Vitexicarpin suppresses malignant progression of colorectal cancer through affecting c-Myc ubiquitination by targeting IMPDH2.

BACKGROUND: Colorectal cancer (CRC) is the second most common cause of cancer-related mortality and is characterised by extensive invasive and metastatic potential. Previous studies have shown that vitexicarpin extracted from the fruits of Vitex rotundifolia can impede tumour progression. However, the molecular mechanisms involved in CRC treatment are still not fully established. PURPOSE: Our study aimed to investigate the anticancer activity, targets, and molecular mechanisms of vitexicarpin in CRC hoping to provide novel therapies for patients with CRC. STUDY DESIGN/METHODS: The impact of vitexicarpin on CRC was assessed through various experiments including MTT, clone formation, EDU, cell cycle, and apoptosis assays, as well as a tumour xenograft model. CETSA, label-free quantitative proteomics, and Biacore were used to identify the vitexicarpin targets. WB, Co-IP, Ubiquitination assay, IF, molecular docking, MST, and cell transfection were used to investigate the mechanism of action of vitexicarpin in CRC cells. Furthermore, we analysed the expression patterns and correlation of target proteins in TCGA and GEPIA datasets and clinical samples. Finally, wound healing, Transwell, tail vein injection model, and tissue section staining were used to demonstrate the antimetastatic effect of vitexicarpin on CRC in vitro and in vivo. RESULTS: Our findings demonstrated that vitexicarpin exhibits anticancer activity by directly binding to inosine monophosphate dehydrogenase 2 (IMPDH2) and that it promotes c-Myc ubiquitination by disrupting the interaction between IMPDH2 and c-Myc, leading to epithelial-mesenchymal transition (EMT) inhibition. Vitexicarpin hinders the migration and invasion of CRC cells by reversing EMT both in vitro and in vivo. Additionally, these results were validated by the overexpression and knockdown of IMPDH2 in CRC cells. CONCLUSION: These results demonstrated that vitexicarpin regulates the interaction between IMPDH2 and c-Myc to inhibit CRC proliferation and metastasis both in vitro and in vivo. These discoveries introduce potential molecular targets for CRC treatment and shed light on new mechanisms for c-Myc regulation in tumours.

Investigation of different ingredients affected the flavor changes of Yu-Shiang shredded pork by using GC-IMS and GC-MS combined with E-nose and E-tongue.

The objective of this study was to assess and compare the characteristics of Yu-Shiang Shredded Pork made with different ingredients by using physicochemical measurements and intelligent sensory analysis. The study revealed that there were 18 varied amino acids present, with the taste active values (TAVs) of Leu, Glu, Asp, Asn, and Ala all higher than 1.0. Intelligent sensory analysis showed that the samples lacking lettuce and fungus had similar aromas and flavors, while those lacking shredded pork and pickled chillies had distinct aromas and flavors. Moreover, VOCs (volatile organic compounds) were detected in five types of Yu-Shiang Shredded Pork, with 43, 42, 53, 36, and 50 identified in GC-MS (gas chromatography-mass spectrometry), respectively. Olefins (20.62 %-30.93 %) were the most abundant. GC-IMS (gas chromatography-ion mobility spectrometry) detected 68 volatiles flavor compounds, with esters having a significantly higher relative content than other compounds, indicating their significant role in the flavor formation process of Yu-Shiang Shredded Pork. Furthermore, the Orthogonal Partial Least Squares-discriminant analysis (OPLS-DA) model analysis identified 19 marker compounds that could differentiate the five types of Yu-Shiang Shredded Pork. These fundamental results lay the groundwork for future research on the connection between ingredients and the flavor characteristics of Yu-Shiang Shredded Pork.

Characterization of flavor and taste profile of different radish (Raphanus Sativus L.) varieties by headspace-gas chromatography-ion mobility spectrometry (GC/IMS) and E-nose/tongue.

