Automated machine learning for early prediction of acute kidney injury in acute pancreatitis.

BACKGROUND: Acute kidney injury (AKI) represents a frequent and grave complication associated with acute pancreatitis (AP), substantially elevating both mortality rates and the financial burden of hospitalization. The aim of our study is to construct a predictive model utilizing automated machine learning (AutoML) algorithms for the early prediction of AKI in patients with AP. METHODS: We retrospectively analyzed patients who were diagnosed with AP in our hospital from January 2017 to December 2021. These patients were randomly allocated into a training set and a validation set at a ratio of 7:3. To develop predictive models for each set, we employed the least absolute shrinkage and selection operator (LASSO) algorithm along with AutoML. A nomogram was developed based on multivariate logistic regression analysis outcomes. The model's efficacy was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Additionally, the performance of the model constructed via AutoML was evaluated using decision curve analysis (DCA), feature importance, SHapley Additive exPlanations (SHAP) plots, and locally interpretable model-agnostic explanations (LIME). RESULTS: This study incorporated a total of 437 patients who met the inclusion criteria. Out of these, 313 were assigned to the training cohort and 124 to the validation cohort. In the training and validation cohorts, AKI occurred in 68 (21.7%) and 29(23.4%) patients, respectively. Comparative analysis revealed that the AutoML models exhibited enhanced performance over traditional logistic regression (LR). Furthermore, the deep learning (DL) model demonstrated superior predictive accuracy, evidenced by an area under the ROC curve of 0.963 in the training set and 0.830 in the validation set, surpassing other comparative models. The key variables identified as significant in the DL model within the training dataset included creatinine (Cr), urea (Urea), international normalized ratio (INR), etiology, smoking, alanine aminotransferase (ALT), hypertension, prothrombin time (PT), lactate dehydrogenase (LDH), and diabetes. CONCLUSION: The AutoML model, utilizing DL algorithm, offers considerable clinical significance in the early detection of AKI among patients with AP.

Application Value of the Automated Machine Learning Model Based on Modified Computed Tomography Severity Index Combined With Serological Indicators in the Early Prediction of Severe Acute Pancreatitis.

BACKGROUND AND AIMS: Machine learning (ML) algorithms are widely applied in building models of medicine due to their powerful studying and generalizing ability. To assess the value of the Modified Computed Tomography Severity Index (MCTSI) combined with serological indicators for early prediction of severe acute pancreatitis (SAP) by automated ML (AutoML). PATIENTS AND METHODS: The clinical data, of the patients with acute pancreatitis (AP) hospitalized in Hospital 1 and hospital 2 from January 2017 to December 2021, were retrospectively analyzed. Serological indicators within 24 hours of admission were collected. MCTSI score was completed by noncontrast computed tomography within 24 hours of admission. Data from the hospital 1 were adopted for training, and data from the hospital 2 were adopted for external validation. The diagnosis of AP and SAP was based on the 2012 revised Atlanta classification of AP. Models were built using traditional logistic regression and AutoML analysis with 4 types of algorithms. The performance of models was evaluated by the receiver operating characteristic curve, the calibration curve, and the decision curve analysis based on logistic regression and decision curve analysis, feature importance, SHapley Additive exPlanation Plot, and Local Interpretable Model Agnostic Explanation based on AutoML. RESULTS: A total of 499 patients were used to develop the models in the training data set. An independent data set of 201 patients was used to test the models. The model developed by the Deep Neural Net (DL) outperformed other models with an area under the receiver operating characteristic curve (areas under the curve) of 0.907 in the test set. Furthermore, among these AutoML models, the DL and gradient boosting machine models achieved the highest sensitivity values, both exceeding 0.800. CONCLUSION: The AutoML model based on the MCTSI score combined with serological indicators has good predictive value for SAP in the early stage.

Phytochemical Engineered Bacterial Outer Membrane Vesicles for Photodynamic Effects Promoted Immunotherapy.

Cancer vaccines are emerging as an attractive modality for tumor immunotherapy. However, their practical application is seriously impeded by the complex fabrication and unsatisfactory outcomes. Herein, we construct bacterial outer membrane vesicles (OMVs)-based in situ cancer vaccine with phytochemical features for photodynamic effects-promoted immunotherapy. By simply fusing thylakoid membranes with OMVs, bacteria-plant hybrid vesicles (BPNs) are prepared. After systemic administration, BPNs can target tumor tissues and stimulate the activation of immune cells, including dendritic cells (DCs). The photodynamic effects derived from thylakoid lead to the disruption of local tumors and then the release of tumor-associated antigens that are effectively presented by DCs, inducing remarkable tumor-specific CD8+T cell responses. Moreover, BPNs can efficiently ameliorate the immunosuppressive tumor microenvironment and further boost immune responses. Therefore, both tumor development and metastasis can be efficiently prevented. This work provides a novel idea for developing a versatile membrane-based hybrid system for highly efficient tumor treatment.

