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The L/C-based fixed-admittance model (L/C model) is usually used in the real-time simulation for power electronic converters. However, the L/C switch model suffers from the problems of virtual power loss and complicated optimal parameter settings. This paper proposes a small-step synthesis real-time simulation method suitable for power electronic converters. By modeling the power electronic converter with a small (nanosecond) time-step and simulating with a normal (microsecond) time-step, the issue of virtual power loss of the L/C model caused by the transient process after the switching action is solved. The real-time simulation experiments with different type converters based on one set of simulation parameters are carried out on FPGA separately to verify the insensitivity to converter topologies. Furthermore, the real-time simulation results of the small-step synthesis method using the L/C model are compared with those of the traditional EMTP method using the L/C model and the Ron/Roff model. The simulation results provide verification of the effectiveness of the small-step synthesis method as well as the insensitivity to carrier frequencies, and L/C model parameters.

BackgroundLow temperature is conducive to the survival of COVID-19. Some studies suggest that cold-chain environment may prolong the survival of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and increase the risk of transmission. However, the effect of cold-chain environmental factors and packaging materials on SARS-CoV-2 stability remains unclear.MethodsThis study aimed to reveal cold-chain environmental factors that preserve the stability of SARS-CoV-2 and further explore effective disinfection measures for SARS-CoV-2 in the cold-chain environment. The decay rate of SARS-CoV-2 pseudovirus in the cold-chain environment, on various types of packaging material surfaces, i.e., polyethylene plastic, stainless steel, Teflon and cardboard, and in frozen seawater was investigated. The influence of visible light (wavelength 450 nm-780 nm) and airflow on the stability of SARS-CoV-2 pseudovirus at -18°C was subsequently assessed.ResultsExperimental data show that SARS-CoV-2 pseudovirus decayed more rapidly on porous cardboard surfaces than on nonporous surfaces, including polyethylene (PE) plastic, stainless steel, and Teflon. Compared with that at 25°C, the decay rate of SARS-CoV-2 pseudovirus was significantly lower at low temperatures. Seawater preserved viral stability both at -18°C and with repeated freeze−thaw cycles compared with that in deionized water. Visible light from light-emitting diode (LED) illumination and airflow at -18°C reduced SARS-CoV-2 pseudovirus stability.ConclusionOur studies indicate that temperature and seawater in the cold chain are risk factors for SARS-CoV-2 transmission, and LED visible light irradiation and increased airflow may be used as disinfection measures for SARS-CoV-2 in the cold-chain environment.

Supplementary Table S1. Sanger validated variants. Supplementary Table S2. Mutations in HSTL driver genes. Supplementary Table S3. Other mutations identified by exome sequencing. Supplementary Table S4. Copy number of HSTL patients and cell lines. Supplementary Table S5. Clinical and pathological characteristics of HSTL patients. Supplementary Tables S6, S7. Comparison to HSTL clinical data in the literature. Supplementary Table S8. Mutational frequencies in other lymphomas. Supplementary Table S9. HSTL mutations in other lymphoma driver genes. Supplementary Table S10. Gene set enrichment analysis of DERL2 SETD2 shRNA.

Supplementary Figure S1. Sanger sequencing chromatograms. Supplementary Figure S2. Cancer cell fraction for driver genes. Supplementary Figure S3. Ideogram with chromosome 7 alterations. Supplementary Figure S4. Examples of Exome Copy Number. Supplementary Figure S5. Exploratory Kaplan-Meier plots for clinical covariates. Supplementary Figure S6. Exploratory Kaplan-Meier plots for molecular covariates. Supplementary Figure S7. Sanger and exome sequencing validation of SETD2 biallelic mutation in one HSTL case. Supplementary Figure S8. SETD2 expression in mutant vs. wildtype cases. Supplementary Figure S9. Mutual exclusivity of STAT5B, PIK3CD, and STAT3 mutations.

