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PURPOSE In sub-Saharan Africa, radiotherapy (RT) utilization and delivery patterns have not been extensively studied in patients with metastatic breast cancer. METHODS A retrospective cohort study of female patients with metastatic breast cancer seen at Parirenyatwa Radiotherapy Centre in Zimbabwe from 2014 to 2018 was conducted. Demographics, pathology, staging, and treatment data were abstracted through chart review. Fisher's exact test and chi-squared test of independence were used to compare proportions, and independent two-sample t-tests were used to compare means. RESULTS Of 351 patients with breast cancer, 152 (43%) had metastatic disease, median age 51 years (interquartile range: 43-61 years). Of those with metastatic disease, 30 patients (20%) received radiation to various metastatic sites: 16 spine; three nonspine bone metastases; six whole brain; and five chest wall or supraclavicular. Patients who received radiation were younger (46 v 52 years; P = .019), but did not differ significantly by performance status than those who did not. The most common dose prescription was 30 Gy in 10 fractions (33%). Five (17%) patients had treatment interruption and two (7%) had treatment noncompletion. Province of origin and clinical tumor stage were significant predictors of RT receipt ( P = .002; and P = .018, respectively). CONCLUSION A minority of patients with metastatic breast cancer received RT (20%), and these were likely to be younger, with advanced tumor stage, and resided in provinces where RT is available. Conventional courses were generally prescribed. There is a need to strongly consider palliative RT as an option for patients with metastatic breast cancer and use of hypofractionated courses (e.g. 8 Gy in one fraction) may support this goal.

We present a novel workflow for forecasting production in unconventional reservoirs using reduced-order models and machine-learning. Our physics-informed machine-learning workflow addresses the challenges to real-time reservoir management in unconventionals, namely the lack of data (i.e., the time-frame for which the wells have been producing), and the significant computational expense of high-fidelity modeling. We do this by applying the machine-learning paradigm of transfer learning, where we combine fast, but less accurate reduced-order models with slow, but accurate high-fidelity models. We use the Patzek model (Proc Natl Acad Sci 11:19731–19736, https://doi.org/10.1073/pnas.1313380110, 2013) as the reduced-order model to generate synthetic production data and supplement this data with synthetic production data obtained from high-fidelity discrete fracture network simulations of the site of interest. Our results demonstrate that training with low-fidelity models is not sufficient for accurate forecasting, but transfer learning is able to augment the knowledge and perform well once trained with the small set of results from the high-fidelity model. Such a physics-informed machine-learning (PIML) workflow, grounded in physics, is a viable candidate for real-time history matching and production forecasting in a fractured shale gas reservoir.

Non-alcoholic fatty liver disease (NAFLD) has become one of the most common chronic liver diseases worldwide. A strong relationship exists between NAFLD and diabetes mellitus. There is growing evidence of a mechanistically complex and strong association between the two diseases. Current data also shows that one disease actually leads to worsening of the other and vice versa. Understanding of the various pathophysiological mechanisms involved, natural history and spectrum of these two diseases is essential not only for early diagnosis and management but also for prevention of severe disease forms. Despite the tremendous progress made in recent times in acquiring knowledge about these highly prevalent diseases, the guidelines and recommendations for screening and management of diabetics with NAFLD remain ambiguous. An interdisciplinary approach is required to not only raise awareness of the prevalence of NAFLD in diabetics but also for better patient management. This can help attenuate the development of significant complications, such as cirrhosis, decompensation and hepatocellular carcinoma in these patients, thereby halting NAFLD in its tracks. This review focuses on the pivotal role of primary care physicians and endocrinologists in identification of NAFLD in diabetics in early stages and the role of proactive screening for prompt referral to hepatologist.

Few sub-Saharan African studies have ascertained utilization for postmastectomy radiation (PMRT) for breast cancer, the second most common cancer among African women. We estimated PMRT utilization and identified predictors of PMRT receipt in Zimbabwe. Retrospective patient cohort included non-metastatic breast cancer patients treated from 2014 to 2019. PMRT eligibility was assigned per NCCN guidelines. Patients receiving chemotherapy for non-metastatic disease were also included. The primary endpoint was receipt of PMRT, defined as chest wall with/without regional nodal radiation. Predictors of receiving PMRT were identified using logistic regression. Model performance was evaluated using the c statistic and Hosmer–Lemeshow test for goodness-of-fit. 201 women with localized disease and median follow-up of 11.4 months (IQR 3.3–17.9) were analyzed. PMRT was indicated in 177 women and utilized in 59(33.3%). Insurance coverage, clinical nodal involvement, higher grade, positive margins, and hormone therapy receipt were associated with higher odds of PMRT receipt. In adjusted models, no hormone therapy (aOR 0.12, 95% CI 0.043, 0.35) and missing grade (aOR 0.07, 95% CI 0.01, 0.38) were associated with lower odds of PMRT receipt. The resulting c statistic was 0.84, with Hosmer–Lemeshow p-value of 0.93 indicating good model fit. PMRT was utilized in 33% of those meeting NCCN criteria. Missing grade and no endocrine therapy receipt were associated with reduced likelihood of PMRT utilization. In addition to practice adjustments such as increasing hypofractionation and increasing patient access to standard oncologic testing at diagnosis could increase postmastectomy utilization.

Quantitative understanding of uranium transport by high temperature fluids is crucial for confident assessment of its migration in a number of natural and artificially induced contexts, such as hydrothermal uranium ore deposits and nuclear waste stored in geological repositories. An additional recent and atypical context would be the seawater inundated fuel of the Fukushima Daiichi Nuclear Power Plant. Given its wide applicability, understanding uranium transport will be useful regardless of whether nuclear power finds increased or decreased adoption in the future. The amount of uranium that can be carried by geofluids is enhanced by the formation of complexes with inorganic ligands. Carbonate has long been touted as a critical transporting ligand for uranium in both ore deposit and waste repository contexts. However, this paradigm has only been supported by experiments conducted at ambient conditions. We have experimentally evaluated the ability of carbonate-bearing fluids to dissolve (and therefore transport) uranium at high temperature, and discovered that in fact, at temperatures above 100 °C, carbonate becomes almost completely irrelevant as a transporting ligand. This demands a re-evaluation of a number of hydrothermal uranium transport models, as carbonate can no longer be considered key to the formation of uranium ore deposits or as an enabler of uranium transport from nuclear waste repositories at elevated temperatures. Carbonate species may play a role in uranium transport in natural systems and nuclear waste repositories at high temperatures. Here uranyl carbonate species are shown to decrease in stability under hydrothermal conditions, suggesting that these species may not mediate transport after all.

Placement of pathology and laboratory medicine (PALM) services requires balancing efficiency (maximizing test volume) with equitable urban–rural access. We compared the association between population density (proxy for efficiency) and travel time to the closest facility (proxy for equitable access) across levels of Tanzania’s public sector health system. We linked geospatial data for Tanzania from multiple sources. Data on facility locations and other geographic measures were collected from government and non-governmental databases. We classified facilities assuming increasing PALM availability by tier: (1) dispensaries, (2) health centres, (3) district hospitals and (4) regional/referral hospitals. We used the AccessMod 5 algorithm to estimate travel time to the closest facility for each tier across Tanzania with 500-m resolution. District-level average population density and travel time to the closest facility were calculated and presented using medians and interquartile ranges. Spatial correlations between these variables were estimated using the global Moran’s I and bivariate Local Indicator of Spatial Autocorrelation, specifying a queen’s neighbourhood matrix. Spatial analysis was restricted to 171 contiguous districts. The study included 5406 dispensaries, 675 health centres, 186 district hospitals and 37 regional/referral hospitals. District-level travel times were shortest for Tier 1 (median: [IQR]: 45.4 min [30.0–74.7]) and longest for Tier 4 facilities (160.2 min [107.3–260.0]). There was a weak spatial autocorrelation across tiers (Tier 1: −0.289, Tier 2: −0.292, Tier 3: −0.271 and Tier 4: −0.258) and few districts were classified as significant spatial outliers. Across tiers, geographic patterns of populated districts surrounded by neighbours with short travel time and sparsely populated districts surrounded by neighbours with long travel time were observed. Similar spatial correlation measures across health system levels suggest that Tanzania’s health system reflects equitable urban–rural access to different PALM services. Longer travel times to hospital-based care could be ameliorated by shifting specialized diagnostics to more accessible lower tiers.

