Whole-genome sequencing reveals a complex African population demographic history and signatures of local adaptation.

We conduct high coverage (>30×) whole-genome sequencing of 180 individuals from 12 indigenous African populations. We identify millions of unreported variants, many predicted to be functionally important. We observe that the ancestors of southern African San and central African rainforest hunter-gatherers (RHG) diverged from other populations >200 kya and maintained a large effective population size. We observe evidence for ancient population structure in Africa and for multiple introgression events from "ghost" populations with highly diverged genetic lineages. Although currently geographically isolated, we observe evidence for gene flow between eastern and southern Khoesan-speaking hunter-gatherer populations lasting until ∼12 kya. We identify signatures of local adaptation for traits related to skin color, immune response, height, and metabolic processes. We identify a positively selected variant in the lightly pigmented San that influences pigmentation in vitro by regulating the enhancer activity and gene expression of PDPK1.

The antigenic anatomy of SARS-CoV-2 receptor binding domain.

Antibodies are crucial to immune protection against SARS-CoV-2, with some in emergency use as therapeutics. Here, we identify 377 human monoclonal antibodies (mAbs) recognizing the virus spike and focus mainly on 80 that bind the receptor binding domain (RBD). We devise a competition data-driven method to map RBD binding sites. We find that although antibody binding sites are widely dispersed, neutralizing antibody binding is focused, with nearly all highly inhibitory mAbs (IC50 < 0.1 µg/mL) blocking receptor interaction, except for one that binds a unique epitope in the N-terminal domain. Many of these neutralizing mAbs use public V-genes and are close to germline. We dissect the structural basis of recognition for this large panel of antibodies through X-ray crystallography and cryoelectron microscopy of 19 Fab-antigen structures. We find novel binding modes for some potently inhibitory antibodies and demonstrate that strongly neutralizing mAbs protect, prophylactically or therapeutically, in animal models.

CherryML: scalable maximum likelihood estimation of phylogenetic models.

Phylogenetic models of molecular evolution are central to numerous biological applications spanning diverse timescales, from hundreds of millions of years involving orthologous proteins to just tens of days relating to single cells within an organism. A fundamental problem in these applications is estimating model parameters, for which maximum likelihood estimation is typically employed. Unfortunately, maximum likelihood estimation is a computationally expensive task, in some cases prohibitively so. To address this challenge, we here introduce CherryML, a broadly applicable method that achieves several orders of magnitude speedup by using a quantized composite likelihood over cherries in the trees. The massive speedup offered by our method should enable researchers to consider more complex and biologically realistic models than previously possible. Here we demonstrate CherryML's utility by applying it to estimate a general 400 × 400 rate matrix for residue-residue coevolution at contact sites in three-dimensional protein structures; we estimate that using current state-of-the-art methods such as the expectation-maximization algorithm for the same task would take >100,000 times longer.

DNA language models are powerful predictors of genome-wide variant effects.

The expanding catalog of genome-wide association studies (GWAS) provides biological insights across a variety of species, but identifying the causal variants behind these associations remains a significant challenge. Experimental validation is both labor-intensive and costly, highlighting the need for accurate, scalable computational methods to predict the effects of genetic variants across the entire genome. Inspired by recent progress in natural language processing, unsupervised pretraining on large protein sequence databases has proven successful in extracting complex information related to proteins. These models showcase their ability to learn variant effects in coding regions using an unsupervised approach. Expanding on this idea, we here introduce the Genomic Pre-trained Network (GPN), a model designed to learn genome-wide variant effects through unsupervised pretraining on genomic DNA sequences. Our model also successfully learns gene structure and DNA motifs without any supervision. To demonstrate its utility, we train GPN on unaligned reference genomes of Arabidopsis thaliana and seven related species within the Brassicales order and evaluate its ability to predict the functional impact of genetic variants in A. thaliana by utilizing allele frequencies from the 1001 Genomes Project and a comprehensive database of GWAS. Notably, GPN outperforms predictors based on popular conservation scores such as phyloP and phastCons. Our predictions for A. thaliana can be visualized as sequence logos in the UCSC Genome Browser (https://genome.ucsc.edu/s/gbenegas/gpn-arabidopsis). We provide code (https://github.com/songlab-cal/gpn) to train GPN for any given species using its DNA sequence alone, enabling unsupervised prediction of variant effects across the entire genome.

