Improving Audio Caption Fluency with Automatic Error Correction

Automated audio captioning (AAC) is an important cross-modality translation task, aiming at generating descriptions for audio clips. However, captions generated by previous AAC models have faced ``false-repetition'' errors due to the training objective. In such scenarios, we propose a new task of AAC error correction and hope to reduce such errors by post-processing AAC outputs. To tackle this problem, we use observation-based rules to corrupt captions without errors, for pseudo grammatically-erroneous sentence generation. One pair of corrupted and clean sentences can thus be used for training. We train a neural network-based model on the synthetic error dataset and apply the model to correct real errors in AAC outputs. Results on two benchmark datasets indicate that our approach significantly improves fluency while maintaining semantic information.Comment: Accepted by NCMMSC 202

Segment Anything Model for Medical Image Analysis: an Experimental Study

Training segmentation models for medical images continues to be challenging due to the limited availability and acquisition expense of data annotations. Segment Anything Model (SAM) is a foundation model trained on over 1 billion annotations, predominantly for natural images, that is intended to be able to segment the user-defined object of interest in an interactive manner. Despite its impressive performance on natural images, it is unclear how the model is affected when shifting to medical image domains. Here, we perform an extensive evaluation of SAM's ability to segment medical images on a collection of 11 medical imaging datasets from various modalities and anatomies. In our experiments, we generated point prompts using a standard method that simulates interactive segmentation. Experimental results show that SAM's performance based on single prompts highly varies depending on the task and the dataset, i.e., from 0.1135 for a spine MRI dataset to 0.8650 for a hip x-ray dataset, evaluated by IoU. Performance appears to be high for tasks including well-circumscribed objects with unambiguous prompts and poorer in many other scenarios such as segmentation of tumors. When multiple prompts are provided, performance improves only slightly overall, but more so for datasets where the object is not contiguous. An additional comparison to RITM showed a much better performance of SAM for one prompt but a similar performance of the two methods for a larger number of prompts. We conclude that SAM shows impressive performance for some datasets given the zero-shot learning setup but poor to moderate performance for multiple other datasets. While SAM as a model and as a learning paradigm might be impactful in the medical imaging domain, extensive research is needed to identify the proper ways of adapting it in this domain.Comment: Link to our code: https://github.com/mazurowski-lab/segment-anything-medica

Automated Grading of Radiographic Knee Osteoarthritis Severity Combined with Joint Space Narrowing

The assessment of knee osteoarthritis (KOA) severity on knee X-rays is a central criteria for the use of total knee arthroplasty. However, this assessment suffers from imprecise standards and a remarkably high inter-reader variability. An algorithmic, automated assessment of KOA severity could improve overall outcomes of knee replacement procedures by increasing the appropriateness of its use. We propose a novel deep learning-based five-step algorithm to automatically grade KOA from posterior-anterior (PA) views of radiographs: (1) image preprocessing (2) localization of knees joints in the image using the YOLO v3-Tiny model, (3) initial assessment of the severity of osteoarthritis using a convolutional neural network-based classifier, (4) segmentation of the joints and calculation of the joint space narrowing (JSN), and (5), a combination of the JSN and the initial assessment to determine a final Kellgren-Lawrence (KL) score. Furthermore, by displaying the segmentation masks used to make the assessment, our algorithm demonstrates a higher degree of transparency compared to typical "black box" deep learning classifiers. We perform a comprehensive evaluation using two public datasets and one dataset from our institution, and show that our algorithm reaches state-of-the art performance. Moreover, we also collected ratings from multiple radiologists at our institution and showed that our algorithm performs at the radiologist level. The software has been made publicly available at https://github.com/MaciejMazurowski/osteoarthritis-classification

The mediating role of negative symptoms in “secondary factors” determining social functioning in chronic schizophrenia

BackgroundChronic schizophrenia is significantly influenced by negative symptoms, with several known contributors to secondary negative symptoms. However, the impact of these factors and negative symptoms on social functioning warrants further exploration.MethodsWe assessed the clinical symptoms, antipsychotic adverse reactions, and social functioning of 283 hospitalized patients with chronic schizophrenia using various standardized interviews and scales. We conducted multiple regression and mediation analyses to elucidate the impact of secondary factors on negative symptoms, and the relationship among these “secondary factors,” negative symptoms, and social functioning.ResultsOur findings identified depressive symptoms, extrapyramidal symptoms, and positive symptoms as significant contributors to secondary negative symptoms. We found that negative symptoms play a notable mediating role in the effect of depressive and positive symptoms on social functioning. However, the relationship between positive symptoms, negative symptoms, and social functioning proved to be intricate.ConclusionOur findings propose that negative symptoms act as pivotal mediators in the correlation between “secondary factors” (including the depressive symptoms and positive symptoms) and social functioning. The treatment of chronic schizophrenia necessitates focusing on key factors such as depressive and positive symptoms, which might significantly contribute to the development of secondary negative symptoms. Further research is essential to clarify the complex relationship among positive symptoms, negative symptoms, and social functioning in schizophrenia

