Onco-critical care has emerged as an important subspecialty at the intersection of critical care medicine and oncology, attracting increasing attention in recent years. With continuous innovations in cancer therapies, patient survival has improved significantly; however, the incidence of associated critical complications has also increased. The reasons for cancer patients requiring intensive care unit admission are diverse and can be broadly categorized into three groups: progression of the underlying malignancy, treatment-related complications, and coexisting classical critical illnesses. Traditional critical care concepts and practices face limitations in addressing the multidimensional and heterogeneous challenges of onco-critical care. Based on the core mechanism of critical illness development—host/organ unregulated response (HOUR)—this article systematically elaborates on how this framework advances understanding and clinical practice into onco-critical care, with emphasis on its manifestations in neuroendocrine, immune-inflammatory, and coagulation-metabolic pathways. The review summarizes recent advances in clinical assessment and phenotyping systems for onco-critical illness and discusses a multidisciplinary, integrated management strategy centered on the "Disease Control, Host Response Modulation, Organ Support" triad. Finally, major challenges and future directions in this field are outlined. By integrating existing evidence and theoretical insights, this review aims to provide new perspectives and a theoretical foundation for the clinical management of onco-critical illness, thereby promoting its evolution toward precision and standardization.

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

This study aims to investigate the potential effect of the water extract of fresh Rehmanniae Radix on hypercholesterolemia in mice that was induced by a high-fat and high-cholesterol diet and explore its possible mechanism from bile acid reabsorption. Male C57BL/6 mice were randomly assigned into the following groups: control, model, low-and high-dose(4 and 8 g·kg~(-1), respectively) fresh Rehmanniae Radix, and positive drug(simvastatin, 0.05 g·kg~(-1)). Other groups except the control group were fed with a high-fat and high-cholesterol diet for 6 consecutive weeks to induce hypercholesterolemia. From the 6th week, mice were administrated with corresponding drugs daily via gavage for additional 6 weeks, while continuing to be fed with a high-fat and high-cholesterol diet. Serum levels of total cholesterol(TC), triglycerides(TG), low density lipoprotein-cholesterol(LDL-c), high density lipoprotein-cholesterol(HDL-c), and total bile acid(TBA), as well as liver TC and TG levels and fecal TBA level, were determined by commercial assay kits. Hematoxylin-eosin(HE) staining, oil red O staining, and transmission electron microscopy were performed to observe the pathological changes in the liver. Three livers samples were randomly selected from each of the control, model, and high-dose fresh Rehmanniae Radix groups for high-throughput transcriptome sequencing. Differentially expressed genes were mined and KEGG pathway enrichment analysis was performed to predict the key pathways and target genes of the water extract of fresh Rehmanniae Radix in the treatment of hypercholesterolemia. RT-qPCR was employed to measure the mRNA levels of cholesterol 7α-hydroxylase(CYP7A1) and cholesterol 27α-hydroxylase(CYP27A1) in the liver. Western blot was employed to determine the protein levels of CYP7A1 and CYP27A1 in the liver as well as farnesoid X receptor(FXR), apical sodium-dependent bile acid transporter(ASBT), and ileum bile acid-binding protein(I-BABP) in the ileum. The results showed that the water extract of fresh Rehmanniae Radix significantly lowered the levels of TC and TG in the serum and liver, as well as the level of LDL-c in the serum. Conversely, it elevated the level of HDL-c in the serum and TBA in feces. No significant difference was observed in the level of TBA in the serum among groups. HE staining, oil red O staining, and transmission electron microscopy showed that the water extract reduced the accumulation of lipid droplets in the liver. Further mechanism studies revealed that the water extract of fresh Rehmanniae Radix significantly down-regulated the protein levels of FXR and bile acid reabsorption-related proteins ASBT and I-BABP. Additionally, it enhanced CYP7A1 and CYP27A1, the key enzymes involved in bile acid synthesis. Therefore, it is hypothesized that the water extract of fresh Rehmanniae Radix may exert an anti-hypercholesterolemic effect by regulating FXR/ASBT/I-BABP signaling, inhibiting bile acid reabsorption, and increasing bile acid excretion, thus facilitating the conversion of cholesterol to bile acids.
Animals ; Male ; Bile Acids and Salts/metabolism* ; Mice, Inbred C57BL ; Mice ; Diet, High-Fat/adverse effects* ; Cholesterol/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Hypercholesterolemia/genetics* ; Receptors, Cytoplasmic and Nuclear/genetics* ; Rehmannia/chemistry* ; Liver/drug effects* ; Humans ; Cholesterol 7-alpha-Hydroxylase/genetics* ; Plant Extracts

