Miracle-dz/UniFAR-FTUs huggingface dataset:
Re-activation of neurogenic niches in aging brain

Recent studies proposing induced glia-to-neuron conversion raised the potential for generating new neurons to replace those lost due to injury, aging or neurodegenerative diseases. Here, single-cell spatial transcriptomics [Multiplexed Error Robust Fluorescence In Situ Hybridization (MERFISH)] is used to construct a spatial cell atlas of the subventricular and dentate gyrus neurogenic niches of young and aged adult murine brain. RNAs that encode the RNA binding protein Polypyrimidine Tract-Binding Protein (PTBP1) in the aged murine brain are determined to be highest in glia that line previously active neurogenic niches. A glial cell population with ependymal character within an initially quiescent subventricular neurogenic niche in the aged murine brain is identified that upon transient suppression of PTBP1 reenters the cell cycle, replicates DNA, and converts into neurons through a canonical adult neurogenesis pathway. Glia-derived neurons migrate from this niche, with some neurons transiting to the striatum and acquiring a transcriptome characteristic of GABAergic inhibitory neurons. Similar PTBP1 expressing quiescent glia are identified in the corresponding neurogenic niche of aged human brain. Thus, transient reduction of PTBP1 holds potential for inducing the generation of new neurons in quiescent neurogenic niches of the aged nervous system, thereby offering promising therapeutic applications. Bullet point summary 1) Single-cell spatial transcriptomics is used to validate active neurogenesis in the two neurogenic niches of the young adult murine brain, determine that those niches are quiescent in the aging adult brain of mice, and demonstrate the absence of neurogenesis in the aging human brain. 2) The RNA binding protein PTBP1 is determined to be most highly expressed within glia that line the aged murine and human neurogenic niches, with its transient reduction sufficient in mice to activate/re-activate expression of genes characteristic of immature neurons. 3) Suppression of PTBP1 using a single intra-cerebral-ventricular injection of PTBP1–targeting antisense oligonucleotide (ASO) induces generation of new immature neurons in the neurogenic niches of the aged mouse brain via a canonical adult neurogenesis pathway. 4) Single-cell RNA signature tracing is used to identify a) a subclass of ependymal cells in a previously quiescent neurogenic niche of the aged mouse brain that convert into GABAergic inhibitory neurons following transient suppression of PTBP1, and b) the molecular steps in the conversion process including cell cycle re-entry, DNA replication, and transcriptome changes that mimic canonical neurogenesis. 5) A similar class of PTBP1-expressing ependymal cells lining the ventricle of the aging non-human primate and human brains is identified, suggesting the promise of re-activation of neurogenesis as a therapeutic approach in humans.
Inferring neural dynamics of memory during naturalistic social communication

Memory processes in complex behaviors like social communication require forming representations of the past that grow with time. The neural mechanisms that support such continually growing memory remain unknown. We address this gap in the context of fly courtship, a natural social behavior involving the production and perception of long, complex song sequences. To study female memory for male song history in unrestrained courtship, we present ‘Natural Continuation’ (NC)—a general, simulation-based model comparison procedure to evaluate candidate neural codes for complex stimuli using naturalistic behavioral data. Applying NC to fly courtship revealed strong evidence for an adaptive population mechanism for how female auditory neural dynamics could convert long song histories into a rich mnemonic format. Song temporal patterning is continually transformed by heterogeneous nonlinear adaptation dynamics, then integrated into persistent activity, enabling common neural mechanisms to retain continuously unfolding information over long periods and yielding state-of-the-art predictions of female courtship behavior. At a population level this coding model produces multi-dimensional advection-diffusion-like responses that separate songs over a continuum of timescales and can be linearly transformed into flexible output signals, illustrating its potential to create a generic, scalable mnemonic format for extended input signals poised to drive complex behavioral responses. This work thus shows how naturalistic behavior can directly inform neural population coding models, revealing here a novel process for memory formation.
Convolutional neural networks as a model for brain area MSTd

