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In stream processing systems, Key Grouping is a commonly employed partitioning scheme for distributing input tuples among parallel instances of stateful operators. With key grouping, tuples shared public keys in the stream are designated to the specific instance responsible for that key. Typically, the implementation of key grouping involves the use of a hash function. While it is convenient and deterministic, it is also known to cause load imbalance between parallel instances, especially in the presence of skewed data streams. Key-Splitting is an effective technique that distributes tasks associated with keys to downstream operators, facilitating load balancing at a relatively low cost. However, overly increasing parallel instances can lead to excessive aggregation costs, becoming a system bottleneck. In this paper, we show the high aggregation cost brought by the Key-Splitting partitioner at different levels of key separation. To address this challenge, we introduce an adaptive Key-Splitting method which controlling the degree of key separation. We propose a partitioner named FlexD, which aims to achieve dynamic adaptation of key separation limits for streaming data. The partitioner employs key grouping to distribute rare keys and dynamic expansion of processing instances to distribute hot keys. We implemented our method on Apache Storm and evaluated it by using real-world and synthetic datasets. Experimental results show that our method achieves a good balance between load balancing and aggregation cost. Moreover, it outperforms existing methods, achieving higher throughput.

The nonclassical ten-pi-electron 5,5-fused thieno[3,4-c]thiadiazole (TTD) unit is an excellent building block for constructing sub-silicon-band gap organic semiconductors. However, no small molecule acceptor (SMA) materials based on TTD have been reported despite the fact that high-sensitivity near-infrared organic photodetectors (OPDs) are generally achieved by using SMAs. In this work, we report a TTD-based narrow band gap (0.95 eV) SMA material TTD(DTC-2FIC)2with strong near-infrared absorption. Employing PTB7-Th as a donor, OPDs based on TTD(DTC-2FIC)2exhibit an optimized responsivity of 0.095 (±0.007) A W–1at 1100 nm and sustain a decent responsivity of 0.074 (±0.008) A W–1at 1200 nm. Moreover, a good specific detectivity over 1 × 1011Jones is achieved at a wavelength of 1200 nm. Detailed characterizations imply that the performance of TTD(DTC-2FIC)2-based OPDs may be substantially improved by choosing lower-mixing donors with shallower energy levels. This work demonstrates that SMAs incorporating TTD as the core unit hold promise for constructing high-sensitivity sub-silicon-band gap OPDs.

IMPORTANCE: Individuals who are incarcerated represent a vulnerable group due to concerns about their ability to provide voluntary and informed consent, and there are considerable legal protections regarding their participation in medical research. Little is known about the quality of surgical care received by this population. OBJECTIVE: To evaluate perioperative surgical care provided to patients who are incarcerated within the Texas Department of Criminal Justice (TDCJ) and compare their outcomes with that of the general nonincarcerated population. DESIGN, SETTING, AND PARTICIPANTS: This cohort study analyzed data from patients who were incarcerated within the TDCJ and underwent general or vascular surgery at the University of Texas Medical Branch (UTMB) from 2012 to 2021. Case-specific outcomes for a subset of these patients and for patients in the general academic medical center population were obtained from the American College of Surgeons National Quality Improvement Program (ACS-NSQIP) and compared. Additional quality metrics (mortality index, length of stay index, and excess hospital days) from the Vizient Clinical Data Base were analyzed for patients in the incarcerated and nonincarcerated groups who underwent surgery at UTMB in 2020 and 2021 to provide additional recent data. Patient-specific demographics, including age, sex, and comorbidities were not available for analysis within this data set. MAIN OUTCOME AND MEASURES: Perioperative outcomes (30-day morbidity, mortality, and readmission rates) were compared between the incarcerated and nonincarcerated groups using the Fisher exact test. RESULTS: The sample included data from 6675 patients who were incarcerated and underwent general or vascular surgery at UTMB from 2012 to 2021. The ACS-NSQIP included data (2012-2021) for 2304 patients who were incarcerated and 602 patients who were not and showed that outcomes were comparable between the TDCJ population and that of the general population treated at the academic medical center with regard to 30-day readmission (6.60% vs 5.65%) and mortality (0.91% vs 1.16%). However, 30-day morbidity was significantly higher in the TDCJ population (8.25% vs 5.48%, P = .01). The 2020 and 2021 data from the Vizient Clinical Data Base included 629 patients who were incarcerated and 2614 who were not and showed that the incarcerated and nonincarcerated populations did not differ with regard to 30-day readmission (12.52% vs 11.30%) or morbidity (1.91% vs 2.60%). Although the unadjusted mortality rate was significantly lower in the TDCJ population (1.27% vs 2.68%, P = .04), mortality indexes, which account for case mix index, were similar between the 2 populations (1.17 vs 1.12). CONCLUSIONS AND RELEVANCE: Findings of this cohort study suggest that patients who are incarcerated have equivalent rates of mortality and readmission compared with a general academic medical center population. Future studies that focus on elucidating the potential factors associated with perioperative morbidity and exploring long-term surgical outcomes in the incarcerated population are warranted.

ObjectiveHepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), mostly characterised by HBV integrations, is prevalent worldwide. Previous HBV studies mainly focused on a few hotspot integrations. However, the oncogenic role of the other HBV integrations remains unclear. This study aimed to elucidate HBV integration-induced tumourigenesis further.DesignHere, we illuminated the genomic structures encompassing HBV integrations in 124 HCCs across ages using whole genome sequencing and Nanopore long reads. We classified a repertoire of integration patterns featured by complex genomic rearrangement. We also conducted a clustered regularly interspaced short palindromic repeat (CRISPR)-based gain-of-function genetic screen in mouse hepatocytes. We individually activated each candidate gene in the mouse model to uncover HBV integration-mediated oncogenic aberration that elicits tumourigenesis in mice.ResultsThese HBV-mediated rearrangements are significantly enriched in a bridge-fusion-bridge pattern and interchromosomal translocations, and frequently led to a wide range of aberrations including driver copy number variations in chr 4q, 5p (TERT), 6q, 8p, 16q, 9p (CDKN2A/B), 17p (TP53) and 13q (RB1), and particularly, ultra-early amplifications in chr8q. Integrated HBV frequently contains complex structures correlated with the translocation distance. Paired breakpoints within each integration event usually exhibit different microhomology, likely mediated by different DNA repair mechanisms. HBV-mediated rearrangements significantly correlated with young age, higher HBV DNA level and TP53mutations but were less prevalent in the patients subjected to prior antiviral therapies. Finally, we recapitulated the TONSLand TMEM65amplification in chr8q led by HBV integration using CRISPR/Cas9 editing and demonstrated their tumourigenic potentials.ConclusionHBV integrations extensively reshape genomic structures and promote hepatocarcinogenesis (graphical abstract), which may occur early in a patient’s life.

Background The Focused Assessment with Sonography in Trauma (FAST) exam is an important component to the evaluation of trauma patients. With advances in technology and meeting limitations due to COVID-19, remote instruction and learning have gained popularity. We sought to determine whether remote instruction of FAST exams was feasible as sustainable surgical education and a possible alternative to traditional in-person teaching.Methods General surgery residents completed a baseline survey and skills assessment on FAST exams and were then randomized to remote or in-person instruction. The remote group participated in an instructional session with a content expert through video conference and then practiced on a simulated mannequin while the expert remotely provided feedback. The in-person group received the experience with the content expert in the room. Both groups completed a post-course survey immediately after the session and a follow-up survey and objective assessment at six-months. Results were compared with two-way analysis of variance (ANOVA).Results 14 residents underwent the curriculum, seven in each group. There was a significant increase in self-reported confidence when comparing pre- and immediate post-course results for both the remote and in-person groups. At six months, confidence scores remained elevated and skill assessment scores improved, although the latter did not reach significance. There was no significant difference in post-course results between the groups.Conclusions Remote instruction of FAST exams was feasible. Pilot data demonstrated an increase in confidence and suggest outcomes that are similar to in-person instruction, which has positive implications for future remote educational and potentially clinical initiatives.

