scholarly journals Real-world Evidence for Improved Outcomes with Histamine Antagonists and Aspirin in 22,560 COVID-19 Patients

2021 ◽  
Author(s):  
Cameron Mura ◽  
Saskia Preissner ◽  
Susanne Nahles ◽  
Max Heiland ◽  
Philip Bourne ◽  
...  
Keyword(s):  
Therapeutic Potential ◽  
General Purpose ◽  
Recent Effort ◽  
Histamine Antagonists ◽  
Histamine H2 Receptor ◽  
Improved Outcomes ◽  
Real World Evidence ◽  
Repurposed Drugs ◽  
The One ◽  
The Cost

Abstract COVID-19 has spurred much interest in the therapeutic potential of repurposed drugs, such as acid-reducing drugs that act as histamine H2 receptor antagonists (H2RA). These compounds, exemplified by famotidine (e.g., Pepcid) and ranitidine (e.g., Zantac), bind the H2R and block the histamine-triggered stimulation of signal transduction cascades. Histamine and H2RAs, on the one hand, and downstream physiological pathways, on the other hand, form a dense web of disparate pathways and signaling networks; these networks are ultimately tied to the dysregulated inflammatory cascades (cytokine storm) that underlies the pathophysiology of COVID-19. Is famotidine beneficial in treating COVID-19? This question remains unresolved, despite much recent effort: over 10 studies have examined the potential value of famotidine in COVID-19, but have found largely contradictory results. Given the conflicting reports, we have undertaken a new analysis reported herein, drawing upon a cohort of 22,560 COVID-19 patients. Using electronic health records, we statistically analyzed outcomes for treatment with the H1RAs loratadine (e.g., Claritin) and cetirizine (e.g., Zyrtec), the H2RA famotidine, the general-purpose anti-inflammatory aspirin, and a famotidine & aspirin combination. For severe cases (requiring respiratory support), we found a significantly reduced fatality risk for famotidine treatment. Notably, famotidine combined with aspirin exhibited a significant synergistic survival benefit (odds ratio of 0.55). The relative risk for death decreased by 32.5%—an immense benefit, given the more than 2.6 million COVID-19-related deaths thus far. The large, multi-center retrospective study reported here, sampling over 250,000 COVID-19 cases internationally, hopefully helps clarify the possible value of clinically-approved histamine antagonists such as famotidine. Given these findings, alongside the cost-effectiveness and mild side-effects of common over-the-counter drugs like famotidine and aspirin, we suggest that further prospective clinical trials, perhaps utilizing the aspirin combination reported here, are advisable.

Machine Learning Through Data Mining

2011 ◽  
pp. 2469-2475
Author(s):  
Diego Liberati
Keyword(s):  
Data Mining ◽  
General Purpose ◽  
Significant Loss ◽  
Present Contribution ◽  
Security Issues ◽  
Critical Issues ◽  
Representative Model ◽  
The One ◽  
The Cost ◽  
Classification Procedures

In dealing with information it often turns out that one has to face a huge amount of data, often not completely homogeneous and often without an immediate grasp of an underlying simple structure. Many records, each one instantiating many variables, are usually collected with the help of various technologies. Given the opportunity to have so many data not easy to correlate by the human reader, but probably hiding interesting properties, one of the typical goals one has in mind is to classify subjects on the basis of a hopefully reduced meaningful subset of the measured variables. The complexity of the problem makes it worthwhile to resort to automatic classification procedures. Then, the question arises of reconstructing a synthetic mathematical model, capturing the most important relations between variables, in order to both discriminate classes of subjects and possibly also infer rules of behaviours that could help identify their habits. Such interrelated aspects will be the focus of the present contribution. The data mining procedures that will be introduced in order to infer properties hidden in the data are in fact so powerful that care should be put in their capability to unveil regularities that the owner of the data would not want to let the processing tool discover, like for instance, in some cases the customer habits investigated via the usual smart card used in commerce with the apparent reward of discounting. Four main general purpose approaches will be briefly discussed in the present article, underlying the cost effectiveness of each one. In order to reduce the dimensionality of the problem, simplifying both the computation and the subsequent understanding of the solution, the critical issues of selecting the most salient variables must be addressed. This step may already be sensitive, pointing to the very core of the information to look at. A very simple approach is to resort to cascading a divisive partitioning of data orthogonal to the principal directions (PDDP) (Boley, 1998) already proven to be successful in the context of analyzing micro-arrays data (Garatti, Bittanti, Liberati, & Maffezzoli, 2007). A more sophisticated possible approach is to resort to a rule induction method, like the one described in Muselli and Liberati (2000). Such a strategy also offers the advantage to extract underlying rules, implying conjunctions or disjunctions between the identified salient variables. Thus, a first idea of their even nonlinear relations is provided as a first step to design a representative model, whose variables will be the selected ones. Such an approach has been shown (Muselli & Liberati, 2002) to be not less powerful over several benchmarks than the popular decision tree developed by Quinlan (1994). An alternative in this sense can be represented by Adaptive Bayesian networks (Yarmus, 2003) whose advantage is also to be available on a commercial wide spread data base tool like Oracle. Dynamics may matter. A possible approach to blindly build a simple linear approximating model is thus to resort to piece-wise affine (PWA) identification (Ferrari-Trecate, Muselli, Liberati, & Morari, 2003). The joint use of (some of) such four approaches briefly described in this article, starting from data without known priors about their relationships, will allow to reduce dimensionality without significant loss in information, then to infer logical relationships, and, finally, to identify a simple input-output model of the involved process that also could be used for controlling purposes, even those potentially sensitive to ethical and security issues.

