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Background Logistic regression is a useful statistical technique commonly used in many fields like healthcare, marketing, or finance to generate insights from binary outcomes (e.g., sick vs. not sick). However, when applying logistic regression to complex survey data, which includes complex sampling designs, specific methodological issues are often overlooked. Methods The systematic review extensively searched the PubMed and ScienceDirect databases from January 2015 to December 2021, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, focusing primarily on the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). 810 articles met the inclusion criteria and were included in the analysis. When discussing logistic regression, the review considered multiple methodological problems such as the model adequacy assessment, handling dependence of observations, utilization of complex survey design, dealing with missing values, outliers, and more. Results Among the selected articles, the DHS database was used the most (96%), with MICS accounting for only 3%, and both DHS and MICS accounting for 1%. Of these, it was found that only 19.7% of the studies employed multilevel mixed-effects logistic regression to account for data dependencies. Model validation techniques were not reported in 94.8% of the studies with limited uses of the bootstrap, jackknife, and other resampling methods. Moreover, sample weights, PSUs, and strata variables were used together in 40.4% of the articles, and 41.7% of the studies did not use any of these variables, which could have produced biased results. Goodness-of-fit assessments were not mentioned in 75.3% of the articles, and the Hosmer–Lemeshow and likelihood ratio test were the most common among those reported. Furthermore, 95.8% of studies did not mention outliers, and only 41.0% of studies corrected for missing information, while only 2.7% applied imputation techniques. Conclusions This systematic review highlights important gaps in the use of logistic regression with complex survey data, such as overlooking data dependencies, survey design, and proper validation techniques, along with neglecting outliers, missing data, and goodness-of-fit assessments, all of which point to the need for clearer methodological standards and more thorough reporting to improve the reliability of results. Future research should focus on consistently following these standards to ensure stronger and more dependable findings.

Fluoropolymers are effective binders and modifiers in Al-based metastable intermolecular composites (MIC) due to their high reactivity and heat release. Recently, two-dimensional functional MXenes offer a distinct modulation pathway in energetic materials which remains unexplored. In this study, we investigated the energy release performance of Al/Co3O4 MICs with modifier of MXene V4C3 and the conventional fluoropolymer polyvinylidene fluoride (PVDF) as comparison. The Al/Co3O4/V4C3 and Al/Co3O4/PVDF composites with varying PVDF/V4C3 contents were prepared and evaluated through thermal analysis, closed-bomb pressure tests, high-speed flame observation, and condensed combustion residue analysis. PVDF promotes pre-ignition via in-situ gas evolution, significantly increasing pressurization rates (up to 4.91 MPa/s), whereas V4C3 enhances thermal stability, shifting the ignition onset temperature from 466.9 °C to 551.7 °C with 70% higher pressurization rate. Both additives convert an uncontrolled explosion into sustained, stabilized combustion with longer flame duration and reduced particle agglomeration. Based on a comparative analysis of the underlying mechanisms by which PVDF and V4C3 modulate the properties of Al/Co3O4 composites, this work provides new design insights for developing advanced Al-based MIC with tailored performance.

MIC-A and MIC-B are the natural ligands for NKG2D, an activator receptor expressed in NK cells. Soluble isoforms of MIC-A and MIC-B (sMICA, sMICB) have been identified in different malignancies, affecting NK cells’ cytotoxicity. The study was performed to determine the levels of sMICA, sMICB, the expression of MIC-A, and MIC-B on tumor tissues, and lymphocyte subpopulations (CD4 + , CD8 + , NK, NKT, Tγδ cells, B cells, monocytes) in 94 patients with non-Hodgkin's lymphoma (NHL) and 72 healthy donors.The most frequent lymphoma was diffuse large B cell lymphoma (48%). Patients with NHL had decreased numbers of CD4 T cells, CD8 T cells, B cells, monocytes, NK cells, type 1 dendritic cells, γδ T cells, and increased iNKT cells. Patients showed higher levels of sMIC-A and similar serum levels of sMIC-B.Survival was poorer in patients having higher LDH values and lower numbers of CD4 T cells, type 1 dendritic cells, gamma-delta T cells, and high levels of sMIC-A.In conclusion, high levels of sMIC and decreased numbers in circulating lymphocyte subsets are related to poor outcomes in NHL.

