Rapid deep learning-assisted predictive diagnostics for point-of-care testing.

Prominent techniques such as real-time polymerase chain reaction (RT-PCR), enzyme-linked immunosorbent assay (ELISA), and rapid kits are currently being explored to both enhance sensitivity and reduce assay time for diagnostic tests. Existing commercial molecular methods typically take several hours, while immunoassays can range from several hours to tens of minutes. Rapid diagnostics are crucial in Point-of-Care Testing (POCT). We propose an approach that integrates a time-series deep learning architecture and AI-based verification, for the enhanced result analysis of lateral flow assays. This approach is applicable to both infectious diseases and non-infectious biomarkers. In blind tests using clinical samples, our method achieved diagnostic times as short as 2 minutes, exceeding the accuracy of human analysis at 15 minutes. Furthermore, our technique significantly reduces assay time to just 1-2 minutes in the POCT setting. This advancement has the potential to greatly enhance POCT diagnostics, enabling both healthcare professionals and non-experts to make rapid, accurate decisions.

High-level production and purification of bioactive recombinant human activin A in Chinese hamster ovary cells.

Activin A, a member of the TGF-ß superfamily, is a homodimer of the inhibin ßΑ subunit that plays a diversity of roles in biological processes. Because of its multiple functions, significant efforts have been made to produce activin A, however, unsatisfactory results were obtained due to its low level of expression. In this study, a stable CHO cell line exhibiting high expression of rhActivin A was isolated and production of rhActivin A was achieved using the cell line from 11-day fed-batch cultures in a 7.5 L bioreactor. The production rate was 0.22 g/L, substantially higher than those reported in previous studies. The culture supernatant of the bioreactor was used to purify rhActivin A (purity: >99%, recovery rate: 47%). The purified rhActivin A exhibited biological activity, with an EC50 of 3.893 ng/mL and a specific activity of 1.38 × 103 IU/mg. The control of process-related impurities in the purified rhActivin A was successful and met the USP recommendations for use in cell therapy. Thus, our production and purification methods were appropriate for large-scale GMP-grade rhActivin A production, which can be used for various purposes including cell therapy.

Predicting the spatio-temporal distribution of the invasive alien plant Andropogon virginicus, in the South Korean peninsula considering long-distance dispersal capacities.

The spread of invasive alien species is a major threat to biodiversity. Estimating the long-distance dispersal capacity of invasive alien plants is vital for understanding their population dynamics and community composition. We predicted the spatial-temporal distribution of the alien plant Andropogon virginicus, in the Korean peninsula under climate change scenario using Random Forest (RF) and Cellular Automaton (CA) methods. Land use, barriers to dispersal, long-distance dispersal frequency, and maximum long-distance dispersal range were considered in our analysis. Our results showed that, among the five selected environmental variables, annual mean temperature and Human Foot-Printing (HFP) were positively associated with the occurrence probability of A. virginicus. This suggests that A. virginicus is likely to spread to the disturbed northern part of the Korean Peninsula due to climate change and habitat preference. When comparing modeling results for dispersal to field survey data, the modeling raster sets drawn from the long-distance dispersal frequency of 0.05 and maximum long-distance dispersal distance of 30 km y-1 had the most similar spatial expansion among the six long-distance dispersal parameter sets. The dispersal directions were associated with the landscape. Specifically, seeds dispersed by wind (anemochorous seeds) could propagate into open landscapes more easily than in forests. Regarding A. virginicus management, this grass can quickly invade bare ground with their wind-dispersed seeds, therefore habitat destruction, such as excessive logging and weeding, should be restrained.

Sample-to-answer platform for the clinical evaluation of COVID-19 using a deep learning-assisted smartphone-based assay.

Since many lateral flow assays (LFA) are tested daily, the improvement in accuracy can greatly impact individual patient care and public health. However, current self-testing for COVID-19 detection suffers from low accuracy, mainly due to the LFA sensitivity and reading ambiguities. Here, we present deep learning-assisted smartphone-based LFA (SMARTAI-LFA) diagnostics to provide accurate decisions with higher sensitivity. Combining clinical data learning and two-step algorithms enables a cradle-free on-site assay with higher accuracy than the untrained individuals and human experts via blind tests of clinical data (n = 1500). We acquired 98% accuracy across 135 smartphone application-based clinical tests with different users/smartphones. Furthermore, with more low-titer tests, we observed that the accuracy of SMARTAI-LFA was maintained at over 99% while there was a significant decrease in human accuracy, indicating the reliable performance of SMARTAI-LFA. We envision a smartphone-based SMARTAI-LFA that allows continuously enhanced performance by adding clinical tests and satisfies the new criterion for digitalized real-time diagnostics.