Neutral sphingomyelinase 2 is required for HIV-1 maturation.

HIV-1 assembly occurs at the inner leaflet of the plasma membrane (PM) in highly ordered membrane microdomains. The size and stability of membrane microdomains is regulated by activity of the sphingomyelin hydrolase neutral sphingomyelinase 2 (nSMase2) that is localized primarily to the inner leaflet of the PM. In this study, we demonstrate that pharmacological inhibition or depletion of nSMase2 in HIV-1-producer cells results in a block in the processing of the major viral structural polyprotein Gag and the production of morphologically aberrant, immature HIV-1 particles with severely impaired infectivity. We find that disruption of nSMase2 also severely inhibits the maturation and infectivity of other primate lentiviruses HIV-2 and simian immunodeficiency virus, has a modest or no effect on nonprimate lentiviruses equine infectious anemia virus and feline immunodeficiency virus, and has no effect on the gammaretrovirus murine leukemia virus. These studies demonstrate a key role for nSMase2 in HIV-1 particle morphogenesis and maturation.

Selective whole-genome amplification reveals population genetics of Leishmania braziliensis directly from patient skin biopsies.

In Brazil, Leishmania braziliensis is the main causative agent of the neglected tropical disease, cutaneous leishmaniasis (CL). CL presents on a spectrum of disease severity with a high rate of treatment failure. Yet the parasite factors that contribute to disease presentation and treatment outcome are not well understood, in part because successfully isolating and culturing parasites from patient lesions remains a major technical challenge. Here we describe the development of selective whole genome amplification (SWGA) for Leishmania and show that this method enables culture-independent analysis of parasite genomes obtained directly from primary patient skin samples, allowing us to circumvent artifacts associated with adaptation to culture. We show that SWGA can be applied to multiple Leishmania species residing in different host species, suggesting that this method is broadly useful in both experimental infection models and clinical studies. SWGA carried out directly on skin biopsies collected from patients in Corte de Pedra, Bahia, Brazil, showed extensive genomic diversity. Finally, as a proof-of-concept, we demonstrated that SWGA data can be integrated with published whole genome data from cultured parasite isolates to identify variants unique to specific geographic regions in Brazil where treatment failure rates are known to be high. SWGA provides a relatively simple method to generate Leishmania genomes directly from patient samples, unlocking the potential to link parasite genetics with host clinical phenotypes.

Liver X Receptor LXRα Promotes Grass Carp Reovirus Infection by Attenuating IRF3-CBP Interaction and Inhibiting RLR Antiviral Signaling.

Liver X receptors (LXRs) are nuclear receptors involved in metabolism and the immune response. Different from mammalian LXRs, which include two isoforms, LXRα and LXRß, only a single LXRα gene exists in the piscine genomes. Although a study has suggested that piscine LXR inhibits intracellular bacterial survival, the functions of piscine LXRα in viral infection are unknown. In this study, we show that overexpression of LXRα from grass carp (Ctenopharyngodon idellus), which is named as gcLXRα, increases host susceptibility to grass carp reovirus (GCRV) infection, whereas gcLXRα knockdown in CIK (C. idellus kidney) cells inhibits GCRV infection. Consistent with these functional studies, gcLXRα knockdown promotes the transcription of antiviral genes involved in the RIG-I-like receptor (RLR) antiviral signaling pathway, including IFN regulatory factor (IRF3) and the type I IFN IFN1. Further results show that gcLXRα knockdown induces the expression of CREB-binding protein (CBP), a transcriptional coactivator. In the knockdown of CBP, the inhibitory effect of gcLXRα knockdown in limiting GCRV infection is completely abolished. gcLXRα also interacts with IRF3 and CBP, which impairs the formation of the IRF3/CBP transcription complex. Moreover, gcLXRα heterodimerizes with RXRg, which cooperatively impair the transcription of the RLR antiviral signaling pathway and promote GCRV infection. Taken together, to our knowledge, our findings provide new insight into the functional correlation between nuclear receptor LXRα and the RLR antiviral signaling pathway, and they demonstrate that gcLXRα can impair the RLR antiviral signaling pathway and the production of type I IFN via forming gcLXRα/RXRg complexes and attenuating IRF3/CBP complexes.

