Palladium-catalyzed (Z)-selective allylation of phosphine oxides with vinylethylene carbonates to construct phosphorus allyl alcohols.

Allylphosphine oxide compounds are important building blocks with broad applications in organic synthesis and pharmaceutical science. Herein, we report an unprecedented palladium-catalyzed allylation of phosphine oxides with vinylethylene carbonates, producing various phosphorus allyl alcohols in excellent yields with high Z-selectivity. In addition, gram-scale synthesis and further functional group transformations demonstrate the practical utility of this synthetic method.

Delta-SVV as a Predictor for Circulating Blood Volume Evaluation during Intraoperative Period: A Prospective Cohort Study.

Background: Precise fluid therapy is extremely important during surgeries, as enough circulating blood volume ensures tissue perfusion and cell oxygenation. Yet, extra fluid volume could cause other adverse events, such as heart failure, intestinal swelling, etc. Thus, precise evaluation of the circulating blood volume is essential for maintaining sufficient circulating blood volume and avoiding excessive fluid infusion. Objective: This study aimed to evaluate the relationship between SVV and circulating blood volume during intraoperative fluid therapy. Methods: SVV was measured by FloTrac/Vigileo in the study. A prospective cohort study was conducted. 103 patients aged from 20 to 60 years old with an ASA Grade I-II and a diagnosis of meningioma less than 3 centimeters planning for selective neurosurgery were randomly divided into the Crystalloid Group and the Colloid Group. After induction, each Patient received 15 ml/kg of Plasma-Lyte-A or 6% hydroxyethyl starch in 30 min followed by continuous infusion at the speed of 0.1 ml/kg during the next 60 min. Hb concentration, Hct, Delta-BV/kg, and Delta-SVV were recorded every 5 minutes. Results: The delta-SVV and Delta-bv/kg were significantly higher in the Crystalloid Group than that of the Colloid Group. There was a strong linear correlation between Delta-SVV and Delta-bv/kg in both Crystalloid Group (Delta-bv / kg = 1.108 Delta-SVV + 0.0712, P < .001) and Colloid Group (Delta-bv / kg = 1.047 Delta-SVV + 0.4153, P < .001). An equation between Delta-bv/kg and Delta-SVV was established (Delta-bv / kg = 1.099 Delta-SVV + 0.1139, P < .001). Conclusion: In conclusion, SVV measured by FloTrac / Vigileo could guile fluid therapy precisely by predicting the blood volume of patients during the intraoperative period, as it has a strong linear correlation with the blood volume of patients who underwent general anesthesia, meaning anesthesiologist could calculate the exact fluid volume for patients' infusion. Further studies with large cohorts and centers would be needed to validate its efficiency.

Classification of cow behavior patterns using inertial measurement units and a fully convolutional network model.

In this study, we aimed to classify 7 cow behavior patterns automatically with an inertial measurement unit (IMU) using a fully convolutional network (FCN) algorithm. Behavioral data of 12 cows were collected by attaching an IMU in a waterproof box on the neck behind the head of each cow. Seven behavior patterns were considered: rub scratching (leg), ruminating-lying, lying, feeding, self-licking, rub scratching (neck), and social licking. To simplify the data and compare classification performance with or without magnetometer data, the 9-axis IMU data were reduced using the square root of the sum of squares to develop 2 datasets. Comparing the classification accuracy of the 3 models using a window size of 64 with 6-axis data and a window size of 128 with both 6-axis and 9-axis data, the best overall accuracy (83.75%) was achieved using the FCN model with a window size of 128 (12.8 s) using all IMU data. This model achieved classification accuracies of 83.2, 96.5, 92.8, 98.1, 82.9, 87.2, and 45.2% for ruminating-lying, lying, feeding, rub scratching (leg), self-licking, rub scratching (neck), and social licking, respectively. As a sequence of varied and intensive movement, the classification accuracy of behavior patterns related to skin disease was lower; better classification of these behavior patterns could be achieved with full IMU data and a larger window size. In the future, additional data will take into account different data types, such as audio and video data, to further enhance performance. In addition, an adaptive sliding window size will be used to improve model performance.

