Characterizing the shear response of polymer-grafted nanoparticles.

Grafting polymer chains to the surface of nanoparticles overcomes the challenge of nanoparticle dispersion within nanocomposites and establishes high-volume fractions that are found to enable enhanced material mechanical properties. This study utilizes coarse-grained molecular dynamics simulations to quantify how the shear modulus of polymer-grafted nanoparticle (PGN) systems in their glassy state depends on parameters such as strain rate, nanoparticle size, grafting density, and chain length. The results are interpreted through further analysis of the dynamics of chain conformations and volume fraction arguments. The volume fraction of nanoparticles is found to be the most influential variable in deciding the shear modulus of PGN systems. A simple rule of mixture is utilized to express the monotonic dependence of shear modulus on the volume fraction of nanoparticles. Due to the reinforcing effect of nanoparticles, shortening the grafted chains results in a higher shear modulus in PGNs, which is not seen in linear systems. These results offer timely insight into calibrating molecular design parameters for achieving the desired mechanical properties in PGNs.

Learning pair potentials using differentiable simulations.

Learning pair interactions from experimental or simulation data is of great interest for molecular simulations. We propose a general stochastic method for learning pair interactions from data using differentiable simulations (DiffSim). DiffSim defines a loss function based on structural observables, such as the radial distribution function, through molecular dynamics (MD) simulations. The interaction potentials are then learned directly by stochastic gradient descent, using backpropagation to calculate the gradient of the structural loss metric with respect to the interaction potential through the MD simulation. This gradient-based method is flexible and can be configured to simulate and optimize multiple systems simultaneously. For example, it is possible to simultaneously learn potentials for different temperatures or for different compositions. We demonstrate the approach by recovering simple pair potentials, such as Lennard-Jones systems, from radial distribution functions. We find that DiffSim can be used to probe a wider functional space of pair potentials compared with traditional methods like iterative Boltzmann inversion. We show that our methods can be used to simultaneously fit potentials for simulations at different compositions and temperatures to improve the transferability of the learned potentials.

Combination of VMD Mapping MFCC and LSTM: A New Acoustic Fault Diagnosis Method of Diesel Engine.

Diesel engines have a wide range of functions in the industrial and military fields. An urgent problem to be solved is how to diagnose and identify their faults effectively and timely. In this paper, a diesel engine acoustic fault diagnosis method based on variational modal decomposition mapping Mel frequency cepstral coefficients (MFCC) and long-short-term memory network is proposed. Variational mode decomposition (VMD) is used to remove noise from the original signal and differentiate the signal into multiple modes. The sound pressure signals of different modes are mapped to the Mel filter bank in the frequency domain, and then the Mel frequency cepstral coefficients of the respective mode signals are calculated in the mapping range of frequency domain, and the optimized Mel frequency cepstral coefficients are used as the input of long and short time memory network (LSTM) which is trained and verified, and the fault diagnosis model of the diesel engine is obtained. The experimental part compares the fault diagnosis effects of different feature extraction methods, different modal decomposition methods and different classifiers, finally verifying the feasibility and effectiveness of the method proposed in this paper, and providing solutions to the problem of how to realise fault diagnosis using acoustic signals.

Atomistic hybrid particle-field molecular dynamics combined with slip-springs: Restoring entangled dynamics to simulations of polymer melts.

In hybrid particle-field (hPF) simulations (J. Chem. Phys., 2009 130, 214106), the entangled dynamics of polymer melts is lost due to chain crossability. Chains cross, because the field-treatment of the nonbonded interactions makes them effectively soft-core. We introduce a multi-chain slip-spring model (J. Chem. Phys., 2013 138, 104907) into the hPF scheme to mimic the topological constraints of entanglements. The structure of the polymer chains is consistent with that of regular molecular dynamics simulations and is not affected by the introduction of slip-springs. Although slight deviations are seen at short times, dynamical properties such as mean-square displacements and reorientational relaxation times are in good agreement with traditional molecular dynamics simulations and theoretical predictions at long times.

The role of the envelope protein in the stability of a coronavirus model membrane against an ethanolic disinfectant.

