Identification of cell surface markers for acute myeloid leukemia prognosis based on multi-model analysis

Given the extremely high inter-patient heterogeneity of acute myeloid leukemia(AML),the identification of biomarkers for prognostic assessment and therapeutic guidance is critical.Cell surface markers(CSMs)have been shown to play an important role in AML leukemogenesis and progression.In the current study,we evaluated the prognostic potential of all human CSMs in 130 AML patients from The Cancer Genome Atlas(TCGA)based on differential gene expression analysis and univariable Cox proportional hazards regression analysis.By using multi-model analysis,including Adaptive LASSO regression,LASSO regression,and Elastic Net,we constructed a 9-CSMs prognostic model for risk stratification of the AML patients.The predictive value of the 9-CSMs risk score was further validated at the transcriptome and proteome levels.Multivariable Cox regression analysis showed that the risk score was an independent prognostic factor for the AML patients.The AML patients with high 9-CSMs risk scores had a shorter overall and event-free survival time than those with low scores.Notably,single-cell RNA-sequencing analysis indicated that patients with high 9-CSMs risk scores exhibited chemotherapy resistance.Furthermore,PI3K inhibitors were identified as potential treatments for these high-risk patients.In conclusion,we constructed a 9-CSMs prognostic model that served as an independent prognostic factor for the survival of AML patients and held the potential for guiding drug therapy.

Preoperative blood markers and intra-abdominal infection after colorectal cancer resection

BACKGROUND Colorectal cancer(CRC)has one of the highest morbidity and mortality rates among digestive tract tumors.Intra-abdominal infection(IAI)is a common postoperative complication that affects the clinical outcomes of patients with CRC and hinders their rehabilitation process.However,the factors influencing abdominal infection after CRC surgery remain unclear;further,prediction models are rarely used to analyze preoperative laboratory indicators and postoperative complications.AIM To explore the predictive value of preoperative blood markers for IAI after radical resection of CRC.METHODS The data of 80 patients who underwent radical resection of CRC in the Anorectal Surgery Department of Suzhou Hospital affiliated with Anhui Medical University were analyzed.These patients were categorized into IAI(n=15)and non-IAI groups(n=65)based on whether IAI occurred.Influencing factors were compared;general data and laboratory indices of both groups were identified.The relationship between the indicators was assessed.Further,a nomogram prediction model was developed and evaluated;its utility and clinical applic-ability were assessed.RESULTS The risk factors for IAI after radical resection of CRC were neutrophil-lymphocyte ratio(NLR),platelet-lymphocyte ratio(PLR),systemic immune-inflammation index(SII),and carcinoembryonic antigen(CEA)levels.NLR was correlated with PLR and SII(r=0.604,0.925,and 0.305,respectively),while PLR was correlated with SII(r=0.787).The nomogram prediction model demonstrated an area under the curve of 0.968[95%confidence interval(CI):0.948-0.988]in the training set(n=60)and 0.926(95%CI:0.906-0.980)in the validation set(n=20).The average absolute errors of the calibration curves for the training and validation sets were 0.032 and 0.048,respectively,indicating a good model fit.The decision curve analysis curves demonstrated high net income above the 5%threshold,indicating the clinical practicality of the model.CONCLUSION The nomogram model constructed using NLR,PLR,SII,and CEA levels had good accuracy and reliability in predicting IAI after radical resection of CRC,potentially aiding clinical treatment decision-making.

