The world faces two seemingly unrelated challenges—a shortfall in the STEM workforce and increasing antibiotic resistance among bacterial pathogens. We address these two challenges with Tiny Earth, an undergraduate research course that excites students about science and creates a pipeline for antibiotic discovery.

Lemonomycin (1) was first isolated from the fermentation broth of Streptomyces candidus in 1964. The complete chemical structure was not elucidated until 2000 with extensive spectroscopic analysis. Lemonomycin is currently known as the only glycosylated tetrahydroisoquinoline antibiotic. Its potent antibacterial activity against Staphylococcus aureus and Bacillus subtilis and complex architecture make it an ideal target for total synthesis. In this short review, we summarize the research status of lemonomycin for biological activity, biosynthesis and chemical synthesis. The unique deoxy aminosugar-lemonose was proposed to play a crucial role in biological activity, as shown in other antibiotics, such as arimetamycin A, nocathiacin I, glycothiohexide α, and thiazamycins. Given the self-resistance of the original bacterial host, the integration of biosynthesis and chemical synthesis to pursue efficient synthesis and further derivatization is in high demand for the development of novel antibiotics to combat antibiotic-resistant infections.

Proteolysis Targeting Chimeras (PROTACs) describe compounds that bind to and induce degradation of a target by simultaneously binding to a ubiquitin ligase. More generally referred to as bifunctional degraders, PROTACs have led the way in the field of targeted protein degradation (TPD) with several compounds currently undergoing clinical testing. Alongside bifunctional degraders, single-moiety compounds, or molecular glue degraders (MGDs), are increasingly being considered as a viable approach for development of therapeutics, driven by advances in rational discovery approaches. This review focusses on drug discovery with respect to bifunctional and molecular glue degraders within the ubiquitin proteasome system, including analysis of mechanistic concepts and discovery approaches, with an overview of current clinical and pre-clinical degrader status in oncology, neurodegenerative and inflammatory disease.

Background: Antibiotic resistance is an urgent issue everywhere in the globe. It is necessary to look into new sources of antibiotics to address this issue. Aim of the study: studying the purification of Corallopyronin B from various soil conditions in Egypt, as well as the antibacterial effectiveness of Corallopyronin B in preclinical animal testing and randomized human clinical trials phases 1/2. Type of the study: Screening experimental study. Methodology: Several soil conditions in Egypt were examined to create bacterial isolates that generated the antibiotic chemical Corallopyronin B. Using reversed-phase HPLC, Myxopyronin B was purified. The test antibiotic's minimum inhibitory concentration( MIC) and in vitro antibacterial activity were ascertained using the paper disc diffusion assay and the broth microdilution technique. Furthermore, in stages 1/2 of randomized clinical trials including human and animal models, pharmacokinetics, adverse drug reactions, and the in vivo antibacterial spectrum were discovered. Results: The soil bacterial isolate Corallococcus coralloides DSM 2259, which was grown on a Casein yeast peptone( CYP) plate, produced Corallopyronin B from its culture supernatant. At MICs more than 100 mcg/ml, the test antibiotic inhibited the growth of many Gram -ve bacteria, including Escherichia coli, while also preventing the growth of numerous Gram +ve bacteria, with MICs ranging from 1 to 10 mcg/ml. Eukaryotic cells, on the other hand, including those in humans and fungi, were unharmed. The test antibiotic was shown to have a bactericidal effect by inhibiting bacterial DNA-dependent RNA polymerase( RNLP). In phases 1/2 of randomized human clinical trials, when 600 mg of the dose per 70 kg of body weight was administered SC, the Cmax was 8.6 mcg/ml at Tmax 1 hour; T1/2 reached 136 min following first-order kinetics of elimination. It stopped acting around 6-7 hours after SC was administered. In the preclinical and randomized human clinical trial phases 1/2, less than 6 percent of experimental candidates had uncommon toxicity, which showed up as reduced bile flow. Protein binding with plasma albumin was detected which reached about 83%. Conclusion: The current work was noteworthy since it involved the production of the bactericidal antibiotic Corallopyronin B from Corallococcus coralloides DSM 2259 which was isolated from several soil environments in Egypt.

Background: Antibiotic resistance is an overwhelming serious difficulty globally. This necessitates the exploration of novel sources of antibiotics to overcome this challenge. Aim of the study: Bacterial Myxopyronin A production from various soil environments Egypt; as well as testing its antimicrobial activity in preclinical animal testing and randomized human clinical trials phases 1/2. Type of the study: Screening experimental study. Methodology: Different soil environments in Egypt were screened for the growth of bacterial isolates producing Myxopyronin A as an antimicrobial agent. Purification of Myxopyronin A was performed via reversed-phase HPLC. Paper disc diffusion assay, as well as the Broth dilution technique, were exploited to assess the invitro antimicrobial and minimum inhibitory concentration( MIC) of the test antibiotic. Furthermore, in vivo antimicrobial spectrum, adverse drug reactions, and pharmacokinetics were detected during animal model testing stages and human randomized clinical trials phases 1/2. Results: From the culture supernatant of the Myxobacterium Myxococcus fulvus 124B02 which was the predominant soil bacterial isolate grown on the Casein yeast peptone plate, Myxopyronin A was produced. The test antibiotic blocked the growth of many Gram +ve bacteria with MICs less than 100 mcg/ ml. In contrast, it inhibited the growth of a few Gram -ve bacteria such as Escherichia coli at MICs greater than 100 mcg/ ml. On the other hand, Eukaryotic cells such as fungal and human cells were not affected. Prokaryotic DNA-dependant-RNA polymerase( RNLP) was noticed to be inhibited via the test antibiotic suggesting its bactericidal action. The maximum concentration was 7-8 mcg/ ml at a maximum time of 2 hours when 600 mg dose was orally administered in randomized human clinical trials phases 1/2, and T1/2 reached 2.5 hours following first-order kinetics of elimination. The duration of its action was nearly 12 hours after oral administration. Rare toxicity was detected during preclinical and randomized human clinical trials phases 1/2 in the form of mild diarrhea and cholestatic jaundice in less than 5 % of experimental candidates. Conclusion: The present study was promising due to the bactericidal antibiotic Myxopyronin A production from Myxococcus fulvus 124B02 isolated from different soil environments in Egypt.

The global usage of veterinary antibiotics is significant. These antibiotics can be released into the aquatic environment and exert toxic effects on non-target organisms. To explore the physiological effects of tetracycline antibiotics on aquatic life, the growth characteristics of and toxin release from the cyanobacterium Microcystis aeruginosa (M. aeruginosa) were studied. Results showed that the toxicity order of the three target antibiotics was TC (tetracycline) > CTC (chlortetracycline hydrochloride) > OTC (oxytetracycline) in terms of inhibition occurrence time and the EC₁₀ and EC₂₅ values. Further, the target antibiotics regulated the production of MC-LR (microcystin-LR) to different degrees. CTC destroyed the M. aeruginosa cells and resulted in a decreased MC-LR release but stimulated the ability to synthesise MC-LR. OTC had a relatively weaker toxicity compared with CTC, while TC was the most toxic among the three antibiotics. Therefore, TC is friendly to the aquatic environment because it simultaneously reduced the intracellular and extracellular MC-LR content. These results aid our understanding of the effects of tetracycline antibiotics on Microcystis aeruginosa, which is important for environmental evaluation and protection. These results are also helpful for guiding the application of veterinary antibiotics in agricultural settings.

Based on screening in computational biology and biological in vitro assays, five natural products isolated from extracts of the herbal medicine toad skin, such as cinobufagin (CBFi), bufalin (BFi), arenobufagin (ABFi), telocinobufagin (TBFi), bufotalin (BFTi), were subjected to molecular docking calculations with the use of SARS-CoV-2 main protease (PDB 6LU7 and 7BTF) and top-scoring ligand-receptor complexes were obtained. The results showed that the binding energy of ABFi to the 3CL protein was -17.044kcal/mol, which was higher than CBFi and TBFi. However, the binding energy of ABFi to the RdRp protease was -23.250 kcal/mol, which was much lower than that of CBFi and TBFi, EVEN lower than that of ABFi to the 3CL protein. ABFi also has polar interactions with amino acids such as Glu811, Ser814, Ser681 and Thr680 of RdRp enzyme. The results revealed that ABFi had a moderate inhibitory effect on the cell proliferation of SARS-CoV-2 in vitro, with an inhibition rate of 61.12%, even weaker than Remdesivir. This new discovery provides us with new ideas for in-depth studies on the development of natural products with this class of structural generalizations as inhibitors of SARS-CoV-2, and provides an experimental basis for the next step of mechanistic studies.

The hospital indoor environment plays a significant role in shaping the microbial exposures that humans encounter. Resistance to antibiotics is one of the mechanisms employed by bacteria to develop resilience against stress in indoor environments. The extensive usage of antibiotics has been a key factor in driving changes in the ecological function of antibiotic resistance genes (ARGs) and their acquisition by pathogenic bacteria. By integrating the 16S rRNA Illumina sequencing and high throughput-qPCR approaches with water and air dust samples across seven departments at Peking University Shenzhen Hospital, China, this study yielded intriguing findings regarding the department-specific variation, transmission, and correlation of bacteria, ARGs and MGEs within the hospital indoor environment. One notable observation was that the seasonal variation played a vital role in shaping the bacterial composition in the overall hospital indoor environment across seven studied departments. Nevertheless, a similar significant seasonal impact was only observed in the blood test room and emergency departments, rather than in the other five departments. Another intriguing finding was the correlation between ARGs and MGEs abundance. This correlation was evident in the overall hospital indoor environment, which was conversely not found in the emergency, pneumology and gynecology departments. Additionally, while there was no significant relationship that occurred between bacterial communities and ARGs/MGEs within the hospital, the gynecology department demonstrated a close link between bacterial communities and the presence of ARGs/MGEs. Notably, the gynecology department also stood out as an important source of bacteria and ARGs/MGEs for other departments. This study underscores the need for careful surveillance and monitoring of antibiotic resistance, particularly in Legionella spp. in man-made water systems. The findings also show the importance of monitoring and understanding the genetic elements such as Tp614 involved in gene transfer and recombination, as well as their impact on antimicrobial treatment efficacy.

Molecularly imprinted polymers (MIPs) were synthesized and applied for the selective extraction of oblongifolin C (OC) from fruit extracts of Garcinia yunnanensis Hu. A series of experiments and computational approaches were employed to improve the efficiency of screening for optimal MIP systems in the study. The molar ratio (1:4) was chosen at last based on the comparison of the binding energy of the complexes between the template (OC) and functional monomers using density functional theory (DFT) at the RI-PBE-D3-gCP/def2-TZVP level of theory. The binding characterization and the molecular recognition mechanism of MIPs were further explained using the molecular modeling method and NMR and IR spectra data. The reusability of this approach was demonstrated in over 20 batch rebinding experiments. 140.5 mg of OC (>95% purity) was obtained from the 5 g extracts with 2 g of MIPs with the best binding properties through gradient elution program from 35% to 70% methanol-water solution. At the same time, another structural analog, 46.5 mg of guttiferone K (GK) (>88% purity), was also obtained by the gradient elution procedure. Our results showed that the structural analogs could be separated from the crude extracts by the molecularly imprinted solid-phase extraction (MISPE) using a gradient elution procedure for the first time.

The first half of the 20th century was noteworthy for the introduction of a unique group of drugs – antibiotics. It drastically changed concepts of infectious diseases treatment, which for centuries remained a scourge of the human population. With improvement of the antibiotic treatment efficacy, humanity has faced the problem of a dramatic increase in antibiotic resistance in bacteria. The COVID-19 pandemic has only exacerbated the problem and posed a new challenge to the medical community in finding solutions, both clinical and organizational and methodological, to fight antibiotic resistance widespread all over the globe. This publication covers some aspects of evolutionary processes in either pathogens or diseases, including ethical perspective.

Lead optimization in drug discovery is a crucial phase where initial hits are refined into compounds with improved pharmacological properties. While traditional methods rely on manual experimentation and modifications, AI-driven techniques have revolutionized this process by leveraging big data and predictive modeling. This review explores how AI-driven approaches accelerate lead optimization, showcasing examples like deep neural networks and reinforcement learning. Integration of multi-omic data and experimental validation further enhances AI-driven strategies. The future lies in refining these AI methods, democratizing tools, and interdisciplinary collaboration to streamline drug discovery and address medical needs efficiently.

Background: Bacteria can survive antibiotic exposure by mechanisms like tolerance without a shift in antimicrobial susceptibility. In this study, we investigated the presence of tolerance to three antimicrobials, ceftriaxone (CRO), azithromycin (AZM), and ciprofloxacin (CIP), in clinical isolates and WHO reference panel of N. gonorrhoeae and explored the prevalence between urogenital and anorectal infection sites. Methods: We examined 66 N. gonorrhoeae clinical isolates, evenly divided between anorectal and urogenital infection sites, using a modified tolerance disk (TD test) for three antibiotics. The isolates underwent a three-step incubation process wherein the isolates were exposed to an antibiotic disc for 20 hours of incubation (Step I), followed by the replacement of the antibiotic disc with a nutrient disc for overnight incubation (Step II) and additional overnight incubation with extra nutrients (Step III). Results: Four isolates were lost due to contamination. Of 62 clinical isolates, 7 exhibited tolerance to AZM, with 6 from anorectal and 1 from urogenital sites (p = 0.0496). Tolerance to CRO was observed in 11 isolates, which was significantly associated with the infection site, with 9 from the anorectum, and 2 from the urogenital site being tolerant (p = 0.02). Tolerance to CIP was found in 11 isolates, but was not significantly associated with the infection site. Tolerance was also detected in 8 (K, M, N, O, P, U, V, W) out of the 14 WHO (World Health Organization) reference strains, with varying patterns of tolerance to CRO (n=8), CIP (n=2) and AZM (n=1). Conclusion: This study identified CRO, AZM, and CIP tolerance in clinical Neisseria gonorrhoeae isolates. Significant variations in tolerance proportions between anorectal and urogenital infection sites, particularly for CRO, were observed. Additionally, tolerance was detected in WHO reference strains.

