This review provides a detailed look at the attributes and immunologic mechanisms of plasmid DNA vaccines and their utility as laboratory tools as well as potential human vaccines. The immunogenicity ...and efficacy of DNA vaccines in a variety of preclinical models is used to illustrate how they differ from traditional vaccines in novel ways due to the in situ antigen production and the ease with which they are constructed. The ability to make new DNA vaccines without needing to handle a virulent pathogen or to adapt the pathogen for manufacturing purposes demonstrates the potential value of this vaccine technology for use against emerging and epidemic pathogens. Similarly, personalized anti‐tumor DNA vaccines can also readily be made from a biopsy. Because DNA vaccines bias the T‐helper (Th) cell response to a Th1 phenotype, DNA vaccines are also under development for vaccines against allergy and autoimmune diseases. The licensure of four animal health products, including two prophylactic vaccines against infectious diseases, one immunotherapy for cancer, and one gene therapy delivery of a hormone for a food animal, provides evidence of the efficacy of DNA vaccines in multiple species including horses and pigs. The size of these target animals provides evidence that the somewhat disappointing immunogenicity of DNA vaccines in a number of human clinical trials is not due simply to the larger mass of humans compared with most laboratory animals. The insights gained from the mechanisms of protection in the animal vaccines, the advances in the delivery and expression technologies for increasing the potency of DNA vaccines, and encouragingly potent human immune responses in certain clinical trials, provide insights for future efforts to develop DNA vaccines into a broadly useful vaccine and immunotherapy platform with applications for human and animal health.
Transcranial electrical stimulation has widespread clinical and research applications, yet its effect on ongoing neural activity in humans is not well established. Previous reports argue that ...transcranial alternating current stimulation (tACS) can entrain and enhance neural rhythms related to memory, but the evidence from non-invasive recordings has remained inconclusive. Here, we measure endogenous spindle and theta activity intracranially in humans during low-frequency tACS and find no stable entrainment of spindle power during non-REM sleep, nor of theta power during resting wakefulness. As positive controls, we find robust entrainment of spindle activity to endogenous slow-wave activity in 66% of electrodes as well as entrainment to rhythmic noise-burst acoustic stimulation in 14% of electrodes. We conclude that low-frequency tACS at common stimulation intensities neither acutely modulates spindle activity during sleep nor theta activity during waking rest, likely because of the attenuated electrical fields reaching the cortical surface.
Experimental studies have shown that disinfection byproducts (DBPs) induce coagulotoxicity, but human evidence is scarce.
This study aimed to explore the relationships of DBP exposures with blood ...coagulation parameters.
Among 858 women from the Tongji Reproductive and Environmental (TREE) study, urinary dichloroacetic acid (DCAA) and trichloroacetic acid (TCAA) were detected as internal biomarkers of DBP exposures. We measured activated partial thromboplastin time (APTT), fibrinogen (Fbg), international normalized ratio (INR), prothrombin time (PT), and thrombin time (TT) as blood coagulation parameters. Multivariable linear regression models were utilized to estimate the relationships between urinary DCAA and TCAA and blood coagulation parameters. The effect modifications by demographic and lifestyle characteristics were further explored.
Elevated tertiles of urinary DCAA concentrations were associated with increased PT and INR (11.29%, 95% CI: 1.66%, 20.92% and 0.99%, 95% CI: 0.08%, 1.90% for the third vs. first tertile, respectively; both P for trends < 0.05). Stratification analysis showed that the positive associations were only observed among younger (< 30 years), leaner (body mass index < 24.0 kg/m
), and non-passive smoking women. Moreover, elevated tertiles of urinary TCAA concentrations in positive associations with PT and INR were observed among younger women (17.89%, 95% CI: 2.50%, 33.29% and 1.82%, 95% CI: 0.34%, 3.30% for the third vs. first tertile, respectively; both P for trends < 0.05) but not among older women (both P for interactions < 0.05).
Higher levels of urinary DCAA and TCAA are associated with prolonged clotting time among women.
The clinical value of serial minimal residual disease (MRD) monitoring in core binding factor (CBF) acute myeloid leukemia (AML) by quantitative RT-PCR was prospectively assessed in 278 patients 163 ...with t(8;21) and 115 with inv(16) entered in the United Kingdom MRC AML 15 trial. CBF transcripts were normalized to 105ABL copies. At remission, after course 1 induction chemotherapy, a > 3 log reduction in RUNX1-RUNX1T1 transcripts in BM in t(8;21) patients and a > 10 CBFB-MYH11 copy number in peripheral blood (PB) in inv(16) patients were the most useful prognostic variables for relapse risk on multivariate analysis. MRD levels after consolidation (course 3) were also informative. During follow-up, cut-off MRD thresholds in BM and PB associated with a 100% relapse rate were identified: for t(8;21) patients BM > 500 copies, PB > 100 copies; for inv(16) patients, BM > 50 copies and PB > 10 copies. Rising MRD levels on serial monitoring accurately predicted hematologic relapse. During follow-up, PB sampling was equally informative as BM for MRD detection. We conclude that MRD monitoring by quantitative RT-PCR at specific time points in CBF AML allows identification of patients at high risk of relapse and could now be incorporated in clinical trials to evaluate the role of risk directed/preemptive therapy.
