Clinical validation of automated depth camera-based measurement of the Fugl-Meyer assessment for upper extremity.

OBJECTIVE: Depth camera-based measurement has demonstrated efficacy in automated assessment of upper limb Fugl-Meyer Assessment for paralysis rehabilitation. However, there is a lack of adequately sized studies to provide clinical support. Thus, we developed an automated system utilizing depth camera and machine learning, and assessed its feasibility and validity in a clinical setting. DESIGN: Validation and feasibility study of a measurement instrument based on single cross-sectional data. SETTING: Rehabilitation unit in a general hospital. PARTICIPANTS: Ninety-five patients with hemiparesis admitted for inpatient rehabilitation unit (2021-2023). MAIN MEASURES: Scores for each item, excluding those related to reflexes, were computed utilizing machine learning models trained on participant videos and readouts from force test devices, while the remaining reflex scores were derived through regression algorithms. Concurrent criterion validity was evaluated using sensitivity, specificity, percent agreement and Cohen's Kappa coefficient for ordinal scores of individual items, as well as correlations and intraclass correlation coefficients for total scores. Video-based manual assessment was also conducted and compared to the automated tools. RESULT: The majority of patients completed the assessment without therapist intervention. The automated scoring models demonstrated superior validity compared to video-based manual assessment across most items. The total scores derived from the automated assessment exhibited a high coefficient of 0.960. However, the validity of force test items utilizing force sensing resistors was relatively low. CONCLUSION: The integration of depth camera technology and machine learning models for automated Fugl-Meyer Assessment demonstrated acceptable validity and feasibility, suggesting its potential as a valuable tool in rehabilitation assessment.

Reliability of a human pose tracking algorithm for measuring upper limb joints: comparison with photography-based goniometry.

BACKGROUND: Range of motion (ROM) measurements are essential for diagnosing and evaluating upper extremity conditions. Clinical goniometry is the most commonly used methods but it is time-consuming and skill-demanding. Recent advances in human tracking algorithm suggest potential for automatic angle measuring from RGB images. It provides an attractive alternative for at-distance measuring. However, the reliability of this method has not been fully established. The purpose of this study is to evaluate if the results of algorithm are as reliable as human raters in upper limb movements. METHODS: Thirty healthy young adults (20 males, 10 females) participated in this study. Participants were asked to performed a 6-motion task including movement of shoulder, elbow and wrist. Images of movements were captured by commercial digital cameras. Each movement was measured by a pose tracking algorithm (OpenPose) and compared with the surgeon-measurement results. The mean differences between the two measurements were compared. Pearson correlation coefficients were used to determine the relationship. Reliability was investigated by the intra-class correlation coefficients. RESULTS: Comparing this algorithm-based method with manual measurement, the mean differences were less than 3 degrees in 5 motions (shoulder abduction: 0.51; shoulder elevation: 2.87; elbow flexion:0.38; elbow extension:0.65; wrist extension: 0.78) except wrist flexion. All the intra-class correlation coefficients were larger than 0.60. The Pearson coefficients also showed high correlations between the two measurements (p < 0.001). CONCLUSIONS: Our results indicated that pose estimation is a reliable method to measure the shoulder and elbow angles, supporting RGB images for measuring joint ROM. Our results presented the possibility that patients can assess their ROM by photos taken by a digital camera. TRIAL REGISTRATION: This study was registered in the Clinical Trials Center of The First Affiliated Hospital, Sun Yat-sen University (2021-387).

Occlusal trauma and excessive occlusal forces: Narrative review, case definitions, and diagnostic considerations.

