Biomedical subjects

Peng Liu

Publications and source records attributed to Peng Liu.

8 recordsLinked to original sources

PubMed2026

Opioid-sparing anesthesia based on opioid-free principles for early recovery after total knee arthroplasty: A randomized controlled trial.

OBJECTIVE: To evaluate whether an opioid-sparing anesthesia strategy (OSA), based on opioid-free anesthesia (OFA), improves early postoperative recovery quality and optimizes functional outcomes after total knee arthroplasty (TKA), compared with conventional opioid-based anesthesia (OBA). DESIGN: A randomized controlled trial with blinding of patients, surgeons, and outcome assessors. SETTING: Single center, July 2025 to February 2026. PATIENTS: 98 adult patients scheduled for elective unilateral TKA. INTERVENTION: Patients were randomized to the OSA or OBA group. The OSA regimen used esketamine and dexmedetomidine as the primary analgesic backbone, whereas the OBA regimen was opioid-based. Both groups received preoperative femoral nerve block and were administered oxycodone at skin incision and closure. Postoperatively, both groups received the same multimodal analgesia and patient-controlled analgesia. MEASUREMENTS: The primary outcome was the 24-h postoperative Quality of Recovery-15 (QoR-15) score. Secondary outcomes included 48-h QoR-15; Oxford Knee Score (OKS) and EQ-5D-3L at 1 and 3 months; high pain at 1 month and chronic postsurgical pain at 3 months. Exploratory outcomes included postoperative C-reactive protein (CRP), and postoperative nausea and vomiting (PONV), among others. RESULTS: At 24 h postoperatively, QoR-15 was higher in the OSA group than in the OBA group (118.4 ± 11.5 vs 113.3 ± 12.2; adjusted difference 5.12, 95% CI 0.51-9.74; P = 0.029), and this advantage persisted at 48 h (adjusted difference 5.54, 95% CI 1.57-9.52; P = 0.007). The OSA group had a lower incidence of PONV (P = 0.025) and lower postoperative CRP levels (P = 0.001). At 1 month, OKS was higher in the OSA group (adjusted difference 2.31, 95% CI 0.34-4.27; P = 0.022), with no significant differences in other secondary outcomes. CONCLUSION: In TKA, this OFA-based OSA strategy improved early postoperative QoR-15 scores. However, the QoR-15 difference did not reach the minimal clinically important difference, so its clinical relevance remains uncertain.

Humans↗

PubMed2026

Quantifying the combined effects of semi-closed terrain and monsoon on PM2.5 and O3 pollution aggregation in the North China Plain.

The North China Plain (NCP) and its surrounding regions represent one of the key priority areas for air pollution control. As anthropogenic emissions decline significantly, the effect of terrain and meteorology on air pollution pattern has become increasingly prominent, particularly given the NCP's unique semi-closed terrain and East Asian monsoon dynamics. However, quantitative characterization of terrain-dominated blocking effects remains unexplored. Here we quantitatively assess the blocking effects of mountains and terrain-coupled meteorological factors on air pollutant dispersion. We find the NCP on the eastern side of the Taihang Mountains showed high PM2.5 and O3 pollution levels, with winter PM2.5 and summer O3 high-value zones showing opposite north-south aggregation patterns. PM2.5 and O3 concentrations were highest in plains, followed by platforms, hills, and finally mountains. Within the 120-km buffer zones of the typical mountains in the NCP and its surrounding regions, PM2.5 and O3 concentrations increased initially with altitude but then decreased markedly above a threshold altitude. Above the threshold altitude, mountain blocking effects became dominant. The effective blocking altitudes of typical mountains in the NCP and its surrounding regions ranged between 22 and 929 m for winter PM2.5 pollution, and between 19 and 1060 m for summer O3 pollution. The Terrain-Wind Close Index indicates that the terrain-coupled East Asian monsoon showed stronger blocking effects on PM2.5 dispersion in southern NCP during winter and on O3 diffusion in northern NCP during summer, matching observed high-pollution zones. This study offers key insights for regional joint air pollution mitigation strategies, as well as regional pollution assessment.

Particulate Matter↗

PubMed2025

MPAC: a computational framework for inferring pathway activities from multi-omic data.