PCR-like performance of rapid test with permselective tunable nanotrap.

Highly sensitive rapid testing for COVID-19 is essential for minimizing virus transmission, especially before the onset of symptoms and in asymptomatic cases. Here, we report bioengineered enrichment tools for lateral flow assays (LFAs) with enhanced sensitivity and specificity (BEETLES2), achieving enrichment of SARS-CoV-2 viruses, nucleocapsid (N) proteins and immunoglobulin G (IgG) with 3-minute operation. The limit of detection is improved up to 20-fold. We apply this method to clinical samples, including 83% with either intermediate (35%) or low viral loads (48%), collected from 62 individuals (n = 42 for positive and n = 20 for healthy controls). We observe diagnostic sensitivity, specificity, and accuracy of 88.1%, 100%, and 91.9%, respectively, compared with commercial LFAs alone achieving 14.29%, 100%, and 41.94%, respectively. BEETLES2, with permselectivity and tunability, can enrich the SARS-CoV-2 virus, N proteins, and IgG in the nasopharyngeal/oropharyngeal swab, saliva, and blood serum, enabling reliable and sensitive point-of-care testing, facilitating fast early diagnosis.

Affordable on-site COVID-19 test using non-powered preconcentrator.

A simple, affordable point of care test (POCT) is necessary for on-site detection of coronavirus disease 2019 (COVID-19). The lateral flow assay (LFA) has great potential for use in POCT mainly because of factors such as low time consumption, low cost, and ease of use. However, it lacks sensitivity and limits of detection (LOD), which are essential for early diagnostics. In this study, we proposed a non-powered preconcentrator (NPP) based on nanoelectrokinetics for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Antigen (Ag) lateral flow assay. The non-powered preconcentrator is composed of glass fiber-based composite paper and ion permselective material, and it can be simply operated by force balancing gravitational, capillary, and depletion-induced forces. The proposed approach helps enrich the SARS-CoV-2 viral nucleocapsid (N) proteins based on a 10-min operation, and it improved the LOD by up to 10-fold. The corresponding virus enrichment, which was evaluated using the reverse-transcriptase polymerase chain reaction (RT-PCR), revealed an improvement in ΔCt values > 3. We successfully demonstrated the enhancement of the NPP-assisted LFA, we extended to applying it to clinical samples. Further, we demonstrated an affordable, easy-to-implement form of LFA by simply designing NPP directly on the LFA buffer tube.

Inhibition of IκB Kinase Is a Potential Therapeutic Strategy to Circumvent Resistance to Epidermal Growth Factor Receptor Inhibition in Triple-Negative Breast Cancer Cells.

Triple-negative breast cancer (TNBC) remains as an intractable malignancy with limited therapeutic targets. High expression of epidermal growth factor receptor (EGFR) has been associated with a poor prognosis of TNBC; however, EGFR targeting has failed with unfavorable clinical outcomes. Here, we performed a combinatorial screening of fifty-five protein kinase inhibitors with the EGFR inhibitor gefitinib in the TNBC cell line MDA-MB-231 and identified the IκB kinase (IKK) inhibitor IKK16 as a sensitizer of gefitinib. Cell viability and clonogenic survival assays were performed to evaluate the antiproliferative effects of the gefitinib and IKK16 (Gefitinib + IKK16) combination in TNBC cell lines. Western blot analyses were also performed to reveal the potential mode of action of this combination. In addition, next-generation sequencing (NGS) analysis was performed in Gefitinib+IKK16-treated cells. The Gefitinib+IKK16 treatment synergistically reduced cell viability and colony formation of TNBC cell lines such as HS578T, MDA-MB-231, and MDA-MB-468. This combination downregulated p-STAT3, p-AKT, p-mTOR, p-GSK3ß, and p-RPS6. In addition, p-NF-κB and the total NF-κB were also regulated by this combination. Furthermore, NGS analysis revealed that NF-κB/RELA targets including CCL2, CXCL8, EDN1, IL-1ß, IL-6, and SERPINE1 were further reduced and several potential tumor suppressors, such as FABP3, FADS2, FDFT1, SEMA6A, and PCK2, were synergistically induced by the Gefitinib-+IKK16 treatment. Taken together, we identified the IKK/NF-κB pathway as a potential target in combination of EGFR inhibition for treating TNBC.

