Long-Term Glucose Forecasting for Open-Source Automated Insulin Delivery Systems: A Machine Learning Study with Real-World Variability Analysis

Glucose forecasting serves as a backbone for several healthcare applications, including real-time insulin dosing in people with diabetes and physical activity optimization. This paper presents a study on the use of machine learning (ML) and deep learning (DL) methods for predicting glucose variability (GV) in individuals with open-source automated insulin delivery systems (AID). A three-stage experimental framework is employed in this work to systematically implement and evaluate ML/DL methods on a large-scale diabetes dataset collected from individuals with open-source AID. The first stage involves data collection, the second stage involves data preparation and exploratory analysis, and the third stage involves developing, fine-tuning, and evaluating ML/DL models. The performance and resource costs of the models are evaluated alongside relative and proportional errors for 17 GV metrics. Evaluation of fine-tuned ML/DL models shows considerable accuracy in glucose forecasting and variability analysis up to 48 h in advance. The average MAE ranges from 2.50 mg/dL for long short-term memory models (LSTM) to 4.94 mg/dL for autoregressive integrated moving average (ARIMA) models, and the RMSE ranges from 3.7 mg/dL for LSTM to 7.67 mg/dL for ARIMA. Model execution time is proportional to the amount of data used for training, with long short-term memory models having the lowest execution time but the highest memory consumption compared to other models. This work successfully incorporates the use of appropriate programming frameworks, concurrency-enhancing tools, and resource and storage cost estimators to encourage the sustainable use of ML/DL in real-world AID systems.European Commission Horizon 2020Marie Skłodowska-Curie Action Research and Innovation Staff Exchange (RISE

Gaba-B Encephalitis in Pakistan: A Rare but Treatable Entity

Autoimmune and paraneoplastic encephalitides are a group of neurologic disorders that present with cognitive decline, neuropsychiatric symptoms, movement disorders, or seizures. These diseases can present before, with, or after the diagnosis of malignancy. We report two cases of GABA-B encephalitis from Pakistan. The first patient was a 67-year-old gentleman presented with cognitive decline and neuropsychiatric symptoms. His CSF analysis showed increased protein levels and GABA-B receptor antibodies. He was treated with pulse steroids, which improved his symptoms. The second patient was a 34-year-old lady with cognitive decline and psychomotor symptoms. Her serum autoimmune antibody panel showed antibodies against GABA-B receptors. She was treated with pulse steroids followed by plasma exchange, but did not improve. A low threshold should be kept for testing for autoimmune and paraneoplastic encephalitides because they are potentially treatable

Stiff person syndrome: a diagnostic and management challenge

Stiff person syndrome (SPS) is a rare neurological disorder characterized by progressive muscle stiffness and rigidity, mostly involving axial muscles, resulting in functional disability. It is associated with elevated anti- Glutamic acid decarboxylase (GAD) antibody levels. Electromyography findings are often diagnostic. We present a case of a 48 years old male, who presented with progressive stiffness and rigidity of axial muscles and limbs. His EMG was consistent with SPS. Anti GAD antibodies were markedly elevated. He was treated with rituximab and has improved significantly. SPS is a difficult diagnosis, usually under diagnosed due to lack of awareness among medical community. There is a dire need to further study the disease and invent better treatment options for patients suffering from SPS

Expression of a full length Arabidopsis vacuolar H+-pyrophosphatase (AVP1) gene in tobacco (Nicotiana tabbacum) to increase tolerance to drought and salt stresses

Among various abiotic stresses salinity and drought are the two major factors limiting the crop productivity. Genetically engineered salt and drought tolerant plants could provide an avenue to the reclamation of farmlands lost to agriculture because of salinity and a lack of rainfall. The Arabidopsis gene AVP1 encodes a vacuolar pyrophosphatase that functions as a proton pump and generates an electrochemical gradient in vacuole, thereby activating vacuolar membrane-antiporters including Na+/H+ antiporter, which helps in sequestration of Na+ into vacuole. In addition, over-expression of AVP1 gene increase vegetative growth by auxin transport and enhances auxin mediated root development, consequently achieving higher water absorption and retention capacities. The goal of present work is amplification of full length AVP1 (3.2kb) gene, from Arabidopsis thaliana genomic DNA through PCR, its cloning into a suitable plant expression vector and transformation in tobacco through Agrobacterium mediated transformation method for its characterization. PCR analysis showed the successful transformation of this gene in Nicotiana tabaccum. Screening of these putative transgenic plants against different salinity levels (50-250mM NaCl) showed that transgenic plants were tolerant to 250mM NaCl whereas the control plants showed wilting within 36-48 hours of salt treatment. Under periodic drought stress treatment transgenic (AVP1) plants were significantly more tolerant than wild type plants. Similarly the results of salinity and drought tolerance experiment in sand under saline and water regime conditions confirmed that introns play a key role in gene expression and regulations and improve the growth of plants. These resistant phenotypes are associated with increased internal stores of solutes

Reporting of mycetoma cases from skin and soft tissue biopsies over a period of ten years: A single center report and literature review from Pakistan

