Brain energy metabolism is optimized to minimize the cost of enzyme synthesis and transport.

The energy metabolism of the brain is poorly understood partly due to the complex morphology of neurons and fluctuations in ATP demand over time. To investigate this, we used metabolic models that estimate enzyme usage per pathway, enzyme utilization over time, and enzyme transportation to evaluate how these parameters and processes affect ATP costs for enzyme synthesis and transportation. Our models show that the total enzyme maintenance energy expenditure of the human body depends on how glycolysis and mitochondrial respiration are distributed both across and within cell types in the brain. We suggest that brain metabolism is optimized to minimize the ATP maintenance cost by distributing the different ATP generation pathways in an advantageous way across cell types and potentially also across synapses within the same cell. Our models support this hypothesis by predicting export of lactate from both neurons and astrocytes during peak ATP demand, reproducing results from experimental measurements reported in the literature. Furthermore, our models provide potential explanation for parts of the astrocyte-neuron lactate shuttle theory, which is recapitulated under some conditions in the brain, while contradicting other aspects of the theory. We conclude that enzyme usage per pathway, enzyme utilization over time, and enzyme transportation are important factors for defining the optimal distribution of ATP production pathways, opening a broad avenue to explore in brain metabolism.

Generation and analysis of context-specific genome-scale metabolic models derived from single-cell RNA-Seq data.

Single-cell RNA sequencing combined with genome-scale metabolic models (GEMs) has the potential to unravel the differences in metabolism across both cell types and cell states but requires new computational methods. Here, we present a method for generating cell-type-specific genome-scale models from clusters of single-cell RNA-Seq profiles. Specifically, we developed a method to estimate the minimum number of cells required to pool to obtain stable models, a bootstrapping strategy for estimating statistical inference, and a faster version of the task-driven integrative network inference for tissues algorithm for generating context-specific GEMs. In addition, we evaluated the effect of different RNA-Seq normalization methods on model topology and differences in models generated from single-cell and bulk RNA-Seq data. We applied our methods on data from mouse cortex neurons and cells from the tumor microenvironment of lung cancer and in both cases found that almost every cell subtype had a unique metabolic profile. In addition, our approach was able to detect cancer-associated metabolic differences between cancer cells and healthy cells, showcasing its utility. We also contextualized models from 202 single-cell clusters across 19 human organs using data from Human Protein Atlas and made these available in the web portal Metabolic Atlas, thereby providing a valuable resource to the scientific community. With the ever-increasing availability of single-cell RNA-Seq datasets and continuously improved GEMs, their combination holds promise to become an important approach in the study of human metabolism.

Increasing instability of a rocky intertidal meta-ecosystem.

Climate change threatens to destabilize ecological communities, potentially moving them from persistently occupied "basins of attraction" to different states. Increasing variation in key ecological processes can signal impending state shifts in ecosystems. In a rocky intertidal meta-ecosystem consisting of three distinct regions spread across 260 km of the Oregon coast, we show that annually cleared sites are characterized by communities that exhibit signs of increasing destabilization (loss of resilience) over the past decade despite persistent community states. In all cases, recovery rates slowed and became more variable over time. The conditions underlying these shifts appear to be external to the system, with thermal disruptions (e.g., marine heat waves, El Niño-Southern Oscillation) and shifts in ocean currents (e.g., upwelling) being the likely proximate drivers. Although this iconic ecosystem has long appeared resistant to stress, the evidence suggests that subtle destabilization has occurred over at least the last decade.

Metastatic triple negative breast cancer adapts its metabolism to destination tissues while retaining key metabolic signatures.

Triple negative breast cancer (TNBC) metastases are assumed to exhibit similar functions in different organs as in the original primary tumor. However, studies of metastasis are often limited to a comparison of metastatic tumors with primary tumors of their origin, and little is known about the adaptation to the local environment of the metastatic sites. We therefore used transcriptomic data and metabolic network analyses to investigate whether metastatic tumors adapt their metabolism to the metastatic site and found that metastatic tumors adopt a metabolic signature with some similarity to primary tumors of their destinations. The extent of adaptation, however, varies across different organs, and metastatic tumors retain metabolic signatures associated with TNBC. Our findings suggest that a combination of anti-metastatic approaches and metabolic inhibitors selected specifically for different metastatic sites, rather than solely targeting TNBC primary tumors, may constitute a more effective treatment approach.