MOTIVATION: Fully capturing cellular state requires examining genomic, epigenomic, transcriptomic, proteomic, and other assays for a biological sample and comprehensive computational modeling to reason with the complex and sometimes conflicting measurements. Modeling these so-called multi-omic data is especially beneficial in disease analysis, where observations across omic data types may reveal unexpected patient groupings and inform clinical outcomes and treatments. RESULTS: We present Multi-omic Pathway Analysis of Cells (MPAC), a computational framework that interprets multi-omic data through prior knowledge from biological pathways. MPAC leverages network relationships encoded in pathways through a factor graph to infer consensus activity levels for proteins and associated pathway entities from multi-omic data, runs permutation testing to eliminate spurious activity predictions, and groups biological samples by pathway activities to allow identifying and prioritizing proteins with potential clinical relevance, e.g. associated with patient prognosis. Using DNA copy number alteration and RNA-seq data from head and neck squamous cell carcinoma patients from The Cancer Genome Atlas as an example, we demonstrate that MPAC predicts a patient subgroup related to immune responses not identified by analysis with either input omic data type alone. Key proteins identified via this subgroup have pathway activities related to clinical outcome as well as immune cell composition. Our MPAC R package enables similar multi-omic analyses on new datasets. AVAILABILITY AND IMPLEMENTATION: The MPAC package is available at Bioconductor https://bioconductor.org/packages/MPAC.

Humans↗

PubMed2025

Selection of geographical populations suitable for artificial breeding of the Northeast China Brown Frog (Rana dybowskii).

Amphibians, as a group greatly disturbed by human activities, are at increased risk of extinction. Rana dybowskii is an anuran species with both ecological and economic significance. Due to environmental changes and human overexploitation, it has been classified as Near-Threatened. This study integrates morphological and molecular immunological approaches to identify R. dybowskii populations with greater survival and disease resistance, based on 32 morphological traits and MHC class I and II polymorphism. Morphological results showed that compared with other populations, Yichun (YC) population had the highest fatness, the lowest IOD/HW, and the largest HW/SVL, HL/SVL, HW/HL, SL/TL. It indicates that YC population shows larger body size, wider vision and stronger jumping ability. The polymorphism of MHC I gene was the highest in Shangzhi (SZ) population, and the polymorphism of MHC II gene was the highest in YC population. Moreover, duplication, selection, and recombination occurred during evolution of MHC class I and II genes. Since both SZ and YC populations scored higher in this category (the variant sites, nucleotide polymorphism, amino-acid divergence/nucleotide divergence, dN/dS, Tajima' D, etc.), they were more resistant to disease. All in all, these results indicated that YC population of the Lesser Khingan Mountains had good morphology and immune results, and R. dybowskii in the Lesser Khingan Mountains might be more suitable to be the original population of artificial breeding, which provided a theoretical basis for the realization of artificial breeding in the next step.

Ranidae↗

PubMed2025

Application of engineered CRISPR/Cas12a variants with altered protospacer adjacent motif specificities for the detection of isoniazid resistance mutations in Mycobacterium tuberculosis.

UNLABELLED: Drug-resistant tuberculosis (TB) is a major global public health concern. Although isoniazid is currently considered one of the most effective first-line drugs for TB treatment, its efficacy is limited by the emergence of resistance. Therefore, it is imperative to develop new methods for detecting drug-resistant TB. In this study, we developed a nucleic acid detection system based on the clustered regularly interspaced short palindromic repeat (CRISPR) Cas12a_RR protein. The system combines recombinase polymerase amplification with an engineered CRISPR/Cas12a_RR protein to enable rapid and specific detection of the katG G944C mutation in isoniazid-resistant Mycobacterium tuberculosis (Mtb). It could detect the target DNA at concentrations as low as 1% in a mixed sample. Compared with TaqMan quantitative polymerase chain reaction and DNA sequencing, the CRISPR/Cas12a_RR system demonstrated superior detection performance in terms of sensitivity, specificity, and cost-effectiveness. Furthermore, it effectively differentiated between drug-resistant Mtb strains from wild-type Mtb strains in clinically isolated samples, with the entire detection process completed in 60 min. In conclusion, the CRISPR/Cas12a_RR detection system offers a novel, rapid, simple, sensitive, and specific approach for identifying isoniazid-resistant Mtb, with significant potential for clinical application, particularly in resource-limited settings. IMPORTANCE: This study presents a novel method for detecting isoniazid-resistant Mycobacterium tuberculosis (Mtb) using clustered regularly interspaced short palindromic repeat (CRISPR)/Cas12a mutants, offering rapid detection, cost-effectiveness, and high specificity, and thereby providing a promising new avenue for detecting isoniazid-resistant Mtb.

Isoniazid↗

PubMed2025

MPAC: a computational framework for inferring pathway activities from multi-omic data.

