Neural Models for Generating Natural Language Summaries from Temporal Personal Health Data.

With an increased interest in the production of personal health technologies designed to track user data (e.g., nutrient  intake, step counts), there is now more opportunity than ever to surface meaningful behavioral insights to everyday users in the form of natural language. This knowledge can increase their behavioral awareness and allow them to take action to meet their health goals. It can also bridge the gap between the vast collection of personal health data and the summary generation required to describe an individual's behavioral tendencies. Previous work has focused on rule-based time-series data summarization methods designed to generate natural language summaries of interesting patterns found within temporal personal health data. We examine recurrent, convolutional, and Transformer-based encoder-decoder models to automatically generate natural language summaries from numeric temporal personal health data. We showcase the effectiveness of our models on real user health data logged in MyFitnessPal (Weber and Achananuparp 2016) and show that we can automatically generate high-quality natural language summaries. Our work serves as a first step towards the ambitious goal of automatically generating novel and meaningful temporal summaries from personal health data.

A Critical Review of Data Science Applications in Resource Recovery and Carbon Capture from Organic Waste.

Municipal and agricultural organic waste can be treated to recover energy, nutrients, and carbon through resource recovery and carbon capture (RRCC) technologies such as anaerobic digestion, struvite precipitation, and pyrolysis. Data science could benefit such technologies by improving their efficiency through data-driven process modeling along with reducing environmental and economic burdens via life cycle assessment (LCA) and techno-economic analysis (TEA), respectively. We critically reviewed 616 peer-reviewed articles on the use of data science in RRCC published during 2002-2022. Although applications of machine learning (ML) methods have drastically increased over time for modeling RRCC technologies, the reviewed studies exhibited significant knowledge gaps at various model development stages. In terms of sustainability, an increasing number of studies included LCA with TEA to quantify both environmental and economic impacts of RRCC. Integration of ML methods with LCA and TEA has the potential to cost-effectively investigate the trade-off between efficiency and sustainability of RRCC, although the literature lacked such integration of techniques. Therefore, we propose an integrated data science framework to inform efficient and sustainable RRCC from organic waste based on the review. Overall, the findings from this review can inform practitioners about the effective utilization of various data science methods for real-world implementation of RRCC technologies.

Toward Subgraph-Guided Knowledge Graph Question Generation With Graph Neural Networks.

Knowledge graph (KG) question generation (QG) aims to generate natural language questions from KGs and target answers. Previous works mostly focus on a simple setting that is to generate questions from a single KG triple. In this work, we focus on a more realistic setting where we aim to generate questions from a KG subgraph and target answers. In addition, most previous works built on either RNN-or Transformer-based models to encode a linearized KG subgraph, which totally discards the explicit structure information of a KG subgraph. To address this issue, we propose to apply a bidirectional Graph2Seq model to encode the KG subgraph. Furthermore, we enhance our RNN decoder with a node-level copying mechanism to allow direct copying of node attributes from the KG subgraph to the output question. Both automatic and human evaluation results demonstrate that our model achieves new state-of-the-art scores, outperforming existing methods by a significant margin on two QG benchmarks. Experimental results also show that our QG model can consistently benefit the question-answering (QA) task as a means of data augmentation.

Machine learning techniques to increase the performance of indirect methane quantification from a single, stationary sensor.

Researchers are searching for ways to better quantify methane emissions from natural gas infrastructure. Current indirect quantification techniques (IQTs) allow for more frequent or continuous measurements with fewer personnel resources than direct methods but lack accuracy and repeatability. Two IQTs are Other Test Method (OTM) 33A and Eddy Covariance (EC). We examined a novel approach to improve the accuracy of single sensor IQT whereby the results from both OTM and EC were combined with two machine learning (ML) models, a random forest (RF) and a neural network (NN). Then, models were enhanced with feature reduction and hyper-parameter tuning and compared to traditional quantification methods. The NN and RF improved upon the default OTM by an average of 44% and 78%, respectively. When compared to traditional OTM estimates with low Data Quality Indicators (DQIs), RF and NN models reduced 1σ errors from ±66% to ±13% and ±34%, respectively. Models also reduced the standard deviation of estimates with 93% and 85% of estimates falling within ±50% of the known release rate. This approach can be deployed with single sensor systems at well sites to improve confidence in reported emissions, reducing the number of anomalous overestimates that would trigger unnecessary site evaluations. Additional improvements could be realized by expanding training datasets with more methane release rates. Further, deployment of such models in a variety of situations could enhance their ability help close the gap between bottom-up inventory and top-down studies by enabling continuous monitoring of temporal emissions that could identify with improved confidence, atypically higher emissions. Accurate remote single sensor systems are key in developing an improved understanding of methane emissions to enable industry to identify and reduce methane emissions.