Sensitivity and specificity of single and combined clouds analyses compared with quantitative motor unit potential analysis.

INTRODUCTION: Turns-amplitude, number of small segments (NSS)-activity, and envelope-activity clouds are three methods of electromyography (EMG) interference pattern analysis. Our objective was to evaluate the sensitivity and specificity of each individual cloud analysis and combined clouds analysis to compare with that of quantitative motor unit potential (QMUP) analysis. METHODS: A total of 379 muscles from 100 patients were analyzed by both QMUP and clouds analyses. Calculation of sensitivity and specificity was based on the clinical diagnosis as the "gold standard." RESULTS: For discrimination of abnormal vs normal and neuropathic vs non-neuropathic, combined clouds analysis had greater sensitivity than QMUP analysis and any single cloud analysis, but there were no differences in specificity. For discrimination of myopathic vs non-myopathic, combined clouds analysis and single cloud analysis had greater sensitivity than QMUP analysis, but there were no differences in specificity. DISCUSSION: Combined clouds analysis was superior to QMUP and each single cloud analysis for distinguishing normal, myopathic, and neuropathic muscles.

Alternate expression of CONSTANS-LIKE 4 in short days and CONSTANS in long days facilitates day-neutral response in Rosa chinensis.

Photoperiodic flowering responses are classified into three major types: long day (LD), short day (SD), and day neutral (DN). The inverse responses to daylength of LD and SD plants have been partly characterized in Arabidopsis and rice; however, the molecular mechanism underlying the DN response is largely unknown. Modern roses are economically important ornamental plants with continuous flowering (CF) features, and are generally regarded as DN plants. Here, RcCO and RcCOL4 were identified as floral activators up-regulated under LD and SD conditions, respectively, in the CF cultivar Rosa chinensis 'Old-Blush'. Diminishing the expression of RcCO or/and RcCOL4 by virus-induced gene silencing (VIGS) delayed flowering time under both SDs and LDs. Interestingly, in contrast to RcCO-silenced plants, the flowering time of RcCOL4-silenced plants was more delayed under SD than under LD conditions, indicating perturbed plant responses to day neutrality. Further analyses revealed that physical interaction between RcCOL4 and RcCO facilitated binding of RcCO to the CORE motif in the promoter of RcFT and induction of RcFT. Taken together, the complementary expression of RcCO in LDs and of RcCOL4 in SDs guaranteed flowering under favorable growth conditions regardless of the photoperiod. This finding established the molecular foundation of CF in roses and further shed light on the underlying mechanisms of DN responses.

Developing normal number of small segments-activity clouds of the electromyography interference pattern.

BACKGROUND: Number of small segments (NSS) and activity analysis is a mature method for electromyographic automatic interference pattern analysis (IPA), but there are few reports on the application of this technique. Our objective was to establish normal reference values of NSS-activity clouds. METHODS: The NSS and activity data of the sternocleidomastoid, deltoid, biceps brachii (long head), extensor digitorum communis, abductor digiti minimi, vastus medialis, tibialis anterior, and gastrocnemius (lateral head) muscles were obtained from 34 men and 25 women, aged 15-80 years, using concentric needle electrodes. A linear regression of log(NSS) vs log(activity) was performed and the slope, intercept and standard deviation were calculated for each muscle. These variables were transformed back to the original parameters to yield clouds. RESULTS: Normal NSS-activity clouds for the above eight muscles were obtained. CONCLUSIONS: Normal reference values of NSS-activity may facilitate detection of early and mild neurogenic and myogenic abnormalities.

Responsive Exosome Nano-bioconjugates for Synergistic Cancer Therapy.

