Limited Set Research Articles

Causal discovery to understand hot corrosion

AbstractGas turbine superalloys experience hot corrosion, driven by factors including corrosive deposit flux, temperature, gas composition, and component material. The full mechanism still needs clarification and research often focuses on laboratory work. As such, there is interest in causal discovery to confirm the significance of factors and identify potential missing causal relationships or codependencies between these factors. The causal discovery algorithm fast causal inference (FCI) has been trialled on a small set of laboratory data, with the outputs evaluated for their significance to corrosion propagation, and compared to existing mechanistic understanding. FCI identified salt deposition flux as the most influential corrosion variable for this limited data set. However, HCl was the second most influential for pitting regions, compared to temperature for more uniformly corroding regions. Thus, FCI generated causal links aligned with literature from a randomised corrosion data set, while also identifying the presence of two different degradation modes in operation.

MiC: Image-text Matching in Circles with cross-modal generative knowledge enhancement

Image-text matching is a challenging task due to vast discrepancies between the visual and textual modalities. Existing solutions tend to focus on a limited set of strongly aligned or misaligned elements, failing to fully bridge the inherent gap between two modalities. In this work, we introduce a collaborative framework that enables simultaneous learning of the matching task alongside two generative processes designed to generate textual and visual knowledge from cross-modal inputs. In such a way, the overall cross-modal consistency is estimated in a dual-view manner by estimating the similarities not only between the original textual and visual data (cross-modal), but also across the input and the generative knowledge (uni-modal). With the incorporation of generative components, the entire matching pipeline forms two closed circles, introducing a novel paradigm of Matching in Circles (MiC). Comprehensive experiments on two public datasets (Flickr30K and MS-COCO) demonstrate the superiority of the proposed method in both image-to-text and text-to-image retrieval scenarios.

HEAL Africa score to predict failure of surgical repair of obstetric urethro-vaginal fistula in the Democratic Republic of the Congo

IntroductionObstetric fistula (OF) repair surgery aims to restore the anatomical and functional integrity of the urinary tract, allowing affected women to regain their dignity and quality of life. However, in some cases, this surgical repair may fail. The objective of this study was to develop a predictive score to identify factors associated with the failure of surgical repair of obstetric urethro-vaginal fistula (FSROUVF) in the Democratic Republic of the Congo (DRC).MethodsThis is an analytical cross-sectional study of 358 patients with obstetric urethro-vaginal fistula (OUVF) who received surgical repair. We conducted bivariate and multivariate analyses. Score discrimination was assessed using the receiver operating characteristic (ROC) curve, C-index, and score calibration according to the Hosmer-Lemeshow test.ResultsSurgical repair of OUVF failed in 24.86% of cases (89/358). After logistic modelling, 6 criteria predicted FSROUVF: the use of intravaginal indigenous products (AOR = 3.59; 95% CI: 1.51–8.53), the presence of fibrosis (AOR = 6.37; 95% CI: 1.70–23.82), the presence of 2 or more fistulas in the same patient (AOR = 7.03; 95% CI: 3.14–15.72), the total urethral damage (AOR = 3.29; 95% CI: 1.36–7.95), the fistula size > 3 cm (AOR = 5.65; 95% CI: 2.12–15.01), and the postoperative infection (AOR = 351.10; 95% CI: 51.15–2409.81). A score of 0 to 14 was obtained, with a value ≤5 points indicating a low risk of FSROUVF, a value between 6 and 8 indicating a moderate risk, and a value ≥9 points corresponding to a high risk of FSROUVF. The area under the ROC curve of the score is 0.938 with a sensitivity of 60.67%, a specificity of 96.28%, a positive predictive value of 84.38%, and a negative predictive value of 88.10%.ConclusionWe report a FSROUVF rate in the DRC approaching a quarter of operative patients. Predictors of failure included fibrosis, presence of 2 or more fistulas, total urethral involvement, fistula size greater than 3 cm, postoperative infection, and use of intravaginal indigenous products. These factors are constitutive of the HEAL Africa score, which once validated, may have value in pre-operative counselling of patients. This study could be valuable for policy and strategies to address the problem of OUVF in the DRC and in resource limited settings more generally.

