Nature Medicine最新文献

Kidney transplantation is the optimal treatment for renal failure. In the United States, a biopsy at the time of organ procurement is often used to assess kidney quality to decide whether it should be used for transplant. This assessment is focused on renal fibrotic burden, because fibrosis is an important measure of irreversible kidney injury. Unfortunately, biopsy at the time of transplant is plagued by problems, including bleeding risk, inaccuracies introduced by sampling bias and rapid sample preparation, and the need for round-the-clock pathology expertise. We developed a quantitative algorithm, called renal H-scan, that can be added to standard ultrasound workflows to quickly and noninvasively measure renal fibrotic burden in preclinical animal models and human transplant kidneys. Furthermore, we provide evidence that biopsy-based fibrosis estimates, because of their highly localized nature, are inaccurate measures of whole-kidney fibrotic burden and do not associate with kidney function post-transplant. In contrast, we show that whole-kidney H-scan fibrosis estimates associate closely with post-transplant renal function. Taken together, our data suggest that the addition of H-scan to standard ultrasound workflows could provide a safe, rapid and easy-to-perform method for accurate quantification of transplant kidney fibrotic burden, and thus better prediction of post-transplant renal outcomes.

Cognitive motor dissociation (CMD) can improve the accuracy to predict recovery of behaviorally unresponsive patients with acute brain injury, but acquisition and analysis of task-based electroencephalography (EEG) are technically challenging. N2 sleep patterns, such as sleep spindles on EEG, have been associated with good outcomes, rely on similar thalamocortical networks as consciousness and could provide less technically challenging complementary outcome predictors. In this prospective observational cohort study of 226 acutely brain injured patients, well-formed sleep spindles (WFSS) were more likely present in those with CMD than in those without CMD, often preceding the detection of CMD. WFSS were associated with a shorter time to recovery of consciousness, and both CMD and WFSS independently predicted recovery of independence, controlling for age, admission neurological status and injury type. WFSS are seen in approximately every third behaviorally unresponsive patient after acute brain injury, frequently precede detection of CMD and are a promising complementary predictor for recovery of consciousness and functional independence.

Although the intraoperative molecular diagnosis of the approximately 100 known brain tumor entities described to date has been a goal of neuropathology for the past decade, achieving this within a clinically relevant timeframe of under 1 h after biopsy collection remains elusive. Advances in third-generation sequencing have brought this goal closer, but established machine learning techniques rely on computationally intensive methods, making them impractical for live diagnostic workflows in clinical applications. Here we present MethyLYZR, a naive Bayesian framework enabling fully tractable, live classification of cancer epigenomes. For evaluation, we used nanopore sequencing to classify over 200 brain tumor samples, including 10 sequenced in a clinical setting next to the operating room, achieving highly accurate results within 15 min of sequencing. MethyLYZR can be run in parallel with an ongoing nanopore experiment with negligible computational overhead. Therefore, the only limiting factors for even faster time to results are DNA extraction time and the nanopore sequencer’s maximum parallel throughput. Although more evidence from prospective studies is needed, our study suggests the potential applicability of MethyLYZR for live molecular classification of nervous system malignancies using nanopore sequencing not only for the neurosurgical intraoperative use case but also for other oncologic indications and the classification of tumors from cell-free DNA in liquid biopsies.

Correction to: Nature Medicine https://doi.org/10.1038/s41591-025-03545-6, published online 24 February 2025.

On 4 February 2025, a list of words was leaked and circulated on various social media platforms that could cause National Science Foundation (NSF) research grants to be pulled when these words are used in their proposals. The list is alarmingly extensive, targeting terms related to gender, diversity, ethnicity, bias and ‘women/female/females’.

A Nature news article also reported that the NSF is actively flagging research grants that are in violation of US President Donald Trump’s executive orders¹. Confirmed internal flags include terms such as ‘broadening participation’, foreign assistance, climate science, domestic energy, and diversity, equity and inclusion (DEI) initiatives¹. Trump’s directives aim to eliminate funding for DEI initiatives and remove all references to these terms from federal resources, including grants from the NSF¹. However, it remains unclear how the list of words was selected, whether banning of these words serves this purpose and, most pressingly, whether grants that use these words even promote purportedly controversial ideologies to begin with.

Over a billion people worldwide live in informal settlements in developing cities¹ without basic infrastructure and services such as safe sanitation and clean water. Often located on marginal flood-prone or unstable land, these communities, which make up 20–40% of the urban population in low- and middle-income countries (LMICs), stand to be some of the most severely affected by a changing climate. More frequent and severe flooding, extreme and inescapable heat, storms, storm surges and episodes of water scarcity, as well as the existential threat of rises in sea level, are already having a disproportionate impact on the residents of these communities, who at the same time are some of the least resourced to deal with such adversities.

Beyond these visible physical threats, however, urban informal settlements (UISs) have many circumstantial factors that make them hotspots for health risks. Through six years of house-to-house surveys and microbiological, spatio–environmental sampling in 24 UIS communities in Makassar, Indonesia, and Suva, Fiji, as part of the Revitalising Informal Settlements and their Environments (RISE) program², we have gained deep insight into the many adversities and health challenges that these settlements face. These findings point to a perfect storm of factors that contribute to health risks in UIS communities, including: lack of effective sanitation resulting in the release of faecal waste into high-density urban communities; repeated flooding and poor drainage resulting in persistent ponding with pathogen-contaminated waters from local and upstream sewage discharge; lack of proper road and pathway access resulting in frequent pedestrian traffic through contaminated waters and sediments; poor quality housing, flooring and toilet facilities; poor or limited access to clean water; close exposure to domestic and wild animals, livestock, vermin and insects; and suboptimal health literacy. The lack of clean pathways and access to households creates a situation in which residents, especially children, are in repeated close contact and interaction with the external fecally contaminated environment, which may then be brought into the home. As a result, residents of these communities experience chronic, habitual exposure to disease-causing pathogens that manifests in high rates of frequent and recurrent locally contracted bacterial illness³. In children, there are long-term consequences related to the impacts of disease burden in early childhood in terms of anemia, stunting and poor cognitive development⁴.

