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In this study functional ultrasound (fUS) imaging has been implemented to explore the local hemodynamics response induced by electrical epidural stimulation and to study real-time in vivo functional changes of the spinal cord, taking advantage of the superior spatiotemporal resolution provided by fUS. By quantifying the hemodynamics and electromyographic response features, we tested the hypothesis that the temporal hemodynamics response of the spinal cord to electrical epidural stimulation could reflect modulation of the spinal circuitry and accordingly respond to the changes in parameters of electrical stimulation. The results of this study for the first time demonstrate that the hemodynamics response to electrical stimulation could reflect a neural-vascular coupling of the spinal cord. Response in the dorsal areas to epidural stimulation was significantly higher and faster compared to the response in ventral spinal cord. Positive relation between the hemodynamics and the EMG responses was observed at the lower frequencies of epidural stimulation (20 and 40 Hz), which according to our previous findings can facilitate spinal circuitry after spinal cord injury, compared to higher frequencies (200 and 500 Hz). These findings suggest that different mechanisms could be involved in spinal cord hemodynamics changes during different parameters of electrical stimulation and for the first time provide the evidence that neural-vascular coupling of the spinal cord circuitry could be related to specific organization of spinal cord vasculature and hemodynamics.

This study discusses the feasibility of diversifying the scope of application of lead-free Sr3ZBr3 (Z = As, Sb) as promising materials for their enhanced electronic, mechanical, optical, thermodynamic, and thermoelectric properties using first-principles calculation based on Density Functional Theory (DFT). Both compounds have cubic crystal structures, and both materials' dynamic stability is validated by the lack of negative frequencies in their phonon dispersion spectra. Besides ground state physical characteristics, we also examined the impact of hydrostatic pressure (0–21 GPa) on electronic, mechanical, and optical properties. The lattice parameters exhibit a linear decrease from 6.27 to 5.61 Å for Sr3AsBr3 and 6.45 to 5.71 Å for Sr3SbBr3 under increasing pressure, attributed to bond length reduction, which alters their physical properties. Initially observed direct band gap (Γ-Γ) of Sr3AsBr3 and Sr3SbBr3 were 2.35 and 2.30 eV using modified Becke-Johnson (mBJ) functional which reduces to 1.15 and 0.82 eV as the compounds go from 0 to 21 GPa pressure. This study reveals enhanced optical properties under pressure, with broader spectral response, increased sensitivity, and improved dielectric constant. Optical absorption and conductivity also shift toward lower-energy photons. The investigation further shows that the compounds show brittle to ductile transition under high pressure. Their ductility and anisotropy nature are further enhanced with pressure along with other mechanical features. The thermodynamic properties indicate their ability to withstand and perform well at high temperatures and pressures. Lastly, the thermoelectric properties of Sr3ZBr3 (Z = As, Sb) were assessed through electrical and thermal conductivity, Seebeck coefficient, power factor (PF), and figure of merit (ZT) as a function of temperature. Both compounds exhibit high PF and near-unity ZT. These findings underscore their potential as strong candidates for optoelectronic and thermoelectric devices, owing to their direct bandgap and exceptional properties.

Jute (Corchorus sp.), a commercially important and eco-friendly crop, is widely cultivated in Bangladesh, India, and China. Some varieties of this tropical plant such as the Corchorus olitorius. Variety accession no. 2015 (acc. 2015) has been found to be low-temperature tolerant. The current study was designed to explore the genome-wide variations present in the tolerant plant acc. 2015 in comparison to the sensitive farmer popular variety Corchorus olitorius var. O9897 using the whole genome resequencing technique. Among different variations, intergenic Single Nucleotide Polymorphism (SNPs) and Insertion-Deletion (InDels) were found in the highest percentage whereas approximately 3% SNPs and 2% InDels were found in exonic regions in both plants. Gene enrichment analysis indicated the presence of acc. 2015 specific SNPs in the genes encoding peroxidase, ER lumen protein retaining receptor, and hexosyltransferase involved in stress response (GO:0006950) which were not present in sensitive variety O9897. Besides, distinctive copy number variation regions (CNVRs) comprising 120 gene loci were found in acc. 2015 with a gain of function from multiple copy numbers but absent in O9897. Gene ontology analysis revealed these gene loci to possess different receptors like kinases, helicases, phosphatases, transcription factors especially Myb transcription factors, regulatory proteins containing different binding domains, annexin, laccase, acyl carrier protein, potassium transporter, and vesicular transporter proteins that are responsible for low temperature induced adaptation pathways in plants. This work of identifying genomic variations linked to cold stress tolerance traits will help to develop successful markers that will pave the way to develop genetically modified cold-resistant jute lines for year-round cultivation to meet the demand for a sustainable fiber crop economy.