The over use of pharmaceutical compounds, essentially antibiotics, led to an increase of their concentrations in aquatic ecosystems. In this study, the white-rot fungus Coriolopsis gallica (high-laccase-producing fungus) was investigated for the biodegradation of ampicillin (AMP) under different cultivation conditions. The biotransformation of the antibiotic was confirmed by means of high-performance liquid chromatography (HPLC), and the antibacterial activity was evaluated via the bacterial growth inhibition agar well diffusion method using Escherichia coli as an ampicillin-sensitive test strain. The results showed that AMP (50 mg L-1) was totally removed by C. gallica after 6 days of incubation in a liquid medium. The antibiotic removal rate was maximal with a fungal culture aged 9 days. Such a culture achieved the removal of a higher concentration of up to 500 mg L-1 of ampicillin in 3 days. This higher antibiotic removal rate was concomitant with the maximal laccase production in culture supernatant. In addition, four consecutive doses of 500 mg L-1 of ampicillin were transformed by the same fungal culture in 24 days. After that, the fungus was unable to remove the antibiotic. The measurement of ligninolytic enzyme activity showed that laccase of C. gallica might participate in the biotransformation of AMP.

Methicillin-resistant Staphylococcus aureus (MRSA) infections, in particular biofilm-organized bacteria, remain a clinical challenge and a serious health problem. Rifabutin (RFB), an antibiotic of the rifamycins class, has shown in previous work excellent anti-staphylococcal activity. Here, we proposed to load RFB in liposomes aiming to promote the accumulation of RFB at infected sites and consequently enhancing the therapeutic potency. Two clinical isolates of MRSA, MRSA-C1 and MRSA-C2, were used to test the developed formulations, as well as the positive control, vancomycin (VCM). RFB in free and liposomal forms displayed high antibacterial activity, with minimal inhibitory concentrations (MIC) ranging from 0.009-0.013 μg/mL and MBIC50 values ranging from 0.008-0.012 μg/mL, in planktonic and biofilm bacteria, respectively. Confocal microscopy studies demonstrated the rapid internalization of unloaded and RFB-loaded liposomes in the bacterial biofilm matrix. In murine models of systemic MRSA-C1 infection, Balb/c mice were treated with RFB formulations and VCM at 20 and 40 mg/kg of body weight, respectively. Obtained data proved the superior therapeutic effectiveness of RFB formulations compared to Control and VCM groups even using a two-fold lower therapeutic dose as demonstrated by significantly reduced bacterial burden and growth index values in major organs. In addition, RFB formulations were the only formulations associated with 100% survival. Globally, this study emphasizes the potential of RFB nanoformulations as an effective and safe approach against MRSA infections.

Bacteria that have become resistant to antibiotics, also known as superbugs,pose a huge threat to the human population. This is because these developed resistance to antibiotics. Antibiotics are a type of medicine that fights bacteria by either killing it or preventing it from growing. Although antibiotics make the once deadly now easily treatable, they can become ineffective as bacteria develop resistance to the antibiotic, causing diseases to become potentially fatal once more. Thus, scientists are rushing to find solutions in this arms race against evolving bacteria by either evolving current antibiotics or discovering new stands to fight evolving bacteria. In order to discover whether bacteria can develop resistance to household antibiotics, a controlled experiment was conducted. This was done by growing bacteria on agar plates with antibiotic ointments applied (in dilution series) to see if antibiotic resistance could build. Theorizing that by lowering the concentration of over the counter antibiotics, resistant bacteria would be selected and my bacterial population would evolve antibiotic resistance.In conclusion of the experiment antibiotic resistance did appear as a trait, but the level of it was inconsistent across the different bacteria populations.

In a dynamic production processes, mechanical degradation poses a significant challenge, impacting product quality and process efficiency. This paper explores a novel approach for monitoring degradation in the context of viscose fiber production, a highly dynamic manufacturing process. Using causal discovery techniques, our method allows domain experts to incorporate background knowledge into the creation of causal graphs. Further, it enhances the interpretability and increases the ability to identify potential problems via changes in causal relations over time. The case study employs a comprehensive analysis of the viscose fiber production process within a prominent textile industry, emphasizing the advantages of causal discovery for monitoring degradation. The results are compared with state-of-the-art methods, which are not considered to be interpretable, specifically LSTM-based autoencoders, showcasing the alignment and validation of our approach. This paper provides valuable information on degradation monitoring strategies, demonstrating the efficacy of causal discovery in dynamic manufacturing environments. The findings contribute to the evolving landscape of process optimization and quality control.

Wilms tumor (WT), the most prevalent type of renal cancer in children, exhibits overall survival rates exceeding 90%. However, chemotherapy resistance, which occurs in approximately 10% of WT cases, is a major challenge for the treatment of WT, particularly for advanced-stage patients. In this study, we aimed to discover potential mutation markers and drug targets associated with chemotherapy resistance in advanced stage WT. We performed exome sequencing to detect somatic mutations and molecular targets in 43 WT samples, comprising 26 advanced stage WTs, of which 7 cases are chemotherapy-resistant. Our analysis revealed four genes (ALPK2, C16orf96, PRKDC, and SVIL) that correlated with chemotherapy resistance and reduced disease-free survival in ad-vanced-stage WT. Additionally, we identified driver mutations in 55 genes within the chemo-therapy-resistant group, including 14 druggable cancer driver genes. Based on the mutation profile of the resistant WT samples, we propose potential therapeutic strategies involving platinum-based agents, PARP inhibitors, and antibiotic/antineoplastic agents. Our findings provide insights into the genetic landscape of WT and offer potential avenues for targeted treatment, particularly for patients with chemotherapy resistance.

Probiotics are microorganisms infused in products for health benefits including acceleration of nutrient digestion, however, it is also important to ensure the safety prior to incorporation. Here, we present evidence of the ability of two probiotic isolates,Lacticaseibacillus paracasei BCRC-16100 and Lacticaseibacillus paracasei ZFM54, in the (1) enhancement of carbohydrate digestion, (2) tolerance to stress, and (3) antibiotic resistance. Approaches include whole genome sequence (WGS) analysis and bioactivity assays. WGS revealed genes suggesting the ability of the two isolates to promote carbohydrate digestion, tolerance to stress and antibiotic resistance. Carbohydrate digestive ability was confirmed through a biochemical assay where the two isolates cause glucose release from starch. The two isolates also showed versatility in a range of temperature and alcohol concentration. For antibiotic resistance particularly on vancomycin, there are three mechanisms namely transporter control, transcriptional regulation, and efflux pump. Furthermore, promoter and transposable element analysis showed that some of the active antibiotic resistant (AbR) genes can be laterally transferred. Altogether, we show the potential of two probiotic isolates to be incorporated in products for improved carbohydrate digestion and the need to address the removal of active and mobile antibiotic resistance genes that may compromise safety.

In this work, the resistance/susceptibility (R/S) profile of Staphylococcus equorum strains (n=30) from cheese to 16 antibiotics was determined by broth microdilution. The minimum inhibitory concentration (MIC) for all antibiotics was low in most strains, although higher MICs compatible with acquired genes were also noted. Genome analysis of 13 strains showed the S. equorum resistome to be composed of intrinsic mechanisms, acquired mutations, and acquired genes. However, the genetic data did not always correlate with the phenotype. As such, a cat gene providing resistance to chloramphenicol was found on a plasmid in one strain; this was able to provide resistance to Staphylococcus aureus after electroporation. An msr(A) polymorphic gene was identified in five strains. The Mrs(A) variants were associated with variable resistance to erythromycin. All strains harboured a polymorphic fosB/fosD gene, although only one acquired copy was associated with strong resistance to fosfomycin. Similarly, a plasmid-associated blaR1-blaZI operon encoding a penicillinase was identified in five ampicillin- and penicillin G-susceptible strains. Identified genes not associated with resistance further included mph(C) in two strains and norA in all strains. The antibiotic R/S status and gene content of S. equorum strains intended to be employed in food systems should be carefully determined.

β-Lactams are pharmacologically important compounds because of their various biological uses, including antibiotic and so on. β-Lactams were synthesized from benzylidene-inden derivatives and acetoxyacetyl chloride. The inhibitory effect of these compounds was also examined for human carbonic anhydrase I and II (hCA I, and II) and acetylcholinesterase (AChE). The results reveal that β-lactams are inhibitors of hCA I, II and AChE. The K_i values of β-lactams (2a-k) were 0.44-6.29 nM against hCA I, 0.93-8.34 nM against hCA II, and 0.25-1.13 nM against AChE. Our findings indicate that β-lactams (2a-k) inhibit both CA isoenzymes and AChE at low nanomolar concentrations.

The exponential rise of bacterial resistance poses a threat to antibiotic efficacy, with a great impact on public health. This study aims to analyze the correlation between antibiotic consumption and the emergence of bacterial resistance. Conducted retrospectively at Charles Nicolle Hospital in Tunis, Tunisia from 2010 to 2022, this study was based on STKMED® software for antibiotic consumption data, hospital administrative records for the number of hospitalization days, and SIRSCAN® software for bacteriological data. Data processing was performed using Excel® software, and analysis was conducted using SPSS23®. In 2022, Consumption was almost evenly split between the two major “AWaRe” groups, with 49.33% for "Access" and 46.89% for "Watch", and the consumption of the "Reserve" group also increased, accounting for 3.77% of the total. Bacterial resistances, notably carbapenem-resistant Klebsiella pneumoniae, increased. Seventy-four significant correlations were identified, including those be-tween carbapenem consumption and resistance in Escherichia coli and Klebsiella pneumoniae strains. However, no significant corre-lation was observed with imipenem-resistant Pseudomonas aeruginosa strains. The significant correlations between the emergence of bacterial resistance and antibiotic use, particularly with antibiotics in the "Watch" and "Reserve" groups, underscore the urgent need to continue efforts to combat this threat through rational antibiotic use.

Candidiasis is considered an emerging public health concern because of the occurrence of drug-resistant Candida strains and the lack of available structurally diverse antifungal drug armamentariums. The indole alkaloid globospiramine from the anticandidal Philippine medicinal plant Voacanga globosa exhibits a variety of biological activities; however, its antifungal properties remain to be explored. In this study, we report the in vitro antifungal activities of globospiramine against Candida albicans and Candida tropicalis and explore its possible target proteins using in silico methods. The colony-forming unit (CFU) viability assay revealed time- and concentration-dependent anticandidal effects of the alkaloid by decreasing almost 50% of the viable CFUs 60 min after treatment. Results of the MIC and MFC assays indicated inhibitory and fungicidal effects of globospiramine against C. albicans (MIC = 8 µg/mL; MFC = 4 µg/mL) and potential fungistatic effects against C. tropicalis at lower concentrations (MIC = 4 µg/mL; MFC > 64 µg/mL). The FAM-FLICA poly-caspase assay showed metacaspase activation in C. albicans cells at concentrations of 16 and 8 µg/mL, which agreed with the MIC and MFC values. Molecular docking and molecular dynamics simulation experiments indicated stable, strong binding of globospiramine with the target proteins 1,3-β-glucan synthase and Als3 adhesin enzymes, which are indirectly involved in apoptotic-driven candidal inhibition.

The emergence of antimicrobial resistance have represented a serious threats for public health and infections due to multidrug-resistant (MDR) microorganisms represent one of the most important causes of death worldwide. The renew of old antimicrobials, such as colistin, have been proposed as valuable therapeutic alternative to the emergence of the MDR microorganisms. Although colistin is well known to presents several adverse toxic effect, its usage in clinical practice have been reconsidered due to the broad spectrum of activity to gram-negative (GN) bacteria and to the important role of “last resort” agent against MDR-GN. Despite the revolutionary prospective of treatment of this old antimicrobial molecule, many questions remain open regarding the emergence of novel phenotypic traits of resistance and the optimal usage of the colistin in clinical practice. In the last years, several forward steps have been done in the understanding of resistance determinants, clinical usage and pharmacological dosage of this molecule, however, different points regarding the role of colistin in clinical practice and the optimal pharmacokinetic/pharmacodynamic targets are not well defined yet. In this review, we summarize the mode of action, the emerging resistance determinants and its optimal administration in the treatment of difficult-to-treat infections due to MDR Gram-negative bacteria.

The integration of bioinformatics in drug discovery has revolutionized the field of pharmaceutical research. The use of computational tools and techniques has enabled researchers to analyze vast amounts of data, identify potential drug targets, and design new drugs with greater precision and efficiency. The integration of bioinformatics has also facilitated the development of personalized medicine, where drugs can be tailored to individual patients based on their genetic makeup. However, there are still challenges that need to be addressed, such as the need for more accurate predictive models and the ethical considerations surrounding the use of patient data. Overall, the integration of bioinformatics in drug discovery holds great promise for improving human health and advancing our understanding of disease mechanisms. In this mini-review, we discuss how Bioinformatics plays a crucial role in each step of drug discovery by providing tools and techniques to analyze large amounts of data generated from various sources, as well as the challenges and the opportunities offered by bioinformatics.

Background: Circulating rare cells participate in breast cancer evolution as systemic components of the disease and thus, are a source of theranostic information. Exploration of cancer-associated rare cells is in its infancy. We determined the validity of a rare-cell detection platform and demonstrated the usefulness of a certain rare cell subset as a novel approach to characterize the breast cancer system. Methods: Linearity of the Rarmax® platform was established using a spike-in approach. The platform includes red blood cell lysis, leukocyte depletion and high-resolution fluorescence image recording. Rare cell analysis was conducted on 28 samples (before and after surgery) from 14 patients with breast cancer, 20 healthy volunteers and 9 non-cancer control volunteers. In-depth identification of rare cells, including circulating tumor cells, endothelial-like cells, erythroblasts and inflammation-associated cells, was performed using a phenotype and morphology-based classification system. Results: The platform performed linearly over a range of 5-950 spiked cells, with an average recovery of 84.6%. Circulating epithelial and endothelial-like cell subsets have been demonstrated to be associated with or independent of cancer with tumor presence. Furthermore, certain cell patterns may be associated with treatment-related adverse effects. The sensitivity in detecting tumor-presence and cancer-associated abnormality before surgery was 50% and 85.7%, respectively and the specificity was 100% and 96.6%, respectively. Conclusion: The present study supports the idea of a cancer-associated rare cell abnormality to represent tumor entities as well as systemic cancer. The latter is independent of the apparent clinical cancer.

