Validations of various in-hand object manipulation strategies employing a novel tactile sensor developed for an under-actuated robot hand.

Prisma Hand II is an under-actuated prosthetic hand developed at the University of Naples, Federico II to study in-hand manipulations during grasping activities. 3 motors equipped on the robotic hand drive 19 joints using elastic tendons. The operations of the hand are achieved by combining tactile hand sensing with under-actuation capabilities. The hand has the potential to be employed in both industrial and prosthetic applications due to its dexterous motion capabilities. However, currently there are no commercially available tactile sensors with compatible dimensions suitable for the prosthetic hand. Hence, in this work, we develop a novel tactile sensor designed based on an opto-electronic technology for the Prisma Hand II. The optimised dimensions of the proposed sensor made it possible to be integrated with the fingertips of the prosthetic hand. The output voltage obtained from the novel tactile sensor is used to determine optimum grasping forces and torques during in-hand manipulation tasks employing Neural Networks (NNs). The grasping force values obtained using a Convolutional Neural Network (CNN) and an Artificial Neural Network (ANN) are compared based on Mean Square Error (MSE) values to find out a better training network for the tasks. The tactile sensing capabilities of the proposed novel sensing method are presented and compared in simulation studies and experimental validations using various hand manipulation tasks. The developed tactile sensor is found to be showcasing a better performance compared to previous version of the sensor used in the hand.

Advances in CRISPR-Cas systems for fungal infections.

Fungi contain a wide range of bioactive secondary metabolites (SMs) that have numerous applications in various fields, including agriculture, medicine, human health, and more. It is common for genes responsible for the production of secondary metabolites (SMs) to form biosynthetic gene clusters (BGCs). The identification and analysis of numerous unexplored gene clusters (BGCs) and their corresponding substances (SMs) has been significantly facilitated by the recent advancements in genomic and genetic technologies. Nevertheless, the exploration of secondary metabolites with commercial value is impeded by a variety of challenges. The emergence of modern CRISPR/Cas technologies has brought about a paradigm shift in fungal genetic engineering, significantly streamlining the process of discovering new bioactive compounds. This study begins with an examination of fungal biosynthetic gene clusters (BGCs) and their interconnections with the secondary metabolites (SMs) they generate. Following that, a brief summary of the conventional methods employed in fungal genetic engineering is provided. This study explores various sophisticated CRISPR/Cas-based methodologies and their utilization in examining the synthesis of secondary metabolites (SMs) in fungi. The chapter provides an in-depth analysis of the limitations and obstacles encountered in CRISPR/Cas-based systems when applied to fungal genetic engineering. It also proposes promising avenues for future research to optimize the efficiency of these systems.

Cascaded Thinning in Upscale and Downscale Representation for EEG Signal Processing.

Smoothing filters are widely used in EEG signal processing for noise removal while preserving signals' features. Inspired by our recent work on Upscale and Downscale Representation (UDR), this paper proposes a cascade arrangement of some effective image-processing techniques for signal filtering in the image domain. The UDR concept is to visualize EEG signals at an appropriate line width and convert it to a binary image. The smoothing process is then conducted by skeletonizing the signal object to a unit width and projecting it back to the time domain. Two successive UDRs could result in a better-smoothing performance, but their binary image conversion should be restricted. The process is computationally ineffective, especially at higher line width values. Cascaded Thinning UDR (CTUDR) is proposed, exploiting morphological operations to perform a two-stage upscale and downscale within one binary image representation. CTUDR is verified on a signal smoothing and classification task and compared with conventional techniques, such as the Moving Average, the Binomial, the Median, and the Savitzky Golay filters. Simulated EEG data with added white Gaussian noise is employed in the former, while cognitive conflict data obtained from a 3D object selection task is utilized in the latter. CTUDR outperforms its counterparts, scoring the best fitting error and correlation coefficient in signal smoothing while achieving the highest gain in Accuracy (0.7640%) and F-measure (0.7607%) when used as a smoothing filter for training data of EEGNet.

Serum Uric Acid Levels as a Risk Stratification Tool in Hypertensive Disorders of Pregnancy: A Retrospective Study.

