PQSDC: a parallel lossless compressor for quality scores data via sequences partition and Run-Length prediction mapping.

MOTIVATION: The quality scores data (QSD) account for 70% in compressed FastQ files obtained from the short and long reads sequencing technologies. Designing effective compressors for QSD that counterbalance compression ratio, time cost, and memory consumption is essential in scenarios such as large-scale genomics data sharing and long-term data backup. This study presents a novel parallel lossless QSD-dedicated compression algorithm named PQSDC, which fulfills the above requirements well. PQSDC is based on two core components: a parallel sequences-partition model designed to reduce peak memory consumption and time cost during compression and decompression processes, as well as a parallel four-level run-length prediction mapping model to enhance compression ratio. Besides, the PQSDC algorithm is also designed to be highly concurrent using multi-core CPU clusters. RESULTS: We evaluate PQSDC and 4 state-of-the-art compression algorithms on 27 real-world datasets, including 61.857 billion QSD characters and 632.908 million QSD sequences. (1) For short reads, compared to baselines, the maximum improvement of PQSDC reaches 7.06% in average compression ratio, and 8.01% in weighted average compression ratio. During compression and decompression, the maximum total time savings of PQSDC are 79.96% and 84.56%, respectively; the maximum average memory savings are 68.34% and 77.63%, respectively. (2) For long reads, the maximum improvement of PQSDC reaches 12.51% and 13.42% in average and weighted average compression ratio, respectively. The maximum total time savings during compression and decompression are 53.51% and 72.53%, respectively; the maximum average memory savings are 19.44% and 17.42%, respectively. (3) Furthermore, PQSDC ranks second in compression robustness among the tested algorithms, indicating that it is less affected by the probability distribution of the QSD collections. Overall, our work provides a promising solution for QSD parallel compression, which balances storage cost, time consumption, and memory occupation primely. AVAILABILITY: The proposed PQSDC compressor can be downloaded from https://github.com/fahaihi/PQSDC. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

High-Pressure-Field Induced Synthesis of Ultrafine-Sized High-Entropy Compounds with Excellent Sodium-Ion Storage.

Emerging high entropy compounds (HECs) have attracted huge attention in electrochemical energy-related applications. The features of ultrafine size and carbon incorporation show great potential to boost the ion-storage kinetics of HECs. However, they are rarely reported because high-temperature calcination tends to result in larger crystallites, phase separation, and carbon reduction. Herein, using the NaCl self-assembly template method, by introducing a high-pressure field in the calcination process, the atom diffusion and phase separation are inhibited for the general formation of HECs, and the HEC aggregation is inhibited for obtaining ultrafine size. The general preparation of ultrafine-sized (< 10 nm) HECs (nitrides, oxides, sulfides, and phosphates) anchored on porous carbon composites is realized. They are demonstrated by combining advanced characterization technologies with theoretical computations. Ultrafine-sized high entropy sulfides-MnFeCoCuSnMo/porous carbon (HES-MnFeCoCuSnMo/PC) as representative anodes exhibit excellent sodium-ion storage kinetics and capacities (a high rating capacity of 278 mAh g-1 at 10 A g-1 for full cell and a high cycling capacity of 281 mAh g-1 at 20 A g-1 after 6000 cycles for half cell) due to the combining advantages of high entropy effect, ultrafine size, and PC incorporation. Our work provides a new opportunity for designing and fabricating ultrafine-sized HECs.

Heat-resistant super-dispersed oxide strengthened aluminium alloys.

Oxided-dispersion-strengthened (ODS) alloys are promising high-strength materials used in extreme environments such as high-temperature and radiation tolerance applications. Until now, ODS alloys have been developed for reducible metals by chemical processing methods, but there are no commercially available ODS alloys for unreducible metals, namely, Al, Mg, Ti, Zr and so on, owing to the challenge of uniformly dispersing oxide particles in these alloys by traditional techniques. Here we present a strategy to achieve ODS Al alloys containing highly dispersive 5 nm MgO nanoparticles by powder metallurgy, using nanoparticles that have in situ-grown graphene-like coatings and hence largely reduced surface energy. Notably, the densely dispersed MgO nanoparticles, which have a fully coherent relationship with an Al matrix, show effective suppression of interfacial vacancy diffusion, thus leading to unprecedented strength (~200 MPa) and creep resistance at temperatures as high as 500 °C. Our processing approach should enable the dispersion of ultrafine nanoparticles in a wide range of alloys for high-temperature-related applications.

Regulating Metal Centers of MOF-74 Promotes PEO-Based Electrolytes for All-Solid-State Lithium-Metal Batteries.

