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Although influences of the Atlantic multidecadal variability (AMV) and atmospheric heat source over the Tibetan Plateau (TPHS) on the East Asian summer rainfall (EASR) have been previously investigated, the relationship between the AMV and TPHS and their synergistic impact on the EASR are still unclear. We investigate the distinct relationship between the AMV and TPHS, and the role of the Tibetan Plateau (TP) on the impact of AMV on the EASR in this study. Results show that the AMV exerts a remote effect on the EASR through an atmospheric teleconnection, and the TP serves as a booster of this remote effect. The warming of the North Atlantic (positive phase of AMV) enhances the Asian summer monsoon through a zonal wave train along the northern midlatitudes, yielding an anomalous tripole rainfall pattern over East Asia. The enhanced warm and moist monsoon airflow converges and climbs up along the southern and eastern flanks of the TP, resulting in stronger latent heating over the TP than over other regions along the same latitude, due to the orographic effect of the huge plateau. The enhanced TPHS, in turn, further strengthens the summer monsoon and the East Asian tripole rainfall pattern by exciting a downstream meridional wave train. When the AMV and TPHS are in phase, the zonal wave train originating from the North Atlantic is strong and propagates eastward to the Asia–Pacific regions, significantly regulating the East Asian summer monsoon. Notably, the TP boosts this remote impact of the AMV through the effect of superimposition. Significance Statement The Atlantic multidecadal variability and atmospheric heat source over the Tibetan Plateau have been proposed as key drivers of the decadal–multidecadal climate variability in East Asia. In this study, we reveal a distinctive relationship between the Atlantic multidecadal variability and atmospheric heat source over the Tibetan Plateau. Moreover, our study shows that the Atlantic multidecadal variability exerts a remote effect on the East Asian summer rain through a zonal atmospheric teleconnection, and the Tibetan Plateau serves as a booster of this remote effect. Our results would be important for the understanding and predicting the decadal–multidecadal variations of summer climate in East Asia.

Background: Hemoglobinopathy is the most common monogenic disease worldwide. The aims of the current study were: (1) to investigate some hematological characteristics of patients with hemoglobinopathies; and (2) to detect the mutation of α-globin and β-globin genes, as well as the association between genotype and degree of anemia. Materials and method: 251 patients with hemoglobinopathies were examined for the α-globin or β-globin gene mutations. Results: 51% were the carriers, and 49% were thalassemia intermedia or thalassemia major. Hematological characteristics were suitable for α-thalassemia or β-thalassemia. Elevenβ-globin gene mutations were observed. The β0/βA, βE/βA, βE/βE, βE/β+, β+/β+ genotypes were only found in β-thalassemia intermedia individuals; the β0/β0 genotype was limited to β-thalassemia major patients; the β+/β0 and βE/β0 genotypes were seen in both types. Four α-globin gene mutations were observed. All α-thalassemia patients were intermedia, the most common genotype was --SEA/-α3.7. Conclusion: There were differences in anemia degree between β-globin genotypes Key words: hemoglobinopathies, α-globin, β-globin.

Background: Thalassemia is the most common monogenic disease worldwide. The severity of thalassemia depends on the degree of imbalance between the α-globin and β-globin chains. The aims of the current study were (1) to describe clinical and hematological characteristics of β-thalassemia patients; and (2) to investigate mutations of β-globin gene using Sanger sequencing, as well as the association between β-globin genotype and severity of β-thalassemia. Materials and method: 57 β-thalassemia patients treated at Hue Central Hospital were examined by sequencing the whole β-globin gene. Results: 80.7% with β-thalassemia intermedia, 19.3% with β-thalassemia major. Patients had 100% anemia, 75.4% splenomegaly, 50.9% hepatomegaly, 38.6% thalassemia facies, 28.1% jaundice and 15.8% iron overload; The red blood cell indices were decreased: Hb 7.5 ± 1.3 g/dL, MCV 70.9 ± 8.4 fL, MCH 20.5 ± 2.1 pg. Hemoglobin composition included HbA 35.2 ± 33.9%, HbA2 6.1 ± 2.7%, HbF 24.8 ± 18.0%, and HbE 38.6 ± 15.2%. Nine β-globin gene mutations were observed. The most common genotype was βE/β0, which occupied 80.7%. The βE/βA, β0/βA and βE/β+ genotypes were only found in β-thalassemia intermedia individuals, while the β0/β0 genotype was limited to β-thalassemia major patients. The βE/β0 genotype was seen in both types. Conclusion: There was differences in age of blood transfusion initiation between the genotypes. Among them, the β0/β0 genotype was the most severe. Key words: β-thalassemia intermedia, β-thalassemia major, genotype.

