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Cerebral vasospasm following an endoscopic endonasal resection of a craniopharyngioma is a rare, devastating occurrence that can lead to delayed cerebral ischemia and a poor neurological outcome if not diagnosed and treated in a timely manner. The etiology of this condition is not well understood. In this chapter, we present a case of cerebral vasospasm following transsphenoidal surgery (TSS) for craniopharyngioma, review the literature, and identify common presenting symptoms, probable predisposing factors, and essential management strategies to treat this condition., Competing Interests: Conflict of Interest. The authors declare that they have no conflicts of interest., (© 2025. The Author(s).)

Drug repurposing is preferred over de-novo drug discovery to unveil the therapeutic applications of existing drug candidates before investing considerable resources in unexplored novel chemical entities. This study demonstrated multifaceted stratagems to reconnoiter promising repurposable candidates against Hepatocellular Carcinoma (HCC) by amalgamating Real-World-Data (RWD) with bioinformatics algorithms corroborated with in-silico and in-vitro studies. At the outset, the RWD from the Food and Drug Administration Adverse Event Reporting System (FAERS) was explored to navigate signals to retrieve repurposable drugs that are inversely associated with HCC via Disproportionality Analysis. Further, transcriptomic analysis was used to capture the potential targets of HCC. Following this, the interactions between repurposable drugs and HCC targets were virtually demonstrated via molecular docking and Molecular Dynamics Simulations (MDS). Furthermore, additional cytotoxicity and gene expression experiments were conducted to corroborate the results. Overall, 64 drugs with Drug Event >5 were shortlisted as prospective repurposable drugs as per the RWD obtained from FAERS. The transcriptomic analysis highlighted significant upregulation of Cyclin A2 (CCNA2) in HCC, which activates Cyclin Dependent Kinase 2 (CDK2). Further, in-silico studies identified Losartan and Allopurinol, with docking scores of -7.11 and -6.219, respectively, as potential repurposable drugs. The selected drugs underwent further scrutiny through in-vitro studies. The treatment of HepG2 cells with Allopurinol resulted in significant downregulation of CCNA2/CDK2 expression with an elevation in reactive oxygen species levels, uncovering Allopurinol's anticancer mechanism through cellular apoptosis. This study suggests the importance of RWD in drug repurposing and the potential of Allopurinol as a repurposable drug against HCC.

Aims: Sevoflurane is an ether-based inhalational anaesthetic that induces and maintains general anaesthesia. Our study aimed to detect sevoflurane-induced nephrogenic diabetes insipidus using data mining algorithms (DMAs) and molecular docking. The FAERS database was analysed using OpenVigil 2.1 for disproportionality analysis., Methods: We analysed FAERS data from 2004 to 2022 to determine the incidence of nephrogenic diabetes insipidus associated with sevoflurane. Reporting odds ratios (RORs) and proportional reporting ratios (PRRs) with 95% confidence intervals were calculated. We also used molecular docking with AutoDock Vina to examine sevoflurane's binding affinity to relevant receptors., Results: A total of 554 nephrogenic diabetes insipidus cases were reported in FAERS, of which 2.5% (14 cases) were associated with sevoflurane. Positive signals were observed for sevoflurane with ROR of 76.012 (95% CI: 44.67-129.35) and PRR of 75.72 (χ 2 : 934.688). Of the 14 cases, 50% required hospitalization, 14% resulted in death, and the remaining cases were categorized as other outcomes. Molecular docking analysis showed that sevoflurane exhibited high binding affinity towards AQP2 (4NEF) and AVPR2 (6U1N) with docking scores of -4.9 and -5.3, respectively., Conclusions: Sevoflurane use is significantly associated with the incidence of nephrogenic diabetes insipidus. Healthcare professionals should be cautious when using this medication and report any adverse events to regulatory agencies. Further research is needed to validate these findings and identify risk factors while performing statistical adjustments to prevent false-positives. Clinical monitoring is crucial to validate potential adverse effects of sevoflurane., (© 2023 The Authors. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

Purpose: To detect the possible safety signal of purine antimetabolites associated with Pneumocystis jirovecii pneumonia through disproportionality analysis in the FDA Adverse Event Reporting System (FAERS) Database., Methods: A case/non-case retrospective disproportionality analysis was performed in the publicly available FAERS database using AERSmine (2004Q1-2021Q3). Four models were developed to explore the signal strength of PAs among different populations with possible confounding factors. Reporting odds ratio (ROR) and Proportional reporting ratio (PRR) was used as the data mining algorithm for the analysis. A value of ROR-1.96SE > 1 and PRR ≥ 2 with an associated X 2 value of 4 or more was considered the threshold for a signal., Results: A total of 7073 reports associated with Pneumocystis jirovecii pneumonia were present in the database, of which 899 reports were associated with purine antimetabolites. A crude signal strength of ROR 15.76(14.70-16.91) was obtained for purine antimetabolites associated PJP, with the highest signal strength reported with fludarabine and thioguanine [ROR 19.63(17.42-22.13); 19.45(13.21-28.63)]. Stratifying the cases based on autoimmune disorders and the cancer population revealed an ROR of 3.33(2.46-4.50) and 2.93(2.26-3.79) respectively. The highest risk of PJP with use of PAs was observed amongst children with a higher risk of nearly 2 times than the adult population [ROR 11.57(9.16-14.62)]., Conclusions: Our study provided evidence on the occurrence of PJP with the use of purine antimetabolites among the autoimmune and cancer population. We identified signals for PJP with azathioprine, mercaptopurine, thioguanine, cladribine, fludarabine, and clofarabine. More research with a superior epidemiological study design of a defined population is required to validate these findings., (© 2023 John Wiley & Sons Ltd.)

A renal allograft transplant recipient presented to our emergency department with pus discharging right-sided cheek swelling. She had the same presentation 1 year after kidney transplant surgery. The abscess was incised and drained, and a sample was sent for culture and sensitivity. The culture initially grew Aspergillus fumigatus for which she was started on itraconazole. While the patient was on antifungal therapy, immunohistochemistry revealed diffuse large B-cell lymphoma to be the primary disease, and rituximab chemotherapy was initiated. The patient is being followed up and is currently in remission.We are reporting this rare case to raise awareness so that clinicians consider the possibility of post-transplant lymphoproliferative disorder when they see a similar presentation., Competing Interests: Competing interests: None declared., (© BMJ Publishing Group Limited 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Rathke's cleft cysts (RCCs) are benign epithelial lesions arising from the Rathke's pouch remnants that fail to regress during embryogenesis. Some RCCs become symptomatic and require treatment. Cyst fenestration and drainage of its contents is the preferred procedure to treat symptomatic cases but carries a risk of recurrence. We propose the use of a novel modified nasoseptal flap technique to partially line the cyst wall to avoid recurrence., Methods: This was a prospective, observational study that included all RCC patients admitted to the Department of Neurosurgery, Aster Medcity, from April 2015 to May 2018. The modified nasoseptal flap technique was performed in all patients. They underwent preoperative and postoperative ophthalmological, endocrine, endoscopic, and MRI evaluations to look for recurrence., Results: Ten patients underwent the modified nasoseptal flap technique. The median follow-up was 36 months. Postoperatively, all patients were relieved from headaches. Moreover, their visual fields and pituitary functions normalized. None of the patients developed recurrence of RCC on follow-up brain MRI. On endoscopic examination, all patients had retained patency of the fenestra. The longest follow-up was 72 months., Conclusions: The modified nasoseptal flap technique maintains patency and avoids recurrence of RCCs on long-term follow-up., Competing Interests: None

