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Sora Mun,1 Seungyeon Lee,2 Yeeun Yun,3 Eun-Jeong Joo,4,5 Hee-Gyoo Kang,1– 3 Jiyeong Lee1,3 1Department of Biomedical Laboratory Science, College of Health Sciences, Eulji University, Gyeonggi, Republic of Korea; 2Department of Senior Healthcare, Graduate School, Eulji University, Gyeonggi, Republic of Korea; 3Department of Biomedical Laboratory Science, Graduate School, Eulji University, Gyeonggi, Republic of Korea; 4Department of Neuropsychiatry, School of Medicine, Eulji University, Daejeon, Republic of Korea; 5Department of Psychiatry, Uijeongbu Eulji Medical Center, Eulji University, Gyeonggi, Republic of KoreaCorrespondence: Hee-Gyoo Kang, Department of Biomedical Laboratory Science, College of Health Sciences, Eulji University, 553 Sanseong-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of Korea, Tel +82-31-740-7315, Email kanghg@eulji.ac.kr Jiyeong Lee, Department of Biomedical Laboratory Science, College of Health Sciences, Eulji University, 712 Dongil-ro, Uijeongbu-si, Gyeonggi-do, Republic of Korea, Tel +82-31-951-3862, Email leejiyeong@eulji.ac.krPurpose: Depressive mood is a major psychiatric symptom that causes serious disturbances in daily life. Unlike physical symptoms, psychiatric symptoms are more difficult to evaluate objectively. Therefore, we aimed to discover biomarkers that reflect changes in serum protein metabolism during a clinical depressive mood.Methods: Serum protein profiling was conducted in participants who were not experiencing a current depressive episode (healthy individuals and patients in remission). Serum proteins were identified and quantified using liquid chromatography–tandem mass spectrometry. Differentially expressed proteins with a p-value < 0.05 were selected, and candidate biomarkers were verified using multiple reaction monitoring analysis for absolute quantification.Results: Apolipoprotein A-IV levels were lower in the group with a current episode of depression than in the remission and healthy control groups. Further, fibronectin levels were also lower in the group with a current episode of depression than in the healthy control group but not in the remission group.Conclusion: We found that apolipoprotein A-IV-mediated inflammation is involved in clinical depressive moods, possibly by inducing neurological changes in the brain. Therefore, apolipoprotein A-IV and fibronectin levels may be explored as potentially novel biomarkers for detecting a current episode of depression.Keywords: biomarkers, depression, liquid chromatography–tandem mass spectrometry, inflammation, neuroinflammation, serum proteomics

Xin Jing,&ast; Yuhui Yun,&ast; Xiang Ji, Ende Yang, Pei Li Department of Thoracic Surgery, Tangdu Hospital, The Fourth Military Medical University, Xi’an, Shaanxi, 710038, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Pei Li; Ende Yang, Department of Thoracic Surgery, Tangdu Hospital, The Fourth Military Medical University, Xi’an, Shaanxi, 710038, People’s Republic of China, Email yanglinglipei@163.com; endeyangfmmu@163.comBackground: Cancer development and tumor immune microenvironment remodeling are closely linked to pyroptosis and inflammasome activation. However, little information is available in single nucleotide polymorphisms (SNPs) in pyroptosis and inflammasome-related genes in patients with lung cancer. This study aims to evaluate the associations between pyroptosis-related gene (NLRP3, NLRC4, and NLRP7) polymorphisms and the risk of lung cancer.Methods: The MassARRAY platform was used to genotype six SNPs of the NLRP3, NLRC4, and NLRP7 genes in 660 lung cancer cases and 660 controls.Results: Individuals with rs35829419-A, rs385076-C, and rs775882-T alleles exhibited a higher risk of lung cancer (p < 0.01), while rs212704-T appears protective (p = 0.006). The rs35829419-AA, rs385076-TC/CC, and rs775882-CT/TT genotypes were associated with various degrees of elevated risk of lung cancer (p< 0.02), whereas rs212704-TT was associated with a reduced risk of the disease (p=0.014). Genetic models analysis showed that rs35829419, rs385076, and rs775882 was associated with an increased risk of lung cancer, while rs212704 was related to a reduced risk in all three models (p < 0.05). The four SNPs remained significant in smoker and nonsmoker subgroups (p < 0.05). However, rs35829419 was correlated with risk of adenocarcinoma and small cell lung cancer, and rs212704 was only protective for squamous cell carcinoma. The rs385076 and rs775882 were associated with all three pathological types (p < 0.01).Conclusion: Besides providing candidate markers for identification of high-risk populations and early prevention of the disease, our research also provided new insight into anti-tumor strategies targeting inflammasomes and pyroptosis.Keywords: lung cancer, single nucleotide polymorphisms, pyroptosis, inflammasome, case–control study

