Bose--Einstein Condensation in the Large Deviations Regime with Applications to Information System Models

We study the large deviations behavior of systems that admit a certain form of a product distribution, which is frequently encountered both in Physics and in various information system models. First, to fix ideas, we demonstrate a simple calculation of the large deviations rate function for a single constraint (event). Under certain conditions, the behavior of this function is shown to exhibit an analogue of Bose--Einstein condensation (BEC). More interestingly, we also study the large deviations rate function associated with two constraints (and the extension to any number of constraints is conceptually straightforward). The phase diagram of this rate function is shown to exhibit as many as seven phases, and it suggests a two--dimensional generalization of the notion of BEC (or more generally, a multi--dimensional BEC). While the results are illustrated for a simple model, the underlying principles are actually rather general. We also discuss several applications and implications pertaining to information system models

Pro-/antiinflammatory dysregulation in early psychosis: Results from a 1-year follow-Up study

Background: Previous studies indicated a systemic deregulation of the pro-/antiinflammatory balance in subjects after 6 months of a first psychotic episode. This disruption was reexamined 12 months after diagnosis to identify potential risk/ protective factors and associations with symptom severity. Methods: Eighty-five subjects were followed during 12 months and the determination of the same pro-/antiinflammatory mediators was carried out in plasma and peripheral blood mononuclear cells. Multivariate logistic regression analyses were used to identify risk/protective factors. Multiple linear regression models were performed to detect the change of each biological marker during follow-up in relation to clinical characteristics and confounding factors. Results: This study suggests a more severe systemic pro-/antiinflammatory deregulation than in earlier pathological stages in first psychotic episode, because not only were intracellular components of the inflammatory response increased but also the majority of soluble elements. Nitrite plasma levels and cyclooxygenase-2 expression in peripheral blood mononuclear cells are reliable potential risk factors and 15d-prostaglandin-J2 plasma levels a protection biomarker. An interesting relationship exists between antipsychotic dose and the levels of prostaglandin-E2 (inverse) and 15d-prostaglandin-J2 (direct). An inverse relationship between the Global Assessment of Functioning scale and lipid peroxidation is also present. Conclusions: Summing up, pro-/antiinflammatory mediators can be used as risk/protection biomarkers. The inverse association between oxidative/nitrosative damage and the Global Assessment of Functioning scale, and the possibility that one of the targets of antipsychotics could be the restoration of the pro-/antiinflammatory balance support the use of antiinflammatory drugs as coadjuvant to antipsychotics

Donor Lymphocyte Infusions After Allogeneic Stem Cell Transplantation in Acute Leukemia: A Survey From the Gruppo Italiano Trapianto Midollo Osseo (GITMO)

We conducted a retrospective multicenter study including pediatric and adult patients with acute leukemia (AL) who received donor lymphocyte infusions (DLIs) after allogeneic hematopoietic stem cell transplantation (HCT) between January 1, 2010 and December 31, 2015, in order to determine the efficacy and toxicity of the immune treatment. Two hundred fifty-two patients, median age 45.1 years (1.6\u201373.4), were enrolled from 34 Italian transplant centers. The underlying disease was acute myeloid leukemia in 180 cases (71%). Donors were HLA identical or 1 locus mismatched sibling (40%), unrelated (40%), or haploidentical (20%). The first DLI was administered at a median time of 258 days (55\u20133,784) after HCT. The main indication for DLI was leukemia relapse (73%), followed by mixed chimerism (17%), and pre-emptive/prophylactic use (10%). Ninety-six patients (38%) received one single infusion, whereas 65 (26%), 42 (17%), and 49 patients (19%) received 2, 3, or 654 infusions, respectively, with a median of 31 days between two subsequent DLIs. Forty percent of evaluable patients received no treatment before the first DLI, whereas radiotherapy, conventional chemotherapy or targeted treatments were administered in 3, 39, and 18%, respectively. In informative patients, a few severe adverse events were reported: grade III\u2013IV graft versus host disease (GVHD) (3%), grade III\u2013IV hematological toxicity (11%), and DLI-related mortality (9%). Forty-six patients (18%) received a second HCT after a median of 232 days (32\u20131,390) from the first DLI. With a median follow-up of 461 days (2\u20133,255) after the first DLI, 1-, 3-, and 5- year overall survival (OS) of the whole group from start of DLI treatment was 55, 39, and 33%, respectively. In multivariate analysis, older recipient age, and transplants from haploidentical donors significantly reduced OS, whereas DLI for mixed chimerism or as pre-emptive/prophylactic treatment compared to DLI for AL relapse and a schedule including more than one DLI significantly prolonged OS. This GITMO survey confirms that DLI administration in absence of overt hematological relapse and multiple infusions are associated with a favorable outcome in AL patients. DLI from haploidentical donors had a poor outcome and may represent an area of further investigation

