Construction of relatedness matrices in autopolyploid populations using low-depth high-throughput sequencing data.

KEY MESSAGE: An improved estimator of genomic relatedness using low-depth high-throughput sequencing data for autopolyploids is developed. Its outputs strongly correlate with SNP array-based estimates and are available in the package GUSrelate. High-throughput sequencing (HTS) methods have reduced sequencing costs and resources compared to array-based tools, facilitating the investigation of many non-model polyploid species. One important quantity that can be computed from HTS data is the genetic relatedness between all individuals in a population. However, HTS data are often messy, with multiple sources of errors (i.e. sequencing errors or missing parental alleles) which, if not accounted for, can lead to bias in genomic relatedness estimates. We derive a new estimator for constructing a genomic relationship matrix (GRM) from HTS data for autopolyploid species that accounts for errors associated with low sequencing depths, implemented in the R package GUSrelate. Simulations revealed that GUSrelate performed similarly to existing GRM methods at high depth but reduced bias in self-relatedness estimates when the sequencing depth was low. Using a panel consisting of 351 tetraploid potato genotypes, we found that GUSrelate produced GRMs from genotyping-by-sequencing (GBS) data that were highly correlated with a GRM computed from SNP array data, and less biased than existing methods when benchmarking against the array-based GRM estimates. GUSrelate provides researchers with a tool to reliably construct GRMs from low-depth HTS data.

Influence of COVID-19 pandemic in India on coronary artery disease clinical presentation, angiography, interventions and in-hospital outcomes: a single centre prospective registry-based observational study.

OBJECTIVE: The study examined the influence of the COVID-19 pandemic in India on variation in clinical features, management and in-hospital outcomes in patients undergoing percutaneous coronary intervention (PCI). DESIGN: Prospective registry-based observational study. SETTING: A tertiary care hospital in India participant in the American College of Cardiology CathPCI Registry. PARTICIPANTS: 7089 successive patients who underwent PCI from April 2018 to March 2023 were enrolled (men 5627, women 1462). Details of risk factors, clinical presentation, coronary angiography, coronary interventions, clinical management and in-hospital outcomes were recorded. Annual data were classified into specific COVID-19 periods according to Government of India guidelines as pre-COVID-19 (April 2018 to March 2019, n=1563; April 2019 to March 2020, n=1594), COVID-19 (April 2020 to March 2020, n=1206; April 2021 to March 2022, n=1223) and post-COVID-19 (April 2022 to March 2023, n=1503). RESULTS: Compared with the patients in pre-COVID-19 and post-COVID-19 periods, during the first COVID-19 year, patients had more hypertension, non-ST elevation myocardial infarction (NSTEMI), lower left ventricular ejection fraction (LVEF) and multivessel coronary artery disease (CAD). In the second COVID-19 year, patients had more STEMI, lower LVEF, multivessel CAD, primary PCI, multiple stents and more vasopressor and mechanical support. There were 99 (1.4%) in-hospital deaths which in the successive years were 1.2%, 1.4%, 0.8%, 2.4% and 1.3%, respectively (p=0.019). Compared with the baseline year, deaths were slightly lower in the first COVID-19-year (age-sex adjusted OR 0.68, 95% CI 0.31 to 1.47) but significantly more in the second COVID-19-year (OR 1.97, 95% CI 1.10 to 3.54). This variation attenuated following adjustment for clinical presentation, extent of CAD, in-hospital treatment and duration of hospitalisation. CONCLUSIONS: In-hospital mortality among patients with CAD undergoing PCI was significantly higher in the second year of the COVID-19 pandemic in India and could be one of the reasons for excess deaths in the country. These patients had more severe CAD, lower LVEF, and more vasopressor and mechanical support and duration of hospitalisation.

Optimised deep k-nearest neighbour's based diabetic retinopathy diagnosis(ODeep-NN) using retinal images.

