Quantification of salt stress in wheat leaves by Raman spectroscopy and machine learning

The salinity level of the growing medium has diverse effects on the development of plants, including both physical and biochemical changes. To determine the salt stress level of a plant endures, one can measure these structural and chemical changes. Raman spectroscopy and biochemical analysis are some of the most common techniques in the literature. Here, we present a combination of machine learning and Raman spectroscopy with which we can both find out the biochemical change that occurs while the medium salt concentration changes and predict the level of salt stress a wheat sample experiences accurately using our trained regression models. In addition, by applying different machine learning algorithms, we compare the level of success for different algorithms and determine the best method to use in this application. Production units can take actions based on the quantitative information they get from the trained machine learning models related to salt stress, which can potentially increase efficiency and avoid the loss of crops.

Altered plasma, urine, and tissue profiles of sulfatides and sphingomyelins in patients with renal cell carcinoma

Renal cell carcinoma (RCC) represents the most common type of kidney cancer with the highest incidence and mortality rate among all urological malignancies. In this study, we show that RCC-related processes change body fluids sphingolipid concentrations, which may be used to monitor cancer occurrence in low-invasive lipid-based blood and urine tests. We investigate 674 plasma, urine, and tissue samples from 369 RCC patients and controls. For the first time, we show the significant concentration changes of low abundant sulfatides in plasma and urine of RCC patients. Elevated concentrations of lactosylsulfatides, decreased concentrations of sphingomyelines with long saturated N-fatty acyls and sulfatides with hydroxylated fatty acyls are the most crucial alternations in RCC. These changes are stage-dependent and are more emphasized in late-stage RCC. Similar trends in body fluids and tissues indicate that RCC widely influences lipid metabolism and highlights the potential of lipidomic profiling for cancer detection.

Revised Michaelis-Menten rate law with time-varying molecular concentrations

Despite over a century's use as a dominant paradigm in the description of biochemical rate processes, the Michaelis-Menten (MM) rate law stands on the restrictive assumption that the concentration of the complex of interacting molecules, at each moment, approaches an equilibrium much faster than the molecular concentration changes. The increasingly-appreciated, remedied form of the MM rate law is also based on this quasi-steady state assumption. Although this assumption may be valid for a range of biochemical systems, the exact extent of such systems is not clear. In this study, we relax the quasi-steady state requirement and propose the revised MM rate law for the interactions of molecules with active concentration changes over time. Our revised rate law, characterized by rigorously-derived time delay effects in molecular complex formation, improves the accuracy of models especially for protein-protein and protein-DNA interactions. Our simulation and empirical data analysis show that the improvement is not limited to the quantitatively better characterization of the dynamics, but also allows the prediction for qualitatively new patterns in the systems of interest. The latter include the oscillation condition and period patterns of the mammalian circadian clock and the spontaneous rhythmicity in the degradation rates of circadian proteins, both not properly captured by the previous approaches. Moreover, our revised rate law is capable of more accurate parameter estimation. This work offers an analytical framework for understanding rich dynamics of biomolecular systems, which goes beyond the quasi-steady state assumption.

Synaptosomal-Associated Protein 25 Gene Polymorphisms Affect Treatment Efficiency of Methylphenidate in Children With Attention-Deficit Hyperactivity Disorder: An fNIRS Study

Methylphenidate (MPH) is the first-line drug for the treatment of children with attention-deficit hyperactivity disorder (ADHD); however, individual curative effects of MPH vary. Many studies have demonstrated that synaptosomal-associated protein 25 (SNAP-25) gene MnlI polymorphisms may be related to the efficacy of MPH. However, the association between SNAP-25MnlI polymorphisms and changes in brain hemodynamic responses after MPH treatment is still unclear. This study used functional near-infrared spectroscopy (fNIRS) to preliminarily investigate the interaction of MPH treatment-related prefrontal inhibitory functional changes with the genotype status of the SNAP-25 gene in children with ADHD. In total, 38 children with ADHD aged 6.76–12.08 years were enrolled in this study and divided into the following two groups based on SNAP-25 gene MnlI polymorphisms: T/T genotype group (wild-type group, 27 children) and G allele carrier group (mutation group, 11 children). The averaged oxygenated hemoglobin concentration changes [Δavg oxy-Hb] and deoxyhemoglobin concentration changes [Δavg deoxy-Hb] in the frontal cortex before MPH treatment and after 1.5 h (post-MPH1.5h) and 4 weeks (post-MPH4w) of MPH treatments were monitored using fNIRS during the go/no-go task. SNAP-IV scores were evaluated both pre-MPH and post-MPH4w treatments. In the T/T genotype group, [Δavg oxy-Hb] in the dorsolateral prefrontal cortex was significantly higher after 4 weeks of MPH (post-MPH4W) treatment than pre-treatment; however, in the G allele group, no significant differences in [Δavg oxy-Hb] were observed between pre- and post-treatments. In the go/no-go task, the accuracy was significantly increased post-MPH4w treatment in the T/T genotype group, while no significant differences were observed in response time and accuracy of the “go” sand no-go task in the G allele group for pre-MPH, post-MPH1.5h, and post-MPH4w treatments. The T/T genotype group exhibited a significant decrease in SNAP-IV scores after MPH treatment, while the G allele group showed no significant difference. In conclusion, fNIRS data combined with SNAP-25 MnlI polymorphism analysis may be a useful biomarker for evaluating the effects of MPH in children with ADHD.