BACKGROUND: Worldwide, hypertensive disorders of pregnancy (HDP) are among the leading causes of maternal and fetal morbidity and mortality. Serum uric acid is a test that can evaluate the severity of HDP and the associated maternal and fetal morbidity and mortality. AIM: To examine the relationship between maternal serum uric acid levels and the severity of HDP and overall pregnancy outcomes. MATERIAL AND METHODS: A retrospective study was conducted on women with a gestational age > 20 weeks and BP >140/90 mmHg over three years. A total of 134 patients were included in the study. Patients with chronic hypertension, hyperuricemia without hypertension, and other major illnesses were excluded. Data were collected from medical records, including age, gravida, parity, weight, height, gestational age, blood pressure at admission, urine albumin, and serum uric acid levels. RESULTS: Of the 134 enrolled women with HDP, 76 had gestational hypertension, 41 had preeclampsia, and 17 had eclampsia. Mean uric acid levels in mg/dL were 6.06±1.651, 6.20±0.824, and 7.38±1.26 in gestational hypertension, preeclampsia, and eclampsia, respectively, which was a significant association (p=0.002). Mean uric acid in mg/dL was 5.86±1.27 in intensive care unit (ICU) patients compared to 6.45±1.39 in ward patients (p=0.015). There was a significantly increased risk of ICU admission and preterm delivery (r=-0.401, p<0.001) in patients with elevated uric acid levels. There was a significantly increased risk of low-birth-weight babies with elevated uric acid levels (r=-0.278, p=0.001). However, there was no statistically significant increased risk of newborn intensive care unit admissions (p=0.264) with elevated uric acid levels. CONCLUSION: Serum uric acid levels vary significantly in HDP and were found to be elevated in severe preeclampsia and eclampsia. It can be considered for risk stratification in HDP based on disease severity; however, its role in determining outcomes is debatable. Using serum uric acid levels in predictive models along with known biomarkers may determine its possible additional value in disease prediction and severity.

Encoding temporal information in deep convolution neural network.

A recent development in deep learning techniques has attracted attention to the decoding and classification of electroencephalogram (EEG) signals. Despite several efforts to utilize different features in EEG signals, a significant research challenge is using time-dependent features in combination with local and global features. Several attempts have been made to remodel the deep learning convolution neural networks (CNNs) to capture time-dependency information. These features are usually either handcrafted features, such as power ratios, or splitting data into smaller-sized windows related to specific properties, such as a peak at 300 ms. However, these approaches partially solve the problem but simultaneously hinder CNNs' capability to learn from unknown information that might be present in the data. Other approaches, like recurrent neural networks, are very suitable for learning time-dependent information from EEG signals in the presence of unrelated sequential data. To solve this, we have proposed an encoding kernel (EnK), a novel time-encoding approach, which uniquely introduces time decomposition information during the vertical convolution operation in CNNs. The encoded information lets CNNs learn time-dependent features in addition to local and global features. We performed extensive experiments on several EEG data sets-physical human-robot collaborations, P300 visual-evoked potentials, motor imagery, movement-related cortical potentials, and the Dataset for Emotion Analysis Using Physiological Signals. The EnK outperforms the state of the art with an up to 6.5% reduction in mean squared error (MSE) and a 9.5% improvement in F1-scores compared to the average for all data sets together compared to base models. These results support our approach and show a high potential to improve the performance of physiological and non-physiological data. Moreover, the EnK can be applied to virtually any deep learning architecture with minimal effort.

Association of Different Anticoagulation Strategies With Outcomes in Patients Hospitalized With Acute Pulmonary Embolism.

Background Therapeutic anticoagulation is the cornerstone of treatment for pulmonary embolism (PE), but the impact of different anticoagulation strategies on patient outcomes remains unclear. In this study, we assessed the association of different anticoagulation strategies with the outcomes of patients with acute PE. Methods A retrospective chart review of 207 patients with acute PE who were admitted to one of three urban teaching hospitals in the Mount Sinai Health System (in New York City) from January 2020 to September 2022 was performed. Demographic, clinical, and radiographic data were recorded for all patients. Multivariate regression analyses were performed to assess the association of different outcomes with the approach of therapeutic anticoagulation used. Results The median age of the included patients was 65 years, and 50.2% were women. The most common approach (n = 153, 73.9%) to therapeutic anticoagulation was initial treatment with unfractionated or low molecular weight heparin followed by a direct-acting oral anticoagulant (DOAC), while heparin alone (either unfractionated or low molecular weight heparin) was used in 37 (17.9%) patients, and another 17 (8.2%) patients were treated with heparin followed by bridging to warfarin. Hospital length of stay was longer for patients in the "heparin to warfarin" group (risk-adjusted incidence rate ratio of 2.52). The rates of in-hospital bleeding, all-cause 30-day mortality, and all-cause 30-day re-admissions did not have any significant association with the therapeutic anticoagulation approach used. Conclusion Patients with acute PE who were initially treated with heparin and subsequently bridged to warfarin had a longer hospital stay. Rates of in-hospital bleeding, 30-day mortality, and 30-day re-admission were not associated with the strategy of therapeutic anticoagulation employed.

