Insights into Nanomedicine for Head and Neck Cancer Diagnosis and Treatment

Head and neck cancers rank sixth among the most common cancers today, and the survival rate has remained virtually unchanged over the past 25 years, due to late diagnosis and ineffective treatments. They have two main risk factors, tobacco and alcohol, and human papillomavirus infection is a secondary risk factor. These cancers affect areas of the body that are fundamental for the five senses. Therefore, it is necessary to treat them effectively and non-invasively as early as possible, in order to do not compromise vital functions, which is not always possible with conventional treatments (chemotherapy or radiotherapy). In this sense, nanomedicine plays a key role in the treatment and diagnosis of head and neck cancers. Nanomedicine involves using nanocarriers to deliver drugs to sites of action and reducing the necessary doses and possible side effects. The main purpose of this review is to give an overview of the applications of nanocarrier systems to the diagnosis and treatment of head and neck cancer. Herein, several types of delivery strategies, radiation enhancement, inside-out hyperthermia, and theragnostic approaches are addressed.     

Risk of Seven-Day Worsening and Death: A New Clinically Derived COVID-19 Score

This monocentric, retrospective, two-stage observational study aimed to recognize the risk factors for a poor outcome in patients hospitalized with SARS-CoV-2 infection, and to develop and validate a risk score that identifies subjects at risk of worsening, death, or both. The data of patients with SARS-CoV-2 infection during the first wave of the pandemic were collected and analyzed as a derivation cohort. Variables with predictive properties were used to construct a prognostic score, which was tried out on a validation cohort enrolled during the second wave. The derivation cohort included 494 patients; the median age was 62 and the overall fatality rate was 22.3%. In a multivariable analysis, age, oxygen saturation, neutrophil-to-lymphocyte ratio, C-reactive protein and lactate dehydrogenase were independent predictors of death and composed the score. A cutoff value of 3 demonstrated a sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV) of 93.5%, 68.5%, 47.4% and 97.2% for death, and 84.9%, 84.5%, 79.6% and 87.9% for worsening, respectively. The validation cohort included 415 subjects. The score application showed a Se, Sp, PPV and NPV of 93.4%, 61.6%, 29.5% and 98.1% for death, and 81%, 76.3%, 72.1% and 84.1% for worsening, respectively. We propose a new clinical, easy and reliable score to predict the outcome in hospitalized SARS-CoV-2 patients.     

Light exposure during sleep impairs cardiometabolic function

This study tested the hypothesis that acute exposure to light during nighttime sleep adversely affects next-morning glucose homeostasis and whether this effect occurs via reduced sleep quality, melatonin suppression, or sympathetic nervous system (SNS) activation during sleep. A total of 20 young adults participated in this parallel-group study design. The room light condition (n = 10) included one night of sleep in dim light (<3 lx) followed by one night of sleep with overhead room lighting (100 lx). The dim light condition (n = 10) included two consecutive nights of sleep in dim light. Measures of insulin resistance (morning homeostatic model assessment of insulin resistance, 30-min insulin area under the curve [AUC] from a 2-h oral glucose tolerance test) were higher in the room light versus dim light condition. Melatonin levels were similar in both conditions. In the room light condition, participants spent proportionately more time in stage N2 and less in slow wave and rapid eye movement sleep. Heart rate was higher and heart rate variability lower (higher sympathovagal balance) during sleep in the room light versus the dim light condition. Importantly, the higher sympathovagal balance during sleep was associated with higher 30-min insulin AUC, consistent with increased insulin resistance the following morning. These results demonstrate that a single night of exposure to room light during sleep can impair glucose homeostasis, potentially via increased SNS activation. Attention to avoiding exposure to light at night during sleep may be beneficial for cardiometabolic health.