Yuhui Yun,1,&ast; Yun Wang,2,&ast; Ende Yang,1 Xin Jing1 1Department of Thoracic Surgery, Tangdu Hospital, The Fourth Military Medical University, Xi’an, Shaanxi, 710038, People’s Republic of China; 2Department of Medical Oncology, Tangdu Hospital, The Fourth Military Medical University, Xi’an, Shaanxi, 710038, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Xin Jing; Ende Yang, Email jingxintd2014@163.com; endeyangfmmu@163.comBackground: Cuproptosis is a novel copper-dependent cell death, and the copper level was increased in lung cancer patients. However, few studies evaluated the association between single-nucleotide polymorphisms (SNPs) in cuproptosis-related genes and lung cancer risk.Methods: Six SNPs of the SLC31A1, FDX1 and ATP7B genes were genotyped in a case–control cohort including 650 lung cancer cases and 650 controls using the MassARRAY platform.Results: The minor alleles of SLC31A1-rs10981694 and FDX1-rs10488764 were associated with an increased risk of lung cancer (rs10981694: OR=1.455, 95% CI: 1.201– 1.763, p< 0.001; rs10488764: OR=1.483, 95% CI: 1.244– 1.768, p< 0.001). In contrast, the minor alleles of rs9535826 and rs9535828 in ATP7B were related to a decreased risk of the disease (rs9535826: OR=0.714, 95% CI: 0.608– 0.838 p< 0.001; rs9535828: OR=0.679, 95% CI: 0.579– 0.796, p< 0.001). The frequencies of rs10981694-TG/GG and rs10488764-GA/AA genotypes were significantly higher in lung cancer cases than that in controls, making them risk genotypes for the disease (p < 0.001); while the rs9535826-TG/GG and rs9535828-GA/AA genotypes were protective genotypes and associated with a reduced risk of the disease (p< 0.001). Genetic model evaluation revealed that SLC31A1-rs10981694 and FDX1-rs10488764 were associated with a growing risk of lung cancer in dominant, recessive and log-additive models (p< 0.001). Moreover, rs9535826 and rs9535828 in ATP7B were related to a declining risk of the disease in three genetic models (p< 0.001). In addition, stratification analysis showed that FDX1-rs10488764 was risk variant for lung cancer in both smokers and nonsmokers, and was associated with risk of each pathological type of lung cancer (p< 0.008).Conclusion: The results shed new light on the correlation between cuproptosis-related genes and risk of lung cancer.Keywords: lung cancer, single-nucleotide polymorphisms, SNPs, solute carrier family 31 member 1, SLC31A1, ferredoxin 1, FDX1, ATPase copper transporting beta, ATP7B

Abstract A first-order random coefficient integer-valued autoregressive model based on the negative binomial thinning operator under r states random environment is introduced. This paper derives numerical characteristics of the proposed model, establishes Yule–Walker estimators of model parameters, and discusses the strong consistency of the obtained estimators. Finally, a simulation is carried out to verify the feasibility of parameter estimation.