Rare Variants in 48 Genes Account for 42% of Cases of Epilepsy With or Without Neurodevelopmental Delay in 246 Pediatric Patients

In order to characterize the genetic architecture of epilepsy in a pediatric population from the Iberian Peninsula (including the Canary Islands), we conducted targeted exome sequencing of 246 patients with infantile-onset seizures with or without neurodevelopmental delay. We detected 107 variants in 48 different genes, which were implicated in neuronal excitability, neurodevelopment, synaptic transmission, and metabolic pathways. In 104 cases (42%) we detected variant(s) that we classified as pathogenic or likely pathogenic. Of the 48 mutated genes, 32 were dominant, 8 recessive and 8 X-linked. Of the patients for whom family studies could be performed and in whom pathogenic variants were identified in dominant or X-linked genes, 82% carried de novo mutations. The involvement of small copy number variations (CNVs) is 9%. The use of progressively updated custom panels with high mean vertical coverage enabled establishment of a definitive diagnosis in a large proportion of cases (42%) and detection of CNVs (even duplications) with high fidelity. In 10.5% of patients we detected associations that are pending confirmation via functional and/or familial studies. Our findings had important consequences for the clinical management of the probands, since a large proportion of the cohort had been clinically misdiagnosed, and their families were subsequently able to avail of genetic counseling. In some cases, a more appropriate treatment was selected for the patient in question, or an inappropriate treatment discontinued. Our findings suggest the existence of modifier genes that may explain the incomplete penetrance of some epilepsy-related genes. We discuss possible reasons for non-diagnosis and future research directions. Further studies will be required to uncover the roles of structural variants, epimutations, and oligogenic inheritance in epilepsy, thereby providing a more complete molecular picture of this disease. In summary, given the broad phenotypic spectrum of most epilepsy-related genes, efficient genomic tools like the targeted exome sequencing panel described here are essential for early diagnosis and treatment, and should be implemented as first-tier diagnostic tools for children with epilepsy without a clear etiologic basis

Medically unexplained pain complaints are associated with underlying unrecognized mood disorders in primary care

<p>Abstract</p> <p>Background</p> <p>Patients with chronic pain frequently display comorbid depression, but the impact of this concurrence is often underestimated and mistreated. The aim of this study was to determine the prevalence of unrecognized major depression and other mood disorders and comorbid unexplained chronic pain in primary care settings and to explore the associated factors.</p> <p>Also, to compare the use of health services by patients with unexplained chronic pain, both with and without mood disorder comorbidity.</p> <p>Methods</p> <p>A cross-sectional study was carried out in a sample of primary care centers. 3189 patients consulting for "unexplained chronic pain" were assessed by the Visual Analogue Scales (VAS) and the Primary Care Evaluation of Mental Disorders (PRIME-MD) questionnaire.</p> <p>Results</p> <p>We report: a) a high prevalence of unrecognized mood disorders in patients suffering from unexplained chronic pain complaints (80.4%: CI 95%: 79.0%; 81.8%); b) a greater susceptibility of women to mood disorders (OR adjusted = 1.48; CI 95%:1.22; 1.81); c) a direct relationship between the prevalence of mood disorders and the duration of pain (OR adjusted = 1.01; CI 95%: 1.01; 1.02) d) a higher comorbidity with depression if the pain etiology was unknown (OR adjusted = 1.74; CI 95%: 1.45; 2.10) and, e) an increased use of health care services in patients with such a comorbidity (p < 0.0001).</p> <p>Conclusions</p> <p>The prevalence of undiagnosed mood disorders in patients with unexplained chronic pain in primary care is very high, leading to dissatisfaction with treatment processes and poorer outcomes. Consequently, it seems necessary to explore this condition more regularly in general practice in order to reach accurate diagnoses and to select the appropriate treatment.</p

Correction to: Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium (<em>Journal of NeuroEngineering and Rehabilitation</em>, (2023), 20, 1, (78), 10.1186/s12984-023-01198-5)