Efficacy of a Diabetes Specific Nutrition Supplement on Glycemic, Anthropometric, Dietary and Gut Health Markers in Adults with Type 2 Diabetes: An RCT

With increasing incidence of diabetes, use of diabetes specific nutrition supplements (DSNS) is common for better management of the disease. To study effect of 12-week DSNS supplementation on glycemic markers, anthropometry, lipid profile, SCFAs, and gut microbiome in individuals with diabetes. Markers studied were glycemic [Fasting Blood Glucose (FBG), Post Prandial Glucose (PPG), HbA1c, Incremental Area under curve (iAUC), Mean Amplitude of Glycemic Excursions (MAGE), Time in/above Range (TIR/TAR)], anthropometry [weight, Body Mass Index (BMI), waist circumference (WC)], lipid profile, diet and gut health [plasma short chain fatty acids (SCFAs)]. N = 210 adults were randomized to receive either DSNS with standard care (DSNS + SC;n = 105) or standard care alone (SC alone;n = 105). After 12 weeks, significant differences between DSNS + SC versus SC alone was observed in FBG [−3 ± 6 vs 14 ± 6 mg/dl;p = 0.03], PPG [−35 ± 9 vs −3 ± 9 mg/dl;p = 0.01], weight [−0.6 ± 0.1 vs 0.2 ± 0.1 kg;p = 0.0001], BMI [−0.3 ± 0.1 vs 0.1 ± 0.1 kg/m2;p = 0.0001] and WC [−0.3 ± 0.2 vs 0.2 ± 0.2 cm;p = 0.01]. HbA1C and low-density lipoprotein (LDL) were significantly reduced in DSNS + SC [−0.2 ± 0.9;p = 0.04 and −5 mg/dl;p = 0.03] respectively with no change in control. Continuous Glucose Monitoring (CGM) reported significant differences between DSNS + SC versus SC alone for mean glucose [−12 ± 65 vs 28 ± 93 mg/dl;p < 0.01], TAR 180 [−9 ± 42 vs 7 ± 45 mg/dl;p = 0.04], TAR 250 [−3 ± 27 vs 9 ± 38 mg/dl;p = 0.05], iAUC [−192 (1.1) vs −48 (1.1) mg/dl;p = 0.03]. MAGE was significantly reduced for both DSNS + SC (−19 ± 67;p < 0.001) and SC alone (−8 ± 70;p = 0.04), with reduction being more pronounced for DSNS + SC. DSNS + SC reported a decrease in carbohydrate energy % [−9.4 (−11.3, −7.6) %;p < 0.0001] and amount [−47.4 (−67.1, −27.7) g;p < 0.0001], increased dietary fiber [9.5 (7.2, 11.8) g;p < 0.0001] and protein energy % [0.9 (0.5, 1.3) %;p < 0.0001] versus SC alone. DSNS + SC reported significant increases versus SC alone in total (0.3 ng/ml;p = 0.03) and individual plasma SCFAs. The consumption of DSNS significantly improves the glycemic, anthropometric, dietary, and gut health markers in diabetes.

Utilizing resequencing big data to facilitate Brassica vegetable breeding:tracing introgression pedigree and developing highly specific markers for clubroot resistance

Clubroot caused by Plasmodiophora brassicae is a devastating disease of Cruciferous crops.Developing cultivars with clubroot resistance(CR)is the most effective control measure.For the two major Brassica vegetable species B.rapa and B.oleracea,several commercial cultivars with unclear CR pedigrees have been intensively used as CR donors in breeding.However,the continuous occurrence of CR-breaking makes the CR pedigree underlying these cultivars one of the breeders'most urgent concerns.The complex intraspecific diversity of these two major Brassica vegetables has also limited the applicability of CR markers in different breeding programs.Here we first traced the pedigree underlying two kinds of CR that have been widely applied in breeding by linkage and introgression analyses based on public resequencing data.In B.rapa,a major locus CRzi8 underlying the CR of the commercial CR donor‘DegaoCR117’was identified.CRzi8 was further shown to have been introgressed from turnip(B.rapa ssp.rapifera)and that it carried a potential functional allele of Crr1a.The turnip introgression carried CRb^(c),sharing the same coding sequence with the CRb that was also identified from chromosome C07 of B.oleracea CR cultivars with different morphotypes.Within natural populations,variation analysis of linkage intervals of CRzi8,PbBa8.1,CRb,and CRb^(c)yielded easily resolved InDel markers(>20 bp)for these fundamental CR genes.The specificity of these markers was tested in diverse cultivars panels,and each exhibited high reliability in breeding.Our research demonstrates the value of the practice of applying resequencing big data to solve urgent concerns in breeding programs.

