Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

Are TrkB receptor agonists the right tool to fulfill the promises for a therapeutic value of the brain-derived neurotrophic factor?

Brain-derived neurotrophic factor signaling via its receptor tro pomyosin receptor kinase B regulates several crucial physiological processes.It has been shown to act in the brain,promoting neuronal survival,growth,and plasticity as well as in the rest of the body where it is involved in regulating for instance aspects of the metabolism.Due to its crucial and very pleiotro pic activity,reduction of brain-derived neurotrophic factor levels and alterations in the brain-derived neurotrophic factor/tropomyosin receptor kinase B signaling have been found to be associated with a wide spectrum of neurological diseases.Howeve r,because of its poor bioavailability and pharmacological properties,brain-derived neurotrophic factor itself has a very low therapeutic value.Moreover,the concomitant binding of exogenous brain-derived neurotrophic factor to the p75 neurotrophin receptor has the potential to elicit several unwanted and deleterious side effects.Therefo re,developing tools and approaches to specifically promote tropomyosin receptor kinase B signaling has become an important goal of translational research.Among the newly developed tools are different categories of tropomyosin receptor kinase B receptor agonist molecules.In this review,we give a comprehensive description of the diffe rent tro pomyosin receptor kinase B receptor agonist drugs developed so far and of the res ults of their application in animal models of several neurological diseases.Moreover,we discuss the main benefits of tropomyosin receptor kinase B receptor agonists,concentrating especially on the new tropomyosin receptor kinase B agonist antibodies.The benefits observed both in vitro and in vivo upon application of tropomyosin receptor kinase B receptor agonist drugs seem to predominantly depend on their general neuroprotective activity and their ability to promote neuronal plasticity.Moreover,tro pomyosin receptor kinase B agonist antibodies have been shown to specifically bind the tropomyosin receptor kinase B receptor and not p75 neurotrophin receptor.Therefore,while,based on the current knowledge,the tropomyosin receptor kinase B receptor agonists do not seem to have the potential to reve rse the disease pathology per se,promoting brainderived neurotrophic factor/tro pomyosin receptor kinase B signaling still has a very high therapeutic relevance.

Hepatocyte growth factor promotes retinal pigment epithelium cell activity through MET/AKT signaling pathway

AIM:To explore the effects of hepatocyte growth factor(HGF)on retinal pigment epithelium(RPE)cell behaviors.METHODS:The human adult retinal pigment epithelial cell line-19(ARPE-19)were treated by HGF or mesenchymalepithelial transition factor(MET)inhibitor SU11274 in vitro.Cell viability was detected by a Cell Counting Kit-8 assay.Cell proliferation and motility was detected by a bromodeoxyuridine incorporation assay and a wound healing assay,respectively.The expression levels of MET,phosphorylated MET,protein kinase B(AKT),and phosphorylated AKT proteins were determined by Western blot assay.The MET and phosphorylated MET proteins were also determined by immunofluorescence assay.RESULTS:HGF increased ARPE-19 cells’viability,proliferation and migration,and induced an increase of phosphorylated MET and phosphorylated AKT proteins.SU11274 significantly reduced cell viability,proliferation,and migration and decreased the expression of MET and AKT proteins.SU11274 suppressed HGF-induced increase of viability,proliferation,and migration in ARPE-19 cells.Additionally,SU11274 also blocked HGF-induced phosphorylation of MET and AKT proteins.CONCLUSION:HGF enhances cellular viability,proliferation,and migration in RPE cells through the MET/AKT signaling pathway,whereas this enhancement is suppressed by the MET inhibitor SU11274.HGF-induced MET/AKT signaling might be a vital contributor of RPE cells survival.

