OBJECTIVE To provide a reference for the pharmaceutical care of a patient with type 2 diabetes mellitus （T2DM） and limb-girdle muscular dystrophy （LGMD） who developed euglycemic diabetic ketoacidosis （euDKA） after taking empagliflozin. METHODS Clinical pharmacists provided pharmaceutical care for a patient with T2DM and LGMD who developed euDKA after taking empagliflozin. According to the patient’s recent use of medications and his conditions， clinical pharmacists assessed the correlation between euDKA and empagliflozin as “very likely”. As to euDKA， clinical pharmacists suggested discontinuing empagliflozin and metformin， and giving intravenous infusion of 10% Glucose injection instead of 5% Glucose injection for fluid resuscitation. Clinical pharmacists monitored the patient’s laboratory indicators such as arterial blood gas analysis， blood/urine ketones and electrolytes. They assisted physicians to decide when to stop intravenous supplements of liquid and insulin. Clinical pharmacists also assisted physicians to adjust the antidiabetic drugs and educated the patient to avoid empagliflozin or other sodium- glucose linked transporter 2 inhibitors （SGLT2i）. RESULTS Physicians adopted the suggestions of clinical pharmacists. After treatment， the patient’s condition improved， and he was allowed to be discharged with medication. CONCLUSIONS euDKA is a relatively rare and serious adverse reaction associated with SGLT2i， and the patients with LGMD are susceptible to euDKA. Clinical pharmacists assist physicians in developing personalized medication plans by evaluating the association between euDKA and empagliflozin， adjusting medication regimens，conducting pharmaceutical monitoring，and other pharmaceutical services. Meanwhile， they provide medication education to patients to ensure their medication safety.

OBJECTIVE To provide a reference for the pharmaceutical care of a patient with type 2 diabetes mellitus （T2DM） and limb-girdle muscular dystrophy （LGMD） who developed euglycemic diabetic ketoacidosis （euDKA） after taking empagliflozin. METHODS Clinical pharmacists provided pharmaceutical care for a patient with T2DM and LGMD who developed euDKA after taking empagliflozin. According to the patient’s recent use of medications and his conditions， clinical pharmacists assessed the correlation between euDKA and empagliflozin as “very likely”. As to euDKA， clinical pharmacists suggested discontinuing empagliflozin and metformin， and giving intravenous infusion of 10% Glucose injection instead of 5% Glucose injection for fluid resuscitation. Clinical pharmacists monitored the patient’s laboratory indicators such as arterial blood gas analysis， blood/urine ketones and electrolytes. They assisted physicians to decide when to stop intravenous supplements of liquid and insulin. Clinical pharmacists also assisted physicians to adjust the antidiabetic drugs and educated the patient to avoid empagliflozin or other sodium- glucose linked transporter 2 inhibitors （SGLT2i）. RESULTS Physicians adopted the suggestions of clinical pharmacists. After treatment， the patient’s condition improved， and he was allowed to be discharged with medication. CONCLUSIONS euDKA is a relatively rare and serious adverse reaction associated with SGLT2i， and the patients with LGMD are susceptible to euDKA. Clinical pharmacists assist physicians in developing personalized medication plans by evaluating the association between euDKA and empagliflozin， adjusting medication regimens，conducting pharmaceutical monitoring，and other pharmaceutical services. Meanwhile， they provide medication education to patients to ensure their medication safety.

Objective To explore the clinical characteristics of patients with diffuse large B-cell lymphoma (DLBCL) accompanied with KMT2D gene mutation and the impact of its co-mutated genes on prognosis. Methods Clinical data of 155 newly diagnosed DLBCL patients were obtained. The second-generation sequencing method was used to detect 475 hotspot genes, including KMT2D mutation. Patients were divided into the KMT2D mutation group and KMT2D wild-type group based on the presence or absence of KMT2D gene mutation. Clinical characteristics, differences in co-mutated genes, and survival differences between the two groups were compared. Results The frequency of KMT2D mutation was 31%, which is predominantly observed in elderly patients (P=0.07) and less in the double-expressor phenotype (P=0.07). Compared with the KMT2D wild-type group, KMT2D gene mutation was associated with higher co-mutation rates of CDKN2A (OR=2.82, P=0.01) and BCL2 (OR=3.84, P=0.016), while being mutually exclusive with MYC gene mutation (OR=0.11, P=0.013). In univariate survival analysis, no statistically significant difference in overall survival (OS) was found between the KMT2D mutation group and the wild-type group (P=0.54). Further analysis of the prognostic significance of KMT2D with other gene mutations indicated that patients with KMT2D^mutBTG2^mut had poorer OS than those with KMT2D^wt BTG2^mut (P=0.07) and KMT2D^wt BTG2^wt (P=0.05). On the contrary, patients with KMT2D^mut CD79B^mut had better OS than those with KMT2D^mut CD79B^wt (P=0.09), with no prognostic impact observed for other co-mutated genes. Multivariate Cox regression analysis revealed that Ann Arbor stages Ⅲ and Ⅳ (HR=2.751, 95%CI: 1.169-6.472, P=0.02), elevated LDH levels (HR=2.461, 95%CI: 1.396-4.337, P=0.002), Ki-67 index>80% (HR=1.875, 95%CI: 1.066-3.299, P=0.029), and KMT2D^mutBTG2^mut(HR=4.566, 95%CI: 1.348-15.471, P=0.015) were independent risk factors for OS in patients with DLBCL (P<0.05). Conclusion DLBCL patients with KMT2D mutation often have multiple gene mutations, among which patients with a co-mutated BTG2 gene have poor prognosis.

