ethicalabs/Research-Intent-Collab huggingface dataset:
Metagenomic analysis of the honey bee queen microbiome reveals low bacterial diversity and Caudoviricetes phages

Abstract                                    In eusocial insects, the health of the queens – the colony founders and sole reproductive females – is a primary determinant for colony success. Queen failure in the honey bee                   Apis mellifera                   , for example, is a major concern of beekeepers that annually suffer with colony losses, necessitating a greater knowledge of queen health. Several studies on the microbiome of honey bees have characterized its diversity and shown its importance for the health of worker bees, the female non-reproductive caste. However, the microbiome of workers differs from that of queens, which in comparison is still poorly studied. Thus, direct investigations of the queen microbiome are required to understand colony-level microbiome assembly, functional roles, and evolution. Here we used metagenomics to comprehensively characterize the honey bee queen microbiome. Comparing samples from different geographic locations and breeder sources, we show that the microbiome of queens is mostly shaped by the environment experienced since early life, and is predicted to play roles in breakdown of the diet, and protection from pathogens and xenobiotics. We also reveal the microbiome of queens comprises only four core bacterial species,                   Apilactobacillus kunkeei                   ,                   Lactobacillus apis, Bombella apis                   and                   Commensalibacter                   sp. Interestingly, in addition to bacteria, we show that bacteriophages infect the queen microbiome, for which Lactobacillaceae are predicted to be the main reservoirs. Together, our results provide the basis to understand the honey bee colony microbiome assemblage, can guide improvements in queen rearing processes, and highlight the importance of bacteriophages for queen microbiome health and microbiome homeostasis in eusocial insects.                                                     Importance                                        The queen caste plays a central role for colony success in eusocial insects, as queens lay eggs, and regulate colony behavior and development. Queen failure can cause colonies to collapse, which is one of the major concerns of beekeepers. Thus, understanding of the biology behind the queen’s health is a pressing issue. Previous studies have shown the bee microbiome plays an important role in worker bee health, but little is known about the queen microbiome and its function                     in vivo                     . Here, we characterized the queen microbiome identifying for the first time present species and their putative functions. We show that the queen microbiome have predicted nutritional and protective roles in queen association, and comprises only four consistently present bacterial species. Additionally, we bring to attention the spread of phages in the queen microbiome, which increased in abundance in failing queens and may impact the fate of the colony.
The cost-effectiveness of in-patient care for COVID-19: implications for health technology assessment in South Africa

Health technology assessment aims to enable the prioritisation of efficient and equitable services and enhance responsiveness to population preferences. Resting on foundations of distributive and procedural justice, it is a fundamental component of a universal health coverage system. The required decision-making for the COVID-19 response stimulated the demand for evidence-informed processes and provides an opportunity to demonstrate how health technology assessment can be conducted in the South African environment. This chapter contributes to strengthening health technology assessment by reflecting on insights gained from research on the cost-effectiveness of in-patient care for COVID-19. Rapid economic evaluations of in-patient interventions for COVID-19, including intensive care, dexamethasone and remdesivir were conducted. These evaluations aimed to inform urgent health policy decisions related to the COVID-19 response and to demonstrate the use and feasibility of a pragmatic approach to health technology assessment. Costs from the health systems perspective, deaths, and disability-adjusted life years (DALYs) averted were estimated. Incremental cost-effectiveness ratios were compared to the estimated marginal productivity of the public health system to gauge cost-effectiveness. Open access models were published to encourage transparency and policy translation. Results indicated that purchasing private sector intensive care was unlikely to be cost-effective, dexamethasone was cost-effective, and remdesivir was cost-saving. Corresponding national policy included a signed service-level agreement to purchase private ICU beds for public patients, and recommendations in favour of dexamethasone and against remdesivir. Policy decisions did not align with findings of two of the three economic evaluations. These analyses and associated policy dissemination demonstrate that health technology assessment need not wait for the perfect system. Rigorous, transparent and rapid economic evaluation to support such assessment for urgent, priority policy decisions can be conducted in the South African context. Institutionalising health technology assessment, including strengthening capacity and funding of analyses, will assist decision-making and sustainability in the National Health Insurance environment.
RECENSIÓN DE: AMBOS, KAI (ED.), ROME STATUTE OF THE INTERNATIONAL CRIMINAL COURT. ARTICLE-BY-ARTICLE COMMENTARY, 4TH ED., BECK-NOMOS-HART, 2022