Introduction The transition to primary school is a significant milestone for children. Transition periods can offer new opportunities to build skills, relationships, and experiences that strengthen self-efficacy. In Singapore, parents play an important role in supporting transition as preschools and primary schools operate independently. Occupational therapists are involved in supporting children with special needs in transitions. Objective Focusing on the transition period of getting children ready for primary school, the objectives are (i) to learn about the strategies that parents used for the purpose of transition and understand the intentions behind what they do and (ii) to compare the transition practices and perceived school readiness between parents of children with and without special needs. Method A longitudinal study involving 48 parents was conducted over 12 months. Parents completed a survey at the start and end of the year to detect changes from baseline, and semi-structured interviews every two months to gather their subjective experiences and track their child’s readiness for transition. The surveys and interviews were conducted on a mobile instant messaging platform. Coding of responses was guided by school readiness domains identified in earlier studies and Occupational Therapy Practice Framework’s approaches to intervention. Results Most parents focused on establishing and maintaining new self-help and academic skills across the year while few were “modifying” or “preventing”. Increasing trends in child readiness were noted for both children with and without special needs. Conclusion In family-centred practice, it is important to recognise parents’ expertise and resources.

Abstract The method of robust approach is applied to estimate drift function and diffusion function of diffusion processes with discrete-time observations. The proposed method combines the ideas of local linear regression technique and maximum likelihood type estimation technique, so the advantages of local linear estimators persist and overcome the disadvantages of least-squares estimator. Moreover, a variable bandwidth instead of a constant bandwidth is considered in the local maximum likelihood type estimators. The consistency and asymptotic normality of the local maximum likelihood type estimators for drift and diffusion functions are developed under some given conditions. We perform a simulation study to evaluate the robust performances of the proposed estimators.

Introduction: The Copenhagen Burnout Inventory (CBI) is a recent burnout measure with a focus on fatigue and exhaustion. It has three factors: personal burnout, work-related burnout, and client-related burnout. This study aimed to translate the CBI into the Malay language and to validate the translated version among a group of medical students. Methods: The forward–backward translation was performed as per standard guidelines. The Malay version of CBI (CBI-M) was distributed to 32 medical students to assess face validity and later to 452 medical students to assess construct validity. The data analysis was performed by Microsoft Excel, SPSS and AMOS. Results: The face validity index of CBI-M was more than 0.8. The three factors of CBI-M achieved good levels of goodness-of-fit indices (Cmin/df = 2.99, RMSEA = 0.066, GFI = 0.906, CFI = 0.938, NFI = 0.910, TLI = 0.925). The composite reliability values of the three factors ranged from 0.84 to 0.87. The Cronbach's alpha values of the three factors ranged from 0.83 to 0.87. Conclusions: This study supports the face and construct validity of the CBI-M with a high internal consistency.

Qunlian Huang,1 Xiaoyan Zhong,1 Ye Yun,1 Bin Yu,2 Yilan Huang1 1Department of Pharmacy, The Affiliated Hospital of Southwest Medical University, 2Department of Clinical Pharmacy, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan Province, People’s Republic of China Objective: The aim of this meta-analysis was to evaluate the efficacy and safety of levomilnacipran extended-release (ER) in the treatment of major depressive disorder (MDD). Methods: Randomized controlled trials were searched by electronic databases. Unpublished data were also searched by the relevant websites. Weighted mean difference (WMD) and risk ratio (RR) with 95% confidence interval (CI) were calculated and pooled using fixed-effects model or random-effects model. Results: Five randomized placebo-controlled trials including 2,637 patients were analyzed. Compared with placebo, levomilnacipran ER had a greater reduction in the Montgomery–Åsberg Depression Rating Scale (MADRS) total score and Sheehan Disability Scale (SDS) total score (MADRS: WMD -3.49 [95% CI -4.28, -2.70; P

We report a spin-rectification effect in a spin-valve structure consisting of ferroelectric croconic acid (C5H2O5) sandwiched between ferromagnetic electrodes La0.7Sr0.3MnO3 and Co, which can be switched between a high-resistance (off) and a low-resistance (on) state by a poling voltage. In the off state, the magnetoresistance (MR) sign reverses with the measurement voltage with a 0.1-V offset, suggesting a spin-rectification behavior, while in the on state the MR remains negative. These observations can be understood in terms of electrically controlled interfacial energy-band alignment either from the electrostatic effect or from the interfacial redox process. The observed spin-rectification effect suggests the possibility of diodelike devices for spin-polarized current.