There are huge differences in the layouts and numbers of sensors in different smart home environments. Daily activities performed by residents trigger a variety of sensor event streams. Solving the problem of sensor mapping is an important prerequisite for the transfer of activity features in smart homes. However, it is common practice among most of the existing approaches that only sensor profile information or the ontological relationship between sensor location and furniture attachment are used for sensor mapping. The rough mapping seriously restricts the performance of daily activity recognition. This paper presents a mapping approach based on the optimal search for sensors. To begin with, a source smart home that is similar to the target one is selected. Thereafter, sensors in both source and target smart homes are grouped by sensor profile information. In addition, sensor mapping space is built. Furthermore, a small amount of data collected from the target smart home is used to evaluate each instance in sensor mapping space. In conclusion, Deep Adversarial Transfer Network is employed to perform daily activity recognition among heterogeneous smart homes. Testing is conducted using the public CASAC data set. The results have revealed that the proposed approach achieves a 7–10% improvement in accuracy, 5–11% improvement in precision, and 6–11% improvement in F1 score, compared with the existing methods.

We consider the higher order Turan inequality and higher order log-concavity for sequences { a n } n ≥ 0 such that a n − 1 a n + 1 a n 2 = 1 + ∑ i = 1 m r i ( log ⁡ n ) n α i + o ( 1 n β ) , where m is a nonnegative integer, α i are real numbers, r i ( x ) are rational functions of x and 0 α 1 α 2 ⋯ α m β . We will give a sufficient condition on the higher order Turan inequality and the l-log-concavity for n sufficiently large. Many P-recursive sequences fall in this frame. At last, we will give a method to find the N such that for any n > N , the higher order Turan inequality holds.

With growing complexity and uncertainty from distributed generations and active customers, distribution networks are facing more unexpected events and topology changes; while very limited measurements may degrade the observability of distribution system states and endanger the security of the system. Meanwhile, massive data from various types of users (if they can be used), can be valuable for power utilities. This makes privacy and data security a more critical issue, while being endowed with operation and market flexibilities. Thus, we propose a blockchain-based privacy-protecting approach for Dynamic Topology Awareness (DTA) to distinguish topology changes from cyber anomalies, including physical, cyber and business layers. At the bottom layer (physical layer), the distribution network is partitioned into subareas and tie-line areas, coping with local data from measurement devices or users. Estimated border values from parallel local estimations would be examined through data consistency checking. And DTA consensus algorithm might be triggered, querying historical status stored as blockchain contracts for anomalies detections and new block formations. Voting mechanism is then adopted to verify new blocks from data tampering. The performance of the proposed DTA approach is validated through simulations to identify topology changes and cyber anomalies, with additional discussions on the trade-off between DTA sensitivity and estimation accuracy.

The frequent switching operations and triggering events of automation devices are poorly documented in distribution management systems, leading to challenging work regarding the timely detection of system state changes. Additionally, the limited measurements in distribution networks and the randomness of plug-and-play devices make obtaining real-time observations of system states difficult. Furthermore, distributed generation (DG) output uncertainties exacerbate the situation. Thus, we propose a dynamic topology awareness (DTA) approach to make judgments regarding operational states and identify all possible topology changes (including normal operations, islanding and outages) in the absence of real-time DG measurements. The method consists of two steps. The first step applies parallel Gaussian mixture model-based probabilistic state estimators (GMM-PSEs) of subareas and extended subareas to calculate the probability distributions of border bus voltages with full consideration of DG uncertainties. The second step utilizes the Kullback-Leibler (KL) divergence measure to evaluate the difference between the two probability distributions estimated by subareas and extended subareas, thereby obtaining an indicator (average KL divergence) for identifying possible topologies. The effectiveness of the proposed method is examined on the IEEE 33-bus and IEEE 123-bus test cases. It is computationally efficient and accurate when identifying all possible topologies under limited measurements and DG uncertainties.

