Blood Biomarkers and Metabolomic Profiling for the Early Diagnosis of Vancomycin-Associated Acute Kidney Injury: A Systematic Review and Meta-Analysis of Experimental Studies

Background: several blood-based biomarkers have been proposed for predicting vancomycin-associated kidney injury (VIKI). However, no systematic analysis has compared their prognostic value. Objective: this systematic review and meta-analysis was designed to investigate the role of blood biomarkers and metabolomic profiling as diagnostic and prognostic predictors in pre-clinical studies of VIKI. Methods: a systematic search of PubMed was conducted for relevant articles from January 2000 to May 2022. Animal studies that administered vancomycin and studied VIKI were eligible for inclusion. Clinical studies, reviews, and non-English literature were excluded. The primary outcome was to investigate the relationship between the extent of VIKI as measured by blood biomarkers and metabolomic profiling. Risk of bias was assessed with the CAMARADES checklist the SYRCLE's risk of bias tool. Standard meta-analysis methods (random-effects models) were used. Results: there were four studies for the same species, dosage, duration of vancomycin administration and measurement only for serum creatine and blood urea nitrogen in rats. A statistically significant increase was observed between serum creatinine in the vancomycin group compared to controls (pooled p = 0.037; Standardized Mean Difference: 2.93; 95% CI: 0.17 to 5.69; I-2 = 92.11%). Serum BUN levels were not significantly different between control and vancomycin groups (pooled p = 0.11; SMD: 3.05; 95% CI: 0.69 to 6.8; I-2 = 94.84%). We did not identify experimental studies using metabolomic analyses in animals with VIKI. Conclusions: a total of four studies in rodents only described outcomes of kidney injury as defined by blood biomarkers. Blood biomarkers represented included serum creatinine and BUN. Novel blood biomarkers have not been explored

An ultra-compact particle size analyser using a CMOS image sensor and machine learning

Light scattering is a fundamental property that can be exploited to create essential devices such as particle analysers. The most common particle size analyser relies on measuring the angle-dependent diffracted light from a sample illuminated by a laser beam. Compared to other non-light-based counterparts, such a laser diffraction scheme offers precision, but it does so at the expense of size, complexity and cost. In this paper, we introduce the concept of a new particle size analyser in a collimated beam configuration using a consumer electronic camera and machine learning. The key novelty is a small form factor angular spatial filter that allows for the collection of light scattered by the particles up to predefined discrete angles. The filter is combined with a light-emitting diode and a complementary metal-oxide-semiconductor image sensor array to acquire angularly resolved scattering images. From these images, a machine learning model predicts the volume median diameter of the particles. To validate the proposed device, glass beads with diameters ranging from 13 to 125 µm were measured in suspension at several concentrations. We were able to correct for multiple scattering effects and predict the particle size with mean absolute percentage errors of 5.09% and 2.5% for the cases without and with concentration as an input parameter, respectively. When only spherical particles were analysed, the former error was significantly reduced (0.72%). Given that it is compact (on the order of ten cm) and built with low-cost consumer electronics, the newly designed particle size analyser has significant potential for use outside a standard laboratory, for example, in online and in-line industrial process monitoring

Interleukin-7 treatment of PML in a patient with idiopathic lymphocytopenia

Objective: To describe the compassionate use of interleukin-7 (IL-7) for treatment of progressive multifocal leukoencephalopathy (PML) in the setting of idiopathic CD8+ greater than CD4+ lymphocytopenia. Methods: A 66-year-old HIV-seronegative man presented with progressive language dysfunction. MRI showed hyperintense lesions in the left hemispheric white matter with mild contrast enhancement. A brain biopsy performed 4 months after symptom onset established the diagnosis of PML. The patient had profound lymphocytopenia with absolute lymphocyte count (ALC) at 168 cells/μL, 87 CD4+ T cells/μL, and 7 CD8+ T cells/μL. There was no evidence of hematologic malignancy or rheumatologic disease. Results: The patient received 3 intramuscular injections of IL-7 at a dose of 10 μg/kg per week with no adverse effects. ALC peaked at 595 cells/μL, CD4+ T cells at 301 cells/μL, and CD8+ T cells at 34 cells/μL 3 weeks after completion of treatment. His lesions on MRI stabilized and neurologic examination mildly improved. JCV-specific T-cell responses measured by intracellular cytokine staining were not altered after treatment with IL-7 but there was a marked increase in regulatory T cells. Conclusion: This case further supports the investigational use of IL-7 in patients who develop PML in the setting of ICL. Classification of evidence: This study provides Class IV evidence that for patients with ICL and PML, IL-7 improves PML-related-outcomes. The study is rated Class IV because it is a case report

