COVID-19 detection from chest X-ray images using CLAHE-YCrCb, LBP, and machine learning algorithms.

BACKGROUND: COVID-19 is a disease that caused a contagious respiratory ailment that killed and infected hundreds of millions. It is necessary to develop a computer-based tool that is fast, precise, and inexpensive to detect COVID-19 efficiently. Recent studies revealed that machine learning and deep learning models accurately detect COVID-19 using chest X-ray (CXR) images. However, they exhibit notable limitations, such as a large amount of data to train, larger feature vector sizes, enormous trainable parameters, expensive computational resources (GPUs), and longer run-time. RESULTS: In this study, we proposed a new approach to address some of the above-mentioned limitations. The proposed model involves the following steps: First, we use contrast limited adaptive histogram equalization (CLAHE) to enhance the contrast of CXR images. The resulting images are converted from CLAHE to YCrCb color space. We estimate reflectance from chrominance using the Illumination-Reflectance model. Finally, we use a normalized local binary patterns histogram generated from reflectance (Cr) and YCb as the classification feature vector. Decision tree, Naive Bayes, support vector machine, K-nearest neighbor, and logistic regression were used as the classification algorithms. The performance evaluation on the test set indicates that the proposed approach is superior, with accuracy rates of 99.01%, 100%, and 98.46% across three different datasets, respectively. Naive Bayes, a probabilistic machine learning algorithm, emerged as the most resilient. CONCLUSION: Our proposed method uses fewer handcrafted features, affordable computational resources, and less runtime than existing state-of-the-art approaches. Emerging nations where radiologists are in short supply can adopt this prototype. We made both coding materials and datasets accessible to the general public for further improvement. Check the manuscript's availability of the data and materials under the declaration section for access.

Lipoprotein(a) and calcific aortic valve disease: current evidence and future directions.

PURPOSE OF REVIEW: Calcific aortic valve disease (CAVD), the most common cause of aortic stenosis (AS), is characterized by slowly progressive fibrocalcific remodelling of the valve cusps. Once symptomatic, severe AS is associated with poor survival unless surgical or transcatheter valve replacement is performed. Unfortunately, no pharmacological interventions have been demonstrated to alter the natural history of CAVD. Lipoprotein(a) [Lp(a)], a low-density lipoprotein-like particle, has been implicated in the pathophysiology of CAVD. RECENT FINDINGS: The mechanisms by which Lp(a) results in CAVD are not well understood. However, the oxidized phospholipids carried by Lp(a) are considered a crucial mediator of the disease process. An increasing number of studies demonstrate a causal association between plasma Lp(a) levels and frequency of AS and need for aortic valve replacement, which is independent of inflammation, as measured by plasma C-reactive protein levels. However, not all studies show an association between Lp(a) and increased progression of calcification in individuals with established CAVD. SUMMARY: Epidemiologic, genetic, and Mendelian randomization studies have collectively suggested that Lp(a) is a causal risk factor for CAVD. Whether Lp(a)-lowering can prevent initiation or slow progression of CAVD remains to be demonstrated.

Annual risk of hepatitis E virus infection and seroreversion: Insights from a serological cohort in Sitakunda, Bangladesh.

Hepatitis E virus (HEV) is a major cause of acute jaundice in South Asia. Gaps in our understanding of transmission are driven by non-specific symptoms and scarcity of diagnostics, impeding rational control strategies. In this context, serological data can provide important proxy measures of infection. We enrolled a population-representative serological cohort of 2,337 individuals in Sitakunda, Bangladesh. We estimated the annual risks of HEV infection and seroreversion both using serostatus changes between paired serum samples collected 9 months apart, and by fitting catalytic models to the age-stratified cross-sectional seroprevalence. At baseline, 15% (95 CI: 14-17%) of people were seropositive, with seroprevalence highest in the relatively urban south. During the study, 27 individuals seroreverted (annual seroreversion risk: 15%, 95 CI: 10-21%), and 38 seroconverted (annual infection risk: 3%, 95CI: 2-5%). Relying on cross-sectional seroprevalence data alone, and ignoring seroreversion, underestimated the annual infection risk five-fold (0.6%, 95 CrI: 0.5-0.6%). When we accounted for the observed seroreversion in a reversible catalytic model, infection risk was more consistent with measured seroincidence. Our results quantify HEV infection risk in Sitakunda and highlight the importance of accounting for seroreversion when estimating infection incidence from cross-sectional seroprevalence data.

