybrid plasmonic probe composed of a fiber taper and silver nanowire to controllably modulate the radiation properties of SPEs with differently oriented polarization. For out-of-plane oriented SPEs such as single CdSe quantum dots, the radiation lifetime could be reduced by a factor as large as seven; for in-plane oriented SPEs such as hBN defect SPEs, the average modulation amplitude varied from 0.69 to 1.23, depending on the position of the probe. The experimental results were highly consistent with the simulations and theory. This work provides an efficient approach for optimizing the properties of SPEs for quantum photonic integration.

Hypoxia-induced polarization of M2 macrophages and C-C motif chemokine ligand 5 secretion promotes the migration and invasion of trophoblasts†.

In the early stage of pregnancy, hypoxia in the placenta is of great significance to the migration and invasion of trophoblasts. In addition, changes to the polarity and activity of macrophages can affect embryo implantation, trophoblast migration and invasion, and vascular remodeling by affecting cytokine secretion. However, the mechanism of the effects of hypoxic conditions in the placenta on trophoblasts remains unknown. We used gene knockdown on macrophages, and drug treatment on trophoblasts, and cultured them under hypoxic and normoxic conditions. The cells were then subjected to wound-healing assays, Transwell cell invasion experiments, quantitative real-time reverse transcription Polymerase Chain Reaction (PCR), western blotting, and immunofluorescence. The polarization of macrophages in each group, the migration and invasion ability of trophoblasts, and changes to the phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway were detected. Hypoxic conditions induce M2 polarization of macrophages. The conditioned medium from macrophages under hypoxic conditions increased the migration and invasion of trophoblasts and enhanced the levels of phosphorylated (p)-PI3K and p-AKT in trophoblasts. After C-C motif chemokine ligand 5 knockdown in macrophages, the ability of conditioned medium from macrophages cultured under hypoxic conditions to promote the migration and invasion of trophoblasts was weakened significantly. The use of PI3K/AKT signaling pathway agonists could reverse the attenuation effect caused by C-C motif chemokine ligand 5 knockdown.

Transverse Mode-Encoded Quantum Gate on a Silicon Photonic Chip.

As an important degree of freedom (d.o.f.) in photonic integrated circuits, the orthogonal transverse mode provides a promising and flexible way to increase communication capability, for both classical and quantum information processing. To construct large-scale on-chip multimode multi-d.o.f.s quantum systems, a transverse mode-encoded controlled-NOT (CNOT) gate is necessary. Here, with the help of our new transverse mode-dependent directional coupler and attenuator, we demonstrate the first multimode implementation of a 2-qubit quantum gate. The ability of the gate is demonstrated by entangling two separated transverse mode qubits with an average fidelity of 0.89±0.02 and the achievement of 10 standard deviations of violations in the quantum nonlocality verification. In addition, a fidelity of 0.82±0.01 is obtained from quantum process tomography used to completely characterize the CNOT gate. Our work paves the way for universal transverse mode-encoded quantum operations and large-scale multimode multi-d.o.f.s quantum systems.

Multilevel monte carlo for cortical circuit models.

Multilevel Monte Carlo (MLMC) methods aim to speed up computation of statistics from dynamical simulations. MLMC is easy to implement and is sometimes very effective, but its efficacy may depend on the underlying dynamics. We apply MLMC to networks of spiking neurons and assess its effectiveness on prototypical models of cortical circuitry under different conditions. We find that MLMC can be very efficient for computing reliable features, i.e., features of network dynamics that are reproducible upon repeated presentation of the same external forcing. In contrast, MLMC is less effective for complex, internally generated activity. Qualitative explanations are given using concepts from random dynamical systems theory.

A data-informed mean-field approach to mapping of cortical parameter landscapes.

