Design and computational evaluation of a novel multi-epitope hybrid vaccine against monkeypox virus: Potential targets and immunogenicity assessment for pandemic preparedness.

Monkeypox is a type of DNA-enveloped virus that belongs to the orthopoxvirus family, closely related to the smallpox virus. It can cause an infectious disease in humans known as monkeypox disease. Although there are multiple drugs and vaccines designed to combat orthopoxvirus infections, with a primary focus on smallpox, the recent spread of the monkeypox virus to over 50 countries have ignited a mounting global concern. This unchecked viral proliferation has raised apprehensions about the potential for a pandemic corresponding to the catastrophic impact of COVID-19. This investigation explored the structural proteins of monkeypox virus as potential candidates for designing a novel hybrid multi-epitope vaccine. The epitopes obtained from the selected proteins were screened to ensure their non-allergenicity, non-toxicity, and antigenicity to trigger T and B-cell responses. The interaction of the vaccine with toll-like receptor-3 (TLR-3) and major histocompatibility complexes (MHCs) was assessed using Cluspro 2.0. To establish the reliability of the docked complexes, a comprehensive evaluation was conducted using Immune and MD Simulations and Normal Mode Analysis. However, to validate the computational results of this study, additional in-vitro and in-vivo research is essential.

Towards a free energy-based elastic network model and its application to the SARS-COV2 binding to ACE2.

Classical normal mode analysis (cNMA) is a standard method for studying the equilibrium vibrations of macromolecules. A major limitation of cNMA is that it requires a cumbersome step of energy minimization that also alters the input structure significantly. Variants of normal mode analysis (NMA) exist that perform NMA directly on PDB structures without energy minimization, while maintaining most of the accuracy of cNMA. Spring-based NMA (sbNMA) is such a model. sbNMA uses an all-atom force field as cNMA does, which includes bonded terms such as bond stretching, bond angle bending, torsional, improper, and non-bonded terms such as van der Waals interactions. Electrostatics was not included in sbNMA because it introduced negative spring constants. In this work, we present a way to incorporate most of the electrostatic contributions in normal mode computations, which marks another significant step toward a free-energy-based elastic network model (ENM) for NMA. The vast majority of ENMs are entropy models. One significance of having a free energy-based model for NMA is that it allows one to study the contributions of both entropy and enthalpy. As an application, we apply this model to study the binding stability between SARS-COV2 and angiotensin converting enzyme 2 (or ACE2). Our results show that the stability at the binding interface is contributed nearly equally by hydrophobic interactions and hydrogen bonds.

TEAS, DHEA, CoQ10, and GH for poor ovarian response undergoing IVF-ET: a systematic review and network meta-analysis.

BACKGROUND: Assisted reproductive technology (ART) has brought good news to infertile patients, but how to improve the pregnancy outcome of poor ovarian response (POR) patients is still a serious challenge and the scientific evidence of some adjuvant therapies remains controversial. AIM: Based on previous evidence, the purpose of this systematic review and network meta-analysis was to evaluate the effects of DHEA, CoQ10, GH and TEAS on pregnancy outcomes in POR patients undergoing in vitro fertilization and embryo transplantation (IVF-ET). In addition, we aimed to determine the current optimal adjuvant treatment strategies for POR. METHODS: PubMed, Embase, The Cochrane Library and four databases in China (CNKI, Wanfang, VIP, SinoMed) were systematically searched up to July 30, 2022, with no restrictions on language. We included randomized controlled trials (RCTs) of adjuvant treatment strategies (DHEA, CoQ10, GH and TEAS) before IVF-ET to improve pregnancy outcomes in POR patients, while the control group received a controlled ovarian stimulation (COS) regimen only. This study was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The surface under the cumulative ranking curve (SUCRA) was used to provide a pooled measure of cumulative ranking for each outcome. RESULTS: Sixteen RCTs (2323 women) with POR defined using the Bologna criteria were included in the network meta-analysis. Compared with the control group, CoQ10 (OR 2.22, 95% CI: 1.05 to 4.71) and DHEA (OR 1.92, 95% CI: 1.16 to 3.16) had obvious advantages in improving the clinical pregnancy rate. CoQ10 was the best in improving the live birth rate (OR 2.36, 95% CI: 1.07 to 5.38). DHEA increased the embryo implantation rate (OR 2.80, 95%CI: 1.41 to 5.57) and the high-quality embryo rate (OR 2.01, 95% CI: 1.07 to 3.78) and number of oocytes retrieved (WMD 1.63, 95% CI: 0.34 to 2.92) showed a greater advantage, with GH in second place. Several adjuvant treatment strategies had no significant effect on reducing the cycle canceling rate compared with the control group. TEAS was the least effective of the four adjuvant treatments in most pooled results, but the overall effect appeared to be better than that of the control group. CONCLUSION: Compared with COS regimen, the adjuvant use of CoQ10, DHEA and GH before IVF may have a better clinical effect on the pregnancy outcome of POR patients. TEAS needs careful consideration in improving the clinical pregnancy rate. Future large-scale RCTs with direct comparisons are needed to validate or update this conclusion. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022304723.

