Various policies require that screening questions be asked of all patients who present to the emergency department (ED). No studies have previously examined the potential time costs of standardized screens. Our objective was to analyze the time nursing spent conducting standardized nursing screens and calculate the corresponding time cost.This was a prospective observational study of ED registered nurses (RN) performing triage assessments on adults presenting to the ED. A study author timed nurses while the RN asked five pre-selected questions from their current triage protocol. The time cost of each question was determined by multiplying the length of time spent asking the question each year by the mean hourly wage of RNs at the study hospital.  × V × S; T = mean time per question (in seconds); V = annual patient volume; S = mean hourly RN wage.We observed 200 triage assessments. During the triage assessments, 130 patients (65%) were asked about pneumococcal vaccine status; 161 (80.5%) about tetanus vaccine status; 184 (92%) about medication allergies; 172 (86%) about influenza vaccine; and 73 (36.5%) about recent travel. The mean time spent per question ranged from 4.37–6.26 seconds. The estimated annual time used to ask the five questions in the study ED is 590.73 hours, which equates to $20,675.50 in nursing costs per year.There are potential monetary and time costs of standardized screening questions in the ED. The values heavily impact time and cost efficiency in the ED and could be redirected to more pertinent patient care. The required screening questions often have an unclear utility on the care that the patient receives in the ED. Further studies are needed to determine cost effectiveness of required ED screenings. The Joint Commission, other medical governing agencies, and various hospital policies mandate that certain screening questions be asked of all patients who come through the emergency department (ED) for evaluation. Before a patient has even seen a physician, they have likely been asked dozens of screening questions as part of the triage or nursing assessment. Screening questions are often implemented with good intentions and some questions serve as public health screening where the ED acts as a safety net.3The downstream consequences of adding on numerous questions to the ED stay are often not considered. There is the potential for a significant amount of nursing time to be used administering assessments. Additionally, the purpose of triage is to identify and prioritize patients who require immediate treatment over those who do not. The required screening questions often have an unclear benefit on determining triage acuity and on the care that the patient receives in the ED. In many instances the addition of screening questions is based on rudimentary studies that do not examine clinical outcomes or costs.4Screening questions can add time to the triage process and ED wait time, and take nurses away from performing more direct patient care. While any individual question may not take long to ask, when you multiply it by the tens of thousands of patients who pass through the ED and the expanding number of screening questions, it quickly adds up to a significant amount of time. Our objective was to analyze the time nursing spent conducting standardized nursing screens and calculate the corresponding time cost.This was a prospective observational study of ED RNs performing triage assessments on adults presenting to the ED for medical care in a single academic hospital in the United States. Institutional review board (IRB) approval for this study was obtained from the Augusta University IRB Office. Augusta University Medical Center (AUMC) is an academic, urban hospital with an ED with 83,860 visits during fiscal year (FY) 2018. The mean RN salary at AUMC during FY18 was $35 per hour ($35/hr); this represents the mean for all RNs in the hospital, including ED nurses.The triage process was observed for all adult patients (age ≥ 18 years) presenting to the ED for treatment. To be included, patients had to go through triage . Patients were excluded if they were discussing sensitive information  or if they were unable to answer triage and nurse screening questions. Patients and triage nurses were provided an information sheet explaining that the study authors were conducting an observation study of nursing procedures. Verbal consent was obtained from nurses and patients. Patients and nurses were given the opportunity to opt out of being observed. All data collected was anonymous and no personal information was collected.After reviewing the triage and in-room nurse screening questions asked at AUMC, we selected five questions to be timed.Have you received a pneumococcal vaccine?Have you had a tetanus shot within the last five years?What are your allergies?Have you received a flu shot this year?Any recent travel?These five questions were selected because they did not impact the patients’ acuity level and all five questions were included in the triage questionnaire. Additional triage questions, such as medical history and history of present illness, were not included in the study because of their potential to impact acuity level.From July 2018 – January 2019, a total of 200 triage assessments were observed. The study authors would select times throughout the day to observe the triage process and collect data. During the triage assessment, the study authors observed triage nurses as they asked the five pre-selected questions. The nurses were not pre-selected and data was collected on whichever nurse was assigned to work in triage. Not all questions were asked of every triaged patient. The questions asked were at the nurses’ discretion and the data collectors did not interfere with the triage process.Time was calculated using a stop clock timer. The timer was started as soon as the nurse began asking the question and stopped when the patient completely answered the question and the topic was changed. We calculated the time cost for each question by multiplying the time spent addressing the question each year by the mean hourly wage of AUMC ED RNs.  × V × S, where T = mean time per question (in seconds), V = annual patient volume at AUMC, S = mean hourly RN wage. We used Google Sheets  for all calculations and statistical analysis.In total, we observed 200 triage assessments during the study period. During the triage assessments, 130 patients (65%) were asked about pneumococcal vaccine status, 161 (80.5%) about tetanus vaccine status, 184 (92%) about medication allergies, 172 about influenza vaccine (86%), and 73 (36.5%) about recent travel. The mean time spent per question ranged from 4.37–6.26 seconds . The estThis is a cursory look at the potential monetary and time costs of standardized screening questions in the ED. The calculated values directly affect time and cost efficiency in the ED process and could potentially be redirected to more direct patient care. For just the five observed triage questions alone, we estimated the nursing time cost to our institution to be $20,675.50. This time cost would be significantly increased if we examined additional triage and nurse screening questions. Furthermore, this is just the time spent in a single ED. If all 136.9 million adult ED visits in the U.S. included the five studied questions the screening would take 964,354 hours to complete.The required screening questions are often unrelated to the patient’s chief complaint and have a debatable impact on the medical management in the ED. Questions that may impact care, such as medication allergies, are typically asked by multiple medical providers during the ED visit, and redundancy leads to additional wasted time and cost. It is unclear whether the standardized questions are suitable for triage where the goal is to identify and prioritize patients who require immediate treatment over those who do not. Previous work has shown that triage assessments can have poor inter-rater and intra-rater agreement.If nurses were liberated from the mandated questions, they could potentially have more time for one-on-one patient care and other aspects of patient care, such as medication administration and lab draws. Although we suspect that reducing the number of required questions would free nurses to spend more time on direct patient care and improve efficiency of ED throughput, additional research will be required to study this hypothesis.Studies evaluating ED screening questions often praise their ability to detect at-risk groups without looking at patient-oriented outcomes or cost. Cost-benefit analyses should be considered prior to mandating additional nurse screening questions as even a few seconds spent on a question adds up to a significant amount of time. A better research agenda is needed to assess the impact of triage questions on patient care.Because this was a prospective observational study, we were unable to definitively state what the time saving would be if the five questions were eliminated. Future projects could implement a treatment group or trial period to evaluate the actual time saving and cost reduction that would occur with questions in the standardized nursing screens. Further, as this was a preliminary observational study, we had a limited sample size of only 200 assessments. Future research would benefit from a larger sample size to obtain more accurate time measurements. Additionally, we did not document the exact number of patients excluded.Given the non-blinded nature of the study, the Hawthorne effect could have influenced our findings. It is possible that the nurses involved in the study may have subconsciously altered their triage process while being observed. Since they knew they were being observed, they may have been trying to be more efficient and get through their questions faster or conversely they could have been more thorough in their assessment and took longer than when they are not observed. Finally, this was just a limited look at the time spent asking five pre-selected triage questions. Future work needs to be done to analyze the time spent asking additional screening questions, such as fall risk, suicidality, domestic abuse/“safe at home,” and alcohol abuse risk.Significant ED nursing time is spent asking triage and nurse screening questions. The evidence is unclear as to whether screening questions improve the care that patients receive in the ED. Our data suggest that there is a significant time cost for asking standardized questions, and further cost-benefit analysis must be conducted to determine the usefulness of including these standardized questions as a part of the ED visit.


