Association of cardiovascular disease with health-related quality of life among older women with early-stage breast cancer undergoing adjuvant endocrine therapy.

INTRODUCTION: Due to the improved overall survival and life expectancy of older women with breast cancer, cardiovascular disease (CVD) arose as the primary cause of non-cancer-related deaths in this population. Therefore, assessing the health-related quality of life (HRQoL) of breast cancer patients with comorbid CVD is becoming increasingly vital. Our study aimed to evaluate the association between comorbid CVD and HRQoL among older women with early-stage breast cancer who are receiving adjuvant endocrine therapy (AET) in the United States. MATERIALS AND METHODS: We conducted a retrospective cohort study using the 2006-2017 Surveillance, Epidemiology, and End Results-Medicare Health Outcomes Survey data. We identified female patients over the age of 65 who were diagnosed with stage I-III hormone receptor-positive breast cancer and treated with AET. HRQoL was assessed by the physical and mental component summary (PCS & MCS) in the health survey. CVD was defined as a history of acute myocardial infarction (AMI), congestive heart failure (CHF), angina, stroke, or other heart-related conditions. We performed multivariate linear regression models while controlling for covariates. RESULTS: Among 3,904 older women, a history of CHF [ß = -1.97, p = 0.025], stroke [ß = -3.00, p < 0.010], or other heart-related condition [ß = -1.10, p = 0.046] was significantly associated with lower PCS. However, no significant differences in PCS scores were found between women with a history of AMI or angina and those without these conditions. Having a history of CHF [ß = -1.72, p = 0.033] or stroke [ß = -1.48, p = 0.038] was significantly associated with lower MCS, whereas a history of angina, AMI, or other heart conditions was not associated with significant differences in MCS. Our study did not observe any significant differences in PCS and MCS between the two types AETs. DISCUSSION: The study found that older women with early-stage breast cancer who were being treated with AETs had a lower HRQoL if they had a history of CHF or stroke. These comorbidities were identified as strong predictors for decreased HRQoL. The findings highlight the significance of managing cardiovascular diseases in such patients for better HRQoL while they receive AET treatment.

Use of machine learning to predict bladder cancer survival outcomes: a systematic literature review.

INTRODUCTION: The objective of this systematic review is to summarize the use of machine learning (ML) in predicting overall survival (OS) in patients with bladder cancer. METHODS: Search terms for bladder cancer, ML algorithms, and mortality were used to identify studies in PubMed and Web of Science as of February 2022. Notable inclusion/exclusion criteria contained the inclusion of studies that utilized patient-level datasets and exclusion of primary gene expression-related dataset studies. Study quality and bias were assessed using the International Journal of Medical Informatics (IJMEDI) checklist. RESULTS: Of the 14 included studies, the most common algorithms were artificial neural networks (n = 8) and logistic regression (n = 4). Nine articles described missing data handling, with five articles removing patients with missing data entirely. With respect to feature selection, the most common sociodemographic variables were age (n = 9), gender (n = 9), and smoking status (n = 3), with clinical variables most commonly including tumor stage (n = 8), grade (n = 7), and lymph node involvement (n = 6). Most studies (n = 10) were of medium IJMEDI quality, with common areas of improvement being the descriptions of data preparation and deployment. CONCLUSIONS: ML holds promise for optimizing bladder cancer care through accurate OS predictions, but challenges related to data processing, feature selection, and data source quality must be resolved to develop robust models. While this review is limited by its inability to compare models across studies, this systematic review will inform decision-making by various stakeholders to improve understanding of ML-based OS prediction in bladder cancer and foster interpretability of future models.

An analysis type known as machine learning has recently become popular to predict survival in bladder cancer patients. However, there is debate on how to best use this method, as well as how to report the results of studies. This review looks at recently published machine learning studies, comparing various model details. Most studies found used hospital data, were clear about model factors, and used a model type called artificial neural networks. While these studies may be better at prediction compared to previous methods, there are consistency and clarity issues. Future studies should ensure that models are explainable and relevant to healthcare leaders.

