Epidemiology of clinically significant migraine in Israel: a retrospective database study.

Background: Epidemiological studies on migraine are valuable for tracking disease trends, identifying risk factors, and informing treatment strategies. This study assessed the prevalence and annual incidence of clinically significant migraine in Israel from 2017 to 2022, with analyses stratified by age, sex, socioeconomic status, and district. Additionally, we compared relevant characteristics between adult migraine and non-migraine members of Leumit Healthcare Services (LHS), a national health provider in Israel.

Actinobacterium-Mediated Green Synthesis of CuO/Zn-Al LDH Nanocomposite Using sp. ISP-2 27: A Synergistic Study that Enhances Antimicrobial Activity.

Bacterial resistance to conventional antibiotics has created an urgent need to develop enhanced alternatives. Nanocomposites combined with promising antibacterial nanomaterials can show improved antimicrobial activity compared to that of their components. In this work, green synthesized CuO nanoparticles (NPs) supported on an anionic clay with a hydrotalcite-like structure such as Zn-Al layered double hydroxide (LDH) nanocomposite were investigated as antimicrobial agents.

Clinical and Radiological Characteristics of Non-Obese Female Patients with Idiopathic Intracranial Hypertension.

While the typical patient with idiopathic intracranial hypertension (IIH) is an obese female of childbearing age, there are unique patient populations, such as non-obese females, that have not been well studied. Characterizing this subpopulation may increase awareness our of it, which may prevent underdiagnosis and improve our understanding of IIH's underlying pathophysiology. We retrospectively reviewed electronic medical records and compared the clinical and radiological characteristics of non-obese (BMI < 30) and obese (BMI > 30) female patients with IIH.

Electroencephalography functional connectivity-A biomarker for painful polyneuropathy.

Background And Purpose: Advanced analysis of electroencephalography (EEG) data has become an essential tool in brain research. Based solely on resting state EEG signals, a data-driven, predictive and explanatory approach is presented to discriminate painful from non-painful diabetic polyneuropathy (DPN) patients.

Methods: Three minutes long, 64 electrode resting-state recordings were obtained from 180 DPN patients.