Perspectives on child health and wellbeing

The coronavirus disease 2019 (COVID-19) pandemic has brought unparalleled challenges to the care of children and adolescents globally. India is currently second on the list of countries with highest case counts and third in terms of deaths. According to data from the Ministry of Health and Family Welfare, as on September 1, 2020, eight percent of the cases and one percent of deaths in India have occurred in children aged under 17 years. COVID-19 appears to be milder in children than in adults, which is quite atypical for a respiratory viral infection, commonly presenting as a self- limiting febrile upper respiratory illness. However, children are still at risk of developing severe illness and complications from COVID-19. These include respiratory failure, damage to the heart, kidneys, and multi-organ system failure, just like in adults. A minority of children can also experience a serious, post-infectious inflammatory syndrome, which is specific to children, difficult to treat and can be associated with long-term consequences. The overall mortality rate due to the disease in much lower in children compared to adults

Researching AI Legibility Through Design

Everyday interactions with computers are increasingly likely to involve elements of Artificial Intelligence (AI). Encompassing a broad spectrum of technologies and applications, AI poses many challenges for HCI and design. One such challenge is the need to make AI’s role in a given system legible to the user in a meaningful way. In this paper we employ a Research through Design (RtD) approach to explore how this might be achieved. Building on contemporary concerns and a thorough exploration of related research, our RtD process reflects on designing imagery intended to help increase AI legibility for users. The paper makes three contributions. First, we thoroughly explore prior research in order to critically unpack the AI legibility problem space. Second, we respond with design proposals whose aim is to enhance the legibility, to users, of systems using AI. Third, we explore the role of design-led enquiry as a tool for critically exploring the intersection between HCI and AI research

HSP27 is a mediator of sustained smooth muscle contraction in response to bombesin

We have identified the low MW 27 kD heat shock protein as a major phosphoprotein constituent of smooth muscle and have investigated its potential role in agonist induced smooth muscle contraction. The neuropeptides bombesin and substance P, which are present in neurons of the anorectal region, induce contraction of isolated smooth muscle cells from this region by activating different intracellular pathways. Substance P-induced contraction is 1,4,5-inositol trisphosphate (IP3)/calmodulin dependent, while contraction induced by bombesin is mediated by a protein kinase C (PKC)-dependent pathway. The sustained contraction induced by bombesin or exogenous PKC was blocked by preincubation of cells with monoclonal antibodies to hsp27, while the transient contraction induced by substance P or IP3 was unaffected by the antibodies. Preincubation with isotype matched control antibodies had no inhibitory effect on contraction induced in response to the agents used. These data support a novel role for hsp27 in the non calmodulin mediated sustained contraction induced by bombesin or PKC.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28974/1/0000001.pd

dc121p-patel

Abstract Researchers have used machine learning algorithms to solve hard problems in a variety of domains, enabling exciting, new applications of computing. However, research results have not transferred to software solutions. In part, this is because developing software with machine learning algorithms is itself difficult. My dissertation work aims to understand why using machine learning is difficult and to create tools that lower the bar so that more developers can effectively use machine learning

Lowering the Barrier to Applying Machine Learning

Thesis (Ph.D.)--University of Washington, 2012Data is driving the future of computation: analysis, visualization, and learning algorithms power systems that help us diagnose cancer, live sustainably, and understand the universe. Yet, the data explosion has outstripped our tools to process it, leaving a gap between powerful new algorithms and what real programmers can apply in practice. I examine how data affects the way we program. Specifically, this dissertation focuses on using machine learning algorithms to train a model. I found that the key barrier to adoption is not a poor understanding of the machine learning algorithms themselves, but rather a poor understanding of the process for applying those algorithms and insufficient tool support for that process. I have created new programming and analysis tools that support programmers by helping them (1) implement machine learning systems and analyze results, (2) debug data, and (3) design and track experiments

Perspectives on child health and wellbeing

The coronavirus disease 2019 (COVID-19) pandemic has brought unparalleled challenges to the care of children and adolescents globally. India is currently second on the list of countries with highest case counts and third in terms of deaths. According to data from the Ministry of Health and Family Welfare, as on September 1, 2020, eight percent of the cases and one percent of deaths in India have occurred in children aged under 17 years. COVID-19 appears to be milder in children than in adults, which is quite atypical for a respiratory viral infection, commonly presenting as a self- limiting febrile upper respiratory illness. However, children are still at risk of developing severe illness and complications from COVID-19. These include respiratory failure, damage to the heart, kidneys, and multi-organ system failure, just like in adults. A minority of children can also experience a serious, post-infectious inflammatory syndrome, which is specific to children, difficult to treat and can be associated with long-term consequences. The overall mortality rate due to the disease in much lower in children compared to adults