The permeability of complex porous materials is of interest to many engineering disciplines. This quantity can be obtained via direct flow simulation, which provides the most accurate results, but is very computationally expensive. In particular, the simulation convergence time scales poorly as the simulation domains become less porous or more heterogeneous. Semi-analytical models that rely on averaged structural properties (i.e., porosity and tortuosity) have been proposed, but these features only partly summarize the domain, resulting in limited applicability. On the other hand, data-driven machine learning approaches have shown great promise for building more general models by virtue of accounting for the spatial arrangement of the domains’ solid boundaries. However, prior approaches building on the convolutional neural network (ConvNet) literature concerning 2D image recognition problems do not scale well to the large 3D domains required to obtain a representative elementary volume (REV). As such, most prior work focused on homogeneous samples, where a small REV entails that the global nature of fluid flow could be mostly neglected, and accordingly, the memory bottleneck of addressing 3D domains with ConvNets was side-stepped. Therefore, important geometries such as fractures and vuggy domains could not be modeled properly. In this work, we address this limitation with a general multiscale deep learning model that is able to learn from porous media simulation data. By using a coupled set of neural networks that view the domain on different scales, we enable the evaluation of large ($$>512^3$$ > 512 3 ) images in approximately one second on a single graphics processing unit. This model architecture opens up the possibility of modeling domain sizes that would not be feasible using traditional direct simulation tools on a desktop computer. We validate our method with a laminar fluid flow case using vuggy samples and fractures. As a result of viewing the entire domain at once, our model is able to perform accurate prediction on domains exhibiting a large degree of heterogeneity. We expect the methodology to be applicable to many other transport problems where complex geometries play a central role.

Background Breast cancer is the second most common cancer among women in Zimbabwe. Patients face socioeconomic barriers to accessing oncology care, including radiotherapy. We sought to understand patterns of care and adherence for women with breast cancer in sub‐Saharan Africa (SSA) with radiotherapy access. Methods A retrospective cohort was created for women with breast cancer evaluated at the Parirenyatwa Hospital Radiotherapy and Oncology Center (RTC) from 2014 to 2018. Clinical data were collected to define patterns of care. Non‐adherence was modeled as a binary outcome with different criteria for patients with localized versus metastatic disease. Results In total, 351 women presented with breast cancer with median age 51 at diagnosis (IQR: 43–61). Receptor status was missing for 71% (248). 199 (57%) had non‐metastatic disease, and 152 (43%) had metastases. Of women with localized disease, 34% received post‐mastectomy radiation. Of women with metastatic disease, 9.7% received radiotherapy. Metastatic disease and missing HIV status were associated with increased odds of study‐defined non‐adherence (aOR: 1.85, 95% CI: 1.05, 3.28; aOR: 2.13, 95% CI: 1.11, 4.05), while availability of ER/PR status was associated with lower odds of non‐adherence (aOR: 0.18, 95% CI: 0.09, 0.36). Conclusions Radiotherapy is likely underutilized for women with breast cancer, even in a setting with public sector availability. Exploring patient‐level factors that influence adherence to care may provide clinicians with better tools to support adherence and improve survival. Greater investment is needed in multidisciplinary, multimodality care for breast cancer in SSA.

Experiments are always the go-to approach to reveal mysterious observations and verify new theories. However, scientific research has shifted to areas that are difficult to probe experimentally. Fo...

The technique of laparoscopic cholecystectomy (LC) has been standardized and it has become a routine and safe operation. However, there are numerous conditions which make the operation difficult necessitating conversion to open surgery. Preoperative prediction of a difficult cholecystectomy and the risk of conversion is of great help both to the patient who can be counseled appropriately pre-operatively and the surgeon who can also schedule his time and team accordingly. This prospective cross-sectional study was conducted on 118 patients undergoing laparoscopic cholecystectomy in Department of General Surgery, Aditya Birla Memorial Hospital, Chinchwad, Pune, over a period of 18 months from October 2015 to March 2017, to evaluate and correlate the clinical, biochemical and ultrasonography findings with the operative findings for anticipating difficult laparoscopic cholecystectomy. The parameters which were studied are age ≥ 60 years, sex, BMI > 30, history of (h/o) previous upper abdominal surgery, history of gall stone related complications, history of prior biliary intervention, biochemical parameters like Hb, TLC and LFT levels, gall bladder wall thickness (≥ 4 mm), pericholecystic collection, gall bladder size (contracted or distended gall bladder), stone impaction at neck/cystic duct and stone size > 1 cm. The operative parameters taken to assess the difficulty of the LC were total time taken to operate from the insertion of the trocar to the extraction of the gall bladder (more than 90 minutes), change of procedure to subtotal cholecystectomy and conversion to OC. Our study results show that significant predictors for difficult LC are increasing age of patients, h/o gall stone related complications, h/o prior biliary intervention, raised TLC and deranged LFT levels, GB wall thickness ≥ 4 mm, pericholecystic fluid collection, tensely distended/contracted GB and stone size > 1cm. However factors like sex of patient, BMI, history of previous upper abdominal surgery, haemoglobin levels and stone impacted at neck of gall bladder showed no significant relation with operative difficulty.

Abstarct Background/Objective Mild and moderate traumatic brain injury (TBI) is a neglected field especially with reference to its association with cognitive, behavioral, and emotional sequelae. The present study aimed to investigate the association of affective symptoms and clinical factors with neurocognitive functioning in complicated mild and moderate TBI patients. Materials and Methods The sample comprised 39 complicated mild and moderate TBI patients with age range of 18 to 59 years. The study was conducted in the Department of Neurosurgery, Banaras Hindu University, Varanasi. The patients were assessed with the neurocognitive tests, Rivermead Post Concussion Symptom Questionnaire, and Hospital Anxiety and Depression Scale. Statistical Analysis Partial correlations and zero order correlations were used to test the relationships between variables. Results The injury-related factors, namely level of consciousness and Glasgow Coma Scale were found to be associated with divided attention and memory dysfunction (p < 0.05), respectively. Anxiety was found to be associated with impairment on all domains of neurocognitive function (p < 0.05) except divided attention. Depressive symptoms were found to be correlated with all the neurocognitive functions (p < 0.05) except focused and divided attention, whereas head injury symptoms correlated with impairment on focused and divided attention (p < 0.05). Conclusion Present study highlights the need to acknowledge affective symptoms along with clinical factors in the planning of the rehabilitation programs for such patients in rural scenario.

