Evaluation of potential human health risks arising from nitrate and fluoride in the groundwater of Aurangabad, Bihar using GIS and chemometric analysis.

This study employed the groundwater pollution index to assess the appropriateness of groundwater for human consumption. Additionally, the hazard index was utilized to evaluate the potential non-carcinogenic risks associated with fluoride and nitrate exposure among children, women, and men in the study region. A total of 103 samples were collected from the Aurangabad district of Bihar. The analyzed samples were assessed using several physicochemical parameters. Major cations in the groundwater are Ca2+ > Mg2+ and major anions are HCO3- > Cl- > SO42- > NO3- > F- > PO43-. Around 17% of the collected groundwater samples surpassed the allowable BIS concentration limits for Nitrate, while approximately 11% surpassed the allowed limits for fluoride concentration. Principal component analysis was utilized for its efficacy and efficiency in the analytical procedure. Four principal components were recovered that explained 69.06% of the total variance. The Hazard Quotient (HQ) of nitrate varies between 0.03-1.74, 0.02-1.47, and 0.03-1.99 for females, males, and children, respectively. The HQ of fluoride varies between 0.04-1.59, 0.04-1.34, and 0.05-1.82 for females, males, and children, respectively. The central part of the district was at high risk according to the spatial distribution maps of the total hazard index (THI). Noncarcinogenic risks due to THI are 47%, 37%, and 28% for children, females, and males, respectively. According to the human health risk assessment, children are more prone to getting affected by polluted water than adults. The groundwater pollution index (GPI) value ranges from 0.46 to 2.27 in the study area. Seventy-five percent of the samples fell under minor pollution and only one fell under high pollution. The spatial distribution of GPI in the research area shows that the central region is highly affected, which means that this water is unsuitable for drinking purposes.

Janus hydrogel loaded with a CO2-generating chemical reaction system: Construction, characterization, and application in fruit and vegetable preservation.

In this study, we inserted a dynamic chemical reaction system that can generate CO2 into Janus hydrogel (JH) to develop a multidimensional preservation platform that integrates hygroscopicity, antibacterial activity, and modified atmospheric capacity. The double gel system developed using sodium alginate/trehalose at a 1:1 ratio effectively encapsulated 90% of citric acid. Furthermore, CO2 loss was avoided by separately embedding NaHCO3/cinnamon essential oil and citric acid microcapsules into a gelatin pad to develop JH. Freeze-dried JH exhibited a porous and asymmetric structure, very strongly absorbing moisture, conducting water, and rapidly releasing CO2 and essential oils. Furthermore, when preserving various fruits and vegetables in practical settings, JH provided several preservation effects, including color protection, microbial inhibition, and antioxidant properties. Our study findings broaden the application of JH technology for developing chemical reaction systems, with the resulting JH holding substantial promise for cold chain logistics.

The Landscape of Care for Women Veterans with Cancer: An Evidence Map.

BACKGROUND: Women are the fastest growing veteran group in the US and the number of women veterans (WVs) with cancer is rising; however, little is known about this population. Cancer care for WVs is complex and it is essential to understand their unique needs and care coordination challenges to provide evidence-based care. The purpose of this review is to map the quantity, distribution, and characteristics of literature describing cancer and its treatment among WVs. METHODS: We searched MEDLINE (via PubMed), Embase (Elsevier), and Web of Science Core Collection (Clarivate) from inception through January, 2024. Publications were eligible that reported gender-specific data on any aspect of cancer care among WVs. Data was abstracted by a single investigator with over-reading. RESULTS: Forty-six reports were included; 44 were observational and 19 had a women-only sample. There were no interventional reports and no qualitative reports had a patient sample. Breast cancer was the most commonly addressed (n = 19). There were six additional reports on sex-specific cancers. Many reports used large VA databases or previous trial data, creating the potential for patient overlap between reports. Among VA-specific areas of interest, only three reports evaluated the potential implications of racial differences and only two included a transgender population. No reports examined the effects of toxic exposures on cancer. Within the NCI Cancer Control Continuum, crosscutting areas were more commonly represented; over half (25) of the reports addressed epidemiology. There were few reports on focus areas and little overlap between focus and crosscutting areas. DISCUSSION: Existing literature provides an inadequate understanding of the population of WVs with cancer. There is scant information regarding the population of WVs with cancer, their care preferences or experiences, or how to best identify and address unmet healthcare needs. It is imperative to expand research to provide evidence-based care for this population.

