Genomic inbreeding analysis reveals resilience and genetic diversity in Indian yak populations.

The yak (Bos grunniens), renowned for its adaptability to extreme cold and hypoxic conditions, stands as a remarkable domestic animal crucial for sustaining livelihoods in harsh climates. We conducted a comprehensive analysis of the whole genome sequence data from three distinct Indian yak populations: Arunachali yak (n = 10), Himachali yak (n = 10), and Ladakhi yak (n = 10). The genomic data for Indian yaks were meticulously generated by our laboratory and compared with their Chinese counterpart, the Jinchuan yak (n = 8), for a more nuanced understanding. Our investigation revealed a total of 37,437 runs of homozygosity (ROH) segments in 34 animals representing four distinct yak populations. The Jinchuan yak population exhibited the highest proportion, constituting 80.8 % of total ROHs, predominantly as small segments (<0.1 Mb), accounting for 63 % of the overall ROHs. Further analysis uncovered a significantly higher degree of inbreeding in Chinese yaks compared to their Indian counterparts. The Indian yak populations, in contrast, demonstrated relatively lower and consistent levels of inbreeding. Moreover, we identified ROH hotspots that covered at least 60 % of individuals in our study, indicating their pivotal role in environmental adaptation. A total of five hotspot regions were detected, housing genes such as ENSBGRG00000015023 (WNT2), YIPF4, SPAST, TLN2, and DSG4. These genes are associated with traits including hair follicle initiation, nutrient stress response, microtubule assembly, development of cardiac muscle, hair follicle, and coat color. This observation strongly suggests that there is substantial selection acting on these genes, emphasizing their important role in environmental adaptation among yak populations.

Shared Decision Making in Hand Surgery.

Shared decision-making (SDM) is a collaborative effort between a physician and a patient to make an informed clinical decision, as defined by each patient's preferences and values. Shared decision-making is particularly used in areas of clinical equipoise or preference-sensitive conditions, which are common in hand surgery. Although there is increased interest in SDM across health care, hand surgeons receive little formal training on SDM. In this review, we explore existing barriers to SDM in hand surgery and provide a framework for participating in SDM discussions.

Assessing genetic parameters for first parity reproductive traits for early selection in Saanen × Beetal goats of India.

The present study aimed to evaluate the genetic parameters of first parity reproductive traits. Information on 762 reproductive records on Saanen × Beetal (S × B) goats reared for approximately five decades was collected from ICAR-National Dairy Research Institute, Karnal, Haryana (1973-2020). For genetic analysis, single-trait and multiple-trait animal models were used. Gibbs sampler for animal model (GSAM) approach was used for estimating (co)variance components of reproductive traits. Six different single-trait animal models (with or without maternal and environmental effects) were used and the deviance information criterion (DIC) determined the best model. The least squares mean for age at first service (AFS), age at first kidding (AFK), service period (SP), dry period (DP), gestation length (GL), kidding interval (KI), litter weight (LW), number of kids born (NKB) and number of female kids born (NFKB) in first parity were 526.99 ± 4.86, 662.96 ± 5.03, 219.11 ± 6.25, 109.38 ± 6.00, 150.48 ± 0.27, 356.63 ± 4.80 days, 3.87 ± 0.05 kg, 1.27 ± 0.02 and 0.67 ± 0.03, respectively. Lower heritability estimates for these reproductive traits revealed a sparse scope for genetic improvement. Multivariate analysis using Model 1 was carried out to evaluate the genetic and phenotypic correlation of these nine reproductive traits. The genetic correlation of DP and SP was negatively with LW, NKB and NFKB, which is favourable as reduction in SP and DP can improve these economically important traits through indirect selection. Consistent efforts towards genetic improvement of these goat flock poses a promising future for meat industry owing to high prolificacy and good reproductive potential in this flock.

Data-driven exploration of swarmalators with second-order harmonics.

