Review on adherence of the literature to official recommendations on albuminuria harmonization and standardization.

Albuminuria standardization is a key issue to produce reliable and equivalent results between laboratories. We investigated whether official recommendations on albuminuria harmonization are followed in the literature. The PubMed database was searched from June 1 to September 26, 2021. The search terms included urine albumin, urine albumin-to-creatinine ratio (uACR), and albuminuria. A total of 159 articles were considered eligible; 50.9 % reported the type of urine collection. Specifically, 58.1 % collected a random spot urine specimen, 21 % collected a first morning void, and 6.2 % collected a 24-h specimen. Overall, 15 % of articles reported data on sample shipping, storage, and centrifugation and 13.3 % mentioned the preanalytical phase without any data on albuminuria. The method for albuminuria was properly described in 31.4 % of articles; of these, 54.9 % used immunological methods, and 8.9 % contained errors or missing data. Most articles (76.7 %) expressed test results as albuminuria-to-creatininuria ratio. Different decision levels were utilized in 130 articles; of these, 36 % used a decision level of ≤30 mg/g creatininuria and 23.7 % used three decision levels (≤30, 30-300, and ≥300 mg/g). The failure to follow guidelines on albuminuria harmonization was mainly found in the preanalytical phase. The poor awareness of the importance of preanalytical steps on test result may be a possible explanation.

Metabolomics can provide new insights into perinatal nutrition.

Perinatal nutrition is a key factor related to the Developmental Origin of Health and Disease hypothesis, which states that each and every event that happens during the periconceptional period and pregnancy can affect the health status of an individual. Metabolomics can be a very useful tool for gathering information about the effect of perinatal nutrition on both mothers and newborn infants. This non-systematic review focuses on the main metabolites detected by this technique, with regard to gestational diabetes, intrauterine growth restriction and breast milk. Conclusion. Nutrition, metabolome and microbiome interactions are gaining interest in the scientific community.

Metabolomics: Perspectives on Clinical Employment in Autism Spectrum Disorder.

Precision medicine is imminent, and metabolomics is one of the main actors on stage. We summarize and discuss the current literature on the clinical application of metabolomic techniques as a possible tool to improve early diagnosis of autism spectrum disorder (ASD), to define clinical phenotypes and to identify co-occurring medical conditions. A review of the current literature was carried out after PubMed, Medline and Google Scholar were consulted. A total of 37 articles published in the period 2010-2022 was included. Selected studies involve as a whole 2079 individuals diagnosed with ASD (1625 males, 394 females; mean age of 10, 9 years), 51 with other psychiatric comorbidities (developmental delays), 182 at-risk individuals (siblings, those with genetic conditions) and 1530 healthy controls (TD). Metabolomics, reflecting the interplay between genetics and environment, represents an innovative and promising technique to approach ASD. The metabotype may mirror the clinical heterogeneity of an autistic condition; several metabolites can be expressions of dysregulated metabolic pathways thus liable of leading to clinical profiles. However, the employment of metabolomic analyses in clinical practice is far from being introduced, which means there is a need for further studies for the full transition of metabolomics from clinical research to clinical diagnostic routine.

Could metabolomics drive the fate of COVID-19 pandemic? A narrative review on lights and shadows.

