Exploring the content of epilepsy fellowship program websites: an analysis of information available to applicants.

BACKGROUND: Program websites are essential resources in the process of residency and fellowship application. We evaluated the information furnished on these resources by Epilepsy fellowship programs. The extent of information provided was compared across geographic zones, academic affiliation, and national ranking. METHODS: A list of Epilepsy fellowship programs was derived from the Fellowship and Residency Electronic Interactive Database (FREIDA). Links to program websites were obtained directly from FREIDA or using Google's search engine. Online data was categorized to reflect program information, education, recruitment, compensation, epilepsy center-specific information, and social media presence. Data points under each category were collected to develop a standardized scoring system. The frequency of criterion present was compared across geographic zones, academic affiliation, and national ranking using parametric and non-parametric statistical tests. Significance was determined at a p-value ≤ 0.05 for all cases. The study utilized IBM SPSS version 28 and Python 3.11.3. RESULTS: We analyzed 80 Epilepsy fellowship programs. The most reported feature was the program director's name and email (100.0%). The least reported features included board pass rates (1.3%), preparatory boot camp (8.8%), and post-fellowship placements (11.3%). Programs were found to be well-represented on X (88.8%), Facebook (81.3%), and Instagram (71.3%). Most (85.0%) of the programs were searchable through Google. The scores for program information, education, recruitment, compensation, epilepsy center-specific information, and social media visibility did not significantly vary based on location, academic affiliation, or rank status. CONCLUSIONS: Our results demonstrate that despite an online presence, there is much room for improvement in the content available to the applicant. To improve the Match process and attract a roster of well-informed fellows, Epilepsy fellowship programs should furnish program websites with up-to-date information relevant to program information, education, recruitment, compensation, and epilepsy center-specific information.

Feature-Based Fusion Using CNN for Lung and Heart Sound Classification.

Lung or heart sound classification is challenging due to the complex nature of audio data, its dynamic properties of time, and frequency domains. It is also very difficult to detect lung or heart conditions with small amounts of data or unbalanced and high noise in data. Furthermore, the quality of data is a considerable pitfall for improving the performance of deep learning. In this paper, we propose a novel feature-based fusion network called FDC-FS for classifying heart and lung sounds. The FDC-FS framework aims to effectively transfer learning from three different deep neural network models built from audio datasets. The innovation of the proposed transfer learning relies on the transformation from audio data to image vectors and from three specific models to one fused model that would be more suitable for deep learning. We used two publicly available datasets for this study, i.e., lung sound data from ICHBI 2017 challenge and heart challenge data. We applied data augmentation techniques, such as noise distortion, pitch shift, and time stretching, dealing with some data issues in these datasets. Importantly, we extracted three unique features from the audio samples, i.e., Spectrogram, MFCC, and Chromagram. Finally, we built a fusion of three optimal convolutional neural network models by feeding the image feature vectors transformed from audio features. We confirmed the superiority of the proposed fusion model compared to the state-of-the-art works. The highest accuracy we achieved with FDC-FS is 99.1% with Spectrogram-based lung sound classification while 97% for Spectrogram and Chromagram based heart sound classification.

Evaluation of Phytochemistry and Pharmacological Properties of Alnus nitida.