An unprecedented cold wave intruded into East Asia in early January 2021 and led to record-breaking or historical extreme low temperatures over vast regions. This study shows that a major stratospheric sudden warming (SSW) event at the beginning of January 2021 exerted an important influence on this cold wave. The major SSW event occurred on 2 January 2021 and subsequently led to the displacement of the stratospheric polar vortex to the East Asian side. Moreover, the SSW event induced the stratospheric warming signal to propagate downward to the mid-to-lower troposphere, which not only enhanced the blocking in the Urals–Siberia region and the negative phase of the Arctic Oscillation, but also shifted the tropospheric polar vortex off the pole. The displaced tropospheric polar vortex, Ural blocking, and another downstream blocking ridge over western North America formed a distinct inverted omega-shaped circulation pattern (IOCP) in the East Asia–North Pacific sector. This IOCP was the most direct and impactful atmospheric pattern causing the cold wave in East Asia. The IOCP triggered a meridional cell with an upward branch in East Asia and a downward branch in Siberia. The meridional cell intensified the Siberian high and low-level northerly winds, which also favored the invasion of the cold wave into East Asia. Hence, the SSW event and tropospheric circulations such as the IOCP, negative phase of Arctic Oscillation, Ural blocking, enhanced Siberian high, and eastward propagation of Rossby wave eventually induced the outbreak of an unprecedented cold wave in East Asia in early January 2021.

Cryo-electron microscopy (cryo-EM) allows a macromolecular structure such as protein-DNA/RNA complexes to be reconstructed in a three-dimensional coulomb potential map. The structural information of these macromolecular complexes forms the foundation for understanding the molecular mechanism including many human diseases. However, the model building of large macromolecular complexes is often difficult and time-consuming. We recently developed DeepTracer-2.0, an artificial intelligence-based pipeline that can build amino acid and nucleic acid backbones from a single cryo-EM map, and even predict the best-fit residues according to the density of side chains. The experiments showed improved accuracy and efficiency when benchmarking the performance on independent experimental maps of protein-DNA/RNA complexes and demonstrated the promising future of macromolecular modeling from cryo-EM maps. Our method and pipeline could benefit researchers worldwide who work in molecular biomedicine and drug discovery, and substantially increase the throughput of the cryo-EM model building. The pipeline has been integrated into the web portal https://deeptracer.uw.edu/.

This study presents a comprehensive analysis of the synergistic impacts of the Atlantic multidecadal oscillation (AMO) and Pacific decadal oscillation (PDO) on the interdecadal variations of summer rainfall in Northeast Asia. Following the construction of four probable scenarios under various combinations of the AMO and PDO phases, it is found that when the AMO and PDO are out of phase, both of them induce a strong or weak East Asian summer monsoon and a low or high pressure system over Northeast Asia through atmospheric teleconnection, which results in significant wet or dry conditions over the whole of Northeast Asia through the effects of superimposition. In contrast, when the AMO and PDO are in-phase, they induce moderate and regional wet or dry conditions in Northeast Asia, and only a slightly strong or weak East Asian summer monsoon through the effects of cancellation. During the mid-1960s–1990s, a period of drought first began in Northeast Asia under a negative AMO and negative PDO in the mid-1960s, which then increased in severity under a negative AMO and positive PDO in the 1980s, before finally coming to an end under a positive AMO and negative PDO in the late 1990s. The interdecadal predictability of summer rainfall in Northeast Asia may reside in the interdecadal behavior of the North Atlantic and Pacific Oceans.

While early genetic and low-resolution structural observations suggested that extracellular conductive filaments on metal-reducing organisms such as Geobacter were composed of type IV pili, it has now been established that bacterial c-type cytochromes can polymerize to form extracellular filaments capable of long-range electron transport. Atomic structures exist for two such cytochrome filaments, formed from the hexaheme cytochrome OmcS and the tetraheme cytochrome OmcE. Due to the highly conserved heme packing within the central OmcS and OmcE cores, and shared pattern of heme coordination between subunits, it has been suggested that these polymers have a common origin. We have now used cryo-electron microscopy (cryo-EM) to determine the structure of a third extracellular filament, formed from the Geobacter sulfurreducens octaheme cytochrome, OmcZ. In contrast to the linear heme chains in OmcS and OmcE from the same organism, the packing of hemes, heme:heme angles, and between-subunit heme coordination is quite different in OmcZ. A branched heme arrangement within OmcZ leads to a highly surface exposed heme in every subunit, which may account for the formation of conductive biofilm networks, and explain the higher measured conductivity of OmcZ filaments. This new structural evidence suggests that conductive cytochrome polymers arose independently on more than one occasion from different ancestral multiheme proteins.

