Enhanced fabrication of size-controllable chitosan-genipin nanoparticles using orifice-induced hydrodynamic cavitation: Process optimization and performance evaluation.

Chitosan nanoparticles (NPs) possess great potential in biomedical fields. Orifice-induced hydrodynamic cavitation (HC) has been used for the enhancement of fabrication of size-controllable genipin-crosslinked chitosan (chitosan-genipin) NPs based on the emulsion cross-linking (ECLK). Experiments have been performed using various plate geometries, chitosan molecular weight and under different operational parameters such as inlet pressure (1-3.5 bar), outlet pressure (0-1.5 bar) and cross-linking temperature (40-70 °C). Orifice plate geometry was a crucial factor affecting the properties of NPs, and the optimized geometry of orifice plate was with single hole of 3.0 mm diameter. The size of NPs with polydispersity index of 0.359 was 312.6 nm at an optimized inlet pressure of 3.0 bar, and the maximum production yield reached 84.82 %. Chitosan with too high or too low initial molecular weight (e.g., chitosan oligosaccharide) was not applicable for producing ultra-fine and narrow-distributed NPs. There existed a non-linear monotonically-increasing relationship between cavitation number (Cv) and chitosan NP size. Scanning electron microscopy (SEM) test indicated that the prepared NPs were discrete with spherical shape. The study demonstrated the superiority of HC in reducing particle size and size distribution of NPs, and the energy efficiency of orifice type HC-processed ECLK was two orders of magnitude than that of ultrasonic horn or high shear homogenization-processed ECLK. In vitro drug-release studies showed that the fabricated NPs had great potential as a drug delivery system. The observations of this study can offer strong support for HC to enhance the fabrication of size-controllable chitosan-genipin NPs.

A method of classification decision based on multi-BiLSTMs for physical loads hierarchy.

Human gait is systematically deformed by physical loads, this study constructs and evaluates an algorithm for classifying different levels of physical loads. The algorithm uses wearable IMUs data to classify different levels of loads. We aim to evaluate classification as strategy for multi-loads recognition for the control of wearable exoskeletons. 10 adults participated in the experiment. In the experiment, the subjects walked on flat ground carrying a backpack with different weight of loads (0, 15 and 25 kg), and three sensors on the lower limbs collected the subjects' gait data in real time. In this study, a method of classification decision based on multiple bidirectional long short-term memory(multi-BiLSTMs) was proposed which was used to classify the load level of the collected data. The classification accuracy of this method reached 94.1%, and the F-score was 0.935-0.952. Compared with LSTM and BiLSTM, the proposed method has better performance in accuracy of load classification. The results of this study contribute to quantify the load, which has promising applications in the medical and labor protection fields.

Ferrofluids transport in bioinspired nanochannels: Application to electrochemical biosensing with magnetic-controlled detection.

Controllable transport of ions, molecules or fluids in bioinspired nanochannels is crucial to study biointeraction occurred in confined space and also develop biosensing platforms or devices. Herein, ferrofluids transport in biofunctionalized nanochannels was investigated and a novel electrochemical biosensing platform with the characteristic of label-free, high sensitivity and rapid response was constructed. The hydrophilic ferrofluids can flux swiftly through the antibody-immobilized nanochannels with the assistance of a permanent magnet. It was initially found that the presence of ferrofluids would depress the redox current of the electrochemical probe [Fe(CN)6]3-. The mechanism of the depressing effect was ascribed to the constrained diffusion of [Fe(CN)6]3- which lowered the concentration of it at the electrode surface and the weak adsorption of the ferrofluids which increased the charge transfer resistance of the interface. Therefore, redox current of the probe was applied to indicate the amount of the ferrofluids fluxing through the bioinspired nanochannels. The steric hindrance of the bioinspired nanochannels changed with the amount of the corresponding target being incubated, resulting in quantitative variation of the redox current. In this way, electrochemical biosensing platform based on ferrofluids transport was constructed. Using carbohydrate antigen 153 (CA153) as a model target, a low detection limit of 0.0013 U·mL-1 was acquired. This magnetic-controlled bioelectrochemical platform was expected to be expanded to other applications such as genetic testing, drug analysis, and molecular identification.

