Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. Septic shock is the primary cause of mortality in sepsis, with its core pathophysiological mechanism being severe ischemia and hypoxia in critical units—composed of microcirculation and the mitochondria of functional cells—resulting from disruptions in blood flow and oxygen flow following a dysregulated host response. Due to the systemically convergent yet clinically heterogeneous nature of the host response, current understanding and management strategies for hemodynamics remain inconsistent, often leading to inadequate resuscitation or overtreatment. To improve the quality of care, based on a systematic review of the "blood flow-oxygen flow" theory, an expert panel emphasizes reevaluating septic shock from an integrated perspective of blood flow and oxygen flow, and has formulated the Expert Consensus on Blood Flow and Oxygen Delivery Phenotyping and Clinical Management of Septic Shock (2025). The consensus proposes that clinical typing of blood flow-oxygen flow should comprehensively consider cardiac function, vascular tone, oxygen flow utilization status in critical units, and disease trajectory, while optimizing subtype identification by integrating host response phenotypes and artificial intelligence technologies. It advocates establishing a continuous assessment system through multi-site oxygen flow monitoring for organ perfusion, peripheral perfusion monitoring, and critical care ultrasound. Under the framework of the "critical care triangle", the consensus promotes the implementation of individualized, bundled management strategies, providing guidance for multiple management points to restore blood flow-oxygen flow matching, reduce the risk of organ failure, and decrease patient mortality.

ObjectiveTo construct and evaluate a mouse model that simulates the pathological progression of immune checkpoint inhibitor-associated pneumonitis (CIP), in order to address the critical issue of the lack of standardized animal models in this research field. MethodsThirty-five SPF-grade 6-week-old male C57BL/6J mice were randomly assigned to a control group (n=5), a bleomycin (BLM) group (n=15), and a BLM+programmed death-1 (PD-1) monoclonal antibody (BLM+PD-1) group (n=15). Corresponding drugs were administered via intraperitoneal injection for intervention. The general condition, body weight changes, survival rate, and pulmonary histopathological alterations were systematically monitored. ResultsCompared with the BLM group, the BLM+PD-1 group exhibited significantly more severe pulmonary fibrosis, characterized by progressive body weight loss and more severe deterioration of general conditions. Histopathological examination showed that pulmonary inflammation was alleviated 4 weeks post-modeling in the BLM group. In contrast, pulmonary lesions continued to worsen in the BLM+PD-1 group, with no evidence of resolution of inflammation 28 days post-modeling. Quantitative immunohistochemical analysis revealed that the positive expression rate of interleukin-17A (IL-17A) in lung tissues reached 34.28% in the BLM+PD-1 group 14 days post-modeling, which was markedly higher than that in the BLM group (24.02%, P < 0.000 1). The positive expression rate of α-smooth muscle actin (α-SMA) was 12.40% in the BLM+PD-1 group 14 days post-modeling, nearly twice the level in the BLM group (5.87%). 28 days post-modeling, the positive expression rate of α-SMA remained at 7.72% in the BLM+PD-1 group, while it declined to 3.38% in the BLM group. ConclusionThe addition of a PD-1 inhibitor to bleomycin treatment accelerates the progression of pulmonary interstitial fibrosis and effectively recapitulates the pathological process of lung injury and fibrosis driven by aberrant immune activation during clinical immunotherapy. Accordingly, this study successfully establishes a dynamic CIP animal model recapitulating the progression from early inflammatory response to pulmonary fibrosis. This model addresses the critical shortage of animal models for this condition and offers an experimental platform for further mechanistic studies and the development of therapeutic strategies.