Diabetes mellitus has been regarded as one of the prime health issues in present days, which can often lead to diabetic retinopathy, a complication of the disease that affects the eyes, causing loss of vision. For precisely detecting the condition's existence, clinicians are required to recognise the presence of lesions in colour fundus images, making it an arduous and time-consuming task. To deal with this problem, a lot of work has been undertaken to develop deep learning-based computer-aided diagnosis systems that assist clinicians in making accurate diagnoses of the diseases in medical images. Contrariwise, the basic operations involved in deep learning models lead to the extraction of a bulky set of features, further taking a long period of training to predict the existence of the disease. For effective execution of these models, feature selection becomes an important task that aids in selecting the most appropriate features, with an aim to increase the classification accuracy. This research presents an optimised deep k-nearest neighbours'-based pipeline model in a bid to amalgamate the feature extraction capability of deep learning models with nature-inspired metaheuristic algorithms, further using k-nearest neighbour algorithm for classification. The proposed model attains an accuracy of 97.67 and 98.05% on two different datasets considered, outperforming Resnet50 and AlexNet deep learning models. Additionally, the experimental results also portray an analysis of five different nature-inspired metaheuristic algorithms, considered for feature selection on the basis of various evaluation parameters.

An augmentation aided concise CNN based architecture for COVID-19 diagnosis in real time.

Over 6.5 million people around the world have lost their lives due to the highly contagious COVID 19 virus. The virus increases the danger of fatal health effects by damaging the lungs severely. The only method to reduce mortality and contain the spread of this disease is by promptly detecting it. Recently, deep learning has become one of the most prominent approaches to CAD, helping surgeons make more informed decisions. But deep learning models are computation hungry and devices with TPUs and GPUs are needed to run these models. The current focus of machine learning research is on developing models that can be deployed on mobile and edge devices. To this end, this research aims to develop a concise convolutional neural network-based computer-aided diagnostic system for detecting the COVID 19 virus in X-ray images, which may be deployed on devices with limited processing resources, such as mobile phones and tablets. The proposed architecture aspires to use the image enhancement in first phase and data augmentation in the second phase for image pre-processing, additionally hyperparameters are also optimized to obtain the optimal parameter settings in the third phase that provide the best results. The experimental analysis has provided empirical evidence of the impact of image enhancement, data augmentation, and hyperparameter tuning on the proposed convolutional neural network model, which increased accuracy from 94 to 98%. Results from the evaluation show that the suggested method gives an accuracy of 98%, which is better than popular transfer learning models like Xception, Resnet50, and Inception.

Low body mass index is associated with adverse cardiovascular outcomes following PCI in India: ACC-NCDR registry.

Objective: Registry-based prospective study was conducted to evaluate association of body mass index (BMI) with major adverse coronary events (MACE) following percutaneous coronary intervention (PCI). Methods: Successive patients undergoing PCI were enrolled from April'19 to March'22 and classified into five BMI categories (<23.0,23.0-24.9,25.0-26.9,27.0-29.9, and ≥30.0 kg/m2). Clinical, angiographic features, interventions and outcomes were obtained by in-person or telephonic follow-up. Primary endpoints were (a) MACE(cardiovascular deaths, acute coronary syndrome or stroke, revascularization, hospitalization and all-cause deaths) and (b)cardiovascular deaths. Cox-proportionate hazard ratios(HR) and 95 % confidence intervals(CI) were calculated. Results: The cohort included 4045 patients. Mean age was 60.3 ± 11y, 3233(79.7 %) were men. There was high prevalence of cardiometabolic risk factors. 90 % patients had acute coronary syndrome(STEMI 39.6 %, NSTEMI/unstable angina 60.3 %), 60.0 % had impaired ejection fraction(EF) and multivessel CAD. Lower BMI groups (<23.0 kg/m2) had higher prevalence of tobacco use, reduced ejection fraction(EF), multivessel CAD, stents, and less primary PCI for STEMI. There was no difference in discharge medications and in-hospital deaths. Median follow-up was 24 months (IQR 12-36), available in 3602(89.0 %). In increasing BMI categories, respectively, MACE was in 10.9,8.9,9.5,9.1 and 6.8 % (R2 = 0.73) and CVD deaths in 5.1,4.5,4.4,5.1 and 3.5 % (R2 = 0.39). Compared to lowest BMI category, age-sex adjusted HR in successive groups for MACE were 0.89,0.87,0.79,0.69 and CVD deaths 0.98,0.87,0.95,0.75 with overlapping CI. HR attenuated following multivariate adjustments. Conclusions: Low BMI patients have higher incidence of major adverse cardiovascular events following PCI in India. These patients are older, with greater tobacco use, lower EF, multivessel CAD, delayed STEMI-PCI, and longer hospitalization.

