Explore the vast range of titles available.

Here, we review a novel concept namely the compensatory immune-regulatory reflex system (CIRS) as applied to the pathophysiology of major depressive disorder (MDD) and bipolar disorder (BD). There is evidence that a substantial subset of individuals with MDD and BD exhibit an activation of the immune-inflammatory response system (IRS), as indicated by an increased production of macrophagic M1 and T helper (Th)-1 pro-inflammatory cytokines, interleukin (IL)-6 trans-signaling, positive acute phase proteins (APPs), and complement factors. These immune aberrations appear to be evident during the course of major affective episodes of either depressive or (hypo) manic polarity. Here, we review (a) the current state of the art of CIRS functions in both mood disorders and (b) the possible role of CIRS-related biomarkers for the understanding of affective disorders within the framework of precision psychiatry that could also provide novel drug targets for both MDD and BD. CIRS-related abnormalities in mood disorders include elevated Th-2 and T regulatory (Treg) activities with increased IL-4 and IL-10 production, classical IL-6 signaling, increased levels of sIL-1R antagonist (sIL-1RA), soluble IL-2 (sIL-2R) and tumor necrosis factor–α- receptors, and positive APPs, including haptoglobin, hemopexin, α1-acid glycoprotein, α1-antitrypsin, and ceruloplasmin. It is concluded that CIRS is involved in MDD and BD by regulating the primary immune-inflammatory response, thereby contributing to spontaneous and antidepressant-promoted recovery from the acute phase of illness. Signs of activated IRS and CIRS pathways are observed in the remitted phases of both disorders indicating that there is no return to the original homeostasis after an acute episode, while later episodes of mood disorders are characterized by sensitized IRS and CIRS responses. New z-unit weighted composite biomarker scores are proposed, which reflect different aspects of IRS versus CIRS activation and may be used to estimate different IRS/CIRS activity ratios in mood and other neuroimmune disorders.

Human mobility has a significant impact on several layers of society, from infrastructural planning and economics to the spread of diseases and crime. Representing the system as a complex network, in which nodes are assigned to regions ( e . g ., a city) and links indicate the flow of people between two of them, physics-inspired models have been proposed to quantify the number of people migrating from one city to the other. Despite the advances made by these models, our ability to predict the number of commuters and reconstruct mobility networks remains limited. Here, we propose an alternative approach using machine learning and 22 urban indicators to predict the flow of people and reconstruct the intercity commuters network. Our results reveal that predictions based on machine learning algorithms and urban indicators can reconstruct the commuters network with 90.4% of accuracy and describe 77.6% of the variance observed in the flow of people between cities. We also identify essential features to recover the network structure and the urban indicators mostly related to commuting patterns. As previously reported, distance plays a significant role in commuting, but other indicators, such as Gross Domestic Product (GDP) and unemployment rate, are also driven-forces for people to commute. We believe that our results shed new lights on the modeling of migration and reinforce the role of urban indicators on commuting patterns. Also, because link-prediction and network reconstruction are still open challenges in network science, our results have implications in other areas, like economics, social sciences, and biology, where node attributes can give us information about the existence of links connecting entities in the network.

Alcohol use disorders consist of disorders characterised by compulsive heavy alcohol use and loss of control over alcohol intake. Alcohol use disorders are some of the most prevalent mental disorders globally, especially in high-income and upper-middle-income countries; and are associated with high mortality and burden of disease, mainly due to medical consequences, such as liver cirrhosis or injury. Despite their high prevalence, alcohol use disorders are undertreated partly because of the high stigma associated with them, but also because of insufficient systematic screening in primary health care, although effective and cost-effective psychosocial and pharmacological interventions do exist. Primary health care should be responsible for most treatment, with routine screening for alcohol use, and the provision of a staggered treatment response, from brief advice to pharmacological treatment. Clinical interventions for these disorders should be embedded in a supportive environment, which can be bolstered by the creation of alcohol control policies aimed at reducing the overall level of consumption.

Bipolar disorder has a yearly prevalence of 2%. Other mental and physical conditions occur with bipolar disorder, which is also associated with an increased risk of suicide. Treatment is complex and relies on lithium or intermittent use of antipsychotic drugs.