The improved lithium-storage performance of Sn@N-G anode could be ascribed to the effective graphene wrapping, which accommodates the large volume change of Sn during the charge–discharge process, while the nitrogen doping increases the electronic conductivity of graphene, as well as provides a large number of active sites as reservoirs for Li+ storage.Sn/Nitrogen-doped reduced graphene oxide (Sn@N-G) composites have been successfully synthesized via a facile method for lithium-ion batteries. Compared with the Sn or Sn/graphene anodes, the Sn@N-G anode exhibits a superb rate capability of 535 mAh g However, the commercialization of these materials is impeded by their limited cycling stability, low initial Coulombic efficiency, or complicated synthesis processes. For instance, Si-based composite anode material is being trialed for commercialization but the Si content is limited to avoid the large volume change (300%) of the electrodes, while for the Li metal anode, the safety concerns of Li dendrites still hinder its application, although great progress has been achieved in recent years. Thus, the development of anode materials with a high specific capacity and good cycling stability, as well as easy synthesis, is still challenging yet desirable for LIBs.To meet the increasing demand for high-energy-density lithium-ion batteries (LIBs), it is critical to develop high-capacity anode and cathode materials with long-term cycling stability and fast charging–discharging capability ,2. On th−1 for Li4.4Sn), high electrical conductivity, low-cost, and eco-friendly nature [Among those promising candidates, the Sn anode has attracted much attention due to its high theoretical capacity  graphitic carbon, has drawn special attention and is preferable to support alloy or metal oxides to improve the electrochemical performance of the electrode materials in various types of rechargeable battery systems due to its outstanding mechanical flexibility, excellent electrical conductivity, and high chemical stability ,14,15. H2 and melamine, and the subsequent carbonization process, in which melamine sponges can construct a 3D carbon network and prevent the evaporation of Sn, allowing high structural stability of graphene. This configuration of Sn@N-G provides many remarkable advantages, such as the flexible graphene, to accommodate the volume change of Sn nanoparticles, N-doping to provide amounts of active sites as reservoirs for Li+ storage, with a 3D N-doped rGO (N-G) network to increase the electric conductivity of the electrode. As a result, the as-synthesized Sn@N-G hybrids exhibit a high reversible specific capacity of 1226 mAh g−1 at 0.1C, a superior rate capability of 535 mAh g−1 at 2C, and an excellent cyclability up to 300 cycles with a capacity retention of 939 mAh g−1 at 0.5C.Herein, we report a facile approach for the synthesis of N-doped rGO networks anchored with Sn nanoparticles (Sn@N-G) as superior LIB anodes. This strategy involves the initial hydrothermal reaction of graphene oxide (GO) solution with SnCl2·2H2O and 0.25 g of melamine foam were dissolved in 30 mL of GO solution (2 mg mL−1). After stirring for 15 min, the mixture was transferred into an autoclave and heated to 180 °C for 6 h. After being cooled down to room temperature, the product was collected and washed with water and alcohol three times. After drying for 12 h at 60 °C, the black powers were heated to 800 °C in a tube furnace with a ramp rate of 5 °C min−1 and then held for 2 h. The whole annealing process was carried out in an Ar atmosphere. After the furnace was completely cooled to room temperature, the Sn-N-G composite was obtained.The graphene oxide (GO) was synthesized by the modified hammer’s method. In a typical synthesis, 0.5 g of SnCl−2. The CR2025-type coin cells were fabricated in a high-purity argon-filled Mbraun glovebox (Germany) with H2O and O2 concentrations lower than 0.1 ppm, using lithium metal as the counter or reference electrode, Celgard 2400 separator and 1 M LiPF6 in a mixture of ethylene carbonate (EC) and diethyl carbonate (DEC) (1:1 in volume) as the electrolyte. The galvanostatic charge and discharge experiments were performed on a Land battery tester in a temperature-controlled thermotank with a potential range of 0.002–3.0 V.To prepare the electrode slurry, the as-prepared Sn@N-G composite was mixed with carbon nanotubes (CNTs), conductive carbon black (Super P), and 5 wt% poly(vinyl difluoride) (PVDF) in the N-methyl pyrrolidone (NMP) solution. The weight ratio of the mixture was 7:1:1:1. The obtained slurries were pasted onto a Cu foil (Φ14 mm) and then dried in the vacuum at 80 °C overnight. The mass loading of active material in each cell was determined to be ~2 mg cm−1 from room temperature to 600 °C.The morphology of Sn@N-G was investigated by Scanning electron microscopy (SEM)  and Transmission electron microscopy (TEM) FEI Tecnai G2 F30, Hillsboro, OR, USA). The structures of materials were detected by X-ray photoelectron spectroscopy (XRD)  and Raman  measurements(532 nm wavelength laser). Surface chemical compositions were measured by X-ray photoelectron spectroscopy (XPS) by using Al Kα radiation .The content of Sn was determined using a TG thermogravimetric analyzer  under an air atmosphere with a heating rate of 10 °C minThe overall synthetic procedure for the Sn@N-G composite is illustrated in The morphologies of Sn@N-G composites have been characterized by scanning electron microscopy (SEM), as shown in −1, G band at 1580 cm−1, and 2D band at 2700 cm−1 of graphene are clearly observed in the spectrum, which corresponds to the first-order zone boundary phonon mode associated with edges, other defects, or disordered carbon, the radial C–C stretching mode of ordered sp2 carbon, and the second-order zone boundary phonon mode for graphene, respectively. The relative intensity of the D band to the G band (ID/IG) is 1.24  appear at 30.6°, 32°, and 44.9°, indicating Sn in the as-prepared sample exists mainly in the form of Sn metal. The Sn@N-G composite was also analyzed using XPS  compositions [In order to further obtain better information on the as-prepared samples, the Raman spectroscopy was collected to evaluate the characteristics and quality of the graphene in the composite, as shown in  is 1.24 a, which sing XPS . Figure sing XPS . The higositions ,30,31.+/Li) is observed in the first cathodic scan and the intensity of this peak decreases in the following cycles, which corresponds to the irreversible reactions related to the formation of SEI films. The broad reduction peaks near 0.5 V is associated with the alloying reaction and formation the Li-Sn alloy based on the reaction of Sn + xLi+ + e− → LixSn, which is in accordance with previous reports of Sn-based anodes [+/Li) are related to the desorption of Li+ from the graphene surface and the LixSn de-alloying reaction. In the following cycle, same cathodic and anodic peaks appeared as in the first cycle, indicating the high Li-storage reversibility of the Sn@N-G anode. Importantly, after the third cycle, the intensity of the oxidation and reduction peaks is almost identical, suggesting a stable SEI formed after the first 3 cycle. In the CV curves, the oxidization and reduction peaks are consistent with the charge–discharge plateaus in To investigate the lithium storage performance of the as-prepared Sn@N-G composite, CR2032 type lithium-ion half cells were constructed for the electrochemical tests. The cyclic voltammograms (CVs) of the first three cycles of Sn@N-G anodes are shown in +/Li). At a current density of 0.1C, the as-prepared anode delivers an initial discharge capacity of 2098 mAhg−1, which is higher than the theoretical specific capacity of Sn. The high initial discharge capacity may originate from the N-doping sites, which serve as reservoirs for Li+ storage, and the solid electrolyte interface (SEI) formation. In addition, a long plateau near 0.5 V (vs. Li+/Li) can be observed and the corresponding charge plateau also appeared near 0.5 V, which indicates a small polarization effect during the charge–discharge process. The charge–discharge behaviors of the Sn@N-G anode at current densities of 0.2C and 0.5C are displayed in −1 are obtained at 0.2C and 0.5C. The charge–discharge curves of different cycles at 0.5C are also shown in −1, respectively, at current densities of 0.1, 0.2, 0.5, 1, and 2C. As the current density turns back to 0.1 C, a high capacity of 933 mAh g−1  is recovered. This superior rate capability is ascribed to the good electronic conductivity of the Sn@N-G composite. The 3D graphene conductive network facilitates the Li+ and electron transportation effectively, and N-doping further improves the electronic conductivity of the graphene sheets. The cycling stability of Sn@N-G, Sn-graphene, and pure Sn anode is compared in −1 after 300 cycles, implying good cycling stability for the Sn@N-G anode (−1 and 764.8 mAhg−1, respectively, as shown in The rate capability and cycling performances of the Sn@N-G anode are shown in -G anode . TEM ima+ storage, as reported previously [+ storage. Interestingly, the capacity of Sn@N-G shows a capacity increasing during long-term cycling, which may be attributed to the improved electrolyte wetting upon cycling and reconstruction of Sn nanoparticles during repeated cycling processes, similar to other conversion reaction-type anodes reported previously ,34. Compeviously . Overall−1 at a current density of 2C, and stable cycling performance of 300 cycles at 0.5C. The superb electrochemical performance of Sn@N-G demonstrates that the facile method is an effective way to synthesize N-doped carbon composite electrodes, which should provide a new solution for developing high-performance materials for batteries applications.In summary, a Sn@N-G composite anode has been successfully fabricated via a facile method. The Sn nanoparticles are uniformly wrapped by 3D graphene layers, which can accommodate the large volume change of Sn particles during the charge–discharge process and provide a conductive network. Moreover, the introduction of N element creates more active sites and improves the electronic conductivity of graphene. As a result, the capacity, rate capability, as well as cycling performance of the Sn@N-G anode is substantially improved. It delivers a high capacity of 535 mAh g