The pathogenesis of neurodegenerative diseases (NDDs) is fundamentally linked to complex and profound alterations in metabolic networks within the brain, which exhibit marked spatial heterogeneity. While conventional bulk metabolomics is powerful for detecting global metabolic shifts, it inherently lacks spatial resolution. This methodological limitation hampers the ability to interrogate critical metabolic dysregulation within discrete anatomical brain regions and specific cellular microenvironments, thereby constraining a deeper understanding of the core pathological mechanisms that initiate and drive NDDs. To address this critical gap, spatial metabolomics, with mass spectrometry imaging (MSI) at its core, has emerged as a transformative approach. It uniquely overcomes the limitations of bulk methods by enabling high-resolution, simultaneous detection and precise localization of hundreds to thousands of endogenous molecules—including primary metabolites, complex lipids, neurotransmitters, neuropeptides, and essential metal ions—directly in situ from tissue sections. This powerful capability offers an unprecedented spatial perspective for investigating the intricate and heterogeneous chemical landscape of NDD pathology, opening new avenues for discovery. Accordingly, this review provides a comprehensive overview of the field, beginning with a discussion of the technical features, optimal application scenarios, and current limitations of major MSI platforms. These include the widely adopted matrix-assisted laser desorption/ionization (MALDI)-MSI, the ultra-high-resolution technique of secondary ion mass spectrometry (SIMS)-MSI, and the ambient ionization method of desorption electrospray ionization (DESI)-MSI, along with other emerging technologies. We then highlight the pivotal applications of spatial metabolomics in NDD research, particularly its role in elucidating the profound chemical heterogeneity within distinct pathological microenvironments. These applications include mapping unique molecular signatures around amyloid β‑protein (Aβ) plaques, uncovering the metabolic consequences of neurofibrillary tangles composed of hyperphosphorylated tau protein, and characterizing the lipid and metabolite composition of Lewy bodies. Moreover, we examine how spatial metabolomics contributes to constructing detailed metabolic vulnerability maps across the brain, shedding light on the biochemical factors that render certain neuronal populations and anatomical regions selectively susceptible to degeneration while others remain resilient. Looking beyond current applications, we explore the immense potential of integrating spatial metabolomics with other advanced research methodologies. This includes its combination with three-dimensional brain organoid models to recapitulate disease-relevant metabolic processes, its linkage with multi-organ axis studies to investigate how systemic metabolic health influences neurodegeneration, and its convergence with single-cell and subcellular analyses to achieve unprecedented molecular resolution. In conclusion, this review not only summarizes the current state and critical role of spatial metabolomics in NDD research but also offers a forward-looking perspective on its transformative potential. We envision its continued impact in advancing our fundamental understanding of NDDs and accelerating translation into clinical practice—from the discovery of novel biomarkers for early diagnosis to the development of high-throughput drug screening platforms and the realization of precision medicine for individuals affected by these devastating disorders.

OBJECTIVE: Although dietary preferences influence chronic diseases, few studies have linked dietary preferences to mortality risk, particularly in large cohorts. To investigate the relationship between dietary preferences and mortality risk (all-cause, cancer, and cardiovascular disease [CVD]) in a large adult cohort. METHODS: A cohort of 1,160,312 adults (mean age 62.48 ± 9.55) from the Shenzhen Healthcare Big Data Cohort (SHBDC) was analyzed. Hazard ratios ( HRs) for mortality were estimated using the Cox proportional hazards model. RESULTS: The study identified 12,308 all-cause deaths, of which 3,865 (31.4%) were cancer-related and 3,576 (29.1%) were attributed to CVD. Compared with a mixed diet of meat and vegetables, a mainly meat-based diet (hazard ratio [ HR] = 1.13; 95% confidence interval [ CI]: 1.02, 1.27) associated with a higher risk of all-cause mortality, while mainly vegetarian ( HR = 0.87; 95% CI: 0.78, 0.97) was linked to a reduced risk. Furthermore, there was a stronger correlation between mortality risk and dietary preference in the > 65 age range. CONCLUSION A meat-based diet was associated with an increased risk of all-cause mortality, whereas a mainly vegetarian diet was linked to a reduced risk.
Humans ; China/epidemiology* ; Middle Aged ; Male ; Female ; Prospective Studies ; Aged ; Cardiovascular Diseases/mortality* ; Diet/statistics & numerical data* ; Neoplasms/mortality* ; Adult ; Cause of Death ; Food Preferences ; Proportional Hazards Models ; Mortality ; Cohort Studies

