Crop type discrimination using Geo-Stat Endmember Extraction and machine learning algorithms.

The identification of crop diversity in today's world is very crucial to ensure adaptation of the crop with changing climate for better productivity as well as food security. Towards this, Hyperspectral Remote Sensing (HRS) is an efficient technique based on imaging spectroscopy that offers the opportunity to discriminate crop types based on morphological as well as physiological features due to availability of contiguous spectral bands. The current work utilized the benefits of Airborne Visible Infrared Imaging spectrometer- New Generation (AVIRIS-NG) data and explored the techniques for classification and identification of crop types. The endmembers were identified using the Geo-Stat Endmember Extraction (GSEE) algorithm for pure pixels identification and to generate the spectral library of the different crop types. Spectral feature comparison was done among AVIRIS-NG, Analytical Spectral Device (ASD)-Spectroradiometer and Continuum Removed (CR) spectra. The best-fit spectra obtained with the Reference ASD-Spectroradiometer and Pure Pixel spectral library were then used for crop discrimination using the ten supervised classifiers namely Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), Support Vector Machine (SVM), Minimum Distance Classifier (MDC), Binary Encoding, deep learning-based Convolution Neural Network (CNN) and different algorithms of Ensemble learning such as Tree Bag, AdaBoost (Adaptive Boosting), Discriminant and RUSBoost (Random Under Sampling). In total, nine crop types were identified, namely, wheat, maize, tobacco, sorghum, linseed, castor, pigeon pea, fennel and chickpea. The performance evaluation of the classifiers was made using various metrics like Overall Accuracy, Kappa Coefficient, Precision, Recall and F1 score. The classifier 2D-CNN was found to be the best with Overall Accuracy, Kappa Coefficient, Precision, Recall and F1 score values of 89.065 %, 0.871,87.565%, 89.541% and 88.678% respectively. The output of this work can be utilized for large scale mapping of crop types at the species level in a short interval of time of a large area with high accuracy.

Role of verbal autopsy in cancer registration: A mixed-methods study from the population-based cancer registry of Northern India.

OBJECTIVES: To describe utilisation of verbal autopsy as one of the data collection approaches in cancer registration in an Indian setting. We aimed to estimate the proportion and epidemiological characteristics of malignancies identified by the Varanasi population-based cancer registry (PBCR) using verbal autopsy between 2017 and 2019 and to develop a thematic network for implementing verbal autopsy. METHODS: This was a cross-sectional mixed-methods study. Quantitative methods were applied to analyse information from PBCR proforma of the verbal autopsy-confirmed cancers; qualitative methods were applied to evaluate verbal autopsy conducted by field staff from key informants. In-depth interviews of field staff for the challenges and potential solutions during verbal autopsy were assessed. RESULTS: Of 6466 registered cancers, 1103 (17.1%) were verbal autopsy-confirmed cancers, which had no other source of information. The majority of verbal autopsy cases were from vulnerable populations who were aged >50 years (721, 65.4%), female (607, 55.1%), from rural backgrounds (853, 77.3%), illiterate or just able to read and write (636, 57.7%), and from lower and middle-income groups (823, 74.6%). Verbal autopsy helped provide information about symptoms and site of disease, diagnostic and treatment details, and disease status. Major challenges during verbal autopsy described by field staff were incomplete cancer treatment, destruction of medical records and non-cooperation by the community and lack of support from the local workforce as cancer is not notifiable. CONCLUSION: Verbal autopsy helped identify cancers that would have been missed during active case finding from available resources. The majority of verbal autopsy-confirmed patients belonged to vulnerable populations. Non-cooperation from community and local health systems was major challenge during verbal autopsy. Developing robust cancer awareness, patient navigation, and social support programmes will strengthen verbal autopsy. Integration of standardised and reproducible methods of verbal autopsy in cancer registry and digitalization of health information, especially in limited-resource settings with weak vital registration, will facilitate completeness in cancer registration.

Nitrogen dioxide as proxy indicator of air pollution from fossil fuel burning in New Delhi during lockdown phases of COVID-19 pandemic period: impact on weather as revealed by Sentinel-5 precursor (5p) spectrometer sensor.