Human Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) infection activates a complex interaction host/virus, leading to the reprogramming of the host metabolism aimed at the energy supply for viral replication. Alterations of the host metabolic homeostasis strongly influence the immune response to SARS-CoV-2, forming the basis of a wide range of outcomes, from the asymptomatic infection to the onset of COVID-19 and up to life-threatening acute respiratory distress syndrome, vascular dysfunction, multiple organ failure, and death. Deciphering the molecular mechanisms associated with the individual susceptibility to SARS-CoV-2 infection calls for a system biology approach; this strategy can address multiple goals, including which patients will respond effectively to the therapeutic treatment. The power of metabolomics lies in the ability to recognize endogenous and exogenous metabolites within a biological sample, measuring their concentration, and identifying perturbations of biochemical pathways associated with qualitative and quantitative metabolic changes. Over the last year, a limited number of metabolomics- and lipidomics-based clinical studies in COVID-19 patients have been published and are discussed in this review. Remarkable alterations in the lipid and amino acid metabolism depict the molecular phenotype of subjects infected by SARS-CoV-2; notably, structural and functional data on the lipids-virus interaction may open new perspectives on targeted therapeutic interventions. Several limitations affect most metabolomics-based studies, slowing the routine application of metabolomics. However, moving metabolomics from bench to bedside cannot imply the mere determination of a given metabolite panel; rather, slotting metabolomics into clinical practice requires the conversion of metabolic patient-specific data into actionable clinical applications.

Serial Troponin for Early Detection of Nivolumab Cardiotoxicity in Advanced Non-Small Cell Lung Cancer Patients.

BACKGROUND: Rare cases of severe myocarditis are reported during treatment with nivolumab. Troponin, a biomarker of cardiac damage, is a key component of the diagnostic workup of many cardiac disorders, including myocarditis. This study investigates the role of troponin to assess cardiac involvement during nivolumab therapy for non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: We evaluated 59 NSCLC patients, analyzing serum samples collected within a translational research study. Troponin above the upper normal limit (0.046 ng/mL) was defined as Tn+, whereas normal but detectable troponin (0.015-0.045) was defined as Tndet. Troponin alterations were interpreted on the grounds of the following elements: peak values and time curve, cardiac comorbidities, signs and symptoms coincident to troponin elevation, ECG, echocardiography, and disease progression. RESULTS: No patient had cardiovascular events. Among 362 available blood samples, Tn+ (max 0.317 ng/mL) was found in 13 determinations belonging to 6 patients. Seven other patients had isolated Tndet. In five patients, Tn+ was attributed to cardiac comorbidities, disease progression, or worsening clinical status. One patient without cardiac history and in good clinical condition had a sustained troponin increase-soon after the start of therapy-and after careful evaluation of all relevant elements, it was interpreted as a marker of nivolumab-related subclinical myocarditis. CONCLUSION: Tn+ may occur in NSCLC patients treated with nivolumab, but in most cases it does not indicate nivolumab cardiotoxicity. In some cases, however, a careful interpretation of troponin alteration, especially at the beginning of therapy, enables identification of subclinical myocarditis, thus allowing early cardiac treatment. IMPLICATIONS FOR PRACTICE: Myocarditis is a rare but serious adverse event of immune checkpoint blockade with nivolumab, which needs to be recognized as soon as possible. This article suggests that troponin, a user-friendly biomarker of myocardial cytotoxicity, might be useful for early detection of immune-mediated myocarditis. However, because troponin abnormalities might also be related to a number of conditions capable of causing myocardial oxygen demand-supply mismatch, a careful cardiac assessment should be performed in non-small cell lung cancer patients in order to properly interpret any troponin increase. According to the available evidence, monitoring troponin during the first weeks of treatment can be considered reasonable.

Combined use of serum (1,3)-ß-D-glucan and procalcitonin for the early differential diagnosis between candidaemia and bacteraemia in intensive care units.