A core-shell magnet Mn70Bi30grown at seeds in magnetic fields and its impacts on its spin-dynamics, Curie point and other tailored properties.

The MnBi alloys is a model series of rare-Earth free magnets for surge of technologies of small parts of automobiles, power generators, medical tools, memory systems, and many others. The magnetics stem primarily at unpaired Mn-3d5spins (a 4.23µBmoment) align parallel via an orbital moment 0.27µBof Bi-5d106s2p3in a crystal lattice. Thus, using a surplus Mn (over Bi) in a Mn70Bi30type alloy designs a spin-rich system of duly tailored properties useful for magnetics and other devices. In this view, we report here a strategy of a refined alloy powder Mn70Bi30can grow into small crystals of hexagonal (h) plates at seeds as annealed in magnetic fields (in H2gas). So, small h-plates (30 to 50 nm widths) are grown up at (002) facets, wherein the edges are turned down in a spiral (≤2.1 nm thicknesses) in a core-shell structure. The results are described with x-ray diffraction, lattice images and magnetic properties of a powder Mn70Bi30(milled in glycine) is annealed at 573 K for different time periods, so to the Mn/Bi order at the permeable facets (seeds). Duly annealed samples exhibit an enhanced magnetization,Ms→ 70.8 emu g-1, with duly promoted coercivityHc→ 10.810 kOe (15.910 kOe at 350 K), energy-product 14.8 MGOe, and the crystal-field-anisotropy,K1→ 7.6 × 107erg cm-3, reported at room temperature. Otherwise,Msshould decline at any surplus 3d5-Mn spins order antiparallel at the antisites. Enhanced Curie point 658.1 K (628 K at Mn50Bi50alloy) anticipates that a surplus Mn does favor the Mn-Bi exchange interactions. Proposed spin models well describe the spin-dynamics and lattice relaxations (on anneals) over the lattice volume (with twins) and spin clusters.

Allelic variants of a potato HEAT SHOCK COGNATE 70 gene confer improved tuber yield under a wide range of environmental conditions.

Previously, we developed and applied a glasshouse screen for potato tuber yield under heat stress and identified a candidate gene (HSc70) for heat tolerance by genetic analysis of a diploid potato population. Specific allelic variants were expressed at high levels on exposure to moderately elevated temperature due to variations in gene promoter sequence. In this study, we aimed to confirm the results from the glasshouse screen in field trials conducted over several seasons and locations including those in Kenya, Malawi and the UK. We extend our understanding of the HSc70 gene and demonstrate that expression level of HSc70 correlates with tolerance to heat stress in a wide range of wild potato relatives. The physiological basis of the protective effect of HSc70 was explored and we show that genotypes carrying the highly expressed HSc70 A2 allele are protected against photooxidative damage to PSII induced by abiotic stresses. Overall, we show the potential of HSc70 alleles for breeding resilient potato genotypes for multiple environments.

Application of blockchain technology in shaping the future of food industry based on transparency and consumer trust.

