A systematic review and meta-analysis of the effects of long-term antibiotic use on cognitive outcomes

Antibiotics are indispensable to infection management. However, use of antibiotics can cause gut microbiota dysbiosis, which has been linked to cognitive impairment by disrupting communication between the gut microbiota and the brain. We conducted a systematic review and meta-analysis on the effects of long-term antibiotic use on cognitive outcomes. We have searched PubMed, Web of Science, Embase, Cochrane Library and Scopus for English publications before March 2023 following the PRISMA guidelines. Screening, data extraction, and quality assessment were performed in duplicate. 960 articles were screened and 16 studies which evaluated the effect of any antibiotic compared to no antibiotics or placebo were included. Case-reports, in vitro and animal studies were excluded. We found that antibiotic use was associated with worse cognitive outcomes with a pooled effect estimate of - 0.11 (95% CI - 0.15, - 0.07, Z = 5.45; P &lt; 0.00001). Subgroup analyses performed on adult vs pediatric patients showed a similar association of antibiotic on cognition in both subgroups. Antibiotic treatment was not associated with worse cognition on subjects with existing cognitive impairment. On the other hand, antibiotic treatment on subjects with no prior cognitive impairment was associated with worse cognitive performance later in life. This calls for future well-designed and well-powered studies to investigate the impact of antibiotics on cognitive performance.</p

A systematic review and meta-analysis of the effects of long-term antibiotic use on cognitive outcomes

Antibiotics are indispensable to infection management. However, use of antibiotics can cause gut microbiota dysbiosis, which has been linked to cognitive impairment by disrupting communication between the gut microbiota and the brain. We conducted a systematic review and meta-analysis on the effects of long-term antibiotic use on cognitive outcomes. We have searched PubMed, Web of Science, Embase, Cochrane Library and Scopus for English publications before March 2023 following the PRISMA guidelines. Screening, data extraction, and quality assessment were performed in duplicate. 960 articles were screened and 16 studies which evaluated the effect of any antibiotic compared to no antibiotics or placebo were included. Case-reports, in vitro and animal studies were excluded. We found that antibiotic use was associated with worse cognitive outcomes with a pooled effect estimate of - 0.11 (95% CI - 0.15, - 0.07, Z = 5.45; P &lt; 0.00001). Subgroup analyses performed on adult vs pediatric patients showed a similar association of antibiotic on cognition in both subgroups. Antibiotic treatment was not associated with worse cognition on subjects with existing cognitive impairment. On the other hand, antibiotic treatment on subjects with no prior cognitive impairment was associated with worse cognitive performance later in life. This calls for future well-designed and well-powered studies to investigate the impact of antibiotics on cognitive performance.</p

Dynamic Interstitial Cell Response during Myocardial Infarction Predicts Resilience to Rupture in Genetically Diverse Mice.

Cardiac ischemia leads to the loss of myocardial tissue and the activation of a repair process that culminates in the formation of a scar whose structural characteristics dictate propensity to favorable healing or detrimental cardiac wall rupture. To elucidate the cellular processes underlying scar formation, here we perform unbiased single-cell mRNA sequencing of interstitial cells isolated from infarcted mouse hearts carrying a genetic tracer that labels epicardial-derived cells. Sixteen interstitial cell clusters are revealed, five of which were of epicardial origin. Focusing on stromal cells, we define 11 sub-clusters, including diverse cell states of epicardial- and endocardial-derived fibroblasts. Comparing transcript profiles from post-infarction hearts in C57BL/6J and 129S1/SvImJ inbred mice, which displays a marked divergence in the frequency of cardiac rupture, uncovers an early increase in activated myofibroblasts, enhanced collagen deposition, and persistent acute phase response in 129S1/SvImJ mouse hearts, defining a crucial time window of pathological remodeling that predicts disease outcome

Metformin intervention prevents cardiac dysfunction in a murine model of adult congenital heart disease.

OBJECTIVE: Congenital heart disease (CHD) is the most frequent birth defect worldwide. The number of adult patients with CHD, now referred to as ACHD, is increasing with improved surgical and treatment interventions. However the mechanisms whereby ACHD predisposes patients to heart dysfunction are still unclear. ACHD is strongly associated with metabolic syndrome, but how ACHD interacts with poor modern lifestyle choices and other comorbidities, such as hypertension, obesity, and diabetes, is mostly unknown. METHODS: We used a newly characterized mouse genetic model of ACHD to investigate the consequences and the mechanisms associated with combined obesity and ACHD predisposition. Metformin intervention was used to further evaluate potential therapeutic amelioration of cardiac dysfunction in this model. RESULTS: ACHD mice placed under metabolic stress (high fat diet) displayed decreased left ventricular ejection fraction. Comprehensive physiological, biochemical, and molecular analysis showed that ACHD hearts exhibited early changes in energy metabolism with increased glucose dependence as main cardiac energy source. These changes preceded cardiac dysfunction mediated by exposure to high fat diet and were associated with increased disease severity. Restoration of metabolic balance by metformin administration prevented the development of heart dysfunction in ACHD predisposed mice. CONCLUSIONS: This study reveals that early metabolic impairment reinforces heart dysfunction in ACHD predisposed individuals and diet or pharmacological interventions can be used to modulate heart function and attenuate heart failure. Our study suggests that interactions between genetic and metabolic disturbances ultimately lead to the clinical presentation of heart failure in patients with ACHD. Early manipulation of energy metabolism may be an important avenue for intervention in ACHD patients to prevent or delay onset of heart failure and secondary comorbidities. These interactions raise the prospect for a translational reassessment of ACHD presentation in the clinic

Palmitoylation of the pore-forming subunit of Ca(v)1.2 controls channel voltage sensitivity and calcium transients in cardiac myocytes

Mammalian voltage-activated L-type Ca2+ channels, such as Ca(v)1.2, control transmem- brane Ca2+ fluxes in numerous excitable tissues. Here, we report that the pore-forming α1C subunit of Ca(v)1.2 is reversibly palmitoylated in rat, rabbit, and human ventricular myocytes. We map the palmitoylation sites to two regions of the channel: The N termi- nus and the linker between domains I and II. Whole-cell voltage clamping revealed a rightward shift of the Ca(v)1.2 current–voltage relationship when α1C was not palmi- toylated. To examine function, we expressed dihydropyridine-resistant α1C in human induced pluripotent stem cell-derived cardiomyocytes and measured Ca2+ transients in the presence of nifedipine to block the endogenous channels. The transients generated by unpalmitoylatable channels displayed a similar activation time course but signifi- cantly reduced amplitude compared to those generated by wild-type channels. We thus conclude that palmitoylation controls the voltage sensitivity of Ca(v)1.2. Given that the identified Ca(v)1.2 palmitoylation sites are also conserved in most Ca(v)1 isoforms, we propose that palmitoylation of the pore-forming α1C subunit provides a means to regulate the voltage sensitivity of voltage-activated Ca 2+ channels in excitable cells

Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning

Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which has been hampered by our inability to monitor serotonin release and transport with high spatial and temporal resolution. We developed and applied a binding-pocket redesign strategy, guided by machine learning, to create a high-performance, soluble, fluorescent serotonin sensor (iSeroSnFR), enabling optical detection of millisecond-scale serotonin transients. We demonstrate that iSeroSnFR can be used to detect serotonin release in freely behaving mice during fear conditioning, social interaction, and sleep/wake transitions. We also developed a robust assay of serotonin transporter function and modulation by drugs. We expect that both machine-learning-guided binding-pocket redesign and iSeroSnFR will have broad utility for the development of other sensors and in vitro and in vivo serotonin detection, respectively