Predicting clinical outcomes of patients with serum thyroglobulin antibodies after thyroidectomy for differentiated thyroid cancer: a retrospective study from a UK regional center.

BACKGROUND: Twenty-twenty-five percent of patients with differentiated thyroid cancer (DTC) can have elevated thyroglobulin antibodies (TgAb). The study aimed to find any prognostic significance of elevated TgAb during follow-up. METHODS: Ten-year retrospective study from a tertiary center including 79 patients with raised TgAb after total/staged thyroidectomy for DTC. We identified patients with stable (7.6%), increasing (15%) and decreasing levels of TgAb (77.2%); groups 1, 2 and 3 respectively. During follow-up we analyzed TgAb in subcategories by TgAb trend (>50% rise, <50% rise, >50% decline, <50% decline, positive to negative/normalization, negative to positive and stable levels), gender, age, surgery, autoimmune disease, histology, RAI uptake, distant metastases, and recurrence. RESULTS: The incidence of raised TgAb levels was 33.2%, with female predominance. No connection was identified regarding other parameters. 11.4% had distant metastases. The highest mean maximum levels of TgAb was in group 2 (1918.75 IU/mL) and the lowest in group 3 (412.70 IU/mL). The recurrence rate changed significantly between the 3 groups: 50% in group 1, 75% in group 2, and 25% in group 3 (P=0.002). Recurrence rates decreased to 15% in the subcategory where TgAb became negative/normal from positive (P=0.0001). In patients with a negative to positive TgAb level trend or >50% rise, recurrence rates were 100% (P=0.041) and 70% (P=0.012) respectively. CONCLUSIONS: Patients with increasing TgAb levels during follow-up have a higher rate of recurrence, distinctly for those with negative to positive trend and >50% rise in TgAb. These patients need closer follow-up, and TgAb may be used as a dynamic follow-up marker.

AMP0: Species-Specific Prediction of Anti-microbial Peptides Using Zero and Few Shot Learning.

Evolution of drug-resistant microbial species is one of the major challenges to global health. Development of new antimicrobial treatments such as antimicrobial peptides needs to be accelerated to combat this threat. However, the discovery of novel antimicrobial peptides is hampered by low-throughput biochemical assays. Computational techniques can be used for rapid screening of promising antimicrobial peptide candidates prior to testing in the wet lab. The vast majority of existing antimicrobial peptide predictors are non-targeted in nature, i.e., they can predict whether a given peptide sequence is antimicrobial, but they are unable to predict whether the sequence can target a particular microbial species. In this work, we have used zero and few shot machine learning to develop a targeted antimicrobial peptide activity predictor called AMP0. The proposed predictor takes the sequence of a peptide and any N/C-termini modifications together with the genomic sequence of a microbial species to generate targeted predictions. Cross-validation results show that the proposed scheme is particularly effective for targeted antimicrobial prediction in comparison to existing approaches and can be used for screening potential antimicrobial peptides in a targeted manner with only a small number of training examples for novel species. AMP0 webserver is available at http://ampzero.pythonanywhere.com.

HemoNet: Predicting hemolytic activity of peptides with integrated feature learning.

Quantifying the hemolytic activity of peptides is a crucial step in the discovery of novel therapeutic peptides. Computational methods are attractive in this domain due to their ability to guide wet-lab experimental discovery or screening of peptides based on their hemolytic activity. However, existing methods are unable to accurately model various important aspects of this predictive problem such as the role of N/C-terminal modifications, D- and L- amino acids, etc. In this work, we have developed a novel neural network-based approach called HemoNet for predicting the hemolytic activity of peptides. The proposed method captures the contextual importance of different amino acids in a given peptide sequence using a specialized feature embedding in conjunction with SMILES-based fingerprint representation of N/C-terminal modifications. We have analyzed the predictive performance of the proposed method using stratified cross-validation in comparison with previous methods, non-redundant cross-validation as well as validation on external peptides and clinical antimicrobial peptides. Our analysis shows the proposed approach achieves significantly better predictive performance (AUC-ROC of 88%) in comparison to previous approaches (HemoPI and HemoPred with AUC-ROC of 73%). HemoNet can be a useful tool in the search for novel therapeutic peptides. The python implementation of the proposed method is available at the URL: https://github.com/adibayaseen/HemoNet.

AMAP: Hierarchical multi-label prediction of biologically active and antimicrobial peptides.

