Sanitary Waters: Is It Worth Looking for Mycobacteria?

The freshwater environment is suitable for nontuberculous mycobacteria (NTMs) growth. Their high adaptability represents a considerable risk for sanitary water systems, which are a potential vector for NTMs transmission. This study investigated the occurrence of NTMs, such as , in hospital water systems to support the surveillance and control of potentially pathogenic NTMs.

sCD14-ST and Related Osteoimmunological Biomarkers: A New Diagnostic Approach to Osteomyelitis.

Osteomyelitis (OM) is a major challenge in orthopedic surgery. The diagnosis of OM is based on imaging and laboratory tests, but it still presents some limitations. Therefore, a deeper comprehension of the pathogenetic mechanisms could enhance diagnostic and treatment approaches.

Training in infection prevention and control: survey on the volume and on the learning demands of healthcare-associated infections control figures in the Emilia-Romagna Region (Northern Italy).

Background: In the context of Infections Prevention and Control activities, the training of healthcare-associated infection control figures is crucial; the COVID-19 pandemic further emphasized the necessity of ensuring a widespread and stable level of skills over time for such professionals. The present work aims to identify the number and training needs of the personnel working in the Emilia-Romagna Region's healthcare facilities as "healthcare-associated infection control figures".

Methods: Data were collected through a survey created by experts from the Regional Group "Training in the prevention and control of antibiotic resistance".

Gauge-Optimal Approximate Learning for Small Data Classification.

Small data learning problems are characterized by a significant discrepancy between the limited number of response variable observations and the large feature space dimension. In this setting, the common learning tools struggle to identify the features important for the classification task from those that bear no relevant information and cannot derive an appropriate learning rule that allows discriminating among different classes. As a potential solution to this problem, here we exploit the idea of reducing and rotating the feature space in a lower-dimensional gauge and propose the gauge-optimal approximate learning (GOAL) algorithm, which provides an analytically tractable joint solution to the dimension reduction, feature segmentation, and classification problems for small data learning problems.

Autophagy Markers Are Altered in Alzheimer's Disease, Dementia with Lewy Bodies and Frontotemporal Dementia.

The accumulation of protein aggregates defines distinct, yet overlapping pathologies such as Alzheimer's disease (AD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD). In this study, we investigated ATG5, UBQLN2, ULK1, and LC3 concentrations in 66 brain specimens and 120 plasma samples from AD, DLB, FTD, and control subjects (CTRL). Protein concentration was measured with ELISA kits in temporal, frontal, and occipital cortex specimens of 32 AD, 10 DLB, 10 FTD, and 14 CTRL, and in plasma samples of 30 AD, 30 DLB, 30 FTD, and 30 CTRL.

Clonal Dissemination of Clinical Isolates in Northern Italy, 2021.

is a concerning pathogen in health care due to its ability to spread in medical settings. In this study, we characterized the genome of three clinical isolates collected in the Emilia-Romagna region of Northeastern Italy from January 2020 to May 2021. Whole-genome sequencing was performed using Illumina iSeq 100 and Oxford Nanopore MinION systems.

Evaluation of Synovial Calprotectin by Using a Lateral Flow Test for the Diagnosis of Prosthetic Joint Infections.

The analysis of synovial fluid is a crucial step in the diagnosis of prosthetic joint infections (PJIs). Recently several studies illustrated the efficacy of synovial calprotectin in supporting the diagnosis of PJI. In this study, synovial calprotectin was analyzed by a commercial stool test to explore whether it might accurately predict PJIs.

Exploring multielement nanogranular coatings to forestall implant-related infections.

Introduction: As we approach the post-antibiotic era, the development of innovative antimicrobial strategies that carry out their activities through non-specific mechanisms could limit the onset and spread of drug resistance. In this context, the use of nanogranular coatings of multielement nanoparticles (NPs) conjugated to the surface of implantable biomaterials might represent a strategy to reduce the systemic drawbacks by locally confining the NPs effects against either prokaryotic or eukaryotic cells.

