TP53 R249S mutation in hepatic organoids captures the predisposing cancer risk.

BACKGROUND AND AIMS: Major genomic drivers of hepatocellular carcinoma (HCC) are nowadays well recognized, although models to establish their roles in human HCC initiation remain scarce. Here, we used human liver organoids in experimental systems to mimic the early stages of human liver carcinogenesis from the genetic lesions of TP53 loss and L3 loop R249S mutation. In addition, chromatin immunoprecipitation sequencing (ChIP-seq) of HCC cell lines shed important functional insights into the initiation of HCC consequential to the loss of tumor-suppressive function from TP53 deficiency and gain-of-function activities from mutant p53. APPROACH AND RESULTS: Human liver organoids were generated from surgical nontumor liver tissues. CRISPR knockout of TP53 in liver organoids consistently demonstrated tumor-like morphological changes, increased in stemness and unrestricted in vitro propagation. To recapitulate TP53 status in human HCC, we overexpressed mutant R249S in TP53 knockout organoids. A spontaneous increase in tumorigenic potentials and bona fide HCC histology in xenotransplantations were observed. ChIP-seq analysis of HCC cell lines underscored gain-of-function properties from L3 loop p53 mutants in chromatin remodeling and overcoming extrinsic stress. More importantly, direct transcriptional activation of PSMF1 by mutant R249S could increase organoid resistance to endoplasmic reticulum stress, which was readily abrogated by PSMF1 knockdown in rescue experiments. In a patient cohort of primary HCC tumors and genome-edited liver organoids, quantitative polymerase chain reaction corroborated ChIP-seq findings and verified preferential genes modulated by L3 mutants, especially those enriched by R249S. CONCLUSIONS: We showed differential tumorigenic effects from TP53 loss and L3 mutations, which together confer normal hepatocytes with early clonal advantages and prosurvival functions.

Steatosis, HBV-related HCC, cirrhosis, and HBsAg seroclearance: A systematic review and meta-analysis.

BACKGROUND AND AIMS: NAFLD and chronic hepatitis B (CHB) infection are common etiologies of HCC. The impact of hepatic steatosis on HCC in CHB, as well as its relationship with the development of cirrhosis, fibrosis, and HBsAg seroclearance, remains controversial. APPROACH AND RESULTS: Data from observational studies were collected through PubMed, EMBASE, and the Cochrane Library from inception to February 1, 2022. Outcomes of interest included the association of hepatic steatosis with HCC, cirrhosis, advanced fibrosis, and HBsAg seroclearance, expressed in terms of pooled ORs. Additional subgroup and sensitivity analyses were performed to validate the robustness of findings. A total of 34 studies with 68,268 patients with CHB were included. Hepatic steatosis was associated with higher odds of HCC (OR, 1.59; 95% CI, 1.12-2.26; I2  = 72.5%), with the association remaining consistent in Asia (OR, 1.56; 95% CI, 1.08-2.25), studies with a median follow-up duration of ≥5 years (OR, 2.82; 95% CI, 1.57-5.08), exclusion of alcohol use (OR, 1.71; 95% CI, 1.01-2.91), and biopsy-proven steatosis (OR, 2.86; 95% CI, 1.61-5.06), although no significant association was noted among nucleos(t)ide analogue-treated patients (OR, 1.05; 95% CI, 0.62-1.77). Steatosis was associated with the development of cirrhosis (OR, 1.52; 95% CI, 1.07-2.16; I2  = 0%) and HBsAg seroclearance (OR, 2.22; 95% CI, 1.58-3.10; I2  = 49.0%). CONCLUSIONS: Hepatic steatosis was associated with an increased risk of HCC and cirrhosis among patients with CHB but with a higher chance of achieving a functional cure, highlighting the importance of identifying concomitant steatosis in CHB.

Performance of continuous controlled attenuation parameter and liver stiffness measurement by the novel SmartExam in metabolic dysfunction-associated steatotic liver disease.

