Scalable optical nose realized with a chemiresistively modulated light-emitter array.

Biological olfaction relies on a large number of receptors that function as sensors to detect gaseous molecules. It has been challenging to realize artificial olfactory systems that contain similarly large numbers of sensory materials. We show that combinatorial materials processing with vapor deposition can be used to fabricate large arrays of distinct chemiresistive sensing materials. By combining these with light-emitting diodes, we obtain an array of chemiresistively-modulated light-emitting diodes, or ChemLEDs, that permit a simultaneous optical read-out in response to an analyte. The optical nose uses a common voltage source and ground for all sensing elements and thus eliminates the need for complex wiring of individual sensors. Our optical nose contains one hundred ChemLEDs and generates unique light patterns in response to gases and their mixtures. Optical pattern recognition methods enable the quantitative prediction of the corresponding concentrations and compositions, thereby paving the way for massively parallel artificial olfactory systems. ChemLEDs open the possibility to explore demanding gas sensing applications, including in environmental, food quality monitoring, and potentially diagnostic settings. This article is protected by copyright. All rights reserved.

Current Status and Future Directions: The Application of Artificial Intelligence/Machine Learning for Precision Medicine.

Technological innovations, such as artificial intelligence (AI) and machine learning (ML), have the potential to expedite the goal of precision medicine, especially when combined with increased capacity for voluminous data from multiple sources and expanded therapeutic modalities; however, they also present several challenges. In this communication, we first discuss the goals of precision medicine, and contextualize the use of AI in precision medicine by showcasing innovative applications (e.g., prediction of tumor growth and overall survival, biomarker identification using biomedical images, and identification of patient population for clinical practice) which were presented during the February 2023 virtual public workshop entitled "Application of Artificial Intelligence and Machine Learning for Precision Medicine," hosted by the US Food and Drug Administration (FDA) and University of Maryland Center of Excellence in Regulatory Science and Innovation (M-CERSI). Next, we put forward challenges brought about by the multidisciplinary nature of AI, particularly highlighting the need for AI to be trustworthy. To address such challenges, we subsequently note practical approaches, viz., differential privacy, synthetic data generation, and federated learning. The proposed strategies - some of which are highlighted presentations from the workshop - are for the protection of personal information and intellectual property. In addition, methods such as the risk-based management approach and the need for an agile regulatory ecosystem are discussed. Finally, we lay out a call for action that includes sharing of data and algorithms, development of regulatory guidance documents, and pooling of expertise from a broad-spectrum of stakeholders to enhance the application of AI in precision medicine.

An AI Approach to Generating MIDD Assets Across the Drug Development Continuum.

Model-informed drug development involves developing and applying exposure-based, biological, and statistical models derived from preclinical and clinical data sources to inform drug development and decision-making. Discrete models are generated from individual experiments resulting in a single model expression that is utilized to inform a single stage-gate decision. Other model types provide a more holistic view of disease biology and potentially disease progression depending on the appropriateness of the underlying data sources for that purpose. Despite this awareness, most data integration and model development approaches are still reliant on internal (within company) data stores and traditional structural model types. An AI/ML-based MIDD approach relies on more diverse data and is informed by past successes and failures including data outside a host company (external data sources) that may enhance predictive value and enhance data generated by the sponsor to reflect more informed and timely experimentation. The AI/ML methodology also provides a complementary approach to more traditional modeling efforts that support MIDD and thus yields greater fidelity in decision-making. Early pilot studies support this assessment but will require broader adoption and regulatory support for more evidence and refinement of this paradigm. An AI/ML-based approach to MIDD has the potential to transform regulatory science and the current drug development paradigm, optimize information value, and increase candidate and eventually product confidence with respect to safety and efficacy. We highlight early experiences with this approach using the AI compute platforms as representative examples of how MIDD can be facilitated with an AI/ML approach.

An exploratory machine learning approach to identify placebo responders in pharmacological binge eating disorder trials.