A novel self-cleaning electrochemical biosensor integrating copper porphyrin-derived metal-organic framework nanofilms, G-quadruplex, and DNA nanomotors for achieving cyclic detection of lead ions.

A self-cleaning electrochemical biosensor based on two-dimensional Cu-porphyrin (Cu-TCPP) metal-organic framework nanofilms, novel super G-quadruplex (G4), and DNA nanomotors was developed for the cyclic detection of Pb2+ ions. The Cu-TCPP framework with inherent peroxidase activity can create an ultra-thin nanofilm that functioned as a carrier to support the metastable G4 comprising four individual DNA strands. The introduction of Pb2+ and the intercalation of hemin can help it to form stable G4-hemin DNAzymes, which exhibits strong catalytic H2O2 reduction activity, and its number will be directly related to the amount of the introduced Pb2+. Moreover, a DNA nanomotor system is introduced to achieve cyclic detection, and the addition of the fuel DNA strands enables G4 to perform a "complete-dissociation-complete" process for achieving self-cleaning of the electrode interface and the cycle detection of Pb2+. The synergistic effects of Cu-TCPP and G4-hemin DNAzymes, which exhibits efficient and catalytic H2O2 reduction, enhance the performance of the electrochemical sensing system. The linear range of this sensor to Pb2+ is 5 nM-5 µM, and the detection limit is 1.7 nM. Compared with the best system in reported studies, its linear range is five times wider and its detection limit is lower than the previously lowest one. Taking advantage of the Pb2+ stabilized G4, the proposed sensor can selectively detect Pb2+ in the presence of other metal ions. The results presented herein comprise a valuable reference for constructing DNA nanoelectronic devices and establish sensitive and cyclic detection of the target and preparing of self-cleaning electrode interfaces.

Electrochemical dopamine sensor based on bi-metallic Co/Zn porphyrin metal-organic framework.

Integrating other metal ions into mono-metallic metal-organic framework (MOF) to form bi-metallic MOF is an effective strategy to enhance the performance of MOFs from the internal structure. In this study, two-dimensional (2D) cobalt/zinc-porphyrin (Co/Zn-TCPP) MOF nanomaterials with different Co/Zn molar ratios were synthesised using a simple surfactant-assisted method, and novel dopamine (DA) sensing methods were constructed based on these materials. The characterisation results showed that all MOF with different Co/Zn molar ratios presented a nanofilm, and the Co and Zn elements were uniformly distributed. All sensors based on CoxZn100-x-TCPP had a certain catalytic performance to DA. Among them, the sensor based on CO25Zn75-TCPP showed the strongest signal response, indicating that the catalytic performance of MOF on DA can be adjusted by changing the Co/Zn molar ratio. The doping of metal ions improves the chemical environment of the pores, and increases the types and spatial arrangement of the active sites of the MOF, which is beneficial to the electron transfer and exchange with DA; Co2+ and Zn2+ active centres have a synergistic promotion effect, so the catalytic activity of MOF is significantly improved. The linear range at the potential of 0.1 V based on Co25Zn75-TCPP for DA was 5 nM-177.8 µM, with a detection limit of 1.67 nM (S/N = 3). The sensor exhibited a good selectivity for detecting DA. This research is expected to provide new ideas and references for constructing high-performance sensing interfaces and platforms.

Direct targeting of wild-type glucocerebrosidase by antipsychotic quetiapine improves pathogenic phenotypes in Parkinson's disease models.

