Rrm3 and Pif1 division of labor during replication through leading and lagging strand G-quadruplex.

Members of the conserved Pif1 family of 5'-3' DNA helicases can unwind G4s and mitigate their negative impact on genome stability. In Saccharomyces cerevisiae, two Pif1 family members, Pif1 and Rrm3, contribute to the suppression of genomic instability at diverse regions including telomeres, centromeres and tRNA genes. While Pif1 can resolve lagging strand G4s in vivo, little is known regarding Rrm3 function at G4s and its cooperation with Pif1 for G4 replication. Here, we monitored replication through G4 sequences in real time to show that Rrm3 is essential for efficient replisome progression through G4s located on the leading strand template, but not on the lagging strand. We found that Rrm3 importance for replication through G4s is dependent on its catalytic activity and its N-terminal unstructured region. Overall, we show that Rrm3 and Pif1 exhibit a division of labor that enables robust replication fork progression through leading and lagging strand G4s, respectively.

Genomics empowering conservation action and improvement of celery in the face of climate change.

MAIN CONCLUSION: Integration of genomic approaches like whole genome sequencing, functional genomics, evolutionary genomics, and CRISPR/Cas9-based genome editing has accelerated the improvement of crop plants including leafy vegetables like celery in the face of climate change. The anthropogenic climate change is a real peril to the existence of life forms on our planet, including human and plant life. Climate change is predicted to be a significant threat to biodiversity and food security in the coming decades and is rapidly transforming global farming systems. To avoid the ghastly future in the face of climate change, the elucidation of shifts in the geographical range of plant species, species adaptation, and evolution is necessary for plant scientists to develop climate-resilient strategies. In the post-genomics era, the increasing availability of genomic resources and integration of multifaceted genomics elements is empowering biodiversity conservation action, restoration efforts, and identification of genomic regions adaptive to climate change. Genomics has accelerated the true characterization of crop wild relatives, genomic variations, and the development of climate-resilient varieties to ensure food security for 10 billion people by 2050. In this review, we have summarized the applications of multifaceted genomic tools, like conservation genomics, whole genome sequencing, functional genomics, genome editing, pangenomics, in the conservation and adaptation of plant species with a focus on celery, an aromatic and medicinal Apiaceae vegetable. We focus on how conservation scientists can utilize genomics and genomic data in conservation and improvement.

ssVERDICT: Self-supervised VERDICT-MRI for enhanced prostate tumor characterization.

PURPOSE: Demonstrating and assessing self-supervised machine-learning fitting of the VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumors) model for prostate cancer. METHODS: We derive a self-supervised neural network for fitting VERDICT (ssVERDICT) that estimates parameter maps without training data. We compare the performance of ssVERDICT to two established baseline methods for fitting diffusion MRI models: conventional nonlinear least squares and supervised deep learning. We do this quantitatively on simulated data by comparing the Pearson's correlation coefficient, mean-squared error, bias, and variance with respect to the simulated ground truth. We also calculate in vivo parameter maps on a cohort of 20 prostate cancer patients and compare the methods' performance in discriminating benign from cancerous tissue via Wilcoxon's signed-rank test. RESULTS: In simulations, ssVERDICT outperforms the baseline methods (nonlinear least squares and supervised deep learning) in estimating all the parameters from the VERDICT prostate model in terms of Pearson's correlation coefficient, bias, and mean-squared error. In vivo, ssVERDICT shows stronger lesion conspicuity across all parameter maps, and improves discrimination between benign and cancerous tissue over the baseline methods. CONCLUSION: ssVERDICT significantly outperforms state-of-the-art methods for VERDICT model fitting and shows, for the first time, fitting of a detailed multicompartment biophysical diffusion MRI model with machine learning without the requirement of explicit training labels.

The curious case of CO2 dissociation on Cu(110).