OBJECTIVES: This narrative review determines the effects of occlusal trauma and excessive occlusal forces on the periodontium, including the initiation and progression of periodontitis, abfraction, and gingival recession. Case definitions, diagnostic considerations, and the effects of occlusal therapy are also reviewed and discussed. IMPORTANCE: The role of occlusal trauma in the initiation and progression of periodontitis remains a controversial subject in periodontology. Because occlusal trauma can only be confirmed histologically, its clinical diagnosis depends on clinical and radiographic surrogate indicators which make clinical trials difficult. FINDINGS: Investigations have generally agreed that occlusal trauma and excessive occlusal forces do not initiate periodontitis or loss of connective tissue attachment. When plaque-induced periodontitis and occlusal trauma are present at the same time, there is weak evidence that the occlusal trauma may increase the rate of connective tissue loss. Occlusal therapy is indicated as part of periodontal therapy to reduce mobility and increase patient comfort and masticatory function. Existing data do not support the existence of abfraction as a cause for gingival recession. CONCLUSIONS: Occlusal trauma does not initiate periodontitis, and there is weak evidence that it alters the progression of the disease. There is no credible evidence to support the existence of abfraction or implicate it as a cause of gingival recession. Reduction of tooth mobility may enhance the effect of periodontal therapy.

Periodontal manifestations of systemic diseases and developmental and acquired conditions: Consensus report of workgroup 3 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions.

BACKGROUND: A variety of systemic diseases and conditions can affect the course of periodontitis or have a negative impact on the periodontal attachment apparatus. Gingival recessions are highly prevalent and often associated with hypersensitivity, the development of caries and non-carious cervical lesions on the exposed root surface and impaired esthetics. Occlusal forces can result in injury of teeth and periodontal attachment apparatus. Several developmental or acquired conditions associated with teeth or prostheses may predispose to diseases of the periodontium. The aim of this working group was to review and update the 1999 classification with regard to these diseases and conditions, and to develop case definitions and diagnostic considerations. METHODS: Discussions were informed by four reviews on 1) periodontal manifestions of systemic diseases and conditions; 2) mucogingival conditions around natural teeth; 3) traumatic occlusal forces and occlusal trauma; and 4) dental prostheses and tooth related factors. This consensus report is based on the results of these reviews and on expert opinion of the participants. RESULTS: Key findings included the following: 1) there are mainly rare systemic conditions (such as Papillon-Lefevre Syndrome, leucocyte adhesion deficiency, and others) with a major effect on the course of periodontitis and more common conditions (such as diabetes mellitus) with variable effects, as well as conditions affecting the periodontal apparatus independently of dental plaque biofilm-induced inflammation (such as neoplastic diseases); 2) diabetes-associated periodontitis should not be regarded as a distinct diagnosis, but diabetes should be recognized as an important modifying factor and included in a clinical diagnosis of periodontitis as a descriptor; 3) likewise, tobacco smoking - now considered a dependence to nicotine and a chronic relapsing medical disorder with major adverse effects on the periodontal supporting tissues - is an important modifier to be included in a clinical diagnosis of periodontitis as a descriptor; 4) the importance of the gingival phenotype, encompassing gingival thickness and width in the context of mucogingival conditions, is recognized and a novel classification for gingival recessions is introduced; 5) there is no evidence that traumatic occlusal forces lead to periodontal attachment loss, non-carious cervical lesions, or gingival recessions; 6) traumatic occlusal forces lead to adaptive mobility in teeth with normal support, whereas they lead to progressive mobility in teeth with reduced support, usually requiring splinting; 7) the term biologic width is replaced by supracrestal tissue attachment consisting of junctional epithelium and supracrestal connective tissue; 8) infringement of restorative margins within the supracrestal connective tissue attachment is associated with inflammation and/or loss of periodontal supporting tissue. However, it is not evident whether the negative effects on the periodontium are caused by dental plaque biofilm, trauma, toxicity of dental materials or a combination of these factors; 9) tooth anatomical factors are related to dental plaque biofilm-induced gingival inflammation and loss of periodontal supporting tissues. CONCLUSION: An updated classification of the periodontal manifestations and conditions affecting the course of periodontitis and the periodontal attachment apparatus, as well as of developmental and acquired conditions, is introduced. Case definitions and diagnostic considerations are also presented.