Designing powerful electromagnetic wave modulators is required for the advancement of optical communication technology. In this work, we study how to efficiently modulate the amplitude of electromagnetic waves in near-infrared region, by the interactions between the interband transition of graphene and the magnetic dipole resonance in metamaterials. The reflection spectra of metamaterials could be significantly reduced in the wavelength range below the interband transition, because the enhanced electromagnetic fields from the magnetic dipole resonance greatly increase the light absorption in graphene. The maximum modulation depth of reflection spectra can reach to about 40% near the resonance wavelength of magnetic dipole, for the interband transition to approach the magnetic dipole resonance, when an external voltage is applied to change the Fermi energy of graphene. Dynamically controlling the spectral properties of electromagnetic waves by external stimuli such as mechanical force, temperature change, electrical voltage, and laser beam –4 has beWe will propose an efficient method to modulate the reflection spectra of electromagnetic waves in near-infrared region, by coupling the interband transition of graphene to the magnetic dipole resonance in metamaterials. It is found that the reflection spectra of metamaterials can be largely reduced in the wavelength range below the interband transition of graphene, because the enhanced electromagnetic fields from the magnetic dipole resonance greatly increase the light absorption in graphene. The maximum modulation depth of reflection amplitude can reach to about 40% near the resonance wavelength of magnetic dipole, for the interband transition to be close to the magnetic dipole resonance, when an external voltage is applied to change the Fermi energy of graphene.We schematically show in Fig. σintra and σinter are the intraband and interband terms of the surface conductivity of graphene, τ is the electron-phonon relaxation time, Ef is the Fermi energy, and tg is the graphene thickness. The studied metamaterials could be realized in experiment with the help of advanced nanofabrication technology [where chnology . FirstlyR-R0)/R0, where R and R0 are the reflection spectra with and without graphene inserted in metamaterials [We first discuss the reflection spectra of metamaterials without graphene, as shown by the black line and squares in Fig. aterials .Fig. 2axoz plane at the wavelength of 1210 nm. The electric fields are mainly distributed around the edges of silver nanostrips, and the magnetic fields are largely localized into the silica region under the silver nanostrips. The field distribution is the typical property of a magnetic dipole resonance [M counteracting the incident magnetic field to form the magnetic dipole resonance. The resonant wavelength depends strongly on the width w of the silver nanostrips, which will have an obvious red-shift when w is increased.To demonstrate that the broad reflection dip is relevant to a magnetic dipole, in Fig. esonance . BetweenEf. The position tunability of interband transition is very helpful to efficiently control the reflection spectra. For Ef to increase from 0.46 to 0.58 eV, the interband transition blue-shifts quickly, as exhibited by the opened circles in Fig. Ef. With decreasing Ef, the modulation depth of reflection spectra becomes larger and has a maximum of nearly 40% when Ef = 0.46 eV. Furthermore, the tunable wavelength range also becomes much broader, because of the continuous red-shift of interband transition when Ef is decreased. However, in the wavelength range over the interband transition, the reflection spectra are not modulated as compared with the case of no graphene, and so, the modulation depth is almost zero.The position of interband transition can be conveniently tuned when an external voltage is applied to change Fermi energy Ef, which can be fully manifested as a sharp spectral feature in the permittivity εg of graphene. In Fig. εg for different Ef. For each Ef, there exists a narrow peak in the real part of εg, and correspondingly an abrupt drop appears in the imaginary part of εg. With decreasing Ef, such a sharp spectral feature red-shifts obviously. In the wavelength range on the right side of the abrupt drop, the imaginary part of εg is very small. This is why the reflection spectra are not modulated for the wavelengths over the interband transition. The position dependence of interband transition on Fermi energy Ef is shown in Fig. εg are in excellent agreement with those indicated by the opened circles in Fig. The interband transition is closely related to Fermi energy We have numerically demonstrated a method to efficiently modulate the reflection spectra of electromagnetic waves in near-infrared region, by coupling the interband transition of graphene to the magnetic dipole resonance in metamaterials. It is found that the reflection spectra can be largely reduced in the wavelength range below the interband transition of graphene, because the enhanced electromagnetic fields from the magnetic dipole resonance greatly increase the light absorption in graphene. The maximum modulation depth of reflection spectra can reach to about 40% near the resonance wavelength of magnetic dipole, for the interband transition to be near the magnetic dipole resonance, when an external voltage is applied to change the Fermi energy of graphene. The reflection modulation effect presented in this work may find potential applications in optical communication systems.


Drosophila model of TDP-43 proteinopathy we found significant alterations in glucose metabolism including increased pyruvate, suggesting that modulating glycolysis may be neuroprotective. Indeed, a high sugar diet improves locomotor and lifespan defects caused by TDP-43 proteinopathy in motor neurons or glia, but not muscle, suggesting that metabolic dysregulation occurs in the nervous system. Overexpressing human glucose transporter GLUT-3 in motor neurons mitigates TDP-43 dependent defects in synaptic vesicle recycling and improves locomotion. Furthermore, PFK mRNA, a key indicator of glycolysis, is upregulated in flies and patient derived iPSC motor neurons with TDP-43 pathology. Surprisingly, PFK overexpression rescues TDP-43 induced locomotor deficits. These findings from multiple ALS models show that mechanistically, glycolysis is upregulated in degenerating motor neurons as a compensatory mechanism and suggest that increased glucose availability is protective.Amyotrophic Lateral Sclerosis (ALS), is a fatal neurodegenerative disorder, with TDP-43 inclusions as a major pathological hallmark. Using a  Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease affecting upper and lower motor neurons resulting in progressive muscle weakness and eventual death . CellulaC. elegans models of neurodegeneration  abnormalities, lifespan, and locomotor defects  motor neurons and postmortem patient spinal cord tissue. In a fly model of TDP-43 proteinopathy, increased dietary glucose improves locomotor function and increases lifespan when TDP-43 is expressed in the central nervous system but not muscles. Additionally, genetic over-expression of human glucose transporters improves locomotor function, mitigates neuromuscular junction defects, and improves lifespan in a variant dependent manner. Finally, motor neuron overexpression of PFK, the rate limiting enzyme in glycolysis, improves locomotor function, suggesting that upregulation of glycolysis is neuroprotective through a compensatory mechanism in ALS. Together, our results show that increased glucose availability protects motor neurons and improves overall outcome in models of TDP-43 proteinopathy.Our lab has developed a  defects . Importa defects . Here, wDrosophila model of TDP-43 proteinopathy that recapitulates key features of the human disease including locomotor dysfunction and reduced survival (WT or D42 >TDP-43G298S) and controls (D42>w1118). These experiments showed significantly increased phosphoenolpyruvate (PEP) and pyruvate in both TDP-43WT and TDP-43G298S suggesting an increase in glucose metabolism  in conjunction with increased sedoheptulose 7-phosphate  suggesting that increased glycolytic input into the Pentose Phosphate Pathway occurs in a variant dependent manner  levels are considered to be rate-limiting and control the rate of glycolysis, thus PFK expression provides a reliable determinant of flux for glucose breakdown  and w1118 controls. These experiments showed that PFK transcript levels are increased in the context of TDP-43WT or TDP-43G298S, albeit statistical significance was only achieved in the mutant TDP-43  was selected due to its role as the commitment step for the pentose phosphate pathway (PPP). Zw transcript levels are increased specifically in TDP-43G298S  thus we focused on PFKP and PFKM. For human tissues we used spinal cords isolated from ALS patients with TDP-43 proteinopathy and controls lacking neurological defects . These experiments show that glycolysis is also upregulated in patient spinal cords and motor neurons consistent with our findings in the fly model. Similarly, G6PD transcript levels are increased by 49% in spinal cords of ALS patients . In contrast, TDP-43G298S expressing neurons showed a significant increase in the FRET/CFP signal compared to controls . These results suggest that glucose flux is specifically enhanced in TDP-43G298S expressing neurons, and further substantiate our findings that glycolysis and the pentose phosphate pathway are significantly increased in the context of TDP-43 proteinopathy.Upon stimulation with glucose, neurons expressing the glucose sensor alone or together with TDP-43 showed a small but significant increase in the FRET/CFP ratio . TDP-43WWT or TDP-43G298S caused locomotor defects as indicated by increased larval turning time compared to controls  versus a regular sugar (RS) diet . However, when using the Mantel-Cox test, which weighs earlier deaths more significantly, we found that GLUT-3 overexpression increases lifespan when TDP-43G298S is expressed in glial cells . GLUT-3 had no effect on lifespan when TDP-43WT was expressed in either motor neurons or glia. Importantly, GLUT-3 overexpression had no effect on TDP-43 suggesting that its protective effect occurs through a mechanism independent of TDP-43 levels  caused by neuronal expression of TDP-43. These defects include a reduction in synaptic bouton number  and TDP-43G298S  expressing larvae . Taken together, these results show that GLUT-3 expression in motor neurons mitigates morphological and functional defects caused by TDP-43 at the NMJ and suggest that increased glucose availability in motor neurons is neuroprotective in ALS.We previously described defects at the n number  and a ren number . To testg larvae . MoreovePFK levels in conjunction with our findings that increased glucose availability is protective suggest that increased glycolysis may be compensatory. To test this hypothesis, we directly manipulated glycolysis genetically, either via PFK overexpression or RNAi knock-down, in the context of TDP-43 proteinopathy. Overexpression of PFK alone in motor neurons negatively altered locomotor activity suggesting that in normal neurons high glycolytic activity may be toxic . However, when PFK was knocked down by RNAi in the context of TDP-43 proteinopathy we found that it significantly increased larval turning times for TDP-43WT albeit it had no effect on TDP-43G298S  sc[*] v(1) P{y[+t7.7] v[+t1.8]=TRiP.HMS01324}attP2) was tested, but was lethal when expressed in motor neurons.Increased be toxic . HoweverPFK in glial cells causes a locomotor defect, while the expression of two independent