High glucose dialysate-induced peritoneal fibrosis: Pathophysiology, underlying mechanisms and potential therapeutic strategies

Peritoneal dialysis is an efficient renal replacement therapy for patients with end-stage kidney disease. However, continuous exposure of the peritoneal membrane to dialysate frequently leads to peritoneal fibrosis, which alters the function of the peritoneal membrane and results in withdrawal from peritoneal dialysis in patients. Among others, high glucose dialysate is considered as a predisposing factor for peritoneal fibrosis in patients on peritoneal dialysis. Glucose-induced inflammation, metabolism disturbance, activation of the renin–angiotensin–aldosterone system, angiogenesis and noninflammation-induced reactive oxygen species are implicated in the pathogenesis of high glucose dialysate-induced peritoneal fibrosis. Specifically, high glucose causes chronic inflammation and recurrent peritonitis, which could cause migration and polarization of inflammatory cells, as well as release of cytokines and fibrosis. High glucose also interferes with lipid metabolism and glycolysis by activating the sterol-regulatory element-binding protein-2/cleavage-activating protein pathway and increasing hypoxia inducible factor-1α expression, leading to angiogenesis and peritoneal fibrosis. Activation of the renin–angiotensin-aldosterone system and Ras-mitogen activated protein kinase signaling pathway is another contributing factor in high glucose dialysate-induced fibrosis. Ultimately, activation of the transforming growth factor-β1/Smad pathway is involved in mesothelial-mesenchymal transition or epithelial-mesenchymal transition, which leads to the development of fibrosis. Although possible intervention strategies for peritoneal dialysate-induced fibrosis by targeting the transforming growth factor-β1/Smad pathway have occasionally been proposed, lack of laboratory evidence renders clinical decision-making difficult. We therefore aim to revisit the upstream pathways of transforming growth factor-beta1/Smad and propose potential therapeutic targets for high glucose-induced peritoneal fibrosis

Therapeutic potential of single-nucleotide polymorphism-mediated interleukin-6 receptor blockade in cancer treatment: A Mendelian randomization study

Background: Interleukin-6 (IL-6) is a crucial member of the cytokine network and plays a pivotal role in the pathogenesis of various diseases, including cancer. IL-6 receptor (IL-6R) blockade is widely employed as a therapeutic strategy; however, its efficacy in anticancer therapy remains ambiguous. Methods: An inverse variance-weighted Mendelian randomization (MR) analysis was conducted to assess the causal effects exerted by IL-6R blockade in remediating cancer. Drug-targeted single-nucleotide polymorphisms (SNPs) were introduced within 300 kb of the IL-6R gene. An instrumental variable comprising 26 SNPs represented IL-6 signaling downregulation and C-reactive protein level reduction. Datasets pertaining to the 33 types of cancer investigated in this study were acquired from the FinnGen genome-wide association study. Results: The selected instrumental variable lowered fibrinogen levels, confirming its ability to mimic IL-6R blockade. IL-6R blockade exhibited therapeutic effects on five different cancer types documented in the FinnGen database (N = 334,364, including 76,781 cancer patients): bladder (odds ratios (OR) = 0.563), laryngeal (OR = 0.293), eye (OR = 0.098), gallbladder (OR = 0.059), and myeloid leukemia (OR = 0.442); however, it simultaneously elevated the risk of developing basal cell carcinoma (OR = 1.312) and melanoma (OR = 1.311). Sensitivity analyses did not alter the primary results. Conclusion: Therefore, this study aimed to evaluate the potential and efficacy of SNP-based IL-6R blockade in treating cancer

Distribution of Phenolic Acids and Antioxidant Activities of Different Bran Fractions from Three Pigmented Wheat Varieties

Phenolic acid profiles and antioxidant activities of outer bran, coarse bran, and shorts from blue, black, and purple wheat were analyzed. Phenolic acids were mainly in the bound form in pigmented wheat bran fractions. Phenolic acid content decreased in the order of outer bran, coarse bran, and shorts for the three pigmented wheat varieties. HPLC analysis of phenolic extracts demonstrated that the bound form of phenolic acids contained more ferulic, isoferulic, and p-coumaric acids compared to their free counterparts. Among the three pigmented wheat varieties, the bran fractions from blue wheat contained higher bound phenolic acids than the other two pigmented wheat bran fractions, except for purple coarse bran. The blue wheat outer bran had the highest total bound phenolic acid of 3458.71 μg/g while the purple wheat shorts had the lowest of 1730.71 μg/g. The contribution of bound phenolic acids to the total phenolic content and antioxidant activity was significantly higher than that of free phenolic acids. Blue wheat bran fractions had the highest radical scavenging activity against DPPH∙ while those of purple wheat gained the highest ABTS∙+ scavenging activity. High correlations were observed between TPC and radical scavenging capacities for DPPH and ABTS (R2>0.85, P<0.05)

