A new oxime synthesized from Senecio nutans SCh. Bip (chachacoma) reduces calcium influx in the vascular contractile response in rat aorta.

Senecio nutans Sch. Bip is an endemic plant commonly employed in the Andes culture to counteract the effects of mountain sickness, and its bioactive molecules could provide new drugs for treating hypertension. The purpose was to determine whether the vascular response of the plant bioactive molecules, such as (5-acetyl-6-hydroxy-2-isopropenyl-2,3-dihydrobenzofurane; Sn-I), could be improved by a simple structural modification to synthesize oximes (Ox-Sn-I). We characterized both compounds using IR and NMR spectroscopy and Heteronuclear Multiple Quantum Coherence (HMQC). We investigated vascular relaxation mechanisms in response to Sn-I and Ox-Sn-I using rat aorta and vascular smooth muscle cells (A7r5) as experimental models. Preincubation of aortic rings with Sn-I (10-5 M) significantly (p < 0.001) decreased the contractile effect in response to phenylephrine (PE) and potassium chloride (KCl). The sensitivity (EC50) to PE significantly (p < 0.01) decreased in the presence of Sn-I (10-5 M), but not with Ox-Sn-I. Sn-I significantly (p < 0.001) reduced the PE-induced contraction under calcium-free conditions. When A7r5 cells were preincubated with Sn-I and Ox-Sn-I (10-5 M), both compounds blunted the increase in intracellular Ca2+ induced by KCl. 2,3-Dihydrobenzofurane derived from S. nutans (Sn-I) reduces the contractile response probably by blocking Ca2+ entry through voltage-gated Ca2+ channels (VGCC) in vascular smooth cells. This effect also causes relaxation in rat aorta mediated by reduction of intracellular Ca2+ concentration, rather than an increase of NO generation in endothelial vascular cells.

Optimizing the Release Pattern of Telenomus podisi for Effective Biological Control of Euschistus heros in Soybean.

An augmentative biological control program using the egg parasitoid Telenomus podisi Ashmead (Hymenoptera: Platygastridae) is a promising tool for the management of the brown stink bug, Euschistus heros (Fabricius) (Hemiptera: Pentatomidae) in soybeans. The T. podisi are released as adults or pupae within lab-reared E. heros eggs. Because of the small size of the parasitoid and potentially limited dispersal ability, determining the optimal release pattern is critical for biological control of the target pest. This study used sentinel E. heros eggs to investigate T. podisi dispersal within soybean crops during two distinct phenological stages: the beginning of flowering (Vn-R1) and the grain-filling phase (R5-R6). Data were analyzed using semi-variograms and kriging maps. The results indicate significant differences in parasitism rates between the two plant growth stages and among different matrices. The maximum dispersal range for T. podisi was calculated at 39.0 m in the Vn-R1 stage with a maximum parasitism rate of 42%, while in the R5-R6 stage, the maximum dispersal range was calculated to be 30.9 m with a maximum parasitism of 73%. Therefore, it is recommended that release points for T. podisi be spaced no further than 30 m apart. These results provide valuable insights for future research and applications in biological control strategies, including adjustment of the logistics and release technique depending upon the crop phenological stage.

Calcium signaling in endothelial and vascular smooth muscle cells: sex differences and the influence of estrogens and androgens.