We explore the dynamics of a swarmalator population comprising second-order harmonics in phase interaction. A key observation in our study is the emergence of the active asynchronous state in swarmalators with second-order harmonics, mirroring findings in the one-dimensional analog of the model, accompanied by the formation of clustered states. Particularly, we observe a transition from the static asynchronous state to the active phase wave state via the active asynchronous state. We have successfully delineated and quantified the stability boundary of the active asynchronous state through a completely data-driven method. This was achieved by utilizing the enhanced image processing capabilities of convolutional neural networks, specifically, the U-Net architecture. Complementing this data-driven analysis, our study also incorporates an analytical stability of the clustered states, providing a multifaceted perspective on the system's behavior. Our investigation not only sheds light on the nuanced behavior of swarmalators under second-order harmonics, but also demonstrates the efficacy of convolutional neural networks in analyzing complex dynamical systems.

Functional transcriptome analysis revealed major changes in pathways affecting systems biology of Tharparkar cattle under seasonal heat stress.

Heat stress significantly disturbs the production, reproduction, and systems biology of dairy cattle. A complex interaction among biological systems helps to combat and overcome heat stress. Indicine cattle breed Tharparkar has been well known for its thermal adaptability. Therefore, present investigation considered RNA-seq technology to explore the functional transcriptomics of Tharparkar cattle with the help of samples collected in spring and summer season. Among differentially expressed genes, about 3280 genes were highly dysregulated, in which 1207 gene were upregulated and 2073 genes were downregulated (|log2fold change|≥ 1 and p ≤ 0.05). Upregulated genes were related to insulin activation, interferons, and potassium ion transport. In contrast, downregulated genes were related to RNA processing, translation, and ubiquitination. Functional annotation revealed that the pathways associated with nervous system (NPFFR1, ROBO3) and metal ion transport (KCNG2, ATP1A2) were highly activated while mRNA processing and translation (EIF4A, EIF4B) and protein processing pathway (VPS4B, PEX13) were highly downregulated. Protein-protein interactions identified hub genes such as ATP13A3, IFNGR2, UBXN7, EIF4A2, SLC12A8 found to play an important role in immune, ubiquitination, translation and transport function. Co-expression network includes LYZ, PNRC1, SQSTM1, EIF4AB and DDX17 genes which are involved in lysosomal activity, tumor inhibition, ubiquitination, and translation initiation. Chemokine signaling pathway associated with immune response was highly upregulated in cluster analysis. The findings of this study provide insights into transcriptome expression and regulation which may better explain complex thermal resilience mechanism of Tharparkar cattle in heat stress under natural conditions. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-024-04018-2.

Functional transcriptome analysis revealed upregulation of MAPK-SMAD signalling pathways in chronic heat stress in crossbred cattle.

Animal geneticists and breeders have the impending challenge of enhancing the resilience of Indian livestock to heat stress through better selection strategies. Climate change's impact on livestock is more intense in tropical countries like India where dairy cattle crossbreeds are more sensitive to heat stress. The main reason for this study was to find the missing relative changes in transcript levels in thermo-neutral and heat stress conditions in crossbred cattle through whole-transcriptome analysis of RNA-Seq data. Differentially expressed genes (DEGs) identified based on the minimum log twofold change value and false discovery rate 0.05 revealed 468 up-regulated genes and 2273 down-regulated significant genes. Functional annotation and pathway analysis of these significant DEGs were compared based on Gene Ontology (Biological process), Kyoto Encyclopedia of Genes and Genome (KEGG), and Reactome pathways using g: Profiler, ShinyGO v0.76, and iDEP.951 web tools. On finding network visualization, the most over-represented and correlated pathways were neuronal and sensory organ development, calcium signalling pathway, Mitogen-activated protein kinase (MAPK) and Smad signalling pathway, Ras-proximate-1, or Ras-related protein 1 (Rap 1) signalling pathway, apoptosis, and oxidative stress. Similarly, down-regulated genes were most expressed in mRNA processing, immune system, B-cell receptor signalling pathway, Nucleotide oligomerization domain (NOD)-like receptors (NLRs) signalling pathway and nonsense-mediated decay (NMD) pathway. The heat stress-responsive genes identified in this study will facilitate our understanding of the molecular basis for climate resilience and heat tolerance in Indian dairy crossbreeds.

