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Abstract Choroid plexus tumors (CPT) are rare and highly vascularized neoplasms that have three histologically confirmed diagnoses, including choroid plexus papilloma, atypical choroid plexus papilloma, and choroid plexus carcinoma (CPC). This study aimed to determine the epidemiology and survival of patients with CPTs and develop a nomogram to quantify the prognosis of the patients with CPT. Data of 808 patients who were diagnosed as CPT between 2000 and 2020 was obtained from the surveillance, epidemiology, and end results database. Descriptive analysis was used to assess the distribution and tumor-related characteristics of the patients with CPT. Independent prognostic factors for patients with CPT were identified by univariate and multivariate Cox regression analysis. The nomogram was established and evaluated by receiver operating characteristic curve, and decision curve analysis (DCA), calibration curves. The independent prognostic factors for patients with CPT are age, tumor size, surgery, chemotherapy, tumor number, pathologies, and race. For the prognostic nomogram, the area under the curve (AUC) of 60-, 120-, and 180-months were 0.855, 0.869 and 0.857 in the training set and 0.836, 0.864 and 0.922 in the test set. The DCA and calibration curve indicated the good performance of the nomogram. Patients with CPTs can be diagnosed at any age. Among the three histopathological tumors, patients with CPC had the worst prognosis. The nomogram was established to predict the prognosis of patients with CPT, which had satisfactory accuracy, and clinical utility may benefit for clinical decision-making.

The expansion applications of semiconducting polymer dots (Pdots) among optical nanomaterial field have long posed a challenge for researchers, promoting their intelligent application in multifunctional nano-imaging systems and integrated nanomedicine carriers for diagnosis and treatment. Despite notable progress, several inadequacies still persist in the field of Pdots, including the development of simplified near-infrared (NIR) optical nanoprobes, elucidation of their inherent biological behavior, and integration of information processing and nanotechnology into biomedical applications. This review aims to comprehensively elucidate the current status of Pdots as a classical nanophotonic material by discussing its advantages and limitations in terms of biocompatibility, adaptability to microenvironments in vivo, etc. Multifunctional integration and surface chemistry play crucial roles in realizing the intelligent application of Pdots. Information visualization based on their optical and physicochemical properties is pivotal for achieving detection, sensing, and labeling probes. Therefore, we have refined the underlying mechanisms and constructed multiple comprehensive original mechanism summaries to establish a benchmark. Additionally, we have explored the cross-linking interactions between Pdots and nanomedicine, potential yet complete biological metabolic pathways, future research directions, and innovative solutions for integrating diagnosis and treatment strategies. This review presents the possible expectations and valuable insights for advancing Pdots, specifically from chemical, medical, and photophysical practitioners’ standpoints.

The paper investigates the issue of post-impact fatigue damage of the 2060 aluminium–lithium alloy, a representative material of third-generation aluminium–lithium alloys extensively employed in the fuselage of C919 aircraft due to its notable attributes of high specific stiffness and strength. Initial impact damage is identified utilizing a residual stress–strain field obtained from a quasi-static simulation. Then, the continuum damage mechanics approach is applied to predict the fatigue life of the impacted 2060 aluminium–lithium alloy plates accounting for the combined effects of residual stress, plastic damage, and fatigue loading. A comparative analysis between calculated and experimental results is conducted to validate the efficacy of the proposed methodology.

BackgroundUnderstanding the epidemiology and prognostic factors of low-grade gliomas (LGGs) can help estimate the public health impact and optimize risk stratification and treatment strategies.Methods3 337 patients diagnosed with LGGs were collected from the Surveillance, Epidemiology, and End Results (SEER) dataset, 2004–2019. The incidence trends of LGGs were analyzed by patient demographics (sex, age, race, and ethnicity). In addition, a competing risk regression model was used to explore the prognostic factors of LGGs by patient demographics, tumor characteristics (histological subtypes, invasiveness, and size), treatment modality, and molecular markers (IDH mutation and 1p/19q codeletion).ResultsLGGs occurred more frequently in male, non-Hispanic, and White populations. The incidence rate of mixed gliomas was stable from 2004 to 2013 and decreased dramatically to nearly zero until 2019. The risk of death increased 1.99 times for every 20-year increase in patient age, and 60 years is a predictive cut-off age for risk stratification of LGGs. Male patients showed poorer LGG-specific survival. Among the different subtypes, astrocytoma has the worst prognosis, followed by mixed glioma and oligodendroglioma. Tumors with larger size (≥5 cm) and invasive behavior tended to have poorer survival. Patients who underwent gross total resection had better survival rates than those who underwent subtotal resection. Among the different treatment modalities, surgery alone had the best survival, followed by surgery + radiotherapy + chemotherapy, but chemotherapy alone had a higher death risk than no treatment. Furthermore, age, invasiveness, and molecular markers were the most robust prognostic factors.ConclusionThis study reviewed the incidence trends and identified several prognostic factors that help clinicians identify high-risk patients and determine the need for postoperative treatment according to guidelines.

