bluuebunny/crossref_metadata_2025 huggingface dataset:
Comprehensive analysis of NT5DC family prognostic and immune significance in breast cancer
Authors: Jia Yiwei , Li Jia , Wu Huizi , Wang Weiwei , Sun Shiyu , Feng Cong , Liu Xuan , Li Chaofan , Zhang Yu , Cai Yifan , Wei Xinyu , Yao Peizhuo , Liu Xuanyu , Zhang Shuqun , Wu Fei
Published: February 2023

Among the most common malignancies, breast cancer has a high incidence and mortality rate. NT5DC family is a highly well-conserved 5′-nucleotidase. Previous studies showed that the progression of tumors was associated with some NT5DC family members. However, there are no studies about the comprehensive analysis such as expression, prognosis, and immune properties of NT5DC family in breast cancer. Based on the data from The Cancer Genome Atlas database, we used UALCAN, Tumor Immune Estimation Resource, Breast cancer gene-expression miner (Bc-GenExMiner), Kaplan–Meier Plotter, TISIDB, cBioPortal, GeneMANIA, Search Tool for the Retrieval of Interacting Genes, Metascape, Tumor Immune Single-cell Hub, The Database for Annotation, Visualization and Integrated Discovery, and Gene Set Cancer Analysis databases to explore expression, prognostic and diagnostic value, genetic alterations, biological function, immune value and drug sensitivity of NT5DC family in breast cancer patients. There was a downregulation of NT5C2, NT5DC1, and NT5DC3 in breast cancer compared to normal tissues, and NT5DC2 instead. All NT5DC family members were associated with the clinicopathological parameters of breast cancer patients. Survival and ROC analysis revealed that NT5DC family genes were related to the prognosis and diagnosis of breast cancer. NT5DC family were mainly involved in nucleotide metabolism. Moreover, NT5DC family were significantly associated with tumor immune microenvironment, diverse immune cells, and immune checkpoints in breast cancer. This research showed that NT5DC family might be novel prognostic biomarkers and immunotherapeutic targets of breast cancer.
Positive Correlation Between 18F-FDG Uptake and Tumor-Proliferating Antigen Ki-67 Expression in Adrenocortical Carcinomas
Authors: Libé Rossella , Pais Aurore , Violon Florian , Guignat Laurence , Bonnet Fideline , Huillard Olivier , Assié Guillaume , Gaillard Martin , Dousset Bertrand , Gaujoux Sébastien , Barat Maxime , Dohan Anthony , Sibony Mathilde , Bertherat Jérôme , Cottereau Anne Segolene , Tenenbaum Florence , Coste Joël , Groussin Lionel
Published: February 2023

Purpose of the Report

Adrenocortical carcinoma (ACC) is an extremely rare endocrine malignancy, which cannot always be diagnosed during conventional radiology and hormonal investigations. 18F-FDG PET could help predict malignancy, but more data are necessary to support future guidelines.

Methods

A cohort of 63 patients with histologically proven ACC (n = 55) or metastatic ACC with steroid oversecretion (n = 8) was assembled. All patients underwent an 18F-FDG PET, and the SUVmax and the adrenal-to-liver SUVmax ratio were calculated. The 18F-FDG PET parameters were compared with clinical, pathological, and outcome data.

Results

Fifty-six of 63 patients (89%) had an ACC with an adrenal-to-liver SUVmax ratio >1.45, which was a previously defined cutoff value to predict malignancy with 100% sensitivity. Seven ACCs (11%) had a lower uptake (adrenal-to-liver SUVmax <1.45), most of them with a proliferation marker Ki-67 expression level <10%. A positive correlation between 18F-FDG PET parameters (SUVmax and adrenal-to-liver SUVmax ratio) and tumor size, ENSAT (European Network for the Study of Adrenal Tumors) staging, total Weiss score, and the Ki-67 was found. The strong correlation between SUVmax and Ki-67 (r = 0.47, P = 0.0009) suggests a relationship between 18F-FDG uptake levels and tumor proliferation. No statistically significant associations between outcome parameters (progression-free or overall survival) and 18F-FDG PET parameters were found.

Conclusions

This large cohort study shows that most cases of ACC demonstrate high 18F-FDG uptake. However, the positive correlation observed between SUVmax and Ki-67 expression levels seems to explain the possibility of identifying some ACC with a low or inexistent 18F-FDG uptake. These findings have practical implications for the management of patients with an adrenal mass.
Meta-analysis of insomnia, suicide, and psychopathology in schizophrenia
Authors: Miller Brian J. , McCall William V.
Published: February 2023

Purpose of review

Insomnia is common in schizophrenia. Insomnia has been associated with suicidal ideation and behavior, as well as greater severity of psychopathology, in schizophrenia. This review performs a meta-analysis of associations between insomnia, suicide, and psychopathology in patients with schizophrenia.

Recent findings

We searched major electronic databases from inception until November 2022 for studies of insomnia, suicide, and psychopathology in patients with schizophrenia. Random effects meta-analysis calculating odds ratios (ORs, for suicide) and effect sizes (ESs, for psychopathology) and 95% confidence intervals (CIs) were performed. Ten studies met the inclusion criteria, comprising 3428 patients with schizophrenia. Insomnia was associated with a significant increased odds of suicidal ideation (OR = 1.84, 95% CI 1.28–2.65, P < 0.01) and suicide attempt or death (OR = 5.83, 95% CI 1.61–2.96, P < 0.01). Insomnia was also associated with total (ES = 0.16, 95% CI 0.09–0.23, P < 0.01), positive (ES = 0.14, 95% CI 0.08–0.20, P = 0.02), and general (ES = 0.17, 95% CI 0.08–0.27, P < 0.01) psychopathology. In meta-regression analyses, BMI was negatively associated with suicidal ideation. Otherwise, age, sex, and study year were all unrelated to the associations.

