A metabolome-derived score predicts metabolic dysfunction-associated steatohepatitis and mortality from liver disease.

BACKGROUND: Metabolic dysfunction-associated steatohepatitis (MASH) is associated with more than a 10-fold increase in liver-related mortality. However, biomarkers predicting both MASH and mortality are missing. We developed a metabolome-derived prediction score for MASH and examined whether it predicts mortality in Chinese and European cohorts. METHODS: The MASH prediction score was developed using a multi-step machine learning strategy, based on 44 clinical parameters and 250 plasma metabolites measured by proton nuclear magnetic resonance (1H-NMR) in 311 Chinese adults undergoing a liver biopsy. External validation was conducted in a Finnish liver biopsy cohort (n=305). We investigated association of the score with all-cause and cause-specific mortality in the population-based Shanghai Changfeng Study (n=5,893) and the UK Biobank (n=111,673). RESULTS: A total of 24 clinical parameters and 194 1H-NMR metabolites were significantly associated with MASH in the Chinese liver biopsy cohort. The final MASH score included body mass index, aspartate transaminase, tyrosine, and the phospholipids-to-total lipids ratio in very-low density lipoprotein. The score identified patients with MASH with AUROCs of 0.87 (95% CI, 0.83-0.91) and 0.81 (95% CI, 0.75-0.87) in the Chinese and Finnish cohorts, with high negative predictive values. Participants with a high or intermediate risk of MASH based on the score had a markedly higher risk of MASLD-related mortality than those with a low risk in Chinese (HR, 23.19; 95%CI, 4.80-111.97) and European individuals (HR, 27.80; 95%CI, 15.08-51.26) after 7.4 and 12.6 years of follow-up. The MASH prediction score was superior to the FIB-4 index and the NAFLD Fibrosis Score in predicting MASLD-related mortality. CONCLUSION: The metabolome-derived MASH prediction score accurately predicts risk of MASH and MASLD-related mortality in both Chinese and European individuals. IMPACT AND IMPLICATIONS: Metabolic dysfunction-associated steatohepatitis (MASH) is associated with more than a 10-fold increase in liver-related death. However, biomarkers predicting not only MASH, but also death due to liver disease, are missing. We established a MASH prediction score based on 44 clinical parameters and 250 plasma metabolites using a machine learning strategy. This metabolome-derived MASH prediction score could accurately identify patients with MASH among both Chinese and Finnish individuals, and it was superior to the FIB-4 index and the NAFLD Fibrosis Score in predicting MASLD-related death in the general population. Thus, the new MASH prediction score is a useful tool for identifying individuals with a markedly increased risk of serious liver-related outcomes among at-risk and general populations.

Reconstructing rapid natural vision with fMRI-conditional video generative adversarial network.

Recent functional magnetic resonance imaging (fMRI) studies have made significant progress in reconstructing perceived visual content, which advanced our understanding of the visual mechanism. However, reconstructing dynamic natural vision remains a challenge because of the limitation of the temporal resolution of fMRI. Here, we developed a novel fMRI-conditional video generative adversarial network (f-CVGAN) to reconstruct rapid video stimuli from evoked fMRI responses. In this model, we employed a generator to produce spatiotemporal reconstructions and employed two separate discriminators (spatial and temporal discriminators) for the assessment. We trained and tested the f-CVGAN on two publicly available video-fMRI datasets, and the model produced pixel-level reconstructions of 8 perceived video frames from each fMRI volume. Experimental results showed that the reconstructed videos were fMRI-related and captured important spatial and temporal information of the original stimuli. Moreover, we visualized the cortical importance map and found that the visual cortex is extensively involved in the reconstruction, whereas the low-level visual areas (V1/V2/V3/V4) showed the largest contribution. Our work suggests that slow blood oxygen level-dependent signals describe neural representations of the fast perceptual process that can be decoded in practice.

First case report of pustules associated with Escherichia fergusonii in the chinese pangolin (Manis pentadactyla aurita).

