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The low bioavailability of most phytochemicals limits their anticancer effects in humans. The present study was designed to test whether combining arctigenin (Arc), a lignan mainly from the seed of Arctium lappa, with green tea (GT) and quercetin (Q) enhances the chemopreventive effect on prostate cancer. We performed in vitro proliferation studies on different cell lines. We observed a strong synergistic anti-proliferative effect of GT+Q+Arc in exposing androgen-sensitive human prostate cancer LNCaP cells. The pre-malignant WPE1-NA22 cell line was more sensitive to this combination. No cytotoxicity was observed in normal prostate epithelial PrEC cells. For an in vivo study, 3-week-old, prostate-specific PTEN (phosphatase and tensin homolog) knockout mice were treated with GT+Q, Arc, GT+Q+Arc, or the control daily until 16 weeks of age. In vivo imaging using prostate-specific membrane antigen (PSMA) probes demonstrated that the prostate tumorigenesis was significantly inhibited by 40% (GT+Q), 60% (Arc at 30 mg/kg bw), and 90% (GT+Q+Arc) compared to the control. A pathological examination showed that all control mice developed invasive prostate adenocarcinoma. In contrast, the primary lesion in the GT+Q and Arc alone groups was high-grade prostatic intraepithelial neoplasia (PIN), with low-grade PIN in the GT+Q+Arc group. The combined effect of GT+Q+Arc was associated with an increased inhibition of the androgen receptor, the PI3K/Akt pathway, Ki67 expression, and angiogenesis. This study demonstrates that combining Arc with GT and Q was highly effective in prostate cancer chemoprevention. These results warrant clinical trials to confirm the efficacy of this combination in humans.

Abstract Background Artemisinin (ART) analogs, such as dihydroartemisinin, arteether, artemether, and artesunate, all featuring an endoperoxide bridge, have demonstrated efficacy against schistosomiasis. Artemisitene (ATT), which contains an additional α, β-unsaturated carbonyl structure, has shown enhanced biological activities. This study aims to evaluate the anti-schistosomaiasis japonica activity of ATT and compare it with ART. Methods We assessed liver inflammation and fibrosis in mice using hematoxylin and eosin staining and Sirius red staining, respectively. RNA sequencing analyzed transcriptomics in female and male Schistosoma japonicum (S. japonicum) adult worms and mice livers, with cytokine profiling and flow cytometry to study immune responses under ART or ATT treatment. Results ATT exhibits a marked reduction in female S. japonicum adult worms and egg numbers, damaging the adult worms’ surface. It also influences the transcription of genes related to cellular anatomical structures. Notably, ATT treatment resulted in significant reductions in liver granuloma size and collagen area, alongside lowering serum levels of glutamic pyruvic and glutamic oxaloacetic transaminase more effectively than ART. Both ART and ATT markedly decreased neutrophil frequency in the liver and elevated eosinophil counts. However, only ATT treatment significantly reduced the M1/M2 and Th1/Th2 indices, indicating a pronounced shift in immune response profiles. ATT-affected host immunity correlated with the extent of liver fibrosis and the count of single males more strongly than ART. Conclusion ATT, as a novel preventive strategy for schistosomiasis japonica in mice, significantly outperforms ART. Graphical Abstract

Abstract Objectives The purpose of this review is to investigate the relationship between gastrointestinal microbiome, obesity, and gestational diabetes mellitus (GDM) in an objective manner. Methods We conducted a thorough and comprehensive search of the English language literatures published in PubMed, Web of Science, and the Cochrane Library from the establishment of the library until 12 December 2023. Our search strategy included both keywords and free words searches, and we strictly applied inclusion and exclusion criteria. Meta-analyses and systematic reviews were prepared. Results Six high-quality literature sources were identified for meta-analysis. However, after detailed study and analysis, a certain degree of heterogeneity was found, and the credibility of the combined analysis results was limited. Therefore, descriptive analyses were conducted. The dysbiosis of intestinal microbiome, specifically the ratio of Firmicutes/Bacteroides, is a significant factor in the development of metabolic diseases such as obesity and gestational diabetes. Patients with intestinal dysbiosis and obesity are at a higher risk of developing GDM. Conclusions During pregnancy, gastrointestinal microbiome disorders and obesity may contribute to the development of GDM, with all three factors influencing each other. This finding could aid in the diagnosis and management of patients with GDM through further research on their gastrointestinal microbiome.