Current treatments for Parkinson's disease (PD) provide only symptomatic relief, with no disease-modifying therapies identified to date. Repurposing FDA-approved drugs to treat PD could significantly shorten the time needed for and reduce the costs of drug development compared with conventional approaches. We developed an efficient strategy to screen for modulators of ß-glucocerebrosidase (GCase), a lysosomal enzyme that exhibits decreased activity in patients with PD, leading to accumulation of the substrate glucosylceramide and oxidized dopamine and α-synuclein, which contribute to PD pathogenesis. Using a GCase fluorescent probe and affinity-based fluorescence polarization assay, we screened 1280 structurally diverse, bioactive, and cell-permeable FDA-approved drugs and found that the antipsychotic quetiapine bound GCase with high affinity. Moreover, quetiapine treatment of induced pluripotent stem cell-derived (iPSC-derived) dopaminergic neurons from patients carrying mutations in GBA1 or LRRK2 led to increased wild-type GCase protein levels and activity and partially lowered accumulation of oxidized dopamine, glucosylceramide, and α-synuclein. Similarly, quetiapine led to activation of wild-type GCase and reduction of α-synuclein in a GBA mutant mouse model (Gba1D409V/+ mice). Together, these results suggest that repurposing quetiapine as a modulator of GCase may be beneficial for patients with PD exhibiting decreased GCase activity.

Fluorescence and electrochemical assay for bimodal detection of lead ions based on Metal-Organic framework nanosheets.

The accurate measurement of heavy metal ions is essential for human health and environmental protection. Here, we report the design of a simple and convenient bimodal strategy for signal-on, label-free lead ion detection in environmental samples based on two-dimensional metal-organic framework (2D-MOF) nanosheets. 2D-MOFs have different affinities toward guanine-rich DNA (ssGDNA) and the G-quadruplex, allowing these structures to be distinguished. The nanosheets were also used as quenchers for fluorescent lead ion detection. Using lead ions to induce G-quadruplex formation from ssGDNA, a simple fluorescence resonance energy transfer (FRET) strategy was developed for lead ion detection; the detection limit was 3.3 nM. Based on changes in the GDNA configuration, the FRET system was converted into an electrochemical sensor for lead ion assays using an electrode modified with the 2D-MOF nanosheets. Electrochemical impedance spectroscopy showed a high sensitivity and a low limit of detection (i.e., 8.7 pM) of the electrode. The adaptability of the bimodal mechanism was verified through the successful detection of lead ions in tap water and fertilizer samples, and the method accuracy was demonstrated through inductively coupled plasma analysis. The developed bimodal device is cost-effective, highly sensitive, and allows for convenient operation, thereby rendering it a promising and reliable system for the detection of lead ions in environmental samples.

A label-free ratiometric immunoassay using bioinspired nanochannels and a smart modified electrode.

Labeling with redox reporter is often required in developing electrochemical bioassay for most proteins or nucleic acid biomarkers. Herein, a label-free ratiometric immunosensing platform is firstly developed by integrating the antibody-conjugated nanochannels with a smart modified electrode. The electrode modifier is the composite of C60, tetraoctylammonium bromide (TOA+) and Prussian blue (PB). Cyclic voltammograms of the ultimate C60-TOA+/PB modified electrode exhibited two pairs of peaks at 0.15 V and -0.13 V, ascribing to the redox of PB and C60, respectively. With the addition of K3[Fe(CN)6] in the electrolyte solution, the peaks of PB decreased due to the adsorption of [Fe(CN)6]3- while the peaks of C60 increased because of the formation of the ternary complex (TC) C60-TOA+-[Fe(CN)6]3-. As a result, the peak current ratio IPB/ITC decreased gradually with the increment of the concentration of [Fe(CN)6]3-. For the nanochannels-based immunosensing platform, the steric hindrance of the bioconjugated nanochannels varied with the loading amount of the target CA125, and thus [Fe(CN)6]3- passing through the channels was quantitatively affected. And the higher CA125 level was, the less [Fe(CN)6]3- concentration was. And thus, the ratio IPB/ITC monitored at the C60-TOA+/PB modified electrode increased with the increase of the concentration of CA125. The ratiometric immunoassay featured a linear calibration range from 1.0 U mL-1 to 100 U mL-1 with a low detection limit of 0.86 U mL-1. In addition, the ratiometric immunosensing platform demonstrated good specificity and stability as well as acceptable accuracy in overcoming the effect of electrode passivation which was an inherent problem of electroanalysis.

