The role of gut microbiota in chronic restraint stress-induced cognitive deficits in mice.

BACKGROUND: Chronic stress induces cognitive deficits. There is a well-established connection between the enteric and central nervous systems through the microbiota-gut-brain (MGB) axis. However, the effects of the gut microbiota on cognitive deficits remain unclear. The present study aimed to elucidate the microbiota composition in cognitive deficits and explore its potential in predicting chronic stress-induced cognitive deficits. METHODS: Mice were randomly divided into control and chronic restraint stress (CRS) groups. The mice subjected to CRS were further divided into cognitive deficit (CRS-CD) and non-cognitive deficit (CRS-NCD) groups using hierarchical cluster analysis of novel object recognition test results. The composition and diversity of the gut microbiota were analyzed. RESULTS: After being subjected to chronic restraint distress, the CRS-CD mice travelled shorter movement distances (p = 0.034 vs. CRS-NCD; p < 0.001 vs. control) and had a lower recognition index than the CRS-NCD (p < 0.0001 vs. CRS-NCD; p < 0.0001 vs. control) and control mice. The results revealed that 5 gut bacteria at genus levels were significantly different in the fecal samples of mice in the three groups. Further analyses demonstrated that Muricomes were not only significantly enriched in the CRS-CD group but also correlated with a decreased cognitive index. The area under the receiver operating curve of Muricomes for CRS-induced cognitive deficits was 0.96. CONCLUSIONS: Our study indicates that the composition of the gut microbiota is involved in the development of cognitive deficits induced by chronic restraint stress. Further analysis revealed that Muricomes have the potential to predict the development of chronic stress-induced cognitive deficits in mice.

Transport Pathways of Nitrate in Stormwater Runoff Inferred from High-Frequency Sampling and Stable Water Isotopes.

Storm events can mobilize nitrogen species from landscapes into streams, exacerbating eutrophication and threatening aquatic ecosystems as well as human health. However, the transport pathways and storm responses of different nitrogen forms remain elusive. We used high-frequency chemical and isotopic sampling to partition sources of stormwater runoff and determine transport pathways of multiple nitrogen forms in an agricultural catchment. Bayesian mixing modeling reveals shallow subsurface water as the dominant source of stormwater runoff, contributing 74% of the water flux and 72, 71, and 79% of total nitrogen (TN), total dissolved nitrogen (TDN), and nitrate (NO3-N), respectively. Groundwater, by contrast, contributed 11% of stormwater runoff and 21, 22, and 17% of TN, TDN, and NO3-N, respectively. The remaining 14% of stormwater runoff can be attributed to rainwater, which contains much less TN, TDN, and NO3-N. Surprisingly, during storm events, the dominant nitrogen form was NO3-N rather than dissolved organic nitrogen. Antecedent conditions and runoff characteristics have an important influence on nitrogen loads during storm events. Our results provide insight into hydrological mechanisms driving nitrogen transport during storm events and may help in developing catchment management practices for reducing nitrogen pollution in aquatic ecosystems.

Using AuNPs-DNA Walker with Fluorophores Detects the Hepatitis Virus Rapidly.

Viral hepatitis is a systemic infectious diseases caused by various hepatitis viruses, primarily leading to liver damage. It is widely prevalent worldwide, with hepatitis viruses categorized into five types: hepatitis A, B, C, D, and E, based on their etiology. Currently, the detection of hepatitis viruses relies on methods such as enzyme-linked immunosorbent assay (ELISA), immunoelectron microscopy to observe and identify viral particles, and in situ hybridization to detect viral DNA in tissues. However, these methods have limitations, including low sensitivity, high error rates in results, and potential false negative reactions due to occult serum infection conditions. To address these challenges, we have designed an AuNPs-DNA walker method that uses gold nanoparticles (AuNPs) and complementary DNA strands for detecting viral DNA fragments through a colorimetric assay and fluorescence detection. The DNA walker, attached to gold nanoparticles, comprises a long walking strand with a probe sequence bound and stem-loop structural strands featuring a modified fluorescent molecule at the 3' end, which contains the DNAzyme structural domain. Upon the addition of virus fragments, the target sequence binds to the probe chains. Subsequently, the long walking strand is released and continuously hybridizes with the stem-loop structural strand. The DNAzyme undergoes hydrolytical cleavage by Mg2+, breaking the stem-loop structural strand into linear single strands. As a result of these structural changes, the negative charge density in the solution decreases, weakening spatial repulsion and rapidly reducing the stability of the DNA walker. This leads to aggregation upon the addition of a high-salt solution, accompanied by a color change. Virus typing can be performed through fluorescence detection. The innovative method can detect DNA/RNA fragments with high specificity for the target sequence, reaching concentrations as low as 1 nM. Overall, our approach offers a more convenient and reliable method for the detection of hepatitis viruses.