Use of co-production to explore food insecurity in adults with severe mental illness living in Northern England: a mixed-methods study.

BACKGROUND: People living with severe mental illness experience premature mortality from diet-related preventable illnesses. Yet, little research focuses on food insecurity with adults with severe mental illness. This coproduced study aimed to understand the experiences of adults with severe mental illness and food insecurity and strategies to help. METHODS: Following a pragmatism philosophical foundation, we undertook a mixed-methods study involving a survey (online and paper versions) and one-to-one semi-structured interviews (online and telephone) during March 7 to Dec 16, 2022. We recruited participants via existing severe mental illness service user groups and social media in Northern England. Eligible participants were adults (≥18 years) self-reporting a diagnosis of severe mental illness. Ethics approval was obtained from Teesside University and the Health Research Authority (Reference: 22/NR/0010; IRAS ID: 306281), with informed consent given. The target sample size, accounting for a typical survey response rate for people with severe mental illness of 10-20%, was 135. A target sample of 20 interviews was agreed to capture a range of views. Food insecurity was defined as the lack of financial resources needed to ensure someone has reliable access to enough food to meet their dietary, nutritional, and social needs. It is sometimes called food poverty. Quantitative data were analysed using descriptive statistics and binary logistic regression and qualitative data using thematic analysis. FINDINGS: 135 participants completed the survey (mean age 44·67 years [SD 14·1]). Participants were predominantly male (53%, n=72), white (87%, n=117), and from the Yorkshire region (50%, n=68). Overall, prevalence of food insecurity was 50·4% (n=68). Discussion across 13 interviews found food insecurity being a long-rooted experience, including familial and intergenerational experiences of food insecurity: "I grew up… with this insecurity around food" (P002). Recommendations for tackling food insecurity centred on food banks, increasing accessibility, and reducing stigma: "I would like to get more information on where the centres are..." (P006) and "I was referred to, erm, a foodbank … but it's still the stigma that's attached to it." (P002). INTERPRETATION: We found a higher prevalence of food insecurity in this study than in the general population (being 15%), yet limited research with adults with severe mental illness perpetuates food insecurity intergenerational injustices. Food insecurity should be eliminated. However, in the meanwhile, there should be widespread easy access to food banks offering nutritional foods. Limitations of this research include not reaching target sample size and a lack of ethnic diversity. FUNDING: National Institute of Health and Care Research (NIHR) Research for Patient Benefit.

Genome-scale metabolic network reconstruction of model animals as a platform for translational research.

Genome-scale metabolic models (GEMs) are used extensively for analysis of mechanisms underlying human diseases and metabolic malfunctions. However, the lack of comprehensive and high-quality GEMs for model organisms restricts translational utilization of omics data accumulating from the use of various disease models. Here we present a unified platform of GEMs that covers five major model animals, including Mouse1 (Mus musculus), Rat1 (Rattus norvegicus), Zebrafish1 (Danio rerio), Fruitfly1 (Drosophila melanogaster), and Worm1 (Caenorhabditis elegans). These GEMs represent the most comprehensive coverage of the metabolic network by considering both orthology-based pathways and species-specific reactions. All GEMs can be interactively queried via the accompanying web portal Metabolic Atlas. Specifically, through integrative analysis of Mouse1 with RNA-sequencing data from brain tissues of transgenic mice we identified a coordinated up-regulation of lysosomal GM2 ganglioside and peptide degradation pathways which appears to be a signature metabolic alteration in Alzheimer's disease (AD) mouse models with a phenotype of amyloid precursor protein overexpression. This metabolic shift was further validated with proteomics data from transgenic mice and cerebrospinal fluid samples from human patients. The elevated lysosomal enzymes thus hold potential to be used as a biomarker for early diagnosis of AD. Taken together, we foresee that this evolving open-source platform will serve as an important resource to facilitate the development of systems medicines and translational biomedical applications.

Is it ethical to use Mechanical Turk for behavioral research? Relevant data from a representative survey of MTurk participants and wages.