Methods: In the present study, two new multielement nanogranular coatings combining Ag and Cu with either Ti or Mg were synthesized by a gas phase physical method and tested against pathogens isolated from periprosthetic joint infections to address their potential antimicrobial value and toxicity in an experimental setting.

MRI-based artificial intelligence to predict infection following total hip arthroplasty failure.

Purpose: To investigate whether artificial intelligence (AI) can differentiate septic from non-septic total hip arthroplasty (THA) failure based on preoperative MRI features.

Materials And Methods: We included 173 patients (98 females, age: 67 ± 12 years) subjected to first-time THA revision surgery after preoperative pelvis MRI. We divided the patients into a training/validation/internal testing cohort (n = 117) and a temporally independent external-testing cohort (n = 56).

The combined evaluation of fibrinogen and D-dimer levels are a helpful tool to exclude periprosthetic knee infection.

This retrospective study was undertaken to (i) define the most appropriate thresholds for serum d-dimer and fibrinogen for differentiating aseptic failure from periprosthetic joint infection (PJI) and (ii) evaluate the predictive value of our d-dimer and fibrinogen threshold compared to previously proposed thresholds. This observational cohort study included consecutive patients who had undergone total knee arthroplasty (TKA) revision between January 2019 and December 2020. International Consensus Meeting diagnostic criteria were used to identify patients affected by the prosthetic infection.

On cheap entropy-sparsified regression learning.

Regression learning is one of the long-standing problems in statistics, machine learning, and deep learning (DL). We show that writing this problem as a probabilistic expectation over (unknown) feature probabilities - thus increasing the number of unknown parameters and seemingly making the problem more complex-actually leads to its simplification, and allows incorporating the physical principle of entropy maximization. It helps decompose a very general setting of this learning problem (including discretization, feature selection, and learning multiple piece-wise linear regressions) into an iterative sequence of simple substeps, which are either analytically solvable or cheaply computable through an efficient second-order numerical solver with a sublinear cost scaling.

A novel bio-inspired strategy to prevent amyloidogenesis and synaptic damage in Alzheimer's disease.

Alzheimer's disease (AD) is an irreversible neurodegenerative disorder that affects millions of people worldwide. AD pathogenesis is intricate. It primarily involves two main molecular players-amyloid-β (Aβ) and tau-which actually have an intrinsic trend to generate molecular assemblies that are toxic to neurons.

Prediction of Long-Term Recovery From Disability Using Hemoglobin-Based Models: Results From a Cohort of 1,392 Patients Undergoing Spine Surgery.

Hemoglobin and its associated blood values are important laboratory biomarkers that mirror the strength of constitution of patients undergoing spine surgery. Along with the clinical determinants available during the preadmission visit, it is important to explore their potential for predicting clinical success from the patient's perspective in order to make the pre-admission visit more patient-centered. We analyzed data from 1,392 patients with spine deformity, disc disease, or spondylolisthesis enrolled between 2016 and 2019 in our institutional Spine Registry.

eSPA+: Scalable Entropy-Optimal Machine Learning Classification for Small Data Problems.

Classification problems in the small data regime (with small data statistic T and relatively large feature space dimension D) impose challenges for the common machine learning (ML) and deep learning (DL) tools. The standard learning methods from these areas tend to show a lack of robustness when applied to data sets with significantly fewer data points than dimensions and quickly reach the overfitting bound, thus leading to poor performance beyond the training set. To tackle this issue, we propose eSPA+, a significant extension of the recently formulated entropy-optimal scalable probabilistic approximation algorithm (eSPA).

Host Environment Shapes Social Behavior as Revealed by Microscopy Pattern Formation and Dynamic Aggregation Analysis.