BACKGROUND: This study aimed to assess the combined performance of serum (1,3)-ß-D-glucan (BDG) and procalcitonin (PCT) for the differential diagnosis between candidaemia and bacteraemia in three intensive care units (ICUs) in two large teaching hospitals in Italy. METHODS: From June 2014 to December 2015, all adult patients admitted to the ICU who had a culture-proven candidaemia or bacteraemia, as well as BDG and PCT measured closely to the time of the index culture, were included in the study. The diagnostic performance of BDG and PCT, used either separately or in combination, was assessed by calculating the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and positive and negative likelihood ratios (LR+ and LR-). Changes from pre-test probabilities to post-test probabilities of candidaemia and bacteraemia were inferred from Fagan's nomograms. RESULTS: One hundred and sixty-six patients were included, 73 with candidaemia (44%) and 93 with bacteraemia (56%). When both markers indicated candidaemia (BDG ≥80 pg/ml and PCT <2 ng/ml) they showed higher PPV (96%) compared to 79% and 66% for BDG or PCT alone, respectively. When both markers indicated bacteraemia (BDG <80 pg/ml and PCT ≥2 ng/ml), their NPV for candidaemia was similar to that of BDG used alone (95% vs. 93%). Discordant BDG and PCT results (i.e. one indicating candidaemia and the other bacteraemia) only slightly altered the pre-test probabilities of the two diseases. CONCLUSIONS: The combined use of PCT and BDG could be helpful in the diagnostic workflow for critically ill patients with suspected candidaemia.

Birch allergy and oral allergy syndrome: The practical relevance of serum immunoglobulin E to Bet v 1.

BACKGROUND: Birch allergy (BA) may frequently be associated with fruit-vegetables oral allergy syndrome (OAS). Bet v 1 is the major birch allergen. Previously, it was reported that serum-specific immunoglobulin E (IgE) level could differentiate allergy from sensitization. Thus, this study aimed to investigate the practical role of Bet v 1 IgE. METHODS: A total of 245 subjects (128 women, 117 men; mean age, 41 years) with suspected allergic rhinitis and sensitization to Bet v 1 were evaluated. Serum IgE to Bet v 1 was assessed by using immuno-enzymatic. BA and OAS were diagnosed according to validated criteria. Symptom severity perception was measured by the visual analog scale. RESULTS: A total of 158 patients (64.5%) had BA. Patients with BA had higher serum Bet v 1 IgE levels than subjects who were sensitized (p < 0.0001). A cutoff value of 8.94 kUA/L predicted BA (area under the curve, 0.76; odds ratio, 6.18). Fifty-three patients with BA (33.5%) had OAS. Patients positive for OAS had higher Bet v 1 levels (p < 0.0001) and more-severe symptoms (p < 0.0001) than patients with BA and negative for OAS. A cutoff value of 17.4 kUA/L predicted OAS (area under the curve, 0.59; odds ratio, 3.19). CONCLUSIONS: The present study demonstrated that serum IgE levels to Bet v 1 could be a useful marker for differentiating between different birch pollen sensitization phenotypes.

Differential diagnosis of pleural mesothelioma using Logic Learning Machine.

BACKGROUND: Tumour markers are standard tools for the differential diagnosis of cancer. However, the occurrence of nonspecific symptoms and different malignancies involving the same cancer site may lead to a high proportion of misclassifications. Classification accuracy can be improved by combining information from different markers using standard data mining techniques, like Decision Tree (DT), Artificial Neural Network (ANN), and k-Nearest Neighbour (KNN) classifier. Unfortunately, each method suffers from some unavoidable limitations. DT, in general, tends to show a low classification performance, whereas ANN and KNN produce a "black-box" classification that does not provide biological information useful for clinical purposes. METHODS: Logic Learning Machine (LLM) is an innovative method of supervised data analysis capable of building classifiers described by a set of intelligible rules including simple conditions in their antecedent part. It is essentially an efficient implementation of the Switching Neural Network model and reaches excellent classification accuracy while keeping low the computational demand. LLM was applied to data from a consecutive cohort of 169 patients admitted for diagnosis to two pulmonary departments in Northern Italy from 2009 to 2011. Patients included 52 malignant pleural mesotheliomas (MPM), 62 pleural metastases (MTX) from other tumours and 55 benign diseases (BD) associated with pleurisies. Concentration of three tumour markers (CEA, CYFRA 21-1 and SMRP) was measured in the pleural fluid of each patient and a cytological examination was also carried out. The performance of LLM and that of three competing methods (DT, KNN and ANN) was assessed by leave-one-out cross-validation. RESULTS: LLM outperformed all other considered methods. Global accuracy was 77.5% for LLM, 72.8% for DT, 54.4% for KNN, and 63.9% for ANN, respectively. In more details, LLM correctly classified 79% of MPM, 66% of MTX and 89% of BD. The corresponding figures for DT were: MPM = 83%, MTX = 55% and BD = 84%; for KNN: MPM = 58%, MTX = 45%, BD = 62%; for ANN: MPM = 71%, MTX = 47%, BD = 76%. Finally, LLM provided classification rules in a very good agreement with a priori knowledge about the biological role of the considered tumour markers. CONCLUSIONS: LLM is a new flexible tool potentially useful for the differential diagnosis of pleural mesothelioma.