Penalized likelihood approach for the four-parameter kappa distribution.

The four-parameter kappa distribution (K4D) is a generalized form of some commonly used distributions such as generalized logistic, generalized Pareto, generalized Gumbel, and generalized extreme value (GEV) distributions. Owing to its flexibility, the K4D is widely applied in modeling in several fields such as hydrology and climatic change. For the estimation of the four parameters, the maximum likelihood approach and the method of L-moments are usually employed. The L-moment estimator (LME) method works well for some parameter spaces, with up to a moderate sample size, but it is sometimes not feasible in terms of computing the appropriate estimates. Meanwhile, using the maximum likelihood estimator (MLE) with small sample sizes shows substantially poor performance in terms of a large variance of the estimator. We therefore propose a maximum penalized likelihood estimation (MPLE) of K4D by adjusting the existing penalty functions that restrict the parameter space. Eighteen combinations of penalties for two shape parameters are considered and compared. The MPLE retains modeling flexibility and large sample optimality while also improving on small sample properties. The properties of the proposed estimator are verified through a Monte Carlo simulation, and an application case is demonstrated taking Thailand's annual maximum temperature data.

Synapto-protective effect of lithium on HIV-1 Tat-induced synapse loss in rat hippocampal cultures.

Human immunodeficiency virus type I (HIV-1) infection of the CNS produces synapse loss which correlates with cognitive decline in patients with HIV-associated neurocognitive disorders (HAND). Lithium is mood stabilizer of unknown mechanism used to treat bipolar disorder and is known to exhibit neuroprotective properties. Here, we studied the effects of lithium on HIV-1 Tat-induced synapses between rat hippocampal neurons. The number of synapses was quantified to detect clusters of the scaffold protein postsynaptic density 95 (PSD95) which is clustered at glutamatergic synapses on cultured rat hippocampal neurons in vitro. Lithium protected synapses from HIV-1 Tat-induced synapse loss and subsequent neuronal death. This synaptic protection was prevented by both the activation of NMDA receptor leading to intracellular signaling and the regulatory pathway of lithium including inositol depletion and glycogen synthase kinase-3ß (GSK-3ß). These results suggest that mood stabilizers might be effective drugs to treat neurodegenerative disorders including HAND.

Spatially Varying Relationships between Alien Plant Distributions and Environmental Factors in South Korea.

Invasive alien plants can severely threaten biodiversity and cause economic losses in the agricultural industry; therefore, identifying the critical environmental factors related to the distribution of alien plants plays a crucial role in ecosystem management. In this study, we applied partial least squares regression (PLSR) and geographically weighted regression (GWR) to estimate the important environmental factors affecting the spread of two invasive and expansive plants, Lactuca scariola L. and Aster pilosus Willd., across South Korea. GWR provides more accurate predictions than ordinary least squares regression, and the local coefficients of GWR allow for the determination of the spatial relationships between alien plant distributions and environmental variables. Based on the model's results, the distributions of these alien species were significantly associated with anthropogenic effects, such as human population density, residential area, and road density. Furthermore, the two alien species can establish themselves in habitats where native plants cannot thrive, owing to their broad tolerance to temperature and drought conditions. This study suggests that urban development and expansion can facilitate the invasion of these species in metropolitan cities.