The long non-coding RNA lncMYOZ2 mediates an AHCY/MYOZ2 axis to promote adipogenic differentiation in porcine preadipocytes.

Long non-coding RNAs (lncRNAs) play a vital role in regulating adipogenesis. However, the associated regulatory mechanisms have yet to be described in detail in pig. In this study, we demonstrate a critical role for lncMYOZ2 in adipogenesis from porcine preadipocytes. Specifically, lncMYOZ2 was more abundant in the adipose tissue of Mashen (fat-type) pigs than for Large White (lean-type) pigs, and knockdown of this lncRNA significantly inhibited the differentiation of porcine preadipocytes into adipocytes. Mechanistically, we used RNA pull-down and RIP assays to establish that lncMYOZ2 interacts with adenosylhomocysteinase (AHCY). Moreover, lncMYOZ2 knockdown increased promoter methylation of the target gene MYOZ2 and lowered its expression. Finally, we describe a positive regulatory role for MYOZ2 in adipogenesis. Collectively, these findings establish lncMYOZ2 as an important epigenetic regulator of adipogenesis via the aforementioned AHCY/MYOZ2 pathway, and provide insights into the role of lncRNAs in porcine adipose development.

NrtNet: An Unsupervised Method for 3D Non-Rigid Point Cloud Registration Based on Transformer.

Self-attention networks have revolutionized the field of natural language processing and have also made impressive progress in image analysis tasks. Corrnet3D proposes the idea of first obtaining the point cloud correspondence in point cloud registration. Inspired by these successes, we propose an unsupervised network for non-rigid point cloud registration, namely NrtNet, which is the first network using a transformer for unsupervised large deformation non-rigid point cloud registration. Specifically, NrtNet consists of a feature extraction module, a correspondence matrix generation module, and a reconstruction module. Feeding a pair of point clouds, our model first learns the point-by-point features and feeds them to the transformer-based correspondence matrix generation module, which utilizes the transformer to learn the correspondence probability between pairs of point sets, and then the correspondence probability matrix conducts normalization to obtain the correct point set corresponding matrix. We then permute the point clouds and learn the relative drift of the point pairs to reconstruct the point clouds for registration. Extensive experiments on synthetic and real datasets of non-rigid 3D shapes show that NrtNet outperforms state-of-the-art methods, including methods that use grids as input and methods that directly compute point drift.

An Improved Mixture Density Network for 3D Human Pose Estimation with Ordinal Ranking.

Estimating accurate 3D human poses from 2D images remains a challenge due to the lack of explicit depth information in 2D data. This paper proposes an improved mixture density network for 3D human pose estimation called the Locally Connected Mixture Density Network (LCMDN). Instead of conducting direct coordinate regression or providing unimodal estimates per joint, our approach predicts multiple possible hypotheses by the Mixture Density Network (MDN). Our network can be divided into two steps: the 2D joint points are estimated from the input images first; then, the information of human joints correlation is extracted by a feature extractor. After the human pose feature is extracted, multiple pose hypotheses are generated via the hypotheses generator. In addition, to make better use of the relationship between human joints, we introduce the Locally Connected Network (LCN) as a generic formulation to replace the traditional Fully Connected Network (FCN), which is applied to a feature extraction module. Finally, to select the most appropriate 3D pose result, a 3D pose selector based on the ordinal ranking of joints is adopted to score the predicted pose. The LCMDN improves the representation capability and robustness of the original MDN method notably. Experiments are conducted on the Human3.6M and MPII dataset. The average Mean Per Joint Position Error (MPJPE) of our proposed LCMDN reaches 50 mm on the Human3.6M dataset, which is on par or better than the state-of-the-art works. The qualitative results on the MPII dataset show that our network has a strong generalization ability.

miR-128 regulated the proliferation and autophagy in porcine adipose-derived stem cells through targeting the JNK signaling pathway.