In the current study, the anti-inflammatory and analgesic potential of Alnus nitida (leaves and fruits) was evaluated in the Sprague-Dawley rat. Traditionally, A. nitida was used for the treatment of inflammatory ailments. However, A. nitida leaves and fruits have not been yet reported regarding any potential medicinal effects. Leaves/fruits of A. nitida were extracted with methanol and fractionated to attain n-hexane, chloroform, ethyl acetate and aqueous fractions. These extracts were then evaluated for in vivo analgesic and anti-inflammatory potential. For in vivo anti-inflammatory activity, carrageenan-induced paw edema assay, Freunds' complete adjuvant-induced edema, xylene-induced ear edema and histamine-induced paw edema models were used in rats, which showed significant (p < 0.01) reduction (70−80%) in edema in comparison of inflammatory controls. On other hand, for the analgesic assessment, hot plate assay and acetic acid-induced writhing tests were used, which showed a significant (p < 0.01) rise in latency time (40−60%) as compared with pain-induced controls. These results were comparable with standard drugs in a concentration-dependent manner and no mortality or toxicity was observed during all experiments. Then, for the identification of chemical constituents gas chromatography−mass spectrometry (GC-MS) analysis was performed, which indicated the presence of neophytadiene, 3,7,11,15-Tetramethyl-2-hexadecen-1-ol, phytol and vitamin E, justifying the use of A. nitida to treat inflammatory disorders.

Factors affecting prognosis of status epilepticus among patients presenting to a tertiary care hospital.

OBJECTIVES: This study aimed to evaluate the etiology, outcomes and prognostic factors associated with status epilepticus (SE) admissions in Neurology Department of a tertiary care hospital. METHODS: A retrospective review was performed on all SE admissions at Dr. Ruth K.M. Pfau Civil Hospital Karachi over a five-year period from July 2015 to June 2020. Demographic, clinical, and etiological factors were investigated for prognostic value. Statistical tests were applied to determine significant prognostic factors. A five percent significance level was used. RESULTS: A total of 176 patients were included in the study. Mortality was reported in 22 cases (12.5%) and morbidity at six months was observed in 44 cases (25.0%). Male gender, previous history of SE, prolonged seizure duration, and late presentation to hospital were significantly associated with mortality (p<0.05). De novo cases of SE tended to be older (p=0.048) and were associated with morbidity at follow-up (p=0.000). The most common causes of epilepsy in our patients with SE were CNS infections (n=54) and Idiopathic epilepsy (n=34). Non-compliance to medicines/under-dosing was the most common provocative factor (n=68). Acute symptomatic causes of SE were more likely to be associated with greater morbidity (p=0.000). Refractory and super-refractory SE were strongly associated with higher mortality (p=0.000). A longer duration of hospital stay was associated with higher morbidity (p=0.000). CONCLUSION: Male gender, poor control of seizures, CNS infections, prolonged seizures, delayed hospital arrival and refractory/super-refractory status epilepticus were key determinants of mortality in our setting. Previous history of status epilepticus, and acute and symptomatic etiologies were associated with higher morbidity.

Depression and its associated factors: perceived stress, social support, substance use and related sociodemographic risk factors in medical school residents in Nairobi, Kenya.

BACKGROUND: Little data exists regarding depression and its associated factors in medical residents and doctors in Sub-Saharan Africa. Residents are at high risk of developing depression owing to the stressful nature of their medical practice and academic training. Depression in medical residents leads to decreased clinical efficiency, and poor academic performance; it can also lead to substance abuse and suicide. Our primary aim was to measure depression prevalence among medical residents in Kenya's largest national teaching and referral hospital. Secondary aims were to describe how depression was associated with perceived stress, perceived social support, substance use, and educational environment. METHODS: We sampled 338 residents belonging to 8 different specialties using self administered questionnaires in this cross-sectional survey between October 2019 and February 2020. Questionnaires included: sociodemographics, the Centres for Epidemiology Depression Scale - Revised, Perceived Stress Scale, Multidimensional Scale of Perceived Social Support, Alcohol, Smoking and Substance Involvement Screening Test, and Postgraduate Hospital Educational Environment Measure. Bivariate and multivariate linear regression were used to assess for risk factors for depression. RESULTS: Mean participant age was 31.8 years and 53.4% were males. Most residents (70.4%) reported no to mild depressive symptoms, 12.7% had moderate, and 16.9% had severe depressive symptoms. Most residents had high social support (71.8%) and moderate stress (61.6%). The educational environment was rated as more positive than negative by 46.3% of residents. Bivariate analyses revealed significant correlations between depressive symptoms, perceived stress, substance use, perceived social support, and educational environment. Multivariate analysis showed that depression was strongly associated with: fewer hours of sleep (ß = - 0.683, p = 0.002), high perceived stress (ß = 0.709, p < 0.001) and low perceived social support (ß = - 2.19, p < 0.001). CONCLUSIONS: Only 30% of medical residents in our study had moderate and severe depressive symptoms. Most residents in our study reported high levels of social support, and moderate levels of stress. Though their overall appraisal of medical residency experience was positive, mental health support and self-care skills in the training of medical professionals needs prioritization.