Exosomes hold great potential in therapeutic development. However, native exosomes usually induce insufficient effects in vivo and simply act as drug delivery vehicles. Herein, we synthesize responsive exosome nano-bioconjugates for cancer therapy. Azide-modified exosomes derived from M1 macrophages are conjugated with dibenzocyclooctyne-modified antibodies of CD47 and SIRPα (aCD47 and aSIRPα) through pH-sensitive linkers. After systemic administration, the nano-bioconjugates can actively target tumors through the specific recognition between aCD47 and CD47 on the tumor cell surface. In the acidic tumor microenvironment, the benzoic-imine bonds of the nano-bioconjugates are cleaved to release aSIRPα and aCD47 that can, respectively, block SIRPα on macrophages and CD47, leading to abolished "don't eat me" signaling and improved phagocytosis of macrophages. Meanwhile, the native M1 exosomes effectively reprogram the macrophages from pro-tumoral M2 to anti-tumoral M1.

Matrix Metalloproteases-Mediated Cleavage on ß-Dystroglycan May Play a Key Role in the Blood-Brain Barrier After Intracerebral Hemorrhage in Rats.

BACKGROUND It is well documented that the Blood-Brain barrier (BBB) can be damaged by matrix metalloproteases (MMPs) after intracerebral hemorrhage (ICH), but little is known about the mechanism of this effect. MATERIAL AND METHODS We established an ICH model in rats by injecting collagenase VII into the striatum. Afterwards, intraperitoneal injection of these rats with 40 mg/kg GM6001 (a MMPs inhibitor). The effects of GM6001 on ICH were investigated by neurological severity score, brain water content, Evans blue staining, hematoxylin-eosin staining, immunohistochemical staining, and Western blot assays. RESULTS We demonstrated that the neurological damage caused by ICH was relieved at 5 and 7 days following administration of GM6001. The impaired BBB induced by ICH was improved in response to GM6001 treatment at around 3 days, as evidenced by alleviated cerebral edema, decreased Evans blue extravasation, and a reduction in inflammatory cellular infiltration. Mechanism analysis revealed that ICH induced the generation of ß-dystroglycan cleavage, which could be suppressed by GM6001 treatment. Furthermore, we found that recombinant MMP2 and MMP9 triggered the cleavage of ß-dystroglycan in vitro, and this action could be inhibited by GM6001 administration. CONCLUSIONS Taken together, our results suggest that MMPs-mediated cleavage on ß-dystroglycan may play an important role in BBB after ICH.

Distinct impacts of reductive soil disinfestation and chemical soil disinfestation on soil fungal communities and memberships.

Soil disinfestation is an important agricultural practice to conquer soil-borne diseases and thereby ensure crop productivity. Reductive soil disinfestation (RSD) had been developed as an environmentally friendly alternative to chemical soil disinfestation (CSD). However, the differences between CSD and RSD on soil-borne pathogen suppression and fungal community structure remain poorly understood. In this work, five treatments, i.e., untreated soil (CK), CSD with 0.5 t ha-1 dazomet (DZ), RSD with 10 t ha-1 ethanol (ET), 15 t ha-1 sugarcane bagasse (SB), and 15 t ha-1 bean dregs (BD), were performed to investigate their influences on disinfestation efficiency, fungal abundance, diversity, and community structure via quantitative PCR and high-throughput sequencing. RSD-related treatments, especially the BD treatment, effectively alleviated soil acidification and salinization. The fungal abundance and microbial activity considerably increased in the BD treatment and significantly declined in the DZ treatment as compared to the CK treatment. Moreover, both CSD and RSD-related treatments significantly inhibited the population of Fusarium oxysporum and the relative abundance of genus Fusarium. Fungal community structure was notably altered by CSD and RSD practices. Furthermore, both CSD and RSD harbored a distinct unique microbiome, with the DZ treatment dominated by the genus Mortierella and BD treatment predominated by the genera Zopfiella, Chaetomium, and Penicillium. Taken together, these results indicate that the BD treatment could considerably alleviate the soil deterioration, improve soil microbial activity, and reassemble a non-pathogen unique microbiome that have more disease-suppressive agents and thus might be a promising disinfestation practice to control soil-borne disease in monoculture system.

In Vivo Oxidative Stress Monitoring Through Intracellular Hydroxyl Radicals Detection by Recyclable Upconversion Nanoprobes.

Oxidative stress, as an essential cause to many diseases via irreversible biomolecule oxidation, can be induced by casual-contacted nanomaterials, which can generate hydroxyl radical (•OH) due to their active surface capacity. Herein, we report a novel upconversion nanoprobe for ratiometric •OH detection and monitoring titanium oxide nanomaterial-induced oxidative stress. Unlike previously developed nanoprobes, the •OH-responsive acceptor in these nanoprobes can be rapidly prepared and easily recycled. With a detection limit of ∼2 nM and a broad linear range of 4 nM-16 µM, the nanoprobe is suitable for both in vitro and in vivo applications. The facile preparation and recyclable strategy provide a new method for developing novel nanoprobes that can directly detect hazardous molecules in biological samples and systems.

