Drug resistance in B and non-B subtypes amongst subjects recently diagnosed as primary/recent or chronic HIV-infected over the period 2013–2016: Impact on susceptibility to first-line strategies including integrase strand-transfer inhibitors

Objectives To characterize the prevalence of transmitted drug resistance mutations (TDRMs) by plasma analysis of 750 patients at the time of HIV diagnosis from January 1, 2013 to November 16, 2016 in the Veneto region (Italy), where all drugs included in the recommended first line therapies were prescribed, included integrase strand transfer inhibitors (InNSTI). Methods TDRMs were defined according to the Stanford HIV database algorithm. Results Subtype B was the most prevalent HIV clade (67.3%). A total of 92 patients (12.3%) were expected to be resistant to one drug at least, most with a single class mutation (60/68–88.2% in subtype B infected subjectsand 23/24–95.8% in non-B subjects) and affecting mainly NNRTIs. No significant differences were observed between the prevalence rates of TDRMs involving one or more drugs, except for the presence of E138A quite only in patients with B subtype and other NNRTI in subjects with non-B infection. The diagnosis of primary/recent infection was made in 73 patients (9.7%): they had almost only TDRMs involving a single class. Resistance to InSTI was studied in 484 subjects (53 with primary-recent infection), one patient had 143C in 2016, a total of thirteen 157Q mutations were detected (only one in primary/recent infection). Conclusions Only one major InSTI-TDRM was identified but monitoring of TDRMs should continue in the light of continuing presence of NNRTI-related mutation amongst newly diagnosed subjects, sometime impacting also to modern NNRTI drugs recommended in first-line therapy

Ostial plication: a rarely reported cause of sudden death

We report a rare case of ostial plication as a potential cause of sudden death. Very few reports and images are available in the specialized literature regarding this anomaly. Ostial plication may be a source of sudden death or cause of death when no other significant autopsy findings are present

Determinação de intensidades amostrais para a estimativa da distribuição diamétrica das espécies Qualea albiflora e Goupia glabra de Sinop - MT.

Resumo

Bifurcation Boundary Conditions for Switching DC-DC Converters Under Constant On-Time Control

Sampled-data analysis and harmonic balance analysis are applied to analyze switching DC-DC converters under constant on-time control. Design-oriented boundary conditions for the period-doubling bifurcation and the saddle-node bifurcation are derived. The required ramp slope to avoid the bifurcations and the assigned pole locations associated with the ramp are also derived. The derived boundary conditions are more general and accurate than those recently obtained. Those recently obtained boundary conditions become special cases under the general modeling approach presented in this paper. Different analyses give different perspectives on the system dynamics and complement each other. Under the sampled-data analysis, the boundary conditions are expressed in terms of signal slopes and the ramp slope. Under the harmonic balance analysis, the boundary conditions are expressed in terms of signal harmonics. The derived boundary conditions are useful for a designer to design a converter to avoid the occurrence of the period-doubling bifurcation and the saddle-node bifurcation.Comment: Submitted to International Journal of Circuit Theory and Applications on August 10, 2011; Manuscript ID: CTA-11-016

Artificial Intelligence in Acute Ischemic Stroke Subtypes According to Toast Classification: A Comprehensive Narrative Review

The correct recognition of the etiology of ischemic stroke (IS) allows tempestive interventions in therapy with the aim of treating the cause and preventing a new cerebral ischemic event. Nevertheless, the identification of the cause is often challenging and is based on clinical features and data obtained by imaging techniques and other diagnostic exams. TOAST classification system describes the different etiologies of ischemic stroke and includes five subtypes: LAAS (large-artery atherosclerosis), CEI (cardio embolism), SVD (small vessel disease), ODE (stroke of other determined etiology), and UDE (stroke of undetermined etiology). AI models, providing computational methodologies for quantitative and objective evaluations, seem to increase the sensitivity of main IS causes, such as tomographic diagnosis of carotid stenosis, electrocardiographic recognition of atrial fibrillation, and identification of small vessel disease in magnetic resonance images. The aim of this review is to provide overall knowledge about the most effective AI models used in the differential diagnosis of ischemic stroke etiology according to the TOAST classification. According to our results, AI has proven to be a useful tool for identifying predictive factors capable of subtyping acute stroke patients in large heterogeneous populations and, in particular, clarifying the etiology of UDE IS especially detecting cardioembolic sources