Social Distancing During the COVID-19 Pandemic and Neonatal Mortality in the US.

Importance: Neonatal mortality is a major public health concern that was potentially impacted by the COVID-19 pandemic. To prepare for future health crises, it is important to investigate whether COVID-19 pandemic-related interventions were associated with changes in neonatal mortality. Objective: To investigate whether social distancing during the pandemic was associated with a higher neonatal mortality rate. Design, Setting, and Participants: This cohort study examined maternal-linked birth and infant death records from the National Center for Health Statistics, a population-level US database, from 2016 through 2020. The mortality rates were correlated using machine learning-based autoregressive integrated moving average (ARIMA) models with the social distancing index (SDI). The reference period was January 2016 through February 2020, and the pandemic period was March through December 2020. Statistical analysis was performed from March 2023 to May 2024. Exposures: SDI, computed from 6 mobility metrics. Main Outcomes and Measures: The primary outcome was neonatal mortality rate, defined as death at age less than 28 days. Results: The study included 18 011 173 births, of which 15 136 596 were from the reference period (7 753 555 [51.22%] male; 11 643 094 [76.92%] with maternal age of 20 to 34 years) and 2 874 577 were from the pandemic period (1 472 539 [51.23%] male; 2 190 158 [76.19%] with maternal age of 20 to 34 years). Through ARIMA-adjusted analyses, accounting for the declining mortality trend in the reference period, the mortality rates during the pandemic period did not significantly differ from the expected rates. SDI did not exhibit significant correlations with neonatal mortality (unadjusted: correlation coefficient [CC], 0.14 [95% CI, -0.53 to 0.70]; ARIMA adjusted: CC, 0.29 [95% CI, -0.41 to 0.77]), early neonatal mortality (unadjusted: CC, 0.33 [95% CI, -0.37 to 0.79]; ARIMA adjusted: CC, 0.45 [95% CI, -0.24 to 0.84]), and infant mortality (unadjusted: CC, -0.09 [95% CI, -0.68 to 0.57]; ARIMA adjusted: CC, 0.35 [95% CI, -0.35 to 0.80]). However, lag analyses found that SDI was associated with higher neonatal and early neonatal mortality rates with a 2-month lag period, but not with infant mortality rate. SDI was also associated with increases in 22-to-27 weeks' and 28-to-32 weeks' preterm delivery with a 1-month lag period. Conclusions and Relevance: In this population-level study of National Center for Health Statistics databases, neonatal, early neonatal, and infant mortality rates did not increase during the initial COVID-19 pandemic period. However, associations were observed between the pandemic period social distancing measures and higher rates of neonatal and early neonatal mortality, as well as preterm birth rate with a lag period, suggesting the importance of monitoring infant health outcomes following pandemic-related population behavior changes.

Cytological diagnosis of lymphoepithelial carcinoma: Simple yet confusing.

Lymphoepithelial carcinoma (LEC) of salivary glands are rare tumours and present as gradually progressing painless masses. LECs have good prognosis and accurate differentiation from secondary tumours and nasopharyngeal carcinoma is essential to dictate management. We present a case of an elderly male presenting with a parotid swelling diagnosed as LEC on fine needle aspiration cytology and confirmed on histopathology and immunohistochemistry.

Achieved oxygen saturations and risk for bronchopulmonary dysplasia with pulmonary hypertension in preterm infants.