Medicinal activities carried out within hospitals lead to a high consumption of antibiotics and subsequently result in a high excretion rate of antibiotic residues. These antibiotics consumed in human medicine are not fully absorbed by the body and are often discharged into the environment as biological waste from infected human patients. The significant water consumption in hospitals and the pharmaceutical impact on wastewater from healthcare facilities facilitate the emergence and spread of antibiotic-resistant bacteria and antibiotic-resistant genes in the environment. Hospital effluents could be doubly involved in the dissemination of antibiotic molecules and multidrug-resistant bacteria in various ecosystems. The objective of this study is to characterize hospital effluents by assessing antibiotic concentrations and the diversity of antibiotic-resistant bacteria in these hospital wastewaters and within the environment (aquatic environments; rivers), as well as to inventory the bacteria present and those carrying antibiotic resistance in both hospital wastewater and the environment.

Mosquitoes conveying Plasmodium store parasites into the skin of the mammalian host. Parasites make a trip through the circulation system to the liver, where they cross a few hepatocytes prior to building up a disease. Inside the last hepatocyte the parasite goes through morphogenesis and afterward abiogenetically partitions to become more than 20,000 blood-infective parasites, called merozoites. On account of P. vivax, P. ovale, and P. cynomolgi, the parasites can stay lethargic in the liver in structures called hypnozoites. The merozoites are delivered once again into the circulation system, where they start the repetitive blood stage. Inside erythrocytes, a little division of parasites separate into male or female gametocytes. These gametocytes are ingested by the mosquito during blood taking care of, where they will duplicate explicitly, in the long run prompting the arrangement of sporozoites

Epilepsy is one of the most prevalent and serious brain disorders, affecting 70 million people worldwide. Antiseizure medications (ASMs) though relieve symptoms and prevent the occurrence of future seizures in epileptic patients have limited effect on epileptogenesis. Addressing the multifaceted nature of epileptogenesis and its association with Nod-like receptor family pyrin domain containing 3 (NLRP3) inflammasome-mediated neuroinflammation requires a comprehensive understanding of the underlying mechanisms for development of targeted therapeutic strategies beyond conventional antiseizure treatments. Several types of NLRP3 inhibitors have been developed and their effect has been validated both in vitro and in vivo models of epileptogenesis. In this review, we discuss the advances in understanding the regulatory mechanisms of NLRP3 activation as well as progress made and challenges facing in the development of NLRP3 inhibitors for the treatment of epilepsy.

Saccharomyces cerevisiae (S. cerevisiae) ethanol fermentation has left an indelible trace in human history. It is regarded as the original beverage synthesis, and has developed into an essential energy supply for mankind today. However, the history of ethanol synthesis using S. cerevisiae, including the mechanism analysis process, has not been carefully and succinctly reported. In this paper, we review the history of ethanol synthesis using S. cerevisiae. In addition, we also review the substrates that drive S. cerevisiae ethanol synthesis, including the utilization of glucose, sucrose, starch and molasses, in order to summarize the current development status and to contribute to the further improvement of this field.

Background: Public misconception and demand for the indication of antibiotics could lead to inappropriate prescribing and consumption. Successful treatment can only be achieved when the public and industrial users have knowledge on antibiotic use and resistance. This survey is aimed to assess antibiotic usage and knowledge regarding antibiotics and antimicrobial resistance (AMR) among undergraduate students of Universiti Brunei Darussalam (UBD), public university located in Brunei Darussalam. Methods: A cross-sectional study was performed using a self-administered questionnaire. The questionnaire was adapted from the World Health Organization (WHO) Antibiotic Resistance, Multi-country public awareness survey distributed online. Students at UBD were invited to participate in the online survey through internal email. The questionnaire consisted of 5 sections: demographic information, antibiotic usage, knowledge on antibiotics, antibiotic resistance (AMR) and use of antibiotics in agriculture. Data were analyzed descriptively and appropriate inferential statistics was used accordingly. Cronbach’s alpha was also done to determine the internal consistency. The section on antibiotic use and knowledge showed good internal consistency of Cronbach’s alpha 0.66 and 0.86 respectively. Research ethics approval was obtained from the PAPRSB Institute of Health Sciences, Universiti Brunei Darussalam (UBD). Results: A total of 145 students returned the complete questionnaire. The result of the study found that 50% of the students had good level of knowledge of antibiotic and antimicrobial resistance with a mean total knowledge score of 11.4 out of 14. Respondents reported the use of antibiotic in the past (69%). Many of the students could identify the use of antibiotics for the treatment of bacterial infection. However, there were also students who incorrectly thought that antibiotics can be used for cold and flu (43%) and fever (41%). Moreover, 76% of the respondents mistakenly believed that antibiotic resistance is the result of the body becoming resistant to antibiotics. Only 12% of the respondents were found to have poor knowledge in the study. Conclusions: Misconceptions in regards to the use of antibiotics for conditions related to viral illnesses was noticed among the respondents in our study. Thus, improving knowledge on antibiotics is crucial to address those beliefs.

Continuous discovery and update of applications or their boundaries running in cloud environments in an automatic way is a highly required function of modern data center ops solutions. Prior attempts to address this problem within various products or projects were/are applying rule-driven approaches or machine learning techniques on specific types of data − network traffic as well as property/configuration data of infrastructure objects, which all have their drawbacks in effectively identifying roles of those resources. The current proposal (ADLog) leverages log data of sources, which contain incomparably richer contextual information, and native constructs of VMware Aria Operations for Logs in terms of Event Types and their distributions to group those entities, potentially automatically enrich with indicative tags, and recommend for further management tasks and policies. Our methods discriminate not only diverse kinds of applications, but also their specific deployments thus providing hierarchical representation of the applications in time and topology. For several applications under Aria Ops management in our experimental test bed, we discover those in terms of similarity behavior of their components with a high accuracy. The validation of the proposal paves the path for an AI-driven solution in the cloud management scenarios.

Background: With continuous advances in next-generation sequencing (NGS), novel hepadnaviruses have been discovered in many species over the last 10 years. Methods: In this study, the cloud search and analysis of NGS data published in Nature by Edgar et al. was used as a basis to re-mine and reanalyze public NGS data for new hepadnaviruses. Results: Ultimately, at least 41 new species of hepadnaviruses were identified, including hepadnaviruses from the model animals hamster and mouse, frog hepadnavirus with pan-species infectivity, and diverse African cichlid hepadnaviruses that circulate within populations. Conclusions: The discovery of the new species of hepadnaviruses not only provides new clues for the study of the origin and evolution of hepadnaviruses, but also can be used to construct new hepadnavirus animal infection models, which will be helpful for the research of eradicative drugs for hepatitis B virus (HBV).

Process model discovery covers different methodologies to mine a process model from traces of process executions, and is gaining an important role in Artificial Intelligence research. Current approaches in the area, with few exceptions, focus on determining a model of the flow of actions only. However, in several contexts, (i) restricting the attention to actions is quite limitative, since the effects of such actions have to be analysed, too, and (ii) traces provide additional pieces of information, in the form of states (i.e., values of parameters possibly affected by the actions): for instance, in several medical domains traces include both actions and measurements of patients’ parameters. In this paper, we propose AS-SIM (Action-State SIM), the first approach able to mine a process model which comprehends two distinct classes of nodes, to capture both actions and states.

A wide variety of bacteria, fungi and plants can produce bioactive secondary metabolites, which are often referred to as natural products. With the rapid development of DNA sequencing technology and bioinformatics, a large number of putative biosynthetic gene clusters have been reported. However, only a few natural products can be detected when isolated species are grown under conventional laboratory conditions, as most biosynthetic gene clusters are not expressed or are expressed at extremely low levels at these conditions. With the rapid development of synthetic biology, advanced genome mining and modification strategies have been reported, and they provide new opportunities for discovery of natural products. This review discusses advances in recent years that can accelerate the design, build, test, and learn (DBTL) cycle of natural product discovery, and prospects trends and key challenges for future research directions.

After screening nearly 1000 synthetic peptides, a synthetic peptide termed JAL-AK22 (KYEGHWYPEKPYKGSGFRCIHI) derived from the BoxA domain in Tob1 protein was found to activate both unfolded and folded proMMP-7. In addition, JAL-AK22 showed auto-proteolytic activity. Interestingly, the smaller derivative of JAL-AK22 termed JAL-TA9 (YKGSGFRMI) also possessed auto-proteolytic activity and cleaved 2 fragment peptides (MMP18-33 and MMP18-40) derived from the prodomain of proMMP-7 under physiological conditions. These proteolytic activities were inhibited by AEBSF, a serine protease inhibitor. Our results demonstrate that a small synthetic peptide consisting of only 9 amino acids has serine protease-like activity and activates proMMP-7 by cleaving the prodomain region. We thus propose calling small peptides possessing with protease-like activity Catalytides (catalytic peptides). We expect that our findings will stimulate the development of novel Catalytides and related applications.

Antisense technologies consist of the utilization of oligonucleotides or oligonucleotide analogs to interfere with undesirable biological processes, commonly through inhibition of expression of selected genes. This field holds a lot of promise for the treatment of a very diverse group of diseases including viral and bacterial infections, genetic disorders, and cancer. To date, drugs approved for utilization in clinics or in clinical trials target diseases other than bacterial infections. Although several groups and companies are working on different strategies, the application of antisense technologies to prokaryotes still lags with respect to those that target other human diseases. In those cases where the focus is on bacterial pathogens, a subset of the research is dedicated to produce antisense compounds that silence or reduce expression of antibiotic resistance genes. Therefore, these compounds will be adjuvants administered with the antibiotic to which they reduce resistance levels. A varied group of oligonucleotide analogs like phosphorothioate or phosphorodiamidate morpholino residues, as well as peptide nucleic acids, locked nucleic acids and bridge nucleic acids, the latter two in gapmer configuration, have been utilized to reduce resistance levels. The major mechanisms of inhibition include eliciting cleavage of the target mRNA by the host’s RNase H or RNase P, and steric hindrance. The different approaches targeted resistance to β-lactams including carbapenems, aminoglycosides, chloramphenicol, macrolides, and fluoroquinolones.

Phytochemicals have a long and successful history in drug discovery. With recent advancements in analytical techniques and methodologies, discovering bioactive leads from natural compounds has become easier. Computational techniques like molecular docking, QSAR modelling and machine learning, and network pharmacology are among the most promising new tools that allow researchers to make predictions concerning natural products' potential targets, thereby guiding experimental validation efforts. Additionally, approaches like LC-MS or LC-NMR speed up compound identification by streamlining analytical processes. Integrating structural and computational biology aids in lead identification, thus providing invaluable information to understand how phytochemicals interact with potential targets in the body. Emerging computational approach is machine learning involving QSAR modelling and deep neural networks that interrelate phytochemical properties with diverse physiological activities such as antimicrobial or anticancer effects.

In the dynamic landscape of drug discovery, Computer-rAided Drug Design (CADD) emerges as a transformative force, bridging the realms of biology and technology. This paper overviews CADD's historical evolution, categorization into structure-based and ligand-based approaches, and its crucial role in rationalizing and expediting drug discovery. As CADD advances, incorporating diverse biological data and ensuring data privacy become paramount. Challenges persist, demanding the optimization of algorithms and robust ethical frameworks. Integrating Machine Learning and Artificial Intelligence amplifies CADD's predictive capabilities, yet ethical considerations and scalability challenges linger. Collaborative efforts and global initiatives, exemplified by platforms like Open Source Malaria, underscore the democratization of drug discovery. The convergence of CADD with personalized medicine offers tailored therapeutic solutions, though ethical dilemmas and accessibility concerns must be navigated. Emerging technologies like quantum computing, immersive technologies, and green chemistry promise to redefine the future of CADD. The trajectory of CADD, marked by rapid advancements, anticipates challenges in ensuring accuracy, addressing biases in AI, and incorporating sustainability metrics. The paper concludes by highlighting the need for proactive measures in navigating the ethical, technological, and educational frontiers of CADD to shape a healthier, brighter future in drug discovery.

Antibiotic resistance is a persistent and growing concern. Our objective was to analyze antibiotic prescribing in the United States (US) in the Medical Expenditure Panel System (MEPS) and to Medicaid patients. We obtained total MEPS prescriptions for eight antibiotics from 2013 to 2020. We extracted prescribing rates per 1,000 Medicaid enrollees for two years, 2018 and 2019, for four broad spectrum (azithromycin, ciprofloxacin, levofloxacin, and moxifloxacin) and four narrow spectrum (amoxicillin, cephalexin, doxycycline, and trimethoprim/sulfamethoxazole) antibiotics. Antibiotics in MEPS decreased from 2013 to 2020 by -38.7% with a larger decline for broad (-53.7%) than narrow (-23.5%) spectrum. Antibiotic prescriptions in Medicaid decreased by -6.7%. Amoxicillin was the predominant antibiotic followed by azithromycin, cephalexin, trimethoprim/sulfamethoxazole, doxycycline, ciprofloxacin, levofloxacin, and moxifloxacin. Substantial geographic variation in antibiotic prescribing existed with 2.8-fold between the highest (Kentucky = 855/1,000) and lowest (Oregon = 299) states. The South prescribed 52.2% more antibiotics (580/1,000) than the West (381/1,000). There were significant correlations across states in antibiotic prescribing. This study identified sizable disparities by geography in prescribing rates of eight antibiotics with over three-fold state level differences. Areas with high antibiotic prescribing rates, particularly for outpatients, may benefit from stewardship programs to reduce potentially unnecessary prescribing.

The mosquito microbiota reduces the vector competence of Anopheles to Plasmodium and affects host fitness, it is therefore considered as a potential target to reduce malaria transmission. While immune induction, secretion of antimicrobials and metabolic competition are three typical mechanisms of microbiota-mediated protection against invasive pathogens in mammals, the involvement of metabolic competition or mutualism in mosquito-microbiota and microbiota-Plasmodium interactions has not been investigated. Here, we describe a metabolome analysis of the midgut of An. coluzzii provided with a sugar-meal or a blood-meal, under conventional or antibiotic-treated conditions. We observed that the antibiotic treatment affects the tricarboxylic acid cycle and nitrogen metabolism, notably resulting in decreased abundance of free amino acids. Linking our results with published data, we identified candidate pathways which may participate in microbiota/Plasmodium interactions via metabolic interactions or immune modulation.

Despite significant strides in prevention, diagnosis, and treatment, cardiovascular diseases remain the number one cause of mortality in the United States, with rates climbing at an alarming rate in the developing world. Targeted delivery of therapeutics to the heart has been a lofty goal to achieve with strategies ranging from direct intra-cardiac or intra-pericardial delivery, intra-coronary infusion, to adeno-associated viral vectors which have preference, if not complete cardio-selectivity, for cardiac tissue. Cell penetrating peptides (CPP) are 5-30 amino acid long peptides that are able to breach cell membrane barriers while carrying cargoes up to several times their size, in an intact functional form. Identified nearly three decades ago, the first of these CPPs came from the HIV coat protein transactivator of transcription. Although a highly efficient CPP, its clinical utility is limited by its robust ability to cross any cell membrane barrier, including crossing the blood-brain barrier and transducing neuronal tissue non-specifically. Several strategies have been utilized to identify cell or tissue specific CPPs, one of which is phage display. Using this latter technique, we identified a cardiomyocyte targeting peptide (CTP) more than a decade ago, a finding that has been corroborated by several independent labs across the world that have utilized CTP for myriad different purposes in pre-clinical animal models. The goal of this publication is to provide a comprehensive review of the identification, validation, and application of CTP, and outlining its potential in diagnostic and therapeutic applications especially in the field of targeted RNA interference.

Mycobacterium tuberculosis (Mtb) is the etiological agent of tuberculosis (TB), a disease that alt-hough preventable and curable, remains a global epidemic due to the emergence of resistance and a latent form responsible for a long period of treatment. Drug discovery in TB is a challenging task due to the heterogeneity of the disease, the emergence of resistance and an uncomplete knowledge of the pathophysiology of the disease. The limited permeability of the cell wall and the presence of multiple efflux pumps remain a major barrier to achieve effective intracellular drug accumulation. While the complete genome sequence of Mtb has been determined and several potential protein targets have been validated, the lack of adequate models for in vitro and in vivo studies is a limit-ing factor in TB drug discovery programs. In current therapeutic regimens, less than 0.5% of bac-terial proteins are targeted being the biosynthesis of the cell wall and the energetic metabolism two of the most important processes exploited for TB chemotherapeutics. This review provides an overview on the current challenges in TB drug discovery and emerging Mtb druggable proteins, and how chemical probes for protein profiling enabled the identification of new targets and bi-omarkers, paving the way to disruptive therapeutic regimens and diagnostic tools.

Around the world, there is no population clear from urinary tract infection (UTI), particularly among women. UTI is considered the most predominant bacterial infection. This study aimed to detect the incidence of the most common major uropathogens in patients severe from urinary tract infection with antibiotic sensitivity tests that assist urologist doctors for appropriate antimicrobial empirical therapy.Methods: This study was carried in a private laboratory in Babil city, Iraq from May 2019 to May 2020. Totally 70 individuals suffering from clear symptoms of UTI, as well as, 20 healthy persons participated in this study as a control group. Then, the standard microbiological methods carried out to isolate and identify bacterial species. Antimicrobial susceptibility tests were performed using different antimicrobial discs by applying the Kirby–Bauer disc diffusion method.Results: Totally, 90 specimens were obtained from them 20 control group, 19 with no growth, and 51 patients with bacterial growth distributed as 43 (83%) females and 8 (17%) males. E. coli were the most common predominant organisms. All isolates were showed a high rate of resistance to evaluated cephalosporins 100% and 82% to cefotaxime and ceftriaxone respectively, while very low resistance recorded in Aminoglycosides 20% and 13% to Gentamicin and amikacin respectively. Most age group infected with UTI was 21-40 years old.Conclusion: The current study showed an increasing burden of urinary tract infection caused by various bacteria implicated in UTI that causes changeable sensitivity to various antimicrobial agents. Therefore, in clinical use appropriate medications should be selected based on the data obtained from antimicrobial susceptibility tests.

Introduction: The combination of Virtual Screening (VS) techniques with in vivo screening in the zebrafish model is currently being used in tandem for drug development in a faster and more efficient way. Areas covered: We review the different virtual screening techniques, the use of zebrafish as a vertebrate model for drug discovery and the synergy that exists between them. Expert opinion: We highlight the advantages of combining virtual and zebrafish larvae screening for drug discovery. On the one hand, VS is a faster and cheaper tool for searching active compounds and possible candidates for therapy than in vivo screening when processing large compound libraries. On the other hand, zebrafish larvae form a vertebrate model which allows in vivo screening of large amounts of the compounds. Importantly physiology and chemical response are mostly conserved between zebrafish and mammals. The availability of the transgenic and mutant zebrafish lines allows an analysis of a specific phenotype upon treatment along with toxicity, off-target effect, side effects, and dosage. Advantages of VS, in vivo whole animal approach screening, and the screening combinations are also reviewed.

Microbiome research has gained considerable interest due to the emerging evidence of its impact on human and animal health. Similar to higher organisms, the gut-associated microbiota of mosquitoes affect host fitness and other phenotypes. It is now well established that microbes can alter pathogen transmission in mosquitoes, either positively or negatively, and avenues are being explored to exploit microbes for vector control. However, less attention has been paid to how microbiota affect phenotypes that impact vectorial capacity. Several mosquito and pathogen components, such as vector density, biting rate, survival, vector competence and pathogen extrinsic incubation period all influence pathogen transmission. Interestingly, the mosquito gut-associated microbes can impact each of these components, and therefore ultimately modulate vectorial capacity. Promisingly, this expands the options available to exploit microbes for vector control by also targeting parameters that affect vectorial capacity. However, there are still many knowledge gaps in the biology of the mosquito – microbe symbiosis that need to be addressed in order to understand these interactions more thoroughly and exploit them efficiently. Here, we review current evidence of the impacts of the microbiome on aspects of vectorial capacity highlighting opportunities for novel vector control strategies and areas where further studies are required.

Induced pluripotent stem cells (iPSC) are derived from reprogrammed adult somatic cells. These adult cells are manipulated in vitro to express genes and factors essential for acquiring and maintaining embryonic stem cell (ESC) properties. This technology is widely applied in many fields, and there has been much attention to developing iPSC-based disease models to validate drug discovery platforms and study pathophysiological molecular processes underlying disease onset. Especially in neurological diseases, there is a great need for iPSC-based technological research, as these cells can be obtained from each patient and carry the individual’s bulk of genetic mutations and properties. Moreover, iPSC can differentiate into multiple cell types. These are essential characteristics since the study of neurological diseases is affected by limited access to injured sites, in vitro models composed of various cell types, the complexity of reproducing the brain’s anatomy, ethical issues, and the fact that post-mortem cell culture is challenging. Neurodegenerative diseases enormously impact global health due to their high incidence, symptoms severity, and usually lack of effective therapies. Recently, analyses using disease-specific iPSC-based models confirmed their efficacy for testing multiple drugs. This review summarizes the advances in iPSC technology used in disease modeling and drug testing with a primary focus on neurodegenerative diseases, including Parkinson’s and Alzheimer’s diseases.

In an era of unparalleled technical advancement, the pharmaceutical industry is struggling to transform data into increased research and development efficiency, and as a corollary, new drugs for patients. Here, we briefly review some of the commonly discussed issues around this counterintuitive innovation crisis. Looking at both industry and science related factors, we posit that traditional preclinical research is front-loading the development pipeline with data and drug candidates that are unlikely to succeed in patients. Applying a first principles analysis, we highlight the critical culprits and provide suggestions as to how these issues can be rectified through pursuit of a Human Data-driven Discovery (HD3) paradigm. Consistent with other examples of disruptive innovation, we propose that new levels of success are not dependent on new inventions, but rather the strategic integration of existing data and technology assets. In support of these suggestions, we highlight the power of HD3, through recently published proof-of-concept applications in the areas of drug safety analysis and prediction, drug repositioning, rational design of combination therapies and the global response to the Covid19 pandemic. We conclude that innovators must play a key role in expediting the path to a largely human focused, systems-based approach to drug discovery and research.

Meprin α is a zinc metalloproteinase (metzincin) that has been implicated in multiple diseases, including fibrosis and cancers. It has proven difficult to find small molecules that are capable of selectively inhibiting meprin α, or its close relative meprin β, over numerous other metzincins which, if inhibited, would elicit unwanted effects. We recently identified possible molecular starting points for meprin α-specific inhibition through an HTS effort (see part I, preceding paper). In part II we report the optimization of a potent and selective hydroxamic acid meprin α inhibitor probe which may help define the therapeutic potential for small molecule meprin α inhibition and spur further drug discovery efforts in the area of zinc metalloproteinase inhibition.

Meprin α and β are zinc-dependent proteinases implicated in multiple diseases including cancers, fibrosis, and Alzheimer’s. However, until recently, only a few inhibitors of either meprin were reported and no inhibitors are in pre-clinical development. Moreover, inhibitors of other metzincins developed in previous years are not effective in inhibiting meprins suggesting the need for de novo discovery effort. To address the paucity of tractable meprin inhibitors we developed ultra-high throughput assays and conducted parallel screening of >650,000 compounds against each meprin. As a result of this effort, we identified 5 selective meprin α hits belonging to three different chemotypes (triazole-hydroxyacetamides, sulfonamide-hydroxypropanamides, and phenoxy-hydroxyacetamides). These hits demonstrated a nanomolar to micromolar inhibitory activity against meprin α with low cytotoxicity and >30-fold selectivity against meprin β and other related metzincincs. These are the most selective inhibitors of meprin α to date.

Viral diseases are one of the leading causes of morbidity and mortality in the world. Virus-specific vaccines and antiviral drugs are the most powerful tools to combat viral diseases. However, broad-spectrum antiviral agents (BSAAs, i.e. compounds targeting viruses belonging to two or more viral families) could provide additional protection of general population from emerging and re-emerging viral diseases reinforcing the arsenal of available antiviral options. Here, we reviewed discovery and development of BSAAs and summarized the information on 120 safe-in-man agents in freely accessible database (https://drugvirus.info/). Future and ongoing pre-clinical and clinical studies will increase the number of BSAAs, expand spectrum of their indications, and identify drug combinations for treatment of emerging and re-emerging viral infections as well as co-infections.

The discovery and settlement of the tiny and remote Easter Island (Rapa Nui) has been a classical controversy for decades. Present-day aboriginal people and their culture are undoubtedly of Polynesian origin but it has been debated whether Native Americans discovered the island before the Polynesian settlement. Until recently, the paradigm was that Easter Island was discovered and settled just once by Polynesians in their millennial-scale eastward migration across the Pacific. However, the evidence for cultivation and consumption of an American plant, the sweet potato (Ipomoea batatas), on the island before the European contact (1722 CE), even prior to the Europe-America contact (1492 CE), revived the controversy. This paper reviews the classical archaeological, ethnological and paleoecological literature on the subject and summarizes the information into four main hypotheses to explain the sweet potato enigma: the long-distance-dispersal hypothesis, the back-and-forth hypothesis, the Heyerdahl hypothesis and the newcomer’s hypothesis. These hypotheses are evaluated in light of the more recent evidence (last decade), including molecular DNA phylogeny and phylogeography of humans and associated plants and animals, physical anthropology (craniometry, dietary analysis) and new paleoecological findings. It is concluded that, with the available evidence, none of the former hypotheses may be rejected and, therefore, all possibilities remain open. For future work, it is recommended to use the multiple-working-hypothesis framework and the strong inference method of hypothesis testing, rather than the ruling theory approach, very common in Easter Island’s research.

Staphylococcus aureus (S. aureus), particularly Methicillin-resistant S. aureus (MRSA), is a life-threatening pathogen that causes a variety of infections in hospital and community settings. It poses a significant risk and challenge for global health that hinders our ability to control and treat bacterial infections. Recently, the emergence and spread of variant strains of bacteria, misuse of the limited available options of effective antibiotics, spread of fake drugs, and climate change that increased the contact between humans and animals’ populations carrying different bacterial has significantly increased the incidence of Multi-Drug Resistance strains (MDR). This in turn, has created a severe problem in the infection control treatment of S. aureus infected patients. Treatment options for MRSA infection are increasingly limited and complicated. Unfortunately, different strains of MRSA are showing tolerance and resistance toward vancomycin, which is the standard of care for complicated MRSA. Therefore, it is crucial now to invest developing new effective anti-biotics and synergies, develop and implement national action plans for the management of an-tibiotic resistance, as well as improving our understanding of the antimicrobial resistance mechanisms. Here, in this review we explain the main mechanisms of antibiotic resistance in MRSA and describes different approaches to manipulate it in MRSA, providing a basis for de-signing effective drugs, and shedding some light on the evolution of S. aureus.