Comparative Effects of Interventions on Phantom Limb Pain: A Network Meta-Analysis.

BACKGROUND: Phantom limb pain (PLP) is a common type of chronic pain that occurs after limb amputation. Many treatment approaches are available; however, the treatment of PLP is still a challenge. This study aimed to quantify and rank the efficacy of interventions for phantom limb pain. METHODS: A comprehensive literature search was performed using the databases of PubMed, MEDLINE, Embase, Web of Science, and Cochrane. A network meta-analysis was applied to formulate direct and indirect comparisons among interventions for PLP. RESULTS: Twenty-two studies comprising 662 patients and 13 different interventions were included in this study. The mirror therapy (MT) (-1.00; 95% confidence interval, -1.94 to -0.07) and MT + phantom exercise (PE) (-6.05; 95% confidence interval, -8.29 to -3.81) group presented significantly lower pain intensity compared with placebo. In SUCRA (surface under the cumulative ranking curve) analysis, the MT+PE and neuromodulation techniques groups had the highest SUCRA value (81.2). CONCLUSIONS: Our results suggest that MT is the most optimal treatment for PLP, and a combination of therapies would enhance the therapeutic effect.

Automatic range of motion measurement via smartphone images for telemedicine examination of the hand.

BACKGROUND: Telemedicine support virtual consultations and evaluations in hand surgery for patients in remote areas during the COVID-19 era. However, traditional physical examination is challenging in telemedicine and it is inconvenient to manually measure the hand range of motion (ROM) from images or videos. Here, we propose an automatic method using the hand pose estimation technique, aiming to measure the hand ROM from smartphone images. METHODS: Twenty-eight healthy volunteers participated in the study. An eight-hand gestures measurement protocol and the Google MediaPipe Hands were used to analyze images and calculate the ROM automatically. Manual goniometry was also performed according to the guideline of the American Medical Association. The correlation between the automatic and manual methods was analyzed by the intraclass correlation coefficient and Pearson correlation coefficient. The clinical acceptance was testified using Bland-Altman plots. RESULTS: A total of 32 parameters of each hand were measured by both methods, and 1792 measurement results were compared. The mean difference between automatic and manual methods is -2.21 ± 9.29° in the angle measurement and 0.48 ± 0.48 cm in the distance measurement. The intraclass correlation coefficient of 75% of parameters was higher than 0.75, the Pearson correlation coefficient of 84% of parameters was over 0.6, and 40.6% of parameters reached well-accepted clinical agreements. CONCLUSIONS: The proposed method provides a helpful protocol for automatic hand ROM measurement based on smartphone images and the MediaPipe Hands pose estimation technique. The automatic measurement is acceptable and comparable with existing methods, showing a possible application in the telemedicine examination of hand surgery.

Precision and accuracy of measuring finger motion with a depth camera: a cross-sectional study of healthy participants.

The purpose of this cross-sectional study was to determine the precision and accuracy of the measurement of finger motion with a depth camera. Fifty-five healthy adult hands were included. Measurements were done with a depth camera and compared with traditional manual goniometer measurements. Repeated measuring showed that the overall repeatability and reproducibility of extension measured with the depth camera were within 3° and 4° and that of flexion were within 13° and 14°. Compared with traditional manual goniometry, biases of extension of all finger joints and flexion of metacarpophalangeal joints were less than 5°, and the average bias of flexion of proximal and distal interphalangeal joints was 29°. We conclude that the measurement of finger extension and flexion of the metacarpophalangeal joints with a depth camera was reliable, but improvement is required in the precision and accuracy of interphalangeal joint flexion.

Validity and Reliability of a Depth Camera-Based Quantitative Measurement for Joint Motion of the Hand.