Constraining the many biological parameters that govern cortical dynamics is computationally and conceptually difficult because of the curse of dimensionality. This paper addresses these challenges by proposing (1) a novel data-informed mean-field (MF) approach to efficiently map the parameter space of network models; and (2) an organizing principle for studying parameter space that enables the extraction biologically meaningful relations from this high-dimensional data. We illustrate these ideas using a large-scale network model of the Macaque primary visual cortex. Of the 10-20 model parameters, we identify 7 that are especially poorly constrained, and use the MF algorithm in (1) to discover the firing rate contours in this 7D parameter cube. Defining a "biologically plausible" region to consist of parameters that exhibit spontaneous Excitatory and Inhibitory firing rates compatible with experimental values, we find that this region is a slightly thickened codimension-1 submanifold. An implication of this finding is that while plausible regimes depend sensitively on parameters, they are also robust and flexible provided one compensates appropriately when parameters are varied. Our organizing principle for conceptualizing parameter dependence is to focus on certain 2D parameter planes that govern lateral inhibition: Intersecting these planes with the biologically plausible region leads to very simple geometric structures which, when suitably scaled, have a universal character independent of where the intersections are taken. In addition to elucidating the geometry of the plausible region, this invariance suggests useful approximate scaling relations. Our study offers, for the first time, a complete characterization of the set of all biologically plausible parameters for a detailed cortical model, which has been out of reach due to the high dimensionality of parameter space.

CRISPR-based detection of Helicobacter pylori in stool samples.

BACKGROUND: Noninvasive detection of Helicobacter pylori plays an important role in clinical practice. However, few noninvasive methods have been applied in epidemiological studies due to the requirement for expensive equipment and complicated processes. The aim of this study was to establish a reliable, fast, and inexpensive noninvasive method based on CRISPR-Cas12a technology for the detection of Helicobacter pylori in stool specimens. METHOD: A novel detection method based on CRISPR-Cas12a technology was established and validated with 41 stool specimens collected from Zhujiang Hospital and compared with reliable Helicobacter pylori detection assays, such as the rapid urease test and urea breath test. RESULT: A CRISPR-Cas12a system-based method was established, and its sensitivity and specificity were evaluated. Utilizing a lateral flow biosensor, the limit of detection was 5 copies/µl, and our method could successfully distinguish Helicobacter pylori from other pathogens, suggesting no cross-reactivity with other pathogens. Furthermore, lateral flow biosensor strips were utilized to test stool specimens, which could display the detection results in an accessible way. CONCLUSION: Our CRISPR-Cas12a system-based method successfully detected Helicobacter pylori in stool specimens. It is a rapid, simple, and inexpensive method for the detection and screening of Helicobacter pylori, which makes it a very promising supplemental test. However, its sensitivity and specificity compared with those of the gold standard test still need to be examined.

Effectiveness of Acupuncture Therapy on Postoperative Nausea and Vomiting After Gynecologic Surgery: A Meta-Analysis and Systematic Review.

PURPOSE: The aim of this study was to evaluate the effectiveness and safety of acupuncture therapy (AT) on postoperative nausea and vomiting (PONV) after gynecologic surgery (GS). DESIGN: A meta-analysis using a systematic search strategy was performed. METHODS: A comprehensive literature search of all published randomized controlled trials or prospective cohort studies assessing the effectiveness of AT on PONV in patients undergoing GS was conducted in three databases: PubMed, EMBASE, and Cochrane Library. The incidence of PONV, the use of rescue antiemetics, and side effects of AT were analyzed using the Review Manager 5.3 software. FINDINGS: Nine randomized controlled trials and one prospective cohort study identified in the literature search from database inception (1966) to December 31, 2019, including 1,075 participants were included in the present study. AT significantly reduced the risk of developing postoperative nausea and postoperative vomiting by 48% (relative risk = 0.52; 95% confidence interval, 0.44 to 0.61; P < .00001) and 42% (relative risk = 0.58; 95% confidence interval, 0.49 to 0.68; P < .00001), respectively. No significant differences in the incidence of side effects such as bleeding and needle pain were observed between groups (P = .54). AT was also associated with a lower rate of rescue antiemetic usage (P < .00001) and a higher degree of satisfaction with postoperative recovery (P < .0001). Moreover, the optimal therapeutic effect of AT on preventing PONV was achieved when the treatment time was controlled within 30 minutes and transcutaneous acupoint electrical stimulation was applied. CONCLUSION: AT is an effective and safe physical therapy for the prophylaxis of PONV in patients undergoing GS.