Biological factors driving colorectal cancer metastasis

Approximately 20%of colorectal cancer(CRC)patients present with metastasis at diagnosis.Among Stage I-III CRC patients who undergo surgical resection,18%typically suffer from distal metastasis within the first three years following initial treatment.The median survival duration after the diagnosis of metastatic CRC(mCRC)is only 9 mo.mCRC is traditionally considered to be an advanced stage malignancy or is thought to be caused by incomplete resection of tumor tissue,allowing cancer cells to spread from primary to distant organs;however,increa-sing evidence suggests that the mCRC process can begin early in tumor development.CRC patients present with high heterogeneity and diverse cancer phenotypes that are classified on the basis of molecular and morphological alterations.Different genomic and nongenomic events can induce subclone diversity,which leads to cancer and metastasis.Throughout the course of mCRC,metastatic cascades are associated with invasive cancer cell migration through the circulatory system,extravasation,distal seeding,dormancy,and reactivation,with each step requiring specific molecular functions.However,cancer cells presenting neoantigens can be recognized and eliminated by the immune system.In this review,we explain the biological factors that drive CRC metastasis,namely,genomic instability,epigenetic instability,the metastatic cascade,the cancer-immunity cycle,and external lifestyle factors.Despite remarkable progress in CRC research,the role of molecular classification in therapeutic intervention remains unclear.This review shows the driving factors of mCRC which may help in identifying potential candidate biomarkers that can improve the diagnosis and early detection of mCRC cases.

Sorl1 knockout inhibits expression of brain-derived neurotrophic factor:involvement in the development of late-onset Alzheimer's disease

Sortilin-related receptor 1(SORL1)is a critical gene associated with late-onset Alzheimer’s disease.SORL1 contributes to the development and progression of this neurodegenerative condition by affecting the transport and metabolism of intracellularβ-amyloid precursor protein.To better understand the underlying mechanisms of SORL1 in the pathogenesis of late-onset Alzheimer s disease,in this study,we established a mouse model of SorI1 gene knockout using cluste red regularly inters paced short palindro mic repeats-associated protein 9 technology.We found that Sorl1-knocko ut mice displayed deficits in learning and memory.Furthermore,the expression of brain-derived neurotrophic factor was significantly downregulated in the hippocampus and co rtex,and amyloidβ-protein deposits were observed in the brains of 5orl1-knockout mice.In vitro,hippocampal neuronal cell synapses from homozygous Sorl1-knockout mice were impaired.The expression of synaptic proteins,including Drebrin and NR2B,was significantly reduced,and also their colocalization.Additionally,by knocking out the Sorl1 gene in N2a cells,we found that expression of the N-methyl-D-aspartate receptor,NR2B,and cyclic adenosine monophosphate-response element binding protein was also inhibited.These findings suggest that SORL1 participates in the pathogenesis of late-onset Alzheimer s disease by regulating the N-methyl-D-aspartate receptor NR2B/cyclic adenosine monophosphate-response element binding protein signaling axis.

Transcription factor OsSPL10 interacts with OsJAmyb to regulate blast resistance in rice

Transcription factors(TFs)play essential roles in transcriptional reprogramming during activation of plant immune responses to pathogens.OsSPL10(SQUAMOSA promoter binding protein-like10)is an important TF regulating trichome development and salt tolerance in rice.Here we report that knockout of OsSPL10 reduces whereas its overexpression enhances rice resistance to blast disease.OsSPL10 positively regulates chitin-induced immune responses including reactive oxygen species(ROS)burst and callose deposition.We show that OsSPL10 physically associates with OsJAmyb,an important TF involved in jasmonic acid(JA)signaling,and positively regulates its protein stability.We then prove that OsJAmyb positively regulates resistance to blast.Our results reveal a molecular module consisting of OsSPL10 and OsJAmyb that positively regulates blast resistance.

Research Progress and Prospects of Total Factor Productivity in the Construction Industry

The high-quality development of the construction industry fundamentally stems from the significant improvement of total factor productivity.Therefore,it is of crucial significance for promoting the development of the construction industry to a higher level by scientifically and accurately measuring the total factor productivity of the construction industry and deeply analyzing the influencing factors behind it.Based on a comprehensive consideration of research methods and influencing factors,this paper systematically reviews the existing relevant literature on total factor productivity in the construction industry,aiming to reveal the current research development trend in this field and point out potential problems.This effort aims to provide a solid theoretical foundation and valuable reference for further in-depth research,and jointly promote the continuous progress and development of total factor productivity research in the construction industry.

