Objective To understand the current status of fear of missing out(FoMO)social interaction in adole-scent patients with severe accidental trauma,and to explore its potential categorical characteristics,and analyze the influencing factors of different categories.Methods A convenience sampling method was employed to select 301 adolescent patients with severe accidental trauma admitted to the surgical and trauma ICU of a tertiary hospital in Chengdu City from January to December 2024.Data were collected using a general information survey,the Fear of Missing Out Scale,the Adolescent Learning Stress Scale,and the Self-Perceived Burden Scale.Latent profile analysis and multiple logistic regression analysis were used to determine different profiles and their influencing factors.Results A total of 245 adolescent patients with severe accidental trauma were ultimately included,with a Fear of Missing Out Scale score of(21.55±8.17),being categorized into 4 potential profiles of"independent type"(28.16％),"normal type"(19.59％),"social dependence type"(22.04％),and"information deficiency type"(30.20％).The results of multiple logistic regression analysis showed that literacy,per capita monthly family income,level of academic stress,level of self-awareness of medical staff care,being an only child,level of self-perceived burden,and length of hospitalization were the factors influencing the potential profiles of FoMO social interaction in adolescent patients with unintentional trauma(all P＜0.05).Conclusion There is group heterogeneity in FoMO social interaction among adolescent patients with severe accidental trauma.Medical staff should develop targeted intervention measures based on the classification characteristics of different profiles of missing anxiety in adolescent accidental trauma patients to alleviate their levels of FoMO social interaction.

Objective:To explore the interactive transfer effects between ICU transferred patients' and their primary caregivers' transfer readiness and relocation stress using the Actor-Partner Interdependence Model (APIM) .Methods:A convenience sampling method was used to select 304 pairs of ICU patients and their primary caregivers, who were transferred from the ICU between January and July 2024 at West China Hospital of Sichuan University. A general information questionnaire, ICU patients Transfer Readiness Scale, Relocation Stress Syndrome Scale-Short Form, Caregiver Preparedness Scale, and Family Relocate Stress Syndrome Scale were used to collect data. The APIM was applied to analyze the relationship between ICU patients' and caregivers' transfer readiness and relocation stress.Results:The transfer readiness scores of 304 pairs of ICU patients and their primary caregivers were (65.22±10.04) and (14.57±4.84) , respectively, and the relocation stress scores were (25.06±5.34) and (50.35±7.38) , respectively. APIM analysis showed that the transfer readiness of ICU patients negatively predicted their own relocation stress ( P<0.05) , and the transfer readiness of primary caregivers negatively predicted their own relocation stress ( P<0.05) . The ICU patients' transfer readiness negatively predicted the primary caregivers' relocation stress ( P<0.05) , while the transfer readiness of primary caregivers did not significantly predict the ICU patients' relocation stress ( P>0.05) . Conclusions:ICU patients' relocation stress is influenced by their own transfer readiness, while primary caregivers' relocation stress is jointly influenced by both their own and the patients' transfer readiness. This suggests that healthcare providers should pay attention to the transmission of relocation stress between ICU patients and their families and actively explore family-based intervention strategies.

Objective:To explore the interactive transfer effects between ICU transferred patients' and their primary caregivers' transfer readiness and relocation stress using the Actor-Partner Interdependence Model (APIM) .Methods:A convenience sampling method was used to select 304 pairs of ICU patients and their primary caregivers, who were transferred from the ICU between January and July 2024 at West China Hospital of Sichuan University. A general information questionnaire, ICU patients Transfer Readiness Scale, Relocation Stress Syndrome Scale-Short Form, Caregiver Preparedness Scale, and Family Relocate Stress Syndrome Scale were used to collect data. The APIM was applied to analyze the relationship between ICU patients' and caregivers' transfer readiness and relocation stress.Results:The transfer readiness scores of 304 pairs of ICU patients and their primary caregivers were (65.22±10.04) and (14.57±4.84) , respectively, and the relocation stress scores were (25.06±5.34) and (50.35±7.38) , respectively. APIM analysis showed that the transfer readiness of ICU patients negatively predicted their own relocation stress ( P<0.05) , and the transfer readiness of primary caregivers negatively predicted their own relocation stress ( P<0.05) . The ICU patients' transfer readiness negatively predicted the primary caregivers' relocation stress ( P<0.05) , while the transfer readiness of primary caregivers did not significantly predict the ICU patients' relocation stress ( P>0.05) . Conclusions:ICU patients' relocation stress is influenced by their own transfer readiness, while primary caregivers' relocation stress is jointly influenced by both their own and the patients' transfer readiness. This suggests that healthcare providers should pay attention to the transmission of relocation stress between ICU patients and their families and actively explore family-based intervention strategies.