BACKGROUND: Escherichia fergusonii is a common conditionally pathogenic bacterium that infects humans and animals. E. fergusonii has been reported to cause diarrhea, respiratory disease, and septicemia, but it is rarely reported to cause skin infections in animals. E. fergusonii has been isolated from the skin and muscular tissue of Chinese pangolin (Manis pentadactyla aurita). To date, there have been no reports of Chinese pangolins with clinical signs of skin diseases. CASE PRESENTATION: This case report describes the clinical case of a subadult (bodyweight: 1.1 kg) female Chinese pangolin from wild rescue with pustules and subcutaneous suppurative infection due to E. fergusonii in the abdominal skin. Bacterial culture, Biochemical analysis, PCR and histopathology were utilized to identify the bacteria in the pustule puncture fluid and infected tissue. To the best of our knowledge, this is the first report of E. fergusonii-related pustules on a Chinese pangolin. CONCLUSION: This case report presents the first observed skin infection in a Chinese pangolin. E. fergusonii infection should be considered as a possible differential diagnosis of pustules and subcutaneous suppurative skin conditions in Chinese pangolins, and we also provide several recommendations for the diagnosis and treatment of this disease.

Ascomylactam C Induces an Immunogenic Cell Death Signature via Mitochondria-Associated ER Stress in Lung Cancer and Melanoma.

Ascomylactam C (AsC) is a new 13-membered-ring macrocyclic alkaloid, which was first isolated and identified in 2019 from the secondary metabolites of the mangrove endophytic fungus Didymella sp. CYSK-4 in the South China Sea. AsC has been found to have a broad-spectrum cytotoxic activity. However, the antitumor effects in vivo and mechanisms of AsC remain unclear. The aim of this study was to describe the effects of AsC on lung cancer and melanoma cells and to explore the antitumor molecular mechanism of AsC. In vitro, we used plate colony formation experiments and demonstrated the ability of AsC to inhibit low-density tumor growth. An Annexin V/PI cell apoptosis detection experiment revealed that AsC induced tumor cell apoptosis. In vivo, AsC suppressed the tumor growth of LLC and B16F10 allograft significantly in mice, and promoted the infiltration of CD4+ T and CD8+ T cells in tumor tissues. Mechanistically, by analyses of Western blotting, immunofluorescence and ELISA analysis, we found that AsC increased ROS formation, induced endoplasmic reticulum (ER) stress, activated the protein kinase RNA-like ER kinase (PERK)/eukaryotic translation initiation factor (eIF2α)/activating transcription factor 4 (ATF4)/C/EBP homologous protein (CHOP) signaling pathway, and induced immunogenic cell death (ICD) of tumor cells. Our results suggest that AsC may be a potentially promising antitumor drug candidate.

An artificial intelligence-based risk prediction model of myocardial infarction.

BACKGROUND: Myocardial infarction can lead to malignant arrhythmia, heart failure, and sudden death. Clinical studies have shown that early identification of and timely intervention for acute MI can significantly reduce mortality. The traditional MI risk assessment models are subjective, and the data that go into them are difficult to obtain. Generally, the assessment is only conducted among high-risk patient groups. OBJECTIVE: To construct an artificial intelligence-based risk prediction model of myocardial infarction (MI) for continuous and active monitoring of inpatients, especially those in noncardiovascular departments, and early warning of MI. METHODS: The imbalanced data contain 59 features, which were constructed into a specific dataset through proportional division, upsampling, downsampling, easy ensemble, and w-easy ensemble. Then, the dataset was traversed using supervised machine learning, with recursive feature elimination as the top-layer algorithm and random forest, gradient boosting decision tree (GBDT), logistic regression, and support vector machine as the bottom-layer algorithms, to select the best model out of many through a variety of evaluation indices. RESULTS: GBDT was the best bottom-layer algorithm, and downsampling was the best dataset construction method. In the validation set, the F1 score and accuracy of the 24-feature downsampling GBDT model were both 0.84. In the test set, the F1 score and accuracy of the 24-feature downsampling GBDT model were both 0.83, and the area under the curve was 0.91. CONCLUSION: Compared with traditional models, artificial intelligence-based machine learning models have better accuracy and real-time performance and can reduce the occurrence of in-hospital MI from a data-driven perspective, thereby increasing the cure rate of patients and improving their prognosis.