Inflammatory and nutritional markers in colorectal cancer: Implications for prognosis and treatment

The prognosis of colorectal cancer(CRC)patients with peritoneal metastasis remains poor despite advancements in detection and treatment.Preoperative inflammatory and nutritional markers have emerged as significant predictors of prognosis in CRC,potentially guiding treatment decisions and improving patient outcomes.This editorial explores the prognostic value of markers such as the neutrophil-to-lymphocyte ratio,hemoglobin,and serum albumin levels.By integrating these markers into prognostic models,clinicians can better stratify patients,personalize treatment strategies,and ultimately enhance clinical outcomes.This review highlights the importance of these markers in providing a comprehensive assessment of patient condition and underscores the need for further research to validate their clinical utility and uncover underlying mecha-nisms.

Hyperhomocysteinemia and Associated Biological Markers in a Congolese Population of Type 2 Diabetes Mellitus in Brazzaville

The search for new biomarkers predictive of type 2 diabetes currently constitutes a research avenue in Bioclinical. Total homocysteine remains a preferred target due to its involvement in the occurrence of degenerative complications in type 2 diabetics. The aim of this work was to study hyperhomocysteinemia and other biochemical markers associated with T2D in the Congolese population. This was an analytical case-control study carried out between October 2022 and October 2023. The study population consisted of 150 subjects including 100 T2D patients and 50 control subjects. The main clinical data were collected on a pre-established form. Homocysteine determination was carried out by the sandwich ELISA method. The other biochemical markers were measured by colorimetric enzymatic methods. Hyperhomocysteinemia was present in 27.3% (41/150) of the entire study population. Type 2 diabetics had a frequency of hyperhomocysteinemia of 36% (36/100) and control 10% (5/50) (p = 0.001). The mean hyperhomocysteinemia concentration was 31.9 μmol/l with extremes ranging from 18 to 103 μmol/l. Means of biological markers between diabetics and controls showed a statistically significant difference (p = 0.01). The risk factors associated with this HHcy were: sex (OR = 3.5), age (OR = 9.4), sedentary lifestyle (OR = 3.4) and glycosylated hemoglobin (OR = 12) with a p-value <0.05 respectively. Our results suggest that hyperhomocysteinemia can be considered as a predictive biomarker in the bioclinic of Congolese type 2 diabetic patients.

Evaluating combined bevacizumab and XELOX in advanced colorectal cancer: Serum markers carcinoembryonic antigen, carbohydrate antigen 125, carbohydrate antigen 199 analysis

BACKGROUND Colorectal cancer ranks third and second among common and fatal cancers.The treatment of metastatic colorectal cancer(mCRC)is generally based on XELOX in clinical practice,which includes capecitabine(CAP)and oxaliplatin.Serum tumor markers carcinoembryonic antigen(CEA),carbohydrate antigen(CA)125 and CA199 are prognostic factors for various tumors.AIM To investigate evaluating combined bevacizumab(BEV)and XELOX in advanced colorectal cancer:Serum markers CEA,CA125,CA199 analysis.METHODS In this retrospective study,a total of 94 elderly patients diagnosed with mCRC were recruited and subsequently categorized into two groups based on the distinct treatment modalities they received.The control group was treated with XELOX plus CAP(n=47),while the observation group was treated with XELOX plus CAP and BEV(n=47).Several indexes were assessed in both groups,including disease control rate(DCR),incidence of adverse effects,serum marker levels(CEA,CA125,and CA19)and progression-free survival(PFS).RESULTS After 9 wk of treatment,the serum levels of CEA,CA199 and CA125 in the observation group were significantly lower than those in the control group(P<0.05).Moreover,the PFS of the observation group(9.12±0.90 mo)was significantly longer than that of the control group(6.49±0.64 mo).Meanwhile,there was no statistically significant difference in the incidence of adverse reactions and DCR between the two groups during maintenance therapy(P>0.05).CONCLUSION On the basis of XELOX treatment,the combination of BEV and CAP can reduce serum tumor marker levels and prolong PFS in patients with mCRC.