Self-Consistent Convolutional Density Functional Approximations: Application to Adsorption at Metal Surfaces.

The exchange-correlation (XC) functional in density functional theory is used to approximate multi-electron interactions. A plethora of different functionals are available, but nearly all are based on the hierarchy of inputs commonly referred to as "Jacob's ladder." This paper introduces an approach to construct XC functionals with inputs from convolutions of arbitrary kernels with the electron density, providing a route to move beyond Jacob's ladder. We derive the variational derivative of these functionals, showing consistency with the generalized gradient approximation (GGA), and provide equations for variational derivatives based on multipole features from convolutional kernels. A proof-of-concept functional, PBEq, which generalizes the PBE α ${\alpha }$ framework with α ${\alpha }$ being a spatially-resolved function of the monopole of the electron density, is presented and implemented. It allows a single functional to use different GGAs at different spatial points in a system, while obeying PBE constraints. Analysis of the results underlines the importance of error cancellation and the XC potential in data-driven functional design. After testing on small molecules, bulk metals, and surface catalysts, the results indicate that this approach is a promising route to simultaneously optimize multiple properties of interest.

Exploration of field-like torque and field-angle tunability in coupled spin-torque nano oscillators for synchronization.

We investigate the influence of field-like torque and the direction of the external magnetic field on a one-dimensional array of serially connected spin-torque nano oscillators (STNOs), having free layers with perpendicular anisotropy, to achieve complete synchronization between them by analyzing the associated Landau-Lifshitz-Gilbert-Slonczewski equation. The obtained results for synchronization are discussed for the cases of 2, 10, and 100 oscillators separately. The roles of the field-like torque and the direction of the external field on the synchronization of the STNOs are explored through the Kuramoto order parameter. While the field-like torque alone is sufficient to bring out global synchronization in the system made up of a small number of STNOs, the direction of the external field is also needed to be slightly tuned to synchronize the one-dimensional array of a large number of STNOs. The formation of complete synchronization through the construction of clusters within the system is identified for the 100 oscillators. The large amplitude synchronized oscillations are obtained for small to large numbers of oscillators. Moreover, the tunability in frequency for a wide range of currents is shown for the synchronized oscillations up to 100 spin-torque oscillators. In addition to achieving synchronization, the field-like torque increases the frequency of the synchronized oscillations. The transverse Lyapunov exponents are deduced to confirm the stable synchronization in coupled STNOs due to the field-like torque and to validate the results obtained in the numerical simulations. The output power of the array is estimated to be enhanced substantially due to complete synchronization by the combined effect of field-like torque and tunability of the field-angle.

Advancing proactive crash prediction: A discretized duration approach for predicting crashes and severity.

Driven by advancements in data-driven methods, recent developments in proactive crash prediction models have primarily focused on implementing machine learning and artificial intelligence. However, from a causal perspective, statistical models are preferred for their ability to estimate effect sizes using variable coefficients and elasticity effects. Most statistical framework-based crash prediction models adopt a case-control approach, matching crashes to non-crash events. However, accurately defining the crash-to-non-crash ratio and incorporating crash severities pose challenges. Few studies have ventured beyond the case-control approach to develop proactive crash prediction models, such as the duration-based framework. This study extends the duration-based modeling framework to create a novel framework for predicting crashes and their severity. Addressing the increased computational complexity resulting from incorporating crash severities, we explore a tradeoff between model performance and estimation time. Results indicate that a 15 % sample drawn at the epoch level achieves a balanced approach, reducing data size while maintaining reasonable predictive accuracy. Furthermore, stability analysis of predictor variables across different samples reveals that variables such as Time of day (Early afternoon), Weather condition (Clear), Lighting condition (Daytime), Illumination (Illuminated), and Volume require larger samples for more accurate coefficient estimation. Conversely, Daytime (Early morning, Late morning, Late afternoon), Lighting condition (Dark lighted), Terrain (Flat), Land use (Commercial, Rural), Number of lanes, and Speed converge towards true estimates with small incremental increases in sample size. The validation reveals that the model performs better in highway segments experiencing more frequent crashes (segments where the duration between crashes is less than 100 h, or approximately 4 days).