Ethanol is highly effective against various enveloped viruses and can disable the virus by disintegrating the protective envelope surrounding it. The interactions between the coronavirus envelope (E) protein and its membrane environment play key roles in the stability and function of the viral envelope. By using molecular dynamics simulation, we explore the underlying mechanism of ethanol-induced disruption of a model coronavirus membrane and, in detail, interactions of the E-protein and lipids. We model the membrane bilayer as N-palmitoyl-sphingomyelin and 1-palmitoyl-2-oleoylphosphatidylcholine lipids and the coronavirus E-protein. The study reveals that ethanol causes an increase in the lateral area of the bilayer along with thinning of the bilayer membrane and orientational disordering of lipid tails. Ethanol resides at the head-tail region of the membrane and enhances bilayer permeability. We found an envelope-protein-mediated increase in the ordering of lipid tails. Our simulations also provide important insights into the orientation of the envelope protein in a model membrane environment. At ∼25 mol. % of ethanol in the surrounding ethanol-water phase, we observe disintegration of the lipid bilayer and dislocation of the E-protein from the membrane environment.

Maternal supplementation of nucleotides improves the behavioral development of prenatal ethanol-exposed mice.

Maternal ethanol consumption during pregnancy can induce learning deficits in the offspring. The objective of this study was to assess whether supplementation of exogenous nucleotides during pregnancy and lactation would ameliorate prenatal ethanol-induced learning and memory deficits in the offspring of mice, and to explore the possible mechanisms. In the present study, pregnant C57BL/6J mice were exposed to ethanol (5 g/kg body weight) intragastrically from gestational day (GD) 6 to GD15. The dams in exogenous nucleotide intervention groups were fed with feed containing 0.01%, 0.04%, or 0.16% nucleotide powder, with control and ethanol groups receiving normal feed. The dams were allowed to deliver naturally and to breast feed their offspring. After weaning, behavioral tests were carried out in the offspring of each group. Serum oxidation indexes were analyzed, and the hippocampus of each offspring was collected and detected for acetyl cholinesterase (AChE) activity and the expression of p-CREB, CREB, and BDNF. The results showed that maternal supplementation with exogenous nucleotides during pregnancy could ameliorate prenatal ethanol-induced learning and memory deficits in the offspring of mice, through improving their antioxidant capacity, reversing hippocampus AChE levels, and allowing the expression of some proteins related to learning and memory. However, different sensitivities were found between the two sexes.

Fructus ligustri lucidi ethanol extract improves bone mineral density and properties through modulating calcium absorption-related gene expression in kidney and duodenum of growing rats.

Optimizing peak bone mass in early life is one of key preventive strategies against osteoporosis. Fructus ligustri lucidi (FLL), the fruit of Ligustrum lucidum Ait., is a commonly prescribed herb in many kidney-tonifying traditional Chinese medicinal formulas to alleviate osteoporosis. Previously, FLL extracts have been shown to have osteoprotective effect in aged or ovariectomized rats. In the present study, we investigated the effects of FLL ethanol extract on bone mineral density (BMD) and mechanical properties in growing male rats and explored the underlying mechanisms. Male weaning Sprague-Dawley rats were randomized into four groups and orally administrated for 4 months an AIN-93G formula-based diet supplementing with different doses of FLL ethanol extract (0.40, 0.65, and 0.90 %) or vehicle control, respectively. Then calcium balance, serum level of Ca, P, 25(OH)2D3, 1,25(OH)2D3, osteocalcin (OCN), C-terminal telopeptide of type I collagen (CTX-I), and parathyroid hormone, bone microarchitecture, and calcium absorption-related genes expression in duodenum and kidney were analyzed. The results demonstrated that FLL ethanol extract increased BMD of growing rats and improved their bone microarchitecture and mechanical properties. FLL ethanol extract altered bone turnover, as evidenced by increasing a bone formation maker, OCN, and decreasing a bone resorption maker, CTX-I. Intriguingly, both Ca absorption and Ca retention rate were elevated by FLL ethanol extract treatment, possibly through the mechanisms of up-regulating the transcriptions of calcitropic genes in kidney (1α-hydroxylase) and duodenum (vitamin D receptor, calcium transporter calbindin-D9k, and transient receptor potential vanilloid 6). In conclusion, FLL ethanol extract increased bone mass gain and improved bone properties via modulating bone turnover and up-regulating calcium absorption-related gene expression in kidney and duodenum, which could then activate 1,25(OH)2D3-dependent calcium transport in male growing rats.