Machine Learning Algorithms Identify Pathogen-Specific Biomarkers of Clinical and Metabolomic Characteristics in Septic Patients with Bacterial Infections.

Sepsis is a high-mortality disease that is infected by bacteria, but pathogens in individual patients are difficult to diagnosis. Metabolomic changes triggered by microbial activity provide us with the possibility of accurately identifying infection. We adopted machine learning methods for training different classifiers with a clinical-metabolomic database from sepsis cases to identify the pathogen of sepsis. Records of clinical indicators and concentration of metabolites were obtained for each patient upon their arrival at the hospital. Machine learning algorithms were used in 100 patients with clear infection and corresponding 29 controls to select specific biosignatures to discriminate microorganism in septic patients. The sensitivity, specificity, and AUC value of clinical and metabolomic characteristics in predicting diagnostic outcomes were determined at admission. Our analyses demonstrate that the biosignatures selected by machine learning algorithms could have diagnostic value on the identification of infected patients and Gram-positive from Gram-negative; related AUC values were 0.94 ± 0.054 and 0.80 ± 0.085, respectively. Pathway and blood disease enrichment analyses of clinical and metabolomic biomarkers among infected patients showed that sepsis disease was accompanied by abnormal nitrogen metabolism, cell respiratory disorder, and renal or intestinal failure. The panel of selected clinical and metabolomic characteristics might be powerful biomarkers to discriminate patients with sepsis.

Facile preparation of novel Pd nanowire networks on a polyaniline hydrogel for sensitive determination of glucose.

In this study, novel Pd nanowire networks (PdNW) grown on three-dimensional polyaniline hydrogel (3D-PANI) were prepared via a facile one-step electrodeposition approach at a constant potential of - 0.2 V and further utilized as an electrochemical sensing material for sensitive determination of glucose in alkaline medium. Compared with the sensor based on Pd nanofilm (PdNF)/3D-PANI prepared by electrodeposition at - 0.9 V, the sensor based on PdNW/3D-PANI presented substantially enhanced electrocatalytic activity towards glucose oxidation, with an excellent sensitivity of 146.6 µA mM-1 cm-2, a linear range from 5.0 to 9800 µM, and a low detection limit of 0.7 µM and was, therefore, demonstrated to be available for the determination of glucose in human serum. These findings are likely attributed to the combination of advantages of both PdNW and 3D-PANI, which outperformed most other Pd-based non-enzymatic glucose sensors reported earlier. Moreover, this non-enzymatic electrochemical sensor based on PdNW/3D-PANI may serve as an alternative tool for the assay of glucose and possibly other biomolecules. Graphical abstract.

Amplified Electrochemical Hydrogen Peroxide Sensing Based on Cu-Porphyrin Metal-Organic Framework Nanofilm and G-Quadruplex-Hemin DNAzyme.

A novel electrochemical hydrogen peroxide (H2O2) sensor based on Cu-porphyrin(Cu-TCPP)/G-quadruplex-hemin nanocomposite was constructed by assembling two-dimensional Cu-TCPP metal-organic framework (MOF) nanofilm and G-quadruplex-hemin DNAzyme. The Cu-TCPP synthesized by the surfactant-assisted method has a wrinkled two-dimensional nanofilm morphology, which gives it a large surface area and accessible active sites. Cu-TCPP exhibits peroxidase activity and good stability and can catalyze the reduction of H2O2. In addition, Cu-TCPP can be used as a nanocarrier for G-quadruplex-hemin DNAzyme with strong peroxidase activity to achieve "biological barcode" amplification and improve stability. The cooperative interaction of Cu-TCPP and G-quadruplex-hemin DNAzyme effectively amplifies the electrochemical response signal. Electrochemical studies have shown that the constructed sensor exhibits good electrochemical sensing performance with three linear ranges: 0.08 µM to 0.11 mM, 0.11-0.91 mM, and 0.91-8.1 mM, with sensitivities of 2315.86, 301.00, and 65.71 µA/(mM cm2), respectively, and the detection limit was 0.03 µM. In addition, the sensor shows good selectivity. In summary, this study provides a simple and effective new strategy for electrochemical sensing based on two-dimensional MOFs and artificial enzymes.