Abstract: Dehydrogenation of propane to propene is one of the important reactions for the production of higher-value chemical intermediates. In the commercial processes, platinum- or chromium oxide-based catalysts have been used for catalytic propane dehydrogenation. Herein, we first report that bulk tungsten oxide can serve as the catalyst for propane dehydrogenation. Tungsten oxide is activated by hydrogen pretreatment and/or co-feeding of hydrogen. Its catalytic activity strongly depends on hydrogen pretreatment time and partial pressure of hydrogen in the feed gas. The activation of tungsten oxide by hydrogen is attributed to reduction of the metal oxide and presence of multivalent oxidation states. Comparison of the catalytic performance of partially reduced WO3−xto other highly active metal oxides shows that WO3−xexhibits superior catalytic activity and selectivity than Cr2O3and Ga2O3. The findings of this work provide the possibility for activation of metal oxides for catalytic reactions and the opportunity for the development of new type of catalytic systems utilizing partially reduced metal oxides. Graphical Abstract: [Figure not available: see fulltext.]

The parametric operations on R 2 are the generalization of Zadeh’s extended algebraic operations on R. We calculated the parametric operations for two 2-dimensional generalized triangular fuzzy sets, for two 2-dimensional quadratic fuzzy numbers, and for two 2-dimensional trapezoidal fuzzy sets. We also calculated the parametric operations between 2-dimensional triangular fuzzy number and 2-dimensional trapezoidal fuzzy sets. The parametric operations on R 3 are the generalization of Zadeh’s extended algebraic operations on R 2, and thus become the generalization of Zadeh’s extended algebraic operations on R. In this paper, we calculate the parametric operations between 3-dimensional triangular fuzzy number and trapezoidal fuzzy set. [ABSTRACT FROM AUTHOR]

Abstract. Recent advancements in the field of medical artificial intelligence (AI) have led to the widespread adoption of foundational and large language models. This review paper explores their applications within medical AI, introducing a novel classification framework that categorizes them as disease-specific, general-domain, and multi-modal models. The paper also addresses key challenges such as data acquisition and augmentation, including issues related to data volume, annotation, multi-modal fusion, and privacy concerns. Additionally, it discusses the evaluation, validation, limitations, and regulation of medical AI models, emphasizing their transformative potential in healthcare. The importance of continuous improvement, data security, standardized evaluations, and collaborative approaches is highlighted to ensure the responsible and effective integration of AI into clinical applications.

Introduction: Treating orthopedic implant-associated infections, especially those caused by Staphylococcus aureus (S. aureus), remains a significant challenge. S. aureus has the ability to invade host cells, enabling it to evade both antibiotics and immune responses during infection, which may result in clinical treatment failures. Therefore, it is critical to identify the host cell type of implant-associated intracellular S. aureus infections and to develop a strategy for highly targeted delivery of antibiotics to the host cells. Objectives: Introduced an antibody-antibiotic conjugate (AAC) for the targeted elimination of intracellular S. aureus. Methods: The AAC comprises of a human monoclonal antibody (M0662) directly recognizes the surface antigen of S. aureus, Staphylococcus protein A, which is conjugated with vancomycin through cathepsin-sensitive linkers that are cleavable in the proteolytic environment of the intracellular phagolysosome. AAC, vancomycin and vancomycin combined with AAC were used in vitro intracellular infection and mice implant infection models. We then tested the effect of AAC in vivo and in vivo by fluorescence imaging, in vivo imaging, bacterial quantitative analysis and bacterial biofilm imaging. Results: In vitro, it was observed that AAC captured extracellular S. aureus and co-entered the cells, and subsequently released vancomycin to induce rapid elimination of intracellular S. aureus. In the implant infection model, AAC significantly improved the bactericidal effect of vancomycin. Scanning electron microscopy showed that the application of AAC effectively blocked the formation of bacterial biofilm. Further histochemical and micro-CT analysis showed AAC significantly reduced the level of bone marrow density (BMD) and bone volume fraction (BV/TV) reduction caused by bacterial infection in the distal femur of mice compared to vancomycin treatment alone. Conclusions: The application of AAC in an implant infection model showed that it significantly improved the bactericidal effects of vancomycin and effectively blocked the formation of bacterial biofilms, without apparent toxicity to the host.