Prognostic Value of Preoperative Serum Levels of Periostin (PN) in Early Breast Cancer (BCa).

PN is a secreted cell adhesion protein critical for carcinogenesis. Elevated serum levels of PN have been implicated as playing an important role in different types of cancer, and a few reports suggest a potential role as a prognostic marker. We evaluated the prognostic significance of preoperative serum PN concentration in patients with BCa receiving curative surgery. Enzyme-Linked Immunosorbent Assay (ELISA) was performed to determine the preoperative serum PN level in 182 patients. The correlations between serum PN concentration with clinical pathological features and PN expression in primary tumor samples were analyzed. The prognostic impact of serum PN levels with all-cause and BCa-specific mortality was also investigated. Appropriate statistics were used. Elevated serum PN levels were significantly associated with patient age (p = 0.005), adjuvant systemic therapy (p = 0.04) and progesterone receptor (PgR) status (p = 0.02). No correlation between PN preoperative serum levels and other clinical-pathological parameters, including either the epithelial or the stromal PN expression of primary tumor or the combination of the two, was found. Similarly, no association between serum PN levels and either all-cause or BCa-specific mortality was found. However, subgroup analysis revealed a correlation between higher PN serum levels and all-cause mortality in patients with node-negative disease (p = 0.05) and in those with a low PgR expression (p = 0.03). Higher levels of serum PN were also found to correlate with BCa-specific mortality in the subgroup of patients who did not receive any adjuvant systemic therapy (p = 0.04). Our findings suggest that PN was detectable in the serum of early BCa patients before surgery and increased base-line serum levels predicted worse long-term survival outcomes in specific subgroups of patients.

A ferroptosis-related ceRNA network for investigating the molecular mechanisms and the treatment of neonatal hypoxic-ischemic encephalopathy.

Background: Neonatal hypoxic-ischemic brain damage (HIBD) is a clinical syndrome causing brain injury in newborns with obscure etiology. Increasing evidence suggests that ferroptosis plays a role in HIBD. This study aimed to clarify the key ferroptosis-related genes (FRGs) of HIBD, construct a long non-coding RNA-microRNA-messenger RNA (lncRNA-miRNA-mRNA) network, and further investigate the pathogenesis of HIBD. Methods: Gene expression data were downloaded from the Gene Expression Omnibus and FerrDb databases. The differentially expressed lncRNAs and FRGs were screened, and the related miRNAs and mRNAs were predicted. The obtained mRNA was intersected with the differentially expressed FRGs (DE-FRGs) to identify the key DE-FRGs. Cell-type Identification by Estimating Relative Subsets of RNA Transcripts method was applied to analyze the immune cell infiltration level and the relationship between key genes and immune cells. Results: Gene differential expression analysis revealed that 1,178 lncRNAs, 207 miRNAs, and 647 mRNAs were differentially expressed in the blood of HIBD patients in comparison to healthy controls. The correlations of the lncRNAs, miRNAs, and mRNAs lead to the establishment of a competing endogenous RNA (ceRNA) network associated with ferroptosis in HIBD. Further validation using an external dataset and quantitative real-time polymerase chain reaction (PCR) analysis of brain tissues from hypoxic-ischemic encephalopathy rats confirmed the expression patterns of three key genes, including HMOX1, MYCN, and QSOX1. Meanwhile, the three key genes were closely correlated with the infiltration of multiple immune cells and might affect the function of HIBD regulatory genes such as CPT2 and GCK. In addition, drug prediction suggested that four drugs, including cephaeline, emetine, mestranol, and sulmazole, might alleviate HIBD. Conclusions: Our study established a ceRNA network, identified three key genes, and predicted four drugs that are associated with ferroptosis in HIBD, which provides new ideas for the investigation of the disease mechanisms and might facilitate the diagnosis and treatment of the disease.