Karyotype establishment and development of specific molecular markers of Aegilops geniculata Roth based on SLAF-seq

The constant evolution of pathogens poses a threat to wheat resistance against diseases,endangering food security.Developing resistant wheat varieties is the most practical approach for circumventing this problem.As a close relative of wheat,Aegilops geniculata,particularly accession SY159,has evolved numerous beneficial traits that could be applied to improve wheat.In this study,we established the karyotype of SY159 by fluorescence in situ hybridization(FISH)using the oligonucleotide probes Oligo-pTa535 and Oligo-pSc119.2 and a complete set of wheat–Ae.geniculata accession TA2899 addition lines as a reference.Using specific-locus amplified fragment sequencing(SLAF-seq)technology,400 specific markers were established for detecting the SY159 chromosomes with efficiencies reaching 81.5%.The SY159-specific markers were used to classify the different homologous groups of SY159 against the wheat-Ae.geniculata addition lines.We used these specific markers on the 7Mg chromosome after classification,and successfully confirmed their suitability for studying the different chromosomes of SY159.This study provides a foundation for accelerating the application of SY159 in genetic breeding programs designed to improve wheat.

Identification of new cotton fiber-quality QTL by multiple genomic analyses and development of markers for genomic breeding

Cotton fiber is one of the main raw materials for the textile industry.In recent years,many cotton fiber quality QTL have been identified,but few were applied in breeding.In this study,a genome wide association study(GWAS)of fiber-quality traits in 265 upland cotton breeding intermediate lines(GhBreeding),combined with genome-wide selective sweep analysis(GSSA)and genomic selection(GS),revealed 25 QTL.Most of these QTL were ignored by only using GWAS.The CRISPR/Cas9 mutants of GhMYB_D13 had shorter fiber,which indicates the credibility of QTL to a certain extent.Then these QTL were verified in other cotton natural populations,5 stable QTL were found having broad potential for application in breeding.Additionally,among these 5 stable QTL,superior genotypes of 4 showed an enrichment in most improved new varieties widely cultivated currently.These findings provide insights for how to identify more QTL through combined multiple genomic analysis to apply in breeding.

Machine Learning for Selecting Important Clinical Markers of Imaging Subgroups of Cerebral Small Vessel DiseaseBased on a Common Data Model

Differences in the imaging subgroups of cerebral small vessel disease(CSVD)need to be further explored.First,we use propensity score matching to obtain balanced datasets.Then random forest(RF)is adopted to classify the subgroups compared with support vector machine(SVM)and extreme gradient boosting(XGBoost),and to select the features.The top 10 important features are included in the stepwise logistic regression,and the odds ratio(OR)and 95%confidence interval(CI)are obtained.There are 41290 adult inpatient records diagnosed with CSVD.Accuracy and area under curve(AUC)of RF are close to 0.7,which performs best in classification compared to SVM and XGBoost.OR and 95%CI of hematocrit for white matter lesions(WMLs),lacunes,microbleeds,atrophy,and enlarged perivascular space(EPVS)are 0.9875(0.9857−0.9893),0.9728(0.9705−0.9752),0.9782(0.9740−0.9824),1.0093(1.0081−1.0106),and 0.9716(0.9597−0.9832).OR and 95%CI of red cell distribution width for WMLs,lacunes,atrophy,and EPVS are 0.9600(0.9538−0.9662),0.9630(0.9559−0.9702),1.0751(1.0686−1.0817),and 0.9304(0.8864−0.9755).OR and 95%CI of platelet distribution width for WMLs,lacunes,and microbleeds are 1.1796(1.1636−1.1958),1.1663(1.1476−1.1853),and 1.0416(1.0152−1.0687).This study proposes a new analytical framework to select important clinical markers for CSVD with machine learning based on a common data model,which has low cost,fast speed,large sample size,and continuous data sources.