OBJECTIVE To study the effect of fluoropezil on embryo-fetal developmental toxicity and toxicokinetics in rabbits,and provide reference for clinical medication.METHODS According to the sequence of pregnancy,pregnant rabbits were divided into five groups:vehicle control group(1%hydroxy-propyl methylcellulose+1.5%polyethylene glycol 400 aqueous solution),positive control group(cyclo-phosphamide 18 mg·kg-1),and fluoropezil(3.6,9.0 and 22.5 mg·kg-1)groups.The vehicle control group and the fluoropezil groups were ig administrated on the 6th to 18th day of gestation(GD6-18)while the positive control group was ig given cyclophosphamide on GD6-20.The pregnant rabbits were sacri-ficed on GD28,and the embryo-fetal development was detected.Sex hormone levels of pregnant rabbits on GD5,GD18 and GD28 were detected by ELISA method.Blood samples with toxokinetics were collected for concomitant toxic generation at the first and last administration,and drug concentrations in fetal,placenta and amniotic fluid were detected with liquid chromatography tandem mass spectrometry(LC-MS/MS).RESULTS Fluoropezil 3.6,9.0 and 22.5 mg·kg-1 had no significant effect on body mass,mass gain,food consumption,pregnancy outcomes,fetal appearance,viscera,skeletal and physical growth and development of pregnant rabbits.Only on GD18 or GD28,the levels of follicle stimulating hormone,estra-diol and progesterone in each dose group fluctuated to some extent.The combined toxokinetics results indicated that fluoropezil could cross the placental barrier of the rabbits,but did not accumulate in preg-nant rabbits or fetuses.Fetal mass,crown-rump length and uterus mass in the cyclophosphamide group were lower than those in the vehicle control group.The appearance and bone of the cyclophos-phamide group were positive.CONCLUSION The no observed adverse effect level(NOAEL)of fluoro-pezil toxicity on rabbit embryo-fetal development is 22.5 mg·kg-1,which is 125 times of the effective dose.At the dosage level of 22.5 mg·kg-1,Cmax is 1093 μg·L-1,and AUC(0-24 h)6650 μg·h·L-1 on GD18.

Gout is a metabolic disease closely associated with hyperuricemia and urate deposition. Because of the complex pathogenesis， high morbidity， multiple complications， and increasingly young patients， gout has received worldwide attention. Currently， western medicine mainly treats gout by lowering the uric acid level and reducing inflammation， which， however， causes serious adverse reactions and has contraindications. Phellodendri Chinensis Cortex （PCC） is the dried bark of Phellodendron chinense， with the effects of clearing heat， drying dampness， purging fire， detoxifying， and treating sores. Studies have shown that PCC and its active components have anti-inflammatory， pain-relieving， uric acid-lowering， and anti-gout activities， with extensive sources and high safety. PCC and its active components could prevent and treat gout through multi-targets and multi-pathways， whereas the systematic review remains to be carried out. Therefore， this paper summarized the pharmacological activities and mechanisms of PCC and its active components in the treatment of gout. The available studies have shown that PCC and its active components exert the anti-gout effect by lowering the uric acid level， reducing inflammation， alleviating oxidative stress， and regulationg intestinal flora， and protecting the kidneys. Particularly， the active components represented by alkaloids contribute obviously to the therapeutic effect of of PCC. Herein， we analyzed the problems and future development of the research on PCC， aiming to provide theoretical support and a scientific basis for the research and development of new drugs against gout.

To explore the clinical and genetic features of Aicardi-Goutières syndrome (AGS) caused by IFIH1 gene mutation.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.