fastCCLasso: a fast and efficient algorithm for estimating correlation matrix from compositional data.

MOTIVATION: The composition and structure of microbial communities on the body surface are closely related to human health. The interaction relationship among microbes can help us understand the formation of the microecological environment and the biological mechanism by which microorganisms influence host health. With the help of high-throughput sequencing technologies, microbial abundances in a natural environment can be directly measured without the isolation of microorganisms in culture. Sequencing experiments in microbiome studies can measure the relative abundance of microbes, which is called compositional data. Although there are already many methods for correlation analysis for compositional data, the computation time or accuracy still needs to be improved for current microbiome studies. RESULTS: We develop a fast and efficient algorithm, called fastCCLasso, based on a penalized weighted least squares for inferring the correlation structure of microbes from compositional data in microbiome studies. We perform a large number of numerical experiments and the simulation results show that fastCCLasso outperforms its competitors in edge detection for inferring the correlation network. We also apply fastCCLasso for estimating microbial networks in microbiome studies and fastCCLasso provides a conservative network with comparable false discovery counts that are derived from shuffled data. AVAILABILITY AND IMPLEMENTATION: FastCCLasso is open source and freely available from https://github.com/ShenZhang-Statistics/fastCCLasso under GNU LGPL v3.

Advanced UPLC-MS/MS Method for the Quantification of SIPI6398 in Rat Plasma and Its Pharmacokinetic Characterization.

SIPI6398 is a novel anti-schizophrenia agent with a new mechanism of action and demonstrates better target selectivity and safety compared to its competitors. However, few in vivo studies on the pharmacokinetics and bioavailability of SIPI6398 have been performed. A rapid and simple ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) approach was developed for accurate quantification of SIPI6398 in rat plasma. A simple protein precipitation of acetonitrile-methanol (9 : 1, v/v) was used to treat plasma. Chromatography was performed on a UPLC HSS T3 column (50 mm × 2.1 mm, 1.8 µm) at a flow rate of 0.4 ml/min. The mobile phase consisted of acetonitrile-water (with 0.1% formic acid) and gradient elution was used, and the elution time was 4 minutes. Quantitative analysis was performed using electrospray ionization (ESI) in positive ion detection mode with multiple reaction monitoring (MRM) mode. To evaluate the pharmacokinetics and bioavailability, SIPI6398 was administered to rats in two different ways: oral (4 mg/kg) and intravenous (2 mg/kg) administration. The calibration curve for the UPLC-MS/MS approach shows excellent linearity in the range of 1-2000 ng/mL with an r value above 0.99. The precision, accuracy, recovery, matrix effect, and stability results all meet the criteria established for biological analytical methods. The UPLC-MS/MS method was successfully applied it to pharmacokinetics study of SIPI6398. The bioavailability of SIPI6398 was calculated to be 13.2%. These studies have the potential to contribute towards a more comprehensive comprehension of the pharmacokinetics and bioavailability of SIPI6398.

Predicting therapeutic response to neoadjuvant immunotherapy based on an integration model in resectable stage IIIA (N2) non-small cell lung cancer.

OBJECTIVE: Accurately predicting response during neoadjuvant chemoimmunotherapy for resectable non-small cell lung cancer (NSCLC) remains clinically challenging. In this study, we investigate the effectiveness of blood-based tumor mutational burden (bTMB) and a deep learning (DL) model in predicting major pathologic response (MPR) and survival from a phase II trial. METHODS: Blood samples were prospectively collected from 45 stage IIIA (N2) NSCLC patients undergoing neoadjuvant chemoimmunotherapy. An integrated model, combining the CT-based DL score, bTMB, and clinical factors, was developed to predict tumor response to neoadjuvant chemoimmunotherapy. RESULTS: At baseline, bTMB were detected in 77.8% (35 of 45) of patients. Baseline bTMB ≥11 Muts/Mb was associated with significantly higher MPR rates (77.8% vs. 38.5%, p = 0.042), and longer disease-free survival (DFS, p = 0.043), but not overall survival (p = 0.131), compared to bTMB < 11 Muts/Mb in 35 patients with bTMB available. The developed DL model achieved an area under the curve (AUC) of 0.703 in all patients. Importantly, the predictive performance of the integrated model improved to an AUC of 0.820 when combining the DL score with bTMB and clinical factors. Baseline circulating tumor DNA (ctDNA) status was not associated with pathological response and survival. Compared to ctDNA residual, ctDNA clearance before surgery was associated with significantly higher MPR rates (88.2% vs. 11.1%, p < 0.001) and improved DFS (p = 0.010). CONCLUSIONS: The integrated model shows promise as a predictor of tumor response to neoadjuvant chemoimmunotherapy. Serial ctDNA dynamics provide a reliable tool for monitoring tumor response.