Dissociation of CO2 on copper surfaces is an important model system for understanding the elementary steps in catalytic conversion of CO2 to methanol. Using molecular beam-surface scattering methods, we measure the initial dissociation probabilities (S0) of CO2 on a flat, clean Cu(110) surface under ultrahigh vacuum conditions. The observed S0 ranges from 3.9 × 10-4 to 1.8 × 10-2 at incidence energies of 0.64-1.59 eV. By extrapolating the trend observed in the incidence energy dependence of S0, we estimate the lower limit of the dissociation barrier on terrace sites to be around 2 eV. We discuss these results in the context of what is known from previous studies on this system using different experiments and theoretical/computational methods. These findings are anticipated to be valuable for correctly understanding the elementary steps in CO2 dissociation on Cu surfaces.

Prediction of bitcoin stock price using feature subset optimization.

In light of recent cryptocurrency value fluctuations, Bitcoin is gradually gaining recognition as an investment vehicle. Given the market's inherent volatility, accurate forecasting becomes crucial for making informed investment decisions. Notably, previous research has utilized machine learning methods to enhance the accuracy of Bitcoin price predictions. However, few studies have explored the potential of employing diverse modeling methods for sampling with varying data formats and dimensional characteristics. This study aims to identify the internal feature subset that yields the highest returns in forecasting Bitcoin's price. Specifically, Bitcoin's internal features were categorized into four groups: currency data, block details, mining information, and network difficulty. Subsequently, a long short-term memory (LSTM) artificial neural network was employed to predict the next day's Bitcoin closing price, utilizing various categorizations of feature subsets. The model underwent training using two and a half years of historical data for each feature. The findings revealed a mean absolute error rate of 6.38% when modeling with the block details category features. This enhanced performance primarily stemmed from the positive relationship between Bitcoin price and this data subset's low ambiguity. Experimental results underscored that, compared to other investigated feature subsets, the categorization of block detail features provided the most accurate Bitcoin price predictions, laying the foundation for future research in this domain.

Support Vector Machine-Based Prediction Models for Drug Repurposing and Designing Novel Drugs for Colorectal Cancer.

Colorectal cancer (CRC) has witnessed a concerning increase in incidence and poses a significant therapeutic challenge due to its poor prognosis. There is a pressing demand to identify novel drug therapies to combat CRC. In this study, we addressed this need by utilizing the pharmacological profiles of anticancer drugs from the Genomics of Drug Sensitivity in Cancer (GDSC) database and developed QSAR models using the Support Vector Machine (SVM) algorithm for prediction of alternative and promiscuous anticancer compounds for CRC treatment. Our QSAR models demonstrated their robustness by achieving a high correlation of determination (R2) after 10-fold cross-validation. For 12 CRC cell lines, R2 ranged from 0.609 to 0.827. The highest performance was achieved for SW1417 and GP5d cell lines with R2 values of 0.827 and 0.786, respectively. Further, we listed the most common chemical descriptors in the drug profiles of the CRC cell lines and we also further reported the correlation of these descriptors with drug activity. The KRFP314 fingerprint was the predominantly occurring descriptor, with the KRFPC314 fingerprint following closely in prevalence within the drug profiles of the CRC cell lines. Beyond predictive modeling, we also confirmed the applicability of our developed QSAR models via in silico methods by conducting descriptor-drug analyses and recapitulating drug-to-oncogene relationships. We also identified two potential anti-CRC FDA-approved drugs, viomycin and diamorphine, using QSAR models. To ensure the easy accessibility and utility of our research findings, we have incorporated these models into a user-friendly prediction Web server named "ColoRecPred", available at https://project.iith.ac.in/cgntlab/colorecpred. We anticipate that this Web server can be used for screening of chemical libraries to identify potential anti-CRC drugs.

Iridium(III)-catalyzed photoredox cross-coupling of alkyl bromides with trialkyl amines: access to α-alkylated aldehydes.

A C(sp3)-C(sp3) cross coupling approach based on an iridium-photocatalytic radical process has been developed enabling the synthesis of various α-alkylated aldehydes from easily available/synthesized alkyl bromides and trialkyl amines under mild photocatalytic conditions. The synthesized aldehydes are also explored as a functional handle for various useful products such as carboxylic acid, alcohol and N-heterocycle synthesis.