In recent years, artificial intelligence (AI) research has showcased tremendous potential to positively impact humanity and society. Although AI frequently outperforms humans in tasks related to classification and pattern recognition, it continues to face challenges when dealing with complex tasks such as intuitive decision making, sense disambiguation, sarcasm detection, and narrative understanding as these require advanced kinds of reasoning, e.g., common-sense reasoning and causal reasoning, which have not been emulated satisfactorily yet. To address these shortcomings, we propose seven pillars that we believe represent the key hallmark features for the future of AI, namely, multidisciplinarity, task decomposition, parallel analogy, symbol grounding, similarity measure, intention awareness, and trustworthiness.

In Spatial crowdsourcing, mobile users perform spatio-temporal tasks that involve travel to specified locations. Spatial crowdsourcing (SC) is enabled by SC platforms that support mobile worker recruitment and retention, as well as task assignment, which is essential to maximize profits that are accrued from serving task requests. Specifically, how to best achieve task assignment in a cost-effective manner while contending with spatio-temporal constraints is a key challenge in SC. To address this challenge, we formalize and study a novel Profit-driven Task Assignment problem. We first establish a task reward pricing model that takes into account the temporal constraints (i.e., expected completion time and deadline) of tasks. Then we adopt an optimal algorithm based on tree decomposition to achieve an optimal task assignment and propose greedy algorithms based on Random Tuning Optimization to improve the computational efficiency. To balance effectiveness and efficiency, we also provide a heuristic task assignment algorithm based on Ant Colony Optimization that assigns tasks by simulating behavior of ant colonies foraging for food. Finally, we conduct extensive experiments using real and synthetic data, offering detailed insight into effectiveness and efficiency of the proposed methods.

The influence of blood eosinophil (EOS) on the effect of pulmonary rehabilitation (PR) has not been investigated previously. The improvement of 6-min walking test (6MWT) distance was more significant in chronic obstructive pulmonary disease (COPD) patients with a high blood EOS count. A high peripheral blood EOS count could be used to predict the improvement in 6MWT distance with PR in COPD patients.

The log-structured merge-tree (LSM-tree)-based key-value store has been widely adopted by many large-scale data storage applications for its excellent write performance. However, such write performance gains mainly come from scarifying read performance due to the leveled and log-structured intrinsic characteristics of the LSM-tree. Therefore, the critical challenge of the existing LSM-tree is how to improve the read efficiency by reducing read amplification. This article for the first time proposes Tidal-tree-Mem, a novel data structure where data flow inside the LSM-tree-like Tidal waves. First, a floating strategy is proposed to allow frequently accessed files at the bottom of the LSM-tree to move to higher positions, reducing read amplification. Second, a stretching strategy is proposed to vary the shape of the LSM-tree to adapt to workloads with different characteristics. To evaluate the performance of Tidal-tree-Mem, we conduct a series of experiments using standard benchmarks from YCSB. The experimental results show that Tidal-tree-Mem can effectively reduce read amplification and the overall latency by over 71.94% and 47.34%, respectively, compared with representative schemes.

The set similarity join finds all pairs of similar sets from two collections of sets. It has many real world applications, such as personalized recommendation and community mining. In this paper, we study the problem of computing the similarity join in a dynamic context, where the sets are updated dynamically. This, however, is inefficient with the state-of-the-art join methods, because they usually assume that data collections are static and have to compute the join result from scratch whenever a set is updated. To address this issue, we propose ${{\sf ALJoin}}$ALJoin, an adaptive filtering approach that computes the join result incrementally based on the update logs. We first investigate the effect of set updates on the similarity values, and on this basis we propose to build a neighborhood index for each set. The neighborhood index of a specific set consists of any other sets that can be transformed into its similar sets within a threshold number of update operations. ${{\sf ALJoin}}$ALJoin then uses this index to effectively identify both similar and dissimilar set pairs based on their update logs. To efficiently build the neighborhood index, we devise several filtering techniques and propose a “lazy-forward” method to reduce the computational cost. In addition, to improve the efficiency on varying workloads, we propose an analytical cost model, and design an online algorithm with performance guarantees to dynamically consolidate the update logs and adapt the neighborhood indexes. We evaluated our method using four real-world datasets. Experimental results show that our approach outperforms existing methods by up to $3.7\times$3.7×.

