Adherence and acceptability of multiple micronutrient supplementation during pregnancy: Study protocol for a cluster-randomized non-inferiority trial in Cambodia.

BACKGROUND: Iron and folic acid (IFA) supplements are currently provided to Cambodian women during pregnancy. However, recent research has found benefits of a multiple micronutrient supplement (MMS) over just IFA alone on several outcomes of perinatal and infant health. The Ministry of Health in Cambodia has proposed a transition from IFA to MMS but to effectively guide this transition requires implementation research on the acceptability and adherence to MMS (over IFA). METHODS: This non-inferiority trial aims to assess the adherence and acceptability of IFA (60 mg elemental iron and 400 µg folic acid) compared to MMS (standard UNIMMAP formulation including 15 micronutrients) during antenatal care in Cambodia. A prospective cohort of 1545 pregnant women will be assigned to one of three trial arms: (1) IFA for 90 days [IFA-90]; (2) MMS for 180 days with two distributions of 90-count tablet bottles [MMS-90]; or (3) MMS for 180 days with one 180-count tablet bottle [MMS-180]. Each arm will enroll 515 women across 48 health centers (clusters) in Kampong Thom Province in Cambodia. The primary outcome is the non-inferiority of adherence rates of MMS-180 compared to IFA-90, as assessed by tablet counts. Mixed-effects logistic and linear regression models will be used to estimate the difference in the adherence rate between the two groups, with an 'a priori' determined non-inferiority margin of 15%. Acceptability of MMS and IFA will be measured using a quantitative survey conducted with enrolled pregnant women at 30-day, 90-day, and 180-day time-points. DISCUSSION: Findings from this study will guide an effective and feasible MMS scale-up strategy for Cambodia. Additionally, the findings will be shared globally with other stakeholders planning to scale up MMS in other countries. TRIAL REGISTRATION: NCT05867836 ( ClinicalTrials.gov , registered May 18, 2023).

A review on potential approach for in silico toxicity analysis of respirable fraction of ambient particulate matter.

Epidemiological and toxicological studies have shown the adverse effect of ambient particulate matter (PM) on respiratory and cardiovascular systems inside the human body. Various cellular and acellular assays in literature use indicators like ROS generation, cell inflammation, mutagenicity, etc., to assess PM toxicity and associated health effects. The presence of toxic compounds in respirable PM needs detailed studies for proper understanding of absorption, distribution, metabolism, and excretion mechanisms inside the body as it is difficult to accurately imitate or simulate these mechanisms in lab or animal models. The leaching kinetics of the lung fluid, PM composition, retention time, body temperature, etc., are hard to mimic in an artificial experimental setup. Moreover, the PM size fraction also plays an important role. For example, the ultrafine particles may directly enter systemic circulations while coarser PM10 may be trapped and deposited in the tracheo-bronchial region. Hence, interpretation of these results in toxicity models should be done judiciously. Computational models predicting PM toxicity are rare in the literature. The variable composition of PM and lack of proper understanding for their synergistic role inside the body are prime reasons behind it. This review explores different possibilities of in silico modeling and suggests possible approaches for the risk assessment of PM particles. The toxicity testing approach for engineered nanomaterials, drugs, food industries, etc., have also been investigated for application in computing PM toxicity.

Erythema Multiforme: Unveiling the Unusual Effect of an Ayurvedic Medication 'Jambavasa' Used in the Treatment of Type 2 Diabetes Mellitus.

Erythema multiforme (EM) is a rare immune-mediated condition that can manifest as cutaneous, mucosal, or both types of lesions. The target lesion, with concentric zones of color change, is a cutaneous feature that is typical of this illness. Despite the fact that a number of factors can lead to EM, the most common being Herpes simplex virus (HSV) infection, drug-induced EM is a rare entity. As disease severity and mucosal involvement vary across individuals, treatment should be optimized for each patient, considering the risk versus benefit ratio. To distinguish EM from other clinical imitators and to confirm the diagnosis, histopathologic tests and other laboratory procedures may be utilized. Our patient presented with symptoms suggestive of a viral infection, such as fever and rash, but the RTPCR report for various viral infections came out to be negative, hence indicative of the diagnosis of drug-induced erythema multiforme.