The application needs of small electronic devices and large-scale power grid storage continuously promote the development of a new battery energy system. Rechargeable metal batteries based on aluminum (Al) are of enormous potential due to the abundant Al reserves, the trivalent charge carrier, high theoretical specific capacity (2980 mAh/g), and volumetric energy density (8046 mAh/cm3). However, the passivating oxide layer on the surface of the Al anode blocks the migration of electrons and ions, resulting in the operation difficulty and irreversibility of aluminum-based batteries. Herein we treated Al anode with a deep eutectic solution (DES) and constructed stable solid interface interphase on its surface, which can effectively prevent surface passivation, improve the chemical properties of the interface, promote ion transfer, and enable aqueous Al batteries with superior electrochemical performance. The assembled symmetric cells with treat Al (TAl) can cycle for more than 300 h with a low overpotential (~0.2 V). The TAl anode coupling with the FPB cathode material to assemble the full cells based on the aqueous electrolyte system can deliver a high discharge capacity of 85 mAh/g and exhibit capacity retention of 58 mAh/g after 150 cycles and an average coulombic efficiency of 97.1% at a current density of 100 mA/g. This work provides a novel surface modification strategy of Al metal anode and demonstrates high stability and cost-effective aqueous Al metal battery system, which suggest the significance for the commercialization of Al-metal batteries and their applications in large-scale energy store.

Resonance Raman optical activity (RROA) is commonly measured as the difference in intensity of Raman scattered right and left circularly polarized light, IR -IL , when a randomly polarized light is in resonance with a chiral molecule. Strong and sometimes mono-signate experimental RROA spectra of several chiral solutes were reported previously, although their signs and relative intensities could not be reproduced theoretically. By examining multiple light-matter interaction events which can occur simultaneously under resonance, we show that a new form of chiral Raman spectroscopy, eCP-Raman, a combination of electronic circular dichroism and circularly polarized Raman, prevails. By incorporating the finite-lifetime approach for resonance, the experimental patterns of the model chiral solutes are captured theoretically by eCP-Raman, without any RROA contribution. The results open opportunity for applications of eCP-Raman spectroscopy and for extracting true RROA experimentally.

The switching frequency of power electronic devices has become much higher than before, which brings great challenges to real-time simulators. The small time step in high switching frequency simulations remarkably increases the difficulty to satisfy the real-time requirement. This article realizes the accurate real-time simulation of a solid-state transformer (SST) with a switching frequency of 50 kHz at the time step of 250 ns on a field-programmable gate array (FPGA)-based platform. The hybrid companion circuit modeling method and the compact-electromagnetic transient program (EMTP) algorithm are proposed in this article to make sure that the simulation loop can complete in less than $1~\mu \text{s}$ . The hybrid companion circuit modeling method can avoid too many digits used in representing simulation variables. The compact-EMTP algorithm is designed by combining the sequential computation tasks of the traditional EMTP to fully utilize the parallelized hardware structure of the FPGA. Besides, a circuit partition method is adopted to further parallelize the circuit solution of the SST circuit. In these ways, the simulation loop of the SST can be completed in 38 clock cycles (about 237.5 ns). The simulation results show that the real-time simulation waveforms are almost consistent with those of the off-line simulation software. Besides, the hardware-in-the-loop (HIL) simulation can also be performed on this platform to test the control functions of the SST.

Increasing operational flexibilities of power system devices and generation/load components have intensified the dynamic changing of power network topologies. Dynamic Topology Awareness (DTA) with limited measurements are vital for subsequent analyses and operations of power distribution networks. Considering the economical limitation of extensive installations of PMUs, thus, we proposed in this paper a DTA method through capturing perturbations in voltage amplitude covariance matrix with statistical inference model that considering non-Gaussian noise and requiring only synchronous measurements of voltage amplitudes. The method was developed and proved to be robust without preconditions of Gaussian noises which is more accordant with practical circumstances. Simulations are performed based on IEEE 123 system, and three types of DTA scenarios can be effectively detected and located with high accuracy.

