Genome-scale clustered regularly interspaced short palindromic repeats screen identifies nucleotide metabolism as an actionable therapeutic vulnerability in diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is the most common malignancy that develops in patients with ataxia-telangiectasia, a cancer-predisposing inherited syndrome characterized by inactivating germline ATM mutations. ATM is also frequently mutated in sporadic DLBCL. To investigate lymphomagenic mechanisms and lymphoma-specific dependencies underlying defective ATM, we applied ribonucleic acid (RNA)-seq and genome-scale loss-offunction clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 screens to systematically interrogate B-cell lymphomas arising in a novel murine model (Atm-/-nu-/-) with constitutional Atm loss, thymic aplasia but residual T-cell populations. Atm-/-nu-/-lymphomas, which phenotypically resemble either activated B-cell-like or germinal center Bcell-like DLBCL, harbor a complex karyotype, and are characterized by MYC pathway activation. In Atm-/-nu-/-lymphomas, we discovered nucleotide biosynthesis as a MYCdependent cellular vulnerability that can be targeted through the synergistic nucleotidedepleting actions of mycophenolate mofetil (MMF) and the WEE1 inhibitor, adavosertib (AZD1775). The latter is mediated through a synthetically lethal interaction between RRM2 suppression and MYC dysregulation that results in replication stress overload in Atm-/-nu-/-lymphoma cells. Validation in cell line models of human DLBCL confirmed the broad applicability of nucleotide depletion as a therapeutic strategy for MYC-driven DLBCL independent of ATM mutation status. Our findings extend current understanding of lymphomagenic mechanisms underpinning ATM loss and highlight nucleotide metabolism as a targetable therapeutic vulnerability in MYC-driven DLBCL.

Fueling the success of transplantation through nutrition: recent insights into nutritional interventions, their interplay with gut microbiota and cellular mechanisms.

PURPOSE OF REVIEW: The role of nutrition in organ health including solid organ transplantation is broadly accepted, but robust data on nutritional regimens remains scarce calling for further investigation of specific dietary approaches at the different stages of organ transplantation. This review gives an update on the latest insights into nutritional interventions highlighting the potential of specific dietary regimens prior to transplantation aiming for organ protection and the interplay between dietary intake and gut microbiota. RECENT FINDINGS: Nutrition holds the potential to optimize patients' health prior to and after surgery, it may enhance patients' ability to cope with the procedure-associated stress and it may accelerate their recovery from surgery. Nutrition helps to reduce morbidity and mortality in addition to preserve graft function. In the case of living organ donation, dietary preconditioning strategies promise novel approaches to limit ischemic organ damage during transplantation and to identify the underlying molecular mechanisms of diet-induced organ protection. Functioning gut microbiota are required to limit systemic inflammation and to generate protective metabolites such as short-chain fatty acids or hydrogen sulfide. SUMMARY: Nutritional intervention is a promising therapeutic concept including the pre- and rehabilitation stage in order to improve the recipients' outcome after solid organ transplantation.

Effect of carbohydrate type in silages and concentrates on feed intake, enteric methane and milk yield from dairy cows.

Dietary carbohydrate manipulation can be used to reduce enteric CH4 emission, but there is a lack of studies on the interaction of different types of carbohydrates that can affect feed intake and ruminal fermentation. Understanding this interaction is necessary to make the most out of CH4 mitigation feeding strategies using different dietary carbohydrates. The aim of this study was to test the effect on enteric CH4 emission, feed intake and milk production response when cows were fed either grass-clover (GCS) or corn silage (CS) as the sole forage source (55% of dry matter, DM), in combination with either barley (BAR) or dried beet pulp (DBP) as a concentrate (21.5% of DM). Twenty-four (half first and half second parity) cows were used in a crossover design with 2 periods of 21 d each, receiving 2 of 4 diets obtained from a 2 × 2 factorial arrangement of the experimental diet. Feed intake, CH4 emission metrics and milk production were recorded at the end of the experimental periods. The diets had NDF concentrations between 258 and 340 g/kg of DM, and starch concentrations between 340 and 7.45 g/kg of DM (CS-BAR and GCS-DBP, respectively). The effects of silage and concentrate on dry matter intake (DMI) were additive, with the highest feed intake in cows fed COR-BAR, followed by cows fed COR-DBP, GCS-BAR, and GCS-DBP (21.2, 19.9, 19.1, and 18.3 kg/d). Energy corrected milk (ECM) yield was not affected by silage source in first parity cows, but it was higher for cows fed CS than cows fed GCS in second parity. The effects of silage and concentrate on CH4 production (g/d), yield (g/kg of DMI) and intensity (g/kg of ECM) were not additive as cows fed GCS had similar responses regardless of the concentrate used, but cows fed CS had lower CH4 production, yield and intensity, when fed BAR instead of DBP. The lower CH4 production, yield and intensity in cows fed CS-BAR compared with other diets could be partially explained by the nonlinear relationship between ruminal VFA and carbohydrates (NDF and starch) concentration reported in literature, however, we observed a linear relationship between acetate:propionate ratio and CH4 yield, suggesting possible other effects. The effects of silage and concentrate on the ruminal VFA were additive in first parity cows, but not in second parity cows. The interaction between dietary CHO type and parity might indicate an effect of feed intake or the energy balance of the cow. Feeding cows silage and concentrate both rich in starch can result in the lowest enteric CH4 emission.