Allosteric regulation and crystallographic fragment screening of SARS-CoV-2 NSP15 endoribonuclease.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). The NSP15 endoribonuclease enzyme, known as NendoU, is highly conserved and plays a critical role in the ability of the virus to evade the immune system. NendoU is a promising target for the development of new antiviral drugs. However, the complexity of the enzyme's structure and kinetics, along with the broad range of recognition sequences and lack of structural complexes, hampers the development of inhibitors. Here, we performed enzymatic characterization of NendoU in its monomeric and hexameric form, showing that hexamers are allosteric enzymes with a positive cooperative index, and with no influence of manganese on enzymatic activity. Through combining cryo-electron microscopy at different pHs, X-ray crystallography and biochemical and structural analysis, we showed that NendoU can shift between open and closed forms, which probably correspond to active and inactive states, respectively. We also explored the possibility of NendoU assembling into larger supramolecular structures and proposed a mechanism for allosteric regulation. In addition, we conducted a large fragment screening campaign against NendoU and identified several new allosteric sites that could be targeted for the development of new inhibitors. Overall, our findings provide insights into the complex structure and function of NendoU and offer new opportunities for the development of inhibitors.

Functional genomics of OCTN2 variants informs protein-specific variant effect predictor for Carnitine Transporter Deficiency.

Genetic variants in SLC22A5, encoding the membrane carnitine transporter OCTN2, cause the rare metabolic disorder Carnitine Transporter Deficiency (CTD). CTD is potentially lethal but actionable if detected early, with confirmatory diagnosis involving sequencing of SLC22A5. Interpretation of missense variants of uncertain significance (VUSs) is a major challenge. In this study, we sought to characterize the largest set to date (n = 150) of OCTN2 variants identified in diverse ancestral populations, with the goals of furthering our understanding of the mechanisms leading to OCTN2 loss-of-function (LOF) and creating a protein-specific variant effect prediction model for OCTN2 function. Uptake assays with 14C-carnitine revealed that 105 variants (70%) significantly reduced transport of carnitine compared to wild-type OCTN2, and 37 variants (25%) severely reduced function to less than 20%. All ancestral populations harbored LOF variants; 62% of green fluorescent protein (GFP)-tagged variants impaired OCTN2 localization to the plasma membrane of human embryonic kidney (HEK293T) cells, and subcellular localization significantly associated with function, revealing a major LOF mechanism of interest for CTD. With these data, we trained a model to classify variants as functional (>20% function) or LOF (<20% function). Our model outperformed existing state-of-the-art methods as evaluated by multiple performance metrics, with mean area under the receiver operating characteristic curve (AUROC) of 0.895 ± 0.025. In summary, in this study we generated a rich dataset of OCTN2 variant function and localization, revealed important disease-causing mechanisms, and improved upon machine learning-based prediction of OCTN2 variant function to aid in variant interpretation in the diagnosis and treatment of CTD.

Kinetic Evaluation on Lithium Polysulfide in Weakly Solvating Electrolyte toward Practical Lithium-Sulfur Batteries.