Analysis of risk factors for late arteriovenous fistula failure and patency rates after angioplasty in hemodialysis patients: a retrospective cohort study.

Background: The incidence of chronic kidney disease (CKD) and end-stage kidney disease (ESKD) is increasing worldwide. Hemodialysis (HD) is the mainstay of renal replacement therapy for patients with ESKD. Risk factors associated with late arteriovenous fistula (AVF) failure in HD patients are poorly investigated. Therefore, the aim of this study was to identify factors associated with late AVF failure in HD patients. Methods: Patients with end-stage renal disease (ESRD) who underwent forearm or upper arm AVF angioplasty at Second Affiliated Hospital of Chongqing Medical University between September 2009 and August 2018 were included. Patients were followed up for 36 months. Baseline characteristics were collected using electronic medical records (EMRs). Variables associated with late AVF failure were identified using Cox proportional hazards models. Results: There were 137 patients (64% male, 36% female) included in this study, with 50 (36.5%) experiencing AVF failure. Univariable log-rank analysis showed that age, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), intact parathyroid hormone (iPTH), albumin (ALB), and AVF patency rate were significantly different between patients who did and did not experience AVF failure. Cox regression analysis showed that CRP [P=0.002, hazard ratio (HR) =2.719, 95% confidence interval (CI) for HR: 1.432-5.164], ESR (P=0.030, HR =2.431, 95% CI: 1.088-5.434), iPTH (P=0.013, HR =0.325, 95% CI: 0.133-0.793), and ALB (P=0.040, HR =0.539, 95% CI: 0.299-0.972) were independently associated with AVF failure. Kaplan-Meier survival analysis showed that the cumulative patency rates of AVF at 6, 12, 18, 24, 30, and 36 months were 84%, 74%, 69%, 64%, 64%, and 64%, respectively. Conclusions: CRP, ESR, iPTH, and ALB were associated with AVF failure and should be used as reference in clinical practice.

Clinical Efficacy and Metabolomics Modifications Induced by Polyphenol Compound Supplementation in the Treatment of Residual Dizziness following Semont Maneuver in Benign Paroxysmal Positional Vertigo (BPPV) of the Posterior Semicircular Canal (PSC): Preliminary Results.

Benign paroxysmal positional vertigo (BPPV) represents the most frequent cause of peripheral vertigo. In most cases, it is successfully treated using the canalith repositioning procedure, but it is often followed by continuous lightheadedness in the absence of vertigo or nystagmus (residual dizziness, RD). Our aim is to describe the clinical effectiveness and the urine metabolomics profile of treating these patients with polyphenol compound supplementation. We enrolled 30 patients reporting RD after BPPV of the posterior semicircular canal (PSC) successfully treated using the Semont maneuver. Supplementation with a polyphenol compound was administered for 60 days, and patients were evaluated after 30 and 60 days of treatment using self-administered questionnaires (Visual Analog Scales for Dizziness and Nausea, Dizziness Handicap Inventory, DHI) and urine metabolomics analysis performed using 1H-NMR spectroscopy and multivariate followed by univariate analysis. Most patients reported excellent or good efficacy in the treatment of RD with a significant decrease in VAS and DHI values. The metabolomics analysis identified six significant metabolites related to the treatment, namely 1-methylnicotinamide, anserine, hippurate, lysine, methyl succinate and urea, indicating the inflammatory activities and antioxidant properties of the polyphenol compound. These preliminary data suggest that supplementation with a polyphenol compound could induce some metabolic changes that can help in recovery from RD. However, future steps will require confirmation with a more significant cohort of patients and an extension of the metabolomics evaluation to other problems concerning the different clinical aspects of BPPV, such as the high rate of relapse.