Two prospective, multicenter studies for the identification of biomarker signatures for early detection of pulmonary hypertension (PH): The CIPHER and CIPHER-MRI studies.

A blood test identifying patients at increased risk of pulmonary hypertension (PH) could streamline the investigative pathway. The prospective, multicenter CIPHER study aimed to develop a microRNA-based signature for detecting PH in breathless patients and enrolled adults with a high suspicion of PH who had undergone right heart catheterization (RHC). The CIPHER-MRI study was added to assess the performance of this CIPHER signature in a population with low probability of having PH who underwent cardiac magnetic resonance imaging (cMRI) instead of RHC. The microRNA signature was developed using a penalized linear regression (LASSO) model. Data were modeled both with and without N-terminal pro-brain natriuretic peptide (NT-proBNP). Signature performance was assessed against predefined thresholds (lower 98.7% CI bound of ≥0.73 for sensitivity and ≥0.53 for specificity, based on a meta-analysis of echocardiographic data), using RHC as the true diagnosis. Overall, 926 CIPHER participants were screened and 888 were included in the analysis. Of 688 RHC-confirmed PH cases, approximately 40% were already receiving PH treatment. Fifty microRNA (from 311 investigated) were algorithmically selected to be included in the signature. Sensitivity [97.5% CI] of the signature was 0.85 [0.80-0.89] for microRNA-alone and 0.90 [0.86-0.93] for microRNA+NT-proBNP, and the corresponding specificities were 0.33 [0.24-0.44] and 0.28 [0.20-0.39]. Of 80 CIPHER-MRI participants with evaluable data, 7 were considered PH-positive by cMRI whereas 52 were considered PH-positive by the microRNA signature. Due to low specificity, the CIPHER miRNA-based signature for PH (either with or without NT-proBNP in model) did not meet the prespecified diagnostic threshold for the primary analysis.

Dual Input Stream Transformer for Vertical Drift Correction in Eye-tracking Reading Data.

We introduce a novel Dual Input Stream Transformer (DIST) for the challenging problem of assigning fixation points from eye-tracking data collected during passage reading to the line of text that the reader was actually focused on. This post-processing step is crucial for analysis of the reading data due to the presence of noise in the form of vertical drift. We evaluate DIST against eleven classical approaches on a comprehensive suite of nine diverse datasets. We demonstrate that combining multiple instances of the DIST model in an ensemble achieves high accuracy across all datasets. Further combining the DIST ensemble with the best classical approach yields an average accuracy of 98.17 %. Our approach presents a significant step towards addressing the bottleneck of manual line assignment in reading research. Through extensive analysis and ablation studies, we identify key factors that contribute to DIST's success, including the incorporation of line overlap features and the use of a second input stream. Via rigorous evaluation, we demonstrate that DIST is robust to various experimental setups, making it a safe first choice for practitioners in the field.

Improved predictions of total kidney volume growth rate in ADPKD using two-parameter least squares fitting.

