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Poverty and associated health-related social needs can negatively impact child health. As pediatric health systems implement social needs screening programs, they should aim to measure and promote equal rates of screening across demographic groups and to support families in connecting to resources.We describe implementation of the Linking Families to Support (LiFTS) quality improvement initiative, an inpatient social needs screening and support program. Our objectives were to (1) implement screening across inpatient units, (2) promote equal screening rates across demographic groups, and (3) optimize rates of resource connection. LiFTS was implemented at a quaternary care children’s hospital. Families of children admitted to participating units during the study period (September 2022-February 2024) were eligible for screening.Over the 18-month project period, we implemented screening in 9 inpatient units. Of 2582 eligible caregivers, 1741 (67.4%) were offered screening. Of these caregivers, 667 (38.3%) declined screening and 1074 (61.6%) completed screening. A total of 496 families (46.2%) reported 1 or more social needs. In analyses stratified by child race, ethnicity, insurance status, and preferred language, we observed equal rates of screening. Among 233 families reached in follow-up, 183 (78.5%) recalled receiving resources and 133 (57.1%) reported connecting to 1 or more resources.Our interdisciplinary team successfully implemented social needs screening across 9 inpatient units, achieved equal rates of screening, and measured caregiver-reported rates of resource connection. Our approach could guide other health systems as they implement social needs screening programs that meet regulatory requirements, prioritize equality in screening, and support resource connection.

In order to predict streamflow and understand the associated snow dynamics in a data scarce situation for the snow-dominated, wooded, hilly Alaknanda River basin in India's Western Himalayan area, the Soil and Water Assessment Tool (SWAT) model was set up. Measured discharge from 2010 to 2012 and 2013 to 2015 were used as calibration and validation data in the current study, respectively. As a warm-up period, data from the first two years (2008–2009) were used. To incorporate SWAT in the study, ArcSWAT interface was used, and parameter optimization was performed using SWAT-CUP/SUFI2 algorithm (Sequential Uncertainty Fitting version 2). The sensitivity analysis revealed that the streamflow of the region is influenced by 20 parameters, indicating their significant role in shaping the hydrological patterns. The temperature lapse rate (TLAPS) was observed to be the most significant parameter. The values of Nash Sutcliffe Efficiency (NSE), the coefficient of determination (R2) and the Percent Bias (PBIAS) for the calibration period were 0.91, 0.92, and + 5.1%, respectively. The validation (2013–2015) of the streamflow data resulted in the values of the NSE, R2, and PBIAS as 0.84, 0.86, and − 2.9%, respectively. In the Alaknanda River Basin, 58.3% of the total precipitation of the whole year was converted into streamflow/total runoff. About 10.61% of the streamflow/total runoff was contributed by the snowmelt of the region, thereby significantly affecting the discharge of the region.

In India, currently, there are no standard guidelines for the management of moderate acute malnutrition (MAM). Previous research in Bangladesh has shown that children with MAM have impaired gut microbiota development, and microbiota-directed complementary foods (MDCF) can potentially repair their gut microbiota.

Intel’s efforts to build a practical quantum computer are focused on developing a scalable spin-qubit platform leveraging industrial high-volume semiconductor manufacturing expertise and 300 mm fabrication infrastructure. Here, we provide an overview of the design, fabrication, and demonstration of a new customized quantum test chip, which contains 12-quantum-dot spin-qubit linear arrays, code named Tunnel Falls. These devices are fabricated using immersion and extreme ultraviolet lithography (EUV), along with other standard high-volume manufacturing (HVM) processes as well as production-level process control. We present key device features and fabrication details as well as qubit characterization results confirming device functionality. These results corroborate our fabrication methods and are a crucial step toward scaling of extensible 2D qubit array schemes.