Clinical Profile, Aetiology and Outcome of Afebrile Seizures in Children

Introduction: Clinical and outcome profiles of childhood seizures can be different in resource limited settings where neurologists face lots of challenges in diagnosis and management of seizure. This study was conducted to investigate the clinical profile, causes and outcome of afebrile seizures in children in resource limited settings. Methods: This was a prospective hospital based study. Children with afebrile seizures were followed up with exclusion of febrile and acute provoked seizures. Clinical, investigation, treatment and outcome parameters were analyzed. Results: Study included 308 (age one month to 20 years) children. Median age at first seizure was 39 (inter quartile range 12-96) months. History of status epilepticus was present in 26.0%. Cause of seizure was known in 44.2%. Seizure was generalized in 79.2%, partial in 14.0% and unclassified in 6.8%. Common causes of seizure were – birth asphyxia (12.3%), neurocysticercosis (8.8%), sequel of nervous system infection (6.5%) and structural brain abnormalities (7.1%). Neurological examination, electroencephalography and computed tomography (CT) were abnormal in 24.4%, 70.5% and 27.9% cases respectively. Seizure control was achieved in 79.3% and by monotherapy in 85.0 % cases. Seizure control with single drug, seizure without recurrence and idiopathic seizure were associated with favourable outcome. Conclusions: Prevention and control of birth asphyxia, neurocysticercosis and nervous system infections are needed to reduce the burden of afebrile seizures in this area. CT is a valuable diagnostic tool and response to monotherapy is good. Seizure control with single drug, seizure without recurrence and idiopathic seizure are favourable prognostic factors. Keywords: afebrile seizure; children; clinical profile; outcome

Re-thinking treatment strategies for febrile neutropenia in paediatric oncology population: the perspective from a developing country

Abstract Background This study was conducted to evaluate the microbiological profile of bacterial isolates in febrile neutropenia in a pediatric oncology unit, thereby, reviewing the use of restricted antibiotics and need for aggressive medical treatment accordingly. Methods A prospective observational study was conducted in a paediatric haemat-oncology division of a tertiary care teaching hospital in southern India from September 2014 to August 2016. One hundred and thirty children with febrile neutropenia were enrolled in the study. Blood cultures were performed using automated system. Cultures from other sites were obtained if needed, based on the clinical profile. Standard antibiotic susceptibility testing was done. Statistical analysis was done using SPSS. Results One hundred and thirty children were enrolled for the study. Two hundred and fifty episodes of febrile neutropenia were studied. Three hundred and eighty four cultures were sent and 92 (24%) cultures were positive. There were 48 (52.2%) Gram negative isolates followed by 33 (35.8%) Gram positive isolates, six (6.5%) fungal isolates and five (5.5%) poly-microbial cultures. Lactose fermenting Gram negative bacilli (20 isolates, 31.5%) were the most frequently isolated in the Gram negative group, with Escherichia coli being the most common organism (19 isolates, 20.6%). Amongst the Gram positive coagulase negative staphylococcus was the most common (twenty seven isolates, 29%). Escherichia coli and Non lactose fermenting gram negative bacteria (NFGNB) had only 36, 25% sensitivity to ceftazidime, respectively. Most Gram negative bacilli were found to have better sensitivity to amikacin (mean: 57%). There was a higher prevalence of extended spectrum beta lactamase producing organisms. Pan drug resistance, Extreme drug resistance and Multi drug resistance was found in three, twenty and thirteen Gram negative isolates respectively.Escherichia coli and Klebsiella were often drug resistant. Significantly higher mortality was associated with Gram negative isolates (eight deaths out of the thirteen deaths, 61.5%). Conclusions Our results show the importance of surveillance, monitoring resistance frequencies and identifying risk factors specific to each region. Given that significant mortality is attributed to drug resistant Gram negative bacilli, early initiation of appropriate antibiotics to cover for drug resistance is required while formulating empirical antibiotic policies for febrile neutropenia in the oncology units in the developing world