Idiopathic mesenteric phlebosclerosis combined with melanosis coli in a 51-year-old woman.

Idiopathic mesenteric phlebosclerosis (IMP) is a rare ischemic colitis characterized by calcification of mesenteric veins and submucosal veins of the colon. Melanosis coli (MC) is a pigmented mucosal lesion comprising macrophages in the lamina propria of the colorectal mucosa that contain lipofuscin. This study reports a case of IMP combined with MC.Clinicians should consider medication history, bowel preparation, and thorough observation to prevent missed IMP diagnosis when coexisting with MC.

Co-Delivery of Doxorubicin and Survivin shRNA-Expressing Plasmid Via Microenvironment-Responsive Dendritic Mesoporous Silica Nanoparticles for Synergistic Cancer Therapy.

PURPOSE: The present study is aimed at designing an appropriate co-delivery system for chemotherapeutic drugs and gene drugs with high loading capacity, on-demand release behaviors, efficient endosomal escape, and enhanced nucleic localization, thereby providing efficacious antitumor activity. METHODS: Schiff-base linked imidazole dendritic mesoporous silica nanoparticles (SL-IDMSN) were developed and employed to load doxorubicin (DOX) and survivin shRNA-expressing plasmid (iSur-pDNA) to form nanocomplexes. The nanoparticles were assessed by structural characterization, drug loading and release, cellular uptake, intracellular distribution, gene transfection, in vitro anti-proliferation of hepatoma cells, and in vivo tumor growth inhibition in H-22 tumor bearing mice. RESULTS: SL-IDMSN showed high loading capacity for both DOX and iSur-pDNA due to their hierarchical mesostructures. The cleavage of Schiff-base linkage on SL-IDMSN in the weakly acidic endosomes/lysosomes led to microenvironment-specific release of both DOX and iSur-pDNA. Meanwhile, the imidazole modification could trigger the efficient endosomal escape via proton sponge effect, thereby enhancing nuclear accumulation of iSur-pDNA and gene silencing efficiency. More importantly, these superior performances of SL-IDMSN resulted in their improved inhibitory effects on in vitro cancer cell proliferation and in vivo tumor growth. CONCLUSIONS: SL-IDMSN is a microenvironment-sensitive and biocompatible nanocarrier for the co-delivery of DOX and iSur-pDNA, which might be a promising carrier for co-delivery of chemotherapeutic drugs and gene drugs for synergistic cancer therapy.

MSGM: An Advanced Deep Multi-Size Guiding Matching Network for Whole Slide Histopathology Images Addressing Staining Variation and Low Visibility Challenges.

Matching whole slide histopathology images to provide comprehensive information on homologous tissues is beneficial for cancer diagnosis. However, the challenge arises with the Giga-pixel whole slide images (WSIs) when aiming for high-accuracy matching. Learning-based methods are difficult to generalize well with large-size WSIs, necessitating the integration of traditional matching methods to enhance accuracy as the size increases. In this paper, we propose a multi-size guiding matching method applicable high-accuracy requirements. Specifically, we design learning multiscale texture to train deep descriptors, called TDescNet, that trains 64 ×64×256 and 256 ×256×128 size convolution layer as C64 and C256 descriptors to overcome staining variation and low visibility challenges. Furthermore, we develop the 3D-ring descriptor using sparse keypoints to support the description of large-size WSIs. Finally, we employ C64, C256, and 3D-ring descriptors to progressively guide refined local matching, utilizing geometric consistency to identify correct matching results. Experiments show that when matching WSIs of size 4096×4096 pixels, our average matching error is 123.48 [Formula: see text] and the success rate is 93.02 % in 43 cases. Notably, our method achieves an average improvement of 65.52 [Formula: see text] in matching accuracy compared to recent state-of-the-art methods, with enhancements ranging from 36.27 [Formula: see text] to 131.66 [Formula: see text]. Therefore, we achieve high-fidelity whole-slice image matching, and overcome staining variation and low visibility challenges, enabling assistance in comprehensive cancer diagnosis through matched WSIs.

Exploring racial and gender disparities in voice biometrics.

Systemic inequity in biometrics systems based on racial and gender disparities has received a lot of attention recently. These disparities have been explored in existing biometrics systems such as facial biometrics (identifying individuals based on facial attributes). However, such ethical issues remain largely unexplored in voice biometric systems that are very popular and extensively used globally. Using a corpus of non-speech voice records featuring a diverse group of 300 speakers by race (75 each from White, Black, Asian, and Latinx subgroups) and gender (150 each from female and male subgroups), we explore and reveal that racial subgroup has a similar voice characteristic and gender subgroup has a significant different voice characteristic. Moreover, non-negligible racial and gender disparities exist in speaker identification accuracy by analyzing the performance of one commercial product and five research products. The average accuracy for Latinxs can be 12% lower than Whites (p < 0.05, 95% CI 1.58%, 14.15%) and can be significantly higher for female speakers than males (3.67% higher, p < 0.05, 95% CI 1.23%, 11.57%). We further discover that racial disparities primarily result from the neural network-based feature extraction within the voice biometric product and gender disparities primarily due to both voice inherent characteristic difference and neural network-based feature extraction. Finally, we point out strategies (e.g., feature extraction optimization) to incorporate fairness and inclusive consideration in biometrics technology.

An explainable COVID-19 detection system based on human sounds.