Modeling of nursing care-associated airborne transmission of SARS-CoV-2 in a real-world hospital setting

Respiratory transmission of SARS-CoV-2 from one older patient to another by airborne mechanisms in hospital and nursing home settings represents an important health challenge during the COVID-19 pandemic. However, the factors that influence the concentration of respiratory droplets and aerosols that potentially contribute to hospital- and nursing care-associated transmission of SARS-CoV-2 are not well understood. To assess the effect of health care professional (HCP) and patient activity on size and concentration of airborne particles, an optical particle counter was placed (for 24 h) in the head position of an empty bed in the hospital room of a patient admitted from the nursing home with confirmed COVID-19. The type and duration of the activity, as well as the number of HCPs providing patient care, were recorded. Concentration changes associated with specific activities were determined, and airway deposition modeling was performed using these data. Thirty-one activities were recorded, and six representative ones were selected for deposition modeling, including patient’s activities (coughing, movements, etc.), diagnostic and therapeutic interventions (e.g., diagnostic tests and drug administration), as well as nursing patient care (e.g., bedding and hygiene). The increase in particle concentration of all sizes was sensitive to the type of activity. Increases in supermicron particle concentration were associated with the number of HCPs (r = 0.66; p < 0.05) and the duration of activity (r = 0.82; p < 0.05), while submicron particles increased with all activities, mainly during the daytime. Based on simulations, the number of particles deposited in unit time was the highest in the acinar region, while deposition density rate (number/cm2/min) was the highest in the upper airways. In conclusion, even short periods of HCP-patient interaction and minimal patient activity in a hospital room or nursing home bedroom may significantly increase the concentration of submicron particles mainly depositing in the acinar regions, while mainly nursing activities increase the concentration of supermicron particles depositing in larger airways of the adjacent bed patient. Our data emphasize the need for effective interventions to limit hospital- and nursing care-associated transmission of SARS-CoV-2 and other respiratory pathogens (including viral pathogens, such as rhinoviruses, respiratory syncytial virus, influenza virus, parainfluenza virus and adenoviruses, and bacterial and fungal pathogens).

Biofabrication of advanced in vitro 3D models to study ischaemic and doxorubicin-induced myocardial damage

Current preclinical in vitro and in vivo models of cardiac injury typical of myocardial infarction (MI, or heart attack) and drug induced cardiotoxicity mimic only a few aspects of these complex scenarios. This leads to a poor translation of findings from the bench to the bedside. In this study, we biofabricated for the first time advanced in vitro models of MI and doxorubicin (DOX) induced injury by exposing cardiac spheroids (CSs) to pathophysiological changes in oxygen (O2) levels or DOX treatment. Then, contractile function and cell death was analyzed in CSs in control versus I/R and DOX CSs. For a deeper dig into cell death analysis, 3D rendering analyses and mRNA level changes of cardiac damage-related genes were compared in control versus I/R and DOX CSs. Overall, in vitro CSs recapitulated major features typical of the in vivo MI and drug induced cardiac damages, such as adapting intracellular alterations to O2 concentration changes and incubation with cardiotoxic drug, mimicking the contraction frequency and fractional shortening and changes in mRNA expression levels for genes regulating sarcomere structure, calcium transport, cell cycle, cardiac remodelling and signal transduction. Taken together, our study supports the use of I/R and DOX CSs as advanced in vitro models to study MI and DOX-induced cardiac damage by recapitulating their complex in vivo scenario.

Update on dyslipidemia in hypothyroidism

Hypothyroidism is often associated with elevated serum levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C) and triglycerides. Thyroid hormone (TH) affects the production, clearance and transformation of cholesterol, but current research shows that thyroid-stimulating hormone (TSH) also participates in lipid metabolism independently of TH. Therefore, the mechanism of hypothyroidism-related dyslipidemia is associated with the decrease of TH and the increase of TSH levels. Some newly identified regulatory factors, such as proprotein convertase subtilisin/kexin type 9 (PCSK9), angiogenin-like proteins (ANGPTL), and fibroblast growth factors (FGF) are the underlying causes of dyslipidemia in hypothyroidism. High-density lipoprotein (HDL) serum concentration changes were not consistent, and its function was reportedly impaired. The current review focuses on the updated understanding of the mechanism of hypothyroidism-related dyslipidemia.