Background and Study Aim: The study was designed to detect novel Adverse Events (AEs) of pantoprazole by disproportionality analysis in the FDA (Food and Drug Administration) database of Adverse Event Reporting System (FAERS) using Data Mining Algorithms (DMAs). Pantoprazole, the most commonly over-utilized Over The Counter (OTC) medication, was selected to assess any short-term or long-term AEs. The study aimed to analyze the novel adverse events of pantoprazole using the FAERS database., Materials and Methods: A retrospective case/non-case disproportionality analysis was performed in the FAERS database. This study was based on AEs reported to FAERS from 2006Q1-2021Q3. Openvigil 2.1 was used for data extraction. Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), and Information Component (IC) were applied to measure the disproportionality in reporting. A value of ROR-1.96SE > 1, PRR ≥ 2, and IC-2SD > 0 were considered as the threshold for a positive signal., Results: A total of 1050 reports of dyspepsia, 7248 reports of hypocalcemia and 995 reports of hyponatremia were identified. A potential positive signal for dyspepsia (ROR-1.96SE = 2.231, PRR = 2.359, IC-2SD = 1.13), hypocalcemia (4.961, 5.45, 2.23) and hyponatremia (3.948, 4.179, 1.92) were identified for pantoprazole., Conclusion: Data mining in the FAERS database produced three potential signals associated with pantoprazole. As a result, further clinical surveillance is needed to quantify and validate potential hazards associated with pantoprazole-related adverse events., Competing Interests: Declaration of competinginterests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Pan-Arab Association of Gastroenterology. Published by Elsevier B.V. All rights reserved.)

Mucormycosis is a dreaded clinical entity caused by filamentous fungi of the order Mucorales mainly affecting immunocompromised individuals. Usually seen involving paranasal sinuses, orbit, lungs and gastrointestinal system, it is extremely rare in other areas. Herein we report a rare presentation of Mucormycosis affecting the ear and neck where early detection, timely intervention, multidisciplinary involvement and judicious use of local antibiotics apart from the mainstay treatment regimen like surgical debridement and intravenous Amphotericin B has saved the patient and given him a reasonably good quality of life devoid of morbidity., Competing Interests: Conflict of interestThe author declares that they have no conflict interest., (© The Author(s) 2020.)

What Is Known and Objective: Red man syndrome (RMS) is a non-IgE-mediated anaphylactoid adverse event frequently witnessed after a rapid infusion of vancomycin. This study aims to unravel drugs and associated off-label targets that induce RMS by exploiting FDA Adverse Event Reporting System (FAERS) and Pharmacovigilance/Pharmacogenomics Insilico Pipeline (PHARMIP)., Methods: The case/non-case retrospective observational study was conducted in the FAERS database. Reporting odds ratio (ROR) and proportional reporting ratio (PRR) data mining algorithms were used to evaluate the strength of the signal. The off-label targets of the drugs with potential signals were obtained using online servers by applying a similarity ensemble approach and a reverse pharmacophore database, which was further validated by molecular docking studies., Results and Discussion: Oritavancin exhibited a strong positive signal (PRR:1185.20 and ROR:1256), which suggests a higher risk for causing RMS. The literature search revealed the involvement of the MRGPRX2 gene in the development of RMS. PHARMIP study unearthed Carbonic anhydrase II (CA2) as the common off-label target among the drugs causing RMS. The results obtained from molecular docking studies reinforced the findings as mentioned earlier, wherein the highest docking score was disinterred for oritavancin (-9.4 for MRGPRX2 and - 8.7 for CA2)., What Is New and Conclusion: Many antibiotics and other classes of medications have been discovered in the quest for drugs that may induce RMS, although a causal relationship could not be established. The implication of MRGPX2 and CA2 in the initial stages of pathogenesis necessitates the development of inhibitors that could be used as potential therapeutic agents against RMS., (© 2022 John Wiley & Sons Ltd.)

Background: Central or atypical skull base osteomyelitis (CSBO) often presents with severe unrelenting headache and progressive mono or polyneuritis cranialis. MRI and CT are used as initial imaging techniques but have a poor specificity and sensitivity., Objective: To analyze our cohort of CSBO., Materials and Methods: Over a 5-year period [2015-2020], we retrospectively analyzed the records of all patients with CSBO who had undergone a 3T MRI Brain, MR angiography, regional FDG PET-CT, and skeletal scintigraphy with 99mTc MDP/SPECT-CT. Surgical biopsy specimens were sent for bacterial and fungal cultures., Results: In total, 17 patients with CSBO were identified. Typically, 88% of patients presented with severe unilateral headache. All patients had at least a cranial mono or polyneuritis. The majority of patients were diabetic [64%]. MRI was normal in 42% of patients, whereas PET-CT and with 99mTc MDP scan and SPECT-CT were abnormal in all patients., Conclusion: Our series of CSBO showed a 40% mortality rate with significant morbidity and relentless progression. Patients required repeated PET CT and bone scans to detect regression of disease activity. The average duration of IV therapy ranged from 3 weeks to 9 months and oral therapy for around 2-3 months. Cure was defined after taking into account the original diagnosis, symptom resolution, and concordant reduction of tissue uptake on PET CT and 99mTc bone scan. The combination of MRI, FDG PET CT, and 99mTc bone scan with concurrent SPECT CT was able to detect disease and disease progression in all patients., Competing Interests: None

Continuous stress exposure negatively impacts mental and physical well-being. Physiological arousal due to stress affects heartbeat frequency, changes breathing pattern and peripheral temperature, among several other bodily responses. Traditionally stress detection is performed by collecting signals such as electrocardiogram (ECG), respiration, and skin conductance response using uncomfortable sensors such as a chestband. In this study, we use earbuds that passively measure photoplethysmography (PPG), core body temperature, and inertial measurements. We have conducted a lab study exposing 18 participants to an evaluated speech task and additional tasks aimed at increasing stress or promoting relaxation. We simultaneously collected PPG, ECG, impedance cardiography (ICG), and blood pressure using laboratory grade equipment as reference measurements. We show that the earbud PPG sensor can reliably capture heart rate and heart rate variability. We further show that earbud signals can be used to classify the physiological responses associated with stress with 91.30% recall, 80.52% precision, and 85.12% F1-score using a random forest classifier with leave-one-subject-out cross-validation. The accuracy can further be improved through multi-modal sensing. These findings demonstrate the feasibility of using earbuds for passively monitoring users' physiological responses.