PFK RNAi lines has no effect on locomotor activity as determined by larval turning assays  while it significantly mitigates TDP-43G298S , which mitigates locomotor defects and increases lifespan in ALS flies while making wild-type larvae sluggish , and (4) lactate export, but not other enzymes or steps involved in glycolysis . Nevertheless, our findings of increased PFK mRNA levels in flies and human tissues, and the genetic interaction experiments support the notion that glycolysis is increased in ALS as a compensatory mechanism (see A possible explanation for why increased glucose availability improves defects caused by TDP-43 proteinopathy is that cells are actively consuming glucose to increase glycolytic flux. A recent study using vertebrate cell lines suggests that glycolytic flux depends on four key steps. They include: (1) glucose uptake by glucose transporters, (2) hexokinase levels, (3) ycolysis . The co-eriments . SurprisDrosophila  w1118; UAS-TDP43WT-YFP (iii) w1118; UAS-TDP43G29S8-YFP (iv) UAS-GLUT3 flies were crossed with the GAL4 motor neuron driver D42. GLUT3 TDP-43 recombinant flies were generated using standard genetic techniques. GLUT3 flies were described in Standard crosses were incubated at 25°C with a 12 hr alternating dark-light cycles. (i) w1118 was crossed with either the D42 or repo GAL4 drivers as a control. Endogenous TDP-43 was knocked down via RNAi using y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HMS01932}attP40 and y[1] v[1]; P{y[+t7.7] v[+t1.8]=TRiP.HM05194}attP2.TDP-43 was expressed in motor neurons and glia using the D42 GAL4  and repoPFK, we used w1118; P{w[+mC]=UAS Pfk.T}3 for over expression, and y1 sc* v1; P{y[+t7.7] v[+t1.8]=TRiP.HMS01324}attP2 or y1 sc* v1; P{y[+t7.7] v[+t1.8]=TRiP .GL00298}attP2  for PFK knock down. attP2 was used as a genetic background control for PFK RNAi knock-down experiments. All lines were obtained from the Bloomington Stock Center.To manipulate PFK RNAi efficiency was assayed by crossing PFK RNAi to D42 GAL4. Ventral nerve cords were dissected and analyzed via qPCR (see below for primers). A Welch's t-test was used to identify significance.Standard yeast/cornmeal/molasses food was heated and then allowed to cool to 55–60˚C. For high sugar supplementation, additional glucose was added to reach a final concentration of 357 g/L (10X compared to regular food). Supplemented food was dispensed into vials and allowed to cool.WT and TDP-43G298S flies were previously described in 2 and placed in a plastic column (diameter 1.3 cm) with a mark at 22 cm. After 20 min recovery, flies were gently tapped to the bottom of the column. Then the percentages of flies reaching the 22 cm mark or remaining at the bottom were counted after 60 s. The test was repeated three times and results were averaged. The data are the mean of at least six trials and are expressed as mean ± SEM. Statistical comparisons were performed using one-way ANOVA followed by Tukey’s multiple-comparison test.Larval turning assays were performed as previously described . BrieflyMetabolomic analysis was conducted by Metabolon, Inc as previously described . Brieflyrd instar larvae per genotype were analyzed in three biological replicates. Standard curve was generated kit provided reagents. Results are shown (Pyruvate was measured using the Pyruvate Assay Kit (Abcam-ab65342) as per manufacturer’s instructions. In brief, 20 3re shown  in nmole2, 10 mM NaHCO3, 5 mM trehalose, 115 mM sucrose, 5 mM HEPES, pH 7.3). RNA was extracted using the RNeasy RNA Extraction Kit (Qiagen) and stored at −80°C. Genomic DNA (gDNA) was cleared using a DNase I (Thermo Fisher Scientific) digestion protocol. Following gDNA clearing, reverse transcription was performed using the Maxima First Strand cDNA Synthesis Kit for RT-qPCR (Thermo Fisher Scientific). The quality of the cDNA was tested using GPDH primers (see below for sequence) and GoTaq endpoint polymerase chain reaction (PCR) protocol (Promega). Quantitative PCR was performed using a SYBR Green protocol (Applied Biosystems) and primers designed to span exon-exon junctions. Each reaction was conducted in 3–6 biological replicates with three technical replicates each. ΔΔCT values are normalized to GPDH : Forward primer - TGGACGAGCTGGTCAAGAAC; Reverse primer - CCACAAGAGCTAAATAGCCGDrosophila G6PD (Zw): Forward primer - AAGCGCCGCAACTCTTTG; Reverse primer - AGGGCGGTGTGATCTTCCDrosophila GPDH: Forward primer - CCGCAGTGCTTGTTTTGCT; Reverse primer – TATGGCCGAACCCCAGTTGPhosphofructokinase P (PFKP): Assay ID Hs00242993_m1Human Phosphofructokinase M (PFKM): Assay ID Hs00175997_m1Human G6PD: Assay ID Hs00166169_m1Human Human GAPDH: Assay ID Hs99999905_m1Third instar larval brains where dissected in HL3-buffer . Of note, the glucose sensor is not sensitive to trehalose . Larvae Fluorescent images were acquired using a Zeiss LSM880 NLO upright multiphoton/confocal microscope. CFP was excited using a 405 nm laser, and images were acquired in both the CFP (CFP 465–499 nm) and the FRET (535–695 nm) detection channels.Data was analyzed using ImageJ with a drift correction plugin turboreg . RegionsEach ROI was imaged every 10 s for 10 min (baseline) and then for another 10 min under high glucose HL-3  at 1:1000 for  or the TLarvae are dissected in HL-3 buffer on a sylgard dish as previously described. FM1-43 dye uptake assays were conducted using 4 μM FM1-43FX, 90 mM KCl, and 2 mM Ca2+ for stimulation. Methods adapted from 2HPO4, 5 mM NaH2PO4) for 30 min. Antibody dilutions are as follows: 1:300 mouse anti-DCSP2 (DSHB), 1:500 anti-mouse Alexa Fluor 568 (Invitrogen), 1:200 Anti-HRP-CY5 conjugate (Invitrogen), and 1:40 Phalloidin-488 (Invitrogen). Blocking solution contained 2% BSA and 5% Normal goat serum. Methods have been previously described in Larval NMJs were dissected and fixed with 3.5% paraformaldehyde in PBS . NIH ImageJ was used to count bouton numbers and measure muscle area. Bouton count was normalized to muscle area to account for size variation.Control iPSC and TDP-43 iPSC cells were differentiated to motor neurons as previously described .To generate cellular fractions, 25 Third instar wandering larvae were flash frozen, followed by homogenization in Trizolreagent using the Bullet Blender Bead Lysis Kit Green in conjunction with a Bullet Blender Blue 24. Homogenates were then centrifuged at 2000 x g for 3 min. The supernatant was separated from both the fat layer and the beads then it was further centrifuged at 25,000 g for 30 min. The resulting supernatant is the soluble fraction and the insoluble fraction is generated by resuspending the pellet in urea buffer , 0.5 mM PMSF, 40 units/μl RNAsin plus, pH 8.5). RNA was isolated from inputs and the cellular fractions utilizing the manufactured described protocol for Trizol reagent. cDNA was then generated utilizing Thermoscientific Maxima First Strand cDNA Synthesis Kit for RT-qPCR. RT-qPCR was conducted on the StepOnePlus RT-qPCR machine utilizing Sybr reagents.All statistical analyses for locomotor assays or qPCR comprising three or more data sets were conducted using Kruskal-Wallis with uncorrected Dunn’s test in Prism v8.0 (GraphPad). When only two data sets were compared, either Welch’s test or Wilcoxon signed-rank test were used. Biological replicates for qPCR and metabolomics are defined as independent sample collections per genotype, from independent genetic crosses. All qPCR experiments included three technical replicates per biological replicate. Outliers were removed using ROUT method (Q = 1%) in Prism v8.0. In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.Thank you for submitting your article "Glycolysis upregulation is neuroprotective as a compensatory mechanism in ALS" for consideration by eLife. Your article has been reviewed by three peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by K VijayRaghavan as the Senior Editor. The reviewers have opted to remain anonymous.The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:Drosophila models of TDP-43 mediated pathogenesis, data are presented in support of the concept that enhancing glycolysis is neuroprotective. In addition to using a fly model, the investigators do provide data that supporting alterations in glycolysis in ALS patient tissue and iPSC-derived motor neurons.Alteration of cellular energetic metabolism in neurodegenerative disease is an area of considerable interest. In this very strong study, largely using Essential revisions:1) Show quantification of gene and protein expression in the experiments where these controls are missing. Reviewers noted this is important to clarify that phenotypes reflect actions of mutant TDP-43 and not simply TDP-43 overexpression.2) Add additional iPScs (to the extent possible – try to find one or two more cells lines) or increase number of experiments (replicates) in patients-derived cells- at least to account for batch to batch variation.3) Provide evidence that the fly models used have TDP-43 pathology (proteinopathies) using IF and western blots. Essential revisions:1) Show quantification of gene and protein expression in the experiments where these controls are missing.We understand this comment as a question of whether mitigating conditions such as GLUT3 or PFK overexpression (OE) exert their action by altering TDP-43 levels. We now include western blot data for both GLUT3 and PFK OE showing that TDP-43 levels are unchanged in the context of either GLUT3 or PFK OE in motor neurons . Therefore the mitigating effects on TDP-43 toxicity observed with GLUT3 and PFK OE likely occur through increased glucose availability and upregulated glycolysis, respectively, and not by altering TDP-43 expression.Reviewers noted this is important to clarify that phenotypes reflect actions of mutant TDP-43 and not simply TDP-43 overexpression.We thank the reviewers for bringing up this important issue about TDP-43 models of proteinopathy. While overexpression of either WT or disease associated G298S causes similar phenotypes at the “whole organism level”, it is important to note that mechanistically, the two variants cause disease using distinct pathways. We have emphasized this issue in the text in several places throughout the Results and Discussion sections.2) Add additional iPScs (to the extent possible – try to find one or two more cells lines) or increase number of experiments (replicates) in patients-derived cells- at least to account for batch to batch variation.We very much agree with this important point and were able to add a third differentiation to our iPSC experiments. All transcripts tested are now significantly altered . We were unable to obtain additional mutant TDP-43 mutant lines from ALS patients. This reflects the low frequency of TDP-43 mutations found in the patient population.3) Provide evidence that the fly models used have TDP-43 pathology (proteinopathies) using IF and western blots.We have previously showed using cellular fractionations and immunofluorescence that TDP-43 overexpression causes insolubilization of TDP-43  and specific mRNAs .