scholarly journals Clinical Evidence for Improved Outcomes with Histamine Antagonists and Aspirin in 22,560 COVID-19 Patients

2021 ◽  
Author(s):  
Cameron Mura ◽  
Saskia Preissner ◽  
Susanne Nahles ◽  
Max Heiland ◽  
Philip E. Bourne ◽  
...  
Keyword(s):  
Therapeutic Potential ◽  
Severe Disease ◽  
Histamine Receptor ◽  
Serum Markers ◽  
Respiratory Support ◽  
Receptor Antagonists ◽  
H2 Receptor Antagonists ◽  
Histamine Antagonists ◽  
Histamine H2 Receptor ◽  
H2 Receptor

COVID-19 has spurred much interest in the therapeutic potential of repurposed drugs. A family of acid-reducing drugs, known as histamine H2 receptor antagonists (H2RA), competitively bind the H2R and block its stimulation by histamine; examples of such drugs are famotidine (e.g., Pepcid) and ranitidine (e.g., Zantac). A dense web of functionalities between histamine and H2RAs, on the one hand, and downstream cellular pathways, on the other hand, links disparate physiological pathways in gastrointestinal contexts (e.g., acid reduction) to the dysregulated inflammatory cascades (cytokine storm) underlying the pathophysiology of COVID-19. Is famotidine beneficial in treating COVID-19? This question remains unresolved, though not for lack of effort: over 10 studies have examined the potential therapeutic value of famotidine in COVID-19, but have found conflicting results (pro-famotidine, anti-famotidine, and neutral). Given the contradictory reports, we have undertaken the new analysis reported herein. Notably, studies published thus far rest upon substantially smaller datasets than drawn upon in the pre-sent work. We analyzed a cohort of 22,560 COVID-19 patients taking H1/H2 receptor antagonists, focusing on 1,379 severe cases requiring respiratory support. We analyzed outcomes for treatment with the H1RAs loratadine (e.g., Claritin) and cetirizine (e.g., Zyrtec), the H2RA famotidine, aspirin, and a famotidine & aspirin combination. For cases that reached the point of respiratory support, we found a significantly reduced fatality risk for famotidine treatment. We did not detect a benefit from dual-histamine receptor blockade (concurrently targeting H1 and H2 receptors). Notably, famotidine combined with aspirin did exhibit a significant synergistic survival benefit (odds ratio of 0.55). The relative risk for death decreased by 32.5%--an immense benefit, given the more than 2.6 million COVID-19-related deaths thus far. We found lower levels of serum markers for severe disease (e.g., C-reactive protein) in famotidine users, consistent with prior findings by others and with a role for famotidine in attenuating cytokine release. The large, international, multi-center retrospective study reported here, sampling over 250,000 COVID-19 cases, hopefully helps clarify the possible value of clinically-approved histamine antagonists such as famotidine. Given these findings, alongside the cost-effectiveness and mild side-effects of popular drugs like famotidine and aspirin, we suggest that further prospective clinical trials, perhaps utilizing the aspirin combination reported here, are advisable.

