Markov State Models: To Optimize or Not to Optimize

Markov state models (MSM) are a popular statistical method for analyzing the conformational dynamics of proteins including protein folding. With all statistical and machine learning (ML) models, choices must be made about the modeling pipeline that cannot be directly learned from the data. These choices, or hyperparameters, are often evaluated by expert judgment or, in the case of MSMs, by maximizing variational scores such as the VAMP-2 score. Modern ML and statistical pipelines often use automatic hyperparameter selection techniques ranging from the simple, choosing the best score from a random selection of hyperparameters, to the complex, optimization via, e.g., Bayesian optimization. In this work, we ask whether it is possible to automatically select MSM models this way by estimating and analyzing over 16,000,000 observations from over 280,000 estimated MSMs. We find that differences in hyperparameters can change the physical interpretation of the optimization objective, making automatic selection difficult. In addition, we find that enforcing conditions of equilibrium in the VAMP scores can result in inconsistent model selection. However, other parameters that specify the VAMP-2 score (lag time and number of relaxation processes scored) have only a negligible influence on model selection. We suggest that model observables and variational scores should be only a guide to model selection and that a full investigation of the MSM properties should be undertaken when selecting hyperparameters.</p

A low-power wave union TDC implemented in FPGA

A low-power time-to-digital convertor (TDC) for an application inside a vacuum has been implemented based on the Wave Union TDC scheme in a low-cost field programmable gate array (FPGA) device. Bench top tests have shown that a time measurement resolution better than 30 ps (standard deviation of time differences between two channels) is achieved. Special firmware design practices are taken to reduce power consumption. The measurements indicate that with 32 channels fitting in the FPGA device, the power consumption on the FPGA core voltage is approximately 9.3 mW/channel and the total power consumption including both core and I/O banks is less than 27 mW/channel

Quantifying rainfall-derived inflow and infiltration in sanitary sewer systems based on conductivity monitoring

Quantifying rainfall-derived inflow and infiltration (RDII) in a sanitary sewer is difficult when RDII and overflow occur simultaneously. This study proposes a novel conductivity-based method for estimating RDII. The method separately decomposes rainfall-derived inflow (RDI) and rainfall-induced infiltration (RII) on the basis of conductivity data. Fast Fourier transform was adopted to analyze variations in the flow and water quality during dry weather. Nonlinear curve fitting based on the least squares algorithm was used to optimize parameters in the proposed RDII model. The method was successfully applied to real-life case studies, in which inflow and infiltration were successfully estimated for three typical rainfall events with total rainfall volumes of 6.25 mm (light), 28.15 mm (medium), and 178 mm (heavy). Uncertainties of model parameters were estimated using the generalized likelihood uncertainty estimation (GLUE) method and were found to be acceptable. Compared with traditional flow-based methods, the proposed approach exhibits distinct advantages in estimating RDII and overflow, particularly when the two processes happen simultaneously

Extensive necrotizing fasciitis of scrotum and abdominal wall: Report of two cases and a review of the literature

The incidence rate of necrotizing fasciitis(NF) is low, but it has a high mortality rate. At present, it lacks experience in clinical treatment in municipal and county-level hospitals, insufficient awareness of disease risk, lack of experience in disease surgical intervention, and lack of a set of mature treatment norms and standards. Most patients have no time to transfer to a higher hospital for treatment. In January and April 2022, two cases of large-scale necrotizing fasciitis of the scrotum and abdominal wall were treated in the Department of Urology of Weifang people's Hospital respectively and were clinically cured after active surgical debridement combined with broad-spectrum antibiotics. Through the retrospective analysis of the diagnosis and treatment of two cases of necrotizing fasciitis, this paper analyzes and summarizes the scope of surgical debridement of NF, postoperative dressing changing skills, timing of multiple debridements, application and timing of vacuum sealing drainage(VSD), and the combined use of antibiotics. To provide experience for clinical diagnosis and treatment of necrotizing fasciitis

Comparative metabolomics combined with genome sequencing provides insights into novel wolfberry-specific metabolites and their formation mechanisms

Wolfberry (Lycium, of the family Solanaceae) has special nutritional benefits due to its valuable metabolites. Here, 16 wolfberry-specific metabolites were identified by comparing the metabolome of wolfberry with those of six species, including maize, rice, wheat, soybean, tomato and grape. The copy numbers of the riboflavin and phenyllactate degradation genes riboflavin kinase (RFK) and phenyllactate UDP-glycosyltransferase (UGT1) were lower in wolfberry than in other species, while the copy number of the phenyllactate synthesis gene hydroxyphenyl-pyruvate reductase (HPPR) was higher in wolfberry, suggesting that the copy number variation of these genes among species may be the main reason for the specific accumulation of riboflavin and phenyllactate in wolfberry. Moreover, the metabolome-based neighbor-joining tree revealed distinct clustering of monocots and dicots, suggesting that metabolites could reflect the evolutionary relationship among those species. Taken together, we identified 16 specific metabolites in wolfberry and provided new insight into the accumulation mechanism of species-specific metabolites at the genomic level