Co-administration of Oral Cholera Vaccine With Oral Polio Vaccine Among Bangladeshi Young Children: A Randomized Controlled Open Label Trial to Assess Interference.

BACKGROUND: Cholera remains a public health threat for low- and middle-income countries, particularly in Asia and Africa. Shanchol™, an inactivated oral cholera vaccine (OCV) is currently in use globally. OCV and oral poliovirus vaccines (OPV) could be administered concomitantly, but the immunogenicity and safety of coadministration among children aged 1-3 years is unknown. METHODS: We undertook an open-label, randomized, controlled, inequality trial in Dhaka city, Bangladesh. Healthy children aged 1-3 years were randomly assigned to 1 of 3 groups: bivalent OPV (bOPV)-alone, OCV-alone, or combined bOPV + OCV and received vaccines on the day of enrollment and 28 days later. Blood samples were collected on the day of enrollment, day 28, and day 56. Serum poliovirus neutralizing antibodies and vibriocidal antibodies against Vibrio cholerae O1 were assessed using microneutralization assays. RESULTS: A total of 579 children aged 1‒3 years were recruited, 193 children per group. More than 90% of the children completed visits at day 56. Few adverse events following immunization were recorded and were equivalent among study arms. On day 28, 60% (90% confidence interval: 53%-67%) and 54% (46%-61%) of participants with co-administration of bOPV + OCV responded to polioviruses type 1 and 3, respectively, compared to 55% (47%-62%) and 46% (38%-53%) in the bOPV-only group. Additionally, >50% of participants showed a ≥4-fold increase in vibriocidal antibody titer responses on day 28, comparable to the responses observed in OCV-only arm. CONCLUSIONS: Co-administration of bOPV and OCV is safe and effective in children aged 1-3 years and can be cost-beneficial. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov (NCT03581734).

Synthesis of Spiroisoindolinones via Ru(II)-Catalyzed Spiroannulation of N-Acyl Ketimines with Aryl Isocyanates/Isothiocyanates through Aromatic C-H Bond Activation.

Herein, we disclose the first report on Ru(II)-catalyzed amidation/thioamidation of 3-hydroxy-3-arylisoindolinones with isocyanates/isothiocyanates, respectively. The reaction furnishes spiroisoindolinones via sequential C-H functionalization of ortho C-H bond followed by intramolecular cyclization in moderate to high yields (up to 94%). Moreover, the developed strategy is highly atom-economical and site-selective and shows diverse substrate generality. Also, synthesized spiroisoindolinones undergo several chemical transformations.

Strategy to Probe the Local Atomic Structure of Luminescent Rare Earth Complexes by X-ray Absorption Near-Edge Spectroscopy Simulation Using a Machine Learning-Based PyFitIt Approach.