Network meta-analysis of first-line immune checkpoint inhibitor therapy in advanced non-squamous non-small cell lung cancer patients with PD-L1 expression ≥ 50.

INTRODUCTION: The optimal first-line immunotherapy regimen for advanced non-squamous non-small cell lung cancer (NS-NSCLC) patients with programmed cell death ligand 1 (PD-L1) expression ≥ 50% remains unclear. Our aim is to determine the most effective treatment regimen through a network meta-analysis (NMA) comparing these treatments. METHODS: A systematic search was performed in PubMed, Cochrane Library, Web of Science, and Embase databases, and a Bayesian network meta-analysis was conducted. To ensure transparency, the study was registered in the International Prospective Register of Systematic Reviews (CRD42022349712). RESULTS: The analysis included 11 randomized controlled trials (RCTs) with 2037 patients and 12 immunotherapy combinations. ICI-ICI, ICI alone, and chemotherapy-ICI showed significant advantages over chemotherapy in terms of overall survival (OS) and progression-free survival (PFS). Pembrolizumab plus chemotherapy showed the best OS results compared to chemotherapy. Tislelizumab plus chemotherapy and sintilimab plus chemotherapy provided the best PFS results. CONCLUSIONS: For NS-NSCLC patients with PD-L1 ≥ 50%, pembrolizumab plus chemotherapy, tislelizumab plus chemotherapy, and sintilimab plus chemotherapy are recommended as good treatment options based on the results of this Network meta-analysis (NMA).

Inconsistency identification in network meta-analysis via stochastic search variable selection.

The reliability of the results of network meta-analysis (NMA) lies in the plausibility of the key assumption of transitivity. This assumption implies that the effect modifiers' distribution is similar across treatment comparisons. Transitivity is statistically manifested through the consistency assumption which suggests that direct and indirect evidence are in agreement. Several methods have been suggested to evaluate consistency. A popular approach suggests adding inconsistency factors to the NMA model. We follow a different direction by describing each inconsistency factor with a candidate covariate whose choice relies on variable selection techniques. Our proposed method, stochastic search inconsistency factor selection (SSIFS), evaluates the consistency assumption both locally and globally, by applying the stochastic search variable selection method to determine whether the inconsistency factors should be included in the model. The posterior inclusion probability of each inconsistency factor quantifies how likely is a specific comparison to be inconsistent. We use posterior model odds or the median probability model to decide on the importance of inconsistency factors. Differences between direct and indirect evidence can be incorporated into the inconsistency detection process. A key point of our proposed approach is the construction of a reasonable "informative" prior concerning network consistency. The prior is based on the elicitation of information derived historical data from 201 published network meta-analyses. The performance of our proposed method is evaluated in two published network meta-analyses. The proposed methodology is publicly available in an R package called ssifs, published on CRAN and developed and maintained by the authors of this work.

Methodological and reporting quality assessment of network meta-analyses in anesthesiology: a systematic review and meta-epidemiological study.

PURPOSE: The scientific rigour of the conduct and reporting of anesthesiology network meta-analyses (NMAs) is unknown. This systematic review and meta-epidemiological study assessed the methodological and reporting quality of NMAs in anesthesiology. METHODS: We searched four databases, including MEDLINE, PubMed, Embase, and the Cochrane Systematic Reviews Database, for anesthesiology NMAs published from inception to October 2020. We assessed the compliance of NMAs against A Measurement Tool to Assess Systematic Reviews (AMSTAR-2), Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement for Network Meta-Analyses (PRISMA-NMA), and PRISMA checklists. We measured the compliance across various items in AMSTAR-2 and PRISMA checklists and provided recommendations to improve quality. RESULTS: Using the AMSTAR-2 rating method, 84% (52/62) of NMAs were rated "critically low." Quantitatively, the median [interquartile range] AMSTAR-2 score was 55 [44-69]%, while the PRISMA score was 70 [61-81]%. Methodological and reporting scores showed a strong correlation (R = 0.78). Anesthesiology NMAs had a higher AMSTAR-2 score and PRISMA score if they were published in higher impact factor journals (P = 0.006 and P = 0.01, respectively) or followed PRISMA-NMA reporting guidelines (P = 0.001 and P = 0.002, respectively). Network meta-analyses from China had lower scores (P < 0.001 and P < 0.001, respectively). Neither score improved over time (P = 0.69 and P = 0.67, respectively). CONCLUSION: The current study highlights numerous methodological and reporting deficiencies in anesthesiology NMAs. Although the AMSTAR tool has been used to assess the methodological quality of NMAs, dedicated tools for conducting and assessing the methodological quality of NMAs are urgently required. STUDY REGISTRATION: PROSPERO (CRD42021227997); first submitted 23 January 2021.

