bluuebunny/crossref_metadata_2025 huggingface dataset:
PROX1 transcription factor controls rhabdomyosarcoma growth, stemness, myogenic properties and therapeutic targets
Authors: Gizaw Nebeyu Yosef , Kallio Pauliina , Punger Tatjana , Gucciardo Erika , Haglund Caj , Böhling Tom , Lehti Kaisa , Sampo Mika , Alitalo Kari , Kivelä Riikka
Published: December 2022

Rhabdomyosarcoma (RMS) is an aggressive pediatric soft-tissue cancer with features of skeletal muscle. Because of poor survival of RMS patients and severe long-term side effects of RMS therapies, alternative RMS therapies are urgently needed. Here we show that the prospero-related homeobox 1 (PROX1) transcription factor is highly expressed in RMS tumors regardless of their cell type of origin. We demonstrate that PROX1 is needed for RMS cell clonogenicity, growth and tumor formation. PROX1 gene silencing repressed several myogenic and tumorigenic transcripts and transformed the RD cell transcriptome to resemble that of benign mesenchymal stem cells. Importantly, we found that fibroblast growth factor receptors (FGFR) mediated the growth effects of PROX1 in RMS. Because of receptor cross-compensation, paralog-specific FGFR inhibition did not mimic the effects of PROX1 silencing, whereas a pan-FGFR inhibitor ablated RMS cell proliferation and induced apoptosis. Our findings uncover the critical role of PROX1 in RMS and offer insights into the mechanisms that regulate RMS development and growth. As FGFR inhibitors have already been tested in clinical phase I/II trials in other cancer types, our findings provide an alternative option for RMS treatment.
Untapped policy avenues to protect coral reef ecosystems
Authors: Carlson Rachel R. , Foo Shawna A. , Burns John H. R. , Asner Gregory P.
Published: December 2022

Coral reefs are experiencing severe decline, and urgent action is required at local and global scales to curb ecosystem loss. Establishing new regulations to protect corals, however, can be time consuming and costly, and it is therefore necessary to leverage existing legal instruments, such as policies originally designed to address terrestrial rather than marine activities, to prevent coral reef degradation. Focusing on the United States, but drawing on successful examples worldwide, we present actionable pathways to increase coral protections under legislation that was originally designed to advance clean freshwater, safe drinking water, and emergency management. We identify specific legal policies and procedures (e.g., industrial permit limits, nonpoint source management incentives, and floodplain restoration programs) that can curb coral reef pollution and can be extended to other countries with similar regulations in place. Coral reef practitioners should consider a broad array of currently underused, actionable, and intersecting environmental policies that can be applied to mitigate coral stress.
Decorating chromatin for enhanced genome editing using CRISPR-Cas9
Authors: Chen Evelyn , Lin-Shiao Enrique , Trinidad Marena , Saffari Doost Mohammad , Colognori David , Doudna Jennifer A.
Published: December 2022

CRISPR-associated (Cas) enzymes have revolutionized biology by enabling RNA-guided genome editing. Homology-directed repair (HDR) in the presence of donor templates is currently the most versatile method to introduce precise edits following CRISPR-Cas-induced double-stranded DNA cuts, but HDR efficiency is generally low relative to end-joining pathways that lead to insertions and deletions (indels). We tested the hypothesis that HDR could be increased using a Cas9 construct fused to PRDM9, a chromatin remodeling factor that deposits histone methylations H3K36me3 and H3K4me3 to mediate homologous recombination in human cells. Our results show that the fusion protein contacts chromatin specifically at the Cas9 cut site in the genome to increase the observed HDR efficiency by threefold and HDR:indel ratio by fivefold compared with that induced by unmodified Cas9. HDR enhancement occurred in multiple cell lines with no increase in off-target genome editing. These findings underscore the importance of chromatin features for the balance between DNA repair mechanisms during CRISPR-Cas genome editing and provide a strategy to increase HDR efficiency.
Human cytomegalovirus induces neuronal enolase to support virally mediated metabolic remodeling
Authors: Moreno Isreal , Rodríguez-Sánchez Irene , Schafer Xenia , Munger Joshua
Published: December 2022

Viruses depend on cellular metabolic resources to supply the energy and biomolecular building blocks necessary for their replication. Human cytomegalovirus (HCMV), a leading cause of birth defects and morbidity in immunosuppressed individuals, induces numerous metabolic activities that are important for productive infection. However, many of the mechanisms through which these metabolic activities are induced and how they contribute to infection are unclear. We find that HCMV infection of fibroblasts induces a neuronal gene signature as well as the expression of several metabolic enzyme isoforms that are typically expressed in other tissue types. Of these, the most substantially induced glycolytic gene was the neuron-specific isoform of enolase 2 (ENO2). Induction of ENO2 expression is important for HCMV-mediated glycolytic activation as well as for the virally induced remodeling of pyrimidine-sugar metabolism, which provides the glycosyl subunits necessary for protein glycosylation. Inhibition of ENO2 expression or activity reduced uridine diphosphate (UDP)-sugar pools, attenuated the accumulation of viral glycoproteins, and induced the accumulation of noninfectious viral particles. In addition, our data indicate that the induction of ENO2 expression depends on the HCMV U
L
38 protein. Collectively, our data indicate that HCMV infection induces a tissue atypical neuronal glycolytic enzyme to activate glycolysis and UDP-sugar metabolism, increase the accumulation of glycosyl building blocks, and enable the expression of an essential viral glycoprotein and the production of infectious virions.
The restart effect in social dilemmas shows humans are self-interested not altruistic
Authors: Burton-Chellew Maxwell N.
Published: December 2022