IRAK-M Plays A Role in the Pathology of Amyotrophic Lateral Sclerosis Through Suppressing the Activation of Microglia.

Microglial activation plays a crucial role in the disease progression in amyotrophic lateral sclerosis (ALS). Interleukin receptor-associated kinases-M (IRAK-M) is an important negative regulatory factor in the Toll-like receptor 4 (TLR4) pathway during microglia activation, and its mechanism in this process is still unclear. In the present study, we aimed to investigate the dynamic changes of IRAK-M and its protective effects for motor neurons in SOD1-G93A mouse model of ALS. qPCR (Real-time Quantitative PCR Detecting System) were used to examine the mRNA levels of IRAK-M in the spinal cord in both SOD1-G93A mice and their age-matched wild type (WT) littermates at 60, 100 and 140 days of age. We established an adeno-associated virus 9 (AAV9)-based platform by which IRAK-M was targeted mostly to microglial cells to investigate whether this approach could provide a protection in the SOD1-G93A mouse. Compared with age-matched WT mice, IRAK-M mRNA level was elevated at 100 and 140 days in the anterior horn region of spinal cords in the SOD1-G93A mouse. AAV9-IRAK-M treated SOD1-G93A mice showed reduction of IL-1ß mRNA levels and significant improvements in the numbers of spinal motor neurons in spinal cord. Mice also showed previously reduction of muscle atrophy. Our data revealed the dynamic changes of IRAK-M during ALS pathological progression and demonstrated that an AAV9-IRAK-M delivery was an effective and translatable therapeutic approach for ALS. These findings may help identify potential molecular targets for ALS therapy.

Metal-polyphenol "prison" attenuated bacterial outer membrane vesicle for chemodynamics promoted in situ tumor vaccines.

As natural adjuvants, the bacterial outer membrane vesicles (OMV) hold great potential in cancer vaccines. However, the inherent immunotoxicity of OMV and the rarity of tumor-specific antigens seriously hamper the clinical translation of OMV-based cancer vaccines. Herein, metal-phenolic networks (MPNs) are used to attenuate the toxicity of OMV, meanwhile, provide tumor antigens via the chemodynamic effect induced immunogenic cell death (ICD). Specifically, MPNs are assembled on the OMV surface through the coordination reaction between ferric ions and tannic acid. The iron-based "prison" is locally collapsed in the tumor microenvironment (TME) with both low pH and high ATP features, and thus the systemic toxicity of OMV is significantly attenuated. The released ferric ions in TME promote the ICD of cancer cells through Fenton reaction and then the generation of abundant tumor antigens, which can be used to fabricate in-situ vaccines by converging with OMV. Together with the immunomodulatory effect of OMV, potent tumor repression on a bilateral tumor model is achieved with good biosafety.

A high-density 1,024-channel probe for brain-wide recordings in non-human primates.

Large-scale neural population recordings with single-cell resolution across the primate brain remain challenging. Here we introduce the Neuroscroll probe that isolates single neuronal activities simultaneously from 1,024 densely spaced channels that are flexibly distributed across the shank of the probe. The Neuroscroll probe length is easily tunable for individual probes from 10 mm to 90 mm, covering the brain size of non-human primates and humans, and the probes remain intact and functional after repeated bending deformations. The Neuroscroll probes provided reliable recordings from large neural populations with high chronic stability up to 105 weeks in rats. Recording with each Neuroscroll probe yielded hundreds of well-isolated single units simultaneously from multiple brain regions distributed across the entire depth of the rhesus macaque brain. With the thousand simultaneously recorded channels, unprecedented probe length, excellent mechanical stability and flexible recording site distribution, the Neuroscroll probes enable a wide range of new experimental paradigms in system neuroscience studies with great versatility.

Shape-changing electrode array for minimally invasive large-scale intracranial brain activity mapping.

