In silico identification of drug targets and vaccine candidates against Bartonella quintana: a subtractive proteomics approach.

BACKGROUND: The availability of genes and protein sequences for parasites has provided valuable information for drug target identification and vaccine development. One such parasite is Bartonella quintana, a Gram-negative, intracellular pathogen that causes bartonellosis in mammalian hosts. OBJECTIVE: Despite progress in understanding its pathogenesis, limited knowledge exists about the virulence factors and regulatory mechanisms specific to B. quintana. METHODS AND FINDINGS: To explore these aspects, we have adopted a subtractive proteomics approach to analyse the proteome of B. quintana. By subtractive proteins between the host and parasite proteome, a set of proteins that are likely unique to the parasite but absent in the host were identified. This analysis revealed that out of the 1197 protein sequences of the parasite, 660 proteins are non-homologous to the human host. Further analysis using the Database of Essential Genes predicted 159 essential proteins, with 28 of these being unique to the pathogen and predicted as potential putative targets. Subcellular localisation of the predicted targets revealed 13 cytoplasmic, eight membranes, one periplasmic, and multiple location proteins. The three-dimensional structure and B cell epitopes of the six membrane antigenic protein were predicted. Four B cell epitopes in KdtA and mraY proteins, three in lpxB and BQ09550, whereas the ftsl and yidC proteins were located with eleven and six B cell epitopes, respectively. MAINS CONCLUSIONS: This insight prioritises such proteins as novel putative targets for further investigations on their potential as drug and vaccine candidates.

One Pot Synthesis, Biological Efficacy of AuNPs and Au-Amoxicillin Conjugates Functionalized with Crude Flavonoids Extract of Micromeria biflora.

Amoxicillin is the most widely used antibiotic in human medicine for treating bacterial infections. However, in the present research, Micromeria biflora's flavonoids extract mediated gold nanoparticles (AuNPs) were conjugated with amoxicillin (Au-amoxi) to study their efficacy against the inflammation and pain caused by bacterial infections. The formation of AuNPs and Au-amoxi conjugates were confirmed by UV-visible surface plasmon peaks at 535 nm and 545 nm, respectively. The scanning electron microscopy (SEM), zeta potential (ZP), and X-ray diffraction (XRD) studies reveal that the size of AuNPs and Au-amoxi are found to be 42 nm and 45 nm, respectively. Fourier-transform infrared spectroscopy (FT-IR) absorption bands at 3200 cm-1, 1000 cm-1, 1500 cm-1, and 1650 cm-1 reveal the possible involvement of different moieties for the formation of AuNPs and Au-amoxi. The pH studies show that AuNPs and Au-amoxi conjugates are stable at lower pH. The carrageenan-induced paw edema test, writhing test, and hot plate test were used to conduct in vivo anti-inflammatory and antinociceptive studies, respectively. According to in vivo anti-inflammatory activity, Au-amoxi compounds have higher efficiency (70%) after 3 h at a dose of 10 mg/kg body weight as compared to standard diclofenac (60%) at 20 mg/kg, amoxicillin (30%) at 100 mg/kg, and flavonoids extract (35%) at 100 mg/kg. Similarly, for antinociceptive activities, writhing test results show that Au-amoxi conjugates produced the same number of writhes (15) but at a lower dose (10 mg/kg) compared to standard diclofenac (20 mg/kg). The hot plate test results demonstrate that the Au-amoxi has a better latency time of 25 s at 10 mg/kg dose when compared to standard Tramadol of 22 s at 30 mg/ kg, amoxicillin of 14 s at 100 mg/kg, and extract of 14 s at 100 mg/kg after placing the mice on the hot plate for 30, 60, and 90 min with a significance of (p ≤ 0.001). These findings show that the conjugation of AuNPs with amoxicillin to form Au-amoxi can boost its anti-inflammatory and antinociceptive potential caused by bacterial infections.

Assessment of heavy metals and associated oxidative stress in occupationally exposed workers from Bannu and Karak Districts in Pakistan.