A novel model for detecting advanced fibrosis in patients with nonalcoholic fatty liver disease.

AIMS: The study aimed to develop a novel noninvasive model to detect advanced fibrosis based on routinely available clinical and laboratory tests. MATERIALS AND METHODS: A total of 309 patients who underwent liver biopsy were randomly divided into the estimation group (n = 201) and validation group (n = 108). The model was developed using multiple regression analysis in the estimation group and further verified in the validation group. Diagnostic accuracy was evaluated using the receiver operating characteristic (ROC) curve. RESULTS: The model was named NAFLD Fibrosis Index (NFI): -10.844 + 0.046 × age - 0.01 × platelet count + 0.19 × 2h postprandial plasma glucose (PG) + 0.294 × conjugated bilirubin - 0.015 × ALT + 0.039 × AST + 0.109 × total iron binding capacity -0.033 × parathyroid hormone (PTH). The area under the ROC curve (AUC) of NFI was 0.86 (95% CI: 0.79-0.93, p < 0.001) in the estimation group and 0.80 (95% CI: 0.69-0.91, p < 0.001) in the validation group, higher than NFS, FIB4, APRI, and BARD, and similar to FibroScan (NFI AUC = 0.77, 95% CI: 0.66-0.89, p = 0.001 vs. FibroScan AUC = 0.76, 95% CI: 0.62-0.90, p = 0.002). By applying the low cut-off value (-2.756), advanced fibrosis could be excluded among 49.3% and 48% of patients in the estimation group (sensitivity: 93.1%, NPV: 97.9%, specificity: 55.2%, and PPV: 26.0%) and validation group (sensitivity: 81.3%, NPV: 94.2%, specificity: 53.3%, and PPV: 23.2%), respectively, allowing them to avoid liver biopsy. CONCLUSIONS: The study has established a novel model for advanced fibrosis, the diagnostic accuracy of which is superior to the current clinical scoring systems and is similar to FibroScan.

Protective Effect of Casticin on Experimental Skin Wound Healing of Rats.

INTRODUCTION: The wound is known as damage to the skin structure by external stimuli, such as cut, bruises, and burn, which typically leaves the internal tissue exposed. The wound repair process when hampered leads to an excessive burden on the healthcare setting. Therefore, there is an urgent need to develop effective agents that can promote the wound healing process. In the present study, we intended to investigate the pharmacological benefit of Casticin (CST), a polymethylflavone against wound. METHODS: The wound in Wistar rats was induced by a surgical procedure. After surgery, the wound was examined for wound size over a period and for the expression of cyclooxygenase-2 and induced collagen III expressions. The effect of CST was examined on tumor necrosis factor α, interferon gamma, interleukin (IL)-10, transforming growth factor beta, and IL-7 by real-time polymerase chain reaction. The expression of matrix metalloproteinases (MMP)-2 and MMP-9 and its natural inhibitor (tissue inhibitors of metalloproteinases, TIMP1), level of macrophages, and lymphocytes were also quantified. The effect of CST was determined also on apoptosis of rats' splenocytes. RESULTS: CST significantly enhances wound healing of rat postsurgery, with maximum activity achieved in the case of a 60 µM treated group. The expression of cyclooxygenase-2 was found reduced together with an increase in collagen III, tumor necrosis factor α, interferon gamma, IL-10, transforming growth factor beta, and IL-7 in the CST group. The levels of MMP-2 and MMP-9 were also found reduced together with an increase in TIMP1 level in CST-treated group. The levels of CD4+, CD8+, and CD11b+ cells at the wound site 24 and 120 h postsurgery was also found reduced in CST-treated group. However, it showed no apoptosis in murine splenocytes. CONCLUSIONS: Collectively, CST can promote the wound healing process by modulation of inflammation and immune response, which induces tissue remodeling.