Do economic games show evidence of altruistic or self-interested motivations in humans? A huge body of empirical work has found contrasting results. While many participants routinely make costly decisions that benefit strangers, consistent with the hypothesis that humans exhibit a biologically novel form of altruism (or “prosociality”), many participants also typically learn to pay fewer costs with experience, consistent with self-interested individuals adapting to an unfamiliar environment. Key to resolving this debate is explaining the famous “restart effect,” a puzzling enigma whereby failing cooperation in public goods games can be briefly rescued by a surprise restart. Here we replicate this canonical result, often taken as evidence of uniquely human altruism, and show that it 1) disappears when cooperation is invisible, meaning individuals can no longer affect the behavior of their groupmates, consistent with strategically motivated, self-interested, cooperation; and 2) still occurs even when individuals are knowingly grouped with computer players programmed to replicate human decisions, consistent with confusion. These results show that the restart effect can be explained by a mixture of self-interest and irrational beliefs about the game’s payoffs, and not altruism. Consequently, our results suggest that public goods games have often been measuring self-interested but confused behaviors and reject the idea that conventional theories of evolution cannot explain the results of economic games.
Acetyl-CoA-mediated autoacetylation of fatty acid synthase as a metabolic switch of de novo lipogenesis in
Drosophila
Authors: Miao Ting , Kim Jinoh , Kang Ping , Fujiwara Hideji , Hsu Fong-Fu , Bai Hua
Published: December 2022

De novo lipogenesis is a highly regulated metabolic process, which is known to be activated through transcriptional regulation of lipogenic genes, including fatty acid synthase (FASN). Unexpectedly, we find that the expression of FASN protein remains unchanged during
Drosophila
larval development from the second to the third instar larval stages (L2 to L3) when lipogenesis is hyperactive. Instead, acetylation of FASN is significantly upregulated in fast-growing larvae. We further show that lysine K813 residue is highly acetylated in developing larvae, and its acetylation is required for elevated FASN activity, body fat accumulation, and normal development. Intriguingly, K813 is autoacetylated by acetyl-CoA (AcCoA) in a dosage-dependent manner independent of acetyltransferases. Mechanistically, the autoacetylation of K813 is mediated by a novel P-loop-like motif (N-xx-G-x-A). Lastly, we find that K813 is deacetylated by Sirt1, which brings FASN activity to baseline level. In summary, this work uncovers a previously unappreciated role of FASN acetylation in developmental lipogenesis and a novel mechanism for protein autoacetylation, through which
Drosophila
larvae control metabolic homeostasis by linking AcCoA, lysine acetylation, and de novo lipogenesis.
DHX15 is involved in SUGP1-mediated RNA missplicing by mutant SF3B1 in cancer
Authors: Zhang Jian , Huang Ji , Xu Ke , Xing Peiqi , Huang Yue , Liu Zhaoqi , Tong Liang , Manley James L.
Published: December 2022

SF3B1
is the most frequently mutated spliceosomal gene in cancer. Several hotspot mutations are known to disrupt the interaction of SF3B1 with another splicing factor, SUGP1, resulting in the RNA missplicing that characterizes mutant SF3B1 cancers. Properties of SUGP1, especially the presence of a G-patch motif, a structure known to function by activating DEAH-box RNA helicases, suggest the requirement of such an enzyme in SUGP1 function in splicing. However, the identity of this putative helicase has remained an important unanswered question. Here, using a variety of protein–protein interaction assays, we identify DHX15 as the critical helicase. We further show that depletion of DHX15 or expression of any of several DHX15 mutants, including one implicated in acute myeloid leukemia, partially recapitulates the splicing defects of mutant SF3B1. Moreover, a DHX15-SUGP1 G-patch fusion protein is able to incorporate into the spliceosome to rescue the splicing defects of mutant SF3B1. We also present the crystal structure of the human DHX15-SUGP1 G-patch complex, which reveals the molecular basis of their direct interaction. Our data thus demonstrate that DHX15 is the RNA helicase that functions with SUGP1 and additionally provide important insight into how mutant SF3B1 disrupts splicing in cancer.
Immersive architectures for visual data literacy
Authors: Rodighiero Dario , Wandl-Vogt Eveline , Carsenat Elian , Döring Jules , Elias Oliver , Fragner Michaela , Farkashazy Stepha
Published: December 2022