BACKGROUND & AIMS: FibroScan® Expert 630 and FibroScan® Mini+430 are novel vibration-controlled transient elastography devices equipped with the same SmartExam software, which allows continuous measurement of controlled attenuation parameter (CAP) during the entire examination. This study aims to compare the CAP variabilities and the quantification for liver fibrosis and steatosis between the conventional FibroScan and the SmartExam-equipped machines in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). METHODS: This retrospective study included 118 patients with biopsy-proven MASLD who underwent liver biopsy at two tertiary centres between 2021 and 2023. Liver stiffness and steatosis measurements were performed using both FibroScan machines and M and XL probes for each individual. Liver histology was used as the reference standard for liver fibrosis and steatosis staging. RESULTS: Standard deviations of continuous CAP (cCAP) were significantly lower than those of CAP for all probes (p < .0001). CAP variability was significantly associated with body mass index (p < .01), probe selection (p < .001) as well as the random effect of centre. Only the effect of probe selection (p < .001) was significantly associated with cCAP variability. No significant difference was found in the performance of staging liver fibrosis and steatosis between two types of machines at the same cut-offs. CONCLUSIONS: The SmartExam-based VCTE reduces the variability of CAP measurement and achieves a similar accuracy as the FibroScan 502 device for the estimation of both hepatic steatosis and fibrosis. Future studies should determine if cCAP is a better tool to monitor changes in steatosis than the original CAP.

Machine-learning model comprising five clinical indices and liver stiffness measurement can accurately identify MASLD-related liver fibrosis.

BACKGROUND & AIMS: aMAP score, as a hepatocellular carcinoma risk score, is proven to be associated with the degree of chronic hepatitis B-related liver fibrosis. We aimed to evaluate the ability of aMAP score for metabolic dysfunction-associated steatotic liver disease (MASLD; formerly NAFLD)-related fibrosis diagnosis and establish a machine-learning (ML) model to improve the diagnostic performance. METHODS: A total of 946 biopsy-proved MASLD patients from China and the United States were included in the analysis. The aMAP score, demographic/clinical indices and liver stiffness measurement (LSM) were included in seven ML algorithms to build fibrosis diagnostic models in the training set (N = 703). The performance of ML models was evaluated in the external validation set (N = 125). RESULTS: The AUROCs of aMAP versus fibrosis-4 index (FIB-4) and aspartate aminotransferase-platelet ratio (APRI) in cirrhosis and advanced fibrosis were (0.850 vs. 0.857 [P = 0.734], 0.735 [P = 0.001]) and (0.759 vs. 0.795 [P = 0.027], 0.709 [P = 0.049]). When using dual cut-off values, aMAP had a smaller uncertainty area and higher accuracy (26.9%, 86.6%) than FIB-4 (37.3%, 85.0%) and APRI (59.0%, 77.3%) in cirrhosis diagnosis. The seven ML models performed satisfactorily in most cases. In the validation set, the ML model comprising LSM and 5 indices (including age, sex, platelets, albumin and total bilirubin used in aMAP calculator), built by logistic regression algorithm (called LSM-plus model), exhibited excellent performance. In cirrhosis and advanced fibrosis detection, the LSM-plus model had higher accuracy (96.8%, 91.2%) than LSM alone (86.4%, 67.2%) and Agile score (76.0%, 83.2%), respectively. Additionally, the LSM-plus model also displayed high specificity (cirrhosis: 98.3%; advanced fibrosis: 92.6%) with satisfactory AUROC (0.932, 0.875, respectively) and sensitivity (88.9%, 82.4%, respectively). CONCLUSIONS: The aMAP score is capable of diagnosing MASLD-related fibrosis. The LSM-plus model could accurately identify MASLD-related cirrhosis and advanced fibrosis.

Aspiration cytology of liver abscess uncovering metastatic rectal mucosal melanoma-A case report.

Aspirates of liver abscess are frequently encountered in routine practice and are often of a low index of suspicion. However, necrotic liver metastasis clinically and radiologically mimics liver abscesses, and malignant cells can be obscured in an inflammation-rich background on cytology. It is important to recognise malignant neoplasms in this scenario, in particular uncommon conditions such as metastatic mucosal melanoma.

Consensus statements on endoscopic ultrasound-guided tissue acquisition. Guidelines from the Asian Endoscopic Ultrasound Group.