Insomnia is associated with suicide and psychopathology in schizophrenia. Formal assessment and treatment of insomnia appears relevant to the clinical care of schizophrenia.
Biofilm thickness controls the relative importance of stochastic and deterministic processes in microbial community assembly in moving bed biofilm reactors
Authors: Fowler S. Jane , Torresi Elena , Dechesne Arnaud , Smets Barth F.
Published: February 2023

Deterministic and stochastic processes are believed to play a combined role in microbial community assembly, though little is known about the factors determining their relative importance. We investigated the effect of biofilm thickness on community assembly in nitrifying moving bed biofilm reactors using biofilm carriers where maximum biofilm thickness is controlled. We examined the contribution of stochastic and deterministic processes to biofilm assembly in a steady state system using neutral community modelling and community diversity analysis with a null-modelling approach. Our results indicate that the formation of biofilms results in habitat filtration, causing selection for phylogenetically closely related community members, resulting in a substantial enrichment of
Nitrospira
spp. in the biofilm communities. Stochastic assembly processes were more prevalent in biofilms of 200 µm and thicker, while stronger selection in thinner (50 µm) biofilms could be driven by hydrodynamic and shear forces at the biofilm surface. Thicker biofilms exhibited greater phylogenetic beta-diversity, which may be driven by a variable selection regime caused by variation in environmental conditions between replicate carrier communities, or by drift combined with low migration rates resulting in stochastic historical contingency during community establishment. Our results indicate that assembly processes vary with biofilm thickness, contributing to our understanding of biofilm ecology and potentially paving the way towards strategies for microbial community management in biofilm systems.
The media composition as a crucial element in high-throughput metabolic network reconstruction
Authors: Borer Benedict , Magnúsdóttir Stefanía
Published: February 2023

In recent years, metagenome-assembled genomes (MAGs) have provided glimpses into the intra- and interspecies genetic diversity and interactions that form the bases of complex microbial communities. High-throughput reconstruction of genome-scale metabolic networks (GEMs) from MAGs is a promising avenue to disentangle the myriad trophic interactions stabilizing these communities. However, high-throughput reconstruction of GEMs relies on accurate gap filling of metabolic pathways using automated algorithms. Here, we systematically explore how the composition of the media (specification of the available nutrients and metabolites) during gap filling influences the resulting GEMs concerning predicted auxotrophies for fully sequenced model organisms and environmental isolates. We expand this analysis by using 106 MAGs from the same species with differing quality. We find that although the completeness of MAGs influences the fraction of gap-filled reactions, the composition of the media plays the dominant role in the accurate prediction of auxotrophies that form the basis of myriad community interactions. We propose that constraining the media composition for gap filling through both experimental approaches and computational approaches will increase the reliability of high-throughput reconstruction of genome-scale metabolic models from MAGs and paves the way for culture independent prediction of trophic interactions in complex microbial communities.
Mycobacterium tuberculosis transcriptome in intraocular tuberculosis
Authors: Kaur Kamaljit , Laal Suman , Ryndak Michelle B.
Published: February 2023

Introduction. Intraocular tuberculosis (IOTB) is a significant cause of visual morbidity in tuberculosis (TB)-endemic countries. Although

Mycobacterium tuberculosis

(M. tb) has been detected in both the retinal pigment epithelial (RPE) cells and in the intraocular fluid (IOF) in some cases, IOTB is paucibacillary in the vast majority of patients. As a result, M. tb pathogenesis in the ocular compartment is poorly defined.

Hypothesis. The transcriptional profile of M. tb in the ocular compartment will differ from those of M. tb in environments that represent earlier stages of infection.

Aim. Our aim is to shed light on the pathogenesis of M. tb in a clinically relevant but challenging environment to study.

Methodology. Whole-genome microarray analysis was performed on M. tb grown in an IOF model (artificial IOF; AIOF) over 6 days against reference log phase bacteria grown in 7H9. Results were compared to published M. tb transcriptomes in other physiologically relevant environments, e.g. RPE cell line.

Results.
M. tb replicates slowly in AIOF. Genes involved in active replication and aerobic respiration as well as lipid metabolism were either downregulated or not differentially expressed. Yet, M. tb in AIOF downregulated genes of the DosR regulon, indicating the suppression of dormancy, similar to M. tb in RPE cells. This transcriptional profile is distinct from the active and virulent transcriptomes of M. tb in alveolar epithelial cells and blood.

Conclusion.
M. tb likely acquires a non-invasive and quiescent phenotype, between active infection and dormancy, upon reaching an extrapulmonary niche, i.e. the ocular environment.
Oral fluid-based lateral flow point-of-care assays for pertussis serology
Authors: Knuutila Aapo , Duncan John , Li Fu , Eletu Seyi , Litt David , Fry Norman , He Qiushui
Published: February 2023

Introduction. Current serological diagnosis of pertussis is usually performed by ELISA, which is typically performed in larger diagnostic or reference laboratories, requires trained staff, and due to sample batching may have longer turnaround times.