A highly anisotropic family of hexagonal bipyramidal Dy(III) unsaturated 18-crown-6 complexes exceeding the blockade barrier over 2700 K: a computational exploration.

In the present work, we have explored a series of unsaturated hexa-18-crown-6 (U18C6) ligands towards designing highly anisotropic Dy(III) based single-ion magnets (SIMs) with the general formula [Dy(U18C6)X2]+ (where U18C6 = [C12H12O6] (1), [C12H12S6] (2), [C12H12Se6] (3), [C12H12O4S2] (4), [C12H12O4Se2] (5) and X = F, Cl, Br, I, OtBu and OSiPh3). By analysing the electronic structure, bonding and magnetic properties, we find that the U18C6 ligands prefer stabilising the highly symmetric eight-coordinated hexagonal bipyramidal geometry (HBPY-8), which is the source of the near-Ising type anisotropy in all the [Dy(U18C6)X2]+ complexes. Moreover, the ability of sulfur/selenium substituted U18C6 ligands to stabilize the highly anisotropic HBPY-8 geometry makes them more promising towards engineering the equatorial ligand field compared to substituted saturated 18C6 ligands where the exodentate arrangement of the S lone pairs results in low symmetry. Magnetic relaxation analysis predicts a record barrier height over 2700 K for [Dy(C12H12O6)F2]+ and [Dy(C12H12S6)X2]+ (where X = F, OtBu and OSiPh3) complexes, nearly 23% higher than those of the top performing Dy(III) based SIMs in the literature.

Waxy papules, infiltrated alopecic plaques, and shin ichthyosis.

A 38-year-old male presented with waxy papules, plaques over the neck and extremities, and ichthyotic scales over the lower limbs. Skin biopsy revealed a dense medium-sized lymphocytic infiltrate in the dermis, with perifollicular accentuation and focal exocytosis into the follicular epithelium with strong positivity for CD 3, 4, and 5. Considering the clinicopathological correlation, a diagnosis of follicular mycosis fungoides (FMF) was made. It is a variant of classic mycosis fungoides (MF) where atypical cells invade the follicular epithelium.

Fieldworker effects on quality of data collected on sensitive questions in National Family Health Surveys: An analysis based on intimate partner violence in India.

National Family Health Survey (NFHS) has played a pivotal role in formulating policies and programs by providing nationally representative data on a wide range of monitoring and impact evaluation indicators in population, health and nutrition. However, due to measurement errors resulting in misreporting, the collection of accurate data on sensitive issues in sample surveys has always been a matter of concern. This study examines the fieldworker effect on the reporting of physical, sexual, and emotional Intimate Partner Violence (IPV) using fifth round of NFHS (2019-21) data in India. The cross-classified multi-level model was used to examine the fieldworker's effect on the reporting of IPV. The fieldworker effect accounted for around 32% of total variation in the reporting of intimate partner violence. The fieldworker's effect varied from 26% to 41 % for physical violence, 29% to 33% for emotional IPV and 30%-36% for sexual IPV. It was observed that variation due to fieldworker for non-sensitive outcomes was negligible.Of total variation, only 1.6% for information related to ever attending school, 4.8% for ever given birth, 5% for currently pregnant and 8.5% for information on ever terminated pregnancy was being explained by the fieldworker. Our results indicate a significant fieldworker influence on the likelihood of reporting intimate partner violence, underlining the need for an increased understanding of the impact of fieldworkers on data outputs, especially-but not exclusively-when queries contain delicate or stigmatized themes. This study highlights the importance of providing extra guidance and special training to the fieldworkers when collecting sensitive information related to IPV.

Latent class analysis of chronic disease co-occurrence, clustering and their determinants in India using Study on global AGEing and adult health (SAGE) India Wave-2.