Application of Convolutional Neural Networks for COVID-19 Detection in X-ray Images Using InceptionV3 and U-Net.

COVID-19 has expanded overall across the globe after its initial cases were discovered in December 2019 in Wuhan-China. Because the virus has impacted people's health worldwide, its fast identification is essential for preventing disease spread and reducing mortality rates. The reverse transcription polymerase chain reaction (RT-PCR) is the primary leading method for detecting COVID-19 disease; it has high costs and long turnaround times. Hence, quick and easy-to-use innovative diagnostic instruments are required. According to a new study, COVID-19 is linked to discoveries in chest X-ray pictures. The suggested approach includes a stage of pre-processing with lung segmentation, removing the surroundings that do not provide information pertinent to the task and may result in biased results. The InceptionV3 and U-Net deep learning models used in this work process the X-ray photo and classifies them as COVID-19 negative or positive. The CNN model that uses a transfer learning approach was trained. Finally, the findings are analyzed and interpreted through different examples. The obtained COVID-19 detection accuracy is around 99% for the best models.

Text messages to improve child diets: Formative research findings and protocol of a randomised controlled trial in Nepal.

Given the role of malnutrition in childhood morbidity and mortality, the prioritisation of maternal and child nutrition programmes has grown significantly in the 21st century. Policies and programmes aim to improve infant and young child feeding, but questions persist about the most effective combination of interventions to achieve desired behaviour change. There is increasing interest in mobile-based interventions globally, but scant evidence exists to guide donors, policymakers and programme implementers on their effectiveness. Formative research was conducted to assess the feasibility and acceptance of text message-based interventions and to guide the final design of the text message intervention. This protocol is for a cluster-randomised controlled trial to test the effectiveness of adding text messaging to other ongoing SBC interventions to promote egg consumption, dietary diversity and other ideal dietary practices, particularly among children 12-23 months of age in Kanchanpur, Nepal. The trial findings will contribute to the emerging body of evidence on the effectiveness of using text messages for behaviour change, specifically for young child dietary outcomes in South Asia. Recent studies have suggested that mobile-based interventions alone may be insufficient but valuable when added to other social and behavioural interventions; this trial will help to provide evidence for or against this emerging theory. This trial was registered at ClinicalTrials.gov on 11 March 2019 (ID: NCT03926689) and has been updated twice.

A Study of the International Stock Market Behavior During COVID-19 Pandemic Using a Driven Iterated Function System.

We propose a novel approach to visualize and compare financial markets across the globe using chaos game representation (CGR) of iterated function systems (IFS). We modified a fractal method, widely used in life sciences, and applied it to study the effect of COVID-19 on global financial markets. This modified driven IFS approach is used to generate compact fractal portraits of the financial markets in form of percentage CGR (PC) plots and subtraction percentage (SP) plots. The markets over different periods are compared and the difference is quantified through a parameter called the proximity (Pr) index. The reaction of the financial market across the globe and volatility to the current pandemic of COVID-19 is studied and modeled successfully. The imminent bearish and a surprise bullish pattern of the financial markets across the world is revealed by this fractal method and provides a new tool to study financial markets.

Distal coronary artery abnormalities in Kawasaki disease: experience on CT coronary angiography in 176 children.