In today’s competitive business environment, family and non-family small and medium enterprises (SMEs) strive to survive despite many challenges. Market knowledge and marketing efforts are crucial for them to sustain and enhance business with limited resources. In this paper, we examined three constructs (i) market orientation, (ii) marketing capabilities and (iii) marketing practices impact on the SMEs’ service sector performance. The interaction effect of ownership type (family and non-family firms) was also observed in the model. Data was collected from 240 SMEs in three major metropolitan cities. This study found positive relationships of each construct (market orientation, (ii) marketing capabilities and (iii) marketing practices) on firm performance as hypothesised. The interaction effect of ownership type i.e. family and non-family, evident on marketing capabilities and SMEs’ performance. Non-family businesses are open for adopting new ideas and personnel into decision making. Family firms should be more adaptable to compete with non-family firms. The managerial and theoretical implications discussed in family and non-family firms’ perspective.

The phenomenon of flow-channeling, or the existence of preferential pathways for flow in fracture networks, is well known. Identification of the channels (“backbone”) allows for system reduction and computational efficiency in simulation of flow and transport through fracture networks. However, the purpose of machine learning techniques for backbone identification in fractured media is two-pronged system reduction for computational efficiency in simulation of flow and transport as well as physical insight into the phenomenon of flow channeling. The most critical aspect of this problem is the need to have a truly “physics-informed” technique that respects the constraint of connectivity. We present a method that views a network as a union of connected paths with each path comprising a sequence of fractures. Thus, the fundamental unit of selection becomes a sequence of fractures, classified based on attributes that characterize the sequence. In summary, this method represents a parametrization of the sample space that ensures every selected sample sub-network (which is the union of all selected sequences of fractures) always respects the constraint of connectivity, demonstrating that it is a truly physics-informed method. The algorithm has a user-defined parameter which allows control of the backbone size when using the random forest or logistic regression classifier. Even when the backbones are less than 30% in size (leading to computational savings), the backbones still capture the behavior of the breakthrough curve of the full network. Moreover, there is no need to check for path connectedness in the backbones unlike previous methods since the backbones are guaranteed to be connected.

We introduce an innovative ensemble analysis framework for organizing, searching, and comparing results produced by hundreds of physical simulations. Our web-based approach is built on standard technologies, utilizes a scalable and modular design, and is suitable for displaying the results of in situ analysis and extreme-scale simulations.

BACKGROUND: Fixation of mesh in pre-peritoneal space is an important step in laparoscopic TAPP hernia repair. Mesh dislocation is one of the most frequent causes responsible for recurrence. Of the many factors inuencing postoperative pain, the technique of xation has been reported to be one of the most signicant determinants. So mesh xation with adhesives instead of mechanical devices has been proposed as a mean to reduce the incidence of postoperative pain. AIM: To compare clinical outcome and morbidity of xation of mesh using brin glue and tackers in trans-abdominal pre-peritoneal inguinal hernia repair METHODOLOGY: We did a prospective randomized comparative study in which we enrolled 50 patients undergoing laparoscopic hernia repair (TAPP). Those who met our inclusion criteria were randomized for study purpose after obtaining informed consent, in 25 patients mesh xed with tackers (group A) and in other 25 patients mesh xed with brin glue (group B). Patients were compared for intraoperative time required for mesh xation, early and late postoperative pain, time required to resume normal daily physical activity, length of hospital stay, hernia recurrence and seroma formation. Postoperative follow up was done up to six months. RESULTS: Two groups were comparable in terms of demographic variables. We observed that postoperative pain, time required resuming normal daily activity and incidence of seroma formation was less in group B (Mesh xed with glue). There was no signicant difference in length of hospital stay in both groups and no evidence of hernia recurrence in both groups during follow up period. CONCLUSION: It can be concluded that xation of mesh with brin glue when compared with tackers, seems to reduce postoperative pain, time to resume daily activities and incidence of seroma formation with no difference in length of hospital stay, early hernia recurrence with longer operative time.

Background: Surgical site infection (SSI) is a significant problem associated with open abdominal surgery resulting in increased morbidity, mortality, and cost of treatment. Surgical site infection is one of the most common post-operative complications, occurring in at least 5% of all patients undergoing surgery and 30-40% of patients undergoing abdominal surgery, depending on the level of contamination. This study compares the subcutaneous single closed suction drain and simple conventional closure of skin incision in emergency laparotomy for hollow viscus perforation.Aim: The aim of the study is to determine whether the insertion of a subcutaneous closed suction drain at the incisional site reduces the incidence of post-operative surgical site infection in emergency laparotomy for hollow viscus perforation.Methodology: This is a prospective study. Fifty patients was enrolled, Patients diagnosed to have acute abdomen clinically and radiologically were planned for emergency exploratory laparotomy. They were further allocated alternately to Group I with subcutaneous closed suction drain and Group II without drain. All the patients underwent laparotomy. Postoperatively wound complications and hospital stay was recorded.Conclusion: Our study shows that subcutaneous negative pressure drainage significantly reduces the post- operative surgical site infection and duration of hospital stay following surgery for hollow viscus perforation. This helps in early recovery, better wound healing, and decreases the financial burden on patients by decreasing hospital stay and infection. As post-operative complications depend on the level of contamination, we recommend use of closed negative pressure subcutaneous drain in all patients with contaminated or dirty wounds.

Acute myeloid leukemia (AML) is an aggressive leukemia with poor outcomes even among patients eligible for intensive anthracycline-based induction chemotherapy [1]. While complete remission (CR) is...