Molecular conformer generation (MCG) is an important task in cheminformatics and drug discovery. The ability to efficiently generate low-energy 3D structures can avoid expensive quantum mechanical simulations, leading to accelerated virtual screenings and enhanced structural exploration. Several generative models have been developed for MCG, but many struggle to consistently produce high-quality conformers for meaningful downstream applications. To address these issues, we introduce CoarsenConf, which coarse-grains molecular graphs based on torsional angles and integrates them into an SE(3)-equivariant hierarchical variational autoencoder. Through equivariant coarse-graining, we aggregate the fine-grained atomic coordinates of subgraphs connected via rotatable bonds, creating a variable-length coarse-grained latent representation. Our model uses a novel aggregated attention mechanism to restore fine-grained coordinates from the coarse-grained latent representation, enabling efficient generation of accurate conformers. Furthermore, we evaluate the chemical and biochemical quality of our generated conformers on multiple downstream applications, including property prediction and large-scale oracle-based protein docking. Overall, CoarsenConf generates more accurate conformer ensembles compared to prior generative models.

Pre-eclampsia is a placental disorder that affects 3–5% of all pregnancies and is a leading cause of maternal and fetal morbidity worldwide1,2. With no drug available to slow disease progression, engineering ionizable lipid nanoparticles (LNPs) for extrahepatic messenger RNA (mRNA) delivery to the placenta is an attractive therapeutic option for pre-eclampsia. Here we use high-throughput screening to evaluate a library of 98 LNP formulations in vivo and identify a placenta-tropic LNP (LNP 55) that mediates more than 100-fold greater mRNA delivery to the placenta in pregnant mice than a formulation based on the Food and Drug Administration-approved Onpattro LNP (DLin-MC3-DMA)3. We propose an endogenous targeting mechanism based on β2-glycoprotein I adsorption that enables LNP delivery to the placenta. In both inflammation- and hypoxia-induced models of pre-eclampsia, a single administration of LNP 55 encapsulating vascular endothelial growth factor (VEGF) mRNA resolves maternal hypertension until the end of gestation. In addition, with our VEGF mRNA LNP 55 therapeutic, we demonstrate improvements in fetal health and partially restore placental vasculature, the local and systemic immune landscape and serum levels of soluble Fms-like tyrosine kinase-1, a clinical biomarker of pre-eclampsia1. Together, these results demonstrate the potential of this mRNA LNP platform for treating placental disorders such as pre-eclampsia.

Introduction: The current gold standard for imaging to rule out extra-hepatic biliary atresia (EHBA) is hepatobiliary scintigraphy (HBS), which involves visually assessing the tracer appearance in the bowel. However, in cases where hepatic function is impaired, biliary-to-bowel transit may not be observable, even in neonatal hepatitis (NH) cases. This study aims to assess the utility of semi-quantitative parameters on HBS to distinguish biliary atresia (BA) from NH when there is a lack of biliary-to-bowel transit for up to 24 h. Materials and methods: The study involved retrospective analysis of patients with the diagnosis of neonatal cholestasis where HBS failed to differentiate BA and NH. Histopathological examination was taken as the gold standard. Semiquantitative parameters calculated include: Liver: blood pool (LBR) and liver: kidney ratios (LKR) at 5 min, 30 min, 1 h and 24 h. Mean values for the two groups were calculated. Student’s t-test was employed to assess the statistical significance of difference of mean between the two groups. Receiver operating characteristic (ROC) curve was also drawn to determine a cut-off of these ratios to differentiate between the two groups using SPSS v26.0. P-value < 0.05 was considered statistically significant. Results: The study included 53 patients (37 males) with a median age of 3 months (range: 24 days to 10 months). Of these, 32 patients had a histopathological diagnosis of BA, while 21 had NH. Mean LBR and LKR at 24 h were statistically different in the two groups (p-value < 0.05). Receiver operating characteristic (ROC) curve analyses showed highest AUC for LBR at 24 h 0.683 (CI:0.532–0.834, p-value 0.017) and LKR at 24 h − 0.669 (CI: 0.511–0.827, p-value:0.036). For diagnosis of BA a cut-off value of ≤4.18 for LBR at 24 h (sensitivity and specificity of 62.5% and 61.9% respectively) and ≤4.64 for LKR at 24 h (sensitivity and specificity of 68.8% and 66.7% respectively) were found to be pertinent. Conclusion: HBS serves as non-invasive imaging of choice to rule out EHBA. Semi-quantitative indices LBR and LKR at the 24-hour can differentiate between EHBA and NH even in cases with compromised hepatic function where traditional visual interpretation of tracer transit proves inadequate.