Purpose: Quantitative measurement of hand motion is essential in evaluating hand function. This study aimed to investigate the validity and reliability of a novel depth camera-based contactless automatic measurement system to assess hand range of motion and its potential benefits in clinical applications. Methods: Five hand gestures were designed to evaluate the hand range of motion using a depth camera-based measurement system. Seventy-one volunteers were enrolled in performing the designed hand gestures. Then, the hand range of motion was measured with the depth camera and manual procedures. System validity was evaluated based on 3 dimensions: repeatability, within-laboratory precision, and reproducibility. For system reliability, linear evaluation, the intraclass correlation coefficient, paired t -test and bias were employed to test the consistency and difference between the depth camera and manual procedures. Results: When measuring phalangeal length, repeatability, within-laboratory precision, and reproducibility were 2.63%, 12.87%, and 27.15%, respectively. When measuring angles of hand motion, the mean repeatability and within-laboratory precision were 1.2° and 3.3° for extension of 5 digits, 2.7° and 10.2° for flexion of 4 fingers, and 3.1° and 5.3° for abduction of 4 metacarpophalangeal joints, respectively. For system reliability, the results showed excellent consistency (intraclass correlation coefficient = 0.823; P < .05) and good linearity with the manual procedures (r = 0.909-0.982, approximately; P < .001). Besides, 78.3% of the measurements were clinically acceptable. Conclusions: Our depth camera-based evaluation system provides acceptable validity and reliability in measuring hand range of motion and offers potential benefits for clinical care and research in hand surgery. However, further studies are required before clinical application. Clinical relevance: This study suggests a depth camera-based contactless automatic measurement system holds promise for assessing hand range of motion in hand function evaluation, diagnosis, and rehabilitation for medical staff. However, it is currently not adequate for all clinical applications.

Predictive markers for anti-inflammatory treatment response in thyroid eye disease.

Anti-inflammatory treatment is the primary and vital therapeutic approach for active, moderate-to-severe thyroid eye disease (TED). Accurate pretreatment prediction of treatment response is of paramount importance for the prognosis of patients. However, relying solely on the clinical activity score asa determinant of activity has led to unsatisfactory treatment outcomes. In recent years, significant advancements have been made in identifying predictive markers for anti-inflammatory treatment response in TED, clinical markers, body fluid biomarkers and imaging biomarkers. Several clinical studies have developed prediction models based on these markers. However, there is still a lack of comprehensive elucidation or comparison between the different markers. Therefore, this review aims to provide a detailed analysis of the definition, characteristics, and application of predictive markers for anti-inflammatory treatment response in TED. Through detailed literature search, 26 articles applying anti-inflammatory treatment effect prediction with a total of 1948 TED patients were used for analysis and discussion. By gaining a better understanding of the current research on predictive markers, we can accelerate and guide the exploration of treatment prediction strategies, leading us towards an era of precise therapy for TED.

The neuropathological mechanism of EV-A71 infection attributes to inflammatory pryoptosis and viral replication via activating the hsa_circ_0045431/ hsa_miR_584/NLRP3 regulatory axis.