Core decomposition on uncertain graphs is a fundamental problem in graph analysis. Given an uncertain graph $\mathcal {G}$G, the core decomposition problem is to determine all $(k,\eta)\text{-cores}$(k,η)-cores in $\mathcal {G}$G, where a $(k,\eta)\text{-core}$(k,η)-core is a maximal subgraph of $\mathcal {G}$G such that each node has an $\eta \text{-}$η-${\mathsf {degree}}$degree no less than $k$k within the subgraph. The $\eta \text{-}$η-${\mathsf {degree}}$degree of a node $v$v is defined as the maximum integer $r$r such that the probability that $v$v has a degree no less than $r$r is larger than or equal to the threshold $\eta \in [0,1]$η∈[0,1]. The state-of-the-art algorithm for solving this problem is based on a peeling technique which iteratively removes the nodes with the smallest $\eta \text{-}$η-${\mathsf {degrees}}$degrees and also dynamically updates their neighbors’ $\eta \text{-}$η-${\mathsf {degrees}}$degrees. Unfortunately, we find that such a peeling algorithm with the dynamical $\eta \text{-}$η-${\mathsf {degree}}$degree updating technique is incorrect due to the inaccuracy of the recursive floating-point number division operations involved in the dynamical updating procedure. To correctly compute the $(k,\eta)\text{-cores}$(k,η)-cores, we first propose a bottom-up algorithm based on an on-demand $\eta \text{-}$η-${\mathsf {degree}}$degree computational strategy. To further improve the efficiency, we also develop a more efficient top-down algorithm with several nontrivial optimization techniques. Both of our algorithms do not involve any floating-point number division operations, thus the correctness can be guaranteed. In addition, we also develop the parallel variants of all the proposed algorithms. Finally, we conduct extensive experiments to evaluate the proposed algorithms using five large real-life datasets. The results show that our algorithms are at least three orders of magnitude faster than the existing exact algorithms on large uncertain graphs. The results also demonstrate the high scalability and parallel performance of the proposed algorithms.

Autism spectrum disorder (ASD) is characterized by poor social communication abilities and repetitive behaviors or restrictive interests, which has brought a heavy burden to families and society. In many attempts to understand ASD neurobiology, resting-state functional magnetic resonance imaging (rs-fMRI) has been an effective tool. However, current ASD diagnosis methods based on rs-fMRI have two major defects. First, the instability of rs-fMRI leads to functional connectivity (FC) uncertainty, affecting the performance of ASD diagnosis. Second, many FCs are involved in brain activity, making it difficult to determine effective features in ASD classification. In this study, we propose an interpretable ASD classifier DeepTSK, which combines a multi-output Takagi-Sugeno-Kang (MO-TSK) fuzzy inference system (FIS) for composite feature learning and a deep belief network (DBN) for ASD classification in a unified network. To avoid the suboptimal solution of DeepTSK, a joint optimization procedure is employed to simultaneously learn the parameters of MO-TSK and DBN. The proposed DeepTSK was evaluated on datasets collected from three sites of the Autism Brain Imaging Data Exchange (ABIDE) database. The experimental results showed the effectiveness of the proposed method, and the discriminant FCs are presented by analyzing the consequent parameters of Deep MO-TSK.

Decentralized storage systems such as blockchain storage applications adopt the distributed storage technology and use distributed storage nodes to store the persistent data. For each off-chain storage node, keyvalue (KV) stores are normally used to manage data. As the most common data structure for KV store, Log Structured Merge Tree (LSM-Tree) eliminates random write operations and keeps acceptable read performance. Although LSM-Tree-based decentralized storage system can provide a secure and reliable storage platform, the unique feature of blockchain applications is not fully exploited. In blockchain storage applications, the generation of keys for KV stores is based on the encrypted data. A physical block in a solid-state drive (SSD) could be filled with data from different system users. This mixture of workloads will lead to the inefficient usage of physical spaces in the SSD and cause extra compaction operations for LSM-Tree. This paper presents Meta-Block, a cross-layer and efficient storage management strategy for decentralized blockchain storage applications. The objective is to capture the features of blockchain storage applications and reduce unnecessary read and write operations across different storage layers. As a cross-layer design, Meta-Block redesigns the organization of LSM-Tree, which can effectively reduce the write amplification. We also design a data prefetching strategy to speed up the indexing and enable direct storage access. We demonstrate the viability of the proposed technique using a set of extensive experiments. Experimental results show that Meta-Block can effectively reduce the write amplification and extend the lifetime of SSDs in comparison with representative schemes.

