Loneliness and Drinking in an HIV Positive Population

Background: Loneliness is a common outcome in the HIV+ community due to the stigma associated with it leading to social isolation. Studies show HIV+ individuals who experience significant loneliness do engage in risky sexual behaviors. Alcohol use also has adverse consequences in this population, interfering with antiretroviral medication adherence thus an increased likelihood of further risky sexual behaviors. Hypothesis: HIV+ individuals who experience an increase in loneliness will have an increase in hazardous drinking behaviors. Methods: 100 patients from an HIV treatment clinic in Jacksonville, Florida were administered the AUDIT scale to measure drinking habits and UCLA loneliness scale. Descriptive statistics and correlations have been reported. Results: The sample included 67% female, 83% African American with a mean age of 45.2 years. 63% were single and 69% were living with a spouse, partner, children, friends or other family members. Mean AUDIT score was 2.8 (SD: 4.47) with a cut-off value of 8, mean UCLA score was 45 .86 (SD: 4.01). Spearman\u27s correlations revealed no significant relationship between age and loneliness (r=0.175) (95% Cl= -0.13, 0.385); or living alone and loneliness (r = 0.03) (95% Cl = -0.202, 0.208). Further, no significant correlations were found between drinking and loneliness (r= -0.083) (95% Cl= -0.208, 0.200). Conclusions: Participants who lived alone scored higher on the UCLA Loneliness Scale, however the relationship was not statistically significant. There was no significant correlation between loneliness and hazardous drinking. This is contrary to prior expectations that participants who have increased loneliness have an increase in hazardous drinking

Clinical characteristics and outcomes of critically ill patients with COVID-19 in a tertiary community hospital in upstate New York.

Background: There are limited reports describing critically ill COVID-19 patients in the state of New York. Methods: We conducted a retrospective analysis of 32 adult critically ill patients admitted to a community hospital in upstate New York, between 14 March and 12 April 2020. We collected demographic, laboratory, ventilator and treatment data, which were analyzed and clinical outcomes tabulated. Results: 32 patients admitted to the intensive care unit (ICU) were included, with mean (±SD) follow-up duration 21 ± 7 days. Mean (±SD) age was 62.2 ± 11.2 years, and 62.5% were men. 27 (84.4%) of patients had one or more medical co-morbidities. The mean (±SD) duration of symptoms was 6.6 (±4.4) days before presentation, with cough (81.3%), dyspnea (68.7%), and fever (65.6%) being the most common. 23 (71.9%) patients received invasive mechanical ventilation. 5 (15.6%) died, 11 (34.4%) were discharged home, and 16 (50%) remained hospitalized, 8 (25%) of which were still in ICU. Mean (±SD) length of ICU stay was 10.2 (±7.7) days, and mean (±SD) length of hospital stay was 14.8 (±7.7) days. Conclusion: Majority of patients were of older age and with medical comorbidities. With adequate resource utilization, mortality of critically ill COVID-19 patients may not be as high as previously suggested. Abbreviations: ACE-i: Angiotensin converting enzyme inhibitor; ARB: Angiotensin receptor blocker; ARDS: Acute Respiratory Distress Syndrome; BiPAP: Bilevel positive airway pressure; CABG: Coronary artery bypass graft; CFR: Case fatality rate; COVID-19: Coronavirus disease 19; CPAP: Continuous positive airway pressure; CRP: C - Reactive Protein; CT: Computed tomography; DVT: Deep vein thrombosis; ECMO: Extra Corporeal Membrane Oxygenation; ESICM: European Society of Intensive Care Medicine; FiO2: Fraction of inspired O2; HFNC: High Flow Nasal Cannula; HITF: Hypoxia-Inducible Transcription Factor; IBM: International Business Machines; ICU: Intensive Care Unit; IL: Interleukin; IMV: Invasive Mechanical Ventilation; IQR: Interquartile Range; ISTH: International Society of Thrombosis Hemostasis; NIV: Non Invasive Ventilation; NY: New York; PAI: Plasminogen activator inhibitor; PaO2: partial pressure of arterial oxygen; PCV: Pressure Control Ventilation; PEEP: Positive End Expiratory Pressure; RGH: Rochester General Hospital; RRH: Rochester Regional Health; RT-PCR: Reverse transcriptase polymerase chain reaction; RSV: Respiratory Syncytial virus; SARS-CoV-2: Severe Acute Respiratory Syndrome Coronavirus 2; SD: Standard Deviation; STEMI: ST segment elevation myocardial infarction; TNF: Tumor necrosis factor; USA: USA; VTE: Venous thromboembolism

Advanced Computational Methodologies Used in the Discovery of New Natural Anticancer Compounds

Natural chemical compounds have been widely investigated for their programmed necrosis causing characteristics. One of the conventional methods for screening such compounds is the use of concentrated plant extracts without isolation of active moieties for understanding pharmacological activity. For the last two decades, modern medicine has relied mainly on the isolation and purification of one or two complicated active and isomeric compounds. The idea of multi-target drugs has advanced rapidly and impressively from an innovative model when first proposed in the early 2000s to one of the popular trends for drug development in 2021. Alternatively, fragment-based drug discovery is also explored in identifying target-based drug discovery for potent natural anticancer agents which is based on well-defined fragments opposite to use of naturally occurring mixtures. This review summarizes the current key advancements in natural anticancer compounds; computer-assisted/fragment-based structural elucidation and a multi-target approach for the exploration of natural compounds