OBJECTIVE: Precise evaluation of coronary artery abnormalities (CAAs) in Kawasaki disease (KD) is essential. The aim of this study is to determine role of CT coronary angiography (CTCA) for detection of CAAs in distal segments of coronary arteries in patients with KD. METHODS: CTCA findings of KD patients with distal coronary artery involvement were compared with those on transthoracic echocardiography (TTE) during the period 2013-21. RESULTS: Among 176 patients with KD who underwent CTCA (128-Slice Dual Source scanner), 23 (13.06%) had distal CAAs (right coronary-15/23; left anterior descending-14/23; left circumflex-4/23 patients). CTCA identified 60 aneurysms-37 proximal (36 fusiform; 1 saccular) and 23 distal (17 fusiform; 6 saccular); 11 patients with proximal aneurysms had distal contiguous extension; 9 patients showed non-contiguous aneurysms in both proximal and distal segments; 4 patients showed distal segment aneurysms in absence of proximal involvement of same coronary artery; 4 patients had isolated distal CAAs. On TTE, only 40 aneurysms could be identified. Further, distal CAAs could not be identified on TTE. CTCA also identified complications (thrombosis, mural calcification and stenosis) that were missed on TTE. CONCLUSIONS: CAAs can, at times, occur in distal segments in isolation and also in association with, or extension of, proximal CAAs. CTCA demonstrates CAAs in distal segments of coronary arteries, including branches, in a significant number of children with KD-these cannot be detected on TTE. CTCA may therefore be considered as a complimentary imaging modality in children with KD who have CAAs on TTE.

Echocardiographic indices of left ventricular function and filling pressure are not related to blood pool activity on pyrophosphate scintigraphy.

BACKGROUND: Pyrophosphate (PYP) imaging has a high diagnostic accuracy for transthyretin cardiac amyloidosis (ATTR-CA). Indeterminate findings are often reported due to persistent blood pool activity, presumed to be from low cardiac output. We evaluated the relationship between blood pool activity on PYP imaging and echocardiographic indices of cardiac function. METHODS: Clinical and imaging data of 189 patients referred for PYP scintigraphy were evaluated. All patients underwent planar imaging and SPECT (diagnostic standard). Among those with a negative PYP SPECT, persistent left ventricular blood pool activity on planar images was inferred by a visual score ≥2 or a heart-to-contralateral (HCL) ratio ≥ 1.5. Absence of blood pool activity was inferred when both visual score was < 2 and HCL was < 1.5. Left ventricular ejection fraction (LVEF), global longitudinal strain (GLS), stroke volume index (SVi), and left atrial pressure (LAP) were calculated from standard transthoracic echocardiograms. RESULTS: ATTR-CA was present in 43 (23%) patients. Among those with a negative PYP SPECT, 11 patients had significant blood pool activity. Patients with ATTR-CA had a lower LVEF, SVi, and GLS, with a higher LAP, compared to those without ATTR-CA. Among those without ATTR-CA, there were no significant differences in these parameters. CONCLUSION: Approximately 8% of patients with a negative PYP SPECT have significant blood pool activity. Measures of cardiac function are not different among those with and without blood pool activity. PYP SPECT should be routinely performed in all patients to avoid false image interpretation.

Automated detection of mild cognitive impairment and dementia from voice recordings: A natural language processing approach.

INTRODUCTION: Automated computational assessment of neuropsychological tests would enable widespread, cost-effective screening for dementia. METHODS: A novel natural language processing approach is developed and validated to identify different stages of dementia based on automated transcription of digital voice recordings of subjects' neuropsychological tests conducted by the Framingham Heart Study (n = 1084). Transcribed sentences from the test were encoded into quantitative data and several models were trained and tested using these data and the participants' demographic characteristics. RESULTS: Average area under the curve (AUC) on the held-out test data reached 92.6%, 88.0%, and 74.4% for differentiating Normal cognition from Dementia, Normal or Mild Cognitive Impairment (MCI) from Dementia, and Normal from MCI, respectively. DISCUSSION: The proposed approach offers a fully automated identification of MCI and dementia based on a recorded neuropsychological test, providing an opportunity to develop a remote screening tool that could be adapted easily to any language.

Ultra-high resolution, multi-scale, context-aware approach for detection of small cancers on mammography.