Genome-Wide Analysis for Yield-Related Agronomic and Biochemical Traits of Chinese and Bangladeshi Grass Pea Genotypes Using SSR Markers

Grass pea(Lathyrus sativus L.)is an imperative food crop cultured in dryland agricultural ecology.It is a vital source of dietary protein to millions of populaces living in low-income countries in South-East Asia and Africa.This study highlights the improvement of genomic properties and their application in marker-trait relationships for 17 yield-related characters in 400 grass pea genotypes from China and Bangladesh.These characters were assessed via 56 polymorphic markers using general linear model(GLM)(P+G+Q)and mixed linear model(MLM)(P+G+Q+K)in the tassel software based on the linkage disequilibrium and population structure analysis.Population structure analysis showed two major groups and one admixed group in the populace.Statistically significant loci pairs of linkage disequilibrium(LD)mean value(D′)was 0.479.A total of 99 and 61 marker-trait associations in GLM and MLM models allied to the 17 traits were accepted at a 5%level of significance.Among these markers,21 markers were associated with more than one trait;12 marker-trait associations passed the Bonferroni correction threshold.Both models found six markers C41936,C39067,C34100,C47146,C47638,and C43047 significantly associated with days to maturity,flower color,plant height,and seed per pod were detected in the Hebei and Liaoyang location(p≤0.01),and the interpretation rate(R^(2)value)11.2%to 43.6%.Conferring to the consequences,the association analysis methodology may operative system for quantitative,qualitative,and biochemical traits related to gene position mapping and support breeders in improving novel approaches for advancing the grass pea quality.

New markers of fibrosis in hepatitis C:A step towards the Holy Grail?

In the present issue of the World Journal of Hepatology,Ferrassi et al examine the problem of liver fibrosis staging in chronic hepatitis C.They identify novel biomarkers in an effort to predict accurate fibrosis staging with the aid of the metabolome of Hepatitis C patients.Overall I think Ferrassi et al took a different approach in identifying fibrosis biomarkers,by looking at the patients’metabolome.Their biomarkers clearly separate patients from controls.They can also separate out,patients with minimal fibrosis(F0-F1 stage)and patients with cirrhosis(F4 stage).Obviously,if these biomarkers were to be widely used,tests for all the important metabolites would need to be readily available for use in hospitals or outpatient setting and that may prove difficult and above all,costly.Nevertheless,this step could eventually lead to a metabolomic approach for novel biomarkers of Fibrosis.Obviously,it would need to be validated,but could represent a step towards the Holy Grail of Hepatology.

Effects of exercise training on glucose metabolism indicators and inflammatory markers in obese children and adolescents:A metaanalysis

BACKGROUND Obesity in children and adolescents is a serious problem,and the efficacy of exercise therapy for these patients is controversial.AIM To assess the efficacy of exercise training on overweight and obese children based on glucose metabolism indicators and inflammatory markers.METHODS The PubMed,Web of Science,and Embase databases were searched for randomized controlled trials related to exercise training and obese children until October 2023.The meta-analysis was conducted using RevMan 5.3 software to evaluate the efficacy of exercise therapy on glucose metabolism indicators and inflammatory markers in obese children.RESULTS In total,1010 patients from 28 studies were included.Exercise therapy reduced the levels of fasting blood glucose(FBG)[standardized mean difference(SMD):-0.78;95%confidence interval(CI):-1.24 to-0.32,P=0.0008],fasting insulin(FINS)(SMD:-1.55;95%CI:-2.12 to-0.98,P<0.00001),homeostatic model assessment for insulin resistance(HOMA-IR)(SMD:-1.58;95%CI:-2.20 to-0.97,P<0.00001),interleukin-6(IL-6)(SMD:-1.31;95%CI:-2.07 to-0.55,P=0.0007),C-reactive protein(CRP)(SMD:-0.64;95%CI:-1.21 to-0.08,P=0.03),and leptin(SMD:-3.43;95%CI:-5.82 to-1.05,P=0.005)in overweight and obese children.Exercise training increased adiponectin levels(SMD:1.24;95%CI:0.30 to 2.18,P=0.01)but did not improve tumor necrosis factor-alpha(TNF-α)levels(SMD:-0.80;95%CI:-1.77 to 0.18,P=0.11).CONCLUSION In summary,exercise therapy improves glucose metabolism by reducing levels of FBG,FINS,HOMA-IR,as well as improves inflammatory status by reducing levels of IL-6,CRP,leptin,and increasing levels of adiponectin in overweight and obese children.There was no statistically significant effect between exercise training and levels of TNF-α.Additional long-term trials should be conducted to explore this therapeutic perspective and confirm these results.