An efficient, fast, and robust algorithm for single diode model parameters estimation of photovoltaic solar cells

AbstractParameter estimation of photovoltaic (PV) solar cells and module models pays attention to researchers owing to their importance in practical considerations. The single diode model (SDM) circuit with five unknown parameters is widely used to model PV solar cells and modules. In this paper, a novel approach called alternate optimization (AO) algorithm based on a discrete search is proposed to estimate the SDM parameters. The proposed algorithm provides efficient and robust performance, considering a limited set of discrete values and increasing the convergence speed. Two practical case studies with actual measurements are considered to assess the proposed AO algorithm: the RTC France solar cell and monocrystalline PV modules with different irradiations and temperatures. The numerical findings underscore the superior performance of the proposed AO algorithm across various metrics. Notably, it achieves an exceptional Root Mean Square Error (RMSE) of 7.7426 × 10−04 for the RTC France PV cell and approximately 1 × 10−03 RMSE for monocrystalline PV modules. Additionally, the algorithm exhibits unparalleled speed, showcasing the fastest convergence with an elapsed time of 1.66 × 10−05—markedly 4.45 times quicker than the fastest method documented in the literature for SDM parameter estimation. Furthermore, the proposed AO algorithm stands out for its efficiency, requiring a maximum of five iterations for parameter estimation, a substantial improvement compared to the more than 10 iterations typically needed by algorithms in the existing literature. Its robustness is also commendable, as evidenced by the stability of final RMSE values across a variety of experiments, distinguishing it from less robust algorithms found in the literature.

MP2RAGE vs. MPRAGE surface-based morphometry in focal epilepsy.

In drug-resistant focal epilepsy, detecting epileptogenic lesions using MRI poses a critical diagnostic challenge. Here, we assessed the utility of MP2RAGE-a T1-weighted sequence with self-bias correcting properties commonly utilized in ultra-high field MRI-for the detection of epileptogenic lesions using a surface-based morphometry pipeline based on FreeSurfer, and compared it to the common approach using T1w MPRAGE, both at 3T. We included data from 32 patients with focal epilepsy (5 MRI-positive, 27 MRI-negative with lobar seizure onset hypotheses) and 94 healthy controls from two epilepsy centres. Surface-based morphological measures and intensities were extracted and evaluated in univariate GLM analyses as well as multivariate unsupervised 'novelty detection' machine learning procedures. The resulting prediction maps were analyzed over a range of possible thresholds using alternative free-response receiver operating characteristic (AFROC) methodology with respect to the concordance with predefined lesion labels or hypotheses on epileptogenic zone location. We found that MP2RAGE performs at least comparable to MPRAGE and that especially analysis of MP2RAGE image intensities may provide additional diagnostic information. Secondly, we demonstrate that unsupervised novelty-detection machine learning approaches may be useful for the detection of epileptogenic lesions (maximum AFROC AUC 0.58) when there is only a limited lesional training set available. Third, we propose a statistical method of assessing lesion localization performance in MRI-negative patients with lobar hypotheses of the epileptogenic zone based on simulation of a random guessing process as null hypothesis. Based on our findings, it appears worthwhile to study similar surface-based morphometry approaches in ultra-high field MRI (≥ 7 T).

Is webcare good for business? A study of the effect of managerial response strategies to online reviews on hotel bookings

PurposeEngaging in webcare, i.e. responding to online reviews, can positively affect consumer attitudes, intentions and behavior. Research is often scarce or inconsistent regarding the effects of specific webcare strategies on business performance. Therefore, this study tests whether and how several webcare strategies affect hotel bookings.Design/methodology/approachWe apply machine learning classifiers to secondary data (webcare messages) to classify webcare variables to be included in a regression analysis looking at the effect of these strategies on hotel bookings while controlling for possible confounds such as seasonality and hotel-specific effects.FindingsThe strategies that have a positive effect on bookings are directing reviewers to a private channel, being defensive, offering compensation and having managers sign the response. Webcare strategies to be avoided are apologies, merely asking for more information, inviting customers for another visit and adding informal non-verbal cues. Strategies that do not appear to affect future bookings are expressing gratitude, personalizing and having staff members (rather than managers) sign webcare.Practical implicationsThese findings help managers optimize their webcare strategy for better business results and develop automated webcare.Originality/valueWe look into several commonly used and studied webcare strategies that affect actual business outcomes, being that most previous research studies are experimental or look into a very limited set of strategies.