Combining Google Earth historical imagery and UAV photogrammetry for urban development analysis.

Rural-urban migration often triggers additional demand for housing and infrastructural development to cater for the growing population in urban areas. Consequently, town planners and urban development authorities need to understand the urban development trend to make sustainable urban planning decisions. Yet, methods to analyse changes and trends in urban spatial development are often complex and require costly data collection. This article thus presents a simplified method to analyse the urban development trend in an area. The method integrates Google Earth (GE) historical imagery (baseline data) and unmanned aerial vehicle (UAV) photogrammetry (recent data) to quantify the changes over time. This approach can be applied to study the urban development trends in low-income countries with budget constraints. The method is discussed under four main headings: (1) background, (2) method details, (3) limitations, and (4) conclusion.•Google Earth historical image can be extracted with its associated world file.•The population of an area can be estimated by using average household size data and the number of residential buildings in the area.•The building height ratio can be used to ascertain if the land is being used parsimoniously.

Elucidating genetic and molecular basis of altered higher-order brain structure-function coupling in major depressive disorder.

Previous studies have shown that major depressive disorder (MDD) patients exhibit structural and functional impairments, but few studies have investigated changes in higher-order coupling between structure and function. Here, we systematically investigated the effect of MDD on higher-order coupling between structural connectivity (SC) and functional connectivity (FC). Each brain region was mapped into embedding vector by the node2vec algorithm. We used support vector machine (SVM) with the brain region embedding vector to distinguish MDD patients from health controls (HCs) and identify the most discriminative brain regions. Our study revealed that MDD patients had decreased higher-order coupling in connections between the most discriminative brain regions and local connections in rich-club organization and increased higher-order coupling in connections between the ventral attentional network and limbic network compared with HCs. Interestingly, transcriptome-neuroimaging association analysis demonstrated the correlations between regional rSC-FC coupling variations between MDD patients and HCs and α/ß-hydrolase domain-containing 6 (ABHD6), ß 1,3-N-acetylglucosaminyltransferase-9(ß3GNT9), transmembrane protein 45B (TMEM45B), the correlation between regional dSC-FC coupling variations and retinoic acid early transcript 1E antisense RNA 1(RAET1E-AS1), and the correlations between regional iSC-FC coupling variations and ABHD6, ß3GNT9, katanin-like 2 protein (KATNAL2). In addition, correlation analysis with neurotransmitter receptor/transporter maps found that the rSC-FC and iSC-FC coupling variations were both correlated with neuroendocrine transporter (NET) expression, and the dSC-FC coupling variations were correlated with metabotropic glutamate receptor 5 (mGluR5). Further mediation analysis explored the relationship between genes, neurotransmitter receptor/transporter and MDD related higher-order coupling variations. These findings indicate that specific genetic and molecular factors underpin the observed disparities in higher-order SC-FC coupling between MDD patients and HCs. Our study confirmed that higher-order coupling between SC and FC plays an important role in diagnosing MDD. The identification of new biological evidence for MDD etiology holds promise for the development of innovative antidepressant therapies.

Inverse Isotope Kinetic Effect of the Charge Transfer Reactions of Ar+ with H2O and D2O.

Hydrogen isotopic effect, as the key to revealing the origin of Earth's water, arises from the H/D mass difference and quantum dynamics at the transition state of reaction. The ion-molecule charge-exchange reaction between water (H2O/D2O) and argon ion (Ar+) proceeds spontaneously and promptly, where there is no transition-state or intermediate complex. In this energetically resonant process, we find an inverse kinetic isotope effect (KIE) leading to the higher charge transfer rate for D2O, by the velocity map imaging measurements of H2O+/D2O+ products. Using the average dipole orientation capture model, we estimate the orientation angles of C2v axis of H2O/D2O relative to the Ar+ approaching direction and attribute to the difference of stereodynamics. According to the long-distance Landau-Zener charge transfer model, this inverse KIE could be also attributed to the density-of-state difference of molecular bending motion between H2O+ and D2O+ around the resonant charge transfer.

