Acute kidney injury (AKI) has high morbidity and mortality, but effective clinical drugs and management are lacking. Previous studies have suggested that macrophages play a crucial role in the inflammatory response to AKI and may serve as potential therapeutic targets. Emerging evidence has highlighted the importance of forkhead box protein O1 (FoxO1) in mediating macrophage activation and polarization in various diseases, but the specific mechanisms by which FoxO1 regulates macrophages during AKI remain unclear. The present study aimed to investigate the role of FoxO1 in macrophages in the pathogenesis of AKI. We observed a significant upregulation of FoxO1 in kidney macrophages following ischemia-reperfusion (I/R) injury. Additionally, our findings demonstrated that the administration of FoxO1 inhibitor AS1842856-encapsulated liposome (AS-Lipo), mainly acting on macrophages, effectively mitigated renal injury induced by I/R injury in mice. By generating myeloid-specific FoxO1-knockout mice, we further observed that the deficiency of FoxO1 in myeloid cells protected against I/R injury-induced AKI. Furthermore, our study provided evidence of FoxO1's pivotal role in macrophage chemotaxis, inflammation, and migration. Moreover, the impact of FoxO1 on the regulation of macrophage migration was mediated through RhoA guanine nucleotide exchange factor 1 (ARHGEF1), indicating that ARHGEF1 may serve as a potential intermediary between FoxO1 and the activity of the RhoA pathway. Consequently, our findings propose that FoxO1 plays a crucial role as a mediator and biomarker in the context of AKI. Targeting macrophage FoxO1 pharmacologically could potentially offer a promising therapeutic approach for AKI.

Objective To investigate the clinical characteristics of women with abnormal uterine bleeding(AUB)in sub-plateau regions and analyze the factors affecting their treatment methods.Methods AUB patients who were hospitalized from Jan 1,2018 to Dec 31,2022,in a sub-plateau region(Yongping County People's Hospital of Yunnan Province)with an average altitude of 1 620 meters were selected.The general clinical characteristics of the patients were summarized,and patients were classified into two categories(with or without uterine structural lesion)and nine subtypes(PALM-COEIN)according to the FIGO recommended etiological classification guidelines.Then the patients were divided into groups based on the presence or absence of uterine structural lesions,ethnic group(Han and minority),conservative drug treatment and surgical treatment groups,blood transfusion and non-blood transfusion groups.Binary Logistic regression analysis was used to identify factors affecting treatment methods.Results A total of 481 AUB patients enrolled,and the delayed consultation rate was as high as 80.46%,and the proportion of overweight and obese patients was 49.90%,which was higher than the average level among Chinese women.The main cause was AUB-O(AUB-ovulatory dysfunction),accounting for 78.59%of cases,the proportion of patients with delayed medical treatment was higher than those without delayed medical treatment(82.17%vs.74.47%).Patients who received blood transfusion were significantly younger,had lower hemoglobin(HGB)levels,fewer pregnancies,and lower BMI compared to those in the non-blood transfusion group(P<0.05).Univariate analysis showed that the surgical treatment group had older age,longer onset time,higher HGB levels,more pregnancies and deliveries,higher BMI,a higher proportion of Han ethnicity patients,lower rates of non-blood transfusion,higher rates of hypertension,and more uterine structural lesions compared to the conservative drug treatment group.Multivariate regression analysis revealed that blood transfusion treatment reduced the probability of surgical treatment.Age and uterine structural lesions were risk factors for requiring surgical treatment,for each additional year of age,the risk of undergoing surgical treatment increased by 10%.The risk of requiring surgical treatment for patients with uterine structural lesions was 2.987 times higher than for those without.Conclusion AUB patients in this sub-plateau regions have a high rate of delayed consultation and a high proportion of overweight and obesity,with AUB-O being the primary cause.Older age and the presence of uterine structural lesions were risk factors for requiring surgical treatment.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

A nodule in the right middle lobe of the lung was treated by a combination of cone-beam CT,three-dimensional registration for fusion imaging,and electromagnetic navigation bronchoscopy-guided thermal ablation.The procedure lasted for 90 min,with no significant bleeding observed under the bronchoscope.The total radiation dose during the operation was 384 mGy.The patient recovered well postoperatively,with only a small amount of blood in the sputum and no pneumothorax or other complications.A follow-up chest CT on the first day post operation showed that the ablation area completely covered the lesion,and the patient was discharged successfully.
Humans ; Bronchoscopy/methods* ; Catheter Ablation/methods* ; Cone-Beam Computed Tomography ; Electromagnetic Phenomena ; Imaging, Three-Dimensional ; Lung Neoplasms/diagnostic imaging* ; Tomography, X-Ray Computed