Novel Genetic Loci in Early-Onset Gout Derived From Whole-Genome Sequencing of an Adolescent Gout Cohort.

OBJECTIVE: Mechanisms underlying the adolescent-onset and early-onset gout are unclear. This study aimed to discover variants associated with early-onset gout. METHODS: We conducted whole-genome sequencing in a discovery adolescent-onset gout cohort of 905 individuals (gout onset 12 to 19 years) to discover common and low-frequency single-nucleotide variants (SNVs) associated with gout. Candidate common SNVs were genotyped in an early-onset gout cohort of 2,834 individuals (gout onset ≤30 years old), and meta-analysis was performed with the discovery and replication cohorts to identify loci associated with early-onset gout. Transcriptome and epigenomic analyses, quantitative real-time polymerase chain reaction and RNA sequencing in human peripheral blood leukocytes, and knock-down experiments in human THP-1 macrophage cells investigated the regulation and function of candidate gene RCOR1. RESULTS: In addition to ABCG2, a urate transporter previously linked to pediatric-onset and early-onset gout, we identified two novel loci (Pmeta < 5.0 × 10-8): rs12887440 (RCOR1) and rs35213808 (FSTL5-MIR4454). Additionally, we found associations at ABCG2 and SLC22A12 that were driven by low-frequency SNVs. SNVs in RCOR1 were linked to elevated blood leukocyte messenger RNA levels. THP-1 macrophage culture studies revealed the potential of decreased RCOR1 to suppress gouty inflammation. CONCLUSION: This is the first comprehensive genetic characterization of adolescent-onset gout. The identified risk loci of early-onset gout mediate inflammatory responsiveness to crystals that could mediate gouty arthritis. This study will contribute to risk prediction and therapeutic interventions to prevent adolescent-onset gout.

A multi-ancestry GWAS meta-analysis of facial features and its application in predicting archaic human features.

Facial morphology, a complex trait influenced by genetics, holds great significance in evolutionary research. However, due to limited fossil evidence, the facial characteristics of Neanderthals and Denisovans have remained largely unknown. In this study, we conducted a large-scale multi-ethnic meta-analysis of the genome-wide association study (GWAS), including 9674 East Asians and 10,115 Europeans, quantitatively assessing 78 facial traits using 3D facial images. We identified 71 genomic loci associated with facial features, including 21 novel loci. We developed a facial polygenic score (FPS) that enables the prediction of facial features based on genetic information. Interestingly, the distribution of FPSs among populations from diverse continental groups exhibited relevant correlations with observed facial features. Furthermore, we applied the FPS to predict the facial traits of seven Neanderthals and one Denisovan using ancient DNA and aligned predictions with the fossil records. Our results suggested that Neanderthals and Denisovans likely shared similar facial features, such as a wider but shorter nose and a wider endocanthion distance. The decreased mouth width was characterized specifically in Denisovans. The integration of genomic data and facial trait analysis provides valuable insights into the evolutionary history and adaptive changes in human facial morphology.

Epidemiologic and genetic associations between primary biliary cholangitis and extrahepatic rheumatic diseases.