Sesame (Sesamum indicum L.) is widely used in many cooking techniques worldwide, and it is known as the ''queen of oilseeds'' because it contains polyunsaturated lipids that prevent oxidative rancidity and carry oil content up to 60%. The salty portions of the country have much lower agricultural yields, cropping intensities, and productivity than the rest of the country. In this paper, we compared the variations of yield performance and salinity torelance between modern and local sesame varieties to select the best-performing varieties under saline conditions in the southwestern coastal region of Bangladesh. The field experiment had been performed during the Kharif-1 season (mid-March to mid-July) of 2022 ​at the BINA (Bangladesh Institute of Nuclear Agriculture) substation farm, Satkhira. Four BINA varieties and two BARI (Bangladesh Agricultural Research Institute) varieties developed sesame varieties, and one local variety, viz. Binatil-1, Binatil-2, Binatil-3, Binatil-4, BARI Til-3, BARI Til-4 and Lal Til (Batiaghata local) were tested under saline conditions. A randomized complete block design was utilized, with three replications of each variety across the experimental field. The greatest plant height (92.00 ​cm) was found in BARI Til-3, whereas the lowest was observed in Binatil-3. BARI Til-4 had the highest number of branches per plant (4.55), whereas the lowest was found in Binatil-1. The highest number of capsules (22.22) was shown in Binatil-3, and the lowest was found in Binatil-1. The maximum number of seeds in capsule-1 (72.55) was demonstrated by Lal Til, and the minimum was observed in BARI Til-4. The Lal Til variety presented the highest seed yield (1.25 ​ha-1), whereas the Binatil-1 variety presented the lowest seed yield. These results indicate that the Lal Til variety performed better in yield. It may be cultivated in the Satkhira region under saline circumstances and used as breeding material for future breeding programs. These findings are highly important for the future of sesame cultivation in Bangladesh and other saline-prone areas.

Resistance to therapy remains a major cause of cancer treatment failures, resulting in many cancer-related deaths. Resistance can occur at any time during the treatment, even at the beginning. The current treatment plan is dependent mainly on cancer subtypes and the presence of genetic mutations. Evidently, the presence of a genetic mutation does not always predict the therapeutic response and can vary for different cancer subtypes. Therefore, there is an unmet need for predictive models to match a cancer patient with a specific drug or drug combination. Recent advancements in predictive models using artificial intelligence have shown great promise in preclinical settings. However, despite massive improvements in computational power, building clinically useable models remains challenging due to a lack of clinically meaningful pharmacogenomic data. In this review, we provide an overview of recent advancements in therapeutic response prediction using machine learning, which is the most widely used branch of artificial intelligence. We describe the basics of machine learning algorithms, illustrate their use, and highlight the current challenges in therapy response prediction for clinical practice.