Fructus Ligustri Lucidi (FLL) ethanol extract increases bone mineral density and improves bone properties in growing female rats.

Osteoporosis is a chronic disease affecting millions of people worldwide. It is generally accepted that acquisition of a high peak bone mass (PBM) early in life can reduce the risk of osteoporosis later in life. The aims of this study were to investigate the effects of Fructus Ligustri Lucidi (FLL) ethanol extract on bone mineral density and its mechanical properties in growing female rats and to explore the underlying mechanisms. The rats were given different doses of FLL extract mixed with AIN-93G formula (0.40, 0.65 and 0.90 %), and a group given AIN-93G diet treatment only was used as control. The intervention lasted for 16 weeks until the animals were about 5 months old, the time when the animals almost reach their PBM. Our results showed that FLL treatment increased bone mineral density and improved bone mechanical properties in the growing female rats in a dose-dependent manner. In addition, FLL treatment significantly decreased the serum bone-resorbing marker, CTX-I, while significantly increasing serum 25(OH)D3 and thereby increasing Ca absorption and Ca retention. Intriguingly, both in vivo and in vitro results demonstrated that FLL treatment could reduce the RANKL/OPG ratio. In conclusion, FLL ethanol extract exerted beneficial effects on peak bone mass acquisition and the improvement of bone mechanical properties by favoring Ca metabolism and decreasing the RANKL/OPG ratio.

Maternal quercetin administration during gestation and lactation decrease endoplasmic reticulum stress and related inflammation in the adult offspring of obese female rats.

PURPOSE: Maternal obesity is a risk factor for metabolic diseases in offspring. The aim of this study was to investigate whether quercetin administration during gestation and lactation could have any protective effect against the impact of maternal obesity on increased sensitivity to obesity and metabolic disorders in offspring. METHODS: Female Sprague-Dawley rats were fed a high-fat diet to induce obesity. Obese dams were administered 0, 50, 100 or 200 mg/kg body weight (BW) quercetin intragastrically during gestation and lactation. Normal weight dams were used as controls. The F1 generation was fed with a standard diet after weaning, and blood glucose, lipids and inflammatory factors were assessed. Expression of biomarkers involved endoplasmic reticulum (ER) stress, and related inflammatory pathways in liver and adipose tissues were analyzed at postnatal day 100. RESULTS: Maternal obesity resulted in increased birth weight, postnatal BW gain, hyperglycemia, hyperlipemia, hyperinsulinemia, increased serum levels of inflammatory factors, and up-regulated biomarkers involved in ER stress and related inflammatory pathways in the offspring. Maternal quercetin intervention (QI) had significant ameliorating effects on maternal blood lipids, especially cholesterol, which resulted in improved glucose metabolism and insulin sensitivity and alleviated ER stress and related inflammation in the grown offspring of obese dams. CONCLUSIONS: Maternal QI in obese dams during gestation and lactation reduced birth weight and postnatal BW gain in the offspring, and helped to improve insulin sensitivity and lipid metabolism of the mature offspring via reducing ER stress and related inflammation in the liver and adipose tissue.

[Effects of quercetin in pregnant and lactation period on weight and expression of insulin-like growth factors-1 mRNA of obese female rats offspring].

OBJECTIVE: To study the effect of quercetin given during pregnancy and lactation period of obese rats on weight and expression of insulin-like growth factors-1 (IGF-1) mRNA of the offspring. METHODS: In the study, 8 healthy weaning female SD rats were randomly selected to feed the basal diet and as blank control group, and the others were fed with high-fat diet. When the average weight of the high-fat diet rats was 20% as many as the average weight of the control group, we believed the model succeeded. Then the female SD rats were mated and the pregnant rats were randomly divided into 5 groups, 8 rats in each. They were fed with high fat diet during pregnancy and lactation, and the obese pregnant rats were respectively irrigated with 0 mg/kg body weight (high-fat control), 50 mg/kg body weight,100 mg/kg body weight, and 200 mg/kg body weight quercetin. The blank control group was fed with basic diet throughout the experimental period. The birth weight, the weights during the development of d7, d21, d56, and d98, and the expressions of IGF-1 mRNA in livers tissue of the F1 generation were measured. RESULTS: The average birth weight of the F1 generation of high fat diet (HFD) group was significantly higher than that of the blank control group. Decreased offspring birth weight was observed with the intervention of quercetin, which effect remained to the delectation. The quercetin also reduced the expression of IGF-1 mRNA in livers of the F1 generation, and this effect remained to the adulthood. The 200 mg/kg body weight quercetin was most significantly effective. CONCLUSION: The averaged birth weight of the F1 generation of obese pregnant rats was significantly increased, and quercetin could effectively inhibit the expression of IGF-1 mRNA in livers of F1 generation to decrease cell proliferation and cell differentiation.