Isolation and characterization of a novel rodent hepevirus in long-tailed dwarf hamsters (Cricetulus longicaudatus) in China.

Hepeviruses have been identified in a broad range of animal hosts, including mammals, birds, and fish. In this study, rodents (n=91) from seven different species and ten pikas (Ochotona curzoniae) were collected in Qinghai Province, China. Using transcriptomic sequencing and confirmatory molecular testing, hepeviruses were detected in 27 of 45 (60 %) long-tailed dwarf hamsters (Cricetulus longicaudatus) and were undetected in other rodents and pika. The complete genome sequences from 14 representative strains were subsequently obtained, and phylogenetic analyses suggested that they represent a novel species within the genus Rocahepevirus, which we tentatively designated as Cl-2018QH. The virus was successfully isolated in human hepatoma (Huh-7) and murine fibroblast (17 Cl-1) cell lines, though both exhibited limited replication as assayed by detection of negative-sense RNA intermediates. A129 immunodeficient mice were inoculated with Cl-2018QH and the virus was consistently detected in multiple organs, despite relatively low viral loads. In summary, this study has described a novel rodent hepevirus, which enhances our knowledge of the genetic diversity of rodent hepeviruses and highlights its potential for cross-species transmission.

Distinct eLPBChAT projections for methamphetamine withdrawal anxiety and primed reinstatement of conditioned place preference.

Methamphetamine (METH) withdrawal anxiety symptom and relapse have been significant challenges for clinical practice, however, the underlying neuronal basis remains unclear. Our recent research has identified a specific subpopulation of choline acetyltransferase (ChAT+) neurons localized in the external lateral portion of parabrachial nucleus (eLPBChAT), which modulates METH primed-reinstatement of conditioned place preference (CPP). Here, the anatomical structures and functional roles of eLPBChAT projections in METH withdrawal anxiety and primed reinstatement were further explored. Methods: In the present study, a multifaceted approach was employed to dissect the LPBChAT+ projections in male mice, including anterograde and retrograde tracing, acetylcholine (Ach) indicator combined with fiber photometry recording, photogenetic and chemogenetic regulation, as well as electrophysiological recording. METH withdrawal anxiety-like behaviors and METH-primed reinstatement of conditioned place preference (CPP) were assessed in male mice. Results: We identified that eLPBChAT send projections to PKCδ-positive (PKCδ+) neurons in lateral portion of central nucleus of amygdala (lCeAPKCδ) and oval portion of bed nucleus of the stria terminalis (ovBNSTPKCδ), forming eLPBChAT-lCeAPKCδ and eLPBChAT-ovBNSTPKCδ pathways. At least in part, the eLPBChAT neurons positively innervate lCeAPKCδ neurons and ovBNSTPKCδ neurons through regulating synaptic elements of presynaptic Ach release and postsynaptic nicotinic acetylcholine receptors (nAChRs). METH withdrawal anxiety and METH-primed reinstatement of CPP respectively recruit eLPBChAT-lCeAPKCδ pathway and eLPBChAT-ovBNSTPKCδ pathway in male mice. Conclusion: Our findings put new insights into the complex neural networks, especially focusing on the eLPBChAT projections. The eLPBChAT is a critical node in the neural networks governing METH withdrawal anxiety and primed-reinstatement of CPP through its projections to the lCeAPKCδ and ovBNSTPKCδ, respectively.

Tunable Magnetism in Atomically Thin Itinerant Antiferromagnet with Room-Temperature Ferromagnetic Order.

