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The potential of hyperspectral measurements for early disease detection has been investigated by many experts over the last 5 years. One of the difficulties is obtaining enough data for training and building a hyperspectral training library. When the goal is to detect disease at a previsible stage, before the pathogen has manifested either its first symptoms or in the area surrounding the existing symptoms, it is impossible to objectively delineate the regions of interest containing the previsible pathogen growth from the areas without the pathogen growth. To overcome this, we propose an image labelling and segmentation algorithm that is able to (a) more objectively label the visible symptoms for the construction of a training library and (b) extend this labelling to the pre-visible symptoms. This algorithm is used to create hyperspectral training libraries for late blight disease (Phytophthora infestans) in potatoes and two types of leaf rust (Puccinia triticina and Puccinia striiformis) in wheat. The model training accuracies were compared between the automatic labelling algorithm and the classic visual delineation of regions of interest using a logistic regression machine learning approach. The modelling accuracies of the automatically labelled datasets were higher than those of the manually labelled ones for both potatoes and wheat, at 98.80% for P. infestans in potato, 97.69% for P. striiformis in soft wheat, and 96.66% for P. triticina in durum wheat.

The philosophy of management of gall bladder cancer ranges from the Japanese aggressive approach (major supra-radical multi-organ resections for advanced disease) at one end to the western pessimistic nihilism (inappropriate management of even early disease) at the other. An Indian “Buddhist” middle path, i.e., aggressive surgical approach towards early (and incidental) gall bladder cancer and non-surgical palliation for advanced gall bladder cancer has been advocated by the author (VKK).

Improving diagnostics has been one of the most important challenges facing health systems in recent years, due to innovation and scientific research, image classification techniques, medical information management systems brought about by health technology, and developments never seen before that enable major breakthroughs in the areas of prevention, early disease detection, and disease control. Blood is investigated through blood count, which is subordinate to manual and/or automated procedures. This reliance on medical fields for new innovations directs this chapter to the development of a deep learning framework for classifying white cell subtypes in digital images that fits the criteria for reliability and efficiency of blood cell detection, making the methodology more accessible to diverse populations. Because laboratory medical examinations are often costly and inaccessible to populations of underdeveloped and developing countries, it is of great importance to create tools that facilitate the obtaining of medical reports at low cost and with high reliability. For this, Python using a Jupyter notebook was developed and experiments were conducted using a dataset containing 12,500 digital images of human blood smear fields comprising nonpathological leukocytes. As a result, the accuracy of the approach was 86.17%, demonstrating the high reliability of the methodology. Therefore the algorithm is considered a reliable, accurate, and inexpensive method and can be employed as the third most practicable procedure for blood counts for often underprivileged people of developing and underdeveloped countries.

The incidence of all head and neck malignancies is rising worldwide, with carcinoma of the larynx constituting approximately 1% of all cancers. Glottic cancer responds quite favorably to intervention due to its early presentation, coupled with the low rate of regional and distant metastases. This chapter discusses risk factors for laryngeal cancer, evidence for diagnostic testing modalities, and current treatment options for early disease.

An automated system for citrus disease detection relies upon using computer-aided tools. By minimizing manual error in disease detection and diagnosis, the computer-aided diagnostic (CAD) tools have acquired a major role in the resources needed to boost and increase the efficiency in production yield. The CAD tools have the properties of automatically speeding up the system’s decision-making capability on the complex disease data. Since these plant diseases can be devastating in terms of economic loss and loss of nutrition, the need for disease detection is growing at an early stage in order to meet human nutritional needs. The use of these computer-aided methods has enabled reducing the loss of production and early disease detection. This article proposes a machine learning-based methodology to automate the process of disease detection thereby reducing the manual efforts. While designing the complete system, the optimization and improvement at every substage are considered in this article so that the complete system possesses high levels of accuracy and thereby can equip farmers to deploy disease detection in a better way.

In the past several decades, acoustic wave biosensors, as an emerging kind of biosensors, have been developed and widely used for the detection of mass, viscosity, conductivity and density. Varieties of applications have been explored such as medical diagnosis, drug screening, environmental monitoring, food analysis and biochemical assay. Among them, the detection of disease-related biomarkers based on acoustic sensors has aroused great research interest all over the world. In this review, the classification and characteristics of acoustic wave biosensors are briefly introduced. Then, some classical studies and recent advances in disease-related biomarker detection utilizing these biosensors are summarized and detailed, respectively. Here, the disease-related biomarkers mainly include antigens, small molecular proteins, cancer cells, viruses and VOCs. Finally, challenges and future trends of these typical acoustic wave biosensors are discussed. Compared with other reviews of acoustic wave sensors, this review highlights the great potential of typical acoustic wave biosensors for early disease screening and diagnosis compared with widely-used medical imaging. Moreover, they are integrated with other technologies for the design of multi-analyte, multi-parameter and intelligent devices, collecting more comprehensive information from biomarkers. This review provides a new perspective on the applications and optimization of acoustic wave biosensors to develop more reliable platforms for disease-related biomarker detection and disease diagnosis.