OBJECTIVES: This consensus was developed by the Asian EUS Group (AEG), who aimed to formulate a set of practice guidelines addressing various aspects of endoscopic ultrasound-guided tissue acquisition (EUS-TA). METHODS: The AEG initiated the development of consensus statements and formed an expert panel comprising surgeons, gastroenterologists, and pathologists. Three online consensus meetings were conducted to consolidate the statements and votes. The statements were presented and discussed in the first two consensus meetings and revised according to comments. Final voting was conducted at a third consensus meeting. The Grading of Recommendations, Assessment, Development, and Evaluation system was adopted to define the strength of the recommendations and quality of evidence. RESULTS: A total of 20 clinical questions and statements regarding EUS-TA were formulated. The committee recommended that fine-needle biopsy (FNB) needles be preferred over conventional fine-needle aspiration (FNA) needles for EUS-TA of subepithelial lesions. For solid pancreatic masses, rapid on-site evaluation is not routinely recommended when FNB needles are used. For dedicated FNB needles, fork-tip and Franseen-tip needles have essentially equivalent performance. CONCLUSION: This consensus provides guidance for EUS-TA, thereby enhancing the quality of EUS-TA.

Targeting PPAR-gamma counteracts tumour adaptation to immune-checkpoint blockade in hepatocellular carcinoma.

OBJECTIVE: Therapy-induced tumour microenvironment (TME) remodelling poses a major hurdle for cancer cure. As the majority of patients with hepatocellular carcinoma (HCC) exhibits primary or acquired resistance to antiprogrammed cell death (ligand)-1 (anti-PD-[L]1) therapies, we aimed to investigate the mechanisms underlying tumour adaptation to immune-checkpoint targeting. DESIGN: Two immunotherapy-resistant HCC models were generated by serial orthotopic implantation of HCC cells through anti-PD-L1-treated syngeneic, immunocompetent mice and interrogated by single-cell RNA sequencing (scRNA-seq), genomic and immune profiling. Key signalling pathway was investigated by lentiviral-mediated knockdown and pharmacological inhibition, and further verified by scRNA-seq analysis of HCC tumour biopsies from a phase II trial of pembrolizumab (NCT03419481). RESULTS: Anti-PD-L1-resistant tumours grew >10-fold larger than parental tumours in immunocompetent but not immunocompromised mice without overt genetic changes, which were accompanied by intratumoral accumulation of myeloid-derived suppressor cells (MDSC), cytotoxic to exhausted CD8+ T cell conversion and exclusion. Mechanistically, tumour cell-intrinsic upregulation of peroxisome proliferator-activated receptor-gamma (PPARγ) transcriptionally activated vascular endothelial growth factor-A (VEGF-A) production to drive MDSC expansion and CD8+ T cell dysfunction. A selective PPARγ antagonist triggered an immune suppressive-to-stimulatory TME conversion and resensitised tumours to anti-PD-L1 therapy in orthotopic and spontaneous HCC models. Importantly, 40% (6/15) of patients with HCC resistant to pembrolizumab exhibited tumorous PPARγ induction. Moreover, higher baseline PPARγ expression was associated with poorer survival of anti-PD-(L)1-treated patients in multiple cancer types. CONCLUSION: We uncover an adaptive transcriptional programme by which tumour cells evade immune-checkpoint targeting via PPARγ/VEGF-A-mediated TME immunosuppression, thus providing a strategy for counteracting immunotherapeutic resistance in HCC.

aMAP Score and Its Combination With Liver Stiffness Measurement Accurately Assess Liver Fibrosis in Chronic Hepatitis B Patients.

