Histidine-rich glycoprotein as a novel predictive biomarker of postoperative complications in intensive care unit patients: a prospective observational study

Background Decrease in histidine-rich glycoprotein (HRG) was reported as a cause of dysregulation of the coagulation-fibrinolysis and immune systems, leading to multi-organ failure, and it may be a biomarker for sepsis, ventilator-associated pneumonia, preeclampsia, and coronavirus disease 2019. However, the usefulness of HRG in perioperative management remains unclear. This study aimed to assess the usefulness of HRG as a biomarker for predicting postoperative complications. Methods This was a single-center, prospective, observational study of 150 adult patients who were admitted to the intensive care unit after surgery. Postoperative complications were defined as those having a grade II or higher in the Clavien-Dindo classification, occurring within 7 days after surgery. The primary outcome was HRG levels in the patients with and without postoperative complications. The secondary outcome was the ability of HRG, white blood cell, C-reactive protein, procalcitonin, and presepsin to predict postoperative complications. Data are presented as number and median (interquartile range). Results The incidence of postoperative complications was 40%. The HRG levels on postoperative day 1 were significantly lower in patients who developed postoperative complications (n = 60; 21.50 [18.12-25.74] mu g/mL) than in those who did not develop postoperative complications (n = 90; 25.46 [21.05-31.63] mu g/mL). The Harrell C-index scores for postoperative complications were HRG, 0.65; white blood cell, 0.50; C-reactive protein, 0.59; procalcitonin, 0.73; and presepsin, 0.73. HRG was independent predictor of postoperative complications when adjusted for age, the presence of preoperative cardiovascular comorbidities, American Society of Anesthesiologists Physical Status Classification, operative time, and the volume of intraoperative bleeding (adjusted hazard ratio = 0.94; 95% confidence interval, 0.90-0.99). Conclusions The HRG levels on postoperative day 1 could predict postoperative complications. Hence, HRG may be a useful biomarker for predicting postoperative complications

Consistently low levels of histidine-rich glycoprotein as a new prognostic biomarker for sepsis: A multicenter prospective observational study

Background Few sepsis biomarkers accurately predict severity and mortality. Previously, we had reported that first-day histidine-rich glycoprotein (HRG) levels were significantly lower in patients with sepsis and were associated with mortality. Since the time trends of HRG are unknown, this study focused on the time course of HRG in patients with sepsis and evaluated the differences between survivors and non-survivors. Methods A multicenter prospective observational study was conducted involving 200 patients with sepsis in 16 Japanese hospitals. Blood samples were collected on days 1, 3, 5, and 7, and 28-day mortality was used for survival analysis. Plasma HRG levels were determined using a modified quantitative sandwich enzyme-linked immunosorbent assay. Results First-day HRG levels in non-survivors were significantly lower than those in survivors (mean, 15.7 [95% confidence interval (CI), 13.4-18.1] vs 20.7 [19.5-21.9] mu g/mL; P = 0.006). Although there was no time x survivors/non-survivors interaction in the time courses of HRG (P = 0.34), the main effect of generalized linear mixed models was significant (P Conclusions HRG levels in non-survivors were consistently lower than those in survivors during the first seven days of sepsis. Repeatedly measured HRG levels were significantly associated with mortality. Furthermore, the predictive power of HRG for mortality may be superior to that of other singular biomarkers, including presepsin, procalcitonin, and C-reactive protein

Activin E Controls Energy Homeostasis in Both Brown and White Adipose Tissues as a Hepatokine

Brown adipocyte activation or beige adipocyte emergence in white adipose tissue (WAT) increases energy expenditure, leading to a reduction in body fat mass and improved glucose metabolism. We found that activin E functions as a hepatokine that enhances thermogenesis in response to cold exposure through beige adipocyte emergence in inguinal WAT (ingWAT). Hepatic activin E overexpression activated thermogenesis through Ucp1 upregulation in ingWAT and other adipose tissues including interscapular brown adipose tissue and mesenteric WAT. Hepatic activin E-transgenic mice exhibited improved insulin sensitivity. Inhibin βE gene silencing inhibited cold-induced Ucp1 induction in ingWAT. Furthermore, in vitro experiments suggested that activin E directly stimulated expression of Ucp1 and Fgf21, which was mediated by transforming growth factor-β or activin type I receptors. We uncovered a function of activin E to stimulate energy expenditure through brown and beige adipocyte activation, suggesting a possible preventive or therapeutic target for obesity

