NLRP3-mediated autophagy dysfunction links gut microbiota dysbiosis to tau pathology in chronic sleep deprivation

Emerging evidence indicates that sleep deprivation(SD)can lead to Alzheimer’s disease(AD)-related pathological changes and cognitive decline.However,the underlying mechanisms remain obscure.In the present study,we identified the existence of a microbiota-gut-brain axis in cognitive deficits resulting from chronic SD and revealed a potential pathway by which gut microbiota affects cognitive functioning in chronic SD.Our findings demonstrated that chronic SD in mice not only led to cognitive decline but also induced gut microbiota dysbiosis,elevated NLRP3 inflammasome expression,GSK-3βactivation,autophagy dysfunction,and tau hyperphosphorylation in the hippocampus.Colonization with the“SD microbiota”replicated the pathological and behavioral abnormalities observed in chronic sleep-deprived mice.Remarkably,both the deletion of NLRP3 in NLRP3-/-mice and specific knockdown of NLRP3 in the hippocampus restored autophagic flux,suppressed tau hyperphosphorylation,and ameliorated cognitive deficits induced by chronic SD,while GSK-3βactivity was not regulated by the NLRP3 inflammasome in chronic SD.Notably,deletion of NLRP3 reversed NLRP3 inflammasome activation,autophagy deficits,and tau hyperphosphorylation induced by GSK-3βactivation in primary hippocampal neurons,suggesting that GSK-3β,as a regulator of NLRP3-mediated autophagy dysfunction,plays a significant role in promoting tau hyperphosphorylation.Thus,gut microbiota dysbiosis was identified as a contributor to chronic SD-induced tau pathology via NLRP3-mediated autophagy dysfunction,ultimately leading to cognitive deficits.Overall,these findings highlight GSK-3βas a regulator of NLRP3-mediated autophagy dysfunction,playing a critical role in promoting tau hyperphosphorylation.

Digital pathology-based artificial intelligence models for differential diagnosis and prognosis of sporadic odontogenic keratocysts

Odontogenic keratocyst(OKC)is a common jaw cyst with a high recurrence rate.OKC combined with basal cell carcinoma as well as skeletal and other developmental abnormalities is thought to be associated with Gorlin syndrome.Moreover,OKC needs to be differentiated from orthokeratinized odontogenic cyst and other jaw cysts.Because of the different prognosis,differential diagnosis of several cysts can contribute to clinical management.We collected 519 cases,comprising a total of 2157 hematoxylin and eosinstained images,to develop digital pathology-based artificial intelligence(AI)models for the diagnosis and prognosis of OKC.The Inception_v3 neural network was utilized to train and test models developed from patch-level images.Finally,whole slide imagelevel AI models were developed by integrating deep learning-generated pathology features with several machine learning algorithms.The AI models showed great performance in the diagnosis(AUC=0.935,95%CI:0.898–0.973)and prognosis(AUC=0.840,95%CI:0.751–0.930)of OKC.The advantages of multiple slides model for integrating of histopathological information are demonstrated through a comparison with the single slide model.Furthermore,the study investigates the correlation between AI features generated by deep learning and pathological findings,highlighting the interpretative potential of AI models in the pathology.Here,we have developed the robust diagnostic and prognostic models for OKC.The AI model that is based on digital pathology shows promise potential for applications in odontogenic diseases of the jaw.

Going straight for the gut:gut-brain axis pathology and treatment of Parkinson's disease

This perspective focuses on the recent literature regarding the role of the gut-brain axis(GBA) in fecal microbiota transplantation(FMT) and stem cell therapy(SCT) in Parkinson's disease(PD).PD is the second most common neurodegenerative disease in the United States,yet therapies remain limited.Current research suggests that the GBA may play a role in the pathogenesis of PD.GBAbased FMT as well as SCT offer promising new avenues for PD treatment.Pro bing the interactions between FMT and SCT with the GBA may reveal novel therapeutics for PD.

