A dataset for fine-grained seed recognition.

The research of plant seeds has always been a focus of agricultural and forestry research, and seed identification is an indispensable part of it. With the continuous application of artificial intelligence technology in the field of agriculture, seed identification through computer vision can effectively promote the development of agricultural and forestry wisdom. Data is the foundation of computer vision, but there is a lack of suitable datasets in the agricultural field. In this paper, a seed dataset named LZUPSD is established. A device based on mobile phones and macro lenses was established to acquire images. The dataset contains 4496 images of 88 different seeds. This dataset can not only be used as data for training deep learning models in the computer field, but also provide important data support for agricultural and forestry research. As an important resource in this field, this dataset plays a positive role in modernizing agriculture and forestry.

T266M variants of ANGPTL4 improve lipid metabolism by modifying their binding affinity to acetyl-CoA carboxylase in obstructive sleep apnea.

BACKGROUND: Angiopoietin-like protein 4 (ANGPTL4) is recognized as a crucial regulator in lipid metabolism. Acetyl-CoA carboxylases (ACACAs) play a role in the ß-oxidation of fatty acids. Yet, the functions of ANGPTL4 and ACACA in dyslipidemia of obstructive sleep apnea (OSA) remain unclear. METHODS: This study included 125 male OSA subjects from the Shanghai Sleep Health Study (SSHS) who were matched for age, body mass index (BMI), and lipid profile. Serum ANGPTL4 levels were measured via ELISA. The ANGPTL4 T266M variants of 4455 subjects along with their anthropometric, fasting biochemical, and standard polysomnographic parameters were collected. Linear regression was used to analyze the associations between quantitative traits and ANGPTL4 T266M. Molecular docking and molecular dynamic simulation were employed to compare the effects of the wild-type ANGPTL4 and its T266M mutation on ACACA. RESULTS: Serum ANGPTL4 levels significantly decreased with increasing OSA severity (non-OSA: 59.6 ± 17.4 ng/mL, mild OSA: 50.0 ± 17.5 ng/mL, moderate OSA: 46.3 ± 15.5 ng/mL, severe OSA: 19.9 ± 14.3 ng/mL, respectively, p = 6.02 × 10-16). No associations were found between T266M and clinical characteristics. Molecular docking indicated that mutant ANGTPL4 T266M had stronger binding affinity for the ACACA protein, compared with wild-type ANGPTL4. In terms of protein secondary structure, mutant ANGTPL4 T266M demonstrated greater stability than wild-type ANGPTL4. CONCLUSIONS: Serum ANGTPL4 levels were significantly decreased in OSA patients, particularly among individuals with severe OSA. Although functional ANGTPL4 T266M variants were not associated with lipid levels in OSA, ANGTPL4 T266M could enhance binding affinity for the ACACA protein, potentially regulating lipid metabolism.

Identification of biomarkers and immune infiltration characterization of lipid metabolism associated genes in osteoarthritis based on machine learning algorithms.

Osteoarthritis (OA) is a prevalent degenerative condition commonly observed in the elderly, leading to consequential disability. Despite notable advancements made in clinical strategies for OA, its pathogenesis remains uncertain. The intricate association between OA and metabolic processes has yet to receive comprehensive exploration. In our investigation, we leveraged public databases and applied machine learning algorithms, including WGCNA, LASSO, RF, immune infiltration analysis, and pathway enrichment analysis, to scrutinize the role of lipid metabolism-associated genes (LAGs) in the OA. Our findings identified three distinct biomarkers, and evaluated their expression to assess their diagnostic value in the OA patients. The exploration of immune infiltration in these patients revealed an intricate relationship between immune cells and the identified biomarkers. In addition, in vitro experiments, including qRT-PCR, Western blot, chondrocyte lipid droplets detection and mitochondrial fatty acid oxidation measurement, further verified abnormal expressions of selected LAGs in OA cartilage and confirmed the correlation between lipid metabolism and OA.

Knowledge, Attitude, and Practice About Antibiotic Use and Antimicrobial Resistance Among Nursing Students in China: A Cross Sectional Study.

