Enhancing prognostic prediction of invasive candidiasis among cancer patients with a serum C5a-based scoring model.

PURPOSE: Invasive candidiasis poses a life-threatening risk, and early prognosis assessment is vital for timely interventions to reduce mortality. Serum C5a levels have recently been linked to prognosis, but confirmation in cancer patients is pending. METHODS: We detected the concentrations of serum C5a in hospitalized cancer patients with invasive candidiasis from 2020 to 2023, and retrospectively analyzed the clinical data. RESULTS: 372 cases were included in this study, with a 90-day mortality rate of 21.8%. Candida albicans (48.7%) remained the predominant pathogen, followed by Candida glabrata (25.5%), Candida tropicalis (12.4%), and Candida parapsilosis (8.3%). Gastrointestinal cancer was the most diagnosed pathology type (37.6%). Serum C5a demonstrated a noteworthy correlation with 90-day mortality, and employing a cutoff value of 36.7 ng/ml revealed significantly higher 90-day mortality in low-C5a patients (41.2%) compared to high-C5a patients (6.3%) (p < 0.001). We also identified no source control, no surgery, metastasis, or chronic renal failure independently correlated with the 90-day mortality. Based on this, a prognostic model combining C5a and clinical parameters was constructed, which performed better than models built solely on C5a or clinical parameters. Furthermore, we weighted scores to each parameter in the model and presented diagnostic sensitivity and specificity corresponding to different score points calculated by the model. CONCLUSION: We constructed a prognostic scoring model including serum C5a and clinical parameters, which would contribute to precise prognosis assessment and benefit the outcome among cancer patients.

SF3B3-regulated mTOR alternative splicing promotes colorectal cancer progression and metastasis.

BACKGROUND: Aberrant alternative splicing (AS) is a pervasive event during colorectal cancer (CRC) development. SF3B3 is a splicing factor component of U2 small nuclear ribonucleoproteins which are crucial for early stages of spliceosome assembly. The role of SF3B3 in CRC remains unknown. METHODS: SF3B3 expression in human CRCs was analyzed using publicly available CRC datasets, immunohistochemistry, qRT-PCR, and western blot. RNA-seq, RNA immunoprecipitation, and lipidomics were performed in SF3B3 knockdown or overexpressing CRC cell lines. CRC cell xenografts, patient-derived xenografts, patient-derived organoids, and orthotopic metastasis mouse models were utilized to determine the in vivo role of SF3B3 in CRC progression and metastasis. RESULTS: SF3B3 was upregulated in CRC samples and associated with poor survival. Inhibition of SF3B3 by RNA silencing suppressed the proliferation and metastasis of CRC cells in vitro and in vivo, characterized by mitochondria injury, increased reactive oxygen species (ROS), and apoptosis. Mechanistically, silencing of SF3B3 increased mTOR exon-skipped splicing, leading to the suppression of lipogenesis via mTOR-SREBF1-FASN signaling. The combination of SF3B3 shRNAs and mTOR inhibitors showed synergistic antitumor activity in patient-derived CRC organoids and xenografts. Importantly, we identified SF3B3 as a critical regulator of mTOR splicing and autophagy in multiple cancers. CONCLUSIONS: Our findings revealed that SF3B3 promoted CRC progression and metastasis by regulating mTOR alternative splicing and SREBF1-FASN-mediated lipogenesis, providing strong evidence to support SF3B3 as a druggable target for CRC therapy.

A novel model for predicting deep-seated candidiasis due to Candida glabrata among cancer patients: A 6-year study in a cancer center of China.

Followed by Candida albicans, Candida glabrata ranks as the second major species contributing to invasive candidiasis. Given the higher medical burden and lower susceptibility to azoles in C. glabrata infections, identifying these infections is critical. From 2016 to 2021, patients with deep-seated candidiasis due to C. glabrata and non-glabrata Candida met the criteria to be enrolled in the study. Clinical data were randomly divided into training and validation cohorts. A predictive model and nomogram were constructed using R software based on the stepwise algorithm and logistic regression. The performance of the model was assessed by the area under the receiver operating characteristic curve and decision curve analysis (DCA). A total of 197 patients were included in the study, 134 of them infected with non-glabrata Candida and 63 with C. glabrata. The predictive model for C. glabrata infection consisted of gastrointestinal cancer, co-infected with bacteria, diabetes mellitus, and kidney dysfunction. The specificity was 84.1% and the sensitivity was 61.5% in the validation cohort when the cutoff value was set to the same as the training cohort. Based on the model, treatment for patients with a high-risk threshold was better than 'treatment for all' in DCA, while opting low-risk patients out of treatment was also better than 'treatment for none' in opt-out DCA. The predictive model provides a rapid method for judging the probability of infections due to C. glabrata and will be of benefit to clinicians making decisions about therapy strategies.