Objective. Unrolled algorithms are a promising approach for reconstruction of CT images in challenging scenarios, such as low-dose, sparse-view and limited-angle imaging. In an unrolled algorithm, a fixed number of iterations of a reconstruction method are unrolled into multiple layers of a neural network, and interspersed with trainable layers. The entire network is then trained end-to-end in a supervised fashion, to learn an appropriate regularizer from training data. In this paper we propose a novel unrolled algorithm, and compare its performance with several other approaches on sparse-view and limited-angle CT. Approach. The proposed algorithm is inspired by the superiorization methodology, an optimization heuristic in which iterates of a feasibility-seeking method are perturbed between iterations, typically using descent directions of a model-based penalty function. Our algorithm instead uses a modified U-net architecture to introduce the perturbations, allowing a network to learn beneficial perturbations to the image at various stages of the reconstruction, based on the training data. Main Results. In several numerical experiments modeling sparse-view and limited angle CT scenarios, the algorithm provides excellent results. In particular, it outperforms several competing unrolled methods in limited-angle scenarios, while providing comparable or better performance on sparse-view scenarios. Significance. This work represents a first step towards exploiting the power of deep learning within the superiorization methodology. Additionally, it studies the effect of network architecture on the performance of unrolled methods, as well as the effectiveness of the unrolled approach on both limited-angle CT, where previous studies have primarily focused on the sparse-view and low-dose cases.

While early genetic and low resolution structural observations suggested that extracellular conductive filaments on metal reducing organisms such as Geobacter were composed of Type IV pili, it has now been established that bacterial c-type cytochromes can polymerize to form extracellular filaments capable of long-range electron transport. Atomic structures exist for two such cytochrome filaments, formed from the hexaheme cytochrome OmcS and the tetraheme cytochrome OmcE. Due to the highly conserved heme packing within the central OmcS and OmcE cores, and shared pattern of heme coordination between subunits, it has been suggested that these polymers have a common origin. We have now used cryo-EM to determine the structure of a third extracellular filament, formed from the Geobacter sulfurreducens octaheme cytochrome, OmcZ. In contrast to the linear heme chains in OmcS and OmcE, the packing of hemes, heme:heme angles, and between-subunit heme coordination is quite different in OmcZ. A branched heme arrangement within OmcZ leads to a highly surface exposed heme in every subunit, which may account for the formation of conductive biofilm networks, and explain the higher measured conductivity of OmcZ filaments. This new structural evidence suggests that conductive cytochrome polymers arose independently on more than one occasion from different ancestral multiheme proteins.

While early genetic and low-resolution structural observations suggested that extracellular conductive filaments on metal-reducing organisms such as

The recent revolution in cryo-electron microscopy has made it possible to determine macromolecular structures directly from cell extracts. However, identifying the correct protein from the cryo-EM map is still challenging and often needs additional sequence information from other techniques, such as tandem mass spectrometry and/or bioinformatics. Here, we present DeepTracer-ID, a server-based approach to identify the candidate protein in a user-provided organism de novo from a cryo-EM map, without the need for additional information. Our method first uses DeepTracer to generate a protein backbone model that best represents the cryo-EM map, and this model is then searched against the library of AlphaFold2 predictions for all proteins in the given organism. This method is highly accurate and robust: in all 13 experimental maps tested blindly, DeepTracer-ID identified the correct proteins as the top candidates. Eight of the maps were of known structures, while the other five unpublished maps were validated by prior protein annotation and careful inspection of the model refined into the map. The program also showed promising results for both homomeric and heteromeric protein complexes. This platform is possible because of the recent breakthroughs in large-scale protein 3D structure prediction.Statement of SignificanceWhile it has now become routine for cryo-EM maps of proteins to reach a near-atomic resolution, potentially allowing for reliable atomic models to be built, there are a growing number of instances where the protein identity may not be known. Without knowing the protein sequence, it is impossible to build an atomic model. DeepTracer-ID is a server-based approach to surmount this problem by identifying the proteins in a given organism that are found in the cryo-EM map. A free web service for global academic access is provided.

Smart homes are an element of developing smart cities. In recent years, countries around the world have spared no effort in promoting smart cities. Smart homes are an interesting technological advancement that can make people’s lives much more convenient. The development of smart homes involves multiple technological aspects, which include big data, mobile networks, cloud computing, Internet of Things, and even artificial intelligence. Digital information is the main component of signal control and flow in a smart home, while information security is another important aspect. In the event of equipment failure, the task of safeguarding the system’s information is of the utmost importance. Since smart homes are automatically controlled, the problem of mobile network security must be taken seriously. To address these issues, this paper focuses on information security, big data, mobile networks, cloud computing, and the Internet of Things. Security efficiency can be enhanced by using a Secure Hash Algorithm 256 (SHA-256), which is an authentication mechanism that, with the help of the user, can authenticate each interaction of a given device with a WebServer by using an encrypted username, password, and token. This framework could be used for an automated burglar alarm system, guest attendance monitoring, and light switches, all of which are easily integrated with any smart city base. In this way, IoT solutions can allow real-time monitoring and connection with central systems for automated burglar alarms. The monitoring framework is developed on the strength of the web application to obtain real-time display, storage, and warning functions for local or remote monitoring control. The monitoring system is stable and reliable when applying SHA-256.

