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.

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.

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.

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.

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.

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.

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.

Cavitary Pulmonary Metastases: CT Features and Their Correlation with the Pathology of the Primary Malignancy

Objective: To study CT features of cavitary pulmonary metastases and to investigate the pos- sible relationship between CT features and the pathology of the primary lesions. Methods: CT ?ndings of 131 cavitary metastatic nodules in 40 patients with pathologically-proved pulmonary metastases were retrospectively analyzed. A comparison between CT signs and the pathologic types of the primary tumors was made. Results: Cavitary metastases and multiple solid nodules coexisted in all patients. Cavitary metastases presented as bubble (n=41), irregular (n=33), cystic (n=26) or small circular (n=31) cavities, with even (n=61) or uneven (n=70) thickness of the cavity wall. Of 131 cavitary nodules, diameter less than 15 mm was seen in 44, between 15–25 mm in 66, 25–40 mm in 17 and larger than 40 mm in 4 respectively. And the wall thickness of the cavity below 4 mm, between 4–15 mm and over 15 mm was respectively seen in 69, 44 and 18 metastatic nodules. Cavitary pulmonary metastases mainly occurred in patients whose primary malignancy was squamous cell carcinoma (n=13) or adenocarcinoma (n=22). Both squamous cell carcinoma and adenocarcinoma had its own CT characteristics. The occurrence of cavity bore no relationship to its site in the lung. Conclusion: Cavitary pulmonary metastases carries certain CT features and its occurrence is related to the pathologic type of the primary malignancy.

Prediction of clinically actionable genetic alterations from colorectal cancer histopathology images using deep learning

BACKGROUND Identifying genetic mutations in cancer patients have been increasingly important because distinctive mutational patterns can be very informative to determine the optimal therapeutic strategy. Recent studies have shown that deep learning-based molecular cancer subtyping can be performed directly from the standard hematoxylin and eosin(H&E) sections in diverse tumors including colorectal cancers(CRCs). Since H&E-stained tissue slides are ubiquitously available, mutation prediction with the pathology images from cancers can be a time-and cost-effective complementary method for personalized treatment.AIM To predict the frequently occurring actionable mutations from the H&E-stained CRC whole-slide images(WSIs) with deep learning-based classifiers.METHODS A total of 629 CRC patients from The Cancer Genome Atlas(TCGA-COAD and TCGA-READ) and 142 CRC patients from Seoul St. Mary Hospital(SMH) were included. Based on the mutation frequency in TCGA and SMH datasets, we chose APC, KRAS, PIK3CA, SMAD4, and TP53 genes for the study. The classifiers were trained with 360 × 360 pixel patches of tissue images. The receiver operating characteristic(ROC) curves and area under the curves(AUCs) for all the classifiers were presented.RESULTS The AUCs for ROC curves ranged from 0.693 to 0.809 for the TCGA frozen WSIs and from 0.645 to 0.783 for the TCGA formalin-fixed paraffin-embedded WSIs.The prediction performance can be enhanced with the expansion of datasets. When the classifiers were trained with both TCGA and SMH data, the prediction performance was improved.CONCLUSION APC, KRAS, PIK3CA, SMAD4, and TP53 mutations can be predicted from H&E pathology images using deep learning-based classifiers, demonstrating the potential for deep learning-based mutation prediction in the CRC tissue slides.

Biobanking in the digital pathology era

Digital Pathology is becoming more and more important to achieve the goal of precision medicine.Advances in whole-slide imaging,software integration,and the accessibility of storage solutions have changed the pathologists’clinical practice,not only in terms of laboratory workflow but also for diagnosis and biomarkers analysis.In parallel with the pathology setting advancement,translational medicine is approaching the unprecedented opportunities unrevealed by artificial intelligence(AI).Indeed,the increased usage of biobanks’datasets in research provided new challenges for AI applications,such as advanced algorithms,and computer-aided techniques.In this scenario,machine learning-based approaches are being propose in order to improve biobanks from biospecimens collection repositories to computational datasets.To date,evidence on how to implement digital biobanks in translational medicine is still lacking.This viewpoint article summarizes the currently available literature that supports the biobanks’role in the digital pathology era,and to provide possible practical applications of digital biobanks.

Management of hilar cholangiocarcinoma in the North of England: Pathology, treatment, and outcome

AIM: To assess the management and outcome of hilar cholangiocarcinoma (Klatskin tumor) in a single tertiary referral center.METHODS: The notes of all patients with a diagnosis of hilar cholangiocarcinoma referred to our unit for over an 8-year period were identified and retrospectively reviewed. Presentation, management and outcome were assessed.RESULTS: Seventy-five patients were identified. The median age was 64 years (range 34-84 years). Male to female ratio was 1:1. Eighty-nine percent of patients presented with jaundice. Most patients referred were under Bismuth classification 3a, 3b or 4. Seventy patients required biliary drainage, 65 patients required 152percutaneous drainage procedures, and 25 had other complications. Forty-one patients had 51 endoscopic drainage procedures performed (15 failed). Of these,36 subsequently required percutaneous drainage. The median number of drainage procedures for all patients was three, 18 patients underwent resection (24%), nine had major complications and three died post-operatively.The 5-year survival rate was 4.2% for all patients, 21%for resected patients and 0% for those who did not undergo resection (P = 0.0021). The median number of admissions after diagnosis in resected patients was two and three in non-resected patients (P＜0.05).Twelve patients had external-beam radiotherapy, seven brachytherapy, and eight chemotherapy. There was no significant benefit in terms of survival (P = 0.46) or hospital admissions.CONCLUSION: Resection increases survival but carries the risk of significant morbidity and mortality.Percutaneous biliary drainage is almost always necessary and endoscopic drainage should be avoided if possible.