The development of antimicrobial resistance to conventional antibiotics is a major global health challenge. Infections caused by multidrug-resistant gram-negative bacteria have been named one of the most urgent global health threats. Considerable efforts are devoted to developing new antibiotic drugs and investigating the mechanism of antibiotic resistance. Recently, Anti-Microbial Peptides (AMPs) have emerged as a new platform for the target and design of novel drug resistant anti-microbial agents promising a new therapeutic strategy. AMPs are rapid, potent, possess an unusually broad spectrum of activity, and have shown efficacy as topical agents. Unlike traditional therapeutics that interfere with essential bacterial enzymes, AMPs interact with microbial membranes through electrostatic interactions and physically damage cell integrity. However, naturally occurring AMPs have limited selectivity and modest efficacy. Therefore, recent efforts have focused on the development of synthetic AMP analogs as suitable drug targets. This work explores the development of novel antimicrobial agents which mimic the structure of graft-copolymers and mirror the mode of action of an AMP. Chitosan-graft-polypeptide side chains are synthesized by the ring-opening polymerization of N-carboxyanhydrides of L-lysine and L-leucine initiated from the functional groups of chitosan. The derivatives with random- and block-copolymer side chains are explored as drug targets. These graft copolymer systems exhibit activity against clinically significant pathogens and disrupt biofilm formation. This work highlights the potential of chitosan-graft-polypeptide structures in biomedical applications.

The antibiotic or antimicrobial resistance is rapidly spreading in microbes relevant to human health. Two visible major contributory factors have been the indiscriminate overuse of antimicrobials for preventing diseases in human and to enhance the productivity in agriculture sector. To mitigate the potential threat posed by post-antibiotic era, the global health stakeholders have been making extra efforts at a war footing to formulate and implement global and national plans of action. In the current article, an endeavour is made to provide a perspective to look beyond the current focus on just use of the antimicrobials. Attention has been drawn towards various obvious and not-so-obvious self-preservation infection-prevention practices in vogue from the pre-antibiotic era whose usage has been on decline in the antibiotic era for various reasons. Particularly, the practices with a clear potential to effectively decrease the spread of pathogens through contact, curtail the evolution and dissemination of the antimicrobial resistance in local environment and its introduction into the global community, should be Identified and strengthened to make them part of comprehensive hygiene and quarantine practices. Broadly, the suggestions pertaining to the personal and community hygiene including bereavement practices, isolation and quarantine of suspected pathogen carriers, and water and environment security have been made to invoke a constructive debate and discussion among various stakeholders for their evaluation and implementation to effectively delay the development of antimicrobial resistance wherever possible and disrupt its spread to pathogens.

Non-systemic oral drugs, which do not get absorbed through the gastrointestinal membrane, are an important group of compounds for targeting diseases residing within the gastrointestinal lumen. However, they require a set of design principles not sufficiently covered by traditional druglikeness metrics, such as Lipinski’s Rule of 5. These druglikeness metrics fail to accurately identify true negative outcomes; such is the requirement for novel cheminformatic based approaches for the discovery of non-systemic small molecules. One such example of these newer metrics is the fraction of SP3-hybridised carbon atoms (fSP3) which has shown promising application as an identifier of poor oral-bioavailability. Herein, we discuss the application of fSP3 in the drug discovery process in a number of case studies, including our own work discovering non-systemic fructose scavengers for the treatment of fructose malabsorption.

Electroencephalography (EEG) is a brain imaging technique in which electrodes are placed on the scalp. EEG signals are commonly decomposed into frequency bands called delta, theta, alpha, and beta.While these bands have been shown to be useful for characterizing various brain states, their utility as a one-size-fits-all analysis tool remains unclear. We present a two-part data-driven methodology for objectively determining the best EEG bands for a given dataset in this paper. First, a decision tree is used to estimate the optimal frequency band boundaries for reproducing the signal’s power spectrum for a predetermined number of bands. The optimal number of bands is then determined using an Akaike Information Criterion (AIC)-inspired quality score that balances goodness-of-fit with a small band count. Data-driven EEG band discovery may aid in objectively capturing key signal components and uncovering new indices of brain activity.

Ebola Virus Disease (EVD) is one of the most lethal transmissible infections characterized by a high fatality rate, and caused by members of the Filoviridae family. The recent large outbreak of EVD in West Africa (2013-2016), highlighted the worldwide danger of this disease and its impact on global public health and economy. The development of highly needed anti-Filoviridae antivirals has been so far hampered by the shortage of tools to study their life cycle in vitro, and therefore screen for potential active compounds outside a biosafety level-4 (BSL-4) containment. Importantly, the development of surrogate models to in vitro study of Filoviridae entry in a BSL-2 setting, such as viral pseudotypes and Ebola virus like particles, tremendously boosted both our knowledge on viral life cycle and the identification of promising anti-Filoviridae compounds interfering with viral entry. In this context, the combination of such surrogate systems with large-scale small molecule compounds and haploid genetic screenings, as well as rational drug design and drug repurposing approaches will prove priceless in our quest for the development of a treatment for EVD.

Cone snails (genus Conus) are venomous marine snails that inject prey with a lethal cocktail of conotoxins, small, secreted, cysteine-rich peptides. Given the diversity and often high affinity for their molecular targets, consisting of ion channels, receptors or transporters, many conotoxins have become invaluable pharmacological probes, drug leads and therapeutics. Transcriptome sequencing of Conus venom glands followed by de novo assembly and homology-based toxin identification and annotation is currently the state-of-the-art for discovery of new conotoxins. However, homology-based search techniques, by definition, can only detect novel toxins that are homologous to previously reported conotoxins. To overcome these obstacles for discovery we have created ConusPipe, a machine learning tool that utilizes prominent chemical characters of conotoxins to predict whether a certain transcript in a Conus transcriptome, which has no otherwise detectable homologs in current reference databases, is a putative conotoxin. By using ConusPipe on RNASeq data of 10 species, we report 5,230 new putative conotoxin transcripts that have no homologues in current reference databases. 893 of these were identified by at least 3 out of 4 models used. These data significantly expand current publicly available conotoxin datasets and our approach provides a new computational avenue for the discovery of novel toxin families.

The Western ‘discovery’ of Japanese cinema in the 1950s prompted scholars to articulate essentialist visions understanding its singularities as a result of its isolation from the rest of the World and its close links to local aesthetic and philosophical traditions. Recent approaches however, have evidenced the limitations of this paradigm of ‘national cinema’. Higson (1989) opened a critical discussion on the existing consumption, text andproduction-based approaches to this concept. This article draws on Higson´s contribution and calls into question traditional theorising of Japanese film as a national cinema. Contradictions are illustrated by assessing the other side of the ‘discovery’ of Japanese cinema: certain gendaigeki works that succeeded at the domestic box office while jidaigeki burst into European film festivals. The Taiyōzoku and subsequent Mukokuseki Action created a new postwar iconography by adapting codes of representation from Hollywood youth and western films. This article does not attempt to deny the uniqueness of this film culture, but rather seeks to highlight the need to reformulate the paradigm of national cinema in the Japanese case, and illustrate the sense in which it was created from outside, failing to recognise its reach transnational intertextuality.

Research is scarce regarding antimicrobial use and antimicrobial resistance (AMR) for specific localities in Northern Ireland (NI). Additionally, the effects of COVID-19 on antimicrobial pre-scribing patterns and AMR are unknown. Between the European Union (EU) and United States (US), AMR causes approximately 68,000 deaths annually. This study will provide a better understanding of antimicrobial use and prescribing patterns in Belfast and link with AMR. An electronic survey was developed and distributed to eighty-five community pharmacists in Belfast. Yearly and monthly prescription data was gathered from the Business Services Organisation and COVID-19 statistics from Gov.uk. All data was analysed on Microsoft Office Excel® and IBM® SPSS® Statistics 25. Overall response rate was 46%. Most pharmacists (82%) failed to address prescriber non-compliance with guidelines and antimicrobial dosing errors (59%). The most common in-dication for antibiotics was upper respiratory tract infections (URTIs). Overprescribing of anti-biotics was perceived as the leading cause of AMR, therefore 69% of pharmacists indicated in-creased General Practitioner (GP) compliance with guidelines would reduce AMR. Pharmacists’ are in an ideal position to reduce AMR through patient education however, it is demonstrated that pharmacists failed to adequately counsel patients on antibiotic use. All GP practices demonstrated inappropriate antibiotic use, especially for URTIs which suggests antibiotic appropriateness should be reviewed. Many patients avoided contact with GP’s during COVID-19 which may have resulted in reduced antibiotic use. This research established amoxicillin as the most commonly prescribed antibiotic, which is contributing to increased AMR with its broad-spectrum activity and has recognised a decrease in antibiotic prescribing during COVID-19. Based on the results found and a critical review of the literature it is recommended antimicrobial guidelines should be re-viewed and improved, enhanced training should be provided to pharmacists and the antibiotic guardian (AG) campaign should be reenergised.

Antibiotic resistance and accordingly their pollution because of uncontrolled usage has emerged as a serious problem in recent years. Hence, there is an increased demand to develope robust, easy, and sensitive methods for rapid evaluation of antibiotic and their residues. Among different analytical methods, the aptamer-based biosensors (aptasensors) have attracted considerable attention because of good selectivity, specificity, and sensitivity. This review gives an overview about recent developed aptasensors for antibiotic detection. The use of various aptamer assays to determine different groups of antibiotics like β-lactams, Aminoglycosides, Anthracyclines, Chloramphenicol, (Fluoro)Quinolones, Lincosamide, Tetracyclines and Sulfonamides are presented in this paper.

Mental health issues can have significant impacts on individuals and communities and hence on social sustainability. There are several challenges facing mental health treatment, however, more important is to remove the root causes of mental illnesses because doing so can help prevent mental health problems from occurring or recurring. This requires a holistic approach to understanding mental health issues that are missing from the existing research. Mental health should be understood in the context of social and environmental factors. More research and awareness are needed, as well as interventions to address root causes. The effectiveness and risks of medications should also be studied. This paper proposes a big data and machine learning-based approach for the automatic discovery of parameters related to mental health from Twitter data. The parameters are discovered from three different perspectives, Drugs & Treatments, Causes & Effects, and Drug Abuse. We used Twitter to gather 1,048,575 tweets in Arabic about psychological health in Saudi Arabia. We built a big data machine learning software tool for this work. A total of 52 parameters were discovered for all three perspectives. We defined 6 macro-parameters (Diseases & Disorders, Individual Factors, Social & Economic Factors, Treatment Options, Treatment Limitations, and Drug Abuse) to aggregate related parameters. We provide a comprehensive account of mental health, causes, medicines and treatments, mental health and drug effects, and drug abuse, as seen on Twitter, discussed by the public and health professionals. Moreover, we identify their associations with different drugs. The work will open new directions for social media-based identification of drug use and abuse for mental health, as well as other micro and macro factors related to mental health. The methodology can be extended to other diseases and provides a potential for discovering evidence for forensics toxicology from social and digital media.

Background: Using the COM-B model as a framework, an EU-wide survey aimed to ascertain multidisciplinary healthcare workers’ (HCWs) knowledge, attitudes and behaviours on antibiotics, antibiotic use and antibiotic resistance. The UK findings are presented. Methods: A 43-item questionnaire was developed through a two-round modified Delphi consensus process. The UK target quota was 1,315 respondents. Results: 2,404 participants responded. The highest proportion were nursing and midwifery professionals (42%), pharmacists (23%) and medical doctors (18%). HCWs correctly answered that antibiotics are not effective against viruses (97%), they have associated side effects (97%), unnecessary use makes antibiotics ineffective (97%) and healthy people can carry antibiotic resistant bacteria (90%). However, fewer than 80% correctly answered that using antibiotics increases a patient’s risk of antimicrobial resistant infection or that resistant bacteria can spread from person to person. Whilst the majority of HCWs (81%) agreed there is a connection between their antibiotic prescribing behaviour and the spread of antibiotic resistant bacteria, only 64% felt that they have a key role in controlling antibiotic resistance. The top three barriers to providing advice or resources were lack of resources (19%), insufficient time (11%) and the patient being uninterested in the information (7%). Approximately 35% of UK respondents who were prescribers prescribed an antibiotic at least once in the last week due to fear of patient deterioration or complications. Conclusion: These findings highlight that a multifaceted approach to tackling the barriers to prudent antibiotic use in the UK is required and provides evidence for guiding targeted policy, intervention development and future research. Education and training should focus on patient communication, information on spreading resistant bacteria and increased risk for individuals.

Since the first published genome sequence of Trypanosoma cruzi in 2005, there has been tremendous technological advance in genomics, reverse genetics, and assay development for this elusive pathogen. However, there is still an unmet need for new and better drugs to treat Chagas disease. Here we introduce a T. cruzi assay strain that is useful for drug research as well as basic studies in host-pathogen interaction. Trypanosoma cruzi STIB980 is a strain of discrete typing unit TcI that grows well in culture as axenic epimastigotes or intracellular amastigotes. We have evaluated the optimal parameters for genetic transfection and constructed derivatives of T. cruzi STIB980 that express reporter genes for fluorescence- or bioluminescence-based drug efficacy testing, as well as a Cas9-expressing line for CRISPR/Cas9-mediated gene editing. The genome of T. cruzi STIB980 was sequenced by combining short-read Illumina with long-read Oxford Nanopore technologies. The latter served for the primary assembly, the former to correct mistakes and fill the gaps. This resulted in a high-quality nuclear haplotype assembly of 28 Mb in 400 contigs, containing 10,043 open-reading frames with a median length of 1077 bp. We believe that T. cruzi STIB980 is a useful addition to the antichagasic toolbox, and propose that it can serve as a DTU TcI reference strain for drug efficacy testing.

The purpose of this paper is to analyze market reflexivity in agricultural futures contracts with different maturities. To this end, we apply a four-dimensional Hawkes model to storable and non-storable agricultural commodities. We find market reflexivity for both storable and non-storable commodities. Reflexivity accounts for about 50 to 70 percent of the total trading activity. Differences between nearby and deferred contracts are less pronounced for non-storable than for storable commodities. We conclude that the co-existence of exogenous and endogenous price dynamics does not change qualitative characteristics of the price discovery process that have been observed earlier without consideration of market reflexivity.