Amyloid-beta pathology-induced nanoscale synaptic disruption:the case of the GABA_B-GIRK assembly

Alzheimer's disease (AD) is characterized by an imbalance between excitatory and inhibitory brain networks,leading to aberrant homeostatic synaptic plasticity.AD has progressively been recognized as syna ptopathy and syna ptic dysfunction has been identified as a key component of its pathogenesis (Schirinzi et al.,2020).Syna ptic dysfunction is believed to precede synapse loss,a primary biological correlate of cognitive decline in AD,inevita bly associated with neuronal death.

Hysterectomies for Gynaecological Pathology: 56 Cases at the Segou Regional Hospital in Mali

Introduction: Hysterectomy is a surgical procedure involving partial or total removal of the uterus. It is the most common gynaecological surgery in the world. Objective: To describe the epidemio-clinical and prognostic aspects of gynaecological hysterectomies. Patients and methods: This was an 18-month retrospective prospective descriptive study with a six-month follow-up period from 1 December 2020 to 31 May 2022 carried out in the gynaecology department of the Segou regional hospital. Results: Fifty-six (56) hysterectomies were performed out of 118 gynaecological surgical procedures (47.45%). The mean age was 47 ± 11.77 years. Large multiparous women were the most common (50%), with an average parity of 4.58. The main indications were uterine fibroids (30.4%), precancerous lesions of the cervix (17.85%) and uterine prolapse (17.85%). The abdominal route was the most commonly used surgical route (82.14%). Hysterectomy was total in 100% of cases and associated with bilateral adnexectomy in 48.2% of cases. The intra- and post-operative prognosis was satisfactory in 94.6% of cases. No deaths were recorded. The average length of stay was 3.28 days, irrespective of the surgical approach. Three cases of dyspareunia were noted among those who had resumed sexual activity.

Constructing a nomogram to predict overall survival of colon cancer based on computed tomography characteristics and clinicopathological factors

BACKGROUND The colon cancer prognosis is influenced by multiple factors,including clinical,pathological,and non-biological factors.However,only a few studies have focused on computed tomography(CT)imaging features.Therefore,this study aims to predict the prognosis of patients with colon cancer by combining CT imaging features with clinical and pathological characteristics,and establishes a nomogram to provide critical guidance for the individualized treatment.AIM To establish and validate a nomogram to predict the overall survival(OS)of patients with colon cancer.METHODS A retrospective analysis was conducted on the survival data of 249 patients with colon cancer confirmed by surgical pathology between January 2017 and December 2021.The patients were randomly divided into training and testing groups at a 1:1 ratio.Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors associated with OS,and a nomogram model was constructed for the training group.Survival curves were calculated using the Kaplan–Meier method.The concordance index(C-index)and calibration curve were used to evaluate the nomogram model in the training and testing groups.RESULTS Multivariate logistic regression analysis revealed that lymph node metastasis on CT,perineural invasion,and tumor classification were independent prognostic factors.A nomogram incorporating these variables was constructed,and the C-index of the training and testing groups was 0.804 and 0.692,respectively.The calibration curves demonstrated good consistency between the actual values and predicted probabilities of OS.CONCLUSION A nomogram combining CT imaging characteristics and clinicopathological factors exhibited good discrimination and reliability.It can aid clinicians in risk stratification and postoperative monitoring and provide important guidance for the individualized treatment of patients with colon cancer.

Using MsfNet to Predict the ISUP Grade of Renal Clear Cell Carcinoma in Digital Pathology Images

Clear cell renal cell carcinoma(ccRCC)represents the most frequent form of renal cell carcinoma(RCC),and accurate International Society of Urological Pathology(ISUP)grading is crucial for prognosis and treatment selection.This study presents a new deep network called Multi-scale Fusion Network(MsfNet),which aims to enhance the automatic ISUP grade of ccRCC with digital histopathology pathology images.The MsfNet overcomes the limitations of traditional ResNet50 by multi-scale information fusion and dynamic allocation of channel quantity.The model was trained and tested using 90 Hematoxylin and Eosin(H&E)stained whole slide images(WSIs),which were all cropped into 320×320-pixel patches at 40×magnification.MsfNet achieved a micro-averaged area under the curve(AUC)of 0.9807,a macro-averaged AUC of 0.9778 on the test dataset.The Gradient-weighted Class Activation Mapping(Grad-CAM)visually demonstrated MsfNet’s ability to distinguish and highlight abnormal areas more effectively than ResNet50.The t-Distributed Stochastic Neighbor Embedding(t-SNE)plot indicates our model can efficiently extract critical features from images,reducing the impact of noise and redundant information.The results suggest that MsfNet offers an accurate ISUP grade of ccRCC in digital images,emphasizing the potential of AI-assisted histopathological systems in clinical practice.