The datafication process transforming society enables us to witness the pandemic from a global perspective. This article provides an example of immersive architecture in which coronavirus-related scientific literature was revealed during Ars Electronica 2021. Like a starry sky, a network visualization representing more than 600,000 articles was showcased in the Deep Space 8K theater, where spectators were accompanied in reading insights. The case study of 3D Cartography of COVID-19 illustrates a novel way to present data in public spaces to foster conversations and reflects on how visual data literacy can be addressed in museums.
Myosin loop-4 is critical for optimal tropomyosin repositioning on actin during muscle activation and relaxation
Authors: Doran Matthew H. , Rynkiewicz Michael J. , Pavadai Elumalai , Bodt Skylar M.L. , Rasicci David , Moore Jeffrey R. , Yengo Christopher M. , Bullitt Esther , Lehman William
Published: December 2022

During force-generating steps of the muscle crossbridge cycle, the tip of the myosin motor, specifically loop-4, contacts the tropomyosin cable of actin filaments. In the current study, we determined the corresponding effect of myosin loop-4 on the regulatory positioning of tropomyosin on actin. To accomplish this, we compared high-resolution cryo-EM structures of myosin S1-decorated thin filaments containing either wild-type or a loop-4 mutant construct, where the seven-residue portion of myosin loop-4 that contacts tropomyosin was replaced by glycine residues, thus removing polar side chains from residues 366–372. Cryo-EM analysis of fully decorated actin-tropomyosin filaments with wild-type and mutant S1, yielded 3.4–3.6 Å resolution reconstructions, with even higher definition at the actin-myosin interface. Loop-4 densities both in wild-type and mutant S1 were clearly identified, and side chains were resolved in the wild-type structure. Aside from loop-4, actin and myosin structural domains were indistinguishable from each other when filaments were decorated with either mutant or wild-type S1. In marked contrast, the position of tropomyosin on actin in the two reconstructions differed by 3 to 4 Å. In maps of filaments containing the mutant, tropomyosin was located closer to the myosin-head and thus moved in the direction of the C-state conformation adopted by myosin-free thin filaments. Complementary interaction energy measurements showed that tropomyosin in the mutant thin filaments sits on actin in a local energy minimum, whereas tropomyosin is positioned by wild-type S1 in an energetically unfavorable location. We propose that the high potential energy associated with tropomyosin positioning in wild-type filaments favors an effective transition to B- and C-states following release of myosin from the thin filaments during relaxation.
A miniaturized spin-exchange relaxation-free atomic magnetometer based on uniform light field
Authors: Li Jiajie , Fang Xiujie , Li Renjie , Chen Baodong , Zhai Yueyang , Liu Ying
Published: December 2022

We experimentally study the dynamic characteristics of a miniaturized spin-exchange relaxation-free (SERF) magnetometer based on uniform light field. The ceramic ferrule is used to expand the Gaussian beam to improve light intensity uniformity, while the volume of the sensor is also reduced. This scheme makes the magnetometer have better sensitivity when the detected light intensity is less than 3.16 mW/cm2 at 120 °C. When the temperature rises to 150 °C the sensitivity under the action of uniform light field is 18.5 fT/Hz1/2. The bandwidth of the sensor remains at the original level and meets application needs. The proposed structure improves transverse polarization uniformity within the miniaturized sensor, which is ideal for the magnetoencephalography and magnetocardiography imaging systems.
Micro-vibration Modeling and Verification of Shutter Mechanism of Survey Space Telescope
Authors: Jiang Tong-Lei , Wen Li-Hua , Zhan Hu , Wang Bo , Yang Yong-Chao
Published: December 2022

The scientific research mission of the Survey Space Telescope (also known as the China Space Station Telescope, CSST) imposes rigorous requirements on the observation precision. However, microvibrations generated by the shutter mechanism can seriously affect the performance of the highly precise and sensitive instruments onboard. This study presents a dynamic model and verifies its performance using experimental results. Indeed, a five-degree-of-freedom nonlinear dynamic model that considers all interference sources and bearing nonlinearity is established. The validity of the proposed model is verified using experimental measurements of the microvibration characteristics. The obtained results proved that the proposed dynamic model can accurately predict the characteristics of the microvibrations caused by the shutter mechanism in the design stage and provide a theoretical basis for the development of CSST.
Noninvasive neuroimaging and spatial filter transform enable ultra low delay motor imagery EEG decoding
Authors: Fang Tao , Wang Junkongshuai , Mu Wei , Song Zuoting , Zhang Xueze , Zhan Gege , Wang Pengchao , Bin Jianxiong , Niu Lan , Zhang Lihua , Kang Xiaoyang
Published: December 2022

