Kallistatin leads to cognition impairment via downregulating glutamine synthetase.

In many neurodegenerative disorders, such as Alzheimer's disease (AD), glutamate-mediated neuronal excitotoxicity is considered the basis for cognitive impairment. The mRNA and protein expression of SERPINA4(Kallistatin) are higher in patients with AD. However, whether Kallistatin plays a regulatory role in glutamate-glutamine cycle homeostasis remains unclear. In this study, we identified impaired cognitive function in Kallistatin transgenic (KAL-TG) mice. Baseline glutamate levels were elevated and miniature excitatory postsynaptic current (mEPSC) frequency was increased in the hippocampus, suggesting the impairment of glutamate homeostasis in KAL-TG mice. Mechanistically, we demonstrated that Kallistatin promoted lysine acetylation and ubiquitination of glutamine synthetase (GS) and facilitated its degradation via the proteasome pathway, thereby downregulating GS. Fenofibrate improved cognitive memory in KAL-TG mice by downregulating serum Kallistatin. Collectively, our study findings provide insights the mechanism by which Kallistatin regulates cognitive impairment, and suggest the potential of fenofibrate to prevente and treat of AD patients with high levels of Kallistatin.

Physical activity during pregnancy and the risk of gestational diabetes mellitus: a systematic review and dose-response meta-analysis.

BACKGROUND: Previous research has indicated the inverse association between physical activity (PA) and gestational diabetes mellitus (GDM). However, the dose-response relationship currently remains undetermined. This study aims to explore the dose-response relationship between PA during the first and second trimesters of pregnancy and GDM risk. METHODS: Studies on the relationship between PA during pregnancy and GDM risk published before April 25, 2023, were searched for in six databases. According to the inclusion and exclusion criteria, all literature was screened for eligibility. The Newcastle-Ottawa Scale (NOS) was used to assess risk of bias. Publication bias was examined using funnel plots, Begg's and Egger's tests, as well as trim-and-fill analysis. We harmonized exposure estimates of PA during pregnancy to the common unit of the metabolic equivalent of task (MET)-h/week. Restricted cubic splines were used to model the dose-response relationship. The criteria from the World Cancer Research Fund were used to assess the certainty of evidence across outcomes. All analyses were performed using Stata 15.1. RESULTS: The results indicated that in contrast with the lowest level of PA, promoting the highest PA level lowers the risk of GDM by 36% (RR = 0.64, 95%CI: 0.53 ~ 0.78). We found a curvilinear dose-response association between PA during the first trimester and incident GDM (Pnonlinearity = 0.012). Compared to inactive pregnant women, for those who achieved the guidelines-suggested minimum level (10 MET-h/week) of PA during the first trimester, the GDM risk was decreased by 13% (RR = 0.87, 95%CI: 0.79 ~ 0.96). A linear relationship was found between PA during the second trimester and the GDM risk (Pnonlinearity = 0.276). The results with a restricted cubic spline model suggested that pregnant women who accumulate 10 MET-h/week have a 1% reduced risk of GDM compared to completely inactive individuals. Twice (20 MET-h/week) or a higher amount of PA (50 MET-h/week) contributed to further reductions in GDM risk. CONCLUSION: There is a dose-response relationship between higher levels of PA in both the first and second trimesters and reduced risk of GDM; the relationship is stronger in the first trimester. Increasing PA during pregnancy can prevent the development of GDM. PROSPERO REGISTRATION NUMBER: CRD42023420564.

Comparative Study of Machine Learning-Based QSAR Modeling of Anti-inflammatory Compounds from Durian Extraction.

Quantitative structure-activity relationship (QSAR) analysis, an in silico methodology, offers enhanced efficiency and cost effectiveness in investigating anti-inflammatory activity. In this study, a comprehensive comparative analysis employing four machine learning algorithms (random forest (RF), gradient boosting regression (GBR), support vector regression (SVR), and artificial neural networks (ANNs)) was conducted to elucidate the activities of naturally derived compounds from durian extraction. The analysis was grounded in the exploration of structural attributes encompassing steric and electrostatic properties. Notably, the nonlinear SVR model, utilizing five key features, exhibited superior performance compared to the other models. It demonstrated exceptional predictive accuracy for both the training and external test datasets, yielding R2 values of 0.907 and 0.812, respectively; in addition, their RMSE resulted in 0.123 and 0.097, respectively. The study outcomes underscore the significance of specific structural factors (denoted as shadow ratio, dipole z, methyl, ellipsoidal volume, and methoxy) in determining anti-inflammatory efficacy. Thus, the findings highlight the potential of molecular simulations and machine learning as alternative avenues for the rational design of novel anti-inflammatory agents.