Food Industries, at this moment, are moving towards a new phase, and this phase will be governed by consumers and not by the industry leaders. The report shows that claims on sustainability, health, wellness, and transparency would govern the future trends in the food industry. Currently, there are several cases of misleading and false claims which hamper consumer trust. So, to uphold consumer trust, authentication of claims through transparency in the food supply chain is required, and blockchain technology can bring transparency at relatively low transaction costs. Once in a blockchain network, data is very difficult to manipulate, with no single point of authority to mess and collapse the system. Though we see mostly the financial systems using blockchain's decentralized functionality, there is a growing trend of innovative applications being built in the supply chain area for contracts and operations. With effort in the right direction and over time, blockchain will recast how operations and processes are done across the industry, including public sectors. The paper reviews the opportunity for the blockchain in enabling food industries for future-readiness, empowering the consumers in verifying the product claims and thus prevent themselves from food fraud. In doing so, the paper considers the future trends in the food industry, identifies current food fraud cases, and outlines the various applications in the agri-food chain and challenges associated with it.

Role of psychrotrophic bacteria and cold-active enzymes in composting methods adopted in cold regions.

Temperature-dependent composting is a challenging task but is worthy if it is done in the right manner. Cold composting has been known to be practiced since ancient times but there were not enough advancements to overcome the long mesophilic phase and bring the compost maturation to a short period. The composting processes that have been well practiced are discussed and the role of psychrotrophic bacteria that produce cold tolerant hydrolytic enzymes has been highlighted. In this chapter, the mechanism of substrate degradation has been elaborated to better understand the need of specific bacteria for a specific kind of substrate allowing fast and efficient decomposition. This chapter attempts to pave an appropriate way and suggest the best-suited method of composting for efficient production of compost by the conservation of heat in cold regions.

The generation of diverse traveling pulses and its solution scheme in an excitable slow-fast dynamics.

In this article, we report on the generation and propagation of traveling pulses in a homogeneous network of diffusively coupled, excitable, slow-fast dynamical neurons. The spatially extended system is modeled using the nearest neighbor coupling theory, in which the diffusion part measures the spatial distribution of coupling topology. We derive analytically the conditions for traveling wave profiles that allow the construction of the shape of traveling nerve impulses. The analytical and numerical results are used to explore the nature of propagating pulses. The symmetric or asymmetric nature of traveling pulses is characterized, and the wave velocity is derived as a function of system parameters. Moreover, we present our results for an extended excitable medium by considering a slow-fast biophysical model with a homogeneous, diffusive coupling that can exhibit various traveling pulses. The appearance of series of pulses is an interesting phenomenon from biophysical and dynamical perspective. Varying the perturbation and coupling parameters, we observe the propagation of activities with various amplitude modulations and transition phases of different wave profiles that affect the speed of pulses in certain parameter regimes. We observe different types of traveling pulses, such as envelope solitons and multi-bump solutions, and show how system parameters and coupling play a major role in the formation of different traveling pulses. Finally, we obtain the conditions for stable and unstable plane waves.

A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method.

Due to the rapid growth in IT technology, digital data have increased availability, creating novel security threats that need immediate attention. An intrusion detection system (IDS) is the most promising solution for preventing malicious intrusions and tracing suspicious network behavioral patterns. Machine learning (ML) methods are widely used in IDS. Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. In the initial phase, the proposed HNIDS utilizes hybrid EGA-PSO methods to enhance the minor data samples and thus produce a balanced data set to learn the sample attributes of small samples more accurately. In the proposed HNIDS, a PSO method improves the vector. GA is enhanced by adding a multi-objective function, which selects the best features and achieves improved fitness outcomes to explore the essential features and helps minimize dimensions, enhance the true positive rate (TPR), and lower the false positive rate (FPR). In the next phase, an IRF eliminates the less significant attributes, incorporates a list of decision trees across each iterative process, supervises the classifier's performance, and prevents overfitting issues. The performance of the proposed method and existing ML methods are tested using the benchmark datasets NSL-KDD. The experimental findings demonstrated that the proposed HNIDS method achieves an accuracy of 98.979% on BCC and 88.149% on MCC for the NSL-KDD dataset, which is far better than the other ML methods i.e., SVM, RF, LR, NB, LDA, and CART.