There has been a concerted effort to change the nomenclature of non-alcoholic fatty liver disease (NAFLD) to metabolic dysfunction-associated fatty liver disease (MAFLD), and one wonders if it is appropriate and timely to bid adieu to the good old term. Numerous reasons have been put forth to justify this, as outlined in a recently published statement proposing the change. However, there are considerable flaws in the proposal, and changing NAFLD to MAFLD is unlikely to move the field forward.We have serious misgivings on this matter.o begin with, the statement by the MAFLD consensus group that the term NAFLD was coined by Ludwig and colleagues is factually incorrect. Although the histological features of NAFLD were first described decades ago, Klatskin and his colleagues, in 1979, were the first to use the term ‘non-alcoholic liver disease’.Later, while reporting similar findings, Ludwig and colleagues coined the term “non-alcoholic steatohepatitis (NASH)”.Although an association between metabolic syndrome (MS) and NAFLD has been established and NAFLD termed the hepatic manifestation of MS, this generalisation has since been questioned, since the complex heterogeneity of this entity precludes any single postulation to explain its pathogenesis. Besides, individuals with normal BMI also develop NAFLD, and studies in non-Caucasian populations have shown that a significant proportion of patients with NAFLD do not have insulin resistance (IR).Further, even with elevated hepatic triacylglycerol and diacylglycerol content, hepatic IR has not been observed in murine models,and dissociation of hepatic steatosis from IR has also been noted in a subset of individuals. Importantly, in subjects with PNPLA3 polymorphisms,steatosis occurs independently of IR and serum lipid concentration. Further, increased serum bile acid levels also seem to be independently associated with NASH in non-diabetics.NAFLD is also associated with gut dysbiosis independent of BMI and IR. Finally, “soft” drink consumption has also been linked to the development of fatty liver independent of obesity, diabetes and hyperlipidemia.and last but not least, cigarette smoking too has been found to be an independent risk factor in NAFLD progression. Thus it is clear that pathogenesis of NAFLD is multifactorial and complex, involving multiple and divergent pathways.In Medicine, a change of name of any disease has significant implications for both medical professionals and patients.The term ‘NAFLD’ aptly describes individuals who have fatty liver but neither consume significant amounts of alcohol nor had any other reason for fatty liver. Research in NAFLD to date has failed to pinpoint any factor as the sole cause for hepatic steatosis and NAFLD still encompasses a spectrum of disorders, metabolic syndrome being a part – maybe a major part – of that spectrum with a relatively barren treatment armamentarium. Will changing nomenclature address these concerns? We fear it might paradoxically misdirect therapeutics in the direction of MS alone which may ultimately turn out to be a red herring. The consensus group found multiple faults with the term NAFLD; these include: i) NAFLD is a disease of exclusion instead of being defined by inclusion, ii) NAFLD is a vastly heterogeneous entity and cannot be managed as one single condition and iii) patients with NAFLD do consume alcohol and the impact of alcohol, albeit in non-significant amounts, is under scrutiny. In Medicine, naming a disease through exclusion has been acceptable since time immemorial. Non-Hodgkin lymphoma encompasses vastly diverse malignancies and yet the terminology very effectively delineates those disorders from Hodgkin lymphoma. Regarding heterogeneity, it is not clear how a mere change of name would make the entity more homogeneous. If the word “metabolic” in MAFLD is meant as a reference to MS, it would be a rejection of much of the scientific evidence gathered on NAFLD pathogenesis. In contrast to the assertion of the proponents of MAFLD, who after splitting “nonalcoholic” into - ‘non’ and ‘alcoholic’, suggest that the word “non” trivializes the problem while the word “alcoholic” demeans the patient, we believe that the word ‘nonalcoholic’ does go a long way in destigmatizing the patient. The European Liver Patients Association (ELPA) is believed to have expressed displeasure with the term NAFLD to the European Commission in 2018, and suggested that a change in nomenclature was required. The degree of assertion and the rationale for such a suggestion are unclear; it is also unclear whether the diverse pathogenesis of NAFLD – especially in non-Caucasians – was considered in the decision. Further, an opinion on the impact of non-significant alcohol intake on hepatic steatosis is also unclear as acknowledged in the consensus statement. Notably, metabolic abnormalities and BMI are well described risk factors for alcoholic liver disease too,but it is unclear why both conditions more or less related to alcohol should be brought under the umbrella of MAFLD. The change of nomenclature has also been argued against since NAFLD is treated by cardiologists, diabetologists and primary care providers in addition to hepatologists; a name change could create unnecessary clinical confusion and coding issues. The heterogeneity of NAFLD and presence of multiple pathophysiological pathways inherent to its progression implies that the time is ripe to classify NAFLD in a novel way that takes into account the various pathophysiological processes. We wish to propose the ‘MEGA-D’ classification emphasising the ‘mega diversity’ or heterogeneity in NAFLD where NAFLD remains the umbrella entity with different subgroups under it (NAFLD-M: Metabolic syndrome associated NAFLD, NAFLD-E: Environmental Stressor Related NAFLD, NAFLD-G: Genetic Factor Associated NAFLD, NAFLD-A: Bile Acid Dysregulation Related NAFLD, NAFLD-D: Gut Dysbiosis Related NAFLD) representing separate pathways culminating in hepatic steatosis. We feel, instead of semantic juggling, collaborative efforts should be launched worldwide to better understand the vast heterogeneity in NAFLD across populations and ethnicities and explore its different pathophysiologic mechanisms, with the sole purpose of modifying disease progression, bolstering the treatment arsenal and curbing this epidemic.

Both communicable and non-communicable chronic respiratory conditions have accorded for suffering of millions of people of all ages and stated to be leading cause of death, morbidity, economic and social pressures, and disability-adjusted life-years (DALYs) worldwide. These illnesses impair patient's health and negatively impacts families and society, particularly in low and middle-income countries. Chronic respiratory diseases (CRDs) affect different organs of respiratory system, involving airways, parenchyma, and pulmonary vasculature. As the number of respiratory diseases are exponentially escalating but still the stakeholders are not paying attention towards its serious complications. Currently, the treatment being used primarily focusses only on alleviating symptoms of these illness rather delivering the therapeutic agent at target site for optimal care and/or prevention. Lately, extensive research is being conducted on airways and systemic inflammation, oxidative stress, airway, or parenchymal rehabilitation. From which macrophages, neutrophils, and T cells, as well as structural cells as fibroblasts, epithelial, endothelial, and smooth muscle cells have been found to be active participants that are involved in these chronic respiratory diseases. The pathogenesis of all these chronic respiratory diseases gets caused differently via mediators and proteins, including cytokines, chemokines, growth factors and oxidants. Presently, the target of prescription therapies is to reduce the inflammation of airways and relieve the airway contraction. In all studies, cytokines have been found to play an imperative role in fostering chronic airway inflammation and remodelling. Owing to the limitations of conventional treatments, the current review aims to summarize the current knowledge about the chronic respiratory disease and discuss further about the various conventional methods that can be used for treating this ailment. Additionally, it also highlights and discusses about the advanced drug delivery system that are being used for targeting the interleukins for the treatment of CRDs.

INTRODUCTION AND OBJECTIVE:Massachusetts (MA) is a northeastern state with universally mandated health insurance since 2006. Although Black men have generally worse prostate cancer outcomes, emergi...

A comprehensive evaluation of toxic chemicals and understanding their potential harm to human physiology is vital in mitigating their adverse effects following exposure from environmental emergencies. In this work, we develop data-driven classification models to facilitate rapid decision making in such catastrophic events and predict the estrogenic activity of environmental toxicants as estrogen receptor-α (ERα) agonists or antagonists. By combining high-content analysis, big-data analytics, and machine learning algorithms, we demonstrate that highly accurate classifiers can be constructed for evaluating the estrogenic potential of many chemicals. We follow a rigorous, high throughput microscopy-based high-content analysis pipeline to measure the single cell-level response of benchmark compounds with known in vivo effects on the ERα pathway. The resulting high-dimensional dataset is then pre-processed by fitting a non-central gamma probability distribution function to each feature, compound, and concentration. The characteristic parameters of the distribution, which represent the mean and the shape of the distribution, are used as features for the classification analysis via Random Forest (RF) and Support Vector Machine (SVM) algorithms. The results show that the SVM classifier can predict the estrogenic potential of benchmark chemicals with higher accuracy than the RF algorithm, which misclassifies two antagonist compounds.

Light alkanes from shale resources can potentially be converted to an easy-to-transport liquid hydrocarbon product by catalytic dehydrogenation followed by catalytic oligomerization. The chemical s...

The American Society for Heating, Refrigeration, and Air Conditioning Engineers (ASHARE) prescribes fixed ventilation rates for the operation of heating, ventilation, and air conditioning (HVAC) systems, which is sub-optimal in terms of controlling indoor air pollutants and energy consumption. This paper relies on a physics-based model of a residential house to predict the concentrations of indoor pollutants such as ozone, formaldehyde (HCHO), and particulate matter (PM) as function of time, outdoor conditions, and indoor emissions. The model captures real-world scenarios such as pollutants entering the house from ambient air through an air handling unit (AHU) and pollutants emitted in the house. A dynamic optimization problem is then formulated and solved to calculate the optimal ventilation rate at each time instant, that minimizes the total energy consumption, while maintaining the indoor pollutant concentrations below or as close as possible to their respective acceptable thresholds. For the considered example day, operation under optimized conditions reduces the peak pollutant concentration by 31%, time of exposure to undesirable concentrations by 48%, and energy consumption of the AHU by 17.7%.