Schizophrenia substantially contributes to the burden of mental disorders. Schizophrenia’s burden and epidemiological estimates in some countries have been published, but updated estimates of prevalence, incidence, and schizophrenia-related disability at the global level are lacking. Here, we present the data from and critically discuss the Global Burden of Diseases, Injuries, and Risk Factors Study data, focusing on temporal changes in schizophrenia’s prevalence, incidence, and disability-adjusted life years (DALYs) globally. From 1990 to 2019, schizophrenia raw prevalence (14.2 to 23.6 million), incidence (941,000 to 1.3 million), and DALYs (9.1 to 15.1 million) increased by over 65%, 37%, and 65% respectively, while age-standardized estimates remained stable globally. In countries with high socio-demographic index (SDI), both prevalence and DALYs increased, while in those with low SDI, the age-standardized incidence decreased and DALYs remained stable. The male/female ratio of burden of schizophrenia has remained stable in the overall population over the past 30 years (i.e., M/F = 1.1), yet decreasing from younger to older age groups (raw prevalence in females higher than males after age 65, with males having earlier age of onset, and females longer life expectancy). Results of this work suggest that schizophrenia’s raw prevalence, incidence, and burden have been increasing since 1990. Age-adjusted estimates did not reduce. Schizophrenia detection in low SDI countries is suboptimal, and its prevention/treatment in high SDI countries should be improved, considering its increasing prevalence. Schizophrenia sex ratio inverts throughout the lifespan, suggesting different age of onset and survival by sex. However, prevalence and burden estimates for schizophrenia are probably underestimated. GBD does not account for mortality from schizophrenia (and other mental disorders, apart from anorexia nervosa).

We prove that centralisers of elements in [finitely generated free]-by-cyclic groups are computable. As a corollary, given two conjugate elements in a [finitely generated free]-by-cyclic group, the set of conjugators can be computed and the conjugacy problem with context-free constraints is decidable. We pose several problems arising naturally from this work.

In massive data analysis, data usually come in streams. In the last years, several studies have investigated novelty detection in these data streams. Different approaches have been proposed and validated in many application domains. A review of the main aspects of these studies can provide useful information to improve the performance of existing approaches, allow their adaptation to new applications and help to identify new important issues to be addresses in future studies. This article presents and analyses different aspects of novelty detection in data streams, like the offline and online phases, the number of classes considered at each phase, the use of ensemble versus a single classifier, supervised and unsupervised approaches for the learning task, information used for decision model update, forgetting mechanisms for outdated concepts, concept drift treatment, how to distinguish noise and outliers from novelty concepts, classification strategies for data with unknown label, and how to deal with recurring classes. This article also describes several applications of novelty detection in data streams investigated in the literature and discuss important challenges and future research directions.

PurposeThis article offers a novel approach that brings together management, engineering and organizational behavior. It focuses on the understanding of organizational dynamics in an era of technological change, upholding the importance of organizational agility and of the cultural paradigm in the management of organizations.Design/methodology/approachIn this work, the authors present the conclusions from a set of studies carried out in organizations operating in technical and technological industries. The authors assessed the capabilities of these organizations in terms of operational excellence maturity and its impact on the organizational culture and organizational agility.FindingsResults show the importance of operational excellence either in developing or expanding organizational agility capabilities while reinforcing the cruciality of an excellence-oriented culture to sustain these efforts over time.Originality/valueIncreasingly unstable business environments have led to a growing interest in how to develop and maintain operational excellence in the face of continued and disruptive change. However, this interest has, so far, been advanced with little empirical evidence to support the corresponding predictions. This work offers the first practical evidence that continued focus and optimization of operations, with the right cultural alignment, helps organizations survive and thrive in increasingly volatile, uncertain, complex and ambiguous environments.

We obtain conditions of uniform continuity for endomorphisms of free-abelian times free groups for the product metric defined by taking the prefix metric in each component and establish an equivalence between uniform continuity for this metric and the preservation of a coarse-median, a concept recently introduced by Fioravanti. Considering the extension of an endomorphism to the completion, we count the number of orbits for the action of the subgroup of fixed points (respectively periodic) points on the set of infinite fixed (respectively periodic) points. Finally, we study the dynamics of infinite points: for automorphisms and some endomorphisms, defined in a precise way, fitting a classification given by Delgado and Ventura, we prove that every infinite point is either periodic or wandering, which implies that the dynamics is asymptotically periodic.