Background: We have reported a positive correlation between S100 calcium-binding protein (S100) A8/S100A9 and sepsis-induced lung damage before. However, limited knowledge exists concerning the biological role of S100A8/A9 in pulmonary vascular endothelial barrier dysfunction, as well as the diagnostic value of S100A8/A9 in sepsis. Methods: Sepsis was induced in C57BL/6J mice and S100A9-knockout (KO) mice through the cecal ligation and puncture (CLP). Pulmonary vascular leakage was determined by measuring extravasated Evans blue (EB). Reverse transcription polymerase chain reaction and the histological score were used to evaluate inflammation and lung injury, respectively. Recombinant S100A8/A9 (rhS100A8/A9) was used to identify the effects of S100A8/A9 on endothelial barrier dysfunction in human umbilical vein endothelial cells (HUVECs). Additionally, the diagnostic value of S100A8/A9 in sepsis was assessed using receiver operating characteristic. Results: S100A8/A9 expression was up-regulated in the lungs of CLP-operated mice. S100A9 KO significantly reversed CLP-induced hypothermia and hypotension, resulting in an improved survival rate. S100A9 KO also decreased the inflammatory response, EB leakage, and histological scores in the lungs of CLP-operated mice. Occludin and VE-cadherin expressions were decreased in the lungs of CLP-operated mice; However, S100A9 KO attenuated this decrease. Moreover, CLP-induced signal transducer and activator of transcription 3 (STAT3) and p38/extracellular signal-regulated kinase (ERK) signalling activation and apoptosis were mitigated by S100A9 KO in lungs. In addition, rhS100A8/A9 administration significantly decreased occludin and VE-cadherin expressions, increased the phosphorylated (p)-ERK/ERK, p-p38/p38, and B-cell leukaemia/lymphoma 2 protein (Bcl-2)-associated X protein/Bcl-2 ratios in HUVECs. Conclusion: The present study demonstrated S100A8/A9 aggravated sepsis-induced pulmonary inflammation, vascular permeability, and lung injury. This was achieved, at least partially, by activating the P38/STAT3/ERK signalling pathways. Moreover, S100A8/A9 showed the potential as a biomarker for sepsis diagnosis.

Rib fracture is the most common injury in chest trauma. Most of patients with rib fractures were treated conservatively, but up to 50% of patients, especially those with combined injury such as flail chest, presented chronic pain or chest wall deformities, and more than 30% had long-term disabilities, unable to retain a full-time job. In the past two decades, surgery for rib fractures has achieving good outcomes. However, in clinic, there are still some problems including inconsistency in surgical indications and quality control in medical services. Before the year of 2018, there were 3 guidelines on the management of regional traumatic rib fractures were published at home and abroad, focusing on the guidance of the overall treatment decisions and plans; another clinical guideline about the surgical treatment of rib fractures lacks recent related progress in surgical treatment of rib fractures. The Chinese Society of Traumatology, Chinese Medical Association, and the Chinese College of Trauma Surgeons, Chinese Medical Doctor Association organized experts from cardiothoracic surgery, trauma surgery, acute care surgery, orthopedics and other disciplines to participate together, following the principle of evidence-based medicine and in line with the scientific nature and practicality, formulated the Chinese consensus for surgical treatment of traumatic rib fractures (STTRF 2021). This expert consensus put forward some clear, applicable, and graded recommendations from seven aspects: preoperative imaging evaluation, surgical indications, timing of surgery, surgical methods, rib fracture sites for surgical fixation, internal fixation method and material selection, treatment of combined injuries in rib fractures, in order to provide guidance and reference for surgical treatment of traumatic rib fractures.