Background We evaluated safety and immunogenicity of the first mRNA vaccines against potentially pandemic avian H10N8 and H7N9 influenza viruses. Methods Two randomized, placebo-controlled, double-blind, phase 1 clinical trials enrolled participants between December 2015 and August 2017 at single centers in Germany (H10N8) and USA (H7N9). Healthy adults (ages 18–64 years for H10N8 study; 18–49 years for H7N9 study) participated. Participants received vaccine or placebo in a 2-dose vaccination series 3 weeks apart. H10N8 intramuscular (IM) dose levels of 25, 50, 75, 100, and 400 µg and intradermal dose levels of 25 and 50 µg were evaluated. H7N9 IM 10-, 25-, and 50-µg dose levels were evaluated; 2-dose series 6 months apart was also evaluated. Primary endpoints were safety (adverse events) and tolerability. Secondary immunogenicity outcomes included humoral (hemagglutination inhibition [HAI], microneutralization [MN] assays) and cell-mediated responses (ELISPOT assay). Results H10N8 and H7N9 mRNA IM vaccines demonstrated favorable safety and reactogenicity profiles. No vaccine-related serious adverse event was reported. For H10N8 (N = 201), 100-µg IM dose induced HAI titers ≥ 1:40 in 100% and MN titers ≥ 1:20 in 87.0% of participants. The 25-µg intradermal dose induced HAI titers > 1:40 in 64.7% of participants compared to 34.5% of participants receiving the IM dose. For H7N9 (N = 156), IM doses of 10, 25, and 50 µg achieved HAI titers ≥ 1:40 in 36.0%, 96.3%, and 89.7% of participants, respectively. MN titers ≥ 1:20 were achieved by 100% in the 10- and 25-µg groups and 96.6% in the 50-µg group. Seroconversion rates were 78.3% (HAI) and 87.0% (MN) for H10N8 (100 µg IM) and 96.3% (HAI) and 100% (MN) in H7N9 (50 µg). Significant cell-mediated responses were not detected in either study. Conclusions The first mRNA vaccines against H10N8 and H7N9 influenza viruses were well tolerated and elicited robust humoral immune responses. ClinicalTrials.gov NCT03076385 and NCT03345043 .

PURPOSE This pilot study evaluated and compared the degree of new bone formation following maxillary sinus graft (MSG) using three different bone graft materials. MATERIAL AND METHODS Patients with an edentulous posterior maxilla (unilateral or bilateral) were included in this study and underwent a two-stage procedure. Each sinus was randomly assigned one of the three graft materials: anorganic bovine bone mineral (ABBM), anorganic equine bone mineral (AEBM), or mineralized cancellous bone allograft (MCBA). Bone core samples were obtained from the lateral wall of the grafted sites at least 8 months after MSG. Bone quality was evaluated during bone core retrieval. The samples were histomorphometrically analyzed using Kruskal-Wallis and Dunn-Bonferroni tests at the significance level of α = .05. RESULTS A total of 28 sinuses (14 unilateral and 7 bilateral) from 21 subjects, with a mean age of 61.5 (range, 33-75) years, were included in the study. Twenty-eight bone cores (ABBM [n = 9], AEBM [n = 9], and MCBA [n = 10]) were obtained at a mean healing time of 9.1 (range, 8-12) months. Six maxillary sinus membrane perforations (≤ 5 mm) were noted and repaired during surgery (21.4%). Histomorphometric analysis of the harvested bone cores revealed statistically significant differences in the percentage of vital bone (VB%), residual bone materials (RBM%), and connective tissue/marrow (CT%) among the different graft materials (Kruskal-Wallis; P < .05). The VB% in the MCBA group (32.0% ± 12.4%) was significantly greater than those in the ABBM (10.9% ± 8.9%) and AEBM (9.1% ± 5.9%) groups (P < .05). The RBM% in the MCBA group (5.5% ± 5.7%) was, however, significantly less than those in the ABBM (34.3% ± 12.1%) and AEBM (38.9% ± 5.3%) groups (P < .05). There were no significant differences in VB% and RBM% between ABBM and AEBM (P = 1.0). Newly formed bone and residual graft materials were integrated into the surrounding tissue with no sign of inflammation or foreign-body reaction. CONCLUSION Within the confines of the study, MCBA has significantly greater new bone formation than ABBM and AEBM. AEBM showed comparable histomorphometric results in all parameters (VB%, RBM%, CT%) to ABBM.

BackgroundSouth Africa has the highest number of people living with HIV (PLWH) and one of the largest antiretroviral therapy (ART) programs globally. High rates of substance use comorbidity exist, including speculation of recreational ART use (i.e., mixing ART with other illicit drugs). Recreational ART use may affect viral load among PLWH due to ART nonadherence and/or viral resistance; however, prior quantitative research has not examined rates of recreational ART use, nor associations with HIV treatment outcomes longitudinally.MethodsData were drawn from a prospective, observational cohort study (n = 500) of ART-eligible adults recruited from two HIV voluntary counseling and testing centers in Cape Town, and Johannesburg, South Africa. Multiple logistic regression models assessed recreational ART use as a predictor of ART initiation over six months and viral load suppression over nine months, above and beyond other substance use (binge drinking and illicit drug use).ResultsApproximately 5% (n = 24) reported recreational ART use, which was less frequent in Cape Town compared to Johannesburg (AOR = 0.025; 95%CI: 0.003-0.19; p

Discrete fracture networks (DFN) are often used to model flow and transport in fractured porous media. The accurate resolution of flow and transport behavior on a large DFN involving thousands of fractures is computationally expensive. This makes uncertainty quantification studies of quantities of interest such as travel time through the network computationally intractable, since hundreds to thousands of runs of the DFN model are required to get bounds on the uncertainty of the predictions. Prior works on the subject demonstrated that the complexity of a DFN could be reduced by considering a sub-network of it (often termed a “backbone” sub-network), one whose flow and transport properties were then shown to be similar to that of the full network. The technique is tantamount to partitioning the complete set of fractures of a network into two disjoint sets, one of which is the backbone sub-network while the other its complement. It is in this context that we present a system-reduction technique for DFNs using supervised machine learning via a Random Forest Classifier that selects a backbone sub-network from the full set of fractures. The in-sample errors (in terms of precision and recall scores) of the trained classifier are found to be very accurate indicators of the out-of-sample errors, thus exhibiting that the classifier generalizes well to test data. Moreover, this system-reduction technique yields sub-networks as small as 12% of the full DFN that still recover transport characteristics of the full network such as the peak dosage and tailing behavior for late times. Most importantly, the sub-networks remain connected, and their size can be controlled by a single dimensionless parameter. Furthermore, measures of KL-divergence and KS-statistic for the breakthrough curves of the sub-networks with respect to the full network show physically realistic trends in that the measures decrease monotonically as the size of the sub-networks increase. The computational efficiency gained by this technique depends on the size of the sub-network, but large reductions in computational time can be expected for small sub-networks, yielding as much as 90% computational savings for sub-networks that are as small as 10-12% of the full network.

Typically, thousands of computationally expensive micro-scale simulations of brittle crack propagation are needed to upscale lower length scale phenomena to the macro-continuum scale. Running such a large number of crack propagation simulations presents a significant computational challenge, making reduced-order models (ROMs) attractive for this task. The ultimate goal of this research is to develop ROMs that have sufficient accuracy and low computational cost so that these upscaling simulations can be readily performed. However, constructing ROMs for these complex simulations presents its own challenge. Here, we present and compare four different approaches for reduced-order modeling of brittle crack propagation in geomaterials. These methods rely on machine learning (ML) and graph-theoretic algorithms to approximate key aspects of the brittle crack problem. These methods also incorporate different physics-based assumptions in order to reduce the training requirements while maintaining accurate physics as much as possible. Results from the ROMs are directly compared against a high-fidelity model of brittle crack propagation. Further, the strengths and weaknesses of the ROMs are discussed, and we conclude that combining smart physics-informed feature engineering with highly trainable ML models provides the best performance. The ROMs considered here have computational costs that are orders-of-magnitude less than the cost associated with high-fidelity physical models while maintaining good accuracy.

