Trazodone and ejaculatory inhibition

A man with urethral polyembolokoilamania successfully treated with electroconvulsive therapy

Polyembolokoilamania is the act of inserting foreign objects into bodily orifices and can be classified as a paraphilia if done for sexual pleasure. Although problematic sexual behaviors are common in dementia, the majority of case reports of urethral polyembolokoilamania in the elderly have occurred in the absence of dementia or cognitive impairment. Little empirical evidence exists for managing problematic sexual behaviors in the elderly and in dementia. Most evidence in the form of case reports demonstrates that behavioral, environmental, and pharmacological interventions can be effective. In this case report, we describe the management of sexually disinhibited behavior in the form of polyembolokoilamania in a 67-year-old man suffering from treatment-resistant depression, obsessive compulsive disorder, and early signs of frontotemporal dementia. The successful treatment included a course of electroconvulsive therapy.

Can the vector space model be used to identify biological entity activities?

BACKGROUND

Biological systems are commonly described as networks of entity interactions. Some interactions are already known and integrate the current knowledge in life sciences. Others remain unknown for long periods of time and are frequently discovered by chance. In this work we present a model to predict these unknown interactions from a textual collection using the vector space model (VSM), a well known and established information retrieval model. We have extended the VSM ability to retrieve information using a transitive closure approach. Our objective is to use the VSM to identify the known interactions from the literature and construct a network. Based on interactions established in the network our model applies the transitive closure in order to predict and rank new interactions.

RESULTS

We have tested and validated our model using a collection of patent claims issued from 1976 to 2005. From 266,528 possible interactions in our network, the model identified 1,027 known interactions and predicted 3,195 new interactions. Iterating the model according to patent issue dates, interactions found in a given past year were often confirmed by patent claims not in the collection and issued in more recent years. Most confirmation patent claims were found at the top 100 new interactions obtained from each subnetwork. We have also found papers on the Web which confirm new inferred interactions. For instance, the best new interaction inferred by our model relates the interaction between the adrenaline neurotransmitter and the androgen receptor gene. We have found a paper that reports the partial dependence of the antiapoptotic effect of adrenaline on androgen receptor.

CONCLUSIONS

The VSM extended with a transitive closure approach provides a good way to identify biological interactions from textual collections. Specifically for the context of literature-based discovery, the extended VSM contributes to identify and rank relevant new interactions even if these interactions occur in only a few documents in the collection. Consequently, we have developed an efficient method for extracting and restricting the best potential results to consider as new advances in life sciences, even when indications of these results are not easily observed from a mass of documents.

Gabapentin-induced sexual dysfunction

Sexual dysfunction is a key adverse effect leading to medication noncompliance. Psychotropic drugs associated with sexual dysfunction include antiepileptic drugs, antidepressants, and antipsychotics. Gabapentin, frequently used off-label to treat psychiatric and pain disorders, has previously been reported to cause sexual dysfunction at a minimum total daily dose of 900 mg. This report addresses dose-dependent gabapentin-induced sexual dysfunction reaching total sexual dysfunction (loss of libido, anejaculation, anorgasmia, and impotence) at a total daily dose of only 300 mg.