Patients with primary biliary cholangitis (PBC) commonly experience extrahepatic rheumatic diseases. However, the epidemiologic and genetic associations as well as causal relationship between PBC and these extrahepatic conditions remain undetermined. In this study, we first conducted systematic review and meta-analyses by analyzing 73 studies comprising 334,963 participants across 17 countries and found strong phenotypic associations between PBC and rheumatic diseases. Next, we utilized large-scale genome-wide association study summary data to define the shared genetic architecture between PBC and rheumatic diseases, including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), systemic sclerosis (SSc) and Sjögren's syndrome (SS). We observed significant genetic correlations between PBC and each of the four rheumatic diseases. Pleiotropy and heritability enrichment analysis suggested the involvement of humoral immunity and interferon-associated processes for the comorbidity. Of note, we identified four variants shared between PBC and RA (rs80200208), SLE (rs9843053), and SSc (rs27524, rs3873182) using cross-trait meta-analysis. Additionally, several pleotropic loci for PBC and rheumatic diseases were found to share causal variants with gut microbes possessing immunoregulatory functions. Finally, Mendelian randomization revealed consistent evidence for a causal effect of PBC on RA, SLE, SSc, and SS, but no or inconsistent evidence for a causal effect of extrahepatic rheumatic diseases on PBC. Our study reveals a profound genetic overlap and causal relationships between PBC and extrahepatic rheumatic diseases, thus providing insights into shared biological mechanisms and novel therapeutic interventions.

The Contribution of Mosaic Chromosomal Alterations to Schizophrenia.

BACKGROUND: Mosaic chromosomal alterations are implicated in neuropsychiatric disorders, but the contribution to schizophrenia (SCZ) risk for somatic copy number variations (sCNVs) emerging in early developmental stages has not been fully established. METHODS: We analyzed blood-derived genotype arrays from 9715 patients with SCZ and 28,822 control participants of Chinese descent using a computational tool (MoChA) based on long-range chromosomal information to detect mosaic chromosomal alterations. We focused on probable early developmental sCNVs through stringent filtering. We assessed the burden of sCNVs across varying cell fraction cutoffs, as well as the frequency with which genes were involved in sCNVs. We integrated this data with the PGC (Psychiatric Genomics Consortium) dataset, which comprises 12,834 SCZ cases and 11,648 controls of European descent, and complemented it with genotyping data from postmortem brain tissue of 936 participants (449 cases and 487 controls). RESULTS: Patients with SCZ had a significantly higher somatic losses detection rate than control participants (1.00% vs. 0.52%; odds ratio = 1.91; 95% CI, 1.47-2.49; two-sided Fisher's exact test, p = 1.49 × 10-6). Further analysis indicated that the odds ratios escalated proportionately (from 1.91 to 2.78) with the increment in cell fraction cutoffs. Recurrent sCNVs associated with SCZ (odds ratio > 8; Fisher's exact test, p < .05) were identified, including notable regions at 10q21.1 (ZWINT), 3q26.1 (SLITRK3), 1q31.1 (BRINP3) and 12q21.31-21.32 (MGAT4C and NTS) in the Chinese cohort, and some regions were validated with PGC data. Cross-tissue validation pinpointed somatic losses at loci like 1p35.3-35.2 and 19p13.3-13.2. CONCLUSIONS: The study highlights the significant impact of mosaic chromosomal alterations on SCZ, suggesting their pivotal role in the disorder's genetic etiology.

Dissecting the genetic and causal relationship between sleep-related traits and common brain disorders.