Objective. The brain-computer interface (BCI) system based on sensorimotor rhythm can convert the human spirit into instructions for machine control, and it is a new human-computer interaction system with broad applications. However, the spatial resolution of scalp electroencephalogram (EEG) is limited due to the presence of volume conduction effects. Therefore, it is very meaningful to explore intracranial activities in a noninvasive way and improve the spatial resolution of EEG. Meanwhile, low-delay decoding is an essential factor for the development of a real-time BCI system. Approach. In this paper, EEG conduction is modeled by using public head anatomical templates, and cortical EEG is obtained using dynamic parameter statistical mapping. To solve the problem of a large amount of computation caused by the increase in the number of channels, the filter bank common spatial pattern method is used to obtain a spatial filter kernel, which reduces the computational cost of feature extraction to a linear level. And the feature classification and selection of important features are completed using a neural network containing band-spatial-time domain self-attention mechanisms. Main results. The results show that the method proposed in this paper achieves high accuracy for the four types of motor imagery EEG classification tasks, with fairly low latency and high physiological interpretability. Significance. The proposed decoding framework facilitates the realization of low-latency human-computer interaction systems.
Coating μm TPB on a cylindrical detector and studying the sample films being cooled to LN and LHe temperatures
Authors: Zhou Jiangfeng , Ouyang Zebang , Liao Junhui , Liang Zhuo , Peng Zhaohua , Zhang Lei , Zhang Lifeng , Zheng Jian
Published: December 2022

ALETHEIA is a newly established dark matter direct detection project that aims at hunting for low-mass WIMPs. TPB is widely implemented in liquid helium and argon experiments to shift VUV photons to visible light. We first report that we have successfully coated ∼ 3 μm TPB on the inner walls of a 10-cm cylindrical PTFE detector; we split the coating process into two steps to have all of the surfaces being coated with the same thickness; three independent methods were applied to figure out the thickness of the TPB coating layers, and consistent results were obtained. Second, with an SEM machine, we scanned the surface of TPB coating sample films exposed to different cryogenic temperatures. The first group of sample layers were immersed into a liquid nitrogen dewar for forty hours, the second group samples were cooled to 4.5 K for three hours, and the third group stayed at room temperature after coating. The SEM-scanned images of the sample films barely show any noticeable difference.
Delay-induced vibrational resonance in the Rayleigh–Plesset bubble oscillator
Authors: Omoteso K A , Roy-Layinde T O , Laoye J A , Vincent U E , McClintock P V E
Published: December 2022

We examine the impacts of time-delay and phase shift between two acoustic driving forces on vibrational resonance (VR) phenomena in the oscillations of a spherical gas bubble. Using the approximate method of direct separation of the motions, we obtain the equation of slow motion and the response amplitude, and we validate the theoretical predictions with numerical simulations. We find that the response amplitude of the system at the lower frequency varies periodically with respect to the phase shift. When the phase shift consists of an even number of periods, it can be optimized to enhance the system’s response in the relevant parameter space of the high-frequency driving force. In addition to the enhancement of the VR peak by variation of the phase shift, our results show that the time-delay also plays a significant role in the bubble’s response to dual-frequency acoustic driving fields. It and can be exploited either to suppress drastically, or to modulate, the resonance peaks, thereby controlling the resonances. Our analysis shows further that cooperation between the time-delay and the amplitude of the high-frequency component of the acoustic waves can induce multiple resonances. These results could potentially be exploited to control and enhance ultrasonic cleaning processes by varying the time-delay parameter in the presence of phase shifted dual-frequency acoustic waves. Moreover, it could be employed to achieve improved accuracy in ultrasonic biomedical diagnosis and tumour therapy, as well as for targeted delivery of reagents transported within bubbles.
Universal characteristics of deep neural network loss surfaces from random matrix theory
Authors: Baskerville Nicholas P , Keating Jonathan P , Mezzadri Francesco , Najnudel Joseph , Granziol Diego
Published: December 2022

This paper considers several aspects of random matrix universality in deep neural networks (DNNs). Motivated by recent experimental work, we use universal properties of random matrices related to local statistics to derive practical implications for DNNs based on a realistic model of their Hessians. In particular we derive universal aspects of outliers in the spectra of deep neural networks and demonstrate the important role of random matrix local laws in popular pre-conditioning gradient descent algorithms. We also present insights into DNN loss surfaces from quite general arguments based on tools from statistical physics and random matrix theory.
The Glauber-Ising chain under low-temperature protocols
Authors: Godrèche Claude , Luck Jean-Marc
Published: December 2022

This work is devoted to an in-depth analysis of arbitrary temperature protocols applied to the ferromagnetic Glauber-Ising chain launched from a disordered initial state and evolving in the low-temperature scaling regime. We focus our study on the density of domain walls and the reduced susceptibility. Both the inverse of the former observable and the latter one provide two independent measures of the typical size of the growing ferromagnetic domains. Their product is thus a dimensionless form factor characterising the pattern of growing ordered domains and providing a measure of the distance of the system to thermal equilibrium. We apply this framework to a variety of protocols: everlasting slow quenches, where temperature decreases continuously to zero in the limit of infinitely long times, slow quenches of finite duration, where temperature reaches zero at some long but finite quenching time, time-periodic protocols with weak and strong modulations, and the two-temperature protocol leading to the memory effect found by Kovacs.
Pulse-shaped broadband multiphoton excitation for single-molecule fluorescence detection in the far field
Authors: Nobis David , Sansom Henry G , Magennis Steven W
Published: December 2022

