Drug resistance is one of the key factors affecting the effectiveness of cancer treatment methods, including chemotherapy, radiotherapy, and immunotherapy. Its occurrence is related to factors such as mRNA expression and methylation within cancer cells. If drug resistance in patients can be accurately identified early, doctors can devise more effective treatment plans, which is of great significance for improving patients' survival rates and quality of life. Cancer drug resistance prediction based on artificial intelligence (AI) technology has emerged as a current research hotspot, demonstrating promising application prospects in guiding clinical individualized and precise medication for cancer patients. This review aims to comprehensively summarize the research progress in utilizing AI algorithms to analyze multi-omics data including genomics, transcriptomics, epigenomics, proteomics, metabolomics, radiomics, and histopathology, for predicting cancer drug resistance. It provides a detailed exposition of the processes involved in data processing and model construction, examines the current challenges faced in this field and future development directions, with the aim of better advancing the progress of precision medicine.

OBJECTIVE: To investigate the role and mechanism of the cyclic guanosine monophosphate-adenosine monophosphate synthase/stimulator of interferon gene (cGAS/STING) pathway in oleic acid-induced acute lung injury (ALI) in mice. METHODS: Male wild-type C57BL/6J mice were randomly divided into five groups (each n = 10): normal control group, ALI model group, and 5, 50, 500 μg/kg inhibitor pretreatment groups. The ALI model was established by tail vein injection of oleic acid (7 mL/kg), while the normal control group received no intervention. The inhibitor pretreatment groups were intraperitoneally injected with the corresponding doses of cGAS inhibitor RU.521 respectively 1 hour before modeling. At 24 hours post-modeling, blood was collected, and mice were sacrificed. Lung tissue pathological changes were observed under light microscopy after hematoxylin-eosin (HE) staining, and pathological scores were assessed. Western blotting was used to detect the protein expressions of cGAS, STING, phosphorylated TANK-binding kinase 1 (p-TBK1), phosphorylated interferon regulatory factor 3 (p-IRF3), and phosphorylated nuclear factor-κB p65 (p-NF-κB p65) in lung tissue. Immunohistochemistry was performed to observe STING and p-NF-κB positive expressions in lung tissue. Serum interferon-β (IFN-β) levels were measured by enzyme-linked immunosorbent assay (ELISA). RESULTS: Compared with the normal control group, the ALI model group exhibited significant focal alveolar thickening, intra-alveolar hemorrhage, pulmonary capillary congestion, and neutrophil infiltration in the pulmonary interstitium and alveoli, along with markedly increased pathological scores (10.33±0.58 vs. 1.33±0.58, P < 0.05). Protein expressions of cGAS, STING, p-TBK1, p-IRF3, and p-NF-κB p65 in lung tissue significantly increased [cGAS protein (cGAS/β-actin): 1.24±0.02 vs. 0.56±0.02, STING protein (STING/β-actin): 1.27±0.01 vs. 0.55±0.01, p-TBK1 protin (p-TBK1/β-actin): 1.34±0.03 vs. 0.22±0.01, p-IRF3 protein (p-IRF3/β-actin): 1.23±0.02 vs. 0.36±0.01, p-NF-κB p65 protein (p-NF-κB p65/β-actin): 1.30±0.02 vs. 0.53±0.02, all P < 0.05], positive expressions of STING and p-NF-κB in lung tissue were significantly elevated [STING (A value): 0.51±0.03 vs. 0.30±0.07, p-NF-κB (A value): 0.57±0.05 vs. 0.31±0.03, both P < 0.05], and serum IFN-β levels were also significantly higher (ng/L: 256.02±3.84 vs. 64.15±1.17, P < 0.05). The cGAS inhibitor pretreatment groups showed restored alveolar structural integrity, reduced inflammatory cell infiltration, and decreased hemorrhage area, along with dose-dependent lower pathological scores as well as the protein expressions of cGAS, STING, p-TBK1, p-IRF3 and p-NF-κB p65 in lung tissue, with significant differences between the 500 μg/kg inhibitor group and ALI model group [pathological score: 2.67±0.58 vs. 10.33±0.58, cGAS protein (cGAS/β-actin): 0.56±0.03 vs. 1.24±0.02, STING protein (STING/β-actin): 0.67±0.03 vs. 1.27±0.01, p-TBK1 protein (p-TBK1/β-actin): 0.28±0.01 vs. 1.34±0.03, p-IRF3 protein (p-IRF3/β-actin): 0.32±0.01 vs. 1.23±0.02, p-NF-κB p65 protein (p-NF-κB p65/β-actin): 0.63±0.01 vs. 1.30±0.02, all P < 0.05]. Compared with the ALI model group, positive expressions of STING and p-NF-κB in lung tissue were significantly reduced in the 500 μg/kg inhibitor group [STING (A value): 0.40±0.01 vs. 0.51±0.03, p-NF-κB (A value): 0.43±0.02 vs. 0.57±0.05, both P < 0.05], and serum IFN-β levels were also markedly reduced (ng/L: 150.03±6.19 vs. 256.02±3.84, P < 0.05). CONCLUSIONS The cGAS/STING pathway is activated in oleic acid-induced ALI, leading to exacerbated inflammatory responses and increased lung damage. RU.521 can inhibit cGAS, thereby down-regulating the expression of pathway proteins and cytokines, and providing protection to lung tissue.
Animals ; Acute Lung Injury/chemically induced* ; Male ; Nucleotidyltransferases/metabolism* ; Mice ; Signal Transduction ; Mice, Inbred C57BL ; Membrane Proteins/metabolism* ; Oleic Acid/adverse effects* ; Transcription Factor RelA/metabolism* ; Lung/pathology* ; Interferon Regulatory Factor-3/metabolism* ; Disease Models, Animal

