Correlation of Pathological Findings with MRI Imaging in Traumatic Spinal Cord Injury in Hyperacute Time Period in Non Human Primate Model

Traumatic Spinal Cord Injury (TSCI) remains a significant cause of human suffering. The World Health Organization estimates that there are between 250,000 to 500,000 new cases every year. Magnetic Resonance Imaging (MRI) has been an important advancement in the diagnosis and management of TSCI. Nevertheless, there is a lack of literature correlating the radiological abnormalities and histopathological findings in the first hour (i.e., hyperacute period) after injury. The aim of this preliminary study is to elucidate the relationship between the MRI abnormalities and histopathological abnormalities in the hyperacute time period. In this study, a non-human primate model (NHP) primate model is used to characterize the histopathological and radiological features. Specifically, an experimental TSCI is created with an epidural catheter. This is followed by MRI imaging. The subject is then humanely euthanized and a post-mortem examination is completed. These results suggest that the noted radiological abnormalities are consistent with a combination of hemorrhage, edema as well as eosinophilic cellular matter in the central canal.

Correlation between Intestinal Health and Coccidiosis Prevalence in Broilers during Different Seasons of the Year in Brazil from 2012 to 2018

Coccidiosis is a disease caused by intracellular protozoan parasites, specifically belonging to the genus Eimeria. These parasites target the gastrointestinal tract in different types of hosts, causing sores in the intestinal lining. The presence of these lesions reduces the animal’s ability to digest and absorb nutrients, significantly impacting their overall performance. The current study aimed to explore the potential correlation between seasonal variations and the incidence of Eimeria spp-induced lesions in broiler chickens’ gastrointestinal tracts in Brazil from 2012 to 2018. A total of 8,607 broiler chickens, aged 14 to 42 days, were sampled from 103 poultry integrated companies in Brazil to conduct intestinal health examinations. The sampling process involved selecting 3 to 6 chickens from each poultry house for examination. The assessment included various abnormalities such as shedding of intestinal cells and excessive fluid and mucus presence, thickening and tension of the intestines, food movement, roughened mucosal surface resembling a Turkish towel in the small intestine, tissue death, duodenal inflammation, intestinal inflammation, gizzard erosion, presence of worms and bedding material, and ingestion of mealworms. During the seasons, winter exhibited the highest average occurrence of Eimeria maxima microorganisms at 52.83%, with E. acervulina following closely at 26.42% in second place. In spring, E. maxima had an occurrence of 11.31%, while in fall, E. tenella had the lowest occurrence at 6.74%. When analyzing the seasonal occurrence of Eimeria, it was observed that E. maxima micro was more common during winter compared to summer (P = 0.0491). However, no discernible variation was observed in the occurrence of the remaining species across different seasons. Research findings suggest that subclinical coccidiosis is most prevalent during the winter season in Brazil. Likewise, clinical disease caused by E. acervulina is also prevalent during this time. In contrast, E. maxima is more likely to cause clinical disease in the spring, whereas E. tenella is more commonly associated with clinical disease in the fall. Lesions induced by Eimeria spp. are associated with factors influencing the overall health of broiler intestines. These findings allow for the utilization of seasonal metrics in disease management, thereby reducing economic losses associated with the condition.

Soluble alpha-synuclein post-translational modifications:unexpected regulators of pathological alpha-synuclein amplification

The build-up of misfoldedα-synuclein(α-syn)in the central nervous system is the pathological hallmark of a number of neurodegenerative diseases that are known asα-synucleinopathies.These include Parkinson’s disease(PD),Parkinson’s disease with dementia(PDD),dementia with Lewy body(LB),multiple system atrophy(MSA),and a subset of Alzheimer’s disease.Growing evidence underscores that the intercellular transmission and amplification of pathologicalα-syn are critical processes underlying the progression ofα-synucleinopathies(Peng et al.,2020),and as such,the study of these processes could lead to the identification of promising therapeutics to mitigate disease progression.Most previous studies have focused solely on pathological seeds in relation to disease progression.