Passive assessment of obstructive pulmonary disease has gained substantial interest over the past few years in the mobile and wearable computing communities. One of the promising approaches is speech-based pulmonary assessment wherein spontaneous or scripted speech is used to evaluate an individual's pulmonary condition. Recent approaches in this regard heavily rely on accurate speech activity segmentation and specific, hand-crafted features. In this paper, we present an end-to-end deep learning approach for detecting obstructive pulmonary disease. We leveraged transfer learning using a network pre-trained for a different audio-based task, and employed our own additional shallow network on top as a binary classifier to indicate if a given speech recording belongs to an asthma or COPD patient. The additional network was a fully connected neural net with 2 hidden layers, and this was evaluated on two real-world datasets. We demonstrated that the system can identify subjects with obtructive pulmonary disease using their speech with 88.3 % precision, 88.8 % recall and 88.3% F-1 score using 10-fold cross-validation. The system showed improved performance in identifying the most severely affected subgroup of patients in the dataset, with an average 93.6 % accuracy.

Atrial Fibrillation (AF) is an important cardiac rhythm disorder, which if left untreated can lead to serious complications such as a stroke. AF can remain asymptomatic, and it can progressively worsen over time; it is thus a disorder that would benefit from detection and continuous monitoring with a wearable sensor. We develop an AF detection algorithm, deploy it on a smartwatch, and prospectively and comprehensively validate its performance on a real-world population that included patients diagnosed with AF. The algorithm showed a sensitivity of 87.8% and a specificity of 97.4% over every 5-minute segment of PPG evaluated. Furthermore, we introduce novel algorithm blocks and system designs to increase the time of coverage and monitor for AF even during periods of motion noise and other artifacts that would be encountered in daily-living scenarios. An average of 67.8% of the entire duration the patients wore the smartwatch produced a valid decision. Finally, we present the ability of our algorithm to function throughout the day and estimate the AF burden, a first-of-this-kind measure using a wearable sensor, showing 98% correlation with the ground truth and an average error of 6.2%.

Breast, lung, prostate, thyroid, and kidney carcinomas are the primary tumors that are known to have bony metastasis. Hepatocellular carcinoma (HCC) frequently involves the lung and lymph nodes and less commonly the osseous system. Numbness/persistent pain in the distribution of the trigeminal nerve is more likely a neuropathy. The causes are idiopathic(common), unintentional injury to the trigeminal nerve during surgery or trauma, blood vessel pressing the trigeminal nerve, tumor infiltration, multiple sclerosis, and stroke. Unresolved facial pains after conventional treatment should prompt additional investigation to rule out other causes. In this case, we report a trigeminal neuropathy of rare cause, which is a solitary metastasis from an inactive HCC involving the osseous structures., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2021, Ram et al.)

Respiratory illnesses are common in the United States and globally; people deal with these illnesses in various forms, such as asthma, chronic obstructive pulmonary diseases, or infectious respiratory diseases (e.g., coronavirus). The lung function of subjects affected by these illnesses degrades due to infection or inflammation in their respiratory airways. Typically, lung function is assessed using in-clinic medical equipment, and quite recently, via portable spirometry devices. Research has shown that the obstruction and restriction in the respiratory airways affect individuals' voice characteristics. Hence, audio features could play a role in predicting the lung function and severity of the obstruction. In this paper, we go beyond well-known voice audio features and create a hybrid deep learning model using CNN-LSTM to discover spatiotemporal patterns in speech and predict the lung function parameters with accuracy comparable to conventional devices. We validate the performance and generalizability of our method using the data collected from 201 subjects enrolled in two studies internally and in collaboration with a pulmonary hospital. SpeechSpiro measures lung function parameters (e.g., forced vital capacity) with a mean normalized RMSE of 12% and R 2 score of up to 76% using 60-second phone audio recordings of individuals reading a passage.Clinical relevance - Speech-based spirometry has the potential to eliminate the need for an additional device to carry out the lung function assessment outside clinical settings; hence, it can enable continuous and mobile track of the individual's condition, healthy or with a respiratory illness, using a smartphone.

Background: Consumer devices with broad reach may be useful in screening for atrial fibrillation (AF) in appropriate populations. However, currently no consumer devices are capable of continuous monitoring for AF., Objective: The purpose of this study was to estimate the sensitivity and specificity of a smartwatch algorithm for continuous detection of AF from sinus rhythm in a free-living setting., Methods: We studied a commercially available smartwatch with photoplethysmography (W-PPG) and electrocardiogram (W-ECG) capabilities. We validated a novel W-PPG algorithm combined with a W-ECG algorithm in a free-living setting, and compared the results to those of a 28-day continuous ECG patch (P-ECG)., Results: A total of 204 participants completed the free-living study, recording 81,944 hours with both P-ECG and smartwatch measurements. We found sensitivity of 87.8% (95% confidence interval [CI] 83.6%-91.0%) and specificity of 97.4% (95% CI 97.1%-97.7%) for the W-PPG algorithm (every 5-minute classification); sensitivity of 98.9% (95% CI 98.1%-99.4%) and specificity of 99.3% (95% CI 99.1%-99.5%) for the W-ECG algorithm; and sensitivity of 96.9% (95% CI 93.7%-98.5%) and specificity of 99.3% (95% CI 98.4%-99.7%) for W-PPG triggered W-ECG with a single W-ECG required for confirmation of AF. We found a very strong correlation of W-PPG in quantifying AF burden compared to P-ECG (r = 0.98)., Conclusion: Our findings demonstrate that a novel algorithm using a commercially available smartwatch can continuously detect AF with excellent performance and that confirmation with W-ECG further enhances specificity. In addition, our W-PPG algorithm can estimate AF burden. Further research is needed to determine whether this algorithm is useful in screening for AF in select at-risk patients., (Copyright © 2021 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

Background: Notoriety bias is defined as "a selection bias in which a case has a greater chance of being reported if the subject is exposed to the studied factor known to cause, thought to cause, or likely to cause the event of interest." This study aimed to determine the existence of notoriety bias in the FDA Adverse Event Reporting System (FAERS) database and estimate the impact of potential notoriety bias induced by safety alerts on signal estimation using disproportionality analysis. Methods: Publicly available FAERS data were downloaded and used for analysis. Thirty-one drugs which had label change/safety alert issued by FDA from 2009 to 2013 were considered. These drugs were reviewed 4 quarters before and after the safety alert notification for the existence of notoriety bias. The impact of notoriety bias induced by safety alerts was analyzed by comparing the signal strength using reporting odds ratio (ROR) and proportional reporting ratio (PRR), 2 years before and after the safety alert. Wilcoxon signed rank test was used to determine whether there were a statistically significant difference before and after the safety alert. Results: There was increased reporting for 11 drugs after the safety alert/label change by the FDA. The reporting of 20 drugs decreased or remained unchanged after the safety alert/label change by the FDA. Wilcoxon signed rank test showed that there is no statistically significant difference with respect to the number of reports before and after the safety alert ( P = .330, Z = -0.974). Fourteen (45.16%) drugs had an increase in ROR, while 17 (54.83%) drugs had a decrease in ROR after safety alert issued by FDA ( P = .953, Z = -0.059). Fourteen (45.16%) drugs had an increase in PRR, while 17 (54.83%) drugs had a decrease in PRR after safety alert issued by the FDA ( P = .914, Z = -0.108). Conclusion: Although few FDA safety alert/warnings had a strong and immediate impact, many had no impact on reporting of AE and signal strength. This study found that overreporting due to notoriety bias does not exist in the FAERS database and the overall disproportionality in signal estimates is not altered by the safety alert., Competing Interests: Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2019.)

