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The interactions between the medial prefrontal cortex (mPFC) and the hippocampus (HC) are critical for memory and decision making and have been specifically implicated in several neurological disorders including schizophrenia, epilepsy, frontotemporal dementia, and Alzheimer's disease. The ventral midline thalamus (vmThal), and lateral entorhinal cortex and perirhinal cortex (LEC/PER) constitute major communication pathways that facilitate mPFC-HC interactions in memory. Although vmThal and LEC/PER circuits have been delineated separately we sought to determine whether these two regions share cell-specific inputs that could influence both routes simultaneously. To do this we used a dual fluorescent retrograde tracing approach using cholera toxin subunit-B (CTB-488 and CTB-594) with injections targeting vmThal and the LEC/PER in rats. Retrograde cell body labeling was examined in key regions of interest within the mPFC-HC system including (1) mPFC, specifically anterior cingulate cortex (ACC), dorsal and ventrys including a thalamic hub through the vmThal and a cortical hub through lateral entorhinal cortex and perirhinal cortex. Our data highlight newly identified dual projecting cell populations in the septum, Sub, and EC of the rat brain. These dual projecting cells may have the ability to modify the information flow within the mPFC-HC circuit through synchronous activity, and thus offer new cell-specific circuit targets for basic and translational studies in memory.The invertebrate immune system possesses a mechanism named extracellular traps (ETs), it has been identified that this mechanism immobilizes and kills pathogens. ETs formation induces modification of histones, chromatin decondensation, and mixes with granule molecules, releasing them into the extracellular space as a defense mechanism. In the present review, we provide an overview on the identification of triggering stimuli such as pathogens, PAMPs, DAMPs, and chemical stimuli, discuss the participation of potential signaling pathways involving MAPK, PI3K, PKC, and ERK molecules that lead to NADPH oxidase or mitochondrial ROS production, and explore the potential relationship with several proteins such as myeloperoxidase, heat sock proteins, peroxinectin, elastase, and apolipoproteins. Furthermore, we also discuss the association of ETs with other immune mechanisms that could collaborate in the elimination of pathogens.
Interrupted Time Series (ITS) are a type of nonrandomized design commonly used to evaluate public health policy interventions, and the impact of exposures, at the population level. Meta-analysis may be used to combine results from ITS across studies (in the context of systematic reviews) or across sites within the same study. We aimed to examine the statistical approaches, methods, and completeness of reporting in reviews that meta-analyze results from ITS.

Eight electronic databases were searched to identify reviews (published 2000-2019) that meta-analyzed at least two ITS. Characteristics of the included reviews, the statistical methods used to analyze the ITS and meta-analyze their results, effect measures, and risk of bias assessment tools were extracted.

Of the 4213 identified records, 54 reviews were included. Nearly all reviews (94%) used two-stage meta-analysis, most commonly fitting a random effects model (69%). Among the 41 reviews that re-analyzed the ITS, linear regression (39%) and ARIMA (20%) were most commonly used; 38% adjusted for autocorrelation. The most common effect measure meta-analyzed was an immediate level-change (46/54). Reporting of the statistical methods and ITS characteristics was often incomplete.

Improvement is needed in the conduct and reporting of reviews that meta-analyze results from ITS.
Improvement is needed in the conduct and reporting of reviews that meta-analyze results from ITS.
Our aim was to identify and synthesize the results from meta-research studies to determine whether and how authors of original studies in clinical health research use systematic reviews when designing new studies.

For this systematic review, we searched MEDLINE (OVID), Embase (OVID) and the Cochrane Methodology Register. We included meta-research studies and primary outcome was the percentage of original studies using systematic reviews to design their study. Risk of bias was assessed using an ad hoc created list of ten items. The results are presented both as a narrative synthesis and a meta-analysis.

Sixteen studies were included. The use of a systematic review to inform the design of new clinical studies varied between 0% and 73%, with a mean percentage of 17%. The number of components of the design in which information from previous systematic reviews was used varied from three to 11.

Clinical health research is characterized by variability regarding the extent to which systematic reviews are used to guide the design. An evidence-based research (EBR) approach towards research design when new clinical health studies are designed is necessary to decrease potential research redundancy and increase end-user value.
Clinical health research is characterized by variability regarding the extent to which systematic reviews are used to guide the design. An evidence-based research (EBR) approach towards research design when new clinical health studies are designed is necessary to decrease potential research redundancy and increase end-user value.
Among ID studies seeking to make causal inferences and pooling individual-level longitudinal data from multiple infectious disease cohorts, we sought to assess what methods are being used, how those methods are being reported, and whether these factors have changed over time.