Purpose: The knowledge, attitude, and practices (KAP) concerning antibiotics by healthcare students have the potential impact on controlling antibiotic abuse and antimicrobial resistance (AMR) growth. This study aims to evaluate the levels and explore the associated factors with KAP on antibiotic use and AMR in Chinese nursing students. Methods: A cross-sectional survey using a self-administered questionnaire consisting of demographics and selected features and KAP on antibiotic use and AMR was conducted to measure KAP levels among nursing students at various universities in Hubei Province, China. The logistic regression analyses were performed to analyze the potential factors associated with the KAP. Results: The survey eventually included a total of 1959 nursing students. The mean scores for KAP were 57.89 ±26.32, 55.00 ±12.50, and 71.88 ±15.63, respectively. Regarding knowledge, 54.3% of participants were unaware that antibiotic was ineffective against viral infections. Regarding attitude, 36% of participants agreed that current antibiotic abuse existed; 96.2% of participants thought it necessary to set up a special course on antibiotics. Regarding practice, only 48.4% of participants usually purchased antibiotics with a prescription. Multivariable analyses indicated that lack of discussion on AMR in school courses was an independent risk factor against KAP, respectively. The main knowledge sources of antibiotic being outside the classroom was an independent risk factor related to knowledge and practice. The average score >80 points was an independent protective factor related to knowledge and practice. Conclusion: The KAP level on antibiotic use and AMR among Hubei nursing students was general and required further strengthening. Nursing students with risk factors should be prioritized in educational interventions. The findings of our study pointed out some directions for tailored interventions to improve the training on antibiotics.

The influence of anterior cervical discectomy and fusion surgery on cervical muscles and the correlation between related muscle changes and surgical efficacy.

BACKGROUND: Anterior cervical discectomy and fusion surgery (ACDF) is a common technique in treating degenerative cervical spondylosis. This study is to evaluate the changes of cervical muscles after ACDF and analyze the correlation between related muscle changes and clinical efficacy. METHODS: Sixty-five postoperative patients (single-level ACDF) with cervical spondylotic myelopathy from January 2013 to December 2022 were analyzed. The measured parameters include: the axial section of longus colli cross-sectional area (AxCSA), the volume of cervical longus, the ratio of long and short diameter line (RLS), the cervical extensor cross-sectional area (CESA), the vertebral body area (VBA), and the CESA/VBA. The visual analog scale (VAS), modified Japanese Orthopedic Association score (mJOA), and neck disability index (NDI) were evaluated. The changes in muscle morphology were analyzed, and the correlation analysis was conducted between morphological changes and function scores. RESULTS: The postoperative AxCSA of surgical segment (3rd month, 12th month, and the last follow-up) was decreased compared to preoperative (141.62 ± 19.78), and the differences were significant (P < 0.05). The corresponding data reduced to (119.42 ± 20.08) mm2, (117.59 ± 19.69) mm2, and (117.41 ± 19.19) mm2, respectively (P < 0.05). The RLS increased, and the volume of cervical longus decreased significantly after surgery (P < 0.05). Negative correlation was found between postoperative volume of cervical longus and VAS at the 3rd month (r = - 0.412), 12th month (r = - 0.272), and last follow-up (r = - 0.391) (P < 0.05). Negative correlation existed between postoperative volume of cervical longus and NDI at the 3rd month (r = - 0.552), 12th month (r = - 0.293), and last follow-up (r = - 0.459) (P < 0.05). CONCLUSION: The volume of cervical longus decreased and its morphology changed after ACDF surgery. The mainly affected muscle was the cervical longus closing to the surgical segment. Negative correlation was found between the postoperative volume of cervical longus and function scores (VAS and NDI).