Objectives: Poor sleep is a vital symptom observed in many psychiatric conditions and is the most neglected and underdiagnosed. The current study aims at assessment of sleep quality among psychiatric patients using the Pittsburgh Sleep Quality Index (PSQI) scale and to identify the predictors of sleep quality., Methods: A hospital-based cross-sectional observational study conducted in the Psychiatry department with a sample size of 256 patients for six months. PSQI scale was used to assess sleep quality and multiple logistic regression was used (to identify) the predictors for poor sleep quality., Results: The mean age of the study population was 37.95 ± 14.11 years, with 148 (58%) male study participants. 192 (75%) of the study population had poor sleep quality with respect to PSQI scale with a mean score of 9.05 ± 4.65 that was well above the expected range (0-5) suggestive of compromised quality of sleep (p=0.001). Poor sleep satisfaction, waking up after the sleep onset, anorexia, day time drowsiness and at least one completely sleepless night in the past one week of admission were identified as good predictors for poor sleep quality., Conclusions: Our study addresses the importance of assessing sleep quality regardless of the psychiatric conditions. We recommend screening patients if they have Poor sleep satisfaction, waking up after the sleep onset, anorexia, day time drowsiness or at least one completely sleepless night in the past one week of admission predictors for comorbid sleep disorders., (© 2021 Walter de Gruyter GmbH, Berlin/Boston.)

Background: Signal strength for any drug-event combination can be determined using disproportionality analysis. Vemurafenib is a BRAF inhibitor approved by the US Food and Drug Administration (FDA) in 2011 for the treatment of metastatic melanoma. This study aims to identify the signal strength of Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS) associated with vemurafenib using disproportionality analysis in FDA database of Adverse Event Reporting System (FAERS)., Methods: Data were obtained from the public release of data in FAERS. The case/non-case method was adopted for the analysis of the association between vemurafenib use and DRESS. The data mining algorithm used for the analysis was the Reporting Odds Ratio (ROR) and Proportional Reporting Ratio (PRR). A value of ROR-1.96SE>1, PRR≥2 was considered as positive signal strength., Results: A total of 7,171 reports for DRESS have been reported in the FDA database. Amongst which, 125 reports were associated with vemurafenib. A cumulative ROR of 17.72 (95% CI 14.83; 21.18) and PRR of 17.46 (95% CI 14.65; 20.81) were observed. Combination treatment of vemurafenib with cobimetinib had a higher number of reports (100) with ROR of 103.42 (84.13- 127.14) and PRR of 94.52 (78.26- 114.15). Four deaths were reported and the non-death serious reports included hospitalization, life-threatening, disability, and other serious events with 61, 11, 2 and 39 reports, respectively., Conclusion: Positive signal strength was observed for vemurafenib associated DRESS. The signal strength was higher for vemurafenib in combination with cobimetinib than vemurafenib alone. Health care professionals should be cautious about encountering serious adverse events and should report such events to the regulatory authorities., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Purpose/background: The study aims to assess whether the early response can predict the outcome at the endpoint for the treatment of first-episode psychosis with risperidone and identify the relationship between initial symptom reduction and late response., Methods/procedures: A prospective observational study with 4 points follow-up (weeks 2, 3, 4, and 8) was conducted in 48 adult first-episode psychosis patients. Symptoms were quantified by the Positive and Negative Syndrome Scale (PANSS) score. The initial recommended dose was 2 mg of risperidone once daily before sleep. The PANSS score on day 1 (before initiation of drug therapy) was considered as the baseline score. Treatment responses were considered as a reduction of more than 20%, 25%, 30% and 50% from the baseline score on first, second, third, and final follow-up, respectively. Receiver operating characteristic curves were generated for predicting response at the endpoint., Findings/results: Thirty-one (65%) patients achieved more than 50% reduction (responders) in PANSS score. The mean total PANSS score of the study population after 8 weeks of therapy was found to be 49.77 (95% confidence interval, 46.10-53.43). The mean percentage reduction in PANSS score after 8 weeks of therapy was found to be 52.92% (95% confidence interval, 48.83-57.01). Week 2 response can be taken as the early response (area under the curve = 81.9, P < 0.001). However, the more accurate prediction was possible with week 4 response (area under the curve = 88.7%, P < 0.001)., Implications/conclusions: Our study suggests that patients with an early response at week 2 are likely to achieve positive response after 8 weeks., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

We report the case of an eight-year-old partially immunized boy who presented with presumed bacterial tonsillitis. He was initially prescribed amoxicillin-clavulanic acid which resulted in the development of an erythematous maculopapular over the face which spread to the trunk and extremities including palms and soles and resolved over the next three days. He was diagnosed to have diphtheria and infectious mononucleosis (IMN) co-infection. He made an uneventful recovery and an extensive review of the literature showed that the incidence of diphtheria and IMN co-infection is a relatively rare clinical entity. We wish to highlight the possibility of such co-infections which often mimic one another., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2020, Cyril et al.)

Background: At present, schizophrenia guidelines recommend waiting for 8 weeks before considering a patient as non-responder. This study aims to detect the optimal early response threshold that best predict the final outcome of olanzapine. Methods: The study was conducted for 8-week, four points follow up (week 2,3,4, and 8) prospective observational study. A reduction of 20, 25, 30% in Positive and Negative Syndrome Scale (PANSS) score from the base line at week 2,3, and 4 respectively were considered as early response. A reduction of 50% at week 8 was considered as responders. Receiver Operating Characteristics (ROC) curves were performed to detect the optimal threshold. Results: Mean total baseline PANSS score was 106.66(95% CI; 100.4, 112.9). Week 2 (AUC = 50.5%, p  > 0.964) and week 3 (AUC = 64.9, p  > 0.13) responses failed to predict the 8th week response. Week 4 response (AUC = 92%, p  < 0.001) can be taken for the prediction of 8th week response (specificity = 72%, sensitivity = 100%, Positive Predictive Value = 61.1%, Negative Predictive Value = 100% and Optimum Early Response (OER) = 29.4%). 25 patients (69%) achieved more than 50% reduction (responders) in PANSS score after 8 weeks of treatment. Conclusions: Our study suggests that patients with early response at week 4 are likely to achieve positive response after 8 weeks. This may help in appropriate clinical decision making for early non-responders.Key PointsThe early response can forecast the outcome at the endpoint for the treatment of FESA reduction of baseline PANSS score by 30% or more after four weeks are likely to have remission after week 8 with olanzapine therapy.

Passive health monitoring has been introduced as a solution for continuous diagnosis and tracking of subjects' condition with minimal effort. This is partially achieved by the technology of passive audio recording although it poses major audio privacy issues for subjects. Existing methods are limited to controlled recording environments and their prediction is significantly influenced by background noises. Meanwhile, they are too compute-intensive to be continuously running on smart phones. In this paper, we implement an efficient and robust audio privacy preserving method that profiles the background audio to focus only on audio activities detected during recording for performance improvement, and to adapt to the noise for more accurate speech segmentation. We analyze the performance of our method using audio data collected by a smart watch in lab noisy settings. Our obfuscation results show a low false positive rate of 20% with a 92% true positive rate by adapting to the recording noise level. We also reduced model memory footprint and execution time of the method on a smart phone by 75% and 62% to enable continuous speech obfuscation.