Addressing the need for modulated spin configurations is crucial, as they serve as the foundational building blocks for next-generation spintronics, particularly in atomically thin structures and at room temperature. In this work, we realize intrinsic ferromagnetism in monolayer flakes and tunable ferro-/antiferromagnetism in (Fe0.56Co0.44)5GeTe2 antiferromagnets. Remarkably, the ferromagnetic ordering (≥1 L) and antiferromagnetic ordering (≥4 L) remain discernible up to room temperature. The TC (∼310 K) of the monolayer flakes sets a record high for known exfoliated monolayer van der Waals magnets. Within the framework of A-type antiferromagnetism, a notable odd-even layer-number effect at elevated temperatures (T = 150 K) is observed. Of particular interest is the strong ferromagnetic order in even-layer flakes at low temperatures. The intricate interplay among magnetic field strength, layer number, and temperature gives rise to a diverse array of phenomena, holding promise not only for new physics but also for practical applications.

Van der Waals Transition Metal Carbo-Chalcogenides: Theoretical Screening and Charge Storage.

High-rate lithium/sodium ion batteries or capacitors are the most promising functional units to achieve fast energy storage that highly depends on charge host materials. Host materials with lamellar structures are a good choice for hybrid charge storage hosts (capacitor or redox type). Emerging layered transition metal carbo-chalcogenides (TMCC) with homogeneous sulfur termination are especially attractive for charge storage. Using density functional theory calculations, six of 30 potential TMCC are screened to be stable, metallic, anisotropic in electronic conduction and mechanical properties due to the lamellar structures. Raman, infrared active modes and frequencies of the six TMCC are well assigned. Interlayer coupling, especially binding energies predict that the bulk layered materials can be easily exfoliated into 2D monolayers. Moreover, Ti2S2C, Zr2S2C are identified as the most gifted Li+/Na+ anode materials with relatively high capacities, moderate volume expansion, relatively low Li+/Na+ migration barriers for batteries or ion-hybrid capacitors. This work provides a foundation for rational materials design, synthesis, and identification of the emerging 2D family of TMCC.

Specific emitter identification based on multiple sequence feature learning.

The specific emitter identification is widely used in electronic countermeasures, spectrum control, wireless network security and other civil and military fields. In response to the problems that the traditional specific emitter identification algorithm relies on a priori knowledge and has poor generalizability, and the existing specific emitter identification algorithm based on deep learning has poor feature selection and the adopted feature extraction network is not targeted, etc., the specific emitter identification algorithm based on multi-sequence feature learning is proposed. Firstly, multiple sequence features of the emitted signal of the communication radiation source are extracted, and these features are combined into multiple sequence features. Secondly, the multiple sequence fusion convolutional network is constructed to fuse and deeply extract the multiple sequence features and complete the classification of individual communication radiation sources through the classifier of neural network. The selected sequence features of this algorithm contain more and more essential RFF information, while the targeted design of the multi-sequence feature fusion learning network can effectively extract the essential RFF information. The results show that the algorithm can significantly improve the performance of SEI compared with the benchmark algorithm, with a recognition rate gain of about 17%.

Enhancing cardiovascular risk prediction through AI-enabled calcium-omics.

Whole-heart coronary calcium Agatston score is a well-established predictor of major adverse cardiovascular events (MACE), but it does not account for individual calcification features related to the pathophysiology of the disease (e.g., multiple-vessel disease, spread of the disease along the vessel, stable calcifications, numbers of lesions, and density). We used novel, hand-crafted calcification features (calcium-omics); Cox time-to-event modeling; elastic net; and up and down synthetic sampling methods for imbalanced data, to assess MACE risk. We used 2457 CT calcium score (CTCS) images enriched for MACE events from our large no-cost CLARIFY program (ClinicalTrials.gov Identifier: NCT04075162). Among calcium-omics features, numbers of calcifications, LAD mass, and diffusivity (a measure of spatial distribution) were especially important determinants of increased risk, with dense calcification (> 1000HU, stable calcifications) associated with reduced risk Our calcium-omics model with (training/testing, 80/20) gave C-index (80.5%/71.6%) and 2-year AUC (82.4%/74.8%). Although the C-index is notoriously impervious to model improvements, calcium-omics compared favorably to Agatston and gave a significant difference (P < 0.001). The calcium-omics model identified 73.5% of MACE cases in the high-risk group, a 13.2% improvement as compared to Agatston, suggesting that calcium-omics could be used to better identity candidates for intensive follow-up and therapies. The categorical net-reclassification index was NRI = 0.153. Our findings from this exploratory study suggest the utility of calcium-omics in improved risk prediction. These promising results will pave the way for more extensive, multi-institutional studies of calcium-omics.