To understand human behavior, social scientists need people and data. In the last decade, Amazon's Mechanical Turk (MTurk) emerged as a flexible, affordable, and reliable source of human participants and was widely adopted by academics. Yet despite MTurk's utility, some have questioned whether researchers should continue using the platform on ethical grounds. The brunt of their concern is that people on MTurk are financially insecure, subject to abuse, and earn inhumane wages. We investigated these issues with two representative probability surveys of the U.S. MTurk population (N = 4094). The surveys revealed: (1) the financial situation of people on MTurk mirrors the general population, (2) most participants do not find MTurk stressful or requesters abusive, and (3) MTurk offers flexibility and benefits that most people value above other options for work. People reported it is possible to earn more than $10 per hour and said they would not trade the flexibility of MTurk for less than $25 per hour. Altogether, our data are important for assessing whether MTurk is an ethical place for research.

Evaluating CloudResearch's Approved Group as a solution for problematic data quality on MTurk.

Maintaining data quality on Amazon Mechanical Turk (MTurk) has always been a concern for researchers. These concerns have grown recently due to the bot crisis of 2018 and observations that past safeguards of data quality (e.g., approval ratings of 95%) no longer work. To address data quality concerns, CloudResearch, a third-party website that interfaces with MTurk, has assessed ~165,000 MTurkers and categorized them into those that provide high- (~100,000, Approved) and low- (~65,000, Blocked) quality data. Here, we examined the predictive validity of CloudResearch's vetting. In a pre-registered study, participants (N = 900) from the Approved and Blocked groups, along with a Standard MTurk sample (95% HIT acceptance ratio, 100+ completed HITs), completed an array of data-quality measures. Across several indices, Approved participants (i) identified the content of images more accurately, (ii) answered more reading comprehension questions correctly, (iii) responded to reversed coded items more consistently, (iv) passed a greater number of attention checks, (v) self-reported less cheating and actually left the survey window less often on easily Googleable questions, (vi) replicated classic psychology experimental effects more reliably, and (vii) answered AI-stumping questions more accurately than Blocked participants, who performed at chance on multiple outcomes. Data quality of the Standard sample was generally in between the Approved and Blocked groups. We discuss how MTurk's Approval Rating system is no longer an effective data-quality control, and we discuss the advantages afforded by using the Approved group for scientific studies on MTurk.

Do you know the Wooly Bully? Testing era-based knowledge to verify participant age online.

People in online studies sometimes misrepresent themselves. Regardless of their motive for doing so, participant misrepresentation threatens the validity of research. Here, we propose and evaluate a way to verify the age of online respondents: a test of era-based knowledge. Across six studies (N = 1543), participants of various ages completed an age verification instrument. The instrument assessed familiarity with cultural phenomena (e.g., songs and TV shows) from decades past and present. We consistently found that our instrument discriminated between people of different ages. In Studies 1a and 1b, self-reported age correlated strongly with performance on the instrument (mean r = .8). In Study 2, the instrument reliably detected imposters who we knew were misrepresenting their age. For impostors, self-reported age did not correlate with performance on the instrument (r = .077). Finally, in Studies 3a, 3b, and 3c, the instrument remained robust with African Americans, people from low educational backgrounds, and recent immigrants to the United States. Thus, our instrument shows promise for verifying the age of online respondents, and, as we discuss, our approach of assessing "insider knowledge" holds great promise for verifying other identities within online studies.

Effectiveness of a neonatal COVID-19 response project: A mixed-methods evaluation using the Donabedian model.

Objective: This article outlines notable findings of a service evaluation of a COVID-19 response project, the Nurture Project (July 2020-March 2021). Method: The Donabedian structure-process-outcome model was used. Mixed-methods online surveys and organisational data were analysed using reflexive thematic analysis and statistical analysis methods. Results: Most staff and service users were satisfied with the project, reporting positive benefits to mental health, child development, and wellbeing. However, project outcome measures (Generalised Anxiety Disorder Scale GAD-7 and the Patient Health Questionnaire PHQ-9) were statistically non-significant. Conclusion: Although the project was considered successful, recommendations for future service evaluation methods, outcome measurement, and future research are provided.

Person identity-specific adaptation effects in the ventral occipito-temporal cortex.