Due to increase in antibiotic resistance in recent years, development of efficient and accurate techniques for discovery and design of biologically active peptides such as antimicrobial peptides (AMPs) has become essential. The screening of natural and synthetic AMPs in the wet lab is a challenge due to time and cost involved in such experiments. Bioinformatics methods can be used to speed up discovery and design of antimicrobial peptides by limiting the wet-lab search to promising peptide sequences. However, most such tools are typically limited to the prediction of whether a peptide exhibits antimicrobial activity or not and they do not identify the exact type of the biological activities of these peptides. In this work, we have designed a machine learning based model called AMAP for predicting biological activity of peptides with a specialized focus on antimicrobial activity prediction. AMAP used multi-label classification to predict 14 different types of biological functions of a given peptide sequence with improved accuracy in comparison to existing state of the art techniques. We have performed stringent performance analyses of the proposed method. In addition to cross-validation and performance comparison with existing AMP predictors, AMAP has also been benchmarked on recently published experimentally verified peptides that were not a part of our training set. We have also analyzed features used in this work and our analysis shows that the proposed predictor can generalize well in predicting biological activity of novel peptide sequences. A webserver of the proposed method is available at the URL: http://faculty.pieas.edu.pk/fayyaz/software.html#AMAP.

Training host-pathogen protein-protein interaction predictors.

Detection of protein-protein interactions (PPIs) plays a vital role in molecular biology. Particularly, pathogenic infections are caused by interactions of host and pathogen proteins. It is important to identify host-pathogen interactions (HPIs) to discover new drugs to counter infectious diseases. Conventional wet lab PPI detection techniques have limitations in terms of cost and large-scale application. Hence, computational approaches are developed to predict PPIs. This study aims to develop machine learning models to predict inter-species PPIs with a special interest in HPIs. Specifically, we focus on seeking answers to three questions that arise while developing an HPI predictor: (1) How should negative training examples be selected? (2) Does assigning sample weights to individual negative examples based on their similarity to positive examples improve generalization performance? and, (3) What should be the size of negative samples as compared to the positive samples during training and evaluation? We compare two available methods for negative sampling: random versus DeNovo sampling and our experiments show that DeNovo sampling offers better accuracy. However, our experiments also show that generalization performance can be improved further by using a soft DeNovo approach that assigns sample weights to negative examples inversely proportional to their similarity to known positive examples during training. Based on our findings, we have also developed an HPI predictor called HOPITOR (Host-Pathogen Interaction Predictor) that can predict interactions between human and viral proteins. The HOPITOR web server can be accessed at the URL: http://faculty.pieas.edu.pk/fayyaz/software.html#HoPItor .

Acquired hemophilia A as a cause of acute upper gastrointestinal hemorrhage.

A 71-year-old man presented to the emergency department with his first episode of hematemesis. He was anemic and coagulopathic on admission, and became hemodynamically unstable requiring surgical intervention to control the bleeding. Prior to surgery, he required 100% plasma exchange with human plasma derived prothrombin complex concentrate (Octaplex) as the exchange fluid. At induction of anesthesia, he received tranexamic acid, prothrombin complex concentrate, and platelets. At the time of knife to skin, he was given coagulation factor VIIa intravenously as a bolus. This treatment was on the recommendation of the hematology team who suspected a diagnosis of acquired hemophilia on the basis of his history and coagulation screen. His bleeding was controlled and a diagnosis of acquired hemophilia A was confirmed in the postoperative period. This was managed with immunosuppressive therapy, and at the 2 year follow-up he remains well and is off all treatment.

Surgeon and haematologist: a review of comprehensive care for patients with inherited bleeding disorders in Northern Ireland.

BACKGROUND: Management of patients with inherited bleeding disorders has improved since the introduction of Comprehensive Care Centres (CCC) in the United Kingdom (UK). In the event such patients need surgery, the aim of the multidisciplinary team is to facilitate outcomes as good as what would be expected in a non-bleeding disorder patient. A review of such comprehensive care was carried out in patients with inherited bleeding disorders when they needed surgery at Northern Ireland CCC. Aims of the study were to evaluate surgical morbidity and mortality in these patients. METHODS: All patients with inherited bleeding disorders who underwent non-orthopaedic surgery between 2008 and 2012 were identified from the CCC records within the Belfast Health and Social Care Trust (BHSCT) in Northern Ireland (NI) and their case records reviewed. RESULTS: 28 patients received elective and emergency surgery during this period. There was minimum morbidity and no mortality in this cohort. CONCLUSIONS: Surgery in patients with inherited bleeding disorders has become safe with the advent of multidisciplinary CCCs. Close communication between surgeon and haematologist is key in the successful management of these complex patients.

