Objective: It is common for women to explore and plan strategies to cope during labour. These strategies are usually focused on pain control and described as either pharmacological or non-pharmacological. As labour is an individual experience, each woman should be enabled to choose strategies that best suit them, and that reflect what they feel influences their sense of capacity to cope. By exploring women’s intentions and choices of strategies, this study aimed to understand how coping strategies can better reflect women’s individual needs and expectations. Design: Survey of 56 pregnant women, including open-ended questions. Setting: Australian tertiary maternity hospital. Population: Nulliparous women. Methods: Content and thematic analysis of open-ended responses. Main outcome measures: A qualitative description of women’s planned coping strategies for labour. Results: Themes related to how women frame the intensity of labour, how they strive for a relationally safe environment and a need to be prepared and knowledgeable. Strategies chosen by women could be grouped into two categories: intrinsic and extrinsic. Intrinsic strategies could be self-generated by women (such as breathing techniques and movement), while extrinsic strategies required either equipment (such as a bath) or others to administer (such as epidural analgesia). Conclusions: Women value having a range of intrinsic and extrinsic strategies that enable autonomy or require external support. This moves beyond the ‘pharmacological and non-pharmacological’ categorisation of strategies. The findings provide a foundation for more targeted research into how women can be supported to individualise and implement these coping strategies in labour.

Background: Perineal trauma during childbirth and postpartum perineal pain significantly affected the new mother’s physical, psychological, and social experiences toward spontaneous vaginal birth. The effects of perineal warm compresses remain inconclusive. Objectives: To assess the effects of perineal warm compresses during the second stage of labor on reducing perineal trauma and postpartum perineal pain relief. Search Strategy: We searched seven bibliographic databases, three register websites of randomized controlled trials (RCTs), and two dissertation databases for publications from inception to March 15, 2023. Selection Criteria: RCTs published in Chinese and English. Data Collection and Analyses: Two independent reviewers conducted the risk of bias assessing, data extraction, and the certainty of the evidence evaluation utilizing the Cochrane risk of bias 2.0 assessment criteria, the Review Manager 5.4, and the online GRADEpro tool respectively. Main Results: Seven RCTs involving 1362 primiparous women were included. The combined results demonstrated a statistical reduction on the second-(RR=0.40, 95 %CI: [0.27,0.59]), third- and/or fourth- degree perineal lacerations(RR=0.34, 95 %CI: [0.20,0.57]), the incidence of episiotomy (RR=0.69, 95 %CI: [0.58,0.83]) and relief on the short-term perineal pain postpartum (within two days) (MD=-0.94, 95 %CI: [-1.10,-0.77]); a potential favorable effect on improving the integrity of perineum (RR=3.36, 95 %CI: [1.22,9.27]); did not show a statistically significant supportive effect on reducing the first-degree perineal lacerations ((RR=1.43, 95 %CI: [1.05,1.95])) and the rate of perineal lacerations requiring suture (RR=0.68, 95 %CI: [0.45,1.02]). Conclusions: Perineal warm compresses effectively reduced the second-, third-/or fourth-degree perineal trauma and decreased the short-term perineal pain after birth.

Quantitative evidence on tree space segregation among avian assemblages in temperate primeval forests is currently lacking. Therefore, our study aimed to determine the species composition of birds across different parts of trees. We investigated whether species richness differs between positions on a tree and how these positions influence the probability of occurrence of specific bird species. To achieve this, we observed birds within permanent plots in Białowieża National Park (BNP) and analyzed the distribution patterns of birds within six vertical and three horizontal sectors of trees. The compositional dissimilarity between tree sectors was assessed using detrended correspondence analysis. We employed generalized linear mixed-effects models to examine differences in species richness and the probability of occurrence for ten of the most frequently observed species across tree sectors. The majority of the BNP bird community was associated with the branches, while other birds occupied the tree crown trunks and the understory trunks. Species richness was the highest on branches in the crown part of trees, followed by lower species richness on trunks associated with crowns, and the lowest richness was observed on branches and trunks in the understory. These results indicate that branches in the middle and lower parts of the crown serve as avian diversity hotspots on trees, likely due to the abundance of various food sources. The differing patterns of tree usage by specific bird species may suggest the avoidance of interspecific competition for resources. Importantly, our study provides a pristine state for future investigations.

