Interviews were conducted by trained research staff in a private setting and data were recorded anonymously, unaccompanied by any unique identifiers. Subjects were first asked the single screening question, “How many times in the past year have you used an illegal drug or used a prescription medication for non-medical reasons?” (where a response of ≥1 is considered positive). If asked to clarify the meaning of “non-medical reasons”, the research associate added "for instance because of the experience or feeling it caused”. After subjects responded to the single screening question, they were asked if they had ever experienced any of a list of problems related to drug use. For this we modified the previously described Short Inventory of Problems-Alcohol and Drug (SIP-AD) questionnaire, which asks about problems ever experienced in the subject’s lifetime related to alcohol or drug use8 (link). We modified this by eliminating the word alcohol from the questions, a modification we hereafter refer to as the Short Inventory of Problems- Drug Use (SIP-DU). In a separate analysis (but in these subjects) we determined the reliability and validity of the SIP-DU as a measure of drug use consequences 9 . The computerized version of the Composite International Diagnostic Interview (CIDI) Substance Abuse Module was used for the assessment of current (12-month) drug use disorders 10 . This structured interview yields a Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) diagnosis of drug abuse or dependence. In addition, as part of the CIDI, subjects were asked detailed questions about current (past year) use of illicit drugs (marijuana, cocaine, heroin, stimulants or hallucinogens) and non-medical use of prescription drugs. Following the interview subjects were asked to undergo oral fluid testing for the presence of common drugs of abuse (opiates, benzodiazepines, cocaine, methamphetamines, tetrahydrocannabinol (THC). Once collected, oral fluid was sent to an outside laboratory for analysis using methodology that yields results comparable to urine drug screening (Intercept™ immunoassay, OraSure Technologies, Bethlehem, PA)11 (link)–14 (link). In order to aid in the interpretation of drug test results subjects had been asked, as part of the interview, if they had recently been prescribed any drugs from a list of opiates or benzodiazepines. Because this question was added to the questionnaire during the study, responses were missing from 23 subjects who underwent oral fluid testing. Subjects were not told that they would be asked to undergo drug testing until the interview was complete. After completing the interview, they were compensated and thanked for their participation. They were then asked to undergo oral fluid testing and a second informed consent process was completed. Following the single drug screening question, but before the other assessments, the 10-item Drug Abuse Screening Test (DAST-10) was administered for comparison 4 (link). As part of a parallel study on screening for unhealthy alcohol use, subjects were also asked a single alcohol screening question (preceding the drug screening question), two other brief alcohol screening questionnaires and a calendar based assessment of past-month alcohol consumption (all after the drug screen and prior to the CIDI) 7 (link).
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Organic Chemical
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Benzodiazepines
Benzodiazepines
Benzodiazepines are a class of psychoactive drugs widely used for their sedative, anxiolytic, anticonvulsant, and muscle relaxant properties.
These compounds act on the gamma-aminobutyric acid (GABA) receptors in the brain, enhancing the inhibitory effects of GABA and producing a calming effect.
Benzodiazepines are commonly prescribed for the treatment of anxiety disorders, insomnia, seizures, and alcohol withdrawal.
However, they also carry a risk of dependence and abuse.
Ongoing research aims to explore new therapeutic applications, optimize dosing regimens, and develop safer alternatives for benzodiazepine use.1
These compounds act on the gamma-aminobutyric acid (GABA) receptors in the brain, enhancing the inhibitory effects of GABA and producing a calming effect.
Benzodiazepines are commonly prescribed for the treatment of anxiety disorders, insomnia, seizures, and alcohol withdrawal.
However, they also carry a risk of dependence and abuse.