Exposure to artificial light during the night is widespread globally, particularly in industrialized countries (1–3). Given that light and dark exposure patterns play a key role in the timing of many behaviors and physiological functions (4), exposure to light in the evening and night has been posited to be deleterious for human health and well-being (1, 5–10). Impacts of light exposure during sleep are not as well studied as other kinds of nighttime light exposure. However, a recent cross-sectional observation study noted that, compared to no light exposure during sleep, any self-reported artificial light exposure in the bedroom during sleep (small nightlight in room, light from outside room, or television/light in room) was associated with obesity in women (11). Furthermore, the incidence of obesity was highest in those who reported sleeping with a television or light on in the bedroom (11). These findings suggest that light in the bedroom during nighttime sleep may negatively influence metabolic regulation.Emerging evidence indicates that light exposure plays a role in human metabolic regulation, with evening light exposure having unfavorable effects on metabolic functions including decreased glucose tolerance and decreased insulin sensitivity (12, 13). In line with these data, we have previously shown that blue-enriched light exposure in the morning and evening alters glucose metabolism, with an increase in insulin resistance compared to dim light exposure (14). In addition, evidence indicates that nighttime indoor light exposure during the habitual sleep period while awake (15), and during sleep itself (16), likely has deleterious metabolic effects. A recent study prospectively measured light exposure in the bedroom during nighttime sleep and showed that higher levels of bedroom light exposure were associated with a higher incidence of type 2 diabetes in an elderly population (16). However, the exact mechanisms by which light exposure, particularly during nighttime sleep, impacts metabolic regulation are not well understood.A proposed pathway to explain the relationship between nighttime light exposure and altered metabolic function is via changes in sleep. Robust evidence from epidemiological and experimental studies indicates that nighttime light exposure, either from outdoor or indoor sources, has negative impacts on subjective and objective sleep quality as indicated by actigraphy or polysomnography (PSG) measures of reduced total sleep time (TST), sleep efficiency (SE), increased wake after sleep onset (WASO), reduced amount of slow wave sleep (SWS), or increased arousal index (AI) (17–20). Given the well-established contribution of sleep disruptions to metabolic dysfunction (21), it is plausible that nighttime light exposure alters glucose metabolism due to disturbances to sleep. However, nighttime light exposure also appears to have a direct effect on glucose regulation that is independent of sleep loss, as shown by a study that subjected healthy male individuals to sleep deprivation in the dark or to sleep deprivation with nighttime light exposure (22). This study showed that a full night of sleep deprivation with nighttime light exposure increased postprandial levels of insulin and glucagon-like peptide-1, increased insulin resistance, and reduced nighttime melatonin; these changes were not observed under conditions of sleep deprivation in darkness.A second proposed mechanism to explain the impairment of glucose metabolism from nighttime light exposure is via light-induced changes to the endogenous circadian system, including suppression and phase shifting of the melatonin rhythm (23). It is well established that light exposure suppresses melatonin secretion (24, 25), and several studies have implicated suppression of nighttime melatonin with incidence of diabetes (26) and insulin resistance (27). The association between altered melatonin levels and changes in glucose regulation may be explained by evidence that melatonin plays a role in the secretion and action of insulin (28–30). In particular, lower melatonin levels resulting from light exposure during the nighttime sleep period, in a fasting condition, have been suggested to alter melatonin’s facilitation of pancreatic β-cell recovery (31). Moreover, evidence shows that light exposure, even of moderate intensity, during the nighttime sleep period can produce a phase shift of the internal circadian system (32, 33). Given the established role of the circadian system in the control of glucose metabolism, light exposure during the nighttime sleep period could facilitate the misalignment between the central clock and peripheral clocks in metabolic tissues, with consequent negative impact on glucose homeostasis (34).A third potential mechanism is the effect of light exposure on autonomic nervous system (ANS) activity. Light exposure has an arousing effect on the sympathetic autonomic system as revealed by the increase in cortisol or heart rate (HR) associated with light exposure mainly during the morning and/or nighttime hours as compared to evening hours (35–37). Beyond the direct excitatory effect exerted by light exposure on sympathetic activity (35), alterations of the ANS characterized by a shift toward an increased sympathetic drive have also been suggested to mediate the negative effects of sleep disruption on many physiological systems such as glucose metabolism (38). Thus, it is plausible that light-induced autonomic activation, either directly and/or mediated by sleep disruption, significantly contributes to the observed relationship between nighttime light exposure and altered glucose metabolism. Notably, sympathetic overactivity has been shown to precede the development of insulin resistance and prediabetes and contribute to the development of obesity and metabolic syndrome (39–41).Prior studies have reported that light exposure during sleep increases HR and decreases HR variability (HRV), consistent with increased sympathetic activation (42–44). These studies either examined bright light (1,000 lx) over the entire sleep period (42) or lower light levels (50 lx or dawn simulation) early or late in the sleep period (43, 44). However, the effect of a single night of moderate room light exposure across the entire nighttime sleep period on autonomic activation and its impact on metabolic function has never been fully investigated.In the present study, we tested the hypothesis that room light exposure (100 lx) during habitual nighttime sleep is associated with increased insulin resistance as measured by the homeostatic model of insulin resistance (HOMA-IR), the Matsuda insulin sensitivity index, and impaired response to an oral glucose tolerance test (OGTT) the next morning. In addition, we hypothesized potential mechanisms of light-induced metabolic changes, such as reduced sleep quality, suppression of melatonin level, and elevated sympathetic activation (HR and HRV) during the sleep period.     

Revisiting the HPLC-FLD Method to Quantify Paralytic Shellfish Toxins: C3,4 Quantification and the First Steps towards Validation

Paralytic shellfish toxins (PSTs) are a large group of biotoxins that cause paralytic shellfish poisoning. Their appearance in natural waters and their ingestion by aquatic species have a huge socio-economic impact, whereby their monitoring is of the upmost relevance to minimize the consequences. For earlier detection and faster response/action by stakeholders, validation of adjusted analytical methods, particularly for lower concentration levels, is important. This work proposes a derived High-Performance Liquid Chromatography method, with fluorescence detection (HPLC-FLD). The main differences from the official method are the size of the HPLC column and the gradient elution conditions. It covers the current eleven certified reference materials (CRM) available on the market, including the most recent—C3,4. This first calibration report for C3,4 suggests limits of detection (LOD) and limits of quantification (LOQ) of 6 nM and 19 nM (~5 µg STX.2HCl eqv./kg and 17 µg STX.2HCl eqv./kg), respectively. For the remaining CRM, LODs ranged between 3 and 28 nM (~0.9 and 127 µg STX.2HCl eqv./kg), while LOQs varied between 11 and 94 nM (~3 and 409 µg STX.2HCl eqv./kg, considering toxicity equivalency factors (TEFs) reported by EFSA).     