Design of a Machine Learning-Based Intelligent Middleware Platform for a Heterogeneous Private Edge Cloud System.

Recent advances in mobile technologies have facilitated the development of a new class of smart city and fifth-generation (5G) network applications. These applications have diverse requirements, such as low latencies, high data rates, significant amounts of computing and storage resources, and access to sensors and actuators. A heterogeneous private edge cloud system was proposed to address the requirements of these applications. The proposed heterogeneous private edge cloud system is characterized by a complex and dynamic multilayer network and computing infrastructure. Efficient management and utilization of this infrastructure may increase data rates and reduce data latency, data privacy risks, and traffic to the core Internet network. A novel intelligent middleware platform is proposed in the current study to manage and utilize heterogeneous private edge cloud infrastructure efficiently. The proposed platform aims to provide computing, data collection, and data storage services to support emerging resource-intensive and non-resource-intensive smart city and 5G network applications. It aims to leverage regression analysis and reinforcement learning methods to solve the problem of efficiently allocating heterogeneous resources to application tasks. This platform adopts parallel transmission techniques, dynamic interface allocation techniques, and machine learning-based algorithms in a dynamic multilayer network infrastructure to improve network and application performance. Moreover, it uses container and device virtualization technologies to address problems related to heterogeneous hardware and execution environments.

Event-Driven Deep Learning for Edge Intelligence (EDL-EI).

Edge intelligence (EI) has received a lot of interest because it can reduce latency, increase efficiency, and preserve privacy. More significantly, as the Internet of Things (IoT) has proliferated, billions of portable and embedded devices have been interconnected, producing zillions of gigabytes on edge networks. Thus, there is an immediate need to push AI (artificial intelligence) breakthroughs within edge networks to achieve the full promise of edge data analytics. EI solutions have supported digital technology workloads and applications from the infrastructure level to edge networks; however, there are still many challenges with the heterogeneity of computational capabilities and the spread of information sources. We propose a novel event-driven deep-learning framework, called EDL-EI (event-driven deep learning for edge intelligence), via the design of a novel event model by defining events using correlation analysis with multiple sensors in real-world settings and incorporating multi-sensor fusion techniques, a transformation method for sensor streams into images, and lightweight 2-dimensional convolutional neural network (CNN) models. To demonstrate the feasibility of the EDL-EI framework, we presented an IoT-based prototype system that we developed with multiple sensors and edge devices. To verify the proposed framework, we have a case study of air-quality scenarios based on the benchmark data provided by the USA Environmental Protection Agency for the most polluted cities in South Korea and China. We have obtained outstanding predictive accuracy (97.65% and 97.19%) from two deep-learning models on the cities' air-quality patterns. Furthermore, the air-quality changes from 2019 to 2020 have been analyzed to check the effects of the COVID-19 pandemic lockdown.

Hypertrophic olivary degeneration following cerebral trauma managed with rehabilitation - A case report.