A systematic review of economic evaluations of tyrosine kinase inhibitors for non-small cell lung cancer (NSCLC).

INTRODUCTION: Although tyrosine kinase inhibitors (TKIs) have improved the efficacy of treatment for non-small cell lung cancer (NSCLC), the accessibility of TKIs is limited due to high costs. Despite the critical role of the cost-effectiveness of TKIs on decision-making, no systematic reviews have compared the cost-effectiveness of comparable TKIs. Therefore, we systemically reviewed the economic evaluation studies on various TKIs for NSCLC. AREAS COVERED: We searched PubMed and the Cochran Library to identify the published economic evaluation studies of TKIs in NSCLC patients that were published by January 2022. All of the included studies (n = 38) evaluated the cost-effectiveness of epidermal growth factor receptor (EGFR)-TKIs (n = 29) or anaplastic lymphocyte kinase (ALK)-TKIs (n = 9). The cost-effectiveness results were reported as the incremental cost-effectiveness ratio per quality-adjusted life-year, except for three studies. EXPERT OPINION: We found that the economic evaluation studies of the first and second generation of EGFR-TKIs and ALK-TKIs varied by the country and study settings, such as comparator and input parameters. In 12 studies, osimertinib (EGFR-TKI) was not cost-effective compared to other first/second EGFR-TKIs, regardless of the study settings. More evidence can be provided about cost-effectiveness of the third-generation TKIs in future research.

Patterns and predictors of oral antipsychotic prescribing in adult patients with schizophrenia.

Background: Evidence increasingly suggests minimal differences in efficacy between oral antipsychotics for the pharmacologic treatment of schizophrenia. As a result, newer treatment guidelines avoid an algorithmic approach to antipsychotic selection and recommend treatment be determined on a case-by-case basis. Objective: To determine patterns and predictors of oral antipsychotic prescribing for adults diagnosed with schizophrenia. Methods: This is a retrospective, cross-sectional study using data from the National Ambulatory Medical Survey (NAMCS) from 2005 to 2016 and 2018. Treatment options were defined as a first-generation antipsychotic (FGA), second-generation antipsychotic (SGA), or no antipsychotic. Multivariable logistic regression analysis was conducted to identify predictors of antipsychotic treatment, adjusting for predisposing, enabling, and need factors. Results: The final study sample consisted of visits by 38,403 adults (unweighted n = 1932; age ≥ 18) diagnosed with schizophrenia in the United States. Risperidone, olanzapine, and quetiapine were the most prescribed antipsychotics. Patients ≥65 years old were half as likely to be prescribed an SGA versus no antipsychotic (OR 0.44, 95% CI [0.31, 0.61]). Patients with a higher number of chronic conditions also had lower odds of being prescribed an SGA or FGA versus no antipsychotic (OR 0.98 [0.97, 0.99]; OR [0.96 [0.96, 0.99]), while patients prescribed a higher number of medications had higher odds of being prescribed an SGA versus no antipsychotic (OR 1.2, 95% CI [1.1, 1.4]). Conclusions: Multiple factors were associated with prescribing an SGA or FGA versus no antipsychotic, but no factors were associated with prescribing an SGA versus FGA. Future studies are needed to determine the reasoning behind differences in antipsychotic prescribing.

Economic Burden of Chronic Comorbidities Among Community-Dwelling Older Adults With Dementia: A Propensity Score Matched National-Level Study.