BackgroundBlood-based amyloid biomarkers may provide a non-invasive, cost-effective and scalable manner for detecting cerebral amyloidosis in early disease stages.MethodsIn this prospective cross-sectional study, we quantified plasma Aβ1–42/Aβ1–40ratios with both routinely available ELISAs and novel SIMOA Amyblood assays, and provided a head-to-head comparison of their performances to detect cerebral amyloidosis in a nondemented elderly cohort (n = 199). Participants were stratified according to amyloid-PET status, and the performance of plasma Aβ1–42/Aβ1–40to detect cerebral amyloidosis was assessed using receiver operating characteristic analysis. We additionally investigated the correlations of plasma Aβ ratios with amyloid-PET and CSF Alzheimer’s disease biomarkers, as well as platform agreement using Passing-Bablok regression and Bland-Altman analysis for both Aβ isoforms.ResultsELISA and SIMOA plasma Aβ1–42/Aβ1–40detected cerebral amyloidosis with identical accuracy (ELISA: area under curve (AUC) 0.78, 95% CI 0.72–0.84; SIMOA: AUC 0.79, 95% CI 0.73–0.85), and both increased the performance of a basic demographic model including only age andAPOE-ε4genotype (p ≤ 0.02). ELISA and SIMOA had positive predictive values of respectively 41% and 36% in cognitively normal elderly and negative predictive values all exceeding 88%. Plasma Aβ1–42/Aβ1–40correlated similarly with amyloid-PET for both platforms (Spearmanρ = − 0.32,p 1–42/t-tau were stronger for ELISA (ρ = 0.41,p = 0.002) than for SIMOA (ρ = 0.29,p = 0.03). Plasma Aβ levels demonstrated poor agreement between ELISA and SIMOA with concentrations of both Aβ1–42and Aβ1–40measured by SIMOA consistently underestimating those measured by ELISA.ConclusionsELISA and SIMOA demonstrated equivalent performances in detecting cerebral amyloidosis through plasma Aβ1–42/Aβ1–40, both with high negative predictive values, making them equally suitable non-invasive prescreening tools for clinical trials by reducing the number of necessary PET scans for clinical trial recruitment.Trial registrationEudraCT 2009-014475-45 (registered on 23 Sept 2009) and EudraCT 2013-004671-12 (registered on 20 May 2014,https://www.clinicaltrialsregister.eu/ctr-search/trial/2013-004671-12/BE).

Real-time and rapid detection of various biomarkers in body fluids has important significance for early disease diagnosis, efficient monitoring of treatment, and evaluation of prognosis. However, traditional detection methods not only require bulky and costly instruments but also are not suitable for the analysis of heterogeneous samples (e.g., serum and urine), limiting their applications in point-of-care testing (POCT). Herein, an integrated photoacoustic (PA) device with a smartphone as the acoustic signal readout has been constructed, greatly reducing the volume and cost of the instrument, and providing a potential miniature platform for POCT of clinical samples. By exploiting the electron transfer product of 3,3',5,5'-tetramethylbenzidine (TMB) (i.e., TMB++) as the PA probe and hemin-graphene oxide (H-GO) complex as the peroxidase, quantitative analysis of uric acid was successfully performed by using only 30 μL of a sample solution. Due to the favorable stability of artificial enzymes, reaction reagents could be effectively embedded in agar gel to make a portable "test strip". Therefore, operators just need to drop clinical samples on the "test strip" for PA analysis, which is user friendly without requiring complex sample preparation steps. In addition, since the acoustic change mainly comes from the PA effect, it has a lower background signal than UV-vis and fluorescence analysis, greatly improving the analytical performance. The simplicity, low cost, and broad adaptability make this miniature PA device attractive for on-site detection, particularly in resource-limited settings.

Introduction: The eyebrows are an important facial feature that shape one’s physical appearance and play a role in non-verbal communication. Partial or complete eyebrow loss is seen in most patients with frontal fibrosing alopecia (FFA). Despite the scarring nature of FFA, eyebrow hair regrowth has been previously reported. Nevertheless, treatment options and supporting evidence remain scarce. Case Presentation: We report eyebrow regrowth in 7 patients with FFA treated with low-dose oral minoxidil (OM). Conclusion: Low-dose OM could be a promising adjunctive therapy for treatment of the eyebrows in patients with FFA, particularly in early disease.