Targeted Next-Generation Sequencing Reveals a Large Novel ß-Thalassemia Deletion that Removes the Entire HBB Gene.

ß-Thalassemia (ß-thal) is one of the most common monogenic recessive inherited diseases worldwide. The mutation spectrum of ß-thal has been increasingly broadened by various genetic testing methods. The discovery and identification of novel and rare pathogenic thalassemia variants enable better disease prevention, especially in high prevalence regions. In this study, a Chinese thalassemia family with an unclear etiology was recruited to the Thalassemia Screening Program. Blood samples collected from them were primarily screened by hematology analysis and clinical routine genetic screening. Subsequently, targeted next-generation sequencing (NGS) and Sanger sequencing were performed to find and identify a novel deletion variant. The deletion, discovered by targeted NGS, was validated through real-time quantitative polymerase chain reaction (qPCR). First, a large novel ß-thal deletion (3488 bp) related to a high Hb F level, NC_000011.9: g.5245533_5249020del (Chongqing deletion) (GRCh37/hg19), was found and identified in the proband and her mother. The deletion removed the entire ß-globin gene and led to absent ß-globin (ß0). We then validated this large novel deletion in the proband and her mother by qPCR. We first discovered and identified a large novel ß-thal deletion related to elevated Hb F level, it helps broaden the spectrum of pathogenic mutants that may cause ß-thal intermedia (ß-TI) or ß-thal major (ß-TM), paving the way for effective thalassemia screening. Next-generation sequencing has the potential of finding rare and novel thalassemia mutants.

Diagnosis and genetic analysis of a case with Bardet-Biedl syndrome caused by compound heterozygous mutations in the BBS12 gene.

Bardet-Biedl syndrome (BBS) is a rare autosomal recessive ciliopathy, which is caused by mutations mainly in genes encoding BBSome complex and IFT complex. Here, we reported a 21-year-old female with BBS characterized by three primary features including obesity, retinitis pigmentosa sine pigmento and bilateral renal cysts. She also had some secondary features such as diabetes mellitus, nonalcoholic fatty liver disease, subclinical hypothyroidism and mild conductive hearing damage. Whole exome sequencing revealed two compound heterozygous mutations in exon 2 of the BBS12 gene (c.188delC, p.T63fs and c.1993_1995del, p.665_665del) in this patient. Sanger sequencing showed that her father and mother carried c.188delC (p.T63fs) and c.1993_1995del (p.665_665del) variants, respectively, while her parents were free of BBS-related symptoms. In conclusion, this case reported two novel mutations (c.188delC, p.T63fs and c.1993_1995del, p.665_665del) of the BBS12 gene in a girl presented with BBS, which provides novel genetic resources for studies of the disease. Meanwhile, the BBS case shows the entire development progress from her birth to adulthood, which helps facilitate clinicians' understanding of BBS.

A dual-channel language decoding from brain activity with progressive transfer training.

When we view a scene, the visual cortex extracts and processes visual information in the scene through various kinds of neural activities. Previous studies have decoded the neural activity into single/multiple semantic category tags which can caption the scene to some extent. However, these tags are isolated words with no grammatical structure, insufficiently conveying what the scene contains. It is well-known that textual language (sentences/phrases) is superior to single word in disclosing the meaning of images as well as reflecting people's real understanding of the images. Here, based on artificial intelligence technologies, we attempted to build a dual-channel language decoding model (DC-LDM) to decode the neural activities evoked by images into language (phrases or short sentences). The DC-LDM consisted of five modules, namely, Image-Extractor, Image-Encoder, Nerve-Extractor, Nerve-Encoder, and Language-Decoder. In addition, we employed a strategy of progressive transfer to train the DC-LDM for improving the performance of language decoding. The results showed that the texts decoded by DC-LDM could describe natural image stimuli accurately and vividly. We adopted six indexes to quantitatively evaluate the difference between the decoded texts and the annotated texts of corresponding visual images, and found that Word2vec-Cosine similarity (WCS) was the best indicator to reflect the similarity between the decoded and the annotated texts. In addition, among different visual cortices, we found that the text decoded by the higher visual cortex was more consistent with the description of the natural image than the lower one. Our decoding model may provide enlightenment in language-based brain-computer interface explorations.

