Choice Of Exchange Rate Regimes For Developing Countries: Better Be Fixed Or Floating?

The following paper is a summary article about the choice of exchange rate regime for a developing country considering the importance of “currency mismatches”, “debt intolerance”, “and fear of floating”, “financial globalization”, “institutions and sudden stops”. In this paper, I first summarize recent researches and papers on this specific issue. In a recent work of theirs, Calvo and Mishkin(2003) argue that much of the debate on choosing an exchange rate regime misses the boat and concludes that choice of exchange rate regime is likely to be of second order importance to the development of good fiscal, financial, and monetary institutions in producing macroeconomic success in emerging market countries and that a focus on institutional reforms rather than on the exchange rate regime may encourage emerging market countries to be healthier and less prone to the crises that we have seen in recent years. Another major study in this subject belong to Obtsfeld(2004) which claim that the measurable gains from financial integration appear to be lower for emerging markets than for higher-income countries, and appear to have been limited by recent crises. Obtsfeld identifies one factor limiting the gains from financial integration as the difficulty emerging economies face in resolving the open-economy trilemma which claim that many emerging economies cannot live comfortably either with fixed or with freely floating exchange rates. And finally, Stanley Fisher (2001) discusses the bipolar or two-corner solution view of intermediate policy regimes between hard pegs and floating are not sustainable and that use of pegged rates for countries open to international capital flows. Finally, I sum up with some concluding remarks. 

Exploiting Pretrained Biochemical Language Models for Targeted Drug Design

Motivation: The development of novel compounds targeting proteins of interest is one of the most important tasks in the pharmaceutical industry. Deep generative models have been applied to targeted molecular design and have shown promising results. Recently, target-specific molecule generation has been viewed as a translation between the protein language and the chemical language. However, such a model is limited by the availability of interacting protein-ligand pairs. On the other hand, large amounts of unlabeled protein sequences and chemical compounds are available and have been used to train language models that learn useful representations. In this study, we propose exploiting pretrained biochemical language models to initialize (i.e. warm start) targeted molecule generation models. We investigate two warm start strategies: (i) a one-stage strategy where the initialized model is trained on targeted molecule generation (ii) a two-stage strategy containing a pre-finetuning on molecular generation followed by target specific training. We also compare two decoding strategies to generate compounds: beam search and sampling. Results: The results show that the warm-started models perform better than a baseline model trained from scratch. The two proposed warm-start strategies achieve similar results to each other with respect to widely used metrics from benchmarks. However, docking evaluation of the generated compounds for a number of novel proteins suggests that the one-stage strategy generalizes better than the two-stage strategy. Additionally, we observe that beam search outperforms sampling in both docking evaluation and benchmark metrics for assessing compound quality. Availability and implementation: The source code is available at https://github.com/boun-tabi/biochemical-lms-for-drug-design and the materials are archived in Zenodo at https://doi.org/10.5281/zenodo.6832145Comment: 12 pages, to appear in Bioinformatic

Exploring Data-Driven Chemical SMILES Tokenization Approaches to Identify Key Protein-Ligand Binding Moieties

Machine learning models have found numerous successful applications in computational drug discovery. A large body of these models represents molecules as sequences since molecular sequences are easily available, simple, and informative. The sequence-based models often segment molecular sequences into pieces called chemical words (analogous to the words that make up sentences in human languages) and then apply advanced natural language processing techniques for tasks such as $\textit{de novo}$ drug design, property prediction, and binding affinity prediction. However, the chemical characteristics and significance of these building blocks, chemical words, remain unexplored. This study aims to investigate the chemical vocabularies generated by popular subword tokenization algorithms, namely Byte Pair Encoding (BPE), WordPiece, and Unigram, and identify key chemical words associated with protein-ligand binding. To this end, we build a language-inspired pipeline that treats high affinity ligands of protein targets as documents and selects key chemical words making up those ligands based on tf-idf weighting. Further, we conduct case studies on a number of protein families to analyze the impact of key chemical words on binding. Through our analysis, we find that these key chemical words are specific to protein targets and correspond to known pharmacophores and functional groups. Our findings will help shed light on the chemistry captured by the chemical words, and by machine learning models for drug discovery at large.Comment: 16 pages, 11 figures, new computational analysis and extended case studie

Validity and Reliability of the Instruments to Measure Colorectal Cancer Screening Benefits and Barriers—Turkish Version