Multi-scale brain attributes contribute to the distribution of diffuse glioma subtypes.

Gliomas are primary brain tumors and are among the most malignant types. Adult-type diffuse gliomas can be classified based on their histological and molecular signatures as IDH-wildtype glioblastoma, IDH-mutant astrocytoma, and IDH-mutant and 1p/19q-codeleted oligodendroglioma. Recent studies have shown that each subtype of glioma has its own specific distribution pattern. However, the mechanisms underlying the specific distributions of glioma subtypes are not entirely clear despite partial explanations such as cell origin. To investigate the impact of multi-scale brain attributes on glioma distribution, we constructed cumulative frequency maps for diffuse glioma subtypes based on T1w structural images and evaluated the spatial correlation between tumor frequency and diverse brain attributes, including postmortem gene expression, functional connectivity metrics, cerebral perfusion, glucose metabolism, and neurotransmitter signaling. Regression models were constructed to evaluate the contribution of these factors to the anatomic distribution of different glioma subtypes. Our findings revealed that the three different subtypes of gliomas had distinct distribution patterns, showing spatial preferences toward different brain environmental attributes. Glioblastomas were especially likely to occur in regions enriched with synapse-related pathways and diverse neurotransmitter receptors. Astrocytomas and oligodendrogliomas preferentially occurred in areas enriched with genes associated with neutrophil-mediated immune responses. The functional network characteristics and neurotransmitter distribution also contributed to oligodendroglioma distribution. Our results suggest that different brain transcriptomic, neurotransmitter, and connectomic attributes are the factors that determine the specific distributions of glioma subtypes. These findings highlight the importance of bridging diverse scales of biological organization when studying neurological dysfunction.

Radiomics analysis of dual-layer spectral-detector CT-derived iodine maps for predicting tumor deposits in colorectal cancer.

OBJECTIVE: To investigate the value of radiomics analysis of dual-layer spectral-detector computed tomography (DLSCT)-derived iodine maps for predicting tumor deposits (TDs) preoperatively in patients with colorectal cancer (CRC). MATERIALS AND METHODS: A total of 264 pathologically confirmed CRC patients (TDs + (n = 80); TDs - (n = 184)) who underwent preoperative DLSCT from two hospitals were retrospectively enrolled, and divided into training (n = 124), testing (n = 54), and external validation cohort (n = 86). Conventional CT features and iodine concentration (IC) were analyzed and measured. Radiomics features were derived from venous phase iodine maps from DLSCT. The least absolute shrinkage and selection operator (LASSO) was performed for feature selection. Finally, a support vector machine (SVM) algorithm was employed to develop clinical, radiomics, and combined models based on the most valuable clinical parameters and radiomics features. Area under receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis were used to evaluate the model's efficacy. RESULTS: The combined model incorporating the valuable clinical parameters and radiomics features demonstrated excellent performance in predicting TDs in CRC (AUCs of 0.926, 0.881, and 0.887 in the training, testing, and external validation cohorts, respectively), which outperformed the clinical model in the training cohort and external validation cohorts (AUC: 0.839 and 0.695; p: 0.003 and 0.014) and the radiomics model in two cohorts (AUC: 0.922 and 0.792; p: 0.014 and 0.035). CONCLUSION: Radiomics analysis of DLSCT-derived iodine maps showed excellent predictive efficiency for preoperatively diagnosing TDs in CRC, and could guide clinicians in making individualized treatment strategies. CLINICAL RELEVANCE STATEMENT: The radiomics model based on DLSCT iodine maps has the potential to aid in the accurate preoperative prediction of TDs in CRC patients, offering valuable guidance for clinical decision-making. KEY POINTS: Accurately predicting TDs in CRC patients preoperatively based on conventional CT features poses a challenge. The Radiomics model based on DLSCT iodine maps outperformed conventional CT in predicting TDs. The model combing DLSCT iodine maps radiomics features and conventional CT features performed excellently in predicting TDs.