The KBTBD6/7-DRD2 axis regulates pituitary adenoma sensitivity to dopamine agonist treatment.

Pituitary adenoma (PA) is one of the most common intracranial tumors, and approximately 40% of all PAs are prolactinomas. Dopamine agonists (DAs), such as cabergoline (CAB), have been successfully used in the treatment of prolactinomas. The expression of dopamine type 2 receptor (DRD2) determines the therapeutic effect of DAs, but the molecular mechanisms of DRD2 regulation are not fully understood. In this study, we first demonstrated that DRD2 underwent proteasome-mediated degradation. We further employed the yeast two-hybrid system and identified kelch repeat and BTB (POZ) domain containing 7 (KBTBD7), a substrate adaptor for the CUL3-RING ubiquitin (Ub) ligase complex, as a DRD2-interacting protein. KBTBD6/7 directly interacted with, and ubiquitinated DRD2 at five ubiquitination sites (K221, K226, K241, K251, and K258). CAB, a high-affinity DRD2 agonist, induced DRD2 internalization, and cytoplasmic DRD2 was degraded via ubiquitination under the control of KBTBD6/7, the activity of which attenuated CAB-mediated inhibition of the AKT/mTOR pathway. KBTBD7 knockout (KO) mice were generated using the CRISPR-Cas9 technique, in which the static level of DRD2 protein was elevated in the pituitary gland, thalamus, and heart, compared to that of WT mice. Consistently, the expression of KBTBD6/7 was negatively correlated with that of DRD2 in human pituitary tumors. Moreover, KBTBD7 was highly expressed in dopamine-resistant prolactinomas, but at low levels in dopamine-sensitive prolactinomas. Knockdown of KBTBD6/7 sensitized MMQ cells and primary pituitary tumor cells to CAB treatment. Conversely, KBTBD7 overexpression increased CAB resistance of estrogen-induced in situ rat prolactinoma model. Together, our findings have uncovered the novel mechanism of DRD2 protein degradation and shown that the KBTBD6/7-DRD2 axis regulates PA sensitivity to DA treatment. KBTBD6/7 may thus become a promising therapeutic target for pituitary tumors.

Ordered Nanostructure Enhances Electrocatalytic Performance by Directional Micro-Electric Field.

Designing high-efficiency catalyst is at the heart of a transition to future renewable energy systems. Great achievements have been made to optimize thermodynamics to reduce energetic barriers of the catalytic reactions. However, little attention has been paid to design catalysts to improve kinetics to enrich the local concentration of reactant molecules surrounding electrocatalysts. Here, we find that well-designed nanocatalysts with periodic structures can optimize kinetics to accelerate mass-transport from bulk electrolyte to the catalyst surface, leading to the enhanced catalytic performance. This achievement stems from regulation of the surface reactant flux due to the gradient of the microelectric field directing uniformly to the nearest catalyst on ordered pattern, so that all of the reactant molecules are utilized sufficiently for reactions, enabling the boost of the electrocatalytic performance. This novel concept is further confirmed in various catalytic systems and nanoassemblies, such as nanoparticles, nanorods, and nanoflakes.

Dietary Silymarin Supplementation Alleviates Zearalenone-Induced Hepatotoxicity and Reproductive Toxicity in Rats.