Lithium-sulfur (Li-S) batteries are highly considered as next-generation energy storage techniques. Weakly solvating electrolyte with low lithium polysulfide (LiPS) solvating power promises Li anode protection and improved cycling stability. However, the cathodic LiPS kinetics is inevitably deteriorated, resulting in severe cathodic polarization and limited energy density. Herein, the LiPS kinetic degradation mechanism in weakly solvating electrolytes is disclosed to construct high-energy-density Li-S batteries. Activation polarization instead of concentration or ohmic polarization is identified as the dominant kinetic limitation, which originates from higher charge-transfer activation energy and a changed rate-determining step. To solve the kinetic issue, a titanium nitride (TiN) electrocatalyst is introduced and corresponding Li-S batteries exhibit reduced polarization, prolonged cycling lifespan, and high actual energy density of 381 Wh kg-1 in 2.5 Ah-level pouch cells. This work clarifies the LiPS reaction mechanism in protective weakly solvating electrolytes and highlights the electrocatalytic regulation strategy toward high-energy-density and long-cycling Li-S batteries.

Deciphering the folate puzzle: Unraveling the impact of genetic variations and metabolites on cancer risk.

The C677T polymorphism in the MTHFR gene and its role in folate metabolism, impacting serum folate metabolites like THF and 5-MTHF, is a critical but underexplored area in cancer research. This nested case-control study utilized data from CHHRS, involving 87,492 hypertensive adults without prior cancer. During a median of 2.02 years, we identified 1332 cancer cases and matched controls based on age, sex, and residency. Serum levels of folate, THF, and 5-MTHF were measured, and the MTHFR C677T gene polymorphism was considered. Statistical analyses included restricted cubic spline regression and conditional logistic regression models. Serum THF levels were inversely associated with overall cancer risk (ORper SD = 0.90, 95% CI = 0.82-0.99), while 5-MTHF levels showed a negative association in the general cohort (ORQ3 vs. Q1 = 0.76, 95% CI = 0.60-0.96; ORQ4 vs. Q1 = 0.75, 95% CI = 0.58-0.98) and in individuals with MTHFR C677T (CC + CT) polymorphism (ORper SD = 0.87, 95% CI = 0.77-0.99; ORQ4 VS. Q1 = 0.79, 95% CI = 0.61-0.98), but a positive association in the MTHFR C677T (TT) subgroup (ORper SD = 1.89, 95% CI = 1.02-3.72; ORQ4 VS. Q1 = 2.17, 95% CI = 1.06-8.21). The impact of folate, THF, and 5-MTHF on cancer risk varied significantly across different cancer types and MTHFR C677T genotypes. This study provides novel insights into the variable effects of folate and its metabolites on cancer risk, influenced by genetic factors like the MTHFR C677T polymorphism and cancer type.

Pushing the Limits of Capacitively Coupled Contactless Conductivity Detection for Capillary Electrophoresis.

Capillary electrophoresis with capacitively coupled contactless conductivity detection (CE-C4D) has proven to be an efficient technique for the separation and detection of charged inorganic, organic, and biochemical analytes. It offers several advantages, including cost-effectiveness, nanoliter injection volume, short analysis time, good separation efficiency, suitability for miniaturization, and portability. However, the routine determination of common inorganic cations (NH4+, K+, Na+, Ca2+, Mg2+, and Li+) and inorganic anions (F-, Cl-, Br-, NO2-, NO3-, PO43-, and SO42-) in water quality monitoring typically exhibits limits of detection of about 0.3-1 µM without preconcentration. This sensitivity often proves insufficient for the applications of CE-C4D in trace analysis situations. Here, we explore methods to push the detection limits of CE-C4D through a comprehensive consideration of signal and noise sources. In particular, we (i) studied the model of C4D and its guiding roles in C4D and CE-C4D, (ii) optimized the bandwidth and noise performance of the current-to-voltage (I-V) converter, and (iii) reduced the noise level due to the strong background signal of the background electrolyte by adaptive differential detection. We characterized the system with Li+; the 3-fold signal-to-noise (S/N) detection limit for Li+ was determined at 20 nM, with a linear range spanning from 60 nM to 1.6 mM. Moreover, the optimized CE-C4D method was applied to the analysis of common mixed inorganic cations (K+, Na+, Ca2+, Mg2+, and Li+), anions (F-, Cl-, Br-, NO2-, NO3-, PO43-, and SO42-), toxic halides (BrO3-) and heavy metal ions (Pb2+, Cd2+, Cr3+, Co2+, Ni2+, Zn2+, and Cu2+) at trace concentrations of 200 nM. All electropherograms showed good S/N ratios, thus proving its applicability and accuracy. Our results have shown that the developed CE-C4D method is feasible for trace ion analysis in water quality control.