Hypothesis and Aim. A rapid point-of-care (POC) assay for pertussis serology would aid in both the diagnosis and surveillance of the disease.

Methodology. A quantitative lateral flow (LF)-based immunoassay with fluorescent Eu-nanoparticle reporters was developed for the detection of anti-pertussis toxin (PT) and adenylate cyclase toxin (ACT) antibodies from oral fluid samples (N=100), from suspected pertussis cases with respiratory symptoms.

Results. LF assay results were compared to those obtained with anti-PT IgG oral fluid ELISA. For an ELISA cut-off value of 50 arbitrary units, the overall agreement between the assays was 91/100 (91 %), the sensitivity was 63/70 (90 %) and the specificity was 28/30 (93 %). No ACT-specific antibodies were detected from oral fluid samples; however, the signal readout positively correlated to those patients with high anti-PT IgG antibodies.

Conclusion. The developed LF assay was a specific, sensitive and rapid test for serological diagnosis of pertussis with anti-PT antibodies and is a suitable POC test using oral fluid samples.
Association of Coronary Stenosis with Cerebral Small Vessel Diseases in Neurologically Asymptomatic Adults
Authors: Min Kyungha , Yun Jae-Moon , Hwang Seo Eun , Nam Ki-Woong , Jeong Han-Yeong , Kwon Hyung-Min , Park Jin-Ho
Published: February 2023

Background

The high prevalence of coronary stenosis in patients with stroke is well established. However, the association between coronary stenosis and cerebral small vessel diseases (cSVD) in asymptomatic populations remains unclear.

Methods

As a cross-sectional study, we evaluated South Korean adults who underwent a health checkup including brain magnetic resonance imaging and coronary computed tomography angiography between January 2010 and December 2013. The degree of coronary stenosis was classified into three groups: no stenosis (0%), non-significant stenosis (1–49%), and significant stenosis (≥50%). cSVD includes silent lacunar infarction (SLI), cerebral microbleeds (CMB), and white matter hyperintensity (WMH). We used binary logistic regression analyses for SLI and CMB, and linear regression analysis for WMH.

Results

A total of 1,571 participants were evaluated. The prevalence of non-significant and significant coronary stenosis was 369 (23.5%) and 95 (6.1%), respectively. The prevalence of SLI and CMB was 112 (7.1%) and 66 (4.2%), respectively. The mean WMH volume was 2.6 ± 6.1 mL. SLI was significantly associated with both non-significant (adjusted odds ratio [aOR] = 1.94;p= 0.004) and significant coronary stenosis (aOR = 2.37;p= 0.011), even showing dose-response relationship (pfor trend = 0.012). For WMH, only significant coronary stenosis was associated with WMH (β = 0.27;p= 0.013) and had a dose–response relationship (pfor trend = 0.012).

Conclusions

The presence and severity of coronary stenosis were significantly associated with SLI and WMH. Physicians who detects any of coronary stenosis or cSVD should pay attention to the possible coexistence of the other disease.
A Pooled Electronic Consultation Program to Improve Access to Genetics Specialists
Authors: Folkerts Emma K. , Pelletier Renée C. , Chung Daniel C. , Goldstein Susan A. , Micalizzi Douglas S. , Shannon Kristen M. , Sweetser David A. , Wong Eugene K. , Rehm Heidi L. , Hull Leland E.
Published: February 2023

Innovative service delivery models are needed to increase access to genetics specialists. Electronic consultation (e-Consult) programs can connect clinicians with specialists. At Massachusetts General Hospital, an e-Consult service was created to address genomics-related questions. In its first year, the e-Consult service triaged 153 requests and completed 122 in an average of 3.2 days. Of the 95 e-Consults with actionable recommendations, there was documentation that most ordering clinicians followed through (82%). A variety of providers used the service, although the majority (77%) were generalists. E-Consult models should be considered as one way to increase access to genetics care.
Oncogenic drivers dictate immune control of acute myeloid leukemia
Authors: Austin Rebecca J. , Straube Jasmin , Halder Rohit , Janardhanan Yashaswini , Bruedigam Claudia , Witkowski Matthew , Cooper Leanne , Porter Amy , Braun Matthias , Souza-Fonseca-Guimaraes Fernando , Minnie Simone A , Cooper Emily , Jacquelin Sebastien , Song Axia , Bald Tobias , Nakamura Kyohei , Hill Geoffrey R. , Aifantis Iannis , Lane Steven W. , Bywater Megan J.
Published: February 2023

Acute myeloid leukemia (AML) is a genetically heterogeneous, aggressive hematological malignancy induced by distinct oncogenic driver mutations. The effect of specific AML oncogenes on immune activation or suppression has not been investigated. Here, we examine immune responses in genetically distinct models of AML and demonstrate that specific AML oncogenes dictate immunogenicity, the quality of immune response and immune escape through immunoediting. Specifically, expression of NrasG12Dalone is sufficient to drive a potent anti-leukemia response through increased MHC Class II expression that can be overcome with increased expression of Myc. These data have important implications for the design and implementation of personalized immunotherapies for patients with AML.