Abstract Background Toosendanin (TSN) is a triterpenoid compound mainly used as an ascaris repellant. Recent studies have shown that it possesses antitumor effects in many types of tumor cells. However, the effects of TSN on glioma cells have rarely been reported. Methods Different assays were performed to investigate the effects of TSN on the different glioma cell lines including U87MG and LN18. The assays included colony formation, wound healing, and transwell assays. Furthermore, Hoechst 33342 staining, flow cytometry, and western blotting analysis were performed to investigate the apoptotic activities of TSN. Finally, the results were confirmed using a xenograft tumor model that comprised of nude mice. Results In vitro, the CCK-8 and colony formation assays showed that TSN effectively inhibited glioma cell proliferation. Moreover, the inhibitory effects on glioma cell migration and invasion were demonstrated through the wound healing and transwell assays, respectively. Hoechst 33342 staining, flow cytometry, and western blotting assays demonstrated the significant effect of TSN in the apoptosis induction of glioma cells. Furthermore, the anti-glioma effect of TSN was exerted through the inhibition of the PI3K/Akt/mTOR signaling pathways as demonstrated by western blotting analysis. In addition, the effects of TSN on glioma cell viability, apoptosis, cell cycle arrest, migration, and invasion were reversed by 740Y-P, a PI3K activator. Finally, the mouse xenograft model confirmed the suppressive effect of TSN on tumor growth in vivo. Conclusion Our results suggest that TSN is a promising chemotherapeutic drug for patients with glioma.

Background: Gliomas are the most common primary intracranial malignant tumors with poor prognosis, despite the remarkable advances in medical technology that have been made. OSW-1, isolated from Ornithogalum saundersiae, possesses anticancer activity against various malignant cancer cells. However, the effects of OSW-1 on gliomas and its potential mechanisms remain unclear.Methods: Network pharmacology was employed for predicting potential key targets and mechanisms of the anticancer effects of OSW-1 on glioma. Experiments, including the Cell Counting Kit-8, colony formation, and flow cytometry, were performed to investigate how OSW-1 affects the biological behavior of glioma cells in vitro. Western blotting was used to detect changes in related proteins, such as those involved in the cell cycle, apoptosis, and signaling pathways. The nude mouse xenograft model was used to detect the effect of OSW-1 on inhibiting the proliferation of glioma cells in vivo.Results: An “OSW-1-Targets-Glioma” intersection network consisting of 151 intersecting genes was acquired to construct a “Protein–Protein Interaction network” and predict the top 10 core targets. According to the Kyoto Encyclopedia of Genes and Genomes pathway analysis, the PI3K/AKT signaling pathway was the top 3-ranked pathway, with 38 enriched intersecting genes. The glioma T98G and LN18 cell lines were used to verify the predictions. OSW-1 significantly inhibited the viability and proliferation of glioma cells in a dose- and time-dependent manner. Flow cytometry showed that OSW-1 arrested the cell cycle at the G2/M phase, and the apoptotic ratio of glioma cells increased significantly with increasing concentrations. Western blotting revealed that the expression levels of p-PI3K and p-AKT1 in glioma cells treated with OSW-1 were significantly lower than those in the controls; however, 740Y-P, a PI3K activator, significantly reversed the inactivation of the PI3K/AKT signaling pathway caused by OSW-1. Furthermore, the mouse xenograft model confirmed the suppressive effect of OSW-1 on tumor growth in vivo.Conclusion: OSW-1 is a promising anti-glioma chemotherapeutic drug owing to its anticancer effects via downregulation of the PI3K/AKT signaling pathway. However, OSW-1 still has a long way to go to become a real anti-glioma drug.

For centuries, cancer has been a lingering dark cloud floating on people’s heads. With rapid population growth and aging worldwide, cancer incidence and mortality are growing rapidly. Despite major advances in oncotherapy including surgery, radiation and chemical therapy, as well as immunotherapy and targeted therapy, cancer is expected be the leading cause of premature death in this century. Nowadays, natural compounds with potential anticancer effects have become an indispensable natural treasure for discovering clinically useful agents and made remarkable achievements in cancer chemotherapy. In this regards, OSW-1, which was isolated from the bulbs of Ornithogalum saundersiae in 1992, has exhibited powerful anticancer activities in various cancers. However, after almost three decades, OSW-1 is still far from becoming a real anticancer agent for its anticancer mechanisms remain unclear. Therefore, in this review we summarize the available evidence on the anticancer effects and mechanisms of OSW-1 in vitro and in vivo, and some insights for researchers who are interested in OSW-1 as a potential anticancer drug. We conclude that OSW-1 is a potential candidate for anticancer drugs and deserves further study.