Identifying the faces of familiar persons requires the ability to assign several different images of a face to a common identity. Previous research showed that the occipito-temporal cortex, including the fusiform and the occipital face areas, is sensitive to personal identity. Still, the viewpoint, facial expression and image-independence of this information are currently under heavy debate. Here we adapted a rapid serial visual stimulation paradigm Johnston et al. (2016, https://doi.org/10.1016/j.cortex.2016.10.002) and presented highly variable ambient-face images of famous persons to measure functional magnetic resonance imaging (fMRI) adaptation. fMRI adaptation is considered as the neuroimaging manifestation of repetition suppression, a neural phenomenon currently explained as a correlate of reduced predictive error responses for expected stimuli. We revisited the question of image-invariant identity-specific encoding mechanisms of the occipito-temporal cortex, using fMRI adaptation with a particular interest in predictive mechanisms. Participants were presented with trials containing eight different images of a famous person, images of eight different famous persons or seven different images of a particular famous person followed by an identity change to violate potential expectation effects about person identity. We found an image-independent adaptation effect of identity for famous faces in the fusiform face area. However, in contrast to previous electrophysiological studies, using similar paradigms, no release of the adaptation effect was observed when identity-specific expectations were violated. Our results support recent multivariate pattern analysis studies, showing image-independent identity encoding in the core face-processing areas of the occipito-temporal cortex. These results are discussed in the frame of recent identity-processing models and predictive mechanisms.

Laparoscopic Colorectal Surgery Outcomes Improved After National Training Program (LAPCO) for Specialists in England.

OBJECTIVE: To examine the impact of The National Training Program for Lapco on the rate of laparoscopic surgery and clinical outcomes of cases performed by Lapco surgeons after completion of training. SUMMARY OF BACKGROUND DATA: Lapco provided competency-based supervised clinical training for specialist colorectal surgeons in England. METHODS: We compared the rate of laparoscopic surgery, mortality, and morbidity for colorectal cancer resections by Lapco delegates and non-Lapco surgeons in 3-year periods preceding and following Lapco using difference in differences analysis. The changes in the rate of post-Lapco laparoscopic surgery with the Lapco sign-off competency assessment and in-training global assessment scores were examined using risk-adjusted cumulative sum to determine their predictive clinical validity with predefined competent scores of 3 and 5 respectively. RESULTS: One hundred eight Lapco delegates performed 4586 elective colo-rectal resections pre-Lapco and 5115 post-Lapco while non-Lapco surgeons performed 72,930 matched cases. Lapco delegates had a 37.8% increase in laparoscopic surgery which was greater than non-Lapco surgeons by 20.9% [95% confidence interval (CI), 18.5-23.3, P < 0.001) with a relative decrease in 30-day mortality by -1.6% (95% CI, -3.4 to -0.2, P = 0.039) and 90-day mortality by -2.3% (95% CI, -4.3 to -0.4, P = 0.018). The change point of risk-adjusted cumulative sum was 3.12 for competency assessment tool and 4.74 for global assessment score whereas laparoscopic rate increased from 44% to 66% and 40% to 56%, respectively. CONCLUSIONS: Lapco increased the rate of laparoscopic colorectal cancer surgery and reduced mortality and morbidity in England. In-training competency assessment tools predicted clinical performance after training.

Machine learning-based investigation of the cancer protein secretory pathway.

Deregulation of the protein secretory pathway (PSP) is linked to many hallmarks of cancer, such as promoting tissue invasion and modulating cell-cell signaling. The collection of secreted proteins processed by the PSP, known as the secretome, is often studied due to its potential as a reservoir of tumor biomarkers. However, there has been less focus on the protein components of the secretory machinery itself. We therefore investigated the expression changes in secretory pathway components across many different cancer types. Specifically, we implemented a dual approach involving differential expression analysis and machine learning to identify PSP genes whose expression was associated with key tumor characteristics: mutation of p53, cancer status, and tumor stage. Eight different machine learning algorithms were included in the analysis to enable comparison between methods and to focus on signals that were robust to algorithm type. The machine learning approach was validated by identifying PSP genes known to be regulated by p53, and even outperformed the differential expression analysis approach. Among the different analysis methods and cancer types, the kinesin family members KIF20A and KIF23 were consistently among the top genes associated with malignant transformation or tumor stage. However, unlike most cancer types which exhibited elevated KIF20A expression that remained relatively constant across tumor stages, renal carcinomas displayed a more gradual increase that continued with increasing disease severity. Collectively, our study demonstrates the complementary nature of a combined differential expression and machine learning approach for analyzing gene expression data, and highlights key PSP components relevant to features of tumor pathophysiology that may constitute potential therapeutic targets.