Rare earth(III) ß-diketonates are highly remarkable luminophores in the visible spectral region among the rare earth compounds, owing to the efficient contribution from the 4f-4f intraconfigurational transitions. To get detailed structural insight into the RE3+ sites (RE = Eu, Gd, and Sm), X-ray absorption near-edge spectroscopy (XANES) can be very potent in probing the local chemical environment around the RE3+ ion. In this work, a PyFitIt machine learning approach was employed as a new strategy to simulate the Eu, Gd, and Sm L3-edge XANES and thereby determine the local atomic structure of the luminescence RE3+ ß-diketonate complexes, [Eu(tta)3(H2O)2], [C4mim][Eu(dbm)4], [Gd(tta)3(H2O)2], and [Sm(dbm)3(phen)] (tta, 3-thenoyltrifluoroacetonate; dbm, dibenzoylmethane; phen, phenanthroline; and C4mim, 1-butyl-3-methylimidazolium bromide). Continuous Cauchy wavelet transform validated the PyFitIt calculated XANES by visualizing very efficiently the coordination geometries, composed of O and O/N backscatterers around the RE3+ (RE = Eu and Gd) and Sm3+ ions, respectively, as a pinkish-red color map in the two-dimensional images of the corresponding complexes. Extended X-ray absorption fine structure fit in Artemis also corroborated the three-dimensional structures generated by PyFitIt XANES simulation for all the compounds. Though, relatively slightly higher bond distance values for the Sm3+ complex are due to the higher atomic radius of the Sm3+ ion when compared to the Eu3+ and Gd3+ complexes. Meanwhile, higher Debye-Waller factor (σ2) values for the [C4mim][Eu(dbm)4] when compared to the [Eu(tta)3(H2O)2] indicated the structure disorder, owing to the distortion in the local geometry. It is noteworthy that the optical properties, described mainly by the Ωλ (λ = 2 and 4) 4f-4f intensity parameters, are very sensitive to the local coordination environment around the Eu3+ ion. Thus, a close agreement between the experimental and theoretically calculated Ωλ parameter values confirmed that the PyFitIt calculated square antiprismatic structures are precisely similar to the real structures of the Eu3+ complexes.

HOMLC-Hyperparameter Optimization for Multi-Label Classification of Intrusion Detection Data for Internet of Things Network.

The comparison of low-rank-based learning models for multi-label categorization of attacks for intrusion detection datasets is presented in this work. In particular, we investigate the performance of three low-rank-based machine learning (LR-SVM) and deep learning models (LR-CNN), (LR-CNN-MLP) for classifying intrusion detection data: Low Rank Representation (LRR) and Non-negative Low Rank Representation (NLR). We also look into how these models' performance is affected by hyperparameter tweaking by using Guassian Bayes Optimization. The tests has been run on merging two intrusion detection datasets that are available to the public such as BoT-IoT and UNSW- NB15 and assess the models' performance in terms of key evaluation criteria, including precision, recall, F1 score, and accuracy. Nevertheless, all three models perform noticeably better after hyperparameter modification. The selection of low-rank-based learning models and the significance of the hyperparameter tuning log for multi-label classification of intrusion detection data have been discussed in this work. A hybrid security dataset is used with low rank factorization in addition to SVM, CNN and CNN-MLP. The desired multilabel results have been obtained by considering binary and multi-class attack classification as well. Low rank CNN-MLP achieved suitable results in multilabel classification of attacks. Also, a Gaussian-based Bayesian optimization algorithm is used with CNN-MLP for hyperparametric tuning and the desired results have been achieved using c and γ for SVM and α and ß for CNN and CNN-MLP on a hybrid dataset. The results show the label UDP is shared among analysis, DoS and shellcode. The accuracy of classifying UDP among three classes is 98.54%.

EEDC: An Energy Efficient Data Communication Scheme Based on New Routing Approach in Wireless Sensor Networks for Future IoT Applications.

Wireless Sensor Networks (WSNs) and the Internet of Things (IoT) have emerged as transforming technologies, bringing the potential to revolutionize a wide range of industries such as environmental monitoring, agriculture, manufacturing, smart health, home automation, wildlife monitoring, and surveillance. Population expansion, changes in the climate, and resource constraints all offer problems to modern IoT applications. To solve these issues, the integration of Wireless Sensor Networks (WSNs) and the Internet of Things (IoT) has come forth as a game-changing solution. For example, in agricultural environment, IoT-based WSN has been utilized to monitor yield conditions and automate agriculture precision through different sensors. These sensors are used in agriculture environments to boost productivity through intelligent agricultural decisions and to collect data on crop health, soil moisture, temperature monitoring, and irrigation. However, sensors have finite and non-rechargeable batteries, and memory capabilities, which might have a negative impact on network performance. When a network is distributed over a vast area, the performance of WSN-assisted IoT suffers. As a result, building a stable and energy-efficient routing infrastructure is quite challenging in order to extend network lifetime. To address energy-related issues in scalable WSN-IoT environments for future IoT applications, this research proposes EEDC: An Energy Efficient Data Communication scheme by utilizing "Region based Hierarchical Clustering for Efficient Routing (RHCER)"-a multi-tier clustering framework for energy-aware routing decisions. The sensors deployed for IoT application data collection acquire important data and select cluster heads based on a multi-criteria decision function. Further, to ensure efficient long-distance communication along with even load distribution across all network nodes, a subdivision technique was employed in each tier of the proposed framework. The proposed routing protocol aims to provide network load balancing and convert communicating over long distances into shortened multi-hop distance communications, hence enhancing network lifetime.The performance of EEDC is compared to that of some existing energy-efficient protocols for various parameters. The simulation results show that the suggested methodology reduces energy usage by almost 31% in sensor nodes and provides almost 38% improved packet drop ratio.