Hypertrophic olivary degeneration is a kind of trans-synaptic degeneration, caused by the interruption of dentato rubro olivary pathway. Magnetic resonance imaging (MRI) has been the best modality to show the signals of olivary nucleus hypertrophy. It appears on T2-weighted magnetic resonance imaging as hyper-intensities. Here we present a unique case of a 27-year-old male with traumatic brain injury causing multiple intracranial haemorrhages and functional impairment, which was revealed on computerised tomography. Tracheotomy and thoracic drainage were performed immediately. Anti-infection therapy, brain protection, and comprehensive arousal therapy were part of the intervention along with a comprehensive rehabilitation programme including occupational therapy, balance training, coordination, bed mobility training, and strengthening exercises. A holistic diagnostic approach can reduce the chances of misdiagnosing post-traumatic Hypertrophic Olivary Degeneration cases. We concluded that a comprehensive physical rehabilitation programme and medical treatment works best to heal the lesion and its resulting traumatic symptoms in cases of Hypertrophic Olivary Degeneration cases.

Impact of musculoskeletal disorders on quality of life of patients visiting tertiary care hospital.

OBJECTIVE: To determine the impact of musculoskeletal disorders on patients' quality of life. METHODS: The cross-sectional study was conducted at the Khyber Teaching Hospital, Peshawar, Pakistan, from September 2018 to March 2019, and comprised patients of either gender having a variety of musculoskeletal disorders. Data was collected using a validated EuroQol-5-Dimension-3-Level scale. Data was analysed using SPSS 20. RESULTS: Of the 377 participants, 204(54.1%) were males, and 173(45.9%) were females. The overall mean age was 35.9±12.5 years. Muscular weakness was the most commonly encountered problem 153(40.6%), followed by muscle stiffness 49(13.0%) and adhesive capsulitis 39(10.3%). Patients with musculoskeletal disorders had moderately good 'health state today' score of 56.03±20.175 on VAS. CONCLUSION: Musculoskeletal disorders were found to have a negative impact on quality of life and health status of the patients.

To determine the frequency of stroke and common factors leading to it after coronary artery bypass grafting.

OBJECTIVE: To determine the frequency of stroke and common factors leading to it after coronary artery bypass grafting. METHODS: This study was conducted at Cardiothoracic Surgery Department, Rehman Medical Institute, Peshawar. Study design was descriptive cross sectional study and the duration of the study was six months. The total sample size was 183 cases using 8.3% frequency of stroke after coronary artery bypass grafting, 95% confidence interval, 4% margin of error, using WHO sample size calculator. RESULTS: In this study mean age was 45 years with SD ± 1.26. Seventy five percent patients were male while 46(25%) females. Six patients (3%) patients had stroke while 177(97%) patients did not have any stroke. Among the six patients who were analyzed, all of them had Diabetes Mellitus and 50% patients had recent AMI, while only one patient had prior history of Atrial Fibrillation. CONCLUSIONS: Diabetes Mellitus is an independent risk factor for stroke after CABG surgery. whereas, recent MI is also associated with increased incidence of stroke in post CABG patients.

Chemically Diverse and Biologically Active Secondary Metabolites from Marine Phylum chlorophyta.

For a long time, algal chemistry from terrestrial to marine or freshwater bodies, especially chlorophytes, has fascinated numerous investigators to develop new drugs in the nutraceutical and pharmaceutical industries. As such, chlorophytes comprise a diverse structural class of secondary metabolites, having functional groups that are specific to a particular source. All bioactive compounds of chlorophyte are of great interest due to their supplemental/nutritional/pharmacological activities. In this review, a detailed description of the chemical diversity of compounds encompassing alkaloids, terpenes, steroids, fatty acids and glycerides, their subclasses and their structures are discussed. These promising natural products have efficiency in developing new drugs necessary in the treatment of various deadly pathologies (cancer, HIV, SARS-CoV-2, several inflammations, etc.). Marine chlorophyte, therefore, is portrayed as a pivotal treasure in the case of drugs having marine provenience. It is a domain of research expected to probe novel pharmaceutically or nutraceutically important secondary metabolites resulting from marine Chlorophyta. In this regard, our review aims to compile the isolated secondary metabolites having diverse chemical structures from chlorophytes (like Caulerpa ssp., Ulva ssp., Tydemania ssp., Penicillus ssp., Codium ssp., Capsosiphon ssp., Avrainvillea ssp.), their biological properties, applications and possible mode of action.