Modern Hopfield Networks for graph embedding.

The network embedding task is to represent a node in a network as a low-dimensional vector while incorporating the topological and structural information. Most existing approaches solve this problem by factorizing a proximity matrix, either directly or implicitly. In this work, we introduce a network embedding method from a new perspective, which leverages Modern Hopfield Networks (MHN) for associative learning. Our network learns associations between the content of each node and that node's neighbors. These associations serve as memories in the MHN. The recurrent dynamics of the network make it possible to recover the masked node, given that node's neighbors. Our proposed method is evaluated on different benchmark datasets for downstream tasks such as node classification, link prediction, and graph coarsening. The results show competitive performance compared to the common matrix factorization techniques and deep learning based methods.

Bisphenol A and Male Infertility: Role of Oxidative Stress.

Bisphenol A (BPA) is an endocrine-disrupting chemical that is capable of mimicking, antagonizing, and interfering with the normal biological functioning of the endocrine system. BPA is used in diverse industries, hence its vast sources of exposure. Although the half-life of BPA is relatively short (<24 hours), studies have reported its detection in the urine of different populations. It, therefore, became important to investigate its effect on general health, including male reproductive health. The adverse effects of BPA on male fertility have been evaluated and reported from both in vivo and in vitro studies. Up to date, reports from randomized controlled trials remain controversial, as some revealed decreased sperm quality, sperm concentration, and total sperm count, while others reported that no adverse effect was seen after exposure. Findings from animal model studies and in vitro experiments have shown that exposure to BPA led to a reduction in sperm quality and increased sperm DNA fragmentation, and some even revealed altered expression of the gene that encodes gonadotropin-releasing hormone. This shows that BPA not only may adversely affect male fertility by acting as an endocrine disruptor but also can potentially impact male fertility via its possible contribution to oxidative stress. Therefore, this book chapter aims to identify and elucidate the effect of BPA exposure on male fertility, and to as well illustrate the mechanisms through which this occurs, while emphasizing the role of oxidative stress as a potential pathway.

Knee meniscal retears after repair: A systematic review comparing diagnostic imaging modalities.

The meniscus is a relatively avascular fibrocartilaginous structure that provides a key role in shock absorption and load transmission. However, accurate diagnosis of meniscal retear can present a clinical challenge. The purpose of this study was to conduct a systematic review on the available literature, which compare the sensitivities, specificities, and accuracies of different diagnostic modalities of diagnosing knee meniscal retears in patients who have undergone surgical meniscal repair, such as Magnetic Resonance Imaging (MRI), Magnetic Resonance Arthrography with intraarticular contrast (direct MRA), and a combination of MRI and direct MRA. Two authors independently searched two databases (PubMed and Scopus) for literature related to knee meniscus retear according to the PRISMA guidelines. Four studies were found, which resulted in 291 patients with 293 menisci. All studies were published in 2008 and 2014. In our analysis, we calculated sensitivity to be 78.79% (95% CI, 64.07-93.51), specificity to be 56.58% (95% CI, 20.21-92.94), and overall accuracy to be 66.25% (95% CI, 54.29-78.22) for MRI and sensitivity to be 87.84% (95% CI, 83.93-91.74), specificity to be 88.68% (95% CI, 81.93-95.43), and overall accuracy to be 87.22% (95% CI, 82.22-91.62) for direct MRA. We recommend the use of direct MRA for the diagnosis of meniscal retears due to its higher sensitivity, specificity, and accuracy as compared to MRI and its reduced cost and invasive nature as compared to second-look arthroscopy. However, our review is limited by the number of studies available on this topic. More studies using study designs such as randomized controlled trials, involving MRI, direct MRA, and combinations of such techniques, should be performed to accurately assess the different techniques and aid in designing guidelines to guide the diagnosis of meniscal retears following meniscal repair.

