The present study was designed to report the prevalence of spotted fever group Rickettsia and Anaplasma in ticks from Pakistan. To address this knowledge gap, ticks were collected from October 2019 to November 2020 from livestock hosts. 390 ticks from Punjab, Khyber Pakhtunkhwa, and Islamabad were investigated for the presence of Rickettsia and Anaplasma. The collected ticks were subjected to molecular studies for detection and characterization of spotted fever group Rickettsia and Anaplasma in ticks from Pakistan. PCR amplification of the ompA gene was used for detection of Rickettsia and portions of the 16S rDNA gene for detection of Anaplasma. Nine species of ticks were tested. 7/390 (2.58%) of ticks were positive for Rickettsia. Rickettsia spp. were detected in Haemaphysalis punctata, Hyalomma anatolicum, Hyalomma scupense, Rhipicephalus microplus, and Rhipicephalus sanguineus. Unknown Rickettsia was detected in Hy. scupense. 57 (14.6%) ticks were also positive for Anaplasma spp. Anaplasma ovis was detected in Hy. anatolicum, Hy. scupense, Hy. excavatum, Rhipicephalus decoloratus, R. microplus, and R. sanguineus. Anaplasma marginale was detected in Hy. anatolicum, Hy. scupense, R. microplus, R. decoloratus, and R. sanguineus. The Anaplasma sequences obtained from this experiment were 99–100% similar to those of documented strains. This study provides information and confirms the presence of spotted fever group Rickettsia and Anaplasma spp. in different tick species. It also highlights the need for control programs to prevent health risks. Further investigation to determine the prevalence and disease burden of these pathogens in Pakistan is necessary.

Parkinson’s disease (PD) has become the second most prominent neurogenerative disorder relating to aging individuals. PD involves the loss of neurons containing dopamine in the midbrain and leads to a number of motor issues as well as non-motor complications such as cognitive and psychological abnormalities. The default mode network (DMN) is a complex brain network primarily active during rest and serves multiple roles relating to memory, self-referential processing, social cognition and consciousness and awareness. Multiple brain regions are involved in the DMN such as the medial prefrontal cortex (mPFC), the posterior cingulate cortex (PCC), the inferior parietal lobule, the precuneus and the lateral temporal cortex. Normal DMN connectivity is vital to preserving consciousness and self-awareness. Neurological pathologies such as PD disrupt DMN connectivity, leading to complex issues. Functional MRI (fMRI) is a neuroimaging modality used to observe brain activity through measuring blood flow differences as it relates to brain activity. DMN connectivity experiments using fMRI find that individuals with PD exhibit impaired DMN connectivity in specific regions including the PCC, mPFC and the precuneus. Individuals with greater PD motor symptoms have also been found to suffer larger alterations in DMN connections anatomically within the frontal lobe and PCC. While fMRI has been utilized as a tool to explore the relationship between PD patients and DMN connectivity, future research should look to develop a better understanding of the specific mechanisms of action that drive this link between DMN abnormality and PD severity.