Performance of liver stiffness measurements obtained with FibroScan is affected by glucose metabolism in patients with nonalcoholic fatty liver disease.

BACKGROUND: The performance of liver stiffness measurements (LSMs) obtained using FibroScan can be affected by several factors, and cut-off values are different for fibrosis caused by various aetiologies. The study aims to evaluate the diagnostic accuracy of LSM in nonalcoholic fatty liver disease (NAFLD) patients with abnormal glucose metabolism and investigate whether the LSM value would be affected by metabolic indicators. METHODS: The study involved 91 NAFLD patients with abnormal glucose metabolism who underwent liver biopsy. The diagnostic accuracy of LSM value was evaluated by the receiver operator characteristic (ROC) curves, with the biopsy results taken as the gold standard. Multivariate linear regression and subgroup analysis were performed to determine the correlated indicators. RESULTS: The areas under the ROC curves (AUROCs) of LSM values for detecting fibrosis stage ≥1, 2, 3 and 4 were 0.793 (95% confidence interval [CI]: 0.695-0.871), 0.764 (95% CI: 0.663-0.846), 0.837 (95% CI: 0.744-0.906) and 0.902 (95% CI: 0.822-0.955), with cut-off values of 6.3, 7.6, 8.3 and 13.8 kPa, respectively. Multivariate linear regression demonstrated that haemoglobin A1c (HbA1c, ß = 0.205, P = 0.026) and alanine aminotransferase (ALT, ß = 0.192, P = 0.047) were independently associated with the LSM value after adjustment for fibrosis stage, ballooning and inflammation grade from liver biopsy. Subgroup analysis demonstrated that LSM values were slightly higher in patients with HbA1c ≥7% than in those with HbA1c < 7% and in patients with body mass index (BMI) ≥30 kg/m2 than in those with BMI < 30 kg/m2. CONCLUSIONS: FibroScan was valuable for the evaluation of liver fibrosis in NAFLD patients with abnormal glucose metabolism. FibroScan is recommended to evaluate severe fibrosis, especially to exclude advanced fibrosis. Glucose metabolism state may affect LSM values.

Identifying drug-related attributes to personalise antihypertensive agents: the outcome report of patients receiving metoprolol therapy.

BACKGROUND: Currently, numerous antihypertensive drugs from different pharmacological classes are available; however, blood pressure control is achieved in only less than a third of patients treated for hypertension. Moreover, providing optimal and personalised treatment for hypertension is challenging. Therefore, in this study, we propose a 'drug-related attributes' sensitive spectrum. This novel concept can assist clinicians in selecting an optimal antihypertensive drug and improve blood pressure control after examining the attributes of a patient. METHODS: We collected clinical data on attributes related to hypertension and its therapy of inpatients from West China Hospital who received metoprolol therapy and constructed the sensitive spectrum using data-visualisation tools. RESULTS: Our analysis revealed that haematocrit, haemoglobin, serum creatinine, serum cystatin C, serum urea, age, sex, systolic pressure, diastolic pressure, pulse pressure, and heart rate are metoprolol-related attributes. CONCLUSION: Our study showed that all metoprolol-related attributes identified are reasonable and helpful in improving the personalisation of metoprolol therapy. The proposed drug-related attributes spectrum can help personalise antihypertensive medication. Moreover, data-visualisation tools can be effectively used to mine the drug-related attributes sensitive spectrum.

Morpheme Transposition of Two-Character Chinese Words in Vertical Visual Fields.