Fully capturing cellular state requires examining genomic, epigenomic, transcriptomic, proteomic, and other assays for a biological sample and comprehensive computational modeling to reason with the complex and sometimes conflicting measurements. Modeling these so-called multi-omic data is especially beneficial in disease analysis, where observations across omic data types may reveal unexpected patient groupings and inform clinical outcomes and treatments. We present Multi-omic Pathway Analysis of Cells (MPAC), a computational framework that interprets multi-omic data through prior knowledge from biological pathways. MPAC leverages network relationships encoded in pathways through a factor graph to infer consensus activity levels for proteins and associated pathway entities from multi-omic data, runs permutation testing to eliminate spurious activity predictions, and groups biological samples by pathway activities to allow identifying and prioritizing proteins with potential clinical relevance, e.g., associated with patient prognosis. Using DNA copy number alteration and RNA-seq data from head and neck squamous cell carcinoma patients from The Cancer Genome Atlas as an example, we demonstrate that MPAC predicts a patient subgroup related to immune responses not identified by analysis with either input omic data type alone. Key proteins identified via this subgroup have pathway activities related to clinical outcome as well as immune cell compositions. Our MPAC R package, available at https://bioconductor.org/packages/MPAC, enables similar multi-omic analyses on new datasets.

Journal Article↗

PubMed2025

N6-methyladenosine modification of the subgroup J avian leukosis viral RNAs attenuates host innate immunity via MDA5 signaling.

Subgroup J avian leukosis virus (ALV-J), a retrovirus, elicits immunosuppression and persistent infections in chickens. Although it is widely acknowledged that ALV-J can evade the host's innate immune defenses, the mechanisms behind this immune evasion remain elusive. N6-methyladenosine (m6A), the most prevalent internal RNA modification, plays a role in innate immune evasion. Our research identified ALV-J as an inefficient stimulator of innate immunity in vitro and in vivo, with its genomic RNA featuring m6A modifications predominantly in the envelope protein (Env) region and 3' untranslated region (3'UTR). To elucidate the functional consequences of m6A modification, we subsequently generated m6A-deficient ALV-J through its culturing in the DF-1 overexpressing fat mass and obesity-associated protein (FTO) cells. The m6A-deficient ALV-J virus, or its RNAs significantly enhanced IFN-β production compared to the wild-type (wt) ALV-J, suggesting a pivotal regulatory function of m6A modifications in modulating innate immune response. Mechanistically, the m6A modification of the ALV-J genomic RNA directly impacted its recognition by MDA5, weakening its binding and ubiquitination and attenuating IFN-β activation. Moreover, m6A-deficient ALV-J, created by inducing mutations in m6A sites within Env and 3'UTR, exhibited reduced replication capacity and elevated IFN-β expression in host cells. Importantly, this phenomenon was abolished in MDA5-knockout DF-1 cells, further demonstrating the core role of MDA5. These data demonstrate that m6A modification of ALV-J genomic RNA dampens the host's innate immune response through MDA5 signaling pathway.

Animals↗

PubMed2024

Metagenome-based diversity and functional analysis of culturable microbes in sugarcane.

UNLABELLED: Sugarcane is a key crop for sugar and energy production, and understanding the diversity of its associated microbes is crucial for optimizing its growth and health. However, there is a lack of thorough investigation and use of microbial resources in sugarcane. This study conducted a comprehensive analysis of culturable microbes and their functional features in different tissues and rhizosphere soil of four diverse sugarcane species using metagenomics techniques. The results revealed significant microbial diversity in sugarcane's tissues and rhizosphere soil, including several important biomarker bacterial taxa identified, which are reported to engage in several processes that support plant growth, such as nitrogen fixation, phosphate solubilization, and the production of plant hormones. The Linear discriminant analysis Effect Size (LEfSe) studies identified unique microbial communities in different parts of the same sugarcane species, particularly Burkholderia, which exhibited significant variations across the sugarcane species. Microbial analysis of carbohydrate-active enzymes (CAZymes) indicated that genes related to sucrose metabolism were mostly present in specific bacterial taxa, including Burkholderia, Pseudomonas, Paraburkholderia, and Chryseobacterium. This study improves understanding of the diversities and functions of endophytes and rhizosphere soil microbes in sugarcane. Moreover, the approaches and findings of this study provide valuable insights for microbiome research and the use of comparable technologies in other agricultural fields. IMPORTANCE: This work utilized metagenomics techniques for conducting a comprehensive examination of culturable microbes and their functional characteristics in various tissues and rhizosphere soil of four distinct sugarcane species. This study enhances comprehension of the diversity and functions of endophytes and rhizosphere soil microbes in sugarcane. Furthermore, the methodologies and discoveries of this work offer new perspectives for microbiome investigation and the use of similar technologies in other agricultural fields.

Saccharum↗