Orthopedic and dental implantations under bacterial infection microenvironment face significant challenges in achieving high-quality bone-implant integration. Designing implant coatings that incorporate both immune defense and anti-inflammation is difficult in conventional single-functional coatings. We introduce a multifunctional nanointerface using a zinc finger-inspired peptide-metal-phenolic nanocoating, designed to enhance implant osseointegration under such conditions. Abaloparatide (ABL), a second-generation anabolic drug for treating osteoporosis, can be integrated into the design of a zinc-phenolic network constructed on the implant surface (ABL@ZnTA). Importantly, the phenolic-coordinated Zn2+ ions in ABL@ZnTA can act as zinc finger motif to co-stabilize the configuration of ABL through multiple molecular interactions, enabling high bioactivity, high loading capacity (1.36 times), and long-term release (>7 days) of ABL. Our results showed that ABL@ZnTA can modulate macrophage polarization from the pro-inflammatory M1 towards the anti-inflammatory M2 phenotype, promoting immune osteogenesis with increased OCN, ALP, and SOD 1 expression. Furthermore, the ABL@ZnTA significantly reduces inflammatory fibrous tissue encapsulation and enhances the long-term stability of the implants, indicated by enhanced binding strength (6 times) and functional connectivity (1.5−3 times) in the rat bone defect model infected by S. aureus. Overall, our research offers a nano-enabled synergistic strategy that balances infection defense and osteogenesis promotion in orthopedic and dental implantations.

Camptothecin (CPT) exhibits potent antitumor activity; however, its clinical application is limited by significant gastrointestinal adverse effects (GAEs). Although the severity of GAEs associated with CPT derivatives has decreased, the incidence rate of these adverse effects has remained high. CPT multifunctional nanoparticles (PCRHNs) have the potential to increase the efficacy of CPT while reducing side effects in major target organs; however, the impact of PCRHNs on the GAEs from CPT remains uncertain. Here, we investigated the therapeutic effects of PCRHNs and different doses of CPT and examined their impacts on the intestinal barrier and the intestinal microbiota. We found that the therapeutic efficacy of PCRHNs + Laser treatment was superior to that of high-dose CPT, and PCRHNs + Laser treatment also provided greater benefits by helping maintain intestinal barrier integrity, intestinal microbiota diversity, and intestinal microbiota abundance. In summary, compared to high-dose CPT treatment, PCRHNs + Laser treatment can effectively balance therapeutic effects and GAEs. A high dose of CPT promotes the enrichment of the pathogenic bacteria Escherichia-Shigella, which may be attributed to diarrhea caused by CPT, thus leading to a reduction in microbial burden; additionally, Escherichia-Shigella rapidly grows and occupies niches previously occupied by other bacteria that are lost due to diarrhea. PCRHNs + Laser treatment increased the abundance of Lactobacillus (probiotics), possibly due to the photothermal effect of the PCRHNs. This effect increased catalase activity, thus facilitating the conversion of hydrogen peroxide into oxygen within tumors and increasing oxygen levels in the body, which is conducive to the growth of facultative anaerobic bacteria.

Objectives: To develop computed tomography (CT)-based models to increase the prediction accuracy of spread through air spaces (STAS) in clinical-stage T1N0 lung adenocarcinoma. Methods: Three cohorts of patients with stage T1N0 lung adenocarcinoma (n = 1258) were analyzed retrospectively. Two models using radiomics and deep neural networks (DNNs) were established to predict the lung adenocarcinoma STAS status. For the radiomic models, features were extracted using PyRadiomics, and 10 features with nonzero coefficients were selected using least absolute shrinkage and selection operator regression to construct the models. For the DNN models, a 2-stage (supervised contrastive learning and fine-tuning) deep-learning model, MultiCL, was constructed using CT images and the STAS status as training data. The area under the curve (AUC) was used to verify the predictive ability of both model types for the STAS status. Results: Among the radiomic models, the linear discriminant analysis model exhibited the best performance, with AUC values of 0.8944 (95% confidence interval [CI], 0.8241-0.9502) and 0.7796 (95% CI, 0.7089-0.8448) for predicting the STAS status on the test and external validation cohorts, respectively. Among the DNN models, MultiCL exhibited the best performance, with AUC values of 0.8434 (95% CI, 0.7580-0.9154) for the test cohort and 0.7686 (95% CI, 0.6991-0.8316) for the external validation cohort. Conclusions: CT-based imaging models (radiomics and DNNs) can accurately identify the STAS status of clinical-stage T1N0 lung adenocarcinoma, potentially guiding surgical decision making and improving patient outcomes.