Effect of curry leaves in lowering blood pressure among hypertensive Indian patients.

Hypertension, commonly known as high or rising blood pressure, is characterized by a consistently elevated blood arterial pressure. It is a significant medical condition called hypertension raises your risk of developing problems with your heart, brain, kidneys, and other organs. Curry leaves work well as a treatment for high blood pressure. Curry leaves are thought to have a potent therapeutic impact for the treatment of high blood pressure since they are low in salt and high in potassium. Therefore, it is of interest to reduce the level of blood pressure among adults in rural area with the help of curry leaves. According to the statistical analysis, the experimental group's post-test mean score for hypertension was 155 with a standard deviation of 13.892 while the control group's post-test mean score was 162 with a standard deviation of 17.20. The estimated unpaired value of t = 11.07 was deemed to be statistically significant at the p 0.05 level and the mean difference was 7. As a result, the null hypothesis was rejected and the research hypothesis was accepted. Giving Curry leaf powder to patients with hypertension as a consequence was an effective intervention.

Knowledge on mucormycosis among nursing Indian students in the state of Gujarat.

The disorder known as angio-invasive mucormycosis is characterized by tissue necrosis and infarction. The Mucorales order of saprophytic fungi is responsible for its development. It is unclear how widespread mucormycosis is in India due to a lack of population-based investigations. Diabetes mellitus is the risk factor that occurs the most frequently, followed by solid organ transplant and hematological cancer. The present study has been carried out to assess the knowledge regarding mucormycosis among nursing students from Nootan College of Nursing, Visnagar, Gujarat. For this we have selected 100 students by using the probability sampling technique. Structured questions were used to assess the knowledge of nursing students regarding mucormycosis. The Score was categorized as poor, average and good. The results show that 45(45%) of the nursing students having poor knowledge, 35(35%) of them were having average knowledge, 20(20%) of them were having good knowledge. There is an association between gender, program and their level of knowledge. Most of the students having poor knowledge regarding mucormycosis and we need to create awareness regarding mucormycosis to Nursing students.

Phase transitions in an adaptive network with the global order parameter adaptation.

We consider an adaptive network of Kuramoto oscillators with purely dyadic coupling, where the adaption is proportional to the degree of the global order parameter. We find only the continuous transition to synchronization via the pitchfork bifurcation, an abrupt synchronization (desynchronization) transition via the pitchfork (saddle-node) bifurcation resulting in the bistable region R_{1}. This is a smooth continuous transition to a weakly synchronized state via the pitchfork bifurcation followed by a subsequent abrupt transition to a strongly synchronized state via a second saddle-node bifurcation along with an abrupt desynchronization transition via the first saddle-node bifurcation resulting in the bistable region R_{2} between the weak and strong synchronization. The transition goes from the bistable region R_{1} to the bistable region R_{2}, and transition from the incoherent state to the bistable region R_{2} as a function of the coupling strength for various ranges of the degree of the global order parameter and the adaptive coupling strength. We also find that the phase-lag parameter enlarges the spread of the weakly synchronized state and the bistable states R_{1} and R_{2} to a large region of the parameter space. We also derive the low-dimensional evolution equations for the global order parameters using the Ott-Antonsen ansatz. Further, we also deduce the pitchfork, first and second saddle-node bifurcation conditions, which is in agreement with the simulation results.

Dizziness Among Population in a Tertiary care Centre in Maduranthagam.