We thank Ronnelid et al for their comments on our paper, ‘Performance of the 2019 EULAR/ACR classification criteria for systemic lupus erythematosus in early disease, across sexes, and ethnicities.’1 In 2019, the authors comparatively evaluated the ‘diagnostic accuracy’ of the 2019 European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR) systemic lupus erythematosus (SLE) criteria2 3 against the 2012 Systemic Lupus International Collaborating Clinics (SLICC) criteria. In referring to their paper,4 we stated that it is inappropriate to evaluate the 2019 EULAR/ACR criteria as diagnostic criteria. Ronnelid et al now point out that diagnostic use of the criteria was not their intention. They make the point that they used the term diagnostic, as diagnostic sensitivity …

This study analyzed the early cancer detection in Russia. Using data from the Russian Ministry of Health from 2005 to 2016, this study aims to evaluate relationships between the number of patients diagnosed with I-II stage of cancer with the number of preventive visits, screening tests, and expedited access to specialists. The results of de-trending time-series model indicate that the number of specialists in outpatient facilities and the number of patients' preventive visits positively affect the number of patients diagnosed with cancer for the first time and the number of patients diagnosed with I-II degree cancer. The Russian Federation's experience suggests that early detection of cancer can be achieved by increasing the number of early cancer screening facilities, providing free screening, and moderating geographical and time constraints that prevent people of different geographic and socio-economic backgrounds from being screened. Another strategy includes dispelling myths associated with cancer screening, fostering outreach and patient education, and assuring availability and timely referrals to specialists and laboratory work.

Circulating biomarkers such as microRNAs (miRNAs), short noncoding RNA strands, represent prognostic and diagnostic indicators for a variety of physiological disorders making their detection and quantification an attractive approach for minimally invasive early disease diagnosis. However, highly sensitive and selective detection methods are required given the generally low abundance of miRNAs in body fluids together with the presence of large amounts of other potentially interfering biomolecules. Although a variety of miRNA isolation and detection methods have been established in clinics, they usually require trained personnel and often constitute labor-, time- and cost-intensive approaches. During the last years, nanoparticle-based biosensors have received increasing attention due to their superior detection efficiency even in very low concentration regimes. This is based on their unique physicochemical properties in combination with their high surface area that allows for the immobilization of multiple recognition sites resulting in fast and effective recognition of analytes. Among various materials, magnetic nanoparticles have been identified as useful tools for the separation, concentration, and detection of miRNAs. Here, we review state-of-the-art technology with regard to magnetic particle-based miRNA detection from body fluids, critically discussing challenges and future perspective of such biosensors while comparing their handling, sensitivity as well as selectivity against the established miRNA isolation and detection methods.

Rationale:Individuals that will develop chronic obstructive pulmonary disease(COPD) could be identified at an early age before clinical manifestations appear. Objective:We investigated risk of Clinical COPD 10 years later in young adults from the general population with and without Early COPD with a focus on smoking exposure. Methods:We included 14,870 individuals aged 20-100 from the Copenhagen General Population Study with spirometry 10 years apart. Early COPD was defined as baseline forced expiratory volume in 1second(FEV1)/forced vital capacity(FVC)

Background The impact of different disease stages and treatment for human epidermal growth factor 2 positive (HER2-positive) breast cancer (BC) on work productivity and health-related quality of life (HRQoL) is poorly understood. Methods This was a UK cross-sectional study of 299 adult patients with HER2-positive early or metastatic BC (NCT03099200). Productivity was assessed using the work productivity and activity impairment scale; HRQoL was measured using EuroQol-5 Dimensions-5 levels (EQ-5D-5L), and Functional Assessment of Cancer Therapy Breast (FACT-G and -B) instruments. Three balanced patient groups were recruited: (1) early BC on treatment post-surgery, (2) early BC after completion of adjuvant treatment, (3) during metastatic BC treatment. Between-group comparisons were performed using an analysis of variance. Results Group 1 comprised 89 patients, Group 2, 108 and Group 3, 102. Age, ethnicity and comorbidities were similar across groups. Patients in Group 3 reported more often being unable to work (significant Bonferroni adjusted p p = 0.002). Group 2 also had significantly lower levels of work absenteeism and overall work impairment compared with Group 1 (p p ≤ 0.002), moderate or worse problems in the EQ-5D-5L self-care and usual activity domains (p ≤ 0.001), and lower HRQoL as assessed by FACT summary scores (p p Conclusions Metastatic disease and treatment of HER2-positive BC adversely impacted on work productivity and HRQoL. The results of this study support the idea that being able to delay or prevent the metastatic recurrence of BC, for example by extending the time patients are in remission or at early stage of BC, has wider benefits in terms of patient productivity and HRQoL.

Hydroxychloroquine (HCQ) exerts antiviral effects through several mechanisms. Our initial experience suggests that HCQ could be used for prophylaxis of COVID-19 infection in health care workers (HCW) and could help to control the virus in the early disease stages. We suggest a prophylactic strategy with HCQ for autumn-winter-spring 2020-2021.

