Objective:To explore the optimal blood glucose-lowering strategies for patients with diabetic ketoacidosis (DKA) to enhance personalized treatment effects using machine learning techniques based on the United States Critical Care Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ).Methods:Utilizing the MIMIC-Ⅳ database, the case data of 2 096 patients with DKA admitted to the intensive care unit (ICU) at Beth Israel Deaconess Medical Center from 2008 to 2019 were analyzed. Machine learning models were developed, and receiver operator characteristic curve (ROC curve) and precision-recall curve (PR curve) were plotted to evaluate the model's effectiveness in predicting four common adverse outcomes: hypoglycemia, hypokalemia, reductions in Glasgow coma scale (GCS), and extended hospital stays. The risk of adverse outcomes was analyzed in relation to the rate of blood glucose decrease. Univariate and multivariate Logistic regression analyses were conducted to examine the relationship between relevant factors and the risk of hypokalemia. Personalized risk interpretation methods and predictive technologies were applied to individualize the analysis of optimal glucose control ranges for patients.Results:The machine learning models demonstrated excellent performance in predicting adverse outcomes in patients with DKA, with areas under the ROC curve (AUROC) and 95% confidence interval (95% CI) for predicting hypoglycemia, hypokalemia, GCS score reduction, and extended hospital stays being 0.826 (0.803-0.849), 0.850 (0.828-0.870), 0.925 (0.903-0.946), and 0.901 (0.883-0.920), respectively. Analysis of the relationship between the rate of blood glucose reduction and the risk of four adverse outcomes showed that a maximum glucose reduction rate > 6.26 mmol·L -1·h -1 significantly increased the risk of hypoglycemia ( P < 0.001); a rate > 2.72 mmol·L -1·h -1 significantly elevated the risk of hypokalemia ( P < 0.001); a rate > 5.53 mmol·L -1·h -1 significantly reduced the risk of GCS score reduction ( P < 0.001); and a rate > 8.03 mmol·L -1·h -1 significantly shortened the length of hospital stay ( P < 0.001). Multivariate Logistic regression analysis indicated significant correlations between maximum bicarbonate levels, blood urea nitrogen levels, and total insulin doses with the risk of hypokalemia (all P < 0.01). In terms of establishing personalized optimal treatment thresholds, assuming optimal glucose reduction thresholds for hypoglycemia, hypokalemia, GCS score reduction, and extended hospital stay were x1, x2, x3, x4, respectively, the recommended glucose reduction rates to minimize the risks of hypokalemia and hypoglycemia should be ≤min{ x1, x2}, while those to reduce GCS score decline and extended hospital stay should be ≥ max{ x3, x4}. When these ranges overlap, i.e., max{ x3, x4} ≤ min{ x1, x2}, this interval was the recommended optimal glucose reduction range. If there was no overlap between these ranges, i.e., max{ x3, x4} > min{ x1, x2}, the treatment strategy should be dynamically adjusted considering individual differences in the risk of various adverse outcomes. Conclusion:The machine learning models shows good performance in predicting adverse outcomes in patients with DKA, assisting in personalized blood glucose management and holding important clinical application prospects.

Lenvatinib, a second-generation multi-receptor tyrosine kinase inhibitor approved by the FDA for first-line treatment of advanced liver cancer, facing limitations due to drug resistance. Here, we applied a multidimensional, high-throughput screening platform comprising patient-derived resistant liver tumor cells (PDCs), organoids (PDOs), and xenografts (PDXs) to identify drug susceptibilities for conquering lenvatinib resistance in clinically relevant settings. Expansion and passaging of PDCs and PDOs from resistant patient liver tumors retained functional fidelity to lenvatinib treatment, expediting drug repurposing screens. Pharmacological screening identified romidepsin, YM155, apitolisib, NVP-TAE684 and dasatinib as potential antitumor agents in lenvatinib-resistant PDC and PDO models. Notably, romidepsin treatment enhanced antitumor response in syngeneic mouse models by triggering immunogenic tumor cell death and blocking the EGFR signaling pathway. A combination of romidepsin and immunotherapy achieved robust and synergistic antitumor effects against lenvatinib resistance in humanized immunocompetent PDX models. Collectively, our findings suggest that patient-derived liver cancer models effectively recapitulate lenvatinib resistance observed in clinical settings and expedite drug discovery for advanced liver cancer, providing a feasible multidimensional platform for personalized medicine.