Objective A wearable wireless chest patch monitoring terminal is designed to realize the acquisition,processing,and wireless transmission of ECG,respiration,and body temperature signals.Methods The analog front-end ADS1292R,which integrates respiratory impedance and ECG front-end,is utilized to collect human ECG and respiratory signals.The body temperature is collected using a low-power,high-precision digital temperature sensor MAX30208.A filter algorithm for signal processing and wireless transmission is designed through a low-power nRF52840 Bluetooth SoC with an Arm Cortex-M4F kernel.Results The experimental results show that the designed monitoring terminal can monitor the ECG,respiration,and body temperature parameters of the human body in real-time and send the monitoring results via Bluetooth,with a continuous working time of more than 13 hours.Conclusion The wearable wireless chest patch monitoring terminal features good portability,long standby time,and high measurement accuracy,and it has promising application prospects in the fields of family health monitoring,mobile medical treatment,and smart healthcare.

Objective:Digestive endoscopy is an important diagnostic and therapeutic tool for digestive system diseases.The artificial intelligence(AI)-assisted system in endoscopy(hereinafter referred to as AI in digestive endoscopy)has broad application prospects in the field of digestive endoscopy.The trust and acceptance of endoscopic subjects are the cornerstone of the research,application,and promotion of AI in digestive endoscopy.Currently,the tools for measuring the acceptance of AI in digestive endoscopy by subjects are limited at home and abroad.This study aims to develop a scale for measuring the acceptance of AI in digestive endoscopy by subjects,then to evaluate its reliability and validity. Methods:By conducting literature research,an item pool and dimensions were constructed,and a preliminary scale was constructed using Delphi method.Through the first stage of the survey on the subjects,the reliability and validity of the scale were tested,and the revised scale was used for the second stage of survey on the subjects to further verify the structural validity of the scale. Results:The acceptance scale for AI in digestive endoscopy included 11 items in 3 dimensions:accuracy,ethics,benefit and willingness.In the first stage of the survey,351 valid questionnaires were collected,and the Cronbach's α was 0.864.The correlation coefficient between the total score of the scale and the score of the test item was 0.636,and the Kaiser-Meyer-Olkin(KMO)value in exploratory factor analysis was 0.788.In the second stage of the survey,335 valid questionnaires were collected,and in confirmatory factor analysis,the χ2/df was 3.774,while the root mean squared error of approximation(RMSEA)was 0.091. Conclusion:Acceptance scale for AI in digestive endoscopy by subjects developed in this study has good reliability and validity.

