The clinical significance of sarcopenia in patients with hepatocellular carcinoma treated with lenvatinib and PD-1 inhibitors.

Background and aim: Sarcopenia has gained considerable attention in the context of hepatocellular carcinoma, as it has been correlated with a poorer prognosis among patients undergoing sorafenib or lenvatinib treatment for hepatocellular carcinoma (HCC). The clinical significance of sarcopenia in first-line advanced HCC patients treated with lenvatinib and programmed death-1 (PD-1) inhibitors needs to be clarified. Methods: Sarcopenia was diagnosed using CT (Computed tomography) or MRI (Magnetic Resonance Imaging), with the psoas muscle index (PMI) as the surrogate marker. Patients were grouped based on sarcopenia presences, and a comparative analysis examined characteristics, adverse events, and prognosis. The Cox regression analysis was applied to identify independent prognostic factors for survival, while nomograms were constructed to predict 1-year survival. Results: Among 180 patients, 46 had sarcopenia. Patients with baseline sarcopenia demonstrated significantly inferior median progression-free survival (mPFS) (3.0 vs. 8.3 months) and median overall survival (mOS) (7.3 vs. 21.6 months). The same results for mPFS (3.3 vs. 9.2 months) and mOS (9.4 vs. 24.2 months) were observed in patients who developed sarcopenia after treatment. Furthermore, significantly higher grade 3 or higher adverse events (AEs) (73.91% vs 41.79%, p<0.001) were recorded in the sarcopenia group compared to the non-sarcopenia group. In the multivariate analysis, distant metastasis, elevated PLR and CRP levels, and low PMI remained independent predictive factors for poor OS. Additionally, skeletal muscle loss remained a significant independent risk factor for PFS. We developed a nomogram incorporating these four indicators, which predicted 12-month survival with a C-index of 0.853 (95% CI, 0.791 - 0.915), aligning well with actual observations. Conclusion: The prognosis of patients with HCC and sarcopenia is significantly worse when treated with lenvatinib and PD-1 inhibitors. The combination regimen of lenvatinib plus PD-1 inhibitors should be cautiously recommended due to the inferior prognosis and higher AEs.

Correlation analysis between HLA-DQA1*0102/DQB1*0602 genotypes and narcolepsy patients in China.

Background and objective: At present, the etiology of narcolepsy is not fully understood, and it is generally believed to be an autoimmune reaction caused by interactions between environmental and genetic factors. Human leukocyte antigen (HLA) class II genes are strongly associated with this gene, especially HLA-DQB1*0602/DQA1*0102. In this study, we mainly analyzed the correlation between different genotypes of HLA-DQB1*0602/DQA1*0102 and clinical manifestations in Chinese patients with narcolepsy. Experimental method: Narcolepsy patients who were treated at the Department of Neurology, The First Affiliated Hospital of Shandong First Medical University from January 2021 to September 2023 were selected. General information, sleep monitoring data, cerebrospinal fluid (CSF) orexin levels, and human leukocyte antigen gene typing data were collected. The statistical analysis was performed using SPSS 26.0, and the graphs were drawn using GraphPad Prism 9.5. Main results: A total of 78 patients were included in this study. The DQA1 and DQB1 gene loci were detected in 54 patients, and only the DQB1 gene locus was detected in 24 narcoleptic patients. The most common allele at the HLA-DQB1 locus was *0602 (89.7%), and the most common genotype at this locus was *0602*0301 (19.2%), followed by *0602*0602 (17.9%). The most common phenotype of the HLA-DQA1 locus is *0102 (92.6%), and the most common genotype of this locus is *0102*0102 (27.8%), followed by *0102*0505 (14.8%). There were significant differences (p < 0.05) between HLA-DQB1*0602-positive and HLA-DQB1*0602-negative patients in terms of orexin-A levels, presence or absence of cataplexy, UNS, PSG sleep latency, REM sleep latency, N1 sleep percentage, oxygen depletion index, and average REM latency on the MSLT. The HLA-DQA1*0102-positive and HLA-DQA1*0102-negative patients showed significant differences (p < 0.05) in disease course, presence or absence of sudden onset, PSG REM sleep latency, N1 sleep percentage, and average REM latency on the MSLT. There were significant differences in the average REM latency of the MSLT between HLA-DQB1*0602/DQA1*0102 homozygous and heterozygous patients p < 0.05, and no differences were found in the baseline data, orexin-A levels, scale scores, or other sleep parameters. Conclusion: Different genotypes of HLA-DQA1*0102/DQB1*0602 are associated with symptoms of cataplexy in Chinese narcoleptic patients. Homozygous individuals have a shorter mean REM latency in the MSLT, greater genetic susceptibility, and relatively more severe sleepiness.

