Mobile Methadone Clinics: A Necessary Step in Fighting the Opioid Epidemic

Part I of this Article will discuss the rise in opioid use disorder, the need for effective treatment, and the utility of methadone maintenance treatment options, as well as the history of the ban on mobile clinics. Part II will discuss the NPRM issued by the DEA on February 26, 2020, and explain the likely impact of the rule. Part III will provide an overview of the NPRM in its current form, explain its likely impact as written and show that mobile clinics are effective treatment options, and then argue that while a great start, the NPRM should be amended to require that mobile clinics offer a behavioral treatment component to maximize the chances of success

A novel structure-based encoding for machine-learning applied to the inference of SH3 domain specificity

MOTIVATION: Unravelling the rules underlying protein-protein and protein-ligand interactions is a crucial step in understanding cell machinery. Peptide recognition modules (PRMs) are globular protein domains which focus their binding targets on short protein sequences and play a key role in the frame of protein-protein interactions. High-throughput techniques permit the whole proteome scanning of each domain, but they are characterized by a high incidence of false positives. In this context, there is a pressing need for the development of in silico experiments to validate experimental results and of computational tools for the inference of domain-peptide interactions. RESULTS: We focused on the SH3 domain family and developed a machine-learning approach for inferring interaction specificity. SH3 domains are well-studied PRMs which typically bind proline-rich short sequences characterized by the PxxP consensus. The binding information is known to be held in the conformation of the domain surface and in the short sequence of the peptide. Our method relies on interaction data from high-throughput techniques and benefits from the integration of sequence and structure data of the interacting partners. Here, we propose a novel encoding technique aimed at representing binding information on the basis of the domain-peptide contact residues in complexes of known structure. Remarkably, the new encoding requires few variables to represent an interaction, thus avoiding the 'curse of dimension'. Our results display an accuracy >90% in detecting new binders of known SH3 domains, thus outperforming neural models on standard binary encodings, profile methods and recent statistical predictors. The method, moreover, shows a generalization capability, inferring specificity of unknown SH3 domains displaying some degree of similarity with the known data

Motzkin numbers, central trinomial coefficients and hybrid polynomials

We show that the formalism of hybrid polynomials, interpolating between Hermite and Laguerre polynomials, is very useful in the study of Motzkin numbers and central trinomial coefficients. These sequences are identified as special values of hybrid polynomials, a fact which we use to derive their generalized forms and new identities satisfied by them.Comment: 13 page

A neural strategy for the inference of SH3 domain-peptide interaction specificity

The SH3 domain family is one of the most representative and widely studied cases of so-called Peptide Recognition Modules (PRM). The polyproline II motif PxxP that generally characterizes its ligands does not reflect the complex interaction spectrum of the over 1500 different SH3 domains, and the requirement of a more refined knowledge of their specificity implies the setting up of appropriate experimental and theoretical strategies. Due to the limitations of the current technology for peptide synthesis, several experimental high-throughput approaches have been devised to elucidate protein-protein interaction mechanisms. Such approaches can rely on and take advantage of computational techniques, such as regular expressions or position specific scoring matrices (PSSMs) to pre-process entire proteomes in the search for putative SH3 targets. In this regard, a reliable inference methodology to be used for reducing the sequence space of putative binding peptides represents a valuable support for molecular and cellular biologists

Pengaruh Pemberian Minyak Nigella Sativa Dan Kombinasinya Dengan Seftriakson Terhadap Jumlah Kuman Methicillin Resistant Staphylococcus Aureus (Mrsa) Pada Kultur Otak Mencit Balb/c

Background Methicillin Resistant Staphylococcus aureus (MRSA) infection cases reported to be high. This matter is caused by the bacteria resistance to many antibiotics, from this point WHO suggested to looking for new antibiotics, in this research utilize N.sativa oil that have antibacterial and immunomodulator effects. The combination of N.sativa oil with ceftriaxone is expected to resolve MRSA infection cases.Aims To investigate the effect of N.sativa oil administration and its combination with ceftriaxone toward MRSA bacteria count in cultured brain of BALB/c mice.Methods Experimental laboratory with post test only control group design. Total sample were 20 male BALB/c mice randomized into 4 groups and adapted for 7days. Every group was injected with MRSA ATCC 43300 0,2ml, after 16 hours K was given aquabidest 0,03 ml, P1 was given ceftriaxone 0,03 ml, P2 was given N.sativa oil 0,3 ml, P3 was given ceftriaxone 0,03 ml and N.sativa 0,3 ml, after 8 hours would be terminated. Data normality test used Saphiro-wilk test followed by Kruskal-Wallis and Mann-Whitney test.Results The result of the average number of MRSA on brain culture, K= 128x103+ 157,25x103 cfu/ml; P1= 4,18x103+3,22x103 cfu/ml; P2= 0,12x103+0,11x103 cfu/ml; P3= 0,68x103 +1,30x103 cfu/ml. Significant differences was found between K with P2 (p=0,009) and P3(p=0,028), while with P1(p=0,346) wasn't. Bacteria count between P1 with P2(p=0,009) and P3(p=0,028) showed a significant differences, and between P2 with P3(p=0,754) there was no significant difference.Conclusion Administration of Nigella sativa oil and its combination with ceftriaxone can decrease number of MRSA bacteria in BALB/c mice's brain cultures

Neutrino Mixing and Oscillations in Quantum Field Theory

We show that the generator of field mixing transformations in Quantum Field Theory induces a non trivial structure in the vacuum which turns out to be a coherent state, both for bosons and for fermions, although with a different condensate structure. The Fock space for mixed fields is unitarily inequivalent to the Fock space of the massive (free) fields in the infinite volume limit. As a practical application we study neutrino mixing and oscillations. A new oscillation formula is found where the oscillation amplitude is depressed, with respect to the usual one, by a factor which is momentum and mass dependent. In the relativistic limit, the usual formula is recovered. We finally discuss in some detail phenomenological features of the modified oscillation formula.Comment: 13 pages, LaTex + 1 figure. Talk given at the XIXth International Conference on Particle Physics and Astrophysics in the Standard Model and Beyond, Bystra, Poland, September 19-26, 199