Urgent Need to Understand and Prevent Gonococcal Infection: From the Laboratory to Real-World Context.

Neisseria gonorrhoeae is widespread globally. Primary prevention is unsuccessful and antimicrobial resistance threatens optimal management. There is no specific vaccine and natural infection studies show that N. gonorrhoeae can avoid and suppress immune responses. In addition to extensive variation in expression and specificity of many gonococcal surface antigens, it induces a robust inflammatory response through the Th17 pathway with a large influx of neutrophils and inflammatory cytokines but evades macrophages. The Th1- and Th2-mediated response is suppressed, resulting in low, short-lived antibody titers. Real-world evidence suggests that gonorrhea cases are reduced among recipients of N. meningitidis group B vaccines containing outer membrane vesicles (OMV). Although the first randomized trial of an OMV-containing MenB vaccine against N. gonorrhoeae infection did not show statistically significant vaccine efficacy, ongoing trials might shed further light. Several candidate vaccine antigens for a gonococcal-specific vaccine are being evaluated preclinically but only one has reached clinical trials.

Advances in the understanding of the pathophysiology of schizophrenia and bipolar disorder through induced pluripotent stem cell models.

The pathophysiology of schizophrenia and bipolar disorder involves a complex interaction between genetic and environmental factors that begins in the early stages of neurodevelopment. Recent advancements in the field of induced pluripotent stem cells (iPSCs) offer a promising tool for understanding the neurobiological alterations involved in these disorders and, potentially, for developing new treatment options. In this review, we summarize the results of iPSC-based research on schizophrenia and bipolar disorder, showing disturbances in neurodevelopmental processes, imbalance in glutamatergic-GABAergic transmission and neuromorphological alterations. The limitations of the reviewed literature are also highlighted, particularly the methodological heterogeneity of the studies, the limited number of studies developing iPSC models of both diseases simultaneously, and the lack of in-depth clinical characterization of the included samples. Further studies are needed to advance knowledge on the common and disease-specific pathophysiological features of schizophrenia and bipolar disorder and to promote the development of new treatment options.

Safety of electroconvulsive therapy (ECT) in pregnancy: a systematic review of case reports and case series.

Pregnancy and the immediate postpartum period are considered at high risk for women who have already received a previous psychiatric diagnosis and might represent a stressful event favoring the onset of new psychiatric disorders. The electroconvulsive therapy (ECT) is effective for the treatment of severe, treatment-resistant mental disorders, and it could represent a therapeutic choice for psychiatric conditions during pregnancy. The purpose of this systematic review is to evaluate the safety of ECT during pregnancy and to update the state of the art of its use. An extensive literature search on PubMed, APA PsycInfo, and Scopus databases for relevant articles published from inception to September 2023 has been performed. A final number of 45 articles (34 case reports and 11 case series, for a total of 130 pregnant women) were included in the present review. The limited evidence confirmed that ECT is effective in determining a partial remission of symptoms in women suffering from severe mental disorders, especially in the presence of suicidal ideation or psychosis, during all pregnancy epochs. However, ECT is not free from side effects, although the majority of possible complications were of low- or moderate-grade and not life-threatening for the women. Exposure to pharmacological treatment before or during the ECT or to the anesthetic during ECT might have contributed to the onset of these complications. ECT techniques evolved over years, increasing the degree of its safety, and according to our review it appears to be relatively safe and effective during pregnancy in the majority of cases.

Clinical and psychological factors associated with resilience in patients with schizophrenia: data from the Italian network for research on psychoses using machine learning.

BACKGROUND: Resilience is defined as the ability to modify thoughts to cope with stressful events. Patients with schizophrenia (SCZ) having higher resilience (HR) levels show less severe symptoms and better real-life functioning. However, the clinical factors contributing to determine resilience levels in patients remain unclear. Thus, based on psychological, historical, clinical and environmental variables, we built a supervised machine learning algorithm to classify patients with HR or lower resilience (LR). METHODS: SCZ from the Italian Network for Research on Psychoses (N = 598 in the Discovery sample, N = 298 in the Validation sample) underwent historical, clinical, psychological, environmental and resilience assessments. A Support Vector Machine algorithm (based on 85 variables extracted from the above-mentioned assessments) was built in the Discovery sample, and replicated in the Validation sample, to classify between HR and LR patients, within a nested, Leave-Site-Out Cross-Validation framework. We then investigated whether algorithm decision scores were associated with the cognitive and clinical characteristics of patients. RESULTS: The algorithm classified patients as HR or LR with a Balanced Accuracy of 74.5% (p < 0.0001) in the Discovery sample, and 80.2% in the Validation sample. Higher self-esteem, larger social network and use of adaptive coping strategies were the variables most frequently chosen by the algorithm to generate decisions. Correlations between algorithm decision scores, socio-cognitive abilities, and symptom severity were significant (pFDR < 0.05). CONCLUSIONS: We identified an accurate, meaningful and generalizable clinical-psychological signature associated with resilience in SCZ. This study delivers relevant information regarding psychological and clinical factors that non-pharmacological interventions could target in schizophrenia.