Small populations of endangered species risk losing already eroded genetic diversity, important for adaptive potential, through the effects of genetic drift. The magnitude of drift can be mitigated by maximising the effective population size, as is the goal of genetic management strategies. Different mating systems, specifically those leading to reproductive skew, exacerbate genetic drift by distorting contributions. In the absence of an active management strategy, reproductive skew will have long-term effects on the genetic composition of a population, particularly where admixture is present. Here we examine the contrasting effects of conservation management strategies in two ex situ populations of the Critically Endangered eastern black rhino (Diceros bicornis michaeli), one managed as a semi-wild population in South Africa (SAx), and one managed under a mean-kinship breeding strategy in European zoos. We use molecular data to reconstruct pedigrees for both populations and validate the method using the zoo studbook. Using the reconstructed pedigree and studbook we show there is male sex-specific skew in both populations. However, the zoo’s mean-kinship breeding strategy effectively reduces reproductive skew in comparison to a semi-wild population with little genetic management. We also show that strong male reproductive skew in SAx has resulted in extensive admixture, which may require a re-evaluation of the population’s original intended role in the black rhino meta-population. With a high potential for admixture in many ex situ populations of endangered species, molecular and pedigree data remain vital tools for populations needing to balance drift and selection.

Background Pediatric rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in children. In low- and middle-income countries (LMIC) such as Pakistan, problems with delayed diagnosis, decreased access to care, treatment abandonment and lack of multidisciplinary care may lead to poor outcomes. Methods A retrospective chart review was conducted from January 1, 2017, to January 1, 2022 to identify patients with low- and intermediate-risk RMS at a tertiary cancer center in Pakistan. Curative treatment was given per the standard arms of the Children’s Oncology Group (COG) studies ARST0331 and ARST1431. Results Forty-eight patients were eligible for survival analysis. The most common tumor region was parameningeal (31.3%). The 3-year overall survival (OS) was 100% for the 14 low-risk patients and 76.5% for the 34 intermediate-risk patients. The worst performing tumor regions were “other sites”. The 3-year event-free survival (EFS) for radiation alone (55%) as a local control modality was worse than for surgery alone (66.7%) or a combination of surgery and radiation (66.7%). One-third of the patient cohort had severe malnutrition (< 5th percentile by weight) which was associated with lower 3-year OS of 75% vs 85.7%. Eight patients (17%) died (3 due to sepsis, 5 due to disease progression), 11 (23%) abandoned treatment and 15 (31%) had progressive disease. Conclusions There was a preponderance of intermediate-risk RMS in this cohort, with 3-year OS approaching that of high-income countries but with a lower PFS and EFS. Sepsis-related deaths, treatment abandonment, and malnutrition remain significant challenges.

As the Universal Health Insurance Plan (RAMU) is being implemented in Mali, community-based health insurance (CBHI) — one of the pillars— must innovate to meet the challenge of universal health coverage. An experimental CBHI was tested in central Mali between 2017 and 2021. This innovative CBHI professionalizes and organizes risk sharing on a larger scale, moving from municipalities to circles (department). A mixed-method study was carried out to assess the acceptability of this innovation among elected representatives of CBHI offices. In April 2021, 118 questionnaires were administered, followed by 43 qualitative interviews from the same sample in October 2021. Sekhon el al. (2017) seven dimensions of acceptability was used as the conceptual model. More than half of individuals (58%) reported above-average acceptability. Elected officials feel well supported in their activities by the Technical Union of Malian Mutuality (UTM), the umbrella organization of CBHI. They show some confidence in their ability to perform their duties effectively despite varying levels of commitment that often fall short of expectations and needs, which they justify by their volunteer status. Elected officials note that the system is very effective despite the nonoptimal conditions linked to the prevailing insecurity. Professionalization appears to be an unavoidable condition for the performance of the innovation, as well as the new community assembly. However, elected officials are concerned about the sustainability. The UTM will play an important role in continuing its support and fulfilling its functions as a delegated management organization within the framework of the RAMU.