Poly(ethylene oxide) (PEO)-based electrolytes have been extensively studied for all-solid-state lithium-metal batteries due to their excellent film-forming capabilities and low cost. However, the limited ionic conductivity and poor mechanical strength of the PEO-based electrolytes cannot prevent the growth of undesirable lithium dendrites, leading to the failure of batteries. Metal-organic frameworks (MOFs) are functional materials with a periodic porous structure that can improve the electrochemical performance of PEO-based electrolytes. However, the enhancement effect of MOFs with different metal centers and the interaction mechanism with PEO remain unclear. Herein, MOF-74s with Cu or Ni centers are prepared and used as fillers of PEO-based electrolytes. Adding 15 wt % of Cu-MOF-74 to the PEO-based electrolyte (15%Cu-MOF/P-Li) effectively improves the ionic conductivity, lithium transference number, and mechanical strength of the PEO-based electrolyte simultaneously. Furthermore, the ordered pore channels of Cu-MOF-74 provide uniform Li-ion transport pathways, facilitating homogeneous Li+ deposition. As a result, the lithium symmetric cell with 15%Cu-MOF/P-Li shows stable cycles for 1080 h at 0.1 mA cm-2 and 0.1 mAh cm-2, and the Li | 15% Cu-MOF/P-Li | LFP full cell exhibits a long cycle life up to 200 cycles at 60 °C and 0.5 C, with a capacity retention rate of 89.7%.

The Synthesis of Three-Dimensional Hexagonal Boron Nitride as the Reinforcing Phase of Polymer-Based Electrolyte for All-Solid-State Li Metal Batteries.

Powdery hexagonal boron nitride (h-BN), as an important material for electrochemical energy storage, has been typically synthesized in bulk and one/two-dimensional (1/2D) nanostructured morphologies. However, until now, no method has been developed to synthesize powdery three-dimensional (3D) h-BN. This work introduces a novel NaCl-glucose-assisted strategy to synthesize micron-sized 3D h-BN with a honeycomb-like structure and its proposed formation mechanism. We propose that NaCl acts as the template of 3D structure and promotes the nitridation reaction by adsorbing NH3 . Glucose facilitates the homogeneous coating of boric acid onto the NaCl surface via functionalizing the NaCl surface. During the nitridation reaction, boron oxides (BO4 and BO3 ) form from a dehydration reaction of boric acid, which is then reduced to O2 -B-N and O-B-N2 intermediates before finally being reduced to BN3 by NH3 . When incorporated into polyethylene oxide-based electrolytes for Li metal batteries, 5 wt % of 3D h-BN significantly enhances ionic conductivity and mechanical strength. Consequently, this composite electrolyte demonstrates superior electrochemical stability. It delivers 300 h of stable cycles in the Li//Li cell at 0.1 mA cm-2 and retains 89 % of discharge capacity (138.9 mAh g-1 ) after 100 cycles at 1 C in the LFP//Li full cell.

KAN0438757, a novel PFKFB3 inhibitor, prevent the progression of severe acute pancreatitis via the Nrf2/HO-1 pathway in infiltrated macrophage.

Acute pancreatitis (AP) is a non-infectious pancreatic enzyme-induced disorder, a life-threatening inflammatory condition that can cause multi-organ dysfunction, characterized by high morbidity and mortality. Several therapies have been employed to target this disorder; however, few happen to be effectively employable even in the early phase. PFKFB3(6-phosphofructo-2-kinase/fructose-2,6-biphosphatase-3) is a critical regulator of glycolysis and is upregulated under inflammatory, mitogenic, and hypoxia conditions. Essential information on the targeting of the inflammatory pathway will present the termination of the disorder and recovery. Herein we investigated the protective function of KAN0438757, a potent inhibitor of PFKFB3, and its mechanism of impeding AP induced in mice. KAN0438757 was confirmed to activate the Nrf2/HO-1 inflammatory signaling pathways in response to caerulein induced acute pancreatitis (CAE-AP) and fatty acid ethyl ester induced severe acute pancreatitis (FAEE-SAP). Additionally, KAN0438757 alleviated the inflammatory process in infiltrated macrophage via the Nrf2/HO-1 inflammatory signaling pathway and demonstrated a significant effect on the growth of mice with induced AP. And more importantly, KAN0438757 displayed negligible toxicity in vivo. Taken together our data suggest KAN0438757 directly suppresses the inflammatory role of PFKFB3 and induces a protective role via the Nrf2/HO-1 pathway, which could prove as an excellent therapeutic platform for SAP amelioration.

A multisite dynamic synergistic oxygen evolution reaction mechanism of Fe-doped NiOOH: a first-principles study.

Changing the composition is an important way to regulate the electrocatalytic performance of the oxygen evolution reaction (OER) for metallic compounds. Clarifying the synergistic mechanism among different compositions is a key scientific problem to be solved urgently. Here, based on first-principles calculations, a Ni-O-Fe multisite dynamic synergistic reaction mechanism (MDSM) for the OER of Fe-doped NiOOH (NiFeOOH) has been discovered. Based on the MDSM, Fe/O/Ni are triggered as the active sites in turn, resulting in an overpotential of 0.33 V. The factors affecting the deprotonation, O-O coupling, and O2 desorption during the OER process are analyzed. The electron channels related to the magnetic states among Fe-O-Ni is revealed, which results in the decoupling between OER sites and the oxidation reaction sites. O-O coupling and O2 desorption are affected by ferromagnetic coupling and the instability of the lattice O during the OER process, respectively. The results give a comprehensive understanding of the active sites in NiFeOOH and provide a new perspective on the synergistic effects among different compositions in metal compounds during the OER process.