RéSUMé: OBJECTIF: La rigueur scientifique de la conduite et de la communication des méta-analyses en réseau (MAR) en anesthésiologie est inconnue. Cette revue systématique et étude méta-épidémiologique a évalué la qualité méthodologique et de communication des MAR en anesthésiologie. MéTHODE: Nous avons mené des recherches dans quatre bases de données, soit MEDLINE, PubMed, Embase et la base de données des revues systématiques Cochrane, pour trouver des MAR en anesthésiologie publiées depuis la création de ces bases de données jusqu'en octobre 2020. Nous avons évalué la conformité des MAR par rapport à trois outils, soit : AMSTAR-2 (outil de mesure pour évaluer les revues systématiques), PRISMA-NMA et les listes de contrôle PRISMA. Nous avons mesuré la conformité de divers éléments des listes de contrôle AMSTAR-2 et PRISMA et formulé des recommandations pour améliorer la qualité. RéSULTATS: En utilisant la méthode de notation AMSTAR-2, 84 % (52/62) des MAR ont reçu la cote « extrêmement faible ¼. Quantitativement, le score médian [écart interquartile] sur l'AMSTAR-2 était de 55 [44-69] %, tandis que le score PRISMA était de 70 [61-81] %. Les scores méthodologiques et de communication ont montré une forte corrélation (R = 0,78). Les MAR en anesthésiologie avaient un score AMSTAR-2 et un score PRISMA plus élevés si elles étaient publiées dans des revues à facteur d'impact plus élevé (P = 0,006 et P = 0,01, respectivement) ou avaient suivi les lignes directrices de PRISMA-NMA en matière de communication des résultats (P = 0,001 et P = 0,002, respectivement). Les méta-analyses en réseau provenant de Chine avaient des scores plus faibles (P < 0,001 et P < 0,001, respectivement). Aucun des deux scores ne s'est amélioré au fil du temps (P = 0,69 et P = 0,67, respectivement). CONCLUSION: La présente étude met en évidence de nombreuses lacunes méthodologiques et de communication dans les MAR en anesthésiologie. Bien que l'outil AMSTAR ait été utilisé pour évaluer la qualité méthodologique des MAR, il est urgent de disposer d'outils spécialisés pour mener des MAR et en évaluer la qualité méthodologique. ENREGISTREMENT DE L'éTUDE: PROSPERO (CRD42021227997); soumis pour la première fois le 23 janvier 2021.

Efficacy and Safety of Botulinum Toxin Type A for Treatment of Glabellar Lines: A Network Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Botulinum toxin type A (BoNT/A) has been used in aesthetic applications worldwide, including glabellar lines. Currently, four BoNT/A preparations were approved for the improvement of moderate-to-severe glabellar lines: onabotulinumtoxinA, abobotulinumtoxinA, incobotulinumtoxinA, and prabotulinumtoxinA. DaxibotulinumtoxinA is a new form of BoNT/A drug that is developed in clinical application. We performed this network meta-analysis (NMA) to assess the efficacy and safety of all these different BoNT/A formulations for treating glabellar lines. METHODS: The investigators searched randomized controlled trials (RCTs) using the Medical Subject Headings (MeSH) terms "botulinum toxin" and "glabellar lines." We searched the relevant studies in electronic databases as following: PubMed, Elsevier, EMBASE and the Cochrane Library. The end points included the percentage of subjects with a glabellar line severity (GLS) score of none (0) or mild (1), and the percentage of subjects achieving ≥ 1-point and 2-point improvement in glabellar line severity at maximum frown at approximately month 1 by the investigators' assessment. RESULTS: All formulations of BoNT/A were far superior to placebo in efficacy. DaxibotulinumtoxinA was the only treatment that significantly increased the proportion of subjects achieving ≥ 1 point improvement in GLS score compared with other BoNT/A formulations. Moreover, daxibotulinumtoxinA was ranked the highest for the proportion of subjects achieving ≥ 2-point improvement in GLS score. No significant differences were revealed for the incidence of any adverse events (AEs) that related to treatment or drug among all BoNT/A preparations. CONCLUSION: The overall results of this NMA suggested that daxibotulinumtoxinA is a new BoNT/A preparation that may be not only more effective but also well-tolerated for the treatment of glabellar lines. LEVEL OF EVIDENCE I: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Meta-Analysis of the Mechanisms Underlying COVID-19 Modulation of Parkinson's Disease.