Background: Understanding chronic disease prevalence, patterns, and co-occurrence is pivotal for effective health care planning and disease prevention strategies. In this paper, we aimed to identify the clustering of major non-communicable diseases among Indian adults aged ≥50 years based on their self-reported diagnosed non-communicable disease status and to find the risk factors that heighten the risk of developing the identified disease clusters. Methods: We utilised data from the nationally representative survey Study on Global AGEing and Adult Health (SAGE Wave-2). The eligible sample size was 6298 adults aged ≥50 years. We conducted the latent class analysis to uncover latent subgroups of multimorbidity and the multinomial logistic regression to identify the factors linked to observed latent class membership. Results: The latent class analysis grouped our sample of men and women >49 years old into three groups - mild multimorbidity risk (41%), moderate multimorbidity risk (30%), and severe multimorbidity risk (29%). In the mild multimorbidity risk group, the most prevalent diseases were asthma and arthritis, and the major prevalent disease in the moderate multimorbidity risk group was low near/distance vision, followed by depression, asthma, and lung disease. Angina, diabetes, hypertension, and stroke were the major diseases in the severe multimorbidity risk category. Individuals with higher ages had an 18% and 15% higher risk of having moderate multimorbidity and severe multimorbidity compared to those in the mild multimorbidity category. Females were more likely to have a moderate risk (3.36 times) and 2.82 times more likely to have severe multimorbidity risk. Conclusions: The clustering of diseases highlights the importance of integrated disease management in primary care settings and improving the health care system to accommodate the individual's needs. Implementing preventive measures and tailored interventions, strengthening the health and wellness centres, and delivering comprehensive primary health care services for secondary and tertiary level hospitalisation may cater to the needs of multimorbid patients.

Hybrid peripheral nerve sheath tumours: MRI features with pathological correlation in 24 cases.

OBJECTIVES: To describe the MRI features of histologically proven hybrid peripheral nerve sheath tumours (HPNST). METHODS: A retrospective analysis of the MRI features of 24 histologically proven cases of HPNST over 7 years. Demographic data obtained from clinical records included age, gender, and date of diagnosis. Two readers independently assessed MRI studies and assessed the following features: involvement of a major nerve, intramuscular location, lesion morphology, entering nerve sign, exiting nerve sign, target sign, fascicular sign, split fat sign, and ancient change (cystic change). Inter-observer agreement was assessed with Cohen's kappa coefficient. Histological diagnosis was based on either image-guided needle biopsy or resection histology. RESULTS: The study included 9 males and 15 females with mean age 50 years (range: 24-78 years). Nine tumours (35%) involved a major nerve including spinal roots (5), radial (1), median (1), tibial (1), and axillary (1), while 5 (21%) tumours were intramuscular. The mean tumour size was 4.2 cm (standard deviation of 2.4 cm). The frequency of MRI features was as follows: lobular contour (71%; 17/24), ancient change (38%; 9/24), fascicular sign (17%; 4/24), entering nerve sign (21%; 5/24), exiting nerve sign (13%; 3/24), target sign (13%; 3/24), and split fat sign (8%; 2/24). Inter-observer agreement was high, ranging from 0.7 to 0.83. CONCLUSIONS: HPNST infrequently demonstrate the classical MRI signs of benign peripheral nerve sheath tumours, but commonly have a lobular morphology and can show ancient/cystic change. ADVANCES IN KNOWLEDGE: This is the first study in the literature analysing the MRI features of histologically proven HPNST. HPNST infrequently shows the classical MRI signs that would be expected with benign peripheral nerve sheath tumours although commonly have a lobular morphology and show cystic change.

The Catalysts-Based Synthetic Approaches to Quinolines: A Review.

The most common heterocyclic aromatic molecule with potential uses in industry and medicine is quinoline. Its chemical formula is C9H7N, and it has a distinctive double-ring structure with a pyridine moiety fused with a benzene ring. Various synthetic approaches synthesize quinoline derivatives. These approaches include solvent-free synthetic approach, mechanochemistry, ultrasonic, photolytic synthetic approach, and microwave and catalytic synthetic approaches. One of the important synthetic approaches is a catalyst-based synthetic approach in which different catalysts are used such as silver-based catalysts, titanium-based nanoparticle catalysts, new iridium catalysts, barium-based catalysts, iron-based catalysts, gold-based catalysts, nickel-based catalyst, some metal-based photocatalyst, α-amylase biocatalyst, by using multifunctional metal-organic framework-metal nanoparticle tandem catalyst etc. In the present study, we summarized different catalyst-promoted reactions that have been reported for the synthesis of quinoline. Hopefully, the study will be helpful for the researchers.