Ongoing research aims to explore new therapeutic applications, optimize dosing regimens, and develop safer alternatives for benzodiazepine use.1
Most cited protocols related to «Benzodiazepines»
Alcohol Problem
Benzodiazepines
Cannabis sativa
Central Nervous System Stimulants
Cocaine
Diagnosis
Dronabinol
Drug Use Disorders
Ethanol
Hallucinogens
Heroin
Illicit Drugs
Immunoassay
Methamphetamine
Opiate Alkaloids
Pharmaceutical Preparations
Substance Abuse
Substance Abuse Detection
Urine
Anesthesiologist
Benzodiazepines
Complete Blood Count
Electrocardiogram
Electrolytes
Infusion Pump
Intravenous Infusion
Ketamine
Ketamine Hydrochloride
Lithium
Liver Function Tests
Major Depressive Disorder
N-Methylaspartate
Normal Saline
Oximetry
Patients
Pharmaceutical Preparations
Placebos
Psychotherapy
Psychotropic Drugs
Safety
Saline Solution
Signs, Vital
Syringes
Valproate
Visually Impaired Persons
Anesthesia
Anesthesiologist
Benzodiazepines
Depression, Bipolar
Electrolytes
Infusion Pump
Intravenous Infusion
Ketamine
Ketamine Hydrochloride
Lithium
Liver Function Tests
N-Methylaspartate
Normal Saline
Oximetry
Patients
Pharmaceutical Preparations
Placebos
Psychotherapy
Psychotropic Drugs
Safety
Saline Solution
Signs, Vital
Syringes
Valproate
Visually Impaired Persons
ACSS2 protein, human
Antidepressive Agents
Anxiety Disorders
Benzodiazepines
CREB3L1 protein, human
Diagnosis
Eligibility Determination
Ethanol
Face
Generic Drugs
Mental Health
Minority Groups
Patients
Pharmaceutical Preparations
Physicians
Pneumocystosis
Psychiatrist
Psychologist
Psychotherapy
Relapse Prevention
SNRIs
Supervision
All analyses were performed using SAS version 9.2 (SAS Institute, Cary, NC), and we used a two tailed P value of less than 0.05 to define statistical significance. We initially used descriptive statistics to characterise the cohort for patterns of post-discharge opioid use. To compare the characteristics of patients who did or did not exhibit prolonged opioid use after discharge we also used bivariate tests (two sample t test, Mann-Whitney U test, χ2 test, Fisher exact test).
We used multivariable logistic regression modelling to determine the adjusted association of prolonged opioid use after discharge (≥1 prescriptions within 1-90 days after surgery along with ≥1 prescriptions within 91-180 days after surgery) with age (categorised as 66-75, 76-85, and ≥86 years), sex, surgery, fifth of neighbourhood income, rural residence, comorbidities (coronary artery disease, heart failure, cerebrovascular disease, peripheral vascular disease, diabetes, hypertension, pulmonary disease, chronic renal insufficiency, malignancy), and preoperative drug use (β blockers, ACE inhibitors, angiotensin receptor blockers, statins, benzodiazepines, SSRIs). All predictor variables were included simultaneously in the multivariable regression model. In the primary analysis, we included all participants in the cohort regardless of whether they survived up to 180 days after surgery. In a sensitivity analysis, we repeated the analyses after restricting the cohort to only those who survived at least 180 days after surgery.
We used multivariable logistic regression modelling to determine the adjusted association of prolonged opioid use after discharge (≥1 prescriptions within 1-90 days after surgery along with ≥1 prescriptions within 91-180 days after surgery) with age (categorised as 66-75, 76-85, and ≥86 years), sex, surgery, fifth of neighbourhood income, rural residence, comorbidities (coronary artery disease, heart failure, cerebrovascular disease, peripheral vascular disease, diabetes, hypertension, pulmonary disease, chronic renal insufficiency, malignancy), and preoperative drug use (β blockers, ACE inhibitors, angiotensin receptor blockers, statins, benzodiazepines, SSRIs). All predictor variables were included simultaneously in the multivariable regression model. In the primary analysis, we included all participants in the cohort regardless of whether they survived up to 180 days after surgery. In a sensitivity analysis, we repeated the analyses after restricting the cohort to only those who survived at least 180 days after surgery.