: Crohn’s disease (CD) is a multifactorial chronic disorder that involves a combination of factors as genetic, immune response and gut microbiota. Actually, the therapy comprises salicylates, immunosuppressive agents, corticosteroids, biologic drugs. International guidelines don’t recommend the use of antibiotics except for septic complications of CD patients. The increased evidence of the implication of gut bacteria in this chronic disease support the rationale for using antibiotics as primary treatment of active CD. In the last decades several pathogens have been reported to be involved in the development of CD, but only Escherichia coli (E.coli) species and Mycobacterium avium paratubercolosis (MAP), aroused the interest due to their strong association with CD pathogenesis. Several meta-analyses have been published concerning antibiotic treatment in CD patients but randomized trials of antibiotic treatments against E.coli and MAP did not show prolonged benefits, and only generated conflicting results so much so that several questions are still unresolved regarding trial design, antibiotic dosing, the formulation used, the treatment course and the outcome measures. In this article we attempted to provide an overview and update of the trials on antibiotic treatment in active CD patients taking into account the role of pathogens, the mechanism by which the different antibiotics act on harmful pathogens, and antibiotic resistance. Finally, we also tried to draw new lines for future studies to use antibiotics to treat active CD patients

Staphylococcus spp. are among the main pathogens responsible for important infections worldwide, both in humans and in domestic or wild animals. Chiropterans, popularly known as bats, inhabit natural environments and human constructions, and have been considered potential disseminators of several pathogens. Studies have shown the expression of the mecA gene in these animals, being a significant threat to One Health. The objective of this study was to determine antibiotic resistance and the presence of the mecA gene in Staphylococcus spp. isolates from bats from forest areas in the municipalities of Paraná, Brazil. A total of 87 frugivorous chiropterans belonging to the family Phyllostomidae were captured. Of these, 87 rectal and 87 oral swabs samples were collected, re-sulting in 32 Staphylococcus spp. isolates. Twenty-four isolates were characterized as coagu-lase-negative, and 8 coagulase-positive Staphylococcus spp. (STACP), which showed notable re-sistance to oxacillin (78.12%), penicillin G (65.62%) and to other antimicrobials as well. One STACP isolate was mecA-positive. Therefore, further studies are needed to elucidate the mechanisms of contamination and dissemination of these pathogens, emphasizing that anthropic actions in na-tural environments, especially those related to the use of antimicrobials, pesticides may be the main reasons for the presence of resistant bacteria in bats.

Epithelial surfaces in humans are home to symbiotic microbes (i.e., microbiota) that influence the defensive function against pathogens depending on the health of the microbiota. Healthy microbiota contribute to the well-being of their host in general (e.g., via the gut-brain-axis), and their respective anatomical site in particular (e.g., oral, urogenital, skin or respiratory microbiota). Despite efforts towards a more responsible use of antibiotics, they are often prescribed for uncomplicated, self-limiting infections and can have a substantial negative impact on the gut microbiota. Treatment alternatives such as non-steroidal anti-inflammatory drugs may also influence the microbiota and thus can have lasting adverse effects. Herbal drugs offer a generally safe treatment option for uncomplicated infections of the urinary or respiratory tract. Additionally, their microbiota preserving properties allow for a more appropriate therapy of uncomplicated infections without contributing to an increase in antibiotic resistance or disturbing the gut microbiota. Here, herbal treatments may be a more appropriate therapy with a generally favorable safety profile.

Diversity as well as temporal and spatial changes of the proportional abundances of different antibiotics (cycling, mixing or combinations thereof) have been hypothesised to be an effective administrative control strategy in hospitals to reduce the prevalence of antibiotic-resistant pathogens in nosocomial or community-acquired infections. However, a rigorous assessment of the efficacy of these control strategies is lacking. The main purpose here is to present a mathematical framework for the assessment of control stategies from a processual stance. To this end, we adopt diverse measures of heterogeneity and diversity of proportional abundances based on the concept of entropy from other fields and adapt them to the needs in assessing the impact of variations in antibiotic consumption on antibiotic resistance. Thereby, we derive a family of diversity measures whose members exhibit different degrees of complexity. Most important, we extent these measures such that they account for the assessment of temporal changes in heterogeneity including otherwise undetected diversity-invariant permutations of antibiotics consumption and prevalence of resistant pathogens. We apply a correlation analysis for the assessment of associations between changes of heterogeneities on the antibiotics and on the pathogen side. As a showcase, which serves as a proof-of-principle, we apply the derived methods to records of antibiotic consumption and prevalence of antibiotic-resistant germs from University Hospital Dresden. Besides the quantification of heterogeneities of antibiotics consumption and antibiotic resistance, we show that a reduction of prevalence of antibiotic-resistant germs correlates with a temporal change of similarity with respect to the first observation of antibiotics consumption, although heterogeneity remains approximately constant. Although an interventional study is pending, our mathematical framework turns out to be a viable concept for the assessment and optimisation of control strategies intended to reduce antibiotic resistance.

Antibiotic Resistance (ABR) is increasing the mortality and morbidity associated with infectious diseases, besides increasing the cost of healthcare, saturating health-system capacity, and adversely affecting food security. Framing an appropriate narrative and engaging local communities through ‘One Health’ approach is essential to complement the top down measures. However, the absence of objective criteria to measure the performance of ABR interventions at community settings make it difficult to mobilize interest and investment for such interventions. An exercise was therefore done to develop an indicator framework for this purpose. An exhaustive list of indicators was developed from experiences gathered through community engagement work in a local panchayat (small administrative area) in Kerala, India, and a consultative process with health, veterinary, environment, and development experts. A prioritization exercise was done, looking at appropriateness, feasibility and validity, by global experts on ABR. A 15-point indicator framework was designed based on the prioritization process. The final set of indicators covers human health, animal health, environment management and Water Sanitation and hygiene (WASH) domains. The indicator framework was piloted in the panchayat(located in Kerala), which attained a score of 34 (maximum 45). The score increased when interventions were implemented to mitigate the ABR drives, indicating the framework is sensitive to change. Simultaneously, the indicator framework was tested in four sites from three other Indian states with different socioeconomic and health profiles, yielding different scores. Those collecting the field data were able to use it with minimal training. To conclude, this indicator framework can help policymakers broadly understand the factors contributing to ABR and measure the performance of interventions they choose to implement in the community

Background: Although rarely indicated, antibiotics are commonly used for acute diarrhoea in China. We conducted a randomized, double blind exploratory clinical trial of loperamide, berberine and turmeric for treatment of acute diarrhoea. Methods: Adults with acute uncomplicated diarrhoea were randomized to 4 groups: (A) loperamide; (B) loperamide and berberine; (C) loperamide and turmeric; (D) loperamide, berberine and turmeric. All participants were given rescue ciprofloxacin for use after 48 hours if symptoms worsened or were unimproved. Primary endpoints were feasibility and ciprofloxacin use during the 2 week follow-up period. Semi-structured interviews were conducted following recruitment. Results: Only 21.5% (278/1295) of patients screened were deemed eligible, and 49% (136/278) of these consented and entered into the final analysis. Most participants had mild symptoms, because most patients with moderate or severe symptoms wanted to be given antibiotics. Follow-up was good (94% at 2 weeks). Only two participants used rescue antibiotics compared to 65% of acute diarrhoea patients in the hospital during the recruitment period. The median symptom duration was: 14 hours in group B (IQR 10-22), 16 hours in group D (IQR 10-22), 18 hours in group A (IQR 10-33), 20 hours in group C (IQR 16-54). Re-consultation rates were low. There were no serious treatment-related adverse events. Most interviewed participants said the treatment was effective. Conclusion: Although recruitment was challenging because of widespread expectations for antibiotics, patients with mild diarrhoea accepted to try an alternative. This therapy requires further evaluation in a fully powered, randomised controlled trial among a broader sample.

Background: As the most invasive breast cancer (BrCa), triple-negative BrCa (TNBC) has the worst survival. The use of dexmedetomidine potentially affected BrCa surgery and dexmedetomidine was reported to have direct effects on TNBC cells. The objective of this study is to explore the mechanisms underlying the effect of dexmedetomidine on TNBC. Methods: Dexmedetomidine targets were predicted using The Cancer Genome Atlas data SwissTargetPrediction. Cell lines MDA-MB-231, MCF7, and MCF10A were used to validate the targets in TNBC with both clinical samples and cell lines. Cancer cell lines and normal breast cell lines were grouped in cancer and normal groups respectively. Both groups were exposed to dexmedetomidine treatment. Cell Counting Kit-8 was used to determine the effect of dexmedetomidine on cells with target silencing. The binding model of the candidate targets was docked and critical amino acids were mutated to validate the binding model. Results: Dexmedetomidine selectively inhibits cancer cells. Catalytic subunit of the DNA-dependent protein kinase (PRKDC), indoleamine 2,3-dioxygenase 1 (IDO1), opioid receptor kappa 1 (OPRK1), glutaminyl-peptide cyclotransferase (QPCT), macrophage migration inhibitory factor (MIF), potassium voltage-gated channel, subfamily H (Eag-related), member 2 (KCNH2), cholinergic receptor, muscarinic 3 (CHRM3), and potassium intermediate/small conductance calcium-activated channel, subfamily N, member 4 (KCNN4) were identified as dexmedetomidine targets in TNBC. The expression levels of PRKDC, IDO1, MIF, KCNH2, CHRM3, and KCNN4 were found to be upregulated in TNBC tissues compared to non-TNBC tissues(p<0.05). Silencing of these genes was found to reduce the sensitivity of TNBC cells to dexmedetomidine(p<0.05). This effect was counteracted when the silenced genes were overexpressed, resulting in an increase in the sensitivity of cells to dexmedetomidine (p<0.05). Furthermore, a direct interaction between dexmedetomidine and IDO1 and CHRM3 was observed, which regulated the sensitivity of cells to dexmedetomidine(p<0.05).Conclusion: IDO1 and CHRM3 are direct targets of dexmedetomidine in TNBC.

Inhibition of amyloid fibril formation could benefit patients with systemic amyloidosis. In this group of diseases, deposition of amyloid fibrils derived from normally soluble proteins leads to progressive tissue damage and organ failure. Although many small molecules have been proposed as inhibitors of amyloid formation, few have been successful in clinical trials. Amyloid formation is complex and several individual steps could be targeted by small molecules. However, the exact mechanism of action for a molecule is often not known, which impedes medicinal chemistry efforts to develop more potent molecules. Furthermore, commonly used assays are prone to artifacts that must be controlled for. Here, potential mechanisms by which small molecules could inhibit aggregation of immunoglobulin light chain dimers, the precursor proteins for AL amyloidosis are studied in assays that recapitulate different aspects of amyloidogenesis in vitro. One molecule reduced unfolding-coupled proteolysis of light chains, but no molecules inhibited aggregation of light chains or disrupted pre-formed amyloid fibrils. This work demonstrates the challenges associated with drug development for amyloidosis, but also highlights the potential to combine therapies that target different aspects of amyloidogenesis.

The morbidity and mortality caused by invasive fungal infections is increasing across the globe due to developments in transplant surgery, the use of immunosuppressive agents, and the emergence of drug-resistant fungal strains, which has led to a challenge in terms of treatment due to the limitations of three classes of drugs. Hence, it is imperative to establish effective strategies to identify and design new antifungal drugs. Drug repurposing is an effective way of expanding the application of existing drugs. In the last years, various existing drugs have been shown to be useful in the prevention and treatment of the invasive fungi. In this review, we summarize the currently used antifungal agents. In addition, the most up to date information on the effectiveness of existing drugs with antifungal activity is discussed. Moreover, the antifungal mechanisms of existing drugs are highlighted. These data will provide valuable knowledge to stimulate further investigation and clinical application in this field.

G protein-coupled receptors (GPCRs) are critical drug targets. GPCRs convey signals from the extracellular to the intracellular environment through G proteins. There is evidence that some ligands that bind to the GPCRs activate different downstream signaling pathways. G protein activation or -arrestin biased signaling involves ligands binding to receptors and stabilizing conformations that trigger a specific pathway. Molecular dynamics (MD) simulations are especially valuable for obtaining detailed mechanistic information, including identification of allosteric sites and understanding modulators' interactions between receptors and ligands. Here, we highlight recent simulation studies and methods used to study biased G protein-coupled receptor signaling and their conformational dynamics. We also highlight applications of MD simulations to drug discovery.

Background: Ongoing molecular profiling studies enabled by advances in biomedical technologies are producing vast amounts of ‘omic’ data for early detection, monitoring, and prognosis of diverse diseases. A major common limitation is the scarcity of biological samples, necessitating integrative modeling frameworks that can make optimal use of available data for disease classification tasks. Related data sets are often available from different studies, but may have been generated using different technology platforms. Thus, there is a critical need for flexible modeling methods that can handle data from diverse sources to facilitate the discovery of robust biomarkers that underlie disease regulatory processes. Results: In this paper, we introduce a novel framework called Knowledge Augmented Rule Learning (KARL), which incorporates two sources of knowledge, domain, and data, for pattern discovery from small and high-dimensional datasets, such as transcriptomic data. We propose KARL as a transfer rule learning framework in which knowledge of the domain is transferred to the learning process on data in order to 1) improve the reliability of the discovered patterns, and 2) study the knowledge of the domain when used along with data for modeling. In this work, we generated KARL models on gene expression datasets for five types of cancer, including brain, breast, colon, lung, and prostate. As our knowledge of the domain, we used the Ingenuity Knowledge Base (IKB) to extract genes related to hallmarks of cancer and annotated these prior relationships before learning classifiers from these datasets. Conclusions: Our results show that KARL produces, on average, rule models that are more robust classifiers than the baseline without such background knowledge, for our tasks of cancer prediction using 25 publicly available gene expression datasets. Moreover, KARL helped us learn insights about previously known relationships in these gene expression datasets, along with new relationships not input as known, to enable informed biomarker discovery for cancer prediction tasks. KARL can be applied to modeling similar data from any other domain and classification task. Future work would involve extensions to KARL to handle hierarchical knowledge to derive more general hypotheses to drive biomedicine.