Heavy metals (HMs) are extensively found in occupationally exposed miners and industrial workers, which may cause serious health-related problems to the large workforce. In order to evaluate the impact of these toxic pollutants, we have investigated the effect of cadmium (Cd), chromium (Cr), copper (Cu), and lead (Pb) concentration on exposed workers of mining, and woolen textile mill and compared the findings with unexposed individuals. From each category like exposed workers (mining, and woolen mill textile site) and unexposed individuals, 50 blood samples were taken. The occurrence of HMs in a sample was investigated through atomic absorption spectrometry while the oxidative stress marker malondialdehyde (MDA) and antioxidant enzyme statuses such as superoxide dismutase (SOD) and catalase (CAT) were analyzed in exposed and control samples. The results showed significant (p < 0.05) variation in Cd, Cr, Cu, and Pb levels in exposed and control samples. The concentration of Cd in the blood of WMWs, KMWs, and control group was 5.75, 3.89, and 0.42 µg/dL, respectively. On the other hand, the concentration of Pb in the blood of WMWs, MWs, and control was 32.34, 24.39, and 0.39 µg/dL while the concentrations of Cr and Cu in the blood of WMWs, MWs, and control group were 11.61 and 104.14 µg/dL, 4.21 and 113.21 µg/dL, 0.32 and 65.53 µg/dL, respectively. An increase in MDA was recorded in the exposed workers' group as compared to control subjects, whereas SOD and CAT activities decreased. Meanwhile, MDA was significantly and positively (p < 0.01) correlated with HMs, while negative significant correlations were found among HMs with SOD and CAT.

Architecting Intelligent Smart Serious Games for Healthcare Applications: A Technical Perspective.

The immune system of human beings plays a pivotal role in guarding against different types of diseases. During the COVID-19 pandemic, people with weak immune systems were more likely to die. Regular physical activities and healthy food intake can significantly improve the immune system; however, people with a sedentary lifestyle and a busy job schedule find it challenging and tedious to maintain regularity. Different approaches have been used over the years to engage people in various physical activities and improve their mental and physical health. The concept of employing serious games (games whose primary purpose is not fun or entertainment, but a serious goal) to effectuate better results has become one of the popular choices among healthcare professionals and research communities. Internet of things (IoT) has enabled digital transformation with smart cities, smart infrastructure, and the fourth industrial revolution. There have been some relevant studies on the encouragement of serious games in healthcare in the past few years. However, few research studies encourage IoT-enabled serious games played with IoT devices (sensors and actuators) by making the game experience more ubiquitous and pervasive. Consequently, the adaptation of the IoT in serious games for healthcare applications is a massive gap despite its growing need in an era significantly affected by COVID-19. This paper discusses the possibilities of integrating serious games with IoT and discusses the standard architecture, core technologies, and possible challenges. Finally, we present a prototype architecture and its various components and a qualitative analysis with recent studies.

Synthesis of Copper Oxide-Based Nanoformulations of Etoricoxib and Montelukast and Their Evaluation through Analgesic, Anti-Inflammatory, Anti-Pyretic, and Acute Toxicity Activities.

Copper oxide nanoparticles (CuO NPs) were synthesized through the coprecipitation method and used as nanocarriers for etoricoxib (selective COX-2 inhibitor drug) and montelukast (leukotriene product inhibitor drug) in combination therapy. The CuO NPs, free drugs, and nanoformulations were investigated through UV/Vis spectroscopy, FTIR spectroscopy, XRD, SEM, and DLS. SEM imaging showed agglomerated nanorods of CuO NPs of about 87 nm size. The CE1, CE2, and CE6 nanoformulations were investigated through DLS, and their particle sizes were 271, 258, and 254 nm, respectively. The nanoformulations were evaluated through in vitro anti-inflammatory activity, in vivo anti-inflammatory activity, in vivo analgesic activity, in vivo anti-pyretic activity, and in vivo acute toxicity activity. In vivo activities were performed on albino mice. BSA denaturation was highly inhibited by CE1, CE2, and CE6 as compared to other nanoformulations in the in vitro anti-inflammatory activity. The in vivo bioactivities showed that low doses (5 mg/kg) of nanoformulations were more potent than high doses (10 and 20 mg/kg) of free drugs in the inhibition of pain, fever, and inflammation. Lastly, CE2 was more potent than that of other nanoformulations.

An IoT-Enabled Information System for Smart Navigation in Museums.