Abstract Background Glioma is a heterogeneous, invasive primary brain tumor with a wide range of patient survival and a lack of reliable prognostic biomarkers. Human telomerase reverse transcriptase (hTERT) has been reported in the presence of multiple transcripts in various tumor systems. The biological function and precise regulatory mechanisms of hTERT transcripts remain uncertain. Methods Alternative splicing of hTERT and telomerase activity were examined in 96 glioma specimens, including 38 glioblastomas (GBMs), 23 oligodendrogliomas (ODMs), and 35 oligoastrocytomas (OAMs). The correlation between telomerase activity or hTERT transcripts and patient clinical characteristics was investigated. We examined the regulation of alternative splicing of hTERT and telomerase activity by G-quadruplex stabilizer CX-5461 in GBM cells. The biological effects of CX-5461 on GBM cell lines, including inhibition of cell proliferation, effects on cell cycle/apoptosis, and telomere DNA damage were further explored. Results The β splicing was verified in human gliomas and hTERT+β was significantly correlated with higher telomerase activity, higher KPS, larger tumor size, and higher tumor grades. Meanwhile, glioma patients lacking hTERT+β expression or telomerase activity showed a significant survival benefit. Notably, CX-5461 altered hTERT splicing patterns, leading to an increase of hTERT-β transcript and a decrease of hTERT+β transcript expression, which inhibits telomerase activity. In addition, CX-5461 had cytotoxic effects on GBM cells and caused telomere DNA damage response, induced G2/M arrest and apoptosis. Conclusions The hTERT+β is verified to be correlated with clinical parameters in gliomas, and could serve as a prognostic marker or possibly therapeutic target for gliomas. CX-5461 can regulate the splicing pattern of hTERT, inhibit telomerase activity, and kill GBM cells.

In recent years, expanding application scenarios have imposed higher demands on the geometric design and performance of metallic structures. Additive manufacturing (AM) has become essential for producing complex, customised geometries. Metallic lattice materials, known for their periodic structural arrangements, offer lightweight solutions ideal for high-strength applications like aerospace. However, during long-term use, these structures are often subjected to cyclic loading, making fatigue resistance a critical property. The complexity of fatigue-related challenges necessitates thorough research to fully understand the fatigue behaviours of these materials. This paper adopts a standard research approach to explore fatigue issues, with a focus on AM metallic lattice materials. It reviews common manufacturing methods and post-processing techniques, with particular emphasis on the unique process-induced defects found in lattice structures. The study also delves into the fatigue behaviours influenced by specific configurations and loading conditions, categorises the factors impacting fatigue failure in lattice materials, and presents a comprehensive review of fatigue life prediction methods, derived from an enhanced understanding of the fatigue process and the development of progressive fatigue failure algorithms. Finally, the current research advancements and limitations are discussed to provide a clearer perspective on the fatigue challenges associated with AM metallic lattice materials.

Abstract Background Tuberculosis (TB) continues to pose a significant threat to global public health. Enhancing patient prognosis is essential for alleviating the disease burden. Objective This study aims to evaluate TB prognosis by incorporating treatment discontinuation into the assessment framework, expanding beyond mortality and drug resistance. Methods Seven feature selection methods and twelve machine learning algorithms were utilized to analyze admission test data from TB patients, identifying predictive features and building prognostic models. SHapley Additive exPlanations (SHAP) were applied to evaluate feature importance in top-performing models. Results Analysis of 1,086 TB cases showed that a K-Nearest Neighbor classifier with Mutual Information feature selection achieved an area under the receiver operation curve (AUC) of 0.87 (95% CI: 0.83–0.92). Key predictors of treatment failure included elevated levels of 5’-nucleotidase, uric acid, globulin, creatinine, cystatin C, and aspartate transaminase. SHAP analysis highlighted 5’-nucleotidase, uric acid, and globulin as having the most significant influence on predicting treatment discontinuation. Conclusion Our model provides valuable insights into TB outcomes based on initial patient tests, potentially guiding prevention and control strategies. Elevated biomarker levels before therapy are associated with increased risk of treatment discontinuation, indicating their potential as early warning indicators.

Abstract Background Hyperphenylalaninemia, a prevalent amino acid metabolism disorder, often results in cognitive impairment. Recent studies have identified a rare variant of this disorder caused by mutations in the DNAJC12 gene. The specific mechanisms by which DNAJC12 mutations lead to hyperphenylalaninemia and the lack of an animal model for study remain significant gaps in understanding. Purpose This study aims to elucidate the role of DNAJC12 in intellectual disability and explore the mechanisms by which DNAJC12 deficiency leads to hyperphenylalaninemia through developing a DNAJC12 gene knockout mouse model. Methods We thoroughly examined the clinical features and genetic mutations evident in two patients with biallelic mutations in the DNAJC12 gene. Based on the patient’s mutation locations, we determined the target site for the knockout utilizing CRISPR/Cas9 technology. To assess the impact of these mutations on DNAJC12 expression, we used quantitative real-time PCR and Western blotting techniques to measure mRNA and protein levels, respectively. The Morris water maze test was administered to evaluate the cognitive functions of the mice. Additionally, we utilized High-Performance Liquid Chromatography (HPLC) to measure serum aromatic amino acids and brain monoamines, facilitating an investigation into the metabolism of phenylalanine and tyrosine. Results We reported two patients with mutations in the DNAJC12 gene. Case 1 carried the mutations c.158-1G > A and c.262 C > T in the DNAJC12 gene. He presented with nocturnal eye closure, crying, and arching back in reverse tension before treatment, suggesting a neurotransmitter metabolism disorder. Case 2 carried the mutations c.473 C > G, and c.102 deletion in the DNAJC12 gene. He showed elevated blood phenylalanine levels, although further clinical details were not available. Based on the patients’ mutation locations, exons 2–4 of the DNAJC12 gene were targeted and eliminated. In our animal model experiments, DNAJC12 gene knockout mice exhibited a complete absence of DNAJC12 expression at both mRNA and protein levels. These knockout mice showed significant deficits in learning and memory performance as assessed by the Morris water maze test. Quantitative real-time PCR analysis indicated no significant differences in the levels of aromatic amino hydroxylases between knockout and wild-type mice. However, Western blot analysis revealed a substantial reduction in phenylalanine hydroxylase (PAH) protein levels in the liver of knockout mice, while tyrosine hydroxylase (TH) and tryptophan hydroxylase 2 (TPH2) expression remained unchanged. HPLC analysis demonstrated increased serum Phe concentrations and decreased levels of brain neurotransmitters in the knockout group. Conclusions We report two patients with four novel DNAJC12 mutations (c.158-1G > A, c.262 C > T, c.473 C > G, c.102delT), expanding the mutation spectrum. Based on the patients’ mutation location, we established the first DNAJC12 gene knockout mouse model. The knockout mice exhibit hyperphenylalaninemia, impaired cognitive function, and decreased monoamine neurotransmitters. DNAJC12 deficiency may contribute to the clinical phenotype via the PAH pathway, potentially at the post-transcriptional level.