OBJECTIVE: To investigate the relationship between physical activity and genetic risk and their combined effects on the risk of developing chronic obstructive pulmonary disease. METHODS: This prospective cohort study included 318,085 biobank participants from the UK. Physical activity was assessed using the short form of the International Physical Activity Questionnaire. The participants were stratified into low-, intermediate-, and high-genetic-risk groups based on their polygenic risk scores. Multivariate Cox regression models and multiplicative interaction analyses were used. RESULTS: During a median follow-up period of 13 years, 9,209 participants were diagnosed with chronic obstructive pulmonary disease. For low genetic risk, compared to low physical activity, the hazard ratios ( HRs) for moderate and high physical activity were 0.853 (95% confidence interval [ CI]: 0.748-0.972) and 0.831 (95% CI: 0.727-0.950), respectively. For intermediate genetic risk, the HRs were 0.829 (95% CI: 0.758-0.905) and 0.835 (95% CI: 0.764-0.914), respectively. For participants with high genetic risk, the HRs were 0.809 (95% CI: 0.746-0.877) and 0.818 (95% CI: 0.754-0.888), respectively. A significant interaction was observed between genetic risk and physical activity. CONCLUSION Moderate or high levels of physical activity were associated with a lower risk of developing chronic obstructive pulmonary disease across all genetic risk groups, highlighting the need to tailor activity interventions for genetically susceptible individuals.
Humans ; Pulmonary Disease, Chronic Obstructive/epidemiology* ; Exercise ; Male ; Female ; Middle Aged ; Prospective Studies ; Aged ; Genetic Predisposition to Disease ; Risk Factors ; United Kingdom/epidemiology* ; Incidence ; Adult

BACKGROUND:A novel aggregation induced luminescence fluorescence probe based on the mechanism of intramolecular motility restriction can be used for the detection of disease markers,tumor diagnosis,and bacterial imaging recognition.OBJECTIVE:To prepare a near-infrared Ⅱ nanoprobe called FA-DSPE-PEG-AIE@NPs based on aggregation-induced luminescence,and to explore its potential of targeted fluorescence imaging and photothermal therapy for prostate cancer.METHODS:Lecithin,polyethylene glycol phospholipids,folate polyethylene glycol phospholipids,and aggregation induced luminescent molecule 2TT-oC26B were used as raw materials.The folate-targeted nanoprobe FA-DSPE-PEG-AIE@NPs were prepared by nanoprecipitation method,and basic characterization of the nanoprobe was detected.PC3 human prostate cancer cells and human umbilical vein endothelial cells were selected as experimental objects.The cytotoxicity and phototoxicity of FA-DSPE-PEG-AIE@NPs were detected.PC3 human prostate cancer cells were selected as the experimental objects.Flow cytometry and calcein/propidium iodide staining were used to assess the efficacy of photothermal therapy.PC3 human prostate cancer cells were injected subcutaneously into the abdomen of BALB/C nude mice to establish a tumor model,and nanoprobes FA-DSPE-PEG-AIE@NPs were injected into the tail vein.The mice were immediately subjected to near-infraced Ⅱ fluorescence imaging.12 hours later,the tumor was irradiated by laser for 5 minutes,and the photothermal treatment effect was observed within 14 days.RESULTS AND CONCLUSION:(1)The nanoprobes FA-DSPE-PEG-AIE@NPs with a mean diameter of(171.0±0.3)nm showed a well-defined spherical morphology.The nanoprobe had a wide absorption spectrum and tail emission extending to the near-infrared Ⅱ which emitted a bright near-infrared Ⅱ fluorescence signal under laser irradiation.(2)The nanoprobes FA-DSPE-PEG-AIE@NPs had low cytotoxicity and high phototoxicity.The results of flow cytometry and calcein/propidium iodide staining showed that nanoprobes FA-DSPE-PEG-AIE@NPs had an obvious photothermal killing effect on human prostate cancer cells.(3)The nanoprobes FA-DSPE-PEG-AIE@NPs successfully achieved near-infrared Ⅱ fluorescence imaging of mouse blood vessels and the maximum enrichment time of the tumor was 12 hours.The vessel widths of the hind leg and single blood vessels of abdomen were estimated to be 0.63 mm and 0.42 mm.The tumor volume of mice was significantly smaller after 14 days of treatment.(4)The results show that nanoprobes FA-DSPE-PEG-AIE@NPs can achieve near-infrared Ⅱ fluorescence imaging and photothermal therapy of prostate cancer effectively,which may provide a new method for early diagnosis and combined treatment of prostate cancer.