Rosenhain Centenary Conference - Titanium alloys for engineering structures

1976 ◽  
Vol 282 (1307) ◽  
pp. 401-411 ◽  
Keyword(s):  
Heat Treatment ◽  
Titanium Alloys ◽  
Alloy Composition ◽  
High Strength ◽  
General Purpose ◽  
Alloy Development ◽  
Engineering Structures ◽  
Factors Affecting ◽  
The One ◽  
The Cost

The range of properties obtainable in titanium alloys derives from the use which is made of the j5~oc phase transformation, and alloying elements are classified according to their effect on the transformation temperature. The relation between composition and heat treatment on the one hand and the resultant microstructure and mechanical properties on the other hand are considered. In addition to the commonly used ‘general purpose’ alloy Ti-6A1-4V, more advanced alloys have been developed for three main applications, namely high strength forging alloys, creep resistant alloys and sheet alloys. For each type of alloy a different balance of material properties is required and the process of optimizing the alloy composition and heat treatment to give the best balance in each case is discussed. Factors affecting the cost of titanium alloys are outlined and consideration is given to the likely trends of titanium alloy development in the future.

scholarly journals COVID-19 and Repurposed Drugs How Much is A Human Life?.

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Carvallo Hector E ◽  
Matozza Francesco ◽  
Hirsch Roberto R
Keyword(s):  
Human Life ◽  
Cost Benefit ◽  
Health Policies ◽  
Global Level ◽  
Benefit Ratio ◽  
Underdeveloped Countries ◽  
Cost Benefit Ratio ◽  
Repurposed Drugs ◽  
The One ◽  
The Cost

The current pandemic due to COVID 19 (SARS COV2) has revealed a disturbing reality most of the world's health systems, and the organizations that govern health policies at a global level, have not been able to meet the expectations that were set on them. On the one hand, W.H.O has shown hesitations, orders, counter-orders, delays and errors that have made it lose credibility. The terrible images of corpses piled up in the corridors of healthcare centers (from underdeveloped countries to the most powerful ones in the planet); will remain forever in our memory. The enormous financial effort made was not always well targeted, and rarely benefited the patients. The cost / benefit ratio was inverted, contributing fortunes in the final monitoring of severe cases, when logic indicates that emphasis should be placed on not reaching severe stages, and must be solved earlier. In this article, we establish a comparison between what is done and what - in our opinion - should be done.

scholarly journals Real-world evidence for improved outcomes with histamine antagonists and aspirin in 22,560 COVID-19 patients

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Cameron Mura ◽  
Saskia Preissner ◽  
Susanne Nahles ◽  
Max Heiland ◽  
Philip E. Bourne ◽  
...  
Keyword(s):  
Real World ◽  
Histamine Antagonists ◽  
Improved Outcomes ◽  
Real World Evidence

Machine Learning Through Data Mining

2012 ◽  
pp. 23-31
Author(s):  
Diego Liberati
Keyword(s):  
Data Mining ◽  
General Purpose ◽  
Significant Loss ◽  
Present Contribution ◽  
Security Issues ◽  
Critical Issues ◽  
Representative Model ◽  
The One ◽  
The Cost ◽  
Classification Procedures