Efficient standardization of clinical T2-weighted images: Phase-conjugacy e-CAMP with projected gradient descent.

PURPOSE: To standardize T 2 $$ {}_2 $$ -weighted images from clinical Turbo Spin Echo (TSE) scans by generating corresponding T 2 $$ {}_2 $$ maps with the goal of removing scanner- and/or protocol-specific heterogeneity. METHODS: The T 2 $$ {}_2 $$ map is estimated by minimizing an objective function containing a data fidelity term in a Virtual Conjugate Coils (VCC) framework, where the signal evolution model is expressed as a linear constraint. The objective function is minimized by Projected Gradient Descent (PGD). RESULTS: The algorithm achieves accuracy comparable to methods with customized sampling schemes for accelerated T 2 $$ {}_2 $$ mapping. The results are insensitive to the tunable parameters, and the relaxed background phase prior produces better T 2 $$ {}_2 $$ maps compared to the strict real-value enforcement. It is worth noting that the algorithm works well with challenging T 2 $$ {}_2 $$ w-TSE data using typical clinical parameters. The observed normalized root mean square error ranges from 6.8% to 12.3% over grey and white matter, a clinically common level of quantitative map error. CONCLUSION: The novel methodological development creates an efficient algorithm that allows for T 2 $$ {}_2 $$ map generated from TSE data with typical clinical parameters, such as high resolution, long echo train length, and low echo spacing. Reconstruction of T 2 $$ {}_2 $$ maps from TSE data with typical clinical parameters has not been previously reported.

Measuring the Scientific Impact of Growth Hormone Treatment in Burns: A Bibliometric Analysis Based on CiteSpace.

This study utilized CiteSpace software to conduct a bibliometric analysis of the literature related to the use of growth hormone in treating burns. The results showed that the research on this topic has attracted increasing attention from scholars worldwide, with the number of publications increasing annually. The research teams and institutions involved in this field are mainly concentrated in China, followed by the United States, Russia, and other countries. The analysis also revealed the prominent co-cited literature and the most influential authors in the field, such as Herndon，DN.and Li Y. The main research themes identified in the literature included the effects of growth hormone on wound healing, tissue repair and regeneration, inflammatory responses, and cell proliferation. Additionally, the research on the clinical applications of growth hormone in burn treatment has been expanded to include areas such as metabolic regulation, immune function, and the prevention of infections. The findings of this study provide useful insights into the current status and future directions of research in the field of growth hormone treatment of burns.

Circ_0000069 promotes the development of hepatocellular carcinoma by regulating CCL25.

BACKGROUND: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths globally, influenced by aberrant circRNA expression. Investigating circRNA-miRNA-mRNA interactions can unveil underlying mechanisms of HCC and identify potential therapeutic targets. METHODS: In this study, we conducted differential analyses of mRNAs, miRNAs, and circRNAs, and established their relationships using various databases such as miRanda, miRDB, and miTarBase. Additionally, functional enrichment and immune infiltration analyses were performed to evaluate the roles of key genes. We also conducted qPCR assays and western blotting (WB) to examine the expression levels of circRNA, CCL25, and MAP2K1 in both HCC cells and clinical samples. Furthermore, we utilized overexpression and knockdown techniques for circ_0000069 and conducted wound healing, transwell invasion assays, and a tumorigenesis experiment to assess the migratory and invasive abilities of HCC cells. RESULTS: Our findings revealed significant differential expression of 612 upregulated genes and 1173 downregulated genes in HCC samples compared to normal liver tissue. Additionally, 429 upregulated circRNAs and 453 downregulated circRNAs were identified. Significantly, circ_0000069 exhibited upregulation in HCC tissues and cell lines. The overexpression of circ_0000069 notably increased the invasion and migration capacity of Huh7 cells, whereas the downregulation of circ_0000069 reduced this capability in HepG2 cells. Furthermore, this effect was counteracted by CCL25 silencing or overexpression, separately. Animal studies further confirmed that the overexpression of hsa_circ_0000069 facilitated tumor growth in xenografted nude mice, while the inhibition of CCL25 attenuated this effect. CONCLUSION: Circ_0000069 appears to promote HCC progression by regulating CCL25, suggesting that both circ_0000069 and CCL25 can serve as potential therapeutic targets.