Voltammetric determination of hydrogen peroxide using AuCu nanoparticles attached on polypyrrole-modified 2D metal-organic framework nanosheets.

AuCu/PPy/Cu-TCPP nanocomposites were synthesized by attaching AuCu nanoparticles to a polypyrrole (PPy)-modified 2D Cu-TCPP metal-organic framework nanosheet; Cu-TCPP can exhibit catalytic activity for the reduction of H2O2. Based on the nanocomposite, a new method for the determination of H2O2 was established. The morphology of the AuCu/PPy/Cu-TCPP was analyzed by transmission electron microscopy. Cu-TCPP exhibited a 2D nanosheet with obvious wrinkles, and a large amount of AuCu was uniformly attached to PPy/Cu-TCPP. The composition and structure were studied by X-ray diffraction, FTIR, and X-ray photoelectron spectroscopy. At the optimal working potential and scan rate of - 0.55 V(vs. SCE) and 100 mV/s, respectively, electrochemical studies indicated that in N2-saturated supporting electrolyte, the method showed good catalytic performance for H2O2, with a detection limit of 6.67 nM (S/N = 3), a linear range of 7.10 µM-24.10 mM, and a sensitivity of 35.0 µA mM-1 cm2. Compared to H2O2 methods based on related materials, this method exhibits a wide linear range, and the detection limit is down to nanomolar. Graphical abstract Schematic presentation of the preparation of AuCu/PPy/Cu-TCPP nanocomposites. AuCu/PPy/Cu-TCPP nanocomposite was prepared by loading gold-copper (AuCu) bimetallic nanoparticles with good catalytic properties on two-dimensional copper (II)-porphyrin (Cu-TCPP) nanosheet metal-organic framework material, whose conductivity was improved by polypyrrole (PPy). A method for the determination of hydrogen peroxide by voltammetric was established.

Sensitive electrochemical sensing platform for selective determination of dopamine based on amorphous cobalt hydroxide/polyaniline nanofibers composites.

In this study, amorphous cobalt hydroxide/polyaniline nanofibers (Co(OH)2/PANINF) composites were successfully prepared. The formation of amorphous Co(OH)2 with irregular surface structure was confirmed by x-ray diffraction, scanning electron microscopy, and selected-area electron diffraction. The non-enzymatic electrochemical sensor for the selective and sensitive determination of dopamine (DA) has been constructed by using Co(OH)2/PANINF composites modified glassy carbon electrode (Co(OH)2/PANINF/GCE), which exhibited excellent electrocatalytic activity toward DA, in a large part owing to the advantages of large surface area of amorphous Co(OH)2 and the synergetic effect between Co(OH)2 and PANINF. The electrochemical kinetics reveal that the DA oxidation involves two electrons and two protons in a quasi-reversible electrode reaction. Differential pulse voltammetry (DPV) studies show remarkable sensing performance for the determination of DA, with a low detection limit of 0.03 µM, and a wide linear range from 0.1 to 200 µM. From a broader perspective, the present study demonstrates that Co(OH)2/PANINF composites would be promising supporting materials for novel sensing platforms.

A novel method to diagnose the infection of enterovirus A71 in children by detecting IgA from saliva.

