AndreaBozzo/ceres-open-data-index huggingface dataset:
Compound 528763: 4-(2,6,6-Trimethylcyclohexa-1,3-dien-1-YL)but-3-EN-2-one

Chemical compound data from PubChem database. IUPAC Name: 4-(2,6,6-trimethylcyclohexa-1,3-dien-1-yl)but-3-en-2-one. Molecular Formula: C13H18O. Molecular Weight: 190.28. This dataset contains comprehensive chemical information including structural data, physical properties, and biological activities. Useful for drug discovery, chemical research, and educational purposes.
Compound 527711: 2,3,4,6,7-Pentachlorodibenzofuran

Chemical compound data from PubChem database. IUPAC Name: 2,3,4,6,7-pentachlorodibenzofuran. Molecular Formula: C12H3Cl5O. Molecular Weight: 340.4. This dataset contains comprehensive chemical information including structural data, physical properties, and biological activities. Useful for drug discovery, chemical research, and educational purposes.
Automated Child Welfare Information System Options for Tribal Title IV-E Agencies

This Information Memorandum (IM) provides introductory information to title IV-E tribes that choose to develop and implement an automated Child Welfare Information System. This IM contains information about how an automated system can support a tribal title IV-E agency’s child welfare program, implementing and maintaining systems, title IV-E funding, and the Comprehensive Child Welfare Information System (CCWIS).

Metadata-only record linking to the original dataset. Open original dataset below.
Compound 526513: Butanedioic acid, isothiocyanato-, diethyl ester

Chemical compound data from PubChem database. IUPAC Name: diethyl 2-isothiocyanatobutanedioate. Molecular Formula: C9H13NO4S. Molecular Weight: 231.27. This dataset contains comprehensive chemical information including structural data, physical properties, and biological activities. Useful for drug discovery, chemical research, and educational purposes.
Abundant protein domains occur in proportion to proteome size

Background
          Conserved domains in proteins have crucial roles in protein interactions, DNA binding, enzyme activity and other important cellular processes. It will be of interest to determine the proportions of genes containing such domains in the proteomes of different eukaryotes.
        
        
          Results
          The average proportion of conserved domains in each of five eukaryote genomes was calculated. In pairwise genome comparisons, the ratio of genes containing a given conserved domain in the two genomes on average reflected the ratio of the predicted total gene numbers of the two genomes. These ratios have been verified using a repository of databases and one of its subdivisions of conserved domains.
        
        
          Conclusions
          Many conserved domains occur as a constant proportion of proteome size across the five sequenced eukaryotic genomes. This raises the possibility that this proportion is maintained because of functional constraints on interacting domains. The universality of the ratio in the five eukaryotic genomes attests to its potential importance.
NCHS - Drug Poisoning Mortality by County: United States

This dataset describes drug poisoning deaths at the U.S. and state level by selected demographic characteristics, and includes age-adjusted death rates for drug poisoning. 

Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent).

Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files (1). Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published.

Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD–10 codes for unintentional poisoning as R99, “Other ill-defined and unspecified causes of mortality” (2). For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Drug poisoning death rates may be underestimated in those instances.

REFERENCES
1. National Center for Health Statistics. National Vital Statistics System: Mortality data. Available from: http://www.cdc.gov/nchs/deaths.htm.

2. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html.
Trazodone hydrochloride oral

RALDESY is a prescription oral solution containing trazodone hydrochloride (10 mg/mL), a serotonin reuptake inhibitor used to treat major depressive disorder. Manufactured by Validus Pharmaceuticals LLC and approved under NDA218637, it comes in 150 mL and 300 mL bottles. This information was generated using AI and is provided for informational and research purposes only.
Compound 528385: Benzaldehyde, 3,4,6-trichloro-2-hydroxy

Chemical compound data from PubChem database. IUPAC Name: 3,4,6-trichloro-2-hydroxybenzaldehyde. Molecular Formula: C7H3Cl3O2. Molecular Weight: 225.5. This dataset contains comprehensive chemical information including structural data, physical properties, and biological activities. Useful for drug discovery, chemical research, and educational purposes.
Compound 525125: 1,3-Benzenedicarboxylic acid, diheptyl ester

Chemical compound data from PubChem database. IUPAC Name: diheptyl benzene-1,3-dicarboxylate. Molecular Formula: C22H34O4. Molecular Weight: 362.5. This dataset contains comprehensive chemical information including structural data, physical properties, and biological activities. Useful for drug discovery, chemical research, and educational purposes.
Compound 525689: p-Chlorobenzylidene-hexyl-amine

