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Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme.

A bstract The nonsingular bounce models usually suffer from the ghost or gradient instabilities, as has been proved recently. In this paper, we propose a covariant effective theory for stable nonsingular bounce, which has the quadratic order of the second order derivative of the field ϕ but the background set only by P ( ϕ, X ). With it, we explicitly construct a fully stable nonsingular bounce model for the ekpyrotic scenario.

Previous studies have shown that translation elongation is regulated by multiple factors, but the observed heterogeneity remains only partially explained. To dissect quantitatively the different determinants of elongation speed, we use probabilistic modeling to estimate initiation and local elongation rates from ribosome profiling data. This model-based approach allows us to quantify the extent of interference between ribosomes on the same transcript. We show that neither interference nor the distribution of slow codons is sufficient to explain the observed heterogeneity. Instead, we find that electrostatic interactions between the ribosomal exit tunnel and specific parts of the nascent polypeptide govern the elongation rate variation as the polypeptide makes its initial pass through the tunnel. Once the N-terminus has escaped the tunnel, the hydropathy of the nascent polypeptide within the ribosome plays a major role in modulating the speed. We show that our results are consistent with the biophysical properties of the tunnel.

Metabolic reprogramming is a hallmark of cancer. However, systematic characterizations of metabolites in triple-negative breast cancer (TNBC) are still lacking. Our study profiled the polar metabolome and lipidome in 330 TNBC samples and 149 paired normal breast tissues to construct a large metabolomic atlas of TNBC. Combining with previously established transcriptomic and genomic data of the same cohort, we conducted a comprehensive analysis linking TNBC metabolome to genomics. Our study classified TNBCs into three distinct metabolomic subgroups: C1, characterized by the enrichment of ceramides and fatty acids; C2, featured with the upregulation of metabolites related to oxidation reaction and glycosyl transfer; and C3, having the lowest level of metabolic dysregulation. Based on this newly developed metabolomic dataset, we refined previous TNBC transcriptomic subtypes and identified some crucial subtype-specific metabolites as potential therapeutic targets. The transcriptomic luminal androgen receptor (LAR) subtype overlapped with metabolomic C1 subtype. Experiments on patient-derived organoid and xenograft models indicate that targeting sphingosine-1-phosphate (S1P), an intermediate of the ceramide pathway, is a promising therapy for LAR tumors. Moreover, the transcriptomic basal-like immune-suppressed (BLIS) subtype contained two prognostic metabolomic subgroups (C2 and C3), which could be distinguished through machine-learning methods. We show that N-acetyl-aspartyl-glutamate is a crucial tumor-promoting metabolite and potential therapeutic target for high-risk BLIS tumors. Together, our study reveals the clinical significance of TNBC metabolomics, which can not only optimize the transcriptomic subtyping system, but also suggest novel therapeutic targets. This metabolomic dataset can serve as a useful public resource to promote precision treatment of TNBC.

The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 system has been widely used for nuclear DNA editing to generate mutations or correct specific disease alleles. Despite its flexible application, it has not been determined if CRISPR/Cas9, originally identified as a bacterial defense system against virus, can be targeted to mitochondria for mtDNA editing. Here, we show that regular FLAG-Cas9 can localize to mitochondria to edit mitochondrial DNA with sgRNAs targeting specific loci of the mitochondrial genome. Expression of FLAG-Cas9 together with gRNA targeting Cox1 and Cox3 leads to cleavage of the specific mtDNA loci. In addition, we observed disruption of mitochondrial protein homeostasis following mtDNA truncation or cleavage by CRISPR/Cas9. To overcome nonspecific distribution of FLAG-Cas9, we also created a mitochondria-targeted Cas9 (mitoCas9). This new version of Cas9 localizes only to mitochondria; together with expression of gRNA targeting mtDNA, there is specific cleavage of mtDNA. MitoCas9-induced reduction of mtDNA and its transcription leads to mitochondrial membrane potential disruption and cell growth inhibition. This mitoCas9 could be applied to edit mtDNA together with gRNA expression vectors without affecting genomic DNA. In this brief study, we demonstrate that mtDNA editing is possible using CRISPR/Cas9. Moreover, our development of mitoCas9 with specific localization to the mitochondria should facilitate its application for mitochondrial genome editing.

Based on the effective field theory (EFT) of cosmological perturbations, we explicitly clarify the pathology in nonsingular cubic Galileon models and show how to cure it in EFT with new insights into this issue. With the least set of EFT operators that are capable to avoid instabilities in nonsingular cosmologies, we construct a nonsingular model dubbed the Genesis-inflation model, in which a slowly expanding phase (namely, Genesis) with increasing energy density is followed by slow-roll inflation. The spectrum of the primordial perturbation may be simulated numerically, which shows itself a large-scale cutoff, as the large-scale anomalies in CMB might be a hint for.