Neuropathological damage has been considered to be the main cause of death from EV-A71 infection, but the underlying mechanism has not been elucidated. Pyroptosis, a new form of inflammatory programmed cell death, has been verified to be involved in the pathogenesis of various viruses. circRNAs are a novel type of endogenous noncoding RNA gaining research interest in recent years, especially their special roles in the process of virus infection. Thus, in this study, we combined EV-A71, pyroptosis and circRNA to find a breakthrough in the pathogenesis of EV-A71 infection. Firstly, whether EV-A71 infection leaded to pyroptosis formation was examined by a series detection of cell death, cell viability, LDH release, caspase 1 activity, the expression levels of pyroptosis-related molecules and the concentrations of IL-1ß and IL-18. Secondly, high-throughput sequencing of circRNAs was carried out to excavate the circRNA-miRNA-mRNA regulatory axis which might be associated with pyroptosis formation. Finally, the gain- and loss-of-functional experiments were further conducted to identify their functions. Our results showed that EV-A71 infection caused pyroptosis formation in SH-SY5Y cells. The circRNA sequencing analyzed the differentially expressed circRNAs and their possible functions. It was found that the hsa_circ_0045431/hsa_miR_584/NLRP3 regulatory axis might be involved in pyroptosis formation during EV-A71 infection. Then, hsa_circ_0045431 sponged hsa_miR_584 and hsa_miR_584 directly targeted NLRP3 were validated by IF, dual-luciferase, qRT-PCR and WB assays. Functional experiments were performed to further uncover that the up-regulation of hsa_circ_0045431 and NLRP3 promoted the inflammatory pyroptosis and viral replication, while the up-regulation of hsa_miR_584 suppressed the inflammatory pyroptosis and viral replication, and vice versa. Collectively, our study demystified that EV-A71 infection induced pyroptosis formation by activating hsa_circ_0045431/hsa_miR_584/NLRP3 regulatory axis, which could further effect viral replication. These findings provided novel insights into the pathogenesis of EV-A71 infection, and meanwhile revealed that the hsa_circ_0045431/ hsa_miR_584/NLRP3 regulatory axis can serve as a potential biological therapeutic target for EV-A71 infection.

Value of the combination of a smartphone-compatible infrared camera and a hand-held doppler ultrasound in preoperative localization of perforators in flaps.

This study was conducted to evaluate the effectiveness of the FLIR ONE PRO, a thermal imaging camera for smartphones, combined with handheld Doppler (HHD) in the localization of perforator arteries and to assess the efficacy of the FLIR ONE PRO in distinguishing perforators of the descending branch of the lateral circumflex femoral artery (LCFA) from other perforators of the anterolateral thigh perforator (ALTP) flap. We enrolled 29 free perforator flaps from 22 patients in our study. Before surgery, dynamic infrared thermography was performed using a FLIR ONE PRO to visualize hotspots on the flaps. Subsequently, HHD was used to further determine the perforators under the hotspots, which were ultimately identified and confirmed through intraoperative findings. Additionally, infrared images of the ALTP flap were analyzed using FLIR Tools. The performances of the FLIR ONE PRO and FLIR ONE PRO + HHD groups were evaluated by comparing the intraoperative findings. Using FLIR ONE PRO + HHD, 119 hotspots and 106 perforators were identified during surgery. Using FLIR ONE PRO + HHD, sensitivity and positive predictive value were 97.87% and 88.46%, respectively, in the young (age≤45 years). In the elderly group (age>45 years), these percentages were 93.22% and 82.09%, respectively. In addition, we found that the FLIR ONE PRO could be useful for differentiating perforators in the descending branch of the LCFA from other perforators within 5 min. The results showed a sensitivity of 96.15%, a specificity of 98.9%, a positive predictive value of 96.15%, and a negative predictive value of 98.9%. Compared to using FLIR ONE PRO alone, the combined application of HHD and FLIR ONE PRO had a higher value in perforator localization by increasing the positive predictive value. The FLIR ONE PRO may have significance in the rapid prediction of perforators deriving from the descending branch of the LCFA.

Sensory attributes, chemical and microbiological properties of cigars aged with different media.

Introduction: Aging is an important process to improve the quality of cigar, but the effect of aging with media on cigar has not been reported.Therefore, this study aimed to prepare different aging media and clarify the influence of media on cigar quality. Methods: Effective media were first screened by sensory evaluation, then the effects of aging media on the chemical composition and microbial community of cigar were investigated. Results: The results showed that: 1) As aging media, coffee formula and cocoa formula could optimize the smoke and aroma characteristics of cigar, and 30 days was the appropriate period for cigar aging. 2) Aging with coffee or cocoa media could increase the content of amino acids, non-volatile organic acids, malic acid and aroma components. Particularly, the content of aroma components increased from 2.48 mg g-1 (W-30) to 3.21 mg g-1 (C-30) and 3.70 mg g-1 (K-30), respectively. 3) Aging with coffee can improve the diversity of bacteria and fungi on the cigar surface and change the succession rule of bacterial community. In contrast, aging with cocoa had no significant effect on microbial diversity of cigar. Discussion: In this study, the influence of aging media on cigar quality was analyzed multidimensionally for the first time, which provided a reference for the development of new aging media and technologies to improve cigar quality.