Vision Transformers in Image Restoration: A Survey.

The Vision Transformer (ViT) architecture has been remarkably successful in image restoration. For a while, Convolutional Neural Networks (CNN) predominated in most computer vision tasks. Now, both CNN and ViT are efficient approaches that demonstrate powerful capabilities to restore a better version of an image given in a low-quality format. In this study, the efficiency of ViT in image restoration is studied extensively. The ViT architectures are classified for every task of image restoration. Seven image restoration tasks are considered: Image Super-Resolution, Image Denoising, General Image Enhancement, JPEG Compression Artifact Reduction, Image Deblurring, Removing Adverse Weather Conditions, and Image Dehazing. The outcomes, the advantages, the limitations, and the possible areas for future research are detailed. Overall, it is noted that incorporating ViT in the new architectures for image restoration is becoming a rule. This is due to some advantages compared to CNN, such as better efficiency, especially when more data are fed to the network, robustness in feature extraction, and a better feature learning approach that sees better the variances and characteristics of the input. Nevertheless, some drawbacks exist, such as the need for more data to show the benefits of ViT over CNN, the increased computational cost due to the complexity of the self-attention block, a more challenging training process, and the lack of interpretability. These drawbacks represent the future research direction that should be targeted to increase the efficiency of ViT in the image restoration domain.

Quantifying irrigation water demand and supply gap using remote sensing and GIS in Multan, Pakistan.

Human interventions and rapid changes in land use adversely affect the adequate distribution of water resources. A research study was conducted to quantify the gap between demand and supply for irrigation water in Multan, Pakistan, which may lead to sustainable water management. Two remotely sensed images (Landsat 8 OLI and Landsat 5 TM) were downloaded for the years 2010 and 2020, and supervised classification method was performed for the selected land use land cover (LULC) classes and basic framework. During the evaluation, the kappa coefficient was found in the ranges of 0.83-0.85, and overall accuracy was found to be more than 80% which indicated a substantial agreement between the classified maps and the ground truth data for both years and seasons. The LULC maps showed that urbanization has increased by 49% during the last decade (2010-2020). Reduction in planting areas for wheat (9%), cotton (24%), and orchards (46%) was observed. An increase in planting areas for rice (92%) and sugarcane (63%) was observed. The changing LULC pattern may be related to variation in water demand and supply for irrigation. The irrigation water demand has decreased by 370.2 Mm3 from 2010 to 2020, due to the reduction in agricultural land and an increase in urbanization. Available irrigation water supply (canals/rainfall) was estimated as 2432 Mm3 for the year 2020 which was 26% less than that of total irrigation water demand (3281 Mm3). The findings also provide the database for sustainable water management and equitable distribution of water in the region.

Posterior fossa epidural hematoma: A 6-year management experience.

Objective: Through this study, we sought to evaluate the management of posterior fossa extradural hematoma (PFEDH). Methods: An observational study was conducted at the Neurosurgery Department of Lady Reading Hospital in Peshawar from January 2015 to December 2020. All patients who had a traumatic acute extradural hematoma (EDH) of the posterior fossa were included, irrespective of age and gender. The clinical predictors and outcomes were assessed, including the CT-scan findings and Glasgow Coma Scale (GCS) score. Results: A total of 104 cases with posterior fossa extradural hematoma were identified from 1252 extradural hematoma patients admitted during the study period. The mean age of the enrolled patients was 18.17 ± 14.31 years. Most of the patients were male (65.39%) and belonged to the pediatric age group, i.e., < 15 years (60.6%). CT scan brain was done in all the cases for diagnosis. In 68.3% of cases, an associated occipital bone fracture was observed. Surgery was done in almost 71.2% of cases, and most of the patients experienced good recovery after surgery, as indicated by the GOS score. Linear regression model revealed that treatment (ß=-0.20, p=0.038), time duration between surgery and trauma (ß=0.43, p=0.000) and GCS category (ß=-0.47, p=0.000) were significantly associated with PFEDH outcomes. Conclusion: In conclusion, PFEDH was frequent among males and the pediatric age group. Serial CT brain is highly recommended in all suspected cases for early diagnosis.