While detection of malignancies on mammography has received a boost with the use of Convolutional Neural Networks (CNN), detection of cancers of very small size remains challenging. This is however clinically significant as the purpose of mammography is early detection of cancer, making it imperative to pick them up when they are still very small. Mammography has the highest spatial resolution (image sizes as high as 3328 × 4096 pixels) out of all imaging modalities, a requirement that stems from the need to detect fine features of the smallest cancers on screening. However due to computational constraints, most state of the art CNNs work on reduced resolution images. Those that work on higher resolutions, compromise on global context and work at single scale. In this work, we show that resolution, scale and image-context are all important independent factors in detection of small masses. We thereby use a fully convolutional network, with the ability to take any input size. In addition, we incorporate a systematic multi-scale, multi-resolution approach, and encode image context, which we show are critical factors to detection of small masses. We show that this approach improves the detection of cancer, particularly for small masses in comparison to the baseline model. We perform a single institution multicentre study, and show the performance of the model on a diagnostic mammography dataset, a screening mammography dataset, as well as a curated dataset of small cancers < 1 cm in size. We show that our approach improves the sensitivity from 61.53 to 87.18% at 0.3 False Positives per Image (FPI) on this small cancer dataset. Model and code are available from  https://github.com/amangupt01/Small_Cancer_Detection.

Sustaining Agriculture and Nutrition Interventions: Continued Engagement of Village Model Farmers in Nepal.

BACKGROUND: In homestead food production (HFP) programs, village model farmers (VMFs), after training, implement agriculture and nutrition activities to improve household knowledge and practices. Little evidence exists on what enables VMFs to remain actively engaged and for impacts to be sustained. OBJECTIVE: To examine variables explaining active engagement of VMFs, at least 4 years post-training, in an HFP program in Nepal. METHODS: We used cross-sectional data, collected from 2018 to 2019, among 4750 VMFs of Suaahara, a multisectoral nutrition program. We assessed whether respondents registered their HFP group with the local government, conducted regular group meetings, discussed vegetable growing and chicken rearing practices with group members, or engaged in saving and credit activities in their HFP group. Outcome variable was a count of these 4 activities in which the VMF engaged. Socioeconomic, demographic, and programmatic explanatory variables were identified a priori and by bivariate analysis and were adjusted in ordinal regression models accounting for clusters. RESULTS: On average, VMFs engaged in 1.4 activities. Having attended primary or secondary school (adjusted odds ratios [AOR] = 1.39), being a female community health volunteer (AOR = 1.27), being from an advantaged caste/ethnic group (AOR = 1.34), receiving additional trainings (AOR = 1.56) and inputs (AOR = 1.31) were associated with more active engagement of VMFs. CONCLUSION: Village model farmers receiving more training and inputs were more likely to remain actively engaged. Female community health workers, people from higher caste/ethnic groups, and those with primary or secondary education were more likely to remain active VMFs and could be targeted for this role in HFP programs leading to sustained impact.

Early Versus Late Administration of P2Y 12 Inhibitors in Non-ST Segment Elevation Myocardial Infarction and Delayed Cardiac Catheterization.

ABSTRACT: Regardless of early invasive or ischemia-guided approaches to non-ST segment elevation myocardial infarction (NSTEMI) management, P2Y 12 inhibitors remain the backbone in therapy. The ideal timing of administration remains unclear. The purpose of this study was to determine the safety and effectiveness of early versus late administration of P2Y 12 inhibitors in patients presenting with an NSTEMI who go to the catheterization laboratory beyond 24 hours from presentation. We performed a single center, retrospective cohort study. Patients were classified into groups depending on whether they received early versus late administration of a P2Y 12 inhibitor. The primary outcome was the rate of major and clinically relevant, nonmajor bleeding (CRNMB). Secondary outcomes included troponin peak and length of stay after cardiac catheterization. Of the 121 patients included, 53 patients were in the early and 68 patients were in the late group. The number of bleeding events were similar between both groups ( P = 1.00). There were 3 (5.7%) major bleeding events in the early group and 5 (7.4%) bleeding events in the late group. There were 5 (9.4%) CRNMB events in the early group and 6 (8.8%) CRNMB events in the late group. There was a significant difference in troponin peak, 4.56 ng/mL in the early group and 1.77 ng/mL in the late group ( P = 0.02). The rate of bleeding did not differ between patients who received early or late administration of P2Y 12 inhibitors for NSTEMI management who undergo delayed cardiac catheterization.