A Hand Features Based Fusion Recognition Network with Enhancing Multi-Modal Correlation

Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features.Nevertheless,two issues persist in multi-modal feature fusion recognition:Firstly,the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities.Secondly,during modal fusion,improper weight selection diminishes the salience of crucial modal features,thereby diminishing the overall recognition performance.To address these two issues,we introduce an enhanced DenseNet multimodal recognition network founded on feature-level fusion.The information from the three modalities is fused akin to RGB,and the input network augments the correlation between modes through channel correlation.Within the enhanced DenseNet network,the Efficient Channel Attention Network(ECA-Net)dynamically adjusts the weight of each channel to amplify the salience of crucial information in each modal feature.Depthwise separable convolution markedly reduces the training parameters and further enhances the feature correlation.Experimental evaluations were conducted on four multimodal databases,comprising six unimodal databases,including multispectral palmprint and palm vein databases from the Chinese Academy of Sciences.The Equal Error Rates(EER)values were 0.0149%,0.0150%,0.0099%,and 0.0050%,correspondingly.In comparison to other network methods for palmprint,palm vein,and finger vein fusion recognition,this approach substantially enhances recognition performance,rendering it suitable for high-security environments with practical applicability.The experiments in this article utilized amodest sample database comprising 200 individuals.The subsequent phase involves preparing for the extension of the method to larger databases.

Pathological diagnosis and immunohistochemical analysis of giant retrosternal goiter in the elderly: A case report

BACKGROUND Elderly giant retrosternal thyroid goiter is a rare yet significant medical condition,often presenting clinical symptoms that can be confused with other diseases,posing diagnostic and therapeutic challenges.This study aims to delve into the characteristics and potential mechanisms of this ailment through pathological diagnosis and immunohistochemical analysis,providing clinicians with more precise diagnostic and treatment strategies.A 77-year-old male,was admitted to hospital with the chief complaint of finding a goiter in the semilunar month during physical examination,accompanied by dyspnea.Locally protruding into the superior mediastinum,the adjacent structure was compressed,the trachea was compressed to the right,and the local lumen was slightly narrowed.The patient was diagnosed with giant retrosternal goiter.Considering dyspnea caused by trachea compression,our department planned to perform giant retrosternal thyroidectomy.Immunohistochemical results:Tg(+),TTF-1(+),Calcitonin(CT)(I),Ki-67(+,about 20%),CD34(-).Retrosternal goiter means that more than 50%of the volume of the thyroid gland is below the upper margin of the sternum.As retrosternal goiter disease is a relatively rare disease,once the disease is diagnosed,it should be timely surgical treatment,and the treatment is more difficult,the need for professional medical team for comprehensive treatment.CONCLUSION The imaging manifestations of giant retrosternal goiter are atypical,histomorphology and immunohistochemistry can assist in its diagnosis.This article reviews the relevant literature of giant retrosternal goiter immunohisto-chemistry and shows that giant retrosternal goiter is positive for Tg,TTF-1,and Ki-67.

Track correlation algorithm based on CNN-LSTM for swarm targets

The rapid development of unmanned aerial vehicle(UAV) swarm, a new type of aerial threat target, has brought great pressure to the air defense early warning system. At present, most of the track correlation algorithms only use part of the target location, speed, and other information for correlation.In this paper, the artificial neural network method is used to establish the corresponding intelligent track correlation model and method according to the characteristics of swarm targets.Precisely, a route correlation method based on convolutional neural networks (CNN) and long short-term memory (LSTM)Neural network is designed. In this model, the CNN is used to extract the formation characteristics of UAV swarm and the spatial position characteristics of single UAV track in the formation,while the LSTM is used to extract the time characteristics of UAV swarm. Experimental results show that compared with the traditional algorithms, the algorithm based on CNN-LSTM neural network can make full use of multiple feature information of the target, and has better robustness and accuracy for swarm targets.

Correlation Study on Grain Size Characteristics and Geotechnical Properties of Surface Sediments in Qingdao Offshore Area

The comprehension of sediment grain size parameters and the corresponding sedimentary environment holds paramount importance in elucidating the engineering geological attributes of the subaqueous seabed.This study delineated the sedimentary environment zoning in the northern sea area of Qingdao through cluster analysis of grain size parameters derived from 123 surface sediment samples.The study analyzed the correlation between sediment geotechnical indices and grain size parameters across diverse sedimentary environments.A correlation equation was established for samples exhibiting a strong correlation.The study found four distinct sedimentary environments in the study area:coastal,transitional,shallow sea,and residual.Within the same sedimentary environment,the average grain size and sorting coefficient exhibit significant correlations with geotechnical indices such as water content,density,shear strength,plastic limit,liquid limit,and plastic index.However,notable disparities in the correlation between grain size parameters and geotechnical indices emerge across different sedimentary environments.