Characterization of tumor evolution by functional clonality and phylogenetics in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a molecularly heterogeneous solid malignancy, and its fitness may be shaped by how its tumor cells evolve. However, ability to monitor tumor cell evolution is hampered by the presence of numerous passenger mutations that do not provide any biological consequences. Here we develop a strategy to determine the tumor clonality of three independent HCC cohorts of 524 patients with diverse etiologies and race/ethnicity by utilizing somatic mutations in cancer driver genes. We identify two main types of tumor evolution, i.e., linear, and non-linear models where non-linear type could be further divided into classes, which we call shallow branching and deep branching. We find that linear evolving HCC is less aggressive than other types. GTF2IRD2B mutations are enriched in HCC with linear evolution, while TP53 mutations are the most frequent genetic alterations in HCC with non-linear models. Furthermore, we observe significant B cell enrichment in linear trees compared to non-linear trees suggesting the need for further research to uncover potential variations in immune cell types within genomically determined phylogeny types. These results hint at the possibility that tumor cells and their microenvironment may collectively influence the tumor evolution process.

Associations between maternal serum neonicotinoid pesticide exposure during pregnancy and newborn telomere length: Effect modification by sampling season.

BACKGROUND: An increasing amount of evidence suggests that telomere length (TL) at birth can predict lifespan and is associated with chronic diseases later in life, but newborn TL may be affected by environmental pollutants. Neonicotinoids (NEOs) are widely used worldwide, and despite an increasing number of studies showing that they may have adverse effects on birth in mammals and even humans, few studies have examined the effect of NEO exposure on newborn TLs. OBJECTIVE: To investigate the effects of prenatal exposure to NEOs and the interactions between NEOs and sampling season on newborn TL. METHODS: We conducted a prospective cohort study of 500 mother-newborn pairs from the Guangxi Zhuang Birth Cohort. Ultraperformance liquid chromatographymass spectrometry was used to detect ten NEOs in maternal serum, and fluorescence quantitative PCR was used to estimate the newborn TL. A generalized linear model (GLM) was used to evaluate the relationships between individual NEO exposures and TLs , and quantile g-computation (Qgcomp) model and Bayesian kernel machine regression (BKMR) model were used to evaluate the combined effect of mixtures of components. RESULTS: The results of the GLM showed that compared with maternal TMX levels < LOD, maternal TMX levels < median were negatively correlated with newborn TL (-6.93%, 95% CI%: -11.92%, -1.66%), and the decrease in newborn TL was more pronounced in girls (-9.60%, 95% CI: -16.84%, -1.72%). Moreover, different kinds of maternal NEO exposure had different effects on newborn TL in different sampling seasons, and the effect was statistically significant in all seasons except in autumn. Mixed exposure analysis revealed a potential positive trend between NEOs and newborn TL, but the association was not statistically significant. CONCLUSION: Prenatal exposure to TMX may shorten newborn TL, and this effect is more pronounced among female newborns. Furthermore, the relationship between NEO exposure and TL may be modified by the sampling season.

Genetic Parameters and Genetic Trends for Johne's Disease in U.S. Holsteins: An Updated Study.

Johne's disease (JD) is an infectious enteric disease in ruminants, causing substantial economic loss annually worldwide. This work aimed to estimate JD's genetic parameters and the phenotypic and genetic trends by incorporating recent data. It also explores the feasibility of a national genetic evaluation for JD susceptibility in Holstein cattle in the United States (US). The data were extracted from a Johne's disease data repository, maintained at the Council on Dairy Cattle Breeding (CDCB), and initially supplied by 2 dairy records processing centers. The data comprised 365,980 Holstein cows from 1,048 herds participating in a voluntary control program for JD. Two protocol kits, Idexx Paratuberculosis Screening Ab Test (IDX) and Parachek® 2 (PCK), were used to analyze milk samples with the Enzyme-Linked Immunosorbent Assay (ELISA) technique. Test results from the first 5 parities were considered. An animal was considered infected if it had at least one positive outcome. The overall average of JD incidence was 4.72% in these US Holstein cattle. Genotypes of 78,964 SNP markers were used for 25,000 animals randomly selected from the phenotyped population. Variance components and genetic parameters were estimated based on 3 models, namely, a pedigree-only threshold model (THR), a single-step threshold model (ssTHR), and a single-step linear model (ssLR). The posterior heritability estimates of JD susceptibility were low to moderate: 0.11 to 0.16 based on the 2 threshold models and 0.05 to 0.09 based on the linear model. The average reliability of estimated breeding values of JD susceptibility using single-step analysis for animals with or without phenotypes varied from 0.18 (THR) to 0.22 (ssLR) for IDX and from 0.14 (THR) to 0.18 (ssTHR and ssLR) for PCK. Despite no prior direct genetic selection against JD, the estimated genetic trends of JD susceptibility were negative and highly significant (P-value <0.01). The correlations of bulls' predicted transmitting abilities with economically important traits such as milk yield, milk protein, milk fat, somatic cell score, and mastitis were low, indicating a non-overlapping genetic selection process with traits in current genetic evaluations. Our results suggest the feasibility of reducing the JD incidence rate by incorporating it into the national genetic evaluation programs.