Cellulose Nanocrystals: Tensile Strength and Failure Mechanisms Revealed Using Reactive Molecular Dynamics.

Cellulose nanocrystals (CNCs) offer excellent mechanical properties. However, measuring the strength by performing reliable experiments at the nanoscale is challenging. In this paper, we model Iß crystalline cellulose using reactive molecular dynamics simulations. Taking the fibril twist into account, structural changes and hydrogen-bonding characteristics of CNCs during the tensile test are inspected and the failure mechanism of CNCs is analyzed down to the scale of individual bonds. The C4-O4 glycosidic bond is found to be responsible for the failure of CNCs. Finally, the effect of strain rate on ultimate properties is analyzed and a nonlinear model is used to predict the ultimate strength of 9.2 GPa and ultimate strain of 8.5% at a 1 s-1 strain rate. This study sheds light on the applications of cellulose in nanocomposites and further modeling of cellulose nanofibres.

Recent Advances in the Surfactant and Controlled Release Polymer-based Solid Dispersion.

The oral route is the most preferred delivery route for drug administration due to its advantages, such as lower cost, improved patient compliance, no need for trained personnel, and less severity of drug reactions in general. The major problem with new molecules in the drug discovery pipeline is poor solubility and dissolution rate that ultimately results in low oral bioavailability. Numerous techniques are available for solubility and bioavailability (BA) enhancement, but out of all, solid dispersion (SD) is proven to be the most feasible due to fewer issues in manufacturing, processing, storage, and transportation. In the past few years, SD has been extensively applied to reinforce the common issues of insoluble drugs. Currently, many hydrophobic and hydrophilic polymers are used to prepare either immediate release or controlled release SDs. Therefore, the biological behavior of the SDs is contingent upon the use of appropriate polymeric carriers and methods of preparation. The exploration of novel carriers and methodologies in SD technology leads to improved BA and therapeutic effectiveness. Moreover, the clinical applicability of SD-based formulations has been increased with the discovery of novel polymeric carriers. In this review, emphasis is laid down on the present status of recent generations of SDs (i.e., surfactant and controlled release polymer-based SD) and their application in modifying the physical properties of the drug and modulation of pharmacological response in different ailments.

Nourishing Hope? Changes in Malnutrition and Changes in Girls' Aspirations-Evidence From the Suaahara II Adolescent Girls Panel in Nepal.

PURPOSE: Malnutrition is a pressing public health challenge in South Asia with adverse consequences for adolescent girls' well-being and, potentially, aspirations as drivers of developmental progress. This study aimed to investigate associations between changes in malnutrition and changes in girls' aspirations in key life domains. METHODS: We analyzed two-period panel data from the Suaahara II Adolescent Girls Panel (10-19 years) in Nepal (2018-2019, n = 613). Height, weight, blood samples, 24-hour dietary recalls, and indicators of girls' educational, occupational, marital, and fertility aspirations were collected. Height-for-age z-scores, body mass index-for-age z-scores, hemoglobin concentration (Hb g/dL), and dietary diversity scores for women were calculated. Through cluster-robust fixed-effects regressions, we examined whether changes in thinness (body mass index-for-age z-scores < -2 standard deviation), anemia (Hb <115 g/L nonpregnant <11 years; Hb <120 g/L nonpregnant >12 years; Hb <110 g/L pregnant), and reaching minimum dietary diversity for women were associated with changes in educational, marital, or fertility aspirations. RESULTS: A change from thinness to no thinness increased girls' aspired ages of having a first child by 2.77 years (standard error [SE] 1.22, p = .025). A change from anemia to no anemia increased girls' aspired years of education by .54 (SE .27, p = .044). This association was stronger for postmenarche girls (b -.62, SE .29, p = .035). No associations were found between changes in minimum dietary diversity for women and any of the aspirations. CONCLUSIONS: Thinness and anemia were negatively associated with adolescent girls' aspirations in domains of fertility and education. Multisectoral integrated policies and programs that improve adolescent nutritional status and diets have the potential to foster adolescent girls' aspirations and thereby increase their future potential.