Randomized, placebo-controlled trials for binge eating disorder (BED) have revealed highly variable, and often marked, rates of short-term placebo response. Several quantitative based analyses in patients with BED have inconsistently demonstrated which patient factors attribute to an increase in placebo response. The objective of this study is to utilize machine learning (ML) algorithms to identify moderators of placebo response in patients with BED. Data were pooled from 12 randomized placebo-controlled trials evaluating different treatment options for BED. The final dataset consisted of 189 adults receiving placebo with complete information of baseline variables. Placebo responders were defined as patients experiencing ≥75% reduction in binge eating frequency (BEF) at study end point. Nine patient prerandomization variables were included as predictors. Patients were divided into training and testing subsets according to an 75%:25% distribution while preserving the proportion of placebo responders. All analysis was performed in the software Pumas 2.0. Gaussian Naïve Bayes algorithm showed the best cross-validation accuracy (~64%) and was chosen as the final algorithm. Shapley analysis suggested that patients with low baseline BEF and anxiety status were strong moderators of placebo response. Upon applying the final algorithm on the test dataset, the resulting sensitivity was 88% and prediction accuracy was 72%. This is the first application of ML to identify moderators of placebo response in BED. The results of this analysis confirm previous findings of lesser baseline disease severity and adds that patients with no anxiety are more susceptible to placebo response.

Amplification of Acoustic Forces Using Microbubble Arrays Enables Manipulation of Centimeter-Scale Objects.

Manipulation of macroscale objects by sound is fundamentally limited by the wavelength and object size. Resonant subwavelength scatterers such as bubbles can decouple these requirements, but typically the forces are weak. Here we show that patterning bubbles into arrays leads to geometric amplification of the scattering forces, enabling the precise assembly and manipulation of cm-scale objects. We rotate a 1 cm object continuously or position it with 15 µm accuracy, using sound with a 50 cm wavelength. The results are described well by a theoretical model. Our results lay the foundation for using secondary Bjerknes forces in the controlled organization and manipulation of macroscale structures.

Population Pharmacokinetics of Vancomycin in Pregnant Women.

Objective: Vancomycin is a glycopeptide antibacterial indicated for serious gram-positive infections. Pharmacokinetics (PK) of vancomycin have not been described in pregnant women. This study aims to characterize the PK disposition of vancomycin in pregnant women based on data acquired from a database of routine hospital care for therapeutic drug monitoring to better inform dosing decisions. Methods: In this study, plasma drug concentration data from 34 pregnant hospitalized women who were administered intravenous vancomycin was analyzed. A population pharmacokinetic (PPK) model was developed using non-linear mixed effects modeling. Model selection was based on statistical criterion, graphical analysis, and physiologic relevance. Using the final model AUC0-24 (PK efficacy index of vancomycin) was compared with non-pregnant population. Results: Vancomycin PK in pregnant women were best described by a two-compartment model with first-order elimination and the following parameters: clearance (inter individual variability) of 7.64 L/hr (32%), central volume of 67.35 L, inter-compartmental clearance of 9.06 L/h, and peripheral volume of 37.5 L in a typical patient with 175 ml/min creatinine clearance (CRCL) and 45 kg fat-free mass (FFM). The calculated geometric mean of AUC0-24 for the pregnant population was 223 ug.h/ ml and 226 ug.h/ ml for the non-pregnant population. Conclusion: Our analysis suggests that vancomycin PK in pregnant women is consistent with non-pregnant adults and the dosing regimens used for non-pregnant patients may also be applicable to pregnant patients.

Ultrasound-Responsive Systems as Components for Smart Materials.

Smart materials can respond to stimuli and adapt their responses based on external cues from their environments. Such behavior requires a way to transport energy efficiently and then convert it for use in applications such as actuation, sensing, or signaling. Ultrasound can carry energy safely and with low losses through complex and opaque media. It can be localized to small regions of space and couple to systems over a wide range of time scales. However, the same characteristics that allow ultrasound to propagate efficiently through materials make it difficult to convert acoustic energy into other useful forms. Recent work across diverse fields has begun to address this challenge, demonstrating ultrasonic effects that provide control over physical and chemical systems with surprisingly high specificity. Here, we review recent progress in ultrasound-matter interactions, focusing on effects that can be incorporated as components in smart materials. These techniques build on fundamental phenomena such as cavitation, microstreaming, scattering, and acoustic radiation forces to enable capabilities such as actuation, sensing, payload delivery, and the initiation of chemical or biological processes. The diversity of emerging techniques holds great promise for a wide range of smart capabilities supported by ultrasound and poses interesting questions for further investigations.

Analysis of energy storage materials for developments in solar cookers.

