bluuebunny/crossref_metadata_2025 huggingface dataset:
Grapevine leaf size influences vine canopy temperature
Authors: Migicovsky Zoë , Swift Joel F. , Helget Zachary , Klein Laura L. , Ly Anh , Maimaitiyiming Matthew , Woodhouse Karoline , Fennell Anne , Kwasniewski Misha , Miller Allison J. , Chitwood Daniel H. , Cousins Peter
Published: July 2022

Premise

Grapevine leaves have diverse shapes and sizes. Their shape and size is known to be influenced by many factors including genetics, vine phytosanitary status, environment, leaf and vine age, and node position on the shoot. In order to determine the importance of grapevine leaf shape and size to canopy temperature, we examined the relationship in five seedling populations grown in a vineyard in California, USA.

Methods

All of the populations had one parent with compound leaves of theVitis piasezkiitype and each population had a different second parent with non-compound leaves. In previous work, we measured leaf shape and size using 21 homologous landmarks. Here, we paired these morphology data with measurements taken using an infrared thermometer to measure the temperature of the canopy. By recording time of sampling and canopy temperature, we were able to determine which vines were cooler or hotter than expected, using a linear model.

Results

We established a relationship between leaf size and canopy temperature: vines with larger leaves were cooler than expected. In contrast, leaf shape was not strongly correlated with variation in temperature.

Conclusions

Ultimately, these findings indicate that vines with larger leaves may contribute to the reduction of overall vine canopy temperature, but further work is needed to determine if this is due to variation in leaf size, differences in the openness of the canopy, or other related traits.
SNVformer: An Attention-based Deep Neural Network for GWAS Data
Authors: Elmes Kieran , Benavides-Prado Diana , Tan Neşet Özkan , Nguyen Trung Bao , Sumpter Nicholas , Leask Megan , Witbrock Michael , Gavryushkin Alex
Published: July 2022

Despite being the widely-used gold standard for linking common genetic variations to phenotypes and disease, genome-wide association studies (GWAS) suffer major limitations, partially attributable to the reliance on simple, typically linear, models of genetic effects. More elaborate methods, such as epistasis-aware models, typically struggle with the scale of GWAS data. In this paper, we build on recent advances in neural networks employing Transformer-based architectures to enable such models at a large scale. As a first step towards replacing linear GWAS with a more expressive approximation, we demonstrate prediction of gout, a painful form of inflammatory arthritis arising when monosodium urate crystals form in the joints under high serum urate conditions, from Single Nucleotide Variants (SNVs) using a scalable (long input) variant of the Transformer architecture. Furthermore, we show that sparse SNVs can be efficiently used by these Transformer-based networks without expanding them to a full genome. By appropriately encoding SNVs, we are able to achieve competitive initial performance, with an AUROC of 83% when classifying a balanced test set using genotype and demographic information. Moreover, the confidence with which the network makes its prediction is a good indication of the prediction accuracy. Our results indicate a number of opportunities for extension, enabling full genome-scale data analysis using more complex and accurate genotype-phenotype association models.
Oscillatory mechanisms of intrinsic brain networks
Authors: Luo Youjing , Meng Xianghong , Zhou Guangyu , Zhou Jiali , Deng Guangzhi , Li Man , Xu Jie , Li Yiman , Luo Yue-jia , Ai Hui , Zelano Christina Maria , Chen Fuyong , Xu Pengfei
Published: July 2022

Neuroimaging studies of hemodynamic fluctuations have shown specific network-based organization of the brain at rest, yet the neurophysiological underpinning of these networks in human brain remain unclear. Here, we recorded resting-state activities of neuronal populations in the key regions of default mode network (DMN, posterior cingulate cortex and medial prefrontal cortex), frontoparietal network (FPN, dorsolateral prefrontal cortex and inferior parietal lobule), and salience network (SN, anterior insula and dorsal anterior cingulate cortex) from 42 human participants using intracranial electroencephalogram (iEEG). We observed stronger within-network connectivity of the DMN, FPN and SN in broadband iEEG power, stronger phase synchronization within the DMN across theta and alpha bands, and weaker phase synchronization within the FPN in delta, theta and alpha band. We also found positive power correlations in high frequency band (70-170Hz) and negative power correlations in alpha and beta band for FPN-DMN and FPN-SN. Robust negative correlations in DMN-SN were found in alpha, beta and gamma band. These findings provide intracranial electrophysiological evidence in support of the network model for intrinsic organization of human brain and shed light on the way how the brain networks communicate at rest.
An integrated model for predicting KRAS dependency
Authors: Tsai Yihsuan S. , Chareddy Yogitha S. , Price Brandon A. , Parker Joel S. , Pecot Chad V.
Published: July 2022

Background

The clinical approvals of KRAS G12C inhibitors has been a revolutionary advance in precision oncology, but response rates are often modest. To improve patient selection, we developed an integrated model to predict KRAS dependency.

Methods and Findings

By integrating molecular profiles of a large panel of cell lines from the DEMETER2 dataset, we built a binary classifier to predict a tumor’s KRAS dependency. Monte Carlo cross validation via ElasticNet within the training set was used to compare model performance and to tune parameters. The final model was then applied to the validation set. We validated the model with genetic depletion assays and an external dataset of lung cancer cells treated with a G12C inhibitor. We then applied the model to several Cancer Genome Atlas (TCGA) datasets. The final “K20” model contains 20 features, including expression of 19 genes and KRAS mutation status. In the validation cohort, K20 had an AUC of 0.94 and accurately predicted KRAS dependency in both mutant and KRAS wild-type cell lines following genetic depletion. It was also highly predictive across an external dataset of lung cancer lines treated with KRAS G12C inhibition. When applied to TCGA datasets, specific subpopulations such as the invasive subtype in colorectal cancer and copy number high pancreatic adenocarcinoma were predicted to have higher KRAS dependency.

Conclusion

The K20 model has simple yet robust predictive capabilities that may provide a useful tool to select patients with KRAS mutant tumors that are most likely to respond to direct KRAS inhibitors.
A community developed conceptual model for reducing long-term health problems in children with intellectual disability in India
Authors: Nair Manisha , Hazarika Mythili , Kishore M Thomas , Sengupta Nabarun , Sheregar Ganesh , MacGregor Hayley , Wickenden Mary , Kaushik Neel Harit , Saikia Prarthana , Kelley Maureen , Shepperd Sasha
Published: July 2022

Children with intellectual disability (ID) have a higher risk of long-term health problems in adulthood. India has the highest prevalence of ID of any country with 1.6 million under-five children living with the condition. Despite this, compared with other children, this neglected population is excluded from mainstream disease prevention and health promotion programmes. Our objective was to develop an evidence-based conceptual framework for a needs-based inclusive intervention to reduce the risk of communicable and non-communicable diseases among children with ID in India.

From April through to July 2020 we undertook community engagement and involvement activities in ten States in India using a community-based participatory approach, guided by the bio-psycho-social model. We adapted the five steps recommended for the design and evaluation of a public participation process for the health sector.

Seventy stakeholders from ten States contributed to the project: 44 parents and 26 professionals who work with people with ID. We mapped the outputs from two rounds of stakeholder consultations with evidence from systematic reviews to develop a conceptual framework that underpins an approach to develop a cross-sectoral family-centred needs-based inclusive intervention to improve health outcomes for children with ID. A working theory of change (ToC) model delineates a pathway that reflected the priorities of the target population. We discussed the models during a third round of consultations to identify limitations, relevance of the concepts, structural and social barriers that could influence acceptability and adherence, success criteria, and integration with existing health system and service delivery.

There are currently no health promotion programmes focusing on children with ID in India despite the population being at a higher risk of developing comorbid health problems. Therefore, an urgent next step is to test the conceptual model to determine acceptance and effectiveness within the context of socio-economic challenges faced by the children and their families in the country.
The Burden of Gallstone Disease in the United States Population
Authors: Unalp-Arida Aynur , Ruhl Constance E.
Published: July 2022

Background and rationale

Gallstone disease is one of the most common digestive disorders in the United States and leads to significant morbidity, mortality, and health care utilization. We used national survey and claims databases to expand on earlier findings and investigate current trends in the gallstone disease burden in the United States.

Methods

The National Ambulatory Medical Care Survey, National Inpatient Sample, Nationwide Emergency Department Sample, Nationwide Ambulatory Surgery Sample, Vital Statistics of the U.S., Optum Clinformatics® Data Mart, and Centers for Medicare and Medicaid Services Medicare 5% Sample databases were used to estimate claims-based prevalence, medical care including cholecystectomy, and mortality with a primary or other gallstone diagnosis. Rates were age-adjusted (for national databases) and shown per 100,000 population.

Results

Gallstone disease prevalence (claims-based, 2019) was 0.72% among commercial insurance enrollees and 2.09% among Medicare beneficiaries and rose over the previous decade in both groups. Recently, in the U.S. population, gallstone disease contributed to approximately 2.2 million ambulatory care visits, 1.2 million emergency department visits, 625,000 hospital discharges, and 2,000 deaths annually. Women had higher medical care rates with a gallstone disease diagnosis, but mortality rates were higher among men. Hispanics had higher ambulatory care visit and hospital discharge rates compared with Whites, but not mortality rates. Blacks had lower ambulatory care visit and mortality rates, but similar hospital discharge rates compared with whites. During the study period, ambulatory care and emergency department visit rates with a gallstone disease diagnosis rose, while hospital discharge and mortality rates declined. Among commercial insurance enrollees, rates were higher compared with national data for ambulatory care visits and hospitalizations, but lower for emergency department visits. Cholecystectomies performed in the U.S. included 605,000 ambulatory laparoscopic, 280,000 inpatient laparoscopic, and 49,000 inpatient open procedures annually. Among commercial insurance enrollees, rates were higher compared with national data for laparoscopic procedures

Conclusion

The gallstone disease burden in the United States is substantial and increasing, particularly among women, Hispanics, and older adults with laparoscopic cholecystectomy as the mainstay treatment. Current practice patterns should be monitored for better health care access.
COVID-19 vaccine hesitancy in Australian patients with solid organ cancers
Authors: Bain N. , Nguyen M. , Grech L. , Day D. , McCartney A. , Webber K. , Kwok A. , Harris S. , Chau H. , Chan B. , Nott L. , Hamad N. , Tognela A. , Underhill C. , Loe B.S. , Freeman D. , Segelov E.
Published: July 2022

Background

Vaccination is the cornerstone of the global public health response to the COVID-19 pandemic. Excess morbidity and mortality of COVID-19 infection is seen in people with cancer. COVID-19 vaccine hesitancy has been observed in this medically vulnerable population, although associated attitudes and beliefs remain poorly understood.

Patients and Methods

An online cross-sectional survey of people with solid organ cancers was conducted through nine health services across Australia. Demographics, cancer-related characteristics, and vaccine uptake were collected. Perceptions and beliefs regarding COVID-19 vaccination were assessed using the Oxford COVID-19 Vaccine Hesitancy Scale, the Oxford COVID-19 Vaccine Confidence and Complacency Scale, and the Disease Influenced Vaccine Acceptance Scale-6.

Results

Between June and October 2021, 2691 people with solid organ cancers completed the survey. Median age was 62.5 years (SD=11.8; range 19-95), 40.9% were male, 71.3% lived in metropolitan areas, and 90.3% spoke English as their first language. The commonest cancer diagnoses were breast (36.6%), genitourinary (18.6%) and gastrointestinal (18.3%); 59.2% had localized disease and 56.0% were receiving anti-cancer therapy. Most participants (79.7%) had at least one COVID-19 vaccine dose. Vaccine uptake was higher in people who were older, male, metropolitan, spoke English as a first language, and had a cancer diagnosis for more than six months. Vaccine hesitancy was higher in people who were younger, female, spoke English as a non-dominant language and lived in a regional location, and lower in people with genitourinary cancer. Vaccinated respondents were more concerned about being infected with COVID-19 and less concerned about vaccine safety and efficacy.

Conclusions

People with cancer have concerns about acquiring COVID-19, which they balance against vaccine-related concerns about the potential impact on their disease progress and/or treatment. Detailed exploration of concerns in cancer patients provides valuable insights, both for discussions with individual patients and public health messaging for this vulnerable population.
A psychometric validation of the Hospital Anxiety and Depression Scale (HADS) in community-dwelling older adults
Authors: Sivertsen Heidi Emly , Helvik Anne-Sofie , Gjøra Linda , Haugan Gørill
Published: July 2022

Objectives

The Hospital Anxiety and Depression scale (HADS) is commonly used to measure anxiety and depression, but the number of studies validating psychometric properties in older adults are limited. To our knowledge, no previous studies have utilized confirmative factor analyses in community-dwelling older adults, regardless of health conditions. Thus, this study aimed to examine the psychometric properties of HADS in older adults living at home in a large Norwegian city.

Methods

In total, 1190 inhabitants ≥70 (range 70 – 96) years completed the HADS inventory in the population-based Trøndelag Health Study (HUNT); termed “HUNT4 70+” in Trondheim, Norway. Confirmatory factor analyses (CFA) were performed to test the dimensionality, reliability, and construct validity.

Results

The original two-factor-solution (Model-1) revealed only partly a good fit to the present data; however, including a cross-loading for item 6D(“I feel cheerful”) along with a correlated error term between item 2D(“I still enjoy the things I used to enjoy”) and 12D(“I look forward with enjoyment to things”), Model-3 with a two-factor solution demonstrated an acceptable/good fit. Good to acceptable measurement reliability was demonstrated, and construct validity was supported.

Conclusions

The HADS involves some items which are not reliable and valid indicators for the depression construct in this population. Especially item 6 which is problematic. To improve the reliability and validity of HADS rewording of some items is recommended.
Does the size of termite mounds affect chances of fire survival? A study of two southern African mound-building termite (Termitidae) species
Authors: de la Fontaine B. , Edwards S.
Published: July 2022

The effect of fire on insects is an under-researched area of ecology, especially in southern Africa. This study focusing on two termite species, Trinervitermes trinervoides and Amitermes sp., aims to determine whether fire survival in termites is related to mound size. 207 termite mounds were sampled across four sites on the periphery of a semi-urban area in Makhanda, South Africa. Each sampling site consisted of a pair of plots, either recently burnt (< 1 year or ~2 years since fire) or unburnt (> 2 years since fire). Mound type, dimensions, the presence of termites and termite species were recorded. Live mounds were significantly larger than dead mounds at both burnt and unburnt plots. For at least one termite species, there was a strong relationship between survivorship and size class of mounds at burnt plots but not at unburnt plots, suggesting that mound size plays a role in fire survival.
CNS myelination requires VAMP2/3-mediated membrane expansion in oligodendrocytes
Authors: Lam Mable , Takeo Koji , Almeida Rafael G. , Cooper Madeline H. , Wu Kathryn , Iyer Manasi , Kantarci Husniye , Zuchero J. Bradley
Published: July 2022

Myelin is required for rapid nerve signaling and is emerging as a key driver of CNS plasticity and disease. How myelin is built and remodeled remains a fundamental question of neurobiology. Central to myelination is the ability of oligodendrocytes to add vast amounts of new cell membrane, expanding their surface areas by many thousand-fold. However, how oligodendrocytes add new membrane to build or remodel myelin is unknown. Here, we show that CNS myelin membrane addition requires exocytosis mediated by the vesicular SNARE proteins VAMP2/3. Genetic inactivation of VAMP2/3 in myelinating oligodendrocytes caused severe hypomyelination and premature death without overt loss of oligodendrocytes. Through live imaging, we discovered that VAMP2/3-mediated exocytosis drives membrane expansion within myelin sheaths to initiate wrapping and power sheath elongation. In conjunction with membrane expansion, mass spectrometry of oligodendrocyte surface proteins revealed that VAMP2/3 incorporates axon-myelin adhesion proteins that are collectively required to form nodes of Ranvier. Together, our results demonstrate that VAMP2/3-mediated membrane expansion in oligodendrocytes is indispensable for myelin formation, uncovering a cellular pathway that could sculpt myelination patterns in response to activity-dependent signals or be therapeutically targeted to promote regeneration in disease.
TPH2 knockout male rats are aggressive, show less anxiety, and exhibit an altered oxytocin system
Authors: Meng Xianzong , Grandjean Joanes , Sbrini Giulia , Schipper Pieter , Hofwijks Nita , Calabrese Francesca , Homberg Judith
Published: July 2022

The central serotoninergic system is critical for stress responsivity and social behavior, and its dysregulations has been centrally implicated in virtually all neuropsychiatric disorders. Genetic serotonin depletion animal models could provide a tool to elucidate the causes and mechanisms of diseases and to develop new treatment approaches. Previously mice lacking tryptophan hydroxylase 2 (Tph2) have been developed, showing altered behaviors and neurotransmission. However, the effect of congenital serotonin deficiency on emotional and social behavior in rats is still largely unknown, as are the underlying mechanisms. In this study, we used Tph2 knockout (Tph2-/-) male rat model to study how the lack of serotonin in the rat brain affects anxiety-like and social behaviors. Since oxytocin is centrally implicated in these behaviors, we furthermore explored whether effects of Tph2 knockout on behavior would relate to changes in the oxytocin system. We show that Tph2-/- rats display reduced anxiety-like behavior and a high level of aggression in social interactions. In addition, oxytocin receptor expression was increased in the infralimbic and prelimbic cortex, paraventricular nucleus, dorsal raphe nucleus and some subregions of hippocampus, which was paralleled by increased levels of oxytocin in the medial frontal cortex, paraventricular nucleus, but not the dorsal raphe nucleus, central amygdala and hippocampus. In conclusion, our study demonstrated reduced anxiety but exaggerated aggression in Tph2-/- male rats and reveals for the first time a potential involvement of altered oxytocin system function.

SIGNIFICANCE STATEMENT

We explored the changes in behavior and oxytocin system functioning in the tryptophan hydroxylase 2 (Tph2) knockout rat model, lacking serotonin in the brain. This rat model contributes to our understanding of the role of serotonin in psychiatric transdiagnostic features and underlying mechanisms. We found that Tph2 knockout male rats are aggressive, less anxious, and exhibit an altered oxytocin system. The observed changes in oxytocin signaling may lead to a new target for the treatment of diseases caused by genetic serotonin deficiency.
Enhanced brain structure-function tethering in transmodal cortex revealed by high-frequency eigenmodes
Authors: Yang Yaqian , Zheng Zhiming , Liu Longzhao , Zheng Hongwei , Zhen Yi , Zheng Yi , Wang Xin , Tang Shaoting
Published: July 2022

The brain’s structural connectome supports signal propagation between neuronal elements, shaping diverse coactivation patterns that can be captured as functional connectivity. While the link between structure and function remains an ongoing challenge, the prevailing hypothesis is that the structure-function relationship may itself be gradually decoupled along a macroscale functional gradient spanning unimodal to transmodal regions. However, this hypothesis is strongly constrained by the underlying models which may neglect requisite signaling mechanisms. Here, we transform the structural connectome into a set of orthogonal eigenmodes governing frequency-specific diffusion patterns and show that regional structure-function relationships vary markedly under different signaling mechanisms. Specifically, low-frequency eigenmodes, which are considered sufficient to capture the essence of the functional network, contribute little to functional connectivity reconstruction in transmodal regions, resulting in structurefunction decoupling along the unimodal-transmodal gradient. In contrast, high-frequency eigenmodes, which are usually on the periphery of attention due to their association with noisy and random dynamical patterns, contribute significantly to functional connectivity prediction in transmodal regions, inducing gradually convergent structure-function relationships from unimodal to transmodal regions. Although the information in high-frequency eigenmodes is weak and scattered, it effectively enhances the structure-function correspondence by 35% in unimodal regions and 56% in transmodal regions. Altogether, our findings suggest that the structure-function divergence in transmodal areas may not be an intrinsic property of brain organization, but can be narrowed through multiplexed and regionally specialized signaling mechanisms.
Disentangling Hierarchical and Sequential Computations during Sentence Processing
Authors: Zacharopoulos Christos-Nikolaos , Dehaene Stanislas , Lakretz Yair
Published: July 2022

Sentences in natural language have a hierarchical structure, that can be described in terms of nested trees. To compose sentence meaning, the human brain needs to link successive words into complex syntactic structures. However, such hierarchical-structure processing could co-exist with a simpler, shallower, and perhaps evolutionarily older mechanism for local, word-by-word sequential processing. Indeed, classic work from psycholinguistics suggests the existence of such non-hierarchical processing, which can interfere with hierarchical processing and lead to sentence-processing errors in humans. However, such interference can arise from two, non mutually exclusive, reasons: interference between words in working memory, or interference between local versus long-distance word-prediction signals. Teasing apart these two possibilities is difficult based on behavioral data alone. Here, we conducted a magnetoen-cephalography experiment to study hierarchical vs. sequential computations during sentence processing in the human brain. We studied whether the two processes have distinct neural signatures and whether sequential interference observed behaviorally is due to memory-based interference or to competing word-prediction signals. Our results show (1) a large dominance of hierarchical processing in the human brain compared to sequential processing, and (2) neural evidence for interference between words in memory, but no evidence for competing prediction signals. Our study shows that once words enter the language system, computations are dominated by structure-based processing and largely robust to sequential effects; and that even when behavioral interference occurs, it need not indicate the existence of a shallow, local language prediction system.
Cellular contributions to ictal population signals
Authors: Lau Lauren A. , Zhao Zhuoyang , Gomperts Stephen N. , Staley Kevin J. , Lillis Kyle P.
Published: July 2022

Objective

The amplitude of ictal activity is a defining feature of epileptic seizures, but the determinants of this amplitude have not been identified. Clinically, ictal amplitudes are measured electrographically (using e.g. EEG, ECoG, and depth electrodes), but these methods do not enable the assessment of the activity of individual neurons. To identify the cellular determinants of the ictal signal, we measured single cell and population electrical activity and neuronal calcium levels via optical imaging of the genetically encoded calcium indicator (GECI) GCaMP.

Methods

Spontaneous seizure activity was assessed in an awake, behaving mouse model of focal cortical injury and in organotypic hippocampal slice cultures (OHSC), an in vitro preparation from which recurrent seizures can be readily captured. Single cell calcium signals were linked to a range of electrical activities by performing simultaneous GECI-based calcium imaging and whole-cell patch-clamp recordings in spontaneously seizing OHSCs. Neuronal resolution calcium imaging was then performed during spontaneous seizures in vivo and in vitro to quantify the cellular contributions to the population-level calcium signal.

Results

Population signal may increase from three potential sources: 1) increased synchrony, i.e. more co-active neurons, 2) altered active state, from bursts of action potentials and/or paroxysmal depolarizing shifts in membrane potential, and 3) altered subthreshold state, which includes all lower levels of activity. The largest contributor to the signal recorded at seizure onset was increased subthreshold activity, consistent with either barrages of excitatory postsynaptic potentials or sustained membrane depolarization. The relative contribution of synchrony increased as seizures progressed, but cell intrinsic alterations in both the subthreshold and active states remained the largest driver of the ictal signal.

Significance

We introduce here a novel method for the quantification of the relative contributions of inter-versus intra-cellular changes to provide a critical link between single neuron activity and population measures of seizure activity.

Key Points

Neuronal calcium as measured by GCaMP reports a range of membrane depolarizations, from EPSPs to action potential firing and paroxysmal depolarizing shifts

The mean population calcium signal is highly correlated with the electrographic local field potential

Increased calcium signal during seizure onset is largely driven by increased subthreshold calcium within individual neurons

Recruitment of newly active neurons is a minor contributor to the increasing population-level signal during the transition to frank seizure
Virus Infection Causes Dysbiosis to Promote Type 1 Diabetes Onset
Authors: Morse Zachary J. , Simister Rachel L. , Crowe Sean A. , Horwitz Marc S. , Osborne Lisa C.
Published: July 2022

Autoimmune disorders like type 1 diabetes (T1D) are complex diseases caused by numerous factors including both genetic variance and environmental influences. Two such exogenous factors, intestinal microbial composition and enterovirus infection, have been independently associated with T1D onset in both humans and animal models. Since environmental factors rarely work in isolation, we examined the cross-talk between the microbiome and Coxsackievirus B4 (CVB4), an enterovirus that accelerates T1D onset in non-obese diabetic (NOD) mice. We demonstrate that CVB4-infection induced restructuring of the intestinal microbiome prior to T1D onset that was associated with thinning of the mucosal barrier, bacterial translocation to the pancreatic lymph node, and increased detection of circulating and intestinal commensal-reactive antibodies. Notably, the CVB4-induced change in community composition was strikingly similar to that of uninfected NOD mice that spontaneously developed diabetes, thus implying a mutual “diabetogenic” microbiome. Furthermore, fecal microbiome transfer (FMT) of the diabetogenic microbiota from CVB4-infected mice was sufficient to enhance T1D susceptibility in naïve NOD recipients. These findings support a model whereby CVB infection disrupts the microbiome and intestinal homeostasis in a way that promotes activation of autoreactive immune cells and T1D.
Nitrate-dependent salt tolerance mediated by OsNLP4-OsMADS27 module
Authors: Alfatih Alamin , Zhang Jing , Song Ying , Jan Sami Ullah , Zhang Zi-Sheng , Xia Jing-Qiu , Zhang Zheng-Yi , Nazish Tahmina , Wu Jie , Zhao Ping-Xia , Xiang Cheng-Bin
Published: July 2022

Salt stress is a major constraint of plant growth and yield. Nitrogen (N) fertilizers are known to alleviate salt stress. However, the underlying molecular mechanisms remain unclear. Here we show that OsNLP4-OsMADS27 module controls nitrate-dependent salt tolerance in rice. The expression ofOsMADS27is specifically induced by nitrate. TheOsMADS27knockout mutants are more sensitive to salt stress than the wild type, whereas theOsMADS27overexpression lines are more tolerant. Transcriptomic analyses revealed that OsMADS27 controls the expression of a number of known stress-responsive genes as well as those involved in ion homeostasis and antioxidation. We demonstrated that OsMADS27 directly binds to the promoter ofOsHKT1.1andOsSPL7to regulate their expression. Notably,OsMADS27-mediated salt tolerance is nitrate-dependent and positively correlated with nitrate concentration. We further showed that OsNLP4, a nitrate-responsive key regulator in N metabolism and N use efficiency, positively regulates the expression ofOsMADS27by directly binding to the nitrate-responsivecis-element in its promoter, thereby transmitting the nitrate signal toOsMADS27and conferring its nitrate dependence. Our results reveal the role of nitrate-responsive OsNLP4-OsMADS27 module and its downstream target genes in salt tolerance, filling the gap in the molecular mechanism of nitrate-dependent salt tolerance of rice. Moreover,OsMADS27overexpression increased grain yield under salt stress in presence of sufficient nitrate, indicating thatOsMADS27is a promising candidate for the improvement of salt tolerance in rice.
Proteomic profile of nuclei containing p62-positive inclusions in neuronal intranuclear inclusion disease
Authors: Kurihara Masanori , Mano Tatsuo , Eto Fumihiro , Yao Ikuko , Sato Kenichiro , Ohtomo Gaku , Bannai Taro , Shibata Shota , Ishiura Hiroyuki , Ikemura Masako , Matsubara Tomoyasu , Morishima Maho , Saito Yuko , Murayama Shigeo , Toda Tatsushi , Setou Mitsutoshi , Iwata Atsushi
Published: July 2022

Neuronal intranuclear inclusion disease (NIID) is a neurodegenerative disease characterized by eosinophilic hyaline intranuclear inclusions in the neurons, glial cells, and other somatic cells. Although CGG repeat expansions in NOTCH2NLC have been identified in most East Asian patients with NIID, the pathophysiology of NIID remains unclear. Intranuclear inclusions are the pathological hallmark of NIID. Previously, immunohistochemistry has revealed that intranuclear inclusions are ubiquitin-, p62-, and SUMO-1-positive, suggesting the possible alteration of the ubiquitin-proteasomal protein degradation system in the nuclei with inclusions. However, the molecular mechanisms within these nuclei remain unclear. Herein, we analyzed the proteomic profile of nuclei with p62-positive inclusions in NIID with CGG repeat expansion in NOTCH2NLC to discover the proteins involved in the NIID pathophysiology. We used fluorescence-activated cell sorting and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to quantify each protein identified in the nuclei with p62-positive inclusions. The distribution of increased proteins in the autopsy brain samples from three NIID patients was confirmed via immunofluorescence. Overall, 526 proteins were identified, of which 243 were consistently quantified using MS. A 1.4-fold increase was consistently observed for 20 proteins in nuclei with p62-positive inclusions compared to those without. Fifteen proteins identified with medium or high confidence in the LC-MS/MS analysis were further evaluated. Gene ontology enrichment analysis showed enrichment of several terms, including poly(A) RNA binding, nucleosomal DNA binding, and protein binding. Immunofluorescence studies confirmed that the fluorescent intensities of increased RNA-binding proteins identified by proteomic analysis, namely hnRNP A3, hnRNP A2/B1, and hnRNP C1/C2, were higher in the nuclei with p62-positive inclusions than those without; however, they were not confined to the intranuclear inclusions. We identified several increased proteins in nuclei with p62-positive inclusions. These data can form the basis for understanding the pathophysiology of NIID.
Discovery of a monomeric green fluorescent protein sensor for chloride by structure-guided bioinformatics
Authors: Peng Weicheng , Maydew Caden , Kam Hiu , Lynd Jacob , Tutol Jasmine N. , Phelps Shelby M. , Abeyrathna Sameera , Meloni Gabriele , Dodani Sheel C.
Published: July 2022

Chloride is an essential anion for all forms of life. Beyond electrolyte balance, an increasing body of evidence points to new roles for chloride in normal physiology and disease. Over the last two decades, this understanding has been advanced by chloride-sensitive fluorescent proteins for imaging applications in living cells. To our surprise, these sensors have been primarily engineered from the green fluorescent protein (GFP) found in the jellyfishAequorea victoria. However, the GFP family has a rich sequence space that could already encode for new sensors with desired properties, thereby minimizing protein engineering efforts and accelerating biological applications. To efficiently sample this space, we present and validate a stepwise bioinformatics strategy focused first on the chloride binding pocket and second on a monomeric oligomerization state. Using this, we identified GFPxm163 from GFPxm found in the jellyfishAequorea macrodactyla. In vitrocharacterization shows that the binding of chloride as well as bromide, iodide, and nitrate rapidly tunes the ground state chromophore equilibrium from the phenolate to the phenol state generating a pH-dependent, turn-off fluorescence response. Furthermore, live-cell fluorescence microscopy reveals that GFPxm163 provides a reversible, yet indirect readout of chloride transport via iodide exchange. With this demonstration, we anticipate that the paring of bioinformatics with protein engineering methods will provide an efficient methodology to discover and design new chloride-sensitive fluorescent proteins for cellular applications.

Abstract Figure
Micropatterned Organoids Enable Modeling of the Earliest Stages of Human Cardiac Vascularization
Authors: Abilez Oscar J. , Yang Huaxiao , Tian Lei , Wilson Kitchener D. , Lyall Evan H. , Shen Mengcheng , Bhoi Rahulkumar , Zhuge Yan , Jia Fangjun , Wo Hung Ta , Zhou Gao , Guan Yuan , Aldana Bryan , Obal Detlef , Peltz Gary , Zarins Christopher K. , Wu Joseph C.
Published: July 2022

Although model organisms have provided insight into the earliest stages of cardiac vascularization, we know very little about this process in humans. Here we show that spatially micropatterned human pluripotent stem cells (hPSCs) enablein vitromodeling of this process, corresponding to the first three weeks ofin vivohuman development. Using four hPSC fluorescent reporter lines, we create cardiac vascular organoids (cVOs) by identifying conditions that simultaneously give rise to spatially organized and branched vascular networks within endocardial, myocardial, and epicardial cells. Using single-cell transcriptomics, we show that the cellular composition of cVOs resembles that of a 6.5 post-conception week (PCW) human heart. We find that NOTCH and BMP pathways are upregulated in cVOs, and their inhibition disrupts vascularization. Finally, using the same vascular-inducing factors to create cVOs, we produce hepatic vascular organoids (hVOs). This suggests there is a conserved developmental program for creating vasculature within different organ systems.

Graphic Abstract
Development of Polymer/DNA Polyplexes System for Nucleic Acid Delivery to the Multicellular OrganismC. elegans
Authors: Yenisert Ferhan , Bayram Nazende Nur , Köseoğlu Beyza Nur , Topuzoğulları Murat , Isoglu Sevil Dincer , Kaplan Oktay I.
Published: July 2022

Gene therapy studies have been of great importance in the elimination of genetic diseases, and the capability of the CRISPR/Cas9 genome editing technique to correct genetic defects has shown great promise. As DNA-based Cas9 nuclease delivery is preferable because of its low cost and higher stability, effective vector-based CRISPR/Cas9 administration is urgently needed. Here, we used the multicellular organismCaenorhabditis elegansto optimize the polymer-mediated DNA delivery system to generate mutants with CRISPR/Cas9. Toward this end, the cationically quaternized polymer of POEGMA-b-P4VP (POEGMA-b-QP4VP) as a carrier of CRISPR/Cas9 components was first synthesized, followed by the formation of plasmid DNA-polymer complex called polyplexes.1H NMR, Zeta-Sizer, Scanning Electron Microscopy (SEM) analysis, and gel retardation experiments confirmed the polyplexes formation, including pRF4 (Roller) and sgRNAdpy-10, which were then incubated withC. elegans. The polymer-mediated delivery system facilitated the generation of transgenic Roller animals and heritable Dumpy mutants with CRISPR/Cas9. Our study for the first time demonstrated optimized administration of CRISPR/Cas 9 components toC. elegans.
Comprehensive collection and prediction of ABC transmembrane protein structures in the AI era of structural biology
Authors: Tordai Hedvig , Suhajda Erzsébet , Sillitoe Ian , Nair Sreenath , Váradi Mihály , Hegedűs Tamás
Published: July 2022

The number of unique transmembrane (TM) protein structures doubled in the last four years that can be attributed to the revolution of cryo-electron microscopy. In addition, AlphaFold2 (AF2) also provided a large number of predicted structures with high quality. However, if a specific protein family is the subject of a study, collecting the structures of the family members is highly challenging in spite of existing general and protein domain-specific databases. Here, we demonstrate this and assess the applicability and usability of automatic collection and presentation of protein structures via the ABC protein superfamily. Our pipeline identifies and classifies transmembrane ABC protein structures using PFAM search and also aims to determine their conformational states based on special geometric measures, conftors. Since the AlphaFold database contains structure predictions only for single polypeptide chains, we performed AF2-Multimer predictions for human ABC half transporters functioning as dimers. Our AF2 predictions warn of possibly ambiguous interpretation of some biochemical data regarding interaction partners and call for further experiments and experimental structure determination. We made our predicted ABC protein structures available through a web application, and we joined the 3D-Beacons Network to reach the broader scientific community through platforms such as PDBe-KB.
Comparison of different models in predicting habitat suitability of rare species in Uzbekistan: 8 rare Tulipa species case-study
Authors: Rustamov Khondamir
Published: July 2022

Species distribution models (SDMs) have become an essential tool in conservational biology, biogeography and ecology. But there is no consequence in what SDM method is the most efficient in predicting suitable habitat distribution of rare species. To explore this issue, we chose 8 rareTulipaspecies in Uzbekistan as case study to test 8 common Machine Learning (GLM, GBM, MARS, CTA, SRE, FDA, RF, MaxEnt) and Deep Neural Network (DNN) SDM models, using three different methods of pseudo-absence data generation (random sampling, random sampling with exclusion buffer, random sampling with environmental profiling). To compare the effectiveness of each model 3 common metrics (Area under ROC (AUC), True skill statistics (TSS) and Cohen’s Kappa (K)) were used. We have found that RF and GBM combined with RSEP strategy are superior to other modeling methods.
Workflow sharing with automated metadata validation and test execution to improve the reusability of published workflows
Authors: Suetake Hirotaka , Fukusato Tsukasa , Igarashi Takeo , Ohta Tazro
Published: July 2022

Background

Many open-source workflow systems have made bioinformatics data analysis procedures portable. Sharing these workflows provides researchers easy access to high-quality analysis methods without the requirement of computational expertise. However, published workflows are not always guaranteed to be reliably reusable. Therefore, a system is needed to lower the cost of sharing workflows in a reusable form.

Results

We introduce Yevis, a system to build a workflow registry that automatically validates and tests workflows to be published. The validation and test are based on the requirements we defined for a workflow being reusable with confidence. Yevis runs on GitHub and Zenodo and allows workflow hosting without the need of dedicated computing resources. A Yevis registry accepts workflow registration via a GitHub pull request, followed by an automatic validation and test process for the submitted workflow. As a proof of concept, we built a registry using Yevis to host workflows from a community to demonstrate how a workflow can be shared while fulfilling the defined requirements.

Conclusions

Yevis helps in the building of a workflow registry to share reusable workflows without requiring extensive human resources. By following Yevis’s workflow-sharing procedure, one can operate a registry while satisfying the reusable work-flow criteria. This system is particularly useful to individuals or communities that want to share workflows but lacks the specific technical expertise to build and maintain a workflow registry from scratch.
Latent Interacting Variable-Effects Modeling of Gut Microbiome Multi-Omics in Inflammatory Bowel Disease
Authors: Munoz Javier. E. , Brubaker Douglas. K.
Published: July 2022

Latent Interacting Variable Effects (LIVE) modeling is a framework to integrate different types of microbiome multi-omics data by combining latent variables from single-omic models into a structured meta-model to determine discriminative, interacting multi-omics features driving disease status. We implemented and tested LIVE modeling in publicly available metagenomics and metabolomics datasets from Crohn’s Disease and Ulcerative Colitis patients. Here, LIVE modeling reduced the number of feature correlations from the original data set for CD and UC to tractable numbers and facilitated prioritization of biological associations between microbes, metabolites, enzymes and IBD status through the application of stringent thresholds on generated inferential statistics. We determined LIVE modeling confirmed previously reported IBD biomarkers and uncovered potentially novel disease mechanisms in IBD. LIVE modeling makes a distinct and complementary contribution to the current methods to integrate microbiome data to predict IBD status because of its flexibility to adapt to different types of microbiome multi-omics data, scalability for large and small cohort studies via reliance on latent variables and dimensionality reduction, and the intuitive interpretability of the linear meta-model integrating -omic data types. The results of LIVE modeling and the biological relationships can be represented in networks that connect local correlation structure of single omic data types with global community and omic structure in the latent variable VIP scores. This model arises as novel tool that allows researchers to be more selective about omic feature interaction without disrupting the structural correlation framework provided by sPLS-DA interaction effects modeling. It will lead to form testable hypothesis by identifying potential and unique interactions between metabolome and microbiome that must be considered for future studies.

AUTHOR SUMMARY

Latent Interacting Variable Effects (LIVE) modeling integrates microbiome multiomics features by encoding them in a set of latent variables (LVs) from single-omic sparse Partial Lease Squares models, and then combine these LVs into structured metamodel to determine the most discriminative features driving IBD. We used publicly available metagenomic and metabolomics data from Crohn’s Disease and Ulcerative Colitis patients to develop LIVE modeling. LIVE modeling reduced data dimensionality efficiently and identified statistical interactions among microbiome multi-omics data, which can be visualized as a mineable network data structure. LIVE modeling confirmed features previously reported and revealed novel microbiome interactions in IBD. LIVE offers a flexible framework for multi-omic modeling that may aid in interpretation of complex microbiome datasets.
Accurate simultaneous sequencing of genetic and epigenetic bases in DNA
Authors: Füllgrabe Jens , Gosal Walraj S , Creed Páidí , Liu Sidong , Lumby Casper K , Morley David J , Ost Tobias W B , Vilella Albert J , Yu Shirong , Bignell Helen , Burns Philippa , Charlesworth Tom , Fu Beiyuan , Fordham Howerd , Harding Nick , Gandelman Olga , Golder Paula , Hodson Christopher , Li Mengjie , Lila Marjana , Liu Yang , Mason Joanne , Mellad Jason , Monahan Jack , Nentwich Oliver , Palmer Alexandra , Steward Michael , Taipale Minna , Vandomme Audrey , San-Bento Rita Santo , Singhal Ankita , Vivian Julia , Wójtowicz Natalia , Williams Nathan , Walker Nicolas J , Wong Nicola C H , Yalloway Gary , Holbrook Joanna D , Balasubaramanian Shankar
Published: July 2022

DNA comprises molecular information stored via genetic bases (G, C, T, A) and also epigenetic bases, principally 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC). Both genetic and epigenetic information are vital to our understanding of biology and disease states. Most DNA sequencing approaches address either genetics or epigenetics and thus capture incomplete information. Methods widely used to detect epigenetic DNA bases typically fail to capture common C-to-T mutations or distinguish 5mC from 5hmC. Here, we present a single-base-resolution sequencing methodology that will simultaneously sequence complete genetics and complete epigenetics in a single workflow. The approach is non-destructive to DNA and provides a digital readout of bases, which we exemplify by simultaneous sequencing of G, C, T, A, 5mC and 5hmC; 6-Letter sequencing. We demonstrate sequencing of human genomic DNA and also cell-free DNA taken from a blood sample of a cancer patient. The approach is accurate, requires low DNA input and has a simple workflow and analysis pipeline. We envisage it will be versatile across many applications in life sciences.