Abstract Toxoplasma gondii is a significant zoonotic pathogen of toxoplasmosis in humans and animals. Here a live attenuated Toxoplasma vaccine of WH3 Δrop18 was developed. The results showed that all mice vaccinated with WH3 Δrop18 were able to survive when challenge with various strains of Toxoplasma, including RH (type I), ME49 (type II), WH3 or WH6 (type Chinese 1). No cysts, if few, in the brain of the vaccinated animals were seen after challenge with cyst forming strains of ME49 or WH6. Vaccination with the WH3 Δrop18 triggered a strong immune response, including significantly increased level of the cytokines (IFN-γ, IL-12, TNF-α and IL-10) and the activation of CD4+ and CD8+ T-lymphocytes and long term of specific antibodies against Toxoplasma. Our results strongly indicate that vaccine of WH3 Δrop18 might provide effective immune protection against a wide range strains of Toxoplasma infections and be a promising live attenuated vaccine candidate.

Abstract Emotion recognition in user‐generated videos plays an essential role in affective computing. In general, visual information directly affects human emotions, so the visual modality is significant for emotion recognition. Most classic approaches mainly focus on local temporal information of videos, which potentially restricts their capacity to encode the correlation of long‐range context. To address this issue, a novel network is proposed to recognize emotions in videos. To be specific, a spatio‐temporal correlation‐aware block is designed to depict the long‐range correlations between input tokens, where the convolutional layers are used to learn the local correlations and the inter‐image cross‐attention is designed to learn the long‐range and spatio‐temporal correlations between input tokens. To generate diverse and challenging samples, a dual‐augmentation fusion layer is devised, which fuses each frame with its corresponding frame in the temporal domain. To produce rich video clips, a long‐range sampling layer is designed, which generates clips in a wide range of spatial and temporal domains. Extensive experiments are conducted on two challenging video emotion datasets, namely VideoEmotion‐8 and Ekman‐6. The experimental results demonstrate that the proposed method obtains better performance than baseline methods. Moreover, the proposed method achieves state‐of‐the‐art results on the two datasets. The source code of the proposed network is available at: https://github.com/JinChow/LRCANet.

Abstract As one of the main occupational hazards, welding fumes can cause oxidative damage and induce series of diseases, such as COPD or asthma. To clarify the effects of the metal fume ultrafine particulates (MF-UFPs) of welding fumes on oxidative damage, UFPs were collected by melt inert gas (MIG) and manual metal arc (MMA) welding, and the composition was confirmed. Human bronchial epithelial 16HBE cells were treated with 0–1000 µg/cm2 MF-UFPs to analyse the cytotoxicity, oxidative stress and cytokines. The protein and mRNA expression of Keap1-Nrf-2/antioxidant response elements (AREs) signalling pathway components were also analysed. After 4 h of treatment, the cell viability decreased 25% after 33.85 and 32.81 µg/cm2 MIG/MMA-UFPs treated. The intracellular ATP concentrations were also decreased significantly, while LDH leakage was increased. The decreased mitochondrial membrane potential and increased ROS suggested the occurrence of oxidative damage, and the results of proteome profiling arrays also showed a significant increase in IL-6 and IL-8. The expression of AREs which related to antioxidant and anti-inflammatory were also increased. These results indicate that the MF-UFPs can cause oxidative stress in 16HBE cells and activate the Nrf-2/ARE signalling pathway to against oxidative damage.

