Academic literature on the topic 'PDMv2'

Background Deep medullary veins (DMVs) are a biomarker of severity and prognosis in patients with acute cerebral infarction. However, their clinical significance remains unclear in patients with transient ischemic attack (TIA). Purpose To determine whether prominent deep medullary veins (PDMVs) are a predictive biomarker for stroke risk after TIA. Material and Methods Clinical and imaging data of 49 patients with TIA and 49 sex- and age-matched controls were studied. PDMVs were defined as DMVs with a score of 3 (TDMVs) or asymmetric DMVs (ADMVs), and the relationship between PDMVs and clinical features was analyzed. The DMV score based on susceptibility weighted imaging (SWI) ranged from 0 (not visible) to 3 (very prominent) and was calculated for both hemispheres separately. A different score in each hemisphere was defined as ADMVs and an equal score was defined as symmetric DMVs. The asymmetry and score of DMVs were compared between the two groups and with respect to the time from TIA onset to imaging analysis. Results Agreement between neuroradiologists for the DMV asymmetry/score on SWI was excellent. The frequency of ADMVs and TDMVs was significantly higher in patients with TIA than controls ( P < 0.05). The patients showed no correlation between the time from TIA onset to imaging and the DMV asymmetry/score ( P > 0.05); PDMVs were not correlated with age, blood pressure, or diabetes. However, PDMVs were associated with the ABCD2 score (≥4), clinical symptoms, and duration of TIA (≥10 min). Conclusion Prominent deep medullary veins is a predictive biomarker for the risk of stroke in many patients having suffered from TIA.

AbstractElectron-donating 1,1,4,4-tetraarylbutadiene is a representative electrochromic dye, and the same chromophore can be found in 9,10-bis(diarylmethylene)-9,10-dihydrophenanthrene (dibenzo-oQD) albeit in a fixed s-cis geometry. Unlike thermodynamically unstable 7,7,8,8-tetraaryl-o-quinodimethane, spontaneous electrocyclization is prohibited by dibenzo-annulation. Several derivatives of dibenzo-oQD were successfully generated despite highly strained geometry caused by steric hindrance between the bulky diarylmethylene units. Their precursors are phenanthrene-9,10-diyl bis(diarylmethylium) dyes (PDM2+) stabilized by four electron-donating alkoxy groups. The redox pairs of dibenzo-oQD/PDM2+ exhibit vivid change in color upon redox interconversion (electrochromism). Both dibenzo-oQD and PDM2+ adopt a helical conformation, whose configuration is unstable. When a chiral alkoxy substituent is attached on each of the aryl groups, the point chirality is successfully transmitted to helicity of PDM2+. Resulting diastereomeric biasing is the key for dibenzo-oQD/PDM2+ to exhibit the two-way-output response (e.g., UV–vis and CD). In addition, much more strained quinodimethane derivatives, 1,2-bis(diarylmethylene)acenaphthene and 1,16-diaryldibenzo[b,n]perylene, were also generated from the dicationic precursors, demonstrating that the reductive transformation can serve as a useful protocol to generate severely deformed π-conjugated systems.

In a one group pretest-posttest design, 15 elite academy cricketers were exposed to two personal-disclosure mutual-sharing (PDMS) sessions during a preseason tour. Within PDMS1, athletes disclosed (via prepared speeches) relationship-oriented information and within PDMS2, mastery oriented information. Social identity, social identity content, and collective efficacy were measured at baseline (1 week before the tour), post-PDMS1, midpoint, and post-PDMS2, while social validation was also obtained after each intervention session. Quantitative data revealed significant increases in social identity and friendships identity content at post-PDMS1, and results identity content and collective efficacy at post-PDMS2. Qualitative social validation data highlighted the thoughts and feelings of the athletes before their speeches and supported the effectiveness of the PDMS sessions. In sum, the data suggest practitioners can develop team outcomes (e.g., a focus on results) through developing specific aspects of teams’ identities. Study limitations, practitioner guidelines, and areas for future research are discussed.