Mayo Imaging Classification (MIC) for predicting future kidney growth in autosomal dominant polycystic kidney disease (ADPKD) patients is calculated from a single MRI/CT scan assuming exponential kidney volume growth and height-adjusted total kidney volume at birth to be 150 mL/m. However, when multiple scans are available, how this information should be combined to improve prediction accuracy is unclear. Herein, we studied ADPKD subjects ( n = 36 ) with 8+ years imaging follow-up (mean = 11 years) to establish ground truth kidney growth trajectory. MIC annual kidney growth rate predictions were compared to ground truth as well as 1- and 2-parameter least squares fitting. The annualized mean absolute error in MIC for predicting total kidney volume growth rate was 2.1 % ± 2 % compared to 1.1 % ± 1 % ( p = 0.002 ) for a 2-parameter fit to the same exponential growth curve used for MIC when 4 measurements were available or 1.4 % ± 1 % ( p = 0.01 ) with 3 measurements averaging together with MIC. On univariate analysis, male sex ( p = 0.05 ) and PKD2 mutation ( p = 0.04 ) were associated with poorer MIC performance. In ADPKD patients with 3 or more CT/MRI scans, 2-parameter least squares fitting predicted kidney volume growth rate better than MIC, especially in males and with PKD2 mutations where MIC was less accurate.

Effect of variability of mechanical properties on the predictive capabilities of vulnerable coronary plaques.

BACKGROUND AND OBJECTIVE: Coronary plaque rupture is a precipitating event responsible for two thirds of myocardial infarctions. Currently, the risk of plaque rupture is computed based on demographic, clinical, and image-based adverse features. However, using these features the absolute event rate per single higher-risk lesion remains low. This work studies the power of a novel framework based on biomechanical markers accounting for material uncertainty to stratify vulnerable and non-vulnerable coronary plaques. METHODS: Virtual histology intravascular ultrasounds from 55 patients, 29 affected by acute coronary syndrome and 26 affected by stable angina pectoris, were included in this study. Two-dimensional vessel cross-sections for finite element modeling (10 sections per plaque) incorporating plaque structure (medial tissue, loose matrix, lipid core and calcification) were reconstructed. A Montecarlo finite element analysis was performed on each section to account for material variability on three biomechanical markers: peak plaque structural stress at diastolic and systolic pressure, and peak plaque stress difference between systolic and diastolic pressures, together with the luminal pressure. Machine learning decision tree classifiers were trained on 75% of the dataset and tested on the remaining 25% with a combination of feature selection techniques. Performance against classification trees based on geometric markers (i.e., luminal, external elastic membrane and plaque areas) was also performed. RESULTS: Our results indicate that the plaque structural stress outperforms the classification capacity of the combined geometric markers only (0.82 vs 0.51 area under curve) when accounting for uncertainty in material parameters. Furthermore, the results suggest that the combination of the peak plaque structural stress at diastolic and systolic pressures with the maximum plaque structural stress difference between systolic and diastolic pressures together with the systolic pressure and the diastolic to systolic pressure gradient is a robust classifier for coronary plaques when the intrinsic variability in material parameters is considered (area under curve equal to [0.91-0.93]). CONCLUSION: In summary, our results emphasize that peak plaque structural stress in combination with the patient's luminal pressure is a potential classifier of plaque vulnerability as it independently considers stress in all directions and incorporates total geometric and compositional features of atherosclerotic plaques.

Circulating angiotensin-(1-7) is decreased in patients with isolated nocturnal hypertension.

Isolated nocturnal hypertension (INHT), defined as nighttime elevated blood pressure (BP) with normal daytime BP assessed by ambulatory BP monitoring, is associated with higher cardiovascular morbidity and mortality. We hypothesized that an alteration in the circulating renin-angiotensin system (RAS) contributes to INHT development. We examined circulating levels of angiotensin (Ang) (1-7) and Ang II and ACE2 activity in 26 patients that met the INHT criteria, out of 50 that were referred for BP evaluation (62% women, 45 ±â€Š16 years old). Those with INHT were older, had a higher BMI, lower circulating Ang-(1-7) (P = 0.002) and Ang II levels (P = 0.02) and no change in ACE2 activity compared to those normotensives. Nighttime DBP was significantly correlated with Ang-(1-7) and Ang II levels. Logistic regression showed significant association in Ang-(1-7) and Ang II levels with INHT. Our study reveals differences in circulating RAS in individuals with INHT.

Adaptive integration of history variables in constrained mixture models for organ-scale growth and remodeling.