OBJECTIVE: This study examined the extent to which chronic comorbidities contribute to excess health care expenditures between older adults with dementia and propensity score (PS)-matched nondementia controls. METHODS: This was a retrospective, cross-sectional, PS-matched case (dementia): control (nondementia) study of older adults (65 y or above) using alternative years data from pooled 2005 to 2015 Medical Expenditure Panel Surveys (MEPS). Chronic comorbidities were identified based on Clinical Classifications System or ICD-9-CM codes. Ordinary least squares regression was utilized to quantify the impact of chronic comorbidities on the excess expenditures with logarithmic transformation. Expenditures were expressed as 2019 US dollars. All analyses accounted for the complex survey design of MEPS. RESULTS: The mean yearly home health care expenditures were particularly higher among older adults with dementia and co-occurring anemia, eye disorders, hyperlipidemia, and hypertension compared with PS-matched controls. Ordinary least squares regression models revealed that home health care expenditures were 131% higher (ß=0.837, P <0.001) among older adults with dementia compared with matched nondementia controls before adjusting for chronic comorbidities. When additionally adjusting for chronic comorbidities, the percentage increase, while still significant ( P <0.001) decreased from 131% to 102%. CONCLUSIONS: The excess home health care expenditures were partially explained by chronic comorbidities among community-dwelling older adults with dementia.

On-chip metal/polypyrrole quasi-reference electrodes for robust ISFET operation.

To operate an ion-sensitive field-effect transistor (ISFETs) it is necessary to set the electrolyte potential using a reference electrode. Conventional reference electrodes are bulky, fragile, and too big for applications where the electrolyte volume is small. Several researchers have proposed tackling this issue using a solid-state planar micro-reference electrode or a reference field-effect transistor. However, these approaches are limited by poor robustness, high cost, or complex integration with other microfabrication processes. Here we report a simple method to create robust on-chip quasi-reference electrodes by electrodepositing polypyrrole on micro-patterned metal leads. The electrodes were fabricated through the polymerization of pyrrole on patterned metals with a cyclic voltammetry process. Open circuit potential measurements were performed to characterize the polypyrrole electrode performance, demonstrating good stability (±1 mV), low drift (∼1 mV h(-1)), and reduced pH response (5 mV per pH). In addition, the polypyrrole deposition was repeated in microelectrodes made of different metals to test compatibility with standard complementary metal-oxide-semiconductor (CMOS) processes. Our results suggest that nickel, a metal commonly used in semiconductor foundries for silicide formation, is a good candidate to form the polypyrrole quasi-reference electrodes. Finally, the polypyrrole microelectrodes were used to operate foundry fabricated ISFETs. These experiments demonstrated that transistors biased with polypyrrole electrodes have pH sensitivity and resolution comparable to ones that are biased with standard reference electrodes. Therefore, the simple fabrication, high compatibility, and robust electrical performance make polypyrrole an ideal choice for the fabrication of outstanding microreference electrodes that enable robust and sensitive operation of multiple ISFET sensors on a chip.

Electronic desalting for controlling the ionic environment in droplet-based biosensing platforms.

The ability to control the ionic environment in saline waters and aqueous electrolytes is useful for desalination as well as electronic biosensing. We demonstrate a method of electronic desalting at micro-scale through on-chip micro electrodes. We show that, while desalting is limited in bulk solutions with unlimited availability of salts, significant desalting of ≥1 mM solutions can be achieved in sub-nanoliter volume droplets with diameters of ∼250 µm. Within these droplets, by using platinum-black microelectrodes and electrochemical surface treatments, we can enhance the electrode surface area to achieve >99% and 41% salt removal in 1 mM and 10 mM salt concentrations, respectively. Through self-consistent simulations and experimental measurements, we demonstrate that conventional double-layer theory over-predicts the desalting capacity and, hence, cannot be used to model systems that are mass limited or undergoing significant salt removal from the bulk. Our results will provide a better understanding of capacitive desalination, as well as a method for salt manipulation in high-throughput droplet-based microfluidic sensing platforms.

Enhanced biosensing resolution with foundry fabricated individually addressable dual-gated ISFETs.