Data independent acquisition tensor (DIAT), a specialized mass spectrometry data format, is intricately crafted for acquiring the meticulous processing and analysis of proteomics data through the advanced methodology of data independent acquisition (DIA). Compared to conventional approaches, DIAT technique has the advantages of the seamless processing of data visualization and efficient deep learning model training, ensuring a convenient user experience. Despite these merits, the DIAT mass spectrometry data format remains a relatively recent introduction. As a consequence, comprehensive principles and methodologies elucidating the nuances of this data format are predominantly found within the confines of specialized literatures. Furthermore, the absence of robust software platform supporting for the utilization of DIAT format data is a key impediment, hindering the widespread application in various scientific domains. In response to these challenges, a meticulously designed software solution for the comprehensive handling and analyzing of DIAT data was introduced in this study. Leveraging the robust capabilities of the PyQt framework, the software embodied a spectrum of functionalities intricately tied to DIAT technique, including DIAT data format conversion, the intuitive visualization of DIAT data, the training of classification models using DIAT data, and the accurate prediction of DIAT data labels through the utilization of trained models. Crucially, each of these functionalities underwent rigorous test using authentic mass spectrometry data. The test results unequivocally showcased the prowess of the DIAT computational software, empowering users to engage effortlessly in complex DIAT data analysis. This not only lowered the entry barriers for users, but also injected a renewed vigor into the field of DIA mass spectrometry data analysis. In summary, DIAT emerged as a trailblazing mass spectrometry data format meticulously tailored for the expeditious processing and analysis of proteomics data acquired through the sophisticated techniques of DIA. This study introduced a groundbreaking software solution, which was developed on the robust PyQt framework, aimed at surmounting the existing limitations associated with the nascent DIAT format. The implemented software was validated through rigorous real-world data testing, not only facilitated sophisticated DIAT data analysis but also significantly contributed to enhance the accessibility and dynamism of DIA mass spectrometry data analysis. This innovative approach will hold immense promise for advancing research and applications in the ever-evolving field of proteomics.

Abstract Background Human adipose stromal cells-derived extracellular vesicles (haMSC-EVs) have been shown to alleviate inflammation in acute lung injury (ALI) animal models. However, there are few systemic studies on clinical-grade haMSC-EVs. Our study aimed to investigate the manufacturing, quality control (QC) and preclinical safety of clinical-grade haMSC-EVs. Methods haMSC-EVs were isolated from the conditioned medium of human adipose MSCs incubated in 2D containers. Purification was performed by PEG precipitation and differential centrifugation. Characterizations were conducted by nanoparticle tracking analysis, transmission electron microscopy (TEM), Western blotting, nanoflow cytometry analysis, and the TNF-α inhibition ratio of macrophage [after stimulated by lipopolysaccharide (LPS)]. RNA-seq and proteomic analysis with liquid chromatography tandem mass spectrometry (LC–MS/MS) were used to inspect the lot-to-lot consistency of the EV products. Repeated toxicity was evaluated in rats after administration using trace liquid endotracheal nebulizers for 28 days, and respiratory toxicity was evaluated 24 h after the first administration. In vivo therapeutic effects were assessed in an LPS-induced ALI/ acute respiratory distress syndrome (ARDS) rat model. Results The quality criteria have been standardized. In a stability study, haMSC-EVs were found to remain stable after 6 months of storage at − 80°C, 3 months at − 20 °C, and 6 h at room temperature. The microRNA profile and proteome of haMSC-EVs demonstrated suitable lot-to-lot consistency, further suggesting the stability of the production processes. Intratracheally administered 1.5 × 108 particles/rat/day for four weeks elicited no significant toxicity in rats. In LPS-induced ALI/ARDS model rats, intratracheally administered haMSC-EVs alleviated lung injury, possibly by reducing the serum level of inflammatory factors. Conclusion haMSC-EVs, as an off-shelf drug, have suitable stability and lot-to-lot consistency. Intratracheally administered haMSC-EVs demonstrated excellent safety at the tested dosages in systematic preclinical toxicity studies. Intratracheally administered haMSC-EVs improved the lung function and exerted anti-inflammatory effects on LPS-induced ALI/ARDS model rats.