Calcium signaling in vascular endothelial cells (ECs) and smooth muscle cells (VSMCs) is essential for the regulation of vascular tone. However, the changes to intracellular Ca2+ concentrations are often influenced by sex differences. Furthermore, a large body of evidence shows that sex hormone imbalance leads to dysregulation of Ca2+ signaling and this is a key factor in the pathogenesis of cardiovascular diseases. In this review, the effects of estrogens and androgens on vascular calcium-handling proteins are discussed, with emphasis on the associated genomic or nongenomic molecular mechanisms. The experimental models from which data were collected were also considered. The review highlights 1) in female ECs, transient receptor potential vanilloid 4 (TRPV4) and mitochondrial Ca2+ uniporter (MCU) enhance Ca2+-dependent nitric oxide (NO) generation. In males, only transient receptor potential canonical 3 (TRPC3) plays a fundamental role in this effect. 2) Female VSMCs have lower cytosolic Ca2+ levels than males due to differences in the activity and expression of stromal interaction molecule 1 (STIM1), calcium release-activated calcium modulator 1 (Orai1), calcium voltage-gated channel subunit-α1C (CaV1.2), Na+-K+-2Cl- symporter (NKCC1), and the Na+/K+-ATPase. 3) When compared with androgens, the influence of estrogens on Ca2+ homeostasis, vascular tone, and incidence of vascular disease is better documented. 4) Many studies use supraphysiological concentrations of sex hormones, which may limit the physiological relevance of outcomes. 5) Sex-dependent differences in Ca2+ signaling mean both sexes ought to be included in experimental design.

Chemical Characterization of Phoenix dactylifera L. Seeds and their Beneficial Effects on the Vascular Response in Hypertensive Rats.

Although Phoenix dactylifera dates are traditionally consumed for their health benefits, no research has been done on the vascular response in hypertensive animals. This study evaluated the vascular relaxation of hydroalcoholic extracts from seeds of three varieties of P. dactylifera; Sukkari seed (SS), Ajwa seed (AS), and Mabroom seed (MS) on L-NAME-induced hypertension and spontaneously hypertensive rats (SHR). Results showed that all extracts (10 µg/mL) caused relaxations higher than 60% in the aortic rings precontracted with 10- 6 M phenylephrine in normotensive rats, the SS extract was the most potent. Endothelial nitric oxide (NO) pathway is involved as significantly reduced vascular relaxation in denuded-endothelium rat aorta and with an inhibitor (10- 4 M L-Nω-Nitro arginine methyl ester; L-NAME) of endothelial nitric oxide synthase (eNOS). Confocal microscopy confirmed that 10 µg/mL SS extract increases NO generation as detected by DAF-FM fluorescence in intact aortic rings. Consistent with these findings, vascular relaxation in intact aortic rings at 10 µg/mL SS extract was significantly decreased in L-NAME-induced hypertensive rats (endothelial dysfunction model), but not in SHR. In both hypertensive models, the denuded endothelium blunted the vascular relaxation. In conclusion, the hydroalcoholic extract of the seed of P. dactylifera (Sukkari, Ajwa and Mabroom varieties) presents a potent endothelium-dependent vascular relaxation, via NO, in normotensive rats as well as in two different models of hypertension. This effect could be mediated by the presence of phenolic compounds identified by UHPLC-ESI-MS/MS, such as protocatechuic acid, and caftaric acid.

EEG Dataset Collection for Mental Workload Predictions in Flight-Deck Environment.

High mental workload reduces human performance and the ability to correctly carry out complex tasks. In particular, aircraft pilots enduring high mental workloads are at high risk of failure, even with catastrophic outcomes. Despite progress, there is still a lack of knowledge about the interrelationship between mental workload and brain functionality, and there is still limited data on flight-deck scenarios. Although recent emerging deep-learning (DL) methods using physiological data have presented new ways to find new physiological markers to detect and assess cognitive states, they demand large amounts of properly annotated datasets to achieve good performance. We present a new dataset of electroencephalogram (EEG) recordings specifically collected for the recognition of different levels of mental workload. The data were recorded from three experiments, where participants were induced to different levels of workload through tasks of increasing cognition demand. The first involved playing the N-back test, which combines memory recall with arithmetical skills. The second was playing Heat-the-Chair, a serious game specifically designed to emphasize and monitor subjects under controlled concurrent tasks. The third was flying in an Airbus320 simulator and solving several critical situations. The design of the dataset has been validated on three different levels: (1) correlation of the theoretical difficulty of each scenario to the self-perceived difficulty and performance of subjects; (2) significant difference in EEG temporal patterns across the theoretical difficulties and (3) usefulness for the training and evaluation of AI models.