Maize multi-omics reveal leaf water status controlling of differential transcriptomes, proteomes and hormones as mechanisms of age-dependent osmotic stress response in leaves.

Drought-induced osmotic stress severely affects the growth and yield of maize. However, the mechanisms underlying the different responses of young and old maize leaves to osmotic stress remain unclear. To gain a systematic understanding of age-related stress responses, we compared osmotic-stress-induced changes in maize leaves of different ages using multi-omics approaches. After short-term osmotic stress, old leaves suffered more severe water deficits than young leaves. The adjustments of transcriptomes, proteomes, and hormones in response to osmotic stress were more dynamic in old leaves. Metabolic activities, stress signaling pathways, and hormones (especially abscisic acid) responded to osmotic stress in an age-dependent manner. We identified multiple functional clusters of genes and proteins with potential roles in stress adaptation. Old leaves significantly accumulated stress proteins such as dehydrin, aquaporin, and chaperones to cope with osmotic stress, accompanied by senescence-like cellular events, whereas young leaves exhibited an effective water conservation strategy mainly by hydrolyzing transitory starch and increasing proline production. The stress responses of individual leaves are primarily determined by their intracellular water status, resulting in differential transcriptomes, proteomes, and hormones. This study extends our understanding of the mechanisms underlying plant responses to osmotic stress.

Sulfurized polyacrylonitrile as cathodes for advanced lithium-sulfur batteries: advances in modification strategies.

Sulfurized polyacrylonitrile (S@PAN) composites have gathered a lot of interest because of their advantages of high theoretical energy density, excellent cycling stability, and environmental friendliness. Meanwhile, their unique "covalent bonding" mechanism effectively avoids the dissolution and shuttling of polysulfides, and thus they are expected to be the most promising candidate for the cathode material in lithium-sulfur (Li-S) batteries. Over the past five years, S@PAN cathode materials have been widely studied in Li-S batteries, and it is very important to summarize the advances over time for their practical applications. This article reviews the latest progress concerning the modification of S@PAN cathode materials for improving poor electrical conductivity, low sulfur content, and sluggish reaction kinetics, and proposes possible research directions. We hope this review provides valuable insights and references for future research on Li-S batteries.

Unilateral biportal endoscopic lumbar interbody fusion (ULIF) versus endoscopic transforaminal lumbar interbody fusion (Endo-TLIF) in the treatment of lumbar spinal stenosis along with intervertebral disc herniation: a retrospective analysis.

OBJECTIVE: This study aims to compare the clinical effects and imaging data of patients who underwent endoscopic transforaminal lumbar interbody fusion (Endo-TLIF) with those who received unilateral biportal endoscopic lumbar interbody fusion (ULIF). METHODS: A retrospective analysis was conducted on the clinical data of 69 patients presenting with typical intermittent claudication and signs and symptoms indicative of unilateral lower extremity nerve root compression, meeting inclusion criteria between April 2022 and June 2022. Among the cohort, 35 patients underwent ULIF group, while 34 patients underwent Endo-TLIF group. We compared perioperative parameters, including intraoperative blood loss, duration of hospital stay, and operation time between the two groups. Pre-operative and post-operative changes in the height and cross-sectional area of the target intervertebral space were also compared between the groups. Finally, we evaluated bone graft size and interbody fusion rates at 6 and 12 months post-surgery using the Brantigan scoring system. RESULTS: The ULIF group had significantly shorter operative times compared to the Endo-TLIF group (P < 0.05). Conversely, the Endo-TLIF group exhibited significantly shorter hospital stays compared to the ULIF group (P < 0.05). However, there were no significant differences in intraoperative bleeding between the two groups (P > 0.05). Furthermore, both groups exhibited postoperative increases in vertebral canal volume compared to baseline (P < 0.05), with no significant difference in the change in the cross-sectional area of the target intervertebral space between the two surgical methods (P > 0.05). Interbody fusion rates were comparable between the two groups at both 6 and 12 months after surgery (P > 0.05). Lastly, the ULIF group had a significantly larger area of bone graft than the Endo-TLIF group (P < 0.05). CONCLUSION: In summary, the ULIF technique, as a novel spinal endoscopy approach, is a safer and more effective minimally invasive surgical method for addressing lumbar spinal stenosis and intervertebral disc herniation in patients. Both surgical methods have their own advantages and drawbacks. With the development of technology and related instruments, the limitations of both techniques can be mitigated for to a certain extent, and they can be applied by more doctors in diverse medical fields in the future.