BACKGROUND: There is a profound connection between abnormal sleep patterns and brain disorders, suggesting a shared influential association. However, the shared genetic basis and potential causal relationships between sleep-related traits and brain disorders are yet to be fully elucidated. METHODS: Utilizing linkage disequilibrium score regression (LDSC) and bidirectional two-sample univariable Mendelian Randomization (UVMR) analyses with large-scale GWAS datasets, we investigated the genetic correlations and causal associations across six sleep traits and 24 prevalent brain disorders. Additionally, a multivariable Mendelian Randomization (MVMR) analysis evaluated the cumulative effects of various sleep traits on each brain disorder, complemented by genetic loci characterization to pinpoint pertinent genes and pathways. RESULTS: LDSC analysis identified significant genetic correlations in 66 out of 144 (45.8 %) pairs between sleep-related traits and brain disorders, with the most pronounced correlations observed in psychiatric disorders (66 %, 48/72). UVMR analysis identified 29 causal relationships (FDR<0.05) between sleep traits and brain disorders, with 19 associations newly discovered according to our knowledge. Notably, major depression, attention-deficit/hyperactivity disorder, bipolar disorder, cannabis use disorder, and anorexia nervosa showed bidirectional causal relations with sleep traits, especially insomnia's marked influence on major depression (IVW beta 0.468, FDR = 5.24E-09). MVMR analysis revealed a nuanced interplay among various sleep traits and their impact on brain disorders. Genetic loci characterization underscored potential genes, such as HOXB2, while further enrichment analyses illuminated the importance of synaptic processes in these relationships. CONCLUSIONS: This study provides compelling evidence for the causal relationships and shared genetic backgrounds between common sleep-related traits and brain disorders.

Haplotype function score improves biological interpretation and cross-ancestry polygenic prediction of human complex traits.

We propose a new framework for human genetic association studies: at each locus, a deep learning model (in this study, Sei) is used to calculate the functional genomic activity score for two haplotypes per individual. This score, defined as the Haplotype Function Score (HFS), replaces the original genotype in association studies. Applying the HFS framework to 14 complex traits in the UK Biobank, we identified 3619 independent HFS-trait associations with a significance of p < 5 × 10-8. Fine-mapping revealed 2699 causal associations, corresponding to a median increase of 63 causal findings per trait compared with single-nucleotide polymorphism (SNP)-based analysis. HFS-based enrichment analysis uncovered 727 pathway-trait associations and 153 tissue-trait associations with strong biological interpretability, including 'circadian pathway-chronotype' and 'arachidonic acid-intelligence'. Lastly, we applied least absolute shrinkage and selection operator (LASSO) regression to integrate HFS prediction score with SNP-based polygenic risk scores, which showed an improvement of 16.1-39.8% in cross-ancestry polygenic prediction. We concluded that HFS is a promising strategy for understanding the genetic basis of human complex traits.

Scattered throughout the human genome are variations in the genetic code that make individuals more or less likely to develop certain traits. To identify these variants, scientists carry out Genome-wide association studies (GWAS) which compare the DNA variants of large groups of people with and without the trait of interest. This method has been able to find the underlying genes for many human diseases, but it has limitations. For instance, some variations are linked together due to where they are positioned within DNA, which can result in GWAS falsely reporting associations between genetic variants and traits. This phenomenon, known as linkage equilibrium, can be avoided by analyzing functional genomics which looks at the multiple ways a gene's activity can be influenced by a variation. For instance, how the gene is copied and decoded in to proteins and RNA molecules, and the rate at which these products are generated. Researchers can now use an artificial intelligence technique called deep learning to generate functional genomic data from a particular DNA sequence. Here, Song et al. used one of these deep learning models to calculate the functional genomics of haplotypes, groups of genetic variants inherited from one parent. The approach was applied to DNA samples from over 350 thousand individuals included in the UK BioBank. An activity score, defined as the haplotype function score (or HFS for short), was calculated for at least two haplotypes per individual, and then compared to various complex traits like height or bone density. Song et al. found that the HFS framework was better at finding links between genes and specific traits than existing methods. It also provided more information on the biology that may be underpinning these outcomes. Although more work is needed to reduce the computer processing times required to calculate the HFS, Song et al. believe that their new method has the potential to improve the way researchers identify links between genes and human traits.

Comparative genomics of macaques and integrated insights into genetic variation and population history.

