Mimicking kidney flow shear efficiently induces aggregation of LECT2, a protein involved in renal amyloidosis.

Aggregation of leukocyte cell-derived chemotaxin 2 (LECT2) causes ALECT2, a systemic amyloidosis that affects the kidney and liver. Previous studies established that LECT2 fibrillogenesis is accelerated by the loss of its bound zinc ion and stirring/shaking. These forms of agitation create heterogeneous shear conditions, including air-liquid interfaces that denature proteins, that are not present in the body. Here, we determined the extent to which a more physiological form of mechanical stress-shear generated by fluid flow through a network of narrow channels-drives LECT2 fibrillogenesis. To mimic blood flow through the kidney, where LECT2 and other proteins form amyloid deposits, we developed a microfluidic device consisting of progressively branched channels narrowing from 5 mm to 20 µm in width. Shear was particularly pronounced at the branch points and in the smallest capillaries. Aggregation was induced within 24 h by shear levels that were in the physiological range and well below those required to unfold globular proteins such as LECT2. EM images suggested the resulting fibril ultrastructures were different when generated by laminar flow shear versus shaking/stirring. Importantly, results from the microfluidic device showed the first evidence that the I40V mutation accelerated fibril formation and increased both the size and the density of the aggregates. These findings suggest that kidney-like flow shear, in combination with zinc loss, acts in combination with the I40V mutation to trigger LECT2 amyloidogenesis. These microfluidic devices may be of general use for uncovering mechanisms by which blood flow induces misfolding and amyloidosis of circulating proteins.

Impact of the pulmonary ventilation function on the prognosis of suspected asthma patients: A retrospective observational study.

OBJECTIVE: Asthma is a common chronic respiratory diseases, and the relationship between pulmonary ventilation function and the prognosis of patients with suspected asthma is not well understood. This study aims to explore the impact of pulmonary ventilation functions on the prognosis of patients with suspected asthma. METHODS: This retrospective observational study included patients with suspected asthma who were diagnosed and treated at the Guangdong Provincial Hospital of Traditional Chinese Medicine between August 2015 and January 2020. The primary outcome of interest was improvement in asthma symptoms, as measured by bronchial provocation test (BPT) results within 1 year after diagnosis. The impact of pulmonary ventilation functions on prognosis was explored by multivariable logistic regression analysis. RESULTS: Seventy-two patients were included in the study. Patients with normal (OR = 0.123, P = 0.004) or generally normal (OR = 0.075, P = 0.039) pulmonary ventilation function were more likely to achieve improvement in asthma symptoms compared with patients with mild obstruction. There were no significant differences between the improvement and non-improvement groups in baseline characteristics. CONCLUSION: These results suggest that suspected asthma patients with normal or generally normal pulmonary ventilation function are more likely to achieve improvement in asthma symptoms within one year compared to patients with mild obstruction.

Supramolecular Peptoid Structure Strengthens Complexation with Polyacrylic Acid Microgels.

We have studied the complexation between cationic antimicrobials and polyanionic microgels to create self-defensive surfaces that responsively resist bacterial colonization. An essential property is the stable sequestration of the loaded (complexed) antimicrobial within the microgel under a physiological ionic strength. Here, we assess the complexation strength between poly(acrylic acid) [PAA] microgels and a series of cationic peptoids that display supramolecular structures ranging from an oligomeric monomer to a tetramer. We follow changes in loaded microgel diameter with increasing [Na+] as a measure of the counterion doping level. Consistent with prior findings on colistin/PAA complexation, we find that a monomeric peptoid is fully released at ionic strengths well below physiological conditions, despite its +5 charge. In contrast, progressively higher degrees of peptoid supramolecular structure display progressively greater resistance to salting out, which we attribute to the greater entropic stability associated with the complexation of multimeric peptoid bundles.

Squeezed state in the hydrodynamic focusing regime for Escherichia coli bacteria detection.

Flow cytometry is an essential technique in single particle analysis and cell sorting for further downstream diagnosis, exhibiting high-throughput and multiplexing capabilities for many biological and biomedical applications. Although many hydrodynamic focusing-based microfluidic cytometers have been demonstrated with reduced size and cost to adapt to point-of-care settings, the operating conditions are not characterized systematically. This study presents the flow transition process in the hydrodynamic focusing mechanism when the flow rate or the Reynolds number increases. The characteristics of flow fields and mass transport were studied under various operating conditions, including flow rates and microchannel heights. A transition from the squeezed focusing state to the over-squeezed anti-focusing state in the hydrodynamic focusing regime was observed when the Reynolds number increased above 30. Parametric studies illustrated that the focusing width increased with the Reynolds number but decreased with the microchannel height in the over-squeezed state. The microfluidic cytometric analyses using microbeads and E. coli show that the recovery rate was maintained by limiting the Reynolds number to 30. The detailed analysis of the flow transition will provide new insight into microfluidic cytometric analyses with a broad range of applications in food safety, water monitoring and healthcare sectors.