In the last decades, many computational models have been developed to predict soft tissue growth and remodeling (G&R). The constrained mixture theory describes fundamental mechanobiological processes in soft tissue G&R and has been widely adopted in cardiovascular models of G&R. However, even after two decades of work, large organ-scale models are rare, mainly due to high computational costs (model evaluation and memory consumption), especially in long-range simulations. We propose two strategies to adaptively integrate history variables in constrained mixture models to enable large organ-scale simulations of G&R. Both strategies exploit that the influence of deposited tissue on the current mixture decreases over time through degradation. One strategy is independent of external loading, allowing the estimation of the computational resources ahead of the simulation. The other adapts the history snapshots based on the local mechanobiological environment so that the additional integration errors can be controlled and kept negligibly small, even in G&R scenarios with severe perturbations. We analyze the adaptively integrated constrained mixture model on a tissue patch for a parameter study and show the performance under different G&R scenarios. To confirm that adaptive strategies enable large organ-scale examples, we show simulations of different hypertension conditions with a real-world example of a biventricular heart discretized with a finite element mesh. In our example, adaptive integrations sped up simulations by a factor of three and reduced memory requirements to one-sixth. The reduction of the computational costs gets even more pronounced for simulations over longer periods. Adaptive integration of the history variables allows studying more finely resolved models and longer G&R periods while computational costs are drastically reduced and largely constant in time.

Crafting medical MCQs with generative AI: A how-to guide on leveraging ChatGPT.

As medical educators grapple with the consistent demand for high-quality assessments, the integration of artificial intelligence presents a novel solution. This how-to article delves into the mechanics of employing ChatGPT for generating Multiple Choice Questions (MCQs) within the medical curriculum. Focusing on the intricacies of prompt engineering, we elucidate the steps and considerations imperative for achieving targeted, high-fidelity results. The article presents varying outcomes based on different prompt structures, highlighting the AI's adaptability in producing questions of distinct complexities. While emphasizing the transformative potential of ChatGPT, we also spotlight challenges, including the AI's occasional "hallucination", underscoring the importance of rigorous review. This guide aims to furnish educators with the know-how to integrate AI into their assessment creation process, heralding a new era in medical education tools.

Encouraging medical students to become surgeons? Impact of psychological and surgical factors on career choice at medical school.

Aim: Training decisions are viewed as a problem by the majority of medical students.In the present study we compared sociodemographic and psychological characteristics of students who are interested in surgical training to those who preferred a non-surgical specialty. Furthermore, we examined whether students who wish to be trained as surgeons performed better than their non-surgical counterparts in a course designed to acquire skills in minimally invasive surgery. Method: From October 2020 to January 2021 we performed a cross-sectional survey among 116 medical students prior to their year of practical training at Christian-Albrechts University in Kiel. Based on their intended field of specialization, the students were divided into a non-surgical and a surgical group. Sociodemographic and psychological characteristics such as self-efficacy expectations, resilience and stress perception were evaluated and compared between groups. Simultaneously, we compared their surgical performance in two laparoscopic exercises and their self-assessment as surgeons. Statistical differences between the training groups were determined by the Mann-Whitney U test or Pearson's Chi square test. Results: Ninety-two students participated in the study, of whom 64.1% intended to train in a non-surgical specialty and 35.9% in a surgical specialty. Students who wished to be trained as surgeons had higher general self-efficacy expectations (p<0.001) and greater resilience (p=0.009). However, on comparison they had a lower stress level (p=0.047). The inter-group comparison of training results and self-assessment as surgeons revealed no unequivocal differences in surgical performance. Conclusion: Interest in surgical specialties is correlated, among other factors, with the strength of psychological skills such as general self-efficacy expectations, resilience and stress perception. Early attention to these psychological resources in academic training might assist medical students in future career choices.

City level water withdrawal and scarcity accounts of China.

In the context of China's freshwater crisis high-resolution data are critical for sustainable water management and economic growth. Yet there is a dearth of data on water withdrawal and scarcity regardless of whether total or subsector amount, for prefectural cities. In administrative and territorial scope, we accounted for water withdrawal of all 63 economic-socio-environmental sectors for all 343 prefectural cities in China, based on a general framework and 2015 data. Spatial and economic-sector resolution is improved compared with previous studies by partitioning general sectors into industrial and agricultural sub-sectors. Construction of these datasets was based on selection of 16 driving forces. We connected a size indicator with corresponding water-withdrawal efficiency. We further accounted for total blue-water withdrawal and quantitative water scarcity status. Then we compared different scopes and methods of official accounts and statistics from various water datasets. These disaggregated and complete data could be used in input-output models for municipal design and governmental planning to help gain in-depth insights into subsector water-saving priorities from local economic activities.

