We have fabricated pentacene organic thin-film transistor (OTFT) driven active matrix organic light-emitting diode (OLED) displays on flexible polyethylene terephthalete substrates. These displays have 48×48 bottom-emission OLED pixels with two pentacene OTFTs used per pixel. Parylene is used to isolate the OTFTs and OLEDs with good OTFT yield and uniformity.

Cyclotides are a family of plant peptides characterized by a cystine knot embedded in a macrocyclic backbone. They bind to and disrupt phospholipid membranes, which explain their lytic activity on cells. In this study, we expose the full antibacterial potency of cyclotides by avoiding its inhibition by rich growth media assay conditions. For that purpose a two-step microdilution assay protocol was developed, using non-growing conditions during initial peptide incubation. A diverse set of cyclotides was tested for antibacterial and antifungal activity, and the results show that most cyclotides are active under these conditions, especially against Gram-negative bacteria. Activity was observed at sub-micromolar concentrations for three of the cyclotides tested, surpassing that of the control peptides LL-37 and melittin. Noteworthy, two anionic cyclotides were active on Pseudomonas aeruginosa at low micromolar concentrations. Broad-spectrum activity was pronounced among cycloviolacin cyclotides, which included activity on Staphylococcus aureus and Candida albicans. The factors influencing their bactericidal spectrum were revealed by correlating antimicrobial activity with membrane permeabilization on various liposome systems and with the physiochemical properties of the cyclotides. Whereas general electrostatic and hydrophobic parameters are more important for broad-spectrum cyclotides; a phospholipid-specific mechanism of membrane permeabilization, through interaction with phosphatidylethanolamine-lipids, is essential for cyclotides active primarily on Gram-negative bacteria.

BackgroundAs online social media have become prominent, much effort has been spent on identifying users with depressive symptoms in order to aim at early diagnosis, treatment, and even prevention by using various online social media. In this paper, we focused on Facebook to discern any correlations between the platform’s features and users’ depressive symptoms. This work may be helpful in trying to reach and detect large numbers of depressed individuals more easily.ObjectiveOur goal was to develop a Web application and identify depressive symptom–related features from users of Facebook, a popular social networking platform.Methods55 Facebook users (male=40, female=15, mean age 24.43, SD 3.90) were recruited through advertisement fliers distributed to students in a large university in Korea. Using EmotionDiary, the Facebook application we developed, we evaluated depressive symptoms using the Center for Epidemiological Studies-Depression (CES-D) scale. We also provided tips and facts about depression to participants and measured their responses using EmotionDiary. To identify the Facebook features related to depression, correlation analyses were performed between CES-D and participants’ responses to tips and facts or Facebook social features. Last, we interviewed depressed participants (CES-D≥25) to assess their depressive symptoms by a psychiatrist.ResultsFacebook activities had predictive power in distinguishing depressed and nondepressed individuals. Participants’ response to tips and facts, which can be explained by the number of app tips viewed and app points, had a positive correlation (P=.04 for both cases), whereas the number of friends and location tags had a negative correlation with the CES-D scale (P=.08 and P=.045 respectively). Furthermore, in finding group differences in Facebook social activities, app tips viewed and app points resulted in significant differences (P=.01 and P=.03 respectively) between probably depressed and nondepressed individuals.ConclusionsOur results using EmotionDiary demonstrated that the more depressed one is, the more one will read tips and facts about depression. We also confirmed depressed individuals had significantly fewer interactions with others (eg, decreased number of friends and location tagging). Our app, EmotionDiary, can successfully evaluate depressive symptoms as well as provide useful tips and facts to users. These results open the door for examining Facebook activities to identify depressed individuals. We aim to conduct the experiment in multiple cultures as well.

As people around the world are spending increasing amounts of time online, the question of how online experiences are linked to health and well-being is essential. This paper presents how activities on Facebook are associated with the depressive states of users. Based on online logs of 212 young adults, we show not only the sheer size of the network but also the frequency and diversity of interactions on social networks have close associations with depression. Depressed individuals reported smaller involved networks regarding comments and likes, the two popular forms of interactions. In contrast to the decreased level of interactions, depressed individuals showed an increase in the wall post rates and were active online during midday, which can be interpreted as an endemic behavior linked to the perceived degree of loneliness among young adults who are avid users of social media. We discuss these findings from theoretical, empirical, and subjective perspectives.

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