A comprehensive study of the overall flavor and taste profile of different radishes is lacking. This study systematically compared the volatile profile of six radish varieties using HS-GC-IMS and their correlation with the E-nose analysis. Organic acids and amino acids were quantified, and their association with the E-tongues analysis was explored. A total of 73 volatile compounds were identified, with diallyl sulfide and dimethyl disulfide being the primary sulfides responsible for the unpleasant flavor in radish. Compared to other varieties, cherry radishes boast a significantly higher concentration of allyl isothiocyanate, which likely contributes to their characteristic radish flavor. Moreover, oxalic acid was identified as the most abundant organic acid in radish, accounting for over 97% of its content, followed by malic acid and succinic acid. In conclusion, the distinct flavor and taste characteristics of different radish varieties partially explain their suitability for diverse culinary preferences.

Monitoring Activity and Gait in Children (MAGIC) using digital health technologies.

BACKGROUND: Digital health technologies (DHTs) can collect gait and physical activity in adults, but limited studies have validated these in children. This study compared gait and physical activity metrics collected using DHTs to those collected by reference comparators during in-clinic sessions, to collect a normative accelerometry dataset, and to evaluate participants' comfort and their compliance in wearing the DHTs at-home. METHODS: The MAGIC (Monitoring Activity and Gait in Children) study was an analytical validation study which enrolled 40, generally healthy participants aged 3-17 years. Gait and physical activity were collected using DHTs in a clinical setting and continuously at-home. RESULTS: Overall good to excellent agreement was observed between gait metrics extracted with a gait algorithm from a lumbar-worn DHT compared to ground truth reference systems. Majority of participants either "agreed" or "strongly agreed" that wrist and lumbar DHTs were comfortable to wear at home, respectively, with 86% (wrist-worn DHT) and 68% (lumbar-worn DHT) wear-time compliance. Significant differences across age groups were observed in multiple gait and activity metrics obtained at home. CONCLUSIONS: Our findings suggest that gait and physical activity data can be collected from DHTs in pediatric populations with high reliability and wear compliance, in-clinic and in home environments. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04823650 IMPACT: Digital health technologies (DHTs) have been used to collect gait and physical activity in adult populations, but limited studies have validated these metrics in children. The MAGIC study comprehensively validates the performance and feasibility of DHT-measured gait and physical activity in the pediatric population. Our findings suggest that reliable gait and physical activity data can be collected from DHTs in pediatric populations, with both high accuracy and wear compliance both in-clinic and in home environments. The identified across-age-group differences in gait and activity measurements highlighted their potential clinical value.

Evaluation of clinical and imaging features for differentiating rhabdomyosarcoma from neuroblastoma in pediatric soft tissue.

Background: In this study, we developed a nomogram predictive model based on clinical, CT, and MRI parameters to differentiate soft tissue rhabdomyosarcoma (RMS) from neuroblastoma (NB) in children preoperatively. Materials and methods: A total of 103 children with RMS (n=37) and NB (n=66) were enrolled in the study from December 2012 to July 2023. The clinical and imaging data (assessed by two experienced radiologists) were analyzed using univariate analysis, and significant factors were further analyzed by multivariable logistic regression using the forward LR method to develop the clinical model, radiological model, and integrated nomogram model, respectively. The diagnostic performances, goodness of fit, and clinical utility of the integrated nomogram model were assessed using the area under the curve (AUC) of the receiver operator characteristics curve (ROC) with a 95% confidence interval (95% CI), calibration curve, and decision curve analysis (DCA) curves, respectively. Diagnostic efficacy between the model and radiologists' interpretations was examined. Results: The median age at diagnosis in the RMS group was significantly older than the NB group (36.0 months vs. 14.5 months; P=0.003); the fever rates in RMS patients were significantly lower than in patients with NB (0.0% vs.16.7%; P=0.022), and the incidence of palpable mass was higher in patients with RMS compared with the NB patients (89.2% vs. 34.8%; P<0.001). Compare NB on image features: RMS occurred more frequently in the head and neck and displayed homogeneous density on non-enhanced CT than NB (48.6% vs. 9.1%; 35.3% vs. 13.8%, respectively; all P<0.05), and the occurrence of characteristics such as calcification, encasing vessels, and intraspinal tumor extension was significantly less frequent in RMS children compared to children with NB (18.9% vs. 84.8%; 13.5% vs. 34.8%; 2.7% vs. 50.0%, respectively; all P <0.05). Two, three, and four features were identified as independent parameters by multivariate logistic regression analysis to develop the clinical, radiological, and integrated nomogram models, respectively. The AUC value (0.962), calibration curve, and DCA showed that the integrated nomogram model may provide better diagnostic performance, good agreement, and greater clinical net benefits than the clinical model, radiological model, and radiologists' subjective diagnosis. Conclusion: The clinical and imaging features-based nomogram has potential for helping radiologists distinguish between pediatric soft tissue RMS and NB patients preoperatively, and reduce unnecessary interventions.