IntroductionNevoid basal cell carcinoma syndrome (NBCCS) is a rare autosomal dominant disorder classically associated with multiple basal cell carcinomas, odontogenic keratocysts and skeletal anomalies. However, its significant phenotypic heterogeneity often delays the diagnosis. Here, we undertake the first comprehensive characterisation of NBCCS and congenital urinary tract anomalies.MethodsClinical evaluation followed by genetic testing was performed on a proband with congenital hydronephrosis due to ureteropelvic obstruction. Then, a cohort of patients with molecularly confirmed NBCCS evaluated at a single institution was analysed, followed by a comprehensive review of the literature.ResultsThe novel, non-canonical splice-site variant c.349+4 delA in PTCH1was detected in a proband, with RNA analysis confirming exon 2 skipping. Of the additional nine NBCCS cases examined at our institution, a second proband with a nonsense variant in PTCH1was identified with renal agenesis and a bladder diverticulum. A literature review then yielded 11 case reports of patients with congenital urinary tract anomalies, most frequently renal agenesis.DiscussionCongenital urinary tract anomalies are a variable finding in NBCCS. Renal ultrasound may be warranted at the time of initial diagnosis, if not previously performed. Moreover, PTCH1should be included in multigene panels that assess for congenital urinary tract disorders.

Neural stimulation is used routinely to diagnose and treat neurological disorders. The stimulation artifacts are, however, problematic for closed-loop neuromodulation therapy, which dynamically adjusts the electrical stimulation parameters based on real-time feedback from the recorded neural activity because they can cause saturation or prolonged recovery times in traditional recording front ends. This article presents a per-pixel second-order $\Delta \Sigma $ analog-to-digital converter (ADC) for direct digitization of neural signals, which addresses the stimulation artifact recovery time in voltage-controlled oscillator (VCO)-based quantizers with a fast-recovery, overrange-detecting phase quantizer. The ADC uses a pseudo-virtual ground feedforwarding (PVG FF) technique and a complementary input ${G} _{\text {m}}$ -C filter with per-pixel decimation. It supports four recording modes covering 2.5–20 kS/s through a power-efficient, bandwidth-scalable continuous time $\Delta \Sigma $ modulator. Fabricated in a 180-nm CMOS process, this $300\times 300~\mu $ m2 ADC achieves $\gt 250\times $ faster (0.05–0.4 ms) stimulation artifact recovery time, enabling in-stimulation recording. Recording with artifact tolerance was demonstrated through an in vivo whisker barrel rat experiment.

Women are the largest growing population of Veterans within the U.S. Department of Veterans Affairs (VA) Health Care System. Among women Veterans, breast cancer is the most common malignancy (30% of all cancers), yet little is known about the unique needs of women Veterans with cancer and how to provide them with high quality care. The VA health care system has initiated multiple system-wide systemic efforts, including launching the Breast and Gynecologic Cancer System of Excellence (BGSOE) to address this knowledge gap. This report summarizes the outcomes of the inaugural 2023 VA Women’s Cancer Research Conference, which assembled 37 multidisciplinary clinicians, scientists, the VA and civilian partners with a shared goal of advancing VA breast cancer research. Conference objectives were to build a collective vision for improving: (1) referral patterns for breast cancer treatment and patient-level outcomes and (2) molecular and genetic testing patterns across the breast cancer continuum among women Veterans. The meeting hosted 15 speakers at the Houston VA Medical Center. Future research priorities for women Veterans with cancer were identified from discussions and a post-conference survey. We then administered a 13-question post-conference survey to conference attendees. Respondents ranked the research priorities. The survey results show that the cross-cutting cancer research priorities designed to transform cancer care for women Veterans at the VA fit into 5 broad areas of study, including (1) care quality for treatment, (2) improving treatment, (3) care quality of molecular and genetic testing, (4) risk reduction through risk assessment and germline genetic testing, and (5) establishing strategic partnerships. Our data elucidate areas for further investigation to improve the delivery of cancer care.