Sex-related differences in within-subject biological variation estimates for 22 essential and non-essential amino acids.

BACKGROUND: Measurement of serum amino acid (AA) concentrations is important in particular for the diagnosis and monitoring of inborn errors of AA metabolism. To ensure optimal clinical interpretation of AAs, reliable biological variation (BV) data are essential. In the present study, we derived BV data for 22 non-essential, conditionally essential, and essential AAs and assessed differences in BV of AAs related to sex. METHODS: Morning blood samples were drawn from 66 subjects (31 males and 35 females) once a week for 10 consecutive weeks. All samples were analyzed in duplicate using liquid chromatography-tandem mass-spectrometry. The data were assessed for outliers, trends, normality and variance homogeneity analysis prior to estimating within-subject (CVI) and between-subject (CVG) BV. RESULTS: CVI estimates ranged from 9.0 % for histidine (male) to 33.0 % for taurine (male). CVI estimates in males and females were significantly different for all AAs except for aspartic acid, citrulline and phenylalanine, in most cases higher in females than in males. Apart from for arginine, CVG estimates in males and females were similar. CONCLUSIONS: In this highly powered BV study, we provide updated BV estimates for 22 AAs and demonstrate that for most AAs, CVI estimates differ between males and females, with implications for interpretation and use of AAs in clinical practice.

Diagnostic value of soluble CD14 subtype (sCD14-ST) presepsin for the postmortem diagnosis of sepsis-related fatalities.

The first aim of this study was to assess the diagnostic performance of presepsin (sCD14-ST) in postmortem serum from femoral blood compared to procalcitonin (PCT) to detect sepsis-related fatalities. The second aim was to compare sCD14-ST levels found in postmortem serum to the values in pericardial fluid to investigate the usefulness of the latter as an alternative biological fluid. Two study groups were formed, a sepsis-related fatalities group and a control group. Radiology (unenhanced CT scans and postmortem angiographies), autopsies, histology, neuropathology, and toxicology as well as other postmortem biochemistry investigations were performed in all cases. Microbiological investigations on right cardiac blood were carried out exclusively in septic cases. The results of this study indicated that postmortem serum PCT and sCD14-ST levels, individually considered, allowed septic cases to be identified. Even though increases in both PCT and sCD14-ST concentrations were observed in the control cases, coherent PCT and sCD14-ST results in cases with suspected sepsis allowed the diagnosis to be confirmed. Conversely, no relevant correlation was identified between postmortem serum and pericardial fluid sCD14-ST levels in either the septic or control groups.

Metabolomics in adult and pediatric nephrology.

Metabolomics, the latest of the "omics" sciences, has a non-selective approach and can thus lead to the identification of all the metabolites (molecules < 1 kDa) in a biological system. The metabolomic profile can be considered the most predictive phenotype capable of evaluating epigenetic modifications determined by external factors. It is so close to the phenotype as to be considered the phenotype itself in its unique individuality (fingerprinting), both in health (phenome), and disease (diseasome). Urine, compared to other biological liquids, has the advantage of being a complex fluid with many components, including intermediate metabolites. Metabolomics may thus play a role in the study of different kidney diseases and overcome diagnostic difficulties. We shall present the studies that to our knowledge have been published on Nephrology and Pediatric Nephrology. Some are experimental while others are clinical. We have not considered carcinomas and transplantations. Although scarce, the data on adults and the very few ones in pediatrics are quite interesting. Further studies on kidneys are needed to determine the practical clinical impact of metabolomics in kidney renal pathologies. The "multiplatform" "omic" study of urine and namely metabolomics can contribute to improving early diagnosis and the outcome of kidney diseases.