Search for methods of quick human organism condition estimation, early disease and pathology detection including...

Everyday wearables such as smartwatches or smart bands can play a pivotal role in the field of fitness and wellness and hold the prospect to be used for early disease detection and monitoring towards Smart Health (sHealth). One of the challenges is the extraction of reliable biomarkers from data collected using these devices in the real world (Living Labs). In this yearlong field study, we collected the nocturnal instantaneous heart rate from 9 participants using wrist-worn commercial smart bands and extracted heart rate variability features (HRV). In addition, we measured core body temperature using our custom-designed flexible Inkjet-Printed (IJP) temperature sensor and SpO2 with a finger pulse oximeter. The core body temperature along with user-reported symptoms have been used for automated spatiotemporal monitoring of flu symptoms severity in real-time. The extracted HRV feature values are within the 95% confidence interval of normative values and shows an anticipated trend for gender and age. The resulting dataset from this study is a novel addition and may be used for future investigations.Clinical Relevance— The findings of this study shows usability of wearables in detection and monitoring of diseases such as obstructive sleep apnea reducing the prevalence of undiagnosed cases. This framework also has potentials to monitor outbreaks of flu and other diseases with spatiotemporal distribution.

Funder: American College of Rheumatology Research and Education Foundation; FundRef: http://dx.doi.org/10.13039/100000960, Funder: National Institute of Arthritis and Musculoskeletal and Skin Diseases; FundRef: http://dx.doi.org/10.13039/100000069, Funder: European League Against Rheumatism; FundRef: http://dx.doi.org/10.13039/501100008741, OBJECTIVES: The European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR) 2019 Classification Criteria for systemic lupus erythematosus (SLE) have been validated with high sensitivity and specificity. We evaluated the performance of the new criteria with regard to disease duration, sex and race/ethnicity, and compared its performance against the Systemic Lupus International Collaborating Clinics (SLICC) 2012 and ACR 1982/1997 criteria. METHODS: Twenty-one SLE centres from 16 countries submitted SLE cases and mimicking controls to form the validation cohort. The sensitivity and specificity of the EULAR/ACR 2019, SLICC 2012 and ACR 1982/1997 criteria were evaluated. RESULTS: The cohort consisted of female (n=1098), male (n=172), Asian (n=118), black (n=68), Hispanic (n=124) and white (n=941) patients; with an SLE duration of 1 to

Blueberries, which are rich in nutrition, are susceptible to fungal infection during postharvest or storage. However, early detection of diseases in blueberry is challenging because of their opaque appearance and the inconspicuousness of spots in the early stage of disease. The goal of this study was to investigate the potential of hyperspectral imaging over the spectral range of 400&ndash, 1000 nm to discriminate early disease in blueberries. Scanning electron microscope observation verified that fungal damage to the cellular structure takes place during the early stages. A total of 400 hyperspectral images, 200 samples each of healthy and early disease groups, were collected to obtain mean spectra of each blueberry samples. Spectral correlation analysis was performed to select an effective spectral range. Partial least square discrimination analysis (PLSDA) models were developed using two types of spectral range (i.e., full wavelength range of 400&ndash, 1000 nm and effective spectral range of 685&ndash, 1000 nm). The results showed that the effective spectral range made it possible to provide better classification results due to the elimination of the influence of irrelevant variables. Moreover, the effective spectral range combined with an autoscale preprocessing method was able to obtain optimal classification accuracies, with recognition rates of 100% and 99% for healthy and early disease blueberries. This study demonstrated that it is feasible to use hyperspectral imaging to measure early disease blueberries.

By using color vegetative indices and Otsu’s thresholding, we develop a method for the segmentation of unhealthy leaves in cruciferous crops as a procedure of automatic early disease detection. We apply the method on aerial RGB images collected at two different sunlight conditions, both containing multiple plants of kohlrabi with bare soil and weeds in the background. By using the M-statistic, we show how the method comprising a redefine set of the vegetative index can better discriminate between healthy leaves, unhealthy leaves, and other backgrounds. Our study indicates that the vegetative indices need to be tuned according to the types of the crop for accurate identification of infectious parts of the plant through the image processing method. We discuss its implications in precision agriculture.

The artificial distinction between relapsing remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS) can lead to substantial difficulties in decisions on disease-modifying therapy (DMT) at this stage of multiple sclerosis (MS). There is not a simple transition between the two; patients may demonstrate background progression with superimposed relapses for many years. Progressive disease almost certainly starts some years before clinical acknowledgement; once it is identified, clinicians face a dilemma about the use of highly effective DMT. The influence of highly effective therapy on relapses and medium-term outcomes in early disease is well established; however, disentangling efficacy in terms of relapses and progression at this later stage is more complex.