Addressing Osteonecrosis: A preventable catastrophe - A multi-center study.

Objectives: To assess the knowledge of medical doctors about osteonecrosis who prescribe radiotherapy and bisphosphonates and dentists who receive these patients with such risk factors. Methods: This cross sectional multicenter study was carried out from 15th October 2021 to 20th November 2021 in different set-ups of Pakistan. A validated and piloted questionnaire was sent to dental and non-dental doctors working in different set-ups of Pakistan through email. All data was analyzed in SPSS version 22 with p value <0.05 being significant. Results: A total of 400 completed responses were received. Only 58% and 67% of the participants were actively educating their patients regarding the hazards of bisphosphonate and radiotherapy, respectively whereas only 45% of the medical doctors referred their patients to dentists before prescribing bisphosphonates and/or radiotherapy. Although the medical doctors had a statistically better knowledge of the definition of osteonecrosis, overall both the dental and non-dental doctors performed poorly regarding answering the questions pertaining to definition, clinical features and risk factors. The dental doctors also showed a poor performance for more technical and in depth questions that was statistically related to lesser work experience, working in a tertiary care facility and previous exposure to such patients. Conclusion: The inadequate awareness of dentists and physicians about the prevention and management of osteonecrosis of jaw is alarming. Efforts should be undertaken to raise the knowledge of dentists and physicians in this regard.

SARS-CoV-2 Seroprevalence before Delta Variant Surge, Chattogram, Bangladesh, March-June 2021.

A March-June 2021 representative serosurvey among Sitakunda subdistrict (Chattogram, Bangladesh) residents found an adjusted prevalence of severe acute respiratory syndrome coronavirus 2 antibodies of 64.1% (95% credible interval 60.0%-68.1%). Before the Delta variant surge, most residents had been infected, although cumulative confirmed coronavirus disease incidence was low.

Uncovering the Anticancer Potential of Polydatin: A Mechanistic Insight.

Polydatin or 3-O-ß-d-resveratrol-glucopyranoside (PD), a stilbenoid component of Polygonum cuspicadum (Polygonaceae), has a variety of biological roles. In traditional Chinese medicine, P. cuspicadum extracts are used for the treatment of infections, inflammation, and cardiovascular disorders. Polydatin possesses a broad range of biological activities including antioxidant, anti-inflammatory, anticancer, and hepatoprotective, neuroprotective, and immunostimulatory effects. Currently, a major proportion of the population is victimized with cervical lung cancer, ovarian cancer and breast cancer. PD has been recognized as a potent anticancer agent. PD could effectively inhibit the migration and proliferation of ovarian cancer cells, as well as the expression of the PI3K protein. The malignancy of lung cancer cells was reduced after PD treatments via targeting caspase 3, arresting cancer cells at the S phase and inhibiting NLRP3 inflammasome by downregulation of the NF-κB pathway. This ceases cell cycle, inhibits VEGF, and counteracts ROS in breast cancer. It also prevents cervical cancer by regulating epithelial-to-mesenchymal transition (EMT), apoptosis, and the C-Myc gene. The objective of this review is thus to unveil the polydatin anticancer potential for the treatment of various tumors, as well as to examine the mechanisms of action of this compound.

Remotely sensed image interpretation for assessment of land use land cover changes and settlement impact on allocated irrigation water in Multan, Pakistan.

