Citations

AbstractBackgroundThe mapping between risk factors and biomarkers with cognitive performance and decline in the older adults is complex and varies significantly across different age and sex groups. Our goals were to (i) develop a machine learning (ML) model to predict baseline cognition and cognitive decline over a 5‐year follow‐up using only baseline assessments, and (ii) identify important modifiable and non‐modifiable predictors of cognitive decline across different age strata.MethodWe utilized longitudinal data from 2219 participants (mean age (SD): 70 (12) years, 49% male) from Mayo Clinic Study of Aging who had 43 features belonging to cardiovascular health, plasma, MRI (diffusion and structural), and lifestyle measures. Cognition was measured using a global cognition z‐score. We built ML models to predict baseline cognition and rate of cognitive decline over 5‐years (linear regression slopes over all individual followup measurements for each participant) using baseline assessments as inputs. We then built a model for each category separately and as a pooled model with all measures included, incorporating education and sex as demographic features in all models (Fig. 1). We applied a multi‐layer stack ensemble ML technique that utilized repeated k‐fold bagging to maximize accuracy. Importance of the top predictors were assessed in three age strata (55‐65 years (31%), 65‐80 years (46%), 80‐95 years (23%)).ResultThe pooled model explained the largest variance for prediction of baseline cognition and cognitive decline (Fig. 2). In individuals ≤80 years, lower NfL was most predictive of higher baseline cognition. A combination of imaging and plasma features predicted the 5‐year cognitive decline. Additionally, in individuals ≤65 years, diabetes and hypertension were important predictors of faster cognitive decline and in those >80, lower BMI and midlife physical/cognitive activity was an important predictor of faster cognitive decline (Fig. 3).ConclusionThe plasma model was best for baseline cognition prediction and imaging model was best for cognitive decline prediction. There was significant heterogeneity in important features across the age strata. In individuals >65 years, plasma GFAP was the most important predictor of cognitive decline. Our model allowed identification of key risk factors that predicted cognitive decline.

Background: Meningiomas are the most common primary central nervous system malignancies accounting for 36% of all intracranial tumors. However, only 1% of meningioma is classified as malignant (anaplastic) meningioma. Due to their rarity, clinical management of these tumors presents several gaps. Methods: We carried out a narrative review aimed to investigate current knowledge of anaplastic meningioma focusing on their pathological and radiological diagnosis, molecular assessment, and loco-regional and systemic management. Results: The most frequent genetic alteration occurring in meningioma is the inactivation in the neurofibromatosis 2 genes (merlin). The accumulation of copy number losses, including 1p, 6p/q, 10q, 14q, and 18p/q, and less frequently 2p/q, 3p, 4p/q, 7p, 8p/q, and 9p, compatible with instability, is restricted to NF2 mutated meningioma. Surgery and different RT approaches represent the milestone of grade 3 meningioma management, while there is a marginal role of systemic therapy. Conclusions: Anaplastic meningiomas are rare tumors, and diagnosis should be suspected and confirmed by trained radiologists and pathologists. Despite the current marginal role of systemic therapy, it is possible that the increasing knowledge of molecular altered pathways of the disease will lead to the development of novel effective systemic treatments.