Recensión de la 4ª edición de la obra: Ambos, Kai (ed.), Rome Statute of the International Criminal Court. Article-by-Article Commentary, 4th ed., Beck-Nomos-hart, 2022.
Evaluation of Human Pharmacokinetics, Therapeutic Dose and Exposure Predictions Using Marketed Oral Drugs

In this article approaches to predict human pharmacokinetics (PK) are discussed and the capability of the exemplified methodologies to estimate individual PK parameters and therapeutic dose for a set of marketed oral drugs has been assessed. For a set of 63 drugs where the minimum efficacious concentration (MEC) and human PK were known, the clinical dose was shown to be well predicted or in some cases over-estimated using a simple one-compartment oral PK model. For a subset of these drugs, in vitro potency against the primary human targets was gathered, and compared to the observed MEC. When corrected for plasma protein binding, the MEC of the majority of compounds was  GFR. For approximately 90% of compounds studied, the predicted CL using in vitro-in vivo (IVIV) extrapolation together with a CL(renal) estimate, where appropriate, was within 2-fold of that observed clinically. Encouragingly volume of distribution at steady state (V(ss)) estimated in preclinical species (rat and dog) when corrected for plasma protein binding, predicted human V(ss) successfully on the majority of occasions--73% of compounds within 2-fold. In this laboratory, absorption estimated from oral rat PK studies was lower than the observed human absorption for most drugs, even when solubility and permeability appeared not to be limiting. Preliminary data indicate absorption in the dog may be more representative of human for compounds absorbed via the transcellular pathway. Using predicted PK and MEC values estimated from in vitro potency assays there was a good correlation between predicted and observed dose. This analysis suggests that for oral therapies, human PK parameters and clinical dose can be estimated from a consideration of data obtained from in vitro screens using human derived material and in vivo animal studies. The benefits and limitations of this holistic approach to PK and dose prediction within the drug discovery process are exemplified and discussed.
Cosmic ray modulation processes in the heliosphere

The solar minimum of 2009 has been identified as an exceptional event with regard to cosmic ray (CR)modulation, since conditions in the heliosphere have reached unprecedented quiet levels. This unique minimum has been observed by the Earth-orbiting satellite, PAMELA, launched in June, 2006, from which vast sets of accurate proton and electron preliminary observations have been made available. These simultaneous measurements from PAMELA provide the ideal opportunity to conduct an in-depth study of CR modulation, in particular charge-sign dependent modulation. In utilizing this opportunity, a three-dimensional, steady-state modulation model was used to reproduce a selection of consecutive PAMELA proton and electron spectra from 2006 to 2009. Thiswas done by assuming full drifts and simplified diffusion coefficients, where the rigidity dependence and absolute value of themean free paths for protons and electrons were sequentially adjusted below 3 GV and 300 MV, respectively. Care has been taken in calculating yearly-averaged current-sheet tilt angle and magnetic field values that correspond to the PAMELA spectra. Following this study where the numerical model was used to investigate the individual effects resulting from changes in the tilt angle, diffusion coefficients, and global drifts, it was found that all these modulation processes played significant roles in contributing to the total increase in CR intensities from 2006 to 2009, as was observed by PAMELA. Furthermore, the effect that drifts has on oppositely charged particles was also evident from the difference between the peak-shaped time profiles of protons and the flatter time profiles of electrons, as is expected for an A < 0 polarity cycle. Since protons, which drift into the heliosphere along the heliospheric current-sheet, haven't yet reached maximum intensity levels by 2008, their intensities increased notably more than electrons toward the end of 2009. The time and energy dependence of the electron to proton ratios were also studied in order to further illustrate and quantify the effect of drifts during this remarkable solar minimum period.
Governing Secondary Research Use of Health Data and Specimens: The Inequitable Distribution of Regulatory Burden Between Federally-Funded and Industry Research

Abstract                Some of the most promising recent advances in health research offer opportunities to improve diagnosis and therapy for millions of patients. They also require access to massive collections of health data and specimens. This need has generated an aggressive and lucrative push toward amassing troves of human data and biospecimens within academia and private industry. But the differences between the strict regulations that govern federally funded researchers in academic medical centers (AMCs) versus those that apply to the collection of health data and specimens by industry can entrench disparities. This article will discuss the value of secondary research with data and specimens and analyze why AMCs have been put at a disadvantage as compared to industry in amassing the large datasets that enable this work. It will explore the limitations of this current governance structure and propose that, moving forward, AMCs should set their own standards for commercialization of the data and specimens they generate in-house, the ability of their researchers to use industry data for their own work, and baseline informed consent standards for their own patients in order to ensure future data accessibility.
Comparing System Dynamics and Agent-Based Simulation for Tumour Growth and its Interactions with Effector Cells