Helping rural women in Pakistan to prevent postpartum hemorrhage: a quasi experimental study.

BACKGROUND: According to the Pakistan Demographic and Health Survey from 2006-2007, the maternal mortality ratio in rural areas is 319 per 100,000 live births. Postpartum hemorrhage is the leading cause of maternal deaths in Pakistan. The objectives of the study were to document the feasibility of distribution of misoprostol tablets by community-based providers mainly traditional birth attendants and acceptability and use of misoprostol by women who gave birth at home. METHODS: A quasi-experimental design, comprising intervention and comparison areas, was used to document the acceptability of providing misoprostol tablets to pregnant women to prevent postpartum hemorrhage in the rural community setting in Pakistan. Data were collected using structured questionnaires administered to women before and after delivery at home and their birth attendants. RESULTS: Out of 770 women who delivered at home, 678 (88%) ingested misoprostol tablets and 647 (84%) ingested the tablets after the birth of the neonate but prior to the delivery of the placenta. The remaining women took misoprostol tablets after delivery of the placenta. Side effects were experienced by 40% of women and were transitory in nature. Among women who delivered at home, 80% said that they would use misoprostol tablets in the future and 74% were willing to purchase them in the future. CONCLUSIONS: Self-administration of misoprostol in the home setting is feasible. Community-based providers, such as traditional birth attendants and community midwives with proper training and counseling, play an important role in reducing postpartum hemorrhage. Proper counseling and information exchange are helpful for introducing new practices in resource-constrained rural communities. Until such a time that skilled birth attendance is made more universally available in the rural setting, alternative strategies, such as training and using the services of traditional birth attendants to provide safe pregnancy care, must be considered.

Countdown to 2015: a case study of maternal and child health service delivery challenges in five districts of Punjab.

OBJECTIVE: To identify the challenges confronting the Pakistan province of Punjab in delivering maternal and child health services at the district level. METHODS: The qualitative assessment was done from May 15 to June 15, 2010, comprising 5 focus group discussions, 5 in-depth interviews with district managers, 49 in-depth interviews with providers, and direct observation of 19 facilities providing comprehensive emergency obstetric care in the districts of Multan, Muzaffargarh, Bahawalpur, Khanewal and Jhelum. Using skilled birth attendance coverage as an indicator, Punjab districts were stratified into three socio-economic strata, and from these the five-districts were selected. RESULTS: Distribution of basic emergency obstetric care facilities by population size was found to be inadequate in all districts. Quality of care was compromised by lack of staff and equipment. No anaesthetist was available in majority of the district hospitals and tehsil facilities. Half of the teshil headquarter hospitals were devoid of staff nurses. Vital medicines used in obstetric care were not available. Partograph was not being used in any of the tehsil-level facilities. Chlorine solution was not present in any of the facilities. Governance issues included multiplicity of command channels, delays in receipt of medicines and political interference. CONCLUSION: If the province has to achieve the related Millennium Development Goals (MDGs), related to maternal and child health, the existing facilities are not adequate. To achieve progress, proven and innovative approaches will have to be put in place that may influence the continuum of care from the household to the health facility.

Primary osteosarcoma of breast.

Primary osteosarcoma of breast is rare. The authors present a case of a 51-year-old female who was admitted with a large necrotising tumour involving the right breast. CT scan confirmed chest wall invasion along with a solitary lung metastasis. She underwent a primary mastectomy with chest wall reconstruction. Unfortunately 3 months later she developed local recurrence.

The 'pulsatile' sebaceous cyst: beware of a superficial temporal artery aneurysm.

True aneurysms of the superficial temporal artery (STA) are quite uncommon. Only 14 such cases are described in the literature. Ultrasound scan (USS) is an appropriate and easily accessible non-invasive diagnostic modality, as it can show both the anatomical and flow characteristics of the aneurysmal vessel. Other conditions to be included in the differential diagnosis are haematoma, angiofibroma, eroding middle meningeal artery aneurysm, abscess or a parotid mass. Operative intervention is indicated to relieve symptoms as in this case, and to prevent rupture.