Coronavirus disease-19 (COVID-19) is caused by the infection of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). The virus enters host cells through receptor-mediated endocytosis of angiotensin-converting enzyme-2 (ACE2), leading to systemic inflammation, also known as a "cytokine storm", and neuroinflammation. COVID-19's upstream regulator, interferon-gamma (IFNG), is downregulated upon the infection of SARS-CoV-2, which leads to the downregulation of ACE2. The neuroinflammation signaling pathway (NISP) can lead to neurodegenerative diseases, such as Parkinson's disease (PD), which is characterized by the formation of Lewy bodies made primarily of the α-synuclein protein encoded by the synuclein alpha (SNCA) gene. We hypothesize that COVID-19 may modulate PD progression through neuroinflammation induced by cytokine storms. This study aimed to elucidate the possible mechanisms and signaling pathways involved in COVID-19-triggered pathology associated with neurodegenerative diseases like PD. This study presents the analysis of the pathways involved in the downregulation of ACE2 following SARS-CoV-2 infection and its effect on PD progression. Through QIAGEN's Ingenuity Pathway Analysis (IPA), the study identified the NISP as a top-five canonical pathway/signaling pathway and SNCA as a top-five upstream regulator. Core Analysis was also conducted on the associated molecules between COVID-19 and SNCA to construct a network connectivity map. The Molecule Activity Predictor tool was used to simulate the infection of SARS-CoV-2 by downregulating IFNG, which leads to the predicted activation of SNCA, and subsequently PD, through a dataset of intermediary molecules. Downstream effect analysis was further used to quantify the downregulation of ACE2 on SNCA activation.

Analysis of changes of cavity volumes in predefined directions of protein motions and cavity flexibility.

Dynamics of protein cavities associated with protein fluctuations and conformational plasticity is essential for their biological function. NMR ensembles, molecular dynamics (MD) simulations, and normal mode analysis (NMA) provide appropriate frameworks to explore functionally relevant protein dynamics and cavity changes relationships. Within this context, we have recently developed analysis of null areas (ANA), an efficient method to calculate cavity volumes. ANA is based on a combination of algorithms that guarantees its robustness against numerical differentiations. This is a unique feature with respect to other methods. Herein, we present an updated and improved version that expands it use to quantify changes in cavity features, like volume and flexibility, due to protein structural distortions performed on predefined biologically relevant directions, for example, directions of largest contribution to protein fluctuations (principal component analysis [PCA modes]) obtained by MD simulations or ensembles of NMR structures, collective NMA modes or any other direction of motion associated with specific conformational changes. A web page has been developed where its facilities are explained in detail. First, we show that ANA can be useful to explore gradual changes of cavity volume and flexibility associated with protein ligand binding. Secondly, we perform a comparison study of the extent of variability between protein backbone structural distortions, and changes in cavity volumes and flexibilities evaluated for an ensemble of NMR active and inactive conformers of the epidermal growth factor receptor structures. Finally, we compare changes in size and flexibility between sets of NMR structures for different homologous chains of dynein.

Comparative efficacy and safety of eleven induction chemotherapy regimens for young adult patients with newly diagnosed acute myeloid leukemia: a network meta-analysis.