An updated meta-analysis on the efficacy and safety of hypoxia-inducible factor prolyl hydroxylase inhibitor treatment of anemia in nondialysis-dependent chronic kidney disease

AbstractBackground Renal anemia, a common complication and threat factor of chronic kidney disease (CKD), has long been treated with injectable erythropoietin-stimulating agents (ESAs). As concerns regarding cardiovascular safety and erythropoietin resistance to ESAs have emerged, alternative therapies are urgently needed. Hypoxia-inducible factor prolyl hydroxylase inhibitor (HIF-PHI), an oral agent, has been proven to be effective in improving renal anemia. However, the effects of HIF-PHIs on nondialysis-dependent CKD (NDD-CKD) have yet to be supported by updated meta-analyses.Methods A meta-analysis of clinical randomized controlled trials (RCTs) on HIF-PHI treatment of NDD-CKD patients based on PubMed, EMBASE, and Cochrane databases as of July 16th, 2023, was conducted. The primary outcomes were the level of hemoglobin (Hb) postintervention and the ratio of Hb responses. Most of the analysis was conducted via RevMan 5.3 software using a random-effects model. Stata (version 15.0) was used to analyze the publication bias.Results Twenty-two studies with a total of 7178 subjects in the HIF-PHI group, 3501 subjects in the ESA group and 2533 subjects in the placebo group were enrolled. HIF-PHIs increased the level of Hb and improved iron metabolism but were not inferior to ESAs in terms of safety.Conclusions HIF-PHIs may be a convenient and safe alternative to ESAs in patients with NDD-CKD and anemia

Effects of IGF-1 on the Three-Dimensional Culture of Ovarian Preantral Follicles and Superovulation Rates in Mice

Insulin-like growth factor-1 (IGF-1) plays a crucial role during folliculogenesis, which has been demonstrated by previous research. However, the optimal IGF-1 dosage in the three-dimensional (3D) culture system is unknown. Mouse secondary follicles (140&ndash;150 &micro;m) were cultured for 6 days within an alginate bead in a medium supplemented with 0 (G0), 5 ng/mL (G5), 10 ng/mL (G10), or 50 ng/mL IGF-1 (G50). Secretions of 17&beta;-estradiol and progesterone were significantly increased in G10 and G50 (p &lt; 0.05). However, G50 significantly inhibited follicular growth (p &lt; 0.05), while G10 showed a higher oocyte maturation rate. Thus, the 10 ng/mL IGF-1 was used in subsequent experiments. IGF-1 enhanced the function of granulosa cells (GCs) by upregulating expressions of Star, Cyp19a1, Hsd3b1, Fshr, and Lhcgr. Oocyte secretory function was promoted by upregulating expressions of Bmp-15,&nbsp;Gdf-9, and Fgf-8. Addition of IGF-1 showed anti-apoptotic effect. However, G10 did not improve fertilization rate of MII oocytes compared to G0. In an intraperitoneal injection experiment in mice, IGF-1 significantly increased the number of ovulated oocytes (p &lt; 0.05). In conclusion, 10 ng/mL IGF-1 can promote the production of mature oocytes in the 3D culture medium and injection of IGF-1 before superovulation increases the number of ovulated oocytes

Effect of Alkali Treatment on Structure and Properties of High Amylose Corn Starch Film

Alkali treatment is used for melt extrusion film formation with corn starch, but optimal conditions for this procedure are still unknown. In this study, the changes in properties and structure of high amylose corn starch (70%) films with different concentrations of sodium hydroxide (NaOH), prepared by melting extrusion, were investigated. With increasing sodium hydroxide concentrations, the tensile strength of the high-amylose starch film decreased gradually, while the elongation at break increased. The tensile strength of the high amylose starch (HAS) film with 2% NaOH-treatment was 10.03 MPa and its elongation at break was 40%. A 2% NaOH-treatment promoted the orderly rearrangement of starch molecules and formed an Eh-type crystal structure, which enlarged the spacing of the single helix structure, increased the molecular mobility of the starch, and slowed down the process of recrystallization; a 10% NaOH-treatment oxidized the hydroxyl groups of the high amylose corn starch during extrusion, formed a poly-carbonyl structure, and initiated the degradation and cross-linking of starch molecule chains