Preservation of the rectum is possible in early rectal cancer with neoadjuvant radiotherapy, delay and local excision-a 12-year single-centre experience of the evolution of early rectal cancer treatment.

AIM: Treatment of early rectal cancer (ERC) is undergoing a revolution towards rectum preservation. Adjuvant and neoadjuvant therapy alongside local excision (LE) means that organ preservation is a real possibility for most patients and a viable alternative for frailer patients. This study presents our 12-year experience as a specialist regional ERC unit, evolving towards organ preservation. METHOD: Data were collected prospectively between 2006 and 2018 for all patients referred to the regional ERC multidisciplinary team with suspected or confirmed ERC. Patients considered suitable for LE, or those declining radical surgery, were offered LE or neoadjuvant short-course radiotherapy (SCRT), delay and LE with subsequent rescue surgery or contact brachytherapy for unfavourable histopathology. RESULTS: In all, 102 patients underwent LE. Ten patients were excluded (N = 92). 45 patients underwent LE directly and 47 patients received SCRT and LE. After SCRT and LE, a pathological complete response was achieved in 44.7%. This approach also resulted in a lower rate of lymphovascular invasion (22.2% vs. 6.4%), fewer distant recurrences (4.4% vs. 0%) and a better disease-specific mortality (11.1% vs. 0%) (P < 0.05). Although statistically insignificant, fewer patients required rescue surgery after SCRT (15.6% vs. 4.3%). CONCLUSION: Organ preservation with a good oncological outcome is better achieved by neoadjuvant radiotherapy, delay and LE. To achieve this, careful patient selection, thorough preoperative investigation, experienced surgical technique and a deep appreciation of tumour biology managed via a dedicated ERC network is paramount.

Investigating balance, gait, and physical function in people who have undergone thoracic surgery for a diagnosis of lung cancer: A mixed-methods study.

OBJECTIVES: Symptoms associated with lung cancer and thoracic surgery might increase fall risk. We aimed to investigate: 1) balance, gait and functional status in people post-thoracic surgery compared to healthy controls; 2) perceptions of balance, gait and functional status. METHODS: Recruitment targeted older adults (≥50 years) who had undergone thoracic surgery for a diagnosis of lung cancer in the previous 3 months, and healthy age-matched controls. Dynamic and static balance, gait velocity, knee-extension strength and physical activity levels were assessed using the BESTest, Kistler force plate, GAITRite system, Biodex System 3 and CHAMPS questionnaire, respectively. Two-part semi-structured interviews were conducted post-surgery. RESULTS: Individuals post-surgery (n = 15) had worse dynamic balance and gait, and lower levels of moderate/vigorous physical activity (MVPA) (all p<0.05) versus healthy controls (n = 15). Strength did not differ between groups (p > 0.05). No associations between BESTest and strength or physical activity existed post-surgery (p > 0.05). Three themes were identified: 1) Symptoms affect daily activities; 2) Functional assessments alter perceptions of balance ability and 3) Open to supervised rehabilitation. CONCLUSION: Balance, gait and MVPA are impaired post-thoracic surgery, yet balance was not viewed to be important in enabling activities of daily living. However, supervised rehabilitation was considered acceptable.

Prediction-error signals to violated expectations about person identity and head orientation are doubly-dissociated across dorsal and ventral visual stream regions.

Predictive coding theories of perception highlight the importance of constantly updated internal models of the world to predict future sensory inputs. Importantly, such theories suggest that prediction-error signalling should be specific to the violation of predictions concerning distinct attributes of the same stimulus. To interrogate this as yet untested prediction, we focused on two different aspects of face perception (identity and orientation) and investigated whether cortical regions which process particular stimulus attributes also signal prediction violations with respect to those same stimulus attributes. We employed a paradigm using sequential trajectories of images to create perceptual expectations about face orientation and identity, and then parametrically violated each attribute. Using MEG data, we identified double dissociations of expectancy violations in the dorsal and ventral visual streams, such that the right fusiform gyrus showed greater prediction-error signals to identity violations than to orientation violations, whereas the left angular gyrus showed the converse pattern of results. Our results suggest that perceptual prediction-error signalling is directly linked to regions associated with the processing of different stimulus properties.