Acoustic signals generated by the human body have often been used as biomarkers to diagnose and monitor diseases. As the pathogenesis of COVID-19 indicates impairments in the respiratory system, digital acoustic biomarkers of COVID-19 are under investigation. In this paper, we explore an accurate and explainable COVID-19 diagnosis approach based on human speech, cough, and breath data using the power of machine learning. We first analyze our design space considerations from the data aspect and model aspect. Then, we perform data augmentation, Mel-spectrogram transformation, and develop a deep residual architecture-based model for prediction. Experimental results show that our system outperforms the baseline, with the ROC-AUC result increased by 5.47%. Finally, we perform an interpretation analysis based on the visualization of the activation map to further validate the model.

In-Home Rehabilitation Using a Smartphone App Coupled With 3D Printed Functional Objects: Single-Subject Design Study.

BACKGROUND: Stroke is a major cause of long-term disability. While there is potential for improvements long after stroke onset, there is little to support functional recovery across the lifespan. mHealth solutions can help fill this gap. mRehab was designed to guide individuals with stroke through a home program and provide performance feedback. OBJECTIVE: To examine if individuals with chronic stroke can use mRehab at home to improve upper limb mobility. The secondary objective was to examine if changes in limb mobility transferred to standardized clinical assessments. METHODS: mRehab consists of a smartphone coupled with 3D printed household items: mug, bowl, key, and doorknob. The smartphone custom app guides task-oriented activities and measures both time to complete an activity and quality of movement (smoothness/accuracy). It also provides performance-based feedback to aid the user in self-monitoring their performance. Task-oriented activities were categorized as (1) object transportation, (2) prehensile grip with supination/pronation, (3) fractionated finger movement, and (4) walking with object. A total of 18 individuals with stroke enrolled in the single-subject experimental design study consisting of pretesting, a 6-week mRehab home program, and posttesting. Pre- and posttesting included both in-laboratory clinical assessments and in-home mRehab recorded samples of task performance. During the home program, mRehab recorded performance data. A System Usability Scale assessed user's perception of mRehab. RESULTS: A total of 16 participants completed the study and their data are presented in the results. The average days of exercise for each mRehab activity ranged from 15.93 to 21.19 days. This level of adherence was sufficient for improvements in time (t15=2.555, P=.02) and smoothness (t15=3.483, P=.003) in object transportation. Clinical assessments indicated improvements in functional performance (t15=2.675, P=.02) and hand dexterity (t15=2.629, P=.02). Participant's perception of mRehab was positive. CONCLUSIONS: Despite heterogeneity in participants' use of mRehab, there were improvements in upper limb mobility. Smartphone-based portable technology can support home rehabilitation programs in chronic conditions such as stroke. The ability to record performance data from home rehabilitation offers new insights into the impact of home programs on outcomes. TRIAL REGISTRATION: ClinicalTrials.gov NCT04363944; https://clinicaltrials.gov/ct2/show/NCT04363944.

Long non-coding RNA FTH1P3 promotes the metastasis and aggressiveness of non-small cell lung carcinoma by inducing epithelial-mesenchymal transition.

Long non-coding RNAs (lncRNAs) ferritin heavy chain 1 pseudogene 3 (FTH1P3) has been suggested to act as an oncogene in many types of human malignancy, but its role in non-small cell lung carcinoma (NSCLC) remains unknown. This study aimed to characterize the biologic functions of FTH1P3 in NSCLC and illuminate its clinical significance. The expression levels of FTH1P3 in NSCLC tissues and cell lines were detected by quantitative real-time PCR assay. The relationship of FTH1P3 expression with clinicopathologic features was evaluated by chi-square test, and its correlation with prognosis of NSCLC patients was analyzed by Kaplan-Meier method with log-rank test. Wound healing and transwell invasion assays were applied to evaluate cell migration and invasion abilities, respectively. Western blotwas performed to detect the changes of epithelial-mesenchymal transition (EMT) related protein expression. The results showed that FTH1P3 was highly expressed in NSCLC tumor tissues and NSCLC-derived cell lines, and high expression of FTH1P3 was associated with advanced TNM stage and lymph node metastasis. NSCLC patients with high FTH1P3 expression had a poor overall survival relative to patients with low FTH1P3 expression. Through loss-of-function studies, FTH1P3 inhibition was demonstrated to suppress NSCLC cell migration and invasion in vitro. Notably, FTH1P3 knockdown could decrease expression of N-cadherin, vimentin and Snail protein of NSCLC cells, but promote E-cadherin protein expression, which was in accordance with its effect on cell migration and invasion. To sum up, our data demonstrated that FTH1P3 predicts a poor prognosis and promotes metastasis and aggressiveness in NSCLC by inducing EMT, suggesting FTH1P3 may be a promising target for gene therapy of NSCLC.

The epidemiological trend of acute promyelocytic leukemia over past four decades: a population-based analysis.

The treatment regimens for acute promyelocytic leukemia (APL) dramatically changed over time. However, its survival trend, based on a large sample size has not been reported. Patients diagnosed with APL were accessed from the Surveillance, Epidemiology, and End Results database. Their incidence and survival trend were evaluated in overall and subgroup levels. The overall incidence of APL increased with an annual percentage change of 5.5% from 1992 to 2006 and remained stable thereafter. In addition, the 5-year relative survival rates of APL improved significantly, from 12.3 to 32.2% to 59.5 to 72.1% over past four decades (p < .0001), sharing similar trend with different subgroups. Importantly, survival disparities exist among races and different socioeconomic status groups, with superior survival in whites and patients in low-poverty regions. Increasing incidence urges for increased awareness of clinicians over diagnosis of APL. In addition, a wider insurance coverage may help balance survival gap.