Prevalence and risk factors of diabetes mellitus among elderly patients in the Lugu community

BACKGROUND Age is a significant risk factor of diabetes mellitus(DM).With the develop of population aging,the incidence of DM remains increasing.Understanding the epidemiology of DM among elderly individuals in a certain area contributes to the DM interventions for the local elderly individuals with high risk of DM.AIM To explore the prevalence of DM among elderly individuals in the Lugu community and analyze the related risk factors to provide a valid scientific basis for the health management of elderly individuals.METHODS A total of 4816 elderly people who came to the community for physical examination were retrospectively analyzed.The prevalence of DM among the elderly was calculated.The individuals were divided into a DM group and a non-DM group according to the diagnosis of DM to compare the differences in diastolic blood pressure(DBP)and systolic blood pressure(SBP),fasting blood glucose,body mass index(BMI),waist-to-hip ratio(WHR)and incidence of hypertension(HT),coronary heart disease(CHD),and chronic kidney disease(CKD).RESULTS DM was diagnosed in 32.70%of the 4816 elderly people.The BMI of the DM group(25.16±3.35)was greater than that of the non-DM group(24.61±3.78).The WHR was 0.90±0.04 in the non-DM group and 0.90±0.03 in the DM group,with no significant difference.The left SBP and SBP in the DM group were 137.9 mmHg±11.92 mmHg and 69.95 mmHg±7.75 mmHg,respectively,while they were 126.6 mmHg±12.44 mmHg and 71.15 mmHg±12.55 mmHg,respectively,in the non-DM group.These findings indicate higher SBP and lower DBP in DM patients than in those without DM.In the DM group,1274 patients were diagnosed with HT,accounting for 80.89%.Among the 3241 non-DM patients,1743(53.78%)were hypertensive and 1498(46.22%)were nonhypertensive.The DM group had more cases of HT than did the non-DM group.There were more patients with CHD or CKD in the DM group than in the non-DM group.There were more patients who drank alcohol more frequently(≥3 times)in the DM group than in the non-DM group.CONCLUSION Older adults in the Lugu community are at a greater risk of DM.In elderly individuals,DM is closely related to high BMI and HT,CHD,and CKD.Physical examinations should be actively carried out for elderly people to determine their BMI,SBP,DBP,and other signs,and sufficient attention should be given to abnormalities in the above signs before further diagnosis.

Analysis of the influencing factors and clinical related characteristics of pulmonary tuberculosis in patients with type 2 diabetes mellitus

BACKGROUND In China,the prevalence of type 2 diabetes mellitus(T2DM)among diabetic patients is estimated to be between 90%-95%.Additionally,China is among the 22 countries burdened by a high number of tuberculosis cases,with approximately 4.5 million individuals affected by active tuberculosis.Notably,T2DM poses a significant risk factor for the development of tuberculosis,as evidenced by the increased incidence of T2DM coexisting with pulmonary tuberculosis(T2DMPTB),which has risen from 19.3%to 24.1%.It is evident that these two diseases are intricately interconnected and mutually reinforcing in nature.AIM To elucidate the clinical features of individuals diagnosed with both T2DM and tuberculosis(T2DM-PTB),as well as to investigate the potential risk factors associated with active tuberculosis in patients with T2DM.METHODS T2DM-PTB patients who visited our hospital between January 2020 and January 2023 were selected as the observation group,Simple DM patients presenting to our hospital in the same period were the control group,Controls and case groups were matched 1:2 according to the principle of the same sex,age difference(±3)years and disease duration difference(±5)years,patients were investigated for general demographic characteristics,diabetes-related characteristics,body immune status,lifestyle and behavioral habits,univariate and multivariate analysis of the data using conditional logistic regression,calculate the odds ratio(OR)values and 95%CI of OR values.RESULTS A total of 315 study subjects were included in this study,including 105 subjects in the observation group and 210 subjects in the control group.Comparison of the results of both anthropometric and biochemical measures showed that the constitution index,systolic blood pressure,diastolic blood pressure and lymphocyte count were significantly lower in the case group,while fasting blood glucose and high-density lipoprotein cholesterol levels were significantly higher than those in the control group.The results of univariate analysis showed that poor glucose control,hypoproteinemia,lymphopenia,TB contact history,high infection,smoking and alcohol consumption were positively associated with PTB in T2DM patients;married,history of hypertension,treatment of oral hypoglycemic drugs plus insulin,overweight,obesity and regular exercise were negatively associated with PTB in T2DM patients.Results of multivariate stepwise regression analysis found lymphopenia(OR=17.75,95%CI:3.40-92.74),smoking(OR=12.25,95%CI:2.53-59.37),history of TB contact(OR=6.56,95%CI:1.23-35.03)and poor glycemic control(OR=3.37,95%CI:1.11-10.25)was associated with an increased risk of developing PTB in patients with T2DM,While being overweight(OR=0.23,95%CI:0.08-0.72)and obesity(OR=0.11,95%CI:0.02-0.72)was associated with a reduced risk of developing PTB in patients with T2DM.CONCLUSION T2DM-PTB patients are prone to worse glycemic control,higher infection frequency,and a higher proportion of people smoking,drinking alcohol,and lack of exercise.Lymphopenia,smoking,history of TB exposure,poor glycemic control were independent risk factors for T2DM-PTB,and overweight and obesity were associated with reduced risk of concurrent PTB in patients with T2DM.