Clinical pathological characteristics of“crawling-type”gastric adenocarcinoma cancer:A case report

BACKGROUND Gastric cancer(GC)is a significant health problem worldwide,and early detection and accurate diagnosis are crucial for improving patient outcomes.Crawling-type gastric adenocarcinoma is a rare subtype of GC that has unique histopathological and clinical characteristics,and its diagnosis and management can be challenging.This pathological type of GC is also rare.CASE SUMMARY Here,we report the case of a patient who underwent ordinary endoscopy,na-rrow-band imaging,and endoscopic ultrasonography intending to determine the extent of tumor invasion and upper abdominal enhanced computed tomography and whether there was tumor metastasis.Then,endoscopic submucosal dissection was performed.After pathological and immunohistochemical examination,the pathological diagnosis was crawling-type gastric adenocarcinoma.This is a very rare and special pathological type of tumor.This case highlights the importance of using advanced endoscopic techniques and pathological examination in diagnosing and managing gastric crawling-type adenocarcinoma.Moreover,the findings underscore the need for continued research and clinical experience in this rare subtype of GC to improve patient outcomes.CONCLUSION The“crawling-type”GC is a rare and specific tumor pathology.It is difficult to identify and diagnose gliomas via endoscopy.The tumor is ill-defined,with a flat appearance and indistinct borders due to the lack of contrast against the background mucosa.Pathology revealed that the tumor cells were hand-like,so the patient has diagnosed with“crawling-type”gastric adenocarcinoma.

Quantum correlations and entanglement in coupled optomechanical resonators with photon hopping via Gaussian interferometric power analysis

Quantum correlations that surpass entanglement are of great importance in the realms of quantum information processing and quantum computation.Essentially,for quantum systems prepared in pure states,it is difficult to differentiate between quantum entanglement and quantum correlation.Nonetheless,this indistinguishability is no longer holds for mixed states.To contribute to a better understanding of this differentiation,we have explored a simple model for both generating and measuring these quantum correlations.Our study concerns two macroscopic mechanical resonators placed in separate Fabry–Pérot cavities,coupled through the photon hopping process.this system offers a comprehensively way to investigate and quantify quantum correlations beyond entanglement between these mechanical modes.The key ingredient in analyzing quantum correlation in this system is the global covariance matrix.It forms the basis for computing two essential metrics:the logarithmic negativity(E_(N)^(m))and the Gaussian interferometric power(P_(G)^(m)).These metrics provide the tools to measure the degree of quantum entanglement and quantum correlations,respectively.Our study reveals that the Gaussian interferometric power(P_(G)^(m))proves to be a more suitable metric for characterizing quantum correlations among the mechanical modes in an optomechanical quantum system,particularly in scenarios featuring resilient photon hopping.

Channel Correlation Based User Grouping Algorithm for Nonlinear Precoding Satellite Communication System

Low Earth Orbit(LEO)multibeam satellites will be widely used in the next generation of satellite communication systems,whose inter-beam interference will inevitably limit the performance of the whole system.Nonlinear precoding such as Tomlinson-Harashima precoding(THP)algorithm has been proved to be a promising technology to solve this problem,which has smaller noise amplification effect compared with linear precoding.However,the similarity of different user channels(defined as channel correlation)will degrade the performance of THP algorithm.In this paper,we qualitatively analyze the inter-beam interference in the whole process of LEO satellite over a specific coverage area,and the impact of channel correlation on Signal-to-Noise Ratio(SNR)of receivers when THP is applied.One user grouping algorithm is proposed based on the analysis of channel correlation,which could decrease the number of users with high channel correlation in each precoding group,thus improve the performance of THP.Furthermore,our algorithm is designed under the premise of co-frequency deployment and orthogonal frequency division multiplexing(OFDM),which leads to more users under severe inter-beam interference compared to the existing research on geostationary orbit satellites broadcasting systems.Simulation results show that the proposed user grouping algorithm possesses higher channel capacity and better bit error rate(BER)performance in high SNR conditions relative to existing works.