BACKGROUND:A novel aggregation induced luminescence fluorescence probe based on the mechanism of intramolecular motility restriction can be used for the detection of disease markers,tumor diagnosis,and bacterial imaging recognition.OBJECTIVE:To prepare a near-infrared Ⅱ nanoprobe called FA-DSPE-PEG-AIE@NPs based on aggregation-induced luminescence,and to explore its potential of targeted fluorescence imaging and photothermal therapy for prostate cancer.METHODS:Lecithin,polyethylene glycol phospholipids,folate polyethylene glycol phospholipids,and aggregation induced luminescent molecule 2TT-oC26B were used as raw materials.The folate-targeted nanoprobe FA-DSPE-PEG-AIE@NPs were prepared by nanoprecipitation method,and basic characterization of the nanoprobe was detected.PC3 human prostate cancer cells and human umbilical vein endothelial cells were selected as experimental objects.The cytotoxicity and phototoxicity of FA-DSPE-PEG-AIE@NPs were detected.PC3 human prostate cancer cells were selected as the experimental objects.Flow cytometry and calcein/propidium iodide staining were used to assess the efficacy of photothermal therapy.PC3 human prostate cancer cells were injected subcutaneously into the abdomen of BALB/C nude mice to establish a tumor model,and nanoprobes FA-DSPE-PEG-AIE@NPs were injected into the tail vein.The mice were immediately subjected to near-infraced Ⅱ fluorescence imaging.12 hours later,the tumor was irradiated by laser for 5 minutes,and the photothermal treatment effect was observed within 14 days.RESULTS AND CONCLUSION:(1)The nanoprobes FA-DSPE-PEG-AIE@NPs with a mean diameter of(171.0±0.3)nm showed a well-defined spherical morphology.The nanoprobe had a wide absorption spectrum and tail emission extending to the near-infrared Ⅱ which emitted a bright near-infrared Ⅱ fluorescence signal under laser irradiation.(2)The nanoprobes FA-DSPE-PEG-AIE@NPs had low cytotoxicity and high phototoxicity.The results of flow cytometry and calcein/propidium iodide staining showed that nanoprobes FA-DSPE-PEG-AIE@NPs had an obvious photothermal killing effect on human prostate cancer cells.(3)The nanoprobes FA-DSPE-PEG-AIE@NPs successfully achieved near-infrared Ⅱ fluorescence imaging of mouse blood vessels and the maximum enrichment time of the tumor was 12 hours.The vessel widths of the hind leg and single blood vessels of abdomen were estimated to be 0.63 mm and 0.42 mm.The tumor volume of mice was significantly smaller after 14 days of treatment.(4)The results show that nanoprobes FA-DSPE-PEG-AIE@NPs can achieve near-infrared Ⅱ fluorescence imaging and photothermal therapy of prostate cancer effectively,which may provide a new method for early diagnosis and combined treatment of prostate cancer.