Abstract The NLR family pyrin domain containing 3 (NLRP3) inflammasome in microglia is intimately linked to the pathogenesis of Alzheimer’s disease (AD). Although NLRP3 inflammasome activity is regulated by cellular metabolism, the underlying mechanism remains elusive. Here, we found that under the pathological conditions of AD, the activation of NLRP3 inflammasome in microglia is accompanied by increased glutamine metabolism. Suppression of glutaminase, the rate limiting enzyme in glutamine metabolism, attenuated the NLRP3 inflammasome activation both in the microglia of AD mice and cultured inflammatory microglia. Mechanistically, inhibiting glutaminase blocked the anaplerotic flux of glutamine to the tricarboxylic acid cycle and amino acid synthesis, down-regulated mTORC1 signaling by phosphorylating AMPK, which stimulated mitophagy and limited the accumulation of intracellular reactive oxygen species, ultimately prevented the activation of NLRP3 inflammasomes in activated microglia during AD. Taken together, our findings suggest that glutamine metabolism regulates the activation of NLRP3 inflammasome through mitophagy in microglia, thus providing a potential therapeutic target for AD treatment.

In the continuous cooling process, the growth of the equiaxed α-phase grains in near-α high-temperature titanium alloys is controlled by the diffusion of alloying elements. Establishing a specific connection between the cooling rate and the diffusion behaviour of alloying elements aids in the precise prediction of the evolution of equiaxed α-phase grain size. This study meticulously controlled the cooling rate during the two-phase region annealing treatment of the Ti65 alloy. Using EPMA technology, the diffusion behaviour of solute elements during cooling was accurately characterized. The study found that slowing the cooling rate promotes the coarsening of the lamellar secondary α-phase grains and the growth of the primary equiaxed α-phase grains. At higher annealing temperatures, the growth of equiaxed α-phase grains can occur at faster cooling rates, while coarse lamellar secondary α-phase grains can be retained at slower cooling rates. The diffusion behaviour of solute elements Al, Ta, Mo, and W between the α-phase and transformed β-phase matrix is significantly influenced by the cooling rate, thus they are considered as the controlling elements for the growth of the equiaxed α-phase grains. Based on the diffusion behaviours of these controlling elements, their single-element diffusion models were categorized and integrated for predicting the grain size of the equiaxed α-phase. The predictions from the revised diffusion model show an excellent agreement with the actual results, with an error margin of about 5%.

Summary: Biomedicine has seen significant advancements in the 21st century, with platelet-rich plasma (PRP) playing a crucial role in clinical practice. This blood derivative, enriched with platelet components, has shown great potential for promoting tissue repair and regeneration. Its wide range of applications and the presence of anti-inflammatory and growth-promoting factors make it a valuable tool in the field of biomedicine. The exploration of PRP in clinical settings has been gaining momentum. Despite its cost-effectiveness, safety, and therapeutic efficacy, the widespread clinical adoption of PRP has been hindered by the absence of consistent preparation standards and standardized treatment protocols. This article provides a comprehensive analysis of the clinical uses, physiological roles, molecular mechanisms, and preparation techniques of PRP in biomedicine. The aim is to offer a thorough understanding of the potential applications and benefits of PRP in medical practice.

Summary: Tuberculosis (TB) remains a leading cause of death globally, with nearly half of TB patients experiencing iron deficiency. The role of iron supplementation as an adjunct therapy remains controversial. This study examines the impact of iron deficiency on TB progression and immune function. We conducted a case-control study involving 808 pulmonary TB patients recruited from Changzhou Third People’s Hospital (2018–2022) to investigate the association between serum iron levels and TB severity. Additionally, we evaluated the relationship between baseline serum iron levels and pulmonary lesion characteristics during antituberculosis treatment using a cohort study of 89 patients. We observed that low serum iron was associated with more severe lung symptoms, decreased MAIT, Vδ2+, and Treg cell percentages, and increased interleukin-1β (IL-1β) and IL-7 levels. Findings suggest that iron deficiency may exacerbate lung lesions by altering T cell subsets and cytokine profiles.