Effects of butyrate on intestinal ischemia-reperfusion injury via the HMGB1-TLR4-MyD88 signaling pathway.

BACKGROUND: This study combined bioinformatics and experimental verification in a mouse model of intestinal ischemia-reperfusion injury (IRI) to explore the protection mechanism exerted by butyrate against IRI. METHODS: GeneCards, Bioinformatics Analysis Tool for Molecular Mechanisms of Traditional Chinese Medicine and GSE190581 were used to explore the relationship between butyrate and IRI and aging. Protein-protein interaction networks involving butyrate and IRI were constructed via the STRING database, with hub gene analysis performed through Cytoscape. Functional enrichment analysis was conducted on intersection genes. A mouse model of IRI was established, followed by direct arterial injection of butyrate. The experiment comprised five groups: normal, sham, model, vehicle, low-dose butyrate, and high-dose butyrate. Intestinal tissue observation was done via transmission electron microscopy (TEM), histological examination via hematoxylin and eosin (H&E) staining, tight junction proteins detection via immunohistochemistry, and Western blot analysis of hub genes. Drug-target interactions were evaluated through molecular docking. RESULTS: Butyrate protected against IRI by targeting 458 genes, including HMGB1 and TLR4. Toll-like receptor pathway was implicated. Butyrate improved intestinal IRI by reducing mucosal damage, increasing tight junction proteins, and lowering levels of HMGB1, TLR4, and MyD88. Molecular docking showed strong binding energies between butyrate and HMGB1 (-3.7 kcal/mol) and TLR4 (-3.8 kcal/mol). CONCLUSIONS: According to bioinformatics predictions, butyrate mitigates IRI via multiple-target and multiple-channel mechanisms. The extent of IRI can be reduced by butyrate through the inhibition of the HMGB1-TLR4-MyD88 signaling pathway, which is related to senescence.

Anion Structure Regulation of Cobalt Silicate Hydroxide Endowing Boosted Oxygen Evolution Reaction.

Transition metal silicates (TMSs) are attempted for the electrocatalyst of oxygen evolution reaction (OER) due to their special layered structure in recent years. However, defects such as low theoretical activity and conductivity limit their application. Researchers always prefer to composite TMSs with other functional materials to make up for their deficiency, but rarely focus on the effect of intrinsic structure adjustment on their catalytic activity, especially anion structure regulation. Herein, applying the method of interference hydrolysis and vacancy reserve, new silicate vacancies (anionic regulation) are introduced in cobalt silicate hydroxide (CoSi), named SV-CoSi, to enlarge the number and enhance the activity of catalytic sites. The overpotential of SV-CoSi declines to 301 mV at 10 mA cm-2 compared to 438 mV of CoSi. Source of such improvement is verified to be not only the increase of active sites, but also the positive effect on the intrinsic activity due to the enhancement of cobalt-oxygen covalence with the variation of anion structure by density functional theory (DFT) method. This work demonstrates that the feasible intrinsic anion structure regulation can improve OER performance of TMSs and provides an effective idea for the development of non-noble metal catalyst for OER.

The impact of Nrf2 knockout on the neuroprotective effects of dexmedetomidine in a mice model of cognitive impairment.