Understanding how bacteria adapt their social behavior to environmental changes is of crucial importance from both biological and clinical perspectives. is among the most common infecting agents in orthopedics, but its recalcitrance to the immune system and to antimicrobial treatments in the physiological microenvironment are still poorly understood. By means of optical and confocal microscopy, image pattern analysis, and mathematical modeling, we show that planktonic biofilm-like aggregates and sessile biofilm lifestyles are two co-existing and interacting phases of the same environmentally adaptive developmental process and that they exhibit substantial differences when is grown in physiological fluids instead of common lab media.

Exploratory assessment of serological tests to determine antibody titer against SARS-CoV-2: Appropriateness and limits.

Background: Serological tests can be used to detect antibodies in the serum of subject's after SARS-CoV-2 infection and vaccination. Currently, variability in antibody titers and the availability of a multiplicity of serological tests have made it necessary to highlight their appropriateness and limitations in various diagnostic settings.

Methods: This study is part of Covidiagnostix, a multicenter project aimed at the assessment of the health technology used in SARS-CoV-2 serological tests.

Megaprostheses for the revision of infected hip arthroplasties with severe bone loss.

Background: Periprosthetic hip infections with severe proximal femoral bone loss may require the use of limb salvage techniques, but no agreement exists in literature regarding the most effective treatment. Aim of this study is to analyze the infection eradication rate and implant survival at medium-term follow-up in patients treated with megaprostheses for periprosthetic hip infections with severe bone loss.

Methods: Twenty-one consecutive patients were retrospectively reviewed at a mean 64-month follow-up (24-120).

COVID-19 in Elderly Patients Surgically Treated for Lower Limbs Fracture.

Background: The coronavirus disease 2019 (COVID-19) pandemic outbreak has posed new problems in the context of patients suffering from other diseases. In particular, musculoskeletal sequelae related to the state of debilitation associated with COVID-19 are important to consider in elderly patients undergoing surgery after lower limbs fracture, especially in the post-operative period. The objective of this study was to evaluate whether COVID-19 influenced biochemical parameter, recovery and mortality of surgically treated patients suffering from lower extremity fractures.

Can the Leukocyte Esterase Strip Test Predict Persistence of Periprosthetic Joint Infection at Second-Stage Reimplantation?

Background: We evaluated the reliability of intraoperative assessment of leukocyte esterase (LE) in synovial fluid samples from patients undergoing reimplantation following implant removal and spacer insertion for periprosthetic joint infection (PJI). Our hypothesis was that a positive intraoperative LE test would be a better predictor of persistent infection than either serum C-reactive protein (CRP) or erythrocyte sedimentation rate (ESR) or the combination of serum CRP and ESR.

Methods: The records of 76 patients who received a 2-stage exchange for PJI were retrospectively reviewed.

Quantitative serological evaluation as a valuable tool in the COVID-19 vaccination campaign.

Objectives: After exceptional research efforts, several vaccines were developed against SARS-CoV-2 which sustains the pandemic COVID-19. The Comirnaty vaccine showed high efficacy in clinical trials and was the first to be approved for its distribution to the general population. We evaluated the immune response induced by the first vaccine dose in different sex/age groups and subjects with or without naturally present anti-SARS-CoV-2 antibodies.

Harmonization of six quantitative SARS-CoV-2 serological assays using sera of vaccinated subjects.

Background And Aims: Vaccines, to limit SARS-CoV-2 infection, were produced and reliable assays are needed for their evaluation. The WHO produced an International-Standard (WHO-IS) to facilitate the standardization/comparison of serological methods. The WHO-IS, produced in limited amount, was never tested for reproducibility.

A five-component infection control bundle to permanently eliminate a carbapenem-resistant Acinetobacter baumannii spreading in an intensive care unit.

Background: Carbapenem-resistant Acinetobacter baumannii (CRAB) infection outbreaks are difficult to control and sometimes require cohorting of CRAB-positive patients or temporary ward closure for environmental cleaning. We aimed at controlling the deadly 2018 CRAB outbreak in a 12 bed- intensive care unit (ICU) including 9 beds in a 220 m open space. We implemented a new multimodal approach without ward closure, cohorting or temporarily limiting admissions.