Cascade testing for hereditary cancer: comprehensive multigene panels identify unexpected actionable findings in relatives.

Current guidelines recommend single variant testing in relatives of patients with known pathogenic or likely pathogenic germline variants in cancer predisposition genes. This approach may preclude the use of risk-reducing strategies in family members who have pathogenic or likely pathogenic germline variants in other cancer predisposition genes. Cascade testing using multigene panels was performed in 3696 relatives of 7433 probands. Unexpected pathogenic or likely pathogenic germline variants were identified in 230 (6.2%) relatives, including 144 who were negative for the familial pathogenic or likely pathogenic variant but positive for a pathogenic or likely pathogenic variant in a different gene than the proband and 74 who tested positive for the familial pathogenic or likely pathogenic variant and had an additional pathogenic or likely pathogenic variant in a different gene than the proband. Of the relatives with unexpected pathogenic or likely pathogenic germline variants, 36.3% would have qualified for different or additional cancer screening recommendations. Limiting cascade testing to only the familial pathogenic or likely pathogenic variant would have resulted in missed, actionable findings for a subset of relatives.

Universal Germline-Genetic Testing for Breast Cancer: Implementation in a Rural Practice and Impact on Shared Decision-Making.

BACKGROUND: Whereas the National Comprehensive Cancer Network (NCCN) criteria restrict germline-genetic testing (GGT) to a subset of breast cancer (BC) patients, the American Society of Breast Surgeons recommends universal GGT. Although the yield of pathogenic germline variants (PGV) in unselected BC patients has been studied, the practicality and utility of incorporating universal GGT into routine cancer care in community and rural settings is understudied. This study reports real-world implementation of universal GGT for patients with breast cancer and genetics-informed, treatment decision-making in a rural, community practice with limited resources. METHODS: From 2019 to 2022, all patients with breast cancer at a small, rural hospital were offered GGT, using a genetics-extender model. Statistical analyses included Fisher's exact test, t-tests, and calculation of odds ratios. Significance was set at p < 0.05. RESULTS: Of 210 patients with breast cancer who were offered GGT, 192 (91.4%) underwent testing with 104 (54.2%) in-criteria (IC) and 88 (45.8%) out-of-criteria (OOC) with NCCN guidelines. Pathogenic germline variants were identified in 25 patients (13.0%), with PGV frequencies of 15 of 104 (14.4%) in IC and ten of 88 (11.4%) in OOC patients (p = 0.495). GGT informed treatment for 129 of 185 (69.7%) patients. CONCLUSIONS: Universal GGT was successfully implemented in a rural, community practice with > 90% uptake. Treatment was enhanced or de-escalated in those with and without clinically actionable PGVs, respectively. Universal GGT for patients with breast cancer is feasible within rural populations, enabling optimization of clinical care to patients' genetic profile, and may reduce unnecessary healthcare, resource utilization.

A deep learning model based on the combination of convolutional and recurrent neural networks to enhance pulse oximetry ability to classify sleep stages in children with sleep apnea.