Energy storage is a common challenge for spacecraft and vehicles, whose operating range and operational availability are limited to a considerable extent by the storage capacity; mass and volume are the main issues. Composite structural batteries (CSBs) are emerging as a new solution to reduce the size of electric systems that can bear loads and store energy. Carbon-fiber-reinforced polymers (CFRP) offer significant advantages over metallic structures. This paper reviews the recent design of multifunctional composites by combining batteries with CFRP to obtain structural lightweight and excellent mechanical properties. The assembly methods for different CSBs based on the type of electrolyte used are discussed. A comparative analysis is performed on the energy density, rate performance, cycle performance, and mechanical performance with a particular focus on the multifunctional efficiency of various CSBs. Furthermore, the opportunities and challenges in CSBs are discussed, and research ideas are proposed for this emerging field.

To overcome the temperature and salt resistance challenges faced by unconventional profile control agents in high-temperature and high-salt reservoirs. A novel low viscosity, temperature and salt stimulus response system named TRE was obtained by using emulsified epoxy resin and curing agent. Experimental work covers from core size to microscopic size to explore the effect and mechanism of enhancing oil recovery. A comprehensive analysis was conducted on the rheological properties, apparent viscosity, plugging ability, profile control capability, macroscopic oil displacement efficiency, and microscopic oil displacement mechanism of TRE emulsion. Our results indicated that the TRE exhibits temperature and salt responsiveness, with a salt tolerance of 7 × 104 mg/L and a phase change temperature of approximately 65 °C. Moreover, at a TRE concentration of 8 wt%, TRE showcased a lower injection viscosity of 1.3 mPa s. The microstructure after phase change was studied using SEM, and the irregular elliptical pore network structure enhanced its long-term thermal stability. Core displacement experiments were conducted to evaluate its plugging performance and profile control capability. The optimal plugging effect and injectability conditions were confirmed at an injection rate of 1 mL/min, an injection volume of 0.8 PV, and a TRE concentration of 8 wt%. As a profile control agent, TRE was well-suited for reservoirs with medium to low permeability, formation salinity ranging from 3 to 7 × 104 mg/L, and temperatures above 65 °C, with a permeability limit of 180.2–720.1 mD. When the heterogeneity was below 9, the TRE exhibited a strong profile control effect, achieving a shunt rate of over 66% in low-permeability cores after plugging. Furthermore, macroscopic and microscopic oil displacement experiments indicated that TRE can effectively plug large and medium pores, and increase the coverage area of small pores. TRE has the advantage of plugging high permeability without complete plugging, which can effectively reduce reservoir heterogeneity and provide a uniform displacement. Following plugging, the swept volume by waterflooding increased by 18.46%, and the recovery rate increased by 19.10%. Temperature and salt responsive TRE exhibit excellent plugging ability, profile control capability, and oil displacement efficiency. Overall, this novel self-assembly system has potential for application in the exploitation of high-temperature and high salinity oil reservoirs.

Due to its large electric dipole moment, the Rydberg atom exhibits a strong response to weak electric fields, hence it is regarded as a highly promising atomic antenna. However, to enhance the reception sensitivity, split-ring resonators are needed normally, which will brings sensing blind spots. Thus it is not conducive to the application of full-coverage space communication. Here we propose that an atomic antenna with an asymmetric parallel-plate resonator, can not only enhance the received signal, but also eliminate sensing blind spots (pattern roundness can reach 7.8 dB while the split-ring resonator can be up to 39 dB). We analyze the influence of structural parameters on the field enhancement factor and directionality, and further discuss the limitation of the sensitivity by using thermal resistor noise theory. This work is expected to pave the way for the development of field-enhanced Rydberg atomic antennas that communicate without a blind spot.