Microvascular structural changes in esophageal squamous cell carcinoma pathology according to intrapapillary capillary loop types under magnifying endoscopy

BACKGROUND The intrapapillary capillary loop(IPCL)characteristics,visualized using magnifying endoscopy,are commonly assessed for preoperative evaluation of the infiltration depth of esophageal squamous cell carcinoma(ESCC).Japan Esophageal Society(JES)classification is the most widely used classification.Microvascular structural changes are evaluated by magnifying endoscopy for the presence or absence of each morphological factor:tortuosity,dilatation,irregular caliber,and different shapes.However,the pathological characteristics of IPCLs have not been thoroughly investigated,especially the microvascular structures corresponding to the deepest parts of the lesions'infiltration.AIM To investigate differences in pathological microvascular structures of ESCC,which correspond to the deepest parts of the lesions'infiltration.METHODS Patients with ESCC and precancerous lesions diagnosed at Peking University Third Hospital were enrolled between January 2019 and April 2023.Patients first underwent magnified endoscopic examination,followed by endoscopic submucosal dissection or surgical treatment.Pathological images were scanned using a threedimensional slice scanner,and the pathological structural differences in different types,according to the JES classification,were analyzed using nonparametric tests and t-tests.RESULTS The 35 lesions were divided into four groups according to the JES classification:A,B1,B2,and B3.Statistical analyses revealed significant differences(aP<0.05)in the short and long calibers,area,location,and density between types A and B.Notably,there were no significant differences in these parameters between types B1 and B2 and between types B2 and B3(P>0.05).However,significant differences in the short calibers,long calibers,and area of IPCL were observed between types B1 and B3(aP<0.05);no significant differences were found in the density or location(P>0.05).CONCLUSION Pathological structures of IPCLs in the deepest infiltrating regions differ among various IPCL types classified by the JES classification under magnifying endoscopy,especially between the types A and B.

A Multi-Task Deep Learning Framework for Simultaneous Detection of Thoracic Pathology through Image Classification

Thoracic diseases pose significant risks to an individual's chest health and are among the most perilous medical diseases. They can impact either one or both lungs, which leads to a severe impairment of a person’s ability to breathe normally. Some notable examples of such diseases encompass pneumonia, lung cancer, coronavirus disease 2019 (COVID-19), tuberculosis, and chronic obstructive pulmonary disease (COPD). Consequently, early and precise detection of these diseases is paramount during the diagnostic process. Traditionally, the primary methods employed for the detection involve the use of X-ray imaging or computed tomography (CT) scans. Nevertheless, due to the scarcity of proficient radiologists and the inherent similarities between these diseases, the accuracy of detection can be compromised, leading to imprecise or erroneous results. To address this challenge, scientists have turned to computer-based solutions, aiming for swift and accurate diagnoses. The primary objective of this study is to develop two machine learning models, utilizing single-task and multi-task learning frameworks, to enhance classification accuracy. Within the multi-task learning architecture, two principal approaches exist soft parameter sharing and hard parameter sharing. Consequently, this research adopts a multi-task deep learning approach that leverages CNNs to achieve improved classification performance for the specified tasks. These tasks, focusing on pneumonia and COVID-19, are processed and learned simultaneously within a multi-task model. To assess the effectiveness of the trained model, it is rigorously validated using three different real-world datasets for training and testing.