PURPOSE: microRNA-128 (miR-128), a brain-enriched microRNA, has been reported to play a crucial role in the treatment of diseases. The c-Jun N-terminal kinase (JNK) signaling pathway exerts various biological functions such as regulation of cell proliferation, differentiation and apoptosis. In this study, we investigated the role of the miRNA-128-JNK signaling pathway in proliferation, apoptosis and autophagy of porcine adipose-derived stem cells (ASCs). METHODS: After over-expressing miR-128 in porcine ASCs, cell proliferation was determined by 2,3-Bis-(2-Methoxy-4-Nitro-5-Sulfophenyl)-2H-Tetrazolium-5-Carboxanilide (XTT) method, cell apoptosis was observed by Flow cytometry (FCM), the expression of miR-128, B-cell lymphoma 2 (Bcl-2), and Bcl-2-associated X protein (Bax) was measured by RNA preparation and reverse transcription polymerase chain reaction (RT-PCR), and protein expression of JNK, phosphorylated JNK (p-JNK) and LC3B was analyzed by Western Blot analysis. RESULTS: The over-expression of miR-128 potently promoted cell proliferation and autophagy while suppressed the apoptosis of porcine ASCs. In addition, the down-regulated expression level of p-JNK was detected in miR-128-over-expressed porcine ASCs. However, followed by the block of the JNK signaling pathway using SP600125 inhibitor, the effects of miR-128 on the proliferation, apoptosis and autophagy of porcine ASCs were significantly suppressed. CONCLUSION: It is demonstrated that the miR-128-JNK signaling pathway is a potential therapeutic target for the treatment of obesity.

IRX5 prompts genomic instability in colorectal cancer cells.

The Iroquois homeobox gene 5 (IRX5), one of the members of the Iroquois homeobox family, has been identified to correlate with worse prognosis in many cancers, including colorectal cancer (CRC). In this study, upregulation of IRX5 revealed a great reduction in the proliferation of CRC colorectal cancer cell line SW480 and DLD-1, which was accompanied by G1/S arrest, increased expression in cyclin E1, P21, and P53 and a decrease in cyclin A2, B1, and D1. Furthermore, IRX5-mediated an increase expression of RH2A protein, the biomarker of DNA damage. Consequently, the SA-ß-gal level is higher in IRX5-overexpression cells compared to control ones, which showed elevated DNA damage triggered cellular senescence. Recapitulating the above findings, IRX5 exhibited higher levels of genomic instability. IRX5 may be a perspective target for cancer therapy and it deserves further investigation.

IRX5 promotes colorectal cancer metastasis by negatively regulating the core components of the RHOA pathway.

Colorectal cancer (CRC) is one of the most common malignant tumors worldwide. As tumor metastasis is the leading cause of death in patients with CRC, it is important to elucidate the molecular mechanisms that drive CRC metastasis. Studies have shown a close relationship between Iroquois homeobox (IRX) family genes and multiple cancers, while the mechanism by which IRX5 promotes CRC metastasis is unclear. Therefore, we focused on the involvement of IRX5 in CRC metastasis. In this study, analyses of clinical data indicated that the expression of IRX5 was coincided with metastatic colorectal tumors tissues and was negatively correlated with the overall survival of patients with CRC. Functional analysis showed that IRX5 promoted the migration and invasion of CRC cells, accompanied by a large number of cellular protrusions. IRX5-overexpressing cells were more likely to form metastatic tumors in nude mice. Further analysis demonstrated that the core components of the RHOA/ROCK1/LIMK1 pathway were significantly inhibited in IRX5-overexpressing cells. Overexpression of LIMK1 effectively reversed the enhanced cellular motility caused by IRX5 overexpression. Moreover, we found that high levels of IRX5 in intestinal tissues were correlated with the inflammatory response. IRX5 was significantly increased in azoxymethane/dextran sodium sulfate intestinal tissue of mice and IRX5-overexpressing may also enhance chemokines CXCL1 and CXCL8. In summary, our findings suggested that IRX5 promoted CRC metastasis by inhibiting the RHOA-ROCK1-LIMK1 axis, which correlates with a poor prognosis.