The nuclear factor erythroid 2-related factor 2 (Nrf2) signalling pathway represents a crucial intrinsic protective system against oxidative stress and inflammation and plays a significant role in various neurological disorders. However, the effect of Nrf2 signalling on the regulation of cognitive impairment remains unknown. Dexmedetomidine (DEX) has neuroprotective effects and can ameliorate lipopolysaccharide (LPS)-induced cognitive dysfunction. Our objective was to observe whether Nrf2 knockout influences the efficacy of DEX in improving cognitive impairment and to attempt to understand its underlying mechanisms. An LPS-induced cognitive dysfunction model in wild-type and Nrf2 knockout mice (Institute of Cancer Research background; male; 8-12 weeks) was used to observe the impact of DEX on cognitive dysfunction. LPS was intraperitoneally injected, followed by novel object recognition and morris water maze experiments 24 h later. Hippocampal tissues were collected for histopathological and molecular analyses. Our research findings suggest that DEX enhances the expression of NQO1, HO-1, PSD95, and SYP proteins in hippocampal tissue, inhibits microglial proliferation, reduces pro-inflammatory cytokines IL-1ß and TNF-ɑ, increases anti-inflammatory cytokine IL-10, and improves dendritic spine density, thereby alleviating cognitive dysfunction induced by LPS. However, the knockout of the Nrf2 gene negated the aforementioned effects of DEX. In conclusion, DEX alleviates cognitive deficits induced by LPS through mechanisms of anti-oxidative stress and anti-inflammation, as well as by increasing synaptic protein expression and dendritic spine density. However, the knockout of the Nrf2 gene reversed the effects of DEX. The Nrf2 signaling pathway plays a crucial role in the mitigation of LPS-induced cognitive impairment by DEX.

DNMT1-targeting remodeling global DNA hypomethylation for enhanced tumor suppression and circumvented toxicity in oral squamous cell carcinoma.

BACKGROUND: The faithful maintenance of DNA methylation homeostasis indispensably requires DNA methyltransferase 1 (DNMT1) in cancer progression. We previously identified DNMT1 as a potential candidate target for oral squamous cell carcinoma (OSCC). However, how the DNMT1- associated global DNA methylation is exploited to regulate OSCC remains unclear. METHODS: The shRNA-specific DNMT1 knockdown was employed to target DNMT1 on oral cancer cells in vitro, as was the use of DNMT1 inhibitors. A xenografted OSCC mouse model was established to determine the effect on tumor suppression. High-throughput microarrays of DNA methylation, bulk and single-cell RNA sequencing analysis, multiplex immunohistochemistry, functional sphere formation and protein immunoblotting were utilized to explore the molecular mechanism involved. Analysis of human samples revealed associations between DNMT1 expression, global DNA methylation and collaborative molecular signaling with oral malignant transformation. RESULTS: We investigated DNMT1 expression boosted steadily during oral malignant transformation in human samples, and its inhibition considerably minimized the tumorigenicity in vitro and in a xenografted OSCC model. DNMT1 overexpression was accompanied by the accumulation of cancer-specific DNA hypomethylation during oral carcinogenesis; conversely, DNMT1 knockdown caused atypically extensive genome-wide DNA hypomethylation in cancer cells and xenografted tumors. This novel DNMT1-remodeled DNA hypomethylation pattern hampered the dual activation of PI3K-AKT and CDK2-Rb and inactivated GSK3ß collaboratively. When treating OSCC mice, targeting DNMT1 achieved greater anticancer efficacy than the PI3K inhibitor, and reduced the toxicity of blood glucose changes caused by the PI3K inhibitor or combination of PI3K and CDK inhibitors as well as adverse insulin feedback. CONCLUSIONS: Targeting DNMT1 remodels a novel global DNA hypomethylation pattern to facilitate anticancer efficacy and minimize potential toxic effects via balanced signaling synergia. Our study suggests DNMT1 is a crucial gatekeeper regarding OSCC destiny and treatment outcome.

Engineering High-Performance Li Metal Batteries through Dual-Gradient Porous Cu-CuZn Host.

Porous copper (Cu) current collectors show promise in stabilizing Li metal anodes (LMAs). However, insufficient lithiophilicity of pure Cu and limited porosity in three-dimensional (3D) porous Cu structures led to an inefficient Li-Cu composite preparation and poor electrochemical performance of Li-Cu composite anodes. Herein, we propose a porous Cu-CuZn (DG-CCZ) host for Li composite anodes to tackle these issues. This architecture features a pore size distribution and lithiophilic-lithiophobic characteristics designed in a gradient distribution from the inside to the outside of the anode structure. This dual-gradient porous Cu-CuZn exhibits exceptional capillary wettability to molten Li and provides a high porosity of up to 66.05%. This design promotes preferential Li deposition in the interior of the porous structure during battery operation, effectively inhibiting Li dendrite formation. Consequently, all cell systems achieve significantly improved cycling stability, including Li half-cells, Li-Li symmetric cells, and Li-LFP full cells. When paired synergistically with the double-coated LiFePO4 cathode, the pouch cell configured with multiple electrodes demonstrates an impressive discharge capacity of 159.3 mAh g-1 at 1C. We believe this study can inspire the design of future 3D Li anodes with enhanced Li utilization efficiency and facilitate the development of future high-energy Li metal batteries.