Factors Associated With Influenza Vaccination During Pregnancy: A Real-World Evidence-Based Study.

Pregnant women are at increased risk of influenza-related complications. However, the rate of influenza vaccination among pregnant women in Taiwan is low. By analyzing real-world data in this study, we investigated the factors associated with influenza vaccination during pregnancy in Taiwan. This study was a cross-sectional study. We collected real-world data from 2 databases in Taiwan: the Birth Certificate Database and the National Health Insurance Research Database. The study population was pregnant between October 2014 and December 2016 in Taiwan. The multivariate logistic regression was performed to identify factors associated with influenza vaccination, including maternal sociodemographics, trimester, comorbidities, and health-care utilization. The vaccination rate of among pregnant women was 8.2%. Factors significantly associated with a high likelihood of influenza vaccination were age between 30 and 34 years (odds ratio [OR]: 1.14; 95% confidence interval [CI]: 1.10-1.19), second trimester (OR: 1.80; 95% CI: 1.75-1.85), income equal to or exceeding NT$ 38 201 (OR: 1.92; 95% CI: 1.86-1.99), hypertension (OR: 1.16; 95% CI: 1.05-1.29), cardiovascular disease (OR: 1.29; 95% CI: 1.17-1.42), autoimmune disease (OR: 1.47; 95% CI: 1.38-1.58), and chronic pulmonary disease (OR: 1.24; 95% CI: 1.18-1.31). A low level of urbanization, at least 1 hospitalization in the previous year, and the presence of pregnancy complications (eg, gestational diabetes, preeclampsia, and placenta previa) were associated with a lower likelihood rate of influenza vaccination. The influenza vaccination rate among pregnant women in Taiwan was low. Age, gestational age, income level, urbanization level, hypertension, cardiovascular disease, autoimmune disease, chronic pulmonary disease, and pregnancy complications may be associated with influenza vaccination among pregnant women.

Designing Potent α-Glucosidase Inhibitors: A Synthesis and QSAR Modeling Approach for Biscoumarin Derivatives.

Nineteen biscoumarins were synthesized, well-characterized, and evaluated against α-glucosidases in vitro. Of these, six compounds (10, 12, 16, and 17-19) were newly synthesized and not previously reported in the chemical literature. The majority of the synthesized derivatives demonstrated significant inhibitory activity. A quantitative structure-activity relationship (QSAR) model was developed, revealing a strong correlation between the anti-α-glucosidase activity and selected molecular descriptors. Based on this model, two new compounds (18 and 19) were designed, which exhibited the strongest inhibition with IC50 values of 0.62 and 1.21 µM, respectively, when compared to the positive control (acarbose) with an IC50 value of 93.63 µM. Enzyme kinetic studies of compounds 18 and 19 revealed their competitive inhibition with Ki values of 3.93 and 1.80 µM, respectively. Computational studies demonstrated that compound 18 could be inserted into the original binding site (OBS) of α-glucosidase MAL12 and form multiple hydrophobic interactions with nearby amino acids, with the bromo group playing an essential role in enhancing the binding strength and stability at the OBS of the enzyme based on the quantum mechanical calculations using the fragment molecular orbital method. These findings provide valuable insights into the design of potent α-glucosidase inhibitors, which may have potential therapeutic applications in the treatment of diabetes and related diseases.

Hair-based rapid UPLC-MS/MS analysis of 36 phencyclidine-type substances in forensic cases.