Insight in cognitive impairment assessed with the Cognitive Assessment Interview in a large sample of patients with schizophrenia.

The Cognitive Assessment Interview (CAI) is an interview-based scale measuring cognitive impairment and its impact on functioning in subjects with schizophrenia (SCZ). The present study aimed at assessing, in a large sample of SCZ (n = 601), the agreement between patients and their informants on CAI ratings, to explore patients' insight in their cognitive deficits and its relationships with clinical and functional indices. Agreement between patient- and informant-based ratings was assessed by the Gwet's agreement coefficient. Predictors of insight in cognitive deficits were explored by stepwise multiple regression analyses. Patients reported lower severity of cognitive impairment vs. informants. A substantial to almost perfect agreement was observed between patients' and informants' ratings. Lower insight in cognitive deficits was associated to greater severity of neurocognitive impairment and positive symptoms, lower severity of depressive symptoms, and older age. Worse real-life functioning was associated to lower insight in cognitive deficit, worse neurocognitive performance, and worse functional capacity. Our findings indicate that the CAI is a valid co-primary measure with the interview to patients providing a reliable assessment of their cognitive deficits. In the absence of informants with good knowledge of the subject, the interview to the patient may represent a valid alternative.

Myocardial bridge in a patient with castration-resistant metastatic prostate cancer treated with enzalutamide.

INTRODUCTION: Myocardial bridge is a morphological anomaly of the heart characterised by the presence of a myocardial segment above a coronary artery, which results in a higher risk of cardiovascular events. In patients with prostate cancer treated with androgen receptor-targeted agents, a higher risk of cardiotoxicity was observed. CASE REPORT: An 88 years old man with metastatic castration-resistant prostate cancer in treatment with enzalutamide, denosumab, and triptorelin presented to our attention complaining dyspnoea and angina pectoris. MANAGEMENT AND OUTCOME: Blood examinations revealed normal Troponin I levels. Transthoracic echocardiography revealed no signs of acute myocardial ischaemia. The treadmill stress test revealed S-T tract under levelling in V4-V6 with a very slow resolution. Coronary angiography identified a myocardial bridge in the medium tract of the interventricular anterior artery. Due to these findings, ranolazine and simvastatin were started and, after multidisciplinary assessment, we decided to continue the treatment with enzalutamide. At the first follow-up visit echocardiography found out the cardiological reports stability and no therapy changes were performed. During follow-up visit cardiological revaluation showed reports stability and no therapy changes were performed. DISCUSSION: Due to the high prevalence of prostate cancer in elderly patients at high cardiovascular risk and the increasing use of androgen receptor-targeted agent, a multidisciplinary approach is highly recommended to weigh survival benefits on toxicities. This case report may support the use of androgen receptor-targeted agent in elderly patients with controlled cardiovascular diseases, a population that is often excluded from randomised trials.

Thalamocortical bistable switch as a theoretical model of fibromyalgia pathogenesis inferred from a literature survey.

Fibromyalgia (FM) is an unsolved central pain processing disturbance. We aim to provide a unifying model for FM pathogenesis based on a loop network involving thalamocortical regions, i.e., the ventroposterior lateral thalamus (VPL), the somatosensory cortex (SC), and the thalamic reticular nucleus (TRN). The dynamics of the loop have been described by three differential equations having neuron mean firing rates as variables and containing Hill functions to model mutual interactions among the loop elements. A computational analysis conducted with MATLAB has shown a transition from monostability to bistability of the loop behavior for a weakening of GABAergic transmission between TRN and VPL. This involves the appearance of a high-firing-rate steady state, which becomes dominant and is assumed to represent pathogenic pain processing giving rise to chronic pain. Our model is consistent with a bulk of literature evidence, such as neuroimaging and pharmacological data collected on FM patients, and with correlations between FM and immunoendocrine conditions, such as stress, perimenopause, chronic inflammation, obesity, and chronic dizziness. The model suggests that critical targets for FM treatment are to be found among immunoendocrine pathways leading to GABA/glutamate imbalance having an impact on the thalamocortical system.

Vertex results for the robust analysis of uncertain biochemical systems.