Potentiating Therapeutic Effects of Epidermal Growth Factor Receptor Inhibition in Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is a subset of breast cancer with aggressive characteristics and few therapeutic options. The lack of an appropriate therapeutic target is a challenging issue in treating TNBC. Although a high level expression of epidermal growth factor receptor (EGFR) has been associated with a poor prognosis among patients with TNBC, targeted anti-EGFR therapies have demonstrated limited efficacy for TNBC treatment in both clinical and preclinical settings. However, with the advantage of a number of clinically approved EGFR inhibitors (EGFRis), combination strategies have been explored as a promising approach to overcome the intrinsic resistance of TNBC to EGFRis. In this review, we analyzed the literature on the combination of EGFRis with other molecularly targeted therapeutics or conventional chemotherapeutics to understand the current knowledge and to provide potential therapeutic options for TNBC treatment.

Ribosomal Protein S6: A Potential Therapeutic Target against Cancer?

Ribosomal protein S6 (RPS6) is a component of the 40S small ribosomal subunit and participates in the control of mRNA translation. Additionally, phospho (p)-RPS6 has been recognized as a surrogate marker for the activated PI3K/AKT/mTORC1 pathway, which occurs in many cancer types. However, downstream mechanisms regulated by RPS6 or p-RPS remains elusive, and the therapeutic implication of RPS6 is underappreciated despite an approximately half a century history of research on this protein. In addition, substantial evidence from RPS6 knockdown experiments suggests the potential role of RPS6 in maintaining cancer cell proliferation. This motivates us to investigate the current knowledge of RPS6 functions in cancer. In this review article, we reviewed the current information about the transcriptional regulation, upstream regulators, and extra-ribosomal roles of RPS6, with a focus on its involvement in cancer. We also discussed the therapeutic potential of RPS6 in cancer.

Generalized Nonlinear Least Squares Method for the Calibration of Complex Computer Code Using a Gaussian Process Surrogate.

The approximated nonlinear least squares (ALS) method has been used for the estimation of unknown parameters in the complex computer code which is very time-consuming to execute. The ALS calibrates or tunes the computer code by minimizing the squared difference between real observations and computer output using a surrogate such as a Gaussian process model. When the differences (residuals) are correlated or heteroscedastic, the ALS may result in a distorted code tuning with a large variance of estimation. Another potential drawback of the ALS is that it does not take into account the uncertainty in the approximation of the computer model by a surrogate. To address these problems, we propose a generalized ALS (GALS) by constructing the covariance matrix of residuals. The inverse of the covariance matrix is multiplied to the residuals, and it is minimized with respect to the tuning parameters. In addition, we consider an iterative version for the GALS, which is called as the max-minG algorithm. In this algorithm, the parameters are re-estimated and updated by the maximum likelihood estimation and the GALS, by using both computer and experimental data repeatedly until convergence. Moreover, the iteratively re-weighted ALS method (IRWALS) was considered for a comparison purpose. Five test functions in different conditions are examined for a comparative analysis of the four methods. Based on the test function study, we find that both the bias and variance of estimates obtained from the proposed methods (the GALS and the max-minG) are smaller than those from the ALS and the IRWALS methods. Especially, the max-minG works better than others including the GALS for the relatively complex test functions. Lastly, an application to a nuclear fusion simulator is illustrated and it is shown that the abnormal pattern of residuals in the ALS can be resolved by the proposed methods.

Efficient production process of bioactive recombinant human leukemia inhibitory factor in Chinese hamster ovary cells.

The rhLIF is widely used as an essential factor in stem cell cultures for cell therapies. However, all the recombinant LIFs commercially available are expensive, and no commercially available rhLIF meet the standards recommended by USP for use in cell therapies. The current study reports the efficient production of N-glycosylated and bioactive rhLIF in CHO cells. The production rate of established rhLIF-expressing rCHO cells was approximately 0.85 g/l in 12-day fed-batch cultures using a 7.5 l bioreactor. The rhLIF protein was purified via a four-step purification procedure with approximately 57% recovery rate and greater than 99% purity. The purified rhLIF was N-glycosylated and biologically active with an EC50 of 0.167 ng/ml and a specific activity of 0.86 × 103 IU/mg. The purification procedure controlled the levels of process-related impurities below critical levels recommended by USP for cytokines used in cell therapies. The current work is the first production process of N-glycosylated and bioactive rhLIF, which can be applied to large-scale manufacture of GMP-grade rhLIF for use as an ancillary material in cell therapy.

Expectation-Maximization Algorithm for the Calibration of Complex Simulator Using a Gaussian Process Emulator.