Static mechanical analysis of the vertebral body after modified anterior cervical discectomy and fusion (partial vertebral osteotomy): a finite element model.

BACKGROUND: Modified anterior cervical discectomy and fusion (Mod ACDF) can effectively address ossification of the posterior longitudinal ligament (OPLL), which is difficult to remove directly from the posterior edge of the vertebral body, with considerably lesser damage as compared to anterior cervical corpectomy and fusion (ACCF). We compared the static mechanics of different anterior approaches by using an ideal finite element model. METHODS: A complete finite element model was established and classified into the following three surgical models according to different model cutting operations: ACDF, ACCF, and Mod ACDF. Three different bone volume situations (normal bone mineral density, osteopenia, and osteoporosis) were simulated. After fixing the lower surface of C5 or C6, a load was applied to the upper surface of C4, and the stress distribution and displacement of the upper surface of C5 or C6 were observed and the related values were recorded. RESULTS: The average Von Mises Stress and displacement levels of Mod ACDF were between those of ACDF and ACCF; with the peak Von Mises Stress occurring on the posterior side of the vertebral body (Points 1-4). The change in Von Mises Stress of the vertebral body is not significant during bone loss. However, the degree of displacement of the vertebral body surface and risk of vertebral collapse are increased (100 N: 13.91 vs. 19.47 vs. 21.62 µm; 150 N: 19.60 vs. 29.30 vs. 31.64 µm; 200 N: 28.53 vs. 38.65 vs. 44.83 µm). CONCLUSIONS: The static biomechanical effects caused by Mod ACDF are intermediate between ACDF and ACCF, and the risk of vertebral body collapse is lower than that by ACCF. Therefore, Mod ACDF may be an effective solution when targeting OPLL with poorly positioned posterior vertebral body edges.

Novel Discrete-Time Recurrent Neural Network for Robot Manipulator: A Direct Discretization Technical Route.

Controlling and processing of time-variant problem is universal in the fields of engineering and science, and the discrete-time recurrent neural network (RNN) model has been proven as an effective method for handling a variety of discrete time-variant problems. However, such model usually originates from the discretization research of continuous time-variant problem, and there is little research on the direct discretization method. To address the aforementioned problem, this article introduces a novel discrete-time RNN model for solving the discrete time-variant problem in a pioneering manner. Specifically, a discrete time-variant nonlinear system, which originates from the mathematical modeling of serial robot manipulator, is presented as a target problem. For solving the problem, first, the technique of second-order Taylor expansion is used to deal with the discrete time-variant nonlinear system, and the novel discrete-time RNN model is proposed subsequently. Second, the theoretical analyses are investigated and developed, which shows the convergence and precision of the proposed discrete-time RNN model. Furthermore, three distinct numerical experiments verify the excellent performance of the proposed discrete-time RNN model. In addition, a robot manipulator example further verifies the effectiveness and practicability of the proposed novel discrete-time RNN model.

MIFNN: Molecular Information Feature Extraction and Fusion Deep Neural Network for Screening Potential Drugs.

Molecular property prediction is essential for drug screening and reducing the cost of drug discovery. Current approaches combined with deep learning for drug prediction have proven their viability. Based on the previous deep learning networks, we propose the Molecular Information Fusion Neural Network (MIFNN). The features of MIFNN are as follows: (1) we extracted directed molecular information using 1D-CNN and the Morgan fingerprint using 2D-CNN to obtain more comprehensive feature information; (2) we fused two molecular features from one-dimensional and two-dimensional space, and we used the directed message-passing method to reduce the repeated collection of information and improve efficiency; (3) we used a bidirectional long short-term memory and attention module to adjust the molecular feature information and improve classification accuracy; (4) we used the particle swarm optimization algorithm to improve the traditional support vector machine. We tested the performance of the model on eight publicly available datasets. In addition to comparing the overall classification capability with the baseline model, we conducted a series of ablation experiments to verify the optimization of different modules in the model. Compared with the baseline model, our model achieved a maximum improvement of 14% on the ToxCast dataset. The performance was very stable on most datasets. On the basis of the current experimental results, MIFNN performed better than previous models on the datasets applied in this paper.

A sample-to-answer DNA detection microfluidic system integrating sample pretreatment and smartphone-readable gradient plasmonic photothermal continuous-flow PCR.