Enterovirus A71 (EV-A71) is one of the main pathogens causing hand, foot, and mouth disease, and often causes diseases of the central nervous system. Early diagnosis is important to prevent EV-A71 outbreaks. The detection of serum immunoglobulin M (IgM) is widely used for the early diagnosis of EV-A71 in clinics, especially in rural areas. However, this technique requires the extraction of blood from children who have thin blood vessels and who might fear the use of needles. Therefore, difficulties in the detection process are often encountered. This study developed a noninvasive method to detect EV-A71-specific immunoglobulin A (IgA) in saliva for the diagnosis of EV-A71 infection. The sensitivity and specificity of IgA detection did not differ significantly compared with IgM detection. IgA antibodies were present in saliva for a relatively shorter period than IgM antibodies were present in serum. The sensitivity of IgA detection was higher than that of IgM detection for secondary EV-A71 infections. These results suggest that the detection of EV-A71-specific IgA in the saliva allows the effective early diagnosis of EV-A71 and may be suitable for detecting EV-A71 infections in children.

Amperometric hydrazine sensor based on the use of a gold nanoparticle-modified nanocomposite consisting of porous polydopamine, multiwalled carbon nanotubes and reduced graphene oxide.

A porous hybrid material was prepared from polydopamine-modified multiwalled carbon nanotubes and reduced graphene oxide. It was employed as a supporting material for an electrochemical hydrazine sensor. Gold nanoparticles with a size of about 13 nm were placed on the material which then was characterized by transmission electron microscopy, field emission-scanning electron microscopy, Raman spectra, FTIR and nitrogen absorption/desorption plots. The material is highly porous and has a specific surface of 290 m2 g-1, which is larger than that of P-MWCNT/rGO alone (149 m2 g-1), and an increased pore volume. It was placed on a glassy carbon electrode (GCE), and cyclic voltammetry, chronoamperometry and amperometric i-t curves were used to characterize the catalytic activity of the sensor. The kinetic parameters of the modified GCE were calculated which proved that it has a high catalytic efficiency in promoting the electron transfer kinetics of hydrazine. The amperometric signal (obtained at a typical working potential of 0.35 V vs. SCE) has two linear ranges, one from 1 µM - 3 mM and one from 3 to 55 mM, with sensitivities of 524 and 98 A mM-1 cm-2, respectively. The detection limit is 0.31 µM. Graphical abstractThe porous nanocomposite was synthesized by etching silver nanoparticles and a enhanced non-enzymatic electrochemical sensor of hydrazine was successfully designed. The electrochemical performances of the modified electrode were also examined.

High-index {hk0} facets platinum concave nanocubes loaded on multiwall carbon nanotubes and graphene oxide nanocomposite for highly sensitive simultaneous detection of dopamine and uric acid.

Carbon materials and the metal nanocrystals enclosed by high-index facets have aroused considerable attention due to their large specific surface area, excellent electrical properties and catalysis activity, and easy accessibility for target molecules. In this study, the Pt concave nanocube (CNC) with high-index {410} and {510} facets was successfully prepared via a simple hydrothermal method. The multiwalled carbon nanotubes (MWCNT) and graphene oxide (GO) were chosen as the supporting materials to further improve the dispersion of Pt CNC and the electrical conductivity of nanocomposite. The nanocomposite was used to modify electrode for sensitive simultaneous detection dopamine and uric acid. The cyclic voltammetry and differential pulse voltammetry were applied to confirm the catalytic activity of proposed sensor. By using the as-synthesized nanomaterial as nonenzymatic sensing material, dopamine and uric acid can be detected with high sensitivity and selectivity. The linear range towards dopamine sensing is from 0.8 to 300 µM, and the limit of detection is 0.27 µM. For uric acid sensing, the sensor exhibited over two wide linear ranges (from 1 µM to 0.3 mM and from 0.3 mM to 1 mM) with a detection limit of 0.35 µM. The sensor also possessed a long-term stability, good reproducibility and a promising application for electrochemical detection of both dopamine and uric acid in real samples.