The Internet of Things (IoT) is a new paradigm that connects objects to provide seamless communication and contextual information to anyone, anywhere, at any time (AAA). These Internet-of-Things-enabled automated objects interact with visitors to present a variety of information during museum navigation and exploration. In this article, a smart navigation and information system (SNIS) prototype for museum navigation and exploration is developed, which delivers an interactive and more exciting museum exploration experience based on the visitor's personal presence. The objects inside a museum share the information that assist and navigate the visitors about the different sections and objects of the museum. The system was deployed inside Chakdara Museum and experimented with 381 users to achieve the results. For results, different users marked the proposed system in terms of parameters such as interesting, reality, ease of use, satisfaction, usefulness, and user friendly. Of these 381 users, 201 marked the system as most interesting, 138 marked most realistic, 121 marked it as easy-in-use, 219 marked it useful, and 210 marked it as user friendly. These statistics prove the efficiency of SNIS and its usefulness in smart cultural heritage, including smart museums, exhibitions and cultural sites.

A Scheduling Mechanism Based on Optimization Using IoT-Tasks Orchestration for Efficient Patient Health Monitoring.

Over the past years, numerous Internet of Things (IoT)-based healthcare systems have been developed to monitor patient health conditions, but these traditional systems do not adapt to constraints imposed by revolutionized IoT technology. IoT-based healthcare systems are considered mission-critical applications whose missing deadlines cause critical situations. For example, in patients with chronic diseases or other fatal diseases, a missed task could lead to fatalities. This study presents a smart patient health monitoring system (PHMS) based on an optimized scheduling mechanism using IoT-tasks orchestration architecture to monitor vital signs data of remote patients. The proposed smart PHMS consists of two core modules: a healthcare task scheduling based on optimization and optimization of healthcare services using a real-time IoT-based task orchestration architecture. First, an optimized time-constraint-aware scheduling mechanism using a real-time IoT-based task orchestration architecture is developed to generate autonomous healthcare tasks and effectively handle the deployment of emergent healthcare tasks. Second, an optimization module is developed to optimize the services of the e-Health industry based on objective functions. Furthermore, our study uses Libelium e-Health toolkit to monitors the physiological data of remote patients continuously. The experimental results reveal that an optimized scheduling mechanism reduces the tasks starvation by 14% and tasks failure by 17% compared to a conventional fair emergency first (FEF) scheduling mechanism. The performance analysis results demonstrate the effectiveness of the proposed system, and it suggests that the proposed solution can be an effective and sustainable solution towards monitoring patient's vital signs data in the IoT-based e-Health domain.

Blockchain-Based Authentication in Internet of Vehicles: A Survey.

Internet of Vehicles (IoV) has emerged as an advancement over the traditional Vehicular Ad-hoc Networks (VANETs) towards achieving a more efficient intelligent transportation system that is capable of providing various intelligent services and supporting different applications for the drivers and passengers on roads. In order for the IoV and VANETs environments to be able to offer such beneficial road services, huge amounts of data are generated and exchanged among the different communicated entities in these vehicular networks wirelessly via open channels, which could attract the adversaries and threaten the network with several possible types of security attacks. In this survey, we target the authentication part of the security system while highlighting the efficiency of blockchains in the IoV and VANETs environments. First, a detailed background on IoV and blockchain is provided, followed by a wide range of security requirements, challenges, and possible attacks in vehicular networks. Then, a more focused review is provided on the recent blockchain-based authentication schemes in IoV and VANETs with a detailed comparative study in terms of techniques used, network models, evaluation tools, and attacks counteracted. Lastly, some future challenges for IoV security are discussed that are necessary to be addressed in the upcoming research.

An Efficient and Reliable Algorithm for Wireless Sensor Network.

In wireless sensor networks (WSN), flooding increases the reliability in terms of successful transmission of a packet with higher overhead. The flooding consumes the resources of the network quickly, especially in sensor networks, mobile ad-hoc networks, and vehicular ad-hoc networks in terms of the lifetime of the node, lifetime of the network, and battery lifetime, etc. This paper aims to develop an efficient and reliable protocol by using multicasting and unicasting to overcome the issue of higher overhead due to flooding. Unicasting is used when the desired destination is at a minimum distance to avoid an extra overhead and increases the efficiency of the network in terms of overhead and energy because unicasting is favorable where the distance is minimum. Similarly, multicasting is used when the desired destination is at maximum distance and increases the network's reliability in terms of throughput. The results are implemented in the Department of Computer Science, Bacha Khan University Charsadda (BKUC), Pakistan, as well as in the Network Simulator-2 (NS-2). The results are compared with benchmark schemes such as PUMA and ERASCA, and based on the results, the performance of the proposed approach is improved in terms of overhead, throughput, and packet delivery fraction by avoiding flooding.

Biomethane production improvement by hydrothermal pretreatment of thickened waste activated sludge.