Smoking is the leading preventable risk factor for disease and death worldwide. Tobacco and its smoke contain a complex mix of over 9 500 chemical substances, including oxidative gases, heavy metals, and 83 known carcinogens. Long-term smoking is a significant risk factor for respiratory diseases such as acute lung injury, emphysema, and pulmonary fibrosis. Damage to alveolar epithelial cells (AECs) is a common pathological feature in these smoking-related lung diseases. AECs, which line the surface of the alveoli, play a crucial role in preventing overexpansion or collapse, secreting cell factors and surfactants, containing abundant mitochondria, and being essential for lung tissue maturation, gas exchange, metabolism, and repair after damage. Damage to these cells can lead to pulmonary edema and alveolar collapse. Cigarette smoke (CS) can disrupt alveolar epithelial cell function through various pathways, resulting in cell death, tissue damage, and the development of lung diseases.This review summarizes recent research on the damage caused by CS to AECs, showing that CS can promote cell death and damage through induction of oxidative stress, autophagy, endoplasmic reticulum stress, mitochondrial dysfunction, inflammation, and epithelial-mesenchymal transition. It also affects the proliferative function of alveolar type II epithelial cells. The review highlights that CS-induced oxidative stress is a key factor in causing various types of damage, with TRP ion channels serving as important triggers. Inhibiting CS-induced oxidative damage can significantly prevent cell death and subsequent diseases such as pulmonary emphysema. The activation of the same pathway induced by CS can lead to different types of cell damage, potentially encouraging the development of different diseases. CS can either directly induce or indirectly promote cell inflammation through endoplasmic reticulum stress, mitochondrial dysfunction, and senescence. There are interconnected relationships between these mechanisms, and SIRT1 is an important protein in preventing CS-induced AECs damage. Increasing SIRT1 activity can alleviate CS-induced autophagy, endoplasmic reticulum stress, and senescence in various cell damages; its substrate NAD⁺ is already used clinically, and its effectiveness in COPD treatment deserves further exploration. The impact of CS on cells varies based on concentration: lower concentrations stimulate stress responses or apoptosis, while higher concentrations lead to apoptosis or necrosis through various mechanisms, ultimately impairing lung epithelial function. When external stimuli exceed the cells’ self-healing capacity, they can cause damage to cells, lung epithelial barriers, and alveoli, promoting the development of related lung diseases. Key proteins that play a protective role may serve as potential targets to mitigate cell damage.This review provides insights into the various mechanisms through which CS induces damage to AECs, covering important transcription factors, DNA repair proteins, and membrane channel proteins, paving the way for the study of new mechanisms and pathways. However, there are still unanswered questions, such as the need for further exploration of the upstream pathways of CS-induced autophagy in AECs and the intrinsic mechanisms of CS in enhancing the stem cell properties of AECs and its relationship to the occurrence of lung cancer.It is expected that this article will provide a theoretical basis for future research on the mechanisms of lung epithelial cell damage caused by CS or its individual components and inspire clinical strategies for the prevention and treatment of smoking-related lung diseases.

As the global population continues to age, the incidence of Alzheimer’s disease (AD), one of the most common neurodegenerative diseases, continues to rise significantly. As the disease progresses, the patient’s daily living abilities gradually decline, potentially leading to a complete loss of self-care abilities. According to estimates by the Alzheimer’s Association and the World Health Organization, AD accounts for 60%-70% of all other dementia cases, affecting over 55 million people worldwide. The case number is estimated to double by 2050. Despite extensive research, the precise etiology and pathogenesis of AD remain elusive. Researchers have a profound understanding of the disease’s pathological hallmarks, which include amyloid plaques and neurofibrillary tangles resulting from the abnormal phosphorylation of Tau protein. However, the exact causes and mechanisms of the disease are still not fully understood, leaving a vital gap in our knowledge and understanding of this debilitating disease. A crucial player that has recently emerged in the field of AD research is the α7 nicotinic acetylcholine receptor (α7nAChR). α7nAChR is composed of five identical α7 subunits that form a homopentamer. This receptor is a significant subtype of acetylcholine receptor in the central nervous system and is widely distributed in various regions of the brain. It is particularly prevalent in the hippocampus and cortical areas, which are regions associated with learning and memory. α7nAChR plays a pivotal role in several neurological processes, including neurotransmitter release, neuronal plasticity, cell signal transduction, and inflammatory response, suggesting its potential involvement in numerous neurodegenerative diseases, including AD. In recent years, the role of α7nAChR in AD has been the focus of extensive research. Emerging evidence suggests that α7nAChR is involved in several critical steps in the disease progression of AD. These include involvement in the metabolism of amyloid β-protein (Aβ), the phosphorylation of Tau protein, neuroinflammatory response, and oxidative stress. Each of these processes contributes to the development and progression of AD, and the involvement of α7nAChR in these processes suggests that it may play a crucial role in the disease’s pathogenesis. The potential significance of α7nAChR in AD is further reinforced by the observation that alterations in its function or expression can have significant effects on cognitive abilities. These findings suggest that α7nAChR could be a promising target for therapeutic intervention in AD. At present, the results of drug clinical studies targeting α7nAChR show that these compounds have improvement and therapeutic effects in AD patients, but they have not reached the degree of being widely used in clinical practice, and their drug development still faces many challenges. Therefore, more research is needed to fully understand its role and to develop effective treatments based on this understanding. This review aims to summarize the current understanding of the association between α7nAChR and AD pathogenesis. We provide an overview of the latest research developments and insights, and highlight potential avenues for future research. As we deepen our understanding of the role of α7nAChR in AD, it is hoped that this will pave the way for the development of novel therapeutic strategies for this devastating disease. By targeting α7nAChR, we may be able to develop more effective treatments for AD, ultimately improving the quality of life for patients and their families.