Progranulin mutations result in impaired processing of prosaposin and reduced glucocerebrosidase activity.

Frontotemporal dementia (FTD) is a common neurogenerative disorder characterized by progressive degeneration in the frontal and temporal lobes. Heterozygous mutations in the gene encoding progranulin (PGRN) are a common genetic cause of FTD. Recently, PGRN has emerged as an important regulator of lysosomal function. Here, we examine the impact of PGRN mutations on the processing of full-length prosaposin to individual saposins, which are critical regulators of lysosomal sphingolipid metabolism. Using FTD-PGRN patient-derived cortical neurons differentiated from induced pluripotent stem cells, as well as post-mortem tissue from patients with FTLD-PGRN, we show that PGRN haploinsufficiency results in impaired processing of prosaposin to saposin C, a critical activator of the lysosomal enzyme glucocerebrosidase (GCase). Additionally, we found that PGRN mutant neurons had reduced lysosomal GCase activity, lipid accumulation and increased insoluble α-synuclein relative to isogenic controls. Importantly, reduced GCase activity in PGRN mutant neurons is rescued by treatment with saposin C. Together, these findings suggest that reduced GCase activity due to impaired processing of prosaposin may contribute to pathogenesis of FTD resulting from PGRN mutations.

Online Signature Verification Based on a Single Template via Elastic Curve Matching.

Person verification using online handwritten signatures is one of the most widely researched behavior-biometrics. Many signature verification systems typically require five, ten, or even more signatures for an enrolled user to provide an accurate verification of the claimed identity. To mitigate this drawback, this paper proposes a new elastic curve matching using only one reference signature, which we have named the curve similarity model (CSM). In the CSM, we give a new definition of curve similarity and its calculation method. We use evolutionary computation (EC) to search for the optimal matching between two curves under different similarity transformations, so as to obtain the similarity distance between two curves. Referring to the geometric similarity property, curve similarity can realize translation, stretching and rotation transformation between curves, thus adapting to the inconsistency of signature size, position and rotation angle in signature curves. In the matching process of signature curves, we design a sectional optimal matching algorithm. On this basis, for each section, we develop a new consistent and discriminative fusion feature extraction for identifying the similarity of signature curves. The experimental results show that our system achieves the same performance with five samples assessed with multiple state-of-the-art automatic signature verifiers and multiple datasets. Furthermore, it suggests that our system, with a single reference signature, is capable of achieving a similar performance to other systems with up to five signatures trained.

A modulator of wild-type glucocerebrosidase improves pathogenic phenotypes in dopaminergic neuronal models of Parkinson's disease.

Mutations in the GBA1 gene encoding the lysosomal enzyme ß-glucocerebrosidase (GCase) represent the most common risk factor for Parkinson's disease (PD). GCase has been identified as a potential therapeutic target for PD and current efforts are focused on chemical chaperones to translocate mutant GCase into lysosomes. However, for several GBA1-linked forms of PD and PD associated with mutations in LRRK2, DJ-1, and PARKIN, activating wild-type GCase represents an alternative approach. We developed a new small-molecule modulator of GCase called S-181 that increased wild-type GCase activity in iPSC-derived dopaminergic neurons from sporadic PD patients, as well as patients carrying the 84GG mutation in GBA1, or mutations in LRRK2, DJ-1, or PARKIN who had decreased GCase activity. S-181 treatment of these PD iPSC-derived dopaminergic neurons partially restored lysosomal function and lowered accumulation of oxidized dopamine, glucosylceramide and α-synuclein. Moreover, S-181 treatment of mice heterozygous for the D409V GBA1 mutation (Gba1D409V/+ ) resulted in activation of wild-type GCase and consequent reduction of GCase lipid substrates and α-synuclein in mouse brain tissue. Our findings point to activation of wild-type GCase by small-molecule modulators as a potential therapeutic approach for treating familial and sporadic forms of PD that exhibit decreased GCase activity.