A mathematical model for the role of dopamine-D2 self-regulation in the production of ultradian rhythms.

Many self-motivated and goal-directed behaviours display highly flexible, approximately 4 hour ultradian (shorter than a day) oscillations. Despite lacking direct correspondence to physical cycles in the environment, these ultradian rhythms may be involved in optimizing functional interactions with the environment and reflect intrinsic neural dynamics. Current evidence supports a role of mesostriatal dopamine (DA) in the expression and propagation of ultradian rhythmicity, however, the biochemical processes underpinning these oscillations remain to be identified. Here, we use a mathematical model to investigate D2 autoreceptor-dependent DA self-regulation as the source of ultradian behavioural rhythms. DA concentration at the midbrain-striatal synapses is governed through a dual-negative feedback-loop structure, which naturally gives rise to rhythmicity. This model shows the propensity of striatal DA to produce an ultradian oscillation characterized by a flexible period that is highly sensitive to parameter variations. Circadian (approximately 24 hour) regulation consolidates the ultradian oscillations and alters their response to the phase-dependent, rapid-resetting effect of a transient excitatory stimulus. Within a circadian framework, the ultradian rhythm orchestrates behavioural activity and enhances responsiveness to an external stimulus. This suggests a role for the circadian-ultradian timekeeping hierarchy in governing organized behaviour and shaping daily experience through coordinating the motivation to engage in recurring, albeit not highly predictable events, such as social interactions.

Molecular neuroimaging in dominantly inherited versus sporadic early-onset Alzheimer's disease.

Approximately 5% of Alzheimer's disease patients develop symptoms before age 65 (early-onset Alzheimer's disease), with either sporadic (sporadic early-onset Alzheimer's disease) or dominantly inherited (dominantly inherited Alzheimer's disease) presentations. Both sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease are characterized by brain amyloid-ß accumulation, tau tangles, hypometabolism and neurodegeneration, but differences in topography and magnitude of these pathological changes are not fully elucidated. In this study, we directly compared patterns of amyloid-ß plaque deposition and glucose hypometabolism in sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease individuals. Our analysis included 134 symptomatic sporadic early-onset Alzheimer's disease amyloid-Positron Emission Tomography (PET)-positive cases from the University of California, San Francisco, Alzheimer's Disease Research Center (mean ± SD age 59.7 ± 5.6 years), 89 symptomatic dominantly inherited Alzheimer's disease cases (age 45.8 ± 9.3 years) and 102 cognitively unimpaired non-mutation carriers from the Dominantly Inherited Alzheimer Network study (age 44.9 ± 9.2). Each group underwent clinical and cognitive examinations, 11C-labelled Pittsburgh Compound B-PET and structural MRI. 18F-Fluorodeoxyglucose-PET was also available for most participants. Positron Emission Tomography scans from both studies were uniformly processed to obtain a standardized uptake value ratio (PIB50-70 cerebellar grey reference and FDG30-60 pons reference) images. Statistical analyses included pairwise global and voxelwise group comparisons and group-independent component analyses. Analyses were performed also adjusting for covariates including age, sex, Mini-Mental State Examination, apolipoprotein ε4 status and average composite cortical of standardized uptake value ratio. Compared with dominantly inherited Alzheimer's disease, sporadic early-onset Alzheimer's disease participants were older at age of onset (mean ± SD, 54.8 ± 8.2 versus 41.9 ± 8.2, Cohen's d = 1.91), with more years of education (16.4 ± 2.8 versus 13.5 ± 3.2, d = 1) and more likely to be apolipoprotein ε4 carriers (54.6% ε4 versus 28.1%, Cramer's V = 0.26), but similar Mini-Mental State Examination (20.6 ± 6.1 versus 21.2 ± 7.4, d = 0.08). Sporadic early-onset Alzheimer's disease had higher global cortical Pittsburgh Compound B-PET binding (mean ± SD standardized uptake value ratio, 1.92 ± 0.29 versus 1.58 ± 0.44, d = 0.96) and greater global cortical 18F-fluorodeoxyglucose-PET hypometabolism (mean ± SD standardized uptake value ratio, 1.32 ± 0.1 versus 1.39 ± 0.19, d = 0.48) compared with dominantly inherited Alzheimer's disease. Fully adjusted comparisons demonstrated relatively higher Pittsburgh Compound B-PET standardized uptake value ratio in the medial occipital, thalami, basal ganglia and medial/dorsal frontal regions in dominantly inherited Alzheimer's disease versus sporadic early-onset Alzheimer's disease. Sporadic early-onset Alzheimer's disease showed relatively greater 18F-fluorodeoxyglucose-PET hypometabolism in Alzheimer's disease signature temporoparietal regions and caudate nuclei, whereas dominantly inherited Alzheimer's disease showed relatively greater hypometabolism in frontal white matter and pericentral regions. Independent component analyses largely replicated these findings by highlighting common and unique Pittsburgh Compound B-PET and 18F-fluorodeoxyglucose-PET binding patterns. In summary, our findings suggest both common and distinct patterns of amyloid and glucose hypometabolism in sporadic and dominantly inherited early-onset Alzheimer's disease.