Comparing the accuracy of transcutaneous sensor and 90-day implantable glucose sensor

Background and aimsContinuous glucose monitoring improves glycemic control in diabetes. This study compared the accuracy of the Dexcom G5 Mobile (Dexcom, San Diego, CA) transcutaneous sensor (DG5) and the first version of Eversense (Senseonics,Inc., Germantown, MD) implantable sensor (EVS).Methods and resultsSubjects with type 1 diabetes (T1D) and using EVS wore simultaneously DG5 for seven days. At day 3, patients were admitted to a clinical research center (CRC) to receive breakfast with delayed and increased insulin bolus to induce glucose excursions. At CRC, venous glucose was monitored every 15 min (or 5 min during hypoglycemia) for 6 h by YSI 2300 STAT PLUS? glucose and lactate analyzer. At home patients were requested to perform 4 fingerstick glucose measurements per day.Eleven patients (9 males, age 47.4 ± 11.3 years, M±SD) were enrolled. During home-stay the median [25th-75th percentile] absolute relative difference (ARD) over all CGM-fingerstick matched-pairs was 11.64% [5.38–20.65]% for the DG5 and 10.75% [5.15–19.74]% for the EVS (p-value = 0.58). At CRC, considering all the CGM-YSI matched-pairs, the DG5 showed overall smaller median ARD than EVS, 7.91% [4.14–14.30]% vs 11.4% [5.04–18.54]% (p-value<0.001). Considering accuracy during blood glucose swings, DG5 performed better than EVS when glucose rate-of-change was ?0.5 to ?1.5 mg/dL/min, with median ARD of 7.34% [3.71–12.76]% vs 13.59% [4.53–20.78]% (p-value<0.001), and for rate-of-change < -1.5 mg/dl/min, with median ARD of 5.23% [2.09–15.29]% vs 12.73% [4.14–20.82]% (p-value = 0.02).ConclusionsDG5 was more accurate than EVS at CRC, especially when glucose decreased. No differences were found at home.     

Preparation,Characterization and Release of Urea from Wheat Gluten Electrospun Membranes

Homogeneous and thin porous membranes composed of oriented fibers were obtained from wheat gluten (WG) using the electrospinning technique. SEM micrographs showed an asymmetric structure and some porosity, which, in addition to a small thickness of 40 μm, are desirable characteristics for the membranes’ potential application in release systems. The membranes were loaded with urea to obtain pastilles. FT-IR and DSC studies confirmed the existence of interactions via hydrogen bonding between urea and WG proteins. The pastilles were studied as prolonged-released systems of urea in water. The release of urea during the first 10 min was very fast; then, the rate of release decreased as it reached equilibrium at 300 min, with a total of ≈98% urea released. TGA analysis showed that the release system obtained is thermally stable up to a temperature of 117 °C. It was concluded that a prolonged-release system of urea could be satisfactorily produced using WG fibers obtained by electrospinning for potential application in agricultural crops.     

Influence of physiological and supraphysiological hyperinsulinemia on skin microcirculation in healthy volunteers

AIM: To examine skin perfusion in dependency on insulinemia in healthy subjects.METHODS: All volunteers were informed in detail about the procedures and signed informed consent. The protocol of this study was approved by the ethical committee. In our study, a two stage hyperinsulinemic euglycemic clamp was performed, with insulinemia 100 and 250 mIU/mL and glycemia 5.0 mmol/L (3% standard deviation). Before the clamp and in steady states, microcirculation was measured by laser Doppler flowmetry and transcutaneous oximetry and energy expenditure was measured by indirect calorimetry. Results (average and standard deviation) were evaluated with paired t-test.RESULTS: Physiological (50 mIU/L) insulinemia led to higher perfusion in both tests; hyperemia after heating to 44%-1848% (984-2046) vs 1599% (801-1836), P < 0.05, half time of reaching peak perfusion after occlusion release 1.2 s (0.9-2.6) vs 4.9 s (1.8-11.4), P < 0.05. Supraphysiological (150 mIU/L) insulinemia led to even higher perfusion in both tests; hyperemia after heating to 44%-1937% (1177-2488) vs 1599% (801-1836), P < 0.005, half time to reach peak perfusion after occlusion release 1.0 s (0.7-1.1) vs 4.9 s (1.8-11.4), P < 0.005. A statistically significant increase occurred in tissue oxygenation in both insulinemia. The difference in perfusion and oxygenation between physiological and supraphysiological hyperinsulinemia was not statistically significant.CONCLUSION: The post occlusive hyperemia test in accordance with heating test showed significantly increasing skin perfusion in the course of artificial hyperinsulinemia. This effect rises non-linearly with increasing insulinemia. Dependency on the dose was not statistically significant.