Improved object detection method for unmanned driving based on Transformers.

The object detection method serves as the core technology within the unmanned driving perception module, extensively employed for detecting vehicles, pedestrians, traffic signs, and various objects. However, existing object detection methods still encounter three challenges in intricate unmanned driving scenarios: unsatisfactory performance in multi-scale object detection, inadequate accuracy in detecting small objects, and occurrences of false positives and missed detections in densely occluded environments. Therefore, this study proposes an improved object detection method for unmanned driving, leveraging Transformer architecture to address these challenges. First, a multi-scale Transformer feature extraction method integrated with channel attention is used to enhance the network's capability in extracting features across different scales. Second, a training method incorporating Query Denoising with Gaussian decay was employed to enhance the network's proficiency in learning representations of small objects. Third, a hybrid matching method combining Optimal Transport and Hungarian algorithms was used to facilitate the matching process between predicted and actual values, thereby enriching the network with more informative positive sample features. Experimental evaluations conducted on datasets including KITTI demonstrate that the proposed method achieves 3% higher mean Average Precision (mAP) than that of the existing methodologies.

Effects of joint screening for prostate, lung, colorectal, and ovarian cancer - results from a controlled trial.

Background: Although screening is widely used to reduce cancer burden, untargeted cancers are frequently missed after single cancer screening. Joint cancer screening is presumed as a more effective strategy to reduce overall cancer burden. Methods: Gender-specific screening effects on PLCO cancer incidence, PLCO cancer mortality, all-neoplasms mortality and all-cause mortality were evaluated, and meta-analyses based on gender-specific screening effects were conducted to achieve the pooled effects. The cut-off value of time-dependent receiver-operating-characteristic curve of 10-year combined PLCO cancer risk was used to reclassify participants into low- and high-risk subgroups. Further analyses were conducted to investigate screening effects stratified by risk groups and screening compliance. Results: After a median follow-up of 10.48 years for incidence and 16.85 years for mortality, a total of 5,506 PLCO cancer cases, 1,845 PLCO cancer deaths, 3,970 all-neoplasms deaths, and 14,221 all-cause deaths were documented in the screening arm, while 6,261, 2,417, 5,091, and 18,516 outcome-specific events in the control arm. Joint cancer screening did not significantly reduce PLCO cancer incidence, but significantly reduced male-specific PLCO cancer mortality (hazard ratio and 95% confidence intervals [HR(95%CIs)]: 0.88(0.82, 0.95)) and pooled mortality [0.89(0.84, 0.95)]. More importantly, joint cancer screening significantly reduced both gender-specific all-neoplasm mortality [0.91(0.86, 0.96) for males, 0.91(0.85, 0.98) for females, and 0.91(0.87, 0.95) for meta-analyses] and all-cause mortality [0.90(0.88, 0.93) for male, 0.88(0.85, 0.92) for female, and 0.89(0.87, 0.91) for meta-analyses]. Further analyses showed decreased risks of all-neoplasm mortality was observed with good compliance [0.72(0.67, 0.77) for male and 0.72(0.65, 0.80) for female] and increased risks with poor compliance [1.61(1.40, 1.85) for male and 1.30(1.13, 1.40) for female]. Conclusion: Joint cancer screening could be recommended as a potentially strategy to reduce the overall cancer burden. More compliance, more benefits. However, organizing a joint cancer screening not only requires more ingenious design, but also needs more attentions to the potential harms. Trial registration: NCT00002540 (Prostate), NCT01696968 (Lung), NCT01696981 (Colorectal), NCT01696994 (Ovarian).