Deforestation of the Amazon rainforest is approaching the worst in history. To protect against deforestation, it is necessary to accurately estimate the deforestation area. However, it is difficult to analyze large areas without direct human access. In addition, even if deforestation is estimated using satellite images, the presence of extensive cloud cover during the rainy season makes it challenging to obtain a clear view of the ground surface. In this paper, we propose a segmentation method based on deep learning and post-processing to predict the deforestation status in the Amazon rainforest area. To train and predict the deforestation area, we utilize a multi-modal satellite imagery dataset, including Sentinel-1, Sentinel-2, and Landsat 8. The proposed approach achieves the highest performance in the official CVPR MultiEarth Workshop 2023 challenge.

Nowadays, Distributed Energy Resources (DERs) and Electric Vehicles (EVs) are being increasingly used in smart distribution networks. There are concerns regarding the use of DERs and EVs which are twofold: (i) they may lead to grid voltage variation and (ii) they have uncertainty in power production. In this paper, a distributed voltage control method is proposed in the simultaneous presence of DERs and EVs preserving the independence and reducing the communications between them while considering probabilistic behaviors. The proposed objective function improves the system voltage profile with the lowest rate of change in the active and reactive power of DERs and EVs. For this purpose, a method is developed for converting the centralized optimization problem to the distributed optimization problem using Dual-Decomposition (DD) and Alternating Direction Method of Multipliers (ADMM) algorithms based on Peer-to-Peer (P2P) communication capabilities of DERs and EVs. The uncertainty of DERs and EVs are modelled by utilizing a scenario-based approach and a Two-Point Estimation Method (2PEM), respectively. The results on the modified IEEE 69-bus test system show that the proposed method can improve the voltage deviation of the worst bus by about 7%, and also reduce grid losses by about 48%.