Recent progress in hair follicle stem cell markers and their regulatory roles

Hair follicle stem cells(HFSCs)in the bulge are a multipotent adult stem cell population.They can periodically give rise to new HFs and even regenerate the epidermis and sebaceous glands during wound healing.An increasing number of biomarkers have been used to isolate,label,and trace HFSCs in recent years.Considering more detailed data from single-cell transcriptomics technology,we mainly focus on the important HFSC molecular markers and their regulatory roles in this review.

Review of the potential value of serum interleukin levels as prognostic biomarkers of liver failure

Liver failure(LF)is prevalent in China and is characterized by complex path-ogenesis,challenging clinical management,poor prognosis,and rising incidence and mortality rates.The immune status is an important factor affecting LF prognosis.Interleukins(Ils)are a type of cytokine that act and interact with multiple cells,including immune cells.These signaling molecules play important roles in intercellular information transmission,including the regulation of immune cells;mediation of the activation,proliferation,and differentiation of T and B cells;and orchestration of the inflammatory response.To date,many studies have explored the correlation between IL expression and liver disease prognosis,but few studies have evaluated Ils as the prognostic biomarkers of LF.This article reviews the potential use of Ils as the prognostic biomarkers of LF.Particularly,it evaluates the predictive values of IL-21,IL-22,and IL-31,the three often overlooked yet promising prognostic biomarkers,in predicting suscept-ibility to LF.Harnessing biomarkers for early prognostic insights can facilitate tailored treatment strategies and enhance patient survival.Thus,this article focuses on the identification of IL-21,IL-22,and IL-33 as biomarkers in preclinical and clinical studies on LF and reviews their role as biomarkers in the pathogenesis and diagnosis of LF.

Impact of oxaliplatin and trastuzumab combination therapy on tumor markers and T lymphocyte subsets for advanced gastric cancer

BACKGROUND Advanced gastric cancer(AGC)remains a challenging malignancy with poor prognosis.The combination of oxaliplatin and trastuzumab has shown promising results in AGC treatment.This study aimed to investigate the effects of oxaliplatin and trastuzumab combination therapy on serum tumor markers and T lymphocyte subsets in patients with AGC and to explore their potential as predictive biomarkers for treatment response.AIM To investigate the impact of oxaliplatin and trastuzumab combination therapy on serum markers and T cell subsets in patients with AGC.METHODS This prospective study enrolled 60 patients with AGC.All patients received oxaliplatin(130 mg/m^(2),every 3 weeks)and trastuzumab(8 mg/kg loading dose,followed by 6 mg/kg every 3 weeks)for six cycles.Serum carcinoembryonic antigen(CEA),cancer antigen 19-9(CA19-9),and cancer antigen 72-4(CA72-4)were measured before and after treatment.T-lymphocyte subsets,including CD3+,CD4+,CD8+,and CD4+/CD8+ratios,were also evaluated.The clinical response was assessed using the Response Evaluation Criteria in Solid Tumors version 1.1.RESULTS After six cycles of treatment,the CEA,CA19-9,and CA72-4 serum levels significantly decreased compared to baseline levels(P<0.001).The percentages of CD3+and CD4+T lymphocytes increased significantly(P<0.05),whereas the percentage of CD8+T lymphocytes decreased(P<0.05).The CD4+/CD8+ratio also significantly increased after treatment(P<0.05).Patients with a higher decrease in serum tumor markers(≥50%reduction)and a higher increase in CD4+/CD8+ratio(≥1.5-fold)showed better clinical response rates(P<0.05).CONCLUSION Oxaliplatin and trastuzumab combination therapy effectively reduced serum tumor marker levels and modulated T lymphocyte subsets in patients with AGC.Combination therapy not only has a direct antitumor effect,but also enhances the immune response in patients with AGC.Serum tumor markers and T lymphocyte subsets may serve as potential predictive biomarkers for treatment response in patients with AGC receiving combination therapy.