Oncological safety of intrafascial nerve-sparing radical prostatectomy compared with conventional process: a pooled review and meta-regression analysis based on available studies.

BACKGROUND: Intrafascial prostatectomy was a modified technique from the conventional nerve-sparing surgery in order to improve patients' post-surgical continence and erectile function; however, ongoing controversy exists regarding the oncological safety of this technique. In this study we aimed to provide a critical and pooled analysis based on published literatures regarding the oncological outcomes after intrafascial nerve-sparing prostatectomy. METHODS: Database searches were performed for published articles till June 2018 on PubMed. Three reviewers screened fulfilled papers and extracted data independently. Main outcome was the positive surgical margins (PSMs) rates stratified by pathological stages. We performed both one-arm and comparative meta-analysis to evaluate the oncological safety of intrafascial technique. Moreover, we built meta-regression models to assess the confounding factors. RESULTS: We retrieved a total of 117 records after electronic search, of which 21 studies were finally included in this review. There were 15 controlled studies and 6 surgical series. Our one-arm meta-analysis demonstrated that the total PSM rates after intrafascial techniques ranging from 2.2 to 35%, with a pooled rate of 14.5% on average (480 of 3151 patients, 95% confidence interval[CI]: 11.2-17.5%). Meta-regression model showed that patients' age, pT2 cancer percentage and Selection Score of Oncological Safety (SSOS) were significantly associated with total PSM rate; moreover, each 1 point of SSOS could decrease the total PSM rate by 1.3% on average. Comparative meta-analysis demonstrated that there was no significant difference between intra- and inter-fascial group regarding PSM rates. CONCLUSIONS: With stringent case selection and when performed by experienced surgeons, intrafascial prostatectomy could offer an acceptable or, at least, equivalent PSM rate compared with the conventional interfascial approach. Preoperative SSOS more than 7 points could be considered as an indication of intrafascial radical prostatectomy.

Plasma Gelsolin Induced Glomerular Fibrosis via the TGF-ß1/Smads Signal Transduction Pathway in IgA Nephropathy.

Glomerular fibrosis has been shown to be closely related to the progression and prognosis of IgA nephropathy (IgAN). However, mechanism underlying IgAN glomerular fibrosis remains unclear. Recently, our study showed that plasma gelsolin (pGSN) was decreased in the serum of an IgAN mouse model and that pGSN deposition was found in the glomeruli. Another cytokine, TGF-ß1, which is closely related to glomerular fibrosis, was also found to be highly expressed in the glomeruli. In the present study, we report that pGSN induces glomerular fibrosis through the TGF-ß1/Smads signal transduction pathway. This is supported by the following findings: human mesangial cells (HMCs) show remarkable morphological changes and proliferation in response to co-stimulation with pGSN and polymeric IgA1 (pIgA1) from IgAN patients compared to other controls. Moreover, ELISA assays showed that more TGF-ß1 secretion was found in HMCs supernatants in the co-stimulation group. Further experiments showed increased TGF-ß1, Smad3, p-Smad2/3, Smad4, and collagen 1 and decreased Smad7 expression in the co-stimulation group. Our present study implied that the synergistic effect of pGSN and pIgA induced glomerular fibrosis via the TGF-ß1/Smads signal transduction pathway. This might be a potential mechanism for the glomerular fibrosis observed in IgAN patients.

Expression and Correlation of HER2/P53/VEGF in Marjolin's Ulcer.