This study evaluated the impact of hydrothermal pretreatment on thickened waste activated sludge (TWAS) for solubilization enhancement and biomethane production improvement through the mesophilic anaerobic digestion process. In order to assess the effect of temperature, retention time and severity index (SI) of the hydrothermal pretreatment, TWAS was exposed to fifteen different pretreatment conditions within a combination of 10 different pretreatment temperature range (150-240 °C), five different retention times (5-30 min) and five different severity indexes (SI = 3, 3.5, 4, 4.5 and 5). The solubilization enhancement was observed in all hydrothermally pretreated samples with the highest solubilization efficiency of 49% in pretreatment conditions of 200 °C and 10 min retention time within the corresponding SI = 4. Biomethane production was not improved in all fifteen pretreatment conditions, pretreatment with SI beyond 4 decreased the biodegradability of TWAS. The highest biomethane production was observed in the pretreatment condition of 170 °C and 10 min with a 40% increase compared to non-pretreated TWAS.

Characterization and synthetic biology of lipase from Bacillus amyloliquefaciens strain.

Lipases with high tolerance to temperature play a significant role in industry from food manufacturing to waste management systems. Thus, there is a need to investigate these enzymes from different geographical areas to look out for a more thermo-stable one. Characterization of lipases through experimental approaches is time consuming process and sometimes the results are ambiguous due to errors. However, integration of computational technologies is quite useful for prediction of optimized conditions. Such technologies can be applied as synthetic biology, which has many major applications in engineered biological approaches for accurate prediction of effects of different physical and chemical parameters on the system. In this study, cloning and expression of a lipase gene from Bacillus amyloliquefaciens, isolated from a novel geographical region of Pakistan, in Escherichia coli DH5α cells followed by sequencing was carried out. To isolate thermostable lipase producing strains, all the samples were kept at 50 °C. Genomic DNA was isolated and signal peptide (1-32 residues) sequence was chopped (ΔSPLipase). The ΔSPLipase was amplified and expressed in Linearized p15TV-L vector. The purified lipase appeared as single band of approximately 26 kDa. Suitable conditions of factors required for maximum lipase activity such as temperature, pH, substrate, organic solvent, detergents and metal ions were predicted through synthetic biology approach and further confirmed in wet lab. The predicted suitable factors for enzyme were almost similar to those determined experimentally. The optimum enzyme activity was recorded at pH 8 and 50 °C temperature. Interestingly, the activity of enzyme was found on a number of solvents, metal ions, detergents, and surfactants. The predicted optimum values and their experimental confirmations highlights the importance of integrated synthetic biology approaches in wet lab experiments. The characterized lipase of B. amyloliquefaciens at molecular level from Pakistani strains displayed good activity on a range of factors that implies this strain to be used for application in industrial level production.

Fractional order mathematical modeling of COVID-19 transmission.

In this article, the mathematical model with different compartments for the transmission dynamics of coronavirus-19 disease (COVID-19) is presented under the fractional-order derivative. Some results regarding the existence of at least one solution through fixed point results are derived. Then for the concerned approximate solution, the modified Euler method for fractional-order differential equations (FODEs) is utilized. Initially, we simulate the results by using some available data for different fractional-order to show the appropriateness of the proposed method. Further, we compare our results with some reported real data against confirmed infected and death cases per day for the initial 67 days in Wuhan city.

Toward Accurate Position Estimation Using Learning to Prediction Algorithm in Indoor Navigation.

Internet of Things is advancing, and the augmented role of smart navigation in automating processes is at its vanguard. Smart navigation and location tracking systems are finding increasing use in the area of the mission-critical indoor scenario, logistics, medicine, and security. A demanding emerging area is an Indoor Localization due to the increased fascination towards location-based services. Numerous inertial assessments unit-based indoor localization mechanisms have been suggested in this regard. However, these methods have many shortcomings pertaining to accuracy and consistency. In this study, we propose a novel position estimation system based on learning to the prediction model to address the above challenges. The designed system consists of two modules; learning to prediction module and position estimation using sensor fusion in an indoor environment. The prediction algorithm is attached to the learning module. Moreover, the learning module continuously controls, observes, and enhances the efficiency of the prediction algorithm by evaluating the output and taking into account the exogenous factors that may have an impact on its outcome. On top of that, we reckon a situation where the prediction algorithm can be applied to anticipate the accurate gyroscope and accelerometer reading from the noisy sensor readings. In the designed system, we consider a scenario where the learning module, based on Artificial Neural Network, and Kalman filter are used as a prediction algorithm to predict the actual accelerometer and gyroscope reading from the noisy sensor reading. Moreover, to acquire data, we use the next-generation inertial measurement unit, which contains a 3-axis accelerometer and gyroscope data. Finally, for the performance and accuracy of the proposed system, we carried out numbers of experiments, and we observed that the proposed Kalman filter with learning module performed better than the traditional Kalman filter algorithm in terms of root mean square error metric.