BACKGROUND & AIMS: The changes in liver stiffness measurement (LSM) are unreliable to estimate regression of fibrosis during antiviral treatment for chronic hepatitis B (CHB) patients. The age-male-albumin-bilirubin-platelets score (aMAP), as an accurate hepatocellular carcinoma risk score, may reflect the liver fibrosis stage. Here, we aimed to evaluate the performance of aMAP for diagnosing liver fibrosis in CHB patients with or without treatment. METHODS: A total of 2053 patients from 2 real-world cohorts and 2 multicentric randomized controlled trials in China were enrolled, among which 2053 CHB patients were included in the cross-sectional analysis, and 889 CHB patients with paired liver biopsies before and after 72 or 104 weeks of treatment were included in the longitudinal analysis. RESULTS: In the cross-sectional analysis, the areas under the receiver operating characteristic curve of aMAP in diagnosing cirrhosis and advanced fibrosis were 0.788 and 0.757, which were comparable with or significantly higher than those of the fibrosis index based on 4 factors and the aspartate aminotransferase-platelet ratio. The stepwise approach using aMAP and LSM further improved performance in detecting cirrhosis and advanced fibrosis with the smallest uncertainty area (29.7% and 46.2%, respectively) and high accuracy (82.3% and 79.8%, respectively). In the longitudinal analysis, we established a novel model (aMAP-LSM model) by calculating aMAP and LSM results before and after treatment, which had satisfactory performance in diagnosing cirrhosis and advanced fibrosis after treatment (area under the receiver operating characteristic curve, 0.839 and 0.840, respectively), especially for those with a significant decrease in LSM after treatment (vs LSM alone, 0.828 vs 0.748; P < .001 [cirrhosis]; 0.825 vs 0.750; P < .001 [advanced fibrosis]). CONCLUSIONS: The aMAP score is a promising noninvasive tool for diagnosing fibrosis in CHB patients. The aMAP-LSM model could accurately estimate fibrosis stage for treated CHB patients.

Detecting Early-Stage Liver Fibrosis Using Macromolecular Proton Fraction Mapping Based on Spin-Lock MRI: Preliminary Observations.

BACKGROUND: Liver fibrosis is characterized by macromolecule depositions. Recently, a novel technology termed macromolecular proton fraction quantification based on spin-lock magnetic resonance imaging (MPF-SL) is reported to measure macromolecule levels. HYPOTHESIS: MPF-SL can detect early-stage liver fibrosis by measuring macromolecule levels in the liver. STUDY TYPE: Retrospective. SUBJECTS: Fifty-five participants, including 22 with no fibrosis (F0) and 33 with early-stage fibrosis (F1-2), were recruited. FIELD STRENGTH/SEQUENCE: 3 T; two-dimensional (2D) MPF-SL turbo spin-echo sequence, 2D spin-lock T1rho turbo spin-echo sequence, and multi-slice 2D gradient echo sequence. ASSESSMENT: Macromolecular proton fraction (MPF), T1rho, liver iron concentration (LIC), and fat fraction (FF) biomarkers were quantified within regions of interest. STATISTICAL TESTS: Group comparison of the biomarkers using Mann-Whitney U tests; correlation between the biomarkers assessed using Spearman's rank correlation coefficient and linear regression with goodness-of-fit; fibrosis stage differentiation using receiver operating characteristic curve (ROC) analysis. P-value < 0.05 was considered statistically significant. RESULTS: Average T1rho was 41.76 ± 2.94 msec for F0 and 41.15 ± 3.73 msec for F1-2 (P = 0.60). T1rho showed nonsignificant correlation with either liver fibrosis (ρ = -0.07; P = 0.61) or FF (ρ = -0.14; P = 0.35) but indicated a negative correlation with LIC (ρ = -0.66). MPF was 4.73 ± 0.45% and 5.65 ± 0.81% for F0 and F1-2 participants, respectively. MPF showed a positive correlation with liver fibrosis (ρ = 0.59), and no significant correlations with LIC (ρ = 0.02; P = 0.89) or FF (ρ = 0.05; P = 0.72). The area under the ROC curve was 0.85 (95% confidence interval [CI] 0.75-0.95) and 0.55 (95% CI 0.39-0.71; P = 0.55) for MPF and T1rho to discriminate between F0 and F1-2 fibrosis, respectively. DATA CONCLUSION: MPF-SL has the potential to diagnose early-stage liver fibrosis and does not appear to be confounded by either LIC or FF. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 3.

Unique molecular characteristics of NAFLD-associated liver cancer accentuate ß-catenin/TNFRSF19-mediated immune evasion.

