UNASSIGNED: Carbapenem resistance is epidemic worldwide, these last resort antimicrobials are listed in the WHO \'watch group\' with higher resistance potential. During the years 2017-18 Pakistan Antimicrobial Resistance Surveillance System reported an increase in carbapenem resistance. However, a comprehensive information on prevalence and molecular epidemiology of carbapenem resistance in Pakistan is not available. This systematic review and meta-analysis is aimed to report the current carbapenem resistance situation in Pakistan and its treatment options.
UNASSIGNED: In this systematic review and meta-analysis, we investigated the pooled prevalence (PPr) of carbapenem resistance in Enterobacteriaceae and non-Enterobacteriaceae by organizing available data, from Web of Science and PubMed by April 2, 2020, in various groups and subgroups including species, years, provinces, extended spectrum β-lactamase production, clinical presentation, carbapenemase and metallo-β-lactamase production, and New Delhi metallo-β-lactamase (NDM) prevalence. Literature review was updated for the studies publisehd by December 07, 2023. Moreover, we descriptively reviewed the molecular epidemiology of carbapenem resistance in Enterobacteriaceae and non-Enterobacteriaceae in Pakistan. Lastly, we statistically explored different treatment options available for carbapenem resistant infections. We used R package \'metafor\' for performing meta-analysis and influence diagnostics and determining treatment options.
UNASSIGNED: From two academic databases Web of Science and PubMed we identified 343 studies. Eighty-eight studies were selected for the systematic review and meta-analysis. Seventy-four studies were selected for phenotypic analysis, 36 for genotypic analysis, and 31 for available treatment options. PPr-ID of 12% [0.12 (0.07, 0.16)] was observed for phenotypic carbapenem resistance in Enterobacteriaceae with more prevalence recorded in Klebsiella pneumoniae 24% [0.24 (0.05, 0.44)] followed by 9% [0.09 (-0.03, 0.20)] in Escherichia coli. During the last two decades we observed a striking increase in carbapenem resistance PPr i.e., from 0% [0.00 (-0.02, 0.03)] to 36% [0.36 (0.17, 0.56)]. blaNDM with PPr 15% [0.15 (0.06, 0.23)] in naive isolates was found to be the fundamental genetic determinant for carbapenem resistance in Enterobacteriaceae in Pakistan. Polymyxin B, colistin, tigecycline, and fosfomycin were identified as the suggested treatment options available for multidrug resistant infections not responding to carbapenems. Various studies reported carbapenem resistance from human, animal, and environment sources.
UNASSIGNED: In conclusion, we found that NDM-1 producing carbapenem resistant Enterobacteriaceae are increasing in Pakistan. Meta-analysis showed that metallo-β-lactamases producing E. coli ST405 and K. pneumoniae sequence type11 are the major resistant clones. Number of reported studies in various subgroups and inconsistency in following CLSI guidelines are the potential limitations of this meta-analysis. A National antimicrobial resistance (AMR) surveillance strategy based on One Health is urgently needed to check any future AMR crisis in Pakistan.

There is extensive choice in R to support meta-analyses.Two packages in this ecosystem include meta and metafor and provide an excellent opportunity to apply a structured checklist previously developed for contrasts between R packages relevant to challenges in ecology and evolution.Meta is a direct, intuitive choice for rapid implementation of general meta-analytical statistics. Metafor is a comprehensive package best suited for relatively more complex models.Both packages provide estimates of heterogeneity, excellent visualization tools, and functions to explore publication bias.The package metafor has a steeper learning curve but greater rewards. Reference to the learning curve and capacities of the statistical software Stata provided a benchmark outside the R ecosystem and confirmed the consistency in statistics.The usefulness of meta-analyses is not just in the synthesis of the research but in the process of doing the scientific synthesis. Reporting of contrasts and checks for robust statistics is an important contribution to more transparent and reproducible scientific syntheses.