Ginseng has been commonly used as a traditional Chinese medicine in Asian countries for thousands of years. Ginsenosides are the main pharmacologically active ingredients isolated from ginseng and have neuroprotective effects in the treatment of neurodegenerative disorders, such as Parkinson's disease (PD) and Alzheimer's disease (AD). To summarise and investigate the protective roles of ginsenosides and their underlying mechanisms in PD and AD, we used ‘‘Ginsenoside”, ‘‘Parkinson's disease”, ‘‘Alzheimer's disease”, ‘‘anti-inflammatory”, ‘‘antioxidant”, and ‘‘apoptosis” as keywords to search and extract relevant literature information from scientific databases such as Elsevier, PubMed, and Google Scholar databases. In particular, we used network pharmacology to identify the potential targets of ginsenosides Rg1 and Rb1 in PD and AD. By analysing the existing research advances and network pharmacology results, we found that the neuroprotective effects of ginsenosides, primarily mediated through anti-inflammation, anti-apoptosis and anti-oxidative stress, etc, may be associated with the PI3K/Akt, BDNF/TrkB, MAPKs, NF-κB, Nrf2 and Wnt/β-catenin signalling pathways. This review systematically summarises the different roles and mechanisms of ginsenosides Rg1, Rb1, and rare ginsenosides in PD and AD and provides new strategies for the treatment of neurodegenerative disorders. Network pharmacology provides a new research paradigm for the treatment of PD and AD using Rg1 and Rb1.

Objectives SLE is a multifaceted autoimmune disorder with a complex pathogenesis involving genetic, environmental and hormonal factors, which converge on immune dysregulation. The T cell receptor (TCR) repertoire’s role in SLE has garnered significant interest due to its potential in both diagnostics and therapeutics. Our study aimed to delineate the variances in the TCRβ repertoire between patients with SLE and healthy individuals, correlating these differences with the severity and subtypes of SLE.Methods We conducted an analysis of blood samples from 50 treatment-naive patients with SLE and 50 healthy donors, employing RNA extraction, high-throughput sequencing and subsequent bioinformatics analysis.Results Our findings revealed significant alterations in TRBV and TRBJ gene usage frequencies, indicative of a skewed TCR repertoire in patients with SLE. Notably, nine hub TRBV genes were identified as potential biomarkers for SLE with high diagnostic accuracy. Furthermore, we observed a reduction in TCR diversity, characterised by a lower diversity 50 value and increased clonal expansion, which correlated with disease severity.Conclusions The TCRβ repertoire is significantly altered in SLE, with potential implications for diagnostics and therapeutics. The identified hub genes may serve as novel biomarkers for SLE, and the findings contribute to the understanding of the immunopathogenesis of the disease.

Background Anti-programmed cell death 1 (PD-1) antibody combined with chemotherapy simultaneously is regarded as the standard treatment for patients with advanced non-small cell lung cancer (NSCLC) by current clinical guidelines. Different immune statuses induced by chemotherapy considerably affect the synergistic effects of the chemo-anti-PD-1 combination. Therefore, it is necessary to determine the optimal timing of combination treatment administration.Methods The dynamic immune status induced by chemotherapy was observed in paired peripheral blood samples of patients with NSCLC using flow cytometry and RNA sequencing. Ex vivo studies and metastatic lung carcinoma mouse models were used to evaluate immune activity and explore the optimal combination timing. A multicenter prospective clinical study of 170 patients with advanced NSCLC was performed to assess clinical responses, and systemic immunity was assessed using omics approaches.Results PD-1 expression on CD8+ T cells was downregulated on day 1 (D1) and D2, but recovered on D3 after chemotherapy administration, which is regulated by the calcium influx-P65 signaling pathway. Programmed cell death 1 ligand 1 expression in myeloid-derived suppressor cells was markedly reduced on D3. RNA sequencing analysis showed that T-cell function began to gradually recover on D3 rather than on D1. In addition, ex vivo and in vivo studies have shown that anti-PD-1 treatment on D3 after chemotherapy may enhance the antitumor response and considerably inhibit tumor growth. Finally, in clinical practice, a 3-day-delay sequential combination enhanced the objective response rate (ORR, 68%) and disease control rate (DCR, 98%) compared with the simultaneous combination (ORR=37%; DCR=81%), and prolonged progression-free survival to a greater extent than the simultaneous combination. The new T-cell receptor clones were effectively expanded, and CD8+ T-cell activity was similarly recovered.Conclusions A 3-day-delay sequential combination might increase antitumor responses and clinical benefits compared with the simultaneous combination.