INTRODUCTION Biodiversity data from surveys and other monitoring programs such as Citizen Science (called ‘CS’ hereafter) play a vital role in estimating species distributions and making conservation decisions . With an influx of data available to researchers through the various biodiversity databases such as iNaturalist , GBIF , Artsdatabanken (https://www.artsdatabanken.no/), eBird , amongst many others, there has been increased coverage and inferences about species distributions. However, these biodiversity data (especially those from CS) are subject to sampling and systematic biases, raising concerns about their use in scientific research . The sampling bias may be due to sampling variation in space and time, and the systematic bias could arise because of species misreporting and misidentification as well as imperfect detection, amongst many others . As discussed by , various statistical approaches have been used in analysing biodiversity data such as the generalised linear (mixed) models , hierarchical models such as N-Mixture models ( and references therein) and joint species distribution models ( and references therein). These methods depend on the type of response variable. Some modellers of biodiversity data use Maxent , a constrained optimisation approach that finds the optimal species density subject to constraints . Attaching any uncertainty to Maxent’s predictions is impossible as a non-stochastic approach. However, has shown that Maxent is equivalent to point process models and that the point process framework can be used to obtain standard errors on model coefficients and predictions. Biodiversity data have also been modelled as typical geostatistic data with a binary response by including pseudo-absences . These pseudo-absences are used to account for the biases in Maxent to generate reliable and unbiased species distribution models . However, this approach adds an arbitrary amount of data and ignores the spatial autocorrelation between absences, as pointed out in . However, some studies have explored different methods to control the selection of pseudo-absences to fit the species distribution models . Furthermore, other approaches propose modelling biodiversity data as a thinned point pattern . A point pattern is a collection of points with random locations. That is, the locations of the points are not fixed or previously chosen. A spatial point process is the model that determines the location and amount of points in an area. Thinning is an operation on point patterns that uses a specified rule to determine which points in the point pattern are deleted. For biodiversity data, the thinning of the point pattern of the true species occurrences is caused by inherent biases in them. For instance, proposed that a single covariate related to a source of bias (e.g. accessibility) should be included in the linear predictor as a log-linear function to determine the probability of retaining an occurrence (i.e. a variable restricted to ( − ∞, 0]) as described in ). and , however, proposed integrating extra sources of information, such as professional surveys, to account for these biases. These biases can be explicitly modelled as a function of known covariates if that information is available or as an extra random effect when data related to the biases is unavailable . However, these approaches do not consider how the various sources of biases discussed in the next paragraphs affect the observed data. Firstly, biodiversity data are typically affected by biased sampling and unbiased imperfect sampling processes. Observers, mostly from CS projects, usually choose where they go. This decision is frequently influenced by factors such as accessibility and where observers expect to find more occurrences (i.e. preferential sampling; ). This is known as the biased sampling process. On the other hand, some areas will be inaccessible due to government regulations or because they are protected areas or a sub-sample of biological materials are taken at a given location . This sampling incompleteness is an example of an unbiased imperfect sampling process. and have acknowledged the role of the sampling process as a thinning factor in the context of point patterns. explored a model that assumes the thinning process as a log-linear function that affects the intensity of the observed point pattern. Further work by and explored the implications of not properly accounting for the sampling bias in biodiversity data. This was done by comparing improvements in goodness-of-fit and ecological interpretability of a model that accounts for sampling bias to approaches such as Maxent or a model that does not account for the sampling bias at all. In both cases, modelling the sampling bias as a thinning operation on a point pattern reduced the bias in the estimated effect of ecological covariates on the spatial distribution of species occurrences. However, these developments have not explored other sources of bias that can affect the process of collecting biodiversity data. Secondly, imperfect detection is also another source of bias in biodiversity data . Imperfect detection occurs when the observer fails to detect the species even though it was present. Detectability must be accounted for in estimating species trend and abundance because some species are overlooked, and the detection of the species will depend on its behaviour . The detection and identification of these species are influenced by the observer’s attention to a particular species and place, time and factors determining visibility, such as weather conditions . Failure to account for the imperfect detection when analysing biodiversity data may bias parameter estimates \citep[especially when the detection probability varies systematically; ][]{welsh2013fitting} and thus make statistical inference less reliable . Integrated species distribution models (hereafter, iSDMs) have been proposed to analyse these observed biodiversity data from various sources and sampling protocols \citep[example of studies that use iSDMs include ][]{koshkina2017integrated, dorazio2014accounting, erickson2021accounting}. These iSDMs capitalize on the strengths of each dataset to better capture species distributions and dynamics . During most biodiversity data collection, more than one species are observed or reported. The report of one species can be misclassified as another. For example, iNaturalist reports potential misclassified species when a species of interest is queried on their website (www.inaturalist.org). Therefore, it is essential that we treat biodiversity data as multispecies data with possible misclassifications and model it as such . Misidentification and/or misreporting species and other sources of false positives (collectively known as misclassification) are critical issues to consider in biodiversity data. Various methods have been developed to model these false positives, such as those proposed by and and references therein. These methods can be model-based, which includes taking a subset of the data with verifiable certainty, instructing observers only to record observations they are sure about, and increasing observer experiences . These methods can also be design-based, for example, dependent double-observer method . Failure to account for misclassification in biodiversity data modelling can increase bias and decrease the precision of the parameter estimates , leading to accidental culling of endangered species and assessments of the population status and incorrect conservation decisions . Accounting for the biases existing in biodiversity data is paramount for users of these data. However, there is no consensus on how this can be done, and it is indeed a growing research field within both statistics and ecology . In this paper, we propose a hierarchical multispecies model for biodiversity data that simultaneously accounts for multiple sources of bias and specifies each of them probabilistically. Some work has been done to propose a framework for observer-based biases in CS data , but no work has been done to develop a Bayesian framework that provides insight into modelling biases in biodiversity data. It relies on a straightforward specification of the observed biodiversity data as a thinned point pattern. This point pattern is affected by common biases such as uneven sampling effort, imperfect detection and misclassification. We propose three stages of thinning, one for each type of bias considered. Each stage produces a probability of retaining a point from the previous stages. This novel approach is flexible and can accommodate more biases in biodiversity data beyond the ones discussed in this paper. This paper aims to introduce our modelling framework and its properties. The proposed framework in this paper is not excused from identifiability issues . A model is not identifiable when multiple combinations of parameter values are solutions to the equation we are interested in solving . Identifiability issues in some complex SDMs cannot be proven mathematically but through numerical integration of its Fisher information matrix . In this study, we also check for identifiability issues in the proposed framework by describing our framework as a generalisation of the developed SDMs that account for sources of biases. Due to these identifiability issues, the inference is non-trivial and thus, the inference is left to a future paper. This paper is organised as follows: in section 2, we introduce the multispecies biodiversity data collection process. In section 3, we explore the properties of the proposed model for biodiversity data by exploring potential issues of identifiability that this model can face and discuss possible ways to solve these issues. Finally, in section 4, we make concluding remarks and suggest future work.