Jiawei Kongsheng Zhenzhong Pill: marker compounds, absorption into the serum (rat), and Q-markers identified by UPLC-Q-TOF-MS/MS.

Background: The Jiawei Kongsheng Zhenzhong pill (JKZP), a Chinese herbal prescription comprised of eight Chinese crude drugs, has been historically employed to treat neurological and psychological disorders. Nevertheless, the ambiguous material basis severely hindered its progress and application. Purpose: The current study aimed to establish a rapid analytical method for identifying the chemical components of the JKZP aqueous extract and the components absorbed into the rat serum to investigate the quality markers (Q-markers) responsible for the neuroprotective effects of JKZP. Methods: The qualitative detection of the chemical components, prototype components, and metabolites of the aqueous extracts of JKZP, as well as the serum samples of rats that were administered the drug, was performed using the ultra-performance liquid chromatography- quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS) technology. This analysis combined information from literature reports and database comparisons. Moreover, the study was conducted to anticipate the potential Q-markers for the neuroprotective effects of JKZP based on the "five principles" of Q-marker determination. Results: A total of 67 compounds and 111 serum components (comprising 33 prototypes and 78 metabolites) were detected and identified. Combining the principles of quality transmission and traceability, compound compatibility environment, component specificity, effectiveness, and measurability, the study predicted that five key compounds, namely, senkyunolide H, danshensu, echinacoside, loganin, and 3,6'-disinapoyl sucrose, may serve as potential pharmacological bases for the neuroprotective effects of JKZP. Conclusion: To summarize, the UPLC-Q-TOF-MS/MS technique can be employed to rapidly and accurately identify compounds in JKZP. Five active compounds have been predicted to be the Q-markers for the neuroprotective effects of JKZP. This discovery serves as a reference for improving quality, advancing further research and development, and utilizing Chinese herbal prescriptions.

Effect of short-term exposure to air pollution on hospital admission for cardiovascular disease: A time-series study in Xiangyang, China.

BACKGROUND: Data on the relationship between short-term exposure to air pollution and cardiovascular diseases (CVDs) and the potential modifying factors are limited and inconsistent. OBJECTIVE: To explore the relationship between short-term exposure to air pollution and CVD risk, and potential modification effect factors. METHOD: A time series study was conducted on 52,991 hospital admissions for CVD from 2015 to 2019 in Xiangyang City, China. Air pollution data from four national fixed monitoring stations were collected to estimate exposure level in Xiangyang City. A quasi-Poisson generalized additive model incorporating a distributed lag nonlinear model was applied to evaluate the association between air pollution and CVD risk. The potential modification effect of sex, age, and season on the above associations was also evaluated. RESULTS: CVD risk was positively associated with air pollution. Peak associations in single lag day structures were observed for particulate matter ≤10 µm in aerodynamic (PM10; RR: 1.040, 95 % CI: 0.996-1.087), PM2.5 (1.025, 1.004-1.045), nitrogen dioxide (NO2; 1.074, 1.039-1.111), and sulfur dioxide (SO2; 1.079, 1.019-1.141) at Lag 0 and ozone (O3; 1.018, 1.004-1.031) at Lag 4. In cumulative lag day structures, the highest RRs were 1.225 (1.079,1.392) for PM10 at Lag 06, 1.054 (1.013, 1.098) for PM2.5 at Lag 03, 1.200 (1.119, 1.287) for NO2 at Lag 04, and 1.135 (1.025, 1.257) for SO2 at Lag 02. Moreover, the association between air pollution and CVD risk was modified by sex and age (P < 0.05). Females and individuals aged ≤65 years were more vulnerable to NO2 and had a higher CVD risk. CONCLUSION: Short-term exposure to air pollution was positively associated with CVD risk. Moreover, sex and age could modify the effect of air pollution on CVD risk. Females and individuals aged ≤65 years had a higher NO2 exposure-induced CVD risk.