Characterization of sleep stages is essential in the diagnosis of sleep-related disorders but relies on manual scoring of overnight polysomnography (PSG) recordings, which is onerous and labor-intensive. Accordingly, we aimed to develop an accurate deep-learning model for sleep staging in children suffering from pediatric obstructive sleep apnea (OSA) using pulse oximetry signals. For this purpose, pulse rate (PR) and blood oxygen saturation (SpO2) from 429 childhood OSA patients were analyzed. A CNN-RNN architecture fed with PR and SpO2 signals was developed to automatically classify wake (W), non-Rapid Eye Movement (NREM), and REM sleep stages. This architecture was composed of: (i) a convolutional neural network (CNN), which learns stage-related features from raw PR and SpO2 data; and (ii) a recurrent neural network (RNN), which models the temporal distribution of the sleep stages. The proposed CNN-RNN model showed a high performance for the automated detection of W/NREM/REM sleep stages (86.0% accuracy and 0.743 Cohen's kappa). Furthermore, the total sleep time estimated for each children using the CNN-RNN model showed high agreement with the manually derived from PSG (intra-class correlation coefficient = 0.747). These results were superior to previous works using CNN-based deep-learning models for automatic sleep staging in pediatric OSA patients from pulse oximetry signals. Therefore, the combination of CNN and RNN allows to obtain additional information from raw PR and SpO2 data related to sleep stages, thus being useful to automatically score sleep stages in pulse oximetry tests for children evaluated for suspected OSA.Clinical Relevance-This research establishes the usefulness of a CNN-RNN architecture to automatically score sleep stages in pulse oximetry tests for pediatric OSA diagnosis.

Metal ions based dynamic nuclear polarization: MI-DNP.

Over the last two decades magic angle spinning dynamic nuclear polarization (MAS DNP) has revolutionized NMR for materials characterization, tackling its main limitation of intrinsically low sensitivity. Progress in theoretical understanding, instrumentation, and sample formulation expanded the range of materials applications and research questions that can benefit from MAS DNP. Currently the most common approach for hyperpolarization under MAS consists in impregnating the sample of interest with a solution containing nitroxide radicals, which upon microwave irradiation serve as exogenous polarizing agents. On the other hand, in metal ion based (MI)-DNP, inorganic materials are doped with paramagnetic metal centres, which then can be used as endogenous polarizing agents. In this work we give an overview of the electron paramagnetic resonance (EPR) concepts required to characterize the metal ions and discuss the expected changes in the NMR response due to the presence of paramagnetic species. We highlight which properties of the electron spins are beneficial for applications as polarizing agents in DNP and how to recognize them, both from the EPR and NMR data. A theoretical description of the main DNP mechanisms is given, employing a quantum mechanical formalism, and these concepts are used to explain the spin dynamics observed in the DNP experiment. In addition, we highlight the main differences between MI-DNP and the more common approaches in MAS DNP, which use organic radicals as exogenous polarizing source. Finally, we review some applications of metal ions as polarizing agents in general and then focus particularly on research questions in materials science that can benefit from MI-DNP.

Prediction of the Sleep Apnea Severity Using 2D-Convolutional Neural Networks and Respiratory Effort Signals.

The high prevalence of sleep apnea and the limitations of polysomnography have prompted the investigation of strategies aimed at automated diagnosis using a restricted number of physiological measures. This study aimed to demonstrate that thoracic (THO) and abdominal (ABD) movement signals are useful for accurately estimating the severity of sleep apnea, even if central respiratory events are present. Thus, we developed 2D-convolutional neural networks (CNNs) jointly using THO and ABD to automatically estimate sleep apnea severity and evaluate the central event contribution. Our proposal achieved an intraclass correlation coefficient (ICC) = 0.75 and a root mean square error (RMSE) = 10.33 events/h when estimating the apnea-hypopnea index, and ICC = 0.83 and RMSE = 0.95 events/h when estimating the central apnea index. The CNN obtained accuracies of 94.98%, 79.82%, and 81.60% for 5, 15, and 30 events/h when evaluating the complete apnea hypopnea index. The model improved when the nature of the events was central: 98.72% and 99.74% accuracy for 5 and 15 events/h. Hence, the information extracted from these signals using CNNs could be a powerful tool to diagnose sleep apnea, especially in subjects with a high density of central apnea events.

An explainable deep-learning model to stage sleep states in children and propose novel EEG-related patterns in sleep apnea.