Spatiotemporal deformation characteristics of Outang landslide and identification of triggering factors using data mining

Since the impoundment of Three Gorges Reservoir(TGR)in 2003,numerous slopes have experienced noticeable movement or destabilization owing to reservoir level changes and seasonal rainfall.One case is the Outang landslide,a large-scale and active landslide,on the south bank of the Yangtze River.The latest monitoring data and site investigations available are analyzed to establish spatial and temporal landslide deformation characteristics.Data mining technology,including the two-step clustering and Apriori algorithm,is then used to identify the dominant triggers of landslide movement.In the data mining process,the two-step clustering method clusters the candidate triggers and displacement rate into several groups,and the Apriori algorithm generates correlation criteria for the cause-and-effect.The analysis considers multiple locations of the landslide and incorporates two types of time scales:longterm deformation on a monthly basis and short-term deformation on a daily basis.This analysis shows that the deformations of the Outang landslide are driven by both rainfall and reservoir water while its deformation varies spatiotemporally mainly due to the difference in local responses to hydrological factors.The data mining results reveal different dominant triggering factors depending on the monitoring frequency:the monthly and bi-monthly cumulative rainfall control the monthly deformation,and the 10-d cumulative rainfall and the 5-d cumulative drop of water level in the reservoir dominate the daily deformation of the landslide.It is concluded that the spatiotemporal deformation pattern and data mining rules associated with precipitation and reservoir water level have the potential to be broadly implemented for improving landslide prevention and control in the dam reservoirs and other landslideprone areas.

Spatial-temporal differentiation and influencing factors of rural settlements in mountainous areas: an example of Liangshan Yi Autonomous Prefecture, Southwestern China

Rural settlement is the basic spatial unit for compact communities in rural area. Scientific exploration of spatial-temporal differentiation and its influencing factors is the premise of spatial layout rationalization. Based on land use data of Liangshan Yi Autonomous Prefecture(hereinafter referred to as Liangshan Prefecture) in Sichuan Province, China from 1980 to 2020, compactness index, fractal dimension, imbalance index, location entropy and the optimal parameters-based geographical detector(OPGD) model are used to analyze the spatial-temporal evolution of the morphological characteristics of rural settlements, and to explore the influence of natural geographical factors, socioeconomic factors, and policy factors on the spatial differentiation of rural settlements. The results show that:(1) From 1980 to 2020, the rural settlements area in Liangshan Prefecture increased by 15.96 km^(2). In space, the rural settlements are generally distributed in a local aggregation, dense in the middle and sparse around the periphery. In 2015, the spatial density and expansion index of rural settlements reached the peak.(2) From 1980 to 2020, the compactness index decreased from 0.7636 to 0.7496, the fractal dimension increased from 1.0283 to 1.0314, and the fragmentation index decreased from 0.1183 to 0.1047. The spatial morphological structure of rural settlements tended to be loose, the shape contour tended to be complex, the degree of fragmentation decreased, and the spatial distribution was significantly imbalanced.(3) The results of OPGD detection in 2015 show that the influence of each factor is slope(0.2371) > traffic accessibility(0.2098) > population(0.1403) > regional GDP(0.1325) > elevation(0.0987) > poverty alleviation(0). The results of OPGD detection in 2020 show that the influence of each factor is slope(0.2339) > traffic accessibility(0.2198) > population(0.1432) > regional GDP(0.1219) > poverty alleviation(0.0992) > elevation(0.093). Natural geographical factors(slope and elevation) are the basic factors affecting the spatial distribution of rural settlements, and rural settlements are widely distributed in the river valley plain and the second half mountain area. Socioeconomic factors(traffic accessibility, population, and regional GDP) have a greater impact on the spatial distribution of rural settlements, which is an important factor affecting the spatial distribution of rural settlements. Policy factors such as poverty alleviation relocation have an indispensable impact on the spatial distribution of rural settlements. The research results can provide decisionmaking basis for the spatial arrangement of rural settlements in Liangshan Prefecture, and optimize the implementation of rural revitalization policies.

