Largely Improving the Output Performance of Stretchable Triboelectric Nanogenerators via Thermo-Compressive Technology.

Stretchable triboelectric nanogenerators (TENGs) are widely applied in wearable and implantable electronics, smart medical devices, and soft robots. However, it is still a challenge to produce stretchable TENGs with both exceptional elasticity and output performance, which limits their application scope. In this work, high-performance stretchable TENGs are developed through a thermo-compression (TC) fabrication process. In particular, a poly(vinylidene fluoride) film is compactly bound to the elastic thermoplastic polyurethane substrate, which inherits excellent stretchability with a strain of up to 815%. Furthermore, owing to the large surface area, tight contact, and effective vertical transport of tribo-induced charges between the coupled fibrous tribo-layer and soft substrate, the TC composite film-based TENGs exhibit a greater output (2-4 times) than unlaminated film-based TENGs. Additionally, the broad universality of this method is proven using various tribo- and substrate materials. The proposed technology provides a novel and effective approach to conjointly boost the output and stretchability of TENGs, showing encouraging application prospects in self-powered wearable and flexible electronics.

Discrete Dynamical Modeling of Influenza Virus Infection Suggests Age-Dependent Differences in Immunity.

Immunosenescence, an age-related decline in immune function, is a major contributor to morbidity and mortality in the elderly. Older hosts exhibit a delayed onset of immunity and prolonged inflammation after an infection, leading to excess damage and a greater likelihood of death. Our study applies a rule-based model to infer which components of the immune response are most changed in an aged host. Two groups of BALB/c mice (aged 12 to 16 weeks and 72 to 76 weeks) were infected with 2 inocula: a survivable dose of 50 PFU and a lethal dose of 500 PFU. Data were measured at 10 points over 19 days in the sublethal case and at 6 points over 7 days in the lethal case, after which all mice had died. Data varied primarily in the onset of immunity, particularly the inflammatory response, which led to a 2-day delay in the clearance of the virus from older hosts in the sublethal cohort. We developed a Boolean model to describe the interactions between the virus and 21 immune components, including cells, chemokines, and cytokines, of innate and adaptive immunity. The model identifies distinct sets of rules for each age group by using Boolean operators to describe the complex series of interactions that activate and deactivate immune components. Our model accurately simulates the immune responses of mice of both ages and with both inocula included in the data (95% accurate for younger mice and 94% accurate for older mice) and shows distinct rule choices for the innate immunity arm of the model between younger and aging mice in response to influenza A virus infection.IMPORTANCE Influenza virus infection causes high morbidity and mortality rates every year, especially in the elderly. The elderly tend to have a delayed onset of many immune responses as well as prolonged inflammatory responses, leading to an overall weakened response to infection. Many of the details of immune mechanisms that change with age are currently not well understood. We present a rule-based model of the intrahost immune response to influenza virus infection. The model is fit to experimental data for young and old mice infected with influenza virus. We generated distinct sets of rules for each age group to capture the temporal differences seen in the immune responses of these mice. These rules describe a network of interactions leading to either clearance of the virus or death of the host, depending on the initial dosage of the virus. Our models clearly demonstrate differences in these two age groups, particularly in the innate immune responses.

APT-MCMC, a C++/Python implementation of Markov Chain Monte Carlo for parameter identification.

The inverse problem associated with fitting parameters of an ordinary differential equation (ODE) system to data is nonlinear and multimodal, which is of great challenge to gradient-based optimizers. Markov Chain Monte Carlo (MCMC) techniques provide an alternative approach to solving these problems and can escape local minima by design. APT-MCMC was created to allow users to setup ODE simulations in Python and run as compiled C++ code. It combines affine-invariant ensemble of samplers and parallel tempering MCMC techniques to improve the simulation efficiency. Simulations use Bayesian inference to provide probability distributions of parameters, which enable analysis of multiple minima and parameter correlation. Benchmark tests result in a 20×-60× speedup but 14% increase in memory usage against emcee, a similar MCMC package in Python. Several MCMC hyperparameters were analyzed: number of temperatures, ensemble size, step size, and swap attempt frequency. Heuristic tuning guidelines are provided for setting these hyperparameters.

A One-Nearest-Neighbor Approach to Identify the Original Time of Infection Using Censored Baboon Sepsis Data.