Advanced OCTA imaging segmentation: Unsupervised, non-linear retinal vessel detection using modified self-organizing maps and joint MGRF modeling.

BACKGROUND AND OBJECTIVE: This paper proposes a fully automated and unsupervised stochastic segmentation approach using two-level joint Markov-Gibbs Random Field (MGRF) to detect the vascular system from retinal Optical Coherence Tomography Angiography (OCTA) images, which is a critical step in developing Computer-Aided Diagnosis (CAD) systems for detecting retinal diseases. METHODS: Using a new probabilistic model based on a Linear Combination of Discrete Gaussian (LCDG), the first level models the appearance of OCTA images and their spatially smoothed images. The parameters of the LCDG model are estimated using a modified Expectation Maximization (EM) algorithm. The second level models the maps of OCTA images, including the vascular system and other retina tissues, using MGRF with analytically estimated parameters from the input images. The proposed segmentation approach employs modified self-organizing maps as a MAP-based optimizer maximizing the joint likelihood and handles the Joint MGRF model in a new, unsupervised way. This approach deviates from traditional stochastic optimization approaches and leverages non-linear optimization to achieve more accurate segmentation results. RESULTS: The proposed segmentation framework is evaluated quantitatively on a dataset of 204 subjects. Achieving 0.92 ± 0.03 Dice similarity coefficient, 0.69 ± 0.25 95-percentile bidirectional Hausdorff distance, and 0.93 ± 0.03 accuracy, confirms the superior performance of the proposed approach. CONCLUSIONS: The conclusions drawn from the study highlight the superior performance of the proposed unsupervised and fully automated segmentation approach in detecting the vascular system from OCTA images. This approach not only deviates from traditional methods but also achieves more accurate segmentation results, demonstrating its potential in aiding the development of CAD systems for detecting retinal diseases.

Multi-objective energy management in a renewable and EV-integrated microgrid using an iterative map-based self-adaptive crystal structure algorithm.

The use of plug-in hybrid electric vehicles (PHEVs) provides a way to address energy and environmental issues. Integrating a large number of PHEVs with advanced control and storage capabilities can enhance the flexibility of the distribution grid. This study proposes an innovative energy management strategy (EMS) using an Iterative map-based self-adaptive crystal structure algorithm (SaCryStAl) specifically designed for microgrids with renewable energy sources (RESs) and PHEVs. The goal is to optimize multi-objective scheduling for a microgrid with wind turbines, micro-turbines, fuel cells, solar photovoltaic systems, and batteries to balance power and store excess energy. The aim is to minimize microgrid operating costs while considering environmental impacts. The optimization problem is framed as a multi-objective problem with nonlinear constraints, using fuzzy logic to aid decision-making. In the first scenario, the microgrid is optimized with all RESs installed within predetermined boundaries, in addition to grid connection. In the second scenario, the microgrid operates with a wind turbine at rated power. The third case study involves integrating plug-in hybrid electric vehicles (PHEVs) into the microgrid in three charging modes: coordinated, smart, and uncoordinated, utilizing standard and rated RES power. The SaCryStAl algorithm showed superior performance in operation cost, emissions, and execution time compared to traditional CryStAl and other recent optimization methods. The proposed SaCryStAl algorithm achieved optimal solutions in the first scenario for cost and emissions at 177.29 €ct and 469.92 kg, respectively, within a reasonable time frame. In the second scenario, it yielded optimal cost and emissions values of 112.02 €ct and 196.15 kg, respectively. Lastly, in the third scenario, the SaCryStAl algorithm achieves optimal cost values of 319.9301 €ct, 160.9827 €ct and 128.2815 €ct for uncoordinated charging, coordinated charging and smart charging modes respectively. Optimization results reveal that the proposed SaCryStAl outperformed other evolutionary optimization algorithms, such as differential evolution, CryStAl, Grey Wolf Optimizer, particle swarm optimization, and genetic algorithm, as confirmed through test cases.