Phencyclidine (PCP) is a frequently abused dissociative agent. It causes confusion, increased tendencies toward violence, and concentration-dependent cytotoxicity after entry into the body. The parent nucleus of phencyclidine-type substances is arylcyclohexylamine, which is easy to modify; therefore, abusers and dealers can readily synthesize substitutes beyond the drug control catalog. An urgent need exists to establish screening methods for phencyclidine-type substances to provide technical support for abuse monitoring. In this study, 20 mg of hair was pulverized in 500 mL of methanol containing 0.5 ng/mL PCP-d5. After ultrasonication, centrifugation, and filtration, the supernatant was analyzed by ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) operating in the multiple reaction monitoring mode. Phencyclidine-type substances were separated in 13 min on a biphenyl column using a mobile phase gradient composed of A (water, formic acid 0.1%, acetonitrile 5%, 20 mmol/L ammonium acetate) and B (acetonitrile). The developed and validated method showed good selectivity, sensitivity (limit of detection: 0.25-2 pg/mg and lower limit of quantitation: 0.5-4 pg/mg), linearity (R2 > 0.994), accuracy, and precision (< 20%), and a dilution effect. The method also showed good recovery and acceptable matrix effects for most of the targeted compounds. This analytical approach was successfully applied for the identification and quantification of phencyclidine-type substances in hair from 87 authentic forensic cases. Nine analytes were detected: ketamine (10.3-26211.3 pg/mg), 2-F-2-oxo-PCE (11.5-4034.9 pg/mg), 2-FDCK (14.0-43290.2 pg/mg), 2-BrDCK (10.6-21170.0 pg/mg), nor2-FDCK (10.1-16767.4 pg/mg), tiletamine (10.1-3250.8 pg/mg), O-PCE (43.3-166.1 pg/mg), DCK (10.2-90.4 pg/mg), and norDCK (24.9-103.0 pg/mg).

Pigment Epithelium-Derived Factor, a Novel Adipokine, Contributes to Gestational Diabetes Mellitus.

CONTEXT: Excessive insulin resistance, inadequate insulin compensation, or both could result in gestational diabetes mellitus (GDM). Levels of pigment epithelium-derived factor (PEDF), a novel adipokine that could induce insulin resistance, are high in patients with obesity and diabetes. However, the impact of PEDF in pregnancy remains unknown. OBJECTIVE: This study aimed to elucidate the role of PEDF on insulin resistance and compensatory elevation of insulin levels during normal pregnancy and in patients with GDM. METHODS: In this population-based and cohort study, logistic regression analysis was performed to determine the association of PEDF/adiponectin/leptin levels with the risk of developing GDM and to predict postpartum prediabetes. PEDF protein, PEDF transgenic mice, PEDF knockout mice, and PEDF-neutralized antibodies were used to observe changes in insulin resistance and insulin levels with pregnancy. RESULTS: Plasma PEDF levels were increased in normal pregnancy and higher in GDM women. Higher PEDF levels were associated with the increased risk of developing GDM and emerged as a significant independent determinant of postpartum prediabetes in GDM women. Mechanistically, in vivo and in vitro experiments revealed that PEDF induced insulin resistance by inhibiting the insulin signaling pathway. CONCLUSION: In addition to insulin resistance and upregulated insulin levels in normal pregnancy and GDM, aberrant PEDF levels can serve as a "fingerprint" of metabolic abnormalities during pregnancy. Thus, PEDF is a valuable biomarker but could interfere with the time course for early diagnosis and prognosis of GDM.

Quantitative Structure-Electrochemistry Relationship (QSER) Studies on Metal-Amino-Porphyrins for the Rational Design of CO2 Reduction Catalysts.

The quantitative structure-electrochemistry relationship (QSER) method was applied to a series of transition-metal-coordinated porphyrins to relate their structural properties to their electrochemical CO2 reduction activity. Since the reactions mainly occur within the core of the metalloporphyrin catalysts, the cluster model was used to calculate their structural and electronic properties using density functional theory with the M06L exchange-correlation functional. Three dependent variables were employed in this work: the Gibbs free energies of H*, C*OOH, and O*CHO. QSER, with the genetic algorithm combined with multiple linear regression (GA-MLR), was used to manipulate the mathematical models of all three Gibbs free energies. The obtained statistical values resulted in a good predictive ability (R2 value) greater than 0.945. Based on our QSER models, both the electronic properties (charges of the metal and porphyrin) and the structural properties (bond lengths between the metal center and the nitrogen atoms of the porphyrin) play a significant role in the three Gibbs free energies. This finding was further applied to estimate the CO2 reduction activities of the metal-monoamino-porphyrins, which will prove beneficial in further experimental developments.