Pyroptosis is a form of programmed cell death that is crucial in the development of various diseases, including autoimmune diseases, atherosclerotic diseases, cancer, and pregnancy complications. In recent years, it has gained significant attention in national and international research due to its association with inflammatory immune overactivation and its involvement in pregnancy complications such as miscarriage and preeclampsia (PE). The mechanisms discussed include the canonical pyroptosis pathway of gasdermin activation and pore formation (caspase-1-dependent pyroptosis) and the non-canonical pyroptosis pathway (cysteoaspartic enzymes other than caspase-1). These pathways work on various cellular and factorial levels to influence normal pregnancy. This review aims to summarize and analyze the pyroptosis pathways associated with abnormal pregnancies and pregnancy complications. The objective is to enhance pregnancy outcomes by identifying various targets to prevent the onset of pyroptosis.

IntroductionImmune-related epidermal necrolysis (irEN), including Stevens-Johnson Syndrome (SJS) and toxic epidermal necrolysis (TEN), represents a potentially lethal reaction to immune checkpoint inhibitors. An optimal treatment strategy remains undefined. This study evaluates the effectiveness and safety of combination therapy with corticosteroids and tumor necrosis factor inhibitors (TNFi) in treating irEN patients.MethodsIn this single-center, prospective, observational study, patients with irEN received either corticosteroid monotherapy or a combination therapy of corticosteroids and TNFi (etanercept for SJS, infliximab for TEN). The primary endpoint was re-epithelization time, with secondary endpoints including corticosteroid exposure, major adverse event incidence, acute mortality rates, and biomarkers indicating disease activity and prognosis. The study was registered at the Chinese Clinical Trial Registry (ChiCTR2100051052).ResultsThirty-two patients were enrolled (21 SJS, 11 TEN); 14 received combination therapy and 18 received corticosteroid monotherapy. IrEN typically occurred after 1 cycle of ICI administration, with a median latency of 16 days. Despite higher SCORTEN scores in the combination group (3 vs. 2, p = 0.008), these patients experienced faster re-epithelization (14 vs. 21 days; p < 0.001), shorter corticosteroid treatment duration (22 vs. 32 days; p = 0.005), and lower prednisone cumulative dose (1177 mg vs. 1594 mg; p = 0.073). Major adverse event rates were similar between groups. Three deaths occurred due to lung infection or disseminated intravascular coagulation, with mortality rates for both groups lower than predicted. Potential risk factors for increased mortality included continuous reduction in lymphocyte subset counts (CD4+ T cells, CD8+ T cells, natural killer cells) and consistent rises in inflammatory markers (serum ferritin, interleukin-6, TNF-α). Re-epithelization time negatively correlated with body mass index and positively correlated with epidermal detachment area and serum levels of interleukin-6 and TNF-α.ConclusionsCorticosteroids combined with TNFi markedly promote re-epithelization, reduce corticosteroid use, and decrease acute mortality in irEN patients without increasing major adverse events, offering a superior alternative to corticosteroid monotherapy. Inflammatory markers and lymphocyte subsets are valuable for assessing disease activity and prognosis.

BACKGROUND Pilomatrixoma, pilomatricoma, or calcifying epithelioma of Malherbe, is a common benign tumor that arises from the base of the hair follicle. Pilomatrixoma has previously been reported at vaccination sites. This report is of a 65-year-old man with an 18-month history of an enlarging pilomatrixoma of the left upper arm at the vaccination site, following a first COVID-19 vaccination. CASE REPORT The case involves a 65-year-old man who developed a left shoulder mass 1.5 years ago. The mass appeared at his COVID-19 vaccine site 3 months after receiving the first dose. The mass measures 3 cm in diameter, was mobile, and exhibited no signs of infection in the physical examination. Surgical excision was performed, and pathology confirmed the mass as a pilomatrixoma, characterized by basaloid cells and keratinization. Three months after surgery, no recurrence was observed. CONCLUSIONS This report has presented an association between vaccination injection sites and pilomatrixoma aligning with previous findings. Enhanced awareness about this condition can substantially improve pilomatrixoma diagnosis accuracy and reduce unnecessary examinations and treatments. Furthermore, we recommend that, along with clinical symptoms, ultrasound imaging be considered a valuable diagnostic tool for pilomatrixoma, with histopathological results to confirm the diagnosis.