Cold-chain environment could extend the survival duration of SARS-CoV-2 and increases the risk of transmission. However, the effect of clod-chain environmental factors and packaging materials on SARS-CoV-2 stability and the efficacy of intervention measures to inactivate SARS-CoV-2 under cold-chain environment remains uncertain. This study aimed to unravel cold-chain environmental factors that preserved the stability of SARS-CoV-2 and disinfection measures against SARS-CoV-2 under the cold-chain environment. The spike gene of SARS-CoV-2 isolated from Wuhan hu-1 was used to construct the SARS-CoV-2 pseudovirus and used as model of the SARS-CoV-2 virus. The decay rate of SARS-CoV-2 pseudovirus in the cold-chain environment, various types of packaging material surfaces i.e., PE plastic, stainless steel, Teflon and cardboard, and in frozen seawater was investigated. The influence of LED visible light(wavelength 450 nm-780 nm) and airflow movement on the stability of SARS-CoV-2 pseudovirus at -18° C were subsequently assessed. The results show that SARS-CoV-2 pseudovirus decayed more rapidly on porous cardboard surface compared with the non-porous surfaces including PE plastic, stainless steel and Teflon. Compared with 25° C, the decay rate of SARS-CoV-2 pseudovirus was significantly lower at low temperature. Seawater preserved viral stability both at -18° C and repeated freeze-thawing cycles compared with deionized water. LED visible light illumination and airflow movement environment at -18° C reduced the SARS-CoV-2 pseudovirus stability. In conclusion, our results indicate cold-chain temperature and seawater as risk factors for SARS-CoV-2 transmission and LED visible light illumination and airflow movement as possible disinfection measures of SARS-CoV-2 under the cold-chain environment.ImportanceIt is widely recognized that low temperature is a condition for maintaining virus vitality, and cold-chain transportation spreads the events of the SARS-CoV-2 were reported. This study provides that the decay rate of the SARS-CoV-2 pseudovirus at low temperatures varies on different packaging materials, and salt ions present in frozen foods such as seafood may protect virus survival. These results provide evidence for the possibility of SARS-CoV-2 transmission through cold-chain transport and also suggest the importance for disinfection of items. However, the commonly used disinfection methods of ultraviolet radiation and chemical reagents are generally not suitable for the disinfection of frozen food. Our study shows LED visible light illumination and airflow movement as possible disinfection measures of SARS-CoV-2 under the cold-chain environment. This has implications for reducing the long-distance transmission of the virus through cold-chain transportation.

This paper presents a novel methodology for the construction of a transient stability boundary (TSB) that overcomes the lack of TSB analytical description for multiple operating states and contingencies in power systems. The proposed approach models the TSB as a nonlinear mapping between the system parameters of interest and the corresponding critical clearing time (CCT). This compact mathematical expression is built based on an efficient discriminative network, broad learning system (BLS). While keeping a high accuracy and generalization ability, the newly introduced construction method provides an efficient update strategy that does not require an entire retraining cycle. These properties make this method suitable for online transient stability assessment (TSA). The prospects of the developed method are verified via case studies by employing the IEEE 9-bus, IEEE 39-bus (New England) test systems and a real system of China Southern Power Grid. In comparison with existing methods, the newly introduced algorithm has a higher prediction accuracy and improved robustness. The demonstrated characteristics indicate that the proposed method may serve as a valuable tool in the framework of online TSA.

In this article, based on sampled-data modeling technique, a second-order equivalent circuit that can describe the global dynamic characteristics of dual active bridge (DAB) converter is developed. The proposed technique can characterize the dynamics of the ac current through the transformer and the output voltage. Afterward, by using a sensitive-based tool, named participation factor, it is identified which state variables are critical for system stability and which state variables provide negligible effects. On this basis, the large-signal equivalent circuit is simplified, meanwhile, the parasitic resistance is still taken into account by an intuitive “loss branch.” This model can be used to comprehensively investigate the relationship of the DAB converter stability versus circuit parameters, controller gain, input/reference voltage, and the load conditions, and these results can be expressed analytically. Furthermore, a linearized control method is proposed to eliminate the nonlinear terms in the equivalent circuit model. It facilitates to reduce the sensitivity of system stability to the load condition and reference voltage and helps to enlarge the stable region. Finally, the proposed model is validated by comparing the results obtained by the model with the simulations and experimental results. The effectiveness of the linearized control method is also demonstrated.