Brain metastases frequently develop in patients with non-small cell lung cancer (NSCLC) and are a common cause of cancer-related deaths, yet our understanding of the underlying human biology is limited. Here we performed multimodal single-nucleus RNA and T cell receptor, single-cell spatial and whole-genome sequencing of brain metastases and primary tumors of patients with treatment-naive NSCLC. Chromosomal instability (CIN) is a distinguishing genomic feature of brain metastases compared with primary tumors, which we validated through integrated analysis of molecular profiling and clinical data in 4,869 independent patients, and a new cohort of 12,275 patients with NSCLC. Unbiased analyses revealed transcriptional neural-like programs that strongly enriched in cancer cells from brain metastases, including a recurring, CIN^high cell subpopulation that preexists in primary tumors but strongly enriched in brain metastases, which was also recovered in matched single-cell spatial transcriptomics. Using multiplexed immunofluorescence in an independent cohort of treatment-naive pairs of primary tumors and brain metastases from the same patients with NSCLC, we validated genomic and tumor-microenvironmental findings and identified a cancer cell population characterized by neural features strongly enriched in brain metastases. This comprehensive analysis provides insights into human NSCLC brain metastasis biology and serves as an important resource for additional discovery.

Glioblastoma (GBM) is an aggressive primary adult brain tumor that rapidly recurs after standard-of-care treatments, including surgery, chemotherapy and radiotherapy. While immune checkpoint inhibitor therapies have transformed outcomes in many tumor types, particularly when used neoadjuvantly or as a first-line treatment, including in melanoma brain metastases, they have shown limited efficacy in patients with resected or recurrent GBM. The lack of efficacy has been attributed to the scarcity of tumor-infiltrating lymphocytes (TILs), an immunosuppressive tumor microenvironment and low tumor mutation burden typical of GBM tumors, plus exclusion of large molecules from the brain parenchyma. We hypothesized that upfront neoadjuvant combination immunotherapy, administered with disease in situ, could induce a stronger immune response than treatment given after resection or after recurrence. Here, we present a case of newly diagnosed IDH-wild-type, MGMT promoter unmethylated GBM, treated with a single dose of neoadjuvant triplet immunotherapy (anti-programmed cell death protein 1 plus anti-cytotoxic T-lymphocyte protein 4 plus anti-lymphocyte-activation gene 3) followed by maximal safe resection 12 days later. The anti-programmed cell death protein 1 drug was bound to TILs in the resected GBM and there was marked TIL infiltration and activation compared with the baseline biopsy. After 17 months, there is no definitive sign of recurrence. If used first line, before safe maximal resection, checkpoint inhibitors are capable of immune activation in GBM and may induce a response. A clinical trial of first-line neoadjuvant combination checkpoint inhibitor therapy in newly diagnosed GBM is planned (GIANT; trial registration no. NCT06816927).

Genomic profiling of central nervous system (CNS) metastases has the potential to guide treatments. In the present study, we included 584 patients with non-small-cell lung cancer and CNS metastases and performed a comprehensive analysis of cerebrospinal fluid (CSF) circulating tumor DNA (ctDNA) with clinicopathological annotation. CSF ctDNA-positive detection was independently associated with shorter survival than negative detection (hazard ratio (HR) = 1.9, 95% confidence interval (CI) = 1.56–2.39; P < 0.0001). Matched tumor–CSF analysis characterized the CSF private molecular features causing poor survival (HR = 1.64, 95% CI = 1.15–2.32, P = 0.006). A multimetric CSF ctDNA prognostic model integrating CSF ctDNA features and clinical factors was developed for risk-stratifying CNS metastases and validated in an independent cohort. Among patients with treatment histories available, those positive for a driver alteration by CSF ctDNA showed a survival benefit from CSF-matched therapy (HR = 0.78, 95% CI = 0.65–0.92, P = 0.003). Longitudinal monitoring by CSF identified CNS-specific resistant mechanisms and a second matched targeted therapy indicating improved survival (HR = 0.56, 95% CI = 0.35–0.91, P = 0.018). These findings support the clinical value of CSF ctDNA for risk-stratifying CNS metastases and guiding therapy.

We were intrigued by the article by M. Arfan Ikram regarding the purported ‘misuse’ of biological aging, recently published in Nature Medicine¹. We are grateful to the author for raising this important issue but would like to offer a counterpoint to enrich the scientific dialogue on this topic.

When Peto and Doll stated “There is no such thing as aging”², they could not have anticipated the remarkable advancements in the understanding of the biology of aging over the subsequent two decades, including the development of various types of aging biomarkers. Although we concur that aging does not equal changes over time (but involves the accumulation of negative consequences of life, such as damage to macromolecules and organelles), dismissing the idea of any biomarkers based on calendar age as an approximate measure of aging seems counterproductive. Calendar age is deeply rooted in human life, science and society; it is reasonable to think that the accumulation of damage over time must come with consequences for health. It is also important to clarify how aging, biological age and disease are defined, because there is wide difference of opinion on these terms and concepts.