Association of HHEX and SLC30A8 Gene Polymorphisms with Gestational Diabetes Mellitus Susceptibility: A Meta-analysis.

Genetics plays a role in the development of gestational diabetes mellitus (GDM), which poses serious risks to pregnant women and their children. Several studies have demonstrated a link between GDM susceptibility and rs13266634 C/T polymorphism in SLC30A8 gene and rs1111875 C/T and rs5015480 C/T, which are located near the linkage disequilibrium block containing the IDE, HHEX, and KIF11 genes. However, the results are conflicting. Therefore, we aimed to investigate the association between susceptibility to GDM and HHEX and SLC30A8 gene polymorphisms. PubMed, Web of Science, EBSCO, CNKI, Wanfang Data, VIP, and SCOPUS were used to search for research articles. The quality of the selected literature was evaluated using the Newcastle-Ottawa scale. A meta-analysis was performed using Stata 15.1. Allelic, dominant, recessive, homozygote, and heterozygote models were used for the analysis. Nine articles with 15 studies were included. (1) Four studies about HHEX rs1111875 showed that the C allele was associated with the susceptibility to GDM; (2) three studies on HHEX rs5015480 indicated that the C allele in rs5015480 was significantly associated with GDM; (3) eight studies about SLC30A8 rs13266634 showed that the C allele was significantly associated with the susceptibility to GDM; and (4) a subgroup analysis showed that the rs5015480 polymorphism in HHEX and rs13266634 polymorphism in SLC30A8 gene were associated with GDM susceptibility in Asians. The meta-analysis provided evidence that the C allele in rs1111875 and rs5015480 in HHEX and rs13266634 in SLC30A8 can increase the risk of GDM.PROSPERO registration number CRD42022342280.

A systematic review and meta-analysis of the effectiveness and safety of COVID-19 vaccination in older adults.

In the coronavirus disease 2019 (COVID-19) pandemic, vaccinations were essential in preventing COVID-19 infections and related mortality in older adults. The objectives of this study were to evaluate the effectiveness and safety of the COVID-19 vaccines in older adults. We systematically searched the electronic bibliographic databases of PubMed, Web of Science, Embase, Cochrane Library, ClinicalTrials.gov, Research Square, and OpenGrey, as well as other sources of gray literature, for studies published between January 1, 2020, and October 1, 2022. We retrieved 22 randomized controlled trials (RCTs), with a total of 3,404,696 older adults (aged over 60 years) participating, that were included in the meta-analysis. No significant publication bias was found. In the cumulative meta-analysis, we found that the COVID-19 vaccines were effective in preventing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (OR = 0.38, 95% CI = 0.23-0.65, p = 0.0004) and in reducing the number of COVID-19-related deaths (OR = 0.16, 95% CI = 0.10-0.25, p < 0.00001) in elderly people. Antibody seroconversion (AS) and geometric mean titer (GMT) levels significantly increased in vaccinated older adults [OR = 24.42, 95% CI = 19.29-30.92; standardized mean difference (SMD) = 0.92, 95% CI = 0.64-1.20, respectively]. However, local and systemic adverse events after COVID-19 vaccine administration were found in older adults (OR = 2.57, 95% CI = 1.83-3.62, p < 0.00001). Although vaccination might induce certain adverse reactions in the elderly population, the available evidence showed that the COVID-19 vaccines are effective and tolerated, as shown by the decrease in COVID-19-related deaths in older adults. It needs to be made abundantly clear to elderly people that the advantages of vaccination far outweigh any potential risks. Therefore, COVID-19 vaccination should be considered as the recommended strategy for the control of this disease by preventing SARS-CoV-2 infection and related deaths in older adults. More RCTs are needed to increase the certainty of the evidence and to verify our conclusions. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022319698, identifier CRD42022319698.

Rational Design of a Low-Data Regime of Pyrrole Antioxidants for Radical Scavenging Activities Using Quantum Chemical Descriptors and QSAR with the GA-MLR and ANN Concepts.