Fluorescence microscopy and spectroscopy were applied for studying the optical properties of a hybrid nanostructure, in which we combine plasmon-induced metal enhanced fluorescence with energy transfer to epitaxial graphene. Covering the layer of silver islands with a monolayer graphene, while turning on the efficient energy transfer from emitters, only moderately affects the enhancement of fluorescence attributed to the plasmon resonance in metallic nanostructures—as evidenced by the analysis of fluorescence decays. The results show that it is feasible to combine the properties of graphene with metal-enhanced fluorescence. The importance of the layer thickness of the emitters is also pointed out. At the nanoscale, bringing two or more nanostructures close together may frequently lead to interactions between them, which in turn induce modifications in the properties of such fabricated hybrid structures . By propThe MEF effect is a process, in which the fluorescence intensity of an emitter is increased via interactions with plasmonic excitations in metallic nanoparticles placed in its vicinity ,4,5. A sPlasmonically active metallic nanostructures can be either based on nanoparticles, synthesized chemically , or plan−4 [On the other hand, the FRET process is associated with transferring the energy between two nanostructures . This no−4 , as conf−4 . Is has −4 ,18.In this work, we study the interplay between MEF and FRET effects in a hybrid nanostructure composed of SIF covered with graphene, on top of which a layer of emitters was deposited. Fluorescence microscopy and spectroscopy allowed us to conclude that covering the plasmonically active layer with graphene is not inhibiting the MEF effect. At the same time, we find an increase in inhomogeneity of fluorescence intensity for graphene-covered SIF layers with a partial correlation between the intensity and fluorescence decays.Silver Island Films were deposited on glass coverslips by reducing silver nitrate with D-glucose, using the protocol described previously . The morAs graphene material, we used Single-Double layer CVD . graphene (SDG) grown on a copper foil, these substrates were purchased from Graphene Supermarket . These graphene structures are characterized by having over 70% of the surface of monolayer graphene, with the rest being a bilayer structure. To transfer graphene on either glass or SIF substrate, we used an approach based on Polymer-Assisted-Transfer method described in . As a haAmphidinium carterae. In its native form PCP is a trimer and its structure was determined using X-ray crystallography [a molecule. All pigments are embedded in a protein matrix, which shields the pigments from the environment. PCP has broad absorption, spanning from 400 to 650 nm, which strongly overlaps with the plasmon resonance of SIF [As a fluorescence probe, Peridinin-Chlorophyll-Protein (PCP) photosynthetic complex was used. It is a simple light-harvesting, water-soluble complex from lography . In thise of SIF . The emie of SIF  and grape of SIF , where, Fluorescence intensity maps were measured using Nikon Eclipse Ti-U  inverted wide-field fluorescence microscope equipped with LED illuminators and Andor iXon Du-888 EMCCD camera . Excitation beam from a LED illuminator, giving the excitation wavelength of 480 nm, was directed by a dichroic mirror T650lpxr  to a microscope objective . In order to avoid issues associated with limited absorption of both graphene and SIF, the experiments were carried out without immersion oil, and the samples were illuminated from the side of the PCP layer. The PCP fluorescence was detected by the same objective and filtered using a combination of FEL650 edge  and ET675/20 bandpass (Chroma) filters. Fluorescence intensity maps with sizes of 90 × 90 µm were measured with typical parameters of electron multiplying gain and an acquisition time of 1000 and 1 s, respectively. In order to assure for sufficient statistics, for each structure 20 fluorescence maps were measured on different locations across the sample. Time and spectrally-resolved measurements were performed using a home-built scanning confocal fluorescence microscope. For excitation of PCP emission we used a 485 nm laser with a repetition rate of 20 MHz and power of 1 µW. The excitation beam was focused on the sample using a microscope objective . The same objective was used to collect the fluorescence signal, which was then directed through a confocal aperture and an edge HQ655LP filter (Chroma) to our detection system. First, for each of the three structures, a fluorescence map was collected, by correlating the movement of a piezoelectric stage with signal readout from SPCM-AQRH-16 avalanche photodiode . For measuring fluorescence intensity maps we used an additional bandpass filter ET675/20 (Chroma). In the next step a series of fluorescence decay curves were acquired for approximately 100 spots across the map with time-correlated single photon counting module  and the same combination of optical filters. Detection was provided by a fast avalanche photodiode  Finally, fluorescence spectra were collected with Andor iDus DV 420A-BV CCD camera coupled with an Amici prism. In this way, complete information about the optical properties of fabricated hybrid nanostructures can be obtained, and the effects of both metal-enhanced fluorescence and energy transfer can be elucidated. In While the results obtained for a single map  equal, approximately, to the average decay time measured for PCP on glass substrate (1) and is consistent with previously reported results [In ubstrate a,b. It i results . While t results , it is rThe results of fluorescence dynamics studies are summarized in We assembled a hybrid nanostructure, which combined the benefits of plasmonic properties characteristic for metallic nanostructures, with unique behavior of graphene as an energy acceptor. The interplay between metal-enhanced fluorescence and fluorescence resonant energy transfer is demonstrated by fluorescence imaging and time-resolved spectroscopy. While the decay time of emitters deposited on SDG@SIF is shorter than for the SIF structure, the intensity decrease is moderate, indicating that the plasmon interactions is still affecting the optical properties of the emitters. This result opens way of exploiting the unique properties of graphene, and also in the context of plasmonically active metallic nanostructures.


Viewing the trend of miniaturization and integration in modern electronic device design, a reconfigurable multi-functional graphene-based metasurface is proposed in this paper. By virtue of the reconfigurability of reflection patterns, this metasurface is able to independently manipulate orthogonal linearly polarized terahertz wave. The building blocks of the proposed metasurface are series of graphene-strips-based unit-cells. Each unit-cell consists of two orthogonal graphene strips and a grounded substrate, which has anisotropic responses for each of orthogonal polarizations (x-polarized and y-polarized waves). The reflection phases of both x- and y-polarized waves can be controlled independently through separate electrical tuning. Based on the proposed metasurface, functionalities including beam splitting, beam deflecting, and linear-to-circular polarization converting using a shared aperture are numerically demonstrated and analyzed. Simulation results demonstrate excellent performance, which is consistent with the theorized expectations. This work paves the way for enhancing the miniaturization of modern electronic/optical devices and potentially has important applications in the next-generation information systems for communication, sensing, and imaging. Metasurface, a two-dimensional 2D) equivalence of metamaterial, has been proposed as an effective way to arbitrarily manipulate amplitude, phase, and polarization of electromagnetic (EM) waves. Recently, many novel metasurface-based devices  have beeD equivalRecently, graphene, a monolayer of carbon atoms, arranged in a honeycomb lattice , has draIn this paper, a reconfigurable multi-functional graphene-based metasurface is proposed, for the effect of greatly increasing the degree of miniaturization and integration of modern electronic devices. By virtue of the reconfigurability of reflected patterns, the proposed graphene-based metasurface can independently manipulate orthogonal linearly polarized terahertz waves. The building blocks of the proposed metasurface are series of graphene-strips-based unit-cells. Each unit-cell consists of two orthogonal graphene strips and a grounded substrate, which has anisotropic responses for each of orthogonal polarizations (x-polarized and y-polarized waves). The normal incident waves can be entirely reflected by the metal-grounded plane on the bottom of the metasurface and the reflection phases of both x- and y-polarized waves are controlled independently via separate electrical tuning. Based on the proposed design, four kinds of functionalities using a shared aperture are numerically demonstrated and analyzed for polarization beam splitting, beam deflection, and linear-to-circular polarization conversion with a deflection angle.x and y directions, as shown in p = 14 x direction, corresponding to the variation of parameter y direction, corresponding to the variation of parameter y direction. Thus, considering the impedance controlling capability of graphene through chemical potential tunning, we can equivalently change these geometrical parameters by tunning the chemical potential of the graphene strips. Concretely, we use chemical potential Electromagnetic waves in THz frequencies can excite prominent plasmonic resonances in graphene. But for the purpose of practical application, these wave-graphene interactions need to be further enhanced. Therefore, using the Fabry–Perot resonant principle , we desious work , paramett and d represent the thickness of SiOd = 25 t = 10 nm, respectively. The bottom metallic material is selected as Au. Importantly, we use the impedance boundary condition of HFSS to characterize the graphene strip, and the surface impedance of the graphene strip is represented as ℏ is the reduced Planck’s constant. T is temperature, In order to obtain better understanding of the proposed unit-cell, detailed analytical methods such as multi-layer , transmiδ=0.0184 . The thide model (1)σ=qe2ications . Furtherications ,36, whicu represents z axial, respectively. The coverage of z axial. Similar, the x axial, respectively, and the coverage of Based on the proposed reconfigurable unit-cell of graphene-based metasurface, we can realize multi-functional applications. Here, four functions are integrated into a shared metasurface aperture. For convenience of expression, F1, F2, F3, and F4 are named for these four different functions, respectively. F1 and F2 are the two similar functions of beam splitting, F3 is the function of beam deflecting, and F4 is the function of linear-to-circular polarization converting, respectively. All these four functions are realized by using a shared aperture with different reflection phase distributions. Phase distributions can be calculated by generalized Snell laws of reflection .(2)ΔΦu. The reflection phases of both x- and y-polarized waves can be controlled independently through separate electrical tuning. Based on the proposed metasurface, functionalities including beam splitting, beam deflection, and linear-to-circular polarization converting using a shared aperture are numerically demonstrated and analyzed. Simulation results demonstrate excellent performance, which is consistent with the theorized expectations. It is worth emphasizing here that, taking into account of the practical fabrication, we can easily fabricate the graphene-based unit-cell which consists of 5 layers, including a graphene-strip layer, an alumina layer, a polysilicon layer, a quartz glasses layer, and a ground plate. The polysilicon can be utilized as an electrode. The surface complex impedance of graphene-patch can be dynamically controlled by varying the DC voltage (VDC) between the graphene-patch and the polysilicon. Concrete procedure to fabricate these kinds of graphene-based metasurface can be found in Ref. , support