The optimal induction chemotherapy regimens for young adult patients with newly diagnosed acute myeloid leukemia (AML) are not well-defined since the lack of direct comparisons between emerging treatments. Network meta-analysis (NMA) is a statistical tool to integrate direct and indirect evidence to evaluate the effect of multiple interventions. Thus, we conducted an NMA to systematically assess the efficacy and safety of different inductions for these patients. PubMed, Embase, Cochrane Library, and Web of Science were searched from establishment to 2020-03-11. Randomized controlled trials (RCTs) using different inductions were included. We deemed 11 trials eligible, including 11 inductions with 5052 participants. Relative risk (RR) and 95% confidence intervals (CIs) were calculated. In terms of complete remission (CR) rate, DAC ranked highest and was significantly higher than IA (RR = 1.27, 95% CI (1.09-1.48)) and DA (RR = 1.28, 95% CI (1.13-1.46)) (p < 0.05). The ranking of DA + Pioglitazone was second only to that of DAC, followed by HAA. For early mortality, HAD, HAA, and DA + GO were significantly higher than DA/IA (p < 0.05). DAC and DA + Pioglitazone showed similar early mortality compared to DA/IA (p > 0.05). Regarding incidence of early grade 3-4 infection, no significant differences between interventions were observed. To conclude, among the included 11 induction regimens, DAC was potentially the top choice for young adult patients with newly diagnosed AML, with highest CR rate, low early mortality, and incidence of early infection. DA + Pioglitazone and HAA also showed a superiority over the others to achieve higher CR rate, while caution should be kept in mind due to the higher early mortality of HAA.

Preventing postpartum hemorrhage after cesarean delivery: a network meta-analysis of available pharmacologic agents.

BACKGROUND: Postpartum hemorrhage causes a quarter of global maternal deaths. The World Health Organization recommends oxytocin as the first line agent to prevent hemorrhage during cesarean delivery. However, some randomized controlled trials suggest that other uterotonics are superior. OBJECTIVE: We conducted a network meta-analysis comparing the ability of pharmacologic agents to reduce blood loss and minimize the need for additional uterotonics during cesarean delivery. DATA SOURCES: We searched the Cochrane Central Register of Controlled Trials, Embase, and MEDLINE databases from inception to May 2020. STUDY ELIGIBILITY CRITERIA: We included randomized controlled trials that compared oxytocin, carbetocin, misoprostol, ergometrine, carboprost, or combinations of these in the prevention of postpartum hemorrhage during cesarean delivery. METHODS: We performed a systematic review followed by an NMA in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Quality of the evidence was assessed with the Confidence in Network Meta-Analysis approach and Grading of Recommendations, Assessment, Development and Evaluations tool within the summary of findings table. Our primary outcomes were the estimated blood loss and need for additional uterotonics. Secondary outcomes included nausea and postpartum hemorrhage of >1000 mL. We performed sensitivity analyses to explore the influence of surgical context and oxytocin administration strategy. RESULTS: A total of 46 studies with 7368 participants were included. Of those, 21 trials (6 agents and 3665 participants) formed the "estimated blood loss" network and, considering the treatment effects, certainty in the evidence, and surface under the cumulative ranking curve scores, carbetocin was assessed to probably be superior to oxytocin, but only in reducing the estimated blood loss by a clinically insignificant volume (54.83 mL; 95% confidence interval, 26.48-143.78). Misoprostol, ergometrine, and the combination of oxytocin and ergometrine were assessed to probably be inferior, whereas the combination of oxytocin and misoprostol was assessed to definitely be inferior to oxytocin. A total of 37 trials (8 agents and 6193 participants) formed the "additional uterotonic" network and, again, carbetocin was assessed to probably be superior to oxytocin, requiring additional uterotonics 185 (95% confidence interval, 130-218) fewer times per 1000 cases. Oxytocin plus misoprostol, oxytocin plus ergometrine, and misoprostol were assessed to probably be inferior, whereas carboprost, ergometrine, and the placebo were definitely inferior to oxytocin. For both primary outcomes, oxytocin administration strategies had a higher probability of being the best uterotonic, if initiated as a bolus. CONCLUSION: Carbetocin is probably the most effective agent in reducing blood loss and the need for additional uterotonics. Oxytocin appears to be more effective when initiated as a bolus.

Method's corner: Allergist's guide to network meta-analysis.

Network meta-analyses (NMAs) simultaneously estimate the effects of multiple possible treatment options for a given clinical presentation. For allergists to benefit optimally from NMAs, they must understand the process and be able to interpret the results. Through a worked example published in Pediatric Allergy and Immunology, we summarize how to identify credible NMAs and interpret them with a focus on recent innovations in the GRADE approach (Grading of Recommendations Assessment, Development, and Evaluation). NMAs build on traditional systematic reviews and meta-analyses that consider only direct paired comparisons by including indirect evidence, thus allowing the simultaneous assessment of the relative effect of all pairs of competing alternatives. Our framework informs clinicians of how to identify credible NMAs and address the certainty of the evidence. Trustworthy NMAs fill a critical gap in providing key inferences using direct and indirect evidence to inform clinical decision making when faced with more than two competing courses of treatment options. This document will help allergists to identify trustworthy NMAs to enhance patient care.