Background Perceptions of benefits and barriers are important determinants in understanding colorectal cancer screening (CRCS) behaviors. There is a need for standardized Turkish tools that measure the benefits and barriers of fecal occult blood test (FOBT) and colonoscopy (COL). Objective The aim of this study was to assess the validity and reliability of the Turkish version of the “Instruments to Measure CRCS Benefits and Barriers.” Methods This methodological study was carried out in 2 stages in primary care and in 394 adults between the ages of 50 and 70 years. In the first stage, some items of the scales demonstrated low/unacceptable corrected item-total and factor loadings, and in the second stage, it was decided to add emoji-based facial scales, which include emoji expressions. Results Results with the emoji-based facial scales included internal consistency coefficients of 0.85 for FOBT benefits, 0.79 for FOBT barriers, 0.84 for COL benefits, and 0.86 for COL barriers; the item-total correlations of FOBT varied between 0.39 and 0.73, whereas those of COL varied between 0.38 and 0.76. The factor loadings of all items were higher than 0.40. Conclusions The emoji-based facial scale for CRC Screening Benefits and Barriers is a valid and reliable tool for measuring the benefits and barriers perceptions of 50- to 70-year-old Turkish adults. Implications for Practice The Instruments to Measure CRCS Benefits and Barriers–Turkish version can provide insights for nurses and healthcare professionals to understand individuals’ perceived FOBT and COL benefits and barriers and to develop effective interventions to increase CRCS rates

Mechanisms of T-Cell Exhaustion in Pancreatic Cancer.

T-cell exhaustion is a phenomenon that represents the dysfunctional state of T cells in chronic infections and cancer and is closely associated with poor prognosis in many cancers. The endogenous T-cell immunity and genetically edited cell therapies (CAR-T) failed to prevent tumor immune evasion. The effector T-cell activity is perturbed by an imbalance between inhibitory and stimulatory signals causing a reprogramming in metabolism and the high levels of multiple inhibitory receptors like programmed cell death protein-1 (PD-1), cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), T cell immunoglobulin and mucin domain-containing protein 3 (TIM-3), and Lymphocyte-activation gene 3 (Lag-3). Despite the efforts to neutralize inhibitory receptors by a single agent or combinatorial immune checkpoint inhibitors to boost effector function, PDAC remains unresponsive to these therapies, suggesting that multiple molecular mechanisms play a role in stimulating the exhaustion state of tumor-infiltrating T cells. Recent studies utilizing transcriptomics, mass cytometry, and epigenomics revealed a critical role of Thymocyte selection-associated high mobility group box protein (TOX) genes and TOX-associated pathways, driving T-cell exhaustion in chronic infection and cancer. Here, we will review recently defined molecular, genetic, and cellular factors that drive T-cell exhaustion in PDAC. We will also discuss the effects of available immune checkpoint inhibitors and the latest clinical trials targeting various molecular factors mediating T-cell exhaustion in PDAC

Risk factors of multidrug-resistant bacteria in community-acquired urinary tract infections

Background: Urinary tract infections (UTIs) are one of the most seen infection among community. Objectives: In this cross-sectional study we aimed to investigate the risk factors of multidrug-resistant (MDR) bacteria that caused community-acquired UTI (CA-UTI). Methods: Consecutive patients admitted to the Urology and Infectious Diseases policlinics with the diagnosis of CA-UTI were included in the study. A standard form including possible predisposing factors for MDR bacteria was applied. Results: In total, 240 patients (51.3% females) were enrolled in the study. The mean age of participants were 59.8 \ub1 18.3 years old. Escherichia coli (n =166; 69.2%)was the most frequently isolated bacteria and its incidence was higher in females than in males (p=0.01). In total, 129 (53.8%) of the identified pathogens were MDR bacteria. According to multivariate analysis, the use of antibiotics three or more times increased the risk of infection with MDR bacteria by 4.6 times, the history of urinary tract infection in the last 6 months by 2 times, being male and over 65 years old by 3 times. Conclusion: Doctors should consider prescribing broad-spectrum antibiotics in patients with severe UTIs with a history of UTI, advanced age, male gender, and multiple antibiotic usage, even if they have a CA-UTI

An international guideline with six personalised titration schedules for preventing myocarditis and pneumonia associated with clozapine