In dealing with information it often turns out that one has to face a huge amount of data, often not completely homogeneous and often without an immediate grasp of an underlying simple structure. Many records, each one instantiating many variables, are usually collected with the help of various technologies. Given the opportunity to have so many data not easy to correlate by the human reader, but probably hiding interesting properties, one of the typical goals one has in mind is to classify subjects on the basis of a hopefully reduced meaningful subset of the measured variables. The complexity of the problem makes it worthwhile to resort to automatic classification procedures. Then, the question arises of reconstructing a synthetic mathematical model, capturing the most important relations between variables, in order to both discriminate classes of subjects and possibly also infer rules of behaviours that could help identify their habits. Such interrelated aspects will be the focus of the present contribution. The data mining procedures that will be introduced in order to infer properties hidden in the data are in fact so powerful that care should be put in their capability to unveil regularities that the owner of the data would not want to let the processing tool discover, like for instance, in some cases the customer habits investigated via the usual smart card used in commerce with the apparent reward of discounting. Four main general purpose approaches will be briefly discussed in the present article, underlying the cost effectiveness of each one. In order to reduce the dimensionality of the problem, simplifying both the computation and the subsequent understanding of the solution, the critical issues of selecting the most salient variables must be addressed. This step may already be sensitive, pointing to the very core of the information to look at. A very simple approach is to resort to cascading a divisive partitioning of data orthogonal to the principal directions (PDDP) (Boley, 1998) already proven to be successful in the context of analyzing micro-arrays data (Garatti, Bittanti, Liberati, & Maffezzoli, 2007). A more sophisticated possible approach is to resort to a rule induction method, like the one described in Muselli and Liberati (2000). Such a strategy also offers the advantage to extract underlying rules, implying conjunctions or disjunctions between the identified salient variables. Thus, a first idea of their even nonlinear relations is provided as a first step to design a representative model, whose variables will be the selected ones. Such an approach has been shown (Muselli & Liberati, 2002) to be not less powerful over several benchmarks than the popular decision tree developed by Quinlan (1994). An alternative in this sense can be represented by Adaptive Bayesian networks (Yarmus, 2003) whose advantage is also to be available on a commercial wide spread data base tool like Oracle. Dynamics may matter. A possible approach to blindly build a simple linear approximating model is thus to resort to piece-wise affine (PWA) identification (Ferrari-Trecate, Muselli, Liberati, & Morari, 2003). The joint use of (some of) such four approaches briefly described in this article, starting from data without known priors about their relationships, will allow to reduce dimensionality without significant loss in information, then to infer logical relationships, and, finally, to identify a simple input-output model of the involved process that also could be used for controlling purposes, even those potentially sensitive to ethical and security issues.

PENGARUH LATIHAN RANGE OF MOTION (ROM) AKTIF ASSITIF TERHADAP RENTANG GERAK SENDI PADA LANSIA YANG MENGALAMI IMMOBILISASI FISIK

2019 ◽  
Vol 13 (2) ◽  
Author(s):  
Andri Setyorini ◽  
Niken Setyaningrum
Keyword(s):  
Range Of Motion ◽  
Human Life ◽  
The Elderly ◽  
General Purpose ◽  
Test Statistic ◽  
Physical Mobility ◽  
Motion Exercise ◽  
The One ◽  
The Individual ◽  
Active Training

Background: Elderly is the final stage of the human life cycle, that is part of the inevitable life process and will be experienced by every individual. At this stage the individual undergoes many changes both physically and mentally, especially setbacks in various functions and abilities he once had. Preliminary study in Social House Tresna Wreda Yogyakarta Budhi Luhur Units there are 16 elderly who experience physical immobilization. In the social house has done various activities for the elderly are still active, but the elderly who experienced muscle weakness is not able to follow the exercise, so it needs to do ROM (Range Of Motion) exercise.   Objective: The general purpose of this research is to know the effect of Range Of Motion (ROM) Active Assitif training to increase the range of motion of joints in elderly who experience physical immobility at Social House of Tresna Werdha Yogyakarta unit Budhi Luhur.   Methode: This study was included in the type of pre-experiment, using the One Group Pretest Posttest design in which the range of motion of the joints before (pretest) and posttest (ROM) was performed  ROM. Subjects in this study were all elderly with impaired physical mobility in Social House Tresna Wreda Yogyakarta Unit Budhi Luhur a number of 14 elderly people. Data analysis in this research use paired sample t-test statistic  Result: The result of this research shows that there is influence of ROM (Range of Motion) Active training to increase of range of motion of joints in elderly who experience physical immobility at Social House Tresna Wredha Yogyakarta Unit Budhi Luhur.  Conclusion: There is influence of ROM (Range of Motion) Active training to increase of range of motion of joints in elderly who experience physical immobility at Social House Tresna Wredha Yogyakarta Unit Budhi Luhur.

scholarly journals General synthetic strategy for regioselective ultrafast formation of disulfide bonds in peptides and proteins

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Shay Laps ◽  
Fatima Atamleh ◽  
Guy Kamnesky ◽  
Hao Sun ◽  
Ashraf Brik
Keyword(s):  
Drug Discovery ◽  
Disulfide Bonds ◽  
Unsolved Problem ◽  
De Novo ◽  
Therapeutic Potential ◽  
Selective Activation ◽  
One Pot ◽  
Synthetic Strategy ◽  
The One ◽  
Game Changer