Upconversion-based hydrogel kit with Python-assisted analysis platform for sample-to-result detection of organophosphorus pesticide.

On-site quantitative analysis of pesticide residues is crucial for monitoring environmental quality and ensuring food safety. Herein, we have developed a reliable hydrogel portable kit using NaYbF4@NaYF4: Yb, Tm upconversion nanoparticles (UCNPs) combined with MnO2 nanoflakes. This portable kit is integrated with a smartphone reader and Python-assisted analysis platform to enable sample-to-result analysis for chlorpyrifos. The novel UCNPs maximizes energy donation to MnO2 acceptor by employing 100 % of activator Yb3+ in the nucleus for NIR excitation energy collection and confining emitter Tm3+ to the surface layer to shorten energy transfer distance. Under NIR excitation, efficient quenching of upconversion blue-violet emission by MnO2 nanoflakes occurs, and the quenched emission is recovered with acetylcholinesterase-mediated reactions. This process allows for the determination of chlorpyrifos by inhibiting enzymatic activity. The UCNPs/MnO2 were embedded to fabricate a hydrogel portable kit, the blue-violet emission images captured by smartphone were converted into corresponding gray values by Python-assisted superiority chart algorithm which achieves a real-time rapid quantitative analysis of chlorpyrifos with a detection limit of 0.17 ng mL-1. At the same time, pseudo-color images were also added by Python in "one run" to distinguish images clearly. This sensor detection with Python-assisted analysis platform provides a new perspective on pesticide monitoring and broadens the application prospects in bioanalysis.

RABV induces biphasic actin cytoskeletal rearrangement through Rac1 activity modulation.

Rabies virus (RABV) is highly lethal and triggers severe neurological symptoms. The neuropathogenic mechanism remains poorly understood. Ras-related C3 botulinum toxin substrate 1 (Rac1) is a Rho-GTPase that is involved in actin remodeling and has been reported to be closely associated with neuronal dysfunction. In this study, by means of a combination of pharmacological inhibitors, small interfering RNA, and specific dominant-negatives, we characterize the crucial roles of dynamic actin and the regulatory function of Rac1 in RABV infection, dominantly in the viral entry phase. The data show that the RABV phosphoprotein interacts with Rac1. RABV phosphoprotein suppress Rac1 activity and impedes downstream Pak1-Limk1-Cofilin1 signaling, leading to the disruption of F-actin-based structure formation. In early viral infection, the EGFR-Rac1-signaling pathway undergoes a biphasic change, which is first upregulated and subsequently downregulated, corresponding to the RABV entry-induced remodeling pattern of F-actin. Taken together, our findings demonstrate for the first time the role played by the Rac1 signaling pathway in RABV infection and may provide a clue for an explanation for the etiology of rabies neurological pathogenesis.IMPORTANCEThough neuronal dysfunction is predominant in fatal rabies, the detailed mechanism by which rabies virus (RABV) infection causes neurological symptoms remains in question. The actin cytoskeleton is involved in numerous viruses infection and plays a crucial role in maintaining neurological function. The cytoskeletal disruption is closely associated with abnormal nervous symptoms and induces neurogenic diseases. In this study, we show that RABV infection led to the rearrangement of the cytoskeleton as well as the biphasic kinetics of the Rac1 signal transduction. These results help elucidate the mechanism that causes the aberrant neuronal processes by RABV infection and may shed light on therapeutic development aimed at ameliorating neurological disorders.

Establishment of a prognosis predictive model for liver cancer based on expression of genes involved in the ubiquitin-proteasome pathway.