Background: Mycetoma is an important neglected tropical disease associated with debilitation, disfigurement and death if not diagnosed and treated adequately. In Pakistan, mycetoma cases have frequently been diagnosed in histopathology and microbiology laboratories. However, there is scarcity of published data from this country. Therefore, the objectives of this study were to evaluate the frequency and type of mycetoma reported in skin and soft tissue biopsies from a single center over 10 years and review of published literature from Pakistan.Method: This descriptive observational retrospective study was conducted at the Aga Khan University Hospital laboratory, Karachi, Pakistan. Laboratory data from 2009-2018 of skin and soft tissue biopsies with positive findings of mycetoma were retrieved from hospital information system. The variables for statistical analysis were age and gender of patient, anatomical site of lesion, residence of patient (geographical location) in the country, etiologic agents of mycetoma and significant gross and microscopic histopathological findings. The data was entered, and descriptive epidemiologic assessment was carried out using MS excel 2013. Geographical information system was used for mapping the location. Literature review of mycetoma cases reported from Pakistan was done on PubMed, Google search and PakMediNet from 1980 till April 2019.Result: During ten years of study period, 89 skin and soft tissue biopsies were reported as mycetoma, majority were eumycetoma [n = 66/89 (74%)] followed by actinomycetoma [n = 23/89 (26%)]. Involvement of lower limb was predominantly observed [n = 74/89 (83%)] in which foot had significant contribution [n = 65/74 (88%)]. Only 18 specimens were submitted for microbiological assessment and six grew agents of mycetoma, with Madurella mycetomatis reported in only three. Well-formed granuloma formation was observed in only 26%[n = 23/89] of cases. Specific geographical location was not identified, and cases were reported from across the country. From Pakistan, only two original papers and 7 case reports were available in published literature.Conclusion: This single center study reports a handful of cases of mycetoma from Pakistan. We conclude that the index of suspicion should remain high among treating surgeons and physicians and clinical laboratories should improve their diagnostic capacity and skills. This will have a great impact on disease outcome and patient\u27s life

Frequency of Congenital Anomalies in Newborns and Its Relation to Maternal Health in a Tertiary Care Hospital in Peshawar, Pakistan

Background: Congenital anomalies are a major cause of perinatal and neonatal deaths, both in low- and high-income countries. They are relatively common worldwide, affecting 3% to 5% of live births. Methods: A cross-sectional study was conducted from January 2014 to June 2014 at the Khyber teaching hospital in Peshawar. Specific patient information was obtained from patient records at the beginning of the study. Those individuals found to have at least one birth defect were approached and their attendants (mothers) were interviewed. Information regarding various risk factors was collected. Descriptive analyses were carried out. Results: Out of 1062 deliveries, 2.9% (31) of newborns had various congenital anomalies.b Hydrocephalus (22.6%), anencephaly (12.9%), and spina bifida (9.7%) were major anomalies. The maternal age ranged from 18 years to 46 years (mean: 30 ± 8). Most of the anomalies (35.5%) were present in the 26-30 years age group. Out of 31 babies, 6.4% had multiple anomalies. The preponderance of various congenital anomalies was seen in parity 1 (35.4%); parities 2 to 4 had lower incidences (35.4%). The consanguinity rate was 67.7%; only 32.3% of patients were using folic acid. History of passive smoking was positive in 16.1% of cases. Conclusion: Anencephaly and hydrocephalus were the most prominent anomaly detected; early prenatal diagnosis may be helpful in decreasing mortality by offering early termination. Low intake of folic acid and a high consanguinity rate were the most common associated risk factors for congenital anomalies. These risk factors may be reduced by creating awareness regarding the avoidance...

Human Cryptosporidiosis: An insight into Epidemiology, Modern Diagnostic Tools and Recent Drug Discoveries

Cryptosporidiosis is an emerging food and water borne zoonotic disease, which is caused by genusCryptosporidium. The first Cryptosporidium spp. was isolated from mice in 1907 and gained importance when it was found in an HIV positive patient. It usually causes self-limiting diarrhea in young children and immunocompetent patients. However, it may lead to chronic diarrhea with life threatening condition in immunocompromised patients. Other complications related to this transmittable infection may include respiratory problems, skin rashes and headache. HIV/AIDS patients are highly susceptible host for this parasite. Cryptosporidium parvum and Cryptosporidium hominis are the known pathogenic species, prevalent among humans and they are being transmitted through contaminated food and water. Usually, the diagnosis of Cryptosporidium spp. is dependent on microscopic technique in many countries, which has a low sensitivity and specificity leading to false positive results. However, for a step forward to successful epidemiological studies, advanced techniques (Serological and DNA-based) provide us the better ways of diagnosis with more sensitivity and specificity. Furthermore, no antiparasitic drug has found to be effective againstCryptosporidium spp. except Nitazoxanide which is FDA-approved and effective only when administered along with antiretroviral therapy. In this regard, present review summarizes the various epidemiological studies conducted around the globe along with modern diagnostic tools and the suitable treatment available now a days. This systemized review will help the scientists to better understand all the aspects of cryptosporidiosis at one platform which may help in designing surveillance studies through selection of sensitive diagnostic techniques. The new drugs mentioned in this review may also help to better control this parasite in humans, especially immunocompromised individuals