Targeted genome editing is an advanced technique that enables precise modification of the nucleic acid sequences in a genome. Genome editing is typically performed using tools, such as molecular scissors, to cut a defined location in a specific gene. Genome editing has impacted various fields of biotechnology, such as agriculture; biopharmaceutical production; studies on the structure, regulation, and function of the genome; and the creation of transgenic organisms and cell lines. Although genome editing is used frequently, it has several limitations. Here, we provide an overview of well-studied genome-editing nucleases, including single-stranded oligodeoxynucleotides (ssODNs), transcription activator-like effector nucleases (TALENs), zinc-finger nucleases (ZFNs), and CRISPR-Cas9 RNA-guided nucleases (CRISPR-Cas9). To this end, we describe the progress toward editable nuclease-based therapies and discuss the minimization of off-target mutagenesis. Future prospects of this challenging scientific field are also discussed. Keywords: genome editing, nucleases, DSB, NHEJ, HDR, ZFNs, TALENs, CRISPR-Cas9, ssODNs, off-target mutagenesis

Resistance versus temperature characteristics of superconducting films have been studied for decades, and are still considered an important subject of condensed matter physics. They have recently received increased attention, primarily motivated by electromagnetic metamaterial strategy, which has been used in the implementation of one-dimensional microwave transmission lines with high-temperature superconducting films. In some of the recent works, it has been argued that the physical measurement of these curves is a strenuous and costly process, which becomes tedious when incessantly performed for a wide range of parameters. Contemplating on their significance, in this work, we propose a resistance–temperature curves approximation framework using three different artificial neural networks architectures, and carry out a detailed comparison between the variants in terms of the accuracy they achieve. We demonstrate that the mean-squared error, between the approximated and the physically measured curves, is negligible, which justifies extrapolation of these curves over a wide range of parameters using the proposed framework.

A highly sensitive dual-polarized 'X' oriented quadruple D-shaped open channel photonic crystal fiber (PCF) based surface plasmon resonance (SPR) sensor for various analyte detection is proposed in this paper. Gold is taken as a plasmonic material for its stability and compatibility. Silicon nitride (Si3N4) and titanium oxide (TiO2) has been used separately as an adhesive layer of gold to elevate the sustainability of the evanescent field. This paper shows a comparative study and inspects the effect of sensing performance between Si3N4 and TiO2 as an adhesive layer of gold. Numerical investigations have been followed up using the finite element method (FEM). For practical feasibility, analyte and plasmonic materials have been placed at the outer surface of the sensor. After watchful investigation, the maximum wavelength sensitivities of 21,000 nm/RIU (Refractive Index Unit) and 18,000 nm/RIU have been found for the y-polarization when using TiO2 and Si3N4, respectively. The highest amplitude sensitivities are of 914RIU−1 and 625RIU−1 for TiO2 and Si3N4, respectively. Furthermore, minimum wavelength resolutions of 4.76 × 10−6 RIU and 5.55 × 10−6 RIU have been observed in y-polarization for TiO2 and Si3N4, respectively. The sensor evinces a maximum figure of merit (FOM) of 236RIU−1 for TiO2. This sensor has the analyte sensing range of 1.31–1.38RI (Refractive Index) for TiO2 and 1.32–1.39RI for Si3N4. The sensor also delivers low confinement loss for Si3N4 and TiO2, which certifies viability in fabricating the design. Recognizing this sensor’s wavelength sensitivity, amplitude sensitivity, and sensing RI range, it could be a promising candidate for detecting different liquid analytes with excellent accuracy.

In this paper, an asymmetric photonic crystal fiber (PCF) working on surface plasmon resonance (SPR) has been proposed and demonstrated using the wavelength interrogation method and lower birefringence peak method. The proposed sensor contains a D-shaped analyte channel that can detect unknown analytes within the sensing range of 1.42–1.47 refractive index units (RIU) of the analytes. The structural asymmetry induces orthogonal x and y polarization modes. The numerical investigations with the finite element method (FEM) reveal that the sensor has a maximum wavelength sensitivity of 80,000 nm/RIU with a sensor resolution of 1.25 × 10−6 RIU for the y polarization mode and the maximum figure of merit (FOM) is found to be of 370.4 RIU−1. For the x polarization mode, the sensor exhibits a maximum wavelength sensitivity of 53,000 nm/RIU with a resolution of 1.89 × 10−6 RIU, having a maximum figure of merit (FOM) of 351 RIU−1. These results are found by using the wavelength interrogation method via confinement loss. On the other hand, the lower birefringence peak method-based analysis reveals a maximum wavelength sensitivity of 50,000 nm/RIU with a resolution of 2 × 10−6 RIU. As such, it is highly suitable for organic chemical detections and medical diagnostics. In addition, this paper studies the fabrication tolerance on the sensor performance.