Incidence and risk factors of depression in patients with metabolic syndrome

BACKGROUND Many studies have explored the relationship between depression and metabolic syndrome(MetS),especially in older people.China has entered an aging society.However,there are still few studies on the elderly in Chinese communities.AIM To investigate the incidence and risk factors of depression in MetS patients in China's Mainland and to construct a predictive model.METHODS Data from four waves of the China Health and Retirement Longitudinal Study were selected,and middle-aged and elderly patients with MetS(n=2533)were included based on the first wave.According to the center for epidemiological survey-depression scale(CESD),participants with MetS were divided into depression(n=938)and non-depression groups(n=1595),and factors related to depression were screened out.Subsequently,the 2-,4-,and 7-year follow-up data were analyzed,and a prediction model for depression in MetS patients was constructed.RESULTS The prevalence of depression in middle-aged and elderly patients with MetS was 37.02%.The prevalence of depression at the 2-,4-,and 7-year follow-up was 29.55%,34.53%,and 38.15%,respectively.The prediction model,constructed using baseline CESD and Physical Self-Maintenance Scale scores,average sleep duration,number of chronic diseases,age,and weight had a good predictive effect on the risk of depression in MetS patients at the 2-year follow-up(area under the curve=0.775,95%confidence interval:0.750-0.800,P<0.001),with a sensitivity of 68%and a specificity of 74%.CONCLUSION The prevalence of depression in middle-aged and elderly patients with MetS has increased over time.The early identification of and intervention for depressive symptoms requires greater attention in MetS patients.

Adolescent suicide risk factors and the integration of socialemotional skills in school-based prevention programs

Adolescents are considered one of the most vulnerable groups affected by suicide.Rapid changes in adolescents’physical and mental states,as well as in their lives,significantly and undeniably increase the risk of suicide.Psychological,social,family,individual,and environmental factors are important risk factors for suicidal behavior among teenagers and may contribute to suicide risk through various direct,indirect,or combined pathways.Social-emotional learning is considered a powerful intervention measure for addressing the crisis of adolescent suicide.When deliberately cultivated,fostered,and enhanced,selfawareness,self-management,social awareness,interpersonal skills,and responsible decision-making,as the five core competencies of social-emotional learning,can be used to effectively target various risk factors for adolescent suicide and provide necessary mental and interpersonal support.Among numerous suicide intervention methods,school-based interventions based on social-emotional competence have shown great potential in preventing and addressing suicide risk factors in adolescents.The characteristics of school-based interventions based on social-emotional competence,including their appropriateness,necessity,cost-effectiveness,comprehensiveness,and effectiveness,make these interventions an important means of addressing the crisis of adolescent suicide.To further determine the potential of school-based interventions based on social-emotional competence and better address the issue of adolescent suicide,additional financial support should be provided,the combination of socialemotional learning and other suicide prevention programs within schools should be fully leveraged,and cooperation between schools and families,society,and other environments should be maximized.These efforts should be considered future research directions.

Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.

Interplay between microglia and environmental risk factors in Alzheimer's disease

Alzheimer s disease,among the most common neurodegenerative disorders,is chara cterized by progressive cognitive impairment.At present,the Alzheimer’s disease main risk remains genetic ris ks,but major environmental fa ctors are increasingly shown to impact Alzheimer’s disease development and progression.Microglia,the most important brain immune cells,play a central role in Alzheimer’s disease pathogenesis and are considered environmental and lifestyle"sensors."Factors like environmental pollution and modern lifestyles(e.g.,chronic stress,poor dietary habits,sleep,and circadian rhythm disorde rs)can cause neuroinflammato ry responses that lead to cognitive impairment via microglial functioning and phenotypic regulation.However,the specific mechanisms underlying interactions among these facto rs and microglia in Alzheimer’s disease are unclear.Herein,we:discuss the biological effects of air pollution,chronic stress,gut micro biota,sleep patterns,physical exercise,cigarette smoking,and caffeine consumption on microglia;consider how unhealthy lifestyle factors influence individual susceptibility to Alzheimer’s disease;and present the neuroprotective effects of a healthy lifestyle.Toward intervening and controlling these environmental risk fa ctors at an early Alzheimer’s disease stage,understanding the role of microglia in Alzheimer’s disease development,and to rgeting strategies to to rget microglia,co uld be essential to future Alzheimer’s disease treatments.