Expanding role and scope of artificial intelligence in the field of gastrointestinal pathology

Digital pathology(DP)and its subsidiaries including artificial intelligence(AI)are rapidly making inroads into the area of diagnostic anatomic pathology(AP)including gastrointestinal(GI)pathology.It is poised to revolutionize the field of diagnostic AP.Historically,AP has been slow to adopt digital technology,but this is changing rapidly,with many centers worldwide transitioning to DP.Coupled with advanced techniques of AI such as deep learning and machine learning,DP is likely to transform histopathology from a subjective field to an objective,efficient,and transparent discipline.AI is increasingly integrated into GI pathology,offering numerous advancements and improvements in overall diagnostic accuracy,efficiency,and patient care.Specifically,AI in GI pathology enhances diagnostic accuracy,streamlines workflows,provides predictive insights,integrates multimodal data,supports research,and aids in education and training,ultimately improving patient care and outcomes.This review summarized the latest developments in the role and scope of AI in AP with a focus on GI pathology.The main aim was to provide updates and create awareness among the pathology community.

Collision tumor of primary malignant lymphoma and adenocarcinoma in the colon diagnosed by molecular pathology:A case report and literature review

BACKGROUND Collision tumors of primary malignant lymphoma and adenocarcinoma in the colon are rare.Primary diffuse large B-cell lymphoma(DLBCL)–adenocarcinoma collision tumors are especially rare.CASE SUMMARY A 74-year-old woman presented with abdominal pain of 1 mo duration.Biopsy under colonoscopy revealed adenocarcinoma of the ascending colon.Subsequently,the patient underwent laparoscopic radical resection of right colon cancer with lymph node dissection.A collision tumor was found incidentally through postoperative pathological sampling.Genetic analysis showed a collision tumor of DLBCL with germinal center B-cell subtype and TP53 mutation,and adenocarcinoma arising in a tubulovillous adenoma in the colon,with BRAF mutation and mutL homolog 1 promoter methylation.The patient died 3 mo after surgery.To our knowledge,this is the 23rd reported case of collision tumor of colorectal adenocarcinoma and lymphoma.The mean age of the 23 patients was 73 years.The most common site was the cecum.There were 15 cases with followup data including 11 living and four dead with a 3-year overall survival rate of 71.5%.CONCLUSION Based on pathological and genetic analysis,surgery combined with chemotherapy or chemoradiotherapy may have good therapeutic effects for collision tumor.

Axial length,vitreoretinal pathology,and anterior chamber depth can predict postoperative refractive outcomes in phacovitrectomy/silicone oil removal

AIM:To evaluate the postoperative refractive prediction error(PE)and determine the factors that af fect the refractive outcomes of combined pars plana vitrectomy(PPV)or silicone oil removal(SOR)with cataract surgery.METHODS:The study is a retrospective,case-series study.Totally 301 eyes of 301 patients undergoing combined PPV/SOR with cataract surgery were enrolled.Eligible individuals were separated into four groups according to their preoperative diagnoses:silicone oil-filled eyes after PPV(group 1),epiretinal membrane(group 2),macular hole(group 3),and primary retinal detachment(RD;group 4).The variables af fecting postoperative refractive outcomes were analyzed,including age,gender,preoperative best-corrected visual acuity(BCVA),axial length(AL),keratometry average,anterior chamber depth(ACD),intraocular tamponade,and vitreoretinal pathology.The outcome measurements include the mean refractive PE and the proportions of eyes with a PE within±0.50 diopter(D)and±1.00 D.RESULTS:For all patients,the mean PE was-0.04±1.17 D,and 50.17%of patients(eyes)had a PE within±0.50 D.There was a significant difference in refractive outcomes among the four groups(P=0.028),with RD(group 4)showing the least favorable refractive outcome.In multivariate regression analysis,only AL,vitreoretinal pathology,and ACD were strongly associated with PE(all P<0.01).Univariate analysis revealed that longer eyes(AL>26 mm)and a deeper ACD were correlated with hyperopic PE,and shorter eyes(AL<26 mm)and a shallower ACD were correlated with myopic PE.CONCLUSION:RD patients have the least favorable refractive outcome.AL,vitreoretinal pathology,and ACD are strongly associated with PE in the combined surgery.These three factors affect refractive outcomes and thus can be used to predict a better postoperative refractive outcome in clinical practice.