Osimertinib is an irreversible third representative epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) for the treatment of non-small cell lung cancer (NSCLC) with T790M resistance and classical EGFR mutations. However, the therapeutic effectiveness of osimertinib is limited by acquired drug-resistance, poor water solubility and low tumor accumulation rates. Nanodrug delivery systems can increase the solubility and stability of drugs, prolong the blood circulation time of drugs, improve the uptake rate of cells, promote drug accumulation in tumor tissues, and improve drug resistance. Thus, they are effective in overcoming the limitations of traditional targeted drugs. In this study, we reviewed the mechanism of action of the third-generation EGFR-TKI osimertinib, focused on research advances in osimertinib nanodrug delivery systems against NSCLC, and explored the challenges and future development direction in this field.

Klebsiella oxytoca is an important opportunistic pathogen which cause community or hospital-acquired infections in adults and children. The disease it most causes is antibiotic-associated hemorrhagic colitis (AAHC). It can also cause diseases such as urinary tract infections, pneumonia and bloodstream infections. The cytotoxins including Tilivalline and Tilimycin are important virulence factors for Klebsiella oxytoca, mainly causing AAHC. This article reviewed the progress of research on the prevalence, pathogenicity and mechanisms of K.oxytoca, hoping to improve the understanding of K.oxytoca and provide guidance on disease prevention and treatment.

The kidneys are one of the main excretory organs for drugs and when drugs are not excreted effectively, they can accumulate in the kidneys or in the interstitial tubules, leading to drug-induced kidney injury. The tubulointerstitium accounts for 80% of the volume of the kidney and is the primary site of response to various types of renal injury. This article focuses on drug-induced acute interstitial nephritis, highlighting its clinical symptoms, listing common induction drugs, analysing pathological features, and explaining its pathogenesis from the perspective of immune response, with the aim of providing a basic and clinical evidence for subsequent studies.

Radiotherapy is widely used in the management of advanced colorectal cancer (CRC). However, the clinical efficacy is limited by the safe irradiated dose. Sensitizing tumor cells to radiotherapy via interrupting DNA repair is a promising approach to conquering the limitation. The BRCA1-BARD1 complex has been demonstrated to play a critical role in homologous recombination (HR) DSB repair, and its functions may be affected by HERC2 or BAP1. Accumulated evidence illustrates that the ubiquitination-deubiquitination balance is involved in these processes; however, the precise mechanism for the cross-talk among these proteins in HR repair following radiation hasn't been defined. Through activity-based profiling, we identified PT33 as an active entity for HR repair suppression. Subsequently, we revealed that BAP1 serves as a novel molecular target of PT33 via a CRISPR-based deubiquitinase screen. Mechanistically, pharmacological covalent inhibition of BAP1 with PT33 recruits HERC2 to compete with BARD1 for BRCA1 interaction, interrupting HR repair. Consequently, PT33 treatment can substantially enhance the sensitivity of CRC cells to radiotherapy in vitro and in vivo. Overall, these findings provide a mechanistic basis for PT33-induced HR suppression and may guide an effective strategy to improve therapeutic gain.

A fundamental challenge that arises in biomedicine is the need to characterize compounds in a relevant cellular context in order to reveal potential on-target or off-target effects. Recently, the fast accumulation of gene transcriptional profiling data provides us an unprecedented opportunity to explore the protein targets of chemical compounds from the perspective of cell transcriptomics and RNA biology. Here, we propose a novel Siamese spectral-based graph convolutional network (SSGCN) model for inferring the protein targets of chemical compounds from gene transcriptional profiles. Although the gene signature of a compound perturbation only provides indirect clues of the interacting targets, and the biological networks under different experiment conditions further complicate the situation, the SSGCN model was successfully trained to learn from known compound-target pairs by uncovering the hidden correlations between compound perturbation profiles and gene knockdown profiles. On a benchmark set and a large time-split validation dataset, the model achieved higher target inference accuracy as compared to previous methods such as Connectivity Map. Further experimental validations of prediction results highlight the practical usefulness of SSGCN in either inferring the interacting targets of compound, or reversely, in finding novel inhibitors of a given target of interest.
Drug Delivery Systems ; Proteins ; Transcriptome