OBJECTIVES: Sepsis therapies have proven to be elusive because of the difficulty of translating biologically sound and effective interventions in animal models to humans. A part of this problem originates from the fact that septic patients present at various times after the onset of sepsis, whereas the exact time of infection is controlled in animal models. We sought to determine whether data mining longitudinal physiologic data in a nonhuman primate model of Escherichia coli-induced sepsis could help inform the time of onset of infection. DESIGN: A nearest-neighbor approach was used to back cast the time of onset of infection in animal models of sepsis. Animal data were censored to simulate prospective monitoring at any moment along the septic infection. This was compared against an uncensored database to find the most similar animal in order to estimate the infection onset time. Leave-one-out cross-validation was used for validation. Biomarker selection was performed based on the criteria of estimation accuracy and/or ease of measurement. SETTING: Computational experimental on existing experimental data. SUBJECTS: Retrospective data from 33 septic baboons (Papio ursinus) subjected to Escherichia coli infusion. Validation was performed using 14 pigs that were subjected to surgically induced fecal peritonitis and 22 pigs that were subjected to lipopolysaccharide infusion. MEASUREMENTS AND MAIN RESULTS: Longitudinal physiologic and serum markers, time of death. The presence of uniquely changing biomarkers during septic infection enabled the estimation of infection onset time in the datasets. Various combinations of temporal biomarkers, such as WBC, oxygen content, mean arterial pressure, and heart rate, yielded estimation accuracies of up to 97.8%. The use of temporal vital signs and a single measurement of serum biomarkers yielded highly accurate estimates without the need for invasive measurements. Validation in the pig data revealed similar results despite the heterogeneity of multiple experimental cohorts. This suggests that the method may be effective if sufficiently similar subjects are present in the database. CONCLUSIONS: One nearest-neighbor analysis showed promise in accurately identifying the onset of infection given a database of known infection times and of sufficient breadth. We suggest that this approach is ready for evaluation within the clinical setting using human data.

MicroRNA function in the profibrogenic interplay upon chronic liver disease.

In chronic liver disease leading to fibrosis, hepatic stellate cells (HSC) differentiate into myofibroblasts. Myofibroblastic HSC have taken center stage during liver fibrogenesis, due to their remarkable synthesis of extracellular matrix proteins, their secretion of profibrogenic mediators and their contribution to hypertension, due to elevated contractility. MicroRNAs (miRNAs) are small, noncoding RNA molecules of 19-24 nucleotides in length. By either RNA interference or inhibition of translational initiation and elongation, each miRNA is able to inhibit the gene expression of a wide panel of targeted transcripts. Recently, it was shown that altered miRNA patterns after chronic liver disease highly affect the progression of fibrosis by their potential to target the expression of extracellular matrix proteins and the synthesis of mediators of profibrogenic pathways. Here, we underline the role of miRNAs in the interplay of the profibrogenic cell communication pathways upon myofibroblastic differentiation of hepatic stellate cells in the chronically injured liver.

High affinity γPNA sandwich hybridization assay for rapid detection of short nucleic acid targets with single mismatch discrimination.

Hybridization analysis of short DNA and RNA targets presents many challenges for detection. The commonly employed sandwich hybridization approach cannot be implemented for these short targets due to insufficient probe-target binding strengths for unmodified DNA probes. Here, we present a method capable of rapid and stable sandwich hybridization detection for 22 nucleotide DNA and RNA targets. Stable hybridization is achieved using an n-alkylated, polyethylene glycol γ-carbon modified peptide nucleic acid (γPNA) amphiphile. The γPNA's exceptionally high affinity enables stable hybridization of a second DNA-based probe to the remaining bases of the short target. Upon hybridization of both probes, an electrophoretic mobility shift is measured via interaction of the n-alkane modification on the γPNA with capillary electrophoresis running buffer containing nonionic surfactant micelles. We find that sandwich hybridization of both probes is stable under multiple binding configurations and demonstrate single base mismatch discrimination. The binding strength of both probes is also stabilized via coaxial stacking on adjacent hybridization to targets. We conclude with a discussion on the implementation of the proposed sandwich hybridization assay as a high-throughput microRNA detection method.

Identification of Clinical Phenotypes in Septic Patients Presenting With Hypotension or Elevated Lactate.

Introduction: Targeted therapies for sepsis have failed to show benefit due to high variability among subjects. We sought to demonstrate different phenotypes of septic shock based solely on clinical features and show that these relate to outcome. Methods: A retrospective analysis was performed of a 1,023-subject cohort with early septic shock from the ProCESS trial. Twenty-three clinical variables at baseline were analyzed using hierarchical clustering, with consensus clustering used to identify and validate the ideal number of clusters in a derivation cohort of 642 subjects from 20 hospitals. Clusters were visualized using heatmaps over 0, 6, 24, and 72 h. Clinical outcomes were 14-day all-cause mortality and organ failure pattern. Cluster robustness was confirmed in a validation cohort of 381 subjects from 11 hospitals. Results: Five phenotypes were identified, each with unique organ failure patterns that persisted in time. By enrollment criteria, all patients had shock. The two high-risk phenotypes were characterized by distinct multi-organ failure patterns and cytokine signatures, with the highest mortality group characterized most notably by liver dysfunction and coagulopathy while the other group exhibited primarily respiratory failure, neurologic dysfunction, and renal dysfunction. The moderate risk phenotype was that of respiratory failure, while low-risk phenotypes did not have a high degree of additional organ failure. Conclusions: Sepsis phenotypes with distinct biochemical abnormalities may be identified by clinical characteristics alone and likely provide an opportunity for early clinical actionability and prognosis.

Fiber-Based Electret Nanogenerator with a Semisupported Structure for Wearable Electronics.