Autophagy and LC3-associated phagocytosis contribute negatively to the killing capability of THP-1-derived macrophages against Candida albicans at the mid-stage.

In innate immunity, macrophages play critical roles in defending against pathogens via the lysosomal degradation function of autophagy. Two distinct autophagy pathways have been identified in decades: canonical autophagy (referred to as autophagy) and LC3-associated phagocytosis (LAP). Since several conflicting findings about the anti-Candida capability of autophagy (or LAP) have been reported, they serve as the foe or friend for Candida survival is still unclearly. The current study showed that the fungicidal process of THP-1-derived macrophages (THP-1-MФ) against Candida albicans is divided into three stages as follows, the early stage (the first 12 h, increasing in the killing capability), the mid-stage (12-24 h, no change in killing capability), and the late stage (24-48 h, decreasing of the killing capability). Autophagic protein LC3B-II reached the peak in THP-1-MФ after 24 h inoculated either with C.albicans or whole glucan particles (WGP). Thus, both anti-Candida roles of autophagy and the LAP pathway have been detected at the mid-stage. For autophagy, after 24 h inoculation with C.albicans, ULK1 increased, but p-ATG13(s318) decreased obviously in THP-1-MФ, and the killing assay showed that autophagy is unhelpful for Candida killing capability. For the LAP pathway, Rubicon and ROS raised significantly in THP-1-MФ after 24 h inoculated with C.albicans; each inhibition would sharply cut down the LC3B-II accumulation, which indicated that LAP had been induced. However, mCherry-GFP-LC3 fluorescent assay exhibited that LAP phago-lysosomal fusion has been blocked, and Rubicon knockdown facilitated the Candida killing activity. These data indicated that autophagy presented as redundant to Candida defense, and LAP phago-lysosomal fusion obstruction impairs the Candida killing capability of THP-1-MФ at the mid-stage. That may explain the no change in Candida killing capability at the mid-stage.

Drug-induced liver injury in COVID-19 treatment: Incidence, mechanisms and clinical management.

The COVID-19 outbreak triggered a serious and potentially lethal pandemic, resulting in massive health and economic losses worldwide. The most common clinical manifestations of COVID-19 patients are pneumonia and acute respiratory distress syndrome, with a variety of complications. Multiple organ failure and damage, ultimately leading to patient death, are possible as a result of medication combinations, and this is exemplified by DILI. We hope to summarize DILI caused by the antiviral drugs favipiravir, remdesivir, lopinavir/ritonavir, and hydroxychloroquine in COVID-19 patients in this review. The incidence of liver injury in the treatment of COVID-19 patients was searched on PubMed to investigate DILI cases. The cumulative prevalence of acute liver injury was 23.7% (16.1%-33.1%). We discuss the frequency of these events, potential mechanisms, and new insights into surveillance strategies. Furthermore, we also describe medication recommendations aimed at preserving DILI caused by treatment in COVID-19 patients.

Case report: Camrelizumab associated with central retinal vein occlusion.

Immunotherapy has revolutionized cancer treatment and become one of the five pillars of cancer therapy. The clinical applications of immunotherapy have been adapted to range from the management of melanoma to most tumor types. As the clinical applications of cancer immunotherapies expand, understanding the treatment-related adverse events of these drugs becomes critical in clinical practice. We report a rare case of ocular immune-related side effects associated with camrelizumab that resulted in vision loss. A 56-year-old male patient was diagnosed with small cell lung cancer. The tumor involved the porta pulmonis and mediastinum upon initial diagnosis; therefore, surgery was not possible. Upon receiving the 10th immunotherapy session with camrelizumab 200 mg, the patient's visual acuity began to decrease in his right eye and a central retinal vein occlusion. Optical coherence tomography revealed significant cystoid exudation in the macular area and vitreous hemorrhage. The patient underwent vitrectomy, phacoemulsification and intraocular lens implantation after symptom onset. Following surgery, the patient's vision was limitedly restored. This is the first clinical report in China of central retinal vein occlusion and vitreous hemorrhage associated with anti-PD-1 therapy, ultimately leading to blindness. Although rare, clinical practitioners should be concerned about ocular adverse events associated with anti-PD-1 immunotherapy and develop a high index of suspicion for this possibility since ophthalmic manifestations that are rapidly detected, closely monitored, and appropriately managed are treatable.