There is little research concerning comparisons and combination of System Dynamics Simulation (SDS) and Agent Based Simulation (ABS). ABS is a paradigm used in many levels of abstraction, including those levels covered by SDS. We believe that the establishment of frameworks for the choice between these two simulation approaches would contribute to the simulation research. Hence, our work aims for the establishment of directions for the choice between SDS and ABS approaches for immune system-related problems. Previously, we compared the use of ABS and SDS for modelling agents' behaviour in an environment with nomovement or interactions between these agents. We concluded that for these types of agents it is preferable to use SDS, as it takes up less computational resources and produces the same results as those obtained by the ABS model. In order to move this research forward, our next research question is: if we introduce interactions between these agents will SDS still be the most appropriate paradigm to be used? To answer this question for immune system simulation problems, we will use, as case studies, models involving interactions between tumour cells and immune effector cells. Experiments show that there are cases where SDS and ABS can not be used interchangeably, and therefore, their comparison is not straightforward.
An Analysis of Caste Discrimination and Untouchability in R.B. Nischal's Poem Paitālā Pukār 2

This paper examines the socio-cultural issues of Dalits. The objective of the study was to analyze caste discrimination and untouchability of Dalits. For this objective, the researcher has employed Stuart Hall's theoretical insights of representation under cultural studies. The poem was selected purposively and it was the library based qualitative research. The data were collected from record-keeping and description. The researcher found that Dalit community that has suffered from the time immemorial in every aspect due to generational, multi-faceted and institutionalized discrimination due to the Hindu caste system in Nepal for religious and political reasons. This unfair practice has left a clear mark of social division, exclusion and inequality which has severely ruined Dalits' life and identity. Addressing this issue in the poem Paital Puk r Ram Bahadur Kami, displays episodes of verbal and physical violence and recurrent intra-caste discrimination. As well as he depicts the traumatic existence of the Dalit oppressed community. Other dominations and discriminations are less traumatic in comparison of cultural trauma which is like an incurable disease. Therefore, this paper displays how the Dalit people have been living in a society bearing harsh torture, trauma and inhuman treatment. Moreover, it is significant for academia for representing diverse cultural experiences and people and it can be a valuable asset for the society.
EFFECTIVENESS OF HUMAN RESOURCES INFORMATION SYSTEM (HRIS) ON ORGANISATIONAL PERFORMANCE IN THE BANKING SECTOR

Human Resources Information System (HRIS) has become an important feature of Human Resource Management (HRM) in the emerging economies including Tanzania. The system has been adopted by several organizations but evaluation of its contribution to organization performance is rarely undertaken. In this paper, we report on the usefulness associated with the Human Resources Information System (HRIS) in banking sector casing Azania Bank Limited. The study aimed at investigating the importance of Human Resource Information Systems to the performance of Azania Bank Limited. The study findings show that HRIS contributes to the organization performance, the study adopted descriptive research targeting 133 respondents serving all employees of ABL headquarters. The data were collected using structured questionnaires which were subjected to descriptive and inferential analysis in the statistical package for social sciences (SPSS). Correlation and regression analysis were also undertaken based on the pre-established regression models. Results indicated that HRIS has significantly improved both employees’ and the managements’ access to human resource data across the institution. It was also established that highly significant (p &lt; 0.001) improvement of working standards was attained as the result of using HRIS. The study concluded that HRIS system is important in an organization due to significant positive correlations between organization performance and HRIS importance (R = 889). A few employees express difficulties in using the HRIS due to low computer literacy. The study recommends that ABL should invest more in exposing its employee to experience and familiarize them with the system and engage employee in the tailoring of organization system by analysis, design, construction and development of the system to improve their performance.
Vietnamese Nurses’ and Nursing students’ conceptions about healthcare associated infections : An empirical research study in patient safety and quality of care

Introduction: Healthcare associated infections (HAIs) are a global problem and lead to a large burden for the patients, healthcare systems and society. In low and middle-income countries the burden and prevalence is higher than in high-income countries. It is possible with good prevention to reduce the prevalence and burden of healthcare associated infections. Aim: Investigate Vietnamese Nurses’ and Nursing students’ conceptions about healthcare associated infections and their role in prevention of healthcare associated infections. Method: Qualitative research with a cross-sectional design and the data was collected through eight semi-structured interviews and unstructured observations. The data was analyzed by content analysis. Results: Four categories were identified in the data analysis: Understanding and conceptions about HAI, Hinders for the prevention of HAI, How to work in a preventive way for HAI, Responsibility for patient safety. Conclusion: The study showed hinders for the nurses to perform their work correctly, limitations in the environment, lack of time, and equipment and supplies. The need for improvements are more nurses, make equipment and supplies more available and more rooms for patients. The participants acknowledge about responsibility and the importance of following guidelines at the hospitals are identified in the result.
Socio-economic geography and the land rights of indigenous peoples in Paraguay