Left atrial remodeling and voltage-guided ablation outcome in persistent atrial fibrillation patients according to CHA2DS2-VASc score.

BACKGROUND: CHA2DS2-VASc score-related differences have been reported in atrial fibrotic remodeling and prognosis of atrial fibrillation (AF) patients after ablation. There are currently no data on the efficacy of low voltage zone (LVZ)-guided ablation in persistent AF patients according to CHA2DS2-VASc score. We assessed in a cohort of persistent AF patients the extent of LVZ, the regional distribution of LA voltage and the outcome of LA voltage-guided substrate ablation in addition to PVI according to CHA2DS2-VASc score. METHODS: 138 consecutive persistent AF patients undergoing a first voltage-guided catheter ablation were enrolled. 58 patients with CHAD2DS2-VASc score ≥ 3 and 80 patients with CHAD2DS2-VASc score ≤ 2 were included. LA voltage maps were obtained using 3D-electroanatomical mapping system in sinus rhythm. LVZ was defined as < 0.5 mV. RESULTS: In the high CHAD2DS2-VASc score group, LA voltage was lower (1.5 [1.1-2.5] vs. 2.3 [1.5-2.8] mV, p = 0.02) and LVZs were more frequently identified (40% vs. 18%), p < 0.01). Female with CHA2DS2-VASc score ≥ 3 (p = 0.031), LA indexed volume (p = 0.009) and P-wave duration ≥ 150 ms (p = 0.001) were predictors of LVZ. After a 36-month follow-up, atrial arrhythmia-free survival was similar between the two groups (logrank test, P = 0.676). CONCLUSIONS: AF patients with CHAD2DS2-VASc score ≥ 3 display more LA substrate remodeling with lower voltage and more LVZs compared with those with CHAD2DS2-VASc score ≤ 2. Despite this atrial remodeling, they had similar and favorable 36 months results after one single procedure. Unlike male with CHAD2DS2-VASc score ≥ 3, female with CHAD2DS2-VASc score ≥ 3 was predictor of LVZ occurrence.

A full reference quality assessment method with fused monocular and binocular features for stereo images.

Aiming to automatically monitor and improve stereoscopic image and video processing systems, stereoscopic image quality assessment approaches are becoming more and more important as 3D technology gains popularity. We propose a full-reference stereoscopic image quality assessment method that incorporate monocular and binocular features based on binocular competition and binocular integration. To start, we create a three-channel RGB fused view by fusing Gabor filter bank responses and disparity maps. Then, using the monocular view and the RGB fusion view, respectively, we extract monocular and binocular features. To alter the local features in the binocular features, we simultaneously estimate the saliency of the RGB fusion image. Finally, the monocular and binocular quality scores are calculated based on the monocular and binocular features, and the quality scores of the stereo image prediction are obtained by fusion. Performance testing in the LIVE 3D IQA database Phase I and Phase II. The results of the proposed method are compared with newer methods. The experimental results show good consistency and robustness.

Trametinib for a child with refractory Rosai-Dorfman-Destombes disease harboring a novel somatic mutation in MAP2K1.

Rosai-Dorfman-Destombes disease (RDD) is a rare histiocytosis characterized by accumulation of S100 + , CD68 + , and CD1a- histiocytes, with emperipolesis. It occurs predominantly in black adolescents and young adults, but rarely in Japanese children. Recently, oncogenic mutations in mitogen-activated protein kinase (MAPK) pathway genes were reported in 30-50% of patients with RDD, and several studies have described treatment of adult patients with MAPK inhibitors. Here, we present the case of a Japanese boy with refractory RDD without signs of cardiofaciocutaneous (CFC) syndrome who harbored MAP2K1 p.Lys59del and responded to trametinib. The patient had lymph node, nasal cavity, kidney, upper respiratory tract, and intracranial involvement. RDD progressed after multi-agent chemotherapy, but responded to trametinib (0.025 mg/kg). Trametinib did not eliminate the mass lesions, but trametinib plus minimal prednisolone (0.1 mg/kg) resulted in a good outcome for more than 15 months, without significant adverse effects. MAP2K1 p.Lys59del has been described as a germline mutation in a patient with CFC syndrome, but not as a somatic mutation in patients with malignancies. Trametinib may be a promising drug for children with RDD that is refractory to multi-agent chemotherapy. Its long-term efficacy and safety alone and in combination with chemotherapy should be investigated.