Deep Lossy Plus Residual Coding for Lossless and Near-Lossless Image Compression.

Lossless and near-lossless image compression is of paramount importance to professional users in many technical fields, such as medicine, remote sensing, precision engineering and scientific research. But despite rapidly growing research interests in learning-based image compression, no published method offers both lossless and near-lossless modes. In this paper, we propose a unified and powerful deep lossy plus residual (DLPR) coding framework for both lossless and near-lossless image compression. In the lossless mode, the DLPR coding system first performs lossy compression and then lossless coding of residuals. We solve the joint lossy and residual compression problem in the approach of VAEs, and add autoregressive context modeling of the residuals to enhance lossless compression performance. In the near-lossless mode, we quantize the original residuals to satisfy a given ℓ∞ error bound, and propose a scalable near-lossless compression scheme that works for variable ℓ∞ bounds instead of training multiple networks. To expedite the DLPR coding, we increase the degree of algorithm parallelization by a novel design of coding context, and accelerate the entropy coding with adaptive residual interval. Experimental results demonstrate that the DLPR coding system achieves both the state-of-the-art lossless and near-lossless image compression performance with competitive coding speed.

Identification of CD8+ T cell-related biomarkers and immune infiltration characteristic of rheumatoid arthritis.

Rheumatoid arthritis (RA) is an autoimmune rheumatic disease, which do not respond well to current treatment partially. Therefore, further in-depth elucidation of the molecular mechanism and pathogenesis of RA is urgently needed for the diagnosis, personalized therapy and drug development. Herein, we collected 111 RA samples from Gene Expression Omnibus (GEO) database, and conducted differentially expressed genes and GESA analysis. Abnormal activation and imbalance of immune cells in RA were observed. WGCNA was utilized to explore the gene modules and CD8+ T cell-related genes (CRGs) were chosen for KEGG and GO analysis. Besides, to explore biomarkers of RA in depth, machine learning algorithms and bioinformatics analysis were used, and we identified GDF15, IGLC1, and IGHM as diagnostic markers of RA, which was confirmed by clinical samples. Next, ssGSEA algorithms were adopted to investigate the differences in immune infiltration of 23 immune cell subsets between RA and healthy control group. Finally, optimal classification analysis based on consensus clustering combined with ssGSEA algorithms were conducted. GDF15 was revealed that to be positively correlated with mast cells and type 2 T helper cells, but negatively correlated with most other immune cells. On the other hand, IGHM and IGLC1 were negatively correlated with CD56dim natural killer cells, while positively associated with other immune cells. Finally, RA samples in subtype A exhibited a higher immune infiltration status. This study could provide guidance for individualized treatment of RA patients and provide new targets for drug design.

Exploration the mechanism of Shenling Baizhu San in the treatment of chronic obstructive pulmonary disease based on UPLC-Q-TOF-MS/MS, network pharmacology and in vitro experimental verification.