A series of pyrrole derivatives and their antioxidant scavenging activities toward the superoxide anion (O2•-), hydroxyl radical (•OH), and 1,1-diphenyl-2-picryl-hydrazyl (DPPH•) served as the training data sets of a quantitative structure-activity relationship (QSAR) study. The steric and electronic descriptors obtained from quantum chemical calculations were related to the three O2•-, •OH, and DPPH• scavenging activities using the genetic algorithm combined with multiple linear regression (GA-MLR) and artificial neural networks (ANNs). The GA-MLR models resulted in good statistical values; the coefficient of determination (R2) of the training set was greater than 0.8, and the root mean square error (RMSE) of the test set was in the range of 0.3 to 0.6. The main molecular descriptors that play an important role in the three types of antioxidant activities are the bond length, HOMO energy, polarizability, and AlogP. In the QSAR-ANN models, a good R2 value above 0.9 was obtained, and the RMSE of the test set falls in a similar range to that of the GA-MLR models. Therefore, both the QSAR GA-MLR and QSAR-ANN models were used to predict the newly designed pyrrole derivatives, which were developed based on their starting reagents in the synthetic process.

Large-number detrital zircon U-Pb ages reveal global cooling caused the formation of the Chinese Loess Plateau during Late Miocene.

The formation and evolution of the landscape of the Chinese Loess Plateau (CLP) is debated because of uncertainties regarding dust provenance. We present a quantitative estimation of dust source contributions to the CLP, based on more than 37,100 detrital zircon U-Pb ages, combined with mineral assemblages and isotope analyses. Our results reveal that the CLP was stepwise formed by ~8 million years (Ma) and is mainly composed of material from the Northeastern Qinghai-Tibetan Plateau, with stepwise shifts in relative contributions of different eolian silt sources occurring at ~2.6 Ma and 1.5 to 1.2 Ma. We infer that these changes were driven by stepwise global cooling, which induced aridification and enhanced silt production in glaciated-cold climate dust source regions, as well as dust ablation in the expanded arid regions. We propose that global cooling, rather than regional tectonic deformation, was the main driver of the formation and evolution of the CLP during late Cenozoic.

Dynamic Strengthening of Carbon Nanotube Fibers under Extreme Mechanical Impulses.

A monofilament fiber spun from individual carbon nanotubes is an arbitrarily long ensemble of weakly interacting, aligned, discrete nanoparticles. Despite the structural resemblance of carbon nanotube monofilament fibers to crystalline polymeric fibers, very little is known about their dynamic collective mechanics, which arise from van der Waals interactions among the individual carbon nanotubes. Using ultrafast stroboscopic microscopy, we study the collective dynamics of carbon nanotube fibers and compare them directly with nylon, Kevlar, and aluminum monofilament fibers under the same supersonic impact conditions. The in situ dynamics and kinetic parameters of the fibers show that the kinetic energy absorption characteristics of the carbon nanotube fibers surpass all other fibers. This study provides insight into the strain-rate-dependent strengthening mechanics of an ensemble of nanomaterials for the development of high-performance fibers used in body armor and other protective nanomaterials possessing exceptional stability in various harsh environments.

Polymer Particles with a Low Glass Transition Temperature Containing Thermoset Resin Enable Powder Coatings at Room Temperature.

Epoxy-based powder coatings are an attractive alternative to solvent-borne coatings. Here, in-house synthesized low glass transition temperature (Tg) particles containing epoxy resin and polymethyl methacrylate formed coatings at room temperature upon impact with a surface. Suspension polymerization was used to prepare particles as a function of diglycidyl ether of bisphenol A (DGEBA) and methyl methacrylate ratios. Higher incorporation of DGEBA decreased the Tg to below ~20°C and eliminated the need to heat the particles and/or aluminum substrates to form coatings. Using an electrostatic powder coating apparatus, a ~70% particle deposition efficiency was achieved on aluminum substrates heated to 200°C. Whereas, at room temperature, high-speed single particle impact experiments proved that particle bonding occurred at a critical velocity of 438 m/s, comparable to commercial cold spray technologies. The in-house synthesized particles used in this study hold potential in traditional and emerging additive manufacturing applications.

Entanglement Density-Dependent Energy Absorption of Polycarbonate Films via Supersonic Fracture.