Despite the prevalence of respiratory diseases, their diagnosis by clinicians is challenging. Accurately assessing airway sounds requires extensive clinical training and equipment that may not be easily available. Current methods that automate this diagnosis are hindered by their use of features that require pulmonary function tests. We leverage the audio characteristics of coughs to create classifiers that can distinguish common respiratory diseases in adults. Moreover, we build on recent advances in generative adversarial networks to augment our dataset with cleverly engineered synthetic cough samples for each class of major respiratory disease, to balance and increase our dataset size. We experimented on cough samples collected with a smartphone from 45 subjects in a clinic. Our CoughGAN-improved Support Vector Machine and Random Forest models show up to 76% test accuracy and 83% F1 score in classifying subjects' conditions between healthy and three major respiratory diseases. Adding our synthetic coughs improves the performance we can obtain from a relatively small unbalanced healthcare dataset by boosting the accuracy over 30%. Our data augmentation reduces overfitting and discourages the prediction of a single, dominant class. These results highlight the feasibility of automatic, cough-based respiratory disease diagnosis using smartphones or wearables in the wild.

Identifying the presence of sputum in the lung is essential in detection of diseases such as lung infection, pneumonia and cancer. Cough type classification (dry/wet) is an effective way of examining presence of lung sputum. This is traditionally done through physical exam in a clinical visit which is subjective and inaccurate. This work proposes an objective approach relying on the acoustic features of the cough sound. A total number of 5971 coughs (5242 dry and 729 wet) were collected from 131 subjects using Smartphone. The data was reviewed and annotated by a novel multi-layer labeling platform. The annotation kappa inter-rater agreement score is measured to be 0.81 and 0.37 for 1st and 2nd layer respectively. Sensitivity and specificity values of 88% and 86% are measured for classification between wet and dry coughs (highest across the literature).

Spirometry test, a measure of the patient's lung function, is the gold standard for diagnosis and monitoring of chronic pulmonary diseases. Spirometry is currently being done in hospital settings by having the patients blow the air out of their lungs forcefully and into the spirometer's tubes under the supervision and constant guidance of clinicians. This test is expensive, cumbersome and not easily applicable to every-day monitoring of these patients. The lung mechanism when performing a cough is very similar to when spirometry test is done. That includes a big inhalation, air compression and forceful exhalation. Therefore, it is reasonable to assume that obstruction of lung airways should have a similar effect on both cough features and spirometry measures. This paper explores the estimation of lung obstruction using cough acoustic features. A total number of 3695 coughs were collected from patients from 4 different conditions and 4 different severity categories along with their lung function measures in a clinical setting using a smartphone's microphone and a hospital-grade spirometry lab. After feature-set optimization and model hyperparameter tuning, the lung obstruction was estimated with MAE (Mean Absolute Error) of 8% for COPD and 9% for asthma populations. In addition to lung obstruction estimation, we were able to classify patients' disease state with 91% accuracy and patients' severity within each disease state with 95% accuracy.Clinical Relevance- This enables effort-independent estimation of lung function spirometry parameters which could potentially lead to passive monitoring of pulmonary patients.

Early detection of chronic diseases helps to minimize the disease impact on patient's health and reduce the economic burden. Continuous monitoring of such diseases helps in the evaluation of rehabilitation program effectiveness as well as in the detection of exacerbation. The use of everyday wearables i.e. chest band, smartwatch and smart band equipped with good quality sensor and light weight machine learning algorithm for the early detection of diseases is very promising and holds tremendous potential as they are widely used. In this study, we have investigated the use of acceleration, electrocardiogram, and respiration sensor data from a chest band for the evaluation of obstructive lung disease severity. Recursive feature elimination technique has been used to identity top 15 features from a set of 62 features including gait characteristics, respiration pattern and heart rate variability. A precision of 0.93, recall of 0.91 and F-1 score of 0.92 have been achieved with a support vector machine for the classification of severe patients from the non-severe patients in a data set of 60 patients. In addition, the selected features showed significant correlation with the percentage of predicted FEV1.Clinical Relevance- The study result indicates that wearable sensor data collected during natural walk can be used in the early evaluation of pulmonary patients thus enabling them to seek medical attention and avoid exacerbation. In addition, it may serve as a complementary tool for pulmonary patient evaluation during a 6-minute walk test.

Automatic cough detection using audio has advanced passive health monitoring on devices such as smart phones and wearables; it enables capturing longitudinal health data by eliminating user interaction and effort. One major issue arises when coughs from surrounding people are also detected; capturing false coughs leads to significant false alarms, excessive cough frequency, and thereby misdiagnosis of user condition. To address this limitation, in this paper, a method is proposed that creates a personal cough model of the primary subject using limited number of cough samples; the model is used by the automatic cough detection to verify whether the identified coughs match the personal pattern and belong to the primary subject. A Gaussian mixture model is trained using audio features from cough to implement the subject verification method; novel cough embeddings are learned using neural networks and integrated into the model to further improve the prediction accuracy. We analyze the performance of the method using our cough dataset collected by a smart phone in a clinical study. Population in the dataset involves subjects categorized of healthy or patients with COPD or Asthma, with the purpose of covering a wider range of pulmonary conditions. Cross-subject validation on a diverse dataset shows that the method achieves an average error rate of less than 10%, using a personal cough model generated by only 5 coughs from the primary subject.

Background Signal generation through data mining algorithms is an innovative and emerging field in pharmacovigilance. Early detection of safety signals is important for public health safety. However, the possibility of generating pseudo signals should not be overlooked. Objective Our study aimed to identify potential signals of aromatase inhibitors associated Osteonecrosis of Jaw and assess the possibilities of the safety signal to be a pseudo signal/false positive in FDA Adverse Event Reporting System (FAERS). Setting Spontaneously reported data in FAERS database. Methods Data for this study were obtained from the public release of data in FAERS. OpenVigil, a pharmacovigilance analytical tool was used to access FAERS data. Reporting Odds Ratio (ROR) was used to assess the relation between the drug and adverse event. A value of ROR-1.96SE  > 1, (SE-standard error) was considered positive. Main outcome measure Signal strength. Results FAERS database had a total of 15,178 reports for Osteonecrosis of Jaw. Amongst which 617 reports were associated with aromatase inhibitors. Signal strength ROR (lower bound of the 95% CI) for letrozole, anastrozole and exemestane associated Osteonecrosis of Jaw without any background correction was 8.34, 6.64 and 15.14 respectively. Upon removing the reports of concomitantly administered drugs (bisphosphonates and denosumab), signal strength drastically decreased to 0.03, 0.36 and 0.47 for letrozole, anastrozole and exemestane respectively. The signal strength of bisphosphonates and denosumab associated Osteonecrosis of Jaw was not changed significantly upon removal of aromatase inhibitors. Conclusion Our study concluded that the signal generated for aromatase inhibitors associated Osteonecrosis of Jaw in FAERS database can be false positive. Careful background corrections with identification of those risk factors are imperative to exclude false positive results.