Marjolin's ulcer is described as malignant lesions developed in the injured skin, which can cause several kinds of malignancies. Our results showed that no HER2 but p53 was detected in Majorlin's ulcer samples. Meanwhile, by statistical analysis, we found that the positive rate of p53 in Majorlin's ulcer samples was associated with the pathological type of ulcer canceration and degree of tumor differentiation. The positive expression rate of vascular endothelial growth factor (VEGF) was 62.5% in poorly differentiated squamous cell carcinoma (SCC), 39.4% in moderately differentiated SCC, and 66.7% in well-differentiated SCC, respectively. Furthermore, some cases of Majorlin's ulcer with positive P53 were negative for VEGF, while some cases with positive VEGF were negative for P53. Image superposition showed that VEGF expression was absent or minimal in p53-positive cases. However, P53 was not expressed or rarely expressed in VEGF-positive cases. Our results of this study will suggest that P53 can be used as the mark of Marjolin's ulcer differentiation, and there may be some interaction between P53 and VEGF in Marjolin's ulcer. The regulation of microenvironment in the oncogenesis, progression, and differentiation of Marjolin's ulcer is complex and needs further study.

Effects of oxytetracycline on variation in intracellular and extracellular antibiotic resistance genes during swine manure composting.

This research aimed to investigate the alterations in extracellular (eARGs) and intracellular (iARGs) antibiotic resistance genes in response to oxytetracycline (OTC), and unravel the dissemination mechanism of ARGs during composting. The findings revealed both low (L-OTC) and high contents (H-OTC) of OTC significantly enhanced absolute abundance (AA) of iARGs (p < 0.05), compared to CK (no OTC). Composting proved to be a proficient strategy for removing eARGs, while AA of eARGs was significantly enhanced in H-OTC (p < 0.05). OTC resulted in an increase in AA of mobile genetic elements (MGEs), ATP levels, antioxidant and DNA repair enzymes in bacteria in compost product. Structural equation model further demonstrated that OTC promoted bacterial DNA repair and antioxidant enzyme activities, altered bacterial community and enhanced MGEs abundance, thereby facilitating iARGs dissemination. This study highlights OTC can increase eARGs and iARGs abundance, underscoring the need for appropriate countermeasures to mitigate potential hazards.

Esculetin Alleviates IL-1ß-Evoked Nucleus Pulposus Cell Death, Extracellular Matrix Remodeling, and Inflammation by Activating Nrf2/HO-1/NF-kb.

Inflammation, extracellular matrix metabolic dysfunction, and oxidative stress are key pathogenic characteristics of intervertebral disk degeneration (IVDD), a major pathogenic cause of low back pain. Esculetin possesses anti-injury, anti-inflammation, and antinociceptive properties. This study aimed to explore its role in IVDD. In this research, esculetin exhibited little cytotoxicity to human nucleus pulposus cells (NPCs). Moreover, esculetin increased cell viability under IL-1ß stimulation but attenuated IL-1ß-induced cell apoptosis and caspase-3 activity. Furthermore, IL-1ß-evoked increases in intracellular reactive oxygen species and malondialdehyde (MDA) levels, and decreases in superoxide dismutase (SOD) activity were reversed after esculetin treatment, indicating the antioxidative stress efficacy of esculetin. Esculetin alleviated the inhibitory effects of IL-1ß on the transcription and protein expression of anabolic biomarkers (collagen II and aggrecan), accompanied by decreases in expression and release of catabolic biomarkers MMP-3 and MMP-13 from NPCs. Moreover, IL-1ß exposure enhanced the expression levels of the inflammatory mediator nitric oxide and inflammatory cytokine IL-6 and TNF-α, which were overturned after esculetin treatment. Additionally, esculetin activated the nuclear factor-erythroid 2-related factor 2 (Nrf2)/heme oxygenase 1 (HO-1) to inhibit the activation of nuclear factor κB (NF-κB) signaling in NPCs. Importantly, suppression of Nrf2 signaling reversed the protective efficacy of esculetin against IL-1ß-mediated oxidative injury, matrix metabolism disruption, and inflammatory response in NPCs. Together, esculetin may alleviate IL-1ß-induced dysfunction in NPCs by regulating the Nrf2/HO-1/NF-kb signaling, indicating its potential as a promising therapeutic agent against IVDD.

Unsupervised distribution-aware keypoints generation from 3D point clouds.