Urinary Metabolomics From a Dose-Fractionated Polymyxin B Rat Model of Acute Kidney Injury

Background: Polymyxin B treatment is limited by kidney injury. This study sought to identify Polymyxin B-related urinary metabolomic profile modifications for early detection of polymyxin-associated nephrotoxicity. Methods: Samples were obtained from a previously conducted study. Male Sprague-Dawley rats received dose-fractionated polymyxin B (12 mg/kg/day) once daily (QD), twice daily (BID), and thrice daily (TID) for three days, with urinary biomarkers and kidney histopathology scores determined. Daily urine was analysed for metabolites via 1H nuclear magnetic resonance (NMR). Principal components analyses identified spectral data trends with orthogonal partial least square discriminant analysis applied to classify metabolic differences. Metabolomes were compared across groups (i.e., those receiving QD, BID, TID, and control) using a mixed-effects models. Spearman correlation was performed for injury biomarkers and the metabolome. Results: A total of 25 rats were treated with Polymyxin B, and n = 2 received saline, contributing 77 urinary samples. Pre-dosing samples clustered well, characterised by higher amounts of citrate, 2-oxoglutarate, and hippurate. Day 1 samples showed higher taurine; day 3 samples had higher lactate, acetate and creatine. Taurine was the only metabolite that significantly increased in both BID and TID compared with the QD group. Day 1 taurine correlated with increasing histopathology scores (rho = 0.4167, P = 0.038) and kidney injury molecule-1 (KIM-1) (rho = 0.4052, P = 0.036), whereas KIM-1 on day 1 and day 3 did not reach significance with histopathology (rho = 0.3248, P = 0.11 and rho = 0.3739, P = 0.066). Conclusions: Polymyxin B causes increased amounts of urinary taurine on day 1, which then normalizes to baseline concentrations. Taurine may provide one of the earlier signals of acute kidney damage caused by polymyxin B

Clinical practice recommendations on the management of perioperative cardiac arrest: A report from the PERIOPCA Consortium

Background: Perioperative cardiac arrest is a rare complication with an incidence of around 1 in 1400 cases, but it carries a high burden of mortality reaching up to 70% at 30 days. Despite its specificities, guidelines for treatment of perioperative cardiac arrest are lacking. Gathering the available literature may improve quality of care and outcome of patients. Methods: The PERIOPCA Task Force identified major clinical questions about the management of perioperative cardiac arrest and framed them into the therapy population [P], intervention [I], comparator [C], and outcome [O] (PICO) format. Systematic searches of PubMed, Embase, and the Cochrane Library for articles published until September 2020 were performed. Consensus-based treatment recommendations were created using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system. The strength of consensus among the Task Force members about the recommendations was assessed through a modified Delphi consensus process. Results: Twenty-two PICO questions were addressed, and the recommendations were validated in two Delphi rounds. A summary of evidence for each outcome is reported and accompanied by an overall assessment of the evidence to guide healthcare providers. Conclusions: The main limitations of our work lie in the scarcity of good quality evidence on this topic. Still, these recommendations provide a basis for decision making, as well as a guide for future research on perioperative cardiac arrest

ViroFind: A novel target-enrichment deep-sequencing platform reveals a complex JC virus population in the brain of PML patients