OBJECTIVE: Characterisation of oxygen saturation (SpO2)-related predictors that correspond with both bronchopulmonary dysplasia-associated pulmonary hypertension (BPD-PH) development and survival status in infants with BPD-PH may improve patient outcomes. This investigation assessed whether (1) infants with BPD-PH compared with infants with BPD alone, and (2) BPD-PH non-survivors compared with BPD-PH survivors would (a) achieve lower SpO2 distributions, (b) have a higher fraction of inspired oxygen (FiO2) exposure and (c) have a higher oxygen saturation index (OSI). DESIGN: Case-control study between infants with BPD-PH (cases) and BPD alone (controls) and by survival status within cases. SETTING: Single-centre study in the USA. PATIENTS: Infants born at <29 weeks' gestation and on respiratory support at 36 weeks' postmenstrual age. EXPOSURES: FiO2 exposure, SpO2 distributions and OSI were analysed over the week preceding BPD-PH diagnosis. MAIN OUTCOMES AND MEASURES: BPD-PH, BPD alone and survival status in infants with BPD-PH. RESULTS: 40 infants with BPD-PH were compared with 40 infants with BPD alone. Infants who developed BPD-PH achieved lower SpO2 compared with infants with BPD (p<0.001), were exposed to a higher FiO2 (0.50 vs 0.34; p=0.02) and had a higher OSI (4.3 vs 2.6; p=0.03). Compared with survivors, infants with BPD-PH who died achieved a lower SpO2 (p<0.001) and were exposed to a higher FiO2 (0.70 vs 0.42; p=0.049). CONCLUSIONS: SpO2-related predictors differed between infants with BPD-PH and BPD alone and among infants with BPD-PH by survival status. The OSI may provide a non-invasive predictor for BPD-PH in preterm infants.

Association of race, ethnicity and insurance status with outcomes for patients with acute pulmonary embolism treated by PERT: a retrospective observational study.

BACKGROUND: Management of PE has become streamlined with the implementation of PE Response Teams (PERT). Race, ethnicity and insurance status are known to influence the outcomes of patients with acute PE. However, whether the implementation of PERT-based care mitigates these racial and ethnic disparities remains unknown. Our aim was to assess the association of race, ethnicity and insurance with outcomes for patients with acute PE managed by PERT. METHODS: We performed a retrospective chart review of 290 patients with acute PE, who were admitted to one of three urban teaching hospitals in the Mount Sinai Health System (New York, NY) from January 2021 to October 2023. A propensity score-weighted analysis was performed to explore the association of race, ethnicity and insurance status with overall outcomes. RESULTS: Median age of included patients was 65.5 years and 149 (51.4%) were female. White, Black and Asian patients constituted 56.2% (163), 39.6% (115) and 3.5% [10] of the cohort respectively. Patients of Hispanic or Latino ethnicity accounted for 8.3% [24] of the sample. The 30-day rates of mortality, major bleeding and 30-day re-admission were 10.3%, 2.1% and 12.8% respectively. Black patients had higher odds of major bleeding (odds ratio [OR]: 1.445; p < 0.0001) when compared to White patients. Patients of Hispanic or Latino ethnicity had lower odds of receiving catheter-directed thrombolysis (OR: 0.966; p = 0.0003) and catheter-directed or surgical embolectomy (OR: 0.906; p < 0.0001) when compared to non-Hispanic/Latino patients. Uninsured patients had higher odds of receiving systemic thrombolysis (OR: 1.034; p = 0.0008) and catheter-directed thrombolysis (OR: 1.059; p < 0.0001), and lower odds of receiving catheter-directed or surgical embolectomy (OR: 0.956; p = 0.015) when compared to insured patients, although the odds of 30-day mortality and 30-day major bleeding were not significantly different. CONCLUSION: Within a cohort of PE patients managed by PERT, there were significant associations between race, ethnicity and overall outcomes. Hispanic or Latino ethnicity and uninsured status were associated with lower odds of receiving catheter-directed or surgical embolectomy. These results suggest that disparities related to ethnicity and insurance status persist despite PERT-based care of patients with acute PE.

Manufacturing and preclinical toxicity of GLP grade gene deleted attenuated Leishmania donovani parasite vaccine.