Characteristics, morbidity and mortality factors associated with Intra-Aortic Balloon Pump in Coronary Artery Bypass Graft Surgery patients.

OBJECTIVE: The aim of our study is to analyze the characteristics, morbidity and mortality of patients requiring an Intra-Aortic Balloon Pump (IABP) in Coronary Artery Bypass Grafting (CABG). METHODS: An analysis was done on the prospectively collected data of 1216 patients who had CABG in our center between July, 2017 and May, 2019 at our hospital. We categorized patients in to an IABP and non-IABP group on the basis of IABP use. We then compared the pre-operative, per-operative and post-operative characteristics of the two groups. We further stratified the patients according to pre-op ejection fraction (EF). RESULTS: Out of 1216 patients, 135(11.10%) patients required an IABP. 70(51.9%) patients of IABP group and 699(64.7%) patients of non-IABP group had hypertension (p-value 0.0036). 23.0% had previous myocardial infarction (MI) in the IABP group and 13.8% had prior myocardial infarction (MI) in non-IABP group (p-value 0.0463). Among the patients requiring an IABP, 21(15.5%) of patients had normal EF (>50%) (P-value<0.0001), 72 (53.3%) had EF 35-50%, and 41(30.3%) patients had EF<35% (p-value <0.0001). Mortality of IABP group (19.3%) was greater than non-IABP group (2.4%) (P-value 0.00001). CONCLUSIONS: Use of IABP increased as the EF decreased. Rate of post-operative stroke, prolonged ICU stay, prolonged ventilation, re-opening due to bleeding and mortality was seen to be significantly higher in the IABP group.

Health and dignity of Palestine refugees at stake: a need for international response to sustain crucial life services at UNRWA.

The UN Sustainable Development Goals affirm equality and dignity as essential to the enjoyment of basic human rights, including the right to the highest attainable standard of physical and mental health, which promotes global solidarity among all people, including refugees. The UN Relief and Works Agency for Palestine Refugees in the Near East (UNRWA) has provided support to Palestine refugees in Jordan, Lebanon, Syria, the Gaza Strip, and the West Bank since the 1950s. Today, however, conflict and violence, occupation, high levels of poverty, and other social determinants of health jeopardize the wellbeing of Palestine refugees. Health concerns include non-communicable diseases, mental health conditions, and access to hospital care. Additionally, UNRWA is continuing to face a severe funding crisis. Using a historical and health policy perspective, this Health Policy examines UNRWA strategies that facilitate continuous provision of health-care services for Palestine refugees. Given the increasingly volatile environment faced by this population, a multifaceted international response is needed to enable UNRWA to deliver sustainable services to Palestine refugees and avert further loss of life, dignity, and hope, pending a just and lasting solution to their plight in accordance with applicable international law and UN General Assembly resolutions.

A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification.

In order to monitor and manage vessels in channels effectively, identification and tracking are very necessary. This work developed a maritime unmanned aerial vehicle (Mar-UAV) system equipped with a high-resolution camera and an Automatic Identification System (AIS). A multi-feature and multi-level matching algorithm using the spatiotemporal characteristics of aerial images and AIS information was proposed to detect and identify field vessels. Specifically, multi-feature information, including position, scale, heading, speed, etc., are used to match between real-time image and AIS message. Additionally, the matching algorithm is divided into two levels, point matching and trajectory matching, for the accurate identification of surface vessels. Through such a matching algorithm, the Mar-UAV system is able to automatically identify the vessel's vision, which improves the autonomy of the UAV in maritime tasks. The multi-feature and multi-level matching algorithm has been employed for the developed Mar-UAV system, and some field experiments have been implemented in the Yangzi River. The results indicated that the proposed matching algorithm and the Mar-UAV system are very significant for achieving autonomous maritime supervision.