Colon and rectal cancer:An emergent public health problem

Colorectal cancer ranks third globally,with a high mortality rate.In the United States,and different countries in Europe,organized population screenings exist and include people between 50 and 74 years of age.These screenings have allowed an early diagnosis and consequently an improvement in health indicators.Colon and rectal cancer(CRC)is a disease of particular interest due to the high global burden associated with it and the role attributed to prevention and early diagnosis in reducing morbidity and mortality.This study is a review of CRC pathology and includes the most recent scientific evidence regarding this pathology,as well as a diagnosis of the epidemiological situation of CRC.Finally,the recommendation from a public health perspective will be discussed in detail taking into account the context and the most current recommendations.

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.

Effects of four regulating-intestine prescriptions on pathology and ultrastructure of colon tissue in rats with ulcerative colitis

AIM: To observe different histomorphologic changes of ulcerative colitis (UC) rats that were treated with four regulating-intestine prescriptions (FRIP), to investigate the curative effects of FRIP and to analyze their treatment mechanism.METHODS: The UC rat model was made by the method of 2,4-dinitro chloro benzene (DNCB) immunity and acetic acid local enema. Ninety-eight SD rats were randomly divided into seven groups, namely, the normal control group, model group, salicylazosulfapyridine (SASP) group,Wumeiwan (WMW) group, Baitouwengtang (BTWT) group,Senglingbaishusan (SLBSS) group, and Tongxieyaofang (TXYF) group. Each group had 14 rats (with equal ratio of male and female). The six animal model groups of UC-SASP, TXYF, WMW, BTWT, SLBSS, TXYF-were treated by distilled water except the normal control group. Changes of the rat's general conditions after treatment were respectively observed, the colon tissue damage scores were given out, the pathology of colonic mucosa and changes of ultrastructure were analyzed.RESULTS: Different pathological changes on histology were shown after treatment by FRIP. The colon tissue damage score in model group was higher than that of FRIP groups and SASP group (q = 4.59, 4.77, P＜0.05 or q = 5.48,6.25, 5.97, P＜0.01). The scores of WMW group, BTWT group and SLBSS group were lower than that of SASP (q = 4.13, P＜0.05 or q = 5.31, 5.12, P＜0.01). There was no remarkable difference between the damage score of TXYF group and SASP group (q = 3.75, P＞0.05). In addition, some apoptosis cells were found in the pathologic control group.CONCLUSION: The model made with DNCB and acetic acid was successful, and FRIP had better curative effect and WMW was the best curative effect, BTW, SLBSS and TXYF were similar to SASP, and we discovered that apoptosis was possibly related to UC.

Correlation between clinicopathology and expression of heat shock protein 70 and glucose-regulated protein 94 in human colonic adenocarcinoma

AIM: To investigate the correlation between clinicopathology and expression of heat shock protein 70 (HSP70) and glucose-regulated protein 94 (grp94) in human colonic carcinoma. METHODS: The expression of HSP70 and grp94 was studied in 80 human colonic cancers with or without metastasis as well as in their adjacent mucous membrane by way of immunohistochemistry and pathology photograph analysis. RESULTS: The expression of HSP70 and grp94 was significantly higher in cancer than that in adjacent mucous membrane (92.5%, 85.0% vs 56.3%, 42.5%, P<0.01). HSP70 and grp94 expressed higher in moderately- and poorly-differentiated colonic cancers than that in their adjacent tissues (93.7%, 87.5%; 100%, 90% vs56.3%, 42.5%;P<0.01). Dukes C and D stages of colonic cancers showed higher positive rates than Dukes A and B stage groups (97.1%, 91.2%; 100%, 90.9%; vs 80%, 70%; 78.6%, 71.4%; P<0.05). There were definite differences in HSP70 and grp94 expression between metastasis groups and non-metastasis groups (100% vs 75%, 100% CONCLUSION: The HSP70 and grp94 expression rates in colonic cancer groups are significantly higher than that in their adjacent mucous membrane. The HSP70 and grp94 expression in poorly-differentiated colonic cancers with metastasis is significantly higher than well-differentiated cancers without metastasis. The overexpression of HSP70 and grp94 can be used as diagnostic or prognostic markers for colonic cancer.