Centrin1 gene deleted Leishmania donovani parasite (LdCen1-/-) was developed and extensively tested experimentally as an intracellular stage-specific attenuated and immunoprotective live parasite vaccine candidate ex vivo using human PBMCs and in vivo in animals. Here we report manufacturing and pre-clinical evaluation of current Good-Laboratory Practice (cGLP) grade LdCen1-/- parasites, as a prerequisite before proceeding with clinical trials. We screened three batches of LdCen1-/- parasites manufactured in bioreactors under cGLP conditions, for their consistency in genetic stability, attenuation, and safety. One such batch was preclinically tested using human PBMCs and animals (hamsters and dogs) for its safety and protective immunogenicity. The immunogenicity of the CGLP grade LdCen1-/- parasites was similar to one grown under laboratory conditions. The cGLP grade LdCen1-/- parasites were found to be safe and non-toxic in hamsters and dogs even at 3 times the anticipated vaccine dose. When PBMCs from healed visceral leishmaniasis (VL) cases were infected with cGLP LdCen1-/-, there was a significant increase in the stimulation of cytokines that contribute to protective responses against VL. This effect, measured by multiplex ELISA, was greater than that observed in PBMCs from healthy individuals. These results suggest that cGLP grade LdCen1-/- manufactured under cGMP complaint conditions can be suitable for future clinical trials.

Hybrid architectures for terahertz molecular polaritonics.

Atoms and their different arrangements into molecules are nature's building blocks. In a regime of strong coupling, matter hybridizes with light to modify physical and chemical properties, hence creating new building blocks that can be used for avant-garde technologies. However, this regime relies on the strong confinement of the optical field, which is technically challenging to achieve, especially at terahertz frequencies in the far-infrared region. Here we demonstrate several schemes of electromagnetic field confinement aimed at facilitating the collective coupling of a localized terahertz photonic mode to molecular vibrations. We observe an enhanced vacuum Rabi splitting of 200 GHz from a hybrid cavity architecture consisting of a plasmonic metasurface, coupled to glucose, and interfaced with a planar mirror. This enhanced light-matter interaction is found to emerge from the modified intracavity field of the cavity, leading to an enhanced zero-point electric field amplitude. Our study provides key insight into the design of polaritonic platforms with organic molecules to harvest the unique properties of hybrid light-matter states.

A high efficiency precision genome editing method with CRISPR in iPSCs.

The use of genetic engineering to generate point mutations in induced pluripotent stem cells (iPSCs) is essential for studying a specific genetic effect in an isogenic background. We demonstrate that a combination of p53 inhibition and pro-survival small molecules achieves a homologous recombination rate higher than 90% using Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) in human iPSCs. Our protocol reduces the effort and time required to create isogenic lines.

A translation proofreader of archaeal origin imparts multi-aldehyde stress tolerance to land plants.

Aldehydes, being an integral part of carbon metabolism, energy generation, and signalling pathways, are ingrained in plant physiology. Land plants have developed intricate metabolic pathways which involve production of reactive aldehydes and its detoxification to survive harsh terrestrial environments. Here, we show that physiologically produced aldehydes, i.e., formaldehyde and methylglyoxal in addition to acetaldehyde, generate adducts with aminoacyl-tRNAs, a substrate for protein synthesis. Plants are unique in possessing two distinct chiral proofreading systems, D-aminoacyl-tRNA deacylase1 (DTD1) and DTD2, of bacterial and archaeal origins, respectively. Extensive biochemical analysis revealed that only archaeal DTD2 can remove the stable D-aminoacyl adducts on tRNA thereby shielding archaea and plants from these system-generated aldehydes. Using Arabidopsis as a model system, we have shown that the loss of DTD2 gene renders plants susceptible to these toxic aldehydes as they generate stable alkyl modification on D-aminoacyl-tRNAs, which are recycled only by DTD2. Bioinformatic analysis identifies the expansion of aldehyde metabolising repertoire in land plant ancestors which strongly correlates with the recruitment of archaeal DTD2. Finally, we demonstrate that the overexpression of DTD2 offers better protection against aldehydes than in wild type Arabidopsis highlighting its role as a multi-aldehyde detoxifier that can be explored as a transgenic crop development strategy.

Prediction of cognitive conflict during unexpected robot behavior under different mental workload conditions in a physical human-robot collaboration.