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.

Histopathology of hepatocellular carcinoma

Hepatocellular carcinoma(HCC)is currently the sixth most common type of cancer with a high mortality rate and an increasing incidence worldwide.Its etiology is usually linked to environmental,dietary or lifestyle factors.HCC most commonly arises in a cirrhotic liver but interestingly an increasing proportion of HCCs develop in the non-fibrotic or minimal fibrotic liver and a shift in the underlying etiology can be observed.Although this process is yet to be completely understood,this changing scenario also has impact on the material seen by pathologists,presenting them with new diagnostic dilemmas.Histopathologic criteria for diagnosing classical,progressed HCC are well established and known,but with an increase in detection of small and early HCCs due to routine screening programs,the diagnosis of these small lesions in core needle biopsies poses a difficult challenge.These lesions can be far more difficult to distinguish from one another than progressed HCC,which is usually a clear cut hematoxylin and eosin diagnosis.Furthermore lesions thought to derive from progenitor cells have recently been reclassified in the WHO.This review summarizes recent developments and tries to put new HCC biomarkers in context with the WHOs reclassification.Furthermore it also addresses the group of tumors known as combined hepatocellular-cholangiocellular carcinomas.

Esophageal mesenchymal tumors:Endoscopy,pathology and immunohistochemistry

AIM： To study the endoscopic, pathological and immunoo histochemical features of esophageal mesenchymal tumors. METHODS： Twenty-nine patients diagnosed as esophageal rnysenchymal tumors by electronic endoscopy and endoscopic ultrasound （EUS） were observed under light microscopes, and all tissues were stained by the immunohistochemical method. The expression of CD117, CD34, SMA and desmin were measured by staining intensity of cells and positive cell ratios. RESULTS： Endoscopically, esophageal gastrointestinal stromal tumors （GISTs） and leiomyomas （LMs） had similar appearances, showing submucosal protuberant lesions. They all showed low echo images originated from the muscularis propria or muscularis mucosa on EUS. Endoscopy and EUS could not exactly differentiate esophageal GISTs from LMs. Microscopically, there were two kinds of cells： spindle cell type and epitheloid cell type in esophageal GISTs. Leiomyomas and leiomyosarcornas were only of spindle cell type. One malignancy was found in five cases of esophageal GISTs, and one malignancy in 24 cases of leiomyomas and leiomyosarcomas. Using Fisher＇s exact method, the differences of malignant lesion proportion were not significant between esophageal LMs and GISTs, 1/5 vs 1/24 （P 〉 0.05）. All cases of esophageal GISTs were positive for CD117, and 3 cases were also positive for CD34. The 24 cases of leiomyomas and leiomyosarcomas were all negative for CD117 and CD34. The differences of positive rates of CD117 and CD34 were significant between esophageal GISTs and LMs, 5/5 vs 0/24, 3/5 vs 0/24 （P 〈 0.005）. All leiomyomas and leiomyosarcomas were positive for SMA, and desmin. Among 5 cases of esophageal GISTs, 2 cases were SMA positive, and 1 case was desmin positive. The differences in positive rates and expression intensity of SMA and desmin were significant between esophageal LMs and GISTs, 24/24 vs 2/5, 24/24 vs 115 （P 〈 0.005）. CONCLUSION： The most common esophageal mesenchymal tumors are leiomyomas, and esophageal GISTs are less common. Most of esophageal LMs and GISTs are benign. Endoscopy and EUS are the effective methods to diagnose esophageal mesenchymal tumors and they can provide useful information for the treatment of these tumors. However, they cannot exactly differentiate esophageal GISTs from LMs. Pathological, especially immunohistochemical features are useful to differentiate GISTs from leiomyomas.

Helicobacter pylori and oral pathology:Relationship with the gastric infection

Helicobacter pylori(H.pylori)has been found in the oral cavity and stomach,and its infection is one of the most frequent worldwide.We reviewed the literature and conducted a Topic Highlight,which identified studies reporting an association between H.pylori-infection in the oral cavity and H.pylori-positive stomach bacterium.This work was designed to determine whether H.pylori is the etiologic agent in periodontal disease,recurrent aphthous stomatitis(RAS),squamous cell carcinoma,burning and halitosis.Record selection focused on the highest quality studies and meta-analyses.We selected 48 articles reporting on the association between saliva and plaque and H.pylori-infection.In order to assess periodontal disease data,we included 12 clinical trials and 1 meta-analysis.We evaluated 13 published articles that addressed the potential association with RAS,and 6 with squamous cell carcinoma.Fourteen publications focused on our questions on burning and halitosis.There is a close relation between H.pylori infection in the oral cavity and the stomach.The mouth is the first extra-gastric reservoir.Regarding the role of H.pylori in the etiology of squamous cell carcinoma,no evidence is still available.

