Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictive Value of Diffusion, Glucose Metabolism Parameters of PET/MR in Patients With Head and Neck Squamous Cell Carcinoma Treated With Chemoradiotherapy

Purpose: This study aims to evaluate the predictive value of the pretreatment, metabolic, and diffusion parameters of a primary tumor assessed with PET/MR on patient clinical outcomes. Methods: Retrospective evaluation was performed using PET/MR image data sets acquired using the single tracer injection dual imaging of 68 histologically proven head and neck cancer patients 4 weeks before receiving definitive chemoradiotherapy (CRT). PET/MR was performed before the CRT and 12 weeks after the CRT for response evaluation. Image data (PET and MRI diffusion-weighted imaging [DWI]) was used to specify the maximum standard uptake value, the peak lean body mass corrected, SUVmax, the metabolic tumor volume, the total lesion glycolysis (SUVmax, SULpeak, MTV, and TLG), and the mean apparent diffusion coefficient (ADCmean) of the primary tumor. Based on the results of the therapeutic response evaluation, two patient subgroups were created: one with a viable tumor and another without. Metabolic and diffusion data, from the pretreatment PET/MR and the therapeutic response, were correlated using Spearman's correlation coefficient and Wilcoxon's test. Results: After completing the CRT, a viable residual tumor was detected in 36/68 (53%) cases, and 32/68 (47%) patients showed complete remission. However, no significant correlation was found between the pretreatment parameter, ADCmean (p = 0.88), and the therapeutic success. The PET parameters, SUVmax and SULpeak, MTV, and TLG (p = 0.032, p = 0.01, p < 0.0001, p = 0.0004) were statistically significantly different between the two patient subgroups. Conclusion: This study found that MRI-based (ADCmean) data from FDG PET/MR pretreatment could not be used to predict therapeutic response although the PET parameters SUVmax, SULpeak, MTV, and TLG proved to be more useful; thus, their inclusion in risk stratification may also be of additional value.
Stress Monitoring and Recent Advancements in Wearable Biosensors

The stress response allows the body to overcome obstacles and prepare for threats, but sustained levels of stress can damage one’s health. Stress has long been measured through physical tests and questionnaires that rely primarily on user-inputted data, which can be subjective and inaccurate. To quantify the amount of stress that the body is experiencing biologically, analytical detection of biomarkers associated with the stress response recently have been developed. Novel stress sensing devices focus on cortisol sweat sensing as a part of wearable, flexible devices. These devices promise a real-time, continuous collection of stress data that can be used in clinical diagnoses or for personal stress monitoring and mediation.
Association of Glomerular Complement C4c Deposition With the Progression of Diabetic Kidney Disease in Patients With Type 2 Diabetes

Objectives: As accumulating data supporting the potential role of the complement system in the pathogenesis of diabetic kidney disease (DKD), the present study aimed to explore the association of glomerular complement C4c deposition with the baseline clinicopathological characteristics and the prognosis of DKD in type 2 diabetes (T2DM) patients. Methods: A total of 79 T2DM patients with biopsy-proven DKD were enrolled. Clinicopathological features and renal outcomes were compared between groups divided by the glomerular C4c deposition patterns and median values of serum C4. Renal outcomes were defined by doubling of serum creatinine level or progression to end-stage renal disease (ESRD). A Cox proportional hazards model was employed to identify the risk factors associated with renal events. Results: Patients with glomerular C4c deposition had worse renal insufficiency than those without C4c deposits, along with higher 24-h urinary protein, triglyceride, but lower serum albumin and higher interstitial inflammation score. Besides, serum C4 levels positively correlated with urinary protein and serum C3 levels. During 21.85 ± 16.32 months of follow-up, Kaplan-Meier curve analysis showed significantly faster deterioration of renal function for patients with positive glomerular C4c deposition as well as higher levels of serum C4. More specifically, more than 50% of the patients with glomerular C4c had co-deposition of C3c or C1q, and patients with glomerular complement complex of C4c and one or two of C3/C1q deposition had more severe proteinuria and a higher rate of DKD progression than those with negative C4c deposits. The univariate Cox regression indicated that factors of combined serum and glomerular C4, urinary protein, serum creatinine, serum C3, combined glomerular C4c and IgM and interstitial inflammation were associated with an increased risk of DKD, but only glomerular C4c intensity (HR 1.584, 95% CI [1.001, 2.508], p = 0.0497), as well as baseline age and diabetic neuropathy, were independent risk factors for renal survival by the multivariate Cox analysis. Conclusions: Glomerular C4c deposition was associated with deteriorated renal function and outcomes in patients with T2DKD. Glomerular C4c deposition was an independent risk factor for DKD progression.
Physical Activity and Sedentary Behavior of Children in Afterschool Programs: An Accelerometer-Based Analysis in Full-Day and Half-Day Elementary Schools in Germany