Accuracy-optimized convolutional neural networks (CNNs) have emerged as highly effective models at predicting neural responses in brain areas along the primate ventral stream, but it is largely unknown whether they effectively model neurons in the complementary primate dorsal stream. We explored how well CNNs model the optic flow tuning properties of neurons in dorsal area MSTd and we compared our results with the Non-Negative Matrix Factorization (NNMF) model proposed by Beyeler, Dutt, & Krichmar (2016), which successfully models many tuning properties of MSTd neurons. To better understand the role of computational properties in the NNMF model that give rise to MSTd-like optic flow tuning, we created additional CNN model variants that implement key NNMF constraints — non-negative weights and sparse coding of optic flow. While the CNNs and NNMF models both accurately estimate the observer’s self-motion from purely translational or rotational optic flow, NNMF and the CNNs with nonnegative weights yield substantially less accurate estimates than the other CNNs when tested on more complex optic flow that combines observer translation and rotation. Despite their poor accuracy, however, neurons in the networks with the nonnegativity constraint give rise to tuning properties that align more closely with those observed in primate MSTd. Interestingly, the addition of the sparsity constraint has a negligible effect on the accuracy of self-motion estimates and model tuning properties. Across all models, we consistently observe the 90-degree offset in the preferred translation and rotation directions found in MSTd neurons, which suggests that this property could emerge through a range of potential computational mechanisms. This work offers a step towards a deeper understanding of the computational properties and constraints that describe optic flow tuning primate area MSTd. Significance Statement One of the most exciting developments in visual neuroscience over the past decade is that convolutional artificial neural networks optimized to accurately categorize natural images effectively model neural activity in ventral visual areas of the primate brain. We explored whether accuracy-optimized neural networks account for well-established properties of MSTd, a brain area in the complementary primate dorsal stream that is involved in self-motion perception during navigation. Our findings indicate that such networks depart substantially from MSTd-like tuning, which suggests the computational goal of MSTd may not be to accurately estimate self-motion. We found that adding computational constraints inspired by an existing MSTd model that performs dimensionality reduction on afferent motion signals improves the correspondence with MSTd.
Estuarine circulation versus tidal pumping: Sediment transport in a well-mixed tidal inlet

High-resolution water column observations have been carried out in the Wadden Sea to understand suspended particulate matter (SPM) transport in well-mixed tidal channels. These observations include more than 4000 consecutive CTD, microstructure shear and turbidity profiles from a free-falling microstructure probe, as well as velocity data from an ADCP and SPM samples for calibration. A horizontal density gradient was established by a landward temperature gradient built up during an extraordinarily warm and calm spring season. Tidal averaging along σ-layers (relative depth) provides the first direct observations of along-channel estuarine circulation in the Wadden Sea, with net inflow near the bottom and outflow near the surface. Increased westerly (up-estuary) winds during the second part of the campaign weakened and eventually even reversed estuarine circulation and yielded a net barotropic eastward transport. SPM concentrations showed a strong quarter-diurnal signal with maxima near full flood and full ebb and were generally lower during the calm period and increased during the windy period, mainly due to wave-related resuspension over nearby intertidal flats. The sediment flux analysis was based on a decomposition of the vertically integrated SPM flux into a barotropic advective component, an estuarine circulation component and a tidal pumping component. As a result, tidal pumping (due to ebb-dominance weakly seaward) dominated the SPM flux during calm conditions, whereas barotropic advection dominated the strong landward SPM flux during the windy period. Along-channel estuarine circulation is found to be of minor importance for the net SPM transport in such well-mixed systems.
Multiscale Modeling of Water Transport and the Influence of Water Quality Parameters on Membrane Processes