Objective:To construct of comprehensive quality of evaluation index system about palliative care in general hospitals, so as to provide reference for promoting the scientific and standardized development of palliative care.Methods:Based on the structure-process-outcome quality model, literature research and Delphi method were used to determine the quality of palliative care evalution index system and index weight for general hospitals.Results:A total of 12 experts were consulted for two rounds,the rates of questionnaire retrieve were 12/15 and 12/12 respectively. The authoritative coefficients were 0.909 and 0.879, the Kendall′s W values were 0.27, 0.32 and 0.26 respectively with good coordination degree ( χ2=6.50, 106.62, 494.64, all P<0.05). Finally, the quality of palliative care indicator system in general hospitals was constructed, which included 3 first-level indicators, 30 second-level indicators and 157 third-level indicators. Conclusions:The establishment process of the construction of quality of palliative care indicator system in general hospitals was scientific and reasonable, focusing on the development characteristics of palliative care and can make significant contributions to improve the quality of palliative care.

Objective To study the effect of gender and maneuvers on anterior cruciate ligament (ACL) injury risk factors for volleyball players. Methods Sports biomechanics data of volleyball players during stop-jump, drop landing and sidestep cutting were collected. The ACL injury rate and biomechanical parameters of simulated injured jumps were obtained with Monte Carlo simulation. The influence of gender and maneuvers on ACL injury risk factors was validated by 2×3 mixed designed two-way ANOVA. Results Sidestep cutting was the highest risk maneuver of ACL injury for both genders (P＜0.001). Compared with male players, female players had a greater risk of ACL injury during sidestep cutting and stop-jump (P＜0.001), while male players were more prone to have ACL injury than female players during drop landing (P＜0.001). The risk factors of ACL injury obtained by simulation were significantly influenced by gender and maneuvers (P＜0.001). Conclusions Male players were more likely to increase ACL load due to smaller knee flexion, forward leg tilt and heel landing than female players during sidestep cutting, while female players owned larger ground reaction force (GRF) and knee extension moment. Smaller knee flexion angle during stop jump was the major risk factor for both genders, however more characteristics contributed to the males. Female players with large GRF, knee valgus and extension moment, and heel-landing were likely to have ACL injury, while the small knee flexion angle was the key risk factor for male players. The results can provide evidences for evaluation of volleyball players’ ACL injury risk, individualized injury prevention protocols, and clinical treatment and rehabilitation directions.

Objective:To explore the knowledge-attitude-practice of pelvic floor muscle training in women with postpartum stress urinary incontinence (SUI) .Methods:From January 2018 to January 2019, we conveniently selected 213 patients in the Pelvic Floor Clinic of a Obstetrics and Gynecology Hospital in Beijing 12 weeks after delivery. We used the Pelvic Floor Muscle Function Training Knowledge-Attitude-Practice and Its Needs in Puerperium Women Questionnaire for investigation, and analyzed the influencing factors of knowledge-attitude-behavior of patients' pelvic floor muscle function training.Results:Among 213 SUI patients, the overall standard score of pelvic floor muscle training knowledge-attitude-practice was (75.70±10.23) . Univariate analysis showed that there were statistical differences in the knowledge-attitude-practice of pelvic floor muscle function training among patients with different age, family monthly income per capita, highest education level, occupational status, delivery method, weight gain during pregnancy, and current urinary incontinence ( P<0.2) .Multiple regression analysis showed that family monthly in comeper capita, weight gain during pregnancy, and current urinary incontinence were the influencing factors of pelvic floor muscle function training knowledge-attitude-practice with a statistical difference ( P<0.05) . Conclusions:Postpartum SUI patients have a positive attitude towards pelvic floor muscle function training, but their cognitive level needs to be improved. Medical and nursing staff should strengthen the publicity and education of relevant knowledge, and enhance patients' awareness of the importance of pelvic floor muscle function training.