Keypoints extraction from 3D objects is a fundamental task in point cloud processing. The ideal keypoints should be an ordered and well-aligned set of points that effectively reflect the shape and structure of the object. To this end, this paper proposes an unsupervised 3D point cloud keypoints generation network with the consideration of the probability distribution of keypoints and spatial distribution among keypoints. The network downsamples and groups the 3D point cloud, obtaining local features of the point cloud. The local features are leveraged to explicitly learn the mixture probability distribution of keypoint position. A composite loss function that comprehensively considers shape similarity, point importance, and geometric constraint is proposed to guide the network in generating keypoints with semantic consistency and regular spatial distribution. The experimental results and quantitative comparisons on the ShapeNet and KeypointNet datasets demonstrate that the proposed method achieves ordered, well-aligned, and robust keypoints generation for 3D point clouds. The source code of the proposed method is available at https://github.com/djzgroup/Keypoints.

Immunotherapy in the context of sepsis-induced immunological dysregulation.

Sepsis is a clinical syndrome caused by uncontrollable immune dysregulation triggered by pathogen infection, characterized by high incidence, mortality rates, and disease burden. Current treatments primarily focus on symptomatic relief, lacking specific therapeutic interventions. The core mechanism of sepsis is believed to be an imbalance in the host's immune response, characterized by early excessive inflammation followed by late immune suppression, triggered by pathogen invasion. This suggests that we can develop immunotherapeutic treatment strategies by targeting and modulating the components and immunological functions of the host's innate and adaptive immune systems. Therefore, this paper reviews the mechanisms of immune dysregulation in sepsis and, based on this foundation, discusses the current state of immunotherapy applications in sepsis animal models and clinical trials.

Elevated Ozone Reduces the Quality of Tea Leaves but May Improve the Resistance of Tea Plants.

Tropospheric ozone (O3) pollution can affect plant nutritional quality and secondary metabolites by altering plant biochemistry and physiology, which may lead to unpredictable effects on crop quality and resistance to pests and diseases. Here, we investigated the effects of O3 (ambient air, Am; ambient air +80 ppb of O3, EO3) on the quality compounds and chemical defenses of a widely cultivated tea variety in China (Camellia sinensis cv. 'Baiye 1 Hao') using open-top chamber (OTC). We found that elevated O3 increased the ratio of total polyphenols to free amino acids while decreasing the value of the catechin quality index, indicating a reduction in leaf quality for green tea. Specifically, elevated O3 reduced concentrations of amino acids and caffeine but shows no impact on the concentrations of total polyphenols in tea leaves. Within individual catechins, elevated O3 increased the concentrations of ester catechins but not non-ester catechins, resulting in a slight increase in total catechins. Moreover, elevated O3 increased the emission of biogenic volatile organic compounds involved in plant defense against herbivores and parasites, including green leaf volatiles, aromatics, and terpenes. Additionally, concentrations of main chemical defenses, represented as condensed tannins and lignin, in tea leaves also increased in response to elevated O3. In conclusion, our results suggest that elevated ground-level O3 may reduce the quality of tea leaves but could potentially enhance the resistance of tea plants to biotic stresses.

INTERPRETABLE MACHINE LEARNING FOR PREDICTING RISK OF INVASIVE FUNGAL INFECTION IN CRITICALLY ILL PATIENTS IN THE INTENSIVE CARE UNIT: A RETROSPECTIVE COHORT STUDY BASED ON MIMIC-IV DATABASE.