Whole-genome transcription has been measured in peripheral blood samples as a candidate biomarker of inflammation associated with major depressive disorder.
We searched for all case-control studies on major depressive disorder that reported microarray or RNA sequencing measurements on whole blood or peripheral blood mononuclear cells. Primary datasets were reanalyzed, when openly accessible, to estimate case-control differences and to evaluate the functional roles of differentially expressed gene lists by technically harmonized methods.
We found 10 eligible studies (N = 1754 depressed cases and N = 1145 healthy controls). Fifty-two genes were called significant by 2 of the primary studies (published overlap list). After harmonization of analysis across 8 accessible datasets (n = 1706 cases, n = 1098 controls), 272 genes were coincidentally listed in the top 3% most differentially expressed genes in 2 or more studies of whole blood or peripheral blood mononuclear cells with concordant direction of effect (harmonized overlap list). By meta-analysis of standardized mean difference across 4 studies of whole-blood samples (n = 1567 cases, n = 954 controls), 343 genes were found with false discovery rate <5% (standardized mean difference meta-analysis list). These 3 lists intersected significantly. Genes abnormally expressed in major depressive disorder were enriched for innate immune-related functions, coded for nonrandom protein-protein interaction networks, and coexpressed in the normative transcriptome module specialized for innate immune and neutrophil functions.
Quantitative review of existing case-control data provided robust evidence for abnormal expression of gene networks important for the regulation and implementation of innate immune response. Further development of white blood cell transcriptional biomarkers for inflamed depression seems warranted.

The aim of this systematic review and meta-analysis (SR-MA) was to identify signaling molecule profiles and blood-derived biomarkers in migraine and cluster headache (CH) patients.
Currently no migraine and CH valid biomarkers are available. Blood tests based on biomarker profiles have been used to gather information about the nervous system. Such tests have not yet been established within the primary headache field.
Case-control and case-crossover studies investigating whole blood, plasma, and serum were identified worldwide. The qualitative synthesis focused on 9 signaling molecules (serotonin [5-HT], calcitonin gene-related peptide [CGRP], endothelin-1 [ET-1], neurokinin A, neurokinin B, neuropeptide Y, pituitary adenylate cyclase-activating peptide 38 [PACAP-38], substance P (SP), and vasoactive intestinal peptide) and the quantitative synthesis on 5-HT and CGRP (≥5 comparisons available). The meta-analysis was conducted using standard and 3-level random effect models.
Fifty-four eligible studies were identified (87.0% migraine, 9.3% CH, 3.7% migraine, and CH), and 2768 headache patients and 1165 controls included. Comparable fluctuations of 5-HT, CGRP, ET-1, PACAP-38, and SP in blood were generally observed between migraine and CH. Significant findings were observed for some subgroups and strata, for example, higher interictal and ictal 5-HT venous blood levels (ratio of means = 1.32, 95% CI: 1.08; 1.61; ratio of means = 1.23, 95% CI: 1.01; 1.49) in episodic migraine with aura with a female-dominated case group, higher interictal CGRP blood levels in episodic migraine (ratio of means = 1.63, 95% CI: 1.18; 2.26), and chronic migraine (ratio of means = 1.89, 95% CI: 1.33; 2.68), and higher ictal CGRP blood levels (ratio of means = 1.35, 95% CI: 1.09; 1.68) in episodic migraine were observed. In most subgroups, the quantitative synthesis revealed a high degree of heterogeneity between studies in part explained by the blood sampling site, specimen source, blood specimen, and sex distribution. Other potential confounders were age, aura, study quality, menstrual cycle, and methodology (eg, storage temperature).
Potential migraine and CH signaling molecule profiles and biomarkers were revealed. Nevertheless, the high degree of heterogeneity between studies impedes identification of valid biomarkers but allowed us to assess the presence of confounders. Consideration of the potential confounders identified in this SR-MA might be of importance in the experimental planning of future studies. This consideration could be incorporated through establishment of specific guidelines.