Hypertensive disorders of pregnancy (HDP) and postpartum depression (PPD) are significant global health challenges affecting maternal and child well-being. HDP, including pre-eclampsia, gestational hypertension, and chronic hypertension, complicate up to 10% of pregnancies worldwide, with profound implications for maternal mortality, particularly in low- to middle-income countries (LMICs) like Ghana. The incidence of HDP is rising globally, contributing substantially to maternal deaths and severe perinatal outcomes such as stillbirth and low birth weight. Concurrently, perinatal mental health issues, including PPD, affect a significant proportion of women globally, with higher prevalence rates observed in LMICs. Despite the known physiological impacts of HDP, their association with maternal mental health remains underexplored, especially in LMIC contexts. A systematic review and meta-analysis were conducted to explore the association between HDP and PPD in LMICs, focusing on available literature and studies from diverse global settings. Additionally, semi-structured qualitative interviews were conducted with healthcare professionals in Ghana to gather insights into local perspectives and experiences regarding this association. The systematic review revealed a consistent association between HDP and increased risk of PPD across various LMIC settings. Meta-analysis findings indicated a significant pooled odds ratio, highlighting a robust statistical linkage between HDP severity and subsequent PPD risk. Qualitative data underscored healthcare professionals’ observations of heightened psychological distress among women with HDP, emphasizing the complex interplay between physiological complications and maternal mental health outcomes in the Ghanaian context. The study findings underscore the critical need for integrated maternal health strategies that address both physical and psychological aspects of pregnancy complications like HDP. By elucidating these connections, the study contributes to advancing evidence-based interventions and support systems tailored to LMIC settings, aiming to mitigate adverse maternal mental health outcomes and improve overall perinatal care in Ghana and similar contexts worldwide. These insights are pivotal for informing policy decisions, guiding healthcare practices, and fostering targeted interventions that enhance maternal well-being during the vulnerable perinatal period.

Asian corn borer, Ostrinia furnacalis Guenée (Lepidoptera: Crambidae), is a major pest in corn production, and its management remains a significant challenge. Current control methods, which rely heavily on synthetic chemical pesticides, are environmentally detrimental and unsustainable, necessitating the development of eco-friendly alternatives. This study investigates the potential of the entomopathogenic nematode Steinernema carpocapsae as a biological control agent for O. furnacalis pupae, focusing on its infection efficacy and the factors influencing its performance. We conducted a series of laboratory experiments to evaluate the effects of distance, pupal developmental stage, soil depth, and light conditions on nematode attraction, pupal mortality and sublethal impacts on pupal longevity and oviposition. Results demonstrated that S. carpocapsae exhibited the highest attraction to pupae at a 3 cm distance, with infection declining significantly at greater distances. Younger pupae (<12 h old), were more attractive to nematodes than older pupae, and female pupae were preferred over males. Nematode infection was highest on the head and thorax of pupae, with a significant reduction in infection observed after 24 h. Infection caused 100% mortality in pupae within 2 cm soil depth, though efficacy was reduced under light conditions. Sublethal effects included a significant reduction in the longevity of infected adults and a decrease in the number of eggs laid by infected females compared to controls. These findings underscore the potential of S. carpocapsae as an effective biocontrol agent for sustainable pest management in corn production, offering a viable alternative to chemical pesticides.

Objectives/Goals: This work aims to identify functional brain networks that differentiate opioid use disorder (OUD) subjects from healthy controls (HC) using machine learning (ML) analysis of resting-state fMRI (rs-fMRI). We investigate the default mode network (DMN), salience network (SN), and executive control network (ECN), as well as demographic features. Methods/Study Population: This work uses high-resolution rs-fMRI data from a National Institute on Drug Abuse study (IRB #HM20023630) with 31 OUD and 45 HC subjects. We extract rs-fMRI blood oxygenation level-dependent (BOLD) features from the DMN, SN, and ECN. The Boruta ML algorithm identifies statistically significant features and brain activity mapping visualizes regions of heightened neural activity for OUD. We conduct fivefold cross-validation classification experiments (OUD vs. HC) to assess the discriminative power of functional network features with and without incorporating demographic features. Demographic features are ranked based on ML classification importance. Follow-up Boruta analysis is performed to study the medial prefrontal cortex (mPFC), posterior cingulate cortex, and temporoparietal junctions in the DMN. Results/Anticipated Results: Boruta ML analysis identifies the DMN as the most salient functional network for differentiating OUD from HC, with 33% of DMN features found significant (p < 0.05), compared to 10% and 0% for the SN and ECN, respectively. The Boruta ML algorithm identifies age and education as the most significant demographic features. Brain activity mapping shows heightened neural activity in the DMN for OUD. The DMN exhibits the greatest discriminative power, with a mean AUC of 69.74%, compared to 47.14% and 54.15% for the SN and ECN, respectively. Fusing DMN BOLD features with the most important demographic features improves the mean AUC to 80.91% and the F1 score to 73.97%. Follow-up Boruta analysis highlights the mPFC as the most important functional hub within the DMN, with 65% significant features. Discussion/Significance of Impact: Our study enhances the understanding of OUD neurobiology, identifying the DMN as the most significant network using ML rs-fMRI BOLD feature analysis. Ethnicity, education, and age rank are the most important demographic features and the mPFC emerges as a key functional hub for OUD. Future research can build on these findings to inform treatment of OUD.