The crab-eating macaques ( Macaca fascicularis ) and rhesus macaques ( M. mulatta ) are widely studied nonhuman primates in biomedical and evolutionary research. Despite their significance, the current understanding of the complex genomic structure in macaques and the differences between species requires substantial improvement. Here, we present a complete genome assembly of a crab-eating macaque and 20 haplotype-resolved macaque assemblies to investigate the complex regions and major genomic differences between species. Segmental duplication in macaques is ∼42% lower, while centromeres are ∼3.7 times longer than those in humans. The characterization of ∼2 Mbp fixed genetic variants and ∼240 Mbp complex loci highlights potential associations with metabolic differences between the two macaque species (e.g., CYP2C76 and EHBP1L1 ). Additionally, hundreds of alternative splicing differences show post-transcriptional regulation divergence between these two species (e.g., PNPO ). We also characterize 91 large-scale genomic differences between macaques and humans at a single-base-pair resolution and highlight their impact on gene regulation in primate evolution (e.g., FOLH1 and PIEZO2 ). Finally, population genetics recapitulates macaque speciation and selective sweeps, highlighting potential genetic basis of reproduction and tail phenotype differences (e.g., STAB1 , SEMA3F , and HOXD13 ). In summary, the integrated analysis of genetic variation and population genetics in macaques greatly enhances our comprehension of lineage-specific phenotypes, adaptation, and primate evolution, thereby improving their biomedical applications in human diseases.

Structurally divergent and recurrently mutated regions of primate genomes.

We sequenced and assembled using multiple long-read sequencing technologies the genomes of chimpanzee, bonobo, gorilla, orangutan, gibbon, macaque, owl monkey, and marmoset. We identified 1,338,997 lineage-specific fixed structural variants (SVs) disrupting 1,561 protein-coding genes and 136,932 regulatory elements, including the most complete set of human-specific fixed differences. We estimate that 819.47 Mbp or ∼27% of the genome has been affected by SVs across primate evolution. We identify 1,607 structurally divergent regions wherein recurrent structural variation contributes to creating SV hotspots where genes are recurrently lost (e.g., CARD, C4, and OLAH gene families) and additional lineage-specific genes are generated (e.g., CKAP2, VPS36, ACBD7, and NEK5 paralogs), becoming targets of rapid chromosomal diversification and positive selection (e.g., RGPD gene family). High-fidelity long-read sequencing has made these dynamic regions of the genome accessible for sequence-level analyses within and between primate species.

Multiomics Analyses Reveal Microbiome-Gut-Brain Crosstalk Centered on Aberrant Gamma-Aminobutyric Acid and Tryptophan Metabolism in Drug-Naïve Patients with First-Episode Schizophrenia.

BACKGROUND AND HYPOTHESIS: Schizophrenia (SCZ) is associated with complex crosstalk between the gut microbiota and host metabolism, but the underlying mechanism remains elusive. Investigating the aberrant neurotransmitter processes reflected by alterations identified using multiomics analysis is valuable to fully explain the pathogenesis of SCZ. STUDY DESIGN: We conducted an integrative analysis of multiomics data, including the serum metabolome, fecal metagenome, single nucleotide polymorphism data, and neuroimaging data obtained from a cohort of 127 drug-naïve, first-episode SCZ patients and 92 healthy controls to characterize the microbiome-gut-brain axis in SCZ patients. We used pathway-based polygenic risk score (PRS) analyses to determine the biological pathways contributing to genetic risk and mediation effect analyses to determine the important neuroimaging features. Additionally, a random forest model was generated for effective SCZ diagnosis. STUDY RESULTS: We found that the altered metabolome and dysregulated microbiome were associated with neuroactive metabolites, including gamma-aminobutyric acid (GABA), tryptophan, and short-chain fatty acids. Further structural and functional magnetic resonance imaging analyses highlighted that gray matter volume and functional connectivity disturbances mediate the relationships between Ruminococcus_torgues and Collinsella_aerofaciens and symptom severity and the relationships between species Lactobacillus_ruminis and differential metabolites l-2,4-diaminobutyric acid and N-acetylserotonin and cognitive function. Moreover, analyses of the Polygenic Risk Score (PRS) support that alterations in GABA and tryptophan neurotransmitter pathways are associated with SCZ risk, and GABA might be a more dominant contributor. CONCLUSIONS: This study provides new insights into systematic relationships among genes, metabolism, and the gut microbiota that affect brain functional connectivity, thereby affecting SCZ pathogenesis.