Automated milk feeders (AMF) are computerized systems that provide producers with a tool that can be used to more efficiently raise dairy calves and allow for easier implementation of a high plane of nutrition during the milk feeding phase. Automated milk feeders also have the ability to track individualized behavioral data, such as milk consumption, drinking speed, and the number of rewarded and unrewarded visits to the feeder, that could potentially be used to predict disease development. The objective of this scoping review was to characterize the body of literature investigating the use of AMF data to predict morbidity and mortality in dairy calves during the preweaning stage. This review lists the parameters that have been examined for associations with disease in calves and identify discrepancies found in the literature. Five databases and relevant conference proceedings were searched. Eligible studies focused on the use of behavioral parameters measured by AMF to predict morbidity or mortality in preweaned dairy calves. Two reviewers independently screened titles and abstracts from 6,675 records identified during the literature search. After title and abstract screening, 382 studies were included and then assessed at the full-text level. Of these, 56 studies fed calves using an AMF and provided some measure of morbidity or mortality. Thirteen examined AMF parameters for associations with morbidity or mortality. The studies were completed in North America (n = 6), Europe (n = 6), and New Zealand (n = 1). The studies varied in sample size, ranging from 30 to 1,052 calves with a median of 100 calves. All 13 studies included enteric disease as an outcome and 11 studies evaluated respiratory disease. Of the studies measuring enteric disease, 8 provided disease definitions (n = 8/13, 61.2%); however, for respiratory disease, only 5 provided a disease definition (n = 5/11, 45.5%). Disease definitions and thresholds varied greatly between studies, with 10 using some form of health scoring. When evaluating feeding metrics as indicators of disease, all 13 studies investigated milk consumption and 6 and 7 studies investigated drinking speed and number of rewarded and unrewarded visits, respectively. Overall, this scoping review identified that daily milk consumption, drinking speed, and rewarded and unrewarded visits may provide insight into early disease detection in preweaned dairy calves. However, the disparity in reporting of study designs and results between included studies made comparisons challenging. In addition, to aid with the interpretation of studies, standardized disease outcomes should be used to improve the utility of this primary research.

Vogt-Koyanagi-Harada disease is a rare autoimmune granulomatous panuveitis with significant associated morbidity. While ocular and meningeal signs are typically observed in the acute stage, the associated classic tegumentary findings are observed subsequently. This case report highlights the imaging findings associated with this entity that serves to emphasize the role of contrast-enhanced brain MRI in early disease detection, which allows for prompt treatment initiation and better disease outcome.

Detailed clinical and radiological assessment and staging of disease in the oral cavity is extremely important as this will influence treatment protocol and subsequent prognosis. It is useful to remember that though the tumour is resectable and treatable in most patients, it may not be amenable for a cure for all. As such, nearly 75% of patients are stage III and IV cancers and only 25–27% have early disease (stage I and II) [1, 2]. The inputs of clinical, radiology and histopathology are discussed in the combined tumour board consisting of a head and neck surgeon, radiation and medical oncologists. Arriving at a decision is often complex and demanding. The first step is to decide whether treatment planned for the patient is curative or palliative treatment [2]. A patient with obvious unresectable disease or even with advanced resectable disease but with poor general condition may be managed with palliative intent.

Introduction Achievement of remission is a key treatment goal for patients with axial spondyloarthritis (axSpA). C-OPTIMISE assessed achievement of sustained clinical remission in patients with axSpA, including radiographic (r) and non-radiographic (nr) axSpA, during certolizumab pegol (CZP) treatment, and subsequent maintenance of remission following CZP dose continuation, dose reduction or withdrawal. Here, we report outcomes from the first 48 weeks (induction period) of C-OPTIMISE, during which patients received open-label CZP. Methods C-OPTIMISE (NCT02505542) was a two-part, multicenter, phase 3b study in adult patients with early axSpA (r-/nr-axSpA), including a 48-week open-label induction period followed by a 48-week maintenance period. Patients with active adult-onset axSpA