Designing a Midwife-Led Birth Center Program Based on the MAP-IT Model: A Sequential Explanatory Mixed-Methods Study.

BACKGROUND: In recent decades, medical supervision of the labor and delivery process has expanded beyond its boundaries to the extent that in many settings, childbirth has become a medical event. This situation has influenced midwifery care. One of the significant barriers to midwives providing care to pregnant women is the medicalization of childbirth. So far, the policies and programs of the Ministry of Health to reduce medical interventions and cesarean section rates have not been successful. Therefore, the current study aims to be conducted with the purpose of "Designing a Midwife-Led Birth Center Program Based on the MAP-IT Model". METHODS/DESIGN: The current study is a mixed-methods sequential explanatory design by using the MAP-IT model includes 5 steps: Mobilize, Assess, Plan, Implement, and Track, providing a framework for planning and evaluating public health interventions in a community. It will be implemented in three stages: The first phase of the research will be a cross-sectional descriptive study to determine the attitudes and preferences towards establishing a midwifery-led birthing center focusing on midwives and women of childbearing age by using two researcher-made questionnaires to assess the participants' attitudes and preferences toward establishing a midwifery-led birthing center. Subsequently, extreme cases will be selected based on the participants' average attitude scores toward establishing a midwifery-led birthing center in the quantitative section. In the second stage of the study, qualitative in-depth interviews will be conducted with the identified extreme cases from the first quantitative phase and other stakeholders (the first and second steps of the MAP-IT model, namely identifying and forming a stakeholder coalition, and assessing community resources and real needs). In this stage, the conventional qualitative content analysis approach will be used. Subsequently, based on the quantitative and qualitative data obtained up to this stage, a midwifery-led birthing center program based on the third step of the MAP-IT model, namely Plan, will be developed and validated using the Delphi method. DISCUSSION: This is the first study that uses a mixed-method approach for designing a midwife-led maternity care program based on the MAP-IT model. This study will fill the research gap in the field of improving midwife-led maternity care and designing a program based on the needs of a large group of pregnant mothers. We hope this program facilitates improved eligibility of midwifery to continue care to manage and improve their health easily and affordably. ETHICAL CODE: IR.MUMS.NURSE.REC. 1403. 014.

In recent decades, medical management of the labor and delivery process has extended beyond its limitations to the extent that in many settings, childbirth has become a medical event. This situation has influenced midwifery care. The global midwifery situation indicates that one in every five women worldwide gives birth without the support of a skilled attendant. One of the significant barriers to midwives providing care to pregnant women is the medicalization of childbirth. In industrialized countries, maternal and infant mortality rates have decreased over the past 60 years due to medical or social reasons. So far, the policies and programs of the Ministry of Health to diminish medical interventions and cesarean section rates have not been successful. Midwifery models in hospital care contain midwives who support women's choices and diverse ideas about childbirth on the one hand, and on the other hand, they must adhere to organizational guidelines as employees, primarily based on a medical and pathological approach rather than a health-oriented and midwifery perspective. Therefore, the current study aims to be conducted with the purpose of "Designing a midwifery-led birth centered maternity program based on the MAP-IT model". It is a Model for Implementing Healthy People 2030, (Mobilize, Assess, Plan, Implement, Track), a step-by-step method for creating healthy communities. Using MAP-IT can help public health professionals and community changemakers implement a plan that is tailored to a community's needs and assets.

Design principles of multi-map variation in biological systems.