As the gold standard for nucleic acid detection, full-process polymerase chain reaction (PCR) analysis often falls into the dilemma of complex workflow, time-consuming, and high equipment costs. Therefore, we designed and optimized a DNA quantification microfluidic system by strategically integrating sample pretreatment and a smartphone-readable gradient plasmonic photothermal (GPPT) continuous-flow PCR (CF-PCR). Through preloading and sequential injection of immiscible extraction reagents, combined with magnetic bead (MB) manipulation, the microfluidic chip successfully purified and concentrated 100 µL of HBV-DNA spiked plasma into a 20-µL purified sample within 14 minutes. With a digital PCR platform, the optimized experiments showed that the DNA extraction efficiency can reach 69% at an immiscible reagent configuration ratio of 10 : 10 : 1 : 12 : 2 (sample : lysis/binding buffer : MB : silicone oil : eluent) and a flow rate of 25 µL min-1. For the first time, we used gold nanorod (AuNR)-doped PDMS to prepare a CF-PCR submodule for the amplification of a 40 µL PCR mixture. Due to the plasmonic photothermal effect of AuNRs and the gradient intensity of an expanded laser spot, the PCR thermal gradient was formed on a coin-sized area. The compact annular thermal-microfluidic layout, optimized DNA dye concentration, and chip transmittance synergistically enable a rarely reported smartphone-based fluorescence CF-PCR, greatly simplifying thermal control and detection setup. Prototype construction and validation experiments show that the microsystem can complete the sample-to-answer quantification of HBV-DNA with a dynamic linear range from 1.2 × 101 to 1.2 × 106 copies per µL in ∼37 minutes. This novel microfluidic solution effectively bridges the technical gap between the CF-PCR, sample pretreatment and result characterization, making the workflow standardized and rapid and requiring <15% of the commercial instrument cost. The simplicity, rapidity and low cost of this work make it promising for applications in decentralized laboratories and low-resource settings.

LEGAN: A Light and Effective Generative Adversarial Network for medical image synthesis.

Medical image synthesis plays an important role in clinical diagnosis by providing auxiliary pathological information. However, previous methods usually utilize the one-step strategy designed for wild image synthesis, which are not sensitive to local details of tissues within medical images. In addition, these methods consume a great number of computing resources in generating medical images, which seriously limits their applicability in clinical diagnosis. To address the above issues, a Light and Effective Generative Adversarial Network (LEGAN) is proposed to generate high-fidelity medical images in a lightweight manner. In particular, a coarse-to-fine paradigm is designed to imitate the painting process of humans for medical image synthesis within a two-stage generative adversarial network, which guarantees the sensitivity to local information of medical images. Furthermore, a low-rank convolutional layer is introduced to construct LEGAN for lightweight medical image synthesis, which utilizes principal components of full-rank convolutional kernels to reduce model redundancy. Additionally, a multi-stage mutual information distillation is devised to maximize dependencies of distributions between generated and real medical images in model training. Finally, extensive experiments are conducted in two typical tasks, i.e., retinal fundus image synthesis and proton density weighted MR image synthesis. The results demonstrate that LEGAN outperforms the comparison methods by a significant margin in terms of Fréchet inception distance (FID) and Number of parameters (NoP).

An in vitro model of microbial contamination in the operating room.

Infection associated with tissue-contacting biomedical devices is a compelling clinical problem initiated by the microbial colonization of the device surface. Among the possible sources of contaminating bacteria is the operating room (OR) itself, where viable bacteria in the atmosphere can sediment onto a device surface intraoperatively. We have developed an aerosolizing system that can reproducibly spray small quantities of aerosolized bacteria onto a surface to mimic OR contamination. This paper describes the design of the system and characterizes key aspects associated with its operation. The area density of sprayed bacteria is on the order of 102 /cm2 . Using titanium (Ti) alloy coupons as test substrates contaminated by staphylococci, we quantify the fraction of bacteria that are well adhered to the substrate, those that can be removed by sonication, and those that are not recovered after spraying. Despite the relatively low levels of surface contamination, we furthermore show that such a model is able to demonstrate a statistically significant reduction in colonization of Ti coupons modified by antimicrobial quaternary ammonium compounds relative to unmodified controls.

A Pocket-Textured Surface for Improving the Tribological Properties of Point Contact under Starved Lubrication.