Quench hardening is the process of heating finished or pre-finished steel parts to a specific temperature in order to reach a phase transformation of steel to austenite (austenitization) followed by quenching in oil, water or brine to induce desired metallurgical properties. During this process, both macroscopic quantities such as temperature and heat duty and microscopic variables, such as austenite grain size, determine the quality of the quenched product. In this paper, we propose a novel model-based approach for optimizing the energy input to an austenitization furnace system by capturing the essential physics at both the aforementioned length scales. The model predicts the energy consumption of the system, the part temperature distribution and the austenite grain size distribution as a function of the processing time and processing conditions. An optimization scheme is proposed to minimize the furnace energy consumption without compromising the part heating requirements and product quality.

Background: There are rich state-based epidemiological evidences on dementia in India, which shows that neurodegenerative disorders are one of the major public health problems. However, inconsistencies and variability have been observed among the findings of most of the reported studies. Objectives: This meta-analysis was conducted to estimate the overall prevalence of dementia in India. Methods: Databases of several web sources, namely EBSCOhost, PubMed, PsycINFO, and Google Scholar were explored for searching the studies that had previously observed the prevalence of dementia in India. Retrieved articles were systematically selected using specific inclusion and exclusion criteria. The quality of the included studies was assessed through guidelines of strengthening the reporting of observational studies in epidemiology, and the risk of bias was assessed using the guidelines of Quality in Prognosis Studies. Meta-analysis was computed using R software (3.5.3) with “metaphor” package. Results: The present meta-analysis included 20 epidemiological studies consisting of 86,312 persons, out of which a total number of 1193 persons reported to have dementia across several states of India. The results of the meta-analysis indicated the number of elderly that suffer from dementia amounts to 20 per 1000 population (95% confidence interval: 0.02–0.03). The prevalence was higher in older age groups (75 years and above) as compared to those below 75 years of age. However, the prevalence rates were similar for males and females and rural and urban population. Conclusion: Dementia is a common neuropsychiatric condition in the Indian elderly population. Further, evidence-based national survey is needed to estimate the exact prevalence of the disease in the country.

Understanding and responding to adverse human health impacts of global environmental change will be a major priority of 21st century public health professionals. The emerging field of planetary health aims to face this challenge by studying and promoting policies that protect the health of humans and of the Earth's natural systems that support them. Public health, drawing on its experience of guiding policies to improve population health, has contributed to planetary health's development. Yet, few public health practitioners are familiar with planetary health's systems-oriented approaches for understanding relationships between economic development, environmental degradation, and human health. In this narrative review, we present key planetary health concepts and show how systems thinking has guided its development. We discuss historical approaches to studying impacts of economic development on human health and the environment. We then review novel conceptual frameworks adopted by planetary health scientists to study and forecast impacts of policies that influence human health and Earth's natural systems at varying spatiotemporal scales. We conclude by presenting examples of how applying the “Doughnut” model (an economic framework where the needs of people are met without overshooting the world's ecological limits) could guide policies for promoting health co-benefits to humans and natural systems.

Background Reducing disparities in men with prostate cancer (PCa) that may be caused by racial and socioeconomic differences is a major public health priority. Few reports have studied whether these disparities have changed over time. Methods Men diagnosed with PCa from January 1, 2000 to December 31, 2015 were identified from the Massachusetts and Pennsylvania cancer registries. All-cause mortality and PCa and cardiovascular cause-specific mortality were assessed. To estimate neighborhood socioeconomic position (nSEP), a summary score was generated using census tract-level measures of income, wealth, educational attainment, and racial and income segregation. Participants were grouped by diagnosis year (2000-2003, 2004-2007, 2008-2011, or 2012-2015), and changing trends in the mortality rate ratio by race and nSEP were estimated using covariate-adjusted Cox models with follow-up for up to 10 years, until death, or until censoring on January 1, 2018. Results There were 193,883 patients with PCa and 43,661 deaths over 1,404,131 person-years of follow-up. The Black-White adjusted hazard ratio (aHR) from 2000 to 2003 through 2012 to 2015 was stable for all-cause mortality (aHR, 1.14 to 0.97; P for heterogeneity = .42), decreased for PCa-specific mortality (aHR, 1.38 to 0.93; P for heterogeneity = .005), and increased for cardiovascular mortality (aHR, 1.09 to 1.28; P for heterogeneity = .034). The aHR comparing those in the lowest versus the highest nSEP quintile increased significantly for all-cause mortality (aHR, 1.54 to 1.79; P for heterogeneity = .008), but not for PCa-specific mortality (aHR, 1.60 to 1.72; P for heterogeneity = .40) or cardiovascular mortality (aHR, 1.72 to 1.89; P for heterogeneity = .085). Conclusions Although Black-White disparities in prostate mortality declined in Massachusetts and Pennsylvania over the study period, nSEP mortality disparity trends were stagnant or increased, warranting further attention. Lay summary Few reports have examined whether racial and socioeconomic disparities in prostate cancer mortality have widened or narrowed in recent years. Using data from 2 state registries (Massachusetts and Pennsylvania) with differing intensities of government-mandated health insurance, trends in racial and neighborhood socioeconomic disparities were studied among Black and White men diagnosed from 2000 to 2015. Overall, trends in racial disparities were stagnant for all-cause mortality, shrank for prostate mortality, and widened for cardiovascular mortality. Disparities associated with neighborhood socioeconomic status either were stagnant or widened across all mortality end points. In general, disparities were more pronounced in Pennsylvania than in Massachusetts.

Background Massachusetts is a northeastern state with universally mandated health insurance since 2006. Although Black men have generally worse prostate cancer outcomes, emerging data suggest that they may experience equivalent outcomes within a fully insured system. In this setting, the authors analyzed treatments and outcomes of non-Hispanic White and Black men in Massachusetts. Methods White and Black men who were 20 years old or older and had been diagnosed with localized intermediate- or high-risk nonmetastatic prostate cancer in 2004-2015 were identified in the Massachusetts Cancer Registry. Adjusted logistic regression models were used to assess predictors of definitive therapy. Adjusted and unadjusted survival models compared cancer-specific mortality. Interaction terms were then used to assess whether the effect of race varied between counties. Results A total of 20,856 men were identified. Of these, 19,287 (92.5%) were White. There were significant county-level differences in the odds of receiving definitive therapy and survival. Survival was worse for those with high-risk cancer (adjusted hazard ratio [HR], 1.50; 95% CI, 1.4-1.60) and those with public insurance (adjusted HR for Medicaid, 1.69; 95% CI, 1.38-2.07; adjusted HR for Medicare, 1.2; 95% CI, 1.14-1.35). Black men were less likely to receive definitive therapy (adjusted odds ratio, 0.78; 95% CI, 0.74-0.83) but had a 17% lower cancer-specific mortality (adjusted HR, 0.83; 95% CI, 0.7-0.99). Conclusions Despite lower odds of definitive treatment, Black men experience decreased cancer-specific mortality in comparison with White men in Massachusetts. These data support the growing body of research showing that Black men may achieve outcomes equivalent to or even better than those of White men within the context of a well-insured population. Lay summary There is a growing body of evidence showing that the excess risk of death among Black men with prostate cancer may be caused by disparities in access to care, with few or no disparities seen in universally insured health systems such as the Veterans Affairs and US Military Health System. Therefore, the authors sought to assess racial disparities in prostate cancer in Massachusetts, which was the earliest US state to mandate universal insurance coverage (in 2006). Despite lower odds of definitive treatment, Black men with prostate cancer experience reduced cancer-specific mortality in comparison with White men in Massachusetts. These data support the growing body of research showing that Black men may achieve outcomes equivalent to or even better than those of White men within the context of a well-insured population.