Objective To understand the current status of fear of missing out(FoMO)social interaction in adole-scent patients with severe accidental trauma,and to explore its potential categorical characteristics,and analyze the influencing factors of different categories.Methods A convenience sampling method was employed to select 301 adolescent patients with severe accidental trauma admitted to the surgical and trauma ICU of a tertiary hospital in Chengdu City from January to December 2024.Data were collected using a general information survey,the Fear of Missing Out Scale,the Adolescent Learning Stress Scale,and the Self-Perceived Burden Scale.Latent profile analysis and multiple logistic regression analysis were used to determine different profiles and their influencing factors.Results A total of 245 adolescent patients with severe accidental trauma were ultimately included,with a Fear of Missing Out Scale score of(21.55±8.17),being categorized into 4 potential profiles of"independent type"(28.16％),"normal type"(19.59％),"social dependence type"(22.04％),and"information deficiency type"(30.20％).The results of multiple logistic regression analysis showed that literacy,per capita monthly family income,level of academic stress,level of self-awareness of medical staff care,being an only child,level of self-perceived burden,and length of hospitalization were the factors influencing the potential profiles of FoMO social interaction in adolescent patients with unintentional trauma(all P＜0.05).Conclusion There is group heterogeneity in FoMO social interaction among adolescent patients with severe accidental trauma.Medical staff should develop targeted intervention measures based on the classification characteristics of different profiles of missing anxiety in adolescent accidental trauma patients to alleviate their levels of FoMO social interaction.

Immune checkpoint inhibitors (ICI) have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). Biomarkers are essential for guiding precision immunotherapy. Tissue-based programmed death ligand 1 (PD-L1) expression and tumor mutational burden (TMB) are currently widely used biomarkers for selecting patients for immunotherapy. However, tissue specimens are often difficult to reach and couldn't overcome spatial and temporal heterogeneity. Blood biomarkers offer an alternative non-invasive solution that could provide a complete insight on patient's immune status and tumor as well, and show their potential in predicting the outcome as well as in monitoring response to immunotherapy. In this article, we summarize current knowledge on blood biomarkers in NSCLC patients treated with ICI, and we hope to provide more references for development of novel biomarkers.
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Objective: To study the prevalence and antimicrobial susceptibility of Ureaplasma urealyticum (Uu) and Mycoplasma hominis (Mh) in Changsha, and provide laboratory evidence for clinical drug use. Methods: A retrospective study was conducted to analyze 53 006 specimens of suspected genital mycoplasma infection in Xiangya Second Hospital of Changsha District and Hunan Wangwang Hospital from 2010 to 2017, and to analyze the infection rate and drug resistance rate of Uu and Mh. Results: From 2010 to 2017, a total of 53 006 specimens were detected, where there were 16 830 cases of Uu infection, the infection rate was 31.75%; 2 471 cases of Mh infection, the infection rate was 4.66%; and 1 071 cases of Uu and Mh mixed infection, the infection rate was 2.02%. Male Uu infection rate was 19.48%(5 989/30 749), which was lower than the female infection rate 48.71%(10 841/22 257) (χ²=5 091, P<0.001); male Mh infection rate was 3.16%(973/30 749), lower than female infection rate 6.73%(1 498/22 257) (χ²=369,P<0.001). The population of genital mycoplasma infection is concentrated between 20 and 40 years old, accounting for 71.76% (12 077/16 830). The drug resistance rates of Uu and Mh to doxycycline and minocycline were less than 2%, while the drug resistance rate to quinolones was higher; The resistance rate of Uu to macrolide antibiotics such as erythromycin, josamycin and clarithromycin were less than 2%, while the resistance rate to azithromycin, erythromycin and roxithromycin were higher, 29.74%(5 006/16 830) and 53.74%(9 045/16 830), respectively, and the resistance rate of Mh to macrolide antibiotics (except josamycin) was higher than 90%.Between 2010 and 2017, a gradually increasing resistance of ureaplasmas to azithromycin, from 3.81% (46/1 206) in 2010 to 53.15% (1 503/2 828) in 2017, and decreasing resistance to gatifloxacin and thiamphenicol were observed, from 76.78% (926/1 206) and 60.28% (727/1 206) in 2010 decreased to 34.23% (968/2 828) and 37.87% (1 071/2 828) in 2017, respectively. The resistance rate of Mh to gatifloxacin and thiamphenicol were decreased, from 68.93% (122/177) and 41.81% (74/177) in 2010 to 53.54% (159/297) and 21.21% (63/297) in 2017, respectively. Conclusions Doxycycline, minocyclinum and josamycin are good treatment options for genital mycoplasma in Changsha. The resistance rate of Uu to azithromycin is increasing, suggesting that the abuse of azithromycin is present in Changsha, and indicating that better management of antibiotics is necessary.

