Are biological systems poised at criticality?

Many of life's most fascinating phenomena emerge from interactions among many elements--many amino acids determine the structure of a single protein, many genes determine the fate of a cell, many neurons are involved in shaping our thoughts and memories. Physicists have long hoped that these collective behaviors could be described using the ideas and methods of statistical mechanics. In the past few years, new, larger scale experiments have made it possible to construct statistical mechanics models of biological systems directly from real data. We review the surprising successes of this "inverse" approach, using examples form families of proteins, networks of neurons, and flocks of birds. Remarkably, in all these cases the models that emerge from the data are poised at a very special point in their parameter space--a critical point. This suggests there may be some deeper theoretical principle behind the behavior of these diverse systems.Comment: 21 page

Role of correlation and regression analysis in the diagnosis of cardiovascular desynchronization among locomotive drivers in Russia

Background. The main manifestations of cardiovascular dysfunctions are increase in blood pressure and heart rate and endothelial dysfunctions leading to cardiovascular diseases (CVDs). This work aims to explain the pathophysiological approach of desynchronization for diagnosis of a disease at an early stage. Subjects and Methods. After clearance from the review board of the institute and informed consent from the subjects, 48 locomotive drivers from Chelyabinsk station were examined. The control group included 28 healthy students and employees of RUDN University who were matched by age and sex. The automated pre-trip medical examination system (hardware-software complex KAPD-01-st “system technologies,” St. Petersburg) was used to measure the heart rate (HR), systolic blood pressure (SBP) and diastolic blood pressure (DBP). The control subjects underwent continuous automatic monitoring (TM2421, A & D, Japan) for 2 to 7 days (96-336 measurements each). This method has also been further illustrated by monitoring data of other persons. Regression analysis was used for correlation of desynchronization with manifestations of CVDs. Results. A total of 380-400 observations were made for each of the screened locomotive drivers. Taking into account only the correlation coefficients without determining their statistical significance, hides the possibility of logical errors. If we classify the strength of the correlation as high, medium and weak, the values of the correlation coefficients in the given example could be interpreted as a manifestation of a strong association. However, the regression coefficients, the magnitude of their standard error and the statistical significance of the estimates confirm a very close relationship between SBP and DBP (P = 0.0004). But at the same time they testify to the independence of the HR both from the SBP (P = 0.279) and from the DBP (P = 0.185). The HR at this point of time was almost constant, as it was controlled by a pacemaker implanted earlier. Conclusions. To identify desynchronization, in addition to evaluating the specific rhythms’ parameters, it requires specialized software tools. However, simple methods can be used to ensure the consistency and /or degree of mismatch in physiological functions. The complex correlation and regression analyses of observed phenomena are easily accessible due to technological advancements. © Nova Science Publishers, Inc

A phase II trial of cisplatin (C), gemcitabine (G) and gefitinib for advanced urothelial tract carcinoma: results of Cancer and Leukemia Group B (CALGB) 90102

Background: This phase II trial (Cancer and Leukemia Group B 90102) sought to determine the efficacy of cisplatin, standard infusion of gemcitabine and gefitinib in patients with advanced urothelial carcinoma

Association of clinical factors and recent anticancer therapy with COVID-19 severity among patients with cancer: a report from the COVID-19 and Cancer Consortium.

Patients with cancer may be at high risk of adverse outcomes from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We analyzed a cohort of patients with cancer and coronavirus 2019 (COVID-19) reported to the COVID-19 and Cancer Consortium (CCC19) to identify prognostic clinical factors, including laboratory measurements and anticancer therapies. Patients with active or historical cancer and a laboratory-confirmed SARS-CoV-2 diagnosis recorded between 17 March and 18 November 2020 were included. The primary outcome was COVID-19 severity measured on an ordinal scale (uncomplicated, hospitalized, admitted to intensive care unit, mechanically ventilated, died within 30 days). Multivariable regression models included demographics, cancer status, anticancer therapy and timing, COVID-19-directed therapies, and laboratory measurements (among hospitalized patients). A total of 4966 patients were included (median age 66 years, 51% female, 50% non-Hispanic white); 2872 (58%) were hospitalized and 695 (14%) died; 61% had cancer that was present, diagnosed, or treated within the year prior to COVID-19 diagnosis. Older age, male sex, obesity, cardiovascular and pulmonary comorbidities, renal disease, diabetes mellitus, non-Hispanic black race, Hispanic ethnicity, worse Eastern Cooperative Oncology Group performance status, recent cytotoxic chemotherapy, and hematologic malignancy were associated with higher COVID-19 severity. Among hospitalized patients, low or high absolute lymphocyte count; high absolute neutrophil count; low platelet count; abnormal creatinine; troponin; lactate dehydrogenase; and C-reactive protein were associated with higher COVID-19 severity. Patients diagnosed early in the COVID-19 pandemic (January-April 2020) had worse outcomes than those diagnosed later. Specific anticancer therapies (e.g. R-CHOP, platinum combined with etoposide, and DNA methyltransferase inhibitors) were associated with high 30-day all-cause mortality. Clinical factors (e.g. older age, hematological malignancy, recent chemotherapy) and laboratory measurements were associated with poor outcomes among patients with cancer and COVID-19. Although further studies are needed, caution may be required in utilizing particular anticancer therapies. NCT04354701