The adaptation of semiconductor technologies for biological applications may lead to a new era of inexpensive, sensitive, and portable diagnostics. At the core of these developing technologies is the ion-sensitive field-effect transistor (ISFET), a biochemical to electrical transducer with seamless integration to electronic systems. We present a novel structure for a true dual-gated ISFET that is fabricated with a silicon-on-insulator (SOI) complementary metal-oxide-semiconductor process by Taiwan Semiconductor Manufacturing Company (TSMC). In contrast to conventional SOI ISFETs, each transistor has an individually addressable back-gate and a gate oxide that is directly exposed to the solution. The elimination of the commonly used floating gate architecture reduces the chance of electrostatic discharge and increases the potential achievable transistor density. We show that when operated in a "dual-gate" mode, the transistor response can exhibit sensitivities to pH changes beyond the Nernst limit. This enhancement in sensitivity was shown to increase the sensor's signal-to-noise ratio, allowing the device to resolve smaller pH changes. An improved resolution can be used to enhance small signals and increase the sensor accuracy when monitoring small pH dynamics in biological reactions. As a proof of concept, we demonstrate that the amplified sensitivity and improved resolution result in a shorter detection time and a larger output signal of a loop-mediated isothermal DNA amplification reaction (LAMP) targeting a pathogenic bacteria gene, showing benefits of the new structure for biosensing applications.

Electrical detection of nucleic acid amplification using an on-chip quasi-reference electrode and a PVC REFET.

Electrical detection of nucleic acid amplification through pH changes associated with nucleotide addition enables miniaturization, greater portability of testing apparatus, and reduced costs. However, current ion-sensitive field effect transistor methods for sensing nucleic acid amplification rely on establishing the fluid gate potential with a bulky, difficult to microfabricate reference electrode that limits the potential for massively parallel reaction detection. Here we demonstrate a novel method of utilizing a microfabricated solid-state quasi-reference electrode (QRE) paired with a pH-insensitive reference field effect transistor (REFET) for detection of real-time pH changes. The end result is a 0.18 µm, silicon-on-insulator, foundry-fabricated sensor that utilizes a platinum QRE to establish a pH-sensitive fluid gate potential and a PVC membrane REFET to enable pH detection of loop mediated isothermal amplification (LAMP). This technique is highly amendable to commercial scale-up, reduces the packaging and fabrication requirements for ISFET pH detection, and enables massively parallel droplet interrogation for applications, such as monitoring reaction progression in digital PCR.

Electrical detection of dsDNA and polymerase chain reaction amplification.

Food-borne pathogens and food safety-related outbreaks have come to the forefront over recent years. Estimates on the annual cost of sicknesses, hospitalizations, and deaths run into the billions of dollars. There is a large body of research on detection of food-borne pathogens; however, the widely accepted current systems are limited by costly reagents, lengthy time to completion, and expensive equipment. Our aim is to develop a label-free method for determining a change in DNA concentration after a PCR assay. We first used impedance spectroscopy to characterize the change in concentration of purified DNA in deionized water within a microfluidic biochip. To adequately measure the change in DNA concentration in PCR solution, it was necessary to go through a purification and precipitation step to minimize the effects of primers, PCR reagents, and excess salts. It was then shown that the purification and precipitation of the fully amplified PCR reaction showed results similar to the control tests performed with DNA in deionized water. We believe that this work has brought label free electrical biosensors for PCR amplification one step closer to reality.

Rapid thermal lysis of cells using silicon-diamond microcantilever heaters.

This paper presents the design and application of microcantilever heaters for biochemical applications. Thermal lysis of biological cells was demonstrated as a specific example. The microcantilever heaters, fabricated from selectively doped single crystal silicon, provide local resistive heating with highly uniform temperature distribution across the cantilevers. Very importantly, the microcantilever heaters were coated with a layer of 100 nm thick electrically insulating ultrananocrystalline diamond (UNCD) layer used for cell immobilization on the cantilever surface. Fibroblast cells or bacterial cells were immobilized on the UNCD/cantilever surfaces and thermal lysis was demonstrated via optical fluorescence microscopy. Upon electrical heating of the cantilever structures to 93 degrees C for 30 seconds, fibroblast cell and nuclear membrane were compromised and the cells were lysed. Over 90% of viable bacteria were also lysed after 15 seconds of heating at 93 degrees C. This work demonstrates the utility of silicon-UNCD heated microcantilevers for rapid cell lysis and forms the basis for other rapid and localized temperature-regulated microbiological experiments in cantilever-based lab on chip applications.