Appropriate nitrogen (N) fertilization and planting density management are critical for efficient production of grain maize (Zea mays L.) and for environmental protection. However, the optimal N fertilization and planting density is still not established for forage maize that is cultivated to promote its vegetative growth and utilized for the above-ground vegetative mass. A two-year field experiment was conducted in the rainfed semiarid region of the Chinese Loess Plateau during the 2021 and 2022 growing seasons. The effects of N application rates and planting densities on the dry matter yields and the water- and N-use efficiencies of forage maize were studied. The experiment includes four N application rates (0, 90, 180, and 270 kg ha−1) and three plant densities (70000, 90000, and 110000 plants ha−1), covering the conventional practices of local farmers. The treatments were organized in a randomized complete block design with four replications. Averaged over the three plant densities, N application rate of 180 kg ha−1 resulted in the maximum average aboveground dry matter yield (18.6 t ha−1), crop N accumulation (228.5 kg ha−1), dry matter water productivity (51.9 kg ha−1 mm−1), and dry matter precipitation productivity (62.9 kg ha−1 mm−1) over the two years. Moreover, increasing N application rates significantly increased the soil nitrate-N accumulation (0–200 cm) but reduced the partial factor productivity of applied N fertilizer. Across the three plant densities, the two-year average soil nitrate-N accumulation was 12.6, 32.1, and 75.7 % higher with 90, 180, and 270 kg N ha−1 compared to no N treatment, respectively. The highest soil nitrate accumulation under 270 kg ha−1 N application rate in 2021 (229.5 kg ha−1) and in 2022 (329.7 kg ha−1) may cause severe nitrate leaching loss and potential soil water contamination, driven by intensive rainfalls. Averaged over the four N rates, planting density of 110000 plants ha−1 increased the crop N accumulation and PFP by 21.2 % and 15.8 % in 2021, compared to 70000 plants ha−1, respectively. The interaction of N application and planting density significantly affected the aboveground dry matter yield, crop water consumption, dry matter precipitation productivity, and crop N accumulation in 2021, but the effect was non-significant in 2022. Based on these findings, application of 180 kg N ha−1 and planting density of 110000 plants ha−1 are suggested as an efficient management strategy for improving productivity of forage maize and soil water and N resources utilization in the arid region of the Loess Plateau and similar areas.

Abstract Background Ciprofol is a promising sedative. This study aims to explore the median effective dose (ED50) of ciprofol in inhibiting responses to fiberoptic bronchoscopy in patients with pulmonary tuberculosis (PTB) of different genders and ages when combined with 0.15 μg/kg sufentanil, and to evaluate its efficacy and safety, providing a reference for the rational use of ciprofol in clinical practice. Methods PTB patients who underwent bronchoscopy examination and treatment at The Third People’s Hospital of Changzhou between May 2023 and June 2023 were selected and divided into four groups using a stratified random method. All patients received intravenous injection of 0.15 μg/kg sufentanil followed by injection of the test dose of ciprofol according to Dixon’s up-and-down method. The initial dose of ciprofol in all four groups was 0.4 mg/kg, with an adjacent ratio of 1:1.1. The next patient received a 10% increase in the dose of ciprofol if the previous patient in the same group experienced positive reactions such as choking cough, frowning, and body movements during the endoscopy. Otherwise, it was judged as a negative reaction, and the next patient received a 10% decrease in the dose of ciprofol. The transition from a positive reaction to a negative reaction was defined as a turning point, and the study of the group was terminated when seven turning points occurred. Hemodynamic parameters, oxygen saturation and adverse reactions were recorded at different time points in all groups. The Probit regression analysis method was used to calculate the ED50 of ciprofol in the four groups and compare between the groups. Results The ED50 of ciprofol combined with 0.15 μg/kg sufentanil for bronchoscopy in the four groups were 0.465 mg/kg, 0.433 mg/kg, 0.420 mg/kg and 0.396 mg/kg, respectively. Conclusion The ED50 of ciprofol used for fiberoptic bronchoscopy varied among PTB patients of different genders and ages. Trial registration The Chinese Clinical Trial Registry, ChiCTR2300071508, Registered on 17 May 2023.

With the increasing frequency of floods, in-depth flood event analyses are essential for effective disaster relief and prevention. Satellite-based flood event datasets have become the primary data source for flood event analyses instead of limited disaster maps due to their enhanced availability. Nevertheless, despite the vast amount of available remote sensing images, existing flood event datasets continue to pose significant challenges in flood event analyses due to the uneven geographical distribution of data, the scarcity of time series data, and the limited availability of flood-related semantic information. There has been a surge in acceptance of deep learning models for flood event analyses, but some existing flood datasets do not align well with model training, and distinguishing flooded areas has proven difficult with limited data modalities and semantic information. Moreover, efficient retrieval and pre-screening of flood-related imagery from vast satellite data impose notable obstacles, particularly within large-scale analyses. To address these issues, we propose a Multimodal Flood Event Dataset (MFED) for deep-learning-based flood event analyses and data retrieval. It consists of 18 years of multi-source remote sensing imagery and heterogeneous textual information covering flood-prone areas worldwide. Incorporating optical and radar imagery can exploit the correlation and complementarity between distinct image modalities to capture the pixel features in flood imagery. It is worth noting that text modality data, including auxiliary hydrological information extracted from the Global Flood Database and text information refined from online news records, can also offer a semantic supplement to the images for flood event retrieval and analysis. To verify the applicability of the MFED in deep learning models, we carried out experiments with different models using a single modality and different combinations of modalities, which fully verified the effectiveness of the dataset. Furthermore, we also verify the efficiency of the MFED in comparative experiments with existing multimodal datasets and diverse neural network structures.