Background: Regular physical activity (PA) and reduced sedentary behavior (SB) are positively related to children's health and considered as pillars of a healthy lifestyle. Full-day schools with their afterschool programs (ASPs) have an impact on children's daily PA and SB. Studies investigating PA and SB in ASPs, which compare PA and SB between the organizational forms full-day and half-day schools, are rare. The aim of this study is to describe elementary school children's PA and SB during ASPs and to compare the results to other time periods of the day, e.g., teaching hours and leisure time. Additionally, PA and SB of children in full-day and half-day schools are compared. Further, relevant factors influencing the achievement of the World Health Organization's (WHO's) PA guidelines for children, e.g., time spent in ASPs, are investigated. Methods: PA and SB of 332 German students (n = 198 full-day school children; n = 134 half-day school children) from 11 different elementary schools were measured via accelerometry for 5 consecutive days within one school week in 2017. PA and SB during ASPs and other times of the day were analyzed via one-way and factorial ANOVA, correlation, and logistic regression. Results: Children attending full-day schools show the highest percentage of moderate-to-vigorous PA (MVPA) (13.7%) and the lowest percentage of SB (49.5%) during ASPs, in comparison with teaching hours and leisure time. In the afternoon hours, full-day school children show 20 min less SB than half-day school children. Children spending more time in ASPs obtain significantly more SB (r = 0.23) and less MVPA (r = −0.15). Further, they less likely reach WHO's PA guidelines odds ratio (OR = 0.98). Conclusion: Peers and the choice as well as offer of extracurricular activities promote PA in ASPs. Media availability leads to higher SB in leisure time. ASPs help to be more active and less sedentary. Time spent in ASPs should be limited, so that full-day school children still have the possibility to join other PA offers in leisure time. ASP time should contain a certain minimum amount of MVPA in line with ASP guidelines.
Fasciola hepatica-Derived Molecules as Regulators of the Host Immune Response

Helminths (worms) are one of the most successful organisms in nature given their ability to infect millions of humans and animals worldwide. Their success can be attributed to their ability to modulate the host immune response for their own benefit by releasing excretory-secretory (ES) products. Accordingly, ES products have been lauded as a potential source of immunomodulators/biotherapeutics for an array of inflammatory diseases. However, there is a significant lack of knowledge regarding the specific interactions between these products and cells of the immune response. Many different compounds have been identified within the helminth “secretome,” including antioxidants, proteases, mucin-like peptides, as well as helminth defense molecules (HDMs), each with unique influences on the host inflammatory response. HDMs are a conserved group of proteins initially discovered in the secretome of the liver fluke, Fasciola hepatica. HDMs interact with cell membranes without cytotoxic effects and do not exert antimicrobial activity, suggesting that these peptides evolved specifically for immunomodulatory purposes. A peptide generated from the HDM sequence, termed FhHDM-1, has shown extensive anti-inflammatory abilities in clinically relevant models of diseases such as diabetes, multiple sclerosis, asthma, and acute lung injury, offering hope for the development of a new class of therapeutics. In this review, the current knowledge of host immunomodulation by a range of F. hepatica ES products, particularly FhHDM-1, will be discussed. Immune regulators, including HDMs, have been identified from other helminths and will also be outlined to broaden our understanding of the variety of effects these potent molecules exert on immune cells.
ONE Health Approach to Address Zoonotic Brucellosis: A Spatiotemporal Associations Study Between Animals and Humans