Monolithic epoxy, because of its brittleness, cannot prevent crack propagation and is vulnerable to fracture. However, it is well established that when reinforced—especially by nano-fillers, such as metallic oxides, clays, carbon nanotubes, and other carbonaceous materials—its ability to withstand crack propagation is propitiously improved. Among various nano-fillers, graphene has recently been employed as reinforcement in epoxy to enhance the fracture related properties of the produced epoxy–graphene nanocomposites. In this review, mechanical, thermal, and electrical properties of graphene reinforced epoxy nanocomposites will be correlated with the topographical features, morphology, weight fraction, dispersion state, and surface functionalization of graphene. The factors in which contrasting results were reported in the literature are highlighted, such as the influence of graphene on the mechanical properties of epoxy nanocomposites. Furthermore, the challenges to achieving the desired performance of polymer nanocomposites are also suggested throughout the article. Polymer Matrix Composites (PMCs) have found extensive applications in aerospace, automotive, and construction, owing to ease of processing and high strength-to-weight ratio, which is an important property required for aerospace applications . Among dTo summarize the research trends related to graphene-based nanocomposites, multiple review articles were recently published in which various aspects of graphene-based nanocomposites were discussed. There are numerous ways to produce and characterize graphene-based materials . GraphenTo date, eclectic reviews on graphene composites are covering a broad range of graphene-related issues; it can, however, be observed that there is an obvious gap in the lack of a review article discussing the mechanical, thermal, and electrical properties of epoxy–graphene nanocomposites. Therefore, this review article discusses the correlation between graphene structure, morphology, weight fraction, dispersion, surface modifications, and the corresponding mechanical, thermal, and electrical properties of epoxy–graphene nanocomposites.There are various types of epoxy which have a wide range of applications because of their superior attributes, such as improvement in composite mechanical properties, acceptable cost, and processing flexibility . PhenoliEpoxy resins are of particular interest to structural engineers because these resins provide a unique balance of chemical and mechanical properties combined with extreme processing versatility . When a Graphene—a densely packed honey-comb crystal lattice made of carbon atoms having a thickness equal to the atomic size of one carbon atom—has revolutionized the scientific parlance due to its exceptional physical, electrical, and chemical properties. The graphene now found in various applications was previously considered only a research material and a theoretical model to describe the properties of other carbonaceous materials such as fullerenes, graphite, Single-Walled Carbon Nanotubes (SWNTs), and Multi-Walled Carbon Nanotubes (MWNTs). It was believed that the real existence of stand-alone single layer graphene would not be possible because of thermal fluctuations, as the stability of long-range crystalline order found in graphene was considered impossible at finite (room) temperatures. This perception was turned into belief by experiments when the stability of thin films was found to have direct relation with the film thickness; i.e., film stability decreases with a decrease in film thickness . HoweverThe ability of a material to resist the propagation of an advancing crack is vital to the prevention of failure/fracture . GraphenThe successful employment of epoxy-based nanocomposites relies on the ability of the composite system to meet design and service requirements. The epoxy-based nanocomposites have found applications in aerospace, automotive, and construction due to ease of processing and high strength-to-weight ratio. In many applications, the composite system undergoes external loadings. The relationship between loads acting on a system and the response of the system towards the applied loads is studied in terms of mechanical properties. Therefore, epoxy-based nanocomposites are supposed to have superior mechanical properties. There are various tests to measure mechanical properties, such as tensile testing, bend testing, creep testing, fatigue testing, and hardness testing, to name a few. These tests usually take specimens of specific geometries and subject to loading at certain rate. In general, the industrial scale samples contain porosity and notches which act as stress concentrators and are deleterious to the mechanical properties of nanocomposites. Sometimes, it becomes difficult to control the maximum flaw size. The shape of the flaw is another very important parameter, as pointed notch (V-notch) is more detrimental than round notch (U-shaped) .Due to the pronounced effect of defects on nanocomposite properties, it is important to understand how a system will tolerate external loading in the presence of a flaw under operating conditions, and how a system will resist the propagation of cracks from these flaws. Therefore, how the material will behave in reality will only be determined when the test specimen contains possible flaws, such as a notch. To deal with this issue in a pragmatic way, an intentional notch is produced in the specimen, and resistance to fracture is measured and is termed fracture toughness. Different specimens are used for fracture toughness, such as notched tension, three-point bending, and compact tension specimen, as shown in K1C). Impact loading methods, such as Charpy and Izod impact tests, are also used to determine impact fracture toughness. Fracture toughness values obtained through different techniques cannot be directly compared [Some of the fracture toughness tests include double torsion, indentation, double cantilever tests, and Chevron notch method. Chevron notch method is popular, as it uses a relatively small amount of material and no material constants are needed for the calculations. The technique is also suitable for high-temperature testing, as flaw healing is not a concern. However, it requires a complex specimen shape that incurs an extra machining cost. The most commonly used specimen is a single-edge notched beam subjected to three or four-point bending. Unfortunately, it has been reported that the results of this test are very sensitive to the notch width and depth. Therefore, a pre-notched or molded beam is preferred. As polymers and polymer nanocomposites can be molded into a desired shape, a specific kind of notch can be replicated in multiple specimens. Due to the reproducibility of notch dimensions, the single-edge notched beam test can give reproducible values of fracture toughness in polymers and polymer nanocomposites. These are the reasons that most of the literature published on polymers and polymer nanocomposites used single-edge notch beams (subjected to three-point bend loading) to determine fracture toughness values , the energy required for fracture is simply the intrinsic surface energy of the materials, as demonstrated by Griffith . For strK1C) can be calculated for a single-edge notched three-point bending specimen using Equation (1), where Pmax is the maximum load of the load–displacement curve (N), f(a/w) is a constant related to the geometry of the sample and is calculated using Equation (2), B is sample thickness (mm), W is sample width (mm), and a is crack length  [G1C) can be calculated using Equation (3), where E is the Young’s modulus obtained from the tensile tests (MPa), and ν is the Poisson’s ratio of the polymer. The geometric function f(a/W) strongly depends on the a/W ratio [Toughness is defined as the ability of a material to absorb energy before fracture takes place. It is usually characterized by the area under a stress–strain curve for a smooth (un-notched) tension specimen loaded slowly to fracture. The term fracture toughness is usually associated with the fracture mechanics methods that deal with the effect of defects on the load-bearing capacity of structural components. The fracture toughness of materials is of great significance in engineering design because of the high probability of flaws being present. Defined another way, it is the critical stress intensity at which final fracture occurs. The plane strain fracture toughness  . The cri/W ratio .The fracture toughness is dependent on many factors, such as type of loading and environment in which the system will be loaded . However2 bonding, which is much stronger than the sp3 bonding found in diamond [2 orbital hybridization between Px and Py that forms a σ-bond [Pz forms a π-bond with half-filled band that allows free motion of electrons. When bombarded with pure carbon atoms, hydrocarbons, or other carbon-containing molecules, the graphene directs the carbon atoms into vacant seats, thereby self-repairing the holes in the graphene sheet. Through their crack deflection modeling, Faber and Evans showed that maximum improvement in fracture toughness, among all other nano-reinforcements, can be obtained using graphene—mainly because of its better capability of deflecting the propagating cracks [Graphene has a