Evaluation of Loquat Jam Quality at Different Cooking Times Based on Physicochemical Parameters, GC-IMS and Intelligent Senses.

The study compared and analyzed the quality of loquat jam with different cooking times through physicochemical parameters, headspace-gas chromatography-ion migration spectroscopy (HS-GC-IMS) and intelligent senses. The results showed that with the prolongation of the cooking time, the color of loquat jam slowly deepened, the energy significantly increased, the adhesiveness, gumminess, hardness and chewiness enhanced, the free amino acid content increased from 22.40 to 65.18 mg/g. The organic acid content increased from 1.64 to 9.82 mg/g. Forty-seven volatile flavor compounds were identified in five types of loquat jam using HS-GC-IMS, among which the relative content of aldehydes was sharply higher than that of other chemical substances, playing an important role in the flavor formation of loquat jam. LJ0, LJ1 and LJ2 had higher aldehyde content, followed by LJ3 and LJ4 had the lowest aldehyde content. The orthogonal partial least squares-discriminant analysis (OPLS-DA) screened 15 marker compounds that could distinguish five types of loquat jam. The E-nose results showed a significant difference in olfactory sense between loquat jam cooked for 100 and 120 min. The E-tongue results corroborated the results of free amino acids (FAAs) and organic acids, indicating that the gustatory sense of loquat jam changed significantly when the cooking time reached 120 min. The results provided a basis for further research on the relationship between the cooking process and quality characteristics of loquat jam.

SciKit digital health package for accelerometry-measured physical activity: comparisons to existing solutions and investigations of age effects in healthy adults.

Introduction: Accelerometry has become increasingly prevalent to monitor physical activity due to its low participant burden, quantitative metrics, and ease of deployment. Physical activity metrics are ideal for extracting intuitive, continuous measures of participants' health from multiple days or weeks of high frequency data due to their fairly straightforward computation. Previously, we released an open-source digital health python processing package, SciKit Digital Health (SKDH), with the goal of providing a unifying device-agnostic framework for multiple digital health algorithms, such as activity, gait, and sleep. Methods: In this paper, we present the open-source SKDH implementation for the derivation of activity endpoints from accelerometer data. In this implementation, we include some non-typical features that have shown promise in providing additional context to activity patterns, and provide comparisons to existing algorithms, namely GGIR and the GENEActiv macros. Following this reference comparison, we investigate the association between age and derived physical activity metrics in a healthy adult cohort collected in the Pfizer Innovation Research Lab, comprising 7-14 days of at-home data collected from younger (18-40 years) and older (65-85 years) healthy volunteers. Results: Results showed that activity metrics derived with SKDH had moderate to excellent ICC values (0.550 to 1.0 compared to GGIR, 0.469 to 0.697 compared to the GENEActiv macros), with high correlations for almost all compared metrics (>0.733 except vs GGIR sedentary time, 0.547). Several features show age-group differences, with Cohen's d effect sizes >1.0 and p-values < 0.001. These features included non-threshold methods such as intensity gradient, and activity fragmentation features such as between-states transition probabilities. Discussion: These results demonstrate the validity of the implemented SKDH physical activity algorithm, and the potential of the implemented PA metrics in assessing activity changes in free-living conditions.

Can Gait Characteristics Be Represented by Physical Activity Measured with Wrist-Worn Accelerometers?

