Supplemental Material, sj-png-1-tct-10.1177_15330338211036314 - Identification of a Signature Comprising 5 Soluble Carrier Family Genes to Predict the Recurrence of Papillary Thyroid Carcinoma

Supplemental Material, sj-png-1-tct-10.1177_15330338211036314 for Identification of a Signature Comprising 5 Soluble Carrier Family Genes to Predict the Recurrence of Papillary Thyroid Carcinoma by Rui Han, Wei Sun and Hao Zhang in Technology in Cancer Research & Treatment</p

sj-xlsx-1-ade-10.1177_16878132231170771 – Supplemental material for Research on the Method of Improving iGPS Dynamic Tracking Accuracy Based on Theoretical Trajectory Backward Compensation

Supplemental material, sj-xlsx-1-ade-10.1177_16878132231170771 for Research on the Method of Improving iGPS Dynamic Tracking Accuracy Based on Theoretical Trajectory Backward Compensation by Rui Han, Erik Trostmann and Thomas Dunker in Advances in Mechanical Engineering</p

sj-rar-2-ade-10.1177_16878132231170771 – Supplemental material for Research on the Method of Improving iGPS Dynamic Tracking Accuracy Based on Theoretical Trajectory Backward Compensation

Supplemental material, sj-rar-2-ade-10.1177_16878132231170771 for Research on the Method of Improving iGPS Dynamic Tracking Accuracy Based on Theoretical Trajectory Backward Compensation by Rui Han, Erik Trostmann and Thomas Dunker in Advances in Mechanical Engineering</p

Additional file 1 of One size does not fit all: an application of stochastic modeling to estimating primary healthcare needs in Ethiopia at the sub-national level

Additional file 1: Table S1. List of Health Extension Program (HEP) primary health care services(25), grouped in service packages. These services are expected to be delivered at the health posts. Table S2. Probability distribution specifications for stochastic parameters. Random sampling occurs for the listed model parameters based on the chosen probability distribution. Mean and delta values for each model parameter are sourced from reported data. Values for p and q are chosen to reflect the desired range of values to sample from. Table S3. Seasonality Curves. Each column of the table represents one seasonality curve, reflecting the relative frequency of observing the condition in each month of the year. The sum across all months of the year for each curve is 1. Table S4. Seasonality Offsets. Seasonality curves are applied to relevant clinical tasks based on the listed offset values for each contact. An offset value specifies the number of months a seasonality curve needs to shift to match the timing of the contact with the health system to receive service: 0 for as is, a positive value for shifting forward, and a negative value for shifting backward.  Figure S1. Population composition in 2020 by age group and region. The total population is shown, broken out by age group, gender, and region. The population includes individuals between the age of 0 and 100, assigned into following groups: infants (i.e., age under 1), under 5 (i.e., age of 1 to 4), 5-14, 15-24, 25-34, 35-44, 45-54, 55-64, 65-100. Figure S2. Seasonality of clinical workload. The month-by-month variation of the clinical workload is shown, broken out for each region, in 2022 and 2035. Values are the ratio of predicted clinical workload for the month, relative to the average predicted monthly workload of the year. Shown are the average values calculated from 100 simulation trials

DataSheet1_Protective effects and mechanisms of the Erzhi formula on glucocorticoid induced primary cortical neuron injury.docx

High concentrations of glucocorticoids (GC) can cross the blood-brain barrier into the brain parenchyma, triggering a stress state that can lead to a range of physiological changes. This study investigated whether Erzhi formula has neuroprotective effects against glucocorticoid damage by establishing a dexamethasone-induced primary cortical neuron injury model in vitro. The results showed that Erzhi formula could reduce dexamethasone-induced apoptosis in primary cultured cortical neurons and improve synaptic damage. Further, network pharmacological analysis revealed that Erzhi formula may exert antidepressant effects by multi-component, multi-target, and multi-pathway characteristics, in which Salidroside, Biochanin-A and other ingredients are key components, HSD11B1, NR3C1, and other proteins are key targets, and steroid metabolism may be a key process in its action. Moreover, our study found that the neuroprotective effect of Erzhi formula might be related to the 11β-HSD1-GC/glucocorticoid receptor (GR) signaling pathway. The Erzhi formula could significantly inhibit the activity of 11β-hydroxysteroid dehydrogenase 1 (11β-HSD1) in vitro using homogeneous time-resolved fluorescence. In addition to providing evidence for the pharmacological effects of the Erzhi formula, the present study lays down the foundation for subsequent experiments.</p

Detecting Plasmon Resonance Energy Transfer with Differential Interference Contrast Microscopy