\ua9 The Author(s) 2024.Following publication of the original article [1], the author noticed the errors in Table 1, and in Discussion section. In Table 1 under Metric (Gait sequence detection) column, the algorithms GSDB was updated with wrong description, input, output, language and citation and GSDc with wrong description has been corrected as shown below: (Table presented.) Description of algorithms for each metric: gait sequence detection (GSD), initial contact event detection (ICD), cadence estimation (CAD) and stride length estimation (SL) Metric Name Description Input Output Language References GSDA Based on a frequency-based approach, this algorithm is implemented on the vertical and anterior–posterior acceleration signals. First, these are band pass filtered to keep frequencies between 0.5 and 3 Hz. Next, a convolution of a 2 Hz sinewave (representing a template for a gait cycle) is performed, from which local maxima will be detected to define the regions of gait acc_v: vertical acceleration acc_ap: anterior–posterior acceleration WinS = 3 s; window size for convolution OL = 1.5 s; overlap of windows Activity_thresh = 0.01; Motion threshold Fs: sampling frequency Start: beginning of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector End: termination of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector Matlab\uae Iluz, Gazit [40] GSDB This algorithm, based on a time domain-approach, detects the gait periods based on identified steps. First, the norm of triaxial acceleration signal is low-pass filtered (FIR, fc = 3.2 Hz), then a peak detection procedure using a threshold of 0.1 [g] is applied to identify steps. Consecutive steps, detected using an adaptive step duration threshold are associated to gait sequences acc_norm: norm of the 3D-accelerometer signal Fs: sampling frequency th: peak detection threshold: 0.1 (g) Start: beginning of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector End: termination of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector Matlab\uae Paraschiv-Ionescu, Newman [41] GSDc This algorithm utilizes the same approach as GSDBthe only difference being a different threshold for peak detection of 0.15 [g] acc_norm: norm of the 3D-accelerometer signal Fs: sampling frequency th: peak detection threshold: 0.15 (g) Start: beginning of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector End: termination of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector Matlab\uae Paraschiv-Ionescu, Newman [41] In Discussion section, the paragraph should read as "Based on our findings collectively, we recommend using GSDB on cohorts with slower gait speeds and substantial gait impairments (e.g., proximal femoral fracture). This may be because this algorithm is based on the acceleration norm (overall accelerometry signal rather than a specific axis/direction (e.g., vertical), hence it is more robust to sensor misalignments that are common in unsupervised real-life settings. Moreover, the use of adaptive threshold, that are derived from the features of a subject’s data and applied to step duration for detection of steps belonging to gait sequences, allows increased robustness of the algorithm to irregular and unstable gait patterns" instead of “Based on our findings collectively, we recommend using GSDB on cohorts with slower gait speeds and substantial gait impairments (e.g., proximal femoral fracture). This may be because this algorithm is based on the acceleration norm (overall accelerometry signal rather than a specific axis/direction (e.g., vertical), hence it is more robust to sensor misalignments that are common in unsupervised real-life settings [41]. Moreover, the use of adaptive thresholds, that are derived from the features of a subject’s data and applied to the amplitude of acceleration norm and to step duration for detection of steps belonging to gait sequences, allows increased robustness of the algorithm to irregular and unstable gait patterns”

Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes

Physical mobility is essential to health, and patients often rate it as a high-priority clinical outcome. Digital mobility outcomes (DMOs), such as real-world gait speed or step count, show promise as clinical measures in many medical conditions. However, current research is nascent and fragmented by discipline. This scoping review maps existing evidence on the clinical utility of DMOs, identifying commonalities across traditional disciplinary divides. In November 2019, 11 databases were searched for records investigating the validity and responsiveness of 34 DMOs in four diverse medical conditions (Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease, hip fracture). Searches yielded 19,672 unique records. After screening, 855 records representing 775 studies were included and charted in systematic maps. Studies frequently investigated gait speed (70.4% of studies), step length (30.7%), cadence (21.4%), and daily step count (20.7%). They studied differences between healthy and pathological gait (36.4%), associations between DMOs and clinical measures (48.8%) or outcomes (4.3%), and responsiveness to interventions (26.8%). Gait speed, step length, cadence, step time and step count exhibited consistent evidence of validity and responsiveness in multiple conditions, although the evidence was inconsistent or lacking for other DMOs. If DMOs are to be adopted as mainstream tools, further work is needed to establish their predictive validity, responsiveness, and ecological validity. Cross-disciplinary efforts to align methodology and validate DMOs may facilitate their adoption into clinical practice