Objectives/Goals: Radiation nephropathy results in morbidity and mortality in patients receiving cancer treatment. In addition, low birth weight and low nephron number are associated with increased risk for chronic kidney disease. This study examined the development and severity of radiation-induced renal hemodynamic dysfunction in a low renal mass mouse model. Methods/Study Population: Male mice (C57Bl/6, 8–12-weeks) were used to determine a suitable radiation dose regimen. Mice were subjected to fractionated bilateral kidney irradiation with 5–6 fractions of an X-ray dose of 0, 6, 8, and 10 Gy at 24-hr intervals using a CT-image-guided irradiator. Body weight and mortality were monitored for 5 weeks in mice. In a separate set of experiments, the low renal mouse model, ROP Os/+, and their normal counterpart, ROP +/+ mice were subjected to 5 fractionated bilateral kidney irradiations at 24-hr intervals with an X-ray dose of 6 Gy. Renal blood flow was assessed from renal artery resistive index (RRI) over 5 weeks post-irradiation using an ultrasound system. Transcutaneous measurement of FITC-sinistrin clearance was used to determine glomerular filtration rate (GFR). Results/Anticipated Results: The C57Bl/6 mice that received 5–6 fractions of 8 and 10 Gy had more than 50% mortality, while 100% of the mice exposed to 5 fractions of 6 Gy survived for 5 weeks. Body weight was also significantly decreased in mice exposed to 5 or 6 fractions of 8 or 10 but not 6 Gy radiation. Nonirradiated C57Bl/6, ROP +/+, and ROP Os/+ mice had similar baseline GFR and RRI. Irradiation of 5 fractions at 6 Gy decreased GFR and increased RRI in C57Bl/6 and ROP +/+ mice. Interestingly, following 5 fractions at 6 Gy irradiation ROP Os/+ mice had 25% lower GFR than wild-type ROP +/+ mice (946.3 ± 50.3 vs. 1232.9 ± 69.3 µL/min/100g BW, p Discussion/Significance of Impact: Our study determined a suitable fractionated bilateral kidney irradiation dose regimen to evaluate radiation nephropathy. Data demonstrated that fractionated bilateral kidney irradiation leads to decreased renal hemodynamics in mice. We also demonstrated that irradiation caused greater renal hemodynamic dysfunction in low renal mass mice.

Objectives/Goals: Colorectal cancer (CRC) is classified into right-sided, left-sided, and rectal cancer. Clinicopathological and molecular features vary along the colorectum, even within subsites, leading to inconsistencies in identifying relevant biomarkers. We created a CRC metabolome map to explore diagnostic and survival heterogeneity across subsites. Methods/Study Population: A total of 372 patient-matched tumor and normal tissue samples were collected from seven colorectal subsites: cecum (n = 63), ascending colon (n = 44), transverse colon (n = 32), descending colon (n = 28), sigmoid colon (n = 75), rectosigmoid colon (n = 38), and rectum (n = 92). Liquid chromatography–mass spectrometry was used to compare metabolite abundances. Cox proportional hazards regression assessed metabolite impact on survival, adjusted for clinical covariates. Parametric and nonparametric tests were applied to compare the metabolite abundances. An interactive, publicly accessible online platform was developed to allow researchers to explore and generate hypotheses from this data. Results/Anticipated Results: Our study identified 39 and 70 significantly altered metabolites, including bile acids and lysophosphatidylcholines, across tumors and normal mucosa, showing metabolic heterogeneity between CRC subsites. We observed significant linear trends in metabolite gradients from the cecum to the rectum, and it was depended on the disease status. Comparison of tumors to patient-matched normal mucosa revealed metabolite changes exclusive to each subsite. Metabolite differences correlated with survival were unique to each subsite. Additionally, we developed an interactive, publicly accessible CRC metabolome database to share this valuable resource: https://colorectal-cancer-metabolome.com/yale-university. Discussion/Significance of Impact: This study provides the first CRC metabolome map, revealing metabolic differences across colorectal subsites. It challenges the right vs. left CRC classification, highlighting subsite-specific biomarker identification. Findings offer insights for personalized treatments tailored to the tumor type to improve patient outcomes.