Background: Brucellosis is one of the most significant zoonosis over the world, threatening both veterinary and human public health. However, few studies were focused on nationwide animal brucellosis and made association with human brucellosis. Methodology and Principal Findings: We conducted a bilingual literature search on Brucella or brucellosis in China on the two largest databases (China National Knowledge Infrastructure and PubMed) and conducted a systematic review. A total of 1,383 Chinese and 81 English publications, published between 1958 and 2018 were identified. From them, 357 publications presenting 692 datasets were subjected to the meta-analysis. The overall prevalence rate is 1.70% (95% CI: 1.66–1.74), with a declining (until the late 1990s) and rising trend (starting the early 2000s). Interestingly, the animal with highest prevalence rate is canine (8.35%, 95% CI: 7.21–9.50), and lowest in cattle (1.22%, 95% CI: 1.17–1.28). The prevalence of Brucella in animals was unequally distributed among the 24 examined regions in China. Conclusions: Brucellosis is a reemerging disease for both humans and animals in China. The observed data suggests that dogs and yaks are the leading reservoirs for Brucella, and the provinces with highest prevalence rates in animals are Hubei, Sichuan, Inner Mongolia, Fujian, and Guizhou. Accordingly targeted intervention policy should be implemented to break the Brucella transmission chain between animals and humans in China.
GZ17-6.02 and Doxorubicin Interact to Kill Sarcoma Cells via Autophagy and Death Receptor Signaling

GZ17-6.02 (602) is presently under phase I clinical evaluation (NCT03775525). We defined the mechanisms by which it interacted with a standard of care therapeutic doxorubicin to kill sarcoma cells. Doxorubicin and 602 interacted to rapidly activate ATM and c-MET, inactivate mTOR, AKT, and p70 S6K, enhance the expression of Beclin1 and reduce the levels of K-RAS and N-RAS. This was followed later by the drugs interacting to reduce expression of MCL-1, BCL-XL, and HDAC6. Knock down of ATM prevented the drugs alone or in combination inactivating mTOR or activating ULK1. Knock down of c-MET significantly enhanced [doxorubicin + 602] lethality. Knock down of ATM and to a greater extent ULK1, Beclin1, or ATG5 significantly reduced killing by 602 alone or when combined with doxorubicin. Expression of an activated mTOR mutant suppressed killing, autophagosome formation and prevented autophagic flux. In the absence of Beclin1, knock down of CD95, or FADD, or over-expression of c-FLIP-s or BCL-XL abolished tumor cell killing. We conclude that 602 and doxorubicin interact to increase autophagosome formation and autophagic flux as well as causing elevated death receptor signaling resulting in mitochondrial dysfunction and tumor cell death.
Immune-Related Gene Expression and Cytokine Secretion Is Reduced Among African American Colon Cancer Patients

Background: Colorectal cancer is the third most deadly cancer among African Americans (AA). When compared to Caucasian Americans (CA), AA present with more advanced disease and lower survival rates. Here, we investigated if differences in tumor immunology could be contributive to disparities observed between these populations. Methods: We examined gene expression of tumor and non-tumor adjacent tissues from AA and CA by whole transcriptome sequencing, and generated scores for immune cell populations by NanoString. In addition, we utilized “The Cancer Genome Atlas” (TCGA) database from AA and CA as a validation cohort. Finally, we measured the secretion of cytokines characteristic of effector T helper cell (Th) subsets by ELISA using plasma from each AA and CA participant. Results: Colon tumors from AA patients showed significant fold-change increase in gene expression when compared to CA for FOXP3 (6.22 vs. 3.22), IL1B (103 vs. 11.4) and IL8 (220 vs. 28.9) (p < 0.05). In contrast, among CA we observed statistically higher gene expression of markers associated with antitumor activity such as GZMB (Granzyme B), IFNG and the immunotherapy targets PDL1 (CD274) and CTLA4 (p < 0.05). TCGA data validated our observed higher gene expression of GZMB and PDL1 in CA patients when compared to AA. Notably, our observations on immune cell populations show that AA tumors have significantly higher number of exhausted CD8+ cells (p < 0.01), mast cells (p < 0.02) and increased T regulatory cells when compared to CA. AA colon cancer patients differed from CA in cytokine production patterns in plasma (i.e., reduced IL-12). Conclusions: Our study demonstrates significant differences of the immunological profiles of colon tumors from AA compared to CA that suggest a deficiency of appropriate immune defense mechanisms in terms of gene expression, recruitment of immune cells and systemic secretion of cytokines. As such, these immune differences could be mitigated through population-specific therapeutic approaches.
Probing the Effective Treatment Thresholds for Alteplase in Acute Ischemic Stroke With Regression Discontinuity Designs