Wearable accelerometers allow for continuous monitoring of function and behaviors in the participant's naturalistic environment. Devices are typically worn in different body locations depending on the concept of interest and endpoint under investigation. The lumbar and wrist are commonly used locations: devices placed at the lumbar region enable the derivation of spatio-temporal characteristics of gait, while wrist-worn devices provide measurements of overall physical activity (PA). Deploying multiple devices in clinical trial settings leads to higher patient burden negatively impacting compliance and data quality and increases the operational complexity of the trial. In this work, we evaluated the joint information shared by features derived from the lumbar and wrist devices to assess whether gait characteristics can be adequately represented by PA measured with wrist-worn devices. Data collected at the Pfizer Innovation Research (PfIRe) Lab were used as a real data example, which had around 7 days of continuous at-home data from wrist- and lumbar-worn devices (GENEActiv) obtained from a group of healthy participants. The relationship between wrist- and lumbar-derived features was estimated using multiple statistical methods, including penalized regression, principal component regression, partial least square regression, and joint and individual variation explained (JIVE). By considering multilevel models, both between- and within-subject effects were taken into account. This work demonstrated that selected gait features, which are typically measured with lumbar-worn devices, can be represented by PA features measured with wrist-worn devices, which provides preliminary evidence to reduce the number of devices needed in clinical trials and to increase patients' comfort. Moreover, the statistical methods used in this work provided an analytic framework to compare repeated measures collected from multiple data modalities.

CT and MR imaging features of soft tissue rhabdoid tumor: compared with rhabdomyosarcoma in children.

Objective: To assess the computed tomography (CT) and magnetic resonance (MR) imaging characteristics of soft tissue rhabdoid tumors (RT) and compare them with those of rhabdomyosarcoma (RMS). Methods: We conducted a retrospective analysis of 49 pediatric patients from 2011 to 2022, comprising 16 patients with soft tissue RT and 33 patients with RMS who underwent CT or MRI scans. Key imaging features, as well as clinical and pathological data, were compared between the two groups. The multivariate logistic regression analysis was used to determine independent differential factors for distinguishing soft tissue RT from RMS, and the model was established. The final prediction model was visualized by nomograms and verified internally by using a bootstrapped resample 1,000 times. The diagnostic accuracy of the combined model was assessed in terms of discrimination, calibration, and clinical utility. Results: Age, sex, number of lesions, and primary locations were similar in both groups. The imaging characteristics, including margin, calcification, surrounding blood vessels, and rim enhancement, were associated with the two groups of soft tissue tumors, as determined by univariate analysis (all p < 0.05). On multivariate logistic regression analysis, the presence of unclear margin (p-value, adjusted odds ratio [95% confidence interval]: 0.03, 7.96 [1.23, 51.67]) and calcification (0.012, 30.37 [2.09, 440.70]) were independent differential factors for predicting soft tissue RT over RMS. The presence of rim enhancement (0.007, 0.05 [0.01, 0.43]) was an independent differential factor for predicting RMS over soft tissue RT. The comprehensive model established by logistic regression analysis showed an AUC of 0.872 with 81.8% specificity and 81.3% sensitivity. The decision curve analysis (DCA) curve displayed that the model achieved a better net clinical benefit. Conclusion: Our study revealed that the image features of calcification, indistinct margins, and a lack of rim enhancement on CT and MRI might be reliable to distinguish soft tissue RT from RMS.

Effects of Waterlogging at Flowering Stage on the Grain Yield and Starch Quality of Waxy Maize.