Statement of Significance

The endogenous immune response against acute myeloid leukemia (AML) is determined by leukemia-specific oncogenic driver mutations. Mutant Nras drives immunological selection of AML.
Pharmacodynamic model of PARP1 inhibition and global sensitivity analyses can lead to cancer biomarker discovery
Authors: Mertins Susan D. , Isenberg Natalie M. , Reyes Kristofer-Roy , Yoon Byung-Jun , Urban Nathan , Jogalekar Manasi P. , Diolaiti Morgan E. , Weil M. Ryan , Stahlberg Eric A.
Published: February 2023

Pharmacodynamic models provide inroads to understanding key mechanisms of action and may significantly improve patient outcomes in cancer with improved ability to determine therapeutic benefit. Additionally, these models may also lead to insights into potential biomarkers that can be utilized for prediction in prognosis and therapeutic decisions. As an example of this potential, here we present an advanced computational Ordinary Differential Equation (ODE) model of PARP1 signalling and downstream effects due to its inhibition. The model has been validated experimentally and further evaluated through a global sensitivity analysis. The sensitivity analysis uncovered two model parameters related to protein synthesis and degradation rates that were also found to contribute the most variability to the therapeutic prediction. Because this variability may define cancer patient subpopulations, we interrogated genomic, transcriptomic, and clinical databases, to uncover a biomarker that may correspond to patient outcomes in the model. In particular, GSPT2, a GTPase with translation function, was discovered and if mutations serve to alter catalytic activity, its presence may explain the variability in the model’s parameters. This work offers an analysis of ODE models, inclusive of model development, sensitivity analysis, and ensuing experimental data analysis, and demonstrates the utility of this methodology in uncovering biomarkers in cancer.

Author summary

Because biochemical reaction networks are complex, dynamic, and typically provide output that results from non-linear interactions, mathematical models of such offer insight into cell function. In the clinic, models including drug action further their usefulness in that they may predict therapeutic outcome and other useful markers such as those for prognosis. In this study, we report a model of drug action that targets a critical protein, that when inhibited, promotes tumor cell death and documented remissions. Because all patients do not respond to the described treatment, a means to find cancer patient subpopulations that might benefit continues to be a challenge. Therefore, we analyzed the pharmacodynamic model by defining the parameters of the greatest variability and interrogated genomic, transcriptomic, and clinical cohort databases with this information and discovered a novel biomarker associated with prognosis in some ovarian and uterine cancer patients and separately, associated with the potential to respond to treatment.
Reelin plasma levels predict cognitive decline in Alcohol Use Disorder: peak levels in patients expressing plasma APOE4 protein
Authors: Escudero Berta , Moya Marta , López-Valencia Leticia , Arias Francisco , Orio Laura
Published: February 2023

Background

Human apolipoprotein (APO)-E4 has been related to neuropsychiatric disorders such as Alzheimer’s disease and cognitive decline. Reelin and Clusterin share the VLDLR and ApoER2 receptors with APOE4. Here we checked the role of these components in Alcohol Use Disorder (AUD)-induced cognitive decline.

Methods

This is a cross-sectional study with AUD-diagnosed patients (DSM-5) (n=24) recruited from an outpatient ‘Alcohol Programme’ and matched controls (n=34). Participants were assessed by the validated ‘Test of Detection of Cognitive Impairment in Alcoholism’ (TEDCA). APOE4 presence in plasma (distinguishing APOE4 carriers and no carriers subjects) and its levels were performed by ‘e4Quant’ technique. The rest of biological markers were tested by Enzyme-Linked Immunosorbent Assay kits.

Results

Plasma APOE4 isoform was present in 37.5% and 58.8% of patients and controls, respectively. Quantification analyses revealed that APOE4 reached similar plasma levels in carriers independently if they were AUD subjects or controls. Circulant plasma APOE4 had a negative effect on AUD’s cognition, specifically affecting Memory/Learning (p<0.01, η2=0.15). Plasma Clusterin and Reelin increased in patients but, interestingly, Reelin plasma levels peaked in patients expressing APOE4 (p<0.05, η2=0.09), who showed reduced VLDL and ApoER2 expression in peripheral blood mononuclear cells (PBMCs). Reelin was a good predictor of cognitive loss in patients, accounting for the 42.3% and 54.0% of general intelligence and executive function impairments, respectively.

Conclusions

Reelin plasma levels are increased in AUD patients who express the APOE4 isoform, predicting cognitive deterioration to a great extent. Remarkably, plasma Reelin helps to differentiate between AUD patients with and without cognitive decline.

Significance Statement

Finding biological markers that predict a worse evolution in neuropsychiatric disorders may help to assist vulnerable patients appropriately. In this sense, in this study we found a biological marker, Reelin, which is elevated in patients with diagnosis of alcohol use disorder (AUD) that underwent an outpatient treatment. Interestingly, Reelin plasma levels were elevated in patients that also express APOE4, an aberrant protein present only in a small percentage of the population which is related to neuroinflammation and cognitive impairment (i.e. it is involved in Alzheimer’s disease). We observed that Reelin plasma levels negatively correlate with cognitive scores, being Reelin a good predictor of cognitive impairment in patients. These results may have implications for the follow-up of AUD patients in outpatient treatment.
Deep learning and likelihood approaches for viral phylogeography converge on the same answers whether the inference model is right or wrong
Authors: Thompson Ammon , Liebeskind Benjamin , Scully Erik J. , Landis Michael
Published: February 2023