Solar energy is accessible freely and can be utilized for many household and industrial applications. The consumption of solar energy for cooking applications has found significant success. Various innovations have been employed in facilitating cooking during off-sunshine hours. Thermal energy storage helps in overcoming the fluctuations in the supply of energy required for cooking during different time periods of the day. This study focuses on the different types of thermal energy storage mediums that are currently utilized in solar cooking. Primarily, oils and pebbles are most commonly used as sensible heat storage (SHS) while organic phase change materials (PCMs) are used as latent heat thermal energy storage materials (LHTES). The properties and performances of various SHS and latent heat storage (LHS) mediums have been compared for their suitable utilization. SHS materials are cost-effective but have lower thermal gradient compared to LHTES materials. The energy storage capability of LHTES is high while degradation with the increasing number of charging and discharging cycles is also considerable. The melting point should be close to the utilization temperature for being used as LHTES as thermal diffusivity of the materials greatly influences the performance of solar cookers. The cooking time is lower for solar cooking systems equipped with energy storage compared to non-equipped cooking systems. It is recognized that the use of energy storage has been proved as a huge advantage to solar cooking systems, however, the design, and heat transfer characteristics of the cooking vessel along with the storage material type and volume must be optimized in order to make this technology more influential.

Light- and magnetically actuated FePt microswimmers.

Externally controlled microswimmers offer prospects for transport in biological research and medical applications. This requires biocompatibility of the swimmers and the possibility to tailor their propulsion mechanisms to the respective low Reynolds number environment. Here, we incorporate low amounts of the biocompatible alloy of iron and platinum (FePt) in its [Formula: see text] phase in microstructures by a versatile one-step physical vapor deposition process. We show that the hard magnetic properties of [Formula: see text] FePt are beneficial for the propulsion of helical micropropellers with rotating magnetic fields. Finally, we find that the FePt coatings are catalytically active and also make for Janus microswimmers that can be light-actuated and magnetically guided.

Soft Urinary Bladder Phantom for Endoscopic Training.

Bladder cancer (BC) is the main disease in the urinary tract with a high recurrence rate and it is diagnosed by cystoscopy (CY). To train the CY procedures, a realistic bladder phantom with correct anatomy and physiological properties is highly required. Here, we report a soft bladder phantom (FlexBlad) that mimics many important features of a human bladder. Under filling, it shows a large volume expansion of more than 300% with a tunable compliance in the range of 12.2 ± 2.8 - 32.7 ± 5.4 mL cmH2O-1 by engineering the thickness of the bladder wall. By 3D printing and multi-step molding, detailed anatomical structures are represented on the inner bladder wall, including sub-millimeter blood vessels and reconfigurable bladder tumors. Endoscopic inspection and tumor biopsy were successfully performed. A multi-center study was carried out, where two groups of urologists with different experience levels executed consecutive CYs in the phantom and filled in questionnaires. The learning curves reveal that the FlexBlad has a positive effect in the endourological training across different skill levels. The statistical results validate the usability of the phantom as a valuable educational tool, and the dynamic feature expands its use as a versatile endoscopic training platform.

Introduction of Structured Feedback to Medical Undergraduate Students in the First Professional.

CONTEXT: Feedback is integral in medical education as it improves learner's knowledge, skills, and professional competence, however it is not routinely practiced in medical colleges. Therefore, the present educational research project was designed in a need-based attempt to introduce and implement a program of structured feedback in the department of biochemistry in the first professional MBBS. AIM: The aim was to introduce and implement a program of structured feedback in biochemistry for 1st year medical undergraduates and to collect students' and faculty perceptions about its effectiveness. SETTINGS AND DESIGN: it was a prospective, nonrandomized, interventional study. METHODS: The study was conducted over 135 first professional undergraduates with six faculties. The feedback questionnaires to assess the perceptions of students and faculty on the feedback program were designed and peer-expert validated. An educational program for giving structured feedback was designed, peer-expert validated, and introduced and perceptions of students and faculty were collected using the feedback questionnaires. The collected data were analyzed in terms of percentages, medians, modes, and satisfaction index and represented in graphs. Transcripts were prepared for qualitative data, themes were identified, and a thematic map was prepared. RESULTS: Students (n = 135) perceived the feedback sessions to be helpful in making them aware about their learning gaps (70%) and facilitated the process of bridging the learning gaps (62%). Students strongly agreed that feedback has helped in better understanding of the topic (82%), better retention (69%), and acted as effective learning tool (68%). The faculty did not find the feedback sessions as extra burden in their routine schedule (83%). The main themes identified were "More interaction with teacher," "Increased motivation," "Student centric," "Less stressful," "Improved confidence," "Identification and bridging of learning gaps," "Improved efficacy to attempt questions," and "Improved learning." CONCLUSIONS: The feedback program was perceived satisfactory by both students and faculty agreeing upon more of such sessions and implementation in the curriculum in the near future.