Stimulus-induced in situ forming hydrogels possess the characteristics of easy management and minimal invasiveness via simple injection at target sites with a liquid and easy forming bulk gels. In the present study, a photoreactive monomer, N’-(2-nitrobenzyl)-N-acryloyl glycinamide (NBNAGA) was introduced to modify polyacrylamide (PAM) hydrogel preparation with stimuli responsiveness. Firstly, poly(acrylamide-co-N’-(2-nitrobenzyl)-N-acryloyl glycinamide), P(AM-co-NBNAGA), copolymer solution was prepared via reversible addition fragmentation chain transfer (RAFT) polymerization using the monomers mixture of AM, NBNAGA, and N,N’- methylene bis-acrylamide (BIS). The obtained polymer solution with viscous, transparent, and flowable appearance contained weak single hydrogen bonding and slight chemical crosslinking in a microscopic perspective. Secondly, without further purification, after irradiation using UV light at 365 nm, poly(acrylamide-co-N-acryloyl glycinamide) (P(AM-co-NAGA)) hydrogel conveniently in situ formed due to the cleavage of o-nitrobenzyl groups and the corresponding emergency of dual hydrogen bonding among “uncaged” dual amide moieties. P(AM-co-NAGA) hydrogel depicted both favorable temperature sensitivity and self-healing properties, then the heating induced in vitro release profiles of doxorubicin (DOX) was analyzed.

The orthogonal experiment method is used in optimal design of laser cladding, such as laser power (P), scanning speed (SS), powder feeding rate (PFR) and shielding gas velocity (SGV) etc. Both the dilution rate and the aspect ratio are investigated by comprehensive scoring method, which transforms multi-index into single index. In view of the nonlinear characteristics of laser cladding process parameters, the optimum level of each factor based on interaction effect is obtained by analyzing binary tables. Finally, the relationship between the laser cladding process parameters and the two indexes (the dilution rate and the ratio of width to height of coating) is obtained. This method has potential applications for the further investigating on the laser cladding process rules.

Based on surface air temperature and precipitation observation data and NCEP/NCAR atmospheric reanalysis data, this study evaluates the prediction of East Asian summer climate during 1959–2016 undertaken by the CESM (Community Earth System Model) large-ensemble initialized decadal prediction (CESM-DPLE) project. The results demonstrate that CESM-DPLE can reasonably capture the basic features of the East Asian summer climate and associated main atmospheric circulation patterns. In general, the prediction skill is quite high for surface air temperature, but less so for precipitation, on the interannual timescale. CESM-DPLE reproduces the anomalies of mid- and high-latitude atmospheric circulation and the East Asian monsoon and climate reasonably well, all of which are attributed to the teleconnection wave train driven by the Atlantic Multidecadal Oscillation (AMO). A transition into the warm phase of the AMO after the late 1990s decreased the geopotential height and enhanced the strength of the monsoon in East Asia via the teleconnection wave train during summer, leading to excessive precipitation and warming over East Asia. Altogether, CESM-DPLE is capable of predicting the summer temperature in East Asia on the interannual timescale, as well as the interdecadal variations of East Asian summer climate associated with the transition of AMO phases in the late 1990s, albeit with certain inadequacies remaining. The CESM-DPLE project provides an important resource for investigating and predicting the East Asian climate on the interannual and decadal timescales.

Electrically conductive appendages from the anaerobic bacterium Geobacter sulfurreducens were first observed two decades ago, with genetic and biochemical data suggesting that conductive fibres were type IV pili. Recently, an extracellular conductive filament of G. sulfurreducens was found to contain polymerized c-type cytochrome OmcS subunits, not pilin subunits. Here we report that G. sulfurreducens also produces a second, thinner appendage comprised of cytochrome OmcE subunits and solve its structure using cryo-electron microscopy at ~4.3 Å resolution. Although OmcE and OmcS subunits have no overall sequence or structural similarities, upon polymerization both form filaments that share a conserved haem packing arrangement in which haems are coordinated by histidines in adjacent subunits. Unlike OmcS filaments, OmcE filaments are highly glycosylated. In extracellular fractions from G. sulfurreducens, we detected type IV pili comprising PilA-N and -C chains, along with abundant B-DNA. OmcE is the second cytochrome filament to be characterized using structural and biophysical methods. We propose that there is a broad class of conductive bacterial appendages with conserved haem packing (rather than sequence homology) that enable long-distance electron transport to chemicals or other microbial cells.

