Correlation Between Temperature Rise After Sympathetic Block and Pain Relief in Patients with Complex Regional Pain Syndrome.

OBJECTIVE: Determine the correlation between post-sympathetic block temperature change and immediate- and intermediate-term pain relief. DESIGN: Retrospective analysis. SETTING: Academic setting. SUBJECTS: Seventy-nine patients with complex regional pain syndrome who underwent sympathetic block. METHODS: Pre- and post-block temperatures in the affected extremity and pain scores immediately (based on 6-hour pain diary) after the block and at the intermediate-term 4- to 8-week follow-up were recorded. Post-block pain reductions of 30-49% and ≥50% were designated as partially sympathetically maintained pain and sympathetically maintained pain, respectively. A decrease in pain score ≥2 points lasting ≥4 weeks was considered a positive intermediate-term outcome for sympathetic block. RESULTS: A weak correlation was found between immediate-term pain relief and the extent of temperature rise for the cohort (R = 0.192, P = 0.043). Greater immediate-term pain reduction was reported among patients who experienced a temperature increase ≥7.5°C (mean 4.1; 95% confidence interval [CI]: 3.33 to 4.76) than among those who experienced a temperature increase <2°C (2.3; 95% CI: 1.36 to 3.31) or ≥2°C to <7.5°C (2.9; 95% CI: 1.8 to 3.9; P = 0.036). The correlations between temperature increase and intermediate-term pain score reduction at 4-8 weeks (R = 0.052, P = 0.329) and between immediate- and intermediate-term pain relief (R = 0.139, P = 0.119) were not statistically significant. CONCLUSIONS: A weak correlation was found for those who experienced greater temperature increases after the block to also experience greater immediate pain relief. Higher temperature increase cutoffs than are typically used might be necessary to determine whether a patient with complex regional pain syndrome has sympathetically maintained pain.

Deep learning for diagnosis of acute promyelocytic leukemia via recognition of genomically imprinted morphologic features.

Acute promyelocytic leukemia (APL) is a subtype of acute myeloid leukemia (AML), classified by a translocation between chromosomes 15 and 17 [t(15;17)], that is considered a true oncologic emergency though appropriate therapy is considered curative. Therapy is often initiated on clinical suspicion, informed by both clinical presentation as well as direct visualization of the peripheral smear. We hypothesized that genomic imprinting of morphologic features learned by deep learning pattern recognition would have greater discriminatory power and consistency compared to humans, thereby facilitating identification of t(15;17) positive APL. By applying both cell-level and patient-level classification linked to t(15;17) PML/RARA ground-truth, we demonstrate that deep learning is capable of distinguishing APL in both discovery and prospective independent cohort of patients. Furthermore, we extract learned information from the trained network to identify previously undescribed morphological features of APL. The deep learning method we describe herein potentially allows a rapid, explainable, and accurate physician-aid for diagnosing APL at the time of presentation in any resource-poor or -rich medical setting given the universally available peripheral smear.

Broad detection of bacterial type III secretion system and flagellin proteins by the human NAIP/NLRC4 inflammasome.

Inflammasomes are cytosolic multiprotein complexes that initiate host defense against bacterial pathogens by activating caspase-1-dependent cytokine secretion and cell death. In mice, specific nucleotide-binding domain, leucine-rich repeat-containing family, apoptosis inhibitory proteins (NAIPs) activate the nucleotide-binding domain, leucine-rich repeat-containing family, CARD domain-containing protein 4 (NLRC4) inflammasome upon sensing components of the type III secretion system (T3SS) and flagellar apparatus. NAIP1 recognizes the T3SS needle protein, NAIP2 recognizes the T3SS inner rod protein, and NAIP5 and NAIP6 recognize flagellin. In contrast, humans encode a single functional NAIP, raising the question of whether human NAIP senses one or multiple bacterial ligands. Previous studies found that human NAIP detects both flagellin and the T3SS needle protein and suggested that the ability to detect both ligands was achieved by multiple isoforms encoded by the single human NAIP gene. Here, we show that human NAIP also senses the Salmonella Typhimurium T3SS inner rod protein PrgJ and that T3SS inner rod proteins from multiple bacterial species are also detected. Furthermore, we show that a single human NAIP isoform is capable of sensing the T3SS inner rod, needle, and flagellin. Our findings indicate that, in contrast to murine NAIPs, promiscuous recognition of multiple bacterial ligands is conferred by a single human NAIP.

Neutrophils and Ly6Chi monocytes collaborate in generating an optimal cytokine response that protects against pulmonary Legionella pneumophila infection.

Early responses mounted by both tissue-resident and recruited innate immune cells are essential for host defense against bacterial pathogens. In particular, both neutrophils and Ly6Chi monocytes are rapidly recruited to sites of infection. While neutrophils and monocytes produce bactericidal molecules, such as reactive nitrogen and oxygen species, both cell types are also capable of synthesizing overlapping sets of cytokines important for host defense. Whether neutrophils and monocytes perform redundant or non-redundant functions in the generation of anti-microbial cytokine responses remains elusive. Here, we sought to define the contributions of neutrophils and Ly6Chi monocytes to cytokine production and host defense during pulmonary infection with Legionella pneumophila, responsible for the severe pneumonia Legionnaires' disease. We found that both neutrophils and monocytes are critical for host defense against L. pneumophila. Both monocytes and neutrophils contribute to maximal IL-12 and IFNγ responses, and monocytes are also required for TNF production. Moreover, natural killer (NK) cells, NKT cells, and γδ T cells are sources of IFNγ, and monocytes direct IFNγ production by these cell types. Thus, neutrophils and monocytes cooperate in eliciting an optimal cytokine response that promotes effective control of bacterial infection.