Chemical compound data from PubChem database. IUPAC Name: 1-(4-chlorophenyl)-N-hexylmethanimine. Molecular Formula: C13H18ClN. Molecular Weight: 223.74. This dataset contains comprehensive chemical information including structural data, physical properties, and biological activities. Useful for drug discovery, chemical research, and educational purposes.
NNDSS - TABLE 1K. Ehrlichiosis and Anaplasmosis, Anaplasma phagocytophilum infection to Ehrlichia chaffeensis infection

NNDSS - TABLE 1K. Ehrlichiosis and Anaplasmosis, Anaplasma phagocytophilum infection to Ehrlichia chaffeensis infection - 2022. In this Table, provisional cases* of notifiable diseases are displayed for United States, U.S. territories, and Non-U.S. residents.

Notes:

•	These are weekly cases of selected infectious national notifiable diseases, from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data reported by the 50 states, New York City, the District of Columbia, and the U.S. territories are collated and published weekly as numbered tables available at https://www.cdc.gov/nndss/data-statistics/index.html. Cases reported by state health departments to CDC for weekly publication are subject to ongoing revision of information and delayed reporting. Therefore, numbers listed in later weeks may reflect changes made to these counts as additional information becomes available. Case counts in the tables are presented as published each week. See also Guide to Interpreting Provisional and Finalized NNDSS Data at https://www.cdc.gov/nndss/docs/Readers-Guide-WONDER-Tables-20210421-508.pdf.
• Notices, errata, and other notes are available in the Notice To Data Users page at https://wonder.cdc.gov/nndss/NTR.html.
•	The list of national notifiable infectious diseases and conditions and their national surveillance case definitions are available at https://ndc.services.cdc.gov/. This list incorporates the Council of State and Territorial Epidemiologists (CSTE) position statements approved by CSTE for national surveillance.

Footnotes:

*Case counts for reporting years 2021 and 2022 are provisional and subject to change. Cases are assigned to the reporting jurisdiction submitting the case to NNDSS, if the case's country of usual residence is the U.S., a U.S. territory, unknown, or null (i.e. country not reported); otherwise, the case is assigned to the 'Non-U.S. Residents' category. Country of usual residence is currently not reported by all jurisdictions or for all conditions. For further information on interpretation of these data, see https://www.cdc.gov/nndss/docs/Readers-Guide-WONDER-Tables-20210421-508.pdf.
†Previous 52 week maximum and cumulative YTD are determined from periods of time when the condition was reportable in the jurisdiction (i.e., may be less than 52 weeks of data or incomplete YTD data).
U: Unavailable — The reporting jurisdiction was unable to send the data to CDC or CDC was unable to process the data.
-: No reported cases — The reporting jurisdiction did not submit any cases to CDC.
N: Not reportable — The disease or condition was not reportable by law, statute, or regulation in the reporting jurisdiction.
NN: Not nationally notifiable — This condition was not designated as being nationally notifiable.
NP: Nationally notifiable but not published.
NC: Not calculated — There is insufficient data available to support the calculation of this statistic.
Cum: Cumulative year-to-date counts.
Max: Maximum — Maximum case count during the previous 52 weeks.
Compound 528120: 2-Ethylthio-3-methyl-5-(2-methylpentyl)pyrazine

Chemical compound data from PubChem database. IUPAC Name: 2-ethylsulfanyl-3-methyl-5-(2-methylpentyl)pyrazine. Molecular Formula: C13H22N2S. Molecular Weight: 238.39. This dataset contains comprehensive chemical information including structural data, physical properties, and biological activities. Useful for drug discovery, chemical research, and educational purposes.
Compound 527204: 2-(4a,8-dimethyl-4,5,6,7,8,8a-hexahydro-3H-naphthalen-2-yl)propanal

Chemical compound data from PubChem database. IUPAC Name: 2-(4a,8-dimethyl-4,5,6,7,8,8a-hexahydro-3H-naphthalen-2-yl)propanal. Molecular Formula: C15H24O. Molecular Weight: 220.35. This dataset contains comprehensive chemical information including structural data, physical properties, and biological activities. Useful for drug discovery, chemical research, and educational purposes.
Blood and alveolar lymphocyte subsets in pulmonary cytomegalovirus infection after lung transplantation

Background
          Cytomegalovirus (CMV) pneumonitis has been shown to be associated with lymphocytic alveolitis after lung transplantation. In the present study, we investigated a series of bronchoalveolar (BAL) and blood samples, collected in the absence of rejection or acute infectious episodes. in order -1: to evaluate intra-alveolar cell population changes concomitant with CMV replication and -2: to reappraise the value of cell population analysis in the management of patients after lung transplantation.
        