Background/Objectives: Oritavancin therapy for complex infections remains challenging due to the lack of well-established dosing regimens. The objective of this work was to apply PK/PD modeling and Monte Carlo simulation considering different PK/PD targets to identify multiple-dosing regimens that may ensure effective concentrations of oritavancin for the treatment of long-term infections. Methods: Plasma concentration–time profiles were simulated for different regimens (single dose of 1200 mg, 1200 mg followed by 800 mg every 7 days (q7d), 1200 mg followed by 800 mg q10d, 1200 mg q7d, 1200 mg q10d, 1200 mg q14d, 1200 mg q21d, and 1200 mg followed by 1200 mg on day 8, then 1200 mg q14d), and the probability of target attainment (PTA), indicative of treatment success, was estimated. Results: All dosing regimens provided probabilities of target attainment of 100% up to MICs of 0.5 mg/L when AUC0–24/MIC and Cmax/MIC were applied. Considering AUC0–72/MIC, the regimens would be adequate up to an MIC of 0.125 mg/L. For fCmin > MIC, all except 1200 mg q21d were adequate for an MIC of 0.125 mg/L, and 1200 mg day 1 + 800 mg q7d and 1200 mg q10d may be useful to treat infections due to bacteria with an MIC of 0.25 mg/L. Conclusions: More studies involving patients with complex infections are needed to better stablish the relationships among plasma concentrations, MIC values, and clinical outcomes. fCmin > MIC should be investigated as a potential PK/PD target for the treatment of these infections with oritavancin.

While patient care, kidney replacement therapy, and transplantation techniques for chronic kidney disease (CKD) have continued to progress, the incidence of malnutrition disorders in CKD appears to have remained unchanged over time. However, there is now a better understanding of the underlying pathophysiology according to the disease background, disease stage, and the treatment received. In CKD patients, the increased production of proinflammatory cytokines and oxidative stress lead to a proinflammatory milieu that is at least partially responsible for the increased morbidity and mortality in this patient population. New insights into the pathogenic role of innate immunity and the proinflammatory cytokine profile, characterized, for instance, by higher levels of IL-6 and TNF-α, explain some of the clinical and laboratory abnormalities observed in these patients. In this article, we will explore currently available nutritional–inflammatory biomarkers in distinct CKD populations (hemodialysis, peritoneal dialysis, transplantation) with a view to evaluating their efficacy as predictors of malnutrition and their involvement in the common proinflammatory process. Although there is a direct relationship between inflammatory-nutritional status, signs and symptoms [e.g., protein-energy wasting (PEW), anorexia], and comorbidities (e.g., atheromatosis, atherosclerosis), we are in need of clearly standardized markers for nutritional-inflammatory assessment to improve their performance and design appropriate bidirectional interventions.

In addition to the maximum plasma concentration (C ) to the minimum inhibitory concentration (MIC) ratio, the 24-hour area under the concentration-time curve (AUC ) to MIC has recently been suggested as pharmacokinetic/pharmacodynamic (PK/PD) targets for efficacy and safety in once-daily dosing of gentamicin (ODDG) in critically ill patients. This study aimed to predict the optimal effective dose and risk of nephrotoxicity for gentamicin in critically ill patients for two different PK/PD targets within the first 3 days of infection. The gathered pharmacokinetic and demographic data in critically ill patients from 21 previously published studies were used to build a one-compartment pharmacokinetic model. The Monte Carlo Simulation (MCS) method was conducted with the use of gentamicin once-daily dosing ranging from 5-10 mg/kg. The percentage target attainment (PTA) for efficacy, C /MIC ~8-10 and AUC /MIC ≥110 targets, were studied. The AUC >700 mg⋅h/L and C >2 mg/L were used to predict the risk of nephrotoxicity. Gentamicin 7 mg/kg/day could achieve both efficacy targets for more than 90% when the MIC was <0.5 mg/L. When the MIC increased to 1 mg/L, gentamicin 8 mg/kg/day could reach the PK/PD and safety targets. However, for pathogens with MIC ≥2 mg/L, no studied gentamicin doses were sufficient to reach the efficacy target. The risk of nephrotoxicity using AUC >700 mg⋅h/L was small, but the risk was greater when applying a C target >2 mg/L. Considering both targets of Cmax/MIC ~8-10 and AUC /MIC ≥110, an initial gentamicin dose of 8 mg/kg/day should be recommended in critically ill patients for pathogens with MIC of ≤1 mg/L. Clinical validation of our results is essential.