ObjectiveThe purpose of this study was to observe the relationship between objectively measured levels of physical activity and cognitive impairment (CI) in the presence or absence of diabetes in middle-aged and elderly hemodialysis patients.MethodsIn this multicenter cross-sectional study, 339 clinically stable hemodialysis patients (210 males; mean age: 67.38 ± 8.07 years) aged ≥55 years were included from 7 dialysis units in Shanghai, China. The Chinese version of the Modified Mini-Mental State Examination (MMSE) was used to assess the CI. The duration of physical activity at different intensities, including moderate to vigorous physical activity (MVPA) as well as light physical activity (LPA), was measured using a triaxial accelerometer (ActiGraph GT3X+, Pensacola, FL, USA). Logistic regression and multiple linear regression were used for analyses.ResultsThe prevalence of CI was higher in hemodialysis patients with comorbid diabetes (24.3%). In diabetic patients, MVPA (increase per 10 min/day) was negatively associated with CI after adjusting for covariates [(OR = 0.89, 95%CI = 0.79–0.99), p = 0.042]. However, no significant association between physical activity and CI was found in non-diabetic hemodialysis patients. Further analyses revealed that MVPA was positively associated with temporal orientation, attention and calculation and recall in diabetic hemodialysis patients.ConclusionPhysical activity was associated with CI in diabetic hemodialysis patients rather than the non-diabetes group. This study is important for early differential diagnosis of CI and improvement of cognitive status in hemodialysis patients.

BackgroundEsketamine, the first Food and Drug Administration-approved fast-acting antidepressant, has limited use because of its addictive properties. Although the combination of dextromethorphan and bupropion partially addresses the limitations of esketamine, concerns remain regarding neurologic side effects related to dextromethorphan metabolites, and seizure risks associated with high-dose bupropion. SAL0114, a novel formulation combining deuterated dextromethorphan (in which hydrogen atoms are replaced with deuterium) with bupropion, seeks to enhance dextromethorphan stability through deuteration of its metabolic sites. This approach is expected to increase antidepressant efficacy, reduce metabolite-induced safety issues, and allow for lower bupropion dosages.MethodsRadioligand competition binding assays were used to evaluate the impact of deuterium substitution on the in vitro activity of dextromethorphan and its metabolite, dextrorphan. In vitro hepatic microsomal stability and in vivo mouse pharmacokinetic assays were performed to assess the effects of deuteration on dextromethorphan stability. Two mouse models of behavioral despair were used to determine the antidepressant and synergistic effects of deuterated dextromethorphan and bupropion. Additionally, a reserpine-induced hypothermia rat model and an ammonia-induced cough mouse model were used to assess the in vivo effects from a pathological perspective.ResultsDeuterated dextromethorphan maintained the same in vitro activity as dextromethorphan while exhibiting twice the metabolic stability both in vitro and in vivo. Combination with bupropion further improved its in vivo stability, increasing the exposure by 2.4 times. The combination demonstrated efficacy and synergistic effects in all tested animal models, showing superior efficacy compared with the dextromethorphan-bupropion combination.ConclusionDeuteration improved dextromethorphan metabolic stability without altering its in vitro activity. Bupropion enhanced this stability and synergistically boosted the antidepressant effect by increasing deuterated dextromethorphan exposure in vivo. This enhanced metabolic stability suggests a reduction in dextromethorphan metabolites associated with clinical neurological side effects. Consequently, SAL0114 is hypothesized to offer improved efficacy and safety compared with the non-deuterated combination, potentially allowing for lower bupropion dosages. Further clinical studies are required to confirm these preclinical findings.

Abstract The application of blockchain technology holds significant potential for improving efficiency, resilience, and transparency within the Fisheries Supply Chain (FSC). This study addresses the critical barriers hindering the adoption of blockchain technology (BT) in the Chinese FSC, recognizing the unique challenges posed by its intricacies. Through a comprehensive literature review, fourteen Critical Barrier Factors (CBFs) were identified, and a grey Delphi method was employed to distill this set. Five pivotal CBFs emerged, including "Regulatory Compliance," "Cost of Implementation," and "Complex Supply Chain Network". A subsequent grey Decision-Making Trial and Evaluation Laboratory (DEMATEL) analysis revealed the causal relationships among these factors, categorizing them into effect and cause groups. "Regulatory Compliance," "Cost of Implementation," and "Complex Supply Chain Network" were identified as primary influencing factors demanding attention for effective BT integration in the FSC. The findings serve as a valuable resource for FSC stakeholders, assisting in prioritizing efforts to address these barriers. The discerned causal relationships provide guidance for managers in optimizing resource allocation. Ultimately, this research advocates for the adoption of blockchain technology in the fisheries supply chain to enhance overall performance and operational efficiency.