Assessing the effects of population-level political, economic and social exposures, interventions and policies on inclusive economy outcomes for health equity in high-income countries: a systematic review of reviews

BackgroundA fairer economy is increasingly recognised as crucial for tackling widening social, economic and health inequalities within society. However, which actions have been evaluated for their impact on inclusive economy outcomes is yet unknown.ObjectiveIdentify the effects of political, economic and social exposures, interventions and policies on inclusive economy (IE) outcomes in high-income countries, by systematically reviewing the review-level evidence.MethodsWe conducted a review of reviews; searching databases (May 2020) EconLit, Web of Science, Sociological s, ASSIA, International Bibliography of the Social Sciences, Public Health Database, Embase and MEDLINE; and registries PROSPERO, Campbell Collaboration and EPPI Centre (February 2021) and grey literature (August/September 2020). We aimed to identify reviews which examined social, political and/or economic exposures, interventions and policies in relation to two IE outcome domains: (i) equitable distribution of the benefits of the economy and (ii) equitable access to the resources needed to participate in the economy. Reviews had to include primary studies which compared IE outcomes within or between groups. Quality was assessed using a modified version of AMSTAR-2 and data synthesised informed by SWiM principles.ResultsWe identified 19 reviews for inclusion, most of which were low quality, as was the underlying primary evidence. Most reviews (n = 14) had outcomes relating to the benefits of the economy (rather than access to resources) and examined a limited set of interventions, primarily active labour market programmes and social security. There was limited high-quality review evidence to draw upon to identify effects on IE outcomes. Most reviews focused on disadvantaged groups and did not consider equity impacts.ConclusionsReview-level evidence is sparse and focuses on ‘corrective’ approaches. Future reviews should examine a diverse set of ‘upstream’ actions intended to be inclusive ‘by design’ and consider a wider range of outcomes, with particular attention to socioeconomic inequalities.

A tertiary care center-based study of a novel ‘ICU Mortality and Prolonged Stay Risk Scoring System’

Background & objective: Intensive care has been associated with high cost and resource-intensive medical care. Therefore, a risk prediction model is required to plan time allocation, human resources, and the required equipment. Various risk predictions for ICU mortality and ‘Prolonged Length of Stay’ (PLOS) scores are already available. Still, the established model, such as the APACHE IV score or SAPS II, sometimes became impractical since they required many laboratory parameters. A model based on co-morbidities and demographic factors may be more useful in limited resources setting. Hence, we developed a simple ICU mortality and PLOS risk prediction model based on co-morbidities and demographic data. Methodology: This retrospective cohort study was performed to develop a risk scoring for mortality and PLOS, using data from Dr. Sardjito Hospital Yogyakarta database between January 01-December 31, 2019. Logistic regression and bootstrap methods were used to create a risk score for estimating the risk. The discrimination performance of the model was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC). The Hosmer-Lemeshow test was employed to assess the model’s calibration. Results: A total of 415 patients were included in this study. The risk factors for mortality were perioperative support medication, kidney failure, neurologic disorder, respiratory failure, and intraoperative blood transfusion. The mortality score of 6 was associated with a 100% probability of mortality. Medical cases, GCS < 8, vasoactive/inotropic medication, sepsis, respiratory failure, and kidney failure were the risk factors for PLOS. PLOS score of 3 was associated with a 100% probability of PLOS. The discrimination for either mortality or PLOS was considered excellent with the AUC (± 95% CI) for mortality 0.896 (0.853-0.94), while for PLOS 0.878 (0.80-0.90). The calibration test found that both models had good calibration with P values of 0.53 and 0.55 for mortality and PLOS, respectively. Conclusion: The ‘Mortality and Prolonged Length of Stay Prediction Score’ based on co-morbidities and demographic data upon admission to ICU had good accuracy and can be applied as a potential new scoring system in healthcare institutions. Abbreviations: APACHE- Acute Physiologic Assessment and Chronic Health Evaluation; AUC; Area Under the Curve GCS- Glasgow Coma Scale; ICU- Intensive Care Unit; PLOS- ‘Prolonged Length of Stay’; PRC- Packed Red Cells; SAPS- Simplified Acute Physiology Score Keywords: Risk Scoring; Mortality; Prolonged Length of Stay; ICU Citation: Widyastuti Y, Jufan AY, Widodo U, Wisudarti CFR, Sudadi, Fauzi RA, Ardiansyah F. A tertiary care center-based study of a novel ‘ICU Mortality and Prolonged Stay Risk Scoring System’. Anaesth. pain intensive care 2024;28(1):100−107; DOI: 10.35975/apic.v28i1.2382 Received: October 02, 2023; Reviewed: November 27, 2023; Accepted: December 17, 2023

Completing the picture of field-grown cereal crops: a new method for detailed leaf surface models in wheat.