Large-scale brain activity mapping is important for understanding the neural basis of behaviour. Electrocorticograms (ECoGs) have high spatiotemporal resolution, bandwidth, and signal quality. However, the invasiveness and surgical risks of electrode array implantation limit its application scope. We developed an ultrathin, flexible shape-changing electrode array (SCEA) for large-scale ECoG mapping with minimal invasiveness. SCEAs were inserted into cortical surfaces in compressed states through small openings in the skull or dura and fully expanded to cover large cortical areas. MRI and histological studies on rats proved the minimal invasiveness of the implantation process and the high chronic biocompatibility of the SCEAs. High-quality micro-ECoG activities mapped with SCEAs from male rodent brains during seizures and canine brains during the emergence period revealed the spatiotemporal organization of different brain states with resolution and bandwidth that cannot be achieved using existing noninvasive techniques. The biocompatibility and ability to map large-scale physiological and pathological cortical activities with high spatiotemporal resolution, bandwidth, and signal quality in a minimally invasive manner offer SCEAs as a superior tool for applications ranging from fundamental brain research to brain-machine interfaces.

Catch bond-inspired hydrogels with repeatable and loading rate-sensitive specific adhesion.

Biological receptor-ligand adhesion governed by mammalian cells involves a series of mechanochemical processes that can realize reversible, loading rate-dependent specific interfacial bonding, and even exhibit a counterintuitive behavior called catch bonds that tend to have much longer lifetimes when larger pulling forces are applied. Inspired by these catch bonds, we designed a hydrogen bonding-meditated hydrogel made from acrylic acid-N-acryloyl glycinamide (AA-NAGA) copolymers and tannic acids (TA), which formed repeatable specific adhesion to polar surfaces in an ultra-fast and robust way, but hardly adhered to nonpolar materials. It demonstrated up to five-fold increase in shear adhesive strength and interfacial adhesive toughness with external loading rates varying from 5 to 500 mm min-1. With a mechanochemical coupling model based on Monte Carlo simulations, we quantitatively revealed the nonlinear dependence of rate-sensitive interfacial adhesion on external loading, which was in good agreement with the experimental data. Likewise, the developed hydrogels were biocompatible, possessed antioxidant and antibacterial properties and promoted wound healing. This work not only reports a stimuli-responsive hydrogel adhesive suitable for multiple biomedical applications, but also offers an innovative strategy for bionic designs of smart hydrogels with loading rate-sensitive specific adhesion for various emerging areas including flexible electronics and soft robotics.

In Vivo Imaging for the Visualization of Extracellular Vesicle-Based Tumor Therapy.

Extracellular vesicles (EVs) exhibiting versatile biological functions provide promising prospects as natural therapeutic agents and drug delivery vehicles. For future clinical translation, revealing the fate of EVs in vivo, especially their accumulation at lesion sites, is very important. The continuous development of in vivo imaging technology has made it possible to track the real-time distribution of EVs. This article reviews the applications of mammal-, plant-, and bacteria-derived EVs in tumor therapy, the labeling methods of EVs for in vivo imaging, the advantages and disadvantages of different imaging techniques, and possible improvements for future work.

Comprehensive analyses of PDHA1 that serves as a predictive biomarker for immunotherapy response in cancer.

Recent studies have proposed that pyruvate dehydrogenase E1 component subunit alpha (PDHA1), a cuproptosis-key gene, is crucial to the glucose metabolism reprogram of tumor cells. However, the functional roles and regulated mechanisms of PDHA1 in multiple cancers are largely unknown. The Cancer Genome Atlas (TCGA), GEPIA2, and cBioPortal databases were utilized to elucidate the function of PDHA1 in 33 tumor types. We found that PDHA1 was aberrantly expressed in most cancer types. Lung adenocarcinoma (LUAD) patients with high PDHA1 levels were significantly correlated with poor prognosis of overall survival (OS) and first progression (FP). Kidney renal clear cell carcinoma (KIRC) patients with low PDHA1 levels displayed poor OS and disease-free survival (DFS). However, for stomach adenocarcinoma (STAD), the downregulated PDHA1 expression predicted a good prognosis in patients. Moreover, we evaluated the mutation diversity of PDHA1 in cancers and their association with prognosis. We also analyzed the protein phosphorylation and DNA methylation of PDHA1 in various tumors. The PDHA1 expression was negatively correlated with tumor-infiltrating immune cells, such as myeloid dendritic cells (DCs), B cells, and T cells in pan-cancers. Mechanically, we used single-cell sequencing to discover that the PDHA1 expression had a close link with several cancer-associated signaling pathways, such as DNA damage, cell invasion, and angiogenesis. At last, we conducted a co-expressed enrichment analysis and showed that aberrantly expressed PDHA1 participated in the regulation of mitochondrial signaling pathways, including oxidative phosphorylation, cellular respiration, and electron transfer activity. In summary, PDHA1 could be a prognostic and immune-associated biomarker in multiple cancers.