During January 21–24, 2016, most land areas in the Northern Hemisphere experienced extreme low temperatures. In North America, a historic snowstorm hit the northern and eastern United States. In East Asia, an unprecedented cold wave occurred and led to record‐breaking low temperatures in many regions. In this study, observational analyses revealed that both extreme events were triggered by a remarkable change in atmospheric circulation in the Arctic region in early January 2016, which switched from a concentric ring pattern to a dipole pattern. The dipole pattern resulted in two inverted Ω‐shaped circulation patterns that dominated the North America and East Asia. The inverted Ω‐shaped circulation patterns induced remarkable tropopause folding, which conveyed high‐potential‐vorticity cold air downwards from the lower stratosphere of Arctic to the middle and lower troposphere of North America, which increased cyclonic vorticity and negative height perturbations, and converged with moist air from the western North Atlantic and Gulf Stream, resulting in a severe snowstorm in the northern and eastern United States from 22 to 24 January. In East Asia, the tropopause folding transported high‐potential‐vorticity cold air downwards to the middle and lower troposphere of East Asia, resulting in the outbreak of a severe cold wave in East Asia from 21 to 24 January.

Dementia is a disease characterized by cognitive impairment that leads to incoherent or illogical thoughts and speech. There are attempts to identify dementia through speech analyses, but there is a dearth of research on casual conversation analysis. This work examined communication impairment detection of people with early-stage memory loss, including mild dementia and mild cognitive impairment. The data sets included semi-structured interviews from two studies conducted at the University of Washington (UW), the DementiaBank’s Pitt Corpus, and the ADReSS Challenge at INTERSPEECH 2020. We applied Transformer-based deep learning models to automatically extract linguistic features for identifying individuals with dementia. Our results showed the models’ abilities on detecting linguistic deficits with the best mean F1-score of 76% on the Pitt Corpus, 84% on the ADReSS, 90% on the augmented ADReSS, and 74% on the UW transcripts. The results suggest the potential possibility of a more flexible examination setting, casual semi-structured individual or group interview, for detecting incoherent or illogical thoughts and speech in patients with dementia.

In contrast to dominant interannual time-scale variability in other ocean basins, the leading observed mode variability in the Atlantic is characterized as a basinwide seesaw-like sea surface temperature variability between the North and South Atlantic on a multidecadal time scale (approximately 60–80 years), known as the Atlantic multidecadal variability (AMV). AMV has been identified as a key driver for climate shifts that occurred in the mid-1960s and late 1990s. Here we attempt to predict the summer AMV by analyzing decadal prediction experiments from two climate models. Results show that these climate models with proper initialization do a better job than uninitialized historical runs, and are capable of predicting the observed AMV time evolution. Our models predict that the AMV will be in a neutral to slightly negative phase, leading to a warm–dry trend over western Europe and North Africa and a cold–wet trend (cold relative to the warming trend) over southeastern China and Indochina in the next few years.

Novel organic/inorganic hybrid star polymer was prepared dually crosslinked within inner-core via divinylbenzene (DVB) and outer-surface via octafunctional polyhedral oligomeric silsesquioxane (POSS). Core cross-linked star polymers bearing dialkynyl-terminated polystyrene arms, (dialkynyl-PS)n-CCL, were synthesized at first by the atom transfer radical polymerization (ATRP) of DVB using α,α-dialkynyl-terminated PS macroinitiator, followed by the subsequent fractionation. Under high dilution conditions, (dialkynyl-PS)n-CCL was subjected to surface cross-linking with octa(3-azidopropyl) polyhedral oligomeric silsesquioxane, POSS-(N3)8, via click reaction, affording POSS-functionalized hybrid polymer doubly cross-linked within core and surface regions, SCL-(PS)n-CCL. FT-IR, 1H NMR, GPC, and elemental analysis results revealed that on average, the obtained hybrid polymer possesses a cross-linked PDVB inner core, ∼14 linear PS arms (the Mw per arm of 5.1 kDa), and ∼4-5 POSS moieties at outer surface. Differential scanning calorimetry (DSC) thermograms and thermogravimetric analysis (TGA) revealed that after surface cross-linking the thermal stability of SCL-(PS)n-CCL is considerably improved. This work provides a proof-of-concept example for the preparation of dually cross-linked hybrid star polymer, which represents a novel category of organic/inorganic composite materials with unique chain architectures.

When meteorological stations are quite unevenly distributed, a simple regional arithmetic mean of observation data may assign an excessive weight to one region with dense stations, which affects the representativeness of the regional mean. In this study, we used the homogenized monthly maximum (Tmax), mean (Tm), and minimum (Tmin) temperature dataset at more than 2400 national surface meteorological stations in China. Based on a thin plate spline (TPS) interpolation method, we selected a three-dimensional (longitude, latitude, and elevation above sea level) interpolation model that is suitable for the temperature curve surface fitting in China, and constructed a gridded temperature dataset with a horizontal resolution of 0.5° during 1961 to 2015. Cross-validation indicates that the annual average of generalized cross-validation (GCV) is relatively small, and the ratio of GCV to the observed temperature is relatively low. Both the root of GCV and the root-mean-square error of temperature are smaller than those of the previous temperature gridded products. A comparison between our dataset and the Climate Research Unit (CRU) TS4.02 dataset indicates that the CRU’s data overestimate the warming trend in China during 1961–1984, whereas underestimate the warming trend during 1985–2015.