BACKGROUND & AIMS: The hepatic manifestation of the metabolic syndrome, non-alcoholic fatty liver disease (NAFLD), can lead to the development of hepatocellular carcinoma (HCC). Despite a strong causative link, NAFLD-HCC is often underrepresented in systematic genome explorations. METHODS: Herein, tumor-normal pairs from 100 patients diagnosed with NAFLD-HCC were subject to next-generation sequencing. Bioinformatic analyses were performed to identify key genomic, epigenomic and transcriptomic events associated with the pathogenesis of NAFLD-HCC. Establishment of primary patient-derived NAFLD-HCC culture was used as a representative human model for downstream in vitro investigations of the underlying CTNNB1 S45P driver mutation. A syngeneic immunocompetent mouse model was used to further test the involvement of CTNNB1mutand TNFRSF19 in reshaping the tumor microenvironment. RESULTS: Mutational processes operative in the livers of patients with NAFLD inferred susceptibility to tumor formation through defective DNA repair pathways. Dense promoter mutations and dysregulated transcription factors accentuated activated transcriptional regulation in NAFLD-HCC, in particular the enrichment of MAZ-MYC activities. Somatic events common in HCCs arising from NAFLD and viral hepatitis B infection underscore similar driver pathways, although an incidence shift highlights CTNNB1mut dominance in NAFLD-HCC (33%). Immune exclusion correlated evidently with CTNNB1mut. Chromatin immunoprecipitation-sequencing integrated with transcriptome and immune profiling revealed a unique transcriptional axis, wherein CTNNB1mut leads to an upregulation of TNFRSF19 which subsequently represses senescence-associated secretory phenotype-like cytokines (including IL6 and CXCL8). This phenomenon could be reverted by the Wnt-modulator ICG001. CONCLUSIONS: The unique mutational processes in the livers of patients with NAFLD and NAFLD-HCC allude to a "field effect" involving a gain-of-function role of CTNNB1 mutations in immune exclusion. LAY SUMMARY: The increasing prevalence of metabolic syndrome in adult populations means that NAFLD is poised to be the major cause of liver cancer in the 21st century. We showed a strong "field effect" in the livers of patients with NAFLD, wherein activated ß-catenin was involved in reshaping the tumor-immune microenvironment.

Nestin as a diagnostic and prognostic marker for combined hepatocellular-cholangiocarcinoma.

BACKGROUND & AIMS: Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is a rare primary liver cancer (PLC) associated with a poor prognosis. Given the challenges in its identification and its clinical implications, biomarkers are critically needed. We aimed to investigate the diagnostic and prognostic value of the immunohistochemical expression of Nestin, a progenitor cell marker, in a large multicentric series of PLCs. METHODS: We collected 461 cHCC-CCA samples from 32 different clinical centers. Control cases included 368 hepatocellular carcinomas (HCCs) and 221 intrahepatic cholangiocarcinomas (iCCAs). Nestin immunohistochemistry was performed on whole tumor sections. Diagnostic and prognostic performances of Nestin expression were determined using receiver-operating characteristic curves and Cox regression modeling. RESULTS: Nestin was able to distinguish cHCC-CCA from HCC with AUCs of 0.85 and 0.86 on surgical and biopsy samples, respectively. Performance was lower for the distinction of cHCC-CCA from iCCA (AUCs of 0.59 and 0.60). Nestin, however, showed a high prognostic value, allowing identification of the subset of cHCC-CCA ("Nestin High", >30% neoplastic cells with positive staining) associated with the worst clinical outcome (shorter disease-free and overall survival) after surgical resection and liver transplantation, as well as when assessment was performed on biopsies. CONCLUSION: We show in different clinical settings that Nestin has diagnostic value and that it is a useful biomarker to identify the subset of cHCC-CCA associated with the worst clinical outcome. Nestin immunohistochemistry may be used to refine risk stratification and improve treatment allocation for patients with this highly aggressive malignancy. LAY SUMMARY: There are different types of primary liver cancers (i.e. cancers that originate in the liver). Accurately identifying a specific subtype of primary liver cancer (and determining its associated prognosis) is important as it can have a major impact on treatment allocation. Herein, we show that a protein called Nestin could be used to refine risk stratification and improve treatment allocation for patients with combined hepatocellular carcinoma, a rare but highly aggressive subtype of primary liver cancer.