California’s Channel Islands are home to two endemic mammalian carnivores: island foxes (Urocyon littoralis) and island spotted skunks (Spilogale gracilis amphiala). Although it is rare for two insular terrestrial carnivores to coexist, these known competitors persist on both Santa Cruz Island and Santa Rosa Island. We hypothesized that examination of their gut microbial communities would provide insight into the factors that enable this coexistence, as microbial symbionts often reflect host evolutionary history and contemporary ecology. Using rectal swabs collected from island foxes and island spotted skunks sampled across both islands, we generated 16S rRNA amplicon sequencing data to characterize their gut microbiomes. While island foxes and island spotted skunks both harbored the core mammalian microbiome, host species explained the largest proportion of variation in the dataset. We further identified intraspecific variation between island populations, with greater differentiation observed between more specialist island spotted skunk populations compared to more generalist island fox populations. This pattern may reflect differences in resource utilization following fine-scale niche differentiation. It may further reflect evolutionary differences regarding the timing of intraspecific separation. Considered together, this study contributes to the growing catalog of wildlife microbiome studies, with important implications for understanding how eco-evolutionary processes enable the coexistence of terrestrial carnivores – and their microbiomes – in island environments.

Fish communities of streams and rivers might substantially be subsidized by terrestrial insects that fall into the water. Although such animal-mediated fluxes are increasingly recognized, little is known on how anthropogenic perturbations may influence the strength of such exchanges. Intense land-use, such as lignite mining may impact a river ecosystem due to the flocculation of iron (III) oxides, and thus altering food web dynamics. We compared sections of the Spree River in North-East Germany that were greatly influenced by iron oxides with sections located downstream of a dam where passive remediation technologies are applied. Compared to locations downstream of the dam, the abundance of benthic macroinvertebrates at locations of high iron concentrations upstream of the dam was significantly reduced. Similarly, catch per unit effort of all fishes was significantly higher in locations downstream of the dam compared to locations upstream of the dam and condition of juvenile and adult piscivorous pike Esox lucius were significantly lower in size in sections of high iron concentrations. Using an estimate of short-term (i.e., metabarcoding of the gut content) as well as longer-term (i.e., hydrogen stable isotopes) resource use, we could demonstrate that two of the three most abundant fish species, perch Perca fluviatilis, and bleak Alburnus alburnus, received higher contributions of terrestrial insects to their diet at locations of high iron concentration. In summary, lotic food webs upstream and downstream of the dam greatly differed in the overall structure with respect to the energy available for the highest tropic levels and the contribution of terrestrial insects to the diet of omnivorous fish. Therefore, human-induced environmental perturbation such as river damming and mining activities represent strong pressures that can alter the flow of energy between aquatic and terrestrial systems, indicating a broad impact on the landscape level.