Towards a Remote Monitoring of Patient Vital Signs Based on IoT-Based Blockchain Integrity Management Platforms in Smart Hospitals.

Over the past several years, many healthcare applications have been developed to enhancethe healthcare industry. Recent advancements in information technology and blockchain technologyhave revolutionized electronic healthcare research and industry. The innovation of miniaturizedhealthcare sensors for monitoring patient vital signs has improved and secured the human healthcaresystem. The increase in portable health devices has enhanced the quality of health-monitoringstatus both at an activity/fitness level for self-health tracking and at a medical level, providing moredata to clinicians with potential for earlier diagnosis and guidance of treatment. When sharingpersonal medical information, data security and comfort are essential requirements for interactionwith and collection of electronic medical records. However, it is hard for current systems to meetthese requirements because they have inconsistent security policies and access control structures.The new solutions should be directed towards improving data access, and should be managed bythe government in terms of privacy and security requirements to ensure the reliability of data formedical purposes. Blockchain paves the way for a revolution in the traditional pharmaceuticalindustry and benefits from unique features such as privacy and transparency of data. In this paper,we propose a novel platform for monitoring patient vital signs using smart contracts based onblockchain. The proposed system is designed and developed using hyperledger fabric, which isan enterprise-distributed ledger framework for developing blockchain-based applications. Thisapproach provides several benefits to the patients, such as an extensive, immutable history log, andglobal access to medical information from anywhere at any time. The Libelium e-Health toolkitis used to acquire physiological data. The performance of the designed and developed system isevaluated in terms of transaction per second, transaction latency, and resource utilization usinga standard benchmark tool known as Hyperledger Caliper. It is found that the proposed systemoutperforms the traditional health care system for monitoring patient data.

Erratum: Ahmad, S.; Malik, S.; Park, D.-H.; Kim, D. Design of Lightweight Driver-Assistance System for Safe Driving in Electric Vehicles.

The authors wish to make the following erratum to this paper [...].

Design of Lightweight Driver-Assistance System for Safe Driving in Electric Vehicles.

Electric-vehicle technology is an emerging area offering several benefits such as economy due to low running costs. Electric vehicles can also help to significantly reduce CO 2 emission, which is a vital factor for environmental pollution. Modern vehicles are equipped with driver-assistance systems that facilitate drivers by offloading some of the tasks a driver does while driving. Human beings are prone to errors. Therefore, accidents and fatalities can happen if the driver fails to perform a particular task within the deadline. In electric vehicles, the focus has always been to optimize the power and battery life, and thus, any additional hardware can affect their battery life significantly. In this paper, the design of driver-assistance systems has been introduced to automate and assist in some of the vital tasks, such as a braking system, in an optimized manner. We revamp the idea of the traditional driver-assistance system and propose a generic lightweight system based on the leading factors and their impact on accidents. We model tasks for these factors and simulate a low-cost driver-assistance system in a real-time context, where these scenarios are investigated and tasks schedulability is formally proved before deploying them in electric vehicles. The proposed driver-assistance system offers many advantages. It decreases the risk of accidents and monitors the safety of driving. If, at some point, the risk index is above a certain threshold, an automated control algorithm is triggered to reduce it by activating different actuators. At the same time, it is lightweight and does not require any dedicated hardware, which in turn has a significant advantage in terms of battery life. Results show that the proposed system not only is accurate but also has a very negligible effect on energy consumption and battery life.

Soil-transmitted helminth infections in school children of three districts of Malakand region, Khyber Pakhtunkhwa, Pakistan.