Association of genetic variations with NAFLD in lean individuals.

BACKGROUND & AIMS: How adiposity influences the effect of genetic variants on non-alcoholic fatty liver disease (NAFLD) in the Asian population remains unclear. We aimed to study the association between genetic risk variants and susceptibility/severity of NAFLD in the lean, overweight and obese individuals. METHODS: Nine hundred and four community subjects underwent proton-magnetic resonance spectroscopy and transient elastography examination. Lean (<23 kg/m2 ), overweight (23-24.9 kg/m2 ) and obesity (≥25 kg/m2 ) were defined according to the body mass index cut-offs for Asians. NAFLD was defined as intrahepatic triglycerides ≥5%. PNPLA3, TM6SF2, MBOAT7 and 9 other gene polymorphisms were analysed by rhAMPTM SNP assays. RESULTS: Five hundred and twenty-nine (58.5%), 162 (17.9%) and 213 (23.6%) subjects were lean, overweight and obese, respectively. The prevalence of NAFLD was 12.4%, 41.4% and 59.1% in the three groups (P < .001). Amongst those with NAFLD, lean subjects (30.3%) were more likely to carry the PNPLA3 rs738409 GG genotype than overweight (17.9%) and obese subjects (17.4%) (P = .003). Compared with the CC genotype, the GG genotype was associated with the greatest increase in the risk of NAFLD in lean subjects (odds ratio [OR] 6.04), compared with overweight (OR 3.43, 95% CI [1.06, 11.14]) and obese subjects (OR 2.51, 95% CI [0.93, 6.78]). Additionally, the TM6SF2 rs58542926 TT genotype was associated with reduced serum triglycerides only in lean subjects. A gene-BMI effect was not observed for the other gene polymorphisms. CONCLUSIONS: The PNPLA3 rs738409 gene polymorphism has a greater effect on liver fat in Asian lean individuals than in overweight or obese ones.

Reliability of the nonalcoholic steatohepatitis clinical research network and steatosis activity fibrosis histological scoring systems.

BACKGROUND AND AIM: We aimed to determine whether lobular inflammation and ballooning grades in the Non-alcoholic Steatohepatitis Clinical Research Network (NASH CRN) scoring system can be directly translated into the same for the Steatosis Activity Fibrosis scoring system (SAF) and to look at intra-observer and inter-observer agreement for each individual histological component and for diagnosis of non-alcoholic steatohepatitis (NASH) using the two scoring systems. METHODS: Four pathologists from two Asian centers scored 20 digitalized slides, twice using the NASH CRN, twice using the SAF. Intra-observer and inter-observer agreement was analyzed using Fleiss' kappa, weighted kappa, or Cohen kappa, where appropriate. RESULTS: The intra-observer discrepancy rate when using the NASH CRN compared with the SAF was higher than when using the individual scoring system for lobular inflammation (15% comparing both scoring systems vs 10% and 1.8% for the NASH CRN and the SAF, respectively) and hepatocyte ballooning (33.8% vs 12.5% and 5%, respectively), but not for diagnosis of NASH (6.3% vs 6.3% and 0%, respectively). Intra-observer and inter-observer agreement was substantial to almost perfect, except for inter-observer agreement for lobular inflammation and diagnosis of NASH, which was only fair to moderate in most instances. CONCLUSION: These findings do not support the direct inter-translation between the NASH CRN and the SAF. However, the diagnosis of NASH during examinations using the NASH CRN may be comparable with diagnosis of NASH using the SAF, vice versa. The inter-observer agreement for lobular inflammation and NASH diagnosis needs to be improved.

A Two-stream Convolutional Network for Musculoskeletal and Neurological Disorders Prediction.