Background: Zearalenone (ZEN) can cause serious defects in development and reproduction in humans and animals. Silymarin shows antioxidant and estrogenic effects. Objective: This study was conducted to determine if silymarin can antagonize ZEN-induced hepatic and reproductive toxicities. Methods: Thirty-five 21-d-old female Sprague-Dawley rats (n = 7/diet) were fed a control diet (Ctrl) or Ctrl plus 20 mg ZEN/kg or Ctrl plus 20 mg ZEN/kg with 100, 200, or 500 mg silymarin/kg for 6 wk. Serum, livers, ovaries, and uterus were collected at week 6 for biochemistry, hormone, and redox status and selected gene and protein assays. Results: The consumption of ZEN decreased (P < 0.05) the final body weight by 17.9%, induced liver injury, increased (P < 0.05) aspartate aminotransferase and alkaline phosphatase activities, and decreased (P < 0.05) total protein and albumin concentrations in serum by 16.7-40.6%. ZEN also caused reproductive toxicity, including decreased (P < 0.05) 17ß-estradiol and increased (P < 0.05) follicle-stimulating hormone concentrations in serum by 12.7-46.3% and induced histopathologic alterations in the liver, ovaries, and uterus. Interestingly, these alterations induced by ZEN were alleviated (P < 0.05) by silymarin supplementation at 100, 200, and 500 mg/kg. Moreover, silymarin supplementation at the 3 doses mitigated (P < 0.05) ZEN-induced impairment in hepatic glutathione peroxidase activity, total antioxidant capacity, and malondialdehyde concentration by 17.6-100%. Meanwhile, silymarin supplementation at all doses upregulated (P < 0.05) phospho-ribosomal protein S6 kinase 1 (p-RPS6KB1) and 3ß-hydroxysteroid dehydrogenase (HSD3B) by 43.0-121% but downregulated (P < 0.05) AMP-activated protein kinase (AMPK) and 3α-hydroxysteroid dehydrogenase (HSD3A) in the liver relative to the ZEN group by 11.2-40.6%. In addition, silymarin supplementation at all doses elevated (P < 0.05) HSD3B by 1.8- to 2.5-fold and decreased (P < 0.05) estrogen receptor 1 (ESR1), ATP binding cassette (ABC) c1, and Abcc5 in ovaries and the uterus by 10.7-63.2%. Conclusion: Dietary silymarin supplementation at 100, 200, and 500 mg/kg protected rats from ZEN-induced hepatotoxicity and reproductive toxicity, potentially through improvement in the antioxidant capacity and regulation in the genes related to protein synthesis, ZEN metabolism, hormone synthesis, and ABC transporters in the tissues.

[A developmental research on wild Dipsacus asper in Chongqing Wulong district].

In order to study the distribution and dynamics growth of wild Dipsacus asper resources in the Wulong district of Chongqing, 9 sample plots were selected for 12 consecutive months in the natural distribution area of the D. asper in Wulong district by using the sample line + plot survey method to conduct a field survey. The results showed that D.asper was distributed in forest edge wasteland or shrub-grassland, and growbetter with loose yellow-brownsoil or red soil, and poor with lithologic soil or impounded surface water.The growth curve of the plant height from June to July and the ground fresh weight from July to August showed a turning point, it might consume large amounts of nutrients during its flowering period, resulting in the restriction of vegetative growth.The highest temperature in the distribution area of D.asperoides in Wulong district is less than 30 °C, the minimum temperature is about 0 °C, and the rainfall is 1 241-1 392 mm. Its growth environment is no severecold in winter, no heat in summer, and abundant rainfall.The main growth stage of D.asper is from July to October, and the range of root dry rate was 0.162 5-0.239 7 in Xiangkou, 0.154 9-0.223 6 in Baima Mountain, and 0.143 7-0.203 3 Xiannv Mountain. The vegetative growth and dry matter accumulation synchronized in the main growth stage, and the accumulation rate of dry matter was faster than that of vegetative growth. The correlation analysis between indicators and root fresh weight showed that the fresh weight of the aerial part and root fresh weight had the best correlation.

Biosimilars: Key regulatory considerations and similarity assessment tools.

A biosimilar drug is defined in the US Food and Drug Administration (FDA) guidance document as a biopharmaceutical that is highly similar to an already licensed biologic product (referred to as the reference product) notwithstanding minor differences in clinically inactive components and for which there are no clinically meaningful differences in purity, potency, and safety between the two products. The development of biosimilars is a challenging, multistep process. Typically, the assessment of similarity involves comprehensive structural and functional characterization throughout the development of the biosimilar in an iterative manner and, if required by the local regulatory authority, an in vivo nonclinical evaluation, all conducted with direct comparison to the reference product. In addition, comparative clinical pharmacology studies are conducted with the reference product. The approval of biosimilars is highly regulated although varied across the globe in terms of nomenclature and the precise criteria for demonstrating similarity. Despite varied regulatory requirements, differences between the proposed biosimilar and the reference product must be supported by strong scientific evidence that these differences are not clinically meaningful. This review discusses the challenges faced by pharmaceutical companies in the development of biosimilars.