Objective. Brain-computer interface (BCI) technology is poised to play a prominent role in modern work environments, especially a collaborative environment where humans and machines work in close proximity, often with physical contact. In a physical human robot collaboration (pHRC), the robot performs complex motion sequences. Any unexpected robot behavior or faulty interaction might raise safety concerns. Error-related potentials, naturally generated by the brain when a human partner perceives an error, have been extensively employed in BCI as implicit human feedback to adapt robot behavior to facilitate a safe and intuitive interaction. However, the integration of BCI technology with error-related potential for robot control demands failure-free integration of highly uncertain electroencephalography (EEG) signals, particularly influenced by the physical and cognitive state of the user. As a higher workload on the user compromises their access to cognitive resources needed for error awareness, it is crucial to study how mental workload variations impact the error awareness as it might raise safety concerns in pHRC. In this study, we aim to study how cognitive workload affects the error awareness of a human user engaged in a pHRC.Approach. We designed a blasting task with an abrasive industrial robot and manipulated the mental workload with a secondary arithmetic task of varying difficulty. EEG data, perceived workload, task and physical performance were recorded from 24 participants moving the robot arm. The error condition was achieved by the unexpected stopping of the robot in 33% of trials.Main results. We observed a diminished amplitude for the prediction error negativity (PEN) and error positivity (Pe), indicating reduced error awareness with increasing mental workload. We further observed an increased frontal theta power and increasing trend in the central alpha and central beta power after the unexpected robot stopping compared to when the robot stopped correctly at the target. We also demonstrate that a popular convolution neural network model, EEGNet, could predict the amplitudes of PEN and Pe from the EEG data prior to the error.Significance. This prediction model could be instrumental in developing an online prediction model that could forewarn the system and operators of the diminished error awareness of the user, alluding to a potential safety breach in error-related potential-based BCI system for pHRC. Therefore, our work paves the way for embracing BCI technology in pHRC to optimally adapt the robot behavior for personalized user experience using real-time brain activity, enriching the quality of the interaction.

Nano-modified screen-printed electrode-based electrochemical immunosensors for oral cancer biomarker detection in undiluted human serum and saliva samples.

This proposed work reports the development of in-house made conductive ink-based screen-printed electrodes (SPEs) for label-free detection of oral cancer biomarkers. Carbon ink synthesis includes graphite powder, gum arabic, and water. The selectivity test of the fabricated SPE involves immobilizing antibodies specific to biomarkers and challenges with redox-active interference, other serum molecules, and non-target biomarkers. Three different biomarkers, cytokeratin-19 fragment (CYFRA 21-1), interleukin 8 (IL-8), and tumor protein p53 (TP-53), act as target entities for the detection of oral cancer in patients' samples (serum, N = 28, and saliva, N = 16) at an early stage. The standard technique enzyme-linked immunosorbent assay (ELISA) was employed to estimate the concentration of the biomarkers in serum and saliva samples. SPEs contain amine (-NH2) functional groups involved in covalent bonding with the carboxyl (-COOH) groups of antibody molecules. These immunosensors exhibited remarkably lower detection limits of 829.5 pg mL-1, 0.543 pg mL-1, and 1.165 pg mL-1, and excellent sensitivity of 0.935 µA mL pg-1 cm-1, 0.039 µA mL pg-1 cm-1, and 0.008 µA mL pg-1 cm-1 for CYFRA 21-1, IL-8, and TP-53 biomarkers, respectively. This sensing platform does not require any functionalization for biomolecule immobilization. Thus, it is a cost-effective, disposable, flexible, miniaturized, and sensitive strip to detect oral cancer biomarkers.

Optimizing light regimes for neutral lipid accumulation in Dunaliella salina MCC 43: a study on physiological status and carbon allocation.