Membrane-based desalination processes have become a viable means of producing potable water to meet water resource needs in both industrialized and developing nations. Extensive experimental investigation, in conjunction with computational modeling is critical in the development of sustainable and cost-effective desalination technologies. The overall goal of this dissertation is to develop a multiscale modeling framework to elucidate water and salt transport mechanisms and the influence of water quality parameters on membrane processes. The key tasks involved in this study are: establish a criterion for estimating water flux using Bayesian inference; develop a multiscale framework to connect molecular dynamics (MD) simulations to the process level; and evaluate the influence of different water chemistry conditions on water flux in forward and reverse osmosis membrane processes. Simulations are conducted to evaluate water transport and natural organic matter (NOM) fouling propensity in cellulose-triacetate (CTA) and nanoporous graphene (NPG) membranes. Bayesian updating of a probabilistic model is performed to estimate membrane permeability and a process model is developed to predict full-scale water flux through the membrane. Results of the Bayesian inference indicate that the use of unique structural configurations in MD simulations is essential to capture realistic membrane properties at the molecular scale. Full-scale water flux predictions based on estimated membrane parameters is within the same order of magnitude of experimental data suggesting that simulations at the molecular level can potentially be scaled up to reflect process level conditions. Moreover, surface functionalization of NPG membranes can enhance water flux and salt rejection and improve antifouling capabilities. NOM adsorption onto NPG membrane is energetically favored and results in water flux decline across the membrane due to increased resistance to flow. The results further indicate that fouling propensity of graphene-based v membranes is influenced by surface functionalization which dictates the strength of the interactions between the membranes and potential foulants. This work highlights the feasibility of forward osmosis processes and the potential application of ultrathin graphene membranes for water desalination. The findings can complement experimental studies to better understand observations at the macro-scale and expedite the development of mechanistic strategies for optimizing membrane performance.
FIU Digital Commons FIU Digital Commons

Objective: Malignancy-related ascites (MRA) is the terminal stage of many advanced cancers, and the treatment is mainly palliative. This study looked for epidemiology and inpatient hospital outcomes of patients with MRA in the United States using a national database. Methods: The current study was a cross-sectional analysis of 2015 National Inpatient Sample data and consisted of patients (cid:2) 18 years with MRA. Descriptive statistics were used for understanding demographics, clinical characteristics, and MRA hospitalization costs. Multivariate regression models were used to identify predictors of length of hospital stay and in-hospital mortality. Results: There were 123 410 MRA hospitalizations in 2015. The median length of stay was 4.7 days (interquartile range [IQR]: 2.5-8.6 days), median cost of hospitalization was US$43 543 (IQR: US$23 485-US$82 248), and in-hospital mortality rate was 8.8% (n ¼ 10 855). Multivariate analyses showed that male sex, black race, and admission to medium and large hospitals were associated with increased hospital length of stay. Factors associated with higher in-hospital mortality rates included male sex; Asian or Pacific Islander race; beneficiaries of private insurance, Medicaid, and self-pay; patients residing in large central and small metro counties; nonelective admission type; and rural and urban nonteaching hospitals. Conclusions: Our study showed that many demographic, socioeconomic, health care, and geographic factors were associated with hospital length of stay and in-hospital mortality and may suggest disparities in quality of care. These factors could be targeted for preventing unplanned hospitalization, decreasing hospital length of stay, and lowering in-hospital mortality for this population
SPOT-1D-LM: Reaching Alignment-profile-based Accuracy in Predicting Protein Secondary and Tertiary Structural Properties without Alignment

Protein language models have emerged as an alternative to multiple sequence alignment for enriching sequence information and improving downstream prediction tasks such as biophysical, structural, and functional properties. Here we show that a combination of traditional one-hot encoding with the embeddings from two different language models (ProtTrans and ESM-1b) allows a leap in accuracy over single-sequence based techniques in predicting protein 1D secondary and tertiary structural properties, including backbone torsion angles, solvent accessibility and contact numbers. This large improvement leads to an accuracy comparable to or better than the current state-of-the-art techniques for predicting these 1D structural properties based on sequence profiles generated from multiple sequence alignments. The high-accuracy prediction in both secondary and tertiary structural properties indicates that it is possible to make highly accurate prediction of protein structures without homologous sequences, the remaining obstacle in the post AlphaFold2 era.
Factors contribute to the incidence of maternal death among pregnant women in Diyala Governorate, Iraq