Methods to assess evidence consistency in dose-response model based network meta-analysis.

Network meta-analysis (NMA) simultaneously estimates multiple relative treatment effects based on evidence that forms a network of treatment comparisons. Heterogeneity in treatment definitions, such as dose, can lead to a violation of the consistency assumption that underpins NMA. Model-based NMA (MBNMA) methods have been proposed that allow functional dose-response relationships to be estimated within an NMA, which avoids lumping different doses together and thereby reduces the likelihood of inconsistency. Dose-response MBNMA relies on appropriate specification of the dose-response relationship as well as consistency of relative effects. In this article we describe methods to check for inconsistency in dose-response MBNMA models. Global and local (node-splitting) tests for inconsistency are described that account for studies with ≥3 arms that are typical in dose-finding trials. We show that consistency needs to be assessed with respect to the choice of dose-response function. We illustrate the methods using a network comparing biologics for moderate-to-severe psoriasis. By comparing results from an Emax and an exponential dose-response function we show that failure to correctly characterise the dose-response can introduce apparent inconsistency. The number of comparisons for which node-splitting is possible is also shown to be dependent on the complexity of the selected dose-response function. We highlight that the nature of dose-finding studies, which typically compare multiple doses of the same agent, provide limited scope to assess inconsistency, but these study designs help guard against inconsistency in the first place. We demonstrate the importance of assessing consistency to obtain robust relative effects to inform drug-development and policy decisions.

Systematic review and network meta-analysis (NMA) for cladribine tablets in achieving sustained disability improvement (SDI) in multiple sclerosis.

INTRODUCTION: This study was performed to compare probabilities of SDI on the Expanded Disability Status Scale (EDSS) in patients with relapsing-remitting multiple sclerosis (RRMS), treated with cladribine tablets (CT) or fingolimod (FTY), natalizumab (NAT), alemtuzumab (ALE) and ocrelizumab (OCR). CLINICAL RATIONALE FOR THE STUDY: Progression of neurological disability as measured by the EDSS has been a common endpoint in multiple sclerosis (MS) trials. Novel therapies can not only slow this process, but in some patients even reverse it. This effect can be measured by the sustained disability improvement (SDI) - an endpoint that seems to continuously gain importance in clinical practice. Despite that, SDI has rarely been explored as an outcome in MS clinical studies, mostly as post-hoc analyses from randomised trials or as retrospective analyses based on patient registry records. MATERIAL AND METHODS: A systematic review was conducted in Medline, Embase and Cochrane to identify clinical trials (RCT or non-RCT) evaluating 6-month SDI. An indirect comparison via network meta-analysis (NMA) was performed. Bayesian inference with Markov chains Monte Carlo methods were applied. RESULTS: Eight trials presenting SDI results and applicable for NMA were included: six non-RCTs, with control groups selected by propensity score matching, and two RCTs. NMA results revealed that probability of achieving 6-month SDI with CT was significantly higher compared to all other high efficacy disease-modifying drugs with available data - HR (95% Crl - Bayesian Credibility Interval) vs. FTY: 4.98 (2.11-11.79); vs. NAT: 3.12 (1.31-7.27); vs. ALE: 9.29 (3.40-25.21). The main results were confirmed in the sensitivity analyses. CONCLUSIONS: Of all considered therapies, treatment with cladribine tablets was associated with a higher probability of sustained disability improvement in RRMS patients. As this conclusion is based on available clinical data of limited quality, future studies, as well as real-world data, would be valuable to provide further evidence regarding the comparative effectiveness of RRMS therapies.

The amounts of thermal vibrations and static disorder in protein X-ray crystallographic B-factors.

Crystallographic B-factors provide direct dynamical information on the internal mobility of proteins that is closely linked to function, and are also widely used as a benchmark in assessing elastic network models. A significant question in the field is: what is the exact amount of thermal vibrations in protein crystallographic B-factors? This work sets out to answer this question. First, we carry out a thorough, statistically sound analysis of crystallographic B-factors of over 10 000 structures. Second, by employing a highly accurate all-atom model based on the well-known CHARMM force field, we obtain computationally the magnitudes of thermal vibrations of nearly 1000 structures. Our key findings are: (i) the magnitude of thermal vibrations, surprisingly, is nearly protein-independent, as a corollary to the universality for the vibrational spectra of globular proteins established earlier; (ii) the magnitude of thermal vibrations is small, less than 0.1 Å2 at 100 K; (iii) the percentage of thermal vibrations in B-factors is the lowest at low resolution and low temperature (<10%) but increases to as high as 60% for structures determined at high resolution and at room temperature. The significance of this work is that it provides for the first time, using an extremely large dataset, a thorough analysis of B-factors and their thermal and static disorder components. The results clearly demonstrate that structures determined at high resolution and at room temperature have the richest dynamics information. Since such structures are relatively rare in the PDB database, the work naturally calls for more such structures to be determined experimentally.