Identification of Cofilin-1 as a novel biomarker of atopic dermatitis using iTRAQ quantitative proteomics.

BACKGROUND: Atopic dermatitis (AD) is a chronic relapsing inflammatory skin condition; however, little is known about the pathogenesis and serum biomarker of this disease. METHODS: Isobaric tagging for relative and absolute quantitation (iTRAQ) proteomic assay was adopted to identify and quantify the differentially expressed proteins (DEPs) in the serum of AD patients. Bioinformatic analysis, including GO, Reactome, GSEA, PPI, and ssGSEA analysis, were used to identified the enriched pathways, hub proteins and immune cells. The expression level and distribution of hub proteins were confirmed by ELISA and IHC. RESULTS: Sixty-six DEPs were identified with iTRAQ proteomic assay by analyzing serum from AD patients and normal subjects. GO and Reactome analysis shown the alternated pathway were mainly involved in immunity, oxidative stress, and actin cytoskeleton. The GSEA and PPI network analysis among the DEPs were carried out and identified Cofilin-1 and profilin-1 as the core components of this network. Additionally, the disruption of Th1/Th2/Th17 cell balance and the significantly reducing of Treg, MDSC, and γδT cells was also found in AD patients using the ssGSEA analysis. Further ELISA and IHC assay validated the significantly elevated expression of Cofilin-1 in AD patients. CONCLUSION: Our results suggested that Cofilin-1 may serve as a novel biomarker for AD diagnosis.

[Low-dose Spiral Computed Tomography in Lung Cancer Screening].

Lung cancer is one of the malignant tumors with the highest morbidity and mortality in the world. The low early diagnosis rate and poor prognosis of patients have caused serious social burden. Regular screening of high-risk population by low-dose spiral computed tomography (LDCT) can significantly improve the early diagnosis rate of lung cancer and bring new opportunities for the diagnosis and treatment of lung cancer. In recent years, LDCT lung cancer screening programs have been carried out in many countries around the world and achieved good results, but there are still some controversies in the selection of screening subjects, screening frequency, cost effectiveness and other aspects. In this paper, the key factors of LDCT lung cancer screening, screening effect, pulmonary nodule management and artificial intelligence contribution to the development of LDCT will be reviewed, and the application progress of LDCT in lung cancer screening will be discussed.
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[Research Progress on the Application of Liquid Biopsy in the Diagnosis 
and Treatment of Small Cell Lung Cancer].

Small cell lung cancer (SCLC) is a malignant tumor with strong invasiveness and high mortality. It has the characteristics of easy metastasis, fast growth, high degree of malignancy and strong invasiveness. The prognosis of patients is generally poor. The current clinical diagnosis of SCLC is mainly based on tissue biopsy, which is invasive, long cycle time and high cost. In recent years, liquid biopsy has been gradually applied because of its non-invasive, comprehensive and real-time characteristics that traditional tissue biopsy does not have. The main detection objects of liquid biopsy include circulating tumor DNA (ctDNA), circulating tumor cells (CTCs) and exosomes in peripheral blood. The application of liquid biopsy in the clinical treatment of SCLC will help clinicians to improve the detailed diagnosis of SCLC patients, as well as the timely control and response to the treatment response of patients.
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Phloretin exhibits potential food-drug interactions by inhibiting human UDP-glucuronosyltransferases in vitro.

Phloretin is a well-known apple polyphenol possessing a wide variety of biological effects and has been widely used in many fields. However, it's unclear whether phloretin has an effect on the activity of human UGT enzymes. Our study indicated that phloretin inhibited human UGTs on a broad spectrum. Further kinetic analysis revealed that phloretin inhibited UGT1A1, 1A6, 1A9, 2B7, and 2B15 in a noncompetitive manner, with calculated Ki of 8.34 µM, 16.69 µM, 10.58 µM, 17.74 µM and 2.46µΜ, respectively, whereas phloretin inhibited UGT1A7 in an un-competitive manner, with calculated Ki of 5.70 µM. According to the quantitative risk prediction, co-administration of phloretin with drugs primarily metabolized by UGT1A7 and/or UGT2B15 may result in potential food-drug interactions. To sum up, when phloretin or phloretin-rich food is administered with medications metabolized by UGT1A7 and/or UGT2B15, concern should be exercised.