OBJECTIVES: Gastrointestinal endoscopy plays an important role in the diagnosis and treatment of gastrointestinal diseases. The satisfaction degree of gastrointestinal endoscopy can directly affect the patient's compliance and further impact the treating effect. At present, there is no scale to evaluate the satisfaction degree of gastrointestinal endoscopy in China. This study aims to develop a satisfaction scale of gastrointestinal endoscopy suitable for national conditions and to evaluate its reliability and validity, which provides a tool for clinic to evaluate patients' satisfaction with gastrointestinal endoscopy. METHODS: The original gastrointestinal endoscopy satisfaction scale was compiled by literature review, consulting senior endoscopists and experts. Through the first round of survey about 120 patients, the original scale was analyzed and modified according to the results to get the gastrointestinal endoscopy satisfaction scale (formal scale). The formal scale was used to conduct the second round of survey about 200 patients. The reliability and validity of the scale were analyzed and evaluated according to the survey results. RESULTS: The reliability of the original scale was good but the validity was poor. The formal scale had 2 dimensions and 10 items, the Cronbach's alpha and split-half reliability were 0.889 and 0.823. The structure validity index χ²/df was 2.513, root mean square error of approximation (RMSEA) was 0.094, goodness of fit index (GFI) was 0.914, adjusted goodness of fit index (AGFI) was 0.861, comparative fit index (CFI) was 0.946, normed fit index (NFI) was 0.915. The aggregate validity was general, the discriminative validity was good, and the direct score of patients was strongly correlated with the total score of the scale. CONCLUSIONS The gastrointestinal endoscopy satisfaction scale has good reliability and validity, which can be used as a tool to evaluate patients' satisfaction with gastrointestinal endoscopy in China.
Humans ; Reproducibility of Results ; China ; Endoscopy, Gastrointestinal ; Patient Compliance ; Personal Satisfaction

OBJECTIVE To observe the clinical efficacy and safety of albumin-bound paclitaxel combined with nedaplatin inductive chemotherapy followed by concurrent radiochemotherapy in the treatment of loco-regionally advanced nasopharyngeal carcinoma. METHODS The clinical data of 45 patients （observation group ） with loco-regionally advanced nasopharyngeal carcinoma（Ⅲ/Ⅳa stage ）who received albumin-bound paclitaxel combined with nedaplatin inductive chemotherapy in our hospital from August 2017 to July 2018 were retrospectively analyzed. Propensity score was used to match 45 patients（control group ）with loco-regionally advanced nasopharyngeal carcinoma who received docetaxel combined with cisplatin and fluorouracil inductive chemotherapy. After inductive chemotherapy ，both groups received intensity-modulated radiochemotherapy （IMRT）；observation group was additionally given concurrent nedaplatin chemotherapy ，and control groups was given concurrent cisplatin chemotherapy. Clinical efficacy and the incidence of ADR were compared between 2 groups. RESULTS All patients completed treatment and 3-year follow-up. After inductive chemotherapy and 1，3 months after concurrent radiochemotherapy ，there was no statistical significance in short-term response between 2 groups（P＞0.05）. There was no significantly difference in 3-years local control rate and 3-years free from distant metastasis between 2 groups（P＞0.05）. The incidences of leucopenia （grade 3 or above ）in the observation group were significantly lower than those in the control group ，and the incidence of peripheral neuropathy in observation group was higher than that in control group （P＜0.05）. The incidences of thrombocytopenia （grade 2 or above ），rash and vomiting （grade 2 or above ）in the observation group were lower than those in the control group ，but the difference was not statistically significant （P＞0.05）. There was no significant difference in the incidence of other ADR between 2 groups（P＞0.05）. CONCLUSIONS Albumin-bound paclitaxel combined with nedaplatin inductive chemotherapy followed by concurrent chemoradiotherapy in the treatment of loco-regionally advanced nasopharyngeal carcinoma is effective and tolerable ．

The morbidity of inflammatory bowel diseases (IBD) is rising rapidly but no curative therapies to prevent its recurrence. Cell death is crucial to maintaining homeostasis. Necroptosis is a newly identified programmed cell death and its roles played in IBD need to be explored. Necroptosis is mediated by receptor interacting protein kinase 1 (RIPK1), RIPK3, and mixed lineage kinase domain-like protein (MLKL), which resulted in cell swelling, plasma membrane rupture, intracellular content leaking, and eventually cell death as well as the promotion of inflammation. Studies have found that inhibiting necroptosis alleviated IBD in animal models and IBD patients with an increased level of necroptosis in inflammatory tissues, indicating that necroptosis is related to the pathogenesis of IBD. However, due to the complexity in regulation of necroptosis and the involvement of multiple functions of relevant signaling molecules, the specific mechanism remains elusive. Necroptosis may play a vital regulatory role in the pathogenesis of IBD, which provides a new idea and method for further exploring the therapeutic target of IBD.