Background: The United States Food and Drug Administration (FDA) has licensed three HPV (Human papilloma virus) vaccines. The centers for disease control and prevention (CDC) and advisory committee on immunization practices (ACIP) recommends routine HPV vaccination at age 11 or 12 years. This study aimed to summarize and characterize adverse events following HPV vaccination reported to VAERS database from July 2006 to May 2017., Methods: A systematic data mining was performed in the VAERS database for reports associated with HPV vaccine. Clinically relevant Vaccine Event Combinations (VEC) were identified in the VAERS database following HPV vaccination. A VEC was considered for analysis only if a minimum of hundred reports were present in database for the given Adverse Event (AE). The data mining algorithm used in this study was reporting odds ratio. A value of ROR-1.96SE >1 was considered as positive signal., Results: VAERS received 49444 reports after receipt of HPV vaccine during the study period. Out of 49444, 2307 unique reactions were identified. A total of 177 death reports and 3526 non death serious reactions were reported to VAERS. ROR showed positive signals for abdominal pain, syncope, dizziness, convulsion, abortion spontaneous, alopecia, amenorrhea, anogenital warts, cervical dysplasia, anaemia, dyskinesia, migrane, blood pressure decreased, fall, head injury, loss of consciousness, pallor, presyncope, seizures., Conclusion: The present analysis did not identify any new/unexpected safety concern and was consistent with the safety data from prelicensure trials. Further epidemiological studies are required to systematically validate the data provided by VAERS., Competing Interests: There are no conflicts of interest., (Copyright: © 2020 Perspectives in Clinical Research.)

We present novel voltage stimulation buffers with controlled output current, along with recording circuits featuring adjustable high-pass cut-off filtering to perform efficient stimulation while actively suppressing stimulation artifacts in high-density microelectrode arrays. Owing to the dense packing and close proximity of the electrodes in such systems, a stimulation through one electrode can cause large electrical artifacts on neighboring electrodes that easily saturate the corresponding recording amplifiers. To suppress such artifacts, the high-pass corner frequencies of all available 2048 recording channels can be raised from several Hz to several kHz by applying a "soft-reset" or pole-shifting technique. With the implemented artifact suppression technique, the saturation time of the recording circuits, connected to electrodes in immediate vicinity to the stimulation site, could be reduced to less than 150 μs. For the stimulation buffer, we developed a circuit, which can operate in two modes: either control of only the stimulation voltage or control of current and voltage during stimulation. The voltage-only controlled mode employs a local common-mode feedback operational transconductance amplifier with a near rail-to-rail input/output range, suitable for driving high-capacitive loads. The current/voltage controlled mode is based on a positive current conveyor generating adjustable output currents, whereas its upper and lower output voltages are limited by two feedback loops. The current/voltage controlled circuit can generate stimulation pulses up to 30 μA with less than ±0.1% linearity error in the low-current mode and up to 300 μA with less than ±0.2% linearity error in the high-current mode.

Background: In current clinical practice, regardless of the clinical guidelines, BZDs and Z drugs are used beyond the period of indication, resulting in undesirable effects. This study aimed to assess feasibility of deprescribing amongst patients utilizing BZDs and Z drugs inappropriately for longer duration than the prescribed period. The study also analysed the Quality of Sleep (QoS) and Cost Savings incurred amongst deprescribed patients., Methods: It was a prospective interventional study conducted in IP and OP settings of Psychiatry Department, Bangalore, India. Based on inclusion criteria, 109 patients were recruited for the study for a period of 7 months. Deprescribing was advised to inappropriate BZD and Z-drug users by clinical pharmacist after discussing with the prescribing psychiatrist. The patients were followed-up twice in a month after deprescribing. QoS was assessed by using Pittsburg Sleep Quality Index (PSQI) scale. The total medications cost incurred per patient/month before and after the intervention among both the groups was measured., Results: Post-intervention, 40(30.69%) BZD users were deprescribed i.e, either dose tapered 6(5.5%), completely ceased 27(24.8%) or on si opus sit (SOS) BZDs prescription 7(6.4%). A majority of 44(40.36%) patients continued BZDs according to the algorithm. Clonazepam 35(87.5%) was the most deprescribed BZD. Deprescribing of BZDs showed an association with QoS of patients, p-value (<0.05). A statistically significant cost reduction was observed after deprescribing BZDs, (Z = 5.465, p=<0.001)., Discussion: Deprescribing BZDs was associated with decline in its usage; implementing deprescribing practice amongst the inappropriate BZD users is feasible, provides an improved QoS and an economic benefit., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Advances in microfabrication technology have enabled the production of devices containing arrays of thousands of closely spaced recording electrodes, which afford subcellular resolution of electrical signals in neurons and neuronal networks. Rationalizing the electrode size and configuration in such arrays demands consideration of application-specific requirements and inherent features of the electrodes. Tradeoffs among size, spatial density, sensitivity, noise, attenuation, and other factors are inevitable. Although recording extracellular signals from neurons with planar metal electrodes is fairly well established, the effects of the electrode characteristics on the quality and utility of recorded signals, especially for small, densely packed electrodes, have yet to be fully characterized. Here, we present a combined experimental and computational approach to elucidating how electrode size, and size-dependent parameters, such as impedance, baseline noise, and transmission characteristics, influence recorded neuronal signals. Using arrays containing platinum electrodes of different sizes, we experimentally evaluated the electrode performance in the recording of local field potentials (LFPs) and extracellular action potentials (EAPs) from the following cell preparations: acute brain slices, dissociated cell cultures, and organotypic slice cultures. Moreover, we simulated the potential spatial decay of point-current sources to investigate signal averaging using known signal sources. We demonstrated that the noise and signal attenuation depend more on the electrode impedance than on electrode size, per se , especially for electrodes <10 μm in width or diameter to achieve high-spatial-resolution readout. By minimizing electrode impedance of small electrodes (<10 μm) via surface modification, we could maximize the signal-to-noise ratio to electrically visualize the propagation of axonal EAPs and to isolate single-unit spikes. Due to the large amplitude of LFP signals, recording quality was high and nearly independent of electrode size. These findings should be of value in configuring in vitro and in vivo microelectrode arrays for extracellular recordings with high spatial resolution in various applications.

Non-invasive electrical stimulation can be used to study and control neural activity in the brain or to alleviate somatosensory dysfunctions. One intriguing prospect is to precisely stimulate individual targeted neurons. Here, we investigated single-neuron current and voltage stimulation in vitro using high-density microelectrode arrays featuring 26,400 bidirectional electrodes at a pitch of 17.5 μm and an electrode area of 5 × 9 μm 2 . We determined optimal waveforms, amplitudes and durations for both stimulation modes. Owing to the high spatial resolution of our arrays and the close proximity of the electrodes to the respective neurons, we were able to stimulate the axon initial segments (AIS) with charges of less than 2 pC. This resulted in minimal artifact production and reliable readout of stimulation efficiency directly at the soma of the stimulated cell. Stimulation signals as low as 70 mV or 100 nA, with pulse durations as short as 18 μs, yielded measurable action potential initiation and propagation. We found that the required stimulation signal amplitudes decreased with cell growth and development and that stimulation efficiency did not improve at higher electric fields generated by simultaneous multi-electrode stimulation.