We consider the problem of assessing the sensitivity of uncertain biochemical systems in the presence of input perturbations (either constant or periodic) around a stable steady state. In particular, we propose approaches for the robust sensitivity analysis of systems with uncertain parameters assumed to take values in a hyper-rectangle. We highlight vertex results, which allow us to check whether a property is satisfied for all parameter choices in the hyper-rectangle by simply checking whether it is satisfied for all parameter choices at the vertices of the hyper-rectangle. We show that, for a vast class of systems, including (bio)chemical reaction networks with mass-action kinetics, the system Jacobian has a totally multiaffine structure (namely, all minors of the Jacobian matrix are multiaffine functions of the uncertain parameters), which can be exploited to obtain several vertex results. We consider different problems: robust non-singularity; robust stability of the steady-state; robust steady-state sensitivity analysis, in the case of constant perturbations; robust frequency-response sensitivity analysis, in the presence of periodic perturbations; and robust adaptation analysis. The developed theory is then applied to gain insight into some examples of uncertain biochemical systems, including the incoherent feed-forward loop, the coherent feed-forward loop, the Brusselator oscillator and the Goldbeter oscillator.

Worldwide initiatives aimed to train professionals in the use of the ICD-11.

BACKGROUND: The chapter on mental disorders of the 11th revision of the International Classification of Diseases (ICD-11) has been now finalized. Training of mental health professionals in the use of the chapter is taking place worldwide. Information is provided on the ICD-11 training courses taking place recently, including that co-organized by the Naples World Health Organization (WHO) Collaborating Centre on Research and Training in Mental Health and the European Psychiatric Association; those which will be held in the next few months, such as the one co-organized by the World Psychiatric Association and the Global Mental Health Academy, to be held online from 8 to 29 November 2021; and the training course set up by the WHO Collaborating Centre on Mental Health at the Columbia University, in collaboration with the WHO Department of Mental Health and Substance Use, which can be accessed only by the members of the WHO Global Clinical Practice Network. CONCLUSION: Psychiatrists of all countries of the world are encouraged to become familiar with the ICD-11 chapter on mental disorders, which will be adopted shortly by most countries worldwide.

Data-driven methods for present and future pandemics: Monitoring, modelling and managing.

This survey analyses the role of data-driven methodologies for pandemic modelling and control. We provide a roadmap from the access to epidemiological data sources to the control of epidemic phenomena. We review the available methodologies and discuss the challenges in the development of data-driven strategies to combat the spreading of infectious diseases. Our aim is to bring together several different disciplines required to provide a holistic approach to epidemic analysis, such as data science, epidemiology, and systems-and-control theory. A 3M-analysis is presented, whose three pillars are: Monitoring, Modelling and Managing. The focus is on the potential of data-driven schemes to address three different challenges raised by a pandemic: (i) monitoring the epidemic evolution and assessing the effectiveness of the adopted countermeasures; (ii) modelling and forecasting the spread of the epidemic; (iii) making timely decisions to manage, mitigate and suppress the contagion. For each step of this roadmap, we review consolidated theoretical approaches (including data-driven methodologies that have been shown to be successful in other contexts) and discuss their application to past or present epidemics, such as Covid-19, as well as their potential application to future epidemics.

Loop analysis of blood pressure/volume homeostasis.

We performed a mathematical analysis of the dynamic control loops regulating the vasomotor tone of vascular smooth muscle, blood volume, and mean arterial pressure, which involve the arginine vasopressin (AVP) system, the atrial natriuretic peptide system (ANP), and the renin-angiotensin-aldosterone system (RAAS). Our loop analysis of the AVP-ANP-RAAS system revealed the concurrent presence of two different regulatory mechanisms, which perform the same qualitative function: one affects blood pressure by regulating vasoconstriction, the other by regulating blood volume. Both the systems are candidate oscillators consisting of the negative-feedback loop of a monotone system: they admit a single equilibrium that can either be stable or give rise to oscillatory instability. Also a subsystem, which includes ANP and AVP stimulation of vascular smooth muscle cells, turns out to be a candidate oscillator composed of a monotone system with multiple negative feedback loops, and we show that its oscillatory potential is higher when the delays along all feedback loops are comparable. Our results give insight into the physiological mechanisms ruling long-term homeostasis of blood hydraulic parameters, which operate based on dynamical loops of interactions.

Die "Präzisionspsychiatrie" muss Teil der "personalisierten Psychiatrie" werden.

'Precision medicine' is defined as 'an emerging approach for treatment and prevention that takes into account each person's variability in genes, environment, and lifestyle'. Sometimes the term 'personalized medicine' is also used, either as a synonym or in a broader sense. In psychiatry, the term 'personalized' applies to different levels of health-care provision, such as the service organization and the choice of treatment plans based on the characterization of the individual patient. This approach is already feasible but, currently, it is often hampered by the shortage of human and financial resources. Recently, the terminology of 'precision medicine' has been extended to psychiatry: the term 'precision psychiatry' refers to the full exploitation of recent scientific and technological advances to achieve a close match between individual biosignature and prevention / treatment strategies. This article provides an overview of recent advances in neuroimaging, multi-omics and computational neuroscience, which have contributed to foster our understanding of the neurobiology of major mental disorders, and led to the implementation of a precision medicine-oriented approach in psychiatry.We argue that, while 'precision psychiatry' represents an important step to further advance the effectiveness of the 'personalized psychiatry', the distinction between the two terms is important to avoid dangerous neglect of the current potential of personalized care in psychiatry and to underscore the need for disseminating good existing practices aimed at organizing mental health services and providing care according to person's psychopathological characteristics, illness trajectory, needs, environment and preferences.In conclusion, 'precision psychiatry' will contribute to advance 'personalized psychiatry', but for the time being keeping the distinction between the two terms will contribute to fully exploit the current potential of personalized care.

Non-clinical safety assessment of single and repeated administration of gE/AS01 zoster vaccine in rabbits.

HZ/su is an investigational recombinant subunit vaccine for the prevention of shingles, a disease resulting from the reactivation of varicella zoster virus. The vaccine is composed of recombinant varicella zoster virus glycoprotein E (gE), and liposome-based Adjuvant System AS01. To evaluate the potential local and systemic effects of this vaccine, three studies were performed in rabbits. In the first two studies, rabbits received a single intramuscular (IM; study 1) or subcutaneous (SC; study 2) dose of gE/AS01, AS01 alone (in study 2 only) or saline, and the local tolerance was evaluated up to 3 days after administration. Under these conditions, only local inflammatory reactions at the injection sites were detected by microscopic evaluation. In the third study, gE/AS01, AS01 alone or saline, were injected SC or IM on four occasions at 2 week intervals. General health status, local tolerance, ophthalmology, haematology and blood chemistry parameters were monitored. Macroscopic and microscopic evaluations were performed after termination of the study. The only treatment-related changes included a transient increase in neutrophils, C-reactive protein and fibrinogen levels and microscopic signs of inflammation at the injection sites, which are expected observations related to the elicited inflammatory reaction. The SC and IM routes of administration produced similar systemic effects. However, microscopic findings at the injection sites differed. One month after the last injection, recovery was complete in all groups. In conclusion, the single and repeated SC and IM administration of the gE/AS01 vaccine were locally and systemically well-tolerated in rabbits and support the clinical development of the vaccine. Copyright © 2016 John Wiley & Sons, Ltd.

IL-1α induces CD11b(low) alveolar macrophage proliferation and maturation during granuloma formation.

Macrophages play a central role in immune and tissue responses of granulomatous lung diseases induced by pathogens and foreign bodies. Circulating monocytes are generally viewed as central precursors of these tissue effector macrophages. Here, we provide evidence that granulomas derive from alveolar macrophages serving as a local reservoir for the expansion of activated phagocytic macrophages. By exploring lung granulomatous responses to silica particles in IL-1-deficient mice, we found that the absence of IL-1α, but not IL-1ß, was associated with reduced CD11b(high) phagocytic macrophage accumulation and fewer granulomas. This defect was associated with impaired alveolar clearance and resulted in the development of pulmonary alveolar proteinosis (PAP). Reconstitution of IL-1α(-/-) mice with recombinant IL-1α restored lung clearance functions and the pulmonary accumulation of CD11b(high) phagocytic macrophages. Mechanistically, IL-1α induced the proliferation of CD11b(low) alveolar macrophages and differentiated these cells into CD11b(high) macrophages which perform critical phagocytic functions and organize granuloma. We newly discovered here that IL-1α triggers lung responses requiring macrophage proliferation and maturation from tissue-resident macrophages.

Computing the structural influence matrix for biological systems.

We consider the problem of identifying structural influences of external inputs on steady-state outputs in a biological network model. We speak of a structural influence if, upon a perturbation due to a constant input, the ensuing variation of the steady-state output value has the same sign as the input (positive influence), the opposite sign (negative influence), or is zero (perfect adaptation), for any feasible choice of the model parameters. All these signs and zeros can constitute a structural influence matrix, whose (i, j) entry indicates the sign of steady-state influence of the jth system variable on the ith variable (the output caused by an external persistent input applied to the jth variable). Each entry is structurally determinate if the sign does not depend on the choice of the parameters, but is indeterminate otherwise. In principle, determining the influence matrix requires exhaustive testing of the system steady-state behaviour in the widest range of parameter values. Here we show that, in a broad class of biological networks, the influence matrix can be evaluated with an algorithm that tests the system steady-state behaviour only at a finite number of points. This algorithm also allows us to assess the structural effect of any perturbation, such as variations of relevant parameters. Our method is applied to nontrivial models of biochemical reaction networks and population dynamics drawn from the literature, providing a parameter-free insight into the system dynamics.