ETHNOPHARMACOLOGICAL RELEVANCE: Shenling Baizhu San (SLBZS) is a formula of traditional Chinese medicine (TCM) that enhances the functions of the qi, spleen, and lung. According to the theory of TCM, chronic obstructive pulmonary disease (COPD) is often caused by lung qi deficiency, and SLBZS is often used in the treatment of COPD and has achieved remarkable results. However, the active components of SLBZS absorbed in serum and the underlying mechanism of SLBZS in treating COPD remain unclear and require further studies. AIM OF THE STUDY: The objective of this study is to investigate the active components of SLBZS in rat serum, as well as the crucial targets and signaling pathways involved in the therapeutic effects of SLBZS for COPD. MATERIALS AND METHODS: First, the absorption components and metabolites of SLBZS in rat serum were identified using ultra-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS). Second, potential targets of SLBZS for the treatment of COPD were acquired from publicly accessible online sources. Cytoscape (v3.7.0) software was used to construct a component-target-pathway network and a protein-protein interaction (PPI) network. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of potential targets was performed using the Metascape database. The binding status of the active components in SLBZS to the potential targets was assessed with molecular docking technology. Finally, a cell model of COPD was successfully developed for experimental validation In vitro. RESULTS: A total of 108 active components were identified, including 30 prototype components and 78 metabolites. A total of 292 potential targets for the treatment of COPD were identified, including TNF, IL-6, TLR9, RELA, and others. The KEGG pathway included inflammatory mediator regulation of TRP channels, necroptosis, and the NF-κB signaling pathway, among others. The In vitro experiments showed that SLBZS-containing serum had the ability to decrease the levels of inflammatory factors and cell death. Additionally, it was observed that SLBZS-containing serum could control the expression levels of TLR9, MyD88, TRAF6, NF-κB, and IκBα at the mRNA and protein levels. These findings suggested that SLBZS-containing serum was likely to be involved in the regulation of the TLR9/NF-κB pathway. CONCLUSIONS: The mechanism of action of SLBZS on COPD was preliminarily elucidated using UPLC-Q-TOF-MS/MS, network pharmacology, and In vitro experiments. The primary active components and potential targets of SLBZS were identified, providing a scientific foundation for further research.

Thermodynamic, electronic, and optical properties of ultra-wide bandgap zirconium-doped tin dioxide from a DFT perspective.

The effects of zirconium doping on the thermodynamic, electronic, and optical properties of tin dioxide are investigated by using density functional theory calculations combined with the cluster expansion method. In the whole composition range, the formation enthalpies of all structures are positive, indicating that SnO2-ZrO2 is an immiscible system and the ZrSnO2 alloy has a tendency of phase separation at low temperature. The x-T phase diagram of ZrSnO2 ternary alloy shows that the critical temperature is 979 K, which means that when the growth temperature of ZrSnO2 crystal is higher than the critical temperature, it is possible to realize the full-component solid solution. The bandgaps of ZrxSn1-xO2 alloys (0 ≤ x ≤ 1) are direct and increase as the Zr composition increases. Zr doping can tune the bandgap of SnO2 from the ultraviolet-B region to the deep ultraviolet region, and has a strong optical response to deep ultraviolet light. The projected density of states and band offsets clearly reveal the reason for the increase of bandgap, which provides useful information to design relevant optoelectronic devices such as quantum wells and solar-blind deep ultraviolet photodetectors.

µMET: A Novel Reusable Microfluidic Chip for Precision Microbial Enumeration Tests.

This work describes µMET, a novel microfluidic device for precise microbial enumeration tests (MET), essential in pharmaceutical, cosmetic, and food industries for ensuring microbiological safety standards. The µMET chip, comprising two hydrophobic glass plates, features a 15-µm deep µMET chamber enhanced by nanopillars and air supply units, facilitating both immediate and growth-dependent MET. Experimental results, with E. coli as a model bacterium, demonstrate that µMET provides counting linearity that outperforms traditional hemocytometers. The chip's design mitigates challenges like evaporation and ensures high-resolution imaging, making it a cost-effective and reusable alternative to conventional methods. Notably, bright-field µMET eliminates the need for fluorescent staining, streamlining operations with deep-learning algorithms for bacterial counts. Furthermore, we have developed a high-parallel µMET chip featuring 16 counting chambers, enhancing throughput and accommodating immediate and growth-dependent MET approaches. Its innovative design and adaptability render the µMET chip as a valuable tool for microbiology, medicine, and industry applications.

The translational potential of miR-26 in atherosclerosis and development of agents for its target genes ACC1/2, COL1A1, CPT1A, FBP1, DGAT2, and SMAD7.