Background: The signal is defined as "reported information on a possible causal relationship between an adverse event and a drug, of which the relationship is unknown or incompletely documented previously"., Objective: To detect novel adverse events of iloperidone by disproportionality analysis in FDA database of Adverse Event Reporting System (FAERS) using Data Mining Algorithms (DMAs)., Methodology: The US FAERS database consists of 1028 iloperidone associated Drug Event Combinations (DECs) which were reported from 2010 Q1 to 2016 Q3. We consider DECs for disproportionality analysis only if a minimum of ten reports are present in database for the given adverse event and which were not detected earlier (in clinical trials). Two data mining algorithms, namely, Reporting Odds Ratio (ROR) and Information Component (IC) were applied retrospectively in the aforementioned time period. A value of ROR-1.96SE>1 and IC- 2SD>0 were considered as the threshold for positive signal., Results: The mean age of the patients of iloperidone associated events was found to be 44years [95% CI: 36-51], nevertheless age was not mentioned in twenty-one reports. The data mining algorithms exhibited positive signal for akathisia (ROR-1.96SE=43.15, IC-2SD=2.99), dyskinesia (21.24, 3.06), peripheral oedema (6.67,1.08), priapism (425.7,9.09) and sexual dysfunction (26.6-1.5) upon analysis as those were well above the pre-set threshold., Conclusion: Iloperidone associated five potential signals were generated by data mining in the FDA AERS database. The result requires an integration of further clinical surveillance for the quantification and validation of possible risks for the adverse events reported of iloperidone., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

A monolithic multi-functional CMOS microelectrode array system was developed that enables label-free electrochemical impedance spectroscopy of cells in vitro at high spatiotemporal resolution. The electrode array includes 59,760 platinum microelectrodes, densely packed within a 4.5 mm × 2.5 mm sensing region at a pitch of 13.5 μm. A total of 32 on-chip lock-in amplifiers can be used to measure the impedance of any arbitrarily chosen subset of electrodes in the array. A sinusoidal voltage, generated by an on-chip waveform generator with a frequency range from 1 Hz to 1 MHz, was applied to the reference electrode. The sensing currents through the selected recording electrodes were amplified, demodulated, filtered, and digitized to obtain the magnitude and phase information of the respective impedances. The circuitry consumes only 412 μW at 3.3 V supply voltage and occupies only 0.1 mm 2 , for each channel. The system also included 2048 extracellular action-potential recording channels on the same chip. Proof of concept measurements of electrical impedance imaging and electrophysiology recording of cardiac cells and brain slices are demonstrated in this paper. Optical and impedance images showed a strong correlation.

This paper describes a novel methodology leveraging particle filters for the application of robust heart rate monitoring in the presence of motion artifacts. Motion is a key source of noise that confounds traditional heart rate estimation algorithms for wearable sensors due to the introduction of spurious artifacts in the signals. In contrast to previous particle filtering approaches, we formulate the heart rate itself as the only state to be estimated, and do not rely on multiple specific signal features. Instead, we design observation mechanisms to leverage the known steady, consistent nature of heart rate variations to meet the objective of continuous monitoring of heart rate using wearable sensors. Furthermore, this independence from specific signal features also allows us to fuse information from multiple sensors and signal modalities to further improve estimation accuracy. The signal processing methods described in this work were tested on real motion artifact affected electrocardiogram and photoplethysmogram data with concurrent accelerometer readings. Results show promising average error rates less than 2 beats/min for data collected during intense running activities. Furthermore, a comparison with contemporary signal processing techniques for the same objective shows how the proposed implementation is also computationally more efficient for comparable performance.

Persisting embryonal infundibular recess (PEIR) is a rare anomaly of the development of the posterior pituitary wherein there is a defect in the third ventricular floor. Earlier reports have found PEIR descending only up to the sella. However, this is the first case of PEIR presenting as a pulsatile nasal mass. A 35-year-old female presented to the otorhinolaryngologist with hyposmia. Diagnostic nasal endoscopy revealed a pulsatile nasal mass. Magnetic resonance imaging revealed a cystic lesion extending from the third ventricular floor to the nasal cavity. There was no associated hydrocephalus or empty sella. The case was successfully managed by the endoscopic endonasal transsphenoidal approach., Competing Interests: There are no conflicts of interest.

Background: Levonorgestrel is most commonly utilized as an emergency oral contraceptive. Little is known and/or studied about the adverse effects of levonorgestrel, therefore, current investigation was aimed to generate signal for unreported adverse drug reactions of levonorgestrel using disproportionality analysis in food and drug administration adverse events reporting system database., Methods: In FDA Adverse Events Reporting System (FAERS) database, all adverse event reports for levonorgestrel between January 2006 to June 2015 were identified and disproportionality analysis was conducted for selected adverse events of levonorgestrel using Reporting Odds Ratio, Proportional Reporting Ratio and Information Component with 95% confidence interval., Results: A disproportionality analysis was done for 15 adverse events of levonorgestrel; out of these, signal for 10 adverse events was found and among them menstruation delayed was reported maximum (1791), followed by pregnancy after post-coital contraception (942), breast tenderness (901), metrorrhagia (899), dysmenorrhea (822), menorrhagia (541), nipple disorder (141), breast enlargement (77), ectopic pregnancy (61) and premenstrual syndrome (35). Pregnancy after post-coital contraception showed the highest signal having the Information Component value of 129.2, Reporting Odds Ratio value of 6.51 and Proportional Reporting Ratio value of 6.49., Conclusion: In this paper, ten novel AEs were identified that were disproportionately reported with the use of LNG by using data mining techniques. Although a causal relationship cannot be established, the number of cases reported suggests that there might be an association. If confirmed by epidemiologic studies, the findings from this study would have potential implications for the use of LNG and patient management in clinical practice., Competing Interests: Conflict of Interest Nil.

Metabolic reprogramming of the tumor microenvironment is recognized as a cancer hallmark. To identify new molecular processes associated with tumor metabolism, we analyzed the transcriptome of bulk and flow-sorted human primary non-small cell lung cancer (NSCLC) together with 18 FDG-PET scans, which provide a clinical measure of glucose uptake. Tumors with higher glucose uptake were functionally enriched for molecular processes associated with invasion in adenocarcinoma and cell growth in squamous cell carcinoma (SCC). Next, we identified genes correlated to glucose uptake that were predominately overexpressed in a single cell-type comprising the tumor microenvironment. For SCC, most of these genes were expressed by malignant cells, whereas in adenocarcinoma, they were predominately expressed by stromal cells, particularly cancer-associated fibroblasts (CAF). Among these adenocarcinoma genes correlated to glucose uptake, we focused on glutamine-fructose-6-phosphate transaminase 2 ( GFPT2 ), which codes for the glutamine-fructose-6-phosphate aminotransferase 2 (GFAT2), a rate-limiting enzyme of the hexosamine biosynthesis pathway (HBP), which is responsible for glycosylation. GFPT2 was predictive of glucose uptake independent of GLUT1, the primary glucose transporter, and was prognostically significant at both gene and protein level. We confirmed that normal fibroblasts transformed to CAF-like cells, following TGFβ treatment, upregulated HBP genes, including GFPT2 , with less change in genes driving glycolysis, pentose phosphate pathway, and TCA cycle. Our work provides new evidence of histology-specific tumor stromal properties associated with glucose uptake in NSCLC and identifies GFPT2 as a critical regulator of tumor metabolic reprogramming in adenocarcinoma. Significance: These findings implicate the hexosamine biosynthesis pathway as a potential new therapeutic target in lung adenocarcinoma. Cancer Res; 78(13); 3445-57. ©2018 AACR ., (©2018 American Association for Cancer Research.)