The present study explored the morpheme transposition process of two-character Chinese words in the upper and lower visual fields by adopting a dual-target rapid serial visual presentation paradigm. The results showed that the identification accuracy of canonical words was better in the lower visual field, whereas the accuracy of transposed words was almost identical in the upper and lower visual fields. Furthermore, there was no significant difference between canonical and transposed words at 0°, 2°, 4°, and 6° eccentricities in the upper visual field. However, the accuracy of canonical words was markedly higher than that of transposed words at 2°, 4°, and 6° eccentricities in the lower visual field. Finally, the character order errors mainly occurred at 0°eccentricity with a duration of 100 ms in vertical visual fields. These findings, taken together, indicated that the character transposition affected the lexical process of two-character Chinese words in the lower visual field but not in the upper visual field, and the character order of words was more likely to be reversed at 0° eccentricity and the initial stage of visual word processing in vertical reading.

Histone methyltransferase SETDB1 promotes colorectal cancer proliferation through the STAT1-CCND1/CDK6 axis.

Upregulation of histone methyltransferase SET domain bifurcated 1 (SETDB1) is associated with poor prognosis in cancer patients. However, the mechanism of oncogenicity of SETDB1 in cancer is hitherto unknown. Here, we show that SETDB1 is upregulated in human colorectal cancer (CRC) where its level correlates with poor clinical outcome. Ectopic SETDB1 promotes CRC cell proliferation, whereas SETDB1 attenuation inhibits this process. Flow cytometry reveals that SETDB1 promotes proliferation by driving the CRC cell cycle from G0/G1 phase to S phase. Mechanistically, SETDB1 binds directly to the STAT1 promoter region resulting in increased STAT1 expression. Functional characterization reveals that STAT1-CCND1/CDK6 axis is a downstream effector of SETDB1-mediated CRC cell proliferation. Furthermore, SETDB1 upregulation is sufficient to accelerate in vivo proliferation in xenograft animal model. Taken together, our results provide insight into the upregulation of SETDB1 within CRC and can lead to novel treatment strategies targeting this cell proliferation-promoting gene.

Long short-term memory-based neural decoding of object categories evoked by natural images.

Visual perceptual decoding is one of the important and challenging topics in cognitive neuroscience. Building a mapping model between visual response signals and visual contents is the key point of decoding. Most previous studies used peak response signals to decode object categories. However, brain activities measured by functional magnetic resonance imaging are a dynamic process with time dependence, so peak signals cannot fully represent the whole process, which may affect the performance of decoding. Here, we propose a decoding model based on long short-term memory (LSTM) network to decode five object categories from multitime response signals evoked by natural images. Experimental results show that the average decoding accuracy using the multitime (2-6 s) response signals is 0.540 from the five subjects, which is significantly higher than that using the peak ones (6 s; accuracy: 0.492; p < .05). In addition, from the perspective of different durations, methods and visual areas, the decoding performances of the five object categories are deeply and comprehensively explored. The analysis of different durations and decoding methods reveals that the LSTM-based decoding model with sequence simulation ability can fit the time dependence of the multitime visual response signals to achieve higher decoding performance. The comparative analysis of different visual areas demonstrates that the higher visual cortex (VC) contains more semantic category information needed for visual perceptual decoding than lower VC.

Efficacy of exenatide and insulin glargine on nonalcoholic fatty liver disease in patients with type 2 diabetes.