Industrial revolution and rapid population growth are responsible for alteration of land into different settlements. These changes may lead to change in land use (LU) and land cover (LC). The LULC changes have impact on hydrological regimes including streams flow pattern and allocated irrigation water (water allocation through Warabandi system). The present study aimed to identify the LULC changes and settlement impact on allocated water using the unsupervised classification and normalized difference vegetation index (NDVI) of Landsat images for the years of 1990 to 2020 in Multan District. The accuracy assessment and Kappa coefficient were also investigated to evaluate quality of results derived from the classified images. The results show that the reduction in waterbody, spare, and dense vegetation was -7.6, -1.7, and -30.7%, respectively. The settlements, barren, and crop lands have increased to 25.2, 10.1, and 4.6%, respectively, from 1990 to 2020. The values of kappa coefficient (0.84-0.85) showed very good level of classification. In addition, the volume of water loss due to change of LULC from waterbody into settlements, barren land, crop land, spare, and dense vegetation was found approximately 472, 44, 133, 54, and 85 m3, respectively, in last 30 years. This volume of water is not reaching equitably to the farming community because of the LU and LC changes and urban settlements. The results indicated that remotely sensed image interpretation technique may be a useful for reallocation of water among farmers in an equitable and efficient way.

Closed Repair Technique: Innovative Surface Design for Polymethylmethacrylate Denture Base Repair.

PURPOSE: This study aimed to evaluate the repair strength of a newly introduced repair technique involving zero-gap repair width. MATERIALS AND METHODS: A total of 36 rectangular prism specimens with dimensions of 64 × 10 × 3.3 mm were prepared from heat-polymerized acrylic resin. Nine specimens were kept intact. The other specimens were sectioned into halves and modified to create repair gaps of 2.5-mm beveled (2.5B) as control, 0-mm beveled (ZB), and 0-mm inverse bi-beveled (ZIBB). The ZIBB group was prepared with a V-shaped internal groove on both halves (repair tunnel), while the intaglio and cameo surfaces were kept intact except for two small holes at the cameo surface for repair resin injection. The 2.5B and ZB groups were repaired conventionally while the ZIBB group was repaired by injecting repair resin into the tunnel through one of the holes until excess material oozed from the other hole. Repaired specimens were thermally cycled at 5 and 55°C for 10,000 cycles with 1 min dwell time. A 3-point bending test was conducted using a universal testing machine for flexural strength and elastic modulus measurement. Kruskal-Wallis/Mann-Whitney tests and ANOVA/post hoc Tukey tests were applied for data analysis (α = 0.05). RESULTS: The flexural strength of repaired specimens was substantially lower than that of intact specimens, and significant differences were present between repaired groups (p ˂ 0.05). ZB and ZIBB had higher flexural strength (p ˂ 0.001) and elastic modulus (p ˂ 0.05) than 2.5B. Among the ZB and ZIBB groups, ZB showed the highest flexural strength, and ZIBB had the highest elastic modulus. CONCLUSION: The closed repair technique improved the flexural strength and elastic modulus of repaired acrylic denture base.

Acute Watery Diarrhea Surveillance During the Rohingya Crisis 2017-2019 in Cox's Bazar, Bangladesh.

BACKGROUND: Forcibly Displaced Myanmar Nationals (FDMNs) fled into Cox's Bazar, Bangladesh due to internal conflict. Considering the public health situation, a surveillance network was established to identify the enteric pathogens and early detection of cholera epidemics. The purpose of this manuscript is to report the clinical, epidemiological determinants of cholera and other enteric pathogens among hospitalized diarrheal patients from FDMNs and host community. METHODS: A total of 11 sentinel surveillance sites were established around the camps in Ukhia and Teknaf Upazila, Cox's Bazar. Rapid diagnostic testing was conducted for immediate detection of cholera cases. Stool samples were transferred to the Infectious Diseases Division, International Centre for Diarrhoeal Disease Research Bangladesh (icddr,b) laboratory for culture. RESULTS: A total of 8134 participants with diarrhea were enrolled from 2017 to 2019: 4881 were FDMNs and 3253 were from the Bangladeshi host community. Among the FDMNs, the proportion of Vibrio cholerae was 0.7%, the proportion of enterotoxigenic Escherichia coli (ETEC) was 4.9%, and the proportion of Shigella was 1.5%. The distributions from host community were 1.2% V cholerae, 1.8% ETEC, and 1.1% Shigella. Similar risk factors have been identified for the diarrheal pathogens for both communities. CONCLUSIONS: This surveillance helped to monitor the situation of diarrheal diseases including cholera in refugee camps as well as in the neighboring host community. These findings lead policymakers to take immediate preventive measures.