The approximated non-linear least squares (ALS) tunes or calibrates the computer model by minimizing the squared error between the computer output and real observations by using an emulator such as a Gaussian process (GP) model. A potential defect of the ALS method is that the emulator is constructed once and it is no longer re-built. An iterative method is proposed in this study to address this difficulty. In the proposed method, the tuning parameters of the simulation model are calculated by the conditional expectation (E-step), whereas the GP parameters are updated by the maximum likelihood estimation (M-step). These EM-steps are alternately repeated until convergence by using both computer and experimental data. For comparative purposes, another iterative method (the max-min algorithm) and a likelihood-based method are considered. Five toy models are tested for a comparative analysis of these methods. According to the toy model study, both the variance and bias of the estimates obtained from the proposed EM algorithm are smaller than those from the existing calibration methods. Finally, the application to a nuclear fusion simulator is demonstrated.

Pharmacokinetic and bioequivalence study of a fixed-dose combination of amlodipine besylate and rosuvastatin calcium compared to co-administration of separate tablets in healthy Korean subjects
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CONTEXT: A fixed-dose combination (FDC) tablet of amlodipine and rosuvastatin was recently developed for the treatment of concomitant hypertension and dyslipidemia and is anticipated to improve medication compliance. OBJECTIVE: This study was performed to compare the single-dose pharmacokinetic properties and safety of DP-R212 (FDC of amlodipine and rosuvastatin) to those of each agent co-administered in healthy Korean subjects. MATERIALS AND METHODS: A total of 36 healthy Korean subjects were enrolled in this randomized, open-label, single-dose, two-treatment, two-way crossover study. During each treatment period, subjects received the test drug (FDC tablet containing amlodipine and rosuvastatin) or reference drugs (individual tablets). Plasma samples were collected pre-dose and at 0.5, 1, 2, 3, 4, 5, 6, 8, 10, 12, 24, 48, and 72 hours post-dose. Safety was assessed by the evaluation of adverse events (AEs), laboratory assessments, 12-lead electrocardiograms (ECGs), physical examinations, and vital sign measurements. RESULTS: The 90% confidence intervals (CIs) of the geometric least-square mean ratios of AUClast and Cmax were 0.9796 - 1.0590 and 1.0135 - 1.0981 for amlodipine, and 0.9156 - 1.0490 and 0.8400 - 1.0306 for rosuvastatin, respectively. All AEs were of mild to moderate intensity, and no significant difference was observed in the incidence of AEs between the treatments. Moreover, the pharmacokinetic properties of the test and reference drugs were bioequivalent to each other, satisfying the regulatory criteria (0.8 - 1.25). DISCUSSION AND CONCLUSION: Both drugs were safe and well tolerated, and the pharmacokinetic profiles were comparable between the treatments.

Mowing: A cause of invasion, but also a potential solution for management of the invasive, alien plant species Erigeron annuus (L.) Pers.

Erigeron annuus is one of the major invasive, alien plants in Korea, and therefore research to manage (control) this invasive plant is essential. In this research, studies were conducted to determine the mechanisms by which E. annuus became the dominant plant at a landfill site and to develop management strategies for this alien plant. Because the seeds and seedling stage did not have superior adaptations to disturbed soil, demonstrate allelopathy, outcompete other species, or show rapid growth, the disturbance from mowing was likely the primary reason for the dominance of E. annuus. The areas without mowing showed a significant decrease in the coverage of E. annuus, whereas the mowed (managed) areas showed a significant increase. Additionally, mowing once increased the weight of reproductive organs by 50% and suppressed the growth of native species. Thus, the primary factor in the invasion of the alien species E. annuus was mowing, and, to control such an invasion, areas should be protected from mowing. Additionally, with selective mowing that targeted only E. annuus, mowing three times produced only approximately 10% of the reproductive organ biomass compared with that of the control. Because the flower stalk of E. annuus was relatively tall compared with that of native species in early summer, selective mowing might also provide a solution to control invasions of E. annuus. Therefore, with improved ecological understanding of the site and species, mowing of the right target during the optimal season and at an appropriate frequency is an environmental friendly solution to the management of E. annuus.

GPCR Kinase (GRK)-2 Is a Key Negative Regulator of Itch: l-Glutamine Attenuates Itch via a Rapid Induction of GRK2 in an ERK-Dependent Way.