The leaf angle distribution (LAD) is an important structural parameter of agricultural crops that influences light interception, radiation fluxes and consequently plant performance. Therefore, LAD and its parametrized form, the Beta distribution, is used in many photosynthesis models. However, in field cultivations, these parameters are difficult to assess and cereal crops in particular pose challenges since their leaves are thin, flexible, and often bent and twisted around their own axis. To our knowledge, there is only a very limited set of methods currently available to calculate LADs of field-grown cereal crops that explicitly takes these special morphological properties into account. In this study, a new processing pipeline is introduced that allows for the generation of realistic leaf surface models and the analysis of LADs of field-grown cereal crops from 3D point clouds. The data acquisition is based on a convenient stereo imaging setup. The approach was validated with different artificial targets and results on the accuracy of the 3D reconstruction, leaf surface modeling and calculated LAD are given. The mean error of the 3D reconstruction was below 1mm for an inclination angle range between 0° and 75° and the leaf surface could be quantified with an average accuracy of 90%. The concordance correlation coefficient (CCC) of 99.6% (p-value = [Formula: see text]) indicated a high correlation between the reconstructed inclination angle and the identity line. The LADs for bent leaves were reconstructed with a mean error of 0.21° and a standard deviation of 1.55°. As an additional parameter, the insertion angle was reconstructed for the artificial leaf model with an average error < 5°. Finally, the method was tested with images of field-grown cereal crops and Beta functions were approximated from the calculated LADs. The mean CCC between reconstructed LAD and calculated Beta function was 0.66. According to Cohen, this indicates a high correlation. This study shows that our image processing pipeline can reconstruct the complex leaf shape of cereal crops from stereo images. The high accuracy of the approach was demonstrated with several validation experiments including artificial leaf targets. The derived leaf models were used to calculate LADs for artificial leaves and naturally grown cereal crops. This helps to better understand the influence of the canopy structure on light absorption and plant performance and allows for a more precise parametrization of photosynthesis models via the derived Beta distributions.

ON THE LIMIT SET OF A COMPLEX HYPERBOLIC TRIANGLE GROUP

Abstract Let $\Gamma =\langle I_{1}, I_{2}, I_{3}\rangle $ be the complex hyperbolic $(4,4,\infty )$ triangle group with $I_1I_3I_2I_3$ being unipotent. We show that the limit set of $\Gamma $ is connected and the closure of a countable union of $\mathbb {R}$ -circles.

Chinese physician perception on the treatment of chemotherapy-induced anemia: online cross-section survey study.

The management of chemotherapy induced anemia (CIA) remains challenging. The potential risk and benefits in providing patient-centered care need to be balanced; the disease is multifactorial; and the major treatments including red blood cell (RBC) transfusions, erythropoiesis-stimulating agents (ESAs) and intravenous injection (i.v.)iron supplementation have a unique set of strengths and limitations. Also, most previous survey based on the patient data could not reveal the process of evaluation and decision-making for CIA treatment from a physician's perspective. As the comparison of China Society of Clinical Oncology (CSCO), National Comprehensive Cancer Network (NCCN) and European Society of Medical Oncology (ESMO) guidelines, the standard of CIA treatment in China will vary from United States and Europe, for example, the initial hemoglobin (Hb) for RBC transfusions. In order to understand the diagnosis, treatment, and unmet medical needs of CIA patients, the China Medical Education Association (CMEA), in conjunction with Cancer Hope Medium, initiated the first national survey of Chinese physicians regarding the diagnosis and treatment of CIA. The CMEA sent an online, 12-item questionnaire (via wjx.cn) to physicians across China from September 1, 2022 to October 22, 2022. Two hundred and sixty-five samples were calculated usingsurveyplanet.com. The questionnaire evaluated the impact of anemia on chemotherapy interruption, initial treatment, the target Hb level of CIA in, and the current status of ESAs prescription in clinical practice. Respondents were asked to score their reasons for not using ESAs (including safety issues, drug access in practice or adherence) and the risk options of the current treatment including ESAs, RBC transfusion, and i.v.iron. A total of 331 questionnaires among 5,000 web visits were gathered, covering 247 hospitals in 29 provinces across China, of which 130 (53%) were tier IIIA hospitals, 50 (20%) were tier III B hospitals, 59 (24%) were tier IIA hospitals, and 8 (3%) were tier II B hospitals. The frequency of chemotherapy dose delay/reduction due to anemia was 24% [standard deviation (SD) 49%]. Most responding physicians rated an initial Hb level for ESAs treatment to be 80 g/L, with a favorable Hb level for chemotherapy being 100 g/L (60%), which would not limit treatment availability. The majority (67.6%, n=221) of physicians who responded indicated that they had used ESAs for anemia correction, while the others (32.4%, n=106) reported never using them. This is the first study in conducting a large-scale survey on the diagnosis and treatment of CIA in China from a physicians' perspective. We found that in China, nearly one-quarter of patients undergoing chemotherapy with concurrent anemia may experience interruption of chemotherapy and that the initiation of anemia treatment is not adequately timed. In treating CIA, most physicians prioritize the completion of chemotherapy via Hb level over treating the symptoms of anemia.

