Deep Learning-Based Surgical Treatment Recommendation and Nonsurgical Prognosis Status Classification for Scaphoid Fractures by Automated X-ray Image Recognition.

Biomedical information retrieval for diagnosis, treatment and prognosis has been studied for a long time. In particular, image recognition using deep learning has been shown to be very effective for cancers and diseases. In these fields, scaphoid fracture recognition is a hot topic because the appearance of scaphoid fractures is not easy to detect. Although there have been a number of recent studies on this topic, no studies focused their attention on surgical treatment recommendations and nonsurgical prognosis status classification. Indeed, a successful treatment recommendation will assist the doctor in selecting an effective treatment, and the prognosis status classification will help a radiologist recognize the image more efficiently. For these purposes, in this paper, we propose potential solutions through a comprehensive empirical study assessing the effectiveness of recent deep learning techniques on surgical treatment recommendation and nonsurgical prognosis status classification. In the proposed system, the scaphoid is firstly segmented from an unknown X-ray image. Next, for surgical treatment recommendation, the fractures are further filtered and recognized. According to the recognition result, the surgical treatment recommendation is generated. Finally, even without sufficient fracture information, the doctor can still make an effective decision to opt for surgery or not. Moreover, for nonsurgical patients, the current prognosis status of avascular necrosis, non-union and union can be classified. The related experimental results made using a real dataset reveal that the surgical treatment recommendation reached 80% and 86% in accuracy and AUC (Area Under the Curve), respectively, while the nonsurgical prognosis status classification reached 91% and 96%, respectively. Further, the methods using transfer learning and data augmentation can bring out obvious improvements, which, on average, reached 21.9%, 28.9% and 5.6%, 7.8% for surgical treatment recommendations and nonsurgical prognosis image classification, respectively. Based on the experimental results, the recommended methods in this paper are DenseNet169 and ResNet50 for surgical treatment recommendation and nonsurgical prognosis status classification, respectively. We believe that this paper can provide an important reference for future research on surgical treatment recommendation and nonsurgical prognosis classification for scaphoid fractures.

Development of machine learning prognostic models for overall survival of prostate cancer patients with lymph node-positive.

Prostate cancer (PCa) patients with lymph node involvement (LNI) constitute a single-risk group with varied prognoses. Existing studies on this group have focused solely on those who underwent prostatectomy (RP), using statistical models to predict prognosis. This study aimed to develop an easily accessible individual survival prediction tool based on multiple machine learning (ML) algorithms to predict survival probability for PCa patients with LNI. A total of 3280 PCa patients with LNI were identified from the Surveillance, Epidemiology, and End Results (SEER) database, covering the years 2000-2019. The primary endpoint was overall survival (OS). Gradient Boosting Survival Analysis (GBSA), Random Survival Forest (RSF), and Extra Survival Trees (EST) were used to develop prognosis models, which were compared to Cox regression. Discrimination was evaluated using the time-dependent areas under the receiver operating characteristic curve (time-dependent AUC) and the concordance index (c-index). Calibration was assessed using the time-dependent Brier score (time-dependent BS) and the integrated Brier score (IBS). Moreover, the beeswarm summary plot in SHAP (SHapley Additive exPlanations) was used to display the contribution of variables to the results. The 3280 patients were randomly split into a training cohort (n = 2624) and a validation cohort (n = 656). Nine variables including age at diagnosis, race, marital status, clinical T stage, prostate-specific antigen (PSA) level at diagnosis, Gleason Score (GS), number of positive lymph nodes, radical prostatectomy (RP), and radiotherapy (RT) were used to develop models. The mean time-dependent AUC for GBSA, RSF, and EST was 0.782 (95% confidence interval [CI] 0.779-0.783), 0.779 (95% CI 0.776-0.780), and 0.781 (95% CI 0.778-0.782), respectively, which were higher than the Cox regression model of 0.770 (95% CI 0.769-0.773). Additionally, all models demonstrated almost similar calibration, with low IBS. A web-based prediction tool was developed using the best-performing GBSA, which is accessible at https://pengzihexjtu-pca-n1.streamlit.app/ . ML algorithms showed better performance compared with Cox regression and we developed a web-based tool, which may help to guide patient treatment and follow-up.