Complexity in biology is often described using a multi-map hierarchical architecture, where the genotype, representing the encoded information, is mapped to the functional level, known as the phenotype, which is then connected to a latent phenotype we refer to as fitness. This underlying architecture governs the processes driving evolution. Furthermore, natural selection, along with other neutral forces, can, in turn, modify these maps. At each level, variation is observed. Here, I propose the need to establish principles that can aid in understanding the transformation of variation within this multi-map architecture. Specifically, I will introduce three, related to the presence of modulators, constraints, and the modular channeling of variation. By comprehending these design principles in various biological systems, we can gain better insights into the mechanisms underlying these maps and how they ultimately contribute to evolutionary dynamics.

Probabilistic Nested Model Selection in Pharmacokinetic Analysis of DCE-MRI Data in Animal Model of Cerebral Tumor.

Purpose: Best current practice in the analysis of dynamic contrast enhanced (DCE)-MRI is to employ a voxel-by-voxel model selection from a hierarchy of nested models. This nested model selection (NMS) assumes that the observed time-trace of contrast-agent (CA) concentration within a voxel, corresponds to a singular physiologically nested model. However, admixtures of different models may exist within a voxel's CA time-trace. This study introduces an unsupervised feature engineering technique (Kohonen-Self-Organizing-Map (K-SOM)) to estimate the voxel-wise probability of each nested model. Methods: Sixty-six immune-compromised-RNU rats were implanted with human U-251N cancer cells, and DCE-MRI data were acquired from all the rat brains. The time-trace of change in the longitudinalrelaxivity Δ R 1 for all animals' brain voxels was calculated. DCE-MRI pharmacokinetic (PK) analysis was performed using NMS to estimate three model regions: Model-1: normal vasculature without leakage, Model-2: tumor tissues with leakage without back-flux to the vasculature, Model-3: tumor vessels with leakage and back-flux. Approximately two hundred thirty thousand (229,314) normalized Δ R 1 profiles of animals' brain voxels along with their NMS results were used to build a K-SOM (topology-size: 8×8, with competitive-learning algorithm) and probability map of each model. K-fold nested-cross-validation (NCV, k=10) was used to evaluate the performance of the K-SOM probabilistic-NMS (PNMS) technique against the NMS technique. Results: The K-SOM PNMS's estimation for the leaky tumor regions were strongly similar (Dice-Similarity-Coefficient, DSC=0.774 [CI: 0.731-0.823], and 0.866 [CI: 0.828-0.912] for Models 2 and 3, respectively) to their respective NMS regions. The mean-percent-differences (MPDs, NCV, k=10) for the estimated permeability parameters by the two techniques were: -28%, +18%, and +24%, for v p , K trans , and v e , respectively. The KSOM-PNMS technique produced microvasculature parameters and NMS regions less impacted by the arterial-input-function dispersion effect. Conclusion: This study introduces an unsupervised model-averaging technique (K-SOM) to estimate the contribution of different nested-models in PK analysis and provides a faster estimate of permeability parameters.

Beyond mutations: Accounting for quantitative changes in the analysis of protein evolution.

Molecular phylogenetic research has relied on the analysis of the coding sequences by genes or of the amino acid sequences by the encoded proteins. Enumerating the numbers of mismatches, being indicators of mutation, has been central to pertinent algorithms. Specific amino acids possess quantifiable characteristics that enable the conversion from "words" (strings of letters denoting amino acids or bases) to "waves" (strings of quantitative values representing the physico-chemical properties) or to matrices (coordinates representing the positions in a comprehensive property space). The application of such numerical representations to evolutionary analysis takes into account not only the occurrence of mutations but also their properties as influences that drive speciation, because selective pressures favor certain mutations over others, and this predilection is represented in the characteristics of the incorporated amino acids (it is not born out solely by the mismatches). Besides being more discriminating sources for tree-generating algorithms than match/mismatch, the number strings can be examined for overall similarity with average mutual information, autocorrelation, and fractal dimension. Bivariate wavelet analysis aids in distinguishing hypermutable versus conserved domains of the protein. The matrix depiction is readily subjected to comparisons of distances, and it allows the generation of heat maps or graphs. This analysis preserves the accepted taxa order where tree construction with standard approaches yields conflicting results (for the protein S100A6). It also aids hypothesis generation about the origin of mitochondrial proteins. These analytical algorithms have been automated in R and are applicable to various processes that are describable in matrix format.