PRaG 3.0 therapy for human epidermal growth factor receptor 2-positive metastatic pancreatic ductal adenocarcinoma:A case report

BACKGROUND Pancreatic ductal adenocarcinoma(PDAC)is a highly fatal disease with limited effective treatment especially after first-line chemotherapy.The human epidermal growth factor receptor 2(HER-2)immunohistochemistry(IHC)positive is associated with more aggressive clinical behavior and shorter overall survival in PDAC.CASE SUMMARY We present a case of multiple metastatic PDAC with IHC mismatch repair proficient but HER-2 IHC weakly positive at diagnosis that didn’t have tumor regression after first-line nab-paclitaxel plus gemcitabine and PD-1 inhibitor treatment.A novel combination therapy PRaG 3.0 of RC48(HER2-antibody-drug conjugate),radio-therapy,PD-1 inhibitor,granulocyte-macrophage colony-stimulating factor and interleukin-2 was then applied as second-line therapy and the patient had confirmed good partial response with progress-free-survival of 6.5 months and overall survival of 14.2 month.She had not developed any grade 2 or above treatment-related adverse events at any point.Percentage of peripheral CD8^(+) Temra and CD4^(+) Temra were increased during first two activation cycles of PRaG 3.0 treatment containing radiotherapy but deceased to the baseline during the maintenance cycles containing no radiotherapy.CONCLUSION PRaG 3.0 might be a novel strategy for HER2-positive metastatic PDAC patients who failed from previous first-line approach and even PD-1 immunotherapy but needs more data in prospective trials.

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.

Predictive factors and model validation of post-colon polyp surgery Helicobacter pylori infection

BACKGROUND Recently,research has linked Helicobacter pylori(H.pylori)stomach infection to colonic inflammation,mediated by toxin production,potentially impacting colorectal cancer occurrence.AIM To investigate the risk factors for post-colon polyp surgery,H.pylori infection,and its correlation with pathologic type.METHODS Eighty patients who underwent colon polypectomy in our hospital between January 2019 and January 2023 were retrospectively chosen.They were then randomly split into modeling(n=56)and model validation(n=24)sets using R.The modeling cohort was divided into an H.pylori-infected group(n=37)and an H.pylori-uninfected group(n=19).Binary logistic regression analysis was used to analyze the factors influencing the occurrence of H.pylori infection after colon polyp surgery.A roadmap prediction model was established and validated.Finally,the correlation between the different pathological types of colon polyps and the occurrence of H.pylori infection was analyzed after colon polyp surgery.RESULTS Univariate results showed that age,body mass index(BMI),literacy,alcohol consumption,polyp pathology type,high-risk adenomas,and heavy diet were all influential factors in the development of H.pylori infection after intestinal polypectomy.Binary multifactorial logistic regression analysis showed that age,BMI,and type of polyp pathology were independent predictors of the occurrence of H.pylori infection after intestinal polypectomy.The area under the receiver operating characteristic curve was 0.969[95%confidence interval(95%CI):0.928–1.000]and 0.898(95%CI:0.773–1.000)in the modeling and validation sets,respectively.The slope of the calibration curve of the graph was close to 1,and the goodness-of-fit test was P>0.05 in the two sets.The decision analysis curve showed a high rate of return in both sets.The results of the correlation analysis between different pathological types and the occurrence of H.pylori infection after colon polyp surgery showed that hyperplastic polyps,inflammatory polyps,and the occurrence of H.pylori infection were not significantly correlated.In contrast,adenomatous polyps showed a significant positive correlation with the occurrence of H.pylori infection.CONCLUSION Age,BMI,and polyps of the adenomatous type were independent predictors of H.pylori infection after intestinal polypectomy.Moreover,the further constructed column-line graph prediction model of H.pylori infection after intestinal polypectomy showed good predictive ability.