Artificial intelligence AI or machine learning has proven to be a potential activity in the health and biomedical sciences. Previous research it has found that AI can learn new data and transform it into the useful knowledge. In the field of pharmacology, the aim is to design more efficient and novel vaccines using this method which are also cost effective. The underlying fact is to predict the molecular mechanism and structure for increased likelihood of developing new drugs. Clinical, electronic and high resolution imaging datasets can be used as inputs to aid the drug development niche. Moreover, the use of comprehensive target activity has been performed for repurposing a drug molecule by extending target profiles of drugs which also include off targets with therapeutic potential providing a new indication.

Acetic acid bacteria (AAB) are major contributors to the production of fermented vinegar, offering various cultural, culinary, and health benefits. Although the residual unpasteurized AAB after vinegar production are not pathogens, these are necessary the safety evaluations including antibiotic resistance for the use as starters. In this research, we investigated the antibiotics resistance profiles of 26 AAB strains, including various species of Komagataeibacter and Acetobacter, against ten different antibiotics using the E-test method. All strains exhibited resistance to aztreonam and clindamycin. Komagataeibacter species demonstrated a 50% resistance rate to ciprofloxacin, analogous to Acetobacter species, but showed twice the resistance rates to chloramphenicol and erythromycin. Genomic analysis of K. saccharivorans CV1 identified intrinsic resistance mechanisms, such as multidrug efflux pumps, thereby enhancing our understanding of antibiotic resistance in acetic acid-producing bacteria. These findings enhance understanding of antibiotic resistance in AAB for food safety and new antimicrobial strategies, suggesting the need for standardized testing methods and molecular genetic study.

The Maastricht VI/Florence consensus recommends, as one of the measures to enhance the efficacy of Helicobacter pylori (H. pylori) infection eradication, a personalized treatment approach involving the selection of an antimicrobial agent based on the pre-determined resistance of H. pylori. To meet the need to develop test systems for personalized drug selection, we conducted a study of H. pylori molecular resistance in Moscow using a self-developed Sanger sequencing test platform. We validated our test system on 25 pure culture samples of H. pylori with known resistance. Sensitivity and specificity for detecting resistance to clarithromycin was 100%, and to levofloxacin - 93% and 92%, respectively. Then we tested our platform on 112 H. pylori -positive patients who had not previously received proton pump inhibitors (PPI) or antibacterial drugs. Mutations indicating resistance to clarithromycin were found in 27 (24%) samples, and to levofloxacin in 26 (23%) samples. Double resistance was observed in 16 (14%) samples. The most common mutations leading to clarithromycin resistance were 2143G and 2142G, to levofloxacin resistance – 261A and 271A in the gyrA gene, which account for 69% of all identified genetic determinants in levofloxacin-resistant bacteria. Thus, a personalized approach to the selection of H. pylori eradication therapy based on the detection of bacterial resistance before prescribing first-line therapy could help avoid the prescription of ineffective H. pylori eradication therapies and, overall, contribute to the control of antibiotic resistance of H. pylori.

Precision farming is transforming how antibiotics get used on farms. It fights the overuse that creates superbugs and harms nature. Farmers now have high-tech tools to use antibiotics ultra-precisely. Drones, AI, and advanced watering equipment help them pinpoint only sick plants and animals needing treatment. This shields crops while avoiding environmental damage. More careful antibiotic use makes livestock healthier and boosts harvests too. And it prevents resistant germs, where antibiotics stop working altogether. The approach helps farms in multiple ways, using fewer resources for even better results. There are some growing pains, like high costs for small farms. And questions around data privacy also cause concern. But overcoming these hurdles could help precision farming spread far and wide. This technology promises safer, greener, and more productive agriculture. Targeted use of antibiotics protects both crops and people from drug-proof germs. And nature benefits when less medicine spreads into soil and water. The future looks bright for farming with precision.

Periodic assessment of bacterial contamination is necessary as it allows proper guidance in cases of eye infections through the use of appropriate antibiotics. Due to the extensive use of antibiotic treatment, most of the contamination flora is resistant to the usual ophthalmic antibiotics. The present study shows an updated picture of the susceptibility of Gram-positive and Gram-negative bacteria found on the ocular surface to the most commonly used antibiotic agents in patients undergoing cataract surgery. A total of 993 patients were included in the study with ages between 44 and 98 years old. Conjunctival culture was collected 7 days before cataract surgery. The response of Gram-positive and Gram-negative bacteria to various antibiotic classes like glycopeptides, cephalosporins, carbapenems, fluoroquinolones, aminoglycosides, phenicols, tetracyclines, rifamycins, macrolides and penicillins was assessed. From the tested antibiotics, vancomycin had 97.8% efficacy on Gram-positive bacteria. In the cephalosporin category, we observed an increased resistance of the cefuroxime for both Gram-positive and negative bacteria. Antibiotics that have more than 90% efficacy on Gram-positive bacteria are: meropenem, imipenem, netilmicin, amikacin and rifampicin. On Gram-negative bacteria, we found 100% efficacy of all tested fluoroquinolones, aminoglycosides (except for tobramycin), doxycycline, azithromycin, clarithromycin and chloramphenicol. The current study illustrates patterns of increased resistance of certain bacteria present on ocular surface to some of the commonly used antibiotics in ophthalmological clinical practice. One such revealing example is cefuroxime, which has been highly used as an intracameral antibiotic for the prevention of bacterial endophthalmitis after cataract surgery.

Antibiotic resistance among bacterial pathogens is recognized as a major threat to human health worldwide. The emergence of multidrug-resistant bacteria can also be found in the community settings, apart from hospital environment, which indicates that reservoirs of antibiotic resistance genes do exist outside the hospital. The growth of antibiotic resistance is a consequence of bacterial adaptations in response to selective pressures. To survive in this hostile environment, bacteria develop defence mechanisms such as chemical modification of antibiotics, enzyme-catalysed antibiotic degradation, altered permeability, antibiotic efflux, mutation of target sites and biofilm formation, resulting in resistance to nearly all currently available antibiotics used in the clinical practice. The present review summarizes insights into the molecular mechanisms underlying the antibiotic resistance which is useful for planning strategies to combat antibiotic resistance and devise innovative therapeutic tools to fight against multidrug-resistant bacterial species.

Antibiotic resistant Pseudomonas aeruginosa infections are the primary cause of mortality in people with cystic fibrosis (CF). Yet it has only recently become appreciated that resistance mutations can also increase P. aeruginosa virulence, even in the absence of antibiotics. Moreover, the mechanisms by which resistance mutations increase virulence are poorly understood. In this study we tested the hypothesis that mutations affecting efflux pumps can directly increase P. aeruginosa virulence. Using genetics, physiological assays, and model infections, we show that efflux pump mutations can increase virulence. Mutations of the mexEF efflux pump system increased swarming, rhamnolipid production, and lethality in a mouse infection model, while mutations in mexR that increased expression of the mexAB-oprM efflux system increased virulence during an acute murine lung infection without affecting swarming or rhamnolipid gene expression. Finally, we show that an efflux pump inhibitor, which represents a proposed novel treatment approach for P. aeruginosa, increased rhamnolipid gene expression in a dose-dependent manner. This finding is important because rhamnolipids are key virulence factors involved in dissemination through epithelial barriers and cause neutrophil necrosis. Together, these data show how current and proposed future anti-Pseudomonal treatments may unintentionally make infections worse by increasing virulence. Therefore, treatments that target efflux should be pursued with caution.

Honey is a complex sweet food stuff with well-established antimicrobial and antioxidant properties. It has been used for millennia in a variety of applications, but those most noteworthy include treatment of surface wounds, burns and inflammation. A variety of substances in honey have been suggested as the key component to its antimicrobial potential; polyphenolic compounds, hydrogen peroxide, methylglyoxal and bee-defensin 1. These components vary greatly across honey samples due to botanical origin, geographical location and the individual bee. The use of medical grade honey, Medihoney and Revamil, in the treatment of surface wounds and burns has been seen to improve the healing process, reduce healing time, reduce scarring and prevent microbial contamination. Therefore, medical grade honeys should be used for these treatments and reduce the demand for antibiotic usage. In this review, we aim to outline the constituents of honey and how they affect the antibiotic potential of honeys in a clinical setting.

This essay is a personal insight based on my own experience in the Iberian Pyrenees, which addresses three situations common in paleoecological research, such as the verification of previously devised hypotheses (anticipation), the finding on unknown events in unstudied sites (discovery) and the finding of unexpected outputs in already known areas (serendipity). The account is concentrated on the value of the coring sites by themselves as generators of paleoecological knowledge, rather than on the actual findings, which are presented and discussed in the corresponding data papers. The main aim is to show that there is still much room for new findings, even in areas that have been surveyed for long time and are supposed to be well known, from a paleoecological perspective. Finally, some general lessons are derived and conceptualized.

In this review we summarize existing trends of flow control used to improve the aerodynamic efficiency of wings. We first discuss active methods to control turbulence, starting with flat-plate geometries and building towards the more complicated flow around wings. Then, we discuss active approaches to control separation, a crucial aspect towards achieving high aerodynamic efficiency. Furthermore, we highlight methods relying on turbulence simulation, and discuss various levels of modelling. Finally, we thoroughly revise data-driven methods, their application to flow control, and focus on deep reinforcement learning (DRL). We conclude that this methodology has the potential to discover novel control strategies in complex turbulent flows of aerodynamic relevance.

Biological systems are highly regulated. They are also highly resistant to sudden perturbations enabling them to maintain the dynamic equilibrium essential for sustenance of life. This robustness is conferred by regulatory mechanisms that influence the activity of enzymes/proteins within their cellular context, to adapt to changing environmental conditions. However, the initial rules governing the study of enzyme kinetics were tested and implemented for mostly cytosolic enzyme systems that were easy to isolate and/or recombinantly express. Moreover, these enzymes lacked complex regulatory modalities. Now, with academic labs and pharmaceutical companies turning their attention to more complex systems (for instance, multi-protein complexes, oligomeric assemblies, membrane proteins and post-translationally modified proteins), the initial axioms defined by Michaelis-Menten (MM) kinetics are rendered inadequate and the development of a new kind of kinetic analysis to study these systems is required. The current review strives to present an overview of enzyme kinetic mechanisms that are atypical and, oftentimes, do not conform to the classical MM kinetics. Further, it presents initial ideas on the design and analysis of experiments in early drug-discovery for such systems, to enable effective screening and characterisation of small-molecule inhibitors with desirable physiological outcomes.

Curcumin and trans-cinnamaldehyde are acrolein-based Michael acceptor compounds that are commonly found in domestic condiments, and known to cause cancer cell death via redox mechanisms. Based on the structural features of these compounds we designed and synthesized several 2-cinnamamido-N-substituted-cinnamamide (bis-cinnamamide) compounds. One of the derivatives, (Z)-2-[(E)-cinnamamido]-3-phenyl-N-propylacrylamide 1512 showed a moderate antiproliferative potency (HCT-116 cell line inhibition of 32.0 µM), good selectivity profile (no inhibition of normal cell lines), and proven cellular activities leading to apoptosis. SAR studies led to more than 10-fold increase in activity. Our most promising compound, [(Z)-3-(1H-indol-3-yl)-N-propyl-2-[(E)-3-(thien-2-yl)propenamido)propenamide] 4112 killed colon cancer cells at IC50 = 0.89 µM (Caco-2), 2.85 µM (HCT-116) and 1.65 µM (HT-29), while exhibiting much weaker potency on C-166 and BHK normal cell lines (IC50 = 71 µM and 77.6 µM, respectively). Cellular studies towards identifying the compounds mechanism of cytotoxic activities revealed that apoptotic induction occurs in part as a result of oxidative stress. Importantly, the compounds showed inhibition of cancer stem cells that are critical for maintaining the potential for self-renewal and stemness. The results presented here show discovery of covalently-acting Michael addition compounds that potently kill cancer cells by a defined mechanism, with minimal effect on normal noncancerous cell.

Antibiotics are released into the environment either directly in an unchanged form or in a partially metabolized form. The discharge is usually through untreated waste or industrial treatment effluents. The potential concern is the uptake of these antibiotics by crops irrigated by treated wastewater. This study collected wastewater from eight points at the Pagla, Kadamtali, Dhaka treatment plant. Here we consider three crucial antibiotics, Doxycycline, Ciprofloxacin, and Tetracycline, used mainly during the last two years of the pandemic. A PDA detector was used in high-performance liquid chromatography (HPLC) analysis to determine the raw and processed effluent antibiotics. The most frequently seen antibiotics in natural wastewater were Doxycycline and Ciprofloxacin, with the highest concentration of 0.23µgL-1and 0.20 µgL-1(raw water), respectively. Tetracycline was not detected in natural water. Contrarily, Doxycycline was discovered in the Pagla plant's completed water and had the highest concentration (0.12 gL-1), whereas Ciprofloxacin and Tetracycline were not found in the dead water. The findings of this study showed that Doxycycline was still present in both the raw and processed effluent. Both natural and finished wastewater was subjected to a microbial-resistant test in the presence of all three antibiotics. The results revealed that the samples detected both heterotrophic bacteria and total coliform. The viable aerobic heterotrophic bacteria ranged between 5.421 and 4.754 log cfu/ml. Total bacteria load gradually decreased in the finished wastewater.