Dizziness is a common chief complaint and there is a broad variety of possible underlying diseases for dizziness. Physicians must distinguish the majority of patients with self-limiting conditions from those with serious illnesses that require acute treatment. Diagnosis can be a challenge sometimes due to lack of dedicated vestibular lab and injudicious use of vestibular suppressant medications. In total of 100 cases were taken into study in which the most common was found to be benign paroxysmal positional vertigo and the most serious was cerebellar infarct and space occupying lesion. Complete evaluation of the patient should be done to arrive at a diagnosis. Therefore, a modification in the assessment methods of the dizzy patients with emphasis on history and clinical presentation seems essential.

Effect of Cholesterol on Biomimetic Membrane Curvature and Coronavirus Fusion Peptide Encapsulation.

Biomimetic cubic phases can be used for protein encapsulation in a variety of applications such as biosensors and drug delivery. Cubic phases with a high concentration of cholesterol and phospholipids were obtained herein. It is shown that the cubic phase structure can be maintained with a higher concentration of biomimetic membrane additives than has been reported previously. Opposing effects on the curvature of the membrane were observed upon the addition of phospholipids and cholesterol. Furthermore, the coronavirus fusion peptide significantly increased the negative curvature of the biomimetic membrane with cholesterol. We show that the viral fusion peptide can undergo structural changes leading to the formation of hydrophobic α-helices that insert into the lipid bilayer. This is of high importance, as a fusion peptide that induces increased negative curvature as shown by the formation of inverse hexagonal phases allows for greater contact area between two membranes, which is required for viral fusion to occur. The cytotoxicity assay showed that the toxicity toward HeLa cells was dramatically decreased when the cholesterol or peptide level in the nanoparticles increased. This suggests that the addition of cholesterol can improve the biocompatibility of the cubic phase nanoparticles, making them safer for use in biomedical applications. As the results, this work improves the potential for the biomedical end-use applications of the nonlamellar lipid nanoparticles and shows the need of systematic formulation studies due to the complex interplay of all components.

Optimization of test day for milk yield recording and sire evaluation in Murrah buffaloes.

In the present study, random regression models (RRM) were used to estimate genetic parameters for test-day milk yield in Murrah buffaloes using Legendre polynomial function (LP), with the objective to find the best combination of "minimum test-day model," which would be essential and sufficient to evaluate the trait successfully. Data included for analysis were 10,615 first lactation monthly test-day milk yield records (5th, 35th, 65th, …, 305th) from 965 Murrah buffaloes for the period 1975-2018. Cubic to octic-order orthogonal polynomials with homogeneous residual variances were used for the estimation of genetic parameters. Random regression models with sixth-order were selected based on goodness of fit criteria like lower AIC, BIC and residual variance. Heritability estimates ranged from 0.079 (TD6) to 0.21(TD10). For both ends of lactation, the additive genetic and environmental variances were higher and ranged from 0.21 ± 0.12 (TD6) to 0.85 ± 0.35 kg2 (TD1) and 3.74 ± 0.36 (TD11) to 1.36 ± 0.14 kg2 (TD9), respectively. Between adjacent test-day records, genetic correlation estimates ranged from 0.09 ± 0.31 (TD1 and TD2) to 0.97 ± 0.03 (TD3 and TD4; TD4 and TD5), but values gradually declined as the distance between test days increased. Negative genetic correlations were also obtained between TD1 with TD3 to TD9, TD2 with TD9 and TD10, and TD3 with TD10. On the basis of genetic correlations, models with 5 and/or 6 test-days combination were able to account for 86.1%-98.7% of variation along the lactation. Models with fourth and fifth-order LP functions were considered to account for variance with combinations of 5 and/or 6 test-day milk yields. The model with 6 test-day combinations had a higher rank correlation (0.93) with model using 11 monthly test-day milk yield records. On the basis of relative efficiency, the model with 6 monthly test day combinations with fifth-order was more efficient (maximum 99%) than the model using 11 monthly test-day milk yield records. Looking into the similar accuracy with the 11TD model, and the low resources requirement, we recommend the use of the "6 test-day combination model" for sire evaluation. These models may help in reducing the cost and time for data recording of milk yield.

Savi-Scout Radar Localization: Transitioning From the Traditional Wire Localization to Wireless Technology for Surgical Guidance at Lumpectomies.