Abstract Hematological malignancies are a group of cancers that affect the blood, bone marrow, and lymphatic system. Cancer stem cells (CSCs) are believed to be responsible for the initiation, progression, and relapse of hematological malignancies. However, identifying and targeting CSCs presents many challenges. We aimed to develop a stemness index (HSCsi) to identify and guide the therapy targeting CSCs in hematological malignancies. We developed a novel one-class logistic regression (OCLR) algorithm to identify transcriptomic feature sets related to stemness in hematologic malignancies. We used the HSCsi to measure the stemness degree of leukemia stem cells (LSCs) and correlate it with clinical outcomes.We analyze the correlation of HSCsi with genes and pathways involved in drug resistance and immune microenvironment of acute myeloid leukemia (AML). HSCsi revealed stemness-related biological mechanisms in hematologic malignancies and effectively identify LSCs. The index also predicted survival and relapse rates of various hematologic malignancies. We also identified potential drugs and interventions targeting cancer stem cells (CSCs) of hematologic malignancies by the index. Moreover, we found a correlation between stemness and bone marrow immune microenvironment in AML. Our study provides a novel method and tool to assess the stemness degree of hematologic malignancies and its implications for clinical outcomes and therapeutic strategies. Our HSC stemness index can facilitate the precise stratification of hematologic malignancies, suggest possible targeted and immunotherapy options, and guide the selection of patients.

Abstract Sea cucumbers are predominant deposit feeders in benthic ecosystems, providing protective benefits to coral reefs by reducing disease prevalence. However, how they receive sufficient nutrition from seabed sediments remains poorly understood. Here, we investigate Holothuria leucospilota, an ecologically significant tropical sea cucumber, to elucidate digestive mechanisms underlying marine deposit-feeding. Genomic analysis reveals intriguing evolutionary adaptation characterized by an expansion of digestive carbohydrase genes and a contraction of digestive protease genes, suggesting specialization in digesting microalgae. Developmentally, two pivotal dietary shifts, namely, from endogenous nutrition to planktonic feeding, and from planktonic feeding to deposit feeding, induce changes in digestive tract enzyme profiles, with adults mainly expressing carbohydrases and lipases. A nuanced symbiotic relationship exists between gut microbiota and the host, namely, specific resident bacteria supply crucial enzymes for food digestion, while other bacteria are digested and provide assimilable nutrients. Our study further identifies Holothuroidea lineage-specific lysozymes that are restrictedly expressed in the intestines to support bacterial digestion. Overall, this work advances our knowledge of the evolutionary innovations in the sea cucumber digestive system which enable them to efficiently utilize nutrients from seabed sediments and promote food recycling within marine ecosystems.

Abstract Background As a supportive treatment, the effectiveness of oxygen therapy in ischemic stroke (IS) patients remains unclear. This study aimed to evaluate the relationships between arterial partial pressure of oxygen (PaO2) and both consciousness at discharge and all-cause mortality risk in ICU IS patients. Methods Blood gas measurements for all patients diagnosed with IS were extracted from the MIMIC-IV database. Patients were classified into four groups based on their average PaO2 during the first ICU day: hypoxemia (PaO2

The purpose of this study was to identify the correlates of depressive symptoms and the prevalence of depression, distress, and demoralization among patients with cancer in Taiwan in relation to their sociodemographics. A cross-sectional study design with convenience sampling was used to recruit 191 consecutive patients with cancer from the Cancer Center of a teaching hospital in northern Taiwan. Multiple linear regression was applied to analyze the determinants of depressive symptoms. The prevalence rates of depression (including suspected cases), distress, and demoralization were 17.8%, 36.1%, and 32.5%, respectively. The regression model explained 42.2% of the total variance, with significant predictors including marital status, life dependence, comorbidity, demoralization, and distress. The results demonstrated that higher levels of distress and demoralization were associated with more depressive symptoms. Demoralization and distress played vital roles in moderating depressive symptoms among patients with cancer. Nursing interventions should integrate appropriate mental health services, such as alleviating distress and demoralization, to prevent the occurrence of depression in patients with cancer.

