The Impact of Micro Factors on the Performance of the Iraq Stock Exchange Index for the Period 2005-2021

Purpose:  The purpose of this study is to determine the impact of some micro factors (liquidity and profitability factors) of the Iraqi banking sector in determining the return of the stock market represented by the return of the Iraqi financial market index using time series analysis according to the ARDL methodology for the period 2005-2021.   Design/methodology/approach:  The study adopted an econometrics analysis of time series using the ARDL (auto-regressive distributed lag) methodology for the period 2005-2021 to investigate the impact of some micro factors (liquidity and profitability ratios) in Iraqi banking sector listed in Iraq stock exchange market on market return (Iraq Stock Exchange Index as a benchmark).   Findings:  The results of this study reveal significant effects of the financial factors for micro factor on the Iraqi Stock Exchange index. It is interesting that the variables of banking liquidity showed a stronger logical relationship with the dependent variable in line with financial theory than the variables of banking profitability. The relationship between the micro factors model and the financial market index required a long-term adjustment equivalent to (0.2124) of the time needed to adjust to the balanced state according to the error correction equation.   Research, Practical & Social implications: These results confirm the importance of taking into account micro-financial factors when making financing and investment decisions, as well as when evaluating the economic situation in the Iraqi banking sector. Understanding the impact of these factors and their relationships contributes to decision-making and enhances general forecasting of future economic volatility and risk management.   Originality/value:  This study provides valuable insights into the dynamics of the Iraqi financial market and highlights the importance of incorporating micro-financial factors into financial analyzes and investment strategies. The study recommends that future research should explore the complex links between macroeconomic factors and the financial market to gain a comprehensive understanding of the economic environment

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

Infection and mortality of healthcare workers worldwide from COVID-19:A systematic review

Objectives To estimate COVID-19 infections and deaths in healthcare workers (HCWs) from a global perspective during the early phases of the pandemic. Design Systematic review. Methods Two parallel searches of academic bibliographic databases and grey literature were undertaken until 8 May 2020. Governments were also contacted for further information where possible. There were no restrictions on language, information sources used, publication status and types of sources of evidence. The AACODS checklist or the National Institutes of Health study quality assessment tools were used to appraise each source of evidence. Outcome measures Publication characteristics, country-specific data points, COVID-19-specific data, demographics of affected HCWs and public health measures employed. Results A total of 152 888 infections and 1413 deaths were reported. Infections were mainly in women (71.6%, n=14 058) and nurses (38.6%, n=10 706), but deaths were mainly in men (70.8%, n=550) and doctors (51.4%, n=525). Limited data suggested that general practitioners and mental health nurses were the highest risk specialities for deaths. There were 37.2 deaths reported per 100 infections for HCWs aged over 70 years. Europe had the highest absolute numbers of reported infections (119 628) and deaths (712), but the Eastern Mediterranean region had the highest number of reported deaths per 100 infections (5.7). Conclusions COVID-19 infections and deaths among HCWs follow that of the general population around the world. The reasons for gender and specialty differences require further exploration, as do the low rates reported in Africa and India. Although physicians working in certain specialities may be considered high risk due to exposure to oronasal secretions, the risk to other specialities must not be underestimated. Elderly HCWs may require assigning to less risky settings such as telemedicine or administrative positions. Our pragmatic approach provides general trends, and highlights the need for universal guidelines for testing and reporting of infections in HCWs. © Author(s) (or their employer(s)) 2020

Infection and mortality of healthcare workers worldwide from COVID-19: a systematic review

To estimate COVID-19 infections and deaths in healthcare workers (HCWs) from a global perspective during the early phases of the pandemic. Systematic review. Two parallel searches of academic bibliographic databases and grey literature were undertaken until 8 May 2020. Governments were also contacted for further information where possible. There were no restrictions on language, information sources used, publication status and types of sources of evidence. The AACODS checklist or the National Institutes of Health study quality assessment tools were used to appraise each source of evidence. Publication characteristics, country-specific data points, COVID-19-specific data, demographics of affected HCWs and public health measures employed. A total of 152 888 infections and 1413 deaths were reported. Infections were mainly in women (71.6%, n=14 058) and nurses (38.6%, n=10 706), but deaths were mainly in men (70.8%, n=550) and doctors (51.4%, n=525). Limited data suggested that general practitioners and mental health nurses were the highest risk specialities for deaths. There were 37.2 deaths reported per 100 infections for HCWs aged over 70 years. Europe had the highest absolute numbers of reported infections (119 628) and deaths (712), but the Eastern Mediterranean region had the highest number of reported deaths per 100 infections (5.7). COVID-19 infections and deaths among HCWs follow that of the general population around the world. The reasons for gender and specialty differences require further exploration, as do the low rates reported in Africa and India. Although physicians working in certain specialities may be considered high risk due to exposure to oronasal secretions, the risk to other specialities must not be underestimated. Elderly HCWs may require assigning to less risky settings such as telemedicine or administrative positions. Our pragmatic approach provides general trends, and highlights the need for universal guidelines for testing and reporting of infections in HCWs

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

The Gene Ontology knowledgebase in 2023.

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

The Gene Ontology Knowledgebase in 2023

: The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and non-coding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains and updates the GO knowledgebase. The GO knowledgebase consists of three components: 1) the Gene Ontology - a computational knowledge structure describing functional characteristics of genes; 2) GO annotations - evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and 3) GO Causal Activity Models (GO-CAMs) - mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised and updated in response to newly published discoveries, and receives extensive QA checks, reviews and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, as well as guidance on how users can best make use of the data we provide. We conclude with future directions for the project

BJS commission on surgery and perioperative care post-COVID-19

Background: Coronavirus disease 2019 (COVID-19) was declared a pandemic by the WHO on 11 March 2020 and global surgical practice was compromised. This Commission aimed to document and reflect on the changes seen in the surgical environment during the pandemic, by reviewing colleagues experiences and published evidence. Methods: In late 2020, BJS contacted colleagues across the global surgical community and asked them to describe how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had affected their practice. In addition to this, the Commission undertook a literature review on the impact of COVID-19 on surgery and perioperative care. A thematic analysis was performed to identify the issues most frequently encountered by the correspondents, as well as the solutions and ideas suggested to address them. Results: BJS received communications for this Commission from leading clinicians and academics across a variety of surgical specialties in every inhabited continent. The responses from all over the world provided insights into multiple facets of surgical practice from a governmental level to individual clinical practice and training. Conclusion: The COVID-19 pandemic has uncovered a variety of problems in healthcare systems, including negative impacts on surgical practice. Global surgical multidisciplinary teams are working collaboratively to address research questions about the future of surgery in the post-COVID-19 era. The COVID-19 pandemic is severely damaging surgical training. The establishment of a multidisciplinary ethics committee should be encouraged at all surgical oncology centres. Innovative leadership and collaboration is vital in the post-COVID-19 era