Angiotensin-Converting Enzyme Inhibitors
Angiotensin Receptor Antagonists
Benzodiazepines
Cerebrovascular Disorders
Chronic Kidney Insufficiency
Congestive Heart Failure
Coronary Artery Disease
Diabetes Mellitus
High Blood Pressures
Hydroxymethylglutaryl-CoA Reductase Inhibitors
Hypersensitivity
Lung Diseases
Malignant Neoplasms
Operative Surgical Procedures
Opioids
Patient Discharge
Patients
Peripheral Vascular Diseases
Pharmaceutical Preparations
Prescriptions
Selective Serotonin Reuptake Inhibitors
Most recents protocols related to «Benzodiazepines»
Example 6
The following example provides details of a study used to determine whether alprazolam-induced changes in subjective experience during psilocybin therapy are due to changes in 5-HT2A occupancy. If not, downstream molecular and cellular effects that may be important in psilocybin's therapeutic effects may be preserved after co-treatment with a benzodiazepine.
In this study, [11C]CIMBI-36 (a selective 5-HT2A receptor agonist positron emission tomography (PET) radioligand) will be used to investigate whether 5-HT2A binding is affected by placebo vs. alprazolam.
At time t=0, subjects will be administered 25 mg psilocybin (PSI) in combination with either a placebo, or alprazolam. At t=2 hours, subjects will be given a tracer dose of [11C]CIMBI-36. At t=2-3 hours, a PET scan will be performed, to determine whether 5-HT2A binding is affected by either dose of alprazolam.
This study may optionally be performed using diazepam instead of alprazolam.
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Alprazolam
Benzodiazepines
Cells
Cimbi-36
Diazepam
Placebos
Positron-Emission Tomography
Psilocybin
Therapeutic Effect
Participants ranged in age from 25 to 58 (mean age 41). Their current living situation was reported as either currently homeless (38%), supported housing (50%), private rented accommodation (6%) and 6% were vulnerably housed in unsuitable accommodation.
Primary presenting substance misuse was reported as opiates (74%), alcohol (13%), and benzodiazepines (13%). Self-identified poor mental health was characterised as suffering from long term depression and anxiety, and 100% had trouble sleeping. 63% of participants reported suicidal ideation within the past 12 months. 25% reported that they had ever been admitted to a psychiatric facility. A minority had psychiatric diagnoses (6%) which were reported as schizophrenia and personality disorder.
Within the previous 12 months, 56% had accessed housing support services, 56% had used substance misuse services, 38% had accessed support for domestic abuse and 25% had accessed mental health support. Fifty percent had visited their GP at least once. Significant acute healthcare use was reported, with at least 18 individual admissions to A&E reported within the group in the previous 12 months.
Primary presenting substance misuse was reported as opiates (74%), alcohol (13%), and benzodiazepines (13%). Self-identified poor mental health was characterised as suffering from long term depression and anxiety, and 100% had trouble sleeping. 63% of participants reported suicidal ideation within the past 12 months. 25% reported that they had ever been admitted to a psychiatric facility. A minority had psychiatric diagnoses (6%) which were reported as schizophrenia and personality disorder.
Within the previous 12 months, 56% had accessed housing support services, 56% had used substance misuse services, 38% had accessed support for domestic abuse and 25% had accessed mental health support. Fifty percent had visited their GP at least once. Significant acute healthcare use was reported, with at least 18 individual admissions to A&E reported within the group in the previous 12 months.