Antimicrobial potential of aqueous extract of Camellia sinensis against representative microbes.

Camellia sinensis is being used for decades for its therapeutic efficacies against physiological problems and microbial infections. This study was undertaken to investigate the antibacterial and antifungal potential of aqueous extract of Camellia sinensis. Antibacterial activity was determined by disc and well diffusion assay. MIC and MBC were calculated by broth dilution method. Miles and Misra technique was used to find out colony forming unit per/ml. All the test organisms revealed a diverse range of vulnerability against aqueous extract. Among Gram positive, MRSA showed to be the most sensitive with least MIC and MBC while among Gram-negative Pseudomonas aeruginosa exhibited the highest sensitivity. In Miles and Misra, a progressive decline in log of CFU/ml was observed. In time-kill assay, a decline was noted in the viable count of S.aureus after exposure to 18% aqueous extract of Camellia sinensis. In the present study aqueous extract of Camellia sinensis found to be effective against Gram positive, Gram negative and fungi. The most important finding of this study is its aqueous extract inhibitory effect against drug-resistant microorganisms e.g. MRSA and P. aeruginosa and Candida albicans.

Nanomedicines for developing cancer nanotherapeutics: from benchtop to bedside and beyond.

Cancer is a devastating disease and remains a significant cause of mortality and morbidity in both developed and developing countries. Although there are large number of drugs that can be used for the treatment of cancer, the problem is selective and specific killing of cancerous cells without harming the normal cells. There are some biological barriers to potential drug delivery in cancer cells like hepatic, renal, abnormal vasculature, dense extracellular matrix, and high interstitial fluid pressure. The physicochemical characteristics of nanoparticles (NPs) such as size, shape, and surface charge may also have significant effects on tumor penetration. NPs coated with drug can be used to overcome these biological barriers to enhance targeted delivery. This literature survey encompasses the biological barriers to potential drug delivery in cancer cells, elaborate on designing strategies to enhance NPs penetration and distribution inside the tumor interstitium. Scientists are now doing great efforts to design next-generation of nanomedicines (NMs) that need to be better targeted with high specificity and efficacy to kill cancer cells. These challenges need to be overcome through collaborations among academia, pharmaceutical industries, and regulatory agencies to eradicate this global menace. Furthermore, this review article has critically discussed the recent developments, controversies, challenges, emerging concepts, and future perspectives in cancer NMs.

HPLC-DAD finger printing, antioxidant, cholinesterase, and α-glucosidase inhibitory potentials of a novel plant Olax nana.

BACKGROUND: The medicinal importance of a novel plant Olax nana Wall. ex Benth. (family: Olacaceae) was revealed for the first time via HPLC-DAD finger printing, qualitative phytochemical analysis, antioxidant, cholinesterase, and α-glucosidase inhibitory assays. METHODS: The crude methanolic extract of O. nana (ON-Cr) was subjected to qualitative phytochemical analysis and HPLC-DAD finger printing. The antioxidant potential of ON-Cr was assessed via 1,1-diphenyl,2-picrylhydrazyl (DPPH), 2,2-azinobis[3-ethylbenzthiazoline]-6-sulfonic acid (ABTS) and hydrogen peroxide (H2O2) free radical scavenging assays. Furthermore, acetylcholinesterase (AChE) & butyrylcholinesterase (BChE) inhibitory activities were performed using Ellman's assay, while α- glucosidase inhibitory assay was carried out using a standard protocol. RESULTS: The qualitative phytochemical analysis of ON-Cr revealed the presence of secondary metabolites like alkaloids, flavonoids, tannins, sterols, saponins and terpenoids. The HPLC-DAD finger printing revealed the presence of 40 potential compounds in ON-Cr. Considerable anti-radical activities was revealed by ON-Cr in the DPPH, ABTS and H2O2 free radical scavenging assays with IC50 values of 71.46, 72.55 and 92.33 µg/mL, respectively. Furthermore, ON-Cr showed potent AChE and BChE inhibitory potentials as indicated by their IC50 values of 33.2 and 55.36 µg/mL, respectively. In the α-glucosidase inhibition assay, ON-Cr exhibited moderate inhibitory propensity with an IC50 value of 639.89 µg/mL. CONCLUSIONS: This study investigated Olax nana for the first time for detailed qualitative phytochemical tests, HPLC-DAD finger printing analysis, antioxidant, anticholinesterase and α-glucosidase inhibition assays. The antioxidant and cholinesterase inhibitory results were considerable and can provide scientific basis for further studies on the neuroprotective and anti-Alzheimer's potentials of this plant. ON-Cr may further be subjected to fractionation and polarity guided fractionation to narrow down the search for isolation of bioactive compounds.