Bioinformatics analysis of differentially expressed proteins in alcoholic fatty liver disease treated with recombinant human cytoglobin.

Cytoglobin (Cygb) is a globin molecule that is ubiquitously expressed in all tissues and has a protective role under oxidative stress. It has also been demonstrated to be effective in the treatment of alcoholic fatty liver disease (AFLD). In order to study the molecular mechanisms underlying its beneficial effects for the treatment of alcoholic liver, two­dimensional electrophoresis and mass spectrometric analysis were performed on serum and liver tissues from an in vivo rat model of AFLD. A total of 26 differentially expressed proteins were identified in the serum and 20 differentially expressed proteins were identified in liver specimens. Using online bioinformatics tools, it was indicated that these differentially expressed proteins were primarily associated with pathways including binding and uptake of ligands by scavenger receptors, response to corticosteroid, plasma lipoprotein remodeling, regulation of complement cascade, hydrogen peroxide catabolic process, as well as response to nutrient and monosaccharide. The present results suggested that recombinant human Cygb exerts its role in the treatment of AFLD primarily through affecting nutrient metabolism, monocarboxylic acid biosynthesis, regulation of glutathione expression, plasma lipoprotein remodeling and removal of metabolic waste from the blood.

Effects of OsCDPK1 on the Structure and Physicochemical Properties of Starch in Developing Rice Seeds.

Overexpression of a constitutively active truncated form of OsCDPK1 (OEtr) in rice produced smaller seeds, but a double-stranded RNA gene-silenced form of OsCDPK1 (Ri) yielded larger seeds, suggesting that OsCDPK1 plays a functional role in rice seed development. In the study presented here, we propose a model in which OsCDPK1 plays key roles in negatively controlling the grain size, amylose content, and endosperm appearance, and also affects the physicochemical properties of the starch. The dehulled transgenic OEtr grains were smaller than the dehulled wild-type grains, and the OEtr endosperm was opaque and had a low amylose content and numerous small loosely packed polyhedral starch granules. However, the OEtr grain sizes and endosperm appearances were not affected by temperature, which ranged from low (22 °C) to high (31 °C) during the grain-filling phase. In contrast, the transgenic Ri grains were larger, had higher amylose content, and had more transparent endosperms filled with tightly packed polyhedral starch granules. This demonstrates that OsCDPK1 plays a novel functional role in starch biosynthesis during seed development and affects the transparent appearance of the endosperm. These results improve our understanding of the molecular mechanisms through which the grain-filling process occurs in rice.

Overexpression of a constitutively active truncated form of OsCDPK1 confers disease resistance by affecting OsPR10a expression in rice.

The rice pathogenesis-related protein OsPR10a was scarcely expressed in OsCDPK1-silenced (Ri-1) rice, which was highly sensitive to pathogen infection. After inoculating the leaves with bacterial blight (Xanthomonas oryzae pv. oryzae; Xoo), we found that the expression of OsPR10a was up- and down-regulated in OEtr-1 (overexpression of the constitutively active truncated form of OsCDPK1) and Ri-1 rice plants, respectively. OsPR10a and OsCDPK1 showed corresponding expression patterns and were up-regulated in response to the jasmonic acid, salicylic acid and Xoo treatments, and OsPR1 and OsPR4 were significantly up-regulated in OEtr-1. These results suggest that OsCDPK1 may be an upstream regulator involved in rice innate immunity and conferred broad-spectrum of disease resistance. Following the Xoo inoculation, the OEtr-1 and Ri-1 seedlings showed enhanced and reduced disease resistance, respectively. The dihybrid rice Ri-1/OsPR10a-Ox not only bypassed the effect of OsCDPK1 silencing on the susceptibility to Xoo but also showed enhanced disease resistance and, consistent with Ri-1 phenotypes, increased plant height and grain size. Our results reveal that OsCDPK1 plays novel key roles in the cross-talk and mediation of the balance between stress response and development and provides a clue for improving grain yield and disease resistance simultaneously in rice.