Dunaliella salina is a favourable source of high lipid feedstock for biofuel and medicinal chemicals. Low biomass output from microalgae is a significant barrier to industrial-scale commercialisation. The current study aimed to determine how photosynthetic efficiency, carbon fixation, macromolecular synthesis, accumulation of neutral lipids, and antioxidative defence (ROS scavenging enzyme activities) of D. salina cells were affected by different light intensities (LI) (50, 100, 200, and 400 µmol m-2 s-1). The cells when exposed to strong light (400 µmol m-2 s-1) led to reduction in chlorophyll a but the carotenoid content increased by 19% in comparison to the control (LI 100). The amount of carbohydrate changed significantly under high light and in spite of stress inflicted on the cells by high irradiation, a considerable increase in activity of carbonic anhydrase and fixation rate of CO2 were recorded, thus, preserving the biomass content. The high light exposed biomass when subjected to nitrogen-deficient medium led to increase in lipid content (59.92% of the dry cell weight). However, neutral lipid made up 78.26% of the total lipid while other lipids like phospholipid and glycolipid content decreased, showing that the lipid was redistributed in these cells under nitrogen deprivation, making the organism more appropriate for biodiesel/jet fuel use. Although D. salina cells had a relatively longer generation time (3.5 d) than other microalgal cells, an economic analysis concluded that the amount of carotenoid they produced and the quality of their lipids made them more suited for commercialization.

Investigation of Luliconazole-Loaded Mucoadhesive Electrospun Nanofibers for Anticandidal Activity in the Management of Vaginal Candidiasis.

In this study, we fabricated and evaluated luliconazole-loaded electrospun nanofibers for anticandidal activity in the management of vaginal candidiasis. Polycaprolactone (PCL)/gelatin nanofibers were designed by the electrospinning technique, and the Box-Behnken design (BBD) was adopted for optimization to get tailored fibers. The luliconazole (LCZ) drug was mixed into different concentrations (2.5, 5, 7.5, and 10%) of tea tree oil (TT oil) and loaded into the PCL/gelatin nanofibrous mats. The effective anticandidal potential of nanofiber samples were analyzed by the disk-diffusion method. Scanning electron microscopy (SEM), Fourier transform infrared (FTIR), differential scanning calorimetry (DSC), XRD analysis, and in silico study were performed. The entrapment efficiency, swelling degree, mechanical strength, contact angle, mucoadhesion, drug release, and permeation study were assessed. The average diameter of the PCL/gelatin-optimized nanofiber was 153 nm. SEM reflected that the fabricated nanofibers were uniform and bead-free. FTIR and DSC analyzed the interaction and physical entrapment of the drug in the polymeric fibers. The entrapment efficiency of the drug-loaded nanofiber was found to be 89.2 ± 0.8%. Maximum swelling percentages at 4 h were 40.8, 18.9, and 14.0% and contact angles were 46.5°, 62.95°, and 65.78° for the blank, TT oil-loaded, and drug-loaded nanofiber, respectively, which indicated the hydrophilic nature of the fibers. The drug-loaded nanofiber had a high tensile strength with satisfactory mucoadhesive property that led to its adhesion to the vaginal mucosa with no tear. The drug-loaded nanofiber had a cumulative drug release of 67.7 ± 3.4% in 48 h, and the 12.8 ± 0.53 mm of zone of inhibition (ZOI) in 48 h illustrated an effective anticandidal activity. The TT oil-loaded nanofiber also exhibited a small ZOI of 4.3 ± 0.30 mm, indicating a synergistic effect to the antifungal activity of the drug-loaded nanofiber. LCZ-loaded nanofibers can emerge as a novel approach for vaginal drug delivery in the treatment of candida infection. Thus, this pharmaceutical investigation can help in formulating preclinical and clinical models.

An investigation into the effectiveness of using acoustic touch to assist people who are blind.

Wearable smart glasses are an emerging technology gaining popularity in the assistive technologies industry. Smart glasses aids typically leverage computer vision and other sensory information to translate the wearer's surrounding into computer-synthesized speech. In this work, we explored the potential of a new technique known as "acoustic touch" to provide a wearable spatial audio solution for assisting people who are blind in finding objects. In contrast to traditional systems, this technique uses smart glasses to sonify objects into distinct sound auditory icons when the object enters the device's field of view. We developed a wearable Foveated Audio Device to study the efficacy and usability of using acoustic touch to search, memorize, and reach items. Our evaluation study involved 14 participants, 7 blind or low-visioned and 7 blindfolded sighted (as a control group) participants. We compared the wearable device to two idealized conditions, a verbal clock face description and a sequential audio presentation through external speakers. We found that the wearable device can effectively aid the recognition and reaching of an object. We also observed that the device does not significantly increase the user's cognitive workload. These promising results suggest that acoustic touch can provide a wearable and effective method of sensory augmentation.