Expression of glucose transporter 1 (SLC2A1) - Clinicopathological associations and survival in an Indian cohort of colorectal cancer patients.

Background: Glucose transporter 1 (GLUT1) facilitates the uptake of glucose in malignant cells. We investigated GLUT1 transcript expression in colorectal cancer (CRC) tumors and explored its relationship to clinicopathological features, diabetes condition, and patient survival. Materials and Methods: The expression of GLUT1 was determined using fluorescent probe-based quantitative real-time polymerase chain reaction assay of tumor tissue and corresponding normal mucosa from 180 archived formalin-fixed, paraffin-embedded tissue blocks of ninety upfront surgically resected colorectal adenocarcinoma cases. Clinical information was collected from the hospital medical records and statistical analyses were performed. Results: Compared to normal mucosa tissue, the GLUT1 expression was significantly elevated in CRC tumor tissue (0.024 ± 0.056 vs. 0.004 ± 0.005; P < 0.0001). The expression was significantly more in poorly differentiated tumors than well/moderately differentiated tumors (P = 0.024) and in patients with liver metastasis (P = 0.013). The high GLUT1 expression correlated with advanced tumor stage (P = 0.003), liver metastasis (P = 0.003), poor tumor differentiation (P = 0.02), and death (P = 0.001). In univariate Cox regression analysis for survival, high GLUT1 expression, presence of any comorbidity, diabetic condition, advanced or metastatic stage, and liver metastasis were significant risk factors for death. CRC patients with high GLUT1 expression showed worse survival outcomes than those with low GLUT1 expression (P = 0.001). Furthermore, the high GLUT1/diabetes (+) patients had an inferior survival outcome than the patients with low GLUT1/diabetes (+) condition. Conclusions: GLUT1 is significantly upregulated in colorectal adenocarcinoma. The expression correlated with poor tumor histology, higher stage, hepatic metastases, and adverse survival in the study cohort.

Hematopoietic Stem Cell Transplant for Hematological Malignancies: Experience from a Tertiary Care Center in Northern India and Review of Indian Data.

Sanjeev Kumar SharmaHematopoietic stem cell transplantation (HSCT) is the preferred treatment for high-risk and relapsed/refractory hematological malignancies. Moreover, with the improved supportive care and increasing acceptance of haploidentical transplantations as an alternative treatment modality, more patients are opting for HSCT as a definite treatment for hematological malignancies. We report here the real-world data and outcome of HSCT done for hematological malignancies at our transplant center. Five hundred and sixteen patients underwent HSCT from August 2010 to November 2019. The most common indications for allogeneic and autologous HSCT were acute myeloid leukemia and multiple myeloma, respectively. The 5-year overall survival and disease-free survival for all transplants were 65% and 33%, respectively. Though outcome of matched sibling donor allogeneic transplant is better than haploidentical donor (HID) transplant, patients having only HID can still be considered for allogeneic HSCT for high-risk diseases. The most common cause of death was infections followed by relapse of the disease.

Structural ordering at magnetic seeds with twins at boundaries of a core-shell alloy Mn60Bi40and tailored magnetic properties.

A spin Mn3d5-rich Mn60Bi40alloy reveals a model system in order to tailor profound magnetic properties at unpaired 3d5spins in such alloys of a core-shell structure. As annealed (at a critical temperature 573 K in H2gas), a refined powder (in glycine) grows onα-MnBi seeds (crystallites) present in it at Mn/Bi atoms order over topological layers, preferentially along (110) planes, at a self-confined structure at seeds of an anisotropic shape of hexagonal (h) plates (25-85 nm widths). In terms of the HRTEM images, the atoms turn down at edges (at the plates grow up) in a spiral layer, ≤ 2.1 nm thickness, of small core-shells. A spin model is proposed to delineate a way at the spins can pin down at the edges, form single magnetic domains, and raise coercivity (Hc), with no much loss of net magnetic moment. The X-ray diffraction and HRTEM images corroborate the results of topological pacing of atoms at the h-plates at anneals. A novelty is that a core-shell leads to tailor a superbHc, as much as 11.110 kOe (16.370 kOe at 350 K), with a fairly large magnetization, 76.5 emu g-1, at near 300 K. An enhanced Curie point 650.1 K (628 K at Mn50Bi50alloy) confers a surplus 3d5-Mn spin sensitively tunesα-MnBi stoichiometry and so its final magnetic structure. A refined alloy powder so made is useful to make powerful magnets and devices in the forms of films and bonded magnets in different shapes for uses as small tools, tweezers, and other devices.