BACKGROUND: The ubiquitin-proteasome pathway (UPP) has been proven to play important roles in cancer. AIM: To investigate the prognostic significance of genes involved in the UPP and develop a predictive model for liver cancer based on the expression of these genes. METHODS: In this study, UPP-related E1, E2, E3, deubiquitylating enzyme, and proteasome gene sets were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, aiming to screen the prognostic genes using univariate and multivariate regression analysis and develop a prognosis predictive model based on the Cancer Genome Atlas liver cancer cases. RESULTS: Five genes (including autophagy related 10, proteasome 20S subunit alpha 8, proteasome 20S subunit beta 2, ubiquitin specific peptidase 17 like family member 2, and ubiquitin specific peptidase 8) were proven significantly correlated with prognosis and used to develop a prognosis predictive model for liver cancer. Among training, validation, and Gene Expression Omnibus sets, the overall survival differed significantly between the high-risk and low-risk groups. The expression of the five genes was significantly associated with immunocyte infiltration, tumor stage, and postoperative recurrence. A total of 111 differentially expressed genes (DEGs) were identified between the high-risk and low-risk groups and they were enriched in 20 and 5 gene ontology and KEGG pathways. Cell division cycle 20, Kelch repeat and BTB domain containing 11, and DDB1 and CUL4 associated factor 4 like 2 were the DEGs in the E3 gene set that correlated with survival. CONCLUSION: We have constructed a prognosis predictive model in patients with liver cancer, which contains five genes that associate with immunocyte infiltration, tumor stage, and postoperative recurrence.

Targeted therapy of kidney disease with nanoparticle drug delivery materials.

With the development of nanomedicine, nanomaterials have been widely used, offering specific drug delivery to target sites, minimal side effects, and significant therapeutic effects. The kidneys have filtration and reabsorption functions, with various potential target cell types and a complex structural environment, making the strategies for kidney function protection and recovery after injury complex. This also lays the foundation for the application of nanomedicine in kidney diseases. Currently, evidence in preclinical and clinical settings supports the feasibility of targeted therapy for kidney diseases using drug delivery based on nanomaterials. The prerequisite for nanomedicine in treating kidney diseases is the use of carriers with good biocompatibility, including nanoparticles, hydrogels, liposomes, micelles, dendrimer polymers, adenoviruses, lysozymes, and elastin-like polypeptides. These carriers have precise renal uptake, longer half-life, and targeted organ distribution, protecting and improving the efficacy of the drugs they carry. Additionally, attention should also be paid to the toxicity and solubility of the carriers. While the carriers mentioned above have been used in preclinical studies for targeted therapy of kidney diseases both in vivo and in vitro, extensive clinical trials are still needed to ensure the short-term and long-term effects of nano drugs in the human body. This review will discuss the advantages and limitations of nanoscale drug carrier materials in treating kidney diseases, provide a more comprehensive catalog of nanocarrier materials, and offer prospects for their drug-loading efficacy and clinical applications.

Barley yellow dwarf virus-GAV 17K protein disrupts thiamine biosynthesis to facilitate viral infection in plants.

Thiamine functions as a crucial activator modulating plant health and broad-spectrum stress tolerances. However, the role of thiamine in regulating plant virus infection is largely unknown. Here, we report that the multifunctional 17K protein encoded by barley yellow dwarf virus-GAV (BYDV-GAV) interacted with barley pyrimidine synthase (HvTHIC), a key enzyme in thiamine biosynthesis. HvTHIC was found to be localized in chloroplast via an N-terminal 74-amino acid domain. However, the 17K-HvTHIC interaction restricted HvTHIC targeting to chloroplasts and triggered autophagy-mediated HvTHIC degradation. Upon BYDV-GAV infection, the expression of the HvTHIC gene was significantly induced, and this was accompanied by accumulation of thiamine and salicylic acid. Silencing of HvTHIC expression promoted BYDV-GAV accumulation. Transcriptomic analysis of HvTHIC silenced and non-silenced barley plants showed that the differentially expressed genes were mainly involved in plant-pathogen interaction, plant hormone signal induction, phenylpropanoid biosynthesis, starch and sucrose metabolism, photosynthesis-antenna protein, and MAPK signaling pathway. Thiamine treatment enhanced barley resistance to BYDV-GAV. Taken together, our findings reveal a molecular mechanism underlying how BYDV impedes thiamine biosynthesis to uphold viral infection in plants.