The Art of Local Tissue Rearrangements in Burn Reconstruction: Z-Plasty and More.

In recent decades, advances in surgical anatomy, burn pathophysiology, surgical techniques, and laser therapy have led to a paradigm shift in how we approach burn scars and contractures. Scar excision and replacement with uninjured tissue, which predominated burn scar treatment for much of the 20th century, is no longer appropriate in many patients. A scar's intrinsic ability to remodel can be induced by reducing tension on the scar using various techniques for local tissue rearrangement. Often in combination with laser therapy, local flaps can optimally camouflage a burn scar with adjacent normal tissue and restore a patient more closely to their preinjury condition.

Assessing Endoscopic Response in Locally Advanced Rectal Cancer Treated with Total Neoadjuvant Therapy: Development and Validation of a Highly Accurate Convolutional Neural Network.

BACKGROUND: Rectal tumors display varying degrees of response to total neoadjuvant therapy (TNT). We evaluated the performance of a convolutional neural network (CNN) in interpreting endoscopic images of either a non-complete response to TNT or local regrowth during watch-and-wait surveillance. METHODS: Endoscopic images from stage II/III rectal cancers treated with TNT from 2012 to 2020 at a single institution were retrospectively reviewed. Images were labelled as Tumor or No Tumor based on endoscopy timing (before, during, or after treatment) and the tumor's endoluminal response. A CNN was trained using ResNet-50 architecture. The area under the curve (AUC) was analyzed during training and for two test sets. The main test set included images of tumors treated with TNT. The other contained images of local regrowth. The model's performance was compared to sixteen surgeons and surgical trainees who evaluated 119 images for evidence of tumor. Fleiss' kappa was calculated by respondent experience level. RESULTS: A total of 2717 images from 288 patients were included; 1407 (51.8%) contained tumor. The AUC was 0.99, 0.98, and 0.92 for training, main test, and local regrowth test sets. The model performed on par with surgeons of all experience levels for the main test set. Interobserver agreement was good ( k = 0.71-0.81). All groups outperformed the model in identifying tumor from images of local regrowth. Interobserver agreement was fair to moderate ( k = 0.24-0.52). CONCLUSIONS: A highly accurate CNN matched the performance of colorectal surgeons in identifying a noncomplete response to TNT. However, the model demonstrated suboptimal accuracy when analyzing images of local regrowth.

Omega-3 fatty acids and major depression: a Mendelian randomization study.