Spatial correlations in ground motion intensity measuring from the 2023 Türkiye earthquake

When evaluating an area's seismic risk or resilience,it is necessary to use the spatial correlation to analyze the ground motion parameters of multiple sites together in an earthquake.These two large earthquakes in Türkiye provided the possibility for spatial correlation analysis of ground motion intensity measurements in this area.Based on the strong motion records provided by The Disaster and Emergency Management Authority of Türkiye(AFAD),this study uses the local ground motion prediction equation in Türkiye to give spatial correlation analysis of Intensity Measurements.This study gives an exponential model based on a semivariogram and compares it with the correlation model obtained from previous studies.

Cross-Project Software Defect Prediction Based on SMOTE and Deep Canonical Correlation Analysis

Cross-Project Defect Prediction(CPDP)is a method that utilizes historical data from other source projects to train predictive models for defect prediction in the target project.However,existing CPDP methods only consider linear correlations between features(indicators)of the source and target projects.These models are not capable of evaluating non-linear correlations between features when they exist,for example,when there are differences in data distributions between the source and target projects.As a result,the performance of such CPDP models is compromised.In this paper,this paper proposes a novel CPDP method based on Synthetic Minority Oversampling Technique(SMOTE)and Deep Canonical Correlation Analysis(DCCA),referred to as S-DCCA.Canonical Correlation Analysis(CCA)is employed to address the issue of non-linear correlations between features of the source and target projects.S-DCCA extends CCA by incorporating the MlpNet model for feature extraction from the dataset.The redundant features are then eliminated by maximizing the correlated feature subset using the CCA loss function.Finally,cross-project defect prediction is achieved through the application of the SMOTE data sampling technique.Area Under Curve(AUC)and F1 scores(F1)are used as evaluation metrics.This paper conducted experiments on 27 projects from four public datasets to validate the proposed method.The results demonstrate that,on average,our method outperforms all baseline approaches by at least 1.2%in AUC and 5.5%in F1 score.This indicates that the proposed method exhibits favorable performance characteristics.

Mesenchymal-epithelial transition factor amplification correlates with adverse pathological features and poor clinical outcome in colorectal cancer

BACKGROUND Colorectal cancer(CRC)is the third most common cancer and the second most common cause of cancer-related mortality worldwide.Mesenchymal-epithelial transition factor(MET)gene participates in multiple tumor biology and shows clinical potential for pharmacological manipulation in tumor treatment.MET amplification has been reported in CRC,but data are very limited.Investigating pathological values of MET in CRC may provide new therapeutic and genetic screening options in future clinical practice.AIM To determine the pathological significance of MET amplification in CRC and to propose a feasible screening strategy.METHODS A number of 205 newly diagnosed CRC patients undergoing surgical resection without any preoperative therapy at Shenzhen Cancer Hospital of Chinese Academy of Medical Sciences were recruited.All patients were without RAS/RAF mutation or microsatellite instability-high.MET amplification and c-MET protein expression were analyzed using fluorescence in situ hybridization(FISH)and immunohistochemistry(IHC),respectively.Correlations between MET aberration and pathological features were detected using the chi-squared test.Progression free survival(PFS)during the two-year follow-up was detected using the Kaplan-Meier method and log rank test.The results of MET FISH and IHC were com pared using one-way ANOVA.RESULTS Polysomy-induced MET amplification was observed in 14.4%of cases,and focal MET amplification was not detected.Polysomy-induced MET amplification was associated with a higher frequency of lymph node metastasis(LNM)(P<0.001)and higher tumor budding grade(P=0.02).In the survival analysis,significant difference was detected between patients with amplified-and non-amplified MET in a two-year follow-up after the first diagnosis(P=0.001).C-MET scores of 0,1+,2+,and 3+were observed in 1.4%,24.9%,54.7%,and 19.0%of tumors,respectively.C-MET overexpression correlated with higher frequency of LNM(P=0.002),but no significant difference of PFS was detected between patients with different protein levels.In terms of concordance between MET FISH and IHC results,MET copy number showed no difference in c-MET IHC 0/1+(3.35±0.18),2+(3.29±0.11)and 3+(3.58±0.22)cohorts,and the MET-to-CEP7 ratio showed no difference in three groups(1.09±0.02,1.10±0.01,and 1.09±0.03).CONCLUSION In CRC,focal MET amplification was a rare event.Polysomy-induced MET amplification correlated with adverse pathological characteristics and poor prognosis.IHC was a poor screening tool for MET amplification.