There has been a long-lasting impact of the lockdown imposed due to COVID-19 on several fronts. One such front is climate which has seen several implications. The consequences of climate change owing to this lockdown need to be explored taking into consideration various climatic indicators. Further impact on a local and global level would help the policymakers in drafting effective rules for handling challenges of climate change. For in-depth understanding, a temporal study is being conducted in a phased manner in the New Delhi region taking NO2 concentration and utilizing statistical methods to elaborate the quality of air during the lockdown and compared with a pre-lockdown period. In situ mean values of the NO2 concentration were taken for four different dates, viz. 4th February, 4th March, 4th April, and 25th April 2020. These concentrations were then compared with the Sentinel (5p) data across 36 locations in New Delhi which are found to be promising. The results indicated that the air quality has been improved maximum in Eastern Delhi and the NO2 concentrations were reduced by one-fourth than the pre-lockdown period, and thus, reduced activities due to lockdown have had a significant impact. The result also indicates the preciseness of Sentinel (5p) for NO2 concentrations.

Evaluation of Medical Certification of Cause of Death in Tertiary Cancer Hospitals in Northern India.

BACKGROUND: Medical certification of cause of death (MCCD) provides valuable data regarding disease burden in a community and for formulating health policy. Inaccurate MCCDs can significantly impair the precision of national health information. OBJECTIVE: To evaluate the accuracy of cause of death certificates prepared at two tertiary cancer care hospitals in Northern India during the study period (May 2018 to December 2020). METHOD: A retrospective observational study at two tertiary cancer care hospitals in Varanasi, India, over a period of two and a half years. Medical records and cause of death certificates of all decedents were examined. Demographic characteristics, administrative details and cause of death data were collected using the WHO recommended death certificates. Accuracy of death certification was validated by electronic medical records and errors were graded. RESULTS: A total of 778 deaths occurred in the two centres during the study period. Of these, only 30 (3.9%) certificates were error-free; 591 (75.9%) certificates had an inappropriate immediate cause of death; 231 (29.7%) certificates had incorrectly labelled modes of death as the immediate cause of death; and 585 (75.2%) certificates had an incorrect underlying cause of death. The majority of certificates were prepared by junior doctors and were significantly associated with higher certification errors. CONCLUSION: A high rate of errors was identified in death certification at the cancer care hospitals during the study period. Inaccurate MCCDs related to cancers can potentially influence cancer statistics and thereby affect policy making for cancer control. IMPLICATIONS: This study has identified the pressing need for appropriate interventions to improve quality of certification through training of doctors.

A Literature-Derived Knowledge Graph Augments the Interpretation of Single Cell RNA-seq Datasets.

Technology to generate single cell RNA-sequencing (scRNA-seq) datasets and tools to annotate them have advanced rapidly in the past several years. Such tools generally rely on existing transcriptomic datasets or curated databases of cell type defining genes, while the application of scalable natural language processing (NLP) methods to enhance analysis workflows has not been adequately explored. Here we deployed an NLP framework to objectively quantify associations between a comprehensive set of over 20,000 human protein-coding genes and over 500 cell type terms across over 26 million biomedical documents. The resultant gene-cell type associations (GCAs) are significantly stronger between a curated set of matched cell type-marker pairs than the complementary set of mismatched pairs (Mann Whitney p = 6.15 × 10-76, r = 0.24; cohen's D = 2.6). Building on this, we developed an augmented annotation algorithm (single cell Annotation via Literature Encoding, or scALE) that leverages GCAs to categorize cell clusters identified in scRNA-seq datasets, and we tested its ability to predict the cellular identity of 133 clusters from nine datasets of human breast, colon, heart, joint, ovary, prostate, skin, and small intestine tissues. With the optimized settings, the true cellular identity matched the top prediction in 59% of tested clusters and was present among the top five predictions for 91% of clusters. scALE slightly outperformed an existing method for reference data driven automated cluster annotation, and we demonstrate that integration of scALE can meaningfully improve the annotations derived from such methods. Further, contextualization of differential expression analyses with these GCAs highlights poorly characterized markers of well-studied cell types, such as CLIC6 and DNASE1L3 in retinal pigment epithelial cells and endothelial cells, respectively. Taken together, this study illustrates for the first time how the systematic application of a literature-derived knowledge graph can expedite and enhance the annotation and interpretation of scRNA-seq data.