Information on prevalence of soil-transmitted helminth (STH) infections among school children is scarce in Pakistan. This study was aimed to investigate the prevalence of soil-transmitted helminth in school children of three districts in, Khyber Pakhtunkhwa, Pakistan. A total of 300 stool samples were examined from August 2015 to August 2016 using direct smear (Normal saline and Lugol's Iodine solution) and the concentration methods. One hundred and eighty seven (62.3%) pupils were found infected with soil-transmitted helminths. One hundred and forty five (77.5%) were infected with single parasite and forty two (22.4%) with multiple infections. Ascaris lumbricoides 125 (66.4%), Trichuris trichura 50 (26.5%) and Ancylostoma duedenale 13 (6.91%) were detected. The children above 8 years in age were more parasitized than below 8 years (p=0.7832; P>0.05). Males were found more parasitized than females (p=0.9315; P>0.05). Children in lower Dir district were found more infected followed by Swat and upper Dir (P< 0.0001; p<0.05). No significant relationship was found among the examined and that of infected children for ages and sex in all the districts. Malakand division is an area with poor hygiene located in temperate zone near the border of Afghanistan and China. The prevalence of reported nematode parasites here compared with the same studies is unexpectedly high. These types of studies should continue time to time to know the hazardous nature of such parasitic infections for the betterment of the human health.

Design and Implementation of Cloud-Centric Configuration Repository for DIY IoT Applications.

The Do-It-Yourself (DIY) vision for the design of a smart and customizable IoT application demands the involvement of the general public in its development process. The general public lacks the technical knowledge for programming state-of-the-art prototyping and development kits. The latest IoT kits, for example, Raspberry Pi, are revolutionizing the DIY paradigm for IoT, and more than ever, a DIY intuitive programming interface is required to enable the masses to interact with and customize the behavior of remote IoT devices on the Internet. However, in most cases, these DIY toolkits store the resultant configuration data in local storage and, thus, cannot be accessed remotely. This paper presents the novel implementation of such a system, which not only enables the general public to customize the behavior of remote IoT devices through a visual interface, but also makes the configuration available everywhere and anytime by leveraging the power of cloud-based platforms. The interface enables the visualization of the resources exposed by remote embedded resources in the form of graphical virtual objects (VOs). These VOs are used to create the service design through simple operations like drag-and-drop and the setting of properties. The configuration created as a result is maintained as an XML document, which is ingested by the cloud platform, thus making it available to be used anywhere. We use the HTTP approach for the communication between the cloud and IoT toolbox and the cloud and real devices, but for communication between the toolbox and actual resources, CoAP is used. Finally, a smart home case study has been implemented and presented in order to assess the effectiveness of the proposed work.

Age of fusion of the distal radial and ulnar epiphyses from hand radiographs-A study in Kashmiri population.

Age estimation is a crucial parameter involved in investigations pertaining to civil and criminal procedures. It also aids in various examinations in forensic medicine, pediatrics, endocrinology and radiology. One of the important methods for skeletal age estimation is the age of fusion of the epiphyses. But there occur variations in the skeletal ages due to environmental, hormonal, ethnic and other factors. Hence, there arises the need for separate standards of ossification for different regions. The present study was conducted to ascertain the age of fusion of the distal radial and ulnar epiphyses in Kashmiri population. A total of 160 healthy subjects, including 80 males and 80 females with ages ranging from 12 to 20years were studied. Their chronological age was obtained and the X-ray of their left hand was taken in the A.P view after taking the consent from their parents. The starting of epiphyseal fusion in lower end of radius in male was observed at 15-16years in 20% of the male population and for females, it was observed at 13-14years in 10% of the female population. The completion of epiphyseal fusion in lower end of radius in 100% males was noticed at 18-19years and for 100% females, it was noticed at 17-18years. The starting up of epiphyseal fusion in lower end of ulna in males was observed at 14-15years in 10% of the male population and for females, it was observed at 13-14years in 10% of the female population. The completion of epiphyseal fusion in lower end of ulna in 100% males was noticed at 18-19years and for 100% females, it was noticed at 17-18years. In case of males the age of fusion of the epiphyses of lower end of radius and lower end of ulna was found to be in the same age group 18 to 19years. Also in case of females the age of fusion of the epiphyses of lower end of radius and lower end of ulna was found to be in the same age group 17 to 18years. It was further observed that females showed fusion in advance of male subjects. The findings of this study were compared with those reported from other states of India and also from other countries.

Royleanumioside--a new phytotoxic triterpenoid from Teucrium royleanum.

Royleanumioside (1), a new lupane type triterpenoid, was secluded from the CHCl3 soluble fraction of Teucrium royleanum. The structure of royleanumioside (1) was ascertained by spectral studies including 1D and 2D NMR spectroscopy and by the assessment with the reported data in literature. This new identified compound 1 was further tested for its phytotoxic activity against lettuce seedlings. Interestingly royleanumioside (1) had shown moderate phytotoxic activity.