Population genetics of marmosets in Asian primate research centers and loci associated with epileptic risk revealed by whole-genome sequencing.

The common marmoset ( Callithrix jacchus) has emerged as a valuable nonhuman primate model in biomedical research with the recent release of high-quality reference genome assemblies. Epileptic marmosets have been independently reported in two Asian primate research centers. Nevertheless, the population genetics within these primate centers and the specific genetic variants associated with epilepsy in marmosets have not yet been elucidated. Here, we characterized the genetic relationships and risk variants for epilepsy in 41 samples from two epileptic marmoset pedigrees using whole-genome sequencing. We identified 14 558 184 single nucleotide polymorphisms (SNPs) from the 41 samples and found higher chimerism levels in blood samples than in fingernail samples. Genetic analysis showed fourth-degree of relatedness among marmosets at the primate centers. In addition, SNP and copy number variation (CNV) analyses suggested that the WW domain-containing oxidoreductase ( WWOX) and Tyrosine-protein phosphatase nonreceptor type 21 ( PTPN21) genes may be associated with epilepsy in marmosets. Notably, KCTD18-like gene deletion was more common in epileptic marmosets than control marmosets. This study provides valuable population genomic resources for marmosets in two Asian primate centers. Genetic analyses identified a reasonable breeding strategy for genetic diversity maintenance in the two centers, while the case-control study revealed potential risk genes/variants associated with epilepsy in marmosets.

Chimeric vaccine design against the epidemic Langya Henipavirus using immunoinformatics and validation via immune simulation approaches.

In July 2022, a new virus called Langya virus (LayV) was discovered in China in patients who had a fever. This virus is a type of Henipavirus (HNV) and is considered a potential threat as it could spread from animals to humans. It causes respiratory disease with symptoms including fever, coughing, and fatigue and is closely linked to two other henipaviruses that are known to infect humans, namely Hendra and Nipah viruses. These viruses may cause fatal respiratory illnesses. Investigators believe that the LayV is spread by shrews, and may have infected humans directly or via an intermediary species. Thus, the use of vaccines or immunizations against LayV is an alternate strategy for disease prevention. In this study, we employed various immunoinformatics methods to predict B cell, HTL and T cell epitopes from the LayV proteome in order to find the most promising candidate for a LayV vaccine. The most potent epitopes that are immunogenic and non-allergenic were joined with each other through suitable linkers. Human ß-defensin 2 was employed as an adjuvant to increase the immunogenicity of the vaccine construct. The final sequence of a multi-epitope vaccine construct was modelled for docking with TLRs. Concisely, our results suggest that the docked complexes of vaccine-TLRs seemed to be stable. Additionally, in silico cloning was done using E. coli as the host in order to validate the expression of our designed vaccine construct. The GC content of 54.39% and CAI value of 0.94 revealed that the vaccine component expresses efficiently in the host. This study presents the novel vaccine construct for LayV which will be essential for further experimental validations to confirm the immunogenicity and safety of the proposed vaccine structure, and eventually to treat HNV-related diseases.

Involvement of iNOS-induced reactive enteric glia cells in gastrointestinal motility disorders of postoperative Ileus mice.