Co4+ in porous ZIF-67-derives intercalating-bridging adsorption of 2-reaction sites for simultaneous 2-electron transfer toward sensitive detection of uric acid.

Metal-organic frameworks (MOFs) have been used to detect uric acid (UA), but still very challenging to achieve a low detection limit due to the low inferior conductivity of MOFs. Herein, three different N-doped ZIF-67-derived carbons were synthesized for the first time by one-step co-pyrolysis of 2-methylimidazole with cobalt nitrate (CN), cobalt acetate (CA) or cobalt chloride (CC) toward UA sensing. Afterwards, the cobalt nitrate-derived Co particle (Co/CN) supported by N-doped ZIF-67-derived carbon displays extremely low detection limit and high sensitivity for UA, outperformed all reported MOFs-based UA sensors. More interestingly, it was discovered that the high valence Co4+ within the Co/CN sample produced in high-acidic environment can intercalate in the frame for a bridge adsorption between two reaction sites, which boosted simultaneous 2-electron transfer, while Co3+ only allows an end-adsorption structure for one-electron transfer being the rate determining step. Furthermore, the bridge adsorption mode of UA on Co4+ -based catalyst was also verified by theoretical DFT calculations and XPS experiment. This work holds great promise for a selective and sensitive UA sensor for practical bioscience and clinic diagnostic applications while shedding lights in fundamental research for innovative designs and developments of high-sensitive electrochemical sensors.

A one-pot CRISPR-RCA strategy for ultrasensitive and specific detection of circRNA.

Accurate and precise detection of circular RNA (circRNA) is imperative for its clinical use. However, the inherent challenges in circRNA detection, arising from its low abundance and potential interference from linear isomers, necessitate innovative solutions. In this study, we introduce, for the first time, the application of the CRISPR/Cas12a system to establish a one-pot, rapid (30 minutes to 2 hours), specific and ultrasensitive circRNA detection strategy, termed RETA-CRISPR (reverse transcription-rolling circle amplification (RT-RCA) with the CRISPR/Cas12a). This method comprises two steps: (1) the RT-RCA process of circRNA amplification, generating repeat units containing the back-splicing junction (BSJ) sequences; and (2) leveraging the protospacer adjacent motif (PAM)-independent Cas12a/crRNA complex to precisely recognize target sequences with BSJ, thereby initiating the collateral cleavage activity of Cas12a to generate a robust fluorescence signal. Remarkably, this approach exhibits the capability to detect circRNAs at a concentration as low as 300 aM. The sensor has been successfully employed for accurate detection of a potential hepatocellular carcinoma biomarker hsa_circ_0001445 (circRNA1445) in various cell lines. In conclusion, RETA-CRISPR seamlessly integrates the advantages of exponential amplification reaction and the robust collateral cleavage activity of Cas12a, positioning it as a compelling tool for practical CRISPR-based diagnostics.

Starch-mediated colloidal chemistry for highly reversible zinc-based polyiodide redox flow batteries.

Aqueous Zn-I flow batteries utilizing low-cost porous membranes are promising candidates for high-power-density large-scale energy storage. However, capacity loss and low Coulombic efficiency resulting from polyiodide cross-over hinder the grid-level battery performance. Here, we develop colloidal chemistry for iodine-starch catholytes, endowing enlarged-sized active materials by strong chemisorption-induced colloidal aggregation. The size-sieving effect effectively suppresses polyiodide cross-over, enabling the utilization of porous membranes with high ionic conductivity. The developed flow battery achieves a high-power density of 42 mW cm-2 at 37.5 mA cm-2 with a Coulombic efficiency of over 98% and prolonged cycling for 200 cycles at 32.4 Ah L-1posolyte (50% state of charge), even at 50 °C. Furthermore, the scaled-up flow battery module integrating with photovoltaic packs demonstrates practical renewable energy storage capabilities. Cost analysis reveals a 14.3 times reduction in the installed cost due to the applicability of cheap porous membranes, indicating its potential competitiveness for grid energy storage.