Likelihood-based deconvolution of bulk gene expression data using single-cell references.

Direct comparison of bulk gene expression profiles is complicated by distinct cell type mixtures in each sample that obscure whether observed differences are actually caused by changes in the expression levels themselves or are simply a result of differing cell type compositions. Single-cell technology has made it possible to measure gene expression in individual cells, achieving higher resolution at the expense of increased noise. If carefully incorporated, such single-cell data can be used to deconvolve bulk samples to yield accurate estimates of the true cell type proportions, thus enabling one to disentangle the effects of differential expression and cell type mixtures. Here, we propose a generative model and a likelihood-based inference method that uses asymptotic statistical theory and a novel optimization procedure to perform deconvolution of bulk RNA-seq data to produce accurate cell type proportion estimates. We show the effectiveness of our method, called RNA-Sieve, across a diverse array of scenarios involving real data and discuss extensions made uniquely possible by our probabilistic framework, including a demonstration of well-calibrated confidence intervals.

Transporter genes in biosynthetic gene clusters predict metabolite characteristics and siderophore activity.

Biosynthetic gene clusters (BGCs) are operonic sets of microbial genes that synthesize specialized metabolites with diverse functions, including siderophores and antibiotics, which often require export to the extracellular environment. For this reason, genes for transport across cellular membranes are essential for the production of specialized metabolites and are often genomically colocalized with BGCs. Here, we conducted a comprehensive computational analysis of transporters associated with characterized BGCs. In addition to known exporters, in BGCs we found many importer-specific transmembrane domains that co-occur with substrate binding proteins possibly for uptake of siderophores or metabolic precursors. Machine learning models using transporter gene frequencies were predictive of known siderophore activity, molecular weights, and a measure of lipophilicity (log P) for corresponding BGC-synthesized metabolites. Transporter genes associated with BGCs were often equally or more predictive of metabolite features than biosynthetic genes. Given the importance of siderophores as pathogenicity factors, we used transporters specific for siderophore BGCs to identify both known and uncharacterized siderophore-like BGCs in genomes from metagenomes from the infant and adult gut microbiome. We find that 23% of microbial genomes from premature infant guts have siderophore-like BGCs, but only 3% of those assembled from adult gut microbiomes do. Although siderophore-like BGCs from the infant gut are predominantly associated with Enterobacteriaceae and Staphylococcus, siderophore-like BGCs can be identified from taxa in the adult gut microbiome that have rarely been recognized for siderophore production. Taken together, these results show that consideration of BGC-associated transporter genes can inform predictions of specialized metabolite structure and function.

Progress of Polymer Electrolytes Worked in Solid-State Lithium Batteries for Wide-Temperature Application.

Solid-state Li-ion batteries have emerged as the most promising next-generation energy storage systems, offering theoretical advantages such as superior safety and higher energy density. However, polymer-based solid-state Li-ion batteries face challenges across wide temperature ranges. The primary issue lies in the fact that most polymer electrolytes exhibit relatively low ionic conductivity at or below room temperature. This sensitivity to temperature variations poses challenges in operating solid-state lithium batteries at sub-zero temperatures. Moreover, elevated working temperatures lead to polymer shrinkage and deformation, ultimately resulting in battery failure. To address this challenge of polymer-based solid-state batteries, this review presents an overview of various promising polymer electrolyte systems. The review provides insights into the temperature-dependent physical and electrochemical properties of polymers, aiming to expand the temperature range of operation. The review also further summarizes modification strategies for polymer electrolytes suited to diverse temperatures. The final section summarizes the performance of various polymer-based solid-state batteries at different temperatures. Valuable insights and potential future research directions for designing wide-temperature polymer electrolytes are presented based on the differences in battery performance. This information is intended to inspire practical applications of wide-temperature polymer-based solid-state batteries.