Bioactive phyto-components are eco-friendly alternatives to harmful synthetic fungicides. Gymnema sylvestrecontains many multifunctional bioactive compounds; however, it is yet to be explored for comprehensive chemical profiling and efficient management of fungal decay in storage. The present study demonstrated optimization of the production of bioactive compounds from G. sylvestreleaves, displaying broad-spectrum efficacy against storage fungi. Ethyl acetate soluble fraction (EAGS) exhibited the highest efficacy against Penicillium expansum2995 (effective concentration for 50% inhibition (EC50) 102.3 µg/ml) followed by Aspergillus flavus8529 (EC50109.5 µg/ml), Penicillium digitatum7910 (EC50201.1 µg/ml), Aspergillus parasiticus6365 (EC50209.6 µg/ml) and Fusarium verticillioides8271 (EC50285.2 µg/ml). Response surface methodology (RSM)-based optimization of ultrasonication-assisted extraction (UAE) of bioactive phyto-compounds revealed a maximum production of EAGS (106.83 mg/g sample) with 50 W amplitude, 10.6 min time and 20 ml solvent/g of sample. Comprehensive phytochemical profiling using UPLC-QToF-MSEgenerated tentative identification of 35 compounds, dominating gymnemic acid VII. Among these, gymnemic acid VII and gymnemagenin were further isolated and characterized using 1H-nuclear magnetic resonance (NMR), 13C-NMR and HRMS. The interaction mechanism of the phyto-components, responsible for fungal growth inhibition, was determined using molecular docking analysis and validated with fungal ergosterol biosynthesis and membrane ionic leakage inhibition. Gymnemic acid I (− 33.7 kJ/mol) and gymnemagenin (− 31.5 kJ/mol) exhibited higher binding affinity with the target-specific protein through conventional hydrogen bonds and hydrophobic pi–alkyl interactions. High-value G. sylvestrephytochemicals could be further exploited to achieve tangible outcomes in managing fungal decay under postharvest storage.

MicroRNAs (miRNAs) associate with Argonaute (AGO) proteins to form complexes that direct mRNA repression. miRNAs are also the subject of regulation. For example, some miRNAs are destabilized through a pathway in which pairing to specialized transcripts recruits the ZSWIM8 E3 ubiquitin ligase, which polyubiquitinates AGO, leading to its degradation and exposure of the miRNA to cellular nucleases. Here, we found that 22 miRNAs in Caenorhabditis elegansare sensitive to loss of EBAX-1, the ZSWIM8 ortholog in nematodes, implying that these 22 miRNAs might be subject to this pathway of target-directed miRNA degradation (TDMD). The impact of EBAX-1 depended on the developmental stage, with the greatest effect on the miRNA pool (14.5%) observed in L1 larvae, and the greatest number of different miRNAs affected (17) observed in germline-depleted adults. The affected miRNAs included the miR-35–42 family, as well as other miRNAs among the least stable in the worm, suggesting that TDMD is a major miRNA-destabilization pathway in the worm. The excess miR-35–42 molecules that accumulated in ebax-1mutants caused increased repression of their predicted target mRNAs and underwent 3′ trimming over time. In general, however, miRNAs sensitive to EBAX-1 loss had no consistent pattern of either trimming or tailing. Replacement of the 3′ region of miR-43 substantially reduced EBAX-1 sensitivity, a result that differed from that observed previously for miR-35. Together, these findings broaden the implied biological scope of TDMD-like regulation of miRNA stability in animals, and indicate that a role for miRNA 3′ sequences is variable in the worm.

Change point detection (CPD) is a valuable technique in time series (TS) analysis, which allows for the automatic detection of abrupt variations within the TS. It is often useful in applications such as fault, anomaly, and intrusion detection systems. However, the inherent unpredictability and fluctuations in many real-time data sources pose a challenge for existing contemporary CPD techniques, leading to inconsistent performance across diverse real-time TS with varying characteristics. To address this challenge, we have developed a novel and robust online CPD algorithm constructed from the principle of discriminant analysis and based upon a newly proposed between-class average and variance evaluation approach, termed B-CAVE. Our B-CAVE algorithm features a unique change point measure, which has only one tunable parameter (i.e. the window size) in its computational process. We have also proposed a new evaluation metric that integrates time delay and the false alarm error towards effectively comparing the performance of different CPD methods in the literature. To validate the effectiveness of our method, we conducted experiments using both synthetic and real datasets, demonstrating the superior performance of the B-CAVE algorithm over other prominent existing techniques.