Multiphoton excitation of fluorescence has many potential advantages over resonant (one-photon) excitation, but the method has not found widespread use for ultrasensitive applications. We recently described an approach to the multiphoton excitation of single molecules that uses a pulse shaper to compress and tailor pulses from an ultrafast broadband laser in order to optimise the brightness and signal-to-background ratio following non-linear excitation. Here we provide a detailed description of the setup and illustrate its use and potential by optimising two-photon fluorescence of a common fluorophore, rhodamine 110, at the single-molecule level. We also show that a DNA oligonucleotide labelled with a fluorescent nucleobase analogue, tC, can be detected using two-photon FCS, whereas one-photon excitation causes rapid photobleaching. The ability to improve the signal-to-background ratio and to reduce the incident power required to attain a given brightness can be applied to the multiphoton excitation of any fluorescent species, from small molecules with low multiphoton cross sections to the brightest nanoparticles.
Synergetic effects of combining TM single- and double-atom catalysts embedded in C2N on inducing half-metallicity: DFT study
Authors: Khan Saba , Feng Yuan-Ping , Tit Nacir
Published: December 2022

Designing 2D-materials that exhibit half-metallic properties is crucially important in spintronic devices that are used in low-power high-density logic circuits. The large pores in the C2N morphology can stably accommodate various configurations of transition-metal (TM) atoms that can lead to ferromagnetic (FMC) and anti-ferromagnetic coupling interactions among them, and thus paving the way for achieving half-metallic characteristics. In the present study, we use manganese ‘Mn’ as a promising catalyst and the spin-polarized density-functional theory to search for suitable configurations of metal atoms that yield half-metallicity. Test samples comprised of single-atom catalyst (SAC) and double-atom catalyst (DAC) of Mn embedded in a C2N sample of size 2 × 2 primitive cells as well as their combinations in neighboring large pores (i.e. SAC–SAC, SAC–DAC, and DAC–DAC). Tests were extended to screen many other TM catalysts and the results showed the existence of half metallicity in just five cases: (a) C2N:Mn (DAC, SAC–SAC, and SAC–DAC); (b) C2N:Fe (DAC); and (c) C2N:Ni (SAC–DAC). Our results further showed the origins of half-metallicity to be attributed to FMC interactions between the catalysts with the six mirror images, formed by the periodic-boundary conditions. The FMC interaction is found to have strength of about 20 meV and critical length scale up to about ∼21–29 Å, dependent on both the type of magnetic impurity and the synergetic effects. The potential relevance of half-metallicity to spintronic device application is discussed. Our theoretical results have been benchmarked to the available data in literature and they were found to be in good agreements.
Markov chain Monte Carlo enhanced variational quantum algorithms
Authors: Patti Taylor L , Shehab Omar , Najafi Khadijeh , Yelin Susanne F
Published: December 2022

Variational quantum algorithms have the potential for significant impact on high-dimensional optimization, with applications in classical combinatorics, quantum chemistry, and condensed matter. Nevertheless, the optimization landscape of these algorithms is generally nonconvex, leading the algorithms to converge to local, rather than global, minima and the production of suboptimal solutions. In this work, we introduce a variational quantum algorithm that couples classical Markov chain Monte Carlo techniques with variational quantum algorithms, allowing the former to provably converge to global minima and thus assure solution quality. Due to the generality of our approach, it is suitable for a myriad of quantum minimization problems, including optimization and quantum state preparation. Specifically, we devise a Metropolis–Hastings method that is suitable for variational quantum devices and use it, in conjunction with quantum optimization, to construct quantum ensembles that converge to Gibbs states. These performance guarantees are derived from the ergodicity of our algorithm’s state space and enable us to place analytic bounds on its time-complexity. We demonstrate both the effectiveness of our technique and the validity of our analysis through quantum circuit simulations for MaxCut instances, solving these problems deterministically and with perfect accuracy, as well as large-scale quantum Ising and transverse field spin models of up to 50 qubits. Our technique stands to broadly enrich the field of variational quantum algorithms, improving and guaranteeing the performance of these promising, yet often heuristic, methods.
Efficient Kohn–Sham density-functional theory implementation of isotropic spectroscopic observables associated with quadratic response functions
Authors: Ahmadzadeh Karan , Li Xin , Rinkevicius Zilvinas , Norman Patrick
Published: December 2022

For general exchange–correlation functionals with a dependence on the local spin densities and spin-density gradients, we provide computationally tractable expressions for the tensor-averaged quadratic response functions pertinent to the experimental observables in second-harmonic generation (SHG). We demonstrate how the tensor-averaged quantities can be implemented with reference to a derived minimal number of first- and second-order perturbed Fock matrices. Our consideration has the capability of treating a situation of resonance enhancement as it is based on damped response theory and allows for the evaluation of tensor-averaged resonant-convergent quadratic response functions using only ∼25% (one-photon off-resonance regions) and ∼50% (one-photon resonance regions) of the number of auxiliary Fock matrices required when explicitly calculating all the needed individual tensor components. Numerical examples of SHG intensities in the one-photon off-resonance region are provided for a sample of makaluvamine derivatives recognized for their large nonlinear optical responses as well as a benchmark set of small- and medium-sized organic molecules.
Federated data processing and learning for collaboration in the physical sciences
Authors: Huang W , Barnard A S
Published: December 2022