Machine Learning Security Defense Algorithms Based on Metadata Correlation Features

With the popularization of the Internet and the development of technology,cyber threats are increasing day by day.Threats such as malware,hacking,and data breaches have had a serious impact on cybersecurity.The network security environment in the era of big data presents the characteristics of large amounts of data,high diversity,and high real-time requirements.Traditional security defense methods and tools have been unable to cope with the complex and changing network security threats.This paper proposes a machine-learning security defense algorithm based on metadata association features.Emphasize control over unauthorized users through privacy,integrity,and availability.The user model is established and the mapping between the user model and the metadata of the data source is generated.By analyzing the user model and its corresponding mapping relationship,the query of the user model can be decomposed into the query of various heterogeneous data sources,and the integration of heterogeneous data sources based on the metadata association characteristics can be realized.Define and classify customer information,automatically identify and perceive sensitive data,build a behavior audit and analysis platform,analyze user behavior trajectories,and complete the construction of a machine learning customer information security defense system.The experimental results show that when the data volume is 5×103 bit,the data storage integrity of the proposed method is 92%.The data accuracy is 98%,and the success rate of data intrusion is only 2.6%.It can be concluded that the data storage method in this paper is safe,the data accuracy is always at a high level,and the data disaster recovery performance is good.This method can effectively resist data intrusion and has high air traffic control security.It can not only detect all viruses in user data storage,but also realize integrated virus processing,and further optimize the security defense effect of user big data.

Enhanced Temporal Correlation for Universal Lesion Detection

Universal lesion detection(ULD)methods for computed tomography(CT)images play a vital role in the modern clinical medicine and intelligent automation.It is well known that single 2D CT slices lack spatial-temporal characteristics and contextual information compared to 3D CT blocks.However,3D CT blocks necessitate significantly higher hardware resources during the learning phase.Therefore,efficiently exploiting temporal correlation and spatial-temporal features of 2D CT slices is crucial for ULD tasks.In this paper,we propose a ULD network with the enhanced temporal correlation for this purpose,named TCE-Net.The designed TCE module is applied to enrich the discriminate feature representation of multiple sequential CT slices.Besides,we employ multi-scale feature maps to facilitate the localization and detection of lesions in various sizes.Extensive experiments are conducted on the DeepLesion benchmark demonstrate that thismethod achieves 66.84%and 78.18%for FS@0.5 and FS@1.0,respectively,outperforming compared state-of-the-art methods.

Repeatability,interocular correlation and agreement of optic nerve head vessel density in healthy eyes:a sweptsource optical coherence tomographic angiography study

AIM:To assess the repeatability,interocular correlation,and agreement of quantitative swept-source optical coherence tomography angiography(OCTA)optic nerve head(ONH)parameters in healthy subjects.METHODS:Thir ty-three healthy subjects were enrolled.The ONH of both eyes were imaged four times by a swept-source-OCTA using a 3 mm×3 mm scanning protocol.Images of the radial peripapillary capillary were analyzed by a customized Matlab program,and the vessel density,fractal dimension,and vessel diameter index were measured.The repeatability of the four scans was determined by the intraclass correlation coefficient(ICC).The most well-centered optic disc from the four repeated scans was then selected for the interocular correlation and agreement analysis using the Pearson correlation coefficient,ICC and Bland-Altman plots.RESULTS:All swept-source-OCTA ONH parameters exhibited certain repeatability,with ICC>0.760 and coefficient of variation(CoV)≤7.301%.The obvious interocular correlation was observed for papillary vessel density(ICC=0.857),vessel diameter index(ICC=0.857)and fractal dimension(ICC=0.906),while circumpapillary vessel density exhibited moderate interocular correlation(ICC=0.687).Bland-Altman plots revealed an agreement range of-5.26%to 6.21%for circumpapillary vessel density.CONCLUSION:OCTA ONH parameters demonstrate good repeatability in healthy subjects.The interocular correlations of papillary vessel density,fractal dimension and vessel diameter index are high,but the correlation for circumpapillary vessel density is moderate.