Background In very low birth weight infants, mother’s own milk (MOM) feeding is an essential part of the bundle of best practices to reduce potentially preventable neonatal morbidities and associated costs. Mothers of preterm infants can have an altered sequence of lactogenesis because of their preterm delivery and mother–infant separation. Healthy mothers with term infants typically experience coming to volume(CTV), that is, MOM volume of ≥ 500 ml/day, by the end of the second week of postpartum. There is paucity of data regarding MOM output in preterm mothers.Objective To assess MOM output and factors influencing MOM volume among mothers delivering <32 weeks during the first two weeks after birth. To determine the proportion of mothers attaining CTV and whether the first two weeks’ MOM volume predicts MOM feeding at discharge and 40 weeks corrected gestational age (CGA).Methodology In this prospective observational study conducted at a tertiary care NICU over a period of 18 months, the milk output of the preterm mothers was quantified, and the proportion of infants fed with MOM at discharge and 40 weeks of corrected age was assessed.Results The median milk output per day at the end of the first and second weeks was 180 IQR (100, 290) ml and 300 IQR (178, 420) ml, respectively. Earlier initiation of kangaroo mother care, higher birth weight of the infant, increase in the frequency of daytime milk expression and non-nutritive suckling (NNS) contributed to increased MOM output per day. The proportion of mothers who came to volume (milk output of ≥500 ml/day) by day 14 was 26 (19%). The proportion of babies on predominant MOM feeding at discharge and at 40 weeks’ follow-up was 96 (72%) and 75 (61.5%) infants, respectively. Mothers who came to volume were more likely to feed MOM at 40 weeks [odds ratio (OR) 5.2 (1.2–23.0)].Conclusion Higher birth weight, more frequency of daytime milk expression, earlier initiation of KMC and NNS and longer duration of KMC are factors improving the MOM output. Mothers who came to volume by the first two weeks after birth sustained feeding with MOM till 40 weeks CGA.

Graphical Abstract:

•Immunodeficient mice with murine HMOX-1 deletion have persisting hRBCs in their peripheral blood.•Immunodeficient mice with murine HMOX-1 deletion have reduced erythrophagocytic macrophages.

In March 2017, the Uttarakhand High Court granted legal personhood to the Ganga and Yamuna rivers, along with their tributaries, marking a significant development in India’s recognition of nature’s rights. This decision came shortly after New Zealand’s Te Awa Tupua (Whanganui River Settlement Act) 2017, which recognised the Whanganui River as a legal entity. While New Zealand’s legal recognition was the result of decades of negotiations, culminating in statutory enactment for a single river, India’s approach was through judicial conferment, a more expedited process which lacked in-depth deliberation. In contrast to the approaches in India and New Zealand, which focus specifically on the rights of rivers, Ecuador and Bolivia have integrated nature’s rights into their constitutions, elevating environmental protection to a constitutional obligation for all of nature. This framework seeks to balance ecological integrity with human interests but faces significant enforcement challenges due to competing development priorities. Although the Supreme Court of India later overturned the Uttarakhand High Court’s ruling as ‘legally unworkable,’ the Indian discourse on the rights of nature can still draw valuable lessons from New Zealand’s Te Awa Tupua enactment and the constitutional recognition of nature’s rights in Ecuador and Bolivia. These examples highlight both the potential and the challenges of granting legal personhood to nature, offering important insights for shaping future policies in India. By synthesising these experiences, this casenote calls for a deeper societal connection to nature, urging a shift in perspective from conquerors to caretakers, and fostering a sustainable and just coexistence with the natural world.

This paper provides developments in statistical shape analysis of shape graphs, and demonstrates them using such complex objects as Retinal Blood Vessel (RBV) networks and neurons. The shape graphs are represented by sets of nodes and edges (articulated curves) connecting some nodes. The goals are to utilize nodes (locations, connectivity) and edges (edge weights and shapes) to: (1) characterize shapes, (2) quantify shape differences, and (3) model statistical variability. We develop a mathematical representation, elastic Riemannian metrics, and associated tools for shape graphs. Specifically, we derive tools for shape graph registration, geodesics, statistical summaries, shape modeling, and shape synthesis. Geodesics are convenient for visualizing optimal deformations, and PCA helps in dimension reduction and statistical modeling. One key challenge lies in comparing shape graphs with vastly different complexities (in number of nodes and edges). This paper introduces a novel multi-scale representation to handle this challenge. Using the notions of (1) “effective resistance” to cluster nodes and (2) elastic shape averaging of edge curves, it reduces graph complexity while retaining overall structures. This allows shape comparisons by bringing graphs to similar complexities. We demonstrate these ideas on 2D RBV networks from the STARE and DRIVE databases and 3D neurons from the NeuroMorpho database.