Many itch mediators activate GPCR and trigger itch via activation of GPCR-mediated signaling pathways. GPCRs are desensitized by GPCR kinases (GRKs). The aim of this study is to explore the role of GRKs in itch response and the link between GRKs and glutamine, an amino acid previously shown to be an itch reliever. Itch responses were evoked by histamine, chloroquine, and dinitrochlorobenzene-induced contact dermatitis (CD). Phosphorylation and protein expression were detected by immunofluorescent staining and Western blotting. GRK2 knockdown using small interfering RNA enhanced itch responses evoked by histamine, chloroquine, and dinitrochlorobenzene-induced CD, whereas GRK2 overexpression using GRK2-expressing adenovirus reduced the itch responses. Glutamine reduced all itch evoked by histamine, chloroquine, and dinitrochlorobenzene-induced CD. Glutamine-mediated inhibition of itch was abolished by GRK2 knockdown. Glutamine application resulted in a rapid and strong expression of GRK2 in not only dinitrochlorobenzene-induced CD (within 10 minutes) but also cultured rat dorsal root ganglion cells, F11 (within 1 minute). ERK inhibitor abrogates glutamine-mediated GRK2 expression and inhibition of itch in dinitrochlorobenzene-induced CD. Our data indicate that GRK2 is a key negative regulator of itch and that glutamine attenuates itch via a rapid induction of GRK2 in an ERK-dependent way.

Usage of Human Mesenchymal Stem Cells in Cell-based Therapy: Advantages and Disadvantages.

The use of human mesenchymal stem cells (hMSCs) in cell-based therapy has attracted extensive interest in the field of regenerative medicine, and it shows applications to numerous incurable diseases. hMSCs show several superior properties for therapeutic use compared to other types of stem cells. Different cell types are discussed in terms of their advantages and disadvantages, with focus on the characteristics of hMSCs. hMSCs can proliferate readily and produce differentiated cells that can substitute for the targeted affected tissue. To maximize the therapeutic effects of hMSCs, a substantial number of these cells are essential, requiring extensive ex vivo cell expansion. However, hMSCs have a limited lifespan in an in vitro culture condition. The senescence of hMSCs is a double-edged sword from the viewpoint of clinical applications. Although their limited cell proliferation potency protects them from malignant transformation after transplantation, senescence can alter various cell functions including proliferation, differentiation, and migration, that are essential for their therapeutic efficacy. Numerous trials to overcome the limited lifespan of mesenchymal stem cells are discussed.

Quantitative analysis of adsorptive interactions of ionic and neutral pharmaceuticals and other chemicals with the surface of Escherichia coli cells in aquatic environment.

Since Escherichia coli is ubiquitous in nature and has been applied to biological, chemical, and environmental processes, molecular-level understanding of adsorptive interactions between chemicals and the bacterial surface is of great importance. To characterise the adsorption properties of the surface of E. coli cells in aquatic environment, the binding affinities (log Kd) of calibration compounds were experimentally measured, and then based on the values and numerically well-defined molecular interaction forces, i.e. linear free energy relationship (LFER) descriptors, a predictive model was developed. The examined substances are composed of cations, anions, and neutral compounds, and the used LFER descriptors are excess molar refraction (E), dipolarity/polarisability (S), H-bonding acidity (A) and basicity (B), McGowan volume (V), and coulombic interactions of cations (J+) and anions (J-). In experimental results, adsorption of anions on the bacterial surface was not observed, while cations exhibited high affinities. In case of neutral compounds, their low quantities were adsorbed, however whose affinities were mostly lower than those of cations. In a LFER study, it was shown that cationic interaction term has the best correlation in R2 of 0.691 and sequential additions of S, A, and V help to increase the prediction accuracy. The LFER model (log Kd = - 0.72-0.79 S + 0.81 A + 0.41 V + 0.85 J+) could predict the log Kd in R2 of 0.871 and SE of 0.402 log unit, and then to check robustness and predictability of the model, we internally validated it by a leave-one-out cross validation (Q2LOO) study. As a result, the Q2LOO value was estimated to be 0.826, which was larger than standard of model acceptability (>0.5).