Omega-3 fatty acids have been implicated in the aetiology of depressive disorders, though trials supplementing omega-3 to prevent major depressive disorder (MDD) have so far been unsuccessful. Whether this association is causal remains unclear. We used two sample Mendelian randomization (MR) to investigate causality. Genetic variants associated with circulating omega-3 and omega-6 fatty acids in UK Biobank (UKBB, n = 115,078) were selected as exposures. The Psychiatric Genomics Consortium (PGC) genome-wide association studies (GWAS) of MDD (n = 430,775; cases = 116,209; controls = 314,566) and recurrent depression (rMDD, n = 80,933; cases = 17,451; controls = 62,482), were used as outcomes. Multivariable MR (MVMR) models were used to account for biologically correlated lipids, such as high- and low-density cholesterol and triglycerides, and to explore the relative importance of longer-chain omega-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) using data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE, n = 8866). Genetic colocalization analyses were used to explore the presence of a shared underlying causal variant between traits. Genetically predicted total omega-3 fatty acids reduced the odds of MDD (ORIVW 0.96 per standard deviation (SD, i.e. 0.22 mmol/l) (95% CIs 0.93-0.98, p = 0.003)). The largest point estimates were observed for eicosapentaenoic acid (EPA), a long-chain omega-3 fatty acid (OREPA 0.92; 95% CI 0.88-0.96; p = 0.0002). The effect of omega-3 fatty acids was robust to MVMR models accounting for biologically correlated lipids. 'Leave-one-out' analyses highlighted the FADS gene cluster as a key driver of the effect. Colocalization analyses suggested a shared causal variant using the primary outcome sample, but genomic confounding could not be fully excluded. This study supports a role for omega-3 fatty acids, particularly EPA, in the aetiology of depression, although pleiotropic mechanisms cannot be ruled out. The findings support guidelines highlighting the importance of EPA dose and ratio for MDD and question whether targeted interventions may be superior to universal prevention trials, as modest effect sizes will limit statistical power.

Keratinocytes Present Staphylococcus aureus Enterotoxins and Promote Malignant and Nonmalignant T Cell Proliferation in Cutaneous T-Cell Lymphoma.

Cutaneous T-cell lymphoma is characterized by malignant T cells proliferating in a unique tumor microenvironment dominated by keratinocytes (KCs). Skin colonization and infection by Staphylococcus aureus are a common cause of morbidity and are suspected of fueling disease activity. In this study, we show that expression of HLA-DRs, high-affinity receptors for staphylococcal enterotoxins (SEs), by KCs correlates with IFN-γ expression in the tumor microenvironment. Importantly, IFN-γ induces HLA-DR, SE binding, and SE presentation by KCs to malignant T cells from patients with Sézary syndrome and malignant and nonmalignant T-cell lines derived from patients with Sézary syndrome and mycosis fungoides. Likewise, preincubation of KCs with supernatant from patient-derived SE-producing S aureus triggers proliferation in malignant T cells and cytokine release (including IL-2), when cultured with nonmalignant T cells. This is inhibited by pretreatment with engineered bacteriophage S aureus-specific endolysins. Furthermore, alteration in the HLA-DR-binding sites of SE type A and small interfering RNA-mediated knockdown of Jak3 and IL-2Rγ block induction of malignant T-cell proliferation. In conclusion, we show that upon exposure to patient-derived S aureus and SE, KCs stimulate IL-2Rγ/Jak3-dependent proliferation of malignant and nonmalignant T cells in an environment with nonmalignant T cells. These findings suggest that KCs in the tumor microenvironment play a key role in S aureus-mediated disease activity in cutaneous T-cell lymphoma.

Nasal filter reveal exposure risks of inhalable particulates and heavy metals in urban women.

Urban populations, especially women, are vunerable to exposure to airborne pollution, particularly inhalable particulates (PM10). Thus, more accurate measurement of PM10 levels and evaluating their health effects is critical for guiding policy to improve human health. Previous studies obtained personal PM10 with time-weighted average by air filter-based sampling (AFS), which ignores individual differences and behavioral patterns. Here, we used nasal filters instead of AFS to obtain actual inhaled PM10 under short-term exposure for urban dwelling women during a severe haze event in Beijing in 2016. The levels of six heavy metals such as As, Cd, Ni, Cr, Pb, and Co in PM10 were investigated, and carcinogenic and non-carcinogenic risks evaluated based on an adjusted US EPA health risk assessment model. The health endpoints for urban dwelling women were further assessed through an exposure-reponse model. We found that the hourly inhaled dose of PM10 obtained through the nasal filter was about 2.5-17.6 times that obtained by AFS, which also resulted in 4.41-11.30 times more morbidity than estimated by AFS (p < 0.05). Proximity to traffic emissions resulted in greater exposure to particulate matter (>18.8 µg/kg·h) and heavy metals (>2.2 ng/kg·h), and these populations are therefore at greatest risk of developing non-cancer (HI = 4.16) and cancer (Rt = 7.8 × 10-3) related morbities.