By elucidating the progressive relationship from the rolling stress state to the activation of slip systems and then to lattice rotation, this paper clarifies the influence mechanism of strain paths on the evolution of α-phase texture in near-α titanium alloys. The distinct rolling textures obtained further provide a robust foundation for investigating whether the competition between different α-phase textures changes with varying cooling rates during β→α phase transformation. In this study, initial Ti65 alloy sheets underwent rolling using three different strain paths (UDR/CDR/MSCR), resulting in the production of three foils characterized by distinct textures. Compressive stress during rolling promotes the activation of basal and pyramidal-II slipping, leading to the formation of a TD-split basal texture in α-phase. Tensile stress during rolling promotes the activation of prismatic slipping, ultimately resulting in a [10 1‾ 0]//RD (in the case of UDR) or [21‾1‾ 0]//RD (in the case of CDR) texture. Variations in stress states along different strain paths led to differences in the global Schmid factor distribution of α-phase for slip systems, ultimately resulting in diverse texture evolution. Subsequently, foil samples underwent two-phase region heat treatments, followed by furnace cooling and air cooling. After furnace cooling, the strength of the transverse texture increased in each type of foils. Conversely, after air cooling, no specific α-phase texture consistently exhibited an increasing trend in the three foils.

The comprehensive detection and identification of active ingredients in complex matrices is a crucial challenge. Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) is the most prominent analytical platform for the exploration of novel active compounds from complex matrices. However, the LC-HRMS-based analysis workflow suffers from several bottleneck issues, such as trace content of target compounds, limited acquisition for fragment information, and uncertainty in interpreting relevant MS2 spectra. Lycibarbarspermidines are vital antioxidant active ingredients in Lycii Fructus, while the reported structures are merely focused on dicaffeoylspermidines due to their low content. To comprehensively detect the new structures of lycibarbarspermidine derivatives, a “depict” strategy was developed in this study. First, potential new lycibarbarspermidine derivatives were designed according to the biosynthetic pathway, and a comprehensive database was established, which enlarged the coverage of lycibarbarspermidine derivatives. Second, the polarity-oriented sample preparation of potential new compounds increased the concentration of the target compounds. Third, the construction of the molecular network based on the fragmentation pathway of lycibarbarspermidine derivatives broadened the comprehensiveness of identification. Finally, the weak response signals were captured by data-dependent scanning (DDA) followed by parallel reaction monitoring (PRM), and the efficiency of acquiring MS2 fragment ions of target compounds was significantly improved. Based on the integrated strategy above, 210 lycibarbarspermidine derivatives were detected and identified from Lycii Fructus, and in particular, 170 potential new compounds were structurally characterized. The integrated strategy improved the sensitivity of detection and the coverage of low-response components, and it is expected to be a promising pipeline for discovering new compounds.

Optimizing plant density and nutrient availability is essential for sustaining high forage yields and promoting environmental health, especially in semi-arid regions with sandy soil. Nonetheless, the mechanisms by which stoichiometric features govern nutrient utilization and forage output are still unidentified. We executed a two-year field experiment, integrating six nitrogen rates (0 (N0), 104 (N1), 138 (N2), 173 (N3), 207 (N4), and 242 (N5) kg N ha−1) and four planting densities (3 (D1), 3.5 (D2), 4 (D3), and 4.5 (D4) million plants ha−1). The C, N, and P contents, along with the C:N:P stoichiometry of different oat organs (leaf, stem, and root) and soil, were determined. It was found that the growth of oats in this area was limited by soil N. The pasture biomass increased nonlinearly with increasing planting density and N rate, and the maximum thresholds for C, N, and P uptake were 389.43 g kg−1, 11.19 g kg−1, and 3.10 g kg−1 at N3, respectively. The maximum thresholds for C, N, and P uptake were 356.45, 9.47, and 2.78 g kg−1 at D3, respectively, with an optimal biomass of 9221.74 kg ha−1; at a planting density of D3, the maximum thresholds for C, N, and P uptake were 329.39, 8.54, and 2.47 g kg−1, with an optimal biomass of 6276.10 kg ha−1. SEM showed that N rate and density increases significantly changed the ecological balance of the soil. The C:N and C:P ratios in oat leaves tend towards lower values, while the N:P ratio tends towards higher values; in contrast, the C:N and C:P ratios in oat stems tend towards higher values, and the N:P ratio tends towards lower values. The nutrient use strategy maintains the stoichiometric balance at the organ level, which in turn improves the accumulation of oat biomass. The best NUE was obtained at an N rate and density of N3D3 with a 144% biomass increase as compared to N0D2. This study provides new insights into nutrient allocation, usage strategies, and the stability of oats in actual sandy land production.

Personalized news recommendations focus on providing users with news that fits their interests and alleviates their information overload. User preference modeling is crucial for achieving personalized news recommendations, and user preferences are usually expressed as long-term and short-term user preferences. Existing news recommendation methods have difficulty accurately matching user preferences with candidate news, which is the main challenge plaguing the news recommendation field. For this purpose, we propose a novel news recommendation method based on candidate-aware long- and short-term preference modeling, named NRCLS. The method contains: (1) a Candidate-Enhanced graph attention network, which learns high-order structural information in graphs, mines the potential relationship between long-term user preferences and candidate news; and (2) a candidate-aware attention network that incorporates news subtopics. In this network, the dynamic impact of candidate news on short-term user preferences is considered. Results on real-world datasets demonstrate the effectiveness of our proposed method in improving the performance of news recommendations. We have also conducted several ablation studies that demonstrate the effectiveness of the core module in NRCLS.