Factors related to post-stroke fatigue from multivariate logistic regression models.

<p>Post-stroke fatigue defined as Fatigue Severity Scale score ≥4 at 13–14 days after stroke; OR = Odds ratio; CI = confidence interval; MRS, Modified Rankin scale.</p><p>Factors related to post-stroke fatigue from multivariate logistic regression models.</p

Characteristics of ischemic stroke participants with and without post-stroke fatigue.

<p>Data presented are n (%) or mean (SD); Fatigue defined as Fatigue Severity Scale score ≥4; BMI, Body mass index; Family function: Family APGAR index.</p><p>Characteristics of ischemic stroke participants with and without post-stroke fatigue.</p

Clinical factors related to post-stroke fatigue in ischemic stroke participants.

<p>Data presented are n(%); Fatigue defined as Fatigue Severity Scale score ≥4; Depression, the Beck Depression Inventory Version II (BDI-II); MRS, Modified Rankin Scale; NIHSS, National Institute of Health Stroke Scale.</p><p>Clinical factors related to post-stroke fatigue in ischemic stroke participants.</p

Flow chart in the selection of study patients.

<p>Flow chart in the selection of study patients.</p

Strain-Induced Isostructural and Magnetic Phase Transitions in Monolayer MoN₂

The change of bonding status, typically occurring only in chemical processes, could dramatically alter the material properties. Here, we show that a tunable breaking and forming of a diatomic bond can be achieved through physical means, i.e., by a moderate biaxial strain, in the newly discovered MoN₂ two-dimensional (2D) material. On the basis of first-principles calculations, we predict that as the lattice parameter is increased under strain, there exists an isostructural phase transition at which the N–N distance has a sudden drop, corresponding to the transition from a N–N nonbonding state to a N–N single bond state. Remarkably, the bonding change also induces a magnetic phase transition, during which the magnetic moments transfer from the N­(2<i>p</i>) sublattice to the Mo­(4<i>d</i>) sublattice; meanwhile, the type of magnetic coupling is changed from ferromagnetic to antiferromagnetic. We provide a physical picture for understanding these striking effects. The discovery is not only of great scientific interest in exploring unusual phase transitions in low-dimensional systems, but it also reveals the great potential of the 2D MoN₂ material in the nanoscale mechanical, electronic, and spintronic applications

Asymmetric Nanochannel–Ionchannel Hybrid for Ultrasensitive and Label-Free Detection of Copper Ions in Blood

Nanochannel/nanopre based analysis methods have attracted increasing interest in recent years due to their exquisite ability to reveal changes in molecular volume. In this work, a highly asymmetric nanochannel–ionchannel hybrid coupled with an electrochemical technique was developed for copper ion (Cu²⁺) detection. Polyglutamic acid (PGA) was modified in a nanochannel array of porous anodic alumina (PAA). When different concentrations of Cu²⁺ were introduced into the nanochannel–ionchannel hybrid in a neutral environment, a Cu²⁺–PGA chelation reaction occurs, resulting in varied current–potential (<i>I–V</i>) properties of the nanochannel–ionchannel hybrid. When PAA was immersed in a low pH solution, the Cu²⁺–PGA complex dissociated. On the basis of the change in ionic current, a label-free assay for Cu²⁺ was achieved along with the ability to regenerate and reuse the constructed platform. Because of the unique mass transfer property of the nanochannel–ionchannel hybrid combined with the highly amplified ionic current magnitude of the nanochannel array, significantly increased assay sensitivity was achieved, as expected. To evaluate the applicability of the present methodology for detecting Cu²⁺ in a real sample, the Cu²⁺ content in real blood samples was analyzed. The results demonstrate that the present method shows excellent selectivity with high sensitivity toward Cu²⁺ detection in real blood samples

Additional file 1 of Automated classification of protein expression levels in immunohistochemistry images to improve the detection of cancer biomarkers

Additional file 1. Table S-1. Comparison of different architectures of deep neural networks. Table S-2. Results of deep learning features

Gold-Catalyzed Oxidative Cyclization of Chiral Homopropargyl Amides: Synthesis of Enantioenriched γ‑Lactams

A gold-catalyzed tandem cycloisomerization/oxidation of homopropargyl amides has been developed, which provides ready access to synthetically useful chiral γ-lactams with excellent ee by combining the chiral <i>tert</i>-butylsulfinimine chemistry and gold catalysis. The utility of this methodology has also been demonstrated in the synthesis of biologically active compound <i>S</i>-MPP and natural product (−)-bgugaine. The use of readily available starting materials, a simple procedure, and mild reaction conditions are other significant features of this method

Biomimetic Polymersomes as Carriers for Hydrophilic Quantum Dots

For polymersomes to achieve their potential as effective delivery vehicles, they must efficiently encapsulate therapeutic agents into either the aqueous interior or the hydrophobic membrane. In this study, cell membrane-mimetic polymersomes were prepared from amphiphilic poly(d,l-lactide)-<i>b</i>-poly(2-methacryloyloxyethylphosphorylcholine) (PLA-<i>b</i>-PMPC) diblock copolymers and were used as encapsulation devices for water-soluble molecules. Thioalkylated zwitterionic phosphorylcholine protected quantum dots (PC@QDs) were chosen as hydrophilic model substrates and successfully encapsulated into the aqueous polymersome interior, as evidenced by transmission electron microscopy (TEM) and flow cytometry. In addition, we also found a fraction of the PC@QDs were bound to both the external and internal surfaces of the polymersome. This interesting immobilization might be due to the ion-pair interactions between the phosphorylcholine groups on the PC@QDs and polymersomes. The experimental encapsulation results support a mechanism of PLA-<i>b</i>-PMPC polymersome formation in which PLA-<i>b</i>-PMPC copolymer chains first form spherical micelles, then worm-like micelles, and finally disk-like micelles which close up to form polymersomes

Additional file 1 of Ensemble learning for predicting ex vivo human placental barrier permeability

Additional file 1: Table S1. The features, experimental CI, predicted CI values, and AD of the training dataset. Table S2. The mean and variance values of the 7 selected informative features for the ensemble model. Table S3. The features, experimental CI, predicted CI values, and AD of the test dataset. Table S4. The rules for defining the applicability domain of the ensemble model based on the training dataset. Table S5. Details of the final prediction model based on all 87 chemicals. Table S6. The rules for defining the applicability domain of the final prediction model. Table S7. The features, experimental CI, predicted CI values, and AD of the external test dataset. Figure S1. The comparison of experimental and predicted CI values of 87 training dataset for leave-one-out cross-validation. Abbreviations: AD, applicability domain; Y, chemicals within the AD (blue dot); N, chemicals out of the AD (red dot)