Fiber-based nanogenerators have great potential applications in wearable electronics such as portable nanodevices, e-skin, and artificial intelligence system. Here, we report a kind of fiber-based electret nanogenerator (FENG) with a semisupported core-shell structure. Owing to its unique structure, the open-circuit voltage and short-circuit current of the FENG reach 40 V and 0.6 µA, respectively, under a short working distance (∼25 µm). No obvious degradation of the output performance under a long-time continuous work (>16 h) and different humidity environments (20-95%) is observed, which demonstrates the FENG's good reliability and stability. Many universal materials, such as cotton rope, conductive sewing thread, and polyvinyl chloride tube, have been successfully used to fabricate FENG. Meanwhile, the FENG-based wearable fabric has been successfully developed to effectively harvest mechanical energy of human motion. The FENG is highly effective, reliable, and stable, promoting the development of fiber-based nanogenerators and their applications in self-powered wearable electronics.

[Analysis of the failure mechanisms of the revision hip arthroplasties].

OBJECTIVE: To investigate the failure mechanisms of revision hip arthroplasties and evaluate the effects of surgical technique, prosthesis design and patient-related risk factors on different failure mechanisms. METHODS: A review of all revision hip arthroplasties from November 1995 to June 2008 identified 30 patients who underwent 30 revisions with 18 males and 12 females. The overall mean age for primary arthroplasties was 49 years (range 25-68 years) and 53 years (range 27-72 years) for index revision arthroplasties and the average interval between these two operations was 43.8 months (0-156 months). The failure mechanisms of index revision arthroplasties and primary arthroplasties were assessed and compared. Direct comparisons were made of data for the different age categories in terms of time to failures and reasons for failures. RESULTS: Regarding revision or prosthesis removal as the end point of the study, the reasons for 30 revision arthroplasties were aseptic loosening in 22 hips (73.3%), infection in 4 hips (13.3%), periprosthetic fracture in 3 hips and instability in 1 hip (3.3%). The overall mean age for last arthroplasties or prosthesis removal was 58 years (range 38-77 years) with an average interval of 78.8 months (range 1-216 months) from previous revision arthroplasties. The mean time to failure for patients above 60 years of age was significantly shorter than patients below 60 years of age (P < 0.01). CONCLUSION: The majority of failure mechanisms of revision hip arthroplasties are ineffective fixation of revisional implants and recurrence of local infection, which reveals the limitations to joint reconstruction philosophy and surgical technique.

[An investigation on failure mechanisms of primary 327 hip arthroplasties].

OBJECTIVE: To summarize the detailed failure mechanisms of revision hip arthroplasties and related risk factors. METHODS: From November 1988 to July 2008 revision of total hip arthroplasties was performed in 327 patients. The medical history, clinical and imaging material and operation records were investigated. RESULTS: Regarding revision as the end point of the study, the reasons for 327 revision arthroplasties were aseptic loosening in 226 hips (69.1%), infection in 52 hips (15.9%), periprosthetic fracture in 22 hips (6.7%), instability in 17 hips (5.2%), stem fracture in 5 hips (1.5%) and liner dissociation in 5 hips (1.5%). CONCLUSIONS: The main failure mechanisms of primary hip arthroplasties are aseptic loosening and infection of implants, which could be attributed to improper selection of operation indications and implants and limitations to surgical philosophy and technique.

Analysis of alternative signaling pathways of endoderm induction of human embryonic stem cells identifies context specific differences.

BACKGROUND: Lineage specific differentiation of human embryonic stem cells (hESCs) is largely mediated by specific growth factors and extracellular matrix molecules. Growth factors initiate a cascade of signals which control gene transcription and cell fate specification. There is a lot of interest in inducing hESCs to an endoderm fate which serves as a pathway towards more functional cell types like the pancreatic cells. Research over the past decade has established several robust pathways for deriving endoderm from hESCs, with the capability of further maturation. However, in our experience, the functional maturity of these endoderm derivatives, specifically to pancreatic lineage, largely depends on specific pathway of endoderm induction. Hence it will be of interest to understand the underlying mechanism mediating such induction and how it is translated to further maturation. In this work we analyze the regulatory interactions mediating different pathways of endoderm induction by identifying co-regulated transcription factors. RESULTS: hESCs were induced towards endoderm using activin A and 4 different growth factors (FGF2 (F), BMP4 (B), PI3KI (P), and WNT3A (W)) and their combinations thereof, resulting in 15 total experimental conditions. At the end of differentiation each condition was analyzed by qRT-PCR for 12 relevant endoderm related transcription factors (TFs). As a first approach, we used hierarchical clustering to identify which growth factor combinations favor up-regulation of different genes. In the next step we identified sets of co-regulated transcription factors using a biclustering algorithm. The high variability of experimental data was addressed by integrating the biclustering formulation with bootstrap re-sampling to identify robust networks of co-regulated transcription factors. Our results show that the transition from early to late endoderm is favored by FGF2 as well as WNT3A treatments under high activin. However, induction of late endoderm markers is relatively favored by WNT3A under high activin. CONCLUSIONS: Use of FGF2, WNT3A or PI3K inhibition with high activin A may serve well in definitive endoderm induction followed by WNT3A specific signaling to direct the definitive endoderm into late endodermal lineages. Other combinations, though still feasible for endoderm induction, appear less promising for pancreatic endoderm specification in our experiments.