Unmasking Fracture Risk in Type 2 Diabetes: The Association of Longitudinal Glycemic Hemoglobin Level and Medications.

CONTEXT: Fracture risk is underestimated in people with type 2 diabetes (T2D). OBJECTIVE: To investigate the longitudinal relationship of glycated hemoglobin (HbA1c) and common medications on fracture risk in people with T2D. METHODS: This retrospective population-based cohort study was conducted using de-identified claims and electronic health record data obtained from the OptumLabs Data Warehouse for the period January 1, 2007, to September 30, 2015. For each individual, the study was conducted within a 2-year HbA1c observation period and a 2-year fracture follow-up period. A cohort of 157 439 individuals with T2D [age ≥ 55 years with mean HbA1c value ≥ 6%] were selected from 4 018 250 US Medicare Advantage/Commercial enrollees with a T2D diagnosis. All fractures and fragility fractures were measured. RESULTS: With covariates adjusted, poor glycemic control in T2D individuals was associated with an 29% increase of all fracture risk, compared with T2D individuals who had adequate glycemic control (HR: 1.29; 95% CI, 1.22-1.36). Treatment with metformin (HR: 0.88; 95% CI, 0.85-0.92) and DPP4 inhibitors (HR: 0.93; 95% CI, 0.88-0.98) was associated with a reduced all fracture risk, while insulin (HR: 1.26; 95% CI, 1.21-1.32), thiazolidinediones (HR: 1.23; 95% CI, 1.18-1.29), and meglitinides (HR: 1.12; 95% CI, 1.00-1.26) were associated with an increased all fracture risk (All P value < 0.05). Bisphosphonates were associated similarly with increased fracture risk in the T2D and nondiabetic groups. CONCLUSION: Longitudinal 2-year HbA1c is independently associated with elevated all fracture risk in T2D individuals during a 2-year follow-up period. Metformin and DPP4 inhibitors can be used for management of T2D fracture risk.

Correlation of Bariatric Surgery Effect on Lipid Profile Among Obese Patients.

Background A considerable subpopulation of patients with morbid obesity present with dyslipidemia. It is characterized by elevated total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL), and low high-density lipoprotein (HDL) concentrations. Sleeve gastrectomy (SG) is considered a method of treating morbid obesity and associated dyslipidemia. Objective To assess the effect of bariatric and metabolic surgery on lipid profile of morbidly obese patients. Methods We used a retrospective approach analyzing the lipid profiles of patients who underwent SG between January 2018 and July 2020. Patients were enrolled according to age (>17 years), pre-operative body mass index (BMI; >30 kg/m2), undergoing SG, and having complete follow-up records of lipid profiles. Baseline and post-operative lipid profiles, their variation, and the percentage of variation were compared. Results We analyzed data of 163 patients who underwent SG. The mean age was 36.75 ± 10.75 years, the mean BMI was 45.66 ±8.46, and the mean pre-operative TC, LDL, HDL, and TG were 4.67 ± 1.02, 2.55 ± 1.1, 1.14 ± 0.32, and 1.5 ± 1.11, respectively. There was a significant change in the mean level of TG as it was significantly higher pre-operatively compared to its mean level post-operatively. Furthermore, a significant change was observed in HDL. There was a non-significant change in levels of TC and LDL post-operatively. Conclusion SG showed to significantly reduce TG and elevate HDL in morbidly obese patients. On the contrary, TC and LDL were non-significantly affected. Further studies with longer follow-up are warranted to provide more reliable evidence.

Effect of Bariatric Surgery on Glycaemic Control in King Fahad Hospital.