Comparative effectiveness of guselkumab in psoriatic arthritis: results from systematic literature review and network meta-analysis.

OBJECTIVE: The efficacy of the novel interleukin (IL)-23p19 inhibitor guselkumab for psoriatic arthritis (PsA) has recently been demonstrated in two phase 3 trials (DISCOVER-1 & -2) but has not been evaluated vs other targeted therapies for PsA. The objective was to compare guselkumab to targeted therapies for PsA for safety and joint and skin efficacy through network meta-analysis (NMA). METHODS: A systematic literature review was conducted in January 2020 to identify randomized controlled trials. Bayesian NMAs were performed to compare treatments on American College of Rheumatology (ACR) 20/50/70 response, mean change from baseline in van der Heijde-Sharp (vdH-S) score, Psoriasis Area Severity Index (PASI) 75/90/100 response, adverse events (AEs) and serious adverse events (SAEs). RESULTS: Twenty-six phase 3 studies evaluating 13 targeted therapies for PsA were included. For ACR 20 response, guselkumab 100 mg every 8 weeks (Q8W) was comparable to IL-17A inhibitors and subcutaneous tumor necrosis factor (TNF) inhibitors. Similar findings were observed for ACR 50 and 70. For vdH-S score, guselkumab Q8W was comparable to other agents except intravenous TNF therapies. Results for PASI 75 and PASI 90 response suggested guselkumab Q8W was better than most other agents. For PASI 100, guselkumab Q8W was comparable to other active agents. For AEs and SAEs, guselkumab Q8W ranked highly but comparative conclusions were uncertain. Similar results were observed for all outcomes for guselkumab 100 mg every four weeks. CONCLUSIONS: In this NMA, guselkumab demonstrated favorable arthritis efficacy comparable to IL-17A and subcutaneous TNF inhibitors while offering better PASI response relative to many other treatments.

Comparing the use of aggregate data and various methods of integrating individual patient data to network meta-analysis and its application to first-line ART.

BACKGROUND: The 2018 World Health Organization HIV guidelines were based on the results of a network meta-analysis (NMA) of published trials. This study employed individual patient-level data (IPD) and aggregate data (AgD) and meta-regression methods to assess the evidence supporting the WHO recommendations and whether they needed any refinements. METHODS: Access to IPD from three trials was granted through ClinicalStudyDataRequest.com (CSDR). Seven modelling approaches were applied and compared: 1) Unadjusted AgD network meta-analysis (NMA) - the original analysis; 2) AgD-NMA with meta-regression; 3) Two-stage IPD-AgD NMA; 4) Unadjusted one-stage IPD-AgD NMA; 5) One-stage IPD-AgD NMA with meta-regression (one-stage approach); 6) Two-stage IPD-AgD NMA with empirical-priors (empirical-priors approach); 7) Hierarchical meta-regression IPD-AgD NMA (HMR approach). The first two were the models used previously. Models were compared with respect to effect estimates, changes in the effect estimates, coefficient estimates, DIC and model fit, rankings and between-study heterogeneity. RESULTS: IPD were available for 2160 patients, representing 6.5% of the evidence base and 3 of 24 edges. The aspect of the model affected by the choice of modeling appeared to differ across outcomes. HMR consistently generated larger intervals, often with credible intervals (CrI) containing the null value. Discontinuations due to adverse events and viral suppression at 96 weeks were the only two outcomes for which the unadjusted AgD NMA would not be selected. For the first, the selected model shifted the principal comparison of interest from an odds ratio of 0.28 (95% CrI: 10.17, 0.44) to 0.37 (95% CrI: 0.23, 0.58). Throughout all outcomes, the regression estimates differed substantially between AgD and IPD methods, with the latter being more often larger in magnitude and statistically significant. CONCLUSIONS: Overall, the use of IPD often impacted the coefficient estimates, but not sufficiently as to necessitate altering the final recommendations of the 2018 WHO Guidelines. Future work should examine the features of a network where adjustments will have an impact, such as how much IPD is required in a given size of network.

When does the use of individual patient data in network meta-analysis make a difference? A simulation study.