Abstract In order to correlate the electrophoretic alterations in the serum proteins and the findings in the bone marrow, with particular reference to atypical lymphocytic forms and plasma cells, 14 cases of lymphosarcoma, six of chronic lymphocytic leukemia and six of Hodgkin’s disease were studied. No numerical relationship could be found between the degree of lymphoid atypia and the changes in serum globulin. A correlation, however, was apparent between the plasma cell concentration in the bone marrow and the changes in the serum gamma globulin, inasmuch as pronounced hypergammaglobulinemia occurred in all four cases of malignant lymphoma associated with bone marrow plasmacytosis (ranging from 2.8 to 12.8 per cent) and hypogammaglobulinemia of moderate to marked degree was present in five of the six cases of malignant lymphoma in which plasma cells were virtually absent in the bone marrow. When the findings of the fixed sections of the marrow are included, plasmacytosis was demonstrated in bone marrow in eight of 10 cases in which serum gamma globulins were elevated. In two cases, serum globulins were qualitatively abnormal. In one, a case (case 15) of Hodgkin’s disease, a small fraction of electrophoretically homogeneous globulin was noted. In the other, case 5, in which the histologic diagnosis was lymphocytic lymphosarcoma, macroglobulins constituted 40 per cent of the serum proteins, and Bence Jones proteinuria was associated. Predominantly mature plasmacytosis of 12.8 per cent was present in the bone marrow. This case may be regarded as illustrative of the interrelationship between myeloma and lymphosarcoma and supports the view21 that, clinically and morphologically, transitional forms occur between lymphatic tumors and plasmacytomas. On the basis of this material, it is suggested that in cases of lymphosarcoma, Hodgkin’s disease and chronic lymphocytic leukemia, alterations in the plasma content of the bone marrow, either as reactive plasmacytosis or as virtual absence of plasma cells, appear to be a major pathogenetic factor in the occurrence of hypergammaglobulinemia and hypogammaglobulinemia, respectively. Hypogammaglobulinemia was observed in three of six cases of chronic lymphocytic leukemia; two of 14 cases of lymphosarcoma; and one of six classified as Hodgkin’s disease. Conversely, quantitative increases in the gamma globulin level occurred in none of the six cases of chronic lymphocytic leukemia; in six of 14 cases of lymphosarcoma (including two of three classified as lymphosarcoma, reticular cell type), and in three of the six cases of Hodgkin’s disease.

ABSTRACTBronchiectasis, conventionally defined as irreversible dilatation of the bronchial tree, is generally suspected on a clinical basis and confirmed by means of chest high‐resolution computed tomography. Clinical manifestations, including chronic productive cough and endobronchial suppuration with persistent chest infection and inflammation, may deeply affect quality of life, both in children/adolescents and adults. Despite many cases being idiopathic or post‐infectious, a number of specific aetiologies have been traditionally associated with bronchiectasis, such as cystic fibrosis (CF), primary ciliary dyskinesia or immunodeficiencies. Nevertheless, bronchiectasis may also develop in patients with bronchial asthma; chronic obstructive pulmonary disease; and, less commonly, rheumatological disorders and inflammatory bowel diseases. Available literature on the development of bronchiectasis in these conditions and on its management is limited, particularly in children. However, bronchiectasis may complicate the clinical course of the underlying condition at any age, and appropriate management requires an integration of multiple skills in a team of complementary experts to provide the most appropriate care to affected children and adolescents. The present review aims at summarizing the current knowledge and available evidence on the management of bronchiectasis in the other conditions mentioned and focuses on the new therapeutic strategies that are emerging as promising tools for improving patients’ quality of life.

Objectives Human pancreatic polypeptide (HPP) is a hormone secreted by the ventral pancreas. While postprandial HPP levels have been studied in chronic pancreatitis (CP) and pancreatic ductal adenocarcinoma (PDAC), there are limited data on fasting HPP in these diseases. Methods Fasting serum HPP was measured in the following groups of patients: CP with diabetes mellitus (DM) (n = 16), CP without DM (n = 34), PDAC with new-onset DM (n = 50), PDAC without DM (n = 49), new-onset type 2 DM (n = 50), and controls without DM (n = 49). Sixty-six had type 3c DM (CP with DM, n = 16; PDAC with new-onset DM, n = 50). Results Median fasting HPP levels (in picograms per milliliter) were similar among all groups. Median (interquartile range) HPP levels in new-onset type 2 DM (n = 50; 288.3 [80.1–1072.1]) were similar to those in type 3c DM (n = 66; 242.3 [64.9–890.9]) (P = 0.71). In PDAC (n = 99), HPP values were similar in pancreatic head (n = 75) versus body/tail (n = 24) tumors (245.3 [64.3–1091.3] vs 334.7 [136.1–841.5]; P = 0.95), regardless of DM. Conclusions Fasting HPP levels are similar in CP, PDAC, and controls regardless of glycemic status.