Progressive left and right heart dysfunction in coronavirus disease-19: Prospective echocardiographic evaluation.

AIMS: Cardiac dysfunction in coronavirus disease-19 (COVID-19) has been reported during acute phase but serial changes have not been well studied. To determine serial changes in type and severity of echocardiographic left and right heart functions we performed a prospective study. METHODS AND RESULTS: Successive COVID-19 patients at discharge from the hospital from June to December 2020 were enrolled. Clinical details were obtained and echocardiography was performed using Philips IE33X-Matrix. Follow-up evaluation was performed after 3 months. In total, 1789 COVID-19 patients were evaluated. Baseline echocardiography was performed in 1000 eligible patients (men 611, women 389). Mean age was 50.2 ± 15 years, hypertension was in 44.0%, diabetes in 49.4%, and coronary disease in 10.8%. COVID-19 was mild in 47.0%, moderate in 39.5%, and severe in 13.5%. Baseline cardiac parameters were more impaired in severe vs. moderate or mild COVID-19. At 3 months, in 632 patients where baseline and follow-up data were available, decline was observed in select left [left ventricular internal diameter in diastole +0.9 ± 0.2 mm, left atrial volume +7.6 ± 0.1 mL/m2, mitral E/e' +4.8 ± 0.1, and left ventricular ejection fraction (LVEF) -3.7 ± 0.2%] and right [right ventricular internal diameter in diastole +2.1 ± 0.1 mm, right atrial internal dimension +1.6 ± 0.1 mm, tricuspid Vmax +1.0 ± 0.1 cm, and tricuspid annulus plane systolic excursion (TAPSE) -2.7 ± 0.2 mm] heart variables (P < 0.001). Compared to mild COVID-19, decline was significantly greater in moderate/severe disease, LVEF -1.1 ± 0.3 vs. -3.8 ± 0.3%; mitral E/e' +3.2 ± 0.1 vs. +4.8 ± 0.1, tricuspid Vmax +0.3 ± 0.1 vs. +1.0 ± 0.1 cm, and TAPSE -0.7 ± 0.2 vs. -2.7 ± 0.2 mm (P < 0.001). CONCLUSION: This study shows impaired cardiac functions in severe and moderate COVID-19 compared to mild at hospital discharge and progressive decline in left and right heart functions at 3 months. Impairment is significantly greater in patients with moderate to severe disease.

Outcomes of COVID-19 in Hematopoietic Stem Cell Transplant Recipients: Multicenter Retrospective Analysis.

COVID-19, caused by the severe acute respiratory syndrome corona virus 2 (SARS-CoV-2), was declared a pandemic by the World Health Organization on March 9, 2020. Hematopoietic stem-cell transplantation (HSCT) recipients may be highly susceptible to infection and related pulmonary complications due to nascent immune systems or organ damage from treatment-related toxicities. Poor outcomes in such group of patients were linked to older age, steroid therapy at the time of COVID-19 infection, and COVID-19 infection within a year of HSCT. We studied a cohort of 28 hematopoietic stem cell transplant recipients (male 17, M:F ratio of 1.5) with COVID-19 infection from 1st June 2020, through 31st December 2020 for outcome. Fever was the most common symptom at the time of presentation in 22 (78.5%) patients. Mortality rate at Day 28 and Day 42 was found to be 4/28 (14.3%) and 7/28 (25%) respectively. Patients within one year of HSCT and severe infection had higher day 28 mortality (with p values = 0.038)". There was no relation of mortality with type of transplant.