Reprint of: Some thoughts about transfer learning. What role for the source domain?

Transfer learning is called for when the training and test data do not share the same input distributions (PXS≠PXT) or/and not the same conditional ones (PY|XS≠PY|XT). In the most general case, the input spaces and/or output spaces can be different: XS≠XT and/or YS≠YT. However, most work assume that XS=XT. Furthermore, a common held assumption is that it is necessary that the source hypothesis be good on the source training data and that the “distance” between the source and the target domains be as small as possible in order to get a good (transferred) target hypothesis.This paper revisits the reasons for these beliefs and discusses the relevance of these conditions. An algorithm is presented which can deal with transfer learning problems where XS≠XT, and that furthermore brings a fresh perspective on the role of the source hypothesis (it does not have to be good) and on what is important in the distance between the source and the target domains (translations between them should belong to a limited set). Experiments illustrate the properties of the method and confirm the theoretical analysis.Determining beforehand a relevant source hypothesis remains an open problem, but the vista provided here helps understanding its role.

Why we cannot always expect life history strategies to directly inform on sensitivity to environmental change.

Variation in life history traits in animals and plants can often be structured along major axes of life history strategies. The position of a species along these axes can inform on their sensitivity to environmental change. For example, species with slow life histories are found to be less sensitive in their long-term population responses to environmental change than species with fast life histories. This provides a tantalizing link between sets of traits and population responses to change, contained in a highly generalizable theoretical framework. Life history strategies are assumed to reflect the outcome of life history tradeoffs that, by their very nature, act at the individual level. Examples include the tradeoff between current and future reproductive success, and allocating energy into growth versus reproduction. But the importance of such tradeoffs in structuring population-level responses to environmental change remains understudied. We aim to increase our understanding of the link between individual-level life history tradeoffs and the structuring of life history strategies across species, as well as the underlying links to population responses to environmental change. We find that the classical association between lifehistory strategies and population responses to environmental change breaks down when accounting for individual-level tradeoffs and energy allocation. Therefore, projecting population responses to environmental change should not be inferred based only on a limited set of species traits. We summarize our perspective and a way forward in a conceptual framework.

Room impulse response reconstruction with physics-informed deep learning

A method is presented for estimating and reconstructing the sound field within a room using physics-informed neural networks. By incorporating a limited set of experimental room impulse responses as training data, this approach combines neural network processing capabilities with the underlying physics of sound propagation, as articulated by the wave equation. The network's ability to estimate particle velocity and intensity, in addition to sound pressure, demonstrates its capacity to represent the flow of acoustic energy and completely characterise the sound field with only a few measurements. Additionally, an investigation into the potential of this network as a tool for improving acoustic simulations is conducted. This is due to its proficiency in offering grid-free sound field mappings with minimal inference time. Furthermore, a study is carried out which encompasses comparative analyses against current approaches for sound field reconstruction. Specifically, the proposed approach is evaluated against both data-driven techniques and elementary wave-based regression methods. The results demonstrate that the physics-informed neural network stands out when reconstructing the early part of the room impulse response, while simultaneously allowing for complete sound field characterisation in the time domain.