Breast-conserving surgery or lumpectomy requires localization of the lesion prior to surgery, which is traditionally accomplished by imaging-guided wire localization. Over the last decade, alternatives to wire localization have emerged. This work reviews the literature on one such wireless technology, SaviScout radar (SSR) system, and shares our experience with using this technology for presurgical tumor localization. The SSR surgical guidance system is non-radioactive. The radiologist implants a reflector device in the breast under mammography or ultrasound guidance at any time prior to surgery. The placement of this reflector can be confirmed from the cadence of a handheld percutaneous probe of a handpiece and console system. Results from several studies show that the surgical outcomes from SSR and wire-localization are similar. SSR provides operational advantages as the scheduling for reflector placement by radiologists is decoupled from surgery, but at an increased cost compared to wire-localization.

Artificial Intelligence in Breast X-Ray Imaging.

This topical review is focused on the clinical breast x-ray imaging applications of the rapidly evolving field of artificial intelligence (AI). The range of AI applications is broad. AI can be used for breast cancer risk estimation that could allow for tailoring the screening interval and the protocol that are woman-specific and for triaging the screening exams. It also can serve as a tool to aid in the detection and diagnosis for improved sensitivity and specificity and as a tool to reduce radiologists' reading time. AI can also serve as a potential second 'reader' during screening interpretation. During the last decade, numerous studies have shown the potential of AI-assisted interpretation of mammography and to a lesser extent digital breast tomosynthesis; however, most of these studies are retrospective in nature. There is a need for prospective clinical studies to evaluate these technologies to better understand their real-world efficacy. Further, there are ethical, medicolegal, and liability concerns that need to be considered prior to the routine use of AI in the breast imaging clinic.

Audit of Prior Screening Mammograms of Screen-Detected Cancers: Implications for the Delay in Breast Cancer Detection.

When cancer is detected in a screening mammogram, on occasion retrospective review of prior screening (pre-index) mammograms indicates a likely presence of cancer. These missed cancers during pre-index screens constitute a delay in detection and diagnosis. This study was undertaken to quantify the missed cancer rate by auditing pre-index screens to improve the quality of mammography screening practice. From a cohort of 135 screen-detected cancers, 120 pre-index screening mammograms could be retrieved and served as the study sample. A consensus read by 2 radiologists who interpreted the pre-index screens in an unblinded manner with full knowledge of cancer location, cancer type, lesion type, and pathology served as the truth or reference standard. Five radiologists interpreted the pre-index screens in a blinded manner. Established performance metrics such as sensitivity and specificity were quantified for each reader in interpreting these pre-index screens in a blinded manner. All five radiologists detected lesions in 8/120 (6.7%) screens. Excluding the 2 readers whose performance was close to random, all the 3 remaining readers detected lesions in 13 pre-index screens. This indicates that there is a delay in diagnosis by at least one cycle from 8/120 (6.7%) to 13/120 (10.8%). There were no observable trends in terms of either the cancer type or the lesion type. Auditing prior screening mammograms in screen-detected cancers can help in identifying the proportion of cases that were missed during interpretation and help in quantifying the delay in breast cancer detection.

The Current State of Timeliness in the Breast Cancer Diagnosis Journey: Abnormal Screening to Biopsy.

There are several steps involved in a breast cancer diagnosis, starting from the initial abnormal screening mammogram. Each step from the additional imaging to a biopsy provokes anxiety. Timely attention to these appointments will not only help allay anxiety but also provide better care. While breast facilities routinely audit their performance, currently timeliness is not one of the audit parameters. The role of timeliness as a robust quality tool is gaining attention. In this study, we review the timeline of care at our facility over a 1-year period (October 2021- September 2022) and compare them with those reported by National Quality Measures for Breast Centers (NQMBC). Race, ethnicity, location, and type of facility affect the outcome of care and contribute to delays in providing care. In this manuscript, we outline some of the major factors. Societal guidelines outlining some metrics for timeliness may be a useful first step.