PMFFRC: a large-scale genomic short reads compression optimizer via memory modeling and redundant clustering.

BACKGROUND: Genomic sequencing reads compressors are essential for balancing high-throughput sequencing short reads generation speed, large-scale genomic data sharing, and infrastructure storage expenditure. However, most existing short reads compressors rarely utilize big-memory systems and duplicative information between diverse sequencing files to achieve a higher compression ratio for conserving reads data storage space. RESULTS: We employ compression ratio as the optimization objective and propose a large-scale genomic sequencing short reads data compression optimizer, named PMFFRC, through novelty memory modeling and redundant reads clustering technologies. By cascading PMFFRC, in 982 GB fastq format sequencing data, with 274 GB and 3.3 billion short reads, the state-of-the-art and reference-free compressors HARC, SPRING, Mstcom, and FastqCLS achieve 77.89%, 77.56%, 73.51%, and 29.36% average maximum compression ratio gains, respectively. PMFFRC saves 39.41%, 41.62%, 40.99%, and 20.19% of storage space sizes compared with the four unoptimized compressors. CONCLUSIONS: PMFFRC rational usage big-memory of compression server, effectively saving the sequencing reads data storage space sizes, which relieves the basic storage facilities costs and community sharing transmitting overhead. Our work furnishes a novel solution for improving sequencing reads compression and saving storage space. The proposed PMFFRC algorithm is packaged in a same-name Linux toolkit, available un-limited at https://github.com/fahaihi/PMFFRC .

Application of hyaluronic acid-based nanoparticles for cancer combination therapy.

Cancer is a significant public health problem in the world. The treatment methods include surgery, chemotherapy, phototherapy, and immunotherapy. Due to their respective limitations, the treatment effect is often unsatisfactory, laying hidden dangers for metastasis and recurrence. Since their exceptional biocompatibility and excellent targeting capabilities, hyaluronic acid-based biomaterials have generated great interest as drug delivery methods for tumor therapy. Moreover, modified HA can self-assemble into hydrogels or nanoparticles (NPs) for precise drug administration. This article summarizes the application of HA-based NPs in combination therapy. Ultimately, it is anticipated that this research will offer guidance for creating various HA-based NPs utilized in numerous cancer therapies.

Gut microbiome as a biomarker for predicting early recurrence of HBV-related hepatocellular carcinoma.

To investigate the potential of the gut microbiome as a biomarker for predicting the early recurrence of HBV-related hepatocellular carcinoma (HCC), we enrolled 124 patients diagnosed with HBV-associated HCC and 82 HBV-related hepatitis, and 86 healthy volunteers in our study, collecting 292 stool samples for 16S rRNA sequencing and 35 tumor tissue samples for targeted metabolomics. We performed an integrated bioinformatics analysis of gut microbiome and tissue metabolome data to explore the gut microbial-liver metabolite axis associated with the early recurrence of HCC. We constructed a predictive model based on the gut microbiota and validated its efficacy in the temporal validation cohort. Dialister, Veillonella, the Eubacterium coprostanoligenes group, and Lactobacillus genera, as well as the Streptococcus pneumoniae and Bifidobacterium faecale species, were associated with an early recurrence of HCC. We also found that 23 metabolites, including acetic acid, glutamate, and arachidonic acid, were associated with the early recurrence of HCC. A comprehensive analysis of the gut microbiome and tissue metabolome revealed that the entry of gut microbe-derived acetic acid into the liver to supply energy for tumor growth and proliferation may be a potential mechanism for the recurrence of HCC mediated by gut microbe. We constructed a nomogram to predict early recurrence by combining differential microbial species and clinical indicators, achieving an AUC of 78.0%. Our study suggested that gut microbes may serve as effective biomarkers for predicting early recurrence of HCC, and the gut microbial-tumor metabolite axis may explain the potential mechanism by which gut microbes promote the early recurrence of HCC.

Review and outlook of global energy use under the impact of COVID-19.

By collecting and sorting the energy demand data of developing and developed countries, this paper makes a comprehensive analysis of their energy demand, including the change of energy demand and the change trend of energy load in various sectors. The survey scope of the article includes the overall change trend of energy supply, natural gas, oil, electricity, coal, renewable energy (such as wind energy, solar energy, geothermal energy, tidal energy, etc.), and the data change of global carbon dioxide emission. Besides, this paper selects a variety of energy sources for comprehensive analysis to analyze the existing change trend in chronological order. The analysis methods include data statistics of primary energy production and consumption, energy intensity analysis of gross domestic product (GDP), production, and demand balance of oil, natural gas, and coal, and study the trade balance between different types of energy in different countries and regions. The regions examined in this review include the organization for economic cooperation and development (OECD); the group of seven (G7); Brazil, Russia, India, China and South Africa (BRICs); the European Union; Europe; North America; the Commonwealth of Independent States (CIS); Asia; Latin America; the Pacific Ocean; the Middle East and Africa. By studying these data, we can make a better summary of the current energy use, so as to conveniently grasp the context of energy development and have a general understanding of the current energy structure. Therefore, individuals and policymakers in the fields of energy trade can think more deeply about the future situation and draw conclusions.