        
          Methods
          We used flow cytometry to investigate modifications of lymphocyte subpopulations related to pulmonary cytomegalovirus infections in blood and BAL samples from a series of 13 lung transplant recipients. After exclusion of samples obtained during pulmonary rejection, bronchiolitis obliterans or acute bacterial infection, 48 blood and BAL samples were retained for analysis: 17 were CMV positive by shell-vial assay and 31 were CMV negative in blood and BAL.
        
        
          Results
          Our results demonstrate that pulmonary CMV infection is associated with a significant increase in the total lymphocyte population in BAL samples, but with minor modifications of the various lymphocyte subpopulations and a significantly higher absolute number of B lymphocytes in blood samples.
        
        
          Conclusions
          Cytomegalovirus pulmonary infection is accompanied by only minor changes in BAL lymphocyte subpopulations. The study of BAL lymphocyte subpopulations therefore appears to be of limited clinical value in the diagnosis of pulmonary CMV infection. However, increased blood B-lymphocytes seems to be a clinical feature associated with CMV infection.
The effect of massage on localized lumbar muscle fatigue

Background
          There is not enough evidence to support the efficacy of massage for muscle fatigue despite wide utilization of the modality in various clinical settings. This study investigated the influence of massage application on localized back muscle fatigue.
        
        
          Methods
          Twenty-nine healthy subjects participated in two experimental sessions (massage and rest conditions). On each test day, subjects were asked to lie in the prone position on a treatment table and perform sustained back extension for 90 seconds. Subjects then either received massage on the lumbar region or rested for a 5 minute duration, then repeated the back extension movement. The median frequency (MDF), mean power frequency (MNF), and root mean square (RMS) amplitude of electromyographic signals during the 90 second sustained lumbar muscle contraction were analyzed. The subjective feeling of fatigue was then evaluated using the Visual Analogue Scale (VAS).
        
        
          Results
          MDF and MNF significantly declined with time under all conditions. There was no significant difference in MDF, MNF or RMS value change between before and after massage, or between rest and massage conditions. There was a significant increase in fatigue VAS at the end of the 2nd back extension with rest condition. There was a significant difference in fatigue VAS change between massage and rest condition.
        
        
          Conclusions
          A significant difference was observed between massage and rest condition on VAS for muscle fatigue. On EMG analysis, there were no significant differences to conclude that massage stimulation influenced the myoelectrical muscle fatigue, which is associated with metabolic and electrical changes.
Encouraging good antimicrobial prescribing practice: A review of antibiotic prescribing policies used in the South East Region of England

Background
          Good prescribing practice has an important part to play in the fight against antimicrobial resistance. Whilst it was perceived that most hospitals and Health Authorities possessed an antibiotic policy, a review of antibiotic policies was conducted to gain an understanding of the extent, quality and usefulness of these policies.
        
        
          Methods
          Letters were sent to pharmacists in hospitals and health authorities in across the South East region of the National Health Service Executive (NHSE) requesting antibiotic policies. data were extracted from the policies to assess four areas; antibiotic specific, condition specific, patient specific issues and underpinning evidence.
        
        
          Results
          Of a possible 41 hospital trusts and 14 health authorities, 33 trusts and 9 health authorities (HAs) provided policies. Both trust and HA policies had a median publication date of 1998 (trust range 1993-99, HA 1994-99). Eleven policies were undated. The majority of policies had no supporting references for the statements made. All policies provided some details on specific antibiotics. Gentamicin and ciprofloxacin were the preferred aminoglycoside and quinolone respectively with cephalosporins being represented by cefuroxime or cefotaxime in trusts and cephradine or cephalexin in HAs. 26 trusts provided advice on surgical prophylaxis, 17 had meningococcal prophylaxis policies and 11 covered methicillin resistant Staphylococcus aureus (MRSA). There was little information for certain groups such as neonates or children, the pregnant or the elderly.
        
        
          Conclusion
          There was considerable variation in content and quality across policies, a clear lack of an evidence base and a need to revise policies in line with current recommendations.
The ESAT-6 gene cluster of

Background
          The genome of Mycobacterium tuberculosis H37Rv has five copies of a cluster of genes known as the ESAT-6 loci. These clusters contain members of the CFP-10 (lhp) and ESAT-6 (esat-6) gene families (encoding secreted T-cell antigens that lack detectable secretion signals) as well as genes encoding secreted, cell-wall-associated subtilisin-like serine proteases, putative ABC transporters, ATP-binding proteins and other membrane-associated proteins. These membrane-associated and energy-providing proteins may function to secrete members of the ESAT-6 and CFP-10 protein families, and the proteases may be involved in processing the secreted peptide.
        