Prediction of blood cell flow is known as the difficult research by reason of the complexity of blood vessel. In this study, considering the complex structure of blood vessels, a mechanical model for red blood cell (RBC) based on unstructured grid has been established to study the flow characteristics of RBCs in complex blood vessels. In the model, the strain-energy function by Skalak is employed to model the shear elasticity and surface-area conservation of the membrane, and the hinge spring is used to describe the forces originating from local bending of the membrane. The immersed boundary method is utilized to couple the interphase force. Using the model, the stretching test of RBC is compared with the experiment data, and the good agreement verified the validation of the present model. The morphology of red blood cell and the blood viscosity in micro-vessel are studied. RBCs move with a symmetric shape (parachute shape) in small blood vessels, and the buckling instability is observed when the RBC flow slowly through a micro-vessel or a converging-diverging capillary. When the vessel diameter is around 10 μm, the reverse Fahraeus-Lindqvist effect is presented. The blood apparent viscosity shows linear increase with the blood hematocrit. In addition, Malaria infection can make the RBC deformability decreased and the blood apparent viscosity increased.

COVID-19 infection causes collapse of glomerular capillaries and loss of podocytes, culminating in a severe kidney disease called COVID-19-associated nephropathy (COVAN). The underlying mechanism of COVAN is unknown. We hypothesized that cytokines induced by COVID-19 trigger expression of pathogenic APOL1 via JAK/STAT signaling, resulting in podocyte loss and COVAN phenotype. Here, based on 9 biopsy-proven COVAN cases, we demonstrated for the first time, to the best of our knowledge, that APOL1 protein was abundantly expressed in podocytes and glomerular endothelial cells (GECs) of COVAN kidneys but not in controls. Moreover, a majority of patients with COVAN carried 2 APOL1 risk alleles. We show that recombinant cytokines induced by SARS-CoV-2 acted synergistically to drive APOL1 expression through the JAK/STAT pathway in primary human podocytes, GECs, and kidney micro-organoids derived from a carrier of 2 APOL1 risk alleles, but expression was blocked by a JAK1/2 inhibitor, baricitinib. We demonstrate that cytokine-induced JAK/STAT/APOL1 signaling reduced the viability of kidney organoid podocytes but was rescued by baricitinib. Together, our results support the conclusion that COVID-19-induced cytokines are sufficient to drive COVAN-associated podocytopathy via JAK/STAT/APOL1 signaling and that JAK inhibitors could block this pathogenic process. These findings suggest JAK inhibitors may have therapeutic benefits for managing cytokine-induced, APOL1-mediated podocytopathy.

Flexible strain sensor has promising features in successful application of health monitoring, electronic skins and smart robotics, etc. Here, we report an ultrasensitive strain sensor with a novel crack-wrinkle structure (CWS) based on graphite nanoplates (GNPs)/thermoplastic urethane (TPU)/polydimethylsiloxane (PDMS) nanocomposite. The CWS is constructed by pressing and dragging GNP layer on TPU substrate, followed by encapsulating with PDMS as a protective layer. On the basis of the area statistics, the ratio of the crack and wrinkle structures accounts for 31.8% and 9.5%, respectively. When the sensor is stretched, the cracks fracture, the wrinkles could reduce the unrecoverable destruction of cracks, resulting in an excellent recoverability and stability. Based on introduction of the designed CWS in the sensor, the hysteresis effect is limited effectively. The CWS sensor possesses a satisfactory sensitivity (GF = 750 under 24% strain), an ultralow detectable limit (strain = 0.1%) and a short respond time of 90 ms. For the sensing service behaviors, the CWS sensor exhibits an ultrahigh durability (high stability > 2×104 stretching-releasing cycles). The excellent practicality of CWS sensor is demonstrated through various human motion tests, including vigorous exercises of various joint bending, and subtle motions of phonation, facial movements and wrist pulse. The present CWS sensor shows great developing potential in the field of cost-effective, portable and high-performance electronic skins.