Numerical Analysis of Broadband Noise Generated by an Airfoil with Spanwise-Varying Leading Edges.

Here, the single-target parameterization of alternatives to leading-edge noise is carried out using analytical models based on the Wiener-Hopf technique. Four leading-edge serration profiles with different frequencies, amplitudes, and phases are implemented to aid the understanding of sound suppression mechanisms. The effects of the serrated shape factor, wavelength, and amplitude are analyzed at tip-to-root ratios of 0.5, 1, and 2, respectively. An effective double-wavelength sinusoidal serration design can substantially reduce the noise emissions of 5.2 dB at h¯ = 2. Additionally, compared to single-wavelength serrations, an additional 1.47 dB noise reduction effect can be obtained by double-wavelength serrations under the appropriate design parameters. The surface pressure and phase distribution of different spanwise-varying leading edges indicate that the phase interference effect affected by source-radiated noise reduction is enhanced by this serration at the hills for serrations with a small curvature, and noise emission in the low-frequency band is more effectively suppressed. The sharper the serration is, the more conducive it is to a reduction in high-frequency noise. Nevertheless, the effectiveness of serrations is usually partially limited by the non-negligible trailing-edge self-noise. The sound source intensity of the root is decreased by the ogee-shaped serrations with a large curvature transition. A secondary noise reduction mechanism with a local source cut-off effect caused by nonlinearity is demonstrated.

Numerical Simulations of Combined Dielectrophoresis and Alternating Current Electrothermal Flow for High-Efficient Separation of (Bio)Microparticles.

High-efficient separation of (bio)microparticles has important applications in chemical analysis, environmental monitoring, drug screening, and disease diagnosis and treatment. As a label-free and high-precision separation scheme, dielectrophoresis (DEP) has become a research hotspot in microparticle separation, especially for biological cells. When processing cells with DEP, relatively high electric conductivities of suspending media are sometimes required to maintain the biological activities of the biosample, which results in high temperature rises within the system caused by Joule heating. The induced temperature gradient generates a localized alternating current electrothermal (ACET) flow disturbance, which seriously impacts the DEP manipulation of cells. Based on this, we propose a novel design of the (bio)microparticle separator by combining DEP with ACET flow to intensify the separation process. A coupling model that incorporates electric, fluid flow, and temperature fields as well as particle tracking is established to predict (bio)microparticle trajectories within the separator. Numerical simulations reveal that both ACET flow and DEP motion act in the same plane but in different directions to achieve high-precision separation between particles. This work provides new design ideas for solving the very tricky Joule heating interference in the DEP separation process, which paves the way for further improving the throughput of the DEP-based (bio)microparticle separation system.

EPIC-0628 abrogates HOTAIR/EZH2 interaction and enhances the temozolomide efficacy via promoting ATF3 expression and inhibiting DNA damage repair in glioblastoma.

The efficacy of temozolomide (TMZ) treatment in glioblastoma (GBM) is influenced by various mechanisms, mainly including the level of O6-methylguanine-DNA methyltransferase (MGMT) and the activity of DNA damage repair (DDR) pathways. In our previous study, we had proved that long non-coding RNA HOTAIR regulated the GBM progression and mediated DDR by interacting with EZH2, the catalytic subunit of PRC2. In this study, we developed a small-molecule inhibitor called EPIC-0628 that selectively disrupted the HOTAIR-EZH2 interaction and promoted ATF3 expression. The upregulation of ATF3 inhibited the recruitment of p300, p-p65, p-Stat3 and SP1 to the MGMT promoter. Hence, EPIC-0628 silenced MGMT expression. Besides, EPIC-0628 induced cell cycle arrest by increasing the expression of CDKN1A and impaired DNA double-strand break repair via suppressing the ATF3-p38-E2F1 pathway. Lastly, EPIC-0628 enhanced TMZ efficacy in GBM in vitro and vivo. Hence, this study provided evidence for the combination of epigenetic drugs EPIC-0628 with TMZ for GBM treatment through the above mechanisms.