This study presents a broad perspective of hybrid process modeling combining the scientific knowledge and data analytics in bioprocessing and chemical engineering with a science‐guided machine ...learning (SGML) approach. We divide the approach into two major categories: ML complements science, and science complements ML. We review the literature relating to the hybrid SGML approach, and propose a systematic classification of hybrid SGML models. For applying ML to improve science‐based models, we present expositions of direct serial and parallel hybrid modeling and their combinations, inverse modeling, reduced‐order modeling, quantifying uncertainty in the process and even discovering governing equations of the process model. For applying scientific principles to improve ML models, we discuss the science‐guided design, learning and refinement. For each subcategory, we identify its requirements, strengths, and limitations, together with their published and potential applications. We also present several examples to illustrate different hybrid SGML methodologies for modeling chemical processes.
We use machine-learning methods on local structure to identify flow defects-or particles susceptible to rearrangement-in jammed and glassy systems. We apply this method successfully to two very ...different systems: a two-dimensional experimental realization of a granular pillar under compression and a Lennard-Jones glass in both two and three dimensions above and below its glass transition temperature. We also identify characteristics of flow defects that differentiate them from the rest of the sample. Our results show it is possible to discern subtle structural features responsible for heterogeneous dynamics observed across a broad range of disordered materials.
Precision spectroscopy of the hydrogen molecule is a test ground of quantum electrodynamics (QED), and it may serve for the determination of fundamental constants. Using a comb-locked cavity ...ring-down spectrometer, for the first time, we observed the Lamb-dip spectrum of the R(1) line in the overtone of hydrogen deuteride (HD). The line position was determined to be 217 105 182.79±0.03_{stat}±0.08_{syst} MHz (δν/ν=4×10^{-10}), which is the most accurate rovibrational transition ever measured in the ground electronic state of molecular hydrogen. Moreover, from calculations including QED effects up to the order m_{e}α^{6}, we obtained predictions for this R(1) line as well as for the HD dissociation energy, which are less accurate but signaling the importance of the complete treatment of nonadiabatic effects. Provided that the theoretical calculation reaches the same accuracy, the present measurement will lead to a determination of the proton-to-electron mass ratio with a precision of 1.3 parts per billion.
Background
Dysregulated bile acid (BA) metabolism has been linked to steatosis, inflammation, and fibrosis in nonalcoholic fatty liver disease (NAFLD).
Aim
To determine whether circulating BA levels ...accurately stage liver fibrosis in NAFLD.
Methods
We recruited 550 Chinese adults with biopsy‐proven NAFLD and varying levels of fibrosis. Ultra‐performance liquid chromatography coupled with tandem mass spectrometry was performed to quantify 38 serum BAs.
Results
Compared to those without fibrosis, patients with mild fibrosis (stage F1) had significantly higher levels of secondary BAs, and increased diastolic blood pressure (DBP), alanine aminotransferase (ALT), body mass index, and waist circumstance (WC). The combination of serum BAs with WC, DBP, ALT, or Homeostatic Model Assessment for Insulin Resistance performed well in identifying mild fibrosis, in men and women, and in those with/without obesity, with AUROCs 0.80, 0.88, 0.75 and 0.78 in the training set (n = 385), and 0.69, 0.80, 0.61 and 0.69 in the testing set (n = 165), respectively. In comparison, the combination of BAs and clinical/biochemical biomarkers performed less well in identifying significant fibrosis (F2‐4). In women and in non‐obese subjects, AUROCs were 0.75 and 0.71 in the training set, 0.65 and 0.66 in the validation set, respectively. However, these AUROCs were higher than those observed for the fibrosis‐4 index, NAFLD fibrosis score, and Hepamet fibrosis score.
Conclusions
Secondary BA levels were significantly increased in NAFLD, especially in those with mild fibrosis. The combination of serum BAs and clinical/biochemical biomarkers for identifying mild fibrosis merits further assessment.
Secondary bile acids were significantly increased in NAFLD, especially in those with mild fibrosis. The combination of serum bile acids and clinical/biochemical biomarkers for identifying mild fibrosis is worthy of further assessment.
Single chip integrated spectrometers are critical to bring chemical and biological sensing, spectroscopy, and spectral imaging into robust, compact and cost-effective devices. Existing on-chip ...spectrometer approaches fail to realize both high resolution and broad band. Here we demonstrate a microring resonator-assisted Fourier-transform (RAFT) spectrometer, which is realized using a tunable Mach-Zehnder interferometer (MZI) cascaded with a tunable microring resonator (MRR) to enhance the resolution, integrated with a photodetector onto a single chip. The MRR boosts the resolution to 0.47 nm, far beyond the Rayleigh criterion of the tunable MZI-based Fourier-transform spectrometer. A single channel achieves large bandwidth of ~ 90 nm with low power consumption (35 mW for MRR and 1.8 W for MZI) at the expense of degraded signal-to-noise ratio due to time-multiplexing. Integrating a RAFT element array is envisaged to dramatically extend the bandwidth for spectral analytical applications such as chemical and biological sensing, spectroscopy, image spectrometry, etc.
Abstract
This paper proposes an advanced encryption standard (AES) cryptosystem based on memristive neural network. A memristive chaotic neural network is constructed by using the nonlinear ...characteristics of a memristor. A chaotic sequence, which is sensitive to initial values and has good random characteristics, is used as the initial key of AES grouping to realize "one-time-one-secret" dynamic encryption. In addition, the Rivest-Shamir-Adleman (RSA) algorithm is applied to encrypt the initial values of the parameters of the memristive neural network. The results show that the proposed algorithm has higher security, a larger key space and stronger robustness than conventional AES. The proposed algorithm can effectively resist initial key-fixed and exhaustive attacks. Furthermore, the impact of device variability on the memristive neural network is analyzed, and a circuit architecture is proposed.