Accurate quantification, naked eyes detection and bioimaging of nitrite using a colorimetric and near-infrared fluorescent probe in food samples and Escherichia coli.

Nitrite (NO2-) is an inorganic contaminant that exists widely in the environment including water and food products, excessive amounts of NO2- would threaten humans and aquatic life. Developing a rapid and convenient sensing method for NO2- remains a great challenge. Herein, a colorimetric and near-infrared fluorescent probe (TBM) was synthesized and applied for sensitively and selectively detecting NO2- in water, food samples and Escherichia coli (E. coli). With the addition of NO2-, the probe TBM solution has a distinct visual color changed from red to colorless and fluorescence intensity at 620 nm quickly decreased. The probe TBM could detect NO2- quantitatively with a detection limit of 85 nM based on a 3σ/slope. Under optimum conditions, TBM has been successfully used to detect NO2- in real-world environmental and dietary samples, with positive results. Besides, paper strips loaded with TBM have been used to visually determine NO2- levels. Most importantly, TBM has also been proven to be able to discriminate from different concentrations of NO2- in E. coli by fluorescence imaging. In summary, the probe TBM was successfully developed for the accurate quantification, naked eyes detection and bioimaging of NO2- in water, food samples and E. coli, which provides a useful tool to better guarantee the quality and safety of daily life and food industry.

Long-term treatment of Nicotinamide mononucleotide improved age-related diminished ovary reserve through enhancing the mitophagy level of granulosa cells in mice.

Ovarian aging affects the reproductive health of elderly women due to decline in oocyte quality, which is closely related to mitochondrial dysfunction. Nicotinamide mononucleotide (NMN), as a precursor of NAD+, effectively regulate mitochondria metabolism in mice. However, roles of NMN in improving age-related diminished ovary reserve remain to be determined. In present study, 4, 8, 12, 24, 40-week old female ICR mice were collected and a 20-week-long administration of NMN was conducted to 40-week-old mice (60WN), meanwhile the control group is given water (60WC). First, we found that 20-week-long administration of NMN to 40-week-old mice exhibited anti-aging and anti-inflammatory effects on organ structures, along with the improvement of estrus cycle condition and endocrine function. The number of primordial, primary, secondary, antral follicles and corpora luteum of ovaries in 60WN group was significantly increased compared with those in 60WC group. Additionally, the protein and gene expressions of P16 of ovaries were significantly reduced in 60WN group than in 60WC group. the mitochondria biogenesis, autophagy level, and proteases activity enhanced in granulosa cells after 20-week-administration of NMN. Present results indicate that NMN has the potential to save diminished ovary reserve by long-term treatment, providing a basis for exploring the role of NMN in anti-ovarian aging by enhancing the mitophagy level of granulosa cells.

Correlations of ALD, Keap-1, and FoxO4 expression with traditional tumor markers and clinicopathological characteristics in colorectal carcinoma.

Aldolase A (A-2) (ALD), Kelch-like-ECH associated protein-1 (Keap-1), and Forkhead box O4 (FoxO4) are key regulatory proteins, which have been proven to be involved in tumor development. However, the clinicopathological significance of ALD, Keap-1, and FoxO4 expressions in colorectal (colon) carcinoma (CRC) is not clearly known. We sought to explore the clinicopathological significance of ALD, Keap-1, and FoxO4 in CRC to provide evidences for potential monitoring index of CRC. Cases of 199 CRC patients were analyzed retrospectively. Evaluation of ALD, cAMP response element-binding protein-2, cyclo-oxygenase 2, FoxO4, Keap-1, and p53 expressions in CRC patients was accomplished with immunohistochemical technique. The patients were divided into negative and positive groups in accordance with immunohistochemical result. We compared the clinicopathological characteristics of the patients in the 2 groups, coupled with analysis of the relationship between 6 aforesaid proteins and clinicopathological characteristics. Herein, we confirmed the association of tumor location with the expression of ALD, Keap-1, and FoxO4. Also, tumor differentiation was observed to associate significantly with the expression of Keap-1, FoxO4, and Cox-2. The data also revealed that there was a correlation between smoking and expression of ALD, Keap-1, FoxO4, p53, and Cox-2. Nevertheless, insignificant difference was observed when clinicopathological characteristics were compared with cAMP response element-binding protein-2 expression. These findings suggest that ALD, Keap-1, and FoxO4 reinvolved in CRC development, and thus may be considered as potential monitoring protein for CRC.