Waterlogging is a common abiotic stress in global maize production. Maize flowering stage (from tasseling to silking) is more fragile to environmental stresses, and this stage frequently overlapped the plum rain season in the middle and lower reaches of Yangtze river in China and affect the yield and quality of spring-sown maize severely. In the present study, the soil moisture content under control and waterlogging conditions at the flowering stage was controlled by a negative-pressure water supply and controlling pot device in a pot trial in 2014-2015. The grain yield, starch content, and starch structural and functional properties under two soil moisture levels were compared using Suyunuo5 (SYN5) and Yunuo7 (YN7) as materials, which are the control hybrids of National waxy maize hybrid regional trials in Southern China. The results observed that the grain yield was reduced by 29.1% for SYN5 with waterlogging due to the decreased grain weight and numbers, which was significantly higher than that of YN7 (14.7%), indicated that YN7 was more tolerant to waterlogging. The grain starch content in YN7 was decreased by 9.4% when plants suffered waterlogging at the flowering stage, whereas the content in SYN5 was only decreased in 2014 and unaffected in 2015. The size of starch granules and proportion of small-molecule amylopectin with waterlogging at the flowering stage increased in SYN5 and decreased in YN7 in both years. The type of starch crystalline structure was not changed by waterlogging, whereas the relative crystallinity was reduced in SYN5 and increased in YN7. The pasting viscosities were decreased, and the pasting temperature was unaffected by waterlogging in general. The gelatinization enthalpy was unaffected by waterlogging in both hybrids in both years, whereas the retrogradation enthalpy and percentage in both hybrids were reduced by waterlogging in 2014 and unaffected in 2015. Between the two hybrids, YN7 has high pasting viscosities and low retrogradation percentage than SYN5, indicated its advantages on produce starch for more viscous and less retrograde food. In conclusion, waterlogging at the flowering stage reduced the grain yield, restricted starch accumulation, and deteriorated the pasting viscosity of waxy maize. Results provide information for utilization of waxy maize grain in food production.

A novel BCL11A polymorphism influences gene expression, therapeutic response and epilepsy risk: A multicenter study.

Background: Genetic factors have been found to be associated with the efficacy and adverse reactions of antiseizure medications. BCL11A is an important regulator of the development of neuronal networks. However, the role of BCL11A in epilepsy remains unclear. This study aimed to evaluate the genetic association of BCL11A with the susceptibility to develop epileptic seizures and therapeutic response of patients with epilepsy in Han Chinese. Methods: We matched 450 epilepsy cases with 550 healthy controls and 131 drug-resistant epilepsy patients with 319 drug-responsive epilepsy patients from two different centers. Genetic association analysis, genetic interaction analysis, expression quantitative trait loci analysis and protein-protein interaction analysis were conducted. Results: Our results showed that rs2556375 not only increases susceptibility to develop epileptic seizures (OR = 2.700, 95% = 1.366-5.338, p = 0.004 and OR = 2.984, 95% = 1.401-6.356, p = 0.005, respectively), but also increases the risk of drug resistance(OR = 21.336, 95%CI =2.489-183.402, p = 0.005). The interaction between rs2556375 and rs12477097 results in increased risk for pharma coresistant. In addition, rs2556375 regulated BCL11A expression in human brain tissues (p = 0.0096 and p = 0.033, respectively). Furthermore, the protein encoded by BCL11A interacted with targets of approved antiepileptic drugs. Conclusion: BCL11A may be a potential therapeutic target for epilepsy. Rs2556375 may increase the risks of epilepsy and drug resistance by regulating BCL11A expression in human brain tissues. Moreover, the interaction between rs2556375 and rs12477097 results in increased risk for drug resistance.

Noninvasive Optical Measurements of Dynamic Cerebral Autoregulation by Inducing Oscillatory Cerebral Hemodynamics.

Objective: Cerebral autoregulation limits the variability of cerebral blood flow (CBF) in the presence of systemic arterial blood pressure (ABP) changes. Monitoring cerebral autoregulation is important in the Neurocritical Care Unit (NCCU) to assess cerebral health. Here, our goal is to identify optimal frequency-domain near-infrared spectroscopy (FD-NIRS) parameters and apply a hemodynamic model of coherent hemodynamics spectroscopy (CHS) to assess cerebral autoregulation in healthy adult subjects and NCCU patients. Methods: In five healthy subjects and three NCCU patients, ABP oscillations at a frequency around 0.065 Hz were induced by cyclic inflation-deflation of pneumatic thigh cuffs. Transfer function analysis based on wavelet transform was performed to measure dynamic relationships between ABP and oscillations in oxy- (O), deoxy- (D), and total- (T) hemoglobin concentrations measured with different FD-NIRS methods. In healthy subjects, we also obtained the dynamic CBF-ABP relationship by using FD-NIRS measurements and the CHS model. In healthy subjects, an interval of hypercapnia was performed to induce cerebral autoregulation impairment. In NCCU patients, the optical measurements of autoregulation were linked to individual clinical diagnoses. Results: In healthy subjects, hypercapnia leads to a more negative phase difference of both O and D oscillations vs. ABP oscillations, which are consistent across different FD-NIRS methods and are highly correlated with a more negative phase difference CBF vs. ABP. In the NCCU, a less negative phase difference of D vs. ABP was observed in one patient as compared to two others, indicating a better autoregulation in that patient. Conclusions: Non-invasive optical measurements of induced phase difference between D and ABP show the strongest sensitivity to cerebral autoregulation. The results from healthy subjects also show that the CHS model, in combination with FD-NIRS, can be applied to measure the CBF-ABP dynamics for a better direct measurement of cerebral autoregulation.