BACKGROUND: The aim of this study was to investigate the efficacy of exenatide and insulin glargine in patients with newly diagnosed type 2 diabetes mellitus (T2DM) and nonalcoholic fatty liver disease (NAFLD). METHODS: We performed a 24-week randomized controlled multicentre clinical trial. Seventy-six patients were randomly assigned 1:1 to receive exenatide or insulin glargine treatment. The endpoints included changes in liver fat content (LFC), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) measured by magnetic resonance spectroscopy, blood glucose, liver enzymes, lipid profile, body weight, and Fibrosis-4 index (FIB-4). RESULTS: LFC, VAT, SAT, and FIB-4 were significantly reduced after exenatide treatment (ΔLFC, -17.55 ± 12.93%; ΔVAT, -43.57 ± 68.20 cm2 ; ΔSAT, -28.44 ± 51.48 cm2 ; ΔFIB-4, -0.10 ± 0.26; all P < .05). In comparison, only LFC (ΔLFC, -10.49 ± 11.38%; P < .05), and not VAT, SAT, or FIB-4 index (all P > .05), was reduced after insulin glargine treatment. Moreover, exenatide treatment resulted in greater reductions in alanine transaminase (ALT), aspartate transaminase (AST), and gamma glutamyl transpeptidase (GGT) than insulin glargine (P < 0.05). The body weight, waist circumference, postprandial plasma glucose, and low-density lipoprotein cholesterol (LDL-C) in the exenatide group also presented greater reductions than the insulin glargine group (P < .05). The proportion of adverse events were comparable between the two groups. CONCLUSION: Both exenatide and insulin glargine reduced LFC in patients with drug-naive T2DM and NAFLD; however, exenatide showed greater reductions in body weight, visceral fat area, liver enzymes, FIB-4, postprandial plasma glucose, and LDL-C.

DS21, a new noninvasive technology, is effective and safe for screening for prediabetes and diabetes in Chinese population.

BACKGROUND: Screening for prediabetes and asymptomatic diabetes is important for preventing development to an irreversible stage. The current diagnosis of prediabetes and diabetes is based on blood glucose or HbA1c (an invasive method). The aim of this study was to assess the efficacy and safety of DS21, a new noninvasive technology, for noninvasive screening for prediabetes and diabetes. METHODS: A total of 939 subjects were divided into a normal control group (NC, n = 308), impaired glucose regulation group (IGR, n = 312), and diabetes (DM) group (n = 319). All subjects underwent the DS21 test, and mean hands-feet, hand, and feet conductance values were analyzed. The diagnostic accuracy of the conductance value was analyzed by receiver-operating characteristic (ROC) curve. RESULTS: The conductance values for hands-feet, hands, and feet in the DM and IGR groups were significantly lower than those in the NC group (all P < 0.01). The area under the ROC curve  (AUCROC) for distinguishing NC/IGR was highest when using hands-feet conductance values (0.766 [95% confidence interval, CI 0.730, 0.803]). However, the AUCROCs of distinguishing NC/abnormal glucose metabolism (AGM, including IGR+DM), non-diabetes (NDM)/DM, and IGR/DM were highest when using conductance values for hands at 0.782 [95% CI 0.752, 0.812], 0.688 [95% CI 0.653, 0.723] and 0.573 [95% CI 0.528, 0.617], respectively (all P < 0.01). Hand conductance of values 75.0 (sensitivity 0.769, specificity 0.660), 77.1 (sensitivity 0.718, specificity 0.695), 68.4 (sensitivity 0.726, specificity 0.555), and 58.1 (sensitivity 0.384, specificity 0.744) were recommended as the screening thresholds for NC/AGM, NC/IGR, NDM/DM, and IGR/DM, respectively. A hand conductance value 66.0 was also recommended to distinguish NC/AGM due to its high sensitivity and high PPV. No adverse events occurred in the test. CONCLUSIONS: DS21 is fast, noninvasive, low cost, reliable and safe, which makes it a feasible device for screening for prediabetes and diabetes, especially in a large population.

IMPACT OF TYPE 2 DIABETES ON NONALCOHOLIC STEATOHEPATITIS AND ADVANCED FIBROSIS IN PATIENTS WITH NONALCOHOLIC FATTY LIVER DISEASE.