Yun Song and colleagues present SMC++, a statistical method for population history inference capable of analyzing unphased whole genomes and sample sizes much larger than can be analyzed by current methods. The authors apply SMC++ to sequence data from human, Drosophila and finch populations. It has recently been demonstrated that inference methods based on genealogical processes with recombination can uncover past population history in unprecedented detail. However, these methods scale poorly with sample size, limiting resolution in the recent past, and they require phased genomes, which contain switch errors that can catastrophically distort the inferred history. Here we present SMC++, a new statistical tool capable of analyzing orders of magnitude more samples than existing methods while requiring only unphased genomes (its results are independent of phasing). SMC++ can jointly infer population size histories and split times in diverged populations, and it employs a novel spline regularization scheme that greatly reduces estimation error. We apply SMC++ to analyze sequence data from over a thousand human genomes in Africa and Eurasia, hundreds of genomes from a Drosophila melanogaster population in Africa, and tens of genomes from zebra finch and long-tailed finch populations in Australia.

Musculoskeletal surgery imposes extended recovery periods and significant financial burdens that can undermine individual and system-level health security. Patients undergoing musculoskeletal surgery often face prolonged recovery and substantial post-discharge costs, yet longitudinal evidence on their healthcare use remains limited. This study quantified two-year post-discharge utilization and identified predictors of high expenditure among Korean musculoskeletal surgery patients. A retrospective cohort was constructed from the 2019-2021 Korea Health Panel. Adults (n = 182) hospitalized for spinal, knee, shoulder or other musculoskeletal disorders between July 2019 and June 2020 were followed for 24 months. Outcomes were total healthcare expenditure (log-transformed) and in the top 25% cost group (\"high-expenditure\") in the second post-discharge year. Among 182 adults hospitalized for musculoskeletal surgery, first-year post-discharge spending averaged US $848 but fell to US $487 in the second year. Readmission fell from 19.2% to 7.1%, and Western-medicine outpatient visits declined from 18.3 ± 25.9 to 13.6 ± 22.9 per person. By contrast, Traditional Korean Medicine (TKM) visits rose from 2.3 ± 6.5 to 3.3 ± 10.0. In multivariable models, metropolitan residence, obesity, additional chronic conditions, and heavier first-year inpatient and outpatient use independently predicted higher second-year costs. Lower household income was associated with lower spending. Index diagnoses were pivotal: spinal disorders and shoulder disorders markedly increased the odds of falling into the top-cost quartile. Among the first-year TKM, frequent chuna/manual therapy sessions were marginally associated with higher costs, suggesting these rehabilitative modalities may serve as proxies for underlying health complexity during the stabilization phase. Spinal and shoulder disorders, metropolitan residence, obesity, multimorbidity, heavy inpatient and outpatient use during the first post-discharge year, and frequent TKM sessions, albeit marginally, jointly predicted the highest second-year expenditures. These findings highlight the value of early risk stratification and tightly coordinated Western-and-traditional care pathways that facilitate the shift from structural repair to functional restoration. From a policy perspective, these results suggest the need for integrated post-discharge care models and targeted financial support strategies to reduce avoidable costs and enhance equity in musculoskeletal rehabilitation.

A bstract We investigate both the null energy condition (NEC) violating scenario and the c T -diminishing scenario for generating enhanced power spectrum of primordial gravitational waves (GWs) during inflation, where c T is the propagating speed of primordial GWs. Both of these two scenarios can be realized stably with theories beyond Horndeski, hence can be uniformly implemented within the framework of the effective field theory. We calculate the power spectrum of primordial GWs by assuming that the inflationary Universe undergoes three phases, where the violation of NEC or the diminishment of c T occurs in the intermediate phase. A template of the spectrum is given for the NEC-violating scenario. We also discuss the underlying relation and discrepancy between these two scenarios with a disformal transformation.

Requiring the existence of a unitary, causal and local UV-completion places a set of positivity bounds on the corresponding effective field theories (EFTs). We discuss the obstructions and possibility in applying the positivity bound to cosmology, in particular the EFT of cosmological perturbations. Taking a c T = 1 beyond-Horndeski EFT as an illustrative example, we derive such bounds, which incorporate the cosmological correction of order H 2 / Λ 2 , Λ being the cutoff scale. The derived bounds are applied to slow-roll inflation with beyond Horndeski operators. It is found that the cosmological positivity bounds may be either stronger or weaker than their flat space counterpart.