White blood cell (WBC) monitoring has reduced clozapine-treated patient deaths associated with agranulocytosis to a rarity. However, clozapine protocols and package inserts worldwide provide no instructions for preventing myocarditis or pneumonia during clozapine titrations. Prescribers worldwide are largely unaware of that. Meanwhile, as they worry about agranulocytosis, their clozapine-treated patients are at risk of dying from pneumonia or myocarditis. Consequently, an international guideline with 104 authors from 50 countries/regions was recently published to provide personalised clozapine titration schedules for adult inpatients. This forum article reviews pneumonia and myocarditis occurring during clozapine titration, as well as the three most innovative aspects of this new guideline: (1) personalised titration, (2) C reactive protein (CRP) measures, and (3) dose predictions based on blood levels. Clozapine metabolism is influenced by 3 levels of complexity: (1) ancestry groups, (2) sex-smoking subgroups, and (3) presence/absence of poor metabolizer status. These 3 groups of variables should determine the maintenance dose and speed of clozapine titration; they are summarised in a table in the full-text. The international clozapine titration guideline recommends measuring CRP levels simultaneously with WBC, at baseline and weekly at least for the first 4 weeks of titration, the highest risk period for clozapine-induced myocarditis

Explaining spatial variation in housing construction activity in Turkey

In Turkey, there has been a strong policy narrative that has emphasized the importance of construction activity as a driver of economic growth. This has given shape to a central state-led policy regime that has sought to ensure that planners and other urban policy makers develop plans and strategies that support construction activity. Against this backdrop, and a recent history of uneven spatial development, this paper seeks to understand what this policy imperative might mean for housing construction activity in different provinces. It seeks to reflect on both the relationship between the state and the market, and the interaction between state policies, economic drivers and levels of construction activity. The evidence presented in the paper suggests that uneven spatial development might be explained in different ways in different provinces. Although, in many cases, patterns of construction activity are consistent with economic fundamentals, there are important exceptions in some regions where arguably activity levels are at odds with prior expectations

Supramolecular peptide nanofiber morphology affects mechanotransduction of stem cells

Chirality and morphology are essential factors for protein function and interactions with other biomacromolecules. Extracellular matrix (ECM) proteins are also similar to other proteins in this sense; however, the complexity of the natural ECM makes it difficult to study these factors at the cellular level. The synthetic peptide nanomaterials harbor great promise in mimicking specific ECM molecules as model systems. In this work, we demonstrate that mechanosensory responses of stem cells are directly regulated by the chirality and morphology of ECM-mimetic peptide nanofibers with strictly controlled characteristics. Structural signals presented on l-amino acid containing cylindrical nanofibers (l-VV) favored the formation of integrin β1-based focal adhesion complexes, which increased the osteogenic potential of stem cells through the activation of nuclear YAP. On the other hand, twisted ribbon-like nanofibers (l-FF and d-FF) guided the cells into round shapes and decreased the formation of focal adhesion complexes, which resulted in the confinement of YAP proteins in the cytosol and a corresponding decrease in osteogenic potential. Interestingly, the d-form of twisted-ribbon like nanofibers (d-FF) increased the chondrogenic potential of stem cells more than their l-form (l-FF). Our results provide new insights into the importance and relevance of morphology and chirality of nanomaterials in their interactions with cells and reveal that precise control over the chemical and physical properties of nanostructures can affect stem cell fate even without the incorporation of specific epitopes

Optogenetic Monitoring of the Glutathione Redox State in Engineered Human Myocardium

Redox signaling affects all aspects of cardiac function and homeostasis. With the development of genetically encoded fluorescent redox sensors, novel tools for the optogenetic investigation of redox signaling have emerged. Here, we sought to develop a human heart muscle model for in-tissue imaging of redox alterations. For this, we made use of (1) the genetically-encoded Grx1-roGFP2 sensor, which reports changes in cellular glutathione redox status (GSH/GSSG), (2) human embryonic stem cells (HES2), and (3) the engineered heart muscle (EHM) technology. We first generated HES2 lines expressing Grx1-roGFP2 in cytosol or mitochondria compartments by TALEN-guided genomic integration. Grx1-roGFP2 sensor localization and function was verified by fluorescence imaging. Grx1-roGFP2 HES2 were then subjected to directed differentiation to obtain high purity cardiomyocyte populations. Despite being able to report glutathione redox potential from cytosol and mitochondria, we observed dysfunctional sarcomerogenesis in Grx1-roGFP2 expressing cardiomyocytes. Conversely, lentiviral transduction of Grx1-roGFP2 in already differentiated HES2-cardiomyocytes and human foreskin fibroblast was possible, without compromising cell function as determined in EHM from defined Grx1-roGFP2-expressing cardiomyocyte and fibroblast populations. Finally, cell-type specific GSH/GSSG imaging was demonstrated in EHM. Collectively, our observations suggests a crucial role for redox signaling in cardiomyocyte differentiation and provide a solution as to how this apparent limitation can be overcome to enable cell-type specific GSH/GSSG imaging in a human heart muscle context