Objective:To present a set of clinically representative quality assurance (QA) test cases for stereotactic radiosurgery (SRT) plans of multiple intracranial metastases, in order to assess the plan quality and machine execution capabilities.Methods:Based on the clinical characteristics of multiple brain metastases, four groups of test cases with three target volumes (TVs), six TVs, nine TVs, and TVs near organs at risk (OARs) were designed. For these cases, SRT plans were developed, and plan quality was assessed using metrics including the Radiation Therapy Oncology Group conformality index (RTOG CI), gradient index (GI), homogeneity index (HI), and the volume of normal brain tissue receiving a dose of 24 Gy ( V24 Gy), which was defined as the volume enclosed by the 24 Gy isodose line around the Brain-PTV ( V24 Gy of Brain-PTV). Verification plans were generated for each test case, including the verification of point doses, planar doses (PD), and SRS MapCHECK (SMC) semiconductor matrix planar doses. Compared with the calculated result of the treatment planning system (TPS), the criteria for the γ analysis of planar doses were set at 1 mm/2% and 2 mm/2%. Results:For the four groups of test cases, the mean CI, GI, HI, and V24 Gy of Brain-PTV were 1.04±0.03, 3.79±0.40, 0.73±0.01 and (7.46±3.80) cm 3, respectively. The mean deviations of the point doses were 0.88%±0.98%, 1.47%±0.79%, 1.52%± 0.76%, and 1.17% ± 0.38%, respectively. The mean γ passing rates of the single fields for PDs were greater than 98% at 2 mm/2% and exceeding 96% at 1 mm/2%, and the mean γ pass rates of the SMC semiconductor matrix for PDs were 97.75% ± 2.31% and 99.33% ± 0.62%, at 1 mm/2% and 2 mm/2% respectively. Conclusions:The proposed QA test cases for SRT of multiple intracranial metastases allow for the effective assessments of the plan quality and machine execution capabilities and, thus, can assist various centers in clinical applications.

Objective:To present a set of clinically representative quality assurance (QA) test cases for stereotactic radiosurgery (SRT) plans of multiple intracranial metastases, in order to assess the plan quality and machine execution capabilities.Methods:Based on the clinical characteristics of multiple brain metastases, four groups of test cases with three target volumes (TVs), six TVs, nine TVs, and TVs near organs at risk (OARs) were designed. For these cases, SRT plans were developed, and plan quality was assessed using metrics including the Radiation Therapy Oncology Group conformality index (RTOG CI), gradient index (GI), homogeneity index (HI), and the volume of normal brain tissue receiving a dose of 24 Gy ( V24 Gy), which was defined as the volume enclosed by the 24 Gy isodose line around the Brain-PTV ( V24 Gy of Brain-PTV). Verification plans were generated for each test case, including the verification of point doses, planar doses (PD), and SRS MapCHECK (SMC) semiconductor matrix planar doses. Compared with the calculated result of the treatment planning system (TPS), the criteria for the γ analysis of planar doses were set at 1 mm/2% and 2 mm/2%. Results:For the four groups of test cases, the mean CI, GI, HI, and V24 Gy of Brain-PTV were 1.04±0.03, 3.79±0.40, 0.73±0.01 and (7.46±3.80) cm 3, respectively. The mean deviations of the point doses were 0.88%±0.98%, 1.47%±0.79%, 1.52%± 0.76%, and 1.17% ± 0.38%, respectively. The mean γ passing rates of the single fields for PDs were greater than 98% at 2 mm/2% and exceeding 96% at 1 mm/2%, and the mean γ pass rates of the SMC semiconductor matrix for PDs were 97.75% ± 2.31% and 99.33% ± 0.62%, at 1 mm/2% and 2 mm/2% respectively. Conclusions:The proposed QA test cases for SRT of multiple intracranial metastases allow for the effective assessments of the plan quality and machine execution capabilities and, thus, can assist various centers in clinical applications.

Objective:The clinical data of prenatal stillbirth were analyzed in order to increase the understand-ing of the causes of stillbirth.Methods:Prenatal stillbirth cases that terminated pregnancy in Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University from January 2018 to December 2022 were col-lected,and the distribution characteristics of clinical data and the stillbirth causes were analyzed.The causes of death were classified according to the standards developed by the Stillbirth Collaborative Research Network(SCRN)in the United States,and they were divided into clear cause-of-death group and unknown cause-of-death group.The different characteristics of the two groups were compared and analyzed.Results:There were 210 ca-ses of prenatal stillbirth during the study period,and 104 cases met the inclusion criteria.Among them,33 cases(31.7%)had autopsy results,39 cases(37.5%)had genetic results,and 75 cases(72.1%)had placental pathol-ogy.According to the classification of SCRN standard,55 cases(52.9%)were probably related to the cause of death,33 cases(31.7%)were classified as possible,13 cases(12.5%)were probably unrelated,and 3 cases(2.9%)could not be attributed to the cause of death,that is,84.6%(88 cases)in the clear cause of death group and 15.4%(16 cases)in the unknown cause of death group.The rate of placental pathological examination in the clear cause of death group was significantly higher than that in the unknown cause of death group(78.4%).In the classification of causes of death,placental pathological changes accounted for the largest proportion,account-ing for 26.9%(28 cases),followed by pregnancy complications accounting for 25.0%(26 cases),and 15.4%of the cases were still unexplained.Conclusions:Placental pathology is of great significance for clarifying the cause of stillbirth.It is feasible to use SCRN to classify the etiology of stillbirth.Pathological placental conditions account for a relatively high proportion in the classification of stillbirth causes.It is recommended that each case of stillbirth placenta should undergo pathological examination.