[Accuracy of key point matrix technology based contactless automatic measurement for joint motion of hand].

Objective: To validate the use of key point matrix technology based contactless automatic measurement for evaluation of joint motion of hand. Methods: Thirty-three volunteers were enrolled to evaluate the extension and flexion of hand joints between May 2021 and November 2021. There were 20 males and 13 females, the age ranged from 16 to 70 years with an average of 30.2 years. The extension angles of 14 joints of 5 fingers (including hyperextension) and the flexion angles of 12 joints of 4 fingers (excluding thumb) of volunteers were measured by key point matrix technology and manual goniometer, respectively. Then 5 participants and repeated measurement experiment were employed to test the system repeatability and accuracy; 28 participants and paired measurement experiment were employed to test the system accuracy. Results: The average repeatability of finger joint motion measured by the key point matrix technology was 1.801° (extension) and 7.823° (flexion), respectively. Compared with manual measurement, the average differences of each finger joint measured by the key point matrix technology were 3.225° in extension and 14.145° in flexion, respectively. The key point matrix technology based contactless automatic evaluation system offered excellent consistency with the manual goniometers ( ICC=0.875). While most of the consistency with manual goniometer of individual joints were at moderate levels (median of ICC, 0.440). The correlation coefficients between the measurement results of the two methods were mainly positive in the extension of the joint ( P<0.05) and negative in the flexion of the joints ( P<0.05). Conclusion: The key point matrix technology based contactless automatic evaluation provides sufficient measurement repeatability and accuracy in evaluation for the joint motion of hand.

Automatic Detection of Horner Syndrome by Using Facial Images.

Horner syndrome is a clinical constellation that presents with miosis, ptosis, and facial anhidrosis. It is important as a warning sign of the damaged oculosympathetic chain, potentially with serious causes. However, the diagnosis of Horner syndrome is operator dependent and subjective. This study aims to present an objective method that can recognize Horner sign from facial photos and verify its accuracy. A total of 173 images were collected, annotated, and divided into training and testing groups. Two types of classifiers were trained (two-stage classifier and one-stage classifier). The two-stage method utilized the MediaPipe face mesh to estimate the coordinates of landmarks and generate facial geometric features accordingly. Then, ten machine learning classifiers were trained based on this. The one-stage classifier was trained based on one of the latest algorithms, YOLO v5. The performance of the classifier was evaluated by the diagnosis accuracy, sensitivity, and specificity. For the two-stage model, the MediaPipe successfully detected 92.2% of images in the testing group, and the Decision Tree Classifier presented the highest accuracy (0.790). The sensitivity and specificity of this classifier were 0.432 and 0.970, respectively. As for the one-stage classifier, the accuracy, sensitivity, and specificity were 0.65, 0.51, and 0.84, respectively. The results of this study proved the possibility of automatic detection of Horner syndrome from images. This tool could work as a second advisor for neurologists by reducing subjectivity and increasing accuracy in diagnosing Horner syndrome.

Automatic detection of abnormal hand gestures in patients with radial, ulnar, or median nerve injury using hand pose estimation.