Analysis of phylogenetic trees has become an essential tool in epidemiology. Likelihood-based methods fit models to phylogenies to draw inferences about the phylodynamics and history of viral transmission. However, these methods are computationally expensive, which limits the complexity and realism of phylodynamic models and makes them ill-suited for informing policy decisions in real-time during rapidly developing outbreaks. Likelihood-free methods using deep learning are pushing the boundaries of inference beyond these constraints. In this paper, we extend, compare and contrast a recently developed deep learning method for likelihood-free inference from trees. We trained multiple deep neural networks using phylogenies from simulated outbreaks that spread among five locations and found they achieve close to the same levels of accuracy as Bayesian inference under the true simulation model. We compared robustness to model misspecification of a trained neural network to that of a Bayesian method. We found that both models had comparable performance, converging on similar biases. We also implemented a method of uncertainty quantification called conformalized quantile regression which we demonstrate has similar patterns of sensitivity to model misspecification as Bayesian highest posterior intervals (HPI) and greatly overlap with HPIs, but have lower precision (more conservative). Finally, we trained and tested a neural network against phylogeographic data from a recent study of the SARS-Cov-2 pandemic in Europe and obtained similar estimates of region-specific epidemiological parameters and the location of the common ancestor in Europe. Along with being as accurate and robust as likelihood-based methods, our trained neural networks are on average over 3 orders of magnitude faster. Our results support the notion that neural networks can be trained with simulated data to accurately mimic the good and bad statistical properties of the likelihood functions of generative phylogenetic models.
Ethnic differences of genetic risk and smoking in lung cancer: two prospective cohort studies
Authors: Zhu Meng , Lv Jun , Huang Yanqian , Ma Hongxia , Li Ni , Wei Xiaoxia , Ji Mengmeng , Ma Zhimin , Song Ci , Wang Cheng , Dai Juncheng , Tan Fengwei , Guo Yu , Walters Robin , Millwood Iona Y. , Hung Rayjean J. , Christiani David C. , Yu Canqing , Jin Guangfu , Chen Zhengming , Wei Qingyi , Amos Christopher I. , Hu Zhibin , Li Liming , Shen Hongbing
Published: February 2023

Background

The relative risk of smoking on lung cancer have been reported to be much higher in white population than that in East Asians. However, it’s unknown whether genetic background underlies this disparity between ethnic groups. To assess the role of ethnic differences in genetic factors associated with this phenomenon.

Methods

We first constructed ethnic-specific polygenic risk scores (PRSs) to quantify individual genetic risk of lung cancer in Chinese and white populations. Then, we compared genetic risk and smoking as well as their interactions on lung cancer between two cohorts, including the China Kadoorie Biobank (CKB) and the UK Biobank (UKB). We also evaluated the absolute risk reduction over a 5-year period.

Results

19 SNPs and 23 SNPs were identified to construct the PRSs in Chinese and white populations, and smoking-related loci were only included in white populations. The PRSs were consistently associated with lung cancer risk respectively, but stronger associations were observed in smokers of the UKB (HR 1.26versus1.15,P=0.028). A significant interaction between genetic risk and smoking on lung cancer was observed in the UKB (RERI, 11.39 [95% CI, 7.01-17.94]), but not in the CKB. By comparing heavy smokers with nonsmokers, a greater absolute risk reduction was found in the UKB (10.95versus7.12 per 1000 person-years,P<0.001), especially for those at high genetic risk.

Conclusions

In China, tobacco control alone is not enough to reduce the burden of lung cancer, and comprehensive policies should be made to lower its high incidence.
Forecasting influenza incidence as an ordinal variable using machine learning
Authors: Wang Haowei , Kwok Kin On , Riley Steven
Published: February 2023

Many mechanisms contribute to the variation in the incidence of influenza disease, such as strain evolution, the waning of immunity and changes in social mixing. Although machine learning methods have been developed for forecasting, these methods are used less commonly in influenza forecasts than statistical and mechanistic models. In this study, we applied a relatively new machine learning method, Extreme Gradient Boosting (XGBoost), to ordinal country-level influenza disease data. We developed a machine learning forecasting framework by adopting the XGBoost algorithm and training it with surveillance data for over 30 countries between 2010 and 2018 from the World Health Organisation’s FluID platform. We then used the model to predict incidence 1- to 4-week ahead. We evaluated the performance of XGBoost forecast models by comparing them with a null model and a historical average model using mean-zero error (MZE) and macro-averaged mean absolute error (mMAE). The XGBoost models were consistently more accurate than the null and historical models for all forecast time horizons. For 1-week ahead predictions across test sets, the mMAE of the XGBoost model with an extending training window was reduced by 78% on average compared to the null model. Although the mMAE increased with longer prediction horizons, XGBoost models showed a 62% reduction in mMAE compared to the null model for 4-week ahead predictions. Our results highlight the potential utility of machine learning methods in forecasting infectious disease incidence when that incidence is defined as an ordinal variable. In particular, the XGBoost model can be easily extended to include more features, thus capturing complex patterns and improving forecast accuracy. Given that many natural extreme phenomena, such as floods and earthquakes, are often described on an ordinal scale when informing planning and response, these results motivate further investigation of using similar scales for communicating risk from infectious diseases.

