Detection of prostate specific antigen (PSA) in human saliva using an ultra-sensitive nanocomposite of graphene nanoplatelets with diblock-co-polymers and Au electrodes.

Prostate-specific antigen (PSA) is a commonly used biomarker for the detection of prostate cancer (PCa) and there are numerous data available for its invasive detection in the serum and whole blood. In this work, an electrochemical sensing method was devised to detect traces of PSA in human saliva using a hybrid nanocomposite of graphene nanoplatelets with diblock co-polymers and Au electrodes (GRP-PS67-b-PAA27-Au). The pure graphitic composition on filter paper provides significantly high electrical and thermal conductivity while PS67-b-PAA27 makes an amphiphilic bridge between GRP units. The sensor utilizes the binding of an anti-PSA antibody with an antigen-PSA to act as a resistor in a circuit providing an impedance change that in turn allows for the detection and quantification of PSA in saliva samples. A miniaturized electrical impedance analyzer was interfaced with a sensor chip and the data were recorded in real-time using a Bluetooth-enabled module. This fully integrated and optimized sensing device exhibited a wide PSA range of detection from 0.1 pg mL-1 to 100 ng mL-1 (R2 = 0.963) with a lower limit of detection of 40 fg mL-1. The performance of the biosensor chip was validated with an enzyme-linked immunosorbent assay technique with a regression coefficient as high as 0.940. The advantages of the newly developed saliva-PSA electrical biosensor over previously reported serum-PSA electrochemical biosensors include a faster response time (3-5 min) to achieve a stable electrical signal for PSA detection, high selectivity, improved sensitivity, no additional requirement of a redox electrolyte for electron exchange and excellent shelf life. The presented sensor is aimed for clinical commercialization to detect PSA in human saliva.

A paradigm for single-case research: the time series study of a long-term psychotherapy for depression.

This study articulates a paradigm for single-case research in psychotherapy. A patient diagnosed as having major depressive disorder was seen in an intensive, twice-weekly psychodynamic psychotherapy for 2 1/2 years. Each session was videotaped, and assessment of patient change were obtained at regular intervals. A time-series analysis was used to model fluctuations in the therapy process to take into account time and the effect of previous events on subsequent changes, thereby preserving the context-determined meaning for therapist and patient actions. A bidirectional analysis of casual effects shows that the influence processes between therapist and patient are mutual and reciprocal and suggests that the effect of the patient on the therapist and on the process has not been made sufficiently explicit in previous models of process and change. The potential of intensive single-case designs for uncovering causal effects in psychotherapy is demonstrated.

Self-derogations and the interpersonal theory.

The interpersonal theory of personality has been applied to explain depressed people's dilemma: The depressed person's submissive behavior invites dominating reactions from other people, and those reactions sustain the depressed person's depression. Experiments 1 and 2 showed that self-derogations connote submissiveness but are generally judged to be neutral in affiliation. Experiment 3 tested implications for the behavior of dysphoric and nondysphoric Ss as they interacted with a self-derogating, other-derogating, or nonderogating confederate partner. Ss selected a topic from a list and talked about it for 1 min: the confederate's script was fixed. The S's judgments of the confederate, choice of topics, satisfaction with the interaction, and actual responses were analyzed. Self-derogators were judged to be submissive, elicited dominating reactions, and selected more topics with negative content.

Electrical potentials in human brain during cognition: new method reveals dynamic patterns of correlation.

A new technique has been developed for identifying, in humans, dynamic spatiotemporal electrical patterns of the brain during purposive behaviors. In this method, single-trial time-series correlations between brain macropotentials recorded from different scalp sites are analyzed by distribution-independent mathematical pattern recognition. Dynamic patterns of correlation clearly distinguished two brief visuomotor tasks differing only in type of mental judgement required (spatial or numeric). These complex patterns shifted in the anterior-posterior and left-right axes between successive 175-millisecond intervals, indicating that many areas in both cerebral hemispheres were involved even in these simple judgements. These patterns were not obtainable by conventional analysis of averaged evoked potentials or by linear analysis of correlations, suggesting that the new technique will advance the study of human brain activity related to cognition and goal-directed behaviors.