The Association Between STX1B Polymorphisms and Treatment Response in Patients With Epilepsy.

Background: Epilepsy is a debilitating brain disease with complex inheritance and frequent treatment resistance. However, the role of STX1B single nucleotide polymorphisms (SNPs) in epilepsy treatment remains unknown. Objective: This study aimed to explore the genetic association of STX1B SNPs with treatment response in patients with epilepsy in a Han Chinese population. Methods: We first examined the associations between STX1B SNPs and epilepsy in 1000 Han Chinese and the associations between STX1B SNPs and drug-resistant epilepsy in 450 subjects. Expression quantitative trait loci analysis was then conducted using 16 drug-resistant epileptic brain tissue samples and results from the BrainCloud database (http://eqtl.brainseq.org). Results: The allelic frequencies of rs140820592 were different between the epilepsy and control groups (p = 0.002) after Bonferroni correction. The rs140820592 was associated with significantly lower epilepsy risk among 1,000 subjects in the dominant model after adjusting for gender and age and Bonferroni correction (OR = 0.542, 95%CI = 0.358-0.819, p = 0.004). The rs140820592 also conferred significantly lower risk of drug-resistant epilepsy among 450 subjects using the same dominant model after adjusting for gender and age and Bonferroni correction (OR = 0.260, 95%CI = 0.103-0.653, p = 0.004). Expression quantitative trait loci analysis revealed that rs140820592 was associated with STX1B expression level in drug-resistant epileptic brain tissues (p = 0.012), and this result was further verified in the BrainCloud database (http://eqtl.brainseq.org) (p = 2.3214 × 10-5). Conclusion: The STX1B rs140820592 may influence the risks of epilepsy and drug-resistant epilepsy by regulating STX1B expression in brain tissues.

The impact of chronotype on circadian rest-activity rhythm and sleep characteristics across the week.

Circadian rhythms are maintained by a complex "system of systems" that continuously coordinates biological processes with each other and the environment. Although humans predominantly entrain to solar time, individual persons vary in their precise behavioral timing due to endogenous and exogenous factors. Endogenous differences in the timing of individual circadian rhythms relative to a common environmental cue are known as chronotypes, ranging from earlier than average (Morningness) to later than average (Eveningness). Furthermore, individual behavior is often constrained by social constructs such as the 7-day week, and the "sociogenic" impact our social calendar has on our behavioral rhythms is likely modified by chronotype. Our aim in this study was to identify and characterize differences in sleep and rest-activity rhythms (RAR) between weekends and weekdays and between-chronotypes. Male volunteers (n = 24, mean age = 23.46 y) were actigraphically monitored for 4 weeks to derive objective behavioral measures of sleep and RARs. Chronotype was assessed through self-report on the Morningness-Eveningness Questionnaire. Sleep characteristics were derived using Actiware; daily rest-activity rhythms were modeled using a basic 3-parameter cosinor function. We observed that both Eveningness and Morningness Chronotypes were more active and slept later on the weekends than on weekdays. Significant between-chronotype differences in sleep timing and duration were observed within individual days of the week, especially during transitions between weekends and the workweek. Moreover, chronotypes significantly varied in their weekly rhythms: e.g. Morningness Chronotypes generally shifted their sleep duration, timing and quality across work/rest transitions quicker than Eveningness Chronotypes. Although our results should be interpreted with caution due to the limitations of our cosinor model and a homogenous cohort, they reinforce a growing body of evidence that day of the week, chronotype and their interactions must be accounted for in observational studies of human behavior, especially when circadian rhythms are of interest.