Systematic review of longitudinal observational infectious disease studies pooling individual-level patient data from 2+ studies published in English in 2009, 2014, or 2019. This systematic review protocol is registered with PROSPERO (CRD42020204104).

Our search yielded 1,462 unique articles. Of these, 16 were included in the final review. Our analysis showed a lack of causal inference methods and of clear reporting on methods and the required assumptions.

There are many approaches to causal inference which may help facilitate accurate inference in the presence of unmeasured and time-varying confounding. In observational ID studies leveraging pooled, longitudinal IPD, the absence of these causal inference methods and gaps in the reporting of key methodological considerations suggests there is ample opportunity to enhance the rigor and reporting of research in this field. Interdisciplinary collaborations between substantive and methodological experts would strengthen future work.
There are many approaches to causal inference which may help facilitate accurate inference in the presence of unmeasured and time-varying confounding. In observational ID studies leveraging pooled, longitudinal IPD, the absence of these causal inference methods and gaps in the reporting of key methodological considerations suggests there is ample opportunity to enhance the rigor and reporting of research in this field. Interdisciplinary collaborations between substantive and methodological experts would strengthen future work.
To predict community acquired pneumonia after respiratory tract infection (RTI) consultations in primary care by applying machine learning to electronic health records.

A population-based cohort study was conducted using primary care electronic health records between 2002 to 2017. Sixteen thousand two hundred eighty-nine patients who consulted with RTIs then subsequently diagnosed with pneumonia within 30 days were compared with a random sample of eligible RTI patients. Variable selection compared logistic regression, random forest and penalized regression models. Prediction models were developed using classification and regression trees (CART) and logistic regression. Model performance was assessed through internal and temporal validations.

Older age, comorbidity, and initial presentation with lower respiratory tract infection (LRTIs) were identified as the main predictors of pneumonia diagnosis. Developed models achieved good discrimination accuracy with AUROC for the logistic regression model being 0.81 (0.80, 0.84) and 0.70 (0.69, 0.71) for CART during internal validation, and 0.80 (0.79, 0.81) vs. 0.68 (0.67, 0.69) for temporal validation.

From a large number of candidate variables, a small number of predictors of pneumonia were consistently identified through machine learning variable selection procedures. Logistic regression generally provided better model performance than CART models.
From a large number of candidate variables, a small number of predictors of pneumonia were consistently identified through machine learning variable selection procedures. Logistic regression generally provided better model performance than CART models.
To explore mortality outcome usage in Cochrane systematic reviews and Core Outcome Sets for research.

Cochrane PICO searches identified Cochrane reviews (published January 2015-March 2021) including mortality outcomes. selleck chemicals These outcomes were categorized according to terminology used all-cause mortality, cause-specific mortality, infant mortality, maternal mortality, survival. Mortality outcomes in Core Outcome Sets (published until 2019 on the Core Outcome Measures in Effectiveness Trials (COMET) database) were also extracted and categorized.

In total, 2454 mortality outcomes were reported in 49% (1978/3999) of Cochrane reviews published January 2015-March 2021 all-cause (37%), infant (23%), maternal (11%), survival (10%), cause-specific (9%). Due to reviews not specifying mortality outcome type or including studies reporting no data, 11% (273/2208) remained uncategorized. Infant mortality and maternal mortality were frequently used together in reviews reporting two mortality outcomes. In total, 226 mortality outcomes were reported in 37% (165/449) of Core Outcome Sets all-cause (48%), survival (27%), cause-specific (12%), infant (9%), maternal (4%). Mortality measurement timing varied.

Mortality outcome usage varies in Cochrane reviews and Core Outcome Sets. This is problematic for evidence-based decision-making. Greater standardization is necessary for effective utilization of health research.
Mortality outcome usage varies in Cochrane reviews and Core Outcome Sets. This is problematic for evidence-based decision-making. Greater standardization is necessary for effective utilization of health research.The regulation of skeletal muscle growth following pro-hypertrophic stimuli requires a coordinated response by different cell types that leads to extracellular matrix (ECM) remodeling and increases in muscle cross-sectional area. Indeed, matricellular proteins serve a key role as communication vehicles that facilitate the propagation of signaling stimuli required for muscle adaptation to environmental challenges. We found that the matricellular protein cellular communication network factor 2 (CCN2), also known as connective tissue growth factor (CTGF), is induced during a time course of overload-driven skeletal muscle hypertrophy in mice. To elucidate the role of CCN2 in mediating the hypertrophic response, we utilized genetically engineered mouse models for myofiber-specific CCN2 gain- and loss-of-function and then examined their response to mechanical stimuli through muscle overload. Interestingly, myofiber-specific deletion of CCN2 blunted muscle's hypertrophic response to overload without interfering with ECM deposition.
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