Postoperative ileus (POI) is the cessation or reduction of gastrointestinal (GI) motility after surgery. Reactive enteric glial cells (EGCs) are critical for maintaining bowel function. However, the triggering mechanisms and downstream effects of reactive EGCs in POI were poorly understood. The goal of this current study was to investigate whether the inducible nitric oxide synthase (iNOS)-driven reactive EGCs participated in GI motility disorders and mechanisms underlying altered GI motility in POI. Intestinal manipulation (IM)-induced POI mice and iNOS-/- mice were used in the study. Longitudinal muscle and myenteric plexuses (LMMPs) from the distal small intestine were stained by immunofluorescence. Our results found that the GI motility disorders occurred in the IM-induced POI mice, and reactive EGCs were observed in LMMPs. Glial metabolic inhibitor gliotoxin fluorocitrate (FC) treatment or iNOS gene knockout attenuated GI motility dysfunction. In addition, we also found that FC treatment or iNOS gene knockout significantly inhibited the fluorescence intensity macrophage colony-stimulating factor (M-CSF), which reduced M2 phenotype macrophages activation in LMMPs of IM-induced POI mice. Our findings demonstrated that iNOS-driven reactive EGCs played a key role and were tightly linked to the MMs homeostasis in the POI mice. EGCs are emerging as a new frontier in neurogastroenterology and a potential therapeutic target.

Peripheral Nerve Block and Peri-operative Neurocognitive Disorders in Older Patients With Hip Fractures: A Systematic Review With Meta-analysis.

Background: Poor pain control and opioid use are risk factors for perioperative neurocognitive disorders (PND). The peripheral nerve block (PNB) can reduce pain and opioid consumption. This systematic review aimed to investigate the effects of PNB on PND in older patients with hip fractures. Methods: The PubMed, Cochrane Central Registers of Controlled Trial, Embase and ClinicalTrials.gov databases were searched from inception until November 19, 2021 for all randomized controlled trials (RCTs) comparing PNB with analgesics. The quality of the selected studies was assessed according to Version 2 of the Cochrane tool for assessing the risk of bias in RCTs. The primary outcome was the incidence of PND. Secondary outcomes included pain intensity and the incidence of postoperative nausea and vomiting. Subgroup analyses were based on population characteristics, type and infusion method of local anesthetics, and type of PNB. Results: Eight RCTs comprising 1015 older patients with hip fractures were included. Compared with analgesics, PNB did not reduce the incidence of PND in the elderly hip fracture population comprising patients with intact cognition and those with pre-existing dementia or cognitive impairment (risk ratio [RR] = .67; 95% confidence interval [CI] = .42 to 1.08; P = .10; I2 = 64%). However, PNB reduced the incidence of PND in older patients with intact cognition (RR = .61; 95% CI = .41 to .91; P = .02; I2 = 0%). Fascia iliaca compartment block, bupivacaine, and continuous infusion of local anesthetics were found to reduce the incidence of PND. Conclusions: PNB effectively reduced PND in older patients with hip fractures and intact cognition. When the study population included patients with intact cognition and those with pre-existing dementia or cognitive impairment, PNB showed no reduction in the incidence of PND. These conclusions should be confirmed with larger, higher-quality RCTs.

Effects of Propofol on Perioperative Sleep Quality in Patients Undergoing Gastrointestinal Endoscopy: A Prospective Cohort Study.

PURPOSE: Some patients experience sleep disturbances after endoscopy performed under sedation. This study aimed to evaluate the effects of propofol on sleep quality after gastrointestinal endoscopy (GE). DESIGN: This study was a prospective cohort study. METHODS: This study enrolled 880 patients who underwent GE. Patients who chose to undergo GE under sedation received intravenous propofol, whereas the control group did not. The Pittsburgh Sleep Quality Index (PSQI) was measured before GE (PSQI-1) and 3 weeks (PSQI-2) after GE. The Groningen Sleep Score Scale (GSQS) was used before GE (GSQS-1) and 1 (GSQS-2) and 7 days (GSQS-3) after GE. FINDINGS: There was a significant increase in GSQS scores from baseline to days 1 and 7 after GE (GSQS-2 vs GSQS-1, P < .001, GSQS-3 vs GSQS-1, P = .008). However, no significant changes were observed in the control group (GSQS-2 vs GSQS-1, P = .38, GSQS-3 vs GSQS-1, P = .66). On day 21, there were no significant changes in the baseline PSQI scores over time in either group (sedation group, P = .96; control group, P = .95). CONCLUSIONS: GE with propofol sedation negatively affected sleep quality for 7 days after GE but not 3 weeks after GE.