Multiple Patterns of Regulation and Overexpression of a Ribonuclease-Like Pathogenesis-Related Protein Gene, OsPR10a, Conferring Disease Resistance in Rice and Arabidopsis.

An abundant 17 kDa RNase, encoded by OsPR10a (also known as PBZ1), was purified from Pi-starved rice suspension-cultured cells. Biochemical analysis showed that the range of optimal temperature for its RNase activity was 40-70°C and the optimum pH was 5.0. Disulfide bond formation and divalent metal ion Mg2+ were required for the RNase activity. The expression of OsPR10a::GUS in transgenic rice was induced upon phosphate (Pi) starvation, wounding, infection by the pathogen Xanthomonas oryzae pv. oryzae (Xoo), leaf senescence, anther, style, the style-ovary junction, germinating embryo and shoot. We also provide first evidence in whole-plant system, demonstrated that OsPR10a-overexpressing in rice and Arabidopsis conferred significant level of enhanced resistance to infection by the pathogen Xoo and Xanthomona campestris pv. campestris (Xcc), respectively. Transgenic rice and Arabidopsis overexpressing OsPR10a significantly increased the length of primary root under phosphate deficiency (-Pi) condition. These results showed that OsPR10a might play multiple roles in phosphate recycling in phosphate-starved cells and senescing leaves, and could improve resistance to pathogen infection and/or against chewing insect pests. It is possible that Pi acquisition or homeostasis is associated with plant disease resistance. Our findings suggest that gene regulation of OsPR10a could act as a good model system to unravel the mechanisms behind the correlation between Pi starvation and plant-pathogen interactions, and also provides a potential application in crops disease resistance.

A general approach to the screening and confirmation of tryptamines and phenethylamines by mass spectral fragmentation.

Certain characteristic fragmentations of tryptamines (indoleethylamine) and phenethylamines are described. Based on the GC-EI/MS, LC-ESI/MS and MALDI/TOFMS, the mass fragmentations of 13 standard compounds, including alpha-methyltryptamine (AMT), N,N-dimethyltryptamine (DMT), 5-methoxy-alpha-methyltryptamine (5-MeO-AMT), N,N-diethyltryptamine (DET), N,N-dipropyltryptamine (DPT), N,N-dibutyltryptamine (DBT), N,N-diisopropyltryptamine (DIPT), 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT), 5-methoxy-N,N-diisopropyltryptamine (5-MeO-DIPT), methamphetamine (MAMP), 3,4-methylenedioxyamphetamine (3,4-MDA), 3,4-methylenedioxymethamphetamine (3,4-MDMA) and 2-methylamino-1-(3,4-methylenedioxyphenyl)butane (MBDB), were compared. As a result, the parent ions of these analytes were hard to be obtained by GC/MS whereas the protonated molecular ions can be observed clearly by means of ESI/MS and MALDI/TOFMS. Furthermore, two major characteristic fragmentations, namely and alpha-cleavage ([M+H](+)-->[3-vinylindole](+)) and beta-cleavage ([M+H](+)-->[CH(2)N(+)R(N1)R(N2)]), are produced when the ESI and MALDI modes are used, respectively. In the case of ESI/MS, the fragment obtained from alpha-cleavage is the major process. In contrast to this, in the case of MALDI/TOFMS, the major fragment is produced via beta-cleavage. The ionization efficiency and fragments formed from either alpha- or beta-cleavages are closely related to the degree of alkylation of the side chain nitrogen in both cases.

Separation of crystal violet dyes and its application to pen ink analysis using CZE and MEKC methods.

A crystal violet (CV) standard was irradiated under a Hg-Cd lamp for different exposure times to obtain various N-demethylation products. CZE effectively separated the photodegradation products based on molecular weight differences. In contrast, micellar EKC (MEKC), using SDS as the surfactant, was ineffective because the binding constants of the demethylation products and SDS were too close for separation. Nevertheless, MEKC analysis of ink has applications in forensic science because MEKC separated neutral components in the inks. Thus, MEKC can be used to obtain an ink "fingerprint" since each ink is unique depending on the location and time it was made. In contrast, CZE is useful for dating inks because CV is the primary ink dye and it photodegrades slowly.