Successful intrathecal chemotherapy combined with radiotherapy followed by pomalidomide and low-dose dexamethasone maintenance therapy for a primary plasma cell leukemia patient

Primary plasma cell leukemia (PPCL) is a rare aggressive variant of plasma cell disorder and frequently presents with extramedullary disease. Central nervous system (CNS) involvement with PPCL has an extremely poor prognosis. We describe a 46-year-old man with PPCL treated with a combination of lenalidomide, bortezomib, and dexamethasone as induction therapy following upfront allogeneic stem cell transplantation (allo-SCT). Despite achieving a very good partial response, the patient suffered from an isolated CNS relapse 12 months after allo-SCT. He was immediately started on concurrent intrathecal chemotherapy (IT) and cranial irradiation (RT). Subsequently, pomalidomide and low-dose dexamethasone (Pd) were given as maintenance therapy. He has been without CNS recurrence for more than 18 months. Our case suggests that concurrent IT and RT followed by Pd maintenance therapy may be an effective option to control CNS relapse of PPCL after allo-SCT

ダイガクセイ ヲ タイショウ ト シタ イノシシ ニク ト ブタ ニク ノ カンノウ ヒョウカ

イノシシ肉とブタ肉の味について,大学生を対象とした官能検査を行った。両者を焼き肉の形で比較したところ,柔らかさではブタが,香りではイノシシが勝っていた。イノシシ肉各部位(ロース,バラ,モモ)間に有意な味の差は見られなかったが,夏肉の評価は冬肉よりも有意に低かった。ブタ肉価格を100としたときに,回答者が妥当と思うイノシシ肉の価格は平均112-138,中央位100-120,最頻値80-100の範囲にあった。このようにイノシシ肉とブタ肉の評価額に大きな差は無かったが,イノシシ肉をブタ肉の2～4倍に高く評価した回答者も一部に見られた。回答者の性別による差のみられた項目はなかった。野生動物肉を食べることへの抵抗感はみられなかった。現在のイノシシ肉は家庭消費肉としての価格競争力は有していないので,消費拡大には価格以外の訴求力が必要と思われる。Quality of wild boar and swine meats were compared through sensory evaluation by university students. While boar meat had a characteristically meaty scent, swine meat was strongly preferred for its softness. There were no qualitative differences in boar meat parts (loin,back rib and thigh). Juicy texture of winter boar meat was superior to dry texture of summer one in most criteria. In general, willingness to pay among respondents for boar and swine meats was roughly the same. Assuming the price of swine meat as 100, appropriate pricing by respondents for various parts of boar meat was 112-138 on average, 100-120 in median, and 80-100 in mode. But some respondents evaluated boar meat as high as high as 400 level. There were no differences in the answer of male and female respondents. Respondents showed no hesitation to eat wildlife meat. For domestic consumption, boar meat seems not to be price-competitive to swine meat. Since there are some people who highly valuate boar meat, appealing to other features of boar meat seems necessary to increase consumption

Online and Stochastic Learning with a Human Cognitive Bias

Sequential learning for classification tasks is an effective tool in the machine learning community. In sequential learning settings, algorithms sometimes make incorrect predictions on data that were correctly classified in the past. This paper explicitly deals with such inconsistent prediction behavior. Our main contributions are 1) to experimentally show its effect for user utilities as a human cognitive bias, 2) to formalize a new framework by internalizing this bias into the optimization problem, 3) to develop new algorithms without memorization of the past prediction history, and 4) to show some theoretical guarantees of our derived algorithm for both online and stochastic learning settings. Our experimental results show the superiority of the derived algorithm for problems involving human cognition