The proliferation of photovoltaics (PV) in distribution systems brings about voltage stability problems. This paper proposes an algorithm to calculate extreme bifurcation intervals considering deep PV penetration levels. The paper applies the sandglass-hyper-ellipsoid-cone model to analyze the correlations among net bus loads representing bidirectional power flows for different PV penetration levels. Using the net bus load model, three extreme bifurcation points on voltage stability limit hypersurface are formulated where two of these points represent the voltage stability bifurcation interval in the forecasted net bus loading direction. An iterative method is applied to obtain bifurcation solutions. The validity of the proposed method is verified by using the IEEE 3-bus system, the IEEE 33-bus system and the IEEE 123-node test feeder. The numerical results demonstrate that the proposed sandglass-hyper-ellipsoid-cone net bus load model and solutions are effective in managing correlated net bus load forecast errors in distribution systems with PV integration.

Lithium metal anode (LMA) is the ultimate “Holy Grail” electrode for next generation high-energy-density batteries. Nevertheless, its instinct high reactivity is a formidable challenge and has intensified side reactions, destabilized the electrode/electrolyte interface and restricted the operating conditions strictly, thus hampering its practical application. Here, we “make up” the Li metal (M-Li) by constructing vaseline-coated layer by a simple dip-coating or casting method. With the chemically stable and hydrophobic vaseline protective layer, the stability of Li towards humid and corrosive atmosphere has been greatly improved. The M-Li guaranteed stable and prolonged cycling life after the anode suffering from corrosion in moist air (relative humidity ~65%) or corrosive electrolyte (with 10,000 ppm H2O or S) both in symmetric cells and LiFePO4 full cells. This work illustrates a convenient, economic, and industrial applicable method for stable LMA.

The increasing integration of wind power generation brings more uncertainty into the power system. Since the correlation may have a notable influence on the power system, the output powers of wind farms are generally considered as correlated random variables in uncertainty analysis. In this paper, the C-vine pair copula theory is introduced to describe the complicated dependence of multidimensional wind power injection, and samples obeying this dependence structure are generated. Monte Carlo simulation is performed to analyze the small signal stability of a test system. The probabilistic stability under different correlation models and different operating conditions scenarios is investigated. The results indicate that the probabilistic small signal stability analysis adopting pair copula model is more accurate and stable than other dependence models under different conditions.

The mechanical behaviors of Zr43.5Cu43.5Ni4Al8Nb1, Zr55.4Cu31.6Ni4Al8Nb1, Ti32.8Zr30.2Ni5.3Cu9Be22.7 (at.%) metallic glass at different strain rates were studied. For all the present alloys, the dispersion over 700 MPa was observed on the strength in the repeated dynamic compressions, which was much stronger than that of the quasi-static compressive strength. Such the dispersion of the dynamic compressive strength was well correlated with the corresponding fracture behaviors. The area of fracture surface was calculated and also showed a strong dispersion for all the fractured specimens tested at the strain rate of 500 s−1 and 1000 s−1. All the specimens showed a linear relationship between the square of dynamic compressive strength and the area of fracture surface in the dynamic compression tests. This phenomenon was mainly thought to be related to the difference of mean initial free volume concentration of different samples, stress concentration caused by the split Hopkinson pressure bar experimental setup and high sensitivity of defects under dynamic deformation. These findings were beneficial to deeply understand the effect of strain rate on the mechanical properties of the metallic glass.

The real-time simulation based on the field programmable gate array (FPGA) is receiving more and more attention. However, up to now, the simulation scale for the power electronic system is not so satisfactory due to the real-time requirement and the FPGA resource limitation. This paper proposes a sub-microsecond level real-time simulation method for microgrids. The power converters are modeled with fixed-admittance models and simulated with a compact electromagnetic transients program (EMTP) algorithm. In the meanwhile, the distribution lines/cables are modeled with π-circuit models and simulated with a distributed circuit solution method, called the latency insertion method (LIM). As a result, the distribution generation (DG) systems are decoupled with each other and can be simulated in parallel. The case study shows that the proposed simulation method consumes much fewer FPGA resources compared with the traditional one. Besides, the time step can be much smaller and doesn't need to increase with the simulation scale. With these advantages, the real-time simulation of a microgrid consisting of three three-phase converters, three boost circuits and 21 three-phase lines can be achieved on the Xilinx Kintex-7 410T FPGA with a minmum time-step of 380 ns.