Automatic deep-learning models used for sleep scoring in children with obstructive sleep apnea (OSA) are perceived as black boxes, limiting their implementation in clinical settings. Accordingly, we aimed to develop an accurate and interpretable deep-learning model for sleep staging in children using single-channel electroencephalogram (EEG) recordings. We used EEG signals from the Childhood Adenotonsillectomy Trial (CHAT) dataset (n = 1637) and a clinical sleep database (n = 980). Three distinct deep-learning architectures were explored to automatically classify sleep stages from a single-channel EEG data. Gradient-weighted Class Activation Mapping (Grad-CAM), an explainable artificial intelligence (XAI) algorithm, was then applied to provide an interpretation of the singular EEG patterns contributing to each predicted sleep stage. Among the tested architectures, a standard convolutional neural network (CNN) demonstrated the highest performance for automated sleep stage detection in the CHAT test set (accuracy = 86.9% and five-class kappa = 0.827). Furthermore, the CNN-based estimation of total sleep time exhibited strong agreement in the clinical dataset (intra-class correlation coefficient = 0.772). Our XAI approach using Grad-CAM effectively highlighted the EEG features associated with each sleep stage, emphasizing their influence on the CNN's decision-making process in both datasets. Grad-CAM heatmaps also allowed to identify and analyze epochs within a recording with a highly likelihood to be misclassified, revealing mixed features from different sleep stages within these epochs. Finally, Grad-CAM heatmaps unveiled novel features contributing to sleep scoring using a single EEG channel. Consequently, integrating an explainable CNN-based deep-learning model in the clinical environment could enable automatic sleep staging in pediatric sleep apnea tests.

Deep learning for obstructive sleep apnea diagnosis based on single channel oximetry.

Obstructive sleep apnea (OSA) is a serious medical condition with a high prevalence, although diagnosis remains a challenge. Existing home sleep tests may provide acceptable diagnosis performance but have shown several limitations. In this retrospective study, we used 12,923 polysomnography recordings from six independent databases to develop and evaluate a deep learning model, called OxiNet, for the estimation of the apnea-hypopnea index from the oximetry signal. We evaluated OxiNet performance across ethnicity, age, sex, and comorbidity. OxiNet missed 0.2% of all test set moderate-to-severe OSA patients against 21% for the best benchmark.

Antispasmodic Effect of Valeriana pilosa Root Essential Oil and Potential Mechanisms of Action: Ex Vivo and In Silico Studies.

Infusions of Valeriana pilosa are commonly used in Peruvian folk medicine for treating gastrointestinal disorders. This study aimed to investigate the spasmolytic and antispasmodic effects of Valeriana pilosa essential oil (VPEO) on rat ileum. The basal tone of ileal sections decreased in response to accumulative concentrations of VPEO. Moreover, ileal sections precontracted with acetylcholine (ACh), potassium chloride (KCl), or barium chloride (BaCl2) were relaxed in response to VPEO by a mechanism that depended on atropine, hyoscine butylbromide, solifenacin, and verapamil, but not glibenclamide. The results showed that VPEO produced a relaxant effect by inhibiting muscarinic receptors and blocking calcium channels, with no apparent effect on the opening of potassium channels. In addition, molecular docking was employed to evaluate VPEO constituents that could inhibit intestinal contractile activity. The study showed that α-cubebene, ß-patchoulene, ß-bourbonene, ß-caryophyllene, α-guaiene, γ-muurolene, valencene, eremophyllene, and δ-cadinene displayed the highest docking scores on muscarinic acetylcholine receptors and voltage-gated calcium channels, which may antagonize M2 and/or M3 muscarinic acetylcholine receptors and block voltage-gated calcium channels. In summary, VPEO has both spasmolytic and antispasmodic effects. It may block muscarinic receptors and calcium channels, thus providing a scientific basis for its traditional use for gastrointestinal disorders.

Computational modeling of membrane trafficking processes: From large molecular assemblies to chemical specificity.