Musculoskeletal and neurological disorders are the most common causes of walking problems among older people, and they often lead to diminished quality of life. Analyzing walking motion data manually requires trained professionals and the evaluations may not always be objective. To facilitate early diagnosis, recent deep learning-based methods have shown promising results for automated analysis, which can discover patterns that have not been found in traditional machine learning methods. We observe that existing work mostly applies deep learning on individual joint features such as the time series of joint positions. Due to the challenge of discovering inter-joint features such as the distance between feet (i.e. the stride width) from generally smaller-scale medical datasets, these methods usually perform sub-optimally. As a result, we propose a solution that explicitly takes both individual joint features and inter-joint features as input, relieving the system from the need of discovering more complicated features from small data. Due to the distinctive nature of the two types of features, we introduce a two-stream framework, with one stream learning from the time series of joint position and the other from the time series of relative joint displacement. We further develop a mid-layer fusion module to combine the discovered patterns in these two streams for diagnosis, which results in a complementary representation of the data for better prediction performance. We validate our system with a benchmark dataset of 3D skeleton motion that involves 45 patients with musculoskeletal and neurological disorders, and achieve a prediction accuracy of 95.56%, outperforming state-of-the-art methods.

Artificial intelligence in prediction of non-alcoholic fatty liver disease and fibrosis.

Artificial intelligence (AI) has become increasingly widespread in our daily lives, including healthcare applications. AI has brought many new insights into better ways we care for our patients with chronic liver disease, including non-alcoholic fatty liver disease and liver fibrosis. There are multiple ways to apply the AI technology on top of the conventional invasive (liver biopsy) and noninvasive (transient elastography, serum biomarkers, or clinical prediction models) approaches. In this review article, we discuss the principles of applying AI on electronic health records, liver biopsy, and liver images. A few common AI approaches include logistic regression, decision tree, random forest, and XGBoost for data at a single time stamp, recurrent neural networks for sequential data, and deep neural networks for histology and images.

Computerised Handwriting Speed Test System (CHSTS): Validation of a handwriting assessment for Chinese secondary students.

BACKGROUND/AIM: Handwriting difficulties can be detrimental to students' performance in school tests and even in public examinations. It is crucial for school-based occupational therapists to identify students with handwriting difficulties and support them with appropriate adaptive strategies. The purpose of this study is to validate a computerised assessment - the Computerised Handwriting Speed Test System (CHSTS) of both Chinese and English handwriting for Chinese secondary students and provide an objective reference for extra time allowance in paper-based examinations. METHODS: The internal consistency, test-retest reliability, convergent and discriminant validity of CHSTS were examined using the data from 512 typically developing students and 64 students with special educational needs (SEN) in Hong Kong mainstream secondary schools. RESULTS: Handwriting performance of senior students was better than that of junior students. High internal consistency was shown by over 0.80 Cronbach's α in all measurement items and over 0.90 item-total correlations in temporal domain items. Intra-class correlation indicated good to excellent test-retest reliability of CHSTS (all P < 0.0001). Principal Component Analysis revealed that four components in CHSTS accounted for over 80% of the variance. Handwriting performance was positively associated with manual coordination, automaticity and oculomotor control (all P < 0.05) in linear regression analyses. Students with SEN could be effectively differentiated from typically developing students (over 75% sensitivity and specificity) based on the CHSTS items. CONCLUSION: Validation of CHSTS is the groundwork for identifying students with handwriting difficulties and providing adaptive strategies including fair special examination arrangements for these students.

Deep Spatio-Temporal Network for Low SNR Cryo-EM Movie Frame Enhancement.

Cryo-EM in single particle analysis is known to have low SNR and requires to utilize several frames of the same particle sample to restore one high-quality image for visualizing that particle. However, the low SNR of cryo-EM movie and motion caused by beam striking make the task very challenging. Video enhancement algorithms in computer vision shed new light on tackling such tasks by utilizing deep neural networks. However, they are designed for natural images with high SNR. Meanwhile, the lack of ground truth in cryo-EM movie seems to be one major limiting factor of the progress. Hence, we present a synthetic cryo-EM movie generation pipeline, which can produce realistic diverse cryo-EM movie datasets with low-SNR movie frames and multiple ground truth values. Then we propose a deep spatio-temporal network (DST-Net) for cryo-EM movie frame enhancement trained on our synthetic data. Spatial and temporal features are first extracted from each frame. Spatio-temporal fusion and high-resolution re-constructor are designed to obtain the enhanced output. For evaluation, we train our model on seven synthetic cryo-EM movie datasets and infer on real cryo-EM data. The experimental results show that DST-Net can achieve better enhancement performance both quantitatively and qualitatively compared with others.