Structural and functional defects within the lungs of children with cystic fibrosis (CF) are detectable soon after birth and progress throughout preschool years often without overt clinical signs or symptoms. By school age, most children have structural changes such as bronchiectasis or gas trapping/hypoperfusion and lung function abnormalities that persist into later life. Despite improved survival, gains in forced expiratory volume in one second (FEV1) achieved across successive birth cohorts during childhood have plateaued, and rates of FEV1decline in adolescence and adulthood have not slowed. This suggests that interventions aimed at preventing lung disease should be targeted to mild disease and commence in early life. Spirometry-based classifications of ‘normal’ (FEV1≥90% predicted) and ‘mild lung disease’ (FEV170%–89% predicted) are inappropriate, given the failure of spirometry to detect significant structural or functional abnormalities shown by more sensitive imaging and lung function techniques. The state and readiness of two imaging (CT and MRI) and two functional (multiple breath washout and oscillometry) tools for the detection and monitoring of early lung disease in children and adults with CF are discussed in this article.Prospective research programmes and technological advances in these techniques mean that well-designed interventional trials in early lung disease, particularly in young children and infants, are possible. Age appropriate, randomised controlled trials are critical to determine the safety, efficacy and best use of new therapies in young children. Regulatory bodies continue to approve medications in young children based on safety data alone and extrapolation of efficacy results from older age groups. Harnessing the complementary information from structural and functional tools, with measures of inflammation and infection, will significantly advance our understanding of early CF lung disease pathophysiology and responses to therapy. Defining clinical utility for these novel techniques will require effective collaboration across multiple disciplines to address important remaining research questions. Future impact on existing management burden for patients with CF and their family must be considered, assessed and minimised.To address the possible role of these techniques in early lung disease, a meeting of international leaders and experts in the field was convened in August 2019 at the Australiasian Cystic Fibrosis Conference. The meeting entitiled ‘Shaping imaging and functional testing for early disease detection of lung disease in Cystic Fibrosis’, was attended by representatives across the range of disciplines involved in modern CF care. This document summarises the proceedings, key priorities and important research questions highlighted.

Quantitative MRI and MRS of muscle are increasingly being used to measure individual pathophysiological processes in Becker muscular dystrophy (BMD). In particular, muscle fat fraction was shown to be highly associated with functional tests in BMD. However, the muscle strength per unit of contractile cross‐sectional area is lower in patients with BMD compared with healthy controls. This suggests that the quality of the non‐fat‐replaced (NFR) muscle tissue is lower than in healthy controls. Consequently, a measure that reflects changes in muscle tissue itself is needed. Here, we explore the potential of water T 2 relaxation times, diffusion parameters and phosphorus metabolic indices as early disease markers in patients with BMD. For this purpose, we examined these measures in fat‐replaced (FR) and NFR lower leg muscles in patients with BMD and compared these values with those in healthy controls. Quantitative proton MRI (three‐point Dixon, multi‐spin‐echo and diffusion‐weighted spin‐echo echo planar imaging) and 2D chemical shift imaging 31P MRS data were acquired in 24 patients with BMD (age 18.8‐66.2 years) and 13 healthy controls (age 21.3‐63.6 years). Muscle fat fractions, phosphorus metabolic indices, and averages and standard deviations (SDs) of the water T 2 relaxation times and diffusion tensor imaging (DTI) parameters were assessed in six individual leg muscles. Phosphodiester levels were increased in the NFR and FR tibialis anterior, FR peroneus and FR gastrocnemius lateralis muscles. No clear pattern was visible for the other metabolic indices. Increased T 2 SD was found in the majority of FR muscles compared with NFR and healthy control muscles. No differences in average water T 2 relaxation times or DTI indices were found between groups. Overall, our results indicate that primarily muscles that are further along in the disease process showed increases in T 2 heterogeneity and changes in some metabolic indices. No clear differences were found for the DTI indices between groups., In this study, diffusion measures and the means and standard deviations of the water T 2 relaxation time and 31P metabolic indices were explored as early markers for muscle tissue changes in the lower leg muscles of patients with Becker muscular dystrophy. Primarily muscles that were further along in the disease process as defined by elevated fat fractions showed increased T 2 heterogeneity in the majority of lower leg muscles and some changes in 31P metabolic indices.

Much research effort has been dedicated to unveiling the complexity of tumors for the development of effective treatment approaches. The idea of applying nanotheranostics for cancer management has transcended from a ‘hype to hope’ scenario. Furthermore, use of engineered hydrogels containing nanotheranostics has paved the path for generating smart cargos for effective diagnosis and remission. Hydrogels, used as reservoirs for smart nanotheranostics, facilitate the sustained release of drugs and imaging agents for a prolonged period of time, thereby assisting in early disease diagnosis, therapy, and prognosis. In this review, we discuss the use of engineered hydrogels as biomedical theranostic agents.

Growing evidence shows that ulcerative colitis (UC) is a progressive disease similar to Crohn’s disease (CD). The UC-related burden is often underestimated by physicians and a standard step-up therapeutic approach is preferred. However, in many patients with UC the disease activity is not adequately controlled by current management, leading to poor long-term prognosis. Data from both randomized controlled trials and real-world studies support early intervention in CD in order to prevent disease progression and irreversible bowel damage. Similarly, an early disease intervention during the so-called “window of opportunity” could lead to better outcomes in UC. Here, we summarize the literature evidence on early intervention in patients with UC, highlighting strengths and limitations of this approach.