This paper reports a novel pocket-textured surface for improving the tribological properties of point contact under starved lubrication by possibly storing and releasing oil, and homogenizing the surface contact pressure. The ball-on-disk experimental results confirmed the coefficient of friction (COF) and wear reduction effect of such pocket-texturing. The maximum reduction rate was 40% compared with a flat surface under the same operating conditions. Analyses on experimental results attributed the oil storage effect and enhanced the secondary lubrication effect within the starved lubrication state, to become the main mechanism. In addition, the plate elasticity and the Hertzian contact principles were employed to estimate the pressure and the load acting on the surface. The experimental results and numerical analysis substantiated the design of pocket-textured surface, making it likely to enlarge about 50% of contact surface and to reduce 90% of equivalent stress in comparison to those of conventional surfaces.

Inhibition Effect of Zoledronate on the Osteoclast Differentiation of RAW264.7 Induced by Titanium Particles.

OBJECTIVE: This study is aimed at studying the effect of zoledronate (ZOL) on the differentiation of osteoclast precursor RAW264.7 cells induced by titanium (Ti) particles and explores the possibility of preventing and treating periprosthetic osteoporosis using ZOL. METHODS: RAW264.7 cells were cultured in vitro. Ti particles were prepared. The cell proliferation curve of RAW264.7 cells was plotted using the MTT assay to find the best concentration of ZOL for intervention. The cells were divided into three groups: control, Ti particles, and Ti particles+ZOL. The cell morphology was observed using tartaric acid-resistant acid phosphatase (TRAP) staining, and the activity of TRAP in cell supernatant was determined using the biochemical method. The number of bone resorption lacunae was detected using toluidine blue staining. The mRNA expression of RANK, NFATcl, CAII, and MMP-9 was detected using real-time polymerase chain reaction. The protein expression of RANK, NFATcl, and MMP-9 was detected using Western blot analysis. RESULTS: Ti particles stimulated the differentiation of RAW264.7 cells into osteoclasts. They also increased the activity of TRAP, number of bone resorption lacunae, and mRNA and protein expression of RANK, NFATcl, and MMP-9. However, ZOL could suppress the effect of TI particles on the osteoclast differentiation of RAW264.7 cells. CONCLUSIONS: ZOL could effectively inhibit the differentiation of RAW264.7 cells into osteoclasts induced by Ti particles, decrease the activity of TRAP, reduce the number of bone resorption lacunae, and decrease the mRNA and protein expression of RANK, NFATcl, and MMP-9. Hence, it may be a promising candidate for preventing and treating periprosthetic osteoporosis after the artificial joint operation.

Self-defensive antimicrobial biomaterial surfaces.

Self-defensive biomaterial surfaces are being developed in order to mitigate infection associated with tissue-contacting biomedical devices. Such infection occurs when microbes colonize the surface of a device and proliferate into a recalcitrant biofilm. A key intervention point centers on preventing the initial colonization. Incorporating antimicrobials within a surface coating can be very effective, but the traditional means of antimicrobial delivery by continuous elution can often be counterproductive. If there is no infection, continuous elution creates conditions that promote the development of resistant microbes throughout the patient. In contrast, a self-defensive coating releases antimicrobial only when and only where there is a microbial challenge to the surface. Otherwise, the antimicrobial remains sequestered within the coating and does not contribute to the development of resistance. A self-defensive surface requires a local trigger that signals the microbial challenge. Three such triggers have been identified as: (1) local pH lowering; (2) local enzyme release; and (3) direct microbial-surface contact. This short review highlights the need for self-defensive surfaces in the general context of the device-infection problem and then reviews key biomaterials developments associated with each of these three triggering mechanisms.

Integrated Single Microbead-Arrayed µ-Fluidic Platform for the Automated Detection of Multiplexed Biomarkers.

An automated, single microbead-arrayed µ-fluidic immunoassay (AMIA) device is innovatively devised in this study, which enables the highly sensitive and simultaneous detection of multiplex biomarkers with fully automatic operations. The AMIA platform not only achieves automated assay processing and multiplexed target detection by integrating single microbead manipulation, sample loading, multistep washing, and immunoreaction on a microfluidic chip but also confers high sensitivity due to the highly efficient signal enriching effect on a single microbead by the use of only a routine sandwich immunoreaction. As such, as low as the pg/mL level of multiplexed protein biomarkers can be simultaneously determined in a quite small volume of serum (∼20 µL is enough), which can well meet the clinical demand for disease screening and prognosis. What is more, the detection results of several clinically important biomarkers in clinical samples with the AMIA platform exhibit excellent consistency with those obtained by using a standard clinical test. Thus, in virtue of the excellent features in terms of high sensitivity, multiplexing capability, generality, and high degree of automation, the AMIA provides a practical and user-friendly platform for assaying different biomarkers in clinical diagnostics and point-of-care testing.