The fracture behavior of glassy polymers is strongly coupled to molecular parameters such as entanglement density as well as extrinsic parameters such as strain rate and test temperature. Here we use laser-induced projectile impact testing (LIPIT) to study the extreme strain rate (≈107 s-1) puncture behavior of free-standing polycarbonate (PC) thin films. We demonstrate that changes to the PC molecular mass and the degree of plasticization can lead to substantial changes in the specific puncture energy. We relate these changes to the alteration of the entanglement density of the polymer that determines the underlying failure mechanism as well as the size of the deformation zone.

Extreme Mechanical Behavior of Nacre-Mimetic Graphene-Oxide and Silk Nanocomposites.

Biological materials have the ability to withstand extreme mechanical forces due to their unique multilevel hierarchical structure. Here, we fabricated a nacre-mimetic nanocomposite comprised of silk fibroin and graphene oxide that exhibits hybridized dynamic responses arising from alternating high-contrast mechanical properties of the components at the nanoscale. Dynamic mechanical behavior of these nanocomposites is assessed through a microscale ballistic characterization using a 7.6 µm diameter silica sphere moving at a speed of approximately 400 m/s. The volume fraction of graphene oxide in these composites is systematically varied from 0 to 32 vol % to quantify the dynamic effects correlating with the structural morphologies of the graphene oxide flakes. Specific penetration energy of the films rapidly increases as the distribution of graphene oxide flakes evolves from noninteracting, isolated sheets to a partially overlapping continuous sheet. The specific penetration energy of the nanocomposite at the highest graphene oxide content tested here is found to be significantly higher than that of Kevlar fabrics and close to that of pure multilayer graphene. This study evidently demonstrates that the morphologies of nanoscale constituents and their interactions are critical to realize scalable high-performance nanocomposites using typical nanomaterial constituents having finite dimensions.

Dynamics and extreme plasticity of metallic microparticles in supersonic collisions.

Metallic microparticles can acquire remarkable nanoscale morphologies after experiencing high velocity collisions, but materials science regarding the extreme events has been limited due to a lack of controlled experiments. In this work, collision dynamics and nonlinear material characteristics of aluminum microparticles are investigated through precise single particle collisions with two distinctive substrates, sapphire and aluminum, across a broad range of collision velocities, from 50 to 1,100 m/s. An empirical constitutive model is calibrated based on the experimental results, and is used to investigate the mechanics of particle deformation history. Real-time and post-impact characterizations, as well as model based simulations, show that significant material flow occurs during the impact, especially with the sapphire substrate. A material instability stemming from plasticity-induced heating is identified. The presented methodology, based on the use of controlled single particle impact data and constitutive models, provides an innovative approach for the prediction of extreme material behavior.

Large-Volume Self-Organization of Polymer/Nanoparticle Hybrids with Millimeter-Scale Grain Sizes Using Brush Block Copolymers.

We report that an exceptionally large volume of highly ordered arrays (single grains) on the order of millimeters in scale can be rapidly created through a unique innate guiding mechanism of brush block copolymers (BBCPs). The grain volume is over 10(9) times larger than that of typical self-assembled linear BCPs (LBCPs). The use of strong interactions between nanoparticles (NPs) and BBCPs enables high loadings of functional materials, up to 76 wt % (46 vol %) in the target domain, while maintaining excellent long-range order. Overall, this work provides a simple method to precisely control the spatial orientation of functionalities at nanometer length scales over macroscopic volumes, thereby enabling the production of hybrid materials for many important applications.

General public perceptions and attitudes toward Alzheimer's disease from five cities in China.

Alzheimer's disease (AD) is the most common type of dementia affecting the aged population worldwide, yet its social perceptions have been less studied. To investigate the perceptions and attitudes toward AD in the Chinese population, a cross-sectional face-to-face survey of 2,000 randomly selected adults was conducted in five representative cities of China. This survey focused on the fear of AD, and the relationship between this variable and each studied factor was analyzed using univariate analysis and multivariate regression analysis. In general, 76.6% of the total respondents had personal fear of developing AD, and such fear was closely related to the proximity to AD and perceived severity of AD, as well as other factors such as gender and self-perceived health. The results strongly suggested that more attention should be paid to public health education of AD, which can only be achieved with the cooperation of government, media, medical institutions, and the community so as to eliminate people's confusion about AD, relieve their psychological burden, and optimize their health-seeking behavior.