Objectives/Goals: To fully understand the scientific objectives, overall financial commitment, and outcome of the pilot projects. Methods/Study Population: We evaluated pilots reported in the in the annual, interim, and final Research Performance Progress Reports (RPPRs) for Clinical and Translational Science Awards (CTSA) Program UM1 and UL1 grants from FYs 2021–2023 to assess research categories across the translational science spectrum. We analyzed the number of pilots involving human subjects, vertebrate animals, both, or neither; financial allocations; publication outputs; and other characteristics. Pilots reported across multiple years were deduplicated and assigned to the latest reporting year. Each pilot was classified into broad (Category 1) and specific (Category 2) areas. Descriptive statistics, including means and frequency distributions, were generated. Multi-year pilots with NA or 0 values used the most recent prior value. Results/Anticipated Results: In the period from FY 2021 to 2023, 61 hubs reported 1,811 unique pilot projects in their RPPRs, receiving a total of approximately $62 million, of which two-thirds were expended. On average, each hub conducted 30 pilots with an award size of about $35K. Just over half of the pilots involved human subjects research (HSR), while about one-third were neither HSR nor vertebrate animal studies (VAS), with the remaining focused primarily on VAS. Notably, only 13% of pilots resulted in peer-reviewed publications. Collaborative efforts were observed in one-third of the projects. The majority of pilots fell into Preclinical Research (46%), followed by Clinical Research (33%) and Public Health (20%). Limitations in data quality were identified, and ten pilots reported $0 awarded funds, which may be captured in future RPPRs. Discussion/Significance of Impact: Analysis of pilots reported in RPPRs from FYs 2021–2023 across 61 hubs shows a strong focus on HSR, highlighting collaborative efforts that enhance translational science and align with CTSA goals. Future analysis will help assess the pilots’ impact and their alignment with NCATS’ mission to expedite research translation into health solutions.

Chickpea provides significant diversification benefits for semiarid cropping systems. However, the crop’s slow emergence and open canopy growth habit make it a poor competitor against rapidly growing weeds during the early season. In 2022 and 2023, field experiments were conducted at two sites, the Montana State University (MSU) Southern Agricultural Research Center, in Huntley, and the MSU Post Agronomy Farm, in Bozeman, to evaluate broadleaf weed management by integrating planting date and fall-applied,soil-active herbicides to chickpea. Application of dimethenamid at 950 g ai ha−1 + pendimethalin at 1.68 kg ai ha−1, and carfentrazone + sulfentrazone at 238 g ai ha−1 resulted in better protection of yield against weeds and provided longer residual activity for control of kochia, redroot pigweed, and common mallow by reducing weed density to 10 to 20 plants m−2 compared with 50 to 70 plants m−2 in an untreated check. Pyridate (700 g ai ha−1) applied postemergence was required with these treatments to eliminate escaped weeds. Early planting provided an additional biomass reduction compared to late planting due to the crop emergence before or around the same time as the weeds. Planting date had no effect on weed density or grain yield in plots that received dimethenamid + pendimethalin and carfentrazone + sulfentrazone, suggesting that these herbicides can extend the planting date window. These herbicide programs and early planting can be integrated with other weed management tactics for additional weed management options in chickpea.