Antibiotic resistance is a major public health issue that requires a multifaceted approach. One potential source of antibiotic-resistant bacteria is wastewater in developing countries, which often lacks proper treatment infrastructure and can release high levels of antibiotics and antibiotic-resistant bacteria into the environment. This review article summarizes current knowledge on strategies to combat antibiotic resistance in wastewater in developing countries. Our review highlights the importance of improving wastewater treatment infrastructure to effectively remove antibiotics and antibiotic-resistant bacteria, implementing measures to reduce the release of antibiotics into the environment, and monitoring and surveillance to track the presence and spread of antibiotic-resistant bacteria in wastewater. We also discuss the potential challenges and barriers to implementing these strategies and the need for further research to determine their effectiveness in real-world settings. Overall, this review highlights the need for a comprehensive approach to address antibiotic resistance in wastewater in developing countries and underscores the importance of addressing this issue to protect public health.

Bacterial resistance to antibiotics is a growing global concern, threatening human and environ-mental health, particularly among urban populations. Wastewater treatment plants (WWTPs) are thought to be “hotspots” for antibiotic resistance dissemination. The conditions of WWTPs, in conjunction with the persistence of commonly used antibiotics, may favor the selection and trans-fer of resistance genes among bacterial populations. WWTPs provide an important ecological niche to examine the spread of antibiotic resistance. We used heterotrophic plate count methods to identify phenotypically resistant cultivable portions of these bacterial communities and charac-terized the composition of the culturable subset of these populations. Resistant taxa were more abundant in raw sewage and wastewater before the biological aeration treatment stage. While some antibiotic resistant bacteria (ARB) were detectable downstream of treated wastewater re-lease, these organisms are not enriched relative to effluent-free upstream water, indicating effi-cient removal during treatment. Combined culture-dependent and culture-independent analyses revealed a stark difference in community composition between culturable fractions and the envi-ronmental source material, irrespective of culturing conditions. Higher proportions of the envi-ronmental populations were recovered than predicted by the widely accepted 1% culturability paradigm. These results represent baseline abundance and compositional data for ARB commu-nities for reference in future studies addressing the dissemination of antibiotic resistance associ-ated with urban wastewater treatment ecosystems.

Analyzing the cells in various body fluids can greatly deepen the understanding of the mechanisms governing the cellular physiology. Because of the variability of physiological and metabolic states, it is important to be able to perform such studies on individual cells. Therefore, we developed an optofluidic system in which we precisely manipulated and monitored individual cells of Escherichia coli. We used laser tweezers Raman spectroscopy (LTRS) in a microchamber chip to manipulate and analyze individual E. coli cells. We subjected the cells to antibiotic cefotaxime, and we observed the changes by the time-lapse microscopy and Raman spectroscopy. We found observable changes in the cellular morphology (cell elongation) and in Raman spectra, which were consistent with other recently published observations. We tested the capabilities of the optofluidic system and found it to be a reliable and versatile solution for this class of microbiological experiments.

Antibiotic resistance has emerged as one of the major concerns to public human health due to issues in treatment and control of major infectious diseases. From discovery of penicillin in 1940, the antibiotic resistance originated and now developed the microorganisms as resistive strains to the major available antibiotics. Furthermore, studies on this captivating activity of the microbes provide insight into the complexities of microbial physiology and may offer some guidance in preventing the onset and consequent development of antibiotic resistance. Despite of initiatives taken in last few decades to overcome the issues, the trends of antibiotic resistance gained much peak. Antibiotic resistance appears to have emerged as a result of various factors including antibiotics being misused and overused in both the medical field and the agricultural sector. Important factors in the development of antibiotic resistance also include bacterial mutation, unplanned evolution, and horizontal gene transfers. In addition, antibiotics resistance imposed the financial consequences to public health and drug development research. Future advancements related to innovative antibiotics and molecular drug designing become challenge for researchers due to intensive multiple antibiotics resistance among human population. Many researches have been conducted on origin, evolutionary aspect of antibiotic resistance and mechanisms of antibiotics resistance, but its effect on future drug development is little understood. Therefore, the recent review will highlight the role of antibiotic resistance in drug designing and impacts of antibiotic resistance on drug development in future.

Atrial fibrillation (AF), the most prevalent type of sustained cardiac dysrhythmia globally, confers strikingly enhanced risks for cognitive dysfunction, stroke, chronic cardiac failure, and sudden cardiovascular demise. Aggregating studies underscore the crucial roles of inherited determinants in the occurrence and perpetuation of AF. However, due to conspicuous genetic heterogeneity, the inherited defects accounting for AF remain largely indefinite. Here, via the whole-genome genotyping with genetic markers and linkage assay in a family suffering AF, a new AF-causative locus was located at human chromosome 7p14.2-p14.3, a ~4.89-cM (~4.43-Mb) interval between the markers D7S526 and D7S2250. Exome-wide sequencing assay unveiled that at the defined locus, solely the mutation in the TBX20 gene, NM_001077653.2: c.695A&gt;G; p.(His232Arg), co-segregated with AF in the family. Additionally, Sanger sequencing assay of TBX20 in another family suffering AF uncovered a novel mutation, NM_001077653.2: c.862G&gt;C; p.(Asp288His). Neither of the two mutations was observed in 600 unrelated control individuals. Functional investigations demonstrated that the two mutations both significantly reduced the transactivation of the target gene KCNH2 (a well-established AF-causing gene) and the ability to bind the promoter of KCNH2, while without effect on the nuclear distribution of TBX20. Conclusively, these findings reveal a new AF-causative locus at human chromosome 7p14.2-p14.3 and strongly indicate TBX20 as a novel AF-causative gene, shedding light on the mechanism underlying AF and suggesting clinical significance for allele-specific treatment of AF patients.

Attention Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder that affects attention and behavioral control, characterized by constant presence of inattention and hyperactivity. This article describes a study that used a database with results from tests of voluntary and automatic attentional orientation activity in a complex network of ADHD patients, in order to understand the characteristics of the elements and attentional variability of patients. Centrality metrics and the Louvain method were applied to obtain the network communities. The most important elements of the network were identified and differences in reaction times of the activities were observed in the identified communities. The study provides useful information to understand of deficit hyperactivity disorder spectrum in patients with ADHD.

Topic discovery is finding the main idea of large amounts of textual data. It indicates the recurring topics in the documents, allowing an overview of the texts. Current topic discovery models receive the texts, with or without pre-processing of Natural Language Processing. The processing consists of stopwords removal, text cleaning and normalization (lowercase conversion). A topic discovery model that receives texts with or without processing generates general topics since the input data is many uncategorized texts. The general topics do not offer a detailed overview of the input texts, and manual text categorization is a time-consuming and tedious task. Accordingly, it is necessary to integrate an automatic text classification task in the topic discovery process to obtain specific topics with their top words that contain relevant relationships based on belonging to a class. Text classification performs a word analysis that makes up a document to decide what class or category is being identified; then, integrating the text classification before a topic discovery process will provide latent topics depicted by top words with a high coherence in each topic based on the previously obtained classes. Therefore, this paper exposes a approach that integrates text classification into topic discovery from large amounts of English textual data, such as 20-Newsgroup and Reuters corpora. The text classification is accomplished with a Convolutional Neural Network(CNN) incorporating three embedding models based on semantic relationships. The topic discovery over categorized texts is realized with Latent Dirichlet Analysis(LDA), Probabilistic Latent Semantic Analysis(PLSA), and Latent Semantic Analysis(LSA) algorithms. An evaluation process was performed based on the normalized topic coherence metric. The 20-Newsgroup corpus was classified, and twenty topics with ten top words were discovered for each class, obtaining 0.1723 normalized topic coherence when applying LDA, 0.1622 with LSA, and 0.1716 with PLSA. The Reuters corpus was also classified, obtaining 0.1441 normalized topic coherence when applying the LDA algorithm to obtain 20 topics for each class.

The worldwide outbreak of SARS-CoV-2 in early 2020 caused numer- ous deaths and unprecedented measures to control its spread. We employed our Computational Analysis of Novel Drug Opportunities (CANDO) multiscale therapeutic discovery, repurposing, and design platform to identify small molecule inhibitors of the virus to treat its resulting indication, COVID-19. Initially, few experimental studies existed on SARS-CoV-2, so we optimized our drug candidate prediction pipelines using results from two independent high-throughput screens against prevalent human coronaviruses. Ranked lists of candidate drugs were generated using our open source cando.py software based on viral protein inhibition and proteomic interaction similarity. For the former viral protein inhibition pipeline, we computed interaction scores between all compounds in the corresponding candidate library and eighteen SARS-CoV proteins using an interaction scoring protocol with extensive parameter optimization which was then applied to the SARS-CoV-2 proteome for prediction. For the latter similarity based pipeline, we computed interaction scores between all compounds and human protein structures in our libraries then used a consensus scoring approach to identify candidates with highly similar proteomic interaction signatures to multiple known anti-coronavirus actives. We published our ranked candidate lists at the very beginning of the COVID-19 pandemic. Since then, 51 of our 276 predictions have demonstrated anti-SARS-CoV-2 activity in published clinical and experimental studies. These results illustrate the ability our platform to rapidly respond to emergent pathogens and provide greater evidence that treating compounds in a multitarget context more accurately describes their behavior in biological systems.

Background: Antibiotic resistance is an urgent issue everywhere in the globe. It is necessary to look into new sources of antibiotics to address this issue. Aim of the study: studying the purification of Corallopyronin B from various soil conditions in Egypt, as well as the antibacterial effectiveness of Corallopyronin B in preclinical animal testing and randomized human clinical trials phases 1/2. Type of the study: Screening experimental study. Methodology: Several soil conditions in Egypt were examined to create bacterial isolates that generated the antibiotic chemical Corallopyronin B. Using reversed-phase HPLC, Myxopyronin B was purified. The test antibiotic's minimum inhibitory concentration( MIC) and in vitro antibacterial activity were ascertained using the paper disc diffusion assay and the broth microdilution technique. Furthermore, in stages 1/2 of randomized clinical trials including human and animal models, pharmacokinetics, adverse drug reactions, and the in vivo antibacterial spectrum were discovered. Results: The soil bacterial isolate Corallococcus coralloides DSM 2259, grown on a Casein yeast peptone( CYP) plate, produced Corallopyronin B from its culture supernatant. At MICs more than 100 mcg/ml, the test antibiotic inhibited the growth of many Gram -ve bacteria, including Escherichia coli, while preventing the growth of numerous Gram +ve bacteria, with MICs ranging from 1 to 10 mcg/ml. Eukaryotic cells, on the other hand, including those in humans and fungi, were unharmed. The test antibiotic was shown to have a bactericidal effect by inhibiting bacterial DNA-dependent RNA polymerase( RNLP). In phases 1/2 of randomized human clinical trials, when 600 mg of the dose per 70 kg of body weight was administered SC, the Cmax was 8.6 mcg/ml at Tmax 1 hour; T1/2 reached 136 min following first-order kinetics of elimination. It stopped acting around 6-7 hours after SC was administered. In the preclinical and randomized human clinical trial phases 1/2, less than 6 percent of experimental candidates had uncommon toxicity, showing reduced bile flow. Protein binding with plasma albumin was detected which reached about 83%. Conclusion: The current work was noteworthy since it involved the production of the bactericidal antibiotic Corallopyronin B from Corallococcus coralloides DSM 2259 which was isolated from several soil environments in Egypt.

The fate of critically sick patients with infections in intensive care units (ICUs) is significantly influenced by antimicrobial resistance, which has become a serious concern in developing nations. This observational study was conducted at the IBN Sina Specialised Hospital in Dhaka, Bangladesh, over a 12-month period from January 2021 to December 2021, in order to track the pattern of antibiotic resistance among the patients admitted to the intensive care unit (ICU). Aspiration pneumonia (29%) and diabetes mellitus (24%), among 200 patients, were the most common main diagnoses. 65 samples (or 26%) of the 250 samples had 85 bacteria identified from them. Urine (14.12%) and tracheal aspirate (64.71%) were the most frequently found sites of infection. In the sample from the tracheal aspirate, Pseudomonas spp. (30.59%), Escherichia coli (24.71%), Acinetobacter spp. (20%), and Klebsiella spp. (14.12) were the most frequently isolated microorganisms. The following antibiotics were shown to have the highest overall patterns of resistance: levofloxacin (68.24), amikacin (64.71), meropenem (49.41), ceftazidime (75.29), ciprofloxacin (78.82), and gentamicin (82.35). The most effective antibiotic against Klebsiella species was meropenem (64.61%), while Acinetobacter species were mostly susceptible to cotrimoxazole (64.67%) and piperacillin + tazobactam (60.50%). Most susceptible to netilmicin (70.48%) and meropenem (49.32%) were Escherichia coli, while Pseudomonas spp. were mostly responsive to colistin (55.14%) and netilmicin (52.25%). Antibiotic resistance is common among intensive care unit (ICU) patients, and most isolated microbes have resistance to traditional medicines.

Seawater has been proposed as a reservoir for antibiotic resistant bacteria and antibiotic resistance genes, thus representing a risk to public health. In this study, we evaluated the presence of antibiotic resistance determinants (bacteria and genes) in 77 seawater samples collected at different points along the coast of the Gulf of Valencia (Spain). Specifically, indicators of fecal contamination bacteria, Escherichia coli and Enterococcus sp. were isolated, and their antibiotic resistance profiles were analyzed by using the Sensititre® system, followed by the detection of main antibiotic resistance genes (blaTEM, qnrS, tetW, sulI, and ermB). The highest frequencies of resistance in E. coli isolates were detected against ampicillin (35.1%) and ciprofloxacin (17.5%), followed by sulfamethoxazole and trimethoprim (15.7%), while 23% of enterococci isolates showed resistance to a single antibiotic, 20% against tetracycline and 3% against daptomycin. By PCR, 93% of the E. coli strains showed the blaTEM and sulI resistance genes. Among the enterococci, the presence of the blaTEM gene was detected in 40% of the isolates, while the rest of the genes were present at very low rates. Among the water samples, 57% were positive for at least one of the tested genes, being blaTEM gene the most commonly found (47%), followed by qnrS (33%) and sulI (23%) genes. These results show that seawater, in addition to having a high rate of fecal contamination, can contribute to the spread of antibiotic resistance.