        
          Results
          Finished and unfinished genome sequencing data of 98 publicly available microbial genomes has been analyzed for the presence of orthologs of the ESAT-6 loci. The multiple duplicates of the ESAT-6 gene cluster found in the genome of M. tuberculosis H37Rv are also conserved in the genomes of other mycobacteria, for example M. tuberculosis CDC1551, M. tuberculosis 210, M. bovis, M. leprae, M. avium, and the avirulent strain M. smegmatis. Phylogenetic analyses of the resulting sequences have established the duplication order of the gene clusters and demonstrated that the gene cluster known as region 4 (Rv3444c-3450c) is ancestral. Region 4 is also the only region for which an ortholog could be found in the genomes of Corynebacterium diphtheriae and Streptomyces coelicolor.
        
        
          Conclusions
          Comparative genomic analysis revealed that the presence of the ESAT-6 gene cluster is a feature of some high-G+C Gram-positive bacteria. Multiple duplications of this cluster have occurred and are maintained only within the genomes of members of the genus Mycobacterium.
Compound 525755: Dipropyloxyhexyloxymethylsilane

Chemical compound data from PubChem database. IUPAC Name: hexoxy-methyl-dipropoxysilane. Molecular Formula: C13H30O3Si. Molecular Weight: 262.46. This dataset contains comprehensive chemical information including structural data, physical properties, and biological activities. Useful for drug discovery, chemical research, and educational purposes.
NSDUH 2021 Editing And Imputation Report

Learn about the editing and statistical imputation procedures that were applied to respondent data for the 2021 National Survey on Drug Use and Health (NSDUH). Logical editing resolves inconsistencies or ambiguous data based on a respondent’s answers to other questions in the survey. Statistical imputation uses mathematical techniques to assign values when they are missing in the data.Introductory Chapters:An introduction, including a discussion of changes from the 2020 to 2021 survey.A description of the procedures and general principles for editing the NSDUH data.A description of the general imputation procedures used in NSDUH.Remaining chapters are descriptions of the editing and imputation for the following types of variables:Front-end demographics.Back-end demographics.Substance use.Special drugs and substance use disorder.Additional substance use, including treatment and emerging issues.Substance use risk and protective factors.Physical and mental health.Roster variables.Income.Health insurance.Pair variables.
An international survey of patients with thalassemia major and their views about sustaining life-long desferrioxamine use

Background
          Management of thalassemia major requires patients to have life-long access to a treatment regimen of regular blood transfusions coupled with iron chelation therapy. The objective of this study was to investigate patients' reasons for missing iron chelation therapy with desferrioxamine, and the support to sustain life-long adherence to treatment.
        
        
          Methods
          From October 1999 to May 2000 a survey of patients with thalassemia major was conducted in ten countries: Cyprus, Egypt, Greece, Hong Kong, India, Iran, Italy, Jordan, Taiwan, and the United States.
        
        
          Results
          1,888 questionnaires (65%) were returned. Most patients (1,573) used desferrioxamine, and 79% administered a dose at least 4 days a week. Inaccessibility of the drug was a common reason for missing a dose in India (51%), and in Iran (25%), whereas, in any other country, it was a reason for less than 17% of patients. Overall, 58% reported reasons for missing a dose related to their beliefs or feelings about the medication, and 42% drug-related side effects.
        
        
          Conclusion
          Many patients miss doses of desferrioxamine and an opportunity remains to develop interventions that provide more support to sustain use of desferrioxamine.
Adult Hospital Inpatient Sepsis Performance Measures and Mortality by Facility: 2015 and 2016

Sepsis is defined as a clinical syndrome in which patients have an infection that is accompanied by an extreme systemic response. Sepsis of sufficient severity that the function of major organ systems in the body (such as heart, kidney, brain, and others) is impaired is referred to as “severe sepsis.” Patients with severe sepsis that have continued organ system impairment and/or low blood pressure that does not respond to treatment with adequate fluid replacement are considered to be in “septic shock.”  The combination of early detection of sepsis coupled with timely, appropriate interventions can significantly improve the chances of survival for patients with all types of sepsis.

The datasets contain hospital-level treatment measures and hospital-level risk-adjusted mortality rates for adult patients, with a diagnosis of severe sepsis or septic shock seen at New York State Article 28 (acute care) facilities and reported to the New York State Department of Health in 2015 and 2016.

The treatment measures and risk adjusted mortality rates are presented by hospital.  Only hospital level measure data for which there were at least ten cases in the denominator is reported.  Statewide measures are calculated using all hospitals, regardless of the number of sepsis cases treated.