Mapping each pre-existing condition's association to short-term and long-term COVID-19 complications.

Understanding the relationships between pre-existing conditions and complications of COVID-19 infection is critical to identifying which patients will develop severe disease. Here, we leverage ~1.1 million clinical notes from 1803 hospitalized COVID-19 patients and deep neural network models to characterize associations between 21 pre-existing conditions and the development of 20 complications (e.g. respiratory, cardiovascular, renal, and hematologic) of COVID-19 infection throughout the course of infection (i.e. 0-30 days, 31-60 days, and 61-90 days). Pleural effusion was the most frequent complication of early COVID-19 infection (89/1803 patients, 4.9%) followed by cardiac arrhythmia (45/1803 patients, 2.5%). Notably, hypertension was the most significant risk factor associated with 10 different complications including acute respiratory distress syndrome, cardiac arrhythmia, and anemia. The onset of new complications after 30 days is rare and most commonly involves pleural effusion (31-60 days: 11 patients, 61-90 days: 9 patients). Lastly, comparing the rates of complications with a propensity-matched COVID-negative hospitalized population confirmed the importance of hypertension as a risk factor for early-onset complications. Overall, the associations between pre-COVID conditions and COVID-associated complications presented here may form the basis for the development of risk assessment scores to guide clinical care pathways.

Highlighting the compound risk of COVID-19 and environmental pollutants using geospatial technology.

The new COVID-19 coronavirus disease has emerged as a global threat and not just to human health but also the global economy. Due to the pandemic, most countries affected have therefore imposed periods of full or partial lockdowns to restrict community transmission. This has had the welcome but unexpected side effect that existing levels of atmospheric pollutants, particularly in cities, have temporarily declined. As found by several authors, air quality can inherently exacerbate the risks linked to respiratory diseases, including COVID-19. In this study, we explore patterns of air pollution for ten of the most affected countries in the world, in the context of the 2020 development of the COVID-19 pandemic. We find that the concentrations of some of the principal atmospheric pollutants were temporarily reduced during the extensive lockdowns in the spring. Secondly, we show that the seasonality of the atmospheric pollutants is not significantly affected by these temporary changes, indicating that observed variations in COVID-19 conditions are likely to be linked to air quality. On this background, we confirm that air pollution may be a good predictor for the local and national severity of COVID-19 infections.

Pre-existing conditions are associated with COVID-19 patients' hospitalization, despite confirmed clearance of SARS-CoV-2 virus.

BACKGROUND: Consecutive negative SARS-CoV-2 PCR test results are being considered to estimate viral clearance in COVID-19 patients. However, there are anecdotal reports of hospitalization from protracted COVID-19 complications despite such confirmed viral clearance, presenting a clinical conundrum. METHODS: We conducted a retrospective analysis of 222 hospitalized COVID-19 patients to compare those that were readmitted post-viral clearance (hospitalized post-clearance cohort, n = 49) with those that were not re-admitted post-viral clearance (non-hospitalized post-clearance cohort, n = 173) between February and October 2020. In order to differentiate these two cohorts, we used neural network models for the 'augmented curation' of comorbidities and complications with positive sentiment in the Electronic Hosptial Records physician notes. FINDINGS: In the year preceding COVID-19 onset, anemia (n = 13 [26.5%], p-value: 0.007), cardiac arrhythmias (n = 14 [28.6%], p-value: 0.015), and acute kidney injury (n = 7 [14.3%], p-value: 0.030) were significantly enriched in the physician notes of the hospitalized post-clearance cohort. INTERPRETATION: Overall, this retrospective study highlights specific pre-existing conditions that are associated with higher hospitalization rates in COVID-19 patients despite viral clearance and motivates follow-up prospective research into the associated risk factors. FUNDING: This work was supported by Nference, inc.

Augmented curation of clinical notes from a massive EHR system reveals symptoms of impending COVID-19 diagnosis.

Understanding temporal dynamics of COVID-19 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, in addition to 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.

Knowledge synthesis of 100 million biomedical documents augments the deep expression profiling of coronavirus receptors.