Potential interactions among myricetin and dietary flavonols through the inhibition of human UDP-glucuronosyltransferase in vitro.

Myricetin is a dietary flavonol and possesses multiple bioactivities, which making it an excellent nutritional supplement and a new drug candidate. However, whether myricetin and other homologous dietary flavonols affect the activities of UDP-glucuronosyltransferases (UGT) enzymes and facilitated food-drug interactions remains unclear. Our results demonstrated that myricetin displayed broad-spectrum inhibition against human UGTs. Myricetin exhibited strong inhibitory effects against UGT1A1, 1A3, 1A6, 1A7, 1A10 (IC50 < 10 µM) with non-competitive inhibition type, while serving as a moderate inhibitor against UGT1A9 and 2B7 (IC50 range from 25 to 29 µM) with competitive and mixed inhibition type, respectively. In Silico docking was carried out to explore the binding models and free energies of myricetin towards inhibitory UGTs. The potential risks of food-drug interactions after myricetin consumption were predicted by combining the in vitro inhibitory data and physiological data. The quantitative prediction in vivo of inhibition on gastrointestinal UGTs by myricetin showed that the inhibition against UGT1A1, 1A3, 1A6, 1A7, 1A9, 1A10 and 2B7 would likely occur with high risk. The follow-up findings demonstrated that morin, kaempferol, quercetin and galangin, the four homologous dietary flavonols, shared similar inhibition patterns towards UGTs. These findings altogether demonstrate that myricetin and homologous dietary flavonols have potent and broad-spectrum inhibitory effects against most human UGTs, thus suggest that much caution should be exercised when flavonols-rich foods or supplements are co-administered with UGT substrate drugs.

[Clinical Trial Progress and Application of Immune Checkpoint Inhibitors 
in the Treatment of Small Cell Lung Cancer].

Small cell lung cancer (SCLC) is a neuroendocrine tumor with fast progression, high malignancy, easy recurrence, and extremely poor prognosis. In the past 30 years, the clinical treatment strategy of SCLC has been mainly chemotherapy and radiotherapy, but the curative effect is not significant; the current immunotherapy of SCLC has gradually entered the clinic and has made certain progress. Tumor immunotherapy includes immune checkpoint inhibitors, tumor vaccines, cytokines, chimeric antigen receptor T-cell immunotherapy (CAR-T) therapy, etc. Currently, immune checkpoint inhibitors are the most widely used. This article summarizes the principles of immune checkpoint inhibitors and related drugs, summarizes their domestic and foreign clinical trials progress in SCLC treatment, reviews the biomarkers used in the therapy, and discusses its future development direction.
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[Advances in Molecular Typing of Small Cell Lung Cancer].

Small cell lung cancer (SCLC) is a highly aggressive and fatal malignant tumor. It has the characteristics of complex etiology, low differentiation, high malignancy, fast growth, strong invasiveness, early metastasis and acquired drug resistance, resulting in poor prognosis. In recent years, with the gradual deepening understanding on the molecular mechanism of SCLC and multi-omics data, it is proposed that molecular typing can be carried out according to the differential expression of key transcription factors, including SCLC-A, SCLC-N, SCLC-P and SCLC-I subtypes. Molecular typing of SCLC and its clinical application will help doctors to further optimize the detailed diagnosis and treatment plan of SCLC patients, so as to prolong the survival time and improve the quality of life of patients.
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Ribosome Proteins Represented by RPL27A Mark the Development and Metastasis of Triple-Negative Breast Cancer in Mouse and Human.