Background: Radial, ulnar, or median nerve injuries are common peripheral nerve injuries. They usually present specific abnormal signs on the hands as evidence for hand surgeons to diagnose. However, without specialized knowledge, it is difficult for primary healthcare providers to recognize the clinical meaning and the potential nerve injuries through the abnormalities, often leading to misdiagnosis. Developing technologies for automatically detecting abnormal hand gestures would assist general medical service practitioners with an early diagnosis and treatment. Methods: Based on expert experience, we selected three hand gestures with predetermined features and rules as three independent binary classification tasks for abnormal gesture detection. Images from patients with unilateral radial, ulnar, or median nerve injuries and healthy volunteers were obtained using a smartphone. The landmark coordinates were extracted using Google MediaPipe Hands to calculate the features. The receiver operating characteristic curve was employed for feature selection. We compared the performance of rule-based models with logistic regression, support vector machine and of random forest machine learning models by evaluating the accuracy, sensitivity, and specificity. Results: The study included 1,344 images, twenty-two patients, and thirty-four volunteers. In rule-based models, eight features were finally selected. The accuracy, sensitivity, and specificity were (1) 98.2, 91.7, and 99.0% for radial nerve injury detection; (2) 97.3, 83.3, and 99.0% for ulnar nerve injury detection; and (3) 96.4, 87.5, and 97.1% for median nerve injury detection, respectively. All machine learning models had accuracy above 95% and sensitivity ranging from 37.5 to 100%. Conclusion: Our study provides a helpful tool for detecting abnormal gestures in radial, ulnar, or median nerve injuries with satisfying accuracy, sensitivity, and specificity. It confirms that hand pose estimation could automatically analyze and detect the abnormalities from images of these patients. It has the potential to be a simple and convenient screening method for primary healthcare and telemedicine application.

High-Performance Organic Solar Modules via Bilayer-Merged-Annealing Assisted Blade Coating.

Although encouraging progress is being made on spin-coated prototype cells, organic solar cells (OSCs) still face significant challenges, yet to be explored, for upscaling the multi-stacked photoactive layers in the construction of large-area modules. Herein, high-performance opaque and semitransparent organic solar modules are developed via a bilayer-merged-annealing (BMA)-assisted blade-coating strategy, achieving impressive efficiencies of 14.79% and 12.01% with respect to active area of 18.73 cm2 , which represent the best organic solar minimodules so far. It is revealed that the BMA strategy effectively resolves the de-wetting issues between polar charge transport layer solution and non-polar bulk heterojunction blends, hence improving the film coverage, along with electronic and electric contacts of multi-stacked photoactive layers. As result, organic solar modules coated under ambient conditions successfully retain the high-efficiency of small-area cells upon 312 times area scaling-up. Overall, this work provides a facile and effective method to fabricate high-performance organic solar modules under ambient conditions.

Gene expression profiles for an immunoscore model in bone and soft tissue sarcoma.

BACKGROUND: Immune infiltration is a prognostic marker to clinical outcomes in various solid tumors. However, reports that focus on bone and soft tissue sarcoma are rare. The study aimed to analyze and identify how immune components influence prognosis and develop a novel prognostic system for sarcomas. METHODS: We retrieved the gene expression data from 3 online databases (GEO, TCGA, and TARGET). The immune fraction was estimated using the CIBERSORT algorithm. After that, we re-clustered samples by K-means and constructed immunoscore by the least absolute shrinkage and selection operator (LASSO) Cox regression model. Next, to confirm the prognostic value, nomograms were constructed. RESULTS: 334 samples diagnosed with 8 tumor types (including osteosarcoma) were involved in our analysis. Patients were next re-clustered into three subgroups (OS, SAR1, and SAR2) through immune composition. Survival analysis showed a significant difference between the two soft tissue groups: patients with a higher proportion of CD8+ T cells, macrophages M1, and mast cells had favorable outcomes (p=0.0018). Immunoscore models were successfully established in OS and SAR2 groups consisting of 12 and 9 cell fractions, respectively. We found immunosocre was an independent factor for overall survival time. Patients with higher immunoscore had poor prognosis (p<0.0001). Patients with metastatic lesions scored higher than those counterparts with localized tumors (p<0.05). CONCLUSIONS: Immune fractions could be a useful tool for the classification and prognosis of bone and soft tissue sarcoma patients. This proposed immunoscore showed a promising impact on survival prediction.