Pulmonary Hydatid Disease with Aspergillosis - An Unusual Association in an Immunocompetent Host.

Echinococcosis is a common cause of pulmonary cavities. Aspergillus fumigatus, a saprophytic fungus, can colonise pulmonary cavities caused by tuberculosis, sarcoidosis, echinococcosis, bronchiectasis and neoplasms. Infection by Aspergillus is often seen in immunosuppressed cases. However, co-infection of Aspergillus with pulmonary echinococcosis is unexpected and very unusual, especially in an immunocompetent patient. We present the case of a 45-year-old immunocompetent male who came with non-resolving pneumonia and fever for 8 months and dyspnoea since 15 days accompanied by recurrent episodes of hemoptysis since 5 days. Chest X Ray and Computed Tomography scan showed a cystic lesion in the middle lobe of the right lung. Middle lobectomy with video-assisted thoracoscopic surgery was performed and histopathology revealed ectocyst of Hydatid cyst which was also colonised by septate fungal hyphae exhibiting acute angled branching, morphologically consistent with Aspergillus. Gomori Methanamine Silver and Periodic Acid Schiff stains highlighted the hyphae of Aspergillus as well as the lamellated membranes of ectocyst and an occasional scolex of Echinococcus. Sections from surrounding lung parenchyma also showed these fungal hyphae within an occasional dilated bronchus. Thus a diagnosis of dual infection of Aspergillosis and Pulmonary Echinococcosis was established. The possibility of dual infection by a saprophytic fungus must be kept in mind while dealing with a case of a cavitary lesion in long-standing and non-resolving pneumonia, even in an immunocompetent patient. Establishing the correct diagnosis of Aspergillosis with Echinococcosis is essential for proper and complete management.

Analysis of personality traits as a risk factor in crash related trauma.

BACKGROUND: Due to increasing stress, individual personality traits are becoming a significant contributor to CRT (Crash Related Trauma). In the present study, we hypothesized that there will be no difference in personality characteristics of CRT patients and control subjects and there will be no association between trauma and personality characteristics of CRT patients. METHOD: A total of 119 cases and 112 controls of age >18 years were selected as per criteria decided. After obtaining ethical clearance, patients presenting to the emergency orthopedic unit were included in the study. After primary management all enrolled subjects were assessed by ICD 10 module screening questionnaire and analyzed for nine personality traits, subject to written informed consent. RESULTS: Of all the cases enrolled 82.35% were males. Impulsive personality trait is found in 84.78% (39/46) cases. There were 46 motorcyclists out of 119 cases enrolled. Most of the personality traits showed a statistical significant association (p < 0.0003) with CRT. CONCLUSION: Majority of CRT victims attending orthopedic emergency unit at trauma center had impulsive and histrionic personality characteristics which accounted for 84.78% and 82.61% cases respectively. These traits showed a statistical significant association with CRT.

Immunohistochemical expression of glial fibrillary acidic protein and CAM5.2 in glial tumors and their role in differentiating glial tumors from metastatic tumors of central nervous system.

BACKGROUND AND OBJECTIVES: Immunohistochemistry (IHC) has become an important tool in the diagnosis of metastatic brain tumors. The judicious use of a panel of selected immunostains is unquestionably helpful in diagnostically challenging cases. In our study, the best combination of immune markers useful in differentiating metastatic carcinoma from high-grade gliomas in central nervous system (CNS) are glial fibrillary acidic protein (GFAP) and cytokeratin (CK) (CAM5.2). MATERIALS AND METHODS: The study was conducted on 80 cases of glial tumors including metastatic tumors to the CNS. Histopathological diagnosis was established on routine hematoxylin and eosin staining of the sections. Special IHC markers, GFAP, and CAM5.2 were used to differentiate glial from metastatic tumors. RESULT: Of total 80 cases, 40 cases of astrocytic tumors, 2 cases of ependymoma, 2 cases of mixed glial tumors, and 16 cases of glioblastoma multiforme were positive for GFAP. Twelve cases of oligodendroglioma were negative for GFAP. The sensitivity of GFAP in glial tumors was statistically significant as 81.1% and specificity 100%, whereas sensitivity and specificity of CAM5.2 in metastatic tumors were 100%. CONCLUSION: IHC plays an important role in diagnosing tumors of CNS and markers such as GFAP and CK (CAM5.2) are quite effective in differentiating glial tumors from metastatic tumors of CNS.