Determinant of m6A regional preference by transcriptional dynamics.

N6-Methyladenosine (m6A) is the most abundant chemical modification occurring on eukaryotic mRNAs, and has been reported to be involved in almost all stages of mRNA metabolism. The distribution of m6A sites is notably asymmetric along mRNAs, with a strong preference toward the 3' terminus of the transcript. How m6A regional preference is shaped remains incompletely understood. In this study, by performing m6A-seq on chromatin-associated RNAs, we found that m6A regional preference arises during transcription. Nucleosome occupancy is remarkedly increased in the region downstream of m6A sites, suggesting an intricate interplay between m6A methylation and nucleosome-mediated transcriptional dynamics. Notably, we found a remarkable slowdown of Pol-II movement around m6A sites. In addition, inhibiting Pol-II movement increases nearby m6A methylation levels. By analyzing massively parallel assays for m6A, we found that RNA secondary structures inhibit m6A methylation. Remarkably, the m6A sites associated with Pol-II pausing tend to be embedded within RNA secondary structures. These results suggest that Pol-II pausing could affect the accessibility of m6A motifs to the methyltransferase complex and subsequent m6A methylation by mediating RNA secondary structure. Overall, our study reveals a crucial role of transcriptional dynamics in the formation of m6A regional preference.

Ti2C3 MXene-based nanocomposite as an intelligent nanoplatform for efficient mild hyperthermia treatment.

Photothermal therapy (PTT) has attracted much attention due to its less invasive, controllable and highly effective nature. However, PTT also suffers from intrinsic cancer resistance mediated by cell survival pathways. These survival pathways are regulated by a variety of proteins, among which heat shock protein (HSP) triggers thermotolerance and protects tumor cells from hyperthermia-induced apoptosis. Confronted by this challenge, we propose and validate here a novel MXene-based HSP-inhibited mild photothermal platform, which significantly enhances the sensitivity of tumor cells to heat-induced stress and thus improves the PPT efficacy. The Ti3C2@Qu nanocomposites are constructed by utilizing the high photothermal conversion ability of Ti3C2 nanosheets in combination with quercetin (Qu) as an inhibitor of HSP70. Qu molecules are loaded onto the nanoplatform in a pH-sensitive controlled release manner. The acidic environment of the tumor causes the burst-release of Qu molecules, which deplete the level of heat shock protein 70 (HSP70) in tumor cells and leave the tumor cells out from the protection of the heat-resistant survival pathway in advance, thus sensitizing the hyperthermia efficacy. The nanostructure, photothermal properties, pH-responsive controlled release, synergistic photothermal ablation of tumor cells in vitro and in vivo, and hyperthermia effect on subcellular structures of the Ti3C2@Qu nanocomposites were systematically investigated.

Near-Infrared Perylenecarboximide Fluorophores for Live-Cell Super-Resolution Imaging.

Organic near-infrared (NIR) photoblinking fluorophores are highly desirable for live-cell super-resolution imaging based on single-molecule localization microscopy (SMLM). Herein we introduce a novel small chromophore, PMIP, through the fusion of perylenecarboximide with 2,2-dimetheylpyrimidine. PMIP exhibits an emission maximum at 732 nm with a high fluorescence quantum yield of 60% in the wavelength range of 700-1000 nm and excellent photoblinking without any additives. With resorcinol-functionalized PMIP (PMIP-OH), NIR SMLM imaging of lysosomes is demonstrated for the first time in living mammalian cells under physiological conditions. Moreover, metabolically labeled nascent DNA is site-specifically detected using azido-functionalized PMIP (PMIP-N3) via click chemistry, thereby enabling the super-resolution imaging of nascent DNA in phosphate-buffered saline with a 9-fold improvement in spatial resolution. These results indicate the potential of PMIP-based NIR blinking fluorophores for biological applications of SMLM.

Identification of prognostic biomarkers of smoking-related lung cancer.