Objectives: Theories on Alzheimer disease (AD) pathogenesis propose a gap between pathological changes and the onset of clinical symptoms. The early detection of cognitive decline is crucial for the implementation of preventive strategies. Mild cognitive impairment (MCI) is a transitional stage and an accurate diagnosis is vital. However, the diagnosis of MCI varies due to inconsistent diagnostic criteria. This study aims to explore the effectiveness of comprehensive neuropsychological (NP) criteria, including all cognitive domains, for diagnosing cognitive impairment in clinical settings. Methods: The study included 509 subjects with subjective cognitive complaints between 2017 and 2021. They were diagnosed using the conventional and NP criteria, and the results were named the complex criteria (conventional criteria-NP criteria). Results: Concordance between the conventional and NP diagnostic criteria diagnoses was 87.82%. Some participants diagnosed with MCI or dementia using the conventional criteria were classified as normal according to the NP criteria. Notably, the MCI-NC and Demantia (DEM)-NC groups exhibited distinct characteristics. The MCI-NC group had higher depression scores and better memory performance and executive function than the MCI-MCI group. The DEM-NC group had better instrumental activities of daily living and lower functional impairment than the DEM-DEM group. Conclusion: This study highlights the complexity of diagnosing cognitive impairment in older adults and the importance of comprehensive criteria. Relying solely on conventional criteria may lead to an overdiagnosis. The NP criteria consider various cognitive domains and better discriminate between individuals with MCIs or other factors that contribute to cognitive difficulties. Further research is required to investigate long-term outcomes and clinical implications of these discrepant diagnoses.

Aim The primary aim of this study was to conduct an open pilot clinical trial of a brief mindfulness-based intervention for persistent postconcussion symptoms that occur after mild traumatic brain injury in military service members. For many service members, operational tempo and other time constraints may prevent them from completing a standard mindfulness-based stress reduction course. Thus, this study sought to examine the effectiveness of a five-session intervention called Mindfulness-Based Stress, Pain, Emotion, and Attention Regulation (MSPEAR). Methods Participants were active duty service members with a history of mild traumatic brain injury (TBI) and persisting postconcussion symptoms, all of whom were recruited from an outpatient TBI rehabilitation program at a military treatment facility. Of the 38 service members that were initially enrolled, 25 completed the 5-session MSPEAR intervention, and 20 returned for a 5-week follow-up evaluation. Questionnaires assessing perceived stress, positive affect, pain interference and catastrophizing, sleep disturbances, perceived behavioral and attention regulation, self-efficacy, and satisfaction with life were administered at pre-intervention, post-intervention, and at 5-week follow-up intervals. Neuropsychological testing at pre-intervention and 5-week follow-up included performance validity measures, attention, working memory, and executive function measures. Results Improvements in perceived stress, positive affect, behavioral regulation, metacognition, sleep disturbance, self-efficacy, and satisfaction with life were found immediately after the MSPEAR intervention and were maintained at the 5-week follow-up. Magnification and helplessness aspects of pain catastrophizing improved when comparing pre-intervention to the 5-week follow-up. Pain interference was not significantly different across study assessment times. Neuropsychological testing revealed improvements in sustained attention, working memory, cognitive flexibility, and inhibitory control when comparing pre-intervention to the 5-week follow-up assessment. Conclusions The MSPEAR intervention appears to show promise as a brief and effective therapy for specific postconcussion symptoms after mild traumatic brain injury in military service members. Each of the components of MSPEAR including stress, pain catastrophizing, emotion, and attention regulation showed improvements in this study, and bears further investigation in a larger scale, preferably randomized controlled trial in those active duty military service members who experience persisting symptoms after a mild traumatic brain injury.

Unveiling the hidden culprit: Parathyroid Adenoma induced recurrent Renal Calculus and Pancreatitis - A Case Report

Title: Emergent Bedside Management of a Pneumatocele in a Neonate via Fogarty CatheterAbstract: Persistent pneumatoceles in neonates increase mortality and little literature regarding emergent treatment in a decompensating patient exists. We present the emergent management of a pneumatocele in a decompensating neonate by isolation with a Fogarty catheter.Keywords: Pneumatocele, Fogarty Catheter, Neonatal Ventilation

A document by ELIAS NDIBAREMA. Click on the document to view its contents.