Bone is one of the most metastatic sites of advanced malignant tumors. With the continuous improvement of diagnosis and treatment of malignant tumors, the survival time of patients is prolonged and incidence of bone metastases also increases. Lung cancer is the leading cause of cancer-related mortality worldwide. It is estimated that the incidence of bone metastases in patients advanced lung cancer is about 30%-40%. The traditional diagnosis of bone metastases in lung cancer is based on clinical symptoms, X ray, computed tomography (CT), magnetic resonance imaging (MRI) and pathology. Recently, a large number of exploratory studies have reported blood biomarkers as indicators of bone metastasis screening and efficacy evaluation. In this review, we summarize the progress of biomarkers in diagnosis of bone metastases of lung cancer.
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Biomarkers, Tumor ; metabolism ; Bone Neoplasms ; metabolism ; physiopathology ; secondary ; Humans ; Lung Neoplasms ; pathology ; Osteogenesis

Objective To investigate the relationship between the composition of vaginal microbiota and the course of cervical precancerous lesion.Methods A total of 64 vaginal swabs were collected from 22 healthy women, 18 CINⅠ patients and 24 CINⅡ/Ⅲ patients who visited Obstetrics and Gynecology of the Second Xiangya Hospital of Central South University during July 2014 and July 2015.The Bacterial genomic DNA was extracted and the V3 and V4 hypervariable regions of 16S rRNA were amplified and high-throughput sequenced.The abundance and composition of vaginal microbiota were analyzed by Uparse, Mothur and LefSe statistical software.Results There was no significant difference in Alpha diversity index between CINⅡ/Ⅲ group(Chao:63±32;ACE:72±38;Simpson:0.70±0.27;Shannon:0.70±0.63) and control group ( Chao:48±24;ACE:54±25;Simpson:0.71±0.27;Shannon:0.65±0.58)(W=192,P=0.11;W=189,P=0.10;W=281,P=0.72;W=241,P=0.62).The ACE(85±37) and Chao(66±25) values of CINⅠgroup were significantly different from those of the control group (ACE:54±25;Chao:48±24)(W=99,P=0.006;W=113,P=0.02).At the phylum level, 78.69%(309 020/392 722) of the vaginal microbiota in the control group was Firmicutes, 16%(62 846/392 722) was Actinobacteria.Firmicutes was reduced to 64.86%(208 422/321 318) and Actinobacteria increased to 27.71%(89 040/321 318) in CINⅠgroup.The composition of vaginal microbiotain in CINⅡ/Ⅲ group was similar to those of control group.At the genus level, the composition of vaginal microbiota were similar between CINⅡ/Ⅲ group and control group, with Lactobacillus as predominant genus[71.81%(307 658/418 424)], Gardnerella[12.91%(55 299/428 424)], others such as Prevotella, atopobium were less.In the CINⅠ group, the abundance of Lactobacillus was decreased to 56.26%(180 787/321 318), Gardnerella was increased to 19.62%(63 057/321 318), and Listeria was increased to 7.7%(24 746/321 318).The composition of vaginal microbiota in the most samples was classified as CSTⅢ and CSTⅠ, with Lactobacillus inersand and Lactobacillus crispatus were dominant respectively.There was no significant difference in the composition of vaginal microbiota between the three groups(χ2=2.72, P=0.949).LEfSe analysis showed that the abundance of bacteria in CIN group and control group were varied.At the genus level, there were significant differences in the abundance of Geobacter, Atopobium and Ureaplasma (P<0.05, P<0.05, P<0.01, respectively).At the species level, there was significant difference in the abundance of Ureaplasma urealyticum serotype 9 (P<0.01).Conclusion The diversity and the composition of vaginal microbiota were similar between CIN patients and healthy women, but the abundances of some bacteria were varied, with Ureaplasma increased in patients with CIN.

