BACKGROUND The possible advantage for weight loss of a diet that emphasizes protein, fat, or carbohydrates has not been established, and there are few studies that extend beyond 1 year. METHODS We randomly assigned 811 overweight adults to one of four diets; the targeted percentages of energy derived from fat, protein, and carbohydrates in the four diets were 20, 15, and 65%; 20, 25, and 55%; 40, 15, and 45%; and 40, 25, and 35%. The diets consisted of similar foods and met guidelines for cardiovascular health. The participants were offered group and individual instructional sessions for 2 years. The primary outcome was the change in body weight after 2 years in two-by-two factorial comparisons of low fat versus high fat and average protein versus high protein and in the comparison of highest and lowest carbohydrate content. RESULTS At 6 months, participants assigned to each diet had lost an average of 6 kg, which represented 7% of their initial weight; they began to regain weight after 12 months. By 2 years, weight loss remained similar in those who were assigned to a diet with 15% protein and those assigned to a diet with 25% protein (3.0 and 3.6 kg, respectively); in those assigned to a diet with 20% fat and those assigned to a diet with 40% fat (3.3 kg for both groups); and in those assigned to a diet with 65% carbohydrates and those assigned to a diet with 35% carbohydrates (2.9 and 3.4 kg, respectively) (P>0.20 for all comparisons). Among the 80% of participants who completed the trial, the average weight loss was 4 kg; 14 to 15% of the participants had a reduction of at least 10% of their initial body weight. Satiety, hunger, satisfaction with the diet, and attendance at group sessions were similar for all diets; attendance was strongly associated with weight loss (0.2 kg per session attended). The diets improved lipid-related risk factors and fasting insulin levels. CONCLUSIONS Reduced-calorie diets result in clinically meaningful weight loss regardless of which macronutrients they emphasize.

Summary Poly(ADP-ribose) is a major regulatory macromolecule in the nucleus, where it regulates transcription, chromosome structure and DNA damage repair. Functions in the interphase cytoplasm are less understood. Here we identify a requirement for poly(ADP-ribose) in the assembly of cytoplasmic stress granules, which accumulate RNA-binding proteins that regulate the translation and stability of mRNAs upon stress. We show that poly(ADP-ribose), 6 specific poly(ADP-ribose) polymerases and 2 poly(ADP-ribose) glycohydrolase isoforms are stress granule components. A subset of stress granule proteins, including microRNA-binding Argonaute family members Ago1-4, are modified by poly(ADP-ribose) and such modification increases upon stress – a condition when both microRNA-mediated translational repression and microRNA-directed mRNA cleavage are relieved. Similar relief of repression is also observed upon overexpression of specific poly(ADP-ribose) polymerases or, conversely, upon knockdown of glycohydrolase. We conclude that poly(ADP-ribose) is a key regulator of post-transcriptional gene expression in the cytoplasm.

The poly(ADP-ribose) polymerase (PARP) protein family generates ADP-ribose (ADPr) modifications onto target proteins using NAD+ as substrate. Based on the composition of three NAD+ coordinating amino acids, the H-Y-E motif, each PARP is predicted to generate either poly(ADP-ribose) (PAR) or mono(ADP-ribose) (MAR). However, the reaction product of each PARP has not been clearly defined, and is an important priority since PAR and MAR function via distinct mechanisms. Here we show that the majority of PARPs generate MAR, not PAR, and demonstrate that the H-Y-E motif is not the sole indicator of PARP activity. We identify automodification sites on seven PARPs, and demonstrate that MAR and PAR generating PARPs modify similar amino acids, suggesting that the sequence and structural constraints limiting PARPs to MAR synthesis do not limit their ability to modify canonical amino acid targets. In addition, we identify cysteine as a novel amino acid target for ADP-ribosylation on PARPs.

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous largescale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.Cancer forms and progresses through a series of critical transitions-from pre-malignant to malignant states, from locally contained to metastatic disease, and from treatment-responsive to treatment-resistant tumors (Figure 1). Although specifics differ across tumor types and patients, all transitions involve complex dynamic interactions between diverse pre-malignant, malignant, and non-malignant cells (e.g., stroma cells and immune cells), often organized in specific patterns within the tumor

Context The role of diet composition in response to overeating and energy dissipation in humans is unclear. Objective To evaluate the effects of overconsumption of low, normal, and high protein diets on weight gain, energy expenditure, and body composition. Design, Setting, and Participants A single-blind, randomized controlled trial of 25 US healthy, weight-stable male and female volunteers, aged 18 to 35 years with a body mass index between 19 and 30. The first participant was admitted to the inpatient metabolic unit in June 2005 and the last in October 2007. Intervention After consuming a weight-stabilizing diet for 13 to 25 days, participants were randomized to diets containing 5% of energy from protein (low protein), 15% (normal protein), or 25% (high protein), which they were overfed during the last 8 weeks of their 10- to 12-week stay in the inpatient metabolic unit. Compared with energy intake during the weight stabilization period, the protein diets provided approximately 40% more energy intake, which corresponds to 954 kcal/d (95% CI, 884–1022 kcal/d). Main Outcome Measures Body composition was measured by dual-energy x-ray absorptiometry biweekly, resting energy expenditure was measured weekly by ventilated hood, and total energy expenditure by doubly labeled water prior to the overeating and weight stabilization periods and at weeks 7 to 8. Results Overeating produced significantly less weight gain in the low protein diet group (3.16 kg; 95% CI, 1.88–4.44 kg) compared with the normal protein diet group (6.05 kg; 95% CI, 4.84–7.26 kg) or the high protein diet group (6.51 kg; 95% CI, 5.23–7.79 kg) (P=.002). Body fat increased similarly in all 3 protein diet groups and represented 50% to more than 90% of the excess stored calories. Resting energy expenditure, total energy expenditure, and body protein did not increase during overfeeding with the low protein diet. In contrast, resting energy expenditure (normal protein diet: 160 kcal/d [95% CI, 102–218 kcal/d]; high protein diet: 227 kcal/d [95% CI, 165–289 kcal/d]) and body protein (lean body mass) (normal protein diet: 2.87 kg [95% CI, 2.11–3.62 kg]; high protein diet: 3.18 kg [95% CI, 2.37–3.98 kg]) increased significantly with the normal and high protein diets. Conclusions Among persons living in a controlled setting, calories alone account for the increase in fat; protein affected energy expenditure and storage of lean body mass, but not body fat storage.