Experimental study of solar energy-based water purifier of single-slope type by incorporating a number of similar evacuated tubular collectors.

This research paper deals with the experimental investigation of solar energy-based water purifier (SEBWP) of single-slope type by incorporating N similar evacuated tubular collectors (ETCs) having series connection. Experimental investigation has been done for a year from August 2018 to July 2019. MATLAB has been used for evaluating performance parameters of the system followed by the validation of these results with their experimental values. A fair agreement has been found between theoretical and experimental values. Values of correlation coefficients for condensing glass temperature, water temperature, and water yield have been found to be 0.9932, 0.9928, and 0.9951 respectively. Further, energy metrics, productivity, cost of producing 1 kg of fresh water, and exergoeconomic and enviroeconomic parameters have been evaluated. Values of energy payback time, per kilogram cost of producing fresh water and exergy loss per unit Rs. have been evaluated to be 1.72 years, Rs. 0.95/kg, and 0.128 kWh/Rs. respectively.

Myeloablative Versus Reduced Intensity Conditioning Regimens for Allogeneic Hematopoietic Stem Cell Transplant for Acute Myeloid Leukemia and Myelodysplastic Syndrome: A Retrospective Analysis.

The conditioning regimens used for the allo-HSCT include either myeloablative conditioning (MAC) or reduced intensity conditioning (RIC) regimens based on the age, performance status and co-morbidities. Studies comparing the survival outcomes of RIC and MAC allo-HSCT in AML and MDS patients have reported contradictory results. We therefore retrospectively analyzed our data of AML and MDS patients who received MAC and RIC allo-HSCT at our center and compared the long term outcome of the two conditioning regimens. One hundred twenty six consecutive patients were evaluated, 32 (25.4%) underwent MAC allo-HSCT and 94 (74.6%) underwent RIC allo-HSCT. The most common MAC regimen used was busulfan plus cyclophosphamide and the most common RIC regimen used was fludarabine plus melphalan. The median age was higher in RIC group (44 years, range 4-75 years) compared to MAC group (31 yrs, range 6-51 yrs, p = 0.001). There was no significant difference in terms of overall survival (p = 0.498), relapse-free survival (p = 0.791) and non-relapse mortality (p = 0.366) between the two groups. In multivariate analysis, only chronic graft-versus-host disease resulted in decreased risk of relapse and improved overall survival irrespective of the conditioning regimens used.

Combining conventional QTL analysis and whole-exome capture-based bulk-segregant analysis provides new genetic insights into tuber sprout elongation and dormancy release in a diploid potato population.

Tuber dormancy and sprouting are commercially important potato traits as long-term tuber storage is necessary to ensure year-round availability. Premature dormancy release and sprout growth in tubers during storage can result in a significant deterioration in product quality. In addition, the main chemical sprout suppressant chlorpropham has been withdrawn in Europe, necessitating alternative approaches for controlling sprouting. Breeding potato cultivars with longer dormancy and slower sprout growth is a desirable goal, although this must be tempered by the needs of the seed potato industry, where dormancy break and sprout vigour are required for rapid emergence. We have performed a detailed genetic analysis of tuber sprout growth using a diploid potato population derived from two highly heterozygous parents. A dual approach employing conventional QTL analysis allied to a combined bulk-segregant analysis (BSA) using a novel potato whole-exome capture (WEC) platform was evaluated. Tubers were assessed for sprout growth in storage at six time-points over two consecutive growing seasons. Genetic analysis revealed the presence of main QTL on five chromosomes, several of which were consistent across two growing seasons. In addition, phenotypic bulks displaying extreme sprout growth phenotypes were subjected to WEC sequencing for performing BSA. The combined BSA and WEC approach corroborated QTL locations and served to narrow the associated genomic regions, while also identifying new QTL for further investigation. Overall, our findings reveal a very complex genetic architecture for tuber sprouting and sprout growth, which has implications both for potato and other root, bulb and tuber crops where long-term storage is essential.