Triple-negative breast cancer (TNBC) is known to have a poor prognosis and limited treatment options. The lack of targeted therapies and poor prognosis of patients with TNBC have made it urgent to discover novel critical diagnosis and therapeutic targets in the TNBC field. Here, in the current study, we integrated the single-cell RNA-sequencing (scRNA-seq) data from four normal mouse mammary tissues and four mouse breast tumors. Comparative analysis was conducted to identify the gene profiles of normal epithelial cells and cancer cells at different models. Surprisingly, two ribosomal protein genes, Rpl27a and Rpl15, were significantly upregulated in the cancer cells in all the TNBC models. Next, we accessed the scRNA-seq data from human primary and metastatic TNBC tissues, and comparative analysis revealed gene profiles of human primary and metastatic TNBC cancer cells. Ribosomal protein genes, represented by RPL27A and RPL15, showed significantly upregulated expression in metastatic TNBC cancer cells. Pathway analysis on the upregulated genes of the metastatic TNBC cancer cells identified the key regulators and signaling pathways that were driving the metastasis of the TNBC cancer cells. Specifically, EIF2 signaling was significantly activated, and major member genes of this signaling pathway were upregulated. In vitro study revealed that targeting RPL27A or EIF2 signaling in a TNBC cell line, MDA-MB-231, significantly reduced cell migration and invasion. Altogether, these data suggested that the RPL27A gene is conducting critical functions in TNBC cancer development and metastasis and is a potential therapeutic target for TNBC.

SCD5 expression correlates with prognosis and response to neoadjuvant chemotherapy in breast cancer.

Neoadjuvant chemotherapy (NACT) represents a standard option for breast cancer. Unfortunately, about 55-80% of breast cancer patients do not have a favorable response to chemotherapy. Highly specific tumor biomarker that can predict the pathological response to neoadjuvant chemotherapy is lacking. Stearoyl-CoA desaturase 5 (SCD5) is an integral membrane protein of the endoplasmic reticulum that participates in lipid metabolism. Previous studies on the role of SCD5 in human cancers drew different conclusions. Therefore, the role of SCD5 in breast cancer remains unclear. Our study aims to understand its expression signature, prognosis value and correlation with pathological response to NACT in breast cancer using bioinformatics from public databases. Analysis of samples from public databases showed that SCD5 expression was down-regulated in some human cancers including breast cancer, and low expression of SCD5 was associated with more aggressive breast cancer phenotypes. Survival analysis revealed that SCD5 expression was related to prognosis in breast cancer. Integrated analysis of multiple public datasets indicated that SCD5 expression signature was associated with pathological response to NACT, particularly in TNBC. Based on functional enrichment analysis, the most affected biological functions in high SCD5-expressing breast cancer tissues were involved in negative regulation of cell cycle. Moreover, a significantly negative correlation between SCD5 expression and several cell cycle regulators was noted. Taken together, SCD5 was involved in the development and progression of breast cancer and might be a predictive biomarker for response to NACT. In conclusion, SCD5 could serve as a predictive biomarker of pathological response to NACT and play a carcinostatic role in breast cancer. These results provided us with clues to better understand SCD5 from the perspective of bioinformatics and highlighted the clinical importance of SCD5 in breast cancer, especially triple negative breast cancer (TNBC).

Bioinformatics analysis of Myelin Transcription Factor 1.

BACKGROUND AND OBJECTIVE: We aimed to further study the role of Myelin Transcription Factor 1(MyT1) in tumor and other diseases and epigenetic regulation, and better understand the regulatory mechanism of MyT1. METHODS: Using bioinformatics analysis, the structure and function of MyT1sequence were predicted and analyzed using bioinformatics analysis, and providing a theoretical basis for further experimental verification and understanding the regulatory mechanism of MyT1. The first, second and third-level structures of MyT1 were predicted and analyzed by bioinformatics analysis tools. RESULTS: MyT1 is found to be an unstable hydrophilic protein, rather than a secretory protein, with no signal peptide or trans-membrane domain; total amino acids located on the surface of the cell membrane. It contains seven zinc finger domains structurally. At sub-cellular level, MyT1 is localized in the nucleus. The phosphorylation site mainly exists in serine, and its secondary structure is mainly composed of random coils and alpha helices; the three-dimensional structure is analyzed by modeling. CONCLUSIONS: In this study, the structure and function of MyT1 protein were predicted, thereby providing a basis for subsequent expression analysis and functional research; it laid the foundation for further investigation of the molecular mechanism involved in the development of diseases.

A predictive nomogram for mortality of cancer patients with invasive candidiasis: a 10-year study in a cancer center of North China.