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Anxiety
Benzodiazepines
Diagnosis, Psychiatric
Drug Abuse
Ethanol
Mental Health
Minority Groups
Ocular Accommodation
Opiate Alkaloids
Personality Disorders
Persons, Homeless
Schizophrenia
Data for this study were drawn from two open prospective cohort studies of PWUD in Vancouver, Canada: the Vancouver Injection Drug Users Study (VIDUS) and the AIDS Care Cohort to evaluate Exposure to Survival Services (ACCESS). Both cohorts have been described in detail in previous literature [24 (link), 27 (link)]. However, to briefly summarize, these cohorts have been recruiting participants through community-based methods, including street outreach, self-referral, and word of mouth since May of 1996. VIDUS includes adults (18 years and older) who are HIV-negative and have injected unregulated drugs within the month prior to their enrolment. ACCESS participants are HIV-positive adults who used any unregulated substance (other than or in addition to cannabis) within the month prior to their enrolment. Participants in the VIDUS cohort who HIV seroconvert after their enrolment are transferred to the ACCESS cohort. All participants provided written informed consent at enrolment and ethics has been approved by Providence Health Care/University of British Columbia’s Research Ethics Board. Both cohorts use harmonized study protocols to facilitate pooled analyses.
At baseline and at 6-month intervals afterwards, participants complete interviewer- and nurse-led questionnaires and provide blood samples for serology, as well as urine for drug screening. The questionnaire covers a variety of topics including demographics, substance use, healthcare access, and socio-structural exposures. To compensate participants for their involvement, participants receive a $40 CAD stipend for every study visit.
Due to the COVID-19 pandemic, all in-person data collection was suspended between March 2020 and July 2020. After July 2020, infection control measures were put in place to resume data collection. Participant interviews were completed over telephone or videoconferencing. Study-owned cell phones and private spaces were loaned to those who required them. They were then able to pick up their cash honoraria in person or have it e-transferred if they had access to a bank account.
Between March and July of 2020, study questionnaires were modified to include questions regarding the COVID-19 pandemic. One of these questions was used to assess the primary outcome of this study, which read as follows: “Has the frequency of your use of these sites [i.e., SCS/OPS] changed since the beginning of the public health emergency?”. The outcome was dichotomized using the following responses: “I use them less” vs. “I use them more” or “My use stayed the same”. Potential correlates were identified based on past studies that assessed SCS access among PWUD [8 (link), 25 (link)], and included: age (per year older), self-identified gender (man vs. woman/other), ethnicity/ancestry (white vs. Black, Indigenous, and people of colour), education (high school or greater vs. other), employment (yes vs. no), residence in Downtown Eastside neighbourhood in Vancouver (yes vs. no), daily non-medical prescription opioid use (yes vs. no), daily cocaine use (yes vs. no), daily crystal methamphetamine use (yes vs. no), daily non-injection crack-cocaine use (yes vs. no), benzodiazepine use (yes vs. no), suspected that a drug used contained fentanyl (yes vs. no), used drugs alone (yes vs. no), engagement in opioid agonist therapy (yes vs. no), non-fatal overdose (yes vs. no), witnessed an overdose (yes vs. no), experience physical violence (yes vs. no), syringe/ drug use equipment sharing (yes vs. no), inability to access treatment (yes vs. no), unstable housing (yes vs. no), sex work (yes vs. no), incarceration (yes vs. no), jacked up (this refers to being stopped, searched, or detained) by the police (yes vs. no), cohort/ HIV status (ACCESS vs. VIDUS), ever tested positive for COVID-19 (yes vs. no), concern about COVID-19 on a scale from 1 to 10, with 10 indicating greatest concern (1–5 vs. 6–10), any chronic health conditions (yes vs. no), and ease of accessing SCS/OPS changed since COVID-19 (same vs. easier vs. harder). All drug use and behavioral variables refer to the 6 months prior to questionnaire date unless otherwise indicated.
Univariable and multivariable logistic regression analyses were used to assess the associations between the correlates of interest and reduced frequency of SCS/OPS use since COVID-19. Correlates of interest with a univariable p-value < 0.10 were included in a backward elimination procedure, with the least significant variable removed at each step until the lowest Akaike Information Criterion (AIC) was achieved. All p-values were two-sided and all statistical analyses were conducted using SAS version 9.4 (SAS Institute, Cary, North Carolina, United States).