Prognostic value and predictive model of tumor markers in stageⅠtoⅢgastric cancer patients

BACKGROUND Preoperative serum tumor markers have been widely used in the diagnosis and treatment of gastric cancer patients.However,few studies have evaluated the prognosis of gastric cancer patients by establishing statistical models with multiple serum tumor indicators.AIM To explore the prognostic value and predictive model of tumor markers in stage I and III gastric cancer patients.METHODS From October 2018 to April 2020,a total of 1236 patients with stage I to III gastric cancer after surgery were included in our study.The relationship between serum tumor markers and clinical and pathological data were analyzed.We established a statistical model to predict the prognosis of gastric cancer based on the results of COX regression analysis.Overall survival(OS)was also compared across different stages of gastric cancer.RESULTS The deadline for follow-up was May 31,2023.A total of 1236 patients were included in our study.Univariate analysis found that age,clinical stage,T and N stage,tumor location,differentiation,Borrmann type,size,and four serum tumor markers were prognostic factors of OS(P<0.05).It was shown that clinical stage,tumor size,alpha foetoprotein,carcinoembryonic antigen,CA125 and CA19-9(P<0.05)were independent prognostic factors for OS.According to the scoring results obtained from the statistical model,we found that patients with high scores had poorer survival time(P<0.05).Furthermore,in stage I patients,the 3-year OS for scores 0-3 ranged from 96.85%,95%,85%,and 80%.In stage II patients,the 3-year OS for scores 0-4 were 88.6%,76.5%,90.5%,65.5%and 60%.For stage III patients,3-year OS for scores 0-6 were 70.9%,68.3%,64.1%,50.9%,38.4%,18.5%and 5.2%.We also analyzed the mean survival of patients with different scores.For stage I patients,the mean OS was 55.980 months.In stage II,the mean OS was 51.550 months.The mean OS for stage III was 39.422 months.CONCLUSION Our statistical model can effectively predict the prognosis of gastric cancer patients.

Laparoscopic vs open surgery for gastric cancer: Assessing time, recovery, complications, and markers

BACKGROUND Gastric cancer(GC)is one of the most common cancers worldwide.Morbidity and mortality have increased in recent years,making it an urgent issue to address.La-paroscopic radical surgery(LRS)is a crucial method for treating patients with GC;However,its influence on tumor markers is still under investigation.The data of 194 patients treated at Chongqing University Cancer Hospital bet-ween January 2018 and January 2019 were retrospectively analyzed.Patients who underwent traditional open surgery and LRS were assigned to the control(n=90)and observation groups(n=104),respectively.Independent sample t-tests andχ2 tests were used to compare the two groups based on clinical efficacy,changes in tumor marker levels after treatment,clinical data,and the incidence of posto-perative complications.To investigate the association between tumor marker levels and clinical efficacy in patients with GC,three-year recurrence rates in the two groups were compared.RESULTS Patients in the observation group had a shorter duration of operation,less in-traoperative blood loss,an earlier postoperative eating time,and a shorter hospital stay than those in the control group(P<0.05).No significant difference was observed between the two groups regarding the number of lymph node dissections(P>0.05).After treatment,the overall response rate in the control group was significantly lower than that in the observation group(P=0.001).Furthermore,after treatment,the levels of carbohydrate antigen 19-9,cancer antigen 72-4,carcinoembryonic antigen,and cancer antigen 125 decreased significantly.The observation group also exhibited a significantly lower incidence rate of postoperative complications compared to the control group(P<0.001).Additionally,the two groups did not significantly differ in terms of three-year survival and recurrence rates(P>0.05).CONCLUSION LRS effectively treats early gastric cancer by reducing intraoperative bleeding,length of hospital stays,and postoperative complications.It also significantly lowers tumor marker levels,thus improving the short-term prognosis of the disease.