Observational analysis shows that the Atlantic Multidecadal Variability (AMV) is a major driver of climate variability in the Northern Hemisphere through a zonal atmospheric teleconnection extending from the North Atlantic Ocean and propagating eastward around the Northern Hemisphere. We studied the fidelity of model simulations in reproducing the observed summer AMV and the associated impacts on the Earth’s climate by analyzing simulations using the National Center for Atmospheric Research Community Earth System Model Version 1 (CESM1), including CESM1 idealized and time–series pacemaker simulations, CESM1 large ensemble twentieth century uninitialized simulations and large ensemble initialized CESM1 decadal predictions. To further compare the fidelity of CESM1, we also analyzed large ensemble simulations from four other models. Our results suggest that the uninitialized large ensemble simulations from all models can produce an AMV time evolution and its regional climate impacts similar to the observations to certain degree. By initializing the observed oceanic condition in decadal prediction simulations, the simulated AMV and its regional impacts are closer to the observed ones than those in uninitialized ensemble simulations. In addition, the time–series pacemaker simulations that nudged the observed North Atlantic sea surface temperature anomalies produces spatiotemporal characteristics of the AMV and AMV climate impacts closer to the observed ones than the uninitialized simulations. We conclude that although coupled models can reproduce the observed AMV and its regional impacts, proper initialization and bias correction of the sea surface temperature spatial structure can significantly improve this capability. Further improvements in the fidelity of the simulated AMV depend on how to reduce model biases, especially the simulated teleconnections.

The N-end rule pathway was one of the first ubiquitin (Ub)-dependent degradation pathways to be identified. Ubr1, a single-chain E3 ligase, targets proteins bearing a destabilizing residue at the N-terminus (N-degron) for rapid K48-linked ubiquitination and proteasome-dependent degradation. How Ubr1 catalyses the initiation of ubiquitination on the substrate and elongation of the Ub chain in a linkage-specific manner through a single E2 ubiquitin-conjugating enzyme (Ubc2) remains unknown. Here, we report the cryo-electron microscopy structures of two complexes representing the initiation and elongation intermediates of Ubr1 captured using chemical approaches. In these two structures, Ubr1 adopts different conformations to facilitate the transfer of Ub from Ubc2 to either an N-degron peptide or a monoubiquitinated degron. These structures not only reveal the architecture of the Ubr1 complex but also provide mechanistic insights into the initiation and elongation steps of ubiquitination catalysed by Ubr1.

Advances in imagery at atomic and near-atomic resolution, such as cryogenic electron microscopy (cryo-EM), have led to an influx of high resolution images of proteins and other macromolecular structures to data banks worldwide. Producing a protein structure from the discrete voxel grid data of cryo-EM maps involves interpolation into the continuous spatial domain. We present a novel data format called the neural cryo-EM map, which is formed from a set of neural networks that accurately parameterize cryo-EM maps and provide native, spatially continuous data for density and gradient. As a case study of this data format, we create graph-based interpretations of high resolution experimental cryo-EM maps. Normalized cryo-EM map values interpolated using the non-linear neural cryo-EM format are more accurate, consistently scoring less than 0.01 mean absolute error, than a conventional tri-linear interpolation, which scores up to 0.12 mean absolute error. Our graph-based interpretations of 115 experimental cryo-EM maps from 1.15 to 4.0 Angstrom resolution provide high coverage of the underlying amino acid residue locations, while accuracy of nodes is correlated with resolution. The nodes of graphs created from atomic resolution maps (higher than 1.6 Angstroms) provide greater than 99% residue coverage as well as 85% full atomic coverage with a mean of than 0.19 Angstrom root mean squared deviation (RMSD). Other graphs have a mean 84% residue coverage with less specificity of the nodes due to experimental noise and differences of density context at lower resolutions. This work may be generalized for transforming any 3D grid-based data format into non-linear, continuous, and differentiable format for the downstream geometric deep learning applications., 15 pages, 8 figures

This paper describes outcomes of the 2019 Cryo-EM Model Challenge. The goals were to (1) assess the quality of models that can be produced from cryogenic electron microscopy (cryo-EM) maps using current modeling software, (2) evaluate reproducibility of modeling results from different software developers and users and (3) compare performance of current metrics used for model evaluation, particularly Fit-to-Map metrics, with focus on near-atomic resolution. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived by 13 participating teams from four benchmark maps, including three forming a resolution series (1.8 to 3.1 Å). The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual experiments and structure data archives such as the Protein Data Bank. We recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed cryo-EM map density., A multi-laboratory study in the form of a community challenge assesses the quality of models that can be produced from cryo-EM maps using different software tools, the reproducibility of models generated by different users and the performance of metrics used for model validation.