At baseline and at 6-month intervals afterwards, participants complete interviewer- and nurse-led questionnaires and provide blood samples for serology, as well as urine for drug screening. The questionnaire covers a variety of topics including demographics, substance use, healthcare access, and socio-structural exposures. To compensate participants for their involvement, participants receive a $40 CAD stipend for every study visit.
Due to the COVID-19 pandemic, all in-person data collection was suspended between March 2020 and July 2020. After July 2020, infection control measures were put in place to resume data collection. Participant interviews were completed over telephone or videoconferencing. Study-owned cell phones and private spaces were loaned to those who required them. They were then able to pick up their cash honoraria in person or have it e-transferred if they had access to a bank account.
Between March and July of 2020, study questionnaires were modified to include questions regarding the COVID-19 pandemic. One of these questions was used to assess the primary outcome of this study, which read as follows: “Has the frequency of your use of these sites [i.e., SCS/OPS] changed since the beginning of the public health emergency?”. The outcome was dichotomized using the following responses: “I use them less” vs. “I use them more” or “My use stayed the same”. Potential correlates were identified based on past studies that assessed SCS access among PWUD [8 (link), 25 (link)], and included: age (per year older), self-identified gender (man vs. woman/other), ethnicity/ancestry (white vs. Black, Indigenous, and people of colour), education (high school or greater vs. other), employment (yes vs. no), residence in Downtown Eastside neighbourhood in Vancouver (yes vs. no), daily non-medical prescription opioid use (yes vs. no), daily cocaine use (yes vs. no), daily crystal methamphetamine use (yes vs. no), daily non-injection crack-cocaine use (yes vs. no), benzodiazepine use (yes vs. no), suspected that a drug used contained fentanyl (yes vs. no), used drugs alone (yes vs. no), engagement in opioid agonist therapy (yes vs. no), non-fatal overdose (yes vs. no), witnessed an overdose (yes vs. no), experience physical violence (yes vs. no), syringe/ drug use equipment sharing (yes vs. no), inability to access treatment (yes vs. no), unstable housing (yes vs. no), sex work (yes vs. no), incarceration (yes vs. no), jacked up (this refers to being stopped, searched, or detained) by the police (yes vs. no), cohort/ HIV status (ACCESS vs. VIDUS), ever tested positive for COVID-19 (yes vs. no), concern about COVID-19 on a scale from 1 to 10, with 10 indicating greatest concern (1–5 vs. 6–10), any chronic health conditions (yes vs. no), and ease of accessing SCS/OPS changed since COVID-19 (same vs. easier vs. harder). All drug use and behavioral variables refer to the 6 months prior to questionnaire date unless otherwise indicated.
Univariable and multivariable logistic regression analyses were used to assess the associations between the correlates of interest and reduced frequency of SCS/OPS use since COVID-19. Correlates of interest with a univariable p-value < 0.10 were included in a backward elimination procedure, with the least significant variable removed at each step until the lowest Akaike Information Criterion (AIC) was achieved. All p-values were two-sided and all statistical analyses were conducted using SAS version 9.4 (SAS Institute, Cary, North Carolina, United States).