Vehicle lightweight promises to drive down the maintenance quality and increase energy efficiency in transportation with the safe and strength performance. The use of fiber reinforced polymer composite materials structural battery vehicles is recognized as an essential enabling technology for achieving high bearing capacity and energy storage capacity. At the same time it improves the energy storage capacity, the overall structural energy storage and space utilization of new energy vehicles. In this study we bring an idea to fabricate composites with integrated lithium-ion pouch batteries. The whole preparation process was carried out at room temperature to prevent thermal damage on battery. Experimental results indicate that the cyclic working voltage and capacity of CFRP structure battery are basically consistent with the monomer lithium-ion polymer battery which obtained from Xinwei battery testing equipment. Therefore, the fabrication process does not damage the lithium-ion polymer battery.

Flexible supercapacitors have attracted more and more attention and research because they can be used as energy storage devices for future flexible electronic devices. In the existing research, graphene has been used to make supercapacitor electrodes, but usually these electrodes have very low specific capacitance or flexibility. Here, a three-dimensional graphene hydrogel for the fabrication of flexible supercapacitors was presented, and the preparation of flexible supercapacitors based on three-dimensional graphene hydrogels was given. Through the research, we find that the prepared flexible supercapacitor has excellent capacitance characteristics, such as high specific capacitance of 168F/g and excellent mechanical flexibility. This study shows that the three-dimensional graphene macro structure has great potential in the preparation of high-performance flexible energy storage devices.

ABSTRACTCircular RNAs (circRNAs) play a critical role in acute cerebral infarction (ACI). Our research discussed the effect of circ-Carm1 in ACI and its potential molecular mechanisms. Healthy controls and patients with ACI were included in this study. The establishment of an oxygen and glucose deprivation/reoxygenation (OGD/R) model of HT22 cells was conducted to mimic ACI in vitro. Quantitative reverse transcription polymerase chain reaction was conducted to determine mRNA levels extracted from serum and HT22 cell samples, and Western blotting was performed to determine protein levels. Terminal deoxynucleotidyl transferase dUTP nick end labeling and cell counting kit 8 assays were conducted to evaluate cellular functions. Concentrations of Fe2+and malondialdehyde, and levels of transferrin receptor 1, glutathione peroxidase 4, and glutathione were evaluated to determine ferroptosis in OGD/R-induced HT22 cells. The binding relationships between mRNAs and miRNAs were verified. circ-Carm1 was highly expressed in OGD/R-treated HT22 cells. Deficiency of circ-Carm1 restored cell viability and suppressed ferroptosis in OGD/R-induced HT22 cells. miR-3098-3p was predicted to be a target of circ-Carm1. The miR-3098-3p inhibitor partly neutralized the functions of circ-Carm1 in OGD/R-induced HT22 cells. Furthermore, acyl-CoA synthetase long-chain family member 4 (ACSL4) was confirmed to be a downstream target of miR-3098-3p and was elevated in OGD/R-induced HT22 cells. Overexpression of ACSL4 mitigated the functions of miR-3098-3p and accelerated HT22 cell dysfunction. Hence, circ-Carm1 is upregulated in ACI. circ-Carm1 suppression protects HT22 cells from dysfunction by inhibiting ferroptosis. Therefore, inducing circ-Carm1 deficiency may be a promising therapeutic method for ACI.

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This paper explores the evolution of pore structure parameters during Zhundong coal and biomass ash sintering at 1473 K. Additionally, the influences of blending biomass ash with different proportions are determined. The pore parameters, including the porosity, diameter, number, and frequency of the equivalent diameter, were processed by reconstructing and processing three-dimensional (3D) data on the basis of X-ray computed microtomography (XCT). The maximum porosities for the cases of pure coal and mixture of 10% biomass and 50% biomass during sintering are determined to be 46.6, 42.6, and 24.0%, respectively, while the frequencies of small pores (<0.2 mm) in the coal ash samples are lower than those in the other cases. In addition, the mineralogical phase transformation during sintering is identified by X-ray diffraction analysis. The condensate in the pores mainly comprises NaCl, CaSO4, and KCl, which indicates that the volatilization of alkali metals and the formation and gasification of anhydrite occur throughout the sintering process.