This paper summarizes the risk assessment and management workflow developed and applied to the Southwest Regional Partnership on Carbon Sequestration (SWP) Phase III Demonstration Project. The risk assessment and management workflow consists of six primary tasks, including management planning, identification, qualitative analysis, quantitative analysis, response planning, and monitoring. Within the workflow, the SWP assembled and iteratively updated a risk registry that identifies risks for all major activities of the project. Risk elements were ranked with respect to the potential impact to the project and the likelihood of occurrence. Both qualitative and quantitative risk analyses were performed. To graphically depict the interactions among risk elements and help building risk scenarios, process influence diagrams were used to represent the interactions. The SWP employed quantitative methods of risk analysis including Response Surface Method (RSM), Polynomial Chaos Expansion (PCE), and the National Risk Assessment Partnership (NRAP) toolset. The SWP also developed risk response planning and performed risk control and monitoring to prevent the risks from affecting the project and ensure the effectiveness of risk management. As part of risk control and monitoring, existing and new risks have been tracked and the response plan was subsequently evaluated. Findings and lessons learned from the SWP’s risk assessment and management efforts will provide valuable information for other commercial geological CO2 storage projects.

By 2050, shale gas production is expected to exceed three-quarters of total US natural gas production. However, current unconventional hydrocarbon gas recovery rates are only around 20%. Maximizing production of this natural resource thus necessitates improved understanding of the fundamental mechanisms underlying hydrocarbon retention within the nanoporous shale matrix. In this study, we integrated molecular simulation with high-pressure small-angle neutron scattering (SANS), an experimental technique uniquely capable of characterizing methane behavior in situ within shale nanopores at elevated pressures. Samples were created using Marcellus shale, a gas-generative formation comprising the largest natural gas field in the United States. Our results demonstrate that, contrary to the conventional wisdom that elevated drawdown pressure increases methane recovery, a higher peak pressure led to the trapping of dense, liquid-like methane in sub-2 nm radius nanopores, which comprise more than 90% of the measured nanopore volume, due to irreversible deformation of the kerogen matrix. These findings have critical implications for pressure management strategies to maximize hydrocarbon recovery, as well as broad implications for fluid behavior under confinement. Liquid-like methane could be trapped in pores of less than 2 nm, rather than recovered, when higher peak pressure is applied during shale gas drilling. This was revealed by integrated molecular simulations and high-pressure small-angle neutron scattering on Marcellus Shale samples.

BackgroundNeighborhood contextual factors are associated with racial disparities among men with prostate cancer (CaP), but studies often separately emphasize socioeconomic status or built environme...

According to WHO, about 422 million people are affected with diabetics and among them 15% of diabetic patients are associated with foot problems. Due to peripheral neuropathy, the patients are unable to sense pressure pain which eventually creates calluses. Thus the aim of this study is to effectively find the risk areas which may form ulcers in the foot. The physical components required for this study are a camera which captures high-quality images of foot and a laptop capable of processing image by using MATLAB (The Mathworks Inc., USA). The algorithm which we developed extracts the high-intensity areas in the foot which are actually the areas where the patient exert high pressure compared to other areas in the foot. This method was evaluated by assessing the foot for 5 normal patients and 5 diabetic patients. It is found that this method is capable of giving the riskier areas of the foot and thereby further prevention of foot ulcer can be done. Our method is time-efficient, cost-efficient, and space-efficient and thus can be easily installed in any hospital for diabetic foot analysis. In most of the cases, the metatarsal head region and plantar medial tubercle region are mainly affected by calluses. By proper diagnosis and daily care of the foot can reduce the risk of ulcer in diabetic patients.

Background : Kratom is a botanical product used as an opium substitute with abuse potential. Methods : Assessment of suspected cases of kratom-induced liver injury in a prospective US cohort. Results : Eleven cases of liver injury attributed to kratom were identified with a recent increase. The majority were male with median age 40 years. All were symptomatic and developed jaundice with a median latency of 14 days. The liver injury pattern was variable, most required hospitalization and all eventually recovered. Biochemical analysis revealed active kratom ingredients. Conclusion : Kratom can cause severe liver injury with jaundice.

Background Alveolar ridge preservation via socket grafting (ARP‐SG) is indicated to attenuate physiologic alveolar bone resorption as a consequence of tooth extraction. However, a specific bone grafting material that is patently superior has not been identified yet. The aim of this randomized controlled trial was to evaluate the efficacy of a moldable alloplastic graft, Poly Lactic‐Co‐Glycolic Acid‐Coated β‐Tricalcium Phosphate (PLGA‐β‐TCP), for ARP purposes [Group A] compared to freeze‐dried bone allograft (FDBA) particles covered with a rapidly absorbable collagen dressing (RACD) [Group B] in function of a panel of radiographic, histomorphometric and implant‐related outcomes. Methods Patients in need of extraction of a single posterior tooth (premolar or molar) and subsequent replacement with a dental implant were recruited and randomly allocated into one of the two treatment groups. Follow‐up visits took place at 1, 2, 4, 8 and 16 weeks. Cone‐beam Computed Tomography (CBCT) scans were obtained at baseline and at 16 weeks. Sites were re‐entered at 20 weeks for bone core biopsy harvesting and subsequent implant placement. After delivery of the final implant‐supported restoration, follow‐up visits were scheduled at 6 and 12 months to monitor peri‐implant tissue health and marginal bone levels using standardized intraoral periapical radiographs. Results A total of 45 patients were initially enrolled in the study, of whom 43 received an implant and 32 completed the study. Healing was uneventful in all sites after ARP‐SG and implant placement. No site required bone augmentation to allow for implant placement. CBCT scan analyses showed no statistically significant differences between groups in terms of reduction of horizontal width, midbuccal / midlingual height and ridge volume. Histomorphometric assessments revealed a statistically significant difference between both groups in terms of mineralized tissue formation (Group A = 27.0±22.1% vs. Group B = 38.2±12.5%; p

Late blight (LB) of potato is considered one of the most devastating plant diseases in the world. Most cultivated potatoes are susceptible to this disease. However, wild relatives of potatoes are an excellent source of LB resistance. We screened 384 accessions of 72 different wild potato species available from the U.S. Potato GeneBank against the LB pathogen Phytophthora infestans in a detached leaf assay (DLA). P. infestans isolates US-23 and NL13316 were used in the DLA to screen the accessions. Although all plants in 273 accessions were susceptible, all screened plants in 39 accessions were resistant. Resistant and susceptible plants were found in 33 accessions. All tested plants showed a partial resistance phenotype in two accessions, segregation of resistant and partial resistant plants in nine accessions, segregation of partially resistant and susceptible plants in four accessions, and segregation of resistant, partially resistant, and susceptible individuals in 24 accessions. We found several species that were never before reported to be resistant to LB: Solanum albornozii, S. agrimoniifolium, S. chomatophilum, S. ehrenbergii, S. hypacrarthrum, S. iopetalum, S. palustre, S. piurae, S. morelliforme, S. neocardenasii, S. trifidum, and S. stipuloideum. These new species could provide novel sources of LB resistance. P. infestans clonal lineage-specific screening of selected species was conducted to identify the presence of RB resistance. We found LB resistant accessions in Solanum verrucosum, Solanum stoloniferum, and S. morelliforme that were susceptible to the RB overcoming isolate NL13316, indicating the presence of RB-like resistance in these species.