PPP1R15A-expressing monocytic MDSCs promote immunosuppressive liver microenvironment in fibrosis-associated hepatocellular carcinoma.

Background & Aims: Recent studies demonstrated the importance of fibrosis in promoting an immunosuppressive liver microenvironment and thereby aggressive hepatocellular carcinoma (HCC) growth and resistance to immune checkpoint blockade (ICB), particularly via monocyte-to-monocytic myeloid-derived suppressor cell (M-MDSC) differentiation triggered by hepatic stellate cells (HSCs). We thus aimed to identify druggable targets in these immunosuppressive myeloid cells for HCC therapy. Methods: M-MDSC signature genes were identified by integrated transcriptomic analysis of a human HSC-monocyte culture system and tumor-surrounding fibrotic livers of patients with HCC. Mechanistic and functional studies were conducted using in vitro-generated and patient-derived M-MDSCs. The therapeutic efficacy of a M-MDSC targeting approach was determined in fibrosis-associated HCC mouse models. Results: We uncovered over-expression of protein phosphatase 1 regulatory subunit 15A (PPP1R15A), a myeloid cell-enriched endoplasmic reticulum stress modulator, in human M-MDSCs that correlated with poor prognosis and ICB non-responsiveness in patients with HCC. Blocking TGF-ß signaling reduced PPP1R15A expression in HSC-induced M-MDSCs, whereas treatment of monocytes by TGF-ß upregulated PPP1R15A, which in turn promoted ARG1 and S100A8/9 expression in M-MDSCs and reduced T-cell proliferation. Consistently, lentiviral-mediated knockdown of Ppp1r15a in vivo significantly reduced ARG1+S100A8/9+ M-MDSCs in fibrotic liver, leading to elevated intratumoral IFN-γ+GZMB+CD8+ T cells and enhanced anti-tumor efficacy of ICB. Notably, pharmacological inhibition of PPP1R15A by Sephin1 reduced the immunosuppressive potential but increased the maturation status of fibrotic HCC patient-derived M-MDSCs. Conclusions: PPP1R15A+ M-MDSC cells are involved in immunosuppression in HCC development and represent a novel potential target for therapies. Impact and implications: Our cross-species analysis has identified PPP1R15A as a therapeutic target governing the anti-T-cell activities of fibrosis-associated M-MDSCs (monocytic myeloid-derived suppressor cells). The results from the preclinical models show that specific inhibition of PPP1R15A can break the immunosuppressive barrier to restrict hepatocellular carcinoma growth and enhance the efficacy of immune checkpoint blockade. PPP1R15A may also function as a prognostic and/or predictive biomarker in patients with hepatocellular carcinoma.

M-Denoiser: Unsupervised image denoising for real-world optical and electron microscopy data.

Real-world microscopy data have a large amount of noise due to the limited light/electron that can be used to capture images. The noise of microscopy data is composed of signal-dependent shot noise and signal-independent read noise, and the Poisson-Gaussian noise model is usually used to describe the noise distribution. Meanwhile, the noise is spatially correlated because of the data acquisition process. Due to the lack of clean ground truth, unsupervised and self-supervised denoising algorithms in computer vision shed new light on tackling such tasks by utilizing paired noisy images or one single noisy image. However, they usually make the assumption that the noise is signal-independent or pixel-wise independent, which contradicts with the actual case. Hence, we propose M-Denoiser for denoising real-world microscopy data in an unsupervised manner. Firstly, the shatter module is used to break the dependency and correlation before denoising. Secondly, a novelly designed unsupervised training loss based on a pair of noisy images is proposed for real-world microscopy data. For evaluation, we train our model on optical and electron microscopy datasets. The experimental results show that M-Denoiser achieves the best performance both quantitatively and qualitatively compared with all the baselines.