Maternal immune activation (MIA) induced by lipopolysaccharides or polyinosinic:polycytidylic acid injections can induce behavioral abnormalities in adult mouse offspring. Here, we used the soluble tachyzoite antigen from Toxoplasma gondii, a parasite that infects approximately two billion people, to induce MIA in mice. The adult male offspring showed autism-relevant behaviors and abnormal brain microstructure, along with a pro-inflammatory T-cell immune profile in the periphery and upregulation of interleukin-6 in brain astrocytes. We show that adoptive transfer of regulatory T (Treg) cells largely reversed these MIA-induced phenotypes. Notably, pathogen-activated maternal Tregcells showed greater rescue efficacy than those from control donors. Single-cell RNA sequencing identified and characterized a unique group of pathogen-activated Tregcells that constitute 32.6% of the pathogen-activated maternal Tregpopulation. Our study establishes a new preclinical parasite-mimicking MIA model and suggests therapeutic potential of adoptive Tregcell transfer in neuropsychiatric disorders associated with immune alterations.

Wind erosion is largely controlled by climate conditions. In this study, we examined the influences of changes in wind speed, soil wetness, snow cover, and vegetation cover related to climate change on wind erosion in northern China during 1981–2016. We used the wind erosion force, defined as wind factor in the Revised Wind Erosion Equation Model, to describe the effect of wind speed on wind erosion. The results show that wind erosion force presented a long-term decreasing trend in the southern Northwest, northern Northwest, and eastern northern China during 1981–2016. In the Gobi Desert, the wind erosion force presented for 1981–1992 a decreasing trend, for 1992–2012 an increasing trend, and thereafter a weakly decreasing trend. In comparison to wind speed, soil wetness and snow cover had weaker influences on wind erosion in northern China, while vegetation cover played a significant role in the decrease of wind erosion in the eastern northern China during 1982–2015.

ABSTRACTThe role of circular RNA in cancer is emerging. A newly reported circular RNA HIPK3(circHIPK3)is critical in cell proliferation of various cancer types, although its role in non-small cell lung cancer (NSCLC), has yet to be elucidated. Our results provided evidence that silencing of circHIPK3significantly impaired cell proliferation, migration, invasion and induced macroautophagy/autophagy. Mechanistically, we uncovered that autophagy was induced upon loss of circHIPK3via the MIR124-3p-STAT3-PRKAA/AMPKa axis in STK11 mutant lung cancer cell lines (A549 and H838). STAT3 abrogation as well as transfection with a MIR124-3pmimic, recapitulated the induction of autophagy. We also demonstrated antagonistic regulation on autophagy between circHIPK3and linear HIPK3(linHIPK3). We therefore propose that the ratio between circHIPK3and linHIPK3(C:L ratio) may reflect autophagy levels in cancer cells. We observed that a high C:L ratio (>0.49) was an indicator of poor survival, especially in advanced-stage NSCLC patients. These results support that circHIPK3is a key autophagy regulator in a subset of lung cancer and has potential clinical use as a prognostic factor. The circular RNA HIPK3(circHIPK3)functions as an oncogene and autophagy regulator may potential use as a prognostic marker and therapeutic target in lung cancer.Abbreviations3-MA: 3-methyladenine; AMPK: AMP-activated protein kinase; ATG7: autophagy related 7; Baf-A: bafilomycin A1; BECN1: beclin 1; circHIPK3: circular HIPK3; CQ: chloroquine; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; GFP: green fluorescent protein; HIPK3: homeodomain interacting protein kinase 3; IL6R: interleukin 6 receptor; MAP1LC3B/LC3B: microtubule associated protein 1 light chain 3 beta; NSCLC: non-small cell lung cancer; RFP: red fluorescent protein; RPS6KB1/S6K: ribosomal protein S6 kinase B1; SQSTM1/p62: sequestosome 1; STAT3: signal transducer and activator of transcription 3; STK11: serine/threonine kinase 11

With the development of the social economy and the continuous improvement of the market economy system, strengthening human resource management is the key to improving market competitiveness. This paper believes that the development of the production process of an enterprise guides the environmental performance evaluation content of each mode of production differently. Therefore, while using environmental performance to evaluate companies, it is also necessary to examine the evaluation content of corporate environmental performance under different production methods. This paper uses the expert survey method to study the performance evaluation. Two members of the expert group actively hope to obtain economic benefits through environmental protection measures, while other expert members have different opinions on this ratio.