Structural Coarse-Graining via Multiobjective Optimization with Differentiable Simulation.

In the realm of multiscale molecular simulations, structure-based coarse-graining is a prominent approach for creating efficient coarse-grained (CG) representations of soft matter systems, such as polymers. This involves optimizing CG interactions by matching static correlation functions of the corresponding degrees of freedom in all-atom (AA) models. Here, we present a versatile method, namely, differentiable coarse-graining (DiffCG), which combines multiobjective optimization and differentiable simulation. The DiffCG approach is capable of constructing robust CG models by iteratively optimizing the effective potentials to simultaneously match multiple target properties. We demonstrate our approach by concurrently optimizing bonded and nonbonded potentials of a CG model of polystyrene (PS) melts. The resulting CG-PS model effectively reproduces both the structural characteristics, such as the equilibrium probability distribution of microscopic degrees of freedom and the thermodynamic pressure of the AA counterpart. More importantly, leveraging the multiobjective optimization capability, we develop a precise and efficient CG model for PS melts that is transferable across a wide range of temperatures, i.e., from 400 to 600 K. It is achieved via optimizing a pairwise potential with nonlinear temperature dependence in the CG model to simultaneously match target data from AA-MD simulations at multiple thermodynamic states. The temperature transferable CG-PS model demonstrates its ability to accurately predict the radial distribution functions and density at different temperatures, including those that are not included in the target thermodynamic states. Our work opens up a promising route for developing accurate and transferable CG models of complex soft-matter systems through multiobjective optimization with differentiable simulation.

Progesterone receptor impairs immune respond and down-regulates sensitivity to anti-LAG3 in breast cancer.

BACKGROUND: Progesterone receptor (PR) serves as a crucial prognostic and predictive marker in breast cancer. Nonetheless, the interplay between PR and the tumor immune microenvironment remains inadequately understood. This investigation employs bioinformatics analyses, mouse models, and clinical specimens to elucidate the impact of PR on immune microenvironment and identify potential targets for immunotherapy, furnishing valuable guidance for clinical practice. METHODS: Analysis of immune infiltration score by Xcell between PR-positive and PR-negative breast cancer tumors. Construction of overexpression mouse progesterone receptor (mPgr) EMT-6 cell was to explore the tumor immune microenvironment. Furthermore, anti- Lymphocyte-activation gene 3 (LAG3) therapy aimed to investigate whether PR could influence the effectiveness of immune treatments. RESULTS: Overexpression mPgr inhibited tumor growth in vitro, but promoted tumor growth in Balb/c mouse. Flow cytometry showed that the proportion and cytotoxicity of CD8+T cells in tumor of overexpressing mPgr group were significantly reduced. The significant reduction in overexpressing mPgr group was found in the proportions of LAG3+CD8+ T cells and LAG3+ Treg T cells. Anti-LAG3 treatment resulted in reduced tumor growth in EV group mouse rather than in overexpressing mPgr group. Patents derived tumor fragment (PDTF) also showed higher anti-tumor ability of CD3+T cell in patents' tumor with PR <20% after anti-human LAG3 treatment in vitro. CONCLUSIONS: The mPgr promotes tumor growth by downregulating the infiltration and function of cytotoxic cell. LAG3 may be a target of ER-positive breast cancer immunotherapy. The high expression of PR hinders the sensitivity to anti-LAG3 treatment.

Machine learning algorithms for identifying contralateral central lymph node metastasis in unilateral cN0 papillary thyroid cancer.