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Clinical efficacy of denosumab, teriparatide, and oral bisphosphonates in the prevention of glucocorticoid-induced osteoporosis: a systematic review and meta-analysis

Abstract Background Continuous use of glucocorticoids (GCs) has become the primary cause of secondary osteoporosis. Bisphosphonate drugs were given priority over denosumab and teriparatide in the 2017 American College of Rheumatology (ACR) guidelines but have a series of shortcomings. This study aims to explore the efficacy and safety of teriparatide and denosumab compared with those of oral bisphosphonate drugs. Methods We systematically searched studies included in the PubMed, Web of Science, Embase, and Cochrane library databases and included randomized controlled trials that compared denosumab or teriparatide with oral bisphosphonates. Risk estimates were pooled using both fixed and random effects models. Results We included 10 studies involving 2923 patients who received GCs for meta-analysis, including two drug base analyses and four sensitivity analyses. Teriparatide and denosumab were superior to bisphosphonates in increasing the bone mineral density (BMD) of the lumbar vertebrae [teriparatide: mean difference [MD] 3.98%, 95% confidence interval [CI] 3.61–4.175%, P = 0.00001; denosumab: MD 2.07%, 95% CI 0.97–3.17%, P = 0.0002]. Teriparatide was superior to bisphosphonates in preventing vertebral fractures and increasing hip BMD [MD 2.39%, 95% CI 1.47–3.32, P < 0.00001]. There was no statistically significant difference between serious adverse events, adverse events, and nonvertebral fracture prevention drugs. Conclusions Teriparatide and denosumab exhibited similar or even superior characteristics to bisphosphonates in our study, and we believe that they have the potential to become first-line GC-induced osteoporosis treatments, especially for patients who have previously received other anti-osteoporotic drugs with poor efficacy

ABCC Transporter Gene <i>MoABC-R1</i> Is Associated with Pyraclostrobin Tolerance in <i>Magnaporthe oryzae</i>

Rice blast is a worldwide fungal disease that poses a threat to food security. Fungicide treatment is one of the most effective methods to control rice blast disease. However, the emergence of fungicide tolerance hampers the control efforts against rice blast. ATP-binding cassette (ABC) transporters have been found to be crucial in multidrug tolerance in various phytopathogenic fungi. This study investigated the association between polymorphisms in 50 ABC transporters and pyraclostrobin sensitivity in 90 strains of rice blast fungus. As a result, we identified MoABC-R1, a gene associated with fungicide tolerance. MoABC-R1 belongs to the ABCC-type transporter families. Deletion mutants of MoABC-R1, abc-r1, exhibited high sensitivity to pyraclostrobin at the concentration of 0.01 μg/mL. Furthermore, the pathogenicity of abc-r1 was significantly diminished. These findings indicate that MoABC-R1 not only plays a pivotal role in fungicide tolerance but also regulates the pathogenicity of rice blast. Interestingly, the combination of MoABC-R1 deletion with fungicide treatment resulted in a three-fold increase in control efficiency against rice blast. This discovery highlights MoABC-R1 as a potential target gene for the management of rice blast

Markov state models: to optimize or not to optimize

Markov state models (MSM) are a popular statistical method for analyzing the conformational dynamics of proteins, including protein folding. With all statistical and machine learning (ML) models choices must be made about the modeling pipeline that cannot be directly learned from the data. These choices, or hyperparameters, are often evaluated by expert judgment or, in the case of MSMs, by maximizing variational scores such as the VAMP-2 score. Modern ML and statistical pipelines often use automatic hyperparameter selection techniques ranging from the simple: choosing the best score from a random selection of hyperparameters to the complex: optimization via e.g., Bayesian optimization. In this work, we ask whether it is possible to automatically select MSM models this way by estimating and analysing over 16\u27000\u27000 observations from over 280\u27000 estimated MSMs. We find that differences in hyperparameters can change the physical interpretation of the optimization objective making automatic selection difficult. In addition, we find that enforcing conditions of equilibrium in the VAMP scores can result in inconsistent model selection. However, other parameters which specify the VAMP-2 score (lag time and number of relaxation processes scored) have only negligible influence on model selection. We suggest that model observables and variational scores should only be a guide to model selection and that a full investigation of the MSM properties be undertaken when selecting hyperparameters