Assessment of Sit-to-Stand Transfers during Daily Life Using an Accelerometer on the Lower Back.

The ability to perform sit-to-stand (STS) transfers has a significant impact on the functional mobility of an individual. Wearable technology has the potential to enable the objective, long-term monitoring of STS transfers during daily life. However, despite several recent efforts, most algorithms for detecting STS transfers rely on multiple sensing modalities or device locations and have predominantly been used for assessment during the performance of prescribed tasks in a lab setting. A novel wavelet-based algorithm for detecting STS transfers from data recorded using an accelerometer on the lower back is presented herein. The proposed algorithm is independent of device orientation and was validated on data captured in the lab from younger and older healthy adults as well as in people with Parkinson's disease (PwPD). The algorithm was then used for processing data captured in free-living conditions to assess the ability of multiple features extracted from STS transfers to detect age-related group differences and assess the impact of monitoring duration on the reliability of measurements. The results show that performance of the proposed algorithm was comparable or significantly better than that of a commercially available system (precision: 0.990 vs. 0.868 in healthy adults) and a previously published algorithm (precision: 0.988 vs. 0.643 in persons with Parkinson's disease). Moreover, features extracted from STS transfers at home were able to detect age-related group differences at a higher level of significance compared to data captured in the lab during the performance of prescribed tasks. Finally, simulation results showed that a monitoring duration of 3 days was sufficient to achieve good reliability for measurement of STS features. These results point towards the feasibility of using a single accelerometer on the lower back for detection and assessment of STS transfers during daily life. Future work in different patient populations is needed to evaluate the performance of the proposed algorithm, as well as assess the sensitivity and reliability of the STS features.

Age and environment-related differences in gait in healthy adults using wearables.

Technological advances in multimodal wearable and connected devices have enabled the measurement of human movement and physiology in naturalistic settings. The ability to collect continuous activity monitoring data with digital devices in real-world environments has opened unprecedented opportunity to establish clinical digital phenotypes across diseases. Many traditional assessments of physical function utilized in clinical trials are limited because they are episodic, therefore, cannot capture the day-to-day temporal fluctuations and longitudinal changes in activity that individuals experience. In order to understand the sensitivity of gait speed as a potential endpoint for clinical trials, we investigated the use of digital devices during traditional clinical assessments and in real-world environments in a group of healthy younger (n = 33, 18-40 years) and older (n = 32, 65-85 years) adults. We observed good agreement between gait speed estimated using a lumbar-mounted accelerometer and gold standard system during the performance of traditional gait assessment task in-lab, and saw discrepancies between in-lab and at-home gait speed. We found that gait speed estimated in-lab, with or without digital devices, failed to differentiate between the age groups, whereas gait speed derived during at-home monitoring was able to distinguish the age groups. Furthermore, we found that only three days of at-home monitoring was sufficient to reliably estimate gait speed in our population, and still capture age-related group differences. Our results suggest that gait speed derived from activities during daily life using data from wearable devices may have the potential to transform clinical trials by non-invasively and unobtrusively providing a more objective and naturalistic measure of functional ability.

Toxin-Induced Acute Delirium.

Acute delirium is a transient state of cerebral dysfunction reflecting an underlying medical decompensation. Toxicity from medications and other substances are a common cause of delirium. History and laboratory testing may be limited by alteration and lack of specific tests for certain compounds. Classes of compounds produce a constellation of symptoms and examination findings recognized as a toxidrome. Cessation of the offending agent, supportive care, and specific antidotal therapy are key to treatment. This article reviews the presentations of the anticholinergic toxidrome, sympathomimetic toxidrome, hallucinogenic toxidrome, γ-aminobutyric acid withdrawal, and Wernicke encephalopathy, as well as their mechanisms and basic management.

Identification of the ZEB2 gene as a potential target for epilepsy therapy and the association between rs10496964 and ZEB2 expression.