Background: The early diagnosis and effective prognostic treatment measures for lung cancer are still limited, leading to a 5-year survival rate of less than 15% for these patients. Smoking is one of the causes of lung cancer, but it is not the initial carcinogenic factor. It is not clear what specific mechanism cigarette induces lung cancer, and there is a lack of research on the relationship between related genes and the prognosis of patients with smoking lung cancer. The objective of this study was to provide new theoretical evidence and potential therapeutic targets for the mechanisms of smoking-related lung cancer formation. Methods: The gene expression profile data from the GSE12428 dataset which includes 63 lung cancer and normal tissue pairs were downloaded from the Gene Expression Omnibus (GEO) database, and data from smokers with lung cancer [both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC)] from The Cancer Genome Atlas (TCGA) database were analyzed. The differential genes in smokers with lung cancer were screened using the linear model for microarray data via R software. The differential gene enrichment analysis was performed using the online analysis software Database for Annotation, Visualization and Integrated Discovery (DAVID). The expression levels of differential genes and their correlation with patient tumor clinical stage were analyzed using gene expression profiling interactive analysis (GEPIA). The overall survival rate was analyzed using Kaplan-Meier curves. Results: In the GSE12428 dataset, 225 upregulated genes and 565 downregulated genes were identified in cancer tissues; based on smoking status, 1 upregulated gene and 4 downregulated genes were identified. Among smokers who also had lung cancer, 4 genes were downregulated, namely CSH1, BPIFA1, SLPI, and SCGB3A1. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that these genes were mainly associated with biological functions such as antibacterial response, humoral immune response, and response to external stimuli. Among them, BPIFA1, SLPI, and SCGB3A1 expression was decreased in lung cancer tissues, with SCGB3A1 showing significant differences. Additionally, high expression of SCGB3A1 was associated with favorable prognosis in patients with lung cancer. Conclusions: Three genes BPIFA1, SLPI and SCGB3A1, were identified as being associated with smokers with lung cancer, with SCGB3A1 showing a close correlation with patient prognosis. These findings provide potential new targets for the treatment of lung cancer. Certainly, this study needs to more investigate the mechanism of these genes regulation.

The industrial robot reducer testing instrument dynamic torsional moment measurement error calibration, based on the Bisquare curve fitting-improved Bayes particle swarm optimization-nonlinear echo state network (BCF-IBPSO-NESN) method.

Industrial robots are important components in the production and manufacturing industry. As a core component of the industrial robot, the industrial robot reducer plays a crucial role in the performance of the entire industrial robot. The error analysis and accuracy traceability of the industrial robot reducer testing instrument are of great significance in improving the quality of the precision reducer. Therefore, it is essential to calibrate the dynamic torsional moment measurement error of the instrument. The features of the dynamic torsional moment measurement error are analyzed in this paper. Based on these features, a new dynamic torsional moment measurement error calibration method is proposed based on the Bisquare curve fitting-improved Bayes particle swarm optimization-nonlinear echo state network (BCF-IBPSO-NESN) algorithm. The proposed method focuses on calibrating the dynamic torsional moment measurement error of the industrial robot reducers in real time. The experimental results show that the dynamic torsional moment measurement error of the input side torsional moment measurement module and the output side torsional moment measurement module can be reduced to ±0.05 Nm and ±1 Nm, respectively. The contribution of this paper is that the method calibrates the dynamic torsional moment measurement error. It supplies a guideline for calibrating the dynamic torsional moment measurement error of the instrument under any load.

Diverse ALS mutations and cross-and multiple-resistance to ALS and EPSPS inhibitors in flucarbazone­sodium-resistant Bromus japonicus populations from Hebei province, China.