PCR-based detection in a micro-fabricated platform.

We present a novel, on-chip system for the electrokinetic capture of bacterial cells and their identification using the polymerase chain reaction (PCR). The system comprises a glass-silicon platform with a set of micro-channels, -chambers, and -electrodes. A platinum thin film resistor, placed in the proximity of the chambers, is used for temperature monitoring. The whole chip assembly is mounted on a Printed Circuit Board (PCB) and wire-bonded to it. The PCB has an embedded heater that is utilized for PCR thermal cycle and is controlled by a Lab-View program. Similar to our previous work, one set of electrodes on the chip inside the bigger chamber (0.6 microl volume) is used for diverting bacterial cells from a flowing stream into to a smaller chamber (0.4 nl volume). A second set of interdigitated electrodes (in smaller chamber) is used to actively trap and concentrate the bacterial cells using dielectrophoresis (DEP). In the presence of the DEP force, with the cells still entrapped in the micro-chamber, PCR mix is injected into the chamber. Subsequently, PCR amplification with SYBR Green detection is used for genetic identification of Listeria monocytogenes V7 cells. The increase in fluorescence is recorded with a photomultiplier tube module mounted over an epifluorescence microscope. This integrated micro-system is capable of genetic amplification and identification of as few as 60 cells of L. monocytogenes V7 in less than 90 min, in 600 nl volume collected from a sample of 10(4) cfu ml(-1). Specificity trials using various concentrations of L. monocytogenes V7, Listeria innocua F4248, and Escherichia coli O157:H7 were carried out successfully using two different primer sets specific for a regulatory gene of L. monocytogenes, prfA and 16S rRNA primer specific for the Listeria spp., and no cross-reactivity was observed.

Cell detection and counting through cell lysate impedance spectroscopy in microfluidic devices.

Cell-based microfluidic devices have attracted interest for a wide range of applications. While optical cell counting and flow cytometry-type devices have been reported extensively, sensitive and efficient non-optical methods to detect and quantify cells attached over large surface areas within microdevices are generally lacking. We describe an electrical method for counting cells based on the measurement of changes in conductivity of the surrounding medium due to ions released from surface-immobilized cells within a microfluidic channel. Immobilized cells are lysed using a low conductivity, hypotonic media and the resulting change in impedance is measured using surface patterned electrodes to detect and quantify the number of cells. We found that the bulk solution conductance increases linearly with the number of isolated cells contributing to solution ion concentration. The method of cell lysate impedance spectroscopy is sensitive enough to detect 20 cells microL(-1), and offers a simple and efficient method for detecting and enumerating cells within microfluidic devices for many applications including measurement of CD4 cell counts in HIV patients in resource-limited settings. To our knowledge, this is the most sensitive approach using non-optical setups to enumerate immobilized cells. The microfluidic device, capable of isolating specific cell types from a complex bio-fluidic and quantifying cell number, can serve as a single use cartridge for a hand-held instrument to provide simple, fast and affordable cell counting in point-of-care settings.

Electrical detection of germination of viable model Bacillus anthracis spores in microfluidic biochips.