High concentrations of non-essential heavy metals/metalloids (arsenic, cadmium, and lead) in soils and irrigation water represent a threat to the environment, food safety, and human and animal health. Microbial bioremediation has emerged as a promising strategy to reduce the concentration of heavy metals in the environment due to the demonstrated ability of microorganisms, especially bacteria, to sequester and transform these compounds. Although several bacterial strains have been reported to be capable of remediation of soils affected by heavy metals, published information has not been comprehensively analyzed to date to recommend the most efficient microbial resources for application in bioremediation or bacterial-assisted phytoremediation strategies that may help improve plant growth and yield in contaminated soils. In this study, we critically analyzed eighty-five research articles published over the past 15 years, focusing on bacteria-assisted remediation strategies for the non-essential heavy metals, arsenic, cadmium, and lead, and selected based on four criteria: i) The bacterial species studied are part of a plant microbiome, i.e., they interact closely with a plant species ii) these same bacterial species exhibit plant growth-promoting characteristics, iii) bacterial resistance to the metal(s) is expressed in terms of the Minimum Inhibitory Concentration (MIC), and iv) metal resistance is related to biochemical or molecular mechanisms. A total of sixty-two bacterial genera, comprising 424 bacterial species/strains associated with fifty plant species were included in our analysis. Our results showed a close relationship between the tolerance level exhibited by the bacteria and metal identity, with lower MIC values found for cadmium and lead, while resistance to arsenic was widespread and significantly higher. In-depth analysis of the most commonly evaluated genera, Agrobacterium, Bacillus, Klebsiella, Enterobacter, Microbacterium, Pseudomonas, Rhodococcus, and Mesorhizobium showed significantly different tolerance levels among them and highlighted the deployment of different biochemical and molecular mechanisms associated with plant growth promotion or with the presence of resistance genes located in the cad and ars operons. In particular, the genera Klebsiella and Enterobacter exhibited the highest levels of cadmium and lead tolerance, clearly supported by molecular and biochemical mechanisms; they were also able to mitigate plant growth inhibition under phytotoxic metal concentrations. These results position Klebsiella and Enterobacter as the best potential candidates for bioremediation and bacteria-assisted phytoremediation strategies in soils contaminated with arsenic, cadmium, and lead.

Acquired resistance is an important driver of multidrug-resistant tuberculosis (TB), even with good treatment adherence. However, exactly what initiates the resistance and how it arises remain poorly understood. To identify the relationship between drug concentrations and drug susceptibility readouts (minimum inhibitory concentrations [MICs]) in the TB cavity. We recruited patients with medically incurable TB who were undergoing therapeutic lung resection while on treatment with a cocktail of second-line anti-TB drugs. On the day of surgery, antibiotic concentrations were measured in the blood and at seven prespecified biopsy sites within each cavity. Mycobacterium tuberculosis was grown from each biopsy site, MICs of each drug identified, and whole-genome sequencing performed. Spearman correlation coefficients between drug concentration and MIC were calculated. Fourteen patients treated for a median of 13 months (range, 5-31 mo) were recruited. MICs and drug resistance-associated single-nucleotide variants differed between the different geospatial locations within each cavity, and with pretreatment and serial sputum isolates, consistent with ongoing acquisition of resistance. However, pretreatment sputum MIC had an accuracy of only 49.48% in predicting cavitary MICs. There were large concentration-distance gradients for each antibiotic. The location-specific concentrations inversely correlated with MICs (P < 0.05) and therefore acquired resistance. Moreover, pharmacokinetic/pharmacodynamic exposures known to amplify drug-resistant subpopulations were encountered in all positions. These data inform interventional strategies relevant to drug delivery, dosing, and diagnostics to prevent the development of acquired resistance. The role of high intracavitary penetration as a biomarker of antibiotic efficacy, when assessing new regimens, requires clarification.

Inefficiency of medical therapies used in order to cure patients with bacterial infections requires not only to actively look for new therapeutic strategies but also to carefully select antibiotics based on variety of parameters, including microbiological. Minimal inhibitory concentration (MIC) defines in vitro levels of susceptibility or resistance of specific bacterial strains to applied antibiotic. Reliable assessment of MIC has a significant impact on the choice of a therapeutic strategy, which affects efficiency of an infection therapy. In order to obtain credible MIC, many elements must be considered, such as proper method choice, adherence to labeling rules, and competent interpretation of the results. In this paper, two methods have been discussed: dilution and gradient used for MIC estimation. Factors which affect MIC results along with the interpretation guidelines have been described. Furthermore, opportunities to utilize MIC in clinical practice, with pharmacokinetic /pharmacodynamic parameters taken into consideration, have been investigated. Due to problems related to PK determination in individual patients, statistical estimation of the possibility of achievement of the PK/PD index, based on the Monte Carlo, was discussed. In order to provide comprehensive insights, the possible limitations of MIC, which scientists are aware of, have been outlined.