Objective: Type 2 diabetes mellitus (T2DM) is a risk factor for nonalcoholic fatty liver disease (NAFLD). The aim of this study was to investigate the effect of T2DM on nonalcoholic steatohepatitis (NASH) and advanced fibrosis. Methods: A total of 221 NAFLD patients who had undergone a liver biopsy were included in this study. Subjects were divided into a non-T2DM group and a T2DM group based on glycemic control. NASH was diagnosed by the joint presence of steatosis, ballooning, and lobular inflammation. The steatosis, activity, and fibrosis (SAF) score and NAFLD activity score (NAS) were used to evaluate the severity of NAFLD. The severity of liver fibrosis was evaluated based on the fibrosis stage. Results: The total percentages of NASH and advanced fibrosis in this study were 95.0% and 50.2%, respectively. The percentages of NASH and advanced fibrosis in NAFLD patients with T2DM were 96.1% and 56.5%, respectively, which were higher than those in the non-T2DM group. SAF score (especially activity and fibrosis stage) and NAS (especially ballooning) were higher in NAFLD patients with T2DM than in NAFLD patients without T2DM. Glycemic control and insulin resistance were positively associated with SAF, NAS, and fibrosis stage. Additionally, T2DM elevated the risk of a high NAS and advanced fibrosis. Conclusion: T2DM increases the risk of serious NASH and advanced fibrosis in patients with NAFLD. Liver biopsy can be performed in NAFLD patients with T2DM to confirm the stage of NAFLD. Screening of NASH and advanced fibrosis in NAFLD patients with T2DM is needed. Abbreviations: ALT = alanine aminotransferase; APO = apolipoprotein; AST = aspartate aminotransferase; BMI = body mass index; CI = confidence interval; FPG = fasting plasma glucose; GGT = gamma-glutamyl transferase; HbA1c = hemoglobin A1c; HDL-c = high-density-lipoprotein cholesterol; 1H-MRS = proton magnetic resonance spectroscopy; HOMA-IR = homeostasis model assessment of insulin resistance; 2hPG = postprandial plasma glucose at 2 hours; LDL-c = low-density-lipoprotein cholesterol; LFC = liver fat content; NAFLD = nonalcoholic fatty liver disease; NAS = NAFLD activity score; NASH = nonalcoholic steatohepatitis; OGTT = oral glucose tolerance test; OR = odds ratio; T2DM = type 2 diabetes mellitus; TC = total cholesterol; TG = triglyceride; SAF = steatosis, activity, and fibrosis; US-FLI = ultrasonographic fatty liver indicator.

Kinesin family member 18B: A contributor and facilitator in the proliferation and metastasis of cutaneous melanoma.

Melanoma is the most aggressive type of cutaneous tumor and the occurrence of metastasis makes it resistant to almost all available treatment and becomes incorrigible. Hence, identifying metastasis-related biomarkers and effective therapeutic targets will assist in preventing metastasis and ameliorating cutaneous melanoma. In our present study, we reported kinesin family member 18B (KIF18B) as a novel contributor in cutaneous melanoma proliferation and metastasis, and it was found to be of great significance in predicting the prognosis of cutaneous melanoma patients. Bioinformatics analysis based on ONCOMINE, The Cancer Genome Atlas, and Genotype-Tissue Expression database revealed that KIF18B was highly expressed in cutaneous melanoma and remarkably correlated with unfavorable clinical outcomes. Consistently, the results of the quantitative real-time polymerase chain reaction exhibited that the expression of KIF18B was significantly higher in cutaneous melanoma cell lines than that in normal cells. In vitro, biological assays found that knockdown of KIF18B in cutaneous melanoma cells noticeably repressed cell proliferation, migration, and invasion, while inducing cell apoptosis. Moreover, the protein expression of E-cadherin was enhanced while the expression of N-cadherin, vimentin, and Snail was decreased in M14 cells after knocking down KIF18B. In addition, the phosphorylation of phosphoinositide 3-kinase (PI3K) and extracellular-signal-regulated kinase (ERK) was significantly suppressed in M14 cells with silenced KIF18B. Above all, our results indicated that the repression of cutaneous melanoma cell migration and proliferation caused by KIF18B depletion suggested an oncogenic role of KIF18B in cutaneous melanoma, which acts through modulating epithelial-mesenchymal transition and ERK/PI3K pathway.