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To investigate the clinical characteristics of women with abnormal uterine bleeding(AUB)in sub-plateau regions and analyze the factors affecting their treatment methods.Methods AUB patients who were hospitalized from Jan 1,2018 to Dec 31,2022,in a sub-plateau region(Yongping County People's Hospital of Yunnan Province)with an average altitude of 1 620 meters were selected.The general clinical characteristics of the patients were summarized,and patients were classified into two categories(with or without uterine structural lesion)and nine subtypes(PALM-COEIN)according to the FIGO recommended etiological classification guidelines.Then the patients were divided into groups based on the presence or absence of uterine structural lesions,ethnic group(Han and minority),conservative drug treatment and surgical treatment groups,blood transfusion and non-blood transfusion groups.Binary Logistic regression analysis was used to identify factors affecting treatment methods.Results A total of 481 AUB patients enrolled,and the delayed consultation rate was as high as 80.46%,and the proportion of overweight and obese patients was 49.90%,which was higher than the average level among Chinese women.The main cause was AUB-O(AUB-ovulatory dysfunction),accounting for 78.59%of cases,the proportion of patients with delayed medical treatment was higher than those without delayed medical treatment(82.17%vs.74.47%).Patients who received blood transfusion were significantly younger,had lower hemoglobin(HGB)levels,fewer pregnancies,and lower BMI compared to those in the non-blood transfusion group(P<0.05).Univariate analysis showed that the surgical treatment group had older age,longer onset time,higher HGB levels,more pregnancies and deliveries,higher BMI,a higher proportion of Han ethnicity patients,lower rates of non-blood transfusion,higher rates of hypertension,and more uterine structural lesions compared to the conservative drug treatment group.Multivariate regression analysis revealed that blood transfusion treatment reduced the probability of surgical treatment.Age and uterine structural lesions were risk factors for requiring surgical treatment,for each additional year of age,the risk of undergoing surgical treatment increased by 10%.The risk of requiring surgical treatment for patients with uterine structural lesions was 2.987 times higher than for those without.Conclusion AUB patients in this sub-plateau regions have a high rate of delayed consultation and a high proportion of overweight and obesity,with AUB-O being the primary cause.Older age and the presence of uterine structural lesions were risk factors for requiring surgical treatment.

OBJECTIVE To analyze the components migrating to blood and metabolites of Polygonum cuspidatum in rats with acute gouty arthritis(AGA).METHODS SD rats were randomly divided into blank group,model group and P.cuspidatum group(10 g/kg,by raw material),with 6 rats in each group.Except for blank group,AGA model was induced in the remaining groups by injecting potassium oxonate and sodium urate;meanwhile,they were administered corresponding drug solutions or water intragastrically,once a day,for 10 consecutive days.The histopathological morphology of the knee joint tissues in rats was observed;rat serum samples were collected,and the components migrating to blood and metabolites of P.cuspidatum were analyzed by using UPLC-Q-Exactive-Orbitrap-MS.RESULTS Following the intervention with P.cuspidatum,the histopathological morphology of the knee joint synovial tissue in AGA rats showed significant improvement,with reduced inflammatory cell infiltration and hyperplasia,and the preservation of the honeycomb-like structure integrity.In both positive and negative ion modes,a total of 67 chemical components were detected in the serum of rats from P.cuspidatum group,including 25 prototype components and 42 metabolites.The involved compound types encompassed stilbenes,anthraquinones,naphthols,and flavonoids,among others.The metabolic reactions identified included methylation,acetylation,sulfation,and glucuronidation.Notably,compounds such as polydatin,resveratrol and emodin were capable of entering the bloodstream in their prototype forms and undergoing in vivo metabolism.CONCLUSIONS Compounds such as polydatin,resveratrol and emodin are likely to be the active components responsible for the anti-AGA effects of P.cuspidatum.

An electroencephalogram(EEG)emotion analysis model(LTNet)that combines long short-term memory(LSTM)and Transformer modules is proposed for addressing the shortcomings of traditional emotion recognition methods in dealing with long-term dependencies.After data preprocessing,the extracted features are input into LTNet.LSTM module and Transformer module model the input sequence independently,and from which deep local features and global features are extracted and then fused using a weighted fusion strategy.Finally,Softmax function is used to classify emotions into 4 categories.Experimental results show that LTNet has an average recognition accuracy of 96.56%in the 5-fold cross-validation on the DEAP dataset,which is 2.74%-21.31%higher than traditional machine learning algorithms and other deep learning methods.

Objective To observe the value of feature pyramid network(FPN)for automatic segmentation and semantic feature classification of spontaneous intracerebral hemorrhage(sICH)hematoma showed on non-contrast CT.Methods Non-contrast CT images of 408 sICH patients in hospital A(training set)and 103 sICH patients in hospital B(validation set)were retrospectively analyzed.Deep learning(DL)segmentation model was constructed based on FPN to segment the hematoma region,and its efficacy was assessed using intersection over union(IoU),Dice similarity coefficient(DSC)and accuracy.Then DL classification model was established to identify the semantic features of sICH hematoma.Receiver operating characteristic curves were drawn,and the area under the curves(AUC)were calculated to evaluate the efficacy of DL classification model for recognizing semantic features of sICH hematoma.Results The IoU,DSC and accuracy of DL segmentation model for 95％sICH hematoma in training set was 0.84±0.07,0.91±0.04 and(88.78±8.04)％,respectively,which was 0.83±0.07,0.91±0.05 and(88.59±7.76)％in validation set,respectively.The AUC of DL classification model for recognizing irregular shape,uneven density,satellite sign,mixed sign and vortex sign of sICH hematoma were 0.946-0.993 and 0.714-0.833 in training set and validation set,respectively.Conclusions FPN could accurately,effectively and automatically segment hematoma of sICH,hence having high efficacy for identifying semantic features of sICH hematoma.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.