Amphiphilic copolymers are recognized as important biomaterials and used as antibacterial agents due to their effective inhibition of bacterial growth. In current study, the amphiphilic copolymers of P(DMAEMA-co-MMA) were synthesized using free radical polymerization by varying the concentrations of hydrophilic monomer 2-dimethylamino ethylmethacrylate (DMAEMA) and hydrophobic monomer methyl methacrylate (MMA) having PDI value of 1.65–1.93. The DMAEMA monomer, through ternary amine with antibacterial property optimized copolymers, P(DMAEMA-co-MMA), compositions to control biofilm adhesion. Antibacterial activity of synthesized copolymers was elucidated against Gram-positive Staphylococcus aureus (ATCC 6538) and Gram-negative Escherchia coli (ATCC 8739) by disk diffusion method, and zones of inhibition were measured. The desired composition that was PDM1 copolymer had shown good zones of inhibition i.e., 19 ± 0.33 mm and 20 ± 0.33 mm for E. coli and S. aureus respectively. The PDM1 and PDM2 have exhibited significant control over bacterial biofilm adhesion as tested by six well plate method. SEM study of bacterial biofilm formation has illustrated that these copolymers act in a similar fashion like cationic biocide. These compositions viz. PDM1 and PDM2, may be useful in development of bioreactors, sensors, surgical equipment and drug delivery devices.

Amphiphilic copolymers are recognized as important biomaterials and used as antibacterial agents due to their effective inhibition of bacterial growth. In current study, the amphiphilic copolymers of P(DMAEMA-co-MMA) were synthesized using free radical polymerization by varying the concentrations of hydrophilic monomer 2-dimethylamino ethylmethacrylate (DMAEMA) and hydrophobic monomer methyl methacrylate (MMA) having PDI value of 1.65–1.93. The DMAEMA monomer, through ternary amine with antibacterial property optimized copolymers, P(DMAEMA-co-MMA), compositions to control biofilm adhesion. Antibacterial activity of synthesized copolymers was elucidated against Gram-positive Staphylococcus aureus (ATCC 6538) and Gram-negative Escherchia coli (ATCC 8739) by disk diffusion method, and zones of inhibition were measured. The desired composition that was PDM1 copolymer had shown good zones of inhibition i.e., 19 ± 0.33 mm and 20 ± 0.33 mm for E. coli and S. aureus respectively. The PDM1 and PDM2 have exhibited significant control over bacterial biofilm adhesion as tested by six well plate method. SEM study of bacterial biofilm formation has illustrated that these copolymers act in a similar fashion like cationic biocide. These compositions viz. PDM1 and PDM2, may be useful in development of bioreactors, sensors, surgical equipment and drug delivery devices.

La evolución del islote de Langerhans, y dentro de éste del pool celular β desde la normalidad hasta la diabetes mellitus tipo 2 (DM2), pasa por diferentes momentos dentro de los que pueden observarse la hiperplasia adaptativa inicial a la insulinorresistencia y su posterior claudicación con una reducción de la masa celular mayor al 50%, aumento de las células α, fibrosis y aparición de depósitos amiloides1. Entre estos dos períodos, se detecta uno intermedio, correspondiente al que clínicamente se manifiesta como prediabetes (PDM2), en el que ya existen alteraciones en la dinámica de secreción normal de la insulina, con pérdida de su primer pico2.Para prevenir la progresión desde la PDM2 a la DM2, se plantean diferentes estrategias terapéuticas:• Monitorizar anualmente a estas personas ante el posible desarrollo de DM2 (E*).• Incorporarlas a programas de cambios en el estilo de vida (CEV) para lograr y mantener una pérdida del peso corporal de al menos el 7% (A).• Incorporarlas a rutinas de actividad física de al menos 150 minutos semanales de caminata enérgica (A).• Con planes de alimentación adecuados (B).• Utilizando programas de asistencia a través de aplicaciones (B).Dado su costo-efectividad (A), todos estos programas deberían ser costeados por el sistema de salud3.Se encontró que, aún sin pérdida de peso, 150 minutos semanales de actividad física (700 kcal/semana) redujeron la incidencia de DM2 en un 44%; también que, si bien un 7% de la pérdida de peso corporal es suficiente para disminuir la incidencia de DM2, los resultados son mejores reduciendo un 10%. Se estimó necesaria una pérdida de peso de entre 0,5 y 1 Kg/semana, con una restricción calórica de entre 500 y 1000 calorías/día, no habiendo un patrón definido respecto de la composición de la dieta para lograr este objetivo4.Dado que los CEV son difíciles de lograr o mantener, se puede considerar el uso de fármacos. Aquellos que demostraron efectividad en estudios aleatorizados prospectivos son: acarbosa, liraglutida, rosiglitazona, pioglitazona, glargina, orlistat, fentermina más topiramato y metformina.La metformina es la recomendada por la American Diabetes Association3 y ésta más acarbosa por la American Association of Clinical Endocrinologist and American College of Endocrinology sumando, de existir PDM2 con más de un criterio diagnóstico, TZD y/o a-GLP1. Debe tenerse en cuenta que, sumado a los CEV, con el objeto de disminuir el peso, se puede agregar medicación u otras terapias como la cirugía bariátrica5.* Nivel de evidencia