This paper proposes an algorithm for the bidirectional evaluation of voltage stability margin (VSM) with a large photovoltaic (PV) power penetration. To address the variability caused by loads and PV for bidirectional VSM, a deep ensemble model with a simultaneous point and probabilistic predictions is developed, which takes advantage of advanced metering infrastructure and weather data. The deep ensemble model consists of offline- and online-trained ensemble, which uses optimization blend and k-means, respectively. The proposed approach can also consider topology changes and environmental impacts (e.g., solar irradiance and temperature), with a major bearing on load/PV models and network parameters. The validity of the proposed approach is verified through its applications to a modified IEEE 33-bus system and IEEE 123-node test feeder, followed by VSM sensitivity analyses (Sen-ELM) and tolerance analyses with the consideration of input errors. The numerical results demonstrate that the proposed VSM approach has a strong generalization capability considering the proliferation of PV energy.

The nuclear pore complex (NPC) comprises more than 30 nucleoporins (NUPs) and is a hallmark of eukaryotes. NUPs have been suggested to be important in regulating gene transcription and 3D genome organization. However, evidence in support of their direct roles remains limited. Here, by CutRun, we find that core NUPs display broad but also cell-type-specific association with active promoters and enhancers in human cells. Auxin-mediated rapid depletion of two NUPs demonstrates that NUP93, but not NUP35, directly and specifically controls gene transcription. NUP93 directly activates genes with high levels of RNA polymerase II loading and transcriptional elongation by facilitating full BRD4 recruitment to their active enhancers. dCas9-based tethering confirms a direct and causal role of NUP93 in gene transcriptional activation. Unexpectedly, in situ Hi-C and H3K27ac or H3K4me1 HiChIP results upon acute NUP93 depletion show negligible changesS2211-1247(22)01437-1 of 3D genome organization ranging from A/B compartments and topologically associating domains (TADs) to enhancer-promoter contacts.

Large numbers of marine glaciers in the Qinghai-Tibet Plateau are especially sensitive to changes of climate and surface conditions and they have suffered fast accumulation and melting and retreated quickly in recent years. In 2017, we surveyed the cold-adapted fungi in these unique habitats and obtained 1208 fungal strains. Based on preliminary analysis of ITS sequences, 41 isolates belonging to the genus Cadophora were detected. As one of the most frequently encountered genera, the Cadophora isolates were studied in detail. Two phylogenetic trees were constructed: one was based on the partial large subunit nrDNA (LSU) to infer taxonomic placement of our isolates and the other was based on multi-locus sequences of LSU, ITS, TUB and TEF-1α to investigate more exact phylogenetic relationships of Cadophora and allied genera. Combined with morphological characteristics, nine Cadophora species were determined, including seven new to science. Among the new species, only C. inflata produced holoblastic conidia and all the others had phialidic conidiogenesis, and some isolates recognized as C. qinghai-tibetana and C. psychrophila had optimum growth temperature at 15°C. With more species involved, the currently circumscribed genus became obviously paraphyletic and all members clustered into two main clades: one clade mainly included most of the Cadophora species which had phialidic conidiogenesis and we referred to as ‘Cadophora s. str.’; the rest Cadophora species had multiform conidiogenesis and clustered in the second clade, with members of other genera in Ploettnerulaceae interspersed among the subclades. Our results showed a high diversity of Cadophora from marine glaciers in the Qinghai-Tibet Plateau and further intense sampling should be necessary for exploring more new species to reconstruct the phylogeny of this important fungal group.