The human body at cellular resolution: the NIH Human Biomolecular Atlas Program HuBMAP consortium* Transformative technologies are enabling the construction of three-dimensional maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years, the NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) intends to develop a widely accessible framework for comprehensively mapping the human body at singlecell resolution by supporting technology development, data acquisition, and detailed spatial mapping. HuBMAP will integrate its efforts with other funding agencies, programs, consortia, and the biomedical research community at large towards the shared vision of a comprehensive, accessible three-dimensional molecular and cellular atlas of the human body, in health and under various disease conditions. t he human body is an incredible machine. Trillions of cells, organized across an array of spatial scales and a multitude of functional states, contribute to a symphony of physiology. While we broadly know how cells are organized in most tissues, a comprehensive understanding of the cellular and molecular states and interactive networks resident in the tissues and organs, from organizational and functional perspectives, is lacking. The specific three-dimensional organization of different cell types, together with the effects of cell-cell and cell-matrix interactions in their natural milieu, have a profound impact on normal function, natural ageing, tissue remodelling, and disease progression in different tissues and organs. Recently, new technologies have enabled the molecular characterization of a multitude of cell types 1-4 and mapping of their spatial relationships in complex tissues at unprecedented scale and single-cell resolution. These advances create the opportunity to build a high-resolution atlas of three-dimensional maps of human tissues and organs. HuBMAP (https://commonfund.nih.gov/hubmap) is an NIHsponsored program with the goals of developing an open framework and technologies for mapping the human body at cellular resolution as well as generating foundational maps for several tissues obtained from normal individuals across a wide range of ages. A previous NIH-sponsored project, GTEx 5 , examined DNA variants and bulk tissue expression patterns across approximately a thousand individuals, but HuBMAP is a distinct project focused on generating molecular maps that are spatially resolved at the single-cell level but using samples from a more limited number of people. To achieve these goals, HuBMAP has been designed as a cohesive and collaborative organization, with a culture of openness and sharing using team science-based approaches 6. The HuBMAP Consortium (https://hubmapconsortium.org/) will actively work with other ongoing initiatives including the Human Cell Atlas 7 , Human Protein Atlas 8 , LIfeTime (https://lifetime-fetflagship.eu/), and related NIH-funded consortia that are mapping specific organs (including the brain 9 , lungs (https://www.lungmap.net/), kidney (https...

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The Human Developmental Cell Atlas (HDCA) initiative, which is part of the Human Cell Atlas, aims to create a comprehensive reference map of cells during development. This will be critical to understanding normal organogenesis, the effect of mutations, environmental factors and infectious agents on human development, congenital and childhood disorders, and the cellular basis of ageing, cancer and regenerative medicine. Here we outline the HDCA initiative and the challenges of mapping and modelling human development using state-of-the-art technologies to create a reference atlas across gestation. Similar to the Human Genome Project, the HDCA will integrate the output from a growing community of scientists who are mapping human development into a unified atlas. We describe the early milestones that have been achieved and the use of human stem-cell-derived cultures, organoids and animal models to inform the HDCA, especially for prenatal tissues that are hard to acquire. Finally, we provide a roadmap towards a complete atlas of human development.Most modern developmental biology research has historically focused on model organisms. Owing to practical challenges, human development-from a fertilized ovum to a fully formed fetus at birth-has remained a poorly understood 'black box'. The implications of a human developmental cell atlas for understanding human development are far-reaching, as many congenital disorders and childhood cancers may originate during susceptible windows of development [1][2][3] . The clinical relevance of the atlas extends into adulthood for ageing, cancer and applications in regenerative medicine and stem cell therapies 4-6 . Furthermore, embryonic and fetal stem cells 7,8 and developmental trajectories provide an essential reference and guide for engineering human stem-cell-derived models 9-13 , organoids 14 and cellular therapies.Human development begins with a fertilized oocyte that divides and differentiates through preimplantation, embryonic and fetal stages (Fig. 1). Early studies began with morphometric and qualitative assessments of human embryos, leading to development of the Carnegie staging system 15 (Fig. 1). Advances in imaging, cytometry and genomics technologies have provided further insights into the complex spatiotemporal changes during organogenesis 16 . Recent progress in single-cell profiling technologies has revolutionized our ability to study human development at an unprecedented resolution 17 . Leveraging these advances to build a comprehensive atlas of human development (from the fertilized oocyte to birth) at cellular resolution is an ambitious endeavour that is similar in scale to the Human Genome Project,