Chronic sexually acquired reactive arthritis secondary to Chlamydiatrachomatis.

Reactive arthritis is included in the spectrum of seronegative spondyloarthritides, occurring secondary to triggers of genitourinary and gastrointestinal tract infections. We describe two cases of sexually acquired reactive arthritis secondary to genital infection by Chlamydia trachomatis, diagnosed by in-house polymerase chain reaction performed on the first void urine. Both patients were managed with a combined approach of short course antibiotics, immunosuppressive agents, biologicals and surgical intervention.

Macrolide and fluoroquinolone resistance associated mutations in Mycoplasma genitalium in men who have sex with men attending STI clinic: A pilot study from India.

Background Increasing rates of macrolide and fluroquinolone resistance in Mycoplasma genitalium (MG) are being reported worldwide with resultant treatment failure. Aims and objectives We aimed to determine the level of antibiotic resistance of MG in men who have sex with men (MSM) attending a sexually transmitted infections (STIs) clinic in New Delhi, India. Methods Real-time polymerase chain reaction (PCR) assays targeting MgPa and pdhD genes were performed to detect MG rectal, urogenital or oropharyngeal infections in 180 MSM between January 2022 and June 2023. Macrolide resistance-associated mutations (MRM) and quinolone resistance-associated mutations (QRM) were detected by specific amplification of domain V of 23SrRNA gene and appropriate regions of parC and gyrA genes respectively followed by sequencing. PCR-based screening for Chlamydia trachomatis (CT) infection was also performed. Results A total of 13 (7.2%) MSM were positive for MG infection. The most common site of infection was anorectum (8/13; 61.5%) followed by the urethra (5/13; 38.5%). None of the patients had infection at both the sites, and no oropharyngeal MG infection was detected. CT infection was detected in 37 (20.6%) MSM. Of the 13 MG-infected MSM, 6 (46.2%) were co-infected with CT. MRM and QRM were found in five (46.2%) and two (15.4%) strains, respectively. Both Quinolone resistance mutation (QRM)-harbouring strains also harboured MRM. All the five MG isolates carried the MRM A2071G. Both the QRM isolates co-harboured the parC and gyrA single-nucleotide polymorphisms. There was no correlation between the presence of antibiotic resistance and co-infection with CT (P = 0.52). Limitation Because all patients in the study were MSM, the high rate of resistance to macrolides and fluoroquinolones could not be extrapolated for non-MSM patients. Conclusion This is a report of an initial survey of antibiotic resistance to MG in a country where its diagnosis and treatment are not routinely available. We found a high prevalence of MG-carrying MRM, QRM and dual-class resistance in MSM in the absence of antibiotic exposure. This study mandates the need for both screening and detection of antimicrobial resistance against MG.

Empowering Little Fighters: Post-Cardiotomy Pediatric ECMO and the Journey to Recovery.

INTRODUCTION: Extra Corporeal Membrane Oxygenation (ECMO) has long been used for cardiorespiratory support in the immediate post-paediatric cardiac surgery period with a 2-3% success as per the ELSO registry. Success in recovery depends upon the optimal delivery of critical care to paediatric patients and a comprehensive healthcare team. METHODOLOGY: The survival benefit of children placed on central veno arterial (VA) ECMO following elective cardiac surgeries for congenital heart disease (n = 672) was studied in a cohort of 29 (4.3%) cases from the period of Jan 2018 to Dec 2022 in our cardiac surgical centre. Indications for placing these patients on central VA ECMO included inability to wean from cardiopulmonary bypass (CPB), low cardiac output syndrome, severe pulmonary arterial hypertension, significant bleeding, anaphylaxis, respiratory failure and severe pulmonary edema. RESULTS: The mean time to initiation of ECMO was less than 5 h and the mean duration of ECMO support was 56 h with a survival rate of 58.3%. Amongst perioperative complications, sepsis and arrhythmia on ECMO were found to be negatively associated with survival. Improvