bluuebunny/crossref_metadata_2025 huggingface dataset:
mebipred: identifying metal-binding potential in protein sequence
Authors: Aptekmann A A , Buongiorno J , Giovannelli D , Glamoclija M , Ferreiro D U , Bromberg Y
Published: May 2022

Motivation

metal-binding proteins have a central role in maintaining life processes. Nearly one-third of known protein structures contain metal ions that are used for a variety of needs, such as catalysis, DNA/RNA binding, protein structure stability, etc. Identifying metal-binding proteins is thus crucial for understanding the mechanisms of cellular activity. However, experimental annotation of protein metal-binding potential is severely lacking, while computational techniques are often imprecise and of limited applicability.

Results

we developed a novel machine learning-based method, mebipred, for identifying metal-binding proteins from sequence-derived features. This method is over 80% accurate in recognizing proteins that bind metal ion-containing ligands; the specific identity of 11 ubiquitously present metal ions can also be annotated. mebipred is reference-free, i.e. no sequence alignments are involved, and is thus faster than alignment-based methods; it is also more accurate than other sequence-based prediction methods. Additionally, mebipred can identify protein metal-binding capabilities from short sequence stretches, e.g. translated sequencing reads, and, thus, may be useful for the annotation of metal requirements of metagenomic samples. We performed an analysis of available microbiome data and found that ocean, hot spring sediments and soil microbiomes use a more diverse set of metals than human host-related ones. For human microbiomes, physiological conditions explain the observed metal preferences. Similarly, subtle changes in ocean sample ion concentration affect the abundance of relevant metal-binding proteins. These results highlight mebipred’s utility in analyzing microbiome metal requirements.

Availability and implementation

mebipred is available as a web server at services.bromberglab.org/mebipred and as a standalone package at https://pypi.org/project/mymetal/.

Supplementary information

Supplementary data are available at Bioinformatics online.
NanoSplicer: accurate identification of splice junctions using Oxford Nanopore sequencing
Authors: You Yupei , Clark Michael B , Shim Heejung
Published: May 2022

Motivation

Long-read sequencing methods have considerable advantages for characterizing RNA isoforms. Oxford Nanopore sequencing records changes in electrical current when nucleic acid traverses through a pore. However, basecalling of this raw signal (known as a squiggle) is error prone, making it challenging to accurately identify splice junctions. Existing strategies include utilizing matched short-read data and/or annotated splice junctions to correct nanopore reads but add expense or limit junctions to known (incomplete) annotations. Therefore, a method that could accurately identify splice junctions solely from nanopore data would have numerous advantages.

Results

We developed ‘NanoSplicer’ to identify splice junctions using raw nanopore signal (squiggles). For each splice junction, the observed squiggle is compared to candidate squiggles representing potential junctions to identify the correct candidate. Measuring squiggle similarity enables us to compute the probability of each candidate junction and find the most likely one. We tested our method using (i) synthetic mRNAs with known splice junctions and (ii) biological mRNAs from a lung-cancer cell-line. The results from both datasets demonstrate NanoSplicer improves splice junction identification, especially when the basecalling error rate near the splice junction is elevated.

Availability and implementation

NanoSplicer is available at https://github.com/shimlab/NanoSplicer and archived at https://doi.org/10.5281/zenodo.6403849. Data is available from ENA: ERS7273757 and ERS7273453.

Supplementary information

Supplementary data are available at Bioinformatics online.
A decade of discovery: the stunning progress of premature ovarian insufficiency research in China
Authors: Wang Xiaoyan , Chen Zi-Jiang
Published: May 2022

Premature ovarian insufficiency (POI) is one of the key aspects of ovarian infertility. Due to early cession of ovarian function, POI imposes great challenges on the physiological and psychological health of women and becomes a common cause of female infertility. In the worldwide, there has been a special outpouring of concern for about 4 million reproductive-aged women suffering from POI in China. Driven by advances in new technologies and efforts invested by Chinses researchers, understanding about POI has constantly been progressing over the past decade. Here, we comprehensively summarize and review the landmark development and achievements from POI studies in China spanning 2011–2020, which aims to provide key insights from bench to bedside.
Multiomics analysis of male infertility
Authors: Wu Xiaolong , Zhou Liwei , Shi Jie , Cheng C Yan , Sun Fei
Published: May 2022

Infertility affects 8–12% of couples globally, and the male factor is a primary cause in ~50% of couples. Male infertility is a multifactorial reproductive disorder, which can be caused by paracrine and autocrine factors, hormones, genes, and epigenetic changes. Recent studies in rodents and most notably in humans using multiomics approach have yielded important insights into understanding the biology of spermatogenesis. Nonetheless, the etiology and pathogenesis of male infertility are still largely unknown. In this review, we summarized and critically evaluated findings based on the use of advanced technologies to compare normal and obstructive azoospermic versus nonobstructive azoospermic men, including whole-genome bisulfite sequencing, single-cell RNA-seq, whole-exome sequencing, and transposase-accessible chromatin using sequencing. It is obvious that the multiomics approach is the method of choice for basic research and clinical studies including clinical diagnosis of male infertility.
Advances in haploid embryonic stem cell research
Authors: Liu Chao , Li Wei
Published: May 2022

Haploid embryonic stem cells are embryonic stem cells of a special type. Their nuclei contain one complete set of genetic material, and they are capable of self-renewal and differentiation. The emergence of haploid embryonic stem cells has aided research in functional genomics, genetic imprinting, parthenogenesis, genetic screening, and somatic cell nuclear transfer. This article reviews current issues in haploid stem cell research based on reports published in recent years and assesses the potential applications of these cells in somatic cell nuclear transfer, genome imprinting, and parthenogenesis.
Responsible governance of human germline genome editing in China
Authors: Peng Yaojin , Lv Jianwei , Ding Lulu , Gong Xia , Zhou Qi
Published: May 2022

Considerable improvements have been made to gene editing technology, which has been increasingly applied to research involving humans. Nevertheless, human heritable germline genome editing is associated with a series of potential ethical, legal, and social risks, which have generated major controversies and discussions worldwide, especially after the “gene-edited babies” incident. Influenced by this incident, China has realized the importance of ethical governance in the field of life science and technology, has accelerated legislative and policy efforts in this field, and has gradually moved toward the direction of “precautionary” ethical governance. Black letter analysis, big data public opinion analysis, and other research methods are used in this paper. This paper explores the scientific background, ethical debates, and latest developments regarding China’s regulatory framework for human germline gene editing after the “gene-edited babies” controversy and provides several recommendations on the future governance system of human germline gene editing in China. This paper argues that in recent years, the ethics governance of germline genome editing in China has been accelerated and great changes have been made. However, the regulatory system for germline genome editing requires further improvement in three aspects: coordination of legislation and agencies, establishment of an ethics review system at high levels, and public participation and education.
Homeostatic feelings and the biology of consciousness
Authors: Damasio Antonio , Damasio Hanna
Published: May 2022

In a new theory of consciousness, Antonio and Hanna Damasio argue that interoception and the generation of homeostatic feelings are crucial to understanding how conscious states emerge.
Longitudinal changes of white matter microstructure following traumatic brain injury in U.S. military service members
Authors: Yeh Ping-Hong , Lippa Sara. M. , Brickell Tracey A. , Ollinger John , French Louis M. , Lange Rael T.
Published: May 2022

The purpose of this study was to analyze quantitative diffusion tensor imaging measures across the spectrum of traumatic brain injury severity and evaluate their trajectories in military service members. Participants were 96 U.S. military service members and veterans who had sustained a mild traumatic brain injury [including complicated mild traumatic brain injury (n = 16) and uncomplicated mild traumatic brain injury (n = 68)], moderate-severe traumatic brain injury (n = 12), and controls (with or without orthopaedic injury, n = 39). All participants had been scanned at least twice, with some receiving up to five scans. Both whole brain voxel-wise analysis and tract-of-interest analysis were applied to assess the group differences of diffusion tensor imaging metrics, and their trajectories between time points of scans and days since injury. Linear mixed modelling was applied to evaluate cross-sectional and longitudinal diffusion tensor imaging metrics changes within and between groups using both tract-of-interest and voxel-wise analyses. Participants with moderate to severe traumatic brain injury had larger white matter disruption both in superficial subcortical and deep white matter, mainly over the anterior part of cerebrum, than those with mild traumatic brain injury, both complicated and uncomplicated, and there was no evidence of recovery over the period of follow-ups in moderate-severe traumatic brain injury, but deterioration was possible. Participants with mild traumatic brain injury had white matter microstructural changes, mainly in deep central white matter over the posterior part of cerebrum, with more spatial involvement in complicated mild traumatic brain injury than in uncomplicated mild traumatic brain injury and possible brain repair through neuroplasticity, e.g. astrocytosis with glial processes and glial scaring. Our results did not replicate ‘V-shaped’ trajectories in diffusion tensor imaging metrics, which were revealed in a previous study assessing the sub-acute stage of brain injury in service members and veterans following military combat concussion. In addition, non-traumatic brain injury controls, though not demonstrating any evidence of sustaining a traumatic brain injury, might have transient white matter changes with recovery afterward. Our results suggest that white matter integrity following a remote traumatic brain injury may change as a result of different underlying mechanisms at the microstructural level, which can have a significant consequence on the long-term well beings of service members and veterans. In conclusion, longitudinal diffusion tensor imaging improves our understanding of the mechanisms of white matter microstructural changes across the spectrum of traumatic brain injury severity. The quantitative metrics can be useful as guidelines in monitoring the long-term recovery.
Machine learning-based prediction of motor status in glioma patients using diffusion MRI metrics along the corticospinal tract
Authors: Shams Boshra , Wang Ziqian , Roine Timo , Aydogan Dogu Baran , Vajkoczy Peter , Lippert Christoph , Picht Thomas , Fekonja Lucius S.
Published: May 2022

Along tract statistics enables white matter characterization using various diffusion MRI metrics. These diffusion models reveal detailed insights into white matter microstructural changes with development, pathology and function. Here, we aim at assessing the clinical utility of diffusion MRI metrics along the corticospinal tract, investigating whether motor glioma patients can be classified with respect to their motor status. We retrospectively included 116 brain tumour patients suffering from either left or right supratentorial, unilateral World Health Organization Grades II, III and IV gliomas with a mean age of 53.51 ± 16.32 years. Around 37% of patients presented with preoperative motor function deficits according to the Medical Research Council scale. At group level comparison, the highest non-overlapping diffusion MRI differences were detected in the superior portion of the tracts’ profiles. Fractional anisotropy and fibre density decrease, apparent diffusion coefficient axial diffusivity and radial diffusivity increase. To predict motor deficits, we developed a method based on a support vector machine using histogram-based features of diffusion MRI tract profiles (e.g. mean, standard deviation, kurtosis and skewness), following a recursive feature elimination method. Our model achieved high performance (74% sensitivity, 75% specificity, 74% overall accuracy and 77% area under the curve). We found that apparent diffusion coefficient, fractional anisotropy and radial diffusivity contributed more than other features to the model. Incorporating the patient demographics and clinical features such as age, tumour World Health Organization grade, tumour location, gender and resting motor threshold did not affect the model’s performance, revealing that these features were not as effective as microstructural measures. These results shed light on the potential patterns of tumour-related microstructural white matter changes in the prediction of functional deficits.
The PxIxIT motif of the RCAN3 inhibits angiogenesis and tumor progression in Triple Negative breast cancer in immunocompetent mice
Authors: Biçer Atilla , López-Henares Patricia , Molero-Magariño Marta , Feu-Llauradó Andrea , Sabariego-Navarro Miguel , Bayod Sergi , Padilla Laura , Taco Mª Rosario , Larriba Sara , Pérez-Riba Mercè , Serrano-Candelas Eva
Published: May 2022

RCAN proteins are endogenous regulators of the calcineurin-cytosolic nuclear factor of activated T cells (CN-NFATc) pathway that bind CN through similar conserved motifs PxIxIT and LxVP of the NFATc family. RCAN1 and RCAN3 protein levels were reported to correlate with overall survival of breast cancer patients. We additionally provided supporting results about RCAN3 role on cancer showing that overexpression of the native PxIxIT sequence of RCAN3-derived R3 peptide (PSVVVH, EGFP-R3178–210) dramatically inhibits tumor growth and tumor angiogenesis in an orthotopic mouse model of Triple Negative Breast Cancer (TNBC) in nude mice. On the other hand, RCAN3 protein and its derived peptide EGFP-R3178–210 bind to CN and inhibit NFAT-mediated cytokine gene expression without affecting CN phosphatase activity suggesting that RCAN3 and EGFP-R3178–210 peptide have tumor suppressor and immunosuppressant activity. Due to the known relationship between tumor development and immune system, as well as the relevance of CN-NFATc in the regulation of the immune system, in the present study we decided to assess the effect of EGFP-R3178–210 peptide in an orthotopic syngeneic TNBC mouse model, in order to ensure that the role of RCAN3 as immunosuppressant do not override its tumor suppressor activity. Our results evidence that EGFP-R3178–210 peptide displays an inhibitory potential on tumor growth and tumor angiogenesis similar to those obtained in the previous orthotopic TNBC model. These results highlight the importance of the RCAN3 peptide as a tumor suppressor protein and totally complement our previous results, indicating that this antitumor activity role is maintained in the presence of a complete functional immune system.
Low G9a expression is a tumor progression factor of colorectal cancer via IL-8 promotion
Authors: Ichikawa Yoshitoshi , Takahashi Hidekazu , Chinen Yoshinao , Arita Asami , Sekido Yuki , Hata Tsuyoshi , Ogino Takayuki , Miyoshi Norikatsu , Uemura Mamoru , Yamamoto Hirofumi , Mizushima Tsunekazu , Doki Yuichiro , Eguchi Hidetoshi
Published: May 2022

The histone methyltransferase G9a is expressed in various types of cancer cells, including colorectal cancer (CRC) cells. Interleukin 8 (IL)-8, also known as C-X-C motif chemokine ligand 8 (CXCL8), is a chemokine that plays a pleiotropic function in the regulation of inflammatory responses and cancer development. Here, we examined the relationship between G9a and IL-8 and the clinical relevance of this association. We immunohistochemically analyzed 235 resected CRC samples to correlate clinical features. Samples with high G9a expression had better overall survival and relapse-free survival than those with low G9a expression. Univariate and multivariate analyses demonstrated that low G9a expression remained a significant independent prognostic factor for increased disease recurrence and decreased survival (P < 0.05). G9a was expressed at high levels in commercially available CRC cell lines HCT116 and HT29. Knockdown of G9a by siRNA, shRNA or the G9a-specific inhibitor BIX01294 upregulated IL-8 expression. The number of spheroids was significantly increased in HCT116 cells with stably suppressed G9a expression, and the number of spheroids was significantly decreased in HCT116 cells with stably suppressed IL-8 expression. Thus, the suppression of IL-8 by G9a may result in a better prognosis in CRC cases with high G9a expression. Furthermore, G9a may suppress cancer stemness and increase chemosensitivity by controlling IL-8. Therefore, G9a is a potential novel marker for predicting CRC prognosis, and therapeutic targeting of G9a in CRC should be controversial.
Auditory cortical plasticity after cochlear implantation in asymmetric hearing loss is related to spatial hearing: a PET H215O study
Authors: Karoui Chadlia , Strelnikov Kuzma , Payoux Pierre , Salabert Anne-Sophie , James Chris J , Deguine Olivier , Barone Pascal , Marx Mathieu
Published: May 2022

In asymmetric hearing loss (AHL), the normal pattern of contralateral hemispheric dominance for monaural stimulation is modified, with a shift towards the hemisphere ipsilateral to the better ear. The extent of this shift has been shown to relate to sound localization deficits. In this study, we examined whether cochlear implantation to treat postlingual AHL can restore the normal functional pattern of auditory cortical activity and whether this relates to improved sound localization. The auditory cortical activity was found to be lower in the AHL cochlear implanted (AHL-CI) participants. A cortical asymmetry index was calculated and showed that a normal contralateral dominance was restored in the AHL-CI patients for the nonimplanted ear, but not for the ear with the cochlear implant. It was found that the contralateral dominance for the nonimplanted ear strongly correlated with sound localization performance (rho = 0.8, P < 0.05). We conclude that the reorganization of binaural mechanisms in AHL-CI subjects reverses the abnormal lateralization pattern induced by the deafness, and that this leads to improved spatial hearing. Our results suggest that cochlear implantation enables the reconstruction of the cortical mechanisms of spatial selectivity needed for sound localization.
The role of rivaroxaban in eosinophilic myocarditis
Authors: Bodagh Carla , Sawh Chris , Garg Pankaj
Published: May 2022

This is a case of eosinophilic myocarditis which had large left-ventricular thrombus seen on echocardiography and cardiac magnetic resonance imaging which was successfully treated with a highly selective direct Factor Xa inhibitor—rivaroxaban.
‘Here comes the story of the Hurricane’: a case report of AL cardiac amyloidosis and myocardial bridging
Authors: Cappannoli Luigi , Ciliberti Giuseppe , Restivo Attilio , Palumbo Pierpaolo , D’Alò Francesco , Sanna Tommaso , Crea Filippo , D’Amario Domenico
Published: May 2022

Background

Cardiac amyloidosis (CA) is a rapidly progressive infiltrative cardiomyopathy, whose role is emerging as a not-so-rare disorder leading to heart failure (HF). Myocardial bridge (MB) is the most common inborn coronary artery variant, and its clinical relevance is still matter of debate. The exceptional coexistence of these two conditions could accelerate disease progression and worsen the already compromised clinical conditions.

Case summary

We present the case of a 76-year-old female patient experiencing relapsing HF decompensation and presenting to our centre with dyspnoea at rest and severe peripheral congestion. Echocardiogram showed severe concentric hypertrophy, severe biventricular contractile dysfunction, and third-degree diastolic dysfunction. Coronary angiography excluded epicardial atherosclerotic disease, though displaying a long intramyocardial course of left anterior descending artery. Physiological invasive test was achieved in terms of instantaneous wave-free ratio (iFR), both at baseline and after inotropic and chronotropic stimuli, and attested haemodynamic significance. Concurrently, the diagnostic flow chart for CA was accomplished, by means of both invasive (periumbilical fat biopsy, bone marrow aspiration) and non-invasive tests (99mTc-diphosphonate scintigraphy, serum-urine immunofixation) that confirmed the suspect of primary amyloidosis. Acute HF therapy was personalized according to the singularity of the case, avoiding both nitrates and beta-blockers, then first cycle of chemotherapy was started.

Discussion

Our clinical case shows a unique interaction between infiltrative cardiomyopathy and coronary artery abnormality. Amyloidosis can contribute to the ischaemic burden of the MB and this may, in turn, abbreviate the path to HF decompensation.
Effectiveness of methotrexate as a second-line treatment for cardiac sarcoidosis assessed via 18F-FDG PET: a case report
Authors: Dotare Taishi , Maeda Daichi , Matsue Yuya , Minamino Tohru
Published: May 2022

Background

Although methotrexate has been widely used as a second-line therapy for cardiac sarcoidosis (CS), it is not clear if it has a direct anti-inflammatory effect.

Case summary

A 65-year-old man presented to our hospital with symptomatic ventricular tachycardia (VT). After cardioversion, electrocardiography showed a first-degree atrioventricular block with a right bundle branch block, and transthoracic echocardiography revealed left ventricular dilatation. After extensive investigations, including fluorine-18 fluorodeoxyglucose positron emission tomography (18F-FDG PET), the patient was diagnosed with CS according to the Japanese Circulation Society guidelines. After the implantation of a transvenous implantable cardioverter defibrillator, corticosteroid therapy was introduced at a starting dose of 30 mg/day. After corticosteroid therapy was tapered to a maintenance dose of 10 mg/day, he had an uneventful clinical course without symptoms for the 1st year after hospital discharge. However, symptomatic VT recurred and 18F-FDG PET showed abnormal patterns of cardiac FDG uptake. Although he was treated with corticosteroid therapy once more, which was gradually up-titrated to a dose of 20 mg/day over a 1-month period, myocardial uptake of 18F-FDG PET remained unchanged. As the patient was considered steroid refractory, second-line treatment with 6 mg/week of methotrexate was introduced, whereas maintaining the dose of corticosteroid therapy at 20 mg/day. After 1 month, 18F-FDG PET showed remarkable reduction in FDG uptake, and the patient had a good clinical course without further episodes of arrhythmia or other symptoms during an 8-month follow-up.

Discussion

Methotrexate may have a direct anti-inflammatory effect in patients with CS refractory to regular corticosteroid therapy.
Changes in PAH and 3-MCPDE contents at the various stages of Camellia oleifera seed oil refining
Authors: Cai Chenggang , Chang Guoli , Zhang Nianhua , Wang Junlin , Wang Liyuan , Wu Pinggu , Yang Dajin
Published: May 2022

Objectives

Polycyclic aromatic hydrocarbons (PAHs) and 3-monochloropropane-1,2-diol ester (3-MCPDE) were studied in camellia oil. It is important to study the changes in the content of PAHs and 3-MCPDE at different refining stages (from crude oil to the final refined oil product) to elucidate the influence of the refining procedures on their change.

Materials and methods

The PAHs and 3-MCPDE in camellia oil from different refining stages (from crude oil to the product) of a plant were analyzed by gas chromatography–mass spectrometry and calculated by the internal standard method.

Results

The overall PAH content was (79.64±2.43) µg/kg in crude camellia oil. After refining treatment, the PAH content decreased to (18.75±0.55) µg/kg. The 3-MCPDE content increased during the refining process from 0 mg/kg in the crude oil to 4.62 mg/kg in the refined oil product.

Conclusions

This is the first study to simultaneously monitor changes in both PAH and 3-MCPDE contents during the production of camellia oil. These results confirmed the effectiveness of the refining method on PAH removal and the increase in 3-MCPDE at high temperature. It is suggested that novel processing methods or refining parameters need further optimization to decrease the overall concentrations of PAHs and 3-MCPDE in camellia oil.
Genome of a novel Sediminibacterium discovered in association with two species of freshwater cyanobacteria from streams in Southern California
Authors: Sethuraman Arun , Stancheva Rosalina , Sanders Ciara , Caceres Lakme , Castro David , Hausknecht-Buss Hannah , Henry Simone , Johansen Haven , Kasler Antolette , Lastor Sandy , Massaro Isabelle , Mekuria Immanuel , Moron-Solano Andrea , Read Niki , Vengerova Gretchen , Zhang Andrew , Zhang Xiaoyu , Read Betsy
Published: May 2022

Here, we report the discovery of a novel Sediminibacterium sequenced from laboratory cultures of freshwater stream cyanobacteria from sites in Southern California, grown in BG11 medium. Our genome-wide analyses reveal a highly contiguous and complete genome (97% BUSCO) that is placed within sediminibacterial clades in phylogenomic analyses. Functional annotation indicates the presence of genes that could be involved in mutualistic/commensal relationship with associated cyanobacterial hosts.
Longitudinal Associations Between Personal Growth and Cognitive Functioning in Adulthood
Authors: Toyama Masahiro
Published: May 2022

Objectives

While personal growth has been found to be associated with multiple aspects of health in adulthood, its associations with cognitive functioning have not been fully understood. The present study aimed to assess both directions of such longitudinal associations.

Method

Using data from the second wave (Time 1 [T1]) and third wave (Time 2 [T2]) of the Midlife in the United States (MIDUS) study (N = 4,206; mean age = 56.0 [standard deviation (SD) = 12.3]), a longitudinal measurement model containing latent variables of episodic memory and executive function was first constructed. Built on the measurement model, a cross-lagged panel model was analyzed to assess relationships between personal growth and the two areas of cognitive functioning, in which T1 personal growth predicted residualized changes in episodic memory and executive function, and T1 episodic memory and executive function predicted change in personal growth, controlling for covariates.

Results

T1 personal growth significantly predicted smaller decreases in episodic memory, whereas it did not predict change in executive function. T1 episodic memory, but not T1 executive function, significantly predicted smaller decreases in personal growth.

Discussion

The present findings were unique, particularly implying potential longitudinal reciprocity between personal growth and episodic memory. These findings and implications can inform future research aimed at exploring approaches to promoting personal growth and cognitive functioning among aging adults.
Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification
Authors: Kanduri Chakravarthi , Pavlović Milena , Scheffer Lonneke , Motwani Keshav , Chernigovskaya Maria , Greiff Victor , Sandve Geir K
Published: May 2022

Background

Machine learning (ML) methodology development for the classification of immune states in adaptive immune receptor repertoires (AIRRs) has seen a recent surge of interest. However, so far, there does not exist a systematic evaluation of scenarios where classical ML methods (such as penalized logistic regression) already perform adequately for AIRR classification. This hinders investigative reorientation to those scenarios where method development of more sophisticated ML approaches may be required.

Results

To identify those scenarios where a baseline ML method is able to perform well for AIRR classification, we generated a collection of synthetic AIRR benchmark data sets encompassing a wide range of data set architecture-associated and immune state–associated sequence patterns (signal) complexity. We trained ≈1,700 ML models with varying assumptions regarding immune signal on ≈1,000 data sets with a total of ≈250,000 AIRRs containing ≈46 billion TCRβ CDR3 amino acid sequences, thereby surpassing the sample sizes of current state-of-the-art AIRR-ML setups by two orders of magnitude. We found that L1-penalized logistic regression achieved high prediction accuracy even when the immune signal occurs only in 1 out of 50,000 AIR sequences.

Conclusions

We provide a reference benchmark to guide new AIRR-ML classification methodology by (i) identifying those scenarios characterized by immune signal and data set complexity, where baseline methods already achieve high prediction accuracy, and (ii) facilitating realistic expectations of the performance of AIRR-ML models given training data set properties and assumptions. Our study serves as a template for defining specialized AIRR benchmark data sets for comprehensive benchmarking of AIRR-ML methods.
Can machine learning reveal precursors of reversals of the geomagnetic axial dipole field?
Authors: Gwirtz K , Davis T , Morzfeld M , Constable C , Fournier A , Hulot G
Published: May 2022

It is well known that the axial dipole part of Earth’s magnetic field reverses polarity, so that the magnetic North Pole becomes the South Pole and vice versa. The timing of reversals is well documented for the past 160 Myr, but the conditions that lead to a reversal are still not well understood. It is not known if there are reliable ‘precursors’ of reversals (events that indicate that a reversal is upcoming) or what they might be. We investigate if machine learning (ML) techniques can reliably identify precursors of reversals based on time-series of the axial magnetic dipole field. The basic idea is to train a classifier using segments of time-series of the axial magnetic dipole. This training step requires modification of standard ML techniques to account for the fact that we are interested in rare events—a reversal is unusual, while a non-reversing field is the norm. Without our tweak, the ML classifiers lead to useless predictions. Perhaps even more importantly, the usable observational record is limited to 0–2 Ma and contains only five reversals, necessitating that we determine if the data are even sufficient to reliably train and validate an ML algorithm. To answer these questions we use several ML classifiers (linear/non-linear support vector machines and long short-term memory networks), invoke a hierarchy of numerical models (from simplified models to 3-D geodynamo simulations), and two palaeomagnetic reconstructions (PADM2M and Sint-2000). The performance of the ML classifiers varies across the models and the observational record and we provide evidence that this is not an artefact of the numerics, but rather reflects how ‘predictable’ a model or observational record is. Studying models of Earth’s magnetic field via ML classifiers thus can help with identifying shortcomings or advantages of the various models. For Earth’s magnetic field, we conclude that the ability of ML to identify precursors of reversals is limited, largely due to the small amount and low frequency resolution of data, which makes training and subsequent validation nearly impossible. Put simply: the ML techniques we tried are not currently capable of reliably identifying an axial dipole moment (ADM) precursor for geomagnetic reversals. This does not necessarily imply that such a precursor does not exist, and improvements in temporal resolution and length of ADM records may well offer better prospects in the future.
Modelling tippers on a sphere
Authors: Kruglyakov Mikhail , Kuvshinov Alexey
Published: May 2022

In the past three decades, an immense amount of magnetic field data (with periods of measurements from months to years) has been collected worldwide, either inland or at the sea bottom. This makes it tempting to estimate from these data magnetotelluric (MT) vertical transfer functions—tippers—and further probe with them the 3-D distribution of electrical conductivity on a continental or even global scale. Such a problem setup requires modelling tippers in spherical geometry. It is known that MT impedances in spherical coordinates can be modelled using different polarizations of a uniform external magnetic field. As for tippers, one needs another type of excitation because the uniform external magnetic field of any polarization contains a non-zero radial component. In the paper, we elaborate a source model, which leads to valid tippers on a whole sphere. We also present a novel, accurate and computationally efficient solver to calculate the electromagnetic field in a spherical shell or a part thereof. To illustrate the workability of both the introduced source model and the developed new solver, we present the results of modelling the ocean induction effect in tippers on a global scale. We performed computations in the models with and without oceanic sediments and show that the sediments substantially influence the results in the coastal regions where the thickness of sediments is comparable with or even exceeds the ocean’s bathymetry.
P- andS-wave velocity estimation by ensemble Kalman inversion of dispersion data for strong motion stations in California
Authors: Bas Elif Ecem , Seylabi Elnaz , Yong Alan , Tehrani Hesam , Asimaki Domniki
Published: May 2022

This study uses an ensemble Kalman method for near-surface seismic site characterization of 154 network earthquake monitoring stations in California to improve the resolution of S-wave velocity (VS) and P-wave velocity (VP) profiles—up to the resolution depth—coupled with better quantification of uncertainties compared to previous site characterization studies at this network. These stations were part of the Yong et al. site characterization project, with selected stations based on future recordings of ground motions that are expected to exceed 10 per cent peak ground acceleration in 50 yr. To estimate VS and VP from experimental dispersion data, Yong et al. investigated these stations using linearized (local search and iteration) routines, and Yong et al. later studied a subset of these stations using nonlinear (global search and optimization) routines. In both studies, the selection of model parameters—that is, discretization of the VS and VP profiles with only five fixed thickness layers—was mainly based on trial and error. In contrast, this paper uses an approximate Bayesian method to assimilate experimental dispersion data and sequentially update an ensemble of particle estimates that span the VS and VP parameter spaces. Doing so, we systematically determine the most probable profiles conditioned on the experimental dispersion data, the introduced noise levels, and a priori knowledge in the form of physical constraints. We consider two configurations to discretize the soil depth from the surface to half of the maximum discernible wavelength obtained from the experimental dispersion data, namely refined and coarse models, and two initial models for each configuration to study solution multiplicity. Our results suggest that using the refined model for the top surface layers improves the resolution of near-surface site characteristics and the model’s success rate in capturing dispersion data at high frequencies. All models result in similar VS but distinct VP profiles, with increasing uncertainty at deeper layers, suggesting that the fundamental mode of Rayleigh wave dispersion data is not adequate to constrain the P-wave velocity profile and the S-wave velocity close to the resolution depth.
Regulation of tomato fruit elongation by transcription factor BZR1.7 through promotion of SUN gene expression
Authors: Yu Ting , Ai Guo , Xie Qingmin , Wang Wenqian , Song Jianwen , Wang Jiaying , Tao Jingbao , Zhang Xingyu , Hong Zonglie , Lu Yongen , Ye Jie , Zhang Yuyang , Zhang Junhong , Ye Zhibiao
Published: May 2022

Fruit shape is an important biological trait that is also of special commercial value in tomato. The SUN gene has been known as a key regulator of tomato fruit elongation for years, but the molecular mechanisms underlying its transcriptional regulation remain little understood. Here, a unique BZR1-like transcription factor, BZR1.7, was identified as a trans-acting factor of the SUN gene promoter that bound to the conserved E-box of the promoter to promote SUN gene expression. Overexpression of BZR1.7 in tomato led to elevated SUN gene expression and formation of elongated fruits. Plants of the BZR1.7 knockout mutant created by gene editing did not exhibit an observable fruit shape phenotype, suggesting possible functional redundancy of BZR1-like genes in tomato. There were seven BZR1-like genes in the tomato genome and overexpression of BZR1.5 and BZR1.6 led to elongated fruit phenotypes similar to those observed in the BZR1.7 overexpression lines, further supporting the notion of functional redundancy of BZR1-like genes in tomato fruit shape specification. Microscopic analysis revealed that there was a decreased number of cell layers in the fruit pericarp in the BZR1.7 overexpression lines. These findings offer new insights into the regulatory mechanism by which BZR1.7 promotes SUN gene expression and regulates fruit elongation in tomato.
Social Workers’ Self-Care Practices: Buffering the Influence of Work–Family Interferences on Burnout and Engagement
Authors: Lombardero-Posada Xoán M , Méndez-Fernández Ana B , Aguiar-Fernández Francisco X , Murcia-Álvarez Evelia , González-Fernández Antonio
Published: May 2022

As a reaction to specific job stressors, social workers can experience job burnout. The job demands-resources theory posits that personal characteristics would mediate the influence of job stressors on either burnout or engagement. Within this framework, this cross-sectional research aimed to analyze the relationships between work–family interferences (as predictors), self-care practices (as mediators), and burnout and engagement (as outcomes). The sample included 437 graduate social workers from Spain. Structural equation modeling showed that family–work and work–family conflicts negatively predicted self-care practices and positively predicted burnout. Professional and personal self-care practices positively predicted engagement, negatively predicted burnout, and attenuated the impact of work–family interferences on burnout and engagement. To the authors’ knowledge, the present article is the first to test the job demands-resources theory with these variables on social workers. The findings support interventions for social work students and professionals enhancing self-care practices to promote engagement and to reduce burnout, and highlight the need to decrease job stressors and enhance job resources for social workers.
Should any use of artificial cycle regimen for frozen-thawed embryo transfer in women capable of ovulation be abandoned: yes, but what’s next for FET cycle practice and research?
Authors: von Versen-Höynck Frauke , Griesinger Georg
Published: May 2022

Over the past decade, the use of frozen-thawed embryo transfer (FET) treatment cycles has increased substantially. The artificial (‘programmed’) cycle regimen, which suppresses ovulation, is widely used for that purpose, also in ovulatory women or women capable of ovulation, under the assumption of equivalent efficacy in terms of pregnancy achievement as compared to a natural cycle or modified natural cycle. The advantage of the artificial cycle is the easy alignment of the time point of thawing and transferring embryos with organizational necessities of the IVF laboratory, the treating doctors and the patient. However, recent data indicate that pregnancy establishment under absence of a corpus luteum as a consequence of anovulation may cause relevant maternal and fetal risks. Herein, we argue that randomized controlled trials (RCTs) are not needed to aid in the clinical decision for or against routine artificial cycle regimen use in ovulatory women. We also argue that RCTs are unlikely to answer the most burning questions of interest in that context, mostly because of lack of power and precision in detecting rare but decisive adverse outcomes (e.g. pre-eclampsia risk or long-term neonatal health outcomes). We pinpoint that, instead, large-scale observational data are better suited for that purpose. Eventually, we propose that the existing understanding and evidence is sufficient already to discourage the use of artificial cycle regimens for FET in ovulatory women or women capable of ovulation, as these may cause a strong deviation from physiology, thereby putting patient and fetus at avoidable health risk, without any apparent health benefit.
A comprehensive review on recent advancements in cooling of solar photovoltaic systems using phase change materials
Authors: Sheik Mohammed Anees , Aravindan M K , Cuce Erdem , Dasore Abhishek , Rajak Upendra , Shaik Saboor , Manokar A Muthu , Riffat Saffa
Published: May 2022

Due to the increasing demand for energy worldwide, photovoltaic (PV) cooling systems have become an important field of research in recent years. The most important factor affecting the performance of a solar PV cell is its operating temperature. For harvesting heat from solar PV systems, phase change material (PCM) is regarded as the most effective material. As a result, this study discusses and describes the effect of using PCM and nanoPCM (NPCM) in cooling PV cells. This research reviews the various feasible hybrid photovoltaic thermal (PVT)–PCM and PVT–NPCM methods used for cooling PV. The concept focusing on PV cooling technology is discussed where air, water and nanofluid are used as the working medium in combination with PCM and NPCM. It is observed that when high performance heat transfer and improved cooling rate are needed, active cooling methods are favoured, whereas passive cooling methods rely on themselves and don’t require extra power. It is also found that the effectiveness of applying PCM or NPCM for thermal control is heavily influenced by atmospheric air temperatures as well as the precise PCM or NPCM used. It is envisaged that this review will help new researchers better understand the qualities and capabilities of each cooling strategy. They are offered to help investigators quickly identify the basic science that led to the development of the thermal performance system and also improve the overall performance of the PV system.
Plasma exchange for severe immune-related adverse events from checkpoint inhibitors: an early window of opportunity?
Authors: Katsumoto Tamiko R , Wilson Kalin L , Giri Vinay K , Zhu Han , Anand Shuchi , Ramchandran Kavitha J , Martin Beth A , Yunce Muharrem , Muppidi Srikanth
Published: May 2022

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of several advanced malignancies leading to durable remission in a subset of patients. Their rapidly expanding use has led to an increased frequency of immune-related adverse events (irAEs). The pathogenesis of irAEs is poorly understood but may involve aberrant activation of T cells leading to inflammatory cytokine release or production of pathogenic antibodies leading to organ damage. Severe irAEs can be extremely debilitating and, in some cases, life threatening. IrAEs may not always be corticosteroid responsive or may require excessively high, often toxic, corticosteroid doses. Therapeutic plasma exchange (PLEX) is a treatment modality that has shown promising results for the management of certain severe irAEs, including irAEs that are not mentioned in current treatment guidelines. PLEX may attenuate ongoing irAEs and prevent delayed irAEs by accelerating clearance of the ICI, or by acutely removing pathogenic antibodies, cytokines, and chemokines. Here, we summarize examples from the literature in which PLEX was successfully used for the treatment of irAEs. We posit that timing may be a critical factor and that earlier utilization of PLEX for life-threatening irAEs may result in more favorable outcomes. In individuals at high risk for irAEs, the availability of PLEX as a potential therapeutic mitigation strategy may encourage life-saving ICI use or rechallenge. Future research will be critical to better define which indications are most amenable to PLEX, particularly to establish the optimal place in the sequence of irAE therapies and to assess the ramifications of ICI removal on cancer outcomes.
When architectural plasticity fails to counter the light competition imposed by planting design: an in silico approach using a functional–structural model of oil palm
Authors: Perez Raphaël P A , Vezy Rémi , Brancheriau Loïc , Boudon Frédéric , Grand François , Ramel Merlin , Artanto Raharjo Doni , Caliman Jean-Pierre , Dauzat Jean
Published: May 2022

Functional–structural plant modelling approaches (FSPM) explore the relationships between the 3D structure and the physiological functioning of plants in relation to environmental conditions. In this study, we present a methodological approach that integrated architectural responses to planting design in an oil palm FSPM, and test the impact of planting design and architectural plasticity on physiological responses such as light interception and carbon assimilation. LiDAR-derived and direct measurements were performed on five planting designs to assess the phenotypic plasticity of architectural traits, and allowed evaluating the variations of the main parameters of an existing 3D plant model. Accordingly, we proposed a neighbourhood index (NI) as a simple explanatory variable of architectural plasticity, and used NI-based allometries to simulate architectural variations in 3D virtual plants. Light interception and carbon assimilation were then simulated on virtual plots reproducing the five studied designs. We found that the main traits affected by plant proximity were leaf dimensions, leaf weight and leaf erectness, whereas other structural traits like the frequency of leaflets along the rachis or biomechanical properties of leaves remained unchanged. Our simulation study highlighted model compliance to reproduce architectural plasticity and illustrated how architectural plasticity improved light interception via leaf area expansion, but how the competition for light imposed by the design can counterbalance this benefit in terms of carbon assimilation at stand scale. We conclude on the importance of planting patterns for plants with low architectural plasticity such as oil palm, and how in silico experiments can help in designing innovative planting patterns.