BACKGROUND: The use of individual patient data (IPD) in network meta-analyses (NMA) is rapidly growing. This study aimed to determine, through simulations, the impact of select factors on the validity and precision of NMA estimates when combining IPD and aggregate data (AgD) relative to using AgD only. METHODS: Three analysis strategies were compared via simulations: 1) AgD NMA without adjustments (AgD-NMA); 2) AgD NMA with meta-regression (AgD-NMA-MR); and 3) IPD-AgD NMA with meta-regression (IPD-NMA). We compared 108 parameter permutations: number of network nodes (3, 5 or 10); proportion of treatment comparisons informed by IPD (low, medium or high); equal size trials (2-armed with 200 patients per arm) or larger IPD trials (500 patients per arm); sparse or well-populated networks; and type of effect-modification (none, constant across treatment comparisons, or exchangeable). Data were generated over 200 simulations for each combination of parameters, each using linear regression with Normal distributions. To assess model performance and estimate validity, the mean squared error (MSE) and bias of treatment-effect and covariate estimates were collected. Standard errors (SE) and percentiles were used to compare estimate precision. RESULTS: Overall, IPD-NMA performed best in terms of validity and precision. The median MSE was lower in the IPD-NMA in 88 of 108 scenarios (similar results otherwise). On average, the IPD-NMA median MSE was 0.54 times the median using AgD-NMA-MR. Similarly, the SEs of the IPD-NMA treatment-effect estimates were 1/5 the size of AgD-NMA-MR SEs. The magnitude of superior validity and precision of using IPD-NMA varied across scenarios and was associated with the amount of IPD. Using IPD in small or sparse networks consistently led to improved validity and precision; however, in large/dense networks IPD tended to have negligible impact if too few IPD were included. Similar results also apply to the meta-regression coefficient estimates. CONCLUSIONS: Our simulation study suggests that the use of IPD in NMA will considerably improve the validity and precision of estimates of treatment effect and regression coefficients in the most NMA IPD data-scenarios. However, IPD may not add meaningful validity and precision to NMAs of large and dense treatment networks when negligible IPD are used.

Meta-Analysis of Methamphetamine Modulation on Amyloid Precursor Protein through HMGB1 in Alzheimer's Disease.

The deposition of amyloid-beta (Aß) through the cleavage of amyloid-beta precursor protein (APP) is a biomarker of Alzheimer's disease (AD). This study used QIAGEN Ingenuity Pathway Analysis (IPA) to conduct meta-analysis on the molecular mechanisms by which methamphetamine (METH) impacts AD through modulating the expression of APP. All the molecules affected by METH and APP were collected from the QIAGEN Knowledge Base (QKB); 78 overlapping molecules were identified. Upon simulation of METH exposure using the "Molecule Activity Predictor" feature, eight molecules were found to be affected by METH and exhibited activation relationships on APP expression at a confidence of p = 0.000453 (Z-score = 3.51, two-tailed). Core Analysis of these eight molecules identified High Mobility Group Box protein 1 (HMGB1) signaling pathway among the top 5 canonical pathways with most overlap with the 8-molecule dataset. Simulated METH exposure increased APP expression through HMGB1 at a confidence of p < 0.00001 (Z-score = 7.64, two-tailed). HMGB1 is a pathogenic hallmark in AD progression. It not only increases the production of inflammatory mediators, but also mediates the disruption of the blood-brain barrier. Our analyses suggest the involvement of HMGB1 signaling pathway in METH-induced modulation of APP as a potential casual factor of AD.

Structural deformability induced in proteins of potential interest associated with COVID-19 by binding of homologues present in ivermectin: Comparative study based in elastic networks models.

The COVID-19 pandemic has accelerated the study of the potential of multi-target drugs (MTDs). The mixture of homologues called ivermectin (avermectin-B1a + avermectin-B1b) has been shown to be a MTD with potential antiviral activity against SARS-CoV-2 in vitro. However, there are few reports on the effect of each homologue on the flexibility and stiffness of proteins associated with COVID-19, described as ivermectin targets. We observed that each homologue was stably bound to the proteins studied and was able to induce detectable changes with Elastic Network Models (ENM). The perturbations induced by each homologue were characteristic of each compound and, in turn, were represented by a disruption of native intramolecular networks (interactions between residues). The homologues were able to slightly modify the conformation and stability of the connection points between the Cα atoms of the residues that make up the structural network of proteins (nodes), compared to free proteins. Each homologue was able to modified differently the distribution of quasi-rigid regions of the proteins, which could theoretically alter their biological activities. These results could provide a biophysical-computational view of the potential MTD mechanism that has been reported for ivermectin.