Assessing the baseline knowledge status and expectations of the target population of any health promotion and secondary prevention program is essential to the success of such intervention. To obtain this information about the Hong Kong population a priori to implementing these preventive strategies for oral cancer in addition to determining the willingness of potential screening participants to take risk-profiling assessments, a cross-sectional survey was conducted between November 2019 and March 2020. A total of 964 residents between the ages 18 and 86 years were invited to participate in this study across the three geographical areas in Hong Kong. Most participants self-reported being aware of oral cancer (86.3%), although the proportion of those with substantial knowledge on salient risk factors and early identifiable signs were very low (2.9%). Age and level of education were the only demographic characteristics associated with the knowledge status. The proportion of participants willing to attend community screening and partake in risk profiling assessment was high (83.9% and 80.9% respectively). Willingness to attend community screening was directly associated with respondents’ self-reported oral cancer awareness status (OR: 1.9, 95% CI: 1.22–2.96). Also, we observed that those participants who were willing to attend screening are more inclined to take risk prediction assessments that those not willing to attend. These findings have showcased the need to intensify health promotion via personal skills development to encourage early disease presentation and will assist in the planning of these programs accordingly in the Hong Kong population.

Objective Dual-energy computed tomography (DECT), along with ultrasound (US), has been increasingly utilized for the diagnosis of gout because of its noninvasive advantages. However, the superiority of DECT over US remains controversial. This meta-analysis was performed to investigate whether DECT is superior to US in the diagnosis of gout. Methods A comprehensive search of PubMed, EMBASE, Cochrane, and Web of Science databases was conducted for potentially eligible articles. Studies that evaluated the utility of DECT or US for gout diagnosis were qualified. Two distinctive ultrasonographic features of gout, namely, the double contour sign and the presence of tophus, were also assessed. The methodological quality of the included studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 criteria. Besides, the subgroup analyses of early disease duration (≤ 2 years) was also performed. Results Twenty-eight studies were included in the meta-analysis. The pooled sensitivity and specificity of DECT were 0.89 (0.80–0.94) and 0.91 (0.88–0.94), respectively. The pooled sensitivity and specificity of US were 0.70 (0.58–0.79) and 0.95 (0.87–0.98), respectively, for double contour sign; 0.57 (0.38–0.74) and 0.99 (0.88–1.00), respectively, for tophus; and 0.84 (0.73–0.91) and 0.84 (0.78–0.89), respectively, for overall consideration of US signs. At the early disease duration (≤ 2 years), the pooled sensitivity and specificity were 0.75 (0.60–0.86) and 0.85 (0.75–0.91), respectively, for DECT; 0.93 (0.72–0.99) and 0.80 (0.71–0.86), respectively, for overall consideration of US signs. Conclusion DECT and US showed promising accuracy for gout diagnosis. DECT has higher sensitivity, specificity, and AUC than overall consideration of US signs and thus has a better diagnostic ability in diagnosing gout. Moreover, the diagnostic sensitivity of DECT is lower than that of overall consideration of US signs at less than 2 years’ disease duration.

Background Heat shock protein (HSP)-90 promotes tumor growth and is overexpressed in many malignancies. HSP90 expression profile and its potential as a therapeutic target in primary and metastatic neuroendocrine tumors (NETs) are not known. Methods HSP90 cytoplasmic expression and Ki-67 index were re-reviewed and scored by a pathologist blinded to all other clinicopathologic variables for patients who underwent resection of primary and metastatic gastroenteropancreatic (GEP) neuroendocrine tumors at a single institution (2000–2013). Primary outcome was recurrence-free survival (RFS). Results Of 263 tumors reviewed, 73% (n = 191) were primary GEP NETs, and 12% (n = 31) were NET liver metastases. Of the primary GEP-NETs, mean age was 56 years, 42% were male; 53% (n = 103) were pancreatic and 23% (n = 44) were small bowel. HSP90 expression was high in 34% (n = 64) and low in 66% (n = 127). Compared to low expression, high HSP90 was associated with advanced T-stage (T3/T4) (47 vs 27%; p = 0.02). Among patients who underwent curative-intent resections for primary, non-metastatic NETs (n = 145), high HSP90 was independently associated with worse RFS (HR 5.09, 95% CI 1.65–15.74; p = 0.005), after accounting for positive margin, LN involvement, increased tumor size, site of primary tumor, and Ki-67. When assessing NET liver metastases, 13% (n = 4) had high HSP90 expression and 87% (n = 26) had low expression. Patients with liver metastases with high HSP90 tended to have worse 1- and 3-year progression-free survival (25%, 25%) compared to those with low HSP90 (69%, 49%; p = 0.059). Conclusion HSP90 exhibits differential expression in resected GEP-NETs and liver metastases. High cytoplasmic expression is associated with early disease recurrence, even after accounting for other adverse pathologic factors. HSP90 inhibition may be a potential therapeutic target for neuroendocrine tumors.