The objective of this meta-analysis was to evaluate the effect of blending canola meal (CM) with other protein sources on production responses in lactating dairy cows. To evaluate this effect, a data set was assembled containing 22 studies reporting at least 3 isonitrogenous dietary treatments (total of 74 treatment means). Each study needed to report 1 diet with CM <0.3 kg/d, 1 or more diets consisting of CM blended with another protein source, and 1 diet with CM as the main protein source in the protein supplement (>85%). The crude protein (CP) concentration of CM averaged 37.4 ± 3.09% (dry matter basis), and the predictor of interest was the intake of CP from CM, which averaged 0.46 ± 0.413 kg/d among studies. The maximal CP from CM ranged from 0.47 to 1.55 kg/d among studies. The quadratic relationship between CP from CM and responses in milk true protein concentration was significant, the maximum response (3.19%) being reached at 0.79 kg of CP from CM; the quadratic relationships were not significant for the other dependent variables. Responses in dry matter intake; yields of milk, energy-corrected milk, and milk true protein; and apparent N efficiency were related positively to CP from CM and negatively for responses in milk fat and milk urea N concentrations. Remembering that diets were isonitrogenous within studies, this indicates no nutritional benefit of blending CM with another protein source. Taken together, the results indicate that the whole-body N utilization efficiency by the dairy cow improved and that more dietary protein was used to synthesize milk protein when CM was used as the sole protein source in the protein supplement up to 1.55 kg/d.

The term \"multilevel meta-analysis\" is encountered not only in applied research studies, but in multilevel resources comparing traditional meta-analysis to multilevel meta-analysis. In this tutorial, we argue that the term \"multilevel meta-analysis\" is redundant since all meta-analysis can be formulated as a special kind of multilevel model. To clarify the multilevel nature of meta-analysis the four standard meta-analytic models are presented using multilevel equations and fit to an example data set using four software programs: two specific to meta-analysis (metafor in R and SPSS macros) and two specific to multilevel modeling (PROC MIXED in SAS and HLM). The same parameter estimates are obtained across programs underscoring that all meta-analyses are multilevel in nature. Despite the equivalent results, not all software programs are alike and differences are noted in the output provided and estimators available. This tutorial also recasts distinctions made in the literature between traditional and multilevel meta-analysis as differences between meta-analytic choices, not between meta-analytic models, and provides guidance to inform choices in estimators, significance tests, moderator analyses, and modeling sequence. The extent to which the software programs allow flexibility with respect to these decisions is noted, with metafor emerging as the most favorable program reviewed.

Pooling information from multiple, independent studies (meta-analysis) adds great value to medical research. Random effects models are widely used for this purpose. However, there are many different ways of estimating model parameters, and the choice of estimation procedure may be influential upon the conclusions of the meta-analysis. In this paper, we describe a recently proposed Bayesian estimation procedure and compare it with a profile likelihood method and with the DerSimonian-Laird and Mandel-Paule estimators including the Knapp-Hartung correction. The Bayesian procedure uses a non-informative prior for the overall mean and the between-study standard deviation that is determined by the Berger and Bernardo reference prior principle. The comparison of these procedures focuses on the frequentist properties of interval estimates for the overall mean. The results of our simulation study reveal that the Bayesian approach is a promising alternative producing more accurate interval estimates than those three conventional procedures for meta-analysis. The Bayesian procedure is also illustrated using three examples of meta-analysis involving real data. Copyright © 2016 John Wiley & Sons, Ltd.

Ecosystem engineering is increasingly recognized as a relevant ecological driver of diversity and community composition. Although engineering impacts on the biota can vary from negative to positive, and from trivial to enormous, patterns and causes of variation in the magnitude of engineering effects across ecosystems and engineer types remain largely unknown. To elucidate the above patterns, we conducted a meta-analysis of 122 studies which explored effects of animal ecosystem engineers on species richness of other organisms in the community. The analysis revealed that the overall effect of ecosystem engineers on diversity is positive and corresponds to a 25% increase in species richness, indicating that ecosystem engineering is a facilitative process globally. Engineering effects were stronger in the tropics than at higher latitudes, likely because new or modified habitats provided by engineers in the tropics may help minimize competition and predation pressures on resident species. Within aquatic environments, engineering impacts were stronger in marine ecosystems (rocky shores) than in streams. In terrestrial ecosystems, engineers displayed stronger positive effects in arid environments (e.g. deserts). Ecosystem engineers that create new habitats or microhabitats had stronger effects than those that modify habitats or cause bioturbation. Invertebrate engineers and those with lower engineering persistence (<1 year) affected species richness more than vertebrate engineers which persisted for >1 year. Invertebrate species richness was particularly responsive to engineering impacts. This study is the first attempt to build an integrative framework of engineering effects on species diversity; it highlights the importance of considering latitude, habitat, engineering functional group, taxon and persistence of their effects in future theoretical and empirical studies.