SCITO-seq: single-cell combinatorial indexed cytometry sequencing.

The development of DNA-barcoded antibodies to tag cell surface molecules has enabled the use of droplet-based single-cell sequencing (dsc-seq) to profile protein abundances from thousands of cells simultaneously. As compared to flow and mass cytometry, the high per cell cost of current dsc-seq-based workflows precludes their use in clinical applications and large-scale pooled screens. Here, we introduce SCITO-seq, a workflow that uses splint oligonucleotides (oligos) to enable combinatorially indexed dsc-seq of DNA-barcoded antibodies from over 105 cells per reaction using commercial microfluidics. By encoding sample barcodes into splint oligos, we demonstrate that multiplexed SCITO-seq produces reproducible estimates of cellular composition and surface protein expression comparable to those from mass cytometry. We further demonstrate two modified splint oligo designs that extend SCITO-seq to achieve compatibility with commercial DNA-barcoded antibodies and simultaneous expression profiling of the transcriptome and surface proteins from the same cell. These results demonstrate SCITO-seq as a flexible and ultra-high-throughput platform for sequencing-based single-cell protein and multimodal profiling.

Palliative Surgery for Patients with Gastroesophageal Junction or Gastric Cancer: A Report on Clinical Observational Outcomes.

BACKGROUND: Few studies have focused on palliative surgery in patients with advanced gastroesophageal junction (GEJ) or gastric cancer. We sought to evaluate clinical observational outcomes following palliative surgery in this population. PATIENTS AND METHODS: Patients with GEJ or gastric cancer who underwent palliative surgery (1/2010-11/2022) were identified. The primary outcomes were symptom improvement, ability to tolerate an oral diet, discharge to home, 30 "good days" without hospitalization, and receipt of systemic treatment. Postoperative outcomes and survival were secondarily evaluated. RESULTS: Among 93 patients, the median age was 59 (IQR 47-68) years, and the median Eastern Cooperative Oncology Group Performance Status (ECOG-PS) was 1 (range 0-3). The most frequent indication for palliative surgery was primary tumor obstruction [75 (81%) patients]. The most common procedures were feeding tube placement in 60 (65%) and intestinal bypass in 15 (16%) patients. A total of 75 (81%) patients experienced symptom improvement. Of these, 19 (25%) developed recurrent and 49 (65%) developed new symptoms. ECOG-PS was significantly associated with symptom-free time. Among those who underwent a bypass, resection, or ostomy creation for malignant obstruction, 16 (80%) tolerated an oral diet. Postoperatively, 87 (94%) were discharged home, 72 (77%) had 30 good days, and 64 (69%) received systemic treatment. Postoperative complications occurred in 35 (38%) patients, and 7 (8%) died within 30 days. The median survival time was 7.7 (95% CI 6.4-10.40) months. CONCLUSIONS: Patients with incurable GEJ or gastric cancer can benefit from palliative surgery. Prognosis and performance status should inform goals-of-care discussions and patient selection for surgical palliation.

Noisy Delay Denoises Biochemical Oscillators.

Genetic oscillations are generated by delayed transcriptional negative feedback loops, wherein repressor proteins inhibit their own synthesis after a temporal production delay. This delay is distributed because it arises from a sequence of noisy processes, including transcription, translocation, translation, and folding. Because the delay determines repression timing and, therefore, oscillation period, it has been commonly believed that delay noise weakens oscillatory dynamics. Here, we demonstrate that noisy delay can surprisingly denoise genetic oscillators. Specifically, moderate delay noise improves the signal-to-noise ratio and sharpens oscillation peaks, all without impacting period and amplitude. We show that this denoising phenomenon occurs in a variety of well-studied genetic oscillators, and we use queueing theory to uncover the universal mechanisms that produce it.