In this paper, a proper concept of a kind of photonic crystal fiber known as D-shaped PCF sensor based on SPR or Surface Plasmon Resonance phenomenon has been discussed. The analysis has been performed numerically using FEM or Finite Element Method and PML (Perfectly Matched Layer) boundary conditions. Modal analysis has been performed keeping the smallest mesh as possible. The main mechanism of the sensor is the interaction between the core guided light beam and the metal layer surface that generates free electrons. The proposed sensor shows a refractive index detection range of 1.42–1.46 RIU, with a metal thickness variation of 35 nm-45 nm and a pitch variation of 1.8 μm–2.0 μm. The sensor obtained the highest sensitivity of 15000 nm/RIU with a maximum 6.67 × 10-6 RIU resolution, using the wavelength interrogation method. Average spectral sensitivity is 8000 nm/RIU. The amplitude interrogation method found a maximum sensitivity of 230 RIU−1 with a resolution of 4.348 × 10-5 RIU. The sensor also shows high linearity fitting and Figure of Merit (FoM). For ease of design, high detection range, high wavelength and amplitude sensitivity, less fabrication complexity, high linearity and stability, the sensor can be a great competitor of the PCF sensors previously proposed.

A highly sensitive Photonic Crystal Fiber (PCF) based Surface Plasmon Resonance (SPR) sensor is demonstrated in this paper in the optimized form of circular slotted lattice (CSL) structure. This proposed model performance is numerically scrutinized by using Finite Element Method (FEM) in presence of Perfectly Matched Layer (PML) and Scattering Boundary Condition. Plasmonic material ‘Gold’ which is chemically inert is used in this structure at the outer surface of the slotted area to mitigate fabrication challenge. This model indicates the highest wavelength sensitivity of 16000 nm/RIU using wavelength interrogation, the amplitude sensitivity of 780 RIU−1 by using amplitude interrogation method and the average spectral sensitivity of 6666 nm/RIU, respectively. Besides, this sensor has the potentiality of detecting analytes within Refractive Index (RI) range 1.4 to 1.46 with maximum wavelength resolution of 6.25 × 10−6 RIU and amplitude resolution of 1.28 × 10−6 RIU, respectively and the maximum figure of merits of 400 RIU−1. Moreover, the variation of structural parameters (such as pitch, plasmon layer thickness etc.) and the impact of these changes are also discussed in details. According to the high sensitivity performance, polynomial fit and high Figure of Merit (FOM), this amend structure can be a strong competitor in the field of biosensing.

Simple structure and high sensitivity with a broad detection range are highly desirable for temperature sensor. This work presents a highly sensitive plasmonic sensor based on D-shaped photonic crystal fiber (PCF) in the near infrared region (900–1900 nm) for temperature measurement. The proposed sensor is designed by finite element method (FEM) based simulation tool and sensing properties are investigated by means of wavelength interrogation method (WIM). To support the surface plasmon oscillation, 45 nm gold film is deposited on the flat portion of the D-shaped PCF which consists of pure silica. Benzene is used as the temperature sensitive material that offers large propagation loss (PL) peak shift. Simulation outcome shows that the maximum possible sensitivity of 110 nm/°C in the temperature range from 10 °C to 70 °C. To our knowledge, the achieved sensitivity is the highest for temperature sensing in the existing literature. In addition, the proposed sensor exhibits the maximum figure of merit (FOM) of 5.5/°C, resolution of 9.09 × 10−4 °C, and excellent fitting characteristics of PL peak wavelengths. Moreover, low PL of the proposed sensor helps to extend the sensor length up to few centimeters. Such excellent results and wider temperature range make sure that the proposed sensor can be an appropriate choice for temperature measurement even in the remote sensing application.