Developing a Mood and Menstrual Tracking App for People With Premenstrual Dysphoric Disorder: User-Centered Design Study.

Background: People with premenstrual dysphoric disorder (PMDD) experience a range of symptoms that increase and decline as a result of the natural hormonal fluctuations of the menstrual cycle. For the diagnosis of PMDD, symptom severity needs to be recorded daily for at least two symptomatic cycles. In recent years, the rise in interest in Femtech (tools and technology developed to address women's health issues) has resulted in a large quantity of "period-tracking apps" being developed and downloaded.

Search for Soft Unclustered Energy Patterns in Proton-Proton Collisions at 13 TeV.

The first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of 138  fb^{-1} of proton-proton collision data at sqrt[s]=13  TeV, collected in 2016-2018 by the CMS detector at the LHC. Such SUEPs are predicted by hidden valley models with a new, confining force with a large 't Hooft coupling. In events with boosted topologies, selected by high-threshold hadronic triggers, the multiplicity and sphericity of clustered tracks are used to reject the background from standard model quantum chromodynamics.

Associations between lifetime reproductive events among postmenopausal women with bipolar disorder.

Purpose: The premenstrual phase of the menstrual cycle, childbirth and perimenopause often coincide with a worsening of mood symptoms in women with bipolar disorder (BD). To date, findings from the limited number of studies investigating associations between these events among women with BD have been inconsistent. This study aimed to investigate associations between episodes in relation to the perimenopause and (i) premenstrual symptoms and (ii) postpartum mood episodes in a large sample of postmenopausal women with BD.