AbstractThe article investigates the long-term tendencies of Paraguayan political-economy, in particular the mounting impacts of export-oriented agribusiness on its indigenous peoples. The analysis is based on the theorisation of the geographical force of subtraction, that is, the evanescent properties of capitalist development, in which economic growth takes place via an interconnected elimination of rights, opportunities and alternatives. The discussion is focussed on the land struggle of the Paĩ Tavyterã in the northeast of Paraguay and members of the same ethnic group who live in Brazil (called Guarani-Kaiowa). It is a relational narrative that draws insights from various actors, communities and situations. The main conclusions are that, despite the fact that Paraguay is now a major exporter of agribusiness commodities, what has prevailed is the accumulation of multiple forms of political, environmental, social and economic violence. At the same time, the decolonising reaction of indigenous peoples, in alliance with other sectors of the working class, aims at reverting the deficit caused by systemic socio-economic subtraction and in pursuit of transformative additions.
A robust, open-source implementation of the locally optimal block preconditioned conjugate gradient for large eigenvalue problems in quantum chemistry

We present two open-source implementations of the Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) algorithm to find a few eigenvalues and eigenvectors of large, possibly sparse matrices. We then test LOBPCG for various quantum chemistry problems, encompassing medium to large, dense to sparse, wellbehaved to ill-conditioned ones, where the standard method typically used is Davidson's diagonalization. Numerical tests show that, while Davidson's method remains the best choice for most applications in quantum chemistry, LOBPCG represents a competitive alternative, especially when memory is an issue, and can even outperform Davidson for ill-conditioned, non diagonally dominant problems.
Using AgMIP Regional Integrated Assessment Methods to Evaluate Vulnerability, Resilience and Adaptive Capacity for Climate Smart Agricultural Systems

The predicted effects of climate change call for a multi-dimensional method to assess the performance of various agricultural systems across economic, environmental and social dimensions. Climate smart agriculture (CSA) recognizes that the three goals of climate adaptation, mitigation and resilience must be integrated into the framework of a sustainable agricultural system. However, current methods to determine a systems’ ability to achieve CSA goals are lacking. This paper presents a new simulation-based method based on the Regional Integrated Assessment (RIA) methods developed by the Agricultural Model Inter-comparison and Improvement Project (AgMIP) for climate impact assessment. This method combines available data, field- and stakeholder-based surveys, biophysical and economic models, and future climate and socio-economic scenarios. It features an integrated farm and household approach and accounts for heterogeneity across biophysical and socioeconomic variables as well as temporal variability of climate indicators. This method allows for assessment of the technologies and practices of an agricultural system to achieve the three goals of CSA. The case study of a mixed crop livestock system in western Zimbabwe is highlighted as a typical smallholder agricultural systems in Africa.
A Systematic Review of Natural Language Processing Methods and Applications in Thyroidology

This study aimed to review the application of natural language processing (NLP) in thyroid-related conditions and to summarize current challenges and potential future directions. We performed a systematic search of databases for studies describing NLP applications in thyroid conditions published in English between January 1, 2012 and November 4, 2022. In addition, we used a snowballing technique to identify studies missed in the initial search or published after our search timeline until April 1, 2023. For included studies, we extracted the NLP method (eg, rule-based, machine learning, deep learning, or hybrid), NLP application (eg, identification, classification, and automation), thyroid condition (eg, thyroid cancer, thyroid nodule, and functional or autoimmune disease), data source (eg, electronic health records, health forums, medical literature databases, or genomic databases), performance metrics, and stages of development. We identified 24 eligible NLP studies focusing on thyroid-related conditions. Deep learning-based methods were the most common (38%), followed by rule-based (21%), and traditional machine learning (21%) methods. Thyroid nodules (54%) and thyroid cancer (29%) were the primary conditions under investigation. Electronic health records were the dominant data source (17/24, 71%), with imaging reports being the most frequently used (15/17, 88%). There is increasing interest in NLP applications for thyroid-related studies, mostly addressing thyroid nodules and using deep learning-based methodologies with limited external validation. However, none of the reviewed NLP applications have reached clinical practice. Several limitations, including inconsistent clinical documentation and model portability, need to be addressed to promote the evaluation and implementation of NLP applications to support patient care in thyroidology.