BACKGROUND: Invasive candidiasis is the most common fungal disease among hospitalized patients and continues to be a major cause of mortality. Risk factors for mortality have been studied previously but rarely developed into a predictive nomogram, especially for cancer patients. We constructed a nomogram for mortality prediction based on a retrospective review of 10 years of data for cancer patients with invasive candidiasis. METHODS: Clinical data for cancer patients with invasive candidiasis during the period of 2010-2019 were studied; the cases were randomly divided into training and validation cohorts. Variables in the training cohort were subjected to a predictive nomogram based on multivariate logistic regression analysis and a stepwise algorithm. We assessed the performance of the nomogram through the area under the receiver operating characteristic (ROC) curve (AUC) and decision curve analysis (DCA) in both the training and validation cohorts. RESULTS: A total of 207 cases of invasive candidiasis were examined, and the crude 30-day mortality was 28.0%. Candida albicans (48.3%) was the predominant species responsible for infection, followed by the Candida glabrata complex (24.2%) and Candida tropicalis (10.1%). The training and validation cohorts contained 147 and 60 cases, respectively. The predictive nomogram consisted of bloodstream infections, intensive care unit (ICU) admitted > 3 days, no prior surgery, metastasis and no source control. The AUCs of the training and validation cohorts were 0.895 (95% confidence interval [CI], 0.846-0.945) and 0.862 (95% CI, 0.770-0.955), respectively. The net benefit of the model performed better than "treatment for all" in DCA and was also better for opting low-risk patients out of treatment than "treatment for none" in opt-out DCA. CONCLUSION: Cancer patients with invasive candidiasis exhibit high crude mortality. The predictive nomogram established in this study can provide a probability of mortality for a given patient, which will be beneficial for therapeutic strategies and outcome improvement.

PPAI: a web server for predicting protein-aptamer interactions.

BACKGROUND: The interactions between proteins and aptamers are prevalent in organisms and play an important role in various life activities. Thanks to the rapid accumulation of protein-aptamer interaction data, it is necessary and feasible to construct an accurate and effective computational model to predict aptamers binding to certain interested proteins and protein-aptamer interactions, which is beneficial for understanding mechanisms of protein-aptamer interactions and improving aptamer-based therapies. RESULTS: In this study, a novel web server named PPAI is developed to predict aptamers and protein-aptamer interactions with key sequence features of proteins/aptamers and a machine learning framework integrated adaboost and random forest. A new method for extracting several key sequence features of both proteins and aptamers is presented, where the features for proteins are extracted from amino acid composition, pseudo-amino acid composition, grouped amino acid composition, C/T/D composition and sequence-order-coupling number, while the features for aptamers are extracted from nucleotide composition, pseudo-nucleotide composition (PseKNC) and normalized Moreau-Broto autocorrelation coefficient. On the basis of these feature sets and balanced the samples with SMOTE algorithm, we validate the performance of PPAI by the independent test set. The results demonstrate that the Area Under Curve (AUC) is 0.907 for prediction of aptamer, while the AUC reaches 0.871 for prediction of protein-aptamer interactions. CONCLUSION: These results indicate that PPAI can query aptamers and proteins, predict aptamers and predict protein-aptamer interactions in batch mode precisely and efficiently, which would be a novel bioinformatics tool for the research of protein-aptamer interactions. PPAI web-server is freely available at http://39.96.85.9/PPAI.

Rapid UV-radiation synthesis of polyacrylate cryogel oil-sorbents with adaptable structure and performance.

Macro-porous poly(lauryl acrylate) cryogel sheets as oil-sorbents were prepared through UV-radiation cryo-polymerizations in 1, 4-dioxane at low temperatures (-5, -2 and 0 °C) within 30 min. The influences of total monomer concentration, crosslinking monomer amount and polymerization temperature on the formation of cryogels were studied. The chemical structure and porous morphology were characterized through the techniques of Fourier transform infrared spectroscopy, thermal gravimetric analysis, contact angle measurement and scanning electron microscopy, confirming the features of high hydrophobicity, macro-porosity and good thermal stability. As well, the comparison between conventional gels prepared at room temperature and cryogels at lower temperatures was made, showing the higher rate of cryo-polymerization than conventional polymerization under the same UV-radiation condition. The swelling investigation was carried out with several organic solvents and oils. Enhanced performance of oil absorption was observed for those cryogels considering the absorption capacity and absorption rate. Variation of initiator amount and acrylate monomers could also modulate the absorption capacity. Those cryogel oil-sorbents exhibited wide adaptability, good reusability and high-temperature tolerance. Thus, this rapid and low-cost fabrication opens out a novel pathway to prepare efficient oil-sorbents used in waste water treatment.