A Negative Association between Plasma Phylloquinone and All-Cause Mortality in Chinese Adults with Hypertension: A Nested Case-Control Study.

BACKGROUND: Previous studies have revealed that vitamin K is essential for preventing various chronic diseases. Phylloquinone is the primary dietary and circulating form of vitamin K. However, data concerning the association between plasma phylloquinone and all-cause mortality are limited. OBJECTIVES: This study aimed to evaluate the association between plasma phylloquinone and risk of all-cause mortality and examine some potential confounders. METHODS: This study is a post hoc analysis of the RCT and a nested, case-control design was used. Enrolled participants had to have hypertension at baseline. Study initiation was 19 May, 2008, and the median follow-up was 4.5 y. A total of 604 mortality cases and 604 controls matched for age, sex, treatment group, and study site were included in this study. Odds ratios (OR) and 95% confidence intervals (CIs) of all-cause mortality were calculated using conditional or unconditional logistic regression, without or with adjusting for pertinent covariates, respectively. The concentration of phylloquinone was measured by liquid chromatography-tandem quadrupole mass spectrometry (LC-MS/MS). RESULTS: The mean and median phylloquinone levels were 1.62 nmol/L and 0.89 nmol/L, respectively. There was a significant negative association between log-transformed plasma phylloquinone and all-cause mortality after controlling for potential confounders (per 1 unit increase-OR: 0.79; 95% CI: 0.66, 0.95). Furthermore, the association of plasma phylloquinone with risk of all-cause mortality differed by body mass index (BMI) (<25 kg/m2 compared with ≥25 kg/m2, P-interaction = 0.004). A significant trend of decreasing risk with increasing concentration of phylloquinone was observed in participants with higher BMI (per 1 unit increase-OR: 0.71; 95% CI: 0.56, 0.90; P = 0.004). No significant correlation was found between phylloquinone and risk of all-cause mortality in those with BMI <25 kg/m2. CONCLUSIONS: In Chinese patients with hypertension, there was a significant negative association between baseline plasma phylloquinone and all-cause mortality, especially among those with higher BMI.

The effect of oxytocin nasal spray on social interaction in young children with autism: a randomized clinical trial.

Early supports to enhance social development in children with autism are widely promoted. While oxytocin has a crucial role in mammalian social development, its potential role as a medication to enhance social development in humans remains unclear. We investigated the efficacy, tolerability, and safety of intranasal oxytocin in young children with autism using a double-blind, randomized, placebo-controlled, clinical trial, following a placebo lead-in phase. A total of 87 children (aged between 3 and 12 years) with autism received 16 International Units (IU) of oxytocin (n = 45) or placebo (n = 42) nasal spray, morning and night (32 IU per day) for twelve weeks, following a 3-week placebo lead-in phase. Overall, there was no effect of oxytocin treatment over time on the caregiver-rated Social Responsiveness Scale (SRS-2) (p = 0.686). However, a significant interaction with age (p = 0.028) showed that for younger children, aged 3-5 years, there was some indication of a treatment effect. Younger children who received oxytocin showed improvement on caregiver-rated social responsiveness ( SRS-2). There was no other evidence of benefit in the sample as a whole, or in the younger age group, on the clinician-rated Clinical Global Improvement Scale (CGI-S), or any secondary measure. Importantly, placebo effects in the lead-in phase were evident and there was support for washout of the placebo response in the randomised phase. Oxytocin was well tolerated, with more adverse side effects reported in the placebo group. This study suggests the need for further clinical trials to test the benefits of oxytocin treatment in younger populations with autism.Trial registration www.anzctr.org.au (ACTRN12617000441314).