E-M349E and NS2A/2B-P1(T) are compensatory mutations of rDTMUV-NS2AB-P1P1'(AA), which regain virus proliferation by enhancing the virus package and restoring NS2A/2B cleavage.

Duck Tembusu virus (DTMUV) belongs to the Flaviviridae family and mainly infects ducks. The genome of DTMUV is translated into a polyprotein, which is further cleaved into several protein by viral NS2B3 protease and host proteases. Crucially, the cleavage of the NS2A/2B precursor during this process is essential for the formation of replication complexes and viral packaging. Previous research has demonstrated that alanine mutations in NS2A/2B (P1P1' (AA)) result in an attenuated strain (rDTMUV-NS2A/2B-P1P1' (AA)) by disrupting NS2A/2B cleavage. In this study, we investigate the effects of the P1P1' (AA) mutation on the viral life cycle and explore compensatory mutations in rDTMUV-NS2A/2B-P1P1' (AA). Infected ducklings exhibit similar body weight gain and viral tissue loads to DTMUV-WT. Compensatory mutations E-M349E and P1(T) emerge, restoring proliferation levels to those of rDTMUV-WT. Specifically, E-M349E enhances viral packaging, while P1(T) reinstates NS2A/2B proteolysis in vitro. Thus, our findings reveal novel compensatory sites capable of restoring the attenuated DTMUV during polyprotein cleavage and packaging.

Analysis of bistatic multiphoton quantum radar cross section for the cylindrical surface.

A closed-form model of bistatic multiphoton quantum radar cross section (QRCS) for the cylindrical surface, the main structure of typical aircraft, especially missiles, is established to analyze the system and scattering characteristics. The influence of curvature of the three-dimensional target on QRCS is analyzed. By comparing and analyzing the bistatic multiphoton QRCS for a cylinder and a rectangular plate, we find that the QRCS for the convex surface target is the extension of the QRCS for the planar target with inhomogeneous atomic arrangement intervals and patterns. The characteristics of cylindrical QRCS are discussed by combining the transceiver system and the photon number of the transmitted signal, and the influences of the cylindrical radius, cylindrical length, and incident photon number on QRCS are analyzed. The bistatic results provide guidance on potential strong scattering directions for the target under various directions of photon incidence. Compared with the plane target, the cylindrical target amplifies scattering intensity near the target surface at the scattering angle side in the bistatic system. A bistatic multiphoton quantum radar system can achieve sharpening and amplification of the main lobe of the QRCS for a cylinder in an extensive scattering angle range. Bistatic multiphoton quantum radar has better visibility for the cylinder with a smaller length. These characteristics will provide prior information for research in many fields, such as photonic technology, radar technology, and precision metrology.

Clinical efficacy of precision liver resection for primary liver cancer.

AIM: Precision liver resection is considered the gold standard in liver surgery. Therefore, optimizing the resection of lesions and minimizing unnecessary time of liver ischemia and hypoxia have become focal points. METHODS: A total of 96 patients with primary liver cancer admitted to Cangzhou People's Hospital from January 2017 and December 2019 were included in this retrospective study, and divided into two groups according to the different surgical treatment, with 50 cases in the control group (conventional hepatic resection) and 46 cases in the observation group (precision liver resection). The surgical indicators, liver function, alpha-fetoprotein (AFP), complications, and three-year follow-up results were analyzed in the two groups. RESULTS: The operation time, intraoperative bleeding, hospital stay, and time of anal venting in the observation group were shorter than those in the control group (P<0.05). One week after surgery, AST, TBiL, ALT, and γ-GT levels decreased in both groups, with more significant decreases in the observation group than those in the control group (P<0.05). PCT and hs-CRP levels in the observation group were significantly lower than those in the control group (P<0.05) observation. The incidences of pleural effusion, bile leak, abdominal infection, pulmonary infection, as well as the total complication rates in the observation group were lower in the observation group than those in the control group (P<0.05). The follow-up data revealed that the observation group exhibited a lower recurrence rate observationand higher survival rate than the control group within 3 years, but these differences were not significant (P>0.05). CONCLUSION: Precision liver resection can effectively treat primary liver cancer, reduce the incidence of complications, and promote patient recovery after surgery.