Once upon a Time Oral Microbiota: A Cinderella or a Protagonist in Autism Spectrum Disorder?

Autism spectrum disorder (ASD) is a neurodevelopmental disorder evolving over the lifetime of individuals. The oral and gut microbial ecosystems are closely connected to each other and the brain and are potentially involved in neurodevelopmental diseases. This narrative review aims to identify all the available evidence emerging from observational studies focused on the role of the oral microbiome in ASD. A literature search was conducted using PubMed and the Cochrane Library for relevant studies published over the last ten years. Overall, in autistic children, the oral microbiota is marked by the abundance of several microbial species belonging to the Proteobacteria phylum and by the depletion of species belonging to the Bacteroidetes phylum. In mouse models, the oral microbiota is marked by the abundance of the Bacteroidetes phylum. Oral dysbiosis in ASD induces changes in the human metabolome, with the overexpression of metabolites closely related to the pathogenesis of ASD, such as acetate, propionate, and indoles, together with the underexpression of butyrate, confirming the central role of tryptophan metabolism. The analysis of the literature evidences the close relationship between oral dysbiosis and autistic core symptoms; the rebuilding of the oral and gut ecosystems by probiotics may significantly contribute to mitigating the severity of ASD symptoms.

Metabolomic Studies in Inborn Errors of Metabolism: Last Years and Future Perspectives.

The inborn errors of metabolism (IEMs or Inherited Metabolic Disorders) are a heterogeneous group of diseases caused by a deficit of some specific metabolic pathways. IEMs may present with multiple overlapping symptoms, sometimes difficult delayed diagnosis and postponed therapies. Additionally, many IEMs are not covered in newborn screening and the diagnostic profiling in the metabolic laboratory is indispensable to reach a correct diagnosis. In recent years, Metabolomics helped to obtain a better understanding of pathogenesis and pathophysiology of IEMs, by validating diagnostic biomarkers, discovering new specific metabolic patterns and new IEMs itself. The expansion of Metabolomics in clinical biochemistry and laboratory medicine has brought these approaches in clinical practice as part of newborn screenings, as an exam for differential diagnosis between IEMs, and evaluation of metabolites in follow up as markers of severity or therapies efficacy. Lastly, several research groups are trying to profile metabolomics data in platforms to have a holistic vision of the metabolic, proteomic and genomic pathways of every single patient. In 2018 this team has made a review of literature to understand the value of Metabolomics in IEMs. Our review offers an update on use and perspectives of metabolomics in IEMs, with an overview of the studies available from 2018 to 2022.

Incidence of Neonatal Seizures in China Based on Electroencephalogram Monitoring in Neonatal Neurocritical Care Units.