Purpose: The incidence of thyroid cancer is growing fast and surgery is the most significant treatment of it. For patients with unilateral cN0 papillary thyroid cancer whether to dissect contralateral central lymph node is still under debating. Here, we aim to provide a machine learning based prediction model of contralateral central lymph node metastasis using demographic and clinical data. Methods: 2225 patients with unilateral cN0 papillary thyroid cancer from Wuhan Union Hospital were retrospectively studied. Clinical and pathological features were compared between patients with contralateral central lymph node metastasis and without. Six machine learning models were constructed based on these patients and compared using accuracy, sensitivity, specificity, area under the receiver operating characteristic and decision curve analysis. The selected models were then verified using data from Differentiated Thyroid Cancer in China study. All statistical analysis and model construction were performed by R software. Results: Male, maximum diameter larger than 1cm, multifocality, ipsilateral central lymph node metastasis and younger than 50 years were independent risk factors of contralateral central lymph node metastasis. Random forest model performed better than others, and were verified in external validation cohort. A web calculator was constructed. Conclusions: Gender, maximum diameter, multifocality, ipsilateral central lymph node metastasis and age should be considered for contralateral central lymph node dissection. The web calculator based on random forest model may be helpful in clinical decision.

Development of a Cation Exchange SPE-HILIC-MS/MS Method for the Determination of Ningnanmycin Residues in Tea and Chrysanthemum.

Ningnanmycin is a widely used antibiotic in agricultural production that effectively controls fungal and viral diseases in tea trees and chrysanthemums. The polarity characteristic of ningnanmycin has posed limitations on the development of robust detection methods, thereby hindering effective monitoring and control measures. By combining cation exchange solid phase extraction (SPE) with hydrophilic interaction chromatography tandem mass spectrometry (HILIC-MS/MS), we have effectively tackled the issue pertaining to the separation and retention of ningnanmycin. The average recoveries of ningnanmycin in green tea, black tea, and chrysanthemum were 77.3-82.0%, 80.1-81.5%, and 74.0-80.0%, respectively. The intraday and interday relative standard deviations (RSDs) were below and equal to 7.7%. Good linearity was observed in the concentration range of 1-1000 µg/L (R2 > 0.998). The limits of detection (LODs) ranged from 1.1 µg/kg to 7.1 µg/kg, and the limits of quantification (LOQs) ranged from 3.6 µg/kg to 23.7 µg/kg for ningnanmycin. These results indicate the good accuracy, repeatability, reproducibility, and sensitivity of the method. It is suitable for detecting ningnanmycin in tea and chrysanthemum.

Cediranib ameliorates portal hypertensive syndrome via inhibition of VEGFR-2 signaling in cirrhotic rats.

Portal hypertension (PHT) is a syndrome caused by systemic and portal hemodynamic disturbances with the progression of cirrhosis. However, the exact mechanisms regulating angiogenesis-related responses in PHT remain unclear. Cediranib is a potent inhibitor of vascular endothelial growth factor receptor (VEGFR) tyrosine kinases, exhibiting a greater affinity for VEGFR-2. Liver cirrhosis was induced by common bile duct ligation (BDL) in Sprague-Dawley rats. Sham-operated rats were controls. BDL and sham rats were randomly allocated to receive Cediranib or vehicle after BDL. On the 28th day, portal hypertension related parameters were surveyed. Cediranib treatment could significantly reduce the portal pressure (PP) in BDL rats, while it did not affect the mean arterial pressure (MAP) in sham groups and BDL groups. Cediranib treatment could significantly affect the stroke volume (SV), cardiac output (CO), cardiac index (CI), systemic vascular resistance (SVR), superior mesenteric artery (SMA) flow and SMA resistance in BDL groups and BDL with Cediranib groups. Cediranib treatment could improve the mesenteric vascular remodeling and contractility. Cediranib treatment significantly reduced mesenteric vascular density. And phospho-VEGFR-2 was significantly downregulated by Cediranib. On the other hand, phospho-endothelial Nitric Oxide Synthases (phospho-eNOS) expressions were upregulated. Cediranib not only improved splanchnic hemodynamics, extrahepatic vascular remodeling and vasodilation, but also alleviated intrahepatic fibrosis and collagen deposition significantly. Cediranib treatment could reduce intrahepatic angiogenesis between BDL-vehicle and BDL-Cediranib rats. In conclusion, Cediranib could improve extrahepatic hyperdynamic circulation by inhibiting extrahepatic angiogenesis through inhibition of the VEGFR-2 signaling pathway, portal collateral circulation formation, as well as eNOS-mediated vasodilatation and vascular remodeling, and at the same time, Cediranib improved intrahepatic fibrogenesis and angiogenesis, which together alleviate cirrhotic PHT syndrome.