Randomized Controlled Trials (RCTs) are considered the gold standard for measuring the efficacy of medical interventions. However, RCTs are expensive, and use a limited population. Techniques to estimate the effects of stroke interventions from observational data that minimize confounding would be useful. We used regression discontinuity design (RDD), a technique well-established in economics, on the Get With The Guidelines-Stroke (GWTG-Stroke) data set. RDD, based on regression, measures the occurrence of a discontinuity in an outcome (e.g., odds of home discharge) as a function of an intervention (e.g., alteplase) that becomes significantly more likely when crossing the threshold of a continuous variable that determines that intervention (e.g., time from symptom onset, since alteplase is only given if symptom onset is less than e.g., 3 h). The technique assumes that patients near either side of a threshold (e.g., 2.99 and 3.01 h from symptom onset) are indistinguishable other than the use of the treatment. We compared outcomes of patients whose estimated onset to treatment time fell on either side of the treatment threshold for three cohorts of patients in the GWTG-Stroke data set. This data set spanned three different treatment thresholds for alteplase (3 h, 2003–2007, N = 1,869; 3 h, 2009–2016, N = 13,086, and 4.5 h, 2009–2016, N = 6,550). Patient demographic characteristics were overall similar across the treatment thresholds. We did not find evidence of a discontinuity in clinical outcome at any treatment threshold attributable to alteplase. Potential reasons for failing to find an effect include violation of some RDD assumptions in clinical care, large sample sizes required, or already-well-chosen treatment threshold.
Commentary: Borrelia miyamotoi: 43 Cases Diagnosed in France by Real-Time PCR in Patients With Persistent Polymorphic Signs and Symptoms

Ixodes ticks are the vector of the Borrelia burgdorferi sensu lato complex causing Lyme borreliosis (LB) and of Borrelia miyamotoi, a relapsing fever Borrelia species causing Borrelia miyamotoi disease (BMD). The latter disease entity was first described in 2011 (1), and its clinical symptoms in patients in Asia, Europe, and the USAmostly consist of a flu-like illness (2). The recent Frontiers in Medicine article by Michel Franck et al. claims to have detected Borrelia miyamotoi DNA in 43 out of 824 French patients with a complex of non-specific symptoms lasting at least 6 months (3). However, we have serious doubts about the author’s findings and conclusions. In this commentary, we describe evident shortcomings of this study and urge for a reconsideration of its interpretation and conclusions.
Formation and synaptic control of active transient working memory representations

Neural representations of working memory maintain information temporarily and make it accessible for processing. This is most feasible in active, spiking representations. State-of-the-art modeling frameworks, however, reproduce working memory representations that are either transient but non-active or active but non-transient. Here, we analyze a biologically motivated working memory model which shows that synaptic short-term plasticity and noise emerging from spiking networks can jointly produce a working memory representation that is both active and transient. We investigate the effect of a synaptic signaling mechanism whose dysregulation is related to schizophrenia and show how it controls transient working memory duration through presynaptic, astrocytic and postsynaptic elements. Our findings shed light on the computational capabilities of healthy working memory function and offer a possible mechanistic explanation for how molecular alterations observed in psychiatric diseases such as schizophrenia can lead to working memory impairments.
Homeotic Regulation of Olfactory Receptor Choice via NFI-dependent Heterochromatic Silencing and Genomic Compartmentalization