Renal artery thrombosis and mucormycosis in a COVID-19 patient.

The novel coronavirus disease 2019 (COVID-19) has been postulated to be associated with hypercoagulability, leading to thromboembolism in major blood vessels. There are also increasing reports of invasive fungal infections in COVID-19 patients. We report a unique case of mucormycosis associated with renal artery thrombosis leading to renal infarction and nephrectomy in a COVID-19 patient. This is the first such reported case to our knowledge.

An Artificial Intelligence-Assisted Method for Dementia Detection Using Images from the Clock Drawing Test.

BACKGROUND: Widespread dementia detection could increase clinical trial candidates and enable appropriate interventions. Since the Clock Drawing Test (CDT) can be potentially used for diagnosing dementia-related disorders, it can be leveraged to develop a computer-aided screening tool. OBJECTIVE: To evaluate if a machine learning model that uses images from the CDT can predict mild cognitive impairment or dementia. METHODS: Images of an analog clock drawn by 3,263 cognitively intact and 160 impaired subjects were collected during in-person dementia evaluations by the Framingham Heart Study. We processed the CDT images, participant's age, and education level using a deep learning algorithm to predict dementia status. RESULTS: When only the CDT images were used, the deep learning model predicted dementia status with an area under the receiver operating characteristic curve (AUC) of 81.3% ± 4.3%. A composite logistic regression model using age, level of education, and the predictions from the CDT-only model, yielded an average AUC and average F1 score of 91.9% ±1.1% and 94.6% ±0.4%, respectively. CONCLUSION: Our modeling framework establishes a proof-of-principle that deep learning can be applied on images derived from the CDT to predict dementia status. When fully validated, this approach can offer a cost-effective and easily deployable mechanism for detecting cognitive impairment.

Comparative Assessment of Peritoneal Membrane Characteristics in Patients on Continuous Ambulatory Peritoneal Dialysis Using Standard Peritoneal Equilibration Test and Fast Peritoneal Equilibration Test.

BACKGROUND: Evaluation of peritoneal membrane permeability in patients on continuous ambulatory peritoneal dialysis (CAPD) is crucial in prescribing treatment regimens. This study evaluated peritoneal membrane characteristics in patients on CAPD using standard peritoneal equilibration test (PET) and fast PET. METHODS: A prospective observational longitudinal study included patients on CAPD with no symptoms of peritonitis for at least 4 weeks before the PET. Both, standard and fast PET were performed using 2.5% glucose-containing dialysate. The dialysate and plasma (D/P) creatinine ratios at each time point (i.e., 0 h, 2nd h, and 4th h) in standard and at 4th hour only in fast PET were determined. Patients were classified according to D/P creatinine value as high, high-average, low-average, low transporter. The follow-up period was 6 months and changes in membrane characteristics were compared again to revalidate the efficacy of fast PET. RESULTS: A total of 50 patients between 41 and 70 years of age were enrolled. The majority had diabetic nephropathy (40%) and chronic glomerulonephritis (28%). Based on transport type, a significant positive correlation was observed between the D/P creatinine ratio of baseline standard PET I and fast PET I (r = 0.992, P ≤ 0.05) and standard PET II and fast PET II (r = 0.969, P ≤ 0.05) done after 6 months. The results of the PET and transport category after 6 months were similar in 82% cases determined by fast PET and 98% cases determined by the standard pet. There was significant agreement between both the methods of PET (K value = 0.872, P < 0.001). A significant (P ≤ 0.001) correlation was observed between standard PET I and standard PET II transport status. CONCLUSION: Fast PET is a good alternative for assessing peritoneal membrane characteristics especially in the setting of less availability of resources and is a less cumbersome procedure as compared to standard PET.