In the last decade, molecular dynamics (MD) simulations have become an essential tool to investigate the molecular properties of membrane trafficking processes, often in conjunction with experimental approaches. The combination of MD simulations with recent developments in structural biology, such as cryo-electron microscopy and artificial intelligence-based structure determination, opens new, exciting possibilities for future investigations. However, the full potential of MD simulations to provide a molecular view of the complex and dynamic processes involving membrane trafficking can only be realized if certain limitations are addressed, and especially those concerning the quality of coarse-grain models, which, despite recent successes in describing large-scale systems, still suffer from far-from-ideal chemical accuracy. In this review, we will highlight recent success stories of MD simulations in the investigation of membrane trafficking processes, their implications for future research, and the challenges that lie ahead in this specific research domain.

Doctors for the people? The problematic distribution of rural service doctors in Ecuador.

Primary health care is at the core of health systems that aim to ensure equitable health outcomes. With an estimated 36% of rural population, Ecuador has a service year programme (created in 1970) for recently graduated doctors to provide primary care services in rural and remote communities. However, little has been done to monitor or evaluate the programme since its inception. The aim of this study was to assess Ecuador's rural medical service implementation with a focus on equitable distribution of doctors across the country. For this purpose, we analysed the distribution of all doctors, including rural service doctors, in health-care facilities across rural and remote areas of Ecuador in the public sector at the canton level for 2015 and 2019, by level of care (primary, secondary and tertiary). We used publicly available data from the Ministry of Public Health, the Ecuadorian Institute of Social Security and the Peasant Social Security. Our analyses show that two of every three rural service doctors are concentrated at the secondary level, while almost one in five rural service doctors, at the tertiary level. Moreover, cantons concentrating most rural service doctors were in the country's major urban centres (Quito, Guayaquil, Cuenca). To our knowledge, this is the first quantitative assessment of the mandatory rural service year in Ecuador in its five-decade existence. We provide evidence of gaps and inequities impacting rural communities and present decision makers with a methodology for placement, monitoring and support of the rural service doctors programme, provided that legal and programmatic reforms come into place. Changing the programme's approach would be more likely to fulfill the intended goals of rural service and contribute to strengthening primary health care.

"Long-term oncologic outcomes and risk factors for distant recurrence after pathologic complete response following neoadjuvant treatment for locally advanced rectal cancer. A nationwide, multicentre study".

BACKGROUND: Pathologic complete response (pCR) after multimodal treatment for locally advanced rectal cancer (LARC) is used as surrogate marker of success as it is assumed to correlate with improved oncologic outcome. However, long-term oncologic data are scarce. METHODS: This retrospective, multicentre study updated the oncologic follow-up of prospectively collected data from the Spanish Rectal Cancer Project database. pCR was described as no evidence of tumour cells in the specimen. Endpoints were distant metastases-free survival (DMFS) and overall survival (OS). Multivariate regression analyses were run to identify factors associated with survival. RESULTS: Overall, 32 different hospitals were involved, providing data on 815 patients with pCR. At a median follow-up of 73.4 (IQR 57.7-99.5) months, distant metastases occurred in 6.4% of patients. Abdominoperineal excision (APE) (HR 2.2, 95%CI 1.2-4.1, p = 0.008) and elevated CEA levels (HR = 1.9, 95% CI 1.0-3.7, p = 0.049) were independent risk factors for distant recurrence. Age (years) (HR 1.1; 95%-CI 1.05-41.09; p < 0.001) and ASA III-IV (HR = 2.0; 95%-CI 1.4-2.9; p < 0.001), were the only factors associated with OS. The estimated 12, 36 and 60-months DMFS rates were 96.9%, 91.3%, and 86.8%. The estimated 12, 36 and 60-months OS rates were 99.1%, 94.9% and 89.3%. CONCLUSIONS: The incidence of metachronous distant metastases is low after pCR, with high rates of both DMFS and OS. The oncologic prognosis in LARC patients that achieve pCR after neoadjuvant chemo-radiotherapy is excellent in the long term.