This study attempts to unmask the relative importance of partisan alignments vis-à-vis the relevance of individual candidate characteristics for the voters. To facilitate this analysis, our study relies on comparing the election outcomes of incumbent parties against those of incumbent candidates using data from the Indian national elections from 1977 to 2014. The idea hinges on the fact that electoral returns may vary according to the ‘ideological’ alignments of the party (incumbent) vis-a-vis the idiosyncratic factors of the candidates (incumbent). We also analyse the role of political reservation in influencing these voters’ alignments. Our results indicate that while, on average, incumbent parties and candidates are significantly disadvantaged in comparison to their non-incumbent counterparts, the electoral choice of the voters favours parties more than the candidates. However, our analysis of the impact of political reservation shows that an incumbent individual candidate faces far less disadvantages than the incumbent parties in reserved constituencies.

Emotional Artificial Intelligence (Emotional AI), with its advanced capability to detect, analyze, and interpret human emotions, presents a groundbreaking opportunity for enhancing various aspects of policing and criminology. This paper delves into the integration of Emotional AI in these fields, highlighting its potential to revolutionize crime detection, prevention, and the improvement of interactions within the criminal justice system. By categorizing the applications of Emotional AI, from predictive policing to emotional assessments during interrogations, the paper explores how this technology can offer novel insights into criminal behavior and support mental health initiatives. Additionally, it addresses the ethical considerations associated with Emotional AI's deployment, such as privacy, bias, and the accuracy of emotion interpretation. The survey synthesizes current challenges and proposes future research directions, aiming to guide the responsible integration of Emotional AI technologies in law enforcement practices. The paper emphasizes the need for a balanced approach that respects individual rights while harnessing Emotional AI's benefits for justice and public safety.

Perceptual image hashing is a significant and time-effective method for recognizing images within extensive databases, focusing on achieving two key objectives: robustness and discrimination. The right balance between these two aspects remains a significant challenge in contemporary hashing research. Moreover, many image hashing algorithms face limitations when performing satisfactorily against specific image processing attacks, such as rotation. With this in mind, a rotation correction based perceptual image hashing system is designed called as Pyramusing a pyramid histogram of gradients (PHOG). The system exploits the properties of log polar transform for invariance to geometric distortions and then the PHOG in blocks for generating the final hash vector. In computing hash similarity, the correlation is employed as the metric of choice. The trade-off between robustness and discrimination is evaluated on benchmark databases against single and double attacks. Furthermore, the comprehensive experiments further confirm that the PHOG method consistently delivers better accuracy than its state-of-the-art methods.

Single-nucleus analysis allows robust cell-type classification and helps to establish relationships between chromatin accessibility and cell-type-specific gene expression. Here, using samples from 92 women of several genetic ancestries, we developed a comprehensive chromatin accessibility and gene expression atlas of the breast tissue. Integrated analysis revealed ten distinct cell types, including three major epithelial subtypes (luminal hormone sensing, luminal adaptive secretory precursor (LASP) and basal-myoepithelial), two endothelial and adipocyte subtypes, fibroblasts, T cells, and macrophages. In addition to the known cell identity genes FOXA1(luminal hormone sensing), EHFand ELF5(LASP), TP63and KRT14(basal-myoepithelial), epithelial subtypes displayed several uncharacterized markers and inferred gene regulatory networks. By integrating breast epithelial cell gene expression signatures with spatial transcriptomics, we identified gene expression and signaling differences between lobular and ductal epithelial cells and age-associated changes in signaling networks. LASP cells and fibroblasts showed genetic ancestry-dependent variability. An estrogen receptor-positive subpopulation of LASP cells with alveolar progenitor cell state was enriched in women of Indigenous American ancestry. Fibroblasts from breast tissues of women of African and European ancestry clustered differently, with accompanying gene expression differences. Collectively, these data provide a vital resource for further exploring genetic ancestry-dependent variability in healthy breast biology.