PURPOSE: To investigate central visual field (VF) defects among four phenotypes of glaucomatous optic discs. DESIGN: Cross-sectional study. METHODS: Optic disc phenotypes were determined in eyes with definite or suspected glaucoma that had a 24–2 VF with mean deviation (MD) better than −12 dB and a 10–2 VF. 10–2 VFs were classified as abnormal based on a cluster criterion. Additionally, the average of the total deviation values at each 10–2 test point was compared by optic disc phenotype. RESULTS: Four glaucomatous optic disc phenotypes were identified in 448 eyes of 309 patients: focal ischemic (FI)(n=121), generalized cup enlargement (GE)(n=109), myopic glaucoma (MY)(n=66), and senile sclerotic (SS)(n=152). Although VF 24–2 MD values were similar among optic disc phenotypes, GE eyes had higher VF 10–2 MD(p=0.004), as well as lower VF 24–2 pattern standard deviation(PSD)(p

Understanding temporal dynamics of COVID-19 patient symptoms could provide fine-grained resolution to guide clinical decision-making. Here, we use deep neural networks over an institution-wide platform for the augmented curation of clinical notes from 77,167 patients subjected to COVID-19 PCR testing. By contrasting Electronic Health Record (EHR)-derived symptoms of COVID-19-positive (COVIDpos; n=2,317) versus COVID-19-negative (COVIDneg; n=74,850) patients for the week preceding the PCR testing date, we identify anosmia/dysgeusia (27.1-fold), fever/chills (2.6-fold), respiratory difficulty (2.2-fold), cough (2.2-fold), myalgia/arthralgia (2-fold), and diarrhea (1.4-fold) as significantly amplified in COVIDpos over COVIDneg patients. The combination of cough and fever/chills has 4.2-fold amplification in COVIDpos patients during the week prior to PCR testing, and along with anosmia/dysgeusia, constitutes the earliest EHR-derived signature of COVID-19. This study introduces an Augmented Intelligence platform for the real-time synthesis of institutional biomedical knowledge. The platform holds tremendous potential for scaling up curation throughput, thus enabling EHR-powered early disease diagnosis.

This editorial provides an overview and summary of recent research articles published in Biosensors journal, volumes 9 (2019) and 10 (2020), within the Special Issue “Noninvasive Early Disease Diagnosis”, which focused on recent sensors, biosensors, and clinical instruments developed for the noninvasive early detection and diagnosis of human, animal, and plant diseases or invasive pests. The six research articles included in this Special Issue provide examples of some of the latest electronic-nose (e-nose) and related volatile organic compound (VOC)-detection technologies, which are being tested and developed to improve the effectiveness and efficiency of innovative diagnostic methodologies for the early detection of particular diseases and pest infestations in living hosts, prior to symptom development.

Introduction Achievement of remission is a key treatment goal for patients with axial spondyloarthritis (axSpA). C-OPTIMISE assessed achievement of sustained clinical remission in patients with axSpA, including radiographic (r) and non-radiographic (nr) axSpA, during certolizumab pegol (CZP) treatment, and subsequent maintenance of remission following CZP dose continuation, dose reduction or withdrawal. Here, we report outcomes from the first 48 weeks (induction period) of C-OPTIMISE, during which patients received open-label CZP. Methods C-OPTIMISE (NCT02505542) was a two-part, multicenter, phase 3b study in adult patients with early axSpA (r-/nr-axSpA), including a 48-week open-label induction period followed by a 48-week maintenance period. Patients with active adult-onset axSpA, < 5 years' symptom duration, and fulfilling Assessment of SpondyloArthritis international Society classification criteria, were included. During the induction period, patients received a loading dose of CZP 400 mg at weeks 0, 2, and 4, followed by CZP 200 mg every 2 weeks (Q2W) up to week 48. The main outcome of the 48-week induction period was the achievement of sustained clinical remission (defined as an Ankylosing Spondylitis Disease Activity Score [ASDAS] < 1.3 at week 32 and < 2.1 at week 36 [or vice versa], and < 1.3 at week 48). Results In total, 736 patients (407 with r-axSpA, 329 with nr-axSpA) were enrolled into the study. At week 48, 43.9% (323/736) of patients achieved sustained remission, including 42.8% (174/407) of patients with r-axSpA and 45.3% (149/329) with nr-axSpA. Patients also demonstrated substantial improvements in axSpA symptoms, MRI outcomes and quality of life measures. Adverse events occurred in 67.9% (500/736) of patients, of which 6.0% (44/736) were serious. Conclusions Over 40% of patients with early axSpA achieved sustained remission during 48 weeks of open-label CZP treatment. Additionally, patients across the axSpA spectrum demonstrated substantial improvements in imaging outcomes and quality of life following treatment. No new safety signals were identified.