With new developments in biomedical technology, it is now a viable therapeutic treatment to alter genes with techniques like CRISPR. At the same time, it is increasingly cheaper to perform whole genome sequencing, resulting in rapid advancement in gene therapy and editing in precision medicine. Understanding the current industry and academic applications of gene therapy provides an important backdrop to future scientific developments. Additionally, machine learning and artificial intelligence techniques allow for the reduction of time and money spent in the development of new gene therapy products and techniques. In this paper, we survey the current progress of gene therapy treatments for several diseases and explore machine learning applications in gene therapy. We also discuss the ethical implications of gene therapy and the use of machine learning in precision medicine. Machine learning and gene therapy are both topics gaining popularity in various publications, and we conclude that there is still room for continued research and application of machine learning techniques in the gene therapy field.

MotivationIt has been a challenge for biologists to determine 3D shapes of proteins from a linear chain of amino acids and understand how proteins carry out life’s tasks. Experimental techniques, such as X-ray crystallography or Nuclear Magnetic Resonance, are time-consuming. This highlights the importance of computational methods for protein structure predictions. In the field of protein structure prediction, ranking the predicted protein decoys and selecting the one closest to the native structure is known as protein model quality assessment (QA), or accuracy estimation problem. Traditional QA methods don’t consider different types of features from the protein decoy, lack various features for training machine learning models, and don’t consider the relationship between features. In this research, we used multi-scale features from energy score to topology of the protein structure, and proposed a hierarchical architecture for training machine learning models to tackle the QA problem.ResultsWe introduce a new single-model QA method that incorporates multi-scale features from protein structures, utilizes the hierarchical architecture of training machine learning models, and predicts the quality of any protein decoy. Based on our experiment, the new hierarchical architecture is more accurate compared to traditional machine learning-based methods. It also considers the relationship between features and generates additional features so machine learning models can be trained more accurately. We trained our new tool, SynthQA, on the CASP dataset (CASP10 to CASP12), and validated our method on 33 targets from the latest CASP 14 dataset. The result shows that our method is comparable to other state-of-the-art single-model QA methods, and consistently outperforms each of the 14 used features.Availabilityhttps://github.com/Cao-Labs/SynthQA.gitContactcaora@plu.edu

This work studies the SWIPT-based half-duplex (HD) decode-and-forward (DF) relay network, wherein the relay user can scavenge power from the source’s radio-frequency (RF) signals and then utilize it to convey the information to the destination. Specifically, two SWIPT-based relaying schemes, termed static power splitting- (SPS-) based relaying (SPSR) and optimal dynamic power splitting- (DPS-) based relaying (ODPSR), are proposed to investigate the benefits of each one fully. Based on the above discussions, the relaying system’s performance for outage probability (OP) is studied. Concretely, we derive the analytical expressions for both SPSR and DPSR methods. Finally, the numerical simulations are executed to corroborate the analysis and simulation results.

Additional file 2: Table S2. Univariate and multivariate analyses of overall survival in all patients.

This paper investigates the decode-and-forward (DF) full-duplex (FD) relaying system under the presence of an eavesdropper. Moreover, the relay node is able to harvest energy from a transmitter, and then it uses the harvested energy for conveying information to the receiver. Besides, both two-hop and direct relaying links are taking into consideration. In the mathematical analysis, we derived the exact expressions for intercept probability and outage probability (OP) by applying maximal ratio combining (MRC) and selection combining (SC) techniques at the receiver. Next, the Monte Carlo simulation is performed to validate the mathematical analysis. The results show that the simulation curves match the mathematic expressions, which confirms the analysis section.

Additional file 3: Table S3. KEGG pathways of overlapping genes from DAVID analysis.

Additional file 1: Table S1. Primers used for quantitative real-time PCR.

Significance Electron cryomicroscopy (cryo-EM), a 2017 Nobel prize-awarded technology, provides direct 3D maps of macromolecules and explains the shape and interactions of protein complexes such as SARS-CoV-2 viral proteins and human cell receptors. This understanding can be combined with detailed structural information gathered using other technologies to form the basis for modeling course of diseases and for designing therapeutic drugs. However, ab initio modeling of protein complex structure remains a challenging problem. Here, we present DeepTracer, a fully automated and robust tool that determines the all-atom structure of a protein complex based solely on its cryo-EM map and amino acid sequence, with improved accuracy and efficiency compared to previous methods. We also provide a web service for global access., Information about macromolecular structure of protein complexes and related cellular and molecular mechanisms can assist the search for vaccines and drug development processes. To obtain such structural information, we present DeepTracer, a fully automated deep learning-based method for fast de novo multichain protein complex structure determination from high-resolution cryoelectron microscopy (cryo-EM) maps. We applied DeepTracer on a previously published set of 476 raw experimental cryo-EM maps and compared the results with a current state of the art method. The residue coverage increased by over 30% using DeepTracer, and the rmsd value improved from 1.29 Å to 1.18 Å. Additionally, we applied DeepTracer on a set of 62 coronavirus-related cryo-EM maps, among them 10 with no deposited structure available in EMDataResource. We observed an average residue match of 84% with the deposited structures and an average rmsd of 0.93 Å. Additional tests with related methods further exemplify DeepTracer’s competitive accuracy and efficiency of structure modeling. DeepTracer allows for exceptionally fast computations, making it possible to trace around 60,000 residues in 350 chains within only 2 h. The web service is globally accessible at https://deeptracer.uw.edu.