In this paper, we present a new impedance-based method to detect viable spores by electrically detecting their germination in real time within microfluidic biochips. We used Bacillus anthracis Sterne spores as the model organism. During germination, the spores release polar and ionic chemicals, such as dipicolinic acid (DPA), calcium ions, phosphate ions, and amino acids, which correspondingly increase the electrical conductivity of the medium in which the spores are suspended. We first present macro-scale measurements demonstrating that the germination of spores can be electrically detected at a concentration of 10(9) spores ml(-1) in sample volumes of 5 ml, by monitoring changes in the solution conductivity. Germination was induced by introducing an optimized germinant solution consisting of 10 mM L-alanine and 2 mM inosine. We then translated these results to a micro-fluidic biochip, which was a three-layer device: one layer of polydimethylsiloxane (PDMS) with valves, a second layer of PDMS with micro-fluidic channels and chambers, and the third layer with metal electrodes deposited on a pyrex substrate. Dielectrophoresis (DEP) was used to trap and concentrate the spores at the electrodes with greater than 90% efficiency, at a solution flow rate of 0.2 microl min(-1) with concentration factors between 107-109 spores ml(-1), from sample volumes of 1-5 microl. The spores were captured by DEP in deionized water within 1 min (total volume used ranged from 0.02 microl to 0.2 microl), and then germinant solution was introduced to the flow stream. The detection sensitivity was demonstrated to be as low as about a hundred spores in 0.1 nl, which is equivalent to a macroscale detection limit of approximately 10(9) spores ml(-1). We believe that this is the first demonstration of this application in microfluidic and BioMEMS devices.

Performance evaluation of a low conductive growth medium (LCGM) for growth of healthy and stressed Listeria monocytogenes and other common bacterial species.

The performance of a low conductive growth medium (LCGM) (conductivity of <1300 microS) was evaluated for its ability to support growth of food borne bacterial pathogens including Listeria monocytogenes and to determine the expression of the two key virulence proteins in L. monocytogenes for possible applications in an impedance-based microfluidic biochip detection platform. Growth of Listeria was monitored spectrophotometrically and the lag phase, generation time, growth rate and maximum population density were determined using the Gompertz equation. LCGM had a lag phase of 2.3 h and showed a higher cell density compared to Luria Bertini (LB) broth. Length of lag phase was highly dependent on initial inoculum concentrations. The changes in conductivity with respect to growth in the low conductive medium were monitored using a conductivity probe. L. monocytogenes growth could be detected within 2 h (0.1 mS) in LCGM and within 6 h in LB. The performance of the media was also evaluated for the recovery of Listeria cells exposed to various stresses as 42 degrees C for 1, 2 or 6 h, an osmotic stress in 10.5% NaCl, an acidic stress at pH 2, 3 or 5 and a combined stress of 10.5% NaCl, pH 5 and 1 h exposure at 42 degrees C. The recovery rate was comparable with that of Tryptic soy broth containing yeast extract (TSBYE). L. monocytogenes in LCGM supported the expression of two key virulence markers, actin polymerization protein (ActA) and internalin B (InlB), which could be detected using specific antibodies. In general LCGM also supported the growth of several other bacterial species suggesting its implication in microbial quality monitoring of products. In conclusion, LCGM is a sensitive low conductive medium that supports the growth as well as the expression of virulence markers for potential applications in sensitive detection of L. monocytogenes or other food borne pathogens in impedance-based sensor platform.

Conductivity and pH dual detection of growth profile of healthy and stressed Listeria monocytogenes.

In this study, growth of Listeria monocytogenes in a low conductivity growth medium (LCGM) was simultaneously monitored by conductivity and pH measurements. Detection times obtained from the conductivity and pH growth curves were inversely related to the initial concentration of L. monocytogenes in the medium. Linear responses were found by plotting detection times obtained from both conductivity and pH growth curves as a function of initial cell concentration in the range of 10(2) to 10(7) cfu/mL. The detection time was approximately 12 and 2 h for 10(2) and 10(7) cfu/mL of viable L. monocytogenes, respectively, using the conductivity growth curves, whereas it was approximately 1 h less using the pH growth curves. This dual detection system was used for evaluating the growth of acid-, temperature-, and salt-treated L. monocytogenes in the medium. Acid stress at pH 2 and 3 for 3 h caused approximately 12 and 4 h delay in the detection time on pH growth curves, while stress at pH 5 for 3 h did not cause a significant delay in detection time. Delay in detection times was also observed for L. monocytogenes cells exposed to 45 degrees C for more than 1 h (2 and 6 h). Exposure to 10% NaCl for 3 h did not cause visible delay in the detection time. These observations on detection times for stressed L. monocytogenes had a consistent trend with the cell number decrease determined by surface plating method.