[Efficacy of iron saturated recombinant human lactoferrin on alleviating iron deficiency anemia in rats].

OBJECTIVE: To investigate the effect of iron saturated recombinant human lactoferrin (Fe-rhLf) on treating iron deficiency anemia (IDA). METHODS: SD rats received iron deficient diet and deionized water during the whole experiment. After 4 weeks, the rats with hemoglobin less than 100 g/L were selected and divided into 5 groups randomly. IDA group received 100 mg/(kg×d) casein dissolved in deionized water intragastrically; FeSO4 group received 5.43 mg/(kg×d) [2.0 mg/(kg×d) iron]+100 mg/(kg×d) casein intragastrically; low dose Fe-rhLf group received 75.53 mg/(kg×d) Fe-rhLf [0.5 mg/(kg×d) iron] +75 mg/(kg×d) casein intragastrically; middle dose group received 151.06 mg/(kg×d) Fe-rhLf [1.0 mg/(kg×d) iron]+50 mg/(kg×d) casein intragastrically; high dose group received 302.11 mg/(kg×d) Fe-rhLf [2.0 mg/(kg×d) iron] intragastrically. After 30 days of intervention, the rats' blood was collected and used to do the routine blood test, serum iron and serum anti-oxidants test. The liver hepcidin and ferroportin mRNA expression was tested by real time PCR. RESULTS: Compared with the animals in the IDA group, Fe-rhLf could increase weight significantly (P<0.05), hematological parameters, like hemoglobin (P<0.01) and red blood cell count (P<0.01) recovered significantly. Compared with animals in FeSO4 group, high dose Fe-rhLf could improve hemoglobin significantly (P<0.05). The liver hepcidin expression was up regulated and ferroportin down regulated. CONCLUSION: Fe-rhLf has a significant effect on treating iron deficiency anemia.

Association between COVID-19 and chronic liver disease: Mechanism, diagnosis, damage, and treatment.

As the outbreak evolves, our understanding of the consequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the resulting coronavirus disease 2019 (COVID-19) on the liver has grown. In this review, we discussed the hepatotropic nature of SARS-CoV-2 and described the distribution of receptors for SARS-CoV-2 (e.g., angiotensin-converting enzyme 2) in the vascular endothelium and cholangiocytes of the liver. Also, we proposed mechanisms for possible viral entry that mediate liver injury, such as liver fibrosis. Due to SARS-CoV-2-induced liver damage, many COVID-19 patients develop liver dysfunction, mainly characterized by moderately elevated serum aminotransferase levels. Patients with chronic liver disease (CLD), such as cirrhosis, hepatocellular carcinoma, nonalcoholic fatty liver disease, and viral hepatitis, are also sensitive to SARS-CoV-2 infection. We discussed the longer disease duration and higher mortality following SARS-CoV-2 infection in CLD patients. Correspondingly, relevant risk factors and possible mechanisms were proposed, including cirrhosis-related immune dysfunction and liver deco-mpensation. Finally, we discussed the potential hepatotoxicity of COVID-19-related vaccines and drugs, which influence the treatment of CLD patients with SARS-CoV-2 infection. In addition, we suggested that COVID-19 vaccines in terms of immunogenicity, duration of protection, and long-term safety for CLD patients need to be further researched. The diagnosis and treatment for liver injury caused by COVID-19 were also analyzed in this review.

Near-infrared-excitable acetylcholinesterase-activated fluorescent probe for sensitive and anti-interference detection of pesticides in colored food.