Abstract Introduction The necessity for tuberculosis preventive treatment (TPT) and routine T-SPOT.TB monitoring in patients with psoriasis and tuberculosis infection (TBI) undergoing interleukin (IL)-17A inhibitor therapy remains uncertain. This study aims to evaluate the long-term safety of IL-17A inhibitors administered without TPT and analyze changes in T-SPOT.TB among these patients. It also identifies risk factors for TBI in patients with psoriasis. Methods This single-center prospective study enrolled adult patients with plaque psoriasis and TBI receiving IL-17A inhibitors. TBI was defined as positive T-SPOT.TB results (≥ 6 spots) without symptoms or evidence of active tuberculosis (ATB). TPT administration was based on contraindications, tuberculosis risk factors, and patient preferences. The primary endpoint was the incidence of ATB over 2 years. Secondary outcomes included T-SPOT.TB changes and TBI risk factors. Results Of the 129 patients with psoriasis and TBI enrolled in the study, 97 (75.2%) did not receive TPT, while 32 (24.8%) did. Among them, 109 patients (84.5%) completed the 2-year follow-up. During the 235 person-years of observation, no ATB cases were identified. Median T-SPOT.TB values showed no significant changes from baseline to year 2 in both the non-TPT (20 vs. 17 spots, p = 0.975) and TPT groups (55 vs. 58 spots, p = 0.830). T-SPOT.TB reversed in 14 patients (12.8%), mostly in the non-TPT group. Moreover, for TBI risk factor analysis, a cohort of 212 patients with psoriasis with negative baseline T-SPOT.TB was evaluated, revealing a TBI prevalence of 37.8%. Logistic regression analysis highlighted age ≥ 45 years (odds ratio [OR] 2.44, 95% confidence interval [CI] 1.50–3.99, p

The control precision of the working device has always been a challenging aspect in unmanned excavator research due to the adoption of a triangular drive mode and a complex hydraulic system in the working mechanism. The article focuses on the research of autonomous control for the downward motion of a robotic arm in an unmanned excavator equipped with a regeneration valve. The study aims to achieve precise tracking of fast movement trajectories during operator manipulation, utilizing Model Predictive Control (MPC). Furthermore, the exceptional disturbance rejection capability of the MPC algorithm is demonstrated through interference application. A comprehensive model considering mechanical, hydraulic, and electrical factors is established for the excavator boom. The MPC algorithm is applied to achieve precise control over the boom descent process, providing a foundation for motion control in unmanned excavators. This article presents a theoretical analysis to elucidate the robustness principle of MPC in the descent control of uncertain dynamic arms. By incorporating real parameters, we successfully track predetermined planned paths at different speeds and validate them on a 20-ton hydraulic excavator. The results demonstrate that the MPC control algorithm accurately manipulates the boom descent motion while exhibiting excellent disturbance rejection performance. Compared to PID control algorithms, MPC offers wider target adaptability range and better disturbance rejection performance, making it suitable for rapid application in controlling working devices of unmanned excavators.

Induction and suppression of antiviral RNA interference (RNAi) has been observed in mammals during infection with at least seven distinct RNA viruses, including some that are pathogenic in humans. However, while the cell-autonomous immune response mediated by antiviral RNAi is gradually being recognized, little is known about systemic antiviral RNAi in mammals. Furthermore, extracellular vesicles (EVs) also function in viral signal spreading and host immunity. Here, we show that upon antiviral RNAi activation, virus-derived small-interfering RNAs (vsiRNAs) from Nodamura virus (NoV), Sindbis virus (SINV), and Zika virus (ZIKV) enter the murine bloodstream via EVs for systemic circulation. vsiRNAs in the EVs are biologically active, since they confer RNA-RNA homology-dependent antiviral activity in both cultured cells and infant mice. Moreover, we demonstrate that vaccination with a live-attenuated virus, rendered deficient in RNAi suppression, induces production of stably maintained vsiRNAs and confers protective immunity against virus infection in mice. This suggests that vaccination with live-attenuated VSR (viral suppressor of RNAi)-deficient mutant viruses could be a new strategy to induce immunity.