Objective:The clinical data of prenatal stillbirth were analyzed in order to increase the understand-ing of the causes of stillbirth.Methods:Prenatal stillbirth cases that terminated pregnancy in Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University from January 2018 to December 2022 were col-lected,and the distribution characteristics of clinical data and the stillbirth causes were analyzed.The causes of death were classified according to the standards developed by the Stillbirth Collaborative Research Network(SCRN)in the United States,and they were divided into clear cause-of-death group and unknown cause-of-death group.The different characteristics of the two groups were compared and analyzed.Results:There were 210 ca-ses of prenatal stillbirth during the study period,and 104 cases met the inclusion criteria.Among them,33 cases(31.7%)had autopsy results,39 cases(37.5%)had genetic results,and 75 cases(72.1%)had placental pathol-ogy.According to the classification of SCRN standard,55 cases(52.9%)were probably related to the cause of death,33 cases(31.7%)were classified as possible,13 cases(12.5%)were probably unrelated,and 3 cases(2.9%)could not be attributed to the cause of death,that is,84.6%(88 cases)in the clear cause of death group and 15.4%(16 cases)in the unknown cause of death group.The rate of placental pathological examination in the clear cause of death group was significantly higher than that in the unknown cause of death group(78.4%).In the classification of causes of death,placental pathological changes accounted for the largest proportion,account-ing for 26.9%(28 cases),followed by pregnancy complications accounting for 25.0%(26 cases),and 15.4%of the cases were still unexplained.Conclusions:Placental pathology is of great significance for clarifying the cause of stillbirth.It is feasible to use SCRN to classify the etiology of stillbirth.Pathological placental conditions account for a relatively high proportion in the classification of stillbirth causes.It is recommended that each case of stillbirth placenta should undergo pathological examination.

Objective:The clinical data of prenatal stillbirth were analyzed in order to increase the understand-ing of the causes of stillbirth.Methods:Prenatal stillbirth cases that terminated pregnancy in Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University from January 2018 to December 2022 were col-lected,and the distribution characteristics of clinical data and the stillbirth causes were analyzed.The causes of death were classified according to the standards developed by the Stillbirth Collaborative Research Network(SCRN)in the United States,and they were divided into clear cause-of-death group and unknown cause-of-death group.The different characteristics of the two groups were compared and analyzed.Results:There were 210 ca-ses of prenatal stillbirth during the study period,and 104 cases met the inclusion criteria.Among them,33 cases(31.7%)had autopsy results,39 cases(37.5%)had genetic results,and 75 cases(72.1%)had placental pathol-ogy.According to the classification of SCRN standard,55 cases(52.9%)were probably related to the cause of death,33 cases(31.7%)were classified as possible,13 cases(12.5%)were probably unrelated,and 3 cases(2.9%)could not be attributed to the cause of death,that is,84.6%(88 cases)in the clear cause of death group and 15.4%(16 cases)in the unknown cause of death group.The rate of placental pathological examination in the clear cause of death group was significantly higher than that in the unknown cause of death group(78.4%).In the classification of causes of death,placental pathological changes accounted for the largest proportion,account-ing for 26.9%(28 cases),followed by pregnancy complications accounting for 25.0%(26 cases),and 15.4%of the cases were still unexplained.Conclusions:Placental pathology is of great significance for clarifying the cause of stillbirth.It is feasible to use SCRN to classify the etiology of stillbirth.Pathological placental conditions account for a relatively high proportion in the classification of stillbirth causes.It is recommended that each case of stillbirth placenta should undergo pathological examination.