Klebsiella pneumoniae infections after liver transplantation:Drug resistance and distribution of pathogens,risk factors,and influence on outcomes

BACKGROUND Liver transplantation(LT)is the only curative treatment for end-stage liver disease.However,LT recipients are susceptible to infection,which is the leading cause of early mortality after LT.Klebsiella pneumoniae infections(KPIs)in the bloodstream are common in LT recipients.We hypothesized that KPIs and carbapenemresistant Klebsiella pneumoniae(CRKP)infections may affect the outcomes of LT recipients.AIM To assess KPI incidence,timing,distribution,drug resistance,and risk factors following LT and its association with outcomes.METHODS This retrospective study included 406 patients undergoing LT at The Third Xiangya Hospital of Central South University,a tertiary hospital,from January 2015 to January 2023.We investigated the risk factors for KPIs and assessed the impact of KPIs and CRKP infections on the prognosis of LT recipients using logistic regression analysis.RESULTS KPI incidence was 7.9%(n=32),with lung/thoracic cavity the most frequent site of infection;the median time from LT to KPI onset was 7.5 d.Of 44 Klebsiella pneumoniae isolates,43(97.7%)and 34(77.3%)were susceptible to polymyxin B or ceftazidime/avibactam and tigecycline,respectively;>70%were resistant to piperacillin/tazobactam,ceftazidime,cefepime,aztreonam,meropenem,and levofloxacin.Female sex[odds ratio(OR)=2.827,95%confidence interval(CI):1.256-6.364;P=0.012],pre-LT diabetes(OR=2.794,95%CI:1.070-7.294;P=0.036),day 1 post-LT alanine aminotransferase(ALT)levels≥1500 U/L(OR=3.645,95%CI:1.671-7.950;P=0.001),and post-LT urethral catheter duration over 4 d(OR=2.266,95%CI:1.016-5.054;P=0.046)were risk factors for KPI.CRKP infections,but not KPIs,were risk factors for 6-month all-cause mortality post-LT.CONCLUSION KPIs occur frequently and rapidly after LT.Risk factors include female sex,pre-LT diabetes,increased post-LT ALT levels,and urethral catheter duration.CRKP infections,and not KPIs,affect mortality.

Analysis of risk factors leading to anxiety and depression in patients with prostate cancer after castration and the construction of a risk prediction model

BACKGROUND Cancer patients often suffer from severe stress reactions psychologically,such as anxiety and depression.Prostate cancer(PC)is one of the common cancer types,with most patients diagnosed at advanced stages that cannot be treated by radical surgery and which are accompanied by complications such as bodily pain and bone metastasis.Therefore,attention should be given to the mental health status of PC patients as well as physical adverse events in the course of clinical treatment.AIM To analyze the risk factors leading to anxiety and depression in PC patients after castration and build a risk prediction model.METHODS A retrospective analysis was performed on the data of 120 PC cases treated in Xi'an People's Hospital between January 2019 and January 2022.The patient cohort was divided into a training group(n=84)and a validation group(n=36)at a ratio of 7:3.The patients’anxiety symptoms and depression levels were assessed 2 wk after surgery with the Self-Rating Anxiety Scale(SAS)and the Selfrating Depression Scale(SDS),respectively.Logistic regression was used to analyze the risk factors affecting negative mood,and a risk prediction model was constructed.RESULTS In the training group,35 patients and 37 patients had an SAS score and an SDS score greater than or equal to 50,respectively.Based on the scores,we further subclassified patients into two groups:a bad mood group(n=35)and an emotional stability group(n=49).Multivariate logistic regression analysis showed that marital status,castration scheme,and postoperative Visual Analogue Scale(VAS)score were independent risk factors affecting a patient's bad mood(P<0.05).In the training and validation groups,patients with adverse emotions exhibited significantly higher risk scores than emotionally stable patients(P<0.0001).The area under the curve(AUC)of the risk prediction model for predicting bad mood in the training group was 0.743,the specificity was 70.96%,and the sensitivity was 66.03%,while in the validation group,the AUC,specificity,and sensitivity were 0.755,66.67%,and 76.19%,respectively.The Hosmer-Lemeshow test showed aχ^(2) of 4.2856,a P value of 0.830,and a C-index of 0.773(0.692-0.854).The calibration curve revealed that the predicted curve was basically consistent with the actual curve,and the calibration curve showed that the prediction model had good discrimination and accuracy.Decision curve analysis showed that the model had a high net profit.CONCLUSION In PC patients,marital status,castration scheme,and postoperative pain(VAS)score are important factors affecting postoperative anxiety and depression.The logistic regression model can be used to successfully predict the risk of adverse psychological emotions.