Research Progress on Application of Molecular Markers in Breeding of Camellia oleifera

Camellia oleifera is an important woody oil tree species unique to China.It is known as the world s four major woody oil crops along with olive,oil palm and coconut.It is known as the‘king of oil’because of its high oil content.With the increase of people's attention to the yield of Camellia oleifera,its high yield has become the focus.In traditional breeding model,judgment is performed by phenotypic traits,but this method is single and easily affected by the environment,and can no longer meet the demand.In contrast,molecular marker breeding is not affected by the environment,and is stable and efficient and capable of accurately mapping target genes,so it has attracted much attention.In this paper,the research progress on C.oleifera germplasm resources diversity,DNA fingerprinting construction,genetic linkage map construction and QTL mapping was summarized,and the application of SSR molecular marker technique combined with association analysis in C.oleifera breeding in recent years was discussed,in order to provide new ideas for high-yield breeding of C.oleifera.

Predictive model for non-malignant portal vein thrombosis associated with cirrhosis based on inflammatory biomarkers

BACKGROUND Portal vein thrombosis(PVT),a complication of liver cirrhosis,is a major public health concern.PVT prediction is the most effective method for PVT diagnosis and treatment.AIM To develop and validate a nomogram and network calculator based on clinical indicators to predict PVT in patients with cirrhosis.METHODS Patients with cirrhosis hospitalized between January 2016 and December 2021 at the First Hospital of Lanzhou University were screened and 643 patients with cirrhosis who met the eligibility criteria were retrieved.Following a 1:1 propensity score matching 572 patients with cirrhosis were screened,and relevant clinical data were collected.PVT risk factors were identified using the least absolute shrinkage and selection operator(LASSO)and multivariate logistic regression analysis.Variance inflation factors and correlation matrix plots were used to analyze multicollinearity among the variables.A nomogram was constructed to predict the probability of PVT based on independent risk factors for PVT,and its predictive performance was verified using a receiver operating characteristic curve(ROC),calibration curves,and decision curve analysis(DCA).Finally,a network calculator was constructed based on the nomograms.RESULTS This study enrolled 286 cirrhosis patients with PVT and 286 without PVT.LASSO analysis revealed 13 variables as strongly associated with PVT occurrence.Multivariate logistic regression analysis revealed nine indicators as independent PVT risk factors,including etiology,ascites,gastroesophageal varices,platelet count,D-dimer,portal vein diameter,portal vein velocity,aspartate transaminase to neutrophil ratio index,and platelet-to-lymphocyte ratio.LASSO and correlation matrix plot results revealed no significant multicollinearity or correlation among the variables.A nomogram was constructed based on the screened independent risk factors.The nomogram had excellent predictive performance,with an area under the ROC curve of 0.821 and 0.829 in the training and testing groups,respectively.Calibration curves and DCA revealed its good clinical performance.Finally,the optimal cutoff value for the total nomogram score was 0.513.The sensitivity and specificity of the optimal cutoff values were 0.822 and 0.706,respectively.CONCLUSION A nomogram for predicting PVT occurrence was successfully developed and validated,and a network calculator was constructed.This can enable clinicians to rapidly and easily identify high PVT risk groups.