Correlation of MRI-determined small bowel Crohn’s disease categories with medical response and surgical pathology

AIM: To determine whether magnetic resonance imaging (MRI) can be used to categorize small bowel Crohn's disease (SB CD) into groups that correlate with response to medical therapy and surgical pathology.METHODS: Data was collected from all patients with MRI evidence of SB CD without significant colonic disease over a 32-mo period. Two radiologists, blinded to clinical findings, evaluated each MRI and grouped them based on bowel wall thickness and wall enhancement. These categories were: (1) "fibrosis", (2) "mild segmental hyper-enhancement and mild wall thickening", (3) "mild segmental hyper-enhancement and marked wall thickening", (4) "marked segmental transmural hyper-enhancement". Patient response to additional medical therapy post-MRI was prospectively determined at 8-wk. Non-responders underwent endoscopy and were offered therapeutic endoscopy or surgery. Surgical pathology was assessed against the MRI category. RESULTS: Fifty-five patients were included. Females and category "2" patients were more likely, and patients with luminal narrowing and hold-up less likely, to respond to medical therapy (P < 0.05). Seventeen patients underwent surgery. The surgical pathologicalfindings of fibrosis and the severity of inflammation correlated with the MRI category in all cases.CONCLUSION: Our fi ndings suggest that SB CD can be grouped by the MRI f indings and that these groups are associated with patients more likely to respond to continued medical therapy. The MRI categories also correlated with the presence and level of intestinal inflammation and fibrosis on surgical pathology, and may be of prognostic use in the management of CD patients.

Helicobacter pylori and corpus gastric pathology are associated with lower serum ghrelin

AIM To evaluate the association of Helicobacter pylori(H. pylori), cag A genotype, and type of gastric pathology with ghrelin, leptin and nutritional status.METHODS Fasted dyspeptic adults(18-70 years) referred for an upper digestive endoscopy were enrolled in this crosssectional study. Height and weight were assessed for body mass index(BMI) calculation. A sociodemographic survey was administered and nutrient intake was evaluated with 24 h dietary recalls. Serum total ghrelin and leptin levels were analyzed by enzymelinked immunosorbent assay. 13 C-Urea Breath Test was performed and four gastric biopsies were obtained during endoscopy for histopathology and H. pylori DNA amplification and genotyping. Data analysis was performed using χ2, Mann-Whitney U, Kruskal-Wallis tests, Spearman's correlation and linear regression.RESULTS One hundred and sixty-three patients(40.8 ± 14.0 years), 98/65 females/males, were included. Overall, persistent H. pylori prevalence was 53.4%(95%CI: 45.7%-65.8%). Neither nutrient intake nor BMI differed significantly between H. pylori positive and negative groups. Serum ghrelin was significantly lower in infected patients [median 311.0 pg/m L(IQR 230.0-385.5)] than in uninfected ones [median 355.0 pg/m L(IQR 253.8-547.8)](P = 0.025), even after adjusting for BMI and gender(P = 0.03). Ghrelin levels tended to be lower in patients carrying cag A positive strains both in the antrum and the corpus; however, differences with those carrying cag A negative strains did not reach statistical significance(P = 0.50 and P = 0.49, respectively). In addition, the type and severity of gastric pathology in the corpus was associated with lower serum ghrelin(P = 0.04), independently of H.pylori status. Conversely, leptin levels did not differ significantly between infected and uninfected patients [median 1.84 ng/m L(0.80-4.85) vs 1.84 ng/m L(0.50-5.09),(P = 0.51)]. CONCLUSION H. pylori infection and severity of gastric corpus pathology are associated with lower serum ghrelin. Further studies could confirm a lower ghrelin prevalence in cag A-positive patients.

Liver pathology of hepatitis C,beyond grading and stagingof the disease

Liver biopsy evaluation plays a critical role in management of patients with viral hepatitis C. In patients with acute viral hepatitis, a liver biopsy, though uncommonly performed, helps to rule out other nonviral causes of deranged liver function. In chronic viral hepatitis C, it is considered the gold standard in assessment of the degree of necroinflammation and the stage of fibrosis, to help guide treatment and determine prognosis. It also helps rule out any concomitant diseases such as steatohepatitis, hemochromatosis or others. In patients with chronic progressive liver disease with cirrhosis and dominant nodules, a targeted liver biopsy is helpful in differentiating a regenerative nodule from dysplastic nodule or hepatocellular carcinoma. In the setting of transplantation, the liver biopsy helps distinguish recurrent hepatitis C from acute rejection and also is invaluable in the diagnosis of fibrosing cholestatic hepatitis, a rare variant of recurrent hepatitis C. This comprehensive review discusses the entire spectrum of pathologic findings in the course of hepatitis C infection.