Retroviruses, especially the pathogenic human immunodeficiency virus type 1 (HIV-1), have severely threatened human health for decades. Retroviruses can form stable latent reservoirs via retroviral DNA integration into the host genome, and then be temporarily transcriptional silencing in infected cells, which makes retroviral infection incurable. Although many cellular restriction factors interfere with various steps of the life cycle of retroviruses and the formation of viral latency, viruses can utilize viral proteins or hijack cellular factors to evade intracellular immunity. Many post-translational modifications play key roles in the cross-talking between the cellular and viral proteins, which has greatly determined the fate of retroviral infection. Here, we reviewed recent advances in the regulation of ubiquitination and SUMOylation in the infection and latency of retroviruses, focusing on both host defense- and virus counterattack-related ubiquitination and SUMOylation system. We also summarized the development of ubiquitination- and SUMOylation-targeted anti-retroviral drugs and discussed their therapeutic potential. Manipulating ubiquitination or SUMOylation pathways by targeted drugs could be a promising strategy to achieve a “sterilizing cure” or “functional cure” of retroviral infection.

This Concept article summarizes recent work on the development of a new form of chiral Raman spectroscopy, eCP-Raman, which combines two spectroscopies: electronic circular dichroism (ECD) and circularly polarized Raman (CP-Raman). First, some puzzling observations while carrying out Raman optical activity (ROA) measurements of several transition metal complexes under resonance are described, as well as the search for the mechanisms responsible. Then an equation for quantifying the eCP-Raman contribution is presented, followed by several examples of how eCP-Raman influences the I

To evaluate the changes of left atrial (LA) geometry and function in patients with rheumatoid arthritis (RA) by conventional echocardiography and two-dimensional speckle tracking imaging (2D-STI). We enrolled 46 RA patients with a duration of

High-altitude polycythemia (HAPC) is a chronic mountain sickness characterized by multiple severe ill-effects. Its pathogenesis is still unclear, and till date, no study has been conducted to investigate the plasma exome profile of Tibetan patients with HAPC. In this study, we aimed to elucidate the pathogenesis of HAPC by determining the microRNA (miRNA) signatures. We compared the plasma exosome miRNA expression profiles of eight patients with HAPC and eight healthy controls using next-generation miRNA sequencing. Further, we extracted and identified plasma exosomes using transmission electron microscopy, nanoparticle tracking analysis, and western blotting. We used quantitative reverse-transcription polymerase chain reaction (qRT-PCR) to validate differentially expressed plasma exosomal miRNAs. Finally, we analyzed the diagnostic values of the differentially expressed miRNAs for HAPC using receiver operating characteristic (ROC) curves. We detected 2007 miRNAs from confirmed plasma exosomes, including 1342 known miRNAs and 665 newly predicted miRNAs. We verified the expression of the top 10 differentially expressed miRNAs via qRT-PCR. Patients with HAPC showed significantly upregulated hsa-miR-122-5p, hsa-miR-423-5p, hsa-miR-4433b-3p, hsa-miR-1291, and hsa-miR-106b-5p expression levels, while hsa-miR-200c-3p expression was downregulated. This study may provide background knowledge for future studies on HAPC studies, which may further facilitate the development of novel therapies against this common disease.

The broad frequency band oscillation accident of the power system caused by the integration of wind power generation seriously threatens the safety and stability of the power system. Frequency domain modeling and analysis is an important method to study system stability. In order to simplify the system complexity, the derivation of the doubly fed induction generator (DFIG) admittance model generally only considering the impact of the current control loop. But when the voltage disturbance occurs at the point of common coupling (PCC), the power control loop will inevitably introduce the power fluctuation into the current control loop, which will affect the admittance characteristics. This paper derives DFIG admittance models under the dq axis that consider both the current control loop and the power control loop of the rotor side converter (RSC). Moreover, comparative analysis of three types of admittance model is carried out, which is based on actual parameters. The results show that it is necessary to consider the controller in modeling and analysis, and the power control loop has a great influence on the DFIG admittance matrix.