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Abuse, Physical
Acquired Immunodeficiency Syndrome
Adult
Benzodiazepines
BLOOD
Cannabis
Chronic Condition
Cocaine
COVID 19
Crack Cocaine
Drug Abuser
Drug Overdose
Emergencies
Ethnicity
Fentanyl
Gender
Infection Control
Interviewers
Methamphetamine
Nurses
Opioids
Oral Cavity
Pharmaceutical Preparations
Substance Use
Urine
Woman
We identified the following potential confounders a priori using directed acyclic graphs28 (link): age at pregnancy, primiparous, marital status, smoking during pregnancy, and Charlson Comorbidity Index (calculated based on 19 conditions; definition in the eMethods in Supplement 1 ). We used a history of self-harm (definition in the eMethods in Supplement 1 ) and psychiatric diagnoses at any time before pregnancy, including schizophrenia, bipolar disorder, depression, other mood disorders, and others (International Classification of Diseases, Eighth Revision [ICD-8] and Tenth Revision [ICD-10] codes listed in eTable 2 in Supplement 1 ); number of psychiatric emergencies; and coprescribed medications (opioid analgesics, antiseizure medications, antipsychotics, benzodiazepine/z-hypnotics, or anxiolytics; ATC codes listed in eTable 3 in Supplement 1 ) in the 6 months before pregnancy as a proxy for disease severity. In addition, we included filling prescriptions for 2 or more classes of antidepressants and having an average daily dose of an antidepressant greater than 1 fluoxetine dose equivalent (ie, 40 mg fluoxetine)29 (link) in the 6 months before pregnancy as an additional proxy of the severity of mental illnesses.
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Analgesics, Opioid
Anti-Anxiety Agents
Antidepressive Agents
Antipsychotic Agents
Benzodiazepines
Bipolar Disorder
Diagnosis, Psychiatric
Dietary Supplements
Emergencies
Fluoxetine
Hypnotics
Mood Disorders
Pharmaceutical Preparations
Pregnancy
Prescriptions
Schizophrenia
The study was approved by the Brandeis University institutional review board and was deemed exempt for the need for informed consent by the Washington State Department of Social and Health Services institutional review board because the data were deidentified, in accordance with 45 CFR §46. The report follows the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE ) reporting guideline for case-control studies. We examined Medicaid outpatient, inpatient, residential, and pharmacy claims from Washington State for 2016 to 2019. Using a clinically driven approach, we captured people who may not have been administratively deemed to have a disability for access to income supports and Medicaid, but who had reached a clinical threshold for diagnosis. Washington is a Medicaid expansion state, with a full continuum of SUD care, including all types of MOUD. For each year, we included adults aged 18 to 64 years with an OUD diagnosis who were continuously eligible for full Medicaid benefits for 12 months, to observe full service use. We defined OUD as at least 1 claim for outpatient, inpatient, or residential services with an OUD diagnosis code in a calendar year (eTable 1 in Supplement 1 ). We excluded 2587 people eligible for both Medicare and Medicaid because Medicare services were unobservable, 1132 people with a benzodiazepine prescription during the same year because concurrent MOUD is associated with increased risk of adverse effects,23 (link) and 132 people because prescription days supply was missing (eFigure in Supplement 1 ). Analyses of MOUD treatment continuity required continuous 6 months of data following the first evidence of MOUD, requiring a look back for claims occurring in the first week of the year to see whether they were the end of an earlier episode.
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Adult
Benzodiazepines
Continuity of Patient Care
Diagnosis
Dietary Supplements
Disabled Persons
Ethics Committees, Research
Inpatient
Outpatients
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SAS 9.4 is an integrated software suite for advanced analytics, data management, and business intelligence. It provides a comprehensive platform for data analysis, modeling, and reporting. SAS 9.4 offers a wide range of capabilities, including data manipulation, statistical analysis, predictive modeling, and visual data exploration.
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SAS version 9.4 is a statistical software package. It provides tools for data management, analysis, and reporting. The software is designed to help users extract insights from data and make informed decisions.
The HiPrep™ 26/10 Desalting Column is a pre-packed size-exclusion chromatography column designed for desalting and buffer exchange of protein and peptide samples. The column is packed with Sephadex™ G-25 resin and has a bed volume of 53 mL. It is suitable for desalting sample volumes up to 26 mL.
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SAS software is a comprehensive analytical platform designed for data management, statistical analysis, and business intelligence. It provides a suite of tools and applications for collecting, processing, analyzing, and visualizing data from various sources. SAS software is widely used across industries for its robust data handling capabilities, advanced statistical modeling, and reporting functionalities.