Local Volume Solvers for Earth System Data Assimilation: Implementation in the Framework for Joint Effort for Data Assimilation Integration

AbstractThe Joint Effort for Data assimilation Integration (JEDI) is an international collaboration aimed at developing an open software ecosystem for model agnostic data assimilation. This paper considers implementation of the model‐agnostic family of the local volume solvers in the JEDI framework. The implemented solvers include the Local Ensemble Transform Kalman Filter (LETKF), the Gain form of the Ensemble Transform Kalman Filter (GETKF), and the optimal interpolation variant of the LETKF (LETKF‐OI). This paper documents the implementation strategy for the family of the local volume solvers within the JEDI framework. We also document an expansive set of localization approaches that includes generic distance‐based localization, localization based on modulated ensemble products, and localizations specific to ocean (based on the Rossby radius of deformation), and land (based on the terrain difference between observation and model grid point). Finally, we apply the developed solvers in a limited set of experiments, including single‐observation experiments in atmosphere and ocean, and cycling experiments for the atmosphere, ocean, land, and aerosol assimilation. We also illustrate how JEDI Ensemble Kalman Filter solvers can be used in a strongly coupled framework using the interface solver approximation, which provides increments to the ocean based on observations from the ocean and atmosphere.

Аргументация и съдебна реторика: абдуктивното разсъждение и абдуктивни схеми в наказателното производство

Abstract: Human thought makes sense of the phenomena, processes and states of affairs of existence by means of its ability to form judgments (inferences). Since existence is vast and knowledge about it is always limited in terms of time, place, and possibility, the human mind derives its knowledge about the world around it (makes sense of it) precisely on the basis of the available set of time, information, and possibilities. In a criminal proceeding, the object of conceptualization (knowledge), based on a known (limited) set of information (evidence), is an event that occurred in the past - human behaviour that society has elevated as a crime. Since the time of Aristotle and Antiquity it has been known that knowledge follows the formula “from the known to the unknown”. Such is basically the formula embodied in abductive reasoning, as a third type of reasoning along with deductive and inductive reasoning. It is this type of reasoning that has been studied theoretically in the context of criminal law. The aim is to bring out the specificities of abductive reasoning and abductive schemes through the methods of desk research, critical reading and comparative analysis of various basic theoretical publications. The research questions are oriented towards the establishment of basic propositions and specific manifestations in the national context in Bulgaria in the field of criminal law and judicial rhetoric. Keywords: abduction, abductive reasoning, abductive schemes, inference, best explanation, hypothesis, justification, proof, criminal process. Rhetoric and Communications Journal, issue 58, January 2024

Control of organic impurities in antibiotics

Introduction: the international, as well as Russian Pharmacopoeia criteria for organic impurity assessment are not applicable to medicinal products obtained by fermentation, therefore the setting of limits for product-related impurities in antibiotics is not regulated by any commonly shared rules. The aim of the study was to analyse and summariese pharmacopoeial requirements for and methodological approaches to organic impurities control in active substances and finished products of semisynthetic antibiotics, peptide antibiotics, and antibiotics obtained by fermentation. Material and methods: the authors analysed the requirements for organic impurities control, as established by the leading world pharmacopoeias and the State Pharmacopoeia of the Russian Federation, using the example of three different groups of antibiotics (semisynthetic antibiotics, antibiotics obtained by fermentation, and peptide antibiotics). The study used comparative analysis and content analysis methods. Results: the study demonstrated that the product-related impurity profiles of the analysed active substances and corresponding finished products often differ significantly across the leading pharmacopoeias, either qualitatively or quantitatively, and do not necessarily comply with the EMA Guideline on setting specifications for related impurities in antibiotics. The methodological approaches to product-related impurity control also differ a lot in terms of pharmacopoeial reference standards used, accelerated stability studies, etc. Conclusion: the complex composition of product-related compounds does not always allow for their unambiguous classification as either impurities or active moieties (e.g. in the case of bleomycin). Most Russian Pharmacopoeia antibiotic monographs are harmonised with the European Pharmacopoeia (Ph. Eur.), which is fraught with problems regarding reference standards (RSs) use, since the composition of Ph. Eur. RSs includes both the active substance and several (sometimes up to 8) impurities. The Russian Pharmacopoeia monographs on antibiotics obtained by a process involving the fermentation stage, include the abnormal toxicity test, which seems redundant in comprehensive impurity control, at least for semisynthetic antibiotics.

Plant choice between arbuscular mycorrhizal fungal species results in increased plant P acquisition.