Japanese brome (Bromus japonicus) has become one of the main weeds in wheat fields in Hebei province of China and causes a large decrease of wheat production. A total of 44 putative resistant and 2 susceptible Japanese brome populations were collected in the 2021/2022 crop season from Hebei province of China to determine resistance levels to flucarbazone­sodium and to investigate the diversity of acetolactate synthase (ALS) mutations, as well as to confirm the cross-and multiple-resistance levels to ALS and EPSPS (5-enolpyruvate shikimate-3-phosphate synthetase) inhibitors. Whole plant bioassay results showed that 15 out of 44 populations tested or 34% were resistant to flucarbazone­sodium. The resistance indices of Japanese brome to flucarbazone­sodium ranged from 43 to 1977. The resistant populations were mainly distributed in Baoding and Shijiazhuang districts, and there was only one resistant population in Langfang district. Resistant Japanese brome had diverse ALS mutations, including Pro-197-Ser, -Thr, -Arg and Asp-376-Glu. The incidence of Pro-197-Ser mutation was the highest at 68%. Application of the CYP450 inhibitor malathion suggested that CYP450 was involved in metabolic resistance in a population without an ALS mutation. The population with Pro-197-Thr mutation evolved weak cross-resistance to mesosulfuron-methyl and pyroxsulam, and it is in the process of evolving multiple-resistance to glyphosate.

A Dual-domain Engineered Antibody for Efficient HBV Suppression and Immune Responses Restoration.

Chronic hepatitis B (CHB) remains a major public health concern because of the inefficiency of currently approved therapies in clearing the hepatitis B surface antigen (HBsAg). Antibody-based regimens have demonstrated potency regarding virus neutralization and HBsAg clearance. However, high dosages or frequent dosing are required for virologic control. In this study, a dual-domain-engineered anti-hepatitis B virus (HBV) therapeutic antibody 73-DY is developed that exhibits significantly improved efficacy regarding both serum and intrahepatic viral clearance. In HBV-tolerant mice, administration of a single dose of 73-DY at 2 mg kg-1 is sufficient to reduce serum HBsAg by over 3 log10 IU mL-1 and suppress HBsAg to < 100 IU mL-1 for two weeks, demonstrating a dose-lowering advantage of at least tenfold. Furthermore, 10 mg kg-1 of 73-DY sustainably suppressed serum viral levels to undetectable levels for ≈ 2 weeks. Molecular analyses indicate that the improved efficacy exhibited by 73-DY is attributable to the synergy between fragment antigen binding (Fab) and fragment crystallizable (Fc) engineering, which conferred sustained viral suppression and robust viral eradication, respectively. Long-term immunotherapy with reverse chimeric 73-DY facilitated the restoration of anti-HBV immune responses. This study provides a foundation for the development of next-generation antibody-based CHB therapies.

1,3-Disubstituted-1,2,4-triazin-6-ones with potent activity against androgen receptor-dependent prostate cancer cells.

Synthesis and biological evaluation of a small, focused library of 1,3-disubstituted-1,2,4-triazin-6-ones for in vitro inhibitory activity against androgen-receptor-dependent (22Rv1) and androgen-receptor independent (PC3) castration-resistant prostate cancer (CRPC) cells led to highly active compounds with in vitro IC50 values against 22Rv1 cells of <200 nM, and with apparent selectivity for this cell type over PC3 cells. From metabolic/PK evaluations of these compounds, a 3-benzyl-1-(2,4-dichlorobenzyl) derivative had superior properties and showed considerably stronger activity, by nearly an order of magnitude, against AR-dependent LNCaP and C4-2B cells compared to AR-independent DU145 cells. This lead compound decreased AR expression in a dose and time dependent manner and displayed promising therapeutic effects in a 22Rv1 CRPC xenograft mouse model. Computational target prediction and subsequent docking studies suggested three potential known prostate cancer targets: p38a MAPK, TGF-ß1, and HGFR/c-Met, with the latter case of c-Met appearing stronger, owing to close structural similarity of the lead compound to known pyridazin-3-one derivatives with potent c-Met inhibitory activity. RNA-seq analysis showed dramatic reduction of AR signalling pathway and/or target genes by the lead compound, subsequently confirmed by quantitative PCR analysis. The lead compound was highly inhibitory against HGF, the c-Met ligand, which fitted well with the computational target prediction and docking studies. These results suggest that this compound could be a promising starting point for the development of an effective therapy for the treatment of CRPC.