Abstract There are considerable researches on risk factors for necrotizing enterocolitis (NEC), focusing primarily on the entire course before onset. However, fewer studies address risk factors within the brief period before NEC occurrence. The current study aims to retrospectively analyze the clinical data of NEC patients while focusing on relevant risk factors in the preceding week of NEC onset. Infants born between January 2019 and December 2021 at Suzhou Municipal Hospital and Suzhou University Children’s Hospital with a birth weight

Abstract Feline infectious peritonitis (FIP) is a lethal, immune-mediated disease in cats caused by feline infectious peritonitis virus (FIPV), a biotype of feline coronavirus (FCoV). In contrast to feline enteric coronavirus (FECV), which exclusively infects enterocytes and causes diarrhea, FIPV specifically targets macrophages, resulting in the development of FIP. The transmission and infection mechanisms of this complex, invariably fatal disease remain unclear, with no effective vaccines or approved drugs for its prevention or control. In this study, a full-length infectious cDNA clone of the wild-type FIPV WSU79-1149 strain was constructed to generate recombinant FIPV (rFIPV-WT), which exhibited similar growth kinetics and produced infectious virus titres comparable to those of the parental wild-type virus. In addition, the superfold green fluorescent protein (msfGFP) and Renilla luciferase (Rluc) reporter genes were incorporated into the rFIPV-WT cDNA construct to generate reporter rFIPV-msfGFP and rFIPV-Rluc viruses. While the growth characteristics of the rFIPV-msfGFP virus were similar to those of its parental rFIPV-WT, the rFIPV-Rluc virus replicated more slowly, resulting in the formation of smaller plaques than did the rFIPV-WT and rFIPV-msfGFP viruses. In addition, by replacing the S, E, M, and ORF3abc genes with msfGFP and Rluc genes, the replicon systems repFIPV-msfGFP and repFIPV-Rluc were generated on the basis of the cDNA construct of rFIPV-WT. Last, the use of reporter recombinant viruses and replicons in antiviral screening assays demonstrated their high sensitivity for quantifying the antiviral effectiveness of the tested compounds. This integrated system promises to significantly streamline the investigation of virus replication within host cells, enabling efficient screening for anti-FIPV compounds and evaluating emerging drug-resistant mutations within the FIPV genome.

Abstract Multi-functional cysteine-targeting covalent warheads possess significant therapeutic potential in medicinal chemistry and chemical biology. Herein, we present novel unsaturated and asymmetric ketone (oxazolinosene) scaffolds that selectively conjugate cysteine residues of peptides and bovine serum albumin under normal physiological conditions. This unsaturated saccharide depletes GSH in NCI-H1299 cells, leading to anti-tumor effects in vitro. The acetyl group of the ketal moiety on the saccharide ring can be converted to other carboxylic acids in a one-pot synthesis. In this way, the loaded acid can be click-released during cysteine conjugation, making the oxazolinosene a potential multifunctional therapeutic agent. The reaction kinetic model for oxazolinosene conjugation to GSH is well established and was used to evaluate oxazolinosene reactivity. The aforementioned oxazolinosenes were stereoselectively synthesized via a one-step reaction of nitriles with saccharides and conveniently converted into a series of α, β-unsaturated ketone N-glycosides as prevalent synthetic building blocks. The reaction mechanisms of oxazolinosene synthesis were investigated through calculations and validated with control experiments. Overall, these oxazolinosenes can be easily synthesized and developed as cysteine-targeted covalent warheads carrying useful click-releasing groups.

Transjugular intrahepatic portosystemic shunt (TIPS) is an essential procedure for the treatment of portal hypertension but can result in hepatic encephalopathy (HE), a serious complication that worsens patient outcomes. Investigating predictors of HE after TIPS is essential to improve prognosis. This review analyzes risk factors and compares predictive models, weighing traditional scores such as Child-Pugh, Model for End-Stage Liver Disease (MELD), and albumin-bilirubin (ALBI) against emerging artificial intelligence (AI) techniques. While traditional scores provide initial insights into HE risk, they have limitations in dealing with clinical complexity. Advances in machine learning (ML), particularly when integrated with imaging and clinical data, offer refined assessments. These innovations suggest the potential for AI to significantly improve the prediction of post-TIPS HE. The study provides clinicians with a comprehensive overview of current prediction methods, while advocating for the integration of AI to increase the accuracy of post-TIPS HE assessments. By harnessing the power of AI, clinicians can better manage the risks associated with TIPS and tailor interventions to individual patient needs. Future research should therefore prioritize the development of advanced AI frameworks that can assimilate diverse data streams to support clinical decision-making. The goal is not only to more accurately predict HE, but also to improve overall patient care and quality of life.