A general term N95 Mask has been widely used by all including the health care personnel. It has been use incorrectly by all and it should be replaced with the term filtering facepiece respirator. There are two types of respirators being used in the world. One is the industrial type whereas the other one is the medical surgical one. The medical surgical masks are an intermediate product between the industrial and the triple layer medical mask. Many other equivalent products like KN95 masks are also available in the market. There is an urgent need of certification because this is the only way quality face masks can be provided to the public in these difficult times of COVID-19. This is essential because of the entry of many counterfeit and uncertified respirators have entered the market.

A postmortem evaluation of a 5-implant-supported mandibular fixed complete denture that had successfully opposed a maxillary conventional complete denture for 30 years was undertaken. Before embalming, radiographs, implant stability measurements, push-in failure load tests, and histomorphometric analyses were performed on the implants and the mandible. Evaluation of this cadaver suggests that an edentulous mandible restored with an implant-supported fixed prosthesis can function successfully for over 30 years with few complications.

Fractured systems are ubiquitous in natural and engineered applications as diverse as hydraulic fracturing, underground nuclear test detection, corrosive damage in materials and brittle failure of metals and ceramics. Microstructural information (fracture size, orientation, etc.) plays a key role in governing the dominant physics for these systems but can only be known statistically. Current models either ignore or idealize microscale information at these larger scales because we lack a framework that efficiently utilizes it in its entirety to predict macroscale behavior in brittle materials. We propose a method that integrates computational physics, machine learning and graph theory to make a paradigm shift from computationally intensive high-fidelity models to coarse-scale graphs without loss of critical structural information. We exploit the underlying discrete structure of fracture networks in systems considering flow through fractures and fracture propagation. We demonstrate that compact graph representations require significantly fewer degrees of freedom (dof) to capture micro-fracture information and further accelerate these models with Machine Learning. Our method has been shown to improve accuracy of predictions with up to four orders of magnitude speedup.

Background Recombinant human bone morphogenetic protein-2 in an absorbable collagen sponge carrier (rhBMP-2/ACS) has been shown to support significant bone formation when used to augment the maxillary sinus for implant dentistry. Nevertheless, bone biomaterials have been suggested to extend rhBMP-2/ACS with limited support of the merits of such approaches. Objectives To evaluate local bone formation/dental implant osseointegration following implantation of rhBMP-2/ACS combined with a ceramic bone biomaterial using a mini-pig sinus augmentation model. Methods Twelve adult Gottingen mini-pigs received rhBMP-2/ACS (rhBMP-2 adjusted to 0.43 mg/cc) alone or combined with an off-the-shelf biphasic ceramic (15%/85% HA/s-TCP) biomaterial at 3:1, 1:1 and 1:3 ratios randomized to contra-lateral maxillary sinus sites yielding rhBMP-2/ACS fractions of 100%, 75%, 50% and 25%, respectively. A 4-cc implant volume was used for all sites. Two threaded dental implants (o4.0 × 11.5 mm) were placed at each site. The animals were euthanized at 8 weeks for histologic analysis. Results Surgical execution and healing were generally uneventful, infraorbital local swelling was observed in all animals until suture removal. rhBMP-2/ACS combined with the ceramic biomaterial did not significantly enhance local bone formation (range 9.0 ± 1.5 to 9.7 ± 2.1 mm) compared with rhBMP-2/ACS alone (8.6 ± 1.1 mm; p > 0.05). Variations in rhBMP-2/ACS to ceramic matrix ratios yielding rhBMP-2 doses approximating 0.4, 0.9, 1.3 and 1.7 mg/sinus did not appreciably influence bone formation/osseointegration. Conclusions Whereas rhBMP-2/ACS supports significant bone formation/osseointegration in the mini-pig sinus augmentation model and thus appears an effective alternative for sinus augmentation procedures, adding a ceramic biomaterial to rhBMP-2/ACS does not produce meaningful biological advantages.

Although there are guidelines for video capsule endoscopy (VCE) and device-assisted enteroscopy (DAE), little is known about fellowship training in these technologies. The aims were to better characterize current small bowel endoscopy training in 3-year GI fellowship programs and 4th-year advanced endoscopy programs in the U.S. We developed an online multiple-choice survey to assess current GI fellowship program training in small bowel endoscopy. The survey was distributed via email to GI fellowship program directors in the U.S. Of the 168 program directors contacted, 59 responded (response rate = 35.1%). There was no statistically significant difference in the availability of VCE or DAE between respondents and non-respondents. VCE training was universally available in 3-year training programs, with 84.8% (50/59) requiring it for fellows. The majority of 3-year GI fellows graduated with independence in VCE: 83.1% (49/59) of programs reported “most” or “all” graduates were able to read independently. DAE techniques were available in 86.4% of training programs (51/59). Training in DAE was more limited and shared between 3-year and 4th-year programs: 12.1% (7/58) of 3-year programs required training in DAE and 22.9% (8/35) of 4th-year programs required training in DAE . Training in VCE is widely available in U.S. GI fellowship programs, although programs have different ways of incorporating this training into the curriculum and of measuring competency. While DAE technology was available in the majority of programs, training was less frequently available, and training is shared between 3-year fellowship programs and 4th-year advanced endoscopy programs .

OBJECTIVEThe challenging nature of neurosurgical residency necessitates that appropriate measures are taken by training programs to ensure that residents are properly progressing through their education. Residents who display a pattern of performance deficiencies must be identified and promptly addressed by faculty and program directors to ensure that resident training and patient care are not affected. While studies have been conducted to characterize these so-called “problem residents” in other specialties, no current data regarding the prevalence and management of such residents in neurosurgery exist. The purpose of this study was to determine the rate and the outcome of problem residents in US neurosurgical residency programs and identify predictive risk factors that portend a resident’s departure from the program.METHODSAn anonymous nationwide survey was sent to all 108 neurosurgical training programs in the US to assess a 20-year history of overall attrition as well as the management course of problem residents, including the specific deficiencies of the resident, management strategies used by faculty, and the eventual outcome of each resident’s training.RESULTSResponses were received from 36 centers covering a total of 1573 residents, with the programs providing a mean 17.4 years’ worth of data (95% CI 15.3–19.4 years). The mean prevalence of problem residents among training programs was 18.1% (95% CI 14.7%–21.6%). The most common deficiencies recognized by program directors were poor communication skills (59.9%), inefficiency in tasks (40.1%), and poor fund of medical knowledge (39.1%). The most common forms of program intervention were additional meetings to provide detailed feedback (93.9%), verbal warnings (78.7%), and formal written remediation plans (61.4%). Of the identified problem residents whose training status is known, 50% graduated or are on track to graduate, while the remaining 50% ultimately left their residency program for other endeavors. Of the 97 residents who departed their programs, 65% left voluntarily (most commonly for another specialty), and 35% were terminated (often ultimately training in another neurosurgery program). On multivariable logistic regression analysis, the following 3 factors were independently associated with departure of a problem resident from their residency program: dishonesty (OR 3.23, 95% CI 1.67–6.253), poor fund of medical knowledge (OR 2.54, 95% CI 1.47–4.40), and poor technical skill (OR 2.37, 95% CI 1.37–4.12).CONCLUSIONSThe authors’ findings represent the first study to characterize the nature of problem residents within neurosurgery. Identification of predictive risk factors, such as dishonesty, poor medical knowledge, and/or technical skill, may enable program directors to preemptively act and address such deficiencies in residents before departure from the program occurs. As half of the problem residents departed their programs, there remains an unmet need for further research regarding effective remediation strategies.