Investigating epithelial-neuronal signaling contribution in visceral pain through colon organoid-dorsal root ganglion neuron co-cultures

Abdominal pain is a common symptom associated with irritable bowel syndrome and inflammatory bowel diseases(IBDs),affecting about 20%of the global population(Grundy et al.,2019).Current pain therapies are poorly effective on visceral pain of intestinal origin and present several side effects,hence the need to identify novel molecular and cellular targets for drug development.

Clinical outcome and prognostic factors of T4N0M0 colon cancer after R0 resection:A retrospective study

BACKGROUND Paradoxically,patients with T4N0M0(stage II,no lymph node metastasis)colon cancer have a worse prognosis than those with T2N1-2M0(stage III).However,no previous report has addressed this issue.AIM To screen prognostic risk factors for T4N0M0 colon cancer and construct a prognostic nomogram model for these patients.METHODS Two hundred patients with T4N0M0 colon cancer were treated at Tianjin Medical University General Hospital between January 2017 and December 2021,of which 112 patients were assigned to the training cohort,and the remaining 88 patients were assigned to the validation cohort.Differences between the training and validation groups were analyzed.The training cohort was subjected to multi-variate analysis to select prognostic risk factors for T4N0M0 colon cancer,followed by the construction of a nomogram model.RESULTS The 3-year overall survival(OS)rates were 86.2%and 74.4%for the training and validation cohorts,respectively.Enterostomy(P=0.000),T stage(P=0.001),right hemicolon(P=0.025),irregular review(P=0.040),and carbohydrate antigen 199(CA199)(P=0.011)were independent risk factors of OS in patients with T4N0M0 colon cancer.A nomogram model with good concordance and accuracy was constructed.CONCLUSION Enterostomy,T stage,right hemicolon,irregular review,and CA199 were independent risk factors for OS in patients with T4N0M0 colon cancer.The nomogram model exhibited good agreement and accuracy.

Aquaporin 5 in Alzheimer’s disease:a link between oral and brain pathology?

The involvement of aquaporins(AQPs)in the development of diseases has been widely described(Azad et al.,2021).AQP5 has been described in astrocytes changing after traumatic brain injuries(Chai et al.,2013),but the precise role of AQP5 in Alzheimer’s disease(AD)pathology is yet to be understood.We have recently reported that AQP5 expression changes during the development of AD(Antequera et al.,2022).The AQP5 expression in salivary glands is decreased in 6-month-old APP/PS1 mice and AD patients.This decrease in AQP5 expression could be involved in the mechanism of salivary gland dysfunction described in a previous study(Antequera et al.,2021).Now,we propose a new indirect role of AQP5 in the connection between infection-induced oral dysbiosis and AD(Sureda et al.,2020).Here,we suggest that the proinflammatory response induced by oral pathogen infection results in the downregulation of AQP5 contributing to the salivary gland secretory dysfunction.All these alterations destabilize the peripheral immune-inflammatory balance and exacerbate neuroinflammation and neurodegeneration leading to AD pathology.

Why is early detection of colon cancer still not possible in 2023?

Colorectal cancer(CRC)screening is a fundamental tool in the prevention and early detection of one of the most prevalent and lethal cancers.Over the years,screening,particularly in those settings where it is well organized,has succeeded in reducing the incidence of colon and rectal cancer and improving the prognosis related to them.Despite considerable advancements in screening technologies and strategies,the effectiveness of CRC screening programs remains less than optimal.This paper examined the multifaceted reasons behind the persistent lack of effect-iveness in CRC screening initiatives.Through a critical analysis of current methodologies,technological limitations,patient-related factors,and systemic challenges,we elucidated the complex interplay that hampers the successful reduction of CRC morbidity and mortality rates.While acknowledging the ad-vancements that have improved aspects of screening,we emphasized the necessity of addressing the identified barriers comprehensively.This study aimed to raise awareness of how important CRC screening is in reducing costs for this disease.Screening and early diagnosis are not only important in improving the prognosis of patients with CRC but can lead to an important reduction in the cost of treating a disease that is often diagnosed at an advanced stage.Spending more sooner can mean saving money later.