bluuebunny/crossref_metadata_2025 huggingface dataset:
Cardiometabolic Disorders in the Offspring of Parents With Severe Mental Illness
Authors: Protsenko Maria , Kerkelä Martta , Miettunen Jouko , Auvinen Juha , Järvelin Marjo-Riitta , Jones Peter B. , Gissler Mika , Veijola Juha
Published: December 2021

Objective

The elevated prevalence of cardiometabolic disorders is consistently reported in patients with severe mental illness (SMI). We explored the association between parental SMI and offspring cardiometabolic morbidity. Our hypothesis was that offspring of people with SMI have increased morbidity risk.

Method

The Northern Finland Birth Cohort 1966 is a study of offspring whose date of birth was expected in 1966. The follow-up lasted until 2015 (49 years). The final study sample included 11,175 children. We used parental SMI as the exposure in the study. The following cardiometabolic disorders were used as outcome measures: diabetes mellitus, hypertension, hyperlipidemia, coronary artery disease, obesity, and cerebrovascular disorders.

Results

There were 139 (14.7%; hazard ratios [HR] = 1.63; 95% confidence interval [CI] = 1.36–1.94) children of parents with SMI who developed cardiometabolic disorder during follow-up and 957 (9.4%) in the comparison cohort. Statistically significant HRs were found in males (HR = 1.95; 95% CI =1.56–2.44), but not in females (HR = 1.29; 95% CI = 0.96–1.73).

Conclusions

Having a cardiometabolic disorder was associated with male offspring of parents with SMI. Our findings suggest that there is an elevated risk of coronary artery disease, hyperlipidemia, obesity, and hypertension in the male offspring of parents with SMI. Our results suggest that the somatic health of offspring of parents with SMI should also be considered in addition to their mental health in clinical practice.
A Parallel Pandemic: Increased Firearm Injuries at Five Northern California Trauma Centers During the COVID-19 Pandemic
Authors: Matthay Zachary A. , Callcut Rachael A. , Kwok Amy M. , Aarabi Shahram , Forrester Joseph D. , Kornblith Lucy Z.
Published: December 2021

Objective:

This study aimed to characterize changes in firearm injuries at 5 level 1 trauma centers in Northern California in the 12 months following the start of the COVID-19 pandemic compared with the preceding 4 years, accounting for regional variations and seasonal trends.

Summary and Background Data:

Increased firearm injuries have been reported during the early peaks of the COVID-19 pandemic despite shelter-in-place restrictions. However, these data are overwhelmingly from singlecenter studies, during the initial phase of the pandemic prior to lifting of shelter-in-place restrictions, or do not account for seasonal trends.

Methods:

An interrupted time-series analysis (ITSA) of all firearm injuries presenting to 5 adult level 1 trauma centers in Northern California was performed (January 2016to February 2021). ITSA modeled the association of the onset of the COVID-19 pandemic (March 2020) with monthly firearm injuries using the ordinary least-squares method, included month indicators to adjust for seasonality, and specified lags of up to 12 months to account for autocorrelation.

Results:

Prior to the start of COVID-19, firearm injuries averaged (±SD) of 86 (±16) and were decreasing by 0.5/month (P < 0.01). The start of COVID- 19 (March 2020) was associated with an alarming increase of 39 firearm injuries/month (P < 0.01) followed by an ongoing rise of 3.5/mo (P < 0.01). This resulted in an average of 130 (±26) firearm injuries/month during the COVID-19 period and included 8 of the 10 highest monthly firearm injury rates in the past 5 years.

Conclusions:

These data highlight an alarming escalation in firearm injuries in the 12 months following the onset of the COVID-19 pandemic in Northern California. Additional studies and resources are needed to better understand and address this parallel public health crisis.
Prognosis of Patients with Esophageal Carcinoma After Routine Thoracic Duct Resection
Authors: Oshikiri Taro , Numasaki Hodaka , Oguma Junya , Toh Yasushi , Watanabe Masayuki , Muto Manabu , Kakeji Yoshihiro , Doki Yuichiro
Published: December 2021

Objective:

To clarify whether routine thoracic duct (TD) resection improves the prognosis of patients with esophageal cancer after radical esophagectomy.

Summary of Background Data:

Although TD resection can cause nutritional disadvantage and immune suppression, it has been performed for the resection of surrounding lymph nodes.

Methods:

We analyzed 12,237 patients from the Comprehensive Registry of Esophageal Cancer in Japan who underwent esophagectomy between 2007 and 2012. TD resection and preservation groups were compared in terms of prognosis, perioperative outcomes, and initial recurrent patterns using strict propensity score matching. Particularly, the year of esophagectomy and history of primary cancer of other organs were added as covariates.

Results:

After propensity score matching, 1638 c-Stage I–IV patients participated in each group. The 5 year overall survival and cause-specific survival rates were 57.5% and 65.6% in the TD-resected group and 55.2% and 63.4% in the TD-preserved group, respectively, without significant differences. The TD-resected group had significantly more retrieved mediastinal nodes (30 vs 21, P < 0.0001) and significantly fewer lymph node recurrence (376 vs 450, P = 0.0029) compared with the TD-preserved group. However, the total number of distant metastatic organs was significantly greater in TD-resected group than in the TD-preserved group (499 vs 421, P = 0.0024).

Conclusions:

TD resection did not improve survival in patients with esoph-ageal cancer. Despite having retrieved more lymph nodes, TD resection caused distant metastases in more organs compared to TD preservation. Hence, prophylactic TD resection should not be recommended in patients with esophageal cancer.
Leptospira ainlahdjerensis sp. nov., Leptospira ainazelensis sp. nov., Leptospira abararensis sp. nov. and Leptospira chreensis sp. nov., four new species isolated from water sources in Algeria
Authors: Korba Anissa Amara , Lounici Hakim , Kainiu Malia , Vincent Antony T. , Mariet Jean-François , Veyrier Fréderic J. , Goarant Cyrille , Picardeau Mathieu
Published: December 2021

Leptospira

strains were isolated from freshwater sampled at four sites in Algeria and characterized by whole-genome sequencing and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). The cells were spiral-shaped and motile. Phylogenetic and MALDI-TOF MS analyses showed that the strains can be clearly distinguished from the other described species in the genus

Leptospir

a, therefore representing two novel species of the pathogen subclade P1 and two novel species of the saprophyte subclade S1. The names Leptospira ainlahdjerensis sp. nov. (type strain 201903070T=KIT0297T=CIP111912T), Leptospira ainazelensis sp. nov. (201903071T=KIT0298T=CIP111913T), Leptospira abararensis sp. nov. (201903074T=KIT0299T=CIP111914T) and Leptospira chreensis (201903075T=KIT0300T=CIP111915T) are proposed.
Paraneptunicella aestuarii gen. nov., sp. nov., a member of the family Alteromonadaceae isolated from seawater in East China Sea
Authors: Zhang Yanzhu , He Shufen , Shi Liufei , Liu Yang , Mao Deqiang , Liu Biying , He Xiaoping , Nowruzi Bahareh , Jung Dawoon , Zhang Weiyan , Ding Lijian , He Shan , Liu Liwei
Published: December 2021

An aerobic Gram-stain-negative, curved rod-shaped and non-spore-forming bacterial strain (NBU2194T) was isolated from seawater collected in an intertidal zone in Ningbo, Zhejiang Province, PR China. It was motile though a single polar flagellum and grew at 20–42 °C (optimum, 30 °C), in 0–2.0 % NaCl (0 %, w/v) and at pH 5.0–9.0 (pH 6.0–7.0). The sole respiratory quinone was ubiquinone-8. The major cellular fatty acids were C16 : 0, C16 : 1
 ω7c and/or C16 : 1
 ω6c. The polar lipids contained diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylglycerol, one unidentified phospholipid and two unidentified aminophosphoglycolipids. A phylogenetic analysis based on 16S rRNA gene sequences and 65 genomic core genes showed that strain NBU2194T formed a distinct lineage in the family

Alteromonadaceae

. The genome of strain NBU2194T was 4 913 533 bp with a DNA G+C content of 43.9 mol% and coded 3895 genes, 12 rRNA genes and 47 tRNA genes. The average nucleotide identity, amino acid identity and digital DNA–DNA hybridization values between strain NBU2194T and related species of

Alteromonadaceae

were below the threshold limit for prokaryotic species delineation. NBU2194T could be distinguished from other genera in the family

Alteromonadaceae

based on phenotypic, chemotaxonomic and genomic characteristics. On the basis of the polyphasic taxonomic evidence collected in this study, strain NBU2194T is considered to represent a novel genus and species in the family

Alteromonadaceae

, for which the name Paraneptunicella aestuarii is proposed. The type strain is NBU2194T (=KCTC 82442T=GDMCC 1.2217T).
Xanthomonas hydrangeae sp. nov., a novel plant pathogen isolated from Hydrangea arborescens
Authors: Dia Nay C. , Van Vaerenbergh Johan , Van Malderghem Cinzia , Blom Jochen , Smits Theo H. M. , Cottyn Bart , Pothier Joël F.
Published: December 2021

This paper describes a novel species isolated in 2011 and 2012 from nursery-grownHydrangea arborescenscultivars in Flanders, Belgium. After 4 days at 28 °C, the strains yielded yellow, round, convex and mucoid colonies. Pathogenicity of the strains was confirmed on its isolation host, as well as onHydrangea quercifolia. Analysis using MALDI-TOF MS identified theHydrangeastrains as belonging to the genusXanthomonasbut excluded them from the speciesXanthomonas hortorum. A phylogenetic tree based ongyrBconfirmed the close relation toX. hortorum. Three fatty acids were dominant in theHydrangeaisolates: anteiso-C15 : 0, iso-C15 : 0and summed feature 3 (C16 : 1 ω7c/C16 : 1 ω6c). UnlikeX. hortorumpathovars, theHydrangeastrains were unable to grow in the presence of lithium chloride and could only weakly utilized-fructose-6-PO4and glucuronamide. Phylogenetic characterization based on multilocus sequence analysis and phylogenomic characterization revealed that the strains are close to, yet distinct from,X. hortorum. The genome sequences of the strains had average nucleotide identity values ranging from 94.35–95.19 % andin silicoDNA–DNA hybridization values ranging from 55.70 to 59.40 % to genomes of theX. hortorumpathovars. A genomics-based loop-mediated isothermal amplification assay was developed which was specific to theHydrangeastrains for its early detection. A novel species,Xanthomonas hydrangeae sp. nov., is proposed with strain LMG 31884T(=CCOS 1956T) as the type strain.
Context-aware genomic surveillance reveals hidden transmission of a carbapenemase-producing Klebsiella pneumoniae
Authors: Viehweger Adrian , Blumenscheit Christian , Lippmann Norman , Wyres Kelly L. , Brandt Christian , Hans Jörg B. , Hölzer Martin , Irber Luiz , Gatermann Sören , Lübbert Christoph , Pletz Mathias W. , Holt Kathryn E. , König Brigitte
Published: December 2021

Genomic surveillance can inform effective public health responses to pathogen outbreaks. However, integration of non-local data is rarely done. We investigate two large hospital outbreaks of a carbapenemase-carrying

Klebsiella pneumoniae

strain in Germany and show the value of contextual data. By screening about 10 000 genomes, over 400 000 metagenomes and two culture collections using in silico and in vitro methods, we identify a total of 415 closely related genomes reported in 28 studies. We identify the relationship between the two outbreaks through time-dated phylogeny, including their respective origin. One of the outbreaks presents extensive hidden transmission, with descendant isolates only identified in other studies. We then leverage the genome collection from this meta-analysis to identify genes under positive selection. We thereby identify an inner membrane transporter (ynjC) with a putative role in colistin resistance. Contextual data from other sources can thus enhance local genomic surveillance at multiple levels and should be integrated by default when available.
Snrpb, the CCMS gene, is required in neural crest cells for proper splicing of genes essential for craniofacial morphogenesis
Authors: Alam Sabrina Shameen , Kumar Shruti , Beauchamp Marie-Claude , Bareke Eric , Boucher Alexia , Nzirorera Nadine , Padilla Reinnier , Zhang Si Jing , Majewski Jacek , Jerome-Majewska Loydie A.
Published: December 2021

Heterozygous mutations in SNRPB, an essential core component of the five small ribonucleoprotein particles of the spliceosome, are responsible for Cerebrocostomandibular Syndrome (CCMS). We show that Snrpb heterozygous embryos arrest shortly after implantation. Additionally, heterozygous deletion of Snrpb in the developing brain and neural crest cells models craniofacial malformations found in CCMS, and results in death shortly after birth. RNAseq analysis of mutant heads prior to morphological defects revealed increased exon-skipping and intron-retention in association with increased 5’ splice site strength. We found increased exon-skipping in negative regulators of the P53-pathway, increased levels of nuclear P53, P53-target genes. However, removing TrP53 in Snrpb heterozygous mutant neural crest cells did not completely rescue craniofacial development. We also found a small but significant increase in exon-skipping of several transcripts required for head and midface development, including Smad2 and Rere. Furthermore, mutant embryos exhibited ectopic or missing expression of Fgf8 and Shh, which are required to coordinate face and brain development. Thus, we propose that mis-splicing of transcripts that regulate P53-activity and craniofacial-specific genes both contribute to craniofacial malformations.
On the survival of individuals diagnosed with type 2 diabetes mellitus in the United Kingdom: a retrospective matched cohort study
Authors: Ncube Njabulo , Kulinskaya Elena , Steel Nicholas , Pchejetski Dmitry
Published: December 2021

Objective

To estimate long-term hazards of all-cause mortality following a diagnosis of type 2 diabetes mellitus (T2DM) using electronic primary care data.

Methodology

Retrospective matched cohort study using electronic health records from THIN primary care database. The study included individuals born between 1930 and 1960, diagnosed with T2DM between 2000 and 2016 and aged 50-74 years and excluded those with pre-existing stroke, cancer, cognitive impairment, lower limb amputation or chronic kidney disease (CKD) stages 3 to 5. T2DM individuals were matched at diagnosis to at most 3 controls by age, gender and general practice (GP) and followed up to 1 January 2017. Time-varying hazards of all-cause mortality were then estimated using Gompertz-double-Cox model with frailty on GP, adjusting for medical history, socio-demographic and lifestyle factors.

Results

A total of 221 182 (57.6% Males, 30.8% T2DM) individuals were selected for the study of whom 29 618 (13.4%) died during follow-up. The adjusted mortality hazard of type 2 diabetes mellitus (T2DM) was estimated to be 1.21[1.12-1.3] and 1.52[1.44-1.6] among individuals diagnosed at 50-59 years and 60-74 years, respectively, compared to controls. Deprivation, obesity, smoking and comorbidities affected survival of cases and controls equally. Compared to the 1930-39 birth cohort, all-cause mortality hazards were reduced in the 1940-49 cohort, but increased at older ages in the 1950-60 birth cohort for both cases and controls.

Conclusion

T2DM is associated with raised all-cause mortality hazards which increase with age of diagnosis. These hazards associated with age at diagnosis are constant across all birth cohorts demonstrating a lack of progress over time in reducing the relative risks of all-cause mortality associated with T2DM. A further study that includes people born after 1960 is needed to fully understand the emerging higher mortality hazards among the younger birth cohorts.

Significancy of this Study

What is already known about this study?

- Diagnosis of type 2 diabetes mellitus (T2DM) is associated with increased all-cause mortality risk.

What are the new findings?

- The increased all-cause mortality associated with T2DM was lower than previously reported.

- The all-cause mortality risk associated with T2DM increased with increasing age at diagnosis.

- The all-cause mortality risk associated with T2DM remained constant across all birth cohorts.

- The all-cause mortality risk is increased at later ages among the younger birth cohorts in individuals with and without T2DM.

How might these results change the focus of research or clinical practice?

- Further research is needed on individuals born after 1960 to explore the increased all-cause mortality hazards in recent birth cohorts.
The dual role of N6-methyladenosine on mouse maternal RNAs and 2-cell specific RNAs revealed by ULI-MeRIP sequencing
Authors: Wu You , Xu Xiaocui , Qi Meijie , Chen Chuan , Li Mengying , Yan Rushuang , Kou Xiaochen , Zhao Yanhong , Liu Wenqiang , Li Yanhe , Liu Xuelian , Zhang Meiling , Yi Chengqi , Wang Hong , Shen Bin , Gao Yawei , Gao Shaorong
Published: December 2021

N6-methyladenosine (m6A) and its regulatory components play critical roles in various developmental processes in mammals(1-5). However, the landscape and function of m6A in the maternal-to-zygotic transition (MZT) remain unclear due to limited materials. Here, by developing an ultralow-input MeRIP-seq method, we revealed the dynamics of the m6A RNA methylome during the MZT process in mice. We found that more than 1/3 maternal decay and 2/3 zygotic mRNAs were modified by m6A. Moreover, m6As are highly enriched in the RNA of transposable elements MTA and MERVL, which are highly expressed in oocytes and 2-cell embryos, respectively. Notably, maternal depletion of Kiaa1429, a component of the m6A methyltransferase complex, leads to a reduced abundance of m6A-marked maternal RNAs, including both genes and MTA, in GV oocytes, indicating m6A-dependent regulation of RNA stability in oocytes. Interestingly, when the writers were depleted, some m6A-marked 2-cell specific RNAs, including Zscan4 and MERVL, appeared normal at the 2-cell stage but failed to be decayed at later stages, suggesting that m6A regulates the clearance of these transcripts. Together, our study uncovered that m6As function in context-specific manners during MZT, which ensures the transcriptome stability of oocytes and regulates the stage specificity of zygotic transcripts after fertilization.

One Sentence Summary

m6A RNA methylation stabilizes the maternal RNAs in mouse oocytes and degrades the 2-cell specific RNAs in the cleavage-stage embryos.
S Gene Target Failure (SGTF) in Commercial Multiplex RT-PCR assay as indicator to detect SARS-CoV-2 VOC B.1.1.7 lineage in Tamil Nadu, India
Authors: Vidya NM , Kumaresan A , Kalaivani V , Rajesh Kumar A , Gurunathan S , Avudai Selvi R , Uma R , Varsha P , Raju S , Sampath P , Selvavinayagam T S
Published: December 2021

Emergence of Severe Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV-2) Variants of Concern (VOC) possessing improved virulence, transmissibility and/or immune-escape capabilities has raised significant public health concerns. In order to identify VOCs, WHO recommends Whole-Genome Sequencing approach, which is costly and involves longer completion time. Hence, potential role of commercial multiplex RT-PCR kit to screen variants rapidly is being attempted in this study. A total of 1200 suspected COVID samples from different districts of Tamil Nadu State (India) were screened with Thermo TaqPath RT-PCR kit and Altona’s Realstar RT-PCR Assay kit. Among 1200 screened, S-gene target failure (SGTF) phenomenon were identified in 112 samples while testing with TaqPath RT-PCR Kit. 100% concordant results were observed between SGTF phenomenon and whole-genome sequencing (WGS) results in detecting SARS-CoV-2 VOC B.1.1.7. TaqPath RT-PCR assay testing can be utilized by laboratories to screen rapidly the VOC B.1.1.7 variants, thus enabling early detection of B.1.1.7 variant infection and transmission in population. This in turn will pave way to implement suitable preventive measures by appropriate authorities to control the transmission of the viral variant.
Anti-SARS-CoV-2 cellular immunity in 571 vaccinees assessed using an interferon-γ release assay
Authors: Uwamino Yoshifumi , Wakui Masatoshi , Yatabe Yoko , Nakagawa Terumichi , Sakai Akiko , Kurafuji Toshinobu , Shibata Ayako , Tomita Yukari , Noguchi Masayo , Tanabe Akiko , Arai Tomoko , Ohno Akemi , Yokota Hiromitsu , Uno Shunsuke , Yamasawa Wakako , Sato Yasunori , Ikeda Mari , Yoshimura Akihiko , Hasegawa Naoki , Saya Hideyuki , Murata Mitsuru
Published: December 2021

Generation of antigen-specific memory T cells has been analyzed only for few coronavirus disease 2019 (COVID-19) vaccinees, whereas antibody titers have been serologically measured for a large number of individuals. Here, we assessed the anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular immune response in a large cohort using interferon (IFN)-γ release assays (IGRAs) based on short-term whole blood culture. The study included 571 individuals who received the viral spike (S) protein-expressing BNT162b2 mRNA SARS-CoV-2 vaccine. Serum IgG titers against the receptor-binding domain (RBD) of S protein were measured. Samples of 28 vaccinees were subjected to flow cytometry analysis of T cells derived from short-term whole blood culture. IFN-γ production triggered by S antigens was observed in most individuals 8 weeks after receiving the second dose of the vaccine, indicating acquisition of T cell memory responses. The frequencies of activated T cell subsets were strongly correlated with IFN-γ levels, supporting the usability of our approach. S antigen-stimulated IFN-γ levels were weakly correlated with anti-RBD IgG titers and associated with pre-vaccination infection and adverse reactions after the second dose. Our approach revealed cellular immunity acquired after COVID-19 vaccination, providing insights regarding the effects and adverse reactions of vaccination.
Evaluation of an ultra-rapid antibiotic susceptibility testing method on positive blood cultures with Escherichia coli
Authors: Baltekin Özden , Johnsson Alexander T. A. , Wong Alicia Y. W. , Nilsson Kajsa , Mert Berivan , Söderberg Lovisa , Wistrand-Yuen Erik , Özenci Volkan
Published: December 2021

Blood stream infection (BSI) is related to high mortality and morbidity. Early antimicrobial therapy is crucial in treating patients with BSI. The most common Gram-negative bacteria causing BSI is Escherichia coli. Targeted effective treatment of patients with BSI is only possible if it is based on antibiotic susceptibility testing (AST) data after blood culture positivity. However, there are very few methods available for rapid phenotypic AST and the fastest method takes 4 h. Here we analyzed the performance of a 30 min ultra-rapid method for AST of E. coli directly from positive blood cultures (BC). In total, 51 positive BC with E. coli were studied, and we evaluated the ultra-rapid method directly on positive BC as well as on E. coli colonies cultured on agar plates. The results obtained by the new method were compared with disk diffusion.

The method provided accurate AST result in 30 min to Ciprofloxacin and Gentamicin for 92% and 84% of the positive BC samples, respectively. For E. coli isolates retrieved from agar plates, 86% and 96% of the AST results were accurate for Ciprofloxacin and Gentamicin, respectively, after 30 min of assay time. When time to result was modulated in-silico from 30 to 60 minutes for the agar plate samples, accuracy of AST results went up to 92% for Ciprofloxacin and to 100% for Gentamicin.

The present study shows that the method is reliable and delivers ultra-rapid AST data in 30 minutes directly from positive BC and as well as from agar plates.
Dynamics of anti-Spike IgG antibody level after full BNT162b2 COVID-19 vaccination in health care workers
Authors: Ikezaki Hiroaki , Nakashima Ryoko , Miyoshi Kahori , Hara Yuichi , Hayashi Jun , Hara Hiroshi , Nomura Hideyuki , Shimono Nobuyuki
Published: December 2021

Introduction

The administration of a third vaccine is ongoing in many countries, but the evaluation of vaccine-induced immunity is still insufficient. This study evaluated anti-spike IgG levels in 373 health care workers six months after the BNT162b2 vaccination.

Methods

Dynamics of anti-spike IgG levels six months after the 2nd vaccination were assessed in 49 participants (Analysis-1). A cross-sectional assessment of anti-spike IgG level was performed in 373 participants (Analysis-2). Participants positive for anti-nucleocapsid IgG or IgM and receiving immunosuppressants were excluded from Analysis-2.

Results

In Analysis 1, the median anti-spike IgG level was lower in the older age group and decreased consistently after the second vaccination regardless of age. In Analysis-2, the anti-spike IgG level was significantly negatively associated with age (r = −0.35, p < 0.01). This correlation remained statistically significant (r = −0.28, p < 0.01) even after adjusting for sex, BMI, smoking habits, alcohol drinking habits, allergies, and the presence of fever or other adverse reactions at the time of the vaccination. Alcohol drinking habit was also associated with the anti-spike IgG level; daily alcohol drinkers had significantly lower anti-spike IgG levels than never alcohol drinkers. Sex, smoking habit, allergy, and fever and other side effects after the vaccination were not associated with anti-spike IgG levels six months after the 2nd vaccination.

Conclusions

Six months after the vaccination, the anti-spike IgG level was substantially low among older persons and daily alcohol drinkers.
mRNA COVID-19 vaccine effectiveness against SARS-CoV-2 infection in a prospective community cohort, rural Wisconsin, November 2020-December 2021
Authors: McLean Huong Q , McClure David L , King Jennifer P , Meece Jennifer K , Pattinson David , Neumann Gabriele , Kawaoka Yoshihiro , Rolfes Melissa A , Belongia Edward A
Published: December 2021

Reduced COVID-19 vaccine effectiveness (VE) has been observed with increasing predominance of the Delta variant. In a prospective rural community cohort of 1265 participants, VE against symptomatic and asymptomatic SARS-CoV-2 infection was 56% for mRNA COVID-19 vaccines.
Early detection and improved genomic surveillance of SARS-CoV-2 variants from deep sequencing data
Authors: Ramazzotti Daniele , Maspero Davide , Angaroni Fabrizio , Antoniotti Marco , Piazza Rocco , Graudenzi Alex
Published: December 2021

In the definition of fruitful strategies to contrast the worldwide diffusion of SARS-CoV-2, maximum efforts must be devoted to the early detection of dangerous variants. An effective help to this end is granted by the analysis of deep sequencing data of viral samples, which are typically discarded after the creation of consensus sequences. Indeed, only with deep sequencing data it is possible to identify intra-host low-frequency mutations, which are a direct footprint of mutational processes that may eventually lead to the origination of functionally advantageous variants. Accordingly, a timely and statistically robust identification of such mutations might inform political decision-making with significant anticipation with respect to standard analyses based on con-sensus sequences.

To support our claim, we here present the largest study to date of SARS-CoV-2 deep sequencing data, which involves 220,788 high quality samples, collected over 20 months from 137 distinct studies. Importantly, we show that a rele-vant number of spike and nucleocapsid mutations of interest associated to the most circulating variants, including Beta, Delta and Omicron, might have been intercepted several months in advance, possibly leading to different public-health decisions. In addition, we show that a refined genomic surveillance system involving high- and low-frequency mutations might allow one to pin-point possibly dangerous emerging mutation patterns, providing a data-driven automated support to epidemiologists and virologists.
Microbial dynamics inference at ecosystem-scale
Authors: Gibson Travis E. , Kim Younhun , Acharya Sawal , Kaplan David E. , DiBenedetto Nicholas , Lavin Richard , Berger Bonnie , Allegretti Jessica R. , Bry Lynn , Gerber Georg K.
Published: December 2021

Dynamical systems models are a powerful tool for analyzing interactions, stability, resilience, and other key properties in biomedically important microbial ecosystems, such as the gut microbiome. Challenges to modeling and inference in this setting include the large number of species present, and data sparsity/noise characteristics. Here, we introduce a Bayesian statistical method, the Microbial Dynamical Systems Inference Engine 2 (MDSINE2), which infers compact and interpretable ecosystems-scale dynamical systems models from microbiome time-series data. We model microbial dynamics as stochastic processes driven by inferred interaction modules, or groups of microbes with similar interaction structure and responses to perturbations. Additionally, we model the noise characteristics of sequencing and qPCR measurements to provide uncertainty quantification for all outputs. To evaluate MDSINE2, and provide a benchmarking resource for the community, we generated the most densely sampled microbiome time-series to date, which consists of a cohort of mice that received fecal transplants from a human donor and were then subjected to dietary and antibiotic perturbations. Benchmarking on simulated and real data demonstrate that MDSINE2 significantly outperforms state-of-the-art methods, and moreover identifies interaction modules that shed new light on ecosystems-scale interactions in the gut microbiome. We provide MDSINE2 as an open-source Python package at:https://github.com/gerberlab/MDSINE2.
Targeted drug release from stable and safe ultrasound-sensitive nanocarriers
Authors: Wilson Matthew G. , Parikh Aarav , Dara Audri , Beaver Alexander , Kubanek Jan
Published: December 2021

Targeted delivery of medication has the promise of increasing the effectiveness and safety of current systemic drug treatments. Focused ultrasound is emerging as noninvasive and practical energy for targeted drug release. However, it has yet to be determined which nanocarriers and ultrasound parameters can provide both effective and safe release. Perfluorocarbon nanodroplets have the potential to achieve these goals, but current approaches have either been effective or safe, but not both. We found that nanocarriers with highly stable perfluorocarbon cores mediate effective drug release so long as they are activated by ultrasound of sufficiently low frequency. We demonstrate a favorable safety profile of this formulation in a non-human primate. To facilitate translation of this approach into humans, we provide an optimized method for manufacturing the nanocarriers. This study provides a recipe and release parameters for effective and safe drug release from nanoparticle carriers in the body part specified by focused ultrasonic waves.
Limited plasticity in gene expression for providing or receiving parental care under different temperatures
Authors: Moss Jeanette B. , Cunningham Christopher B. , McKinney Elizabeth C. , Moore Allen J.
Published: December 2021

Parenting is thought to evolve to buffer offspring from variable, unpredictable, and challenging environmental conditions. In the subsocial carrion beetle, Nicrophorus orbicollis, stressful temperatures during parenting do not affect parental behavior despite imposing steep fitness costs to parents. Here, we ask if plasticity of gene expression underpins this behavioral stability or facilitates independent compensation by larvae. To test this we characterized gene expression of parents and offspring before and during active parenting under benign (20°C) and stressful (24°C) temperatures to identify genes of parents and offspring associated with thermal response, parenting/being parented, and gene expression plasticity associated with behavioral stability of parental care. The main effects of thermal and social condition each shaped patterns of gene expression in females, males, and larvae. In addition, we implicated 79 genes in females as ‘buffering’ parental behavior across environments. The majority of these underwent significant changes in expression in actively parenting mothers at the benign temperature, but not at the stressful temperature. Our results suggest that neither genetic programs for parenting nor their effects on offspring gene expression are fundamentally different under stressful conditions, and that behavioral stability is associated primarily with the maintenance of existing genetic programs rather than replacement or supplementation. Thus, while selection for compensatory gene expression could expand the range of thermal conditions parents will tolerate, without expanding the toolkit of genes involved selection is unlikely to lead to adaptive changes of function.
Evolutionary learning in the brain by heterosynaptic plasticity
Authors: Bi Zedong , Chen Guozhang , Yang Dongping , Zhou Yu , Tian Liang
Published: December 2021

How the brain modifies synapses to improve the performance of complicated networks remains one of the biggest mysteries in neuroscience. Canonical models suppose synaptic weights change according to pre- and post-synaptic activities (i.e., local plasticity rules), implementing gradient-descent algorithms. However, the lack of experimental evidence to confirm these models suggests that there may be important ingredients neglected by these models. For example, heterosynaptic plasticity, non-local rules mediated by inter-cellular signaling pathways, and the biological implementation of evolutionary algorithms (EA), another machine-learning paradigm that successfully trains large-scale neural networks, are seldom explored. Here we propose and systematically investigate an EA model of brain learning with non-local rules alone. Specifically, a population of agents are represented by different information routes in the brain, whose task performances are evaluated through gating on individual routes alternatively. The selection and reproduction of agents are realized by dopamine-guided heterosynaptic plasticity. Our EA model provides a framework to re-interpret the biological functions of dopamine, meta-plasticity of dendritic spines, memory replay, and the cooperative plasticity between the synapses within a dendritic neighborhood from a new and coherent aspect. Neural networks trained with the model exhibit analogous dynamics to the brain in cognitive tasks. Our EA model manifests broad competence to train spiking or analog neural networks with recurrent or feedforward architecture. Our EA model also demonstrates its powerful capability to train deep networks with biologically plausible binary weights in MNIST classification and Atari-game playing tasks with performance comparable with continuous-weight networks trained by gradient-based methods. Overall, our work leads to a fresh understanding of the brain learning mechanism unexplored by local rules and gradient-based algorithms.
Using deep convolutional neural networks to forecast spatial patterns of Amazonian deforestation
Authors: Ball James , Petrova Katerina , Coomes David A. , Flaxman Seth
Published: December 2021

Abstract

Tropical forests are subject to diverse deforestation pressures but their conservation is essential to achieve global climate goals. Predicting the location of deforestation is challenging due to the complexity of the natural and human systems involved but accurate and timely forecasts could enable effective planning and on-the-ground enforcement practices to curb deforestation rates. New computer vision technologies based on deep learning can be applied to the increasing volume of Earth observation data to generate novel insights and make predictions with unprecedented accuracy.

Here, we demonstrate the ability of deep convolutional neural networks to learn spatiotemporal patterns of deforestation from a limited set of freely available global data layers, including multispectral satellite imagery, the Hansen maps of historic deforestation (2001-2020) and the ALOS JAXA digital surface model, to forecast future deforestation (2021). We designed four original deep learning model architectures, based on 2D Convolutional Neural Networks (2DCNN), 3D Convolutional Neural Networks (3DCNN), and Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNN) to produce spatial maps that indicate the risk to each forested pixel (~30 m) in the landscape of becoming deforested within the next year. They were trained and tested on data from two ~80,000 km2 tropical forest regions in the Southern Peruvian Amazon.

We found that the networks could predict the likely location of future deforestation to a high degree of accuracy. Our best performing model – a 3DCNN – had the highest pixel-wise accuracy (80-90%) when validated on 2020 deforestation based 2014-2019 training. Visual examination of the forecasts indicated that the 3DCNN network could automatically discern the drivers of forest loss from the input data. For example, pixels around new access routes (e.g. roads) were assigned high risk whereas this was not the case for recent, concentrated natural loss events (e.g. remote landslides).

CNNs can harness limited time-series data to predict near-future deforestation patterns, an important step in using the growing volume of satellite remote sensing data to curb global deforestation. The modelling framework can be readily applied to any tropical forest location and used by governments and conservation organisations to prevent deforestation and plan protected areas.
Inhibition of the sodium-dependent HCO3- transporter SLC4A4, produces a cystic fibrosis-like airway disease phenotype
Authors: Saint-Criq Vinciane , Guequén Anita , Philp Amber , Villanueva Sandra , Apablaza Tábata , Fernández-Moncada Ignacio , Mansilla Agustín , Delpiano Livia , Ruminot Iván , Carrasco Cristian , Gray Michael A. , Flores Carlos A.
Published: December 2021

Bicarbonate secretion is a fundamental process involved in maintaining acid-base homeostasis. Disruption of bicarbonate entry into airway lumen, as has been observed in cystic fibrosis, produces several defects in lung function due to thick mucus accumulation. Bicarbonate is critical for correct mucin deployment and there is increasing interest in understanding its role in airway physiology, particularly in the initiation of lung disease in children affected by cystic fibrosis, in the absence of detectable bacterial infection. The current model of anion secretion in mammalian airways consists of CFTR and TMEM16A as apical anion exit channels, with limited capacity for bicarbonate transport compared to chloride. However, both channels can couple to SLC26A4 anion exchanger to maximise bicarbonate secretion. Nevertheless, current models lack any details about the identity of the basolateral protein(s) responsible for bicarbonate uptake into airway epithelial cells. We report herein that the electrogenic, sodium-dependent, bicarbonate cotransporter, SLC4A4, is expressed in the basolateral membrane of human and mouse airways, and that it’s pharmacological inhibition or genetic silencing reduces bicarbonate secretion. In fully differentiated primary human airway cells, SLC4A4 inhibition induced an acidification of the airways surface liquid and markedly reduced the capacity of cells to recover from an acid load. Studies in the Slc4a4-null mice revealed a previously unreported lung phenotype, characterized by mucus accumulation and reduced mucociliary clearance. Collectively, our results demonstrate that the reduction of SLC4A4 function induced a CF-like phenotype, even when chloride secretion remained intact, highlighting the important role SLC4A4 plays in bicarbonate secretion and mammalian airway function.
Embryo-scale epithelial buckling forms a propagating furrow that initiates gastrulation
Authors: Fierling Julien , John Alphy , Delorme Barthélémy , Torzynski Alexandre , Blanchard Guy , Lye Claire , Malandain Grégoire , Sanson Bénédicte , Étienne Jocelyn , Marmottant Philippe , Quilliet Catherine , Rauzi Matteo
Published: December 2021

Cell apical constriction driven by actomyosin contraction forces is a conserved mechanism during tissue folding in embryo development. While much effort has been made to better understand the molecular mechanisms responsible for apical constriction, it is still not clear if apical actomyosin contraction forces are necessary or sufficient per se to drive tissue folding. To tackle this question, we use the Drosophila embryo model system that forms a furrow on the ventral side, initiating mesoderm internalization. Past computational models support the idea that cell apical contraction forces may not be sufficient and that active or passive cell apico-basal forces may be necessary to drive cell wedging and tissue furrowing. By using 3D computational modelling and in toto embryo image analysis and manipulation, we now challenge this idea and show that embryo-scale force balance of the tissue surface, rather than cell-autonomous shape changes, is necessary and sufficient to drive a buckling of the epithelial surface forming a furrow which propagates and initiates embryo gastrulation.
High content screening and computational prediction reveal viral genes that suppress innate immune response
Authors: Ng Tai L. , Olson Erika J. , Yoo Tae Yeon , Weiss H. Sloane , Koide Yukiye , Koch Peter D. , Rollins Nathan J. , Mach Pia , Meisinger Tobias , Bricken Trenton , Chang Timothy Z. , Molloy Colin , Zürcher Jérôme , Mitchison Timothy J. , Glass John I. , Marks Debora S. , Way Jeffrey C. , Silver Pamela A.
Published: December 2021

Suppression of the host innate immune response is a critical aspect of viral replication. Upon infection, viruses may introduce one or more proteins that inhibit key immune pathways, such as the type I interferon pathway. However, the ability to predict and evaluate viral protein bioactivity on targeted pathways remains challenging and is typically done on a single virus/gene basis. Here, we present a medium-throughput high-content cell-based assay to reveal the immunosuppressive effects of viral proteins. To test the predictive power of our approach, we developed a library of 800 genes encoding known, predicted, and uncharacterized human viral genes. We find that previously known immune suppressors from numerous viral families such as Picornaviridae and Flaviviridae recorded positive responses. These include a number of viral proteases for which we further confirmed that innate immune suppression depends on protease activity. A class of predicted inhibitors encoded by Rhabdoviridae viruses was demonstrated to block nuclear transport, and several previously uncharacterized proteins from uncultivated viruses were shown to inhibit nuclear transport of the transcription factors NF-κB and IRF3. We propose that this pathway-based assay, together with early sequencing, gene synthesis, and viral infection studies, could partly serve as the basis for rapid in vitro characterization of novel viral proteins.

IMPORTANCE

Infectious diseases caused by viral pathogens exacerbate healthcare and economic burdens. Numerous viral biomolecules suppress the human innate immune system, enabling viruses to evade an immune response from the host. Despite our current understanding of viral replications and immune evasion, new viral proteins, including those encoded by uncultivated viruses or emerging viruses, are being unearthed at a rapid pace from large scale sequencing and surveillance projects. The use of medium- and high-throughput functional assays to characterize immunosuppressive functions of viral proteins can advance our understanding of viral replication and possibly treatment of infections. In this study we assembled a large viral gene library from diverse viral families and developed a high content assay to test for inhibition of innate immunity pathways. Our work expands the tools that can rapidly link sequence and protein function, representing a practical step towards early-stage evaluation of emerging and understudied viruses.
Shared regulation and functional relevance of local gene co-expression revealed by single cell analysis
Authors: Ribeiro Diogo M. , Ziyani Chaymae , Delaneau Olivier
Published: December 2021

Most human genes are co-expressed with a nearby gene. Yet, previous studies only reported this extensive local gene co-expression using bulk RNA-seq. Here, we leverage single cell datasets in >85 individuals to identify gene co-expression across cells, unbiased by cell type heterogeneity and benefiting from the co-occurrence of transcription events in single cells. We discover thousands of co-expressed genes in two cell types and (i) compare single cell to bulk RNA-seq in identifying local gene co-expression, (ii) show that many co-expressed genes – but not the majority – are composed of functionally-related genes and (iii) provide evidence that these genes are transcribed synchronously and their co-expression is maintained up to the protein level. Finally, we identify gene-enhancer associations using multimodal single cell data, which reveal that >95% of co-expressed gene pairs share regulatory elements. Our in-depth view of local gene co-expression and regulatory element co-activity advances our understanding of the shared regulatory architecture between genes.
A mean-field toolbox for spiking neuronal network model analysis
Authors: Layer Moritz , Senk Johanna , Essink Simon , van Meegen Alexander , Bos Hannah , Helias Moritz
Published: December 2021

Mean-field theory of spiking neuronal networks has led to numerous advances in our analytical and intuitive understanding of the dynamics of neuronal network models during the past decades. But, the elaborate nature of many of the developed methods, as well as the difficulty of implementing them, may limit the wider neuroscientific community from taking maximal advantage of these tools. In order to make them more accessible, we implemented an extensible, easy-to-use open-source Python toolbox that collects a variety of mean-field methods for the widely used leaky integrate-and-fire neuron model. The Neuronal Network Mean-field Toolbox (NNMT) in its current state allows for estimating properties of large neuronal networks, such as firing rates, power spectra, and dynamical stability in mean-field and linear response approximation, without running simulations on high performance systems. In this article we describe how the toolbox is implemented, show how it is used to calculate neuronal network properties, and discuss different use-cases, such as extraction of network mechanisms, parameter space exploration, or hybrid modeling approaches. Although the initial version of the toolbox focuses on methods that are close to our own past and present research, its structure is designed to be open and extensible. It aims to provide a platform for collecting analytical methods for neuronal network model analysis and we discuss how interested scientists can share their own methods via this platform.