Frequency of success and complications of primary endoscopic third ventriculostomy in infants with obstructive hydrocephalous.

OBJECTIVES: To determine the success rate and complications of primary endoscopic third ventri-culostomy (ETV) in infants with obstructive hydrocephalous. METHODS: This case series was conducted at the Department of Neurosurgery, Medical and Teaching Institute, Lady Reading Hospital Peshawar from July 2016 to June 2018. All consecutive patients with age less than one year who underwent ETV for primary obstructive hydrocephalous, of both gender, were included in the study. The patients were followed up to six months after surgery. The data was entered in a specially designed Performa. Patients' data was analyzed using SPSS version 21.0. RESULTS: We had total 21 patients with age less than one year during the study period. Male patients were 11 (52.4%). Success rate of ETV at six months of follow up was 12 (57.1%). Post-op complications observed were in 9.52% (2/21) cases. One patient had cerebrospinal fluid CSF) leak and the other had significant bleed. CONCLUSION: ETV is successful in 57.1% of infants with obstructive type of hydrocephalous. The post op complications in case of ETV are lower than Ventriculo-peritoneal shunts. Therefore, ETV can be offered to infants having obstructive hydrocephalous.

Meaningful in-training and end-of-training assessment: The need for implementing a continuous workplace-based formative assessment system in our training programs.

Objectives: To analyze the systems and tools involved in assessment of skill procurement and demonstrating workplace skills in postgraduate medical training. Methods: This cross-sectional survey was carried out by enrolling trainee doctors currently working in Medical, Surgical, Dental and Allied specialties of the country by sending a validated and piloted questionnaire through email. Data collection was done from 20th April to 20th May 2021. Data was analysed using SPSS v. 21.0. Results: A total of 351 completed responses were received from 10 major cities of the country. Multiple aspects of entry-into-training, in-training and end-of-training evaluation showed poor correlation with the required training goals. A comparison of assessment for entry-into-supervised training (FCPS-I) versus independent practice (FCPS-II) showed a dismal situation regarding assessing affective skills like leadership, teamwork, coping with pressure and self-awareness. The concept of maintaining portfolios was completely alien to the trainees and the assessment tools used for demonstrating workplace skills were outdated. The lack of a continuous, periodic and balanced assessment (65%); detailed feedback (61.5%); fair exams (59%); variability in scoring system (58%) and professionalism of the examiners (57.5%) were the most frequently selected perceived flaws in the assessment system by the participants. Conclusion: There are multiple lacunae regarding competency-based assessment systems in our training programs and a massive scope for improvement. Assessment systems should be implemented as continuous process of learning, self-reflection, feedback and revalidation throughout the training tenure at regular and multiple points.

Evaluation of anti-inflammatory and analgesic effects of Hertia intermedia (Boiss.) Kuntze extract.

Hertia intermedia is a traditional medicinal plant of Balochistan, used for pain management and stomach problems. Current research work was intended to evaluate the anti-inflammatory and analgesic activities of crude ethanolic extract of H. intermedia. Anti-inflammatory activity was determined by the carrageenan-induced and histamine-induce Rat paw edema in rats, analgesic activity was determined by acetic acid-Induced writhing test, formalin-induced hind paw licking in mice and Tail immersion test. H. intermedia crude ethanolic extract showed significant (p<0.05) effect in both carrageenan and histamine-induced rat paw edema at both 250 and 500 mg/kg oral doses. There were significant analgesic activities in comparison with standard drug and control (p<0.05). It is concluded that H. intermedia crude ethanolic extract possesses significant anti-inflammatory and analgesic effects. However further studies may be carried out to isolate the phytochemicals responsible for anti-inflammatory and analgesic activities.