Property analysis and prediction is a challenging topic in fields such as chemistry, nanotechnology and materials science, and often suffers from lack of data. Federated learning (FL) is a machine learning (ML) framework that encourages privacy-preserving collaborations between data owners, and potentially overcomes the need to combine data that may contain proprietary information. Combining information from different data sets within the same domain can also produce ML models with more general insight and reduce the impact of the selection bias inherent in small, individual studies. In this paper we propose using horizontal FL to mitigate these data limitation issues and explore the opportunity for data-driven collaboration under these constraints. We also propose FedRed, a new dimensionality reduction method for FL, that allows faster convergence and accounts for differences between individual data sets. The FL pipeline has been tested on a collection of eight different data sets of metallic nanoparticles, and while there are expected losses compared to a combined data set that does not preserve the privacy of the collaborators, we obtained extremely good result compared to local training on individual data sets. We conclude that FL is an effective and efficient method for the physical science domain that could hugely reduce the negative effect of insufficient data.
Mildly reduced graphene oxide membranes for water purification applications
Authors: Kumar Shani , Garg Amit , Chowdhuri Arijit
Published: December 2022

Presently carbon allotropes namely graphene, graphene oxide (GO) and reduced graphene oxide (RGO) are being extensively utilized for water purification applications. The presence of myriad types of oxygen functional groups in the GO, however, makes this material very hydrophilic, allowing it to absorb water and to swell in moist or watery environments and to significantly damage its intended performance. In contrast, fully reduced graphene oxide membranes are not stable due to fewer oxide groups which are mainly responsible for GO flakes stacking. In the present work, the aforementioned problems are overcome by optimizing the oxygenated functional groups to develop mildly reduced graphene oxide (MRGO) membrane over PVDF (polyvinylidene fluoride) support. GO is reduced by L-Ascorbic Acid (LAA) with different amounts of wt.% and an optimized MRGO membrane is achieved at 10 wt.% of LAA, which is stable and showing comparatively lower swelling than GO membrane. All related structural and optical characterizations like XRD, SEM, EDAX, Raman, FTIR, and Contact angle have been done to evaluate the effect of mild reduction of GO. The studies are indicative of their potential application in water purification.
CLIP: accurate prediction of disordered linear interacting peptides from protein sequences using co-evolutionary information
Authors: Peng Zhenling , Li Zixia , Meng Qiaozhen , Zhao Bi , Kurgan Lukasz
Published: December 2022

One of key features of intrinsically disordered regions (IDRs) is facilitation of protein–protein and protein–nucleic acids interactions. These disordered binding regions include molecular recognition features (MoRFs), short linear motifs (SLiMs) and longer binding domains. Vast majority of current predictors of disordered binding regions target MoRFs, with a handful of methods that predict SLiMs and disordered protein-binding domains. A new and broader class of disordered binding regions, linear interacting peptides (LIPs), was introduced recently and applied in the MobiDB resource. LIPs are segments in protein sequences that undergo disorder-to-order transition upon binding to a protein or a nucleic acid, and they cover MoRFs, SLiMs and disordered protein-binding domains. Although current predictors of MoRFs and disordered protein-binding regions could be used to identify some LIPs, there are no dedicated sequence-based predictors of LIPs. To this end, we introduce CLIP, a new predictor of LIPs that utilizes robust logistic regression model to combine three complementary types of inputs: co-evolutionary information derived from multiple sequence alignments, physicochemical profiles and disorder predictions. Ablation analysis suggests that the co-evolutionary information is particularly useful for this prediction and that combining the three inputs provides substantial improvements when compared to using these inputs individually. Comparative empirical assessments using low-similarity test datasets reveal that CLIP secures area under receiver operating characteristic curve (AUC) of 0.8 and substantially improves over the results produced by the closest current tools that predict MoRFs and disordered protein-binding regions. The webserver of CLIP is freely available at http://biomine.cs.vcu.edu/servers/CLIP/ and the standalone code can be downloaded from http://yanglab.qd.sdu.edu.cn/download/CLIP/.
Dimensionality reduction approach for many-objective epistasis analysis
Authors: Yang Cheng-Hong , Hou Ming-Feng , Chuang Li-Yeh , Yang Cheng-San , Lin Yu-Da
Published: December 2022