The COVID-19 pandemic demands assimilation of all biomedical knowledge to decode mechanisms of pathogenesis. Despite the recent renaissance in neural networks, a platform for the real-time synthesis of the exponentially growing biomedical literature and deep omics insights is unavailable. Here, we present the nferX platform for dynamic inference from over 45 quadrillion possible conceptual associations from unstructured text, and triangulation with insights from single-cell RNA-sequencing, bulk RNA-seq and proteomics from diverse tissue types. A hypothesis-free profiling of ACE2 suggests tongue keratinocytes, olfactory epithelial cells, airway club cells and respiratory ciliated cells as potential reservoirs of the SARS-CoV-2 receptor. We find the gut as the putative hotspot of COVID-19, where a maturation correlated transcriptional signature is shared in small intestine enterocytes among coronavirus receptors (ACE2, DPP4, ANPEP). A holistic data science platform triangulating insights from structured and unstructured data holds potential for accelerating the generation of impactful biological insights and hypotheses.

Hypopharyngeal Airway Surgery for Obstructive Sleep Apnea: Morbidity in the Early Postoperative Period.

STUDY OBJECTIVE: To determine if hypopharyngeal surgery for obstructive sleep apnea is associated with significant morbidity in the early post-operative period. METHODS: Patients with a diagnosis of obstructive sleep apnea who underwent hypopharyngeal surgery at a tertiary care facility between November 2012 and September 2013 were included in this study. Surgical outcomes were assessed from medical records review and a 14 question telephone survey. Results: Twenty-two patients underwent hypopharyngeal surgery for obstructive sleep apnea (OSA). No patient experienced intra-operative complications, post-operative O2 desaturation <90%, prolonged admission for inadequate pain control, pulmonary edema, or airway compromise requiring re-intubation. Post-operative complications included one episode of nasal hemorrhage, one infection requiring hospitalization, and one episode of dehydration treated with IV fluids. 25% of patients experienced some degree of post-operative dysphonia, and 87.5% of patients experienced post-operative dysphagia. The average rating for post-operative pharyngeal pain was 3.5 of 10 by week 3 and 1.75 of 10 by week 4. Most patients described decreased snoring (93.75%), improved feeling of overall health (75%), and increased daytime energy (62.5%). All patients undergoing hypopharyngeal airway surgery were discharged within 23 hours. CONCLUSION: Hypopharyngeal surgery is a safe and well tolerated procedure for the treatment of OSA. Our findings suggest that hypopharyngeal surgery may be performed on an outpatient basis.

Stapler-assisted closure in total laryngectomy.

The total laryngectomy is a surgical procedure that requires technically sound reconstruction in order to preserve a patient's swallowing function. Traditionally, a handsewn technique has been utilized to accomplish this endeavor. Recent applications of surgical stapling devices have been noted in an attempt to circumvent the need for handsewn reconstruction. This paper documents the application of a surgical stapling device in reconstructing a total laryngectomy defect. A brief review of the literature is provided to compare the differences between handsewn techniques and stapling techniques.

Oropharyngeal reconstruction using the supraclavicular artery island flap: a new flap alternative.

UNLABELLED: Oropharyngeal reconstruction following head and neck oncologic resection has utilized local, regional, and free tissue transfer flap options. The modality utilized is often guided by the type of defect created as well as the surgeon's preference. In this article, the authors introduce the application of the supraclavicular artery island flap as a reconstructive modality following oropharyngeal oncologic ablation. Five patients underwent head and neck oncologic resection for oropharyngeal squamous cell carcinoma followed by single-stage reconstruction with an ipsilateral supraclavicular artery island flap. There were no flap failures and only one postoperative complication consisting of a postoperative oral-cutaneous fistula that resolved without surgical intervention. There were no donor-site complications. The supraclavicular artery island flap is a viable alternative for oropharyngeal reconstruction following head and neck oncologic resection. It is a regional flap that can be harvested without microsurgical expertise and yields reliable postoperative results. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, IV.

Bezold's abscess: a unique complication of otitis media.

Otitis media is one of the more common pathologic entities treated by primary care physicians and otolaryngologists. With antibiotic therapy, the majority of these infections do not progress beyond the primary disease process. However, there are situations during which the primary otitis media may not resolve, and complications can form as a result of its persistence. One such complication is the formation of a Bezold's abscess. This results from an underlying coalescent mastoiditis which progresses laterally into the deep neck space. The following is a case presentation of a Bezold's abscess followed by a discussion detailing the pathophysiology, presentation, diagnosis, and treatment of this disease process.

Reconstruction of large lateral facial defects utilizing variations of the cervicopectoral rotation flap.

Large lateral facial defects as a result of trauma or head and neck oncologic surgery can present a challenging reconstructive dilemma for the operating surgeon. A number of options currently exist for reconstructing such defects, including skin grafts, myocutaneous flaps, and free vascularized flaps. The decision to utilize one approach versus another depends largely on the nature of the defect, anatomical location, and the experience of the surgeon. This article describes our experience utilizing cervicopectoral rotation flaps with and without myocutaneous flaps to reconstruct large lateral facial defects after head and neck oncologic surgery.

An efficient high-order algorithm for acoustic scattering from penetrable thin structures in three dimensions.

This paper presents a high-order accelerated algorithm for the solution of the integral-equation formulation of volumetric scattering problems. The scheme is particularly well suited to the analysis of "thin" structures as they arise in certain applications (e.g., material coatings); in addition, it is also designed to be used in conjunction with existing low-order FFT-based codes to upgrade their order of accuracy through a suitable treatment of material interfaces. The high-order convergence of the new procedure is attained through a combination of changes of parametric variables (to resolve the singularities of the Green function) and "partitions of unity" (to allow for a simple implementation of spectrally accurate quadratures away from singular points). Accelerated evaluations of the interaction between degrees of freedom, on the other hand, are accomplished by incorporating (two-face) equivalent source approximations on Cartesian grids. A detailed account of the main algorithmic components of the scheme are presented, together with a brief review of the corresponding error and performance analyses which are exemplified with a variety of numerical results.

Laryngeal trauma: review of literature.

Laryngeal trauma is a rare injury that can lead to rapid airway deterioration if not treated in a timely, proper manner. Due to its infrequent occurrence, many different management strategies have evolved. All approaches stress an immediate stabilization of the airway, followed by a diagnostic protocol that demarcates different groupings based on the extent of laryngeal trauma. Treatment regimens, ranging from medical to surgical, are then based on such groupings. The uniformity of the management strategy mentioned above is misleading given the variation of management in the literature. This paper reviews the management strategy for laryngeal trauma, while detailing the different approaches described in the literature.

Intracapsular versus standard tonsillectomy: review of literature.

For the past century, standard (total) tonsillectomy has been the preferred method for treating illness resulting from tonsillar infection and hypertrophy. With the advent of antibiotics, however, more cases of tonsillitis are treated medically. As a result, tonsillectomies are being performed less frequently for infection than for obstructive symptoms associated with tonsillar hypertrophy and sleep-disordered breathing. This shift has led to the re-emergence of the tonsillotomy, and more specifically the partial or intracapsular tonsillectomy, as an option for treating tonsillar hypertrophy, mainly in an effort to reduce the post-operative complications of pain, subsequent dehydration from lack of oral intake, and, potentially, delayed postoperative bleeding. The following is a review of the literature comparing intracapsular tonsillectomy to standard tonsillectomy for tonsillar hypertrophy associated with sleep-disordered breathing.

Mucosal melanoma: case report and review.

Mucosal melanoma is a rare form of cancer that results from an abnormal proliferation of melanocytes within mucosal surfaces of the body. Due to the limited number of cases in the general public and even fewer cases in the reported literature, it is difficult to conduct research on this cancer. The following is a case presentation of a sinonasal mucosal melanoma followed by a review of the current literature detailing the epidemiology, signs and symptoms, diagnostic methods, and various methods of treatment that are currently used to combat this illness.

Brown bowel syndrome: case report and review.

Brown bowel syndrome is characterized by deposits of lipofuscin in the tunica muscularis of the small intestine. Its etiology is associated with chronic malabsorption resulting in a deficiency of vitamin E. This hypovitaminosis is believed to cause a mitochondrial myopathy secondary to loss of the antioxidant properties of vitamin E, which further worsens the malabsorption and leads to atonic, dilated segments of bowel. Current treatment options involve nutritional supplementation, surgical resection of the affected segments, and intestinal transplantation.