Importance: Neonatal seizures pose a significant challenge in critical care, and continuous video electroencephalography (cEEG) monitoring holds promise for early detection of seizures. However, large-scale data on the incidence of neonatal seizures and monitoring systems in China are lacking. Objectives: To determine the incidence of neonatal seizures in infants with high risk in China. Design, Setting, and Participants: A large, cross-sectional multicenter study was conducted from January 2017 to December 2018 in the neonatal intensive care units (NICUs) of 7 tertiary medical centers in China. Neonates with high risk were included, and cEEG monitoring was conducted. Data were collected between January 1, 2017, and January 31, 2020. The data were analyzed between January 2021 and January 2022. Main Outcomes and Measures: The incidence of neonatal seizures, categorized by etiology, and seizure burden. Results: A total of 20 310 neonates with high risk were included (10 495 [51.7%] male; mean [SD] postmenstrual age, 37.7 [3.7] weeks), and seizures were observed in 3423 infants (16.9%). The highest proportion of seizures was attributed to acute neonatal encephalopathy (1448 [42.3%]). The incidence of seizures decreased with postmenstrual age and birth weight, with the highest occurrence observed in neonates with postmenstrual age of less than 28 weeks (237 of 879 [27.0%]) or birth weight of less than 1.0 kg (269 of 914 [29.4%]). Preterm infants had a higher proportion of moderate and severe seizure burdens compared with full-term infants (moderate severity: 248 of 1199 [20.7%] vs 454 of 2224 [20.4%]), but no significant differences were observed in etiology. Seizure burden was highest with genetic syndromes (49 of 188 [26.1%]), central nervous system malformations (33 of 127 [26.0%]), and inborn errors of metabolism (27 of 113 [23.9%]). During hospitalization, 7.8% of neonates with seizures died (267 neonates), with 81.3% of these cases having a moderate or severe seizure burden (217 neonates). Mortality was generally higher in preterm vs full-term infants (98 of 1199 [8.2%] vs 169 of 2224 [7.6%]) and increased with the severity of seizure burden (217 of 267 neonates with moderate or severe burden [81.3%]). Conclusions and Relevance: This cross-sectional study of neonatal seizures underscores the substantial burden seizures pose to high-risk infants with brain injury in China, particularly those who are born prematurely or who have congenital conditions.

The impact of the secondary infections in ICU patients affected by COVID-19 during three different phases of the SARS-CoV-2 pandemic.

Microbial secondary infections can contribute to an increase in the risk of mortality in COVID-19 patients, particularly in case of severe diseases. In this study, we collected and evaluated the clinical, laboratory and microbiological data of COVID-19 critical ill patients requiring intensive care (ICU) to evaluate the significance and the prognostic value of these parameters. One hundred seventy-eight ICU patients with severe COVID-19, hospitalized at the S. Francesco Hospital of Nuoro (Italy) in the period from March 2020 to May 2021, were enrolled in this study. Clinical data and microbiological results were collected. Blood chemistry parameters, relative to three different time points, were analyzed through multivariate and univariate statistical approaches. Seventy-four percent of the ICU COVID-19 patients had a negative outcome, while 26% had a favorable prognosis. A correlation between the laboratory parameters and days of hospitalization of the patients was observed with significant differences between the two groups. Moreover, Staphylococcus aureus, Enterococcus faecalis, Candida spp, Pseudomonas aeruginosa and Klebsiella pneumoniae were the most frequently isolated microorganisms from all clinical specimens. Secondary infections play an important role in the clinical outcome. The analysis of the blood chemistry tests was found useful in monitoring the progression of COVID-19.

Multi-level analysis of the gut-brain axis shows autism spectrum disorder-associated molecular and microbial profiles.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by heterogeneous cognitive, behavioral and communication impairments. Disruption of the gut-brain axis (GBA) has been implicated in ASD although with limited reproducibility across studies. In this study, we developed a Bayesian differential ranking algorithm to identify ASD-associated molecular and taxa profiles across 10 cross-sectional microbiome datasets and 15 other datasets, including dietary patterns, metabolomics, cytokine profiles and human brain gene expression profiles. We found a functional architecture along the GBA that correlates with heterogeneity of ASD phenotypes, and it is characterized by ASD-associated amino acid, carbohydrate and lipid profiles predominantly encoded by microbial species in the genera Prevotella, Bifidobacterium, Desulfovibrio and Bacteroides and correlates with brain gene expression changes, restrictive dietary patterns and pro-inflammatory cytokine profiles. The functional architecture revealed in age-matched and sex-matched cohorts is not present in sibling-matched cohorts. We also show a strong association between temporal changes in microbiome composition and ASD phenotypes. In summary, we propose a framework to leverage multi-omic datasets from well-defined cohorts and investigate how the GBA influences ASD.