The development of a common and anti-interference acetylcholinesterase (AChE) inhibition assay for plant-originated food samples has been of great challenge because of the prevalent and strong signal interferences from natural pigments. Plant pigments normally exhibit non-negligible absorbance in the UV-visible region. As a result, the signals of a typical near-infrared (NIR) fluorescent probe could be disturbed through primary inner filter effect if it is excited by UV-visible light during plant sample analysis. In this work, an NIR-excitable AChE-activated fluorescent probe was biomimetically designed and synthesized. And the NIR-excitation strategy was utilized for the anti-interference detection of organophosphate and carbamate pesticides in colored samples with this probe. Sensitive and rapid response to AChE and pesticides was achieved due to the high affinity of the biomimetic recognition unit in the probe. The limits of detection for four representative pesticides including dichlorvos, carbofuran, chlorpyrifos and methamidophos reached 0.0186 µg/L, 2.20 µg/L, 12.3 µg/L and 13.6 µg/L, respectively. Most importantly, fluorescent response to pesticide contents could be accurately measured in the coexistence of different plant pigments by this probe, and the measured results showed completely irrelevance to the plant pigments and their colors. Taking advantage of such probe, the new developed AChE inhibition assay showed good sensitivity and anti-interference ability in the detection of organophosphate and carbamate pesticides in real samples.

Construction and validation of nomograms to reduce completion thyroidectomy by predicting lymph node metastasis in low-risk papillary thyroid carcinoma.

CONTEXT: More than 5 central lymph nodes metastases (CLNM) or lateral lymph node metastasis (LLNM) indicates a higher risk of recurrence in low-risk papillary thyroid carcinoma (PTC) and may lead to completion thyroidectomy (CTx) in patients initially undergoing lobectomy. OBJECTIVE: To screen potentially high-risk patients from low-risk patients by using preoperative and intraoperative clinicopathological features to predict lymph node status. METHODS: A retrospective analysis of 8301 PTC patients in Wuhan Union Hospital database (2009-2021) was performed according to the 2015 American Thyroid Association (ATA) and 2021 National Comprehensive Cancer Network (NCCN) guidelines, respectively. Logistic regression and best subsets regression were used to identify risk factors. Nomograms were established and externally validated using the Differentiated Thyroid Cancer in China cohort. RESULTS: More than 5 CLNM or LLNM was detected in 1648 (19.9%) patients. Two predictive models containing age, gender, maximum tumor size, free thyroxine (FT4) and palpable node (all p < 0.05) were established. The nomogram based on NCCN criteria showed better discriminative power and consistency with a specificity of 0.706 and a sensitivity of 0.725, and external validation indicated that 76% of potentially high-risk patients could achieve preoperative conversion of surgical strategy. CONCLUSIONS: Models based on large cohorts with good predictive performance were constructed and validated. Preoperative low-risk (T1-2N0M0) patients with age younger than 40 years, male gender, large tumor size, low FT4 and palpable nodes may be at high risk of LLNM or more than 5 CLNM, and they should receive more aggressive initial therapy to reduce CTx.

Slip-Spring Hybrid Particle-Field Molecular Dynamics for Coarse-Graining Branched Polymer Melts: Polystyrene Melts as an Example.

The topology of chains significantly modifies the dynamical properties of polymer melts. Here, we extend a recently developed efficient simulation method, namely the slip-spring hybrid particle-field (SS-hPF) model, to study the structural and dynamical properties of branched polymer melts over large spatial-temporal scales. In the coarse-grained SS-hPF simulation of polymers, the bonded potentials are derived by iterative Boltzmann inversion from the underlying fine-grained model. The nonbonded potentials are computed from a density functional field instead of pairwise interactions used in standard molecular dynamics simulations, which increases the computational efficiency by a factor of 10-20. The entangled dynamics is lost due to the soft-core nature of density functional field interactions. It is recovered by a multichain slip-spring model that is rigorously parametrized from existing experimental or simulation data. To quantitatively predict the relaxation and diffusion of branched polymers, which are dominated by arm retraction rather than chain reptation, the slip-spring algorithm is augmented to improve the polymer dynamics near the branch point. Multiple dynamical observables, e.g., diffusion coefficients, arm relaxations, and tube survival probabilities, are characterized in an example coarse-grained model of symmetric and asymmetric star-shaped polystyrene melts. Consistent dynamical behaviors are identified and compared with theoretical predictions. With a single rescaling factor, the prediction of diffusion coefficients agrees well with the available experimental measurements. In this work, an efficient approach is provided to build chemistry-specific coarse-grained models for predicting the dynamics of branched polymers.