Deep nucleotide sequencing enables the unbiased, broad-spectrum detection of viruses in clinical samples without requiring an a priori hypothesis for the source of infection. However, its use in clinical research applications is limited by low cost-effectiveness given that most of the sequencing information from clinical samples is related to the human genome, which renders the analysis of viral genomes challenging. To overcome this limitation we developed ViroFind, an in-solution target-enrichment platform for virus detection and discovery in clinical samples. ViroFind comprises 165,433 viral probes that cover the genomes of 535 selected DNA and RNA viruses that infect humans or could cause zoonosis. The ViroFind probes are used in a hybridization reaction to enrich viral sequences and therefore enhance the detection of viral genomes via deep sequencing. We used ViroFind to detect and analyze all viral populations in the brain of 5 patients with progressive multifocal leukoencephalopathy (PML) and of 18 control subjects with no known neurological disease. Compared to direct deep sequencing, by using ViroFind we enriched viral sequences present in the clinical samples up to 127-fold. We discovered highly complex polyoma virus JC populations in the PML brain samples with a remarkable degree of genetic divergence among the JC virus variants of each PML brain sample. Specifically for the viral capsid protein VP1 gene, we identified 24 single nucleotide substitutions, 12 of which were associated with amino acid changes. The most frequent (4 of 5 samples, 80%) amino acid change was D66H, which is associated with enhanced tissue tropism, and hence likely a viral fitness advantage, compared to other variants. Lastly, we also detected sparse JC virus sequences in 10 of 18 (55.5%) of control samples and sparse human herpes virus 6B (HHV6B) sequences in the brain of 11 of 18 (61.1%) control subjects. In sum, ViroFind enabled the in-depth analysis of all viral genomes in PML and control brain samples and allowed us to demonstrate a high degree of JC virus genetic divergence in vivo that has been previously underappreciated. ViroFind can be used to investigate the structure of the virome with unprecedented depth in health and disease state

Using Simulation to Assess the Opportunities of Dynamic Waste Collection

In this paper, we illustrate the use of discrete event simulation to evaluate how dynamic planning methodologies can be best applied for the collection of waste from underground containers. We present a case study that took place at the waste collection company Twente Milieu, located in The Netherlands. Even though the underground containers are already equipped with motion sensors, the planning of container emptying’s is still based on static cyclic schedules. It is expected that the use of a dynamic planning methodology, that employs sensor information, will result in a more efficient collection process with respect to customer satisfaction, profits, and CO2 emissions. In this research we use simulation to (i) evaluate the current planning methodology, (ii) evaluate various dynamic planning possibilities, (iii) quantify the benefits of switching to a dynamic collection process, and (iv) quantify the benefits of investing in fill‐level sensors. After simulating all scenarios, we conclude that major improvements can be achieved, both with respect to logistical costs as well as customer satisfaction

Light pollution: The possible consequences of excessive illumination on retina

Light is the visible part of the electromagnetic radiation within a range of 380-780 nm; (400-700 on primates retina). In vertebrates, the retina is adapted to capturing light photons and transmitting this information to other structures in the central nervous system. In mammals, light acts directly on the retina to fulfill two important roles: (1) the visual function through rod and cone photoreceptor cells and (2) non-image forming tasks, such as the synchronization of circadian rhythms to a 24 h solar cycle, pineal melatonin suppression and pupil light reflexes. However, the excess of illumination may cause retinal degeneration or accelerate genetic retinal diseases. In the last century human society has increased its exposure to artificial illumination, producing changes in the Light/Dark cycle, as well as in light wavelengths and intensities. Although, the consequences of unnatural illumination or light pollution have been underestimated by modern society in its way of life, light pollution may have a strong impact on people's health. The effects of artificial light sources could have direct consequences on retinal health. Constant exposure to different wavelengths and intensities of light promoted by light pollution may produce retinal degeneration as a consequence of photoreceptor or retinal pigment epithelium cells death. In this review we summarize the different mechanisms of retinal damage related to the light exposure, which generates light pollution.Fil: Contin, Maria Ana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigaciones en Química Biológica de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Centro de Investigaciones en Química Biológica de Córdoba; ArgentinaFil: Benedetto, María Mercedes. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigaciones en Química Biológica de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Centro de Investigaciones en Química Biológica de Córdoba; ArgentinaFil: Quinteros Quintana, María Luz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigaciones en Química Biológica de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Centro de Investigaciones en Química Biológica de Córdoba; ArgentinaFil: Guido, Mario Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigaciones en Química Biológica de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Centro de Investigaciones en Química Biológica de Córdoba; Argentin