Authors

“RNA + peptide editing are two successive independent mechanisms required to generate a plethora of new functional isoforms in a wide range of binding protein families”. I discuss the characteristics of ‘Chemosensory Proteins’ CSPs in insects and their potential role in life origins and evolution, review diversity of CSP proteins, and present a fresh view on the molecular evolution and origins of life. I specifically address the relationship between the observed mutations in insect CSPs and the origin of life. The group in Jinan discovered a high level of pinpoint mutations on the RNA and peptide sequences of Bombyx mori chemosensory proteins (BmorCSPs) and odor-binding proteins (BmorOBPs). A new phylogenetic analysis of peptide mutations is presented, adding to the pioneering work, which discovered that binding protein mutations might have spread from bacteria to moths and other insect groups. Then, emphasis is placed on specific mechanisms of non-random mutations that alter α-helical profiling and introduce new functions at the protein level. I describe observed BmorCSP mutations in several insect species that occur through various mechanisms such as RNA editing and/or protein recoding in the ribosome, and I propose that such mechanisms may have played a role in the emergence and evolution of life on Earth’s crust. RNA + Peptide lays the groundwork for the proposed RNA Peptide World theory of life’s origin and evolution on Earth’s crust, which is stated further below.

A document by Giovanna Bonadonna. Click on the document to view its contents.

A document by Yan Barabinot. Click on the document to view its contents.

Editorial. Platelet purinergic receptors and non-thrombotic diseases.Simon C. Pitchford1* and Dingxin Pan.11Pulmonary Pharmacology Unit, Institute of Pharmaceutical Science, King’s College London, London, UK.*Author for correspondence and reprint requests:Dr Simon PitchfordPulmonary Pharmacology UnitInstitute of Pharmaceutical Science5.43 Franklin Wilkins Building150 Stamford StreetWaterloo CampusKing’s College LondonLondon UKSE1 9NHPhone: +44 2078484266Fax: +44 207 8484788Simon.pitchford@kcl.ac.uk

Atypical Ataxia-Telangiectasia with cervical dystonia: A case report

Desert locusts ( Schistocerca gregaria) pause a significant threat on food security. However, they also serve as a nutrient-rich delicacy in many African and Arab communities where they are traditionally harvested for food and feed during outbreaks. Traditional harvesting methods are inefficient, laborious and time-consuming hence, the need to explore more convenient and efficient techniques. This study assessed preferential selection and feeding behavior of desert locusts to identify trap plants that could attract and aggregate them for easy harvesting. Four trap plants (cowpea, finger millet, sorghum, and amaranth) and four repellent plants (neem, pencil cactus, garlic, and cayenne red pepper) were evaluated through multiple-choice experiments. A complete randomized design (CRD), mature adult, immature adult and hopper stages of desert locust replicated thrice were involved . One-way analysis of variance (ANOVA) was used to determine whether treatment effects was significant or not, and mean differences between treatments at p<0.05 were separated using post-hoc Tukey HSD. Cowpea was the most preferred trap plant by the three locust stages, while neem exhibited the most potent repellent effect. Neem as a push plant repelled locusts thereby reducing infestation and damage of cowpeas as a pull plant when both plants were grown in the same pot in a “push-pull” system. However, cowpea attracted large numbers of locusts repelled by neem for harvesting when both plants were grown in separate pots. These findings provide valuable insights on the potential of exploiting trap and repellents to enhance aggregation and harvesting of desert locusts for use as food and feed.

Food touches every human and every other species in the world throughout daily life. Food is therefore the subject of extensive regulation nationally, internationally across trade agreements, and under some religious law as well. Nanotechnology has been applied to food since the late 20 th century with attendant implications for food quality, quantity, and distribution. Applications of nanotechnology impacting food “from field to fork” include: more effective formulation of fertilizers, pesticides, and herbicides; nanosilver as an antibacterial in food handling and refrigeration; carbon nanotubes for secure and durable packaging Titanium dioxide to make food white, fluffy, and attractive to consumers; and nano-biosensors to detect temperature changes that might cause spoilage, thereby helping to prevent food loss. One nanoscale material in particular, Titanium Dioxide, has been subject to litigation and banned in Europe. By contrast, it is generally recognized as safe under USA laws, and has no specific federal limit if it consists of one percent or less of the total food involved. But, California’s assembly has also introduced legislation to ban this substance, and therefore the role of nanotechnology applied to food, shaping new laws and spawning litigation, is a hot new legal issue.