ABSTRACT: The delayed diagnosis of invasive fungal infection (IFI) is highly correlated with poor prognosis in patients. Early identification of high-risk patients with invasive fungal infections and timely implementation of targeted measures is beneficial for patients. The objective of this study was to develop a machine learning-based predictive model for invasive fungal infection in patients during their intensive care unit (ICU) stay. Retrospective data was extracted from adult patients in the MIMIC-IV database who spent a minimum of 48 h in the ICU. Feature selection was performed using LASSO regression, and the dataset was balanced using the BL-SMOTE approach. Predictive models were built using six machine learning algorithms. The Shapley additive explanation algorithm was used to assess the impact of various clinical features in the optimal model, enhancing interpretability. The study included 26,346 ICU patients, of whom 379 (1.44%) were diagnosed with invasive fungal infection. The predictive model was developed using 20 risk factors, and the dataset was balanced using the borderline-SMOTE (BL-SMOTE) algorithm. The BL-SMOTE random forest model demonstrated the highest predictive performance (area under curve = 0.88, 95% CI = 0.84-0.91). Shapley additive explanation analysis revealed that the three most influential clinical features in the BL-SMOTE random forest model were dialysis treatment, APSIII scores, and liver disease. The machine learning model provides a reliable tool for predicting the occurrence of IFI in ICU patients. The BL-SMOTE random forest model, based on 20 risk factors, exhibited superior predictive performance and can assist clinicians in early assessment of IFI occurrence in ICU patients. Importance: Invasive fungal infections are characterized by high incidence and high mortality rates characteristics. In this study, we developed a clinical prediction model for invasive fungal infections in critically ill patients based on machine learning algorithms. The results show that the machine learning model based on 20 clinical features has good predictive value.

Development and validation of machine learning models to predict MDRO colonization or infection on ICU admission by using electronic health record data.

BACKGROUND: Multidrug-resistant organisms (MDRO) pose a significant threat to public health. Intensive Care Units (ICU), characterized by the extensive use of antimicrobial agents and a high prevalence of bacterial resistance, are hotspots for MDRO proliferation. Timely identification of patients at high risk for MDRO can aid in curbing transmission, enhancing patient outcomes, and maintaining the cleanliness of the ICU environment. This study focused on developing a machine learning (ML) model to identify patients at risk of MDRO during the initial phase of their ICU stay. METHODS: Utilizing patient data from the First Medical Center of the People's Liberation Army General Hospital (PLAGH-ICU) and the Medical Information Mart for Intensive Care (MIMIC-IV), the study analyzed variables within 24 h of ICU admission. Machine learning algorithms were applied to these datasets, emphasizing the early detection of MDRO colonization or infection. Model efficacy was evaluated by the area under the receiver operating characteristics curve (AUROC), alongside internal and external validation sets. RESULTS: The study evaluated 3,536 patients in PLAGH-ICU and 34,923 in MIMIC-IV, revealing MDRO prevalence of 11.96% and 8.81%, respectively. Significant differences in ICU and hospital stays, along with mortality rates, were observed between MDRO positive and negative patients. In the temporal validation, the PLAGH-ICU model achieved an AUROC of 0.786 [0.748, 0.825], while the MIMIC-IV model reached 0.744 [0.723, 0.766]. External validation demonstrated reduced model performance across different datasets. Key predictors included biochemical markers and the duration of pre-ICU hospital stay. CONCLUSIONS: The ML models developed in this study demonstrated their capability in early identification of MDRO risks in ICU patients. Continuous refinement and validation in varied clinical contexts remain essential for future applications.

A new border for circadian rhythm gene NFIL3 in diverse fields of cancer.

The circadian rhythm disorder and abnormal expression of rhythm genes are related to many diseases, especially cancer. Rhythm gene NFIL3 is involved in energy metabolism and immune cell differentiation, and its aberrant expression is associated with metabolic diseases and inflammation. Previously, numerous studies have shown that aberrant NFIL3 expression is associated with tumorigenesis, progression, and chemotherapy resistance. For instance, NFIL3 performs as a nuclear transcription factor, impacts cell proliferation, represses apoptosis, and promotes cancer cell invasion and metastasis by regulating the transcription of target genes. In addition, NFIL3 expressed in cancer cells influences the type and proportion of infiltrated immune cells in the tumor microenvironment. Increased expression of NFIL3 induces the chemotherapy and immunotherapy resistance in cancer. In this review, we summarized the pathological functions of NFIL3 in tumorigenesis, cancer development, and treatment. The rhythm gene NFIL3 can be used as a promising target in cancer therapy in the future.