DNA methylation patterns-based subtype distinction and identification of soft tissue sarcoma prognosis.

ABSTRACT: Soft tissue sarcomas (STSs) are heterogeneous at the clinical with a variable tendency of aggressive behavior. In this study, we constructed a specific DNA methylation-based classification to identify the distinct prognosis-subtypes of STSs based on the DNA methylation spectrum from the TCGA database. Eventually, samples were clustered into 4 subgroups, and their survival curves were distinct from each other. Meanwhile, the samples in each subgroup reflected differentially in several clinical features. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was also conducted on the genes of the corresponding promoter regions of the above-described specific methylation sites, revealing that these genes were mainly concentrated in certain cancer-associated biological functions and pathways. In addition, we calculated the differences among clustered methylation sites and performed the specific methylation sites with LASSO algorithm. The selection operator algorithm was employed to derive a risk signature model, and a prognostic signature based on these methylation sites performed well for risk stratification in STSs patients. At last, a nomogram consisted of clinical features and risk score was developed for the survival prediction. This study declares that DNA methylation-based STSs subtype classification is highly relevant for future development of personalized therapy as it identifies the prediction value of patient prognosis.

Novel therapeutic compounds for prostate adenocarcinoma treatment: An analysis using bioinformatic approaches and the CMap database.

INTRODUCTION: Prostate adenocarcinoma is the most frequently diagnosed malignancy, particularly for people >70 years old. The main challenge in the treatment of advanced neoplasm is bone metastasis and therapeutic resistance for known oncology drugs. Novel treatment methods to prolong the survival time and improve the life quality of these specific patients are required. The present study attempted to screen potential therapeutic compounds for the tumor through bioinformatics approaches, in order to provide conceptual treatment for this malignant disease. METHODS: Differentially expressed genes were obtained from the Gene Expression Omnibus database and submitted into the Connectivity Map database for the detection of potentially associated compounds. Target genes were extracted from the search results. Functional annotation and pathway enrichment were performed for the confirmation. Survival analysis was used to measure potential therapeutic effects. RESULTS: It was revealed that 3 compounds (vanoxerine, tolnaftate, and gabexate) may help to prolong the disease-free survival time from tumor metastasis of patients with the tumor. A total of 6 genes [also-keto reductase family 1 member C3 (AKR1C3), collagen type III α 1 chain (COL3A1), lipoprotein lipase (LPL), glucuronidase, ß pseudogene 11 (GUSBP11), apolipoprotein E (APOE), and collagen type I α 1 chain (COL1A1)] were identified to be the potential therapeutic targets for the aforementioned compounds. CONCLUSION: In the present study, it was speculated that 3 compounds may function as the potential therapeutic drugs of bone metastatic prostate adenocarcinoma; however, further studies verifying vitro and in vivo are necessary.

Agricultural nanodiagnostics for plant diseases: recent advances and challenges.

Crop diseases caused by pathogenic microorganisms pose severe threats to the global food supply. Effective diagnostic tools for timely determination of plant diseases become essential to the assurance of agricultural sustainability and global food security. Nucleic acid- and antibody-based molecular assays are gold-standard methodologies for the diagnosis of plant diseases, but the analyzing procedures are complex and laborious. The prominent physical or chemical properties of nanomaterials have enabled their use as innovative and high-performance diagnostic tools for numerous plant pathogens and other important disease biomarkers. Engineered nanomaterials have been incorporated into traditional laboratory molecular assays or sequencing technologies that offer notable enhancement in sensitivity and selectivity. Meanwhile, nanostructure-supported noninvasive detection tools combined with portable imaging devices (e.g., smartphones) have paved the way for fast and on-site diagnosis of plant diseases and long-term monitoring of plant health conditions, especially in resource-poor settings.