Need of Revision of Lower Limb Amputations in a North Indian Tertiary Care Centre.

INRTODUCTION: Amputation of the extremity is a big challenge to mankind. Revision rate of primary amputations stands high despite of maximum care at tertiary care centres. The purpose of this study was to establish cause for the revision, identify preventable cause and to assess outcome of revision amputation surgery. MATERIALS AND METHODS: We performed a retrospective study on lower limb revision amputations in Department of Physical Medicine and Rehabilitation and Department of Orthopaedic Surgery, King George Medical University between Jan 2012 to Jan 2015. All patients of any age group and gender admitted for revision amputation were included in the study population. RESULTS: A total of 32 patients who required revision amputation of lower limbs was included in the study, out of these 62.50 % were male and 37.50 % were female. Age of the patients ranged from 5 to 72 years with mean of 42 years. Most common level of initial amputation was below knee (56.25 %) followed by above knee amputation (31.25%). Most common indication for initial amputation was trauma (43.75%) followed by infection, vascular diseases, malignancy and leprosy. Poor stump formation was found to be most common indication for revision amputation (37.50%) followed by infection (25%), recurrent ulceration (18.75%), stitch abscess (6.25%), neuroma (6.25%), and necrosis (6.25%). All patients were treated successfully. CONCLUSION: Revision amputation increases morbidity. Poor stump formation at the time of initial amputation and infection are the most common indication for revision surgery. These are the preventable causes and every effort should be made to alleviate these as well as other preventable causes.

Repositioning the knee joint in human body FE models using a graphics-based technique.

OBJECTIVE: Human body finite element models (FE-HBMs) are available in standard occupant or pedestrian postures. There is a need to have FE-HBMs in the same posture as a crash victim or to be configured in varying postures. Developing FE models for all possible positions is not practically viable. The current work aims at obtaining a posture-specific human lower extremity model by reconfiguring an existing one. METHODOLOGY: A graphics-based technique was developed to reposition the lower extremity of an FE-HBM by specifying the flexion-extension angle. Elements of the model were segregated into rigid (bones) and deformable components (soft tissues). The bones were rotated about the flexion-extension axis followed by rotation about the longitudinal axis to capture the twisting of the tibia. The desired knee joint movement was thus achieved. Geometric heuristics were then used to reposition the skin. A mapping defined over the space between bones and the skin was used to regenerate the soft tissues. Mesh smoothing was then done to augment mesh quality. RESULTS: The developed method permits control over the kinematics of the joint and maintains the initial mesh quality of the model. For some critical areas (in the joint vicinity) where element distortion is large, mesh smoothing is done to improve mesh quality. CONCLUSIONS: A method to reposition the knee joint of a human body FE model was developed. Repositions of a model from 9 degrees of flexion to 90 degrees of flexion in just a few seconds without subjective interventions was demonstrated. Because the mesh quality of the repositioned model was maintained to a predefined level (typically to the level of a well-made model in the initial configuration), the model was suitable for subsequent simulations.

Emulsion stabilization using ionic liquid [BMIM]+[NTf2]- and performance evaluation on the extraction of chromium.

This study focuses on the role of a hydrophobic ionic liquid 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, [BMIM](+)[NTf(2)](-) in the preparation of emulsion liquid membrane (ELM) phase containing kerosene as solvent, Span 80 as surfactant, NaOH as internal phase and TOMAC (tri-n-octylmethylammonium chloride) a second ionic liquid as carrier. The first time used [BMIM](+)[NTf(2)](-) in ELM was found to play the role of a stabilizer. The emulsion prepared using [BMIM](+) [NTf(2)](-) has a long period of stability of about 7h (at 3% (w/w) of [BMIM](+)[NTf(2)](-)) which otherwise has a brief stability up to only 7 min. The stability of the emulsion increases with the increase in concentration of [BMIM](+)[NTf(2)](-) up to 3% (w/w). Nevertheless, with further increase in concentration of [BMIM](+)[NTf(2)](-), a reduction in the stability occurs. The extraction experiments were carried out after holding the ELM for 2h after the preparation and a removal efficiency of approximately 80% was obtained for Cr. The destabilization of the emulsion was studied by observing the change in the interface height. An empirical correlation for the stability of the emulsion has been proposed.