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Diazepam is a benzodiazepine-class pharmaceutical compound used in various laboratory and research applications. It functions as a central nervous system depressant with sedative, hypnotic, anxiolytic, anticonvulsant, and muscle relaxant properties.
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Stata version 15 is a data analysis and statistical software package. It provides a range of tools for data management, statistical analysis, and visualization. Stata version 15 supports a variety of data types and offers a comprehensive set of statistical procedures.
Sourced in Germany
The DrugTest 5000 is a portable, easy-to-use drug screening device developed by Dräger. It is designed to quickly and accurately detect the presence of various illicit drugs and certain medications in saliva samples. The device utilizes advanced analytical technology to provide reliable results, making it a useful tool for applications that require on-site drug testing.
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FG-7142 is a laboratory instrument used for analytical purposes. It is designed to perform specific measurements and analyses as part of research and testing procedures. The core function of FG-7142 is to provide accurate and reliable data to support scientific investigations and product development.
Sourced in United Kingdom, United States, Israel
Picrotoxin is a chemical compound that functions as a non-competitive antagonist of the gamma-aminobutyric acid (GABA) receptor. It is commonly used in scientific research as a tool to study GABA receptor function and neurotransmission.
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SAS software version 9.4 is a comprehensive data analysis and management solution. It provides advanced statistical and analytical capabilities for organizations to manage, analyze, and report on their data. The software includes a range of tools and features to support various data-driven tasks, such as data manipulation, statistical modeling, and predictive analytics.
More about "Benzodiazepines"
Benzodiazepines are a class of psychoactive drugs that are widely used for their sedative, anxiolytic (anti-anxiety), anticonvulsant, and muscle relaxant properties.
These compounds, which include drugs like Diazepam (Valium), act on the gamma-aminobutyric acid (GABA) receptors in the brain, enhancing the inhibitory effects of GABA and producing a calming effect.
Benzodiazepines are commonly prescribed for the treatment of anxiety disorders, insomnia, seizures, and alcohol withdrawal.
However, they also carry a risk of dependence and abuse, which has led to ongoing research to explore new therapeutic applications, optimize dosing regimens, and develop safer alternatives.
The SAS 9.4 software and Stata version 15 are statistical analysis tools that can be used to study the effects and usage of benzodiazepines.
The HiPrep™ 26/10 Desalting Column from GE is a laboratory tool that can be used in benzodiazepine research, while the DrugTest 5000 is a device used for the detection of benzodiazepines and other drugs.
Compounds like Picrotoxin and FG-7142 are also related to benzodiazepines, as they interact with the GABA receptors in the brain and can have similar effects.
Ongoing research aims to explore the full potential of benzodiazepines and develop safer alternatives to address the issues of dependence and abuse.
These compounds, which include drugs like Diazepam (Valium), act on the gamma-aminobutyric acid (GABA) receptors in the brain, enhancing the inhibitory effects of GABA and producing a calming effect.
Benzodiazepines are commonly prescribed for the treatment of anxiety disorders, insomnia, seizures, and alcohol withdrawal.
However, they also carry a risk of dependence and abuse, which has led to ongoing research to explore new therapeutic applications, optimize dosing regimens, and develop safer alternatives.
The SAS 9.4 software and Stata version 15 are statistical analysis tools that can be used to study the effects and usage of benzodiazepines.
The HiPrep™ 26/10 Desalting Column from GE is a laboratory tool that can be used in benzodiazepine research, while the DrugTest 5000 is a device used for the detection of benzodiazepines and other drugs.
Compounds like Picrotoxin and FG-7142 are also related to benzodiazepines, as they interact with the GABA receptors in the brain and can have similar effects.
Ongoing research aims to explore the full potential of benzodiazepines and develop safer alternatives to address the issues of dependence and abuse.