AbstractDespite six decades of efforts to synthesize peptides and proteins bearing multiple disulfide bonds, this synthetic challenge remains an unsolved problem in most targets (e.g., knotted mini proteins). Here we show a de novo general synthetic strategy for the ultrafast, high-yielding formation of two and three disulfide bonds in peptides and proteins. We develop an approach based on the combination of a small molecule, ultraviolet-light, and palladium for chemo- and regio-selective activation of cysteine, which enables the one-pot formation of multiple disulfide bonds in various peptides and proteins. We prepare bioactive targets of high therapeutic potential, including conotoxin, RANTES, EETI-II, and plectasin peptides and the linaclotide drug. We anticipate that this strategy will be a game-changer in preparing millions of inaccessible targets for drug discovery.

scholarly journals Monoclonal Antibodies Targeting CGRP: From Clinical Studies to Real-World Evidence—What Do We Know So Far?

2021 ◽  
Vol 14 (7) ◽  
pp. 700
Author(s):  
Theodoros Mavridis ◽  
Christina I. Deligianni ◽  
Georgios Karagiorgis ◽  
Ariadne Daponte ◽  
Marianthi Breza ◽  
...  
Keyword(s):  
Monoclonal Antibodies ◽  
Real World ◽  
Large Scale ◽  
Randomized Clinical Trials ◽  
Clinical Investigation ◽  
Phase Iii ◽  
Real World Evidence ◽  
Symptomatic Management ◽  
Repurposed Drugs ◽  
Cephalic Pain

Now more than ever is the time of monoclonal antibody use in neurology. In headaches, disease-specific and mechanism-based treatments existed only for symptomatic management of migraines (i.e., triptans), while the standard prophylactic anti-migraine treatments consist of non-specific and repurposed drugs that share limited safety profiles and high risk for interactions with other medications, resulting in rundown adherence rates. Recent advances in headache science have increased our understanding of the role of calcitonin gene relate peptide (CGRP) and pituitary adenylate cyclase-activating polypeptide (PACAP) pathways in cephalic pain neurotransmission and peripheral or central sensitization, leading to the development of monoclonal antibodies (mAbs) or small molecules targeting these neuropeptides or their receptors. Large scale randomized clinical trials confirmed that inhibition of the CGRP system attenuates migraine, while the PACAP mediated nociception is still under scientific and clinical investigation. In this review, we provide the latest clinical evidence for the use of anti-CGRP in migraine prevention with emphasis on efficacy and safety outcomes from Phase III and real-world studies.

scholarly journals A Study on the Feasibility of Anaerobic Co-Digestion of Raw Cheese Whey with Coffee Pulp Residues

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3611
Author(s):  
Sandra Gonzalez-Piedra ◽  
Héctor Hernández-García ◽  
Juan M. Perez-Morales ◽  
Laura Acosta-Domínguez ◽  
Juan-Rodrigo Bastidas-Oyanedel ◽  
...  
Keyword(s):  
Methane Production ◽  
Kinetic Models ◽  
Cheese Whey ◽  
Maximum Yield ◽  
Gompertz Model ◽  
Coffee Pulp ◽  
The One ◽  
The Cost ◽  
Best Fit ◽  
Cheese Production

In this paper, a study on the feasibility of the treatment of raw cheese whey by anaerobic co-digestion using coffee pulp residues as a co-substrate is presented. It considers raw whey generated in artisanal cheese markers, which is generally not treated, thus causing environmental pollution problems. An experimental design was carried out evaluating the effect of pH and the substrate ratio on methane production at 35 °C (i.e., mesophilic conditions). The interaction of the parameters on the co-substrate degradation and the methane production was analyzed using a response surface analysis. Furthermore, two kinetic models were proposed (first order and modified Gompertz models) to determine the dynamic profiles of methane yield. The results show that co-digestion of the raw whey is favored at pH = 6, reaching a maximum yield of 71.54 mLCH4 gVSrem−1 (31.5% VS removed) for raw cheese whey and coffee pulp ratio of 1 gVSwhey gVSCoffe−1. The proposed kinetic models successfully fit the experimental methane production data, the Gompertz model being the one that showed the best fit. Then, the results show that anaerobic co-digestion can be used to reduce the environmental impact of raw whey. Likewise, the methane obtained can be integrated into the cheese production process, which could contribute to reducing the cost per energy consumption.

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