Objective To examine the association of pre?pregnancy body mass and weight gain during pregnancy with macrosomia. Methods From January 2015 to December 2015, a total of 20 477 pregnant women were recruited by probabilistic proportional scale sampling with simple randomization in Sichuan, Yunnan and Guizhou Provinces. Basic information of pregnant women, weight gain during pregnancy and weight of newborn were collected. A multiple logistic regression model was used to assess the association between the pre?pregnancy body mass and gestational weight gain indicators with macrosomia. Results 20 321 mother?infant were included in the final analysis. 20 321 pregnant women were (30.09 ± 4.10) years old and delivered at (39.20 ± 1.29) weeks, among which 12 341 (60.73%) cases were cesarean delivery. The birth weight of 20 321 infants were (3 292.26 ± 431.67) grams, and 970 (4.77%) were macrosomia. The multiple logistic regression model showed that after adjusting for the age of women, compared to the normal weight group in the pre?pregnancy, the overweight and obesity group elevated the risk of macrosomia, with OR (95%CI) about 1.99 (95%CI: 1.69-2.35) and 4.05 (95%CI: 3.05-5.39), respectively. After adjusting for the age, the pre?pregnancy BMI, delivery weeks, delivery mode and infant's gender, compared to the weight?gain appropriate group, higher weight gain rate in the mid?pregnancy and excessive total gestational weight gain elevated the risk of macrosomia, with OR (95%CI) about 1.99 (95%CI:1.66-2.39) and 1.80 (95%CI: 1.55-2.08), respectively. Conclusion The overweight before pregnancy, obesity before pregnancy, the rate of weight gain in the second trimester and the high total weight gain during pregnancy could increase the risk of macrosomia.

Brain-computer interface (BCI) provides a direct communicating and controlling approach between the brain and surrounding environment, which attracts a wide range of interest in the fields of brain science and artificial intelligence. It is a core to decode the electroencephalogram (EEG) feature in the BCI system. The decoding efficiency highly depends on the feature extraction and feature classification algorithms. In this paper, we first introduce the commonly-used EEG features in the BCI system. Then we introduce the basic classical algorithms and their advanced versions used in the BCI system. Finally, we present some new BCI algorithms proposed in recent years. We hope this paper can spark fresh thinking for the research and development of high-performance BCI system.
Algorithms ; Brain ; physiology ; Brain-Computer Interfaces ; Electroencephalography ; Humans ; Pattern Recognition, Automated

Objective: To examine the association of pre-pregnancy body mass and weight gain during pregnancy with macrosomia. Methods: From January 2015 to December 2015, a total of 20 477 pregnant women were recruited by probabilistic proportional scale sampling with simple randomization in Sichuan, Yunnan and Guizhou Provinces. Basic information of pregnant women, weight gain during pregnancy and weight of newborn were collected. A multiple logistic regression model was used to assess the association between the pre-pregnancy body mass and gestational weight gain indicators with macrosomia. Results: 20 321 mother-infant were included in the final analysis. 20 321 pregnant women were (30.09±4.10) years old and delivered at (39.20±1.29) weeks, among which 12 341 (60.73%) cases were cesarean delivery. The birth weight of 20 321 infants were (3 292.26±431.67) grams, and 970 (4.77%) were macrosomia. The multiple logistic regression model showed that after adjusting for the age of women, compared to the normal weight group in the pre-pregnancy, the overweight and obesity group elevated the risk of macrosomia, with OR (95%CI) about 1.99 (95%CI: 1.69−2.35) and 4.05 (95%CI: 3.05−5.39), respectively. After adjusting for the age, the pre-pregnancy BMI, delivery weeks, delivery mode and infant′s gender, compared to the weight-gain appropriate group, higher weight gain rate in the mid-pregnancy and excessive total gestational weight gain elevated the risk of macrosomia, with OR (95%CI) about 1.99 (95%CI: 1.66−2.39) and 1.80 (95%CI: 1.55−2.08), respectively. Conclusion The overweight before pregnancy, obesity before pregnancy, the rate of weight gain in the second trimester and the high total weight gain during pregnancy could increase the risk of macrosomia.