Arbuscular mycorrhizal fungi (AMF) are plant root symbionts that provide phosphorus (P) to plants in exchange for photosynthetically fixed carbon (C). Previous research has shown that plants-given a choice among AMF species-may preferentially allocate C to AMF species that provide more P. However, these investigations rested on a limited set of plant and AMF species, and it therefore remains unclear how general this phenomenon is. Here, we combined 4 plant and 6 AMF species in 24 distinct plant-AMF species compositions in split-root microcosms, manipulating the species identity of AMF in either side of the root system. Using 14C and 32P/33P radioisotope tracers, we tracked the transfer of C and P between plants and AMF, respectively. We found that when plants had a choice of AMF species, AMF species which transferred more P acquired more C. Evidence for preferential C allocation to more beneficial AMF species within individual plant roots was equivocal. However, AMF species which transferred more P to plants did so at lower C-to-P ratios, highlighting the importance both of absolute and relative costs of P acquisition from AMF. When plants had a choice of AMF species, their shoots contained a larger total amount of P at higher concentrations. Our results thus highlight the benefits of plant C choice among AMF for plant P acquisition.

Clinical practice applicability and relevance to non-specialists of a paediatric EEG online learning tool

BackgroundPaediatric electroencephalography (EEG) training is inadequate amongst healthcare practitioners and technicians managing children with epilepsy in sub-Saharan Africa. An entry level handbook was developed for healthcare practitioners in sub-Saharan Africa and subsequently made globally accessible via the International Child Neurology Teaching Network.AimTo investigate the usefulness of a paediatric online EEG handbook.MethodA survey of the ICNApedia online EEG handbook was circulated (December 2021–June 2022), to all 108 handbook registered participants (39 countries) via the research electronic data capture (REDCap) from the University of Cape Town (UCT).ResultsFifty participants from 25 countries responded: 8 from high income, 16 upper-middle income, 21 lower-middle income and 5 from low-income. 32 (64%) fully and 18 (36%) partially completed the survey. 35/50 (70%) had completed the handbook and seven respondents had partially completed the handbook. Responses supported the handbook as a good entry point to learn EEGs, especially for paediatrics. Likert scale ratings supported the handbook as relevant for gaining/enhancing knowledge and improving diagnosis and management of patients with confidence. The handbook was considered user friendly, comprehensible, and provided a practical experience. For improving EEG reading skills the handbook helped skills development via reinforcement and good illustrations. 29/32 (90%) of respondents confirmed that they are using learnt skills from the handbook in their current work.ConclusionIn resource limited settings non-specialist clinicians often provide extended services including EEG interpretation. The survey supports that the handbook is supporting this niche skills area, especially for the accessibility of knowledge gained. The handbook will continue to be adapted in-line with survey feedback.

Molecular typing of clinical and non-clinical &lt;i&gt;Escherichia coli&lt;/i&gt; from Rivers State, Nigeria using amplification-based RAPD and ERIC-PCR typing methods

Due to the diverse nature of Escherichia coli, typing of these organisms is essential. This can provide key epidemiological information not just on the strains in circulation and their relationship, but also on the development and spread of drug resistant clones. Affordable PCR-based typing techniques have resulted in an increase in typing studies particularly in resource limited settings. But information from Nigeria on strain typing is limited. This study was therefore aimed at typing clinical and non-clinical strains of E. coli from Nigeria using the PCR based Random Amplification of Polymorphic DNA (RAPD) and Enterobacterial Repetitive Intergenic Consensus-PCR (ERIC-PCR) typing methods. &#x0D; E. coli was isolated from clinical and non-clinical sources using Eosin Methylene Blue agar. Characteristic green metallic sheen colonies associated with E. coli were purified, identities determined using standard biochemical tests and confirmed using molecular methods. Susceptibility testing was carried out using the modified Kirby-Bauer disc diffusion test and RAPD and ERIC-PCR typing carried out on 48 confirmed E. coli isolates as previously described. ERIC-PCR typing resulted in the generation of 38 unique patterns with a 0.94 diversity. Nine of these were singletons comprised of only a single isolate, while the remaining 29 patterns were grouped to 10 clusters. RAPD gave similar results of 37 patterns, 9 singletons, 0.94 diversity and 13 clusters. For ERIC-PCR, all isolates with identical patterns were from the same source. RAPD, however, had identical patterns present in isolates from different sources. &#x0D; Using the ERIC-PCR typing method, this study was able to identify non-clinical isolates as distinct from the clinical E. coli isolates as evidenced by 100% identical ERIC-PCR profiles of isolates from the same source and a lack of 100% relatedness in isolates from different sources.