Author Summary

Accurate and timely influenza forecasting is essential to help policymakers improve influenza preparedness and responses to potential outbreaks and allocate medical resources effectively. Here, we present a machine learning framework based on Extreme Gradient Boosting (XBoost) for forecast influenza activity. We used publicly available weekly influenza-like illness (ILI) incidence data in 32 countries. The predictive performance of the machine learning framework was evaluated using several accuracy metrics and compared with baseline models. XGBoost model was shown to be the most accurate prediction approach, and its accuracy remained stable with increasing prediction time horizons. Our results suggest that the machine learning framework for forecasting ILI has the potential to be adopted as a valuable public health tool globally in the future.
Deficiency for scavenger receptors Stabilin-1 and Stabilin-2 leads to age-dependent renal and hepatic depositions of fasciclin domain proteins TGFBI and Periostin in mice
Authors: Leibing Thomas , Riedel Anna , Xi Yannick , Adrian Monica , Krzistetzko Jessica , Kirkamm Christof , Dormann Christof , Schledzewski Kai , Goerdt Sergij , Géraud Cyrill
Published: February 2023

Background

Stabilin-1 and Stabilin-2 are two major scavenger receptors of liver sinusoidal endothelial cells that mediate removal of diverse molecules from the plasma. Double-knockout mice (Stab-DKO) develop impaired kidney function and a decreased lifespan, while single Stabilin deficiency or therapeutic inhibition ameliorates atherosclerosis and Stab1-inhibition is subject of clinical trials in immuno-oncology. Although POSTN and TFGBI have recently been described as novel Stabilin ligands, the dynamics and functional implications of these ligands have not been comprehensively studied.

Methods

Immunofluorescence, Western Blotting and Simple Western™ as well as in situ hybridization (RNAScope™) und qRT-PCR were used to analyze transcription levels and tissue distribution of POSTN and TGFBI in Stab-KO mice. Stab-POSTN-Triple deficient mice were generated to assess kidney and liver fibrosis and function in young and aged mice.

Results

TGFBI and POSTN protein accumulated in kidney and liver tissue in Stab-DKO mice during aging despite unchanged transcriptional levels. Stab-POSTN-Triple KO mice showed glomerulofibrosis and a reduced lifespan comparable to Stab-DKO mice. However, alterations of the glomerular diameter and vascular density were partially normalized in Stab-POSTN-Triple KO.

Conclusion

TGFBI and POSTN are Stabilin-ligands that are deposited in an age-dependent manner in the kidneys and liver due to insufficient scavenging in the liver. Functionally, POSTN appears to partially contribute to the observed renal phenotype in Stab-DKO mice. This study provides details on downstream effects how how Stabilin dysfunction affects distant organs on a molecular and functional level.
Red2Flpe-SCON: A Versatile, Multicolor Strategy for Generating Mosaic Conditional Knockout Mice
Authors: Wu Szu-Hsien Sam , Kim Somi , Lee Heetak , Lee Ji-Hyun , Colozza Gabriele , Park So-Yeon , Bakonyi Réka , Teriyapirom Isaree , Hallay Natalia , Pilat-Carrota Sandra , Theussl Hans-Christian , Kim Jihoon , Lee Joo-Hyeon , Simons Benjamin D. , Kim Jong Kyoung , Koo Bon-Kyoung
Published: February 2023

Image-based lineage tracing enables tissue turnover kinetics and lineage potentials of different adult cell populations to be investigated. Previously, we reported a genetic mouse model system,Red2Onco, which ectopically expressed mutated oncogenes together with red fluorescent proteins (RFP). This system enabled the expansion kinetics and neighboring effects of oncogenic clones to be dissected. We now report Red2Flpe-SCON: a new mosaic knockout system that uses multicolor reporters to label both mutant and wild-type cells. We have developed theRed2Flpemouse line for red clone-specific Flpe expression, as well as the FRT-based SCON (ShortConditional IntrON) method to facilitate tunable conditional mosaic knockouts in mice. We used the Red2Flpe-SCON method to study Sox2 mutant clonal analysis in the esophageal epithelium of adult mice which revealed that the stem cell gene, Sox2, is not essential for adult stem cell maintenance itself, but rather for stem cell proliferation and differentiation.
Metabolomic and transcriptomic analyses ofFmo5-/-mice reveal roles for flavin-containing monooxygenase 5 (FMO5) in NRF2-mediated oxidative stress, the unfolded protein response, lipid homeostasis, and carbohydrate and one-carbon metabolism
Authors: Phillips Ian R. , Veeravalli Sunil , Khadayate Sanjay , Shephard Elizabeth A.
Published: February 2023

Flavin-containing monooxygenase 5 (FMO5) is a member of the FMO family of proteins best known for their roles in the detoxification of foreign chemicals and more recently in endogenous metabolism. We have previously shown thatFmo5-/-mice display an age-related lean phenotype, with much reduced weight gain from 20 weeks of age. The phenotype is characterized by decreased fat deposition, lower plasma concentrations of glucose and cholesterol, higher glucose tolerance and insulin sensitivity, and resistance to diet-induced obesity. In the present study we report the use of metabolomic and transcriptomic analyses of livers ofFmo5-/-and wild-type mice to identify factors underlying the lean phenotype ofFmo5-/-mice and gain insights into the function of FMO5. Disruption of theFmo5gene has wide-ranging effects on the abundance of metabolites and expression of genes in the liver. The results reveal that FMO5 is involved in upregulating the NRF2-mediated oxidative stress response, the unfolded protein response and response to hypoxia and cellular stress, indicating a role for the enzyme in adaptation to oxidative and metabolic stress. FMO5 also plays a role in stimulating a wide range of metabolic pathways and processes, particularly ones involved in the regulation of lipid homeostasis, the uptake and metabolism of glucose, the generation of cytosolic NADPH, and in one-carbon metabolism. The results predict that FMO5 acts by stimulating the NRF2, XBP1, PPARA and PPARG regulatory pathways, while inhibiting STAT1 and IRF7 pathways.
Logistics of Bone Mineralization in the Chick Embryo Studied by 3D Cryo FIB-SEM Imaging
Authors: Raguin Emeline , Weinkamer Richard , Schmitt Clemens , Curcuraci Luca , Fratzl Peter
Published: February 2023