Although the mechanisms of recording bioelectrical signals from different types of electrogenic cells (neurons, cardiac cells etc.) by means of planar metal electrodes have been extensively studied, the recording characteristics and conditions for very small electrode sizes are not yet established. Here, we present a combined experimental and computational approach to elucidate, how the electrode size influences the recorded signals, and how inherent properties of the electrode, such as impedance, noise, and transmission characteristics shape the signal. We demonstrate that good quality recordings can be achieved with electrode diameters of less than 10 µm, provided that impedance reduction measures have been implemented and provided that a set of requirements for signal amplification has been met.

Background: Signal detection is one of the most advanced and emerging field in pharmacovigilance. It is a modern method of detecting new reaction (which can be desired or undesired) of a drug. It facilitates early adverse drug reaction detection which enables health professionals to identify adverse events that may not have been identified in pre-marketing clinical trials. Vortioxetine, the first mixed serotonergic antidepressant was initially approved by the US Food and Drug Administration (USFDA) on September 30, 2013 for the treatment of adults with Major Depressive Disorder (MDD). This study was to identify the signal strength for vortioxetine associated ADRs using data mining technique in USFDA Adverse Event Reporting System (AERS) database., Methodology: Most commonly used three data mining algorithms, Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR) and Information Component (IC) were selected for the study and they were applied retrospectively in USFDA AERS database from 2015Q1 to 2016Q3. A value of ROR-1.96SE >1, PRR≥2, IC- 2SD>0 were considered as the positive signal., Result: A study population of 61,22,000 were reported all over the world. Among which 3481 reactions were associated with vortioxetine which comprised of 632 unique events encompassed with 27 clinically relevant reactions. ROR, PRR and IC showed positive signal for weight loss, agitation, anger, ketoacidosis, insomnia and abnormal dreams., Conclusion: The present study suggests that vortioxetine may result in these adverse events. Further pharmacoepidemiologic studies are necessary to confirm this conclusion and to improve the precision of the prevalence and/or the risk factors of this ADRs., (Copyright © 2017 Elsevier B.V. All rights reserved.)

In this work we explore the viability of a multimodal sensing device that can be integrated in a wearable form factor for daily, non-invasive ambulatory blood pressure (BP) monitoring. A common approach in previous research has been to rely on measuring the pulse transit time (PTT), which has been shown to be correlated with the BP. In this work, we look into the feasibility of measuring PTT using sensors separated by a small distance on one arm so that any eventual realization of the system is convenient to wear and use over long periods of time. Moreover, we investigate the combined use of two different modalities for cardiovascular measurement: the optical photoplethysmogram (PPG) as well as the bio-potential based impedance (Bio-Z) measurement. These two modalities have been previously only studied on their own or in conjunction with the electrocardiogram (ECG) for the purpose of estimating PTT. We measure the PTT from the wrist to the finger using Bio-Z and PPG sensors, and compare it to the conventional PTT measured from the ECG to PPG at the finger, in order to prove that it can be an effective replacement for existing PTT measurement strategies. Moreover, successful measurement of PTT with two different modalities of sensors at close proximity will allow designs with multiple heterogeneous sensors on a more versatile wearable sensing platform that is optimized for power and is more robust to environmental or skin contact changes. This will enable the next generation of smart watches that capture PTT and BP. Experiments were conducted in vivo with simultaneous ECG, Bio-Z and PPG sensors, and results indicate that the PTT calculated from the Bio-Z and PPG sensors placed at a close distance correlates well with the more established PTT measurement using the ECG in conjunction with PPG, with correlation coefficient as high as 0.92.

We present a CMOS-based high-density microelectrode array (HD-MEA) system that enables high-density mapping of brain slices in-vitro with multiple readout modalities. The 4.48×2.43 mm 2 array consists of 59,760 micro-electrodes at 13.5 µm pitch (5487 electrodes/mm 2 ). The overall system features 2048 action-potential, 32 local-field-potential and 32 current recording channels, 32 impedance-measurement and 28 neurotransmitter-detection channels and 16 voltage/current stimulation channels. The system enables real-time and label-free monitoring of position, size, morphology and electrical activity of brain slices.

Biological cells are characterized by highly complex phenomena and processes that are, to a great extent, interdependent. To gain detailed insights, devices designed to study cellular phenomena need to enable tracking and manipulation of multiple cell parameters in parallel; they have to provide high signal quality and high spatiotemporal resolution. To this end, we have developed a CMOS-based microelectrode array system that integrates six measurement and stimulation functions, the largest number to date. Moreover, the system features the largest active electrode array area to date (4.48×2.43 mm 2 ) to accommodate 59,760 electrodes, while its power consumption, noise characteristics, and spatial resolution (13.5 μm electrode pitch) are comparable to the best state-of-the-art devices. The system includes: 2,048 action-potential (AP, bandwidth: 300 Hz to 10 kHz) recording units, 32 local-field-potential (LFP, bandwidth: 1 Hz to 300 Hz) recording units, 32 current recording units, 32 impedance measurement units, and 28 neurotransmitter detection units, in addition to the 16 dual-mode voltage-only or current/voltage-controlled stimulation units. The electrode array architecture is based on a switch matrix, which allows for connecting any measurement/stimulation unit to any electrode in the array and for performing different measurement/stimulation functions in parallel.

A monolithic measurement platform was implemented to enable label-free in-vitro electrical impedance spectroscopy measurements of cells on multi-functional CMOS microelectrode array. The array includes 59,760 platinum microelectrodes, densely packed within a 4.5 mm × 2.5 mm sensing region at a pitch of 13.5 μm. The 32 on-chip lock-in amplifiers can be used to measure the impedance of any arbitrarily chosen electrodes on the array by applying a sinusoidal voltage, generated by an on-chip waveform generator with a frequency range from 1 Hz to 1 MHz, and measuring the respective current. Proof-of-concept measurements of impedance sensing and imaging are shown in this paper. Correlations between cell detection through optical microscopy and electrochemical impedance scanning were established.

Here, we present 2048 low-noise, low-offset, and low-power action-potential recording channels, integrated in a multi-functional high-density microelectrode array. A resistively loaded open-loop topology has been adapted for the first-stage amplifier to achieve 2.4 µVrms noise levels at low power consumption. Two novel pseudo-resistor structures have been used to realize very low HPF corner frequencies with small variations across all channels. The adjustability of pseudo resistors has been exploited to realize a "soft" reset technique that suppresses stimulation artifacts so that the amplifiers can recover from saturation within 200 µs. The chips were fabricated in a 0.18 µm 6M1P CMOS process, and measurement results are presented to show the performance of the proposed circuit structures and techniques.