: The mortality of a woman during pregnancy, childbirth, and within 42 days after giving birth has an immediate detrimental effect on both her family and community, Annually, it is estimated that over 770 women in the United States die due to pregnancy or complications associated to pregnancy. Maternal mortality is a significant medical issue that places a strain on the global healthcare system and necessitates meticulous investigation to identify its underlying causes. This prospective study was carried out to examine the various factors that influence maternal mortality among pregnant women in the Diyala Governorate. Assuming that the elements that govern maternal mortality include age, cause of death, residency, and number of children, these factors were involved in this study. A cross-sectional study was conducted among 75 pregnant women in Diyala Governorate to assess these characteristics. The aim was to determine the link between maternal mortality and parameters such as age, causes of death, residency, and parity among women. Study results revealed that the predominant number of fatalities among women took place within the age range of 21 to 30, with the subsequent highest occurrence observed among women aged 31 to 40,Cardiovascular disease was the primary determinant of these deaths, representing 43% of all mortality causes, Uterine hemorrhage was the second most common cause of mortality, responsible for 29% of all deaths, The survey also found that women residing in rural areas had a significantly greater mortality rate, accounting for 53%, compared to their urban counterparts; in addition, the survey revealed that 76% of the female population consisted of multigravida women, indicating that they had experienced numerous pregnancies, in contrast to primigravida women who were pregnant for the first time. Study's findings posit that cardiovascular disease is the leading cause of death for women overall, particularly among younger women (those aged 21–30), rural women, and women who have already given birth many times.
The Effects of Cerebral Vasospasm on Cerebral Blood Flow and the Effects of Induced Hypertension: A Mathematical Modelling Study

Background: Induced hypertension has been used to promote cerebral blood flow under vasospastic conditions although there is no randomised clinical trial to support its use. We sought to mathematically model the effects of vasospasm on the cerebral blood flow and the effects of induced hypertension. Methods: The Anatomically Detailed Arterial Network (ADAN) model is employed as the anatomical substrate in which the cerebral blood flow is simulated as part of the simulation of the whole body arterial circulation. The pressure drop across the spastic vessel is modelled by inserting a specific constriction model within the corresponding vessel in the ADAN model. We altered the degree of vasospasm, the length of the vasospastic segment, the location of the vasospasm, the pressure (baseline mean arterial pressure [MAP] 90 mm Hg, hypertension MAP 120 mm Hg, hypotension), and the presence of collateral supply. Results: Larger decreases in cerebral flow were seen for diffuse spasm and more severe vasospasm. The presence of collateral supply could maintain cerebral blood flow, but only if the vasospasm did not occur distal to the collateral. Induced hypertension caused an increase in blood flow in all scenarios, but did not normalise blood flow even in the presence of moderate vasospasm (30%). Hypertension in the presence of a complete circle of Willis had a marginally greater effect on the blood flow, but did not normalise flow. Conclusion: Under vasospastic condition, cerebral blood flow varies considerably. Hypertension can raise the blood flow, but it is unable to restore cerebral blood flow to baseline.
The Effect of Entrepreneurial Performance among the Mango Growers in Salem District of Tamil Nadu

The study was undertaken with the objectives of analysis of entrepreneurial performance of mango growers in Salem district of Tamil Nadu. Sankari Block was selected based on the maximum area under mango cultivation. A sample size of 120 mango cultivating farmers was selected by using the proportionate random sampling technique. The required data were collected by personal interview utilizing a well-structured and pre-tested interview schedule. The result revealed that the 60 per cent of the respondents came under a medium level of entrepreneurial performance of mango farming. Around one-fourth of the respondents came under low level of entrepreneurial performance and only a small proportion of the respondents (13.33%) were under high level of entrepreneurial performance of mango cultivation.
Journal of Community Hospital Internal Medicine Perspectives Journal of Community Hospital Internal Medicine Perspectives