Atherosclerosis is one of the leading causes of death worldwide. miR-26 is a potential biomarker of atherosclerosis. Standardized diagnostic tests for miR-26 (MIR26-DX) have been developed, but the fastest progress has been in predicting the efficacy of IFN-α therapy for hepatocellular carcinoma (HCC, phase 3). MiR-26 slows atherosclerosis development by suppressing ACC1/2, ACLY, ACSL3/4, ALDH3A2, ALPL, BMP2, CD36, COL1A1, CPT1A, CTGF, DGAT2, EHHADH, FAS, FBP1, GATA4, GSK3ß, G6PC, Gys2, HMGA1, HMGB1, LDLR, LIPC, IL-1ß, IL-6, JAG2, KCNJ2, MALT1, ß-MHC, NF-κB, PCK1, PLCß1, PYGL, RUNX2, SCD1, SMAD1/4/5/7, SREBF1, TAB3, TAK1, TCF7L2, and TNF-α expression. Many agents targeting these genes, such as the ACC1/2 inhibitors GS-0976, PF-05221304, and MK-4074; the DGAT2 inhibitors IONIS-DGAT2Rx, PF-06427878, PF-0685571, and PF-07202954; the COL1A1 inhibitor HT-100; the stimulants 68Ga-CBP8 and RCT-01; the CPT1A inhibitors etomoxir, perhexiline, and teglicar; the FBP1 inhibitors CS-917 and MB07803; and the SMAD7 inhibitor mongersen, have been investigated in clinical trials. Interestingly, miR-26 better reduced intima-media thickness (IMT) than PCSK9 or CT-1 knockout. Many PCSK9 inhibitors, including alirocumab, evolocumab, inclisiran, AZD8233, Civi-007, MK-0616, and LIB003, have been investigated in clinical trials. Recombinant CT-1 was also investigated in clinical trials. Therefore, miR-26 is a promising target for agent development. miR-26 promotes foam cell formation by reducing ABCA1 and ARL4C expression. Multiple materials can be used to deliver miR-26, but it is unclear which material is most suitable for mass production and clinical applications. This review focuses on the potential use of miR-26 in treating atherosclerosis to support the development of agents targeting it.

Development of macrophage-associated genes prognostic signature predicts clinical outcome and immune infiltration for sepsis.

Sepsis is a major global health problem, causing a significant burden of disease and death worldwide. Risk stratification of sepsis patients, identification of severe patients and timely initiation of treatment can effectively improve the prognosis of sepsis patients. We procured gene expression datasets for sepsis (GSE54514, GSE65682, GSE95233) from the Gene Expression Omnibus and performed normalization to mitigate batch effects. Subsequently, we applied weighted gene co-expression network analysis to categorize genes into modules that exhibit correlation with macrophage activity. To pinpoint macrophage-associated genes (MAAGs), we executed differential expression analysis and single sample gene set enrichment analysis. We then established a prognostic model derived from four MAAGs that were significantly differentially expressed. Functional enrichment analysis and immune infiltration assessments were instrumental in deciphering the biological mechanisms involved. Furthermore, we employed principal component analysis and conducted survival outcome analyses to delineate molecular subgroups within sepsis. Four novel MAAGs-CD160, CX3CR1, DENND2D, and FAM43A-were validated and used to create a prognostic model. Subgroup classification revealed distinct molecular profiles and a correlation with 28-day survival outcomes. The MAAGs risk score was developed through univariate Cox, LASSO, and multivariate Cox analyses to predict patient prognosis. Validation of the risk score upheld its prognostic significance. Functional enrichment implicated ribonucleoprotein complex biogenesis, mitochondrial matrix, and transcription coregulator activity in sepsis, with an immune infiltration analysis indicating an association between MAAGs risk score and immune cell populations. The four MAAGs exhibited strong diagnostic capabilities for sepsis. The research successfully developed a MAAG-based prognostic model for sepsis, demonstrating that such genes can significantly stratify risk and reflect immune status. Although in-depth mechanistic studies are needed, these findings propose novel targets for therapy and provide a foundation for future precise clinical sepsis management.