With the intersection and convergence of multiple disciplines and technologies, more and more researchers are actively exploring interdisciplinary cooperation outside their main research fields. Facing a new research field, researchers often hope to quickly learn what is being studied in this field, which research points are receiving high attention, which researchers are studying these research points, and then consider the possibility of collaborating with core researchers on these research points. In addition, students who are preparing for academic further education usually conduct research on mentors and mentors’ research platforms, including academic connections, employment opportunities, etc. In order to satisfy these requirements, we (1) design a research point state map based on a science map to help researchers and students understand the development state of a new research field; (2) design a bar-link author-affiliation information graph to help researchers and students clarify academic networks of scholars and find suitable collaborators or mentors; (3) designs citation pattern histogram to quickly discover research achievements with high research value, such as the Sleeping Beauty papers, recently hot papers, classic papers and so on. Finally, an interactive analytical system named PubExplorer was implemented with IEEE VIS publication data, and its effectiveness is verified through case studies.

Online quantitative analysis of reaction gases or exhaust in industrial production is of great significance to improve the production capacity and process.Anovel method is developed for the online quantitative analysis of reaction gases or exhaust using quantitative mathematical models combined with the linear regression algorithm of machine learning. After accurately estimating the component gases and their contents in the reaction gases or exhaust, a ratio matrix is constructed to separate the relevant overlapping peaks. The ratio and calibration standard gases are detected, filtered, normalized, and linearly regressed with an online process mass spectrometer to correct the ratio matrices and obtain the relative sensitivity matrices. A quantitative mathematical model can be established to obtain the content of each component of the reaction gases or exhaust in real time. The maximum quantification error and relative standard deviation of the method are within 0.3% and 1%, after online quantification of the representative yeast fermenter tail gas.

Trajectory planning plays a crucial role in achieving unmanned excavator operations. The quality of trajectory planning results heavily relies on the level of rules extracted from objects such as scenes and optimization objectives, using traditional theoretical methods. To address this issue, this study focuses on professional operators and employs machine learning methods for job trajectory planning, thereby obtaining planned trajectories which exhibit excellent characteristics similar to those of professional operators. Under typical working conditions, data collection and analysis are conducted on the job trajectories of professional operators, with key points being extracted. Machine learning is then utilized to train models under different parameters in order to obtain the optimal model. To ensure sufficient samples for machine learning training, the bootstrap method is employed to adequately expand the sample size. Compared with the traditional spline curve method, the trajectories generated by machine learning models reduce the maximum speeds of excavator boom arm, dipper stick, bucket, and swing joint by 8.64 deg/s, 10.24 deg/s, 18.33 deg/s, and 1.6 deg/s, respectively; moreover, the error does not exceed 2.99 deg when compared with curves drawn by professional operators; and, finally, the trajectories generated by this model are continuously differentiable without position or velocity discontinuities, and their overall performance surpasses that of those generated by the traditional spline curve method. This paper proposes a trajectory generation method that combines excellent operators with machine learning and establishes a machine learning-based trajectory-planning model that eliminates the need for manually establishing complex rules. It is applicable to motion path planning in various working conditions of unmanned excavators.

Abstract The application of novel bioorganic fertilizer (BIO) has been established as a weed biocontrol strategy, and reduce herbicides pollution and negatively effects on agricultural ecosystems. However, its long-term influences on soil bacterial communities are unknown. Here, 16 S rRNA sequencing to identify the changes that occur in soil bacterial community and enzyme under BIO treatments after five years in a field experiment. BIO application effectively controlled weeds, however no obvious differences between treatments were observed under BIO-50, BIO-100, BIO-200 and BIO-400 treatment. Anaeromyxobacter and Clostridium_ sensu_ stricto_1 were the two dominant genera among BIO-treated soil samples. The BIO-800 treatment had a slight influence on the species diversity index, which was more remarkable after five years. The seven significantly-different genera between BIO-800 treatment and untreated soils included C._sensu_stricto_1, Syntrophorhabdus, Candidatus_Koribacter, Rhodanobacter, Bryobacter, Haliangium, Anaeromyxobacter. In addition, BIO application had different effects on soil enzymatic activities and chemical properties. The extractable P and pH saliency correlated with Haliangium and C._Koribacter, and C._sensu_stricto_1 observably correlated with exchangeable K, hydrolytic N and organic matter. Taken together, our data suggest that BIO application effectively controlled weeds and a slight influence on soil bacterial communities and enzymes. These findings expand our knowledge of the application of BIO as widely used as a sustainable weed control in rice paddy.