Cells are fundamental units of life. The coordination of cellular functions and behaviors relies on a cascade of molecular networks. Technologies that enable exploration and manipulation of specific molecular events in living cells with high spatiotemporal precision would be critical for pathological study, disease diagnosis, and treatment. Framework nucleic acids (FNAs) represent a novel class of nucleic acid materials characterized by their monodisperse and rigid nanostructure. Leveraging their exceptional programmability, convenient modification property, and predictable atomic-level architecture, FNAs have attracted significant attention in diverse cellular applications such as cell recognition, imaging, manipulation, and therapeutic interventions. In this perspective, we will discuss the utilization of FNAs in living cell systems while critically assessing the opportunities and challenges presented in this burgeoning field.

The sluggish CO2reduction and evolution reaction kinetics are thorny problems for developing high-performance Li–CO2batteries. For the complicated multiphase reactions and multielectron transfer processes in Li–CO2batteries, exploring efficient cathode catalysts and understanding the interplay between structure and activity are crucial to couple with these pendent challenges. In this work, we applied the CoS as a model catalyst and adjusted its electronic structure by introducing sulfur vacancies to optimize the d-band and p-band centers, which steer the orbital hybridization and boost the redox kinetics between Li and CO2, thus improving the discharge platform of Li–CO2batteries and altering the deposition behavior of discharge products. As a result, a highly efficient bidirectional catalyst exhibits an ultrasmall overpotential of 0.62 V and a high energy efficiency of 82.8% and circulates stably for nearly 600 h. Meanwhile, density functional theory calculations and multiphysics simulations further elucidate the mechanism of bidirectional activity. This work not only provides a proof of concept to design a remarkably efficient catalyst but also sheds light on promoting the reversible Li–CO2reaction by tailoring the electronic structure.

An efficient strategy for the synthesis of benzofuro[2,3-b]pyrazines was developed. These tricyclic scaffolds were formed through a multistep cascade sequence, which includes double insertion of isonitriles and chemoselective bicyclization. In this reaction, a nanopalladium was used as a recyclable catalyst. Product 3wexhibited excellent anticancer activity toward T-24 (IC50= 12.5 ± 0.9 μM) and HeLa (IC50= 14.7 ± 1.6 μM) cells. We also explored the action mechanism of 3won T-24 cells.

In this study, the possible influence of the Antarctic oscillation (AAO) on winter haze pollution (indicated by atmospheric visibility after rain, fog, dust, snowstorms, etc. are removed) in North China (NC) was investigated. The results show that the mean winter visibility (December‐January‐February visibility) throughout most of eastern China is negatively correlated with the preceding AAO (August‐September‐October (ASO)‐AAO), especially in NC. The interannual correlation coefficient between DJF‐VIS in NC and the ASO‐AAO is −0.52, which is significant at the 99% level. The negative correlation suggests that an enhancing (weakening) ASO‐AAO could be conducive to increases (decreases) of haze pollution in NC in boreal winter. The responses of local and regional meteorological conditions to the ASO‐AAO support the relationship between the ASO‐AAO and winter air pollution in NC. A preliminary mechanism analysis shows that a positive ASO‐AAO may induce a sea surface temperature warming tendency in the Northwestern Southern Indian Ocean. This warming then causes a wave train‐like pattern in the upper troposphere along the jet stream and an anomalous zonal cell that weakens the regional Hadley circulation from the Maritime continents to East Asia. All of these factors are favorable to the formation of anomalous southerly and haze pollution in NC. Haze pollution in North China is significantly correlated with the preceding AAOThe responses of local and regional meteorological conditions to the AAO lend support to the findingsThe southern Indian Ocean may exert an important influence on the link between haze pollution and the AAO through two possible pathways