Expression of one out of >1000 olfactory receptor (OR) genes is stochastic but, yet, spatially organized in stereotypic anatomical segments, or “zones”, along the dorsoventral axis of the mouse olfactory epithelium. We discovered that zonal OR expression is specified by OR chromatin structure and genome architecture during olfactory neuron differentiation. Specifically, across every zone dorsally expressed ORs have higher levels of heterochromatic marks and long-range contacts than ORs expressed ventrally. However, OR heterochromatin levels and frequency of genomic contacts between ORs gradually increase towards ventral zones. Consequently, ORs from dorsal indexes accumulate high H3K9me3/H3K79me3 enrichment and become silenced in ventral zones, while ORs from ventral indexes lack activating long-range genomic interactions and, thus, cannot be chosen in dorsal segments. This process is regulated by NFIA, B, and X gradients along the dorsoventral axis, triple deletion of which causes homeotic transformations on zonal OR expression, heterochromatin formation, and genomic compartmentalization.
Automatic de novo atomic-accuracy structure determination for cryo-EM maps using deep learning

Motivation and Results Advances in microscopy instruments and image processing algorithms have led to an increasing number of cryo-EM maps. However, building accurate models for the EM maps at 3-5 Å resolution remains challenging and time-consuming. Here, we present a fully automatic de novo structure determination method using a deep learning-based framework, named as DeepMM, which automatically builds atomic-accuracy all-atom models from cryo-EM maps at near-atomic resolution. In our method, the main-chain and Cα positions as well as their amino acid and secondary structure types are predicted in the EM map using Densely Connected Convolutional Networks. DeepMM was extensively validated on 40 simulated maps at 5 Å resolution and 30 experimental maps at 2.6-4.8 Å resolution as well as an EMDB-wide data set of 2931 experimental maps at 2.6-4.9 Å resolution. DeepMM built correct models for >60% of the cases, and it outperformed existing state-of-the-art algorithms including RosettaES, MAINMAST, and Phenix. Availability http://huanglab.phys.hust.edu. cn/DeepMM/
Natural selection and the advantage of recombination

The ubiquity of sex and recombination in nature is widely viewed as enigmatic, despite an abundance of limited-scope explanations. Natural selection, it seems, should amplify well-matched combinations of genes. Recombination would break up these well-matched combinations and should thus be suppressed. We show, to the contrary, that on average: 1) natural selection amplifies poorly-matched gene combinations and 2) creates time-averaged negative associations in the process. Recombination breaks up these poorly-matched combinations, neutralizes the negative associations, and should thus be passively and universally favored.
Abundant proteins contribute strongly to noise in the growth rate of optimally growing bacteria

In bacterial cells, protein expression is a highly stochastic process. At the same time, physiological variables such as the cellular growth rate also fluctuate significantly. A common intuition is that, due to their relatively high noise amplitudes, proteins with a low mean expression level are the most important causes of these fluctuations on a larger, physiological scale. Noise in highly expressed proteins, whose stochastic fluctuations are relatively small, is often ignored. In this work, we challenge this intuition by developing a theory that predicts the contribution of a protein’s expression noise to the noise in the instantaneous, cellular growth rate. Using mathematical analysis, we decomposed the contribution of each protein into two factors: the noise amplitude of the protein, and the sensitivity of the growth rate to fluctuations in that protein’s concentration. Next, we incorporated evolution, which has shaped the mean abundances of growth-related proteins to optimise the growth rate, causing protein abundances, but also cellular sensitivities to be non-random. We show that in cells that grow optimally fast, the growth rate is most sensitive to fluctuations in highly abundant proteins. This causes such proteins to overall contribute strongly to the noise in the growth-rate, despite their low noise levels. The results are confirmed in a stochastic toy model of cellular growth.