The Internet of Thing (IoT) has been one of the main focus areas of the research community in recent years, their peculiar requirements help net- work administrators to design and ensure the functionalities and resources of each device. Generally, two types of devices—constrained and uncon- strained devices—are typical in the IoT environment. Devices with limited resources—for example, sensors and actuators—are known as constrained de- vices. The unconstrained devices include gateways or border routers. Such devices are challenging in terms of their deployment because of their con- nectivity, channel selection, multiple interfaces, local and global address as- signment, address resolution, remote access, mobility, routing, border router scope, and security. To deal with these peculiar services, the availability of the IoT system ensures that the desired network services are available even in the presence of denial-of-service attacks, and the use of the system has become a difficult but mandatory task for network designers. To this end, I present a novel design for Wireless Sensor Networks (WSNs) which is the subsystem of IoTs, to address these challenges by shifting mandatory functionalities from unreliable to reliable and stable domains. Moreover, energy conservation is another aspect that is one of the main constraints and the traditional IPv6 Neighbor Discovery (IPv6-ND) is not designed nor suitable to cope with it. In spite of that, non-transitive wireless links and the use of heavy multicast transmission make it inefficient and sometimes impractical in a Low-Power and Lossy Network (LLN). Due to these peculiarities, significant work has been done by the Internet Engineering Task Force (IETF) to optimize IPv6-ND, known as IPv6 over Low power Wireless Personal Area Network - Neighbor Discovery (6LoWPAN-ND). The implementation of the 6LoWPAN-ND protocol in mesh-under works totally opposite to its main purpose because it reduces the multicast transmission but increases the unicast transmission in a drastic way. On the other hand, IPv6-ND works in a reactive way but the network resilience in terms of re- liability and robustness becomes questionable. Obtained results prove to answer a few questions. For example, is there a need for a 6LoWPAN-ND protocol for a given LLN or not? What would be the benefits or drawbacks if we utilize it? What will happen if we are not interested to adopt this protocol for LLNs and keep using the IPv6-ND protocol? All these questions addresses in terms of IoT resiliency. Another aspect is the availability of the application services and user privacy in IoT systems. Due to the drastic increase of IoT devices, increasing demand for application services with strict Quality of Service (QoS) requirements. Therefore, service providers are dealing with the functional integration of the classical cloud computing architecture with edge computing networks. However, considering the limited capacity of the edge nodes requires a proper virtual functions allotment to advance the user satisfaction and service perfection. However, demand prediction is crucial but essential in services management. High variability of application requests that result in inaccurate forecasts becomes a big challenge. The Federated learning methods provide a solution to train mathematical learning models at the end-user sites. Network functions virtualization leverages the IT virtualization technologies to virtualize entire classes of network node functions into building blocks that may connect, or chain together, to create and deliver communication services. To preserve the data security and maximize service provider revenue, I use the federated learning approach for the prediction of virtual functions demand in the Internet of Everything (IoE) based edge-cloud computing systems. Additionally, my work proposes a matching-based tasks allocation with some numerical results that validate the proposed approach by comparing it with a chaos theory prediction scheme. The services offered through IoT systems, much like any system on the Internet, must not only be studied and improved, they must be continuously monitored to ensure security and resilience. It is important to know what kind of services they provide, how they evolve, and what is the network performance? One of the most promising ways to enable continuous QoE monitor is to use a novel IPv6 extension header called Performance and Diagnostic Metrics (PDM) Destination Option header, defined in RFC8250. This IETF standard defines an optional header that is included in each packet to offer sequence numbers and timing information for measurement purposes. These measurements can be analyzed in real-time or later. Currently, PDM data is provided in clear text so malicious actors may be able to gather information for future assaults. The standard proposal, which is still being worked on, uses a lightweight handshake (registration procedure) and encryption to safeguard data. It also includes a list of additional performance measures that might be useful for further performance evaluation of IoT systems. My proposal uses the Internet Research Task Force (IRTF) Hybrid Public Key Encryption (HPKE) framework [23] to provide confidentiality and integrity to PDM data and is currently the candidate system to secure both PDMv2 [46] and Messaging Layer Security (MLS) [22].