In epistasis analysis, single-nucleotide polymorphism–single-nucleotide polymorphism interactions (SSIs) among genes may, alongside other environmental factors, influence the risk of multifactorial diseases. To identify SSI between cases and controls (i.e. binary traits), the score for model quality is affected by different objective functions (i.e. measurements) because of potential disease model preferences and disease complexities. Our previous study proposed a multiobjective approach-based multifactor dimensionality reduction (MOMDR), with the results indicating that two objective functions could enhance SSI identification with weak marginal effects. However, SSI identification using MOMDR remains a challenge because the optimal measure combination of objective functions has yet to be investigated. This study extended MOMDR to the many-objective version (i.e. many-objective MDR, MaODR) by integrating various disease probability measures based on a two-way contingency table to improve the identification of SSI between cases and controls. We introduced an objective function selection approach to determine the optimal measure combination in MaODR among 10 well-known measures. In total, 6 disease models with and 40 disease models without marginal effects were used to evaluate the general algorithms, namely those based on multifactor dimensionality reduction, MOMDR and MaODR. Our results revealed that the MaODR-based three objective function model, correct classification rate, likelihood ratio and normalized mutual information (MaODR-CLN) exhibited the higher 6.47% detection success rates (Accuracy) than MOMDR and higher 17.23% detection success rates than MDR through the application of an objective function selection approach. In a Wellcome Trust Case Control Consortium, MaODR-CLN successfully identified the significant SSIs (P < 0.001) associated with coronary artery disease. We performed a systematic analysis to identify the optimal measure combination in MaODR among 10 objective functions. Our combination detected SSIs-based binary traits with weak marginal effects and thus reduced spurious variables in the score model. MOAI is freely available at https://sites.google.com/view/maodr/home.
RatesTools: a Nextflow pipeline for detecting de novo germline mutations in pedigree sequence data
Authors: Armstrong Ellie E , Campana Michael G
Published: December 2022

Here, we introduce RatesTools, an automated pipeline to infer de novo mutation rates from parent–offspring trio data of diploid organisms. By providing a reference genome and high-coverage, whole-genome resequencing data of a minimum of three individuals (sire, dam and offspring), RatesTools provides a list of candidate de novo mutations and calculates a putative mutation rate. RatesTools uses several quality filtering steps, such as discarding sites with low mappability and highly repetitive regions, as well as sites with low genotype and mapping qualities to find potential de novo mutations. In addition, RatesTools implements several optional filters based on post hoc assumptions of the heterozygosity and mutation rate of the organism. Filters are highly customizable to user specifications in order to maximize utility across a wide range of applications.

Availability and implementation

RatesTools is freely available at https://github.com/campanam/RatesTools under a Creative Commons Zero (CC0) license. The pipeline is implemented in Nextflow (Di Tommaso et al., 2017), Ruby (http://www.ruby-lang.org), Bash (https://www.gnu.org/software/bash/) and R (R Core Team, 2020) with reliance upon several other freely available tools. RatesTools is compatible with macOS and Linux operating systems.

Supplementary information

Supplementary data are available at Bioinformatics online.
Impact of rectal washout on recurrence and survival after anterior resection for rectal cancer
Authors: Svensson Neufert Rebecca , Jörgren Fredrik , Buchwald Pamela
Published: December 2022

Background

Rectal washout (RW) is routinely performed during anterior resection (AR) for rectal cancer to reduce local recurrence (LR), although is sometimes not performed during minimally invasive surgery (MIS) procedures due to technical challenges and time consumption. The aim was to investigate the impact of RW on the oncological outcome after AR for rectal cancer in a registry cohort.

Methods

Data on patients registered in the Swedish Colorectal Cancer Registry who had undergone elective radical (R0) AR for TNM stage I–III rectal cancer between 2007 and 2017 with a 3-year follow-up were analysed. Multivariable analyses were performed and the primary endpoint was LR at 3 and 5 years after AR. The occurrence of distant metastasis (DM) and overall recurrence (OAR), overall survival, and relative survival were also analysed as a secondary aim. A subgroup analysis was performed for the same outcomes in patients treated with MIS.

Results

Out of 6186 patients (1923 with TNM stage I, 1907 with TNM stage II, and 2356 with TNM stage III), RW was performed in 5706 (92.2 per cent). The median age of the cohort was 67 years. RW did not impact the 3-year risk of LR. LR within 5 years occurred in 104 of 4583 patients (2.3 per cent) in the RW group compared with 16 of 408 patients (3.9 per cent) in the no RW group (P = 0.037). In multivariable analysis of the LR risk, the HR was 0.53 (95 per cent c.i. 0.31 to 0.90), favouring RW. There were no differences in rates of DM and OAR, overall survival, and relative survival. A subgroup analysis of the 1410 patients undergoing MIS did not demonstrate any differences between the groups, given, however, the low rate of LR.

Conclusions

RW in AR for rectal cancer does not impact the 3-year oncological outcome; however, after the 5-year follow-up a reduction in LR risk was observed after RW.
Industry and academia—a perfect match
Authors: van Vuuren Hennie J J , Cooper Terrance G
Published: December 2022