honeycomb lattice having sp diamond . There ia σ-bond . The orbg cracks ,100.As graphene is a 2D structure, each carbon atom can undergo chemical reaction from the sides, resulting in high chemical reactivity. The carbon atoms on the edge of graphene sheet have three incomplete bonds (in single layer graphene) that impart especially high chemical reactivity to edge carbon atoms. In addition, defects within a graphene sheet are high energy sites and preferable sites for chemical reactants. All these factors make graphene a very highly chemical reactive entity. The graphene oxide can be reduced by using Al particles and potassium hydroxide . The graν is Poisson’s ratio, L is graphene sheet size, t is thickness of graphene sheet, ε is edge contraction on a suspended graphene sheet, and A is wrinkle amplitude [Wrinkling is a large and out-of-plane deflection caused by compression (in-plane) or shear. Wrinkling is usually found in thin and flexible materials, such as cloth fabric . Graphenmplitude .Palmeri et al. showed that the graphene sheets have a coiled structure that helps them to store a sufficient amount of energy . The indK1C strongly depends upon the surface area of the reinforcement, as it influences the matrix–reinforcement interfacial interactions. When the reinforcement has a large surface area, the interfacial area increases, which increases the number of routes for the transport of load from matrix to reinforcement [w × t = 1 µm × 0.1 µm × 10 nm. The density of both short carbon fiber and graphene is taken to be 2.26 to make comparison based on dimensions only. The surface area of 1 g of carbon fibers is 19 m2 and that of graphene is 98 m2. It can be observed that although the lengths of both reinforcements are the same and the width of graphene is equal to the diameter of a short carbon fiber, there is a large difference in surface areas when the thickness of graphene is kept 10 nm. This difference will further increase if graphene dimensions are reduced. The specific surface area of graphene is as high as 2600 m2/g [orcement . On the orcement . One reaorcement . The surorcement . To make600 m2/g ,112. It 600 m2/g ,114. The600 m2/g ,116. The600 m2/g .Zhao and Hoa used a theoretical computer simulation approach to study the improvement in toughness when epoxy is reinforced with 2D nano-reinforcements of different particle size ,119. TheThe relationship between graphene size and stress concentration factor can be correlated with the facile analogy of substitutional solid solution. The extent of strain field produced by a foreign atom depends upon the difference in atomic sizes of the foreign and parent atoms. When there is a large difference between foreign and parent atoms, a large strain field around the atom is generated. On the contrary, when the difference in atomic sizes of parent and foreign atoms is small, the strain field is limited. As both atomic and GNPs sizes are in the nano-meter range, the analogy can arguably be applied to an epoxy–graphene system where large sheet size will cause higher stress concentration factor than that produced by small sheet size. Therefore, graphene with smaller sheet size can be more efficient in improving the fracture toughness than the larger graphene sheets.The increase in the fracture toughness of epoxy was found to be strongly dependent upon the graphene sheet size . For theK1C values dropped when weight fraction was increased beyond 0.1 wt %. This decrease in K1C with increasing weight fraction can be correlated with crack generation and dispersion state.Wang et al. used Graphene Oxide (GO) of three different sizes, namely GO-1, GO-2, GO-3, having average diameters 10.79, 1.72, and 0.70 µm, respectively, to produce nanocomposites using an epoxy matrix . They obK1C first increases with GO and then starts decreasing in all three of the cases. The increase in K1C is due to the reinforcing effect of GO, while the drop in K1C is due to crack generation and agglomeration. The addition of a high GO weight fraction generates cracks that reduce the fracture toughness of the nanocomposite [The omposite . The othomposite .K1C was achieved for different epoxy–graphene nanocomposites are shown in K1C values were achieved at or below 1 wt % of graphene, and K1C dropped when the weight fraction of graphene was raised beyond 1 wt %. The decrease in K1C with a higher weight fraction of graphene can be correlated with the dispersion state of graphene. As graphene weight fraction increases beyond 1 wt %, the dispersion state becomes inferior. The maximum increase in K1C was 131%, which is achieved at 1 wt % graphene [K1C improvement up to 131%, which is the maximum among the improvements in K1C values reported in epoxy–graphene nanocomposites.The weight fractions of reinforcements at which maximum graphene . However1C is achieved. In addition, the increase in K1C at fixed GNP wt % is not the same. For example, at 0.5 wt %, the % increase in K1C is reported to be up to 45% by Chandrasekaran et al. [K1C was observed when dispersion was carried out with only sonication, and a higher improvement in K1C was observed when sonication was assisted with a secondary dispersion method, especially mechanical stirring.It can be observed from n et al. , and abon et al. . TherefoK1C, while the poorly dispersed RGO-epoxy showed only a 24% improvement in K1C. It shows that better dispersion of graphene can significantly improve the fracture toughness of epoxy nanocomposites [The end product of most of the graphene synthesis methods is agglomerated graphene . In addimposites .K1C as a function of dispersion mode is shown in K1C values were significantly increased. The maximum improvement of 131% in K1C was achieved when a combination of sonication and mechanical stirring was employed [K1C was achieved with a combination of sonication and magnetic stirring, an increase in K1C of 109% [K1C improvements are achieved when sonication is coupled with ball milling [K1C was not achieved. Although three roll milling  is an efficient way of dispersing the reinforcement into the polymer matrix due to high shear forces, the maximum improvement in K1C using three roll mill was reported as 86% [Several dispersion modes to disperse reinforcement into epoxy matrix were successfully adopted .Achieving maximum improvement in fracture toughness of polymers by using graphene depends on the ability to optimize the dispersibility of graphene and the interfacial interactions with the epoxy matrix. As described previously, graphene tends to agglomerate due to the weak Van der Waals interactions, and its smoother surface texture inhibits strong interfacial interactions. To tackle the limited dispersibility and interfacial bonding of graphene, surface modifications are carried out ,138,139.3, H2SO4, or their mixture, or strong oxidants including KMnO4, ozone, and reactive plasma [In chemical functionalization, chemical entities are typically attached covalently. For example, in defect functionalization, functional groups are attached at the defect sites of graphene, such as –COOH (carboxylic acid) and –OH (hydroxyl) groups. Defects can be any departure from regularity, including pentagons and heptagons in the hexagonal structure of graphene. Defects may also be produced by reaction with strong acids such as HNOe plasma . The fune plasma . Unlike e plasma . Surfacte plasma .K1C values with corresponding improvements (%) in K1C values are shown in The different functionalization methods adopted to study their influence on In thermosetting materials, such as epoxy, high crosslink density is desirable for the improvement of mechanical properties. However, high crosslink density has a detrimental effect on fracture toughness . TherefoTg; (2) the reactive fillers could lower the crosslinking density of epoxy, which should decrease Tg. An increase in Tg shows that interfacial interactions dominate the crosslinking density effect [The graphene affects the crosslink density of epoxy . When gry effect .Monolithic epoxy exhibits a bamboo-like brittle fracture pattern . However1C also improved with the incorporation of graphene in epoxy nanocomposites. Meng et al. produced epoxy–graphene nanocomposites and reported an increase in G1C of up to 597% [The literature shows an absence of consensus on the role of graphene in improving other mechanical properties of nanocomposites. Some authors reported significant improvement in the mechanical properties of nanocomposites reinforced with GNPs ,153,154. to 597% .Keff) of graphene-based polymer nanocomposites has a non-linear dependence on graphene weight fraction [Keff of graphene-based nanocomposites [Due to the superior thermal conductivity of graphene, graphene-based polymer nanocomposites are promising candidates for high-performance thermal interface materials . The disfraction ,177,178.mposites . Their mmposites ,181. The4% [Hu et al. used a molecular dynamics approach to show that the agglomeration of graphene is of major concern in increasing the thermal conductivity of the system . The var4% .Tailoring the electrical properties of graphene can unlock its many potential electronic applications ,195. ForEpoxy is an excellent matrix for graphene composites because of its efficient properties such as enhancement in composite mechanical properties, processing flexibility, and acceptable cost .Graphene can significantly enhance the fracture toughness of epoxy nanocomposites—i.e., up to 131% . When epThe graphene sheets with smaller length, width, and thickness are more efficient in improving the fracture toughness than those with larger dimensions . Large gUniformly dispersed graphene improves fracture toughness significantly as compared to the poorly dispersed graphene . It is eThree roll milling or calendering process is an efficient way of dispersing the reinforcement into a polymer matrix, as it involves high shear forces ,247,248.In thermosetting materials such as epoxy, high crosslink density is desirable for improved mechanical properties. However, fracture toughness is dropped with high crosslinking .The literature has proved the absence of consensus of graphene’s role in improving the mechanical properties of nanocomposites ,153,154.The following are the key points related to epoxy/graphene nanocomposites:


TARDBP, the gene encoding TDP-43, but also occurs in ALS/FTD patients without known genetic cause or in patients with various other ALS/FTD gene mutations. Mutations in progranulin (GRN), which result in a reduction of ~ 50% of progranulin protein (PGRN) levels, cause FTD with TDP-43 pathology. How loss of PGRN leads to TDP-43 pathology and whether or not PGRN expression protects against TDP-43-induced neurodegeneration is not yet clear.TAR DNA binding protein 43 (TDP-43) is the main disease protein in most patients with amyotrophic lateral sclerosis (ALS) and about 50% of patients with frontotemporal dementia (FTD). TDP-43 pathology is not restricted to patients with missense mutations in We studied the effect of PGRN on the neurodegenerative phenotype in TDP-43(A315T) mice.PGRN reduced the levels of insoluble TDP-43 and histology of the spinal cord revealed a protective effect of PGRN on the loss of large axon fibers in the lateral horn, the most severely affected fiber pool in this mouse model. Overexpression of PGRN significantly slowed down disease progression, extending the median survival by approximately 130 days. A transcriptome analysis did not point towards a single pathway affected by PGRN, but rather towards a pleiotropic effect on different pathways.Our findings reveal an important role of PGRN in attenuating mutant TDP-43-induced neurodegeneration.The online version of this article (10.1186/s13024-018-0288-y) contains supplementary material, which is available to authorized users. In FTD, neuronal loss in the frontal and anterior temporal lobes gives rise to behavioral changes and/or language impairments . In ALS,RN) gene –10. SuchRN) gene –13, alsoRN) gene  and genee in ALS .The preferential expression of PGRN in neurons and activated microglia points towards its most important functions in the central nervous system , 17. PGRHow shortage of PGRN causes TDP-43 pathology remains incompletely understood, but dysfunctional lysosomal degradation pathways with reduced clearance of TDP-43 could contribute to the accumulation of pathological TDP-43 species , 35.We previously showed that PGRN has neuroprotective effects in a zebrafish model of mutant TDP-43 induced motor neuron damage . HoweverGRN overexpressing mice were bred in a C57BL/6 J background and maintained as previously described [The TDP-43(A315T) and escribed , 39 and Iba1, TARDBP, Tardbp and Grn. Gene expression was normalized to the expression of three reference genes using SYBR Green reagents (Thermo Fisher Scientific) with the following primer pairs: adaptor-related protein complex 3, delta 1 subunit (Ap3d1) , MON2 homolog (Mon2)  and F-box protein 38 (Fbxo38) . Expression levels were analyzed using qBase+ .For qRT-PCR analysis, first-strand cDNA was synthesized using SuperScript III (Invitrogen). PCR reactions were performed using TaqMan assays  for Salmon (v0.8.1) [tximport function the R-package tximport (v1.6.0) [EdgeR (v3.20.5) [p-value (Benjamini and Hochberg method) was smaller than 0.05 and the absolute value of the log fold change (logFC) was larger or equal to 1. Genes were regarded as corrected by GRN overexpression, when the gene was differentially expressed between NTG and TDP-43(A315T) (FDR < 0.05 and |logFC| ≥ 1) mice but not differentially expressed between NTG and TDP-43(A315T)xGRN mice . Pathway analysis were performed using Ingenuity Pathway Analysis (QIAGEN). Gene set enrichment analysis (GSEA) on gene ontology (GO) terms was performed using the logFC values of the differential expression analysis and the R-packages gage (v2.28.0) and gageData_(v2.16.0).RNA sequencing was performed by the Nucleomics Core Facility . From extracted RNA, libraries were made using the Illumina TruSeq Stranded mRNA Library protocol. These libraries were sequenced on an Illumina HiSeq single-end 51 bp and an average of 19.3 million reads per sample (range 17.7–21.2). To estimate the expression of the transcript of every sample, reads were counted using (v0.8.1)  against (v1.6.0) . Differev3.20.5) . Genes wSpinal cords from mice of 200–240 days were fixed overnight in 4% glutaraldehyde in PBS (pH 7.4), washed with PBS and post-fixed for 2 h in 1% osmium tetroxide. Dehydration of the samples was performed using an ethanol gradient as follows: 15 min in 50%, 15 min in 70%, 15 min in 90% and 3 times 15 min in 100% ethanol. After a washing step in 100% propylene oxide , the samples were embedded using increasing ratios of TAAB medium  and propylene oxide: 1–2 h with a 1:2 ratio, overnight with a 1:1 ratio, 1–2 h with a 2:1 ratio and twice 2 h with 100% TAAB medium. The samples were subsequently baked for 72 h in a 60 °C oven before cutting 1 μm semi thin sections with a Reichert Ultracut microtome . Sections were stained 20 s with toluidine blue. Photographs of the lateral column of the spinal cord were taken with a Zeiss Imager.M1, using a 100X objective. To measure the average area of all axon fibers, a custom analysis macro was created in ImageJ  which was then applied to each image.Proteins were extracted from brain cortex samples using T-PER reagent (Sigma-Aldrich) supplemented with Complete™, EDTA-free protease inhibitor cocktail (Sigma-Aldrich). Protein concentrations were determined using the microBCA kit (Thermo Fisher Scientific) according to the manufacturer’s instructions. To study the insoluble protein fraction, equal amounts of protein extract were first centrifuged at 4 °C at maximum speed during 20 min. The obtained supernatant was used as the soluble fraction. The pellet was washed and gently vortexed with 1000 μl RIPA buffer (Sigma) containing cOmplete™ (Sigma), and PhosSTOP™ (Sigma). After a second centrifugation step the pellet was dissolved in sodium dodecyl sulfate (SDS) and used as the insoluble fraction.Reducing sample buffer (Thermo Fisher Scientific) was added to samples containing equal amounts of protein and heated for 5 min at 95 °C before separation on a sodium dodecyl sulfate–polyacrylamide electrophoresis gel. After electrophoresis, the proteins were transferred to a polyvinylidene difluoride membrane . Non-specific binding was blocked using 5% blotting-grade blocker , diluted in Tris-Buffered Saline Tween  for 1 h at room temperature before. Primary antibodies were incubated overnight at 4 °C, diluted in blocking-grade buffer and directed against TDP-43 , GAPDH  PGRN (1:200 R&D systems) and CTSD . HRP-coupled secondary antibodies , diluted in TBS-T, were incubated for 1 h at room temperature. Blots were visualized using the enhanced chemiluminescent substrate (Thermo Fisher Scientific) and imaged with an ImageQuant LAS 4000 system . Western blots were quantified using ImageQuant TL (v. 7.0). To quantify total TDP-43 levels, the sum of the intensities of the mTDP-43 band and the hTDP-43 band was used. CTSD activity measurements were performed using the CTSD activity assay kit (Abcam), following the manufacturer’s instructions.All statistical analyses were performed using GraphPad Prism , unless otherwise stated. Statistical tests used are indicated in the figure legends. Non-parametric testing was performed when the data was not normally distributed.GRN overexpression on TDP-43(A315T) induced neurodegeneration, TDP-43(A315T) mice, which express human mutant TDP-43 under the control of the prion promoter, were crossed with human GRN overexpressing mice, which carry a copy of human GRN cDNA in the ROSA26 locus resulting in human PGRN protein overexpression [To study the therapeutic potential of human pression . TDP-43 mice and PGRN overexpression did not influence the expression of these genes  transgene expression Fig.  and did 5T transgnes Fig. . OverexpTDP-43(A315T) mice do not display clear mislocalisation of TDP-43 or TDP-43 inclusions. However, accumulation of TDP-43 in the insoluble fraction was observed in TDP-43(A315T) mice, especially in the spinal cord  in this region was not affected by TDP-43(A315T) expression and was also not changed by PGRN overexpression  mice . The mosion Fig. . Howeverion Fig. .Fig. 4PGNext, the effect of PGRN was assessed on the clinical phenotype of TDP-435A315T) mice. The disease onset, as determined by the appearance of a swimming gait and the inability to lift up the lower part of the body from the ground, which is quite variable in this model, was not altered by PGRN overexpression Fig. . In contWith these results, we provide evidence for a protective effect of PGRN on TDP-43(A315T) induced neurodegeneration, as the increase in disease duration was accompanied by reduced insoluble TDP-43 levels and protection of large axon fibers in the spinal cord.n = 3 per group). The downregulation of endogenous mouse Tardbp in TDP-43(A315T) mice was confirmed and this was not altered by PGRN overexpression xGRN mice compared to endogenous mouse Grn was estimated to be 2.36 (95% CI 1.00–3.72) . Interestingly, using String DB, the proteins encoded by these 3 genes clustered in a protein-protein interaction network  and TDP-43(A315T)xGRN mice  is an interferon-inducible ER protein that functions as an innate immunity factor [PINK1 fibroblasts [Fbxo22 is a member of the ubiquitin ligase complex important for ubiquitination and degradation of proteins and also plays a role in macrophage activation [Topoisomerase II alfa (Top2a) catalyzes transient breaking and ligation of dsDNA during transcription and translation and has been involved in inflammation-induced DNA damage [Top2a and GRN are upregulated in glioblastomas [GRN overexpression was shown to protect against DNA damage induced by the Top2a inhibitor tomozolomide in glioblastoma cell lines [How PGRN specifically reduces insoluble TDP-43 levels and prevents TDP-43 mediated neurodegeneration requires further investigation. Of the 35 genes with differential expression in the mutant TDP-43 mice, PGRN corrected the levels of 7 of them. Some of these are indirectly connected to each other in a protein interaction network and can be linked to innate or adaptive immunity. roblasts . Finallytivation . TopoisoA damage . Apart fA damage , could blastomas , 52 and GRN haploinsufficiency [In addition, a direct neurotrophic effect of PGRN may occur without changes in gene expression. Neuroprotective effects of PGRN have also been observed in models of other brain disorders, suggesting that PGRN may have beneficial effects in various brain diseases not restricted to FTD with ficiency . PGRN trficiency , 55, Alzficiency  and stroficiency , 57 and Our data show that PGRN reduces insoluble TDP-43 levels, slows down axonal degeneration and prolongs survival in mutant TDP-43 mice. With our study, we add TDP-43 linked neurodegeneration to the list of disorders for which PGRN treatment could be beneficial.Additional file 1:Table S1. Results of the gene set enrichment analysis. Table S2. List of the 35 differentially expressed genes when comparing NTG controls to TDP-43(A315T) mice. Figure S1. PGRN overexpression does not affect endogenous PGRN or CTSD levels/activity. Figure S2. RNAseq results. Figure S3. Western blot of Rsad2. (A) Western blot for Rsad2 in brain and spinal cord lysates from NTG, TDP-43(A315T) and TDP-43(A315T)xGRN mice. (B) Quantification of Rsad2 bands from brain and spinal cord of NTG, TDP-43(A315T) and TDP-43(A315T)xGRN mice . (ZIP 1920 kb)