During skeletal development, bone growth and mineralization require transport of substantial amounts of calcium, while maintaining very low concentration. How an organism overcomes this major logistical challenge remains mostly unexplained. To shed some light on the dynamics of this process, we use cryogenic Focused Ion Beam-Scanning Electron Microscopy (cryo-FIB/SEM) to image forming bone tissue at day 13 of a chick embryo femur. We visualize both cells and matrix in 3D and observe calcium-rich intracellular vesicular structures. Counting the number of these vesicles per unit volume and measuring their calcium content based on the electron back-scattering signal, we are able to estimate the intracellular velocity at which these vesicles need to travel to transport all the calcium required for the mineral deposited in one day within the collagenous tissue. We estimate this velocity at 0.27 μm/s, which is too large for a diffusion process and rather suggests active transport through the cellular network. We conclude that calcium logistics is hierarchical and based on several transport mechanisms: first through the vasculature using calcium-binding proteins and the blood flow, then active transport over tens of micrometers through the network of osteoblasts and osteocytes and, finally, diffusive transport over the last one or two microns.
Diols and sugar substitutes in attractive toxic sugar baits targetingAedes aegyptiandAedes albopictus(Diptera: Culicidae) mosquitoes
Authors: Pullmann-Lindsley Heidi , Bartlett-Miller Ava , Pitts R Jason
Published: February 2023

Around the world, mosquitoes continue to transmit disease-causing pathogens while also developing resistance to insecticides. We previously discovered that a generally regarded as safe (GRAS) compound, 1,2-propanediol, reduces adult mosquito survivorship when ingested. In this study, we assess and compare five more chemically related compounds for mosquito lethality and eight GRAS sugar substitutes to determine toxic effects. We conducted a series of feeding assays to determine if ingesting the compounds influenced mosquito mean survivorship in locally collected lab-reared populations ofAedes aegypti(Linnaeus, 1762) andAedes albopictus(Skuse, 1894) mosquitoes. Our results indicate that 1,2-propanediol, 1,3-propanediol, 1,5-pentanediol, 1,6-hexanediol, 2-methyl-1,3-propanediol, DL-dithiothreitol, acesulfame potassium, allulose, erythritol, sodium saccharin, stevia, and sucralose significantly reduced the mean survivorship of one or both species. Short-term trials with the most toxic compounds revealed that they could substantially affect survivorship after 24 hours. We also found that many of the compounds yielded different responses in the two species and that male mosquitoes expired to a greater extent than female mosquitoes. These findings indicate that several of the compounds may be highly effective for local mosquito vector population and disease control through functioning as components in attractive toxic sugar bait systems (ATSBs)
Atrophic astrocytes in aged marmosets present tau hyperphosphorylation, RNA oxidation, and DNA fragmentation
Authors: Rodríguez-Callejas Juan D. , Fuchs Eberhard , Perez-Cruz Claudia
Published: February 2023

Astrocytes perform multiple essential functions in the brain showing morphological changes. Hypertrophic astrocytes are commonly observed in cognitively healthy aged animals, implying a functional defense mechanism without losing neuronal support. In neurodegenerative diseases, astrocytes show morphological alterations, such as decreased process length and reduced number of branch points, known asastroglial atrophy, with detrimental effects on neuronal cells. The common marmoset (Callithrix jacchus) is a non-human primate that, with age, develops several features that resemble neurodegeneration. In this study, we characterize the morphological alterations in astrocytes of adolescent (mean 1.75 y), adult (mean 5.33 y), old (mean 11.25 y), and aged (mean 16.83 y) male marmosets. We observed a significantly reduced arborization in astrocytes of aged marmosets compared to younger animals in the hippocampus and entorhinal cortex. These astrocytes also show oxidative damage to RNA and increased nuclear pTau (AT100). Astrocytes lacking S100A10 protein show a more severe atrophy and DNA fragmentation. Our results demonstrate the presence of atrophic astrocytes in the brains of aged marmosets.
IDSL.CSA: Composite Spectra Analysis for Chemical Annotation of Untargeted Metabolomics Datasets
Authors: Fakouri Baygi Sadjad , Kumar Yashwant , Barupal Dinesh Kumar
Published: February 2023

Poor chemical annotation of high-resolution mass spectrometry data limit applications of untargeted metabolomics datasets. Our new software, the Integrated Data Science Laboratory for Metabolomics and Exposomics – Composite Spectra Analysis (IDSL.CSA) R package, generates composite mass spectra libraries from MS1-only data, enabling the chemical annotation of LC/HRMS peaks regardless of the availability of MS2 fragmentation spectra. We demonstrate comparable annotation rates for commonly detected endogenous metabolites in human blood samples using IDSL.CSA libraries versus MS/MS libraries in validation tests. IDSL.CSA can create and search composite spectra libraries from any untargeted metabolomics dataset generated using high-resolution mass spectrometry coupled to liquid or gas chromatography instruments. The cross-applicability of these libraries across independent studies may provide access to new biological insights that may be missed due to the lack of MS2 fragmentation data. The IDSL.CSA package is available in the R CRAN repository athttps://cran.r-project.org/package=IDSL.CSA. Detailed documentation and tutorials are provided athttps://github.com/idslme/IDSL.CSA.