My career developed very differently from those of most academic researchers. After school, I worked for 6 years in industries that employed yeast to manufacture ethanol and beer. At university, I was trained as a microbiologist with very little training in molecular biology. I retrained in 1987 in molecular yeast genetics and focused on genetic engineering of industrial yeasts to minimize the production of spoilage compounds in wine and ethyl carbamate, a carcinogen, in wine. The malolactic yeast ML01 and the urea-degrading yeast were the first genetically enhanced yeasts that obtained US FDA approval for commercial applications. Apart from applied research, I was fascinated by classic molecular yeast genetic studies using sophisticated techniques such as transcriptomics, proteomics, and metabolomics. Doing research at the University of British Columbia was stimulating and exciting, we established a core microarray and metabolomics facility that was used by many scientists at UBC and hospitals in Vancouver. I also established a state-of-the-art Wine Library that was used to study aging of wines produced in British Columbia. Finally, I have been fortunate to know and collaborate with leading yeast scientists who motivated me.
Comparisons between non-interferometric and interferometric passive surface wave imaging methods—towards linear receiver array
Authors: Cheng Feng , Xia Jianghai , Xu Zongbo , Ajo-Franklin Jonathan B
Published: December 2022

Passive seismic methods in highly populated urban areas have gained much attention from the geophysics and civil engineering communities. Linear arrays are usually deployed for passive surface wave investigations because of their high convenience, and passive surface wave imaging methods commonly used for linear arrays can be grouped as non-interferometric methods (e.g. passive multichannel analysis of surface wave, refraction microtremor) and interferometric methods (e.g. multichannel analysis of passive surface waves and spatial autocorrelation). It is well known that the seismic interferometry method is able to retrieve Green’s function between inter-station pairs based on passive seismic data and that is how interferometric methods work. Although non-interferometric methods are also popular and effective in near-surface seismic imaging, particularly in the geotechnical industry, there is no theoretical proof to clarify the accuracy and/or the bias of these methods. In this study, we use numerical derivations and simulations to demonstrate the underlying physics for both non-interferometric and interferometric methods, under two common noise source environments including a homogeneous source distribution and a dominant in-line source distribution. We also prove the strength of interferometric methods for accurate dispersion imaging over the non-interferometric methods, and provide a way to estimate the biases in non-interferometric measurements. Finally, we present comprehensive comparisons between different passive surface wave methods with three typical field examples considering various observation systems.
Partitioning local seismogram wavefields using continuous wavelet transform methods for IRIS wavefield experiment arrays
Authors: Bolarinwa Oluwaseyi J , Langston Charles A
Published: December 2022

We applied nonlinear thresholding and scale–time gating in the continuous wavelet transform (CWT) domain to denoise, identify and characterize seismic phases contained in gradiometer and phased array waveforms of four seismic events recorded during the 2016 Incorporated Research Institutions of Seismology Wavefields Experiment in northern Oklahoma. A dense, 80-element three component phased array was subset from the linear array deployments to examine background noise, waveform coherence and seismic wave composition for local explosion and earthquake waveforms. CWT techniques were also used to significantly improve gradiometery analyses for data recorded by the geodetic array subexperiment. We observed as much as two orders of magnitude gain in the data signal-to-noise ratio. We also saw improvement in array beam quality after denoising the seismic data. Using the signal partitioning technique, we were able to extract and identify many phases based on their positions on the scale–time plane. CWT denoising and wavefield decomposition techniques also improved gradiometry analysis results from the 112-element geodetic array (also called the gradiometer) since waves could be separated before the computation of wave attributes. The operations of removing noise and gating out signal phases improved signal coherence across array records and provided clear P wave onsets on horizontal records, which can mitigate phase picking error and resulting event location uncertainty.
Population diversity analyses provide insights into key horticultural traits of Chinese native thymes
Authors: Sun Meiyu , Zhang Yanan , Bai Hongtong , Sun Guofeng , Zhang Jinzheng , Shi Lei
Published: December 2022

Chinese native thymes (CNTs) in the genus Thymus (family Lamiaceae) are rich in bioactive terpenes, which exert antiviral, anti-inflammatory, antioxidation, immunological, and antimicrobial effects. Plants exhibit morphological variation, including erect-type and creeping-type growth forms; however, the molecular mechanisms underlying important horticultural traits have not been determined. Here, we collected 39 CNTs providing strategic plant resources for studies of lignin, terpenoids, and glandular trichomes of thymes. Using resequencing data as well as phenotypic, metabonomic, phylogenetic, population genetic, and transcriptomic analyses, we identified and characterized key genes involved in lignin biosynthesis, terpenoid biosynthesis, and glandular trichome formation. We found many regulatory genes or transcription factors related to these three important horticultural traits, including genes encoding caffeic acid O-methyltransferase (COMT), terpene synthase (TPS), v-myb avian myeloblastosis viral oncogene homolog (MYB), and homeodomain-leucine zipper (HD-ZIP). Population diversity analyses provided insights into growth form, terpenoid, and glandular trichome evolution in CNTs. Furthermore, our results revealed that T. mongolicus accessions might be wild ancestors, and T. quinquecostatus, T. quinquecostatus var. asiaticus, and T. quinquecostatus var. przewalskii might be transitional accessions that derived from T. mongolicus accessions. Finally, T. nervulosus, T. inaequalis, T. mandschuricus, T. curtus, T. amurensis, T. proximus, T. altaicus, T. roseus, and T. marschallianus showed high divergence. We found evidence for introgression between erect-type European cultivated thymes and CNTs. These findings improve our understanding of the determinants of variation in horticultural traits and provide candidate loci for research and breeding.