Background: This study assessed the global trends and burden of severe chest injury, including rib fractures, lung contusions, and heart injuries from 1990 to 2019. Herein, we predicted the burden patterns and temporal trends of severe chest injuries to provide epidemiological evidence globally and in China. Methods: In our analysis, the age-standardized incidence rate (ASIR), prevalence rate (ASPR), and years lived with disability rate (ASYR) of severe chest injury were analyzed by gender, age, sociodemographic index, and geographical region between 1990 and 2019 using data from the Global Burden of Disease study 2019. Trends were depicted by calculating the estimated annual percentage changes (EAPCs). The impact of age, period, and cohort factors was assessed using an Age-Period-Cohort model. Autoregressive integrated moving average (ARIMA) model was employed to predict severe chest injury trends from 2020 to 2050. Results: In 2019, the global number of severe chest injury cases reached 7.95 million, with the highest incidence rate observed in Central Europe (209.61). Afghanistan had the highest ASIRs at 277.52, while North Korea had the lowest ASIRs at 41.02. From 1990 to 2019, the Syrian Arab Republic saw significant increases in ASIR, ASPR, and ASYR, with EAPCs of 10.4%, 9.31%, and 10.3%, respectively. Burundi experienced a decrease in ASIR with an EAPC of − 6.85% (95% confidence interval [CI] − 11.11, − 2.37), while Liberia’s ASPR and ASYR declined with EAPCs of − 3.22% (95% CI − 4.73, − 1.69) and − 5.67% (95% CI − 8.00, − 3.28), respectively. Falls and road injuries remained the most common causes. The relative risk of severe chest injury by age, period, and cohort demonstrated a complex effect globally and in China. The ARIMA model forecasted a steady increase in global numbers from 2020 to 2050, while in China, it forecasted an increase in incidence, a decrease in ASIR and ASYR, and an increase in ASPR. Conclusions: This study provides a groundbreaking analysis of global severe chest injury, shedding light on its measures and impact. These findings highlight the need for timely, specialized care and addressing regional disparities to mitigate the severe chest injury burden.

In recent years, global natural disasters have been frequent and resulted in great casualties and property loss. Since Wenchuan earthquake, the disaster emergency rescue system of China has obtained considerable development in various aspects including team construction, task scheduling, personnel training, facilities and equipments, logistics, etc. On April 25, 2015, an earthquake that measured 8.1 on the Richter scale attacked Nepal. Chinese government firstly organized a medical team, named China Medical Team, and sent it to the attacked region in Nepal to implement medical rescue. The medical team completed the rescue mission successfully and creatively based on their experiences.

Nuclear factor-κB (NF-κB) family plays an important role in the development of sepsis in critically ill patients. Although several single nucleotide polymorphisms (SNPs) have been identified in the NF-κB family genes, only a few SNPs have been studied. A total of 753 patients with major blunt trauma were included in this study. Tag SNPs (tSNPs) were selected from the NF-κB family genes (NFKB1, NFKB2, RELA, RELB and REL) through construction of haplotype blocks. The SNPs selected from genes within the canonical NF-κB pathway (including NFKB1, RELA and REL), which played a critical role in innate immune responses were genotyped using pyrosequencing method and analyzed in relation to the risk of development of sepsis and multiple organ dysfunction (MOD) syndrome. Moreover, the rs842647 polymorphism was analyzed in relation to tumor necrosis factor α (TNF-α) production by peripheral blood leukocytes in response to bacterial lipoprotein stimulation. Eight SNPs (rs28362491, rs3774932, rs4648068, rs7119750, rs4803789, rs12609547, rs1560725 and rs842647) were selected from the NF-κB family genes. All of them were shown to be high-frequency SNPs in this study cohort. Four SNPs (rs28362491, rs4648068, rs7119750 and rs842647) within the canonical NF-κB pathway were genotyped, and rs842647 was associated with sepsis morbidity rate and MOD scores. An association was also observed between the rs842647 A allele and lower TNF-α production. rs842647 polymorphism might be used as relevant risk estimate for the development of sepsis and MOD syndrome in patients with major trauma.

Objective: Pneumonia is a common pulmonary complication of flail chest, causing high morbidity and mortality rates in affected patients. The existing methods for identifying pneumonia have low accuracy, and their use may delay antimicrobial therapy. However, machine learning can be combined with electronic medical record systems to identify information and assist in quick clinical decision-making. Our study aimed to develop a novel machine-learning model to predict pneumonia risk in flail chest patients.Methods: From January 2011 to December 2021, the electronic medical records of 169 adult patients with flail chest at a tertiary teaching hospital in an urban level I Trauma Centre in Chongqing were retrospectively analysed. Then, the patients were randomly divided into training and test sets at a ratio of 7:3. Using the Fisher score, the best subset of variables was chosen. The performance of the seven models was evaluated by computing the area under the receiver operating characteristic curve (AUC). The output of the XGBoost model was shown using the Shapley Additive exPlanation (SHAP) method.Results: Of 802 multiple rib fracture patients, 169 flail chest patients were eventually included, and 86 (50.80%) were diagnosed with pneumonia. The XGBoost model performed the best among all seven machine-learning models. The AUC of the XGBoost model was 0.895 (sensitivity: 84.3%; specificity: 80.0%).Pneumonia in flail chest patients was associated with several features: systolic blood pressure, pH value, blood transfusion, and ISS.Conclusion: Our study demonstrated that the XGBoost model with 32 variables had high reliability in assessing risk indicators of pneumonia in flail chest patients. The SHAP method can identify vital pneumonia risk factors, making the XGBoost model's output clinically meaningful.