Gold nanoparticles are ideal probes for studying intracellular environments and energy transfer mechanisms due to their plasmonic properties. Plasmon resonance energy transfer (PRET) relies on a plasmonic nanoparticle to donate energy to a nearby resonant acceptor molecule, a process which can be observed due to the plasmonic quenching of the donor nanoparticle. In this study, a gold nanosphere was used as the plasmonic donor, while the metalloprotein cytochrome c was used as the acceptor molecule. Differential interference contrast (DIC) microscopy allows for simultaneous monitoring of complex environments and noble metal nanoparticles in real time. Using DIC and specially designed microfluidic channels, we were able to monitor PRET at the single gold particle level and observe the reversibility of PRET upon the introduction of phosphate-buffered saline to the channel. In an additional experiment, single gold particles were internalized by HeLa cells and were subsequently observed undergoing PRET as the cell hosts underwent morphological changes brought about by ethanol-induced apoptosis

DataSheet1_Control Strategy of Distributed Energy Micro-Grid Involving Distribution System Resilience.docx

To realize low-carbon energy systems, distributed energy storage systems and flexible loads have been integrated into power grids. System reliability, economy, and resilience, therefore, face significant challenges. This article presents modeling of a distributed energy micro-grid including wind turbines, micro gas turbines, waste heat recovery devices, electric boilers, direct-fired boilers, battery energy storage, interruptible loads, and transferable loads. At the same time, the optimal configuration of energy storage and the demand-side response modeling are studied, and the combined optimization control strategy of the two is demonstrated. The simulation results indicate that the proposed control strategy has better performance than the traditional operation. In addition, this article also clarifies the impact of control strategy on distribution system resilience. The results show that the control strategy proposed in this article can achieve the resource complementarity of demand-side response and energy storage, and realize the integrated coordination of source, network, load, and storage. The distributed energy micro-grid under this control strategy has the best overall economic benefit and the best capacity to accommodate load growth.</p

Designed Polyhydroxyproline Helical Peptide with Ultrarobust Antifouling Capability for Electrochemical Sensing in Diverse Complex Biological Fluids

Developing a generalized strategy for the nonfouling detection of biomarkers in diverse biological fluids presents a significant challenge. Herein, a polyhydroxyproline helical peptide (PHHP) was designed and adopted to fabricate electrochemical microsensors capable of detecting targets in various biological media. The PHHP possessed unique properties such as strong hydrophilicity, rigid structure, and lack of ionizable side-chain groups. Compared with common zwitterionic peptides (ZIPs), the PHHP exhibited similar antifouling capability but exceptional stability, allowing its antifouling performance to be unaffected by environmental alteration. The PHHP can prevent biofouling even in fluctuating pH conditions, high ionic strength environments, and the presence of high-valence ions and resist the protease hydrolysis. The PHHP-modified carbon fiber microelectrode was further immobilized with an aptamer to construct an antifouling microsensor for cortisol detection across diverse biofluids, and the microsensor exhibited acceptable accuracy and higher sensitivity than the ELISA method. In addition, different biological samples of mice were collected in situ using a microsensing device, and cortisol levels were analyzed in each specifically tailored region. This nonfouling sensing strategy based on PHHP allows a comprehensive assessment of biomarkers in both spatial and temporal dimensions in diverse biological environments, holding promising potential for early disease diagnosis and real-time health monitoring

Revealing Solid–Liquid Equilibrium Behavior of 4‑Fluorobenzoic Acid in 12 Pure Solvents from 283.15 to 323.15 K by Experiments and Molecular Simulations

The solubility of 4-fluorobenzoic acid (4FBA) in 12 pure solvents (methanol, ethanol, 1-propanol, 2-propanol, 1-butanol, isobutanol, 1-pentanol, ethyl formate, methyl acetate, ethyl acetate, acetonitrile, and acetone) from 283.15 to 323.15 K at atmospheric pressure was determined using the gravimetric method. Within the experimental temperature range, the solubility of 4FBA increased with increasing temperature in all solvents. Four thermodynamic models (modified Apelblat model, NRTL model, Van’t Hoff model, and λh model) were selected to correlate the experimental solubility data of 4FBA and assess the goodness of fit. The results revealed that the modified Apelblat equation exhibited the highest fitting accuracy. Furthermore, the mixing thermodynamic properties (mixing Gibbs free energy, mixing enthalpy, and mixing entropy) derived from the NRTL equation indicated that the mixing process of 4FBA in the selected solvents is spontaneous and entropy-driven. To elucidate the solid–liquid equilibrium behavior of 4FBA in pure solvents, the structural properties of the solute–solvent molecules were investigated. The physicochemical properties of solvents, solvation free energies, and radial distribution functions were studied to explain the solid–liquid equilibrium behavior of 4FBA