Objective:The clinical data of prenatal stillbirth were analyzed in order to increase the understand-ing of the causes of stillbirth.Methods:Prenatal stillbirth cases that terminated pregnancy in Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University from January 2018 to December 2022 were col-lected,and the distribution characteristics of clinical data and the stillbirth causes were analyzed.The causes of death were classified according to the standards developed by the Stillbirth Collaborative Research Network(SCRN)in the United States,and they were divided into clear cause-of-death group and unknown cause-of-death group.The different characteristics of the two groups were compared and analyzed.Results:There were 210 ca-ses of prenatal stillbirth during the study period,and 104 cases met the inclusion criteria.Among them,33 cases(31.7%)had autopsy results,39 cases(37.5%)had genetic results,and 75 cases(72.1%)had placental pathol-ogy.According to the classification of SCRN standard,55 cases(52.9%)were probably related to the cause of death,33 cases(31.7%)were classified as possible,13 cases(12.5%)were probably unrelated,and 3 cases(2.9%)could not be attributed to the cause of death,that is,84.6%(88 cases)in the clear cause of death group and 15.4%(16 cases)in the unknown cause of death group.The rate of placental pathological examination in the clear cause of death group was significantly higher than that in the unknown cause of death group(78.4%).In the classification of causes of death,placental pathological changes accounted for the largest proportion,account-ing for 26.9%(28 cases),followed by pregnancy complications accounting for 25.0%(26 cases),and 15.4%of the cases were still unexplained.Conclusions:Placental pathology is of great significance for clarifying the cause of stillbirth.It is feasible to use SCRN to classify the etiology of stillbirth.Pathological placental conditions account for a relatively high proportion in the classification of stillbirth causes.It is recommended that each case of stillbirth placenta should undergo pathological examination.

Objective:The clinical data of prenatal stillbirth were analyzed in order to increase the understand-ing of the causes of stillbirth.Methods:Prenatal stillbirth cases that terminated pregnancy in Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University from January 2018 to December 2022 were col-lected,and the distribution characteristics of clinical data and the stillbirth causes were analyzed.The causes of death were classified according to the standards developed by the Stillbirth Collaborative Research Network(SCRN)in the United States,and they were divided into clear cause-of-death group and unknown cause-of-death group.The different characteristics of the two groups were compared and analyzed.Results:There were 210 ca-ses of prenatal stillbirth during the study period,and 104 cases met the inclusion criteria.Among them,33 cases(31.7%)had autopsy results,39 cases(37.5%)had genetic results,and 75 cases(72.1%)had placental pathol-ogy.According to the classification of SCRN standard,55 cases(52.9%)were probably related to the cause of death,33 cases(31.7%)were classified as possible,13 cases(12.5%)were probably unrelated,and 3 cases(2.9%)could not be attributed to the cause of death,that is,84.6%(88 cases)in the clear cause of death group and 15.4%(16 cases)in the unknown cause of death group.The rate of placental pathological examination in the clear cause of death group was significantly higher than that in the unknown cause of death group(78.4%).In the classification of causes of death,placental pathological changes accounted for the largest proportion,account-ing for 26.9%(28 cases),followed by pregnancy complications accounting for 25.0%(26 cases),and 15.4%of the cases were still unexplained.Conclusions:Placental pathology is of great significance for clarifying the cause of stillbirth.It is feasible to use SCRN to classify the etiology of stillbirth.Pathological placental conditions account for a relatively high proportion in the classification of stillbirth causes.It is recommended that each case of stillbirth placenta should undergo pathological examination.

Objective:The clinical data of prenatal stillbirth were analyzed in order to increase the understand-ing of the causes of stillbirth.Methods:Prenatal stillbirth cases that terminated pregnancy in Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University from January 2018 to December 2022 were col-lected,and the distribution characteristics of clinical data and the stillbirth causes were analyzed.The causes of death were classified according to the standards developed by the Stillbirth Collaborative Research Network(SCRN)in the United States,and they were divided into clear cause-of-death group and unknown cause-of-death group.The different characteristics of the two groups were compared and analyzed.Results:There were 210 ca-ses of prenatal stillbirth during the study period,and 104 cases met the inclusion criteria.Among them,33 cases(31.7%)had autopsy results,39 cases(37.5%)had genetic results,and 75 cases(72.1%)had placental pathol-ogy.According to the classification of SCRN standard,55 cases(52.9%)were probably related to the cause of death,33 cases(31.7%)were classified as possible,13 cases(12.5%)were probably unrelated,and 3 cases(2.9%)could not be attributed to the cause of death,that is,84.6%(88 cases)in the clear cause of death group and 15.4%(16 cases)in the unknown cause of death group.The rate of placental pathological examination in the clear cause of death group was significantly higher than that in the unknown cause of death group(78.4%).In the classification of causes of death,placental pathological changes accounted for the largest proportion,account-ing for 26.9%(28 cases),followed by pregnancy complications accounting for 25.0%(26 cases),and 15.4%of the cases were still unexplained.Conclusions:Placental pathology is of great significance for clarifying the cause of stillbirth.It is feasible to use SCRN to classify the etiology of stillbirth.Pathological placental conditions account for a relatively high proportion in the classification of stillbirth causes.It is recommended that each case of stillbirth placenta should undergo pathological examination.