As a most important Chinese materia medica, Aconiti Lateralis Radix Praeparata(Fuzi) had been widely used in China for thousands of years. This herbalogical study was systematically performed based on variation characteristics of the naming, habitat, harvesting, processing and properties. The sharp toxicity of Fuzi had been well known since the spring and autumn period in the history, which was much earlier than that its medical properties was understood and applied. Sichuan province was regarded as the geo-authentic region of Fuzi all along, where the best quality goods could be provided for clinic use. The study showed the harvesting time of Fuzi was changing in different periods, and the possible effects were of climate change and artificial planting. The perishable characteris-tics of Fuzi severely limited its storage period; therefore, different kinds of storage methods were effectively used since Tang Dynasty. For thousands of years, Fuzi had been processed with various accessories to reduce toxicity, while simultaneously the study on processing mechanism was on going all the time. Fuzi was widely used in clinical practice to cure Yang depletion syndrome, which was based on its function of enhancing Yang and removing cold. Along with the further study on quality evaluation standard, Fuzi will probably get a much wider range of applications.

Si Yang Dong,* Hao Chen,* Li Zhi Lin, Lingli Jin, Dan Xiang Chen, Ou Chen Wang, Zhi Qiang Ye Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhi Qiang Ye; Ou Chen WangDepartment of Thyroid and Breast Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325000 People’s Republic of ChinaTel/Fax +86 13867705524Email yezhiqiang1982@126.com woc@wmu.edu.cnBackground: Microfibril-associated protein 2 (MFAP2) is a protein coding gene that exerts important phenotypic effects on cell motility, and increasing research has indicated that MFAP2 was correlated with many cancers. However, the functional and potential clinical role of MFAP2 in papillary thyroid cancer (PTC) has not yet been verified.Materials and Methods: We performed whole transcriptome sequencing on 78 paired PTC tissues and corresponding adjacent normal tissues and found that MFAP2 was highly expressed in PTC tissues. Then, we analyzed the expression of MFAP2 and its relation with the clinicopathological features of PTC in The Cancer Genome Atlas (TCGA) PTC genomic dataset. We detected MFAP2 expression in 40 paired PTC tissues and corresponding adjacent normal tissues through RT-qPCR (real time-quantitative polymerase chain reaction) to validate the sequencing data and TCGA cohort. Cell functional assays were performed to elucidate the function of MFAP2 in PTC cells, Western blot assay was performed to explore the correlation between MFAP2 and EMT (epithelial-mesenchymal transition)-related proteins.Results: Statistical analysis showed that MFAP2 was obviously upregulated in PTC tissues compared to matched normal tissues, and the expression levels of MFAP2 in PTC tissues were strongly related with lymph node metastasis (p=0.016). The results of RT-qPCR of our own tissue specimens showed the same conclusions as that in TCGA dataset. The results of functional assays in PTC cell lines showed that MFAP2 could promote proliferation, colony formation, migration and invasion abilities and decrease the apoptotic rate in PTC cells. Western Blot assay showed that MFAP2 could regulate the expression of EMT-related proteins.Conclusion: MFAP2 increases the proliferation, motility and decreases the apoptosis of PTC cells, and might be a potential therapeutic target for papillary thyroid cancer.Keywords: biomarker, proliferation, migration, epithelial-mesenchymal transition, EMT, apoptosis

Preclinical studies of traumatic brain injury (TBI) are often performed using a murine model of mild traumatic brain injury (mTBI) due to highly controlled settings and high reproducibility in this experimental model, compared to studies of human TBI. We have previously demonstrated persistent changes in the sleep wake cycle using a widely accepted mouse model of mTBI. The gold standard of sleep wake assessment is achieved by recording brain electroencephalogram (EEG), which not only allows for standard sleep staging but also allows further signal processing through quantitative EEG methods. Conventional methods of sleep staging require manual scoring by a trained expert. Here, a 1-D deep convolutional neural network (Deep CNN) is proposed to automatically score sleep stages and identify mTBI from a single-channel EEG signal with duration of 64 seconds by classifying the EEG signal into one of four classes: sham (control) wake, sham (control) sleep, mTBI wake, and mTBI sleep. We demonstrated that the proposed Deep CNN has the ability to learn features to classify the target classes. Deployment of the trained model on Raspberry Pi further indicates the capacity to perform classification in real time and mobile applications. Thus, the proposed system has the potential to provide a low-cost and fast method for detection of TBI in individuals.