Postpartum depression and partner support during the period of lactation:Correlation research and its influencing factors

BACKGROUND Postpartum depression(PPD)not only affects the psychological and physiological aspects of maternal health but can also affect neonatal growth and development.Partners who are in close contact with parturient women play a key role in communication and emotional support.This study explores the PPD support relationship with partners and its influencing factors,which is believed to establish psychological well-being and improve maternal partner support.AIM To explore the correlation between PPD and partner support during breastfeeding and its influencing factors.METHODS Convenience sampling was used to select lactating women(200 women)who underwent postpartum examinations at the Huzhou Maternity and Child Health Care Hospital from July 2022 to December 2022.A cross-sectional survey was conducted on the basic information(general information questionnaire),depression level[edinburgh postnatal depression scale(EPDS)],and partner support score[dyadic coping inventory(DCI)]of the selected subjects.Pearson’s correlation analysis was used to analyze the correlation between PPD and DCI in lactating women.Factors affecting PPD levels during lactation were analyzed using multiple linear regression.RESULTS The total average score of EPDS in 200 lactating women was(9.52±1.53),and the total average score of DCI was(115.78±14.90).Dividing the EPDS,the dimension scores were:emotional loss(1.91±0.52),anxiety(3.84±1.05),and depression(3.76±0.96).Each dimension of the DCI was subdivided into:Pressure communication(26.79±6.71),mutual support(39.76±9.63),negative support(24.97±6.68),agent support(6.87±1.92),and joint support(17.39±4.19).Pearson’s correlation analysis demonstrated that the total mean score and individual dimension scores of EPDS during breastfeeding were inversely correlated with the total score of partner support,stress communication,mutual support,and cosupport(P<0.05).The total mean score of the EPDS and its dimensions were positively correlated with negative support(P<0.05).Multiple linear regression analysis showed that the main factors affecting PPD during breastfeeding were marital harmony,newborn health,stress communication,mutual support,negative support,cosupport,and the total score of partner support(P<0.05).CONCLUSION PPD during breastfeeding was associated with marital harmony,newborn health,stress communication,mutual support,negative support,joint support,and the total DCI score.

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.

Pathological mechanism of immune disorders in diabetic kidney disease and intervention strategies

Diabetic kidney disease is one of the most severe chronic microvascular complications of diabetes and a primary cause of end-stage renal disease.Clinical studies have shown that renal inflammation is a key factor determining kidney damage during diabetes.With the development of immunological technology,many studies have shown that diabetic nephropathy is an immune complex disease,and that most patients have immune dysfunction.However,the immune response associated with diabetic nephropathy and autoimmune kidney disease,or caused by ischemia or infection with acute renal injury,is different,and has a complicated pathological mechanism.In this review,we discuss the pathogenesis of diabetic nephropathy in immune disorders and the intervention mechanism,to provide guidance and advice for early intervention and treatment of diabetic nephropathy.

Prediction of pathological complete response and prognosis in locally advanced rectal cancer

BACKGROUND Colorectal cancer is currently the third most common malignant tumor and the second leading cause of cancer-related death worldwide.Neoadjuvant chemoradiotherapy(nCRT)is standard for locally advanced rectal cancer(LARC).Except for pathological examination after resection,it is not known exactly whether LARC patients have achieved pathological complete response(pCR)before surgery.To date,there are no clear clinical indicators that can predict the efficacy of nCRT and patient outcomes.AIM To investigate the indicators that can predict pCR and long-term outcomes following nCRT in patients with LARC.METHODS Clinical data of 128 LARC patients admitted to our hospital between September 2013 and November 2022 were retrospectively analyzed.Patients were categorized into pCR and non-pCR groups.Univariate analysis(using the χ^(2) test or Fisher’s exact test)and logistic multivariate regression analysis were used to study clinical predictors affecting pCR.The 5-year disease-free survival(DFS)and overall survival(OS)rates were calculated using Kaplan-Meier analysis,and differences in survival curves were assessed with the log-rank test.RESULTS Univariate analysis showed that pretreatment carcinoembryonic antigen(CEA)level,lymphocyte-monocyte ratio(LMR),time interval between neoadjuvant therapy completion and total mesorectal excision,and tumor size were correlated with pCR.Multivariate results showed that CEA≤5 ng/mL(P=0.039),LMR>2.73(P=0.023),and time interval>10 wk(P=0.039)were independent predictors for pCR.Survival analysis demonstrated that patients in the pCR group had significantly higher 5-year DFS rates(94.7%vs 59.7%,P=0.002)and 5-year OS rates(95.8%vs 80.1%,P=0.019)compared to the non-pCR group.Tumor deposits(TDs)were significantly correlated with shorter DFS(P=0.002)and OS(P<0.001).CONCLUSION Pretreatment CEA,LMR,and time interval contribute to predicting nCRT efficacy in LARC patients.Achieving pCR demonstrates longer DFS and OS.TDs correlate with poor prognosis.