OBJECTIVE: An association between the rs10496964 polymorphism and the ZEB2 gene has not yet been reported, and the role of ZEB2 in epilepsy therapy is also unclear. The aims of this research were to evaluate the role of ZEB2 in the therapy of epilepsy and to explore the association between rs10496964 and ZEB2 expression. METHODS: We used the expression quantitative trait loci (eQTL) dataset resource from the Brain eQTL Almanac to evaluate the association between rs10496964 and ZEB2 expression in human brain tissue. Pathway and process enrichment analysis, protein-protein interaction analysis, and PhosphoSitePlus® analysis were then performed to further evaluate the role of ZEB2 in the therapy of epilepsy. RESULTS: The rs10496964 polymorphism was found to regulate the expression of ZEB2 in human brain tissue. The ZEB2 protein interacts with the targets of approved antiepileptic drugs, and a post-translational acetylation modification of ZEB2 was associated with an epilepsy drug therapy. CONCLUSION: Our findings suggest that ZEB2 may be involved in the therapy of epilepsy, and rs10496964 regulates ZEB2 expression in human brain tissue.

Facile Formation of Anatase/Rutile TiO2 Nanocomposites with Enhanced Photocatalytic Activity.

Anatase/rutile mixed-phase TiO2 nanoparticles were synthesized through a simple sol-gel route with further calcination using inexpensive titanium tetrachloride as a titanium source, which effectively reduces the production cost. The structural and optical properties of the prepared materials were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), and UV-vis adsorption. The specific surface area was also analyzed by Brunauer-Emmett-Teller (BET) method. The anatase/rutile mixed-phase TiO2 nanocomposites containing of rod-like, cuboid, and some irregularly shaped anatase nanoparticles (exposed {101} facets) with sizes ranging from tens to more than 100 nanometers, and rod-like rutile nanoparticles (exposed {110} facets) with sizes ranging from tens to more than 100 nanometers. The photocatalytic activities of the obtained anatase/rutile mixed-phase TiO2 nanoparticles were investigated and compared by evaluating the degradation of hazardous dye methylene blue (MB) under ultraviolet light illumination. Compared to the commercial Degussa P25-TiO2, the mixed-phase TiO2 nanocomposites show better photocatalytic activity, which can be attributed to the optimal anatase to rutile ratio and the specific exposed crystal surface on the surface. The anatase/rutile TiO2 nanocomposites obtained at pH 1.0 (pH1.0-TiO2) show the best photocatalytic activity, which can be attributed to the optimal heterojunction structure, the smaller average particle size, and the presence of a specific exposed crystal surface. The enhanced photocatalytic activity makes the prepared anatase/rutile TiO2 photocatalysts a potential candidate in the removal of the organic dyes from colored wastewater.

Blockage of TGF-α Induced by Spherical Silica Nanoparticles Inhibits Epithelial-Mesenchymal Transition and Proliferation of Human Lung Epithelial Cells.

Background. Xuanwei City in Yunnan province has been one of the towns with highest lung cancer mortality in China. The high content of amorphous silica in the bituminous coal from Xuanwei of Yunnan is mainly present as irregular and spherical silica nanoparticles (SiNPs). It has been reported that silica nanoparticles in bituminous coal correlated with the high incidence of lung cancer in Xuanwei. To explore the role and mechanism of SiNPs in the tumorigenesis of lung cancer in Xuanwei, human mononuclear cells (THP-1) and human bronchial epithelial cells (BEAS-2B) were cocultured in a transwell chamber. Combined with Benzo[a]pyrene-7, 8-dihydrodiol-9, and 10-epoxide (BPDE), SiNPs could significantly promote the proliferation and Epithelial-Mesenchymal Transition (EMT) and inhibit apoptosis of BEAS-2B cells and induce the release of TGF-α from THP-1 cells. After neutralizing TGF-α with antibody, the proliferation and EMT were decreased and enhanced apoptosis of BEAS-2B cells. Furthermore, the results showed that TGF-α in the sera of patients with lung adenocarcinoma in Xuanwei were significantly higher than in patients with benign pulmonary lesions in Xuanwei and those with lung adenocarcinoma in outside of Xuanwei of Yunnan. Taken together, our study found that SiNPs promoted the proliferation and EMT of BEAS-2B cells by inducing the release of TGF-α from THP-1 cells.