Background : Coronavirus-19, primarily a respiratory virus, affects multiple organs and can lead to exacerbation of autoimmune or systemic conditions. Patients with autoimmune diseases, rheumatoid arthritis particularly, are susceptible to infection and complications from COVID-19. RA has become well-associated with COVID-19 infections, but large-scale studies evaluating outcomes among this vulnerable group are limited. Methods : For the retrospective analysis, we used the National Inpatient Sample database to compare COVID-19 patients with and without RA. A total of 1,050,040 adult hospitalizations were included in the study between January 1 to December 31, 2020: COVID-19 with RA ( n ¼ 21,545; 2.1%) and COVID-19 without RA ( n ¼ 1,028,495; 97.9%). The primary outcome was in-hospital mortality. Secondary outcomes included mechanical ventilation requirement, vasopressor use, cardiac arrest, cardiogenic shock, acute kidney injury, acute kidney injury requiring hemodialysis, gastrostomy, tracheostomy, length of stay, health care utilization costs, and disposition. A secondary analysis evaluating in-hospital mortality and mechanical ventilation with respect to age was conducted. Results : COVID-19 patients with RA had signi ﬁ cantly increased in-hospital mortality compared to COVID-19 patients without RA (12.9% vs 11.1%, adjusted OR [aOR]: 1.2 [95% CI 1.1 e 1.3], p < 0.001). This cohort also had signi ﬁ cantly increased rates of mechanical ventilation, pressor use, and cardiogenic shock. Conclusions : Given limited large evidence regarding COVID-19 with respect to RA, future research should be focused on this topic to improve outcomes for this subset of patients.
ARPN Journal of Science and Technology::Absorption Capacity of CO2, NO2, and Dustfall Emission from Transportation, Industry, and Livestock Sectors in Bogor City by Bogor Botanical Garden

One of the environmental issues was the increasing of air pollution concentration. On the other hand, Bogor Botanical Gardens had high potential as an air quality controller. This study aims to calculate Bogor Botanical Gardens plants ability to reduce CO2, NO2, and dustfall emission, analyzing the correlation of leave morphology with the plant ability in absorb dustfall, and determine criteria of plant that can reduce CO2, NO2, and dustfall. Total amount of CO2, NO2, and dustfall emission and Bogor Botanical Garden sink ability was calculated by secondary data from multiple source unit and its corresponding emission factors. The ability of several plants to absorb dustfall was calculated by gravimetric method using samples from Bogor Botanical Garden. The sample plants were Sansevieria trifasciata, Cinnamomum multiflorum, Callicarpa pedunculata, Carmona retusa, and Antigonon leptopus. The analysis showed that Bogor Botanical Gardens were able to reduce CO2 emissions by 28.7%, NO2 by 2.2%, and dustfall by 11.4%. Plant ability to absorb dustfall was 0.02-0.7 mg/cm 2 . The most effective species to absorb dustfall was Carmona retusa with maximum capacity of 0.7 mg/cm 2 .
Sustainable paper-based packaging from hemp hurd fiber: A potential material for thermoformed molded fiber packaging

Hemp hurd fiber, a low-value waste stream from the hemp industry, has potential downstream applications as an alternative to non-renewable plastics for single-use food service ware and packaging applications. Packaging paper substrates made from chemically pulped hemp hurd, mixed in varying ratios with bleached thermomechanical radiata pine pulp were developed and tested. Handsheets were characterized using several mechanical property tests including tensile strength, tearing resistance, burst strength, short-span compression, ring crush, together with Gurley air resistance, contact angle, and Cobb60 tests. Generally, addition of hemp hurd fibers significantly improved handsheet mechanical properties. Hot-pressing of the handsheets so as to approximate molded fiber thermoforming further enhanced their performance, with pure hemp hurd handsheets having the highest mechanical properties and barrier performance. A prototype was successfully thermoformed from hemp fiber, demonstrating overall feasibility of this fibre source for molded fibre objects.