Background and objective Treatment options for patients with squamous cell carcinoma of the lung (SCC) are limited in chemotherapy. However, not all patients could benefit form standard platinum regimen. Considering the dismal prognosis of patients with advanced SCC, a greater focus on selecting sensitive chemotherapy regimens remains of up-most importance to improve outcomes in this disease. In this study, we used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to detect pre-chemotherapy serum peptides in advanced lung squamous cell carcinoma patients accepting paclitaxel combined with platinum chemotherapy and to analyze the correlation between serum peptides and che-motherapy efcacy. Methods Patients with advanced lung squamous cell carcinoma received paclitaxel combining with plati-num chemotherapy and evaluated the efcacy every two cycles. Evaluation of complete response (CR) or partial response (PR) patients defined as sensitive group, progressive disease (PD) patients defined as resistant group. Serum samples were collected from patients with lung squamous cell carcinoma. Eighty-one patients were randomly divided into training group (sensitive group Ⅰ and resistant group Ⅰ) and validation group (sensitive group Ⅱ and resistant group Ⅱ) according to the ratio of 3:1. Se-rum samples were pretreated and Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) was used to detect serum peptide fingerprints. ClinProTools software was used to analyze the differences between the sensitive group Ⅰ and the resistant group Ⅰ. Three kinds of biological algorithms (SNN, GA, QC) built in CPT software were used to establish the curative effect prediction model respectively and the optimal algorithm was selected. The validation group was used for blind verification. Results Thirty sensitive patients and 31 resistant patients were enrolled in the training group. Ten sensitive patients and 10 resistant patients were included in the validation group. The training group had 96 differentially expressed peptides in the sensitive and resistant patients, with 16 statistically significant peptides (P<0.001). The predictive model was established by 5 polypeptides (1,897.75 Da, 2,023.93 Da, 3,683.36 Da, 4,269.56 Da, 5,341.29 Da). The recognition rate of this model was 89.18% and the cross validation rate was 95.11%. The accuracy of the model was 85%, the sensitivity was 90.0% and the specificity was 80.0%. The median PFS in the sensitive group was better than patients in the resistant group (7.2 months 95%CI: 4.4-14.5 vs 1.8 months 95%CI: 0.7-3.5). The results showed that the differential peptides 4,232.04 Da and 4,269.56 Da were correlated with PFS in patients with lung squamous cell carcinoma (P<0.001). Conclusion MALDI-TOF-MS was used to detect the difference of serum peptides between sensitive and resistant groups. The preliminary curative effect prediction model was used to predict the efcacy of paclitaxel combined with platinum regimen. However, this model need further investigations to verify the accuracy and the sensitivity.

Lung cancer, of which approximately 85% are non-small cell lung cancer (NSCLC), is one of the most prevalent cancers and the most leading cause of cancer mortality. Despite recent improvements in its treatment, the prognosis remains dismal. Previous studies have clearly proved that estrogen and estrogen receptors (ER) are involve in the pathogenesis and development of lung cancer. More and more evidences showed antiestrogen therapy may reverse the drug-resistance of platinum based chemotherapy in NSCLC patients and can enhance curative effect of epidermal growth factor receptor tyrosine kinase inhibitor. We will review recent progress in the function of estrogen in NSCLC and the treatment based on the ER sig-naling pathways for NSCLC in this article.