Disaster Management System Aided by Named Data Network of Things: Architecture, Design, and Analysis.

Disasters are the uncertain calamities which within no time can change the situation quite drastically. They not only affect the system's infrastructure but can also put an adverse effect on human life. A large chunk of the IP-based Internet of Things (IoT) schemes tackle disasters such as fire, earthquake, and flood. Moreover, recently proposed Named Data Networking (NDN) architecture exhibited promising results for IoT as compare to IP-based approaches. Therefore to tackle disaster management system (DMS), it is needed to explore it through NDN architecture and this is the main motivation behind this work. In this research, a NDN based IoT-DMS (fire disaster) architecture is proposed, named as NDN-DISCA. In NDN-DISCA, NDN producer pushes emergency content towards nearby consumers. To provide push support, Beacon Alert Message (BAM) is created using fixed sequence number. NDN-DISCA is simulated in ndnSIM considering the disaster scenario of IoT-based smart campus (SC). From results, it is found that NDN-DISCA exhibits minimal delay and improved throughput when compared to the legacy NDN and existing PUSH schemes.

Structural Diversity, Biological Properties and Applications of Natural Products from Cyanobacteria. A Review.

Nowadays, various drugs on the market are becoming more and more resistant to numerous diseases, thus declining their efficacy for treatment purposes in human beings. Antibiotic resistance is one among the top listed threat around the world which eventually urged the discovery of new potent drugs followed by an increase in the number of deaths caused by cancer due to chemotherapy resistance as well. Accordingly, marine cyanobacteria, being the oldest prokaryotic microorganisms belonging to a monophyletic group, have proven themselves as being able to generate pharmaceutically important natural products. They have long been known to produce distinct and structurally complex secondary metabolites including peptides, polyketides, alkaloids, lipids, and terpenes with potent biological properties and applications. As such, this review will focus on recently published novel compounds isolated from marine cyanobacteria along with their potential bioactivities such as antibacterial, antifungal, anticancer, anti-tuberculosis, immunosuppressive and anti-inflammatory capacities. Moreover, various structural classes, as well as their technological uses will also be discussed.

Assessment of the quality of life of spinal cord injury patients in Peshawar.

OBJECTIVE: To assess the quality of life of spinal cord injury patients. METHODS: This cross-sectional study was conducted at Paraplegic Centre Hayatabad, Peshawar, Pakistan, from November 2015 to January 2016, and comprised spinal cord injury patients. A 26-item World Health Organisation quality of life questionnaire was used. Some of the patients were recruited from the paraplegic centre while others participated by filling an online questionnaire. SPSS 20 was used for data analysis. RESULTS: Of the 54 participants, 35(64.8%) were male and 19(35.2%) were female. Besides, 50(92.6%) participants were paraplegic while 4(7.4%) were tetraplegic. The overall mean score for the physical health domain was 54.79±18.39, psychological health domain 52.33±19.37, social relationship 58.79±20.69 and environmental domain 54.11±17.25. CONCLUSIONS: Patients with spinal cord injuries had moderate level of quality of life.