For Table of Contents Only
Evaluating the Performance of Widely Used Phylogenetic Models for Gene Expression Evolution
Authors: Dimayacyac Jose Rafael , Wu Shanyun , Jiang Daohan , Pennell Matt
Published: February 2023

Phylogenetic comparative methods are increasingly used to test hypotheses about the evolutionary processes that drive divergence in gene expression among species. However, it is unknown whether the distributional assumptions of phylogenetic models designed for quantitative phenotypic traits are realistic for expression data and importantly, the reliability of conclusions of phylogenetic comparative studies of gene expression may depend on whether the data is well-described by the chosen model. To evaluate this, we first fit several phylogenetic models of trait evolution to 8 previously published comparative expression datasets, comprising a total of 54,774 genes with 145,927 unique gene-tissue combinations. Using a previously developed approach, we then assessed how well the best model of the set described the data in an absolute (not just relative) sense. First, we find that Ornstein-Uhlenbeck models, in which expression values are constrained around an optimum, were the preferred model for 66% of gene-tissue combinations. Second, we find that for 61% of gene-tissue combinations, the best fit model of the set was found to perform well; the rest were found to be performing poorly by at least one of the test statistics we examined. Third, we find that when simple models do not perform well, this appears to be typically a consequence of failing to fully account for heterogeneity in the rate of the evolution. We advocate that assessment of model performance should become a routine component of phylogenetic comparative expression studies; doing so can improve the reliability of inferences and inspire the development of novel models.
The evolutionary history of spines – a Cenozoic arms race with mammals
Authors: Gélin Uriel , Charles-Dominique Tristan , Davies T. Jonathan , Svenning Jens-Christian , Bond William J. , Tomlinson Kyle W.
Published: February 2023

The role of mammal herbivory in plant evolution is largely unrecognised. Spines on stems are a common and important feature found in ∼9% of eudicot woody plant species worldwide. Spines evolved independently multiple times during the Cenozoic. The timing and extent of spiny plant diversification varied among continents, pointing towards continental rather than global drivers. Spine evolution is closely related to radiation of extant ungulates and extinct ground sloths, rather than climate variation. Diversification began in the Paleogene in herbivore species-rich Eurasia and North America, emerging later in the Neogene in species-poorer South America, Africa and Australia. Spiny lineages expanded their ecological footprint over non-spiny plants, mainly through intercontinental migrations, indicating that spines likely provided a competitive advantage with increasing, and novel, mammal herbivory pressure.
Trial Averaging for Deep EEG Classification
Authors: Williams Jacob M. , Samal Ashok , Johnson Matthew R.
Published: February 2023

Many signals, particularly of biological origin, suffer from a signal-to-noise ratio sufficiently low that it can be difficult to classify individual examples reliably, even with relatively sophisticated machine-learning techniques such as deep learning. In some cases, the noise can be high enough that it is even difficult to achieve convergence during training. We considered this problem for one data type that often suffers from such difficulties, namely electroencephalography (EEG) data from cognitive neuroscience studies in humans. One solution to increase signal-to-noise is, of course, to perform averaging among trials, which has been employed before in other studies of human neuroscience but not, to our knowledge, investigated rigorously, particularly not in deep learning. Here, we parametrically studied the effects of different amounts of trial averaging during training and/or testing in a human EEG dataset, and compared the results to that of a related algorithm, Mixup. Broadly, we found that even a small amount of averaging could significantly improve classification, particularly when both training and testing data were subjected to averaging. Simple averaging clearly outperformed Mixup, although the benefits of averaging differed across classification categories. Overall, our results confirm the value of averaging during training and testing when single-trial classification is not strictly necessary for the application in question.

Highlights

Averaging trials can dramatically improve performance in classification of EEG data

The benefits can be seen when averaging on both training and test datasets

Simple trial averaging outperformed a popular related algorithm, Mixup

However, effects of averaging differed across different stimulus categories
RNA-catalyzed RNA Ligation within Prebiotically Plausible Model Protocells
Authors: DasGupta Saurja , Zhang Stephanie J. , Smela Merrick P. , Szostak Jack W.
Published: February 2023

Demonstrating RNA catalysis within prebiotically relevant models of primordial cells (protocells) remains a challenge in Origins of life research. Fatty acid vesicles encapsulating genomic and catalytic RNAs (ribozymes) are attractive models for protocells; however, RNA catalysis has largely been incompatible with fatty acid vesicles due to their instability in the presence of Mg2+at concentrations required for ribozyme function. Here, we report a ribozyme that catalyzes template-directed RNA ligation at low Mg2+concentrations and thus remains active within stable vesicles. Ribose and adenine, both prebiotically relevant molecules, were found to greatly reduce Mg2+-induced RNA leakage from vesicles. When we co-encapsulated the ribozyme, substrate, and template within fatty acid vesicles, we observed efficient RNA-catalyzed RNA ligation upon subsequent addition of Mg2+. Our work shows that RNA-catalyzed RNA assembly can occur efficiently within prebiotically plausible fatty acid vesicles and represents a step toward the replication of primordial genomes within self-replicating protocells.