Dose-dependent modulation of the visually evoked N1/N170 by perceptual surprise: a clear demonstration of prediction-error signalling.

Prediction-error checking processes play a key role in predictive coding models of perception. However, neural indices of such processes have yet to be unambiguously demonstrated. To date, experimental paradigms aiming to study such phenomena have relied upon the relative frequency of stimulus repeats and/or 'unexpected' events that are physically different from 'expected' events. These features of experimental design leave open alternative explanations for the observed effects. A definitive demonstration requires that presumed prediction error-related responses should show contextual dependency (rather than simply effects of frequency or repetition) and should not be attributable to low-level stimulus differences. Most importantly, prediction-error signals should show dose dependency with respect to the degree to which expectations are violated. Here, we exploit a novel experimental paradigm specifically designed to address these issues, using it to interrogate early latency event-related potentials (ERPs) to contextually expected and unexpected visual stimuli. In two electroencephalography (EEG) experiments, we demonstrate that an N1/N170 evoked potential is robustly modulated by unexpected perceptual events ('perceptual surprise') and shows dose-dependent sensitivity with respect to both the influence of prior information and the extent to which expectations are violated. This advances our understanding of perceptual predictions in the visual domain by clearly identifying these evoked potentials as an index of visual surprise.

Editorial Commentary: Return to Sport: An Ill-Defined Parameter.

Femoroacetabular impingement syndrome (FAIS) is a common cause of hip pain and dysfunction in athletes, which can impair their ability to perform and compete in sports. Hip arthroscopy has become a popular and successful treatment option for the management of FAIS and the return to sport (RTS) of athletes. The concept of RTS has evolved in the last years. Various different factors need to be considered when evaluating RTS after hip arthroscopy for FAIS, such as (1) the definition of RTS (return to participation, RTS, return to performance), (2) the sport type (high-impact vs low-impact) and sport level (professional vs recreational), and (3) the time to follow-up evaluation. In addition, return to high-impact sports, such as soccer, might not be the best recommendation for some patients undergoing hip arthroscopy for FAIS, as it may accelerate the degeneration of the hip joint. Future research should consider all these aspects of the RTS outcome after hip arthroscopy for FAIS. Valid RTS rates are of utmost importance to provide adequate expectations to patients and to guide decision-making of hip surgeons.

Decentralization and efficiency of subsidy targeting: Evidence from chiefs in rural Malawi.

Lower-income countries spend vast sums on subsidies. Beneficiaries are typically selected via either a proxy-means test (PMT) or through a decentralized identification process led by local leaders. A decentralized allocation may offer informational advantages, but may be prone to elite capture. We study this trade-off in the context of two large-scale subsidy programs in Malawi (for agricultural inputs and food) decentralized to traditional leaders ("chiefs") who are asked to target the needy. Using household panel data, we find that nepotism exists but has only limited mistargeting consequences. Importantly, we find that chiefs target households with higher returns to farm inputs, generating an allocation that is more productively efficient than what could be achieved through strict poverty-targeting. This could be welfare improving, since within-village redistribution is common. Productive efficiency targeting is concentrated in villages with above-median levels of redistribution.

Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors.

Novel therapies are undergoing clinical trials, for example, the Hsp90 inhibitor, XL888, in combination with BRAF inhibitors for the treatment of therapy-resistant melanomas. Unfortunately, our data show that this combination elicits a heterogeneous response in a panel of melanoma cell lines including PDX-derived models. We sought to understand the mechanisms underlying the differential responses and suggest a patient stratification strategy. Thermal proteome profiling (TPP) identified the protein targets of XL888 in a pair of sensitive and unresponsive cell lines. Unbiased proteomics and phosphoproteomics analyses identified CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors and its expression is regulated by the transcription factor MITF upon XL888 treatment. The CDK2 inhibitor, dinaciclib, attenuated resistance to both classes of inhibitors and combinations thereof. Notably, we found that MITF expression correlates with CDK2 upregulation in patients; thus, dinaciclib would warrant consideration for treatment of patients unresponsive to BRAF-MEK and/or Hsp90 inhibitors and/or harboring MITF amplification/overexpression.