BACKGROUND: Laparoscopic Sleeve Gastrectomy (LSG) is an approved procedure for weight reduction in obese patients. This outcome of weight loss is essential to achieve optimal control in patients with type 2 diabetes mellitus (T2DM). OBJECTIVES: This study was designed to evaluate the effect of LSG on glycemic control among a sample of obese patients in Al-Madinah Al-Munawwarah, Saudi Arabia, through assessment of reduction in hemoglobin A1c (HbA1c) associated with weight loss following LSG. METHODS: In this cross-sectional study, we studied 102 patients with a body mass index (BMI) of ≥30 kg/m2 and aged ≥18 years who underwent LSG between January 2017 and December 2019. Patient age, characteristics, preoperative and postoperative records of BMI and HbA1c were collected. The data of BMI and HbA1c were analyzed based on baseline and mean postoperative readings with variable postoperative visits after LSG. RESULTS: There was a 30% reduction in BMI and a 26.4% reduction in HbA1c following LSG from baseline in all patients. We noted 44 patients achieved BMI <40kg/m2 with HbA1c <6.5% and 32 patients achieved BMI <40kg/m2 with HbA1c <5.7% within a mean follow-up time of 10 months. CONCLUSIONS: Laparoscopic Sleeve Gastrectomy (LSG) has a positive effect on glycemic control in obese patients in short term, evidenced by the significant reduction of weight and HbA1c. Larger longitudinal studies are needed to assess the long-term impact of LSG glycemic control and the related factors associated with maintaining weight reduction and optimal glycemic control in Saudi Arabia for patients with obesity.

Impact of Bilateral versus Single Internal Thoracic Artery Grafting on the Long-Term Survival in Adults: A Systematic Review.

OBJECTIVE: To analyse the survival of patients who had undergone bilateral internal thoracic artery grafting versus those with single internal thoracic artery grafting from the available literature. Moreover, this study will review the available literature regarding which of the two techniques seems to be the safest with long-term survival and reduced mortality rates. METHODS: A literature search of the databases was conducted to retrieve studies that fall under the study design of cohort and randomized controlled clinical trials in English from January 2015 to July 2021. Finally, seven studies were selected: four cohort studies and three other from a randomized trial. RESULTS: The cohort studies revealed that bilateral internal thoracic artery grafting is associated with lower mortality rates and better long-term survival outcomes than single internal thoracic artery grafting, while the ART randomized controlled clinical trials showed that there is no significant difference in mortality rates between both the coronary artery bypass grafting techniques. However, all studies concluded that bilateral internal thoracic artery grafting is associated with a higher frequency of deep sternal wound infections. CONCLUSION: The discrepancy in results between the cohort studies and randomized controlled clinical trial remains persistent. However, the stated advantages of bilateral internal thoracic artery grafting are not strong enough to convince surgeons to alter their practice and the wide magnitude of expectations from the ART study was reckoned as inadequate. This may well be due to the presence of limited criteria for bilateral internal thoracic artery grafting in identifying the impact on survival of extended arterial revascularization, and there is a new colossal expectation from the ongoing randomized trial based on multiple arterial grafting versus single arterial grafting.

Late presentation of extrauterine adenomyomas after laparoscopic morcellation at hysterectomy: a case report.

BACKGROUND: An adenomyoma is a well circumscribed form of adenomyosis and can be located within the myometrium, in the endometrium as a polyp, or extrauterine with the last being the rarest presentation amongst the three. With the ongoing advancement in gynecological surgery, the use of electromechanical morcellators have made the removal of large and dense specimens possible with minimally invasive techniques. However, it has also caused an increase in complications which were previously rare. Whilst the tissue is being grinded within the abdominal cavity, residual tissue can spread and remain inside, allowing for implantation to occur and thereby giving rise to recurrence of uterine tissue as a new late postoperative complication. Case presentation A 45-year-old woman presented with worsening constipation and right iliac fossa pain. Her past surgical history consists of laparoscopic supra-cervical hysterectomy that was indicated due to uterine fibroids. Computerized tomography and magnetic resonance imaging were done, which showed an irregular lobulated heterogeneous mass seen in the presacral space to the right, located on the right lateral aspect of the recto-sigmoid, measuring 4.5 × 4.3 × 4.3 cm in size. A transvaginal ultrasound revealed a cyst in the left ovary. The patient had a treatment course over several months that included Dienogest (progestin) and Goserelin (GnRH analogue) with add-back therapy. In line with the declining response to medications, the patient was advised for a laparoscopic ovarian cystectomy. During the surgery, an additional lesion was found as a suspected fibroid and the left ovarian cyst was identified as pockets of peritoneal fluid which was sent for cytology. The surgical pathology report confirmed adenomyosis in both specimens, namely the right mass and the initially suspected fibroid. CONCLUSION: In this case report, we showcase a rare occurrence of an extrauterine adenomyoma presenting two years post laparoscopic morcellation at hysterectomy. This poses questions regarding the benefits versus risks of power morcellation in laparoscopic hysterectomy.

The positive environmental impact of virtual isotretinoin management.

BACKGROUND/OBJECTIVES: Other medical specialties have studied how their practices influence the environment, but environmental impact studies in the field of dermatology remain limited. With respect to dermatology, vehicle emissions by patients traveling to and from appointments are an important factor influencing climate change. This study was undertaken to determine the greenhouse gas emissions avoided by managing isotretinoin virtually at West Virginia University Hospital. METHODS: A retrospective cross-sectional study was conducted during the COVID-19 outbreak from March 25 to December 1, 2020, where travel data were acquired and converted to emission data. RESULTS: 5,137 kg of GHG emissions in CO2 equivalents were prevented by managing isotretinoin virtually during the study period. 49 400 kg of GHG emissions in CO2 equivalents would be prevented annually. This is the emission load released when 24 690 kg of coal are burned. CONCLUSIONS: Environmental impact studies in the field of dermatology remain limited. GHG emissions were significantly reduced by virtually managing isotretinoin at a single institution. The practice of dermatology could reduce its carbon footprint by managing isotretinoin virtually, even in non-pandemic periods. Given that isotretinoin management represents a small percentage of the overall carbon footprint associated with dermatology, dermatologists should identify other conditions amenable to virtual medicine to produce greater environmental impact.

Noninvasive prediction of carotid artery atherosclerosis by multiple abdominal fat indices measured via ultrasonography.

PURPOSE: The purpose of this study was to evaluate the efficiency of multiple abdominal fat indices as measured via ultrasonography for predicting the presence and severity of carotid artery atherosclerosis and to compare the predictive capacity of ultrasonographic measurements to that of anthropometric measurements. METHODS: A total of 92 patients were included in this study. All participants underwent clinical and laboratory assessments, and anthropometric measurements were obtained. Ultrasound examinations were performed to measure the values of all abdominal fat indices and the intimamedia thickness, as well as to detect the presence of atherosclerotic plaques. Univariate and multivariate logistic regression analyses were performed. RESULTS: In the multivariate analysis, significant associations were detected between carotid artery atherosclerosis and posterior right perinephric fat thickness (PRPFT) (hazard ratio [HR], 15.23; P<0.001), preperitoneal fat thickness (PPFT) (HR, 4.31; P=0.003), visceral adipose tissue volume (VAT) (HR, 7.61; P<0.001), visceral fat thickness (VFT) (HR, 8.84; P<0.001), the ratio of VFT to subcutaneous fat thickness (VFT/SCFT) (HR, 9.39; P<0.001), and waist-to-height ratio (WHtR) (HR, 2.65; P=0.046). In the multivariate analysis, significant associations were also detected between carotid artery plaque and PRPFT (HR, 7.09; P<0.001), the abdominal wall fat index (AFI) (HR, 3.58; P=0.010), and VFT/SCFT (HR, 4.17; P=0.006). CONCLUSION: Many abdominal fat indices as measured by ultrasound were found to be strong predictors of carotid artery atherosclerosis, including PRPFT, VFT/SCFT, VFT, VAT, PPFT, and WHtR. Moreover, PRPFT, VFT/SCFT, and AFI were identified as strong predictors of the presence of carotid artery plaque.

Clinical and surgical aspects of congenital lobar over-inflation: a single center retrospective study.

BACKGROUND: Congenital lobar overinflation (CLOI) is one of the most important causes of infantile respiratory distress (RD). We aim to evaluate our experience in CLOI management emphasizing on clinical features, diagnostic modalities, surgery and outcomes. METHODS: This is a retrospective study for all CLOI cases undergoing surgical management at Qena University Hospital. Demographic data, clinical data, radiographic findings, surgery and postoperative follow-up were reviewed. RESULTS: A total of 37 neonates and infants with CLOI were presented to our center between January 2015 and January 2019; their mean age was 111.43 ± 65.19 days and 22 were males. All cases presented with RD; and cyanosis in 19 cases. 15 cases presented with recurrent pneumonia and fever. Diminished breath sounds on the affected side and wheezes were the main clinical findings in 30 and 22 cases respectively. On CXR, emphysema was detected in all cases. A confirmatory CT chest was done for all cases. Left upper lobe was affected in 23 cases, right middle lobe in 7 and right upper lobe in 7 cases. Lobectomy was done in thirty-one cases; their mean age at surgery was 147.58 ± 81.49 days and 19 were males. Postoperative complications were noted in 5 cases and postoperative ventilation was required for 2 of them. No morbidity or mortality was reported. The follow-up duration ranged from 3 months to 1 year and all patients were doing well except one case that lost follow up after 3 months. CONCLUSION: CLOI is a rare bronchopulmonary malformation that requires a high index of clinical suspicion, especially in persistent and recurrent infantile RD. CT chest is the most useful diagnostic modality. Early management of CLOI improves outcome and avoid life-threatening complications. Surgical management is the treatment of choice in our center without recorded mortality.

Correction to: Percutaneous ozone nucleolysis for lumbar disc herniation.

The published version of this article unfortunately contained a mistake. Affiliation 2 was presented incorrectly in the original article. The updated affiliation is Neuroradiology Unit, Bellaria Hospital, IRCCS Institute of Neurological Sciences, Bologna, Italy.

Percutaneous ozone nucleolysis for lumbar disc herniation.

PURPOSE: All percutaneous minimally invasive disc treatments are typically indicated to contained disc herniations. Our study's aim is to evaluate prospectively the efficacy of ozone nucleolysis in the treatment of either contained or uncontained lumbar disc herniations. METHODS: Fifty-two patients, aged 27-87 years, with symptomatic herniated lumbar discs, without migration, sequestration, or severe degenerative disc changes, who failed conservative treatment, were included in our study. The patients underwent fluoroscopic-guided intradiscal oxygen-ozone mixture injection (5 ml) at a concentration of 27-30 µg/ml and periradicular injection of the same O2-O3 mixture (10 ml), steroid (1 ml), and local anesthetic (1 ml). Clinical outcomes were evaluated, based on the Oswestry Disability Index (ODI) and pain intensity (0-5) scale results, obtained initially and at 2- and 6-month controls. Our results were analyzed by ANOVA and chi-squared (χ2) tests. RESULTS: Our initial results obtained at 2-month control were promising, indicating a significant decrease in pain disability and intensity in 74% (37) and 76% (38) of the patients respectively, and minimally increased to 76% (38) and 78% (39) at 6-month control (P < 0.001 and CI 99.9%). The mean preprocedure ODI and pain intensity scores were 35 ± 14.36 and 2.38 ± 0.90, respectively, which were reduced to 19.36 ± 13.12 and 1.04 ± 0.92 at 6-month control. Our failure had been mostly related to long symptoms duration of more than 1 year. No complications were recorded. CONCLUSION: Ozone nucleolysis is a safe cost-effective minimally invasive technique for treatment of contained and uncontained lumbar disc herniations.

NSIT: novel sequence identification tool.

Novel sequences are DNA sequences present in an individual's genome but absent in the human reference assembly. They are predicted to be biologically important, both individual and population specific, and consistent with the known human migration paths. Recent works have shown that an average person harbors 2-5 Mb of such sequences and estimated that the human pan-genome contains as high as 19-40 Mb of novel sequences. To identify them in a de novo genome assembly, some existing sequence aligners have been used but no computational method has been specifically proposed for this task. In this work, we developed NSIT (Novel Sequence Identification Tool), a software that can accurately and efficiently identify novel sequences in an individual's de novo whole genome assembly. We identified and characterized 1.1 Mb, 1.2 Mb, and 1.0 Mb of novel sequences in NA18507 (African), YH (Asian), and NA12878 (European) de novo genome assemblies, respectively. Our results show very high concordance with the previous work using the respective reference assembly. In addition, our results using the latest human reference assembly suggest that the amount of novel sequences per individual may not be as high as previously reported. We additionally developed a graphical viewer for comparisons of novel sequence contents. The viewer also helped in identifying sequence contamination; we found 130 kb of Epstein-Barr virus sequence in the previously published NA18507 novel sequences as well as 287 kb of zebrafish repeats in NA12878 de novo assembly. NSIT requires [Formula: see text]2GB of RAM and 1.5-2 hrs on a commodity desktop. The program is applicable to input assemblies with varying contig/scaffold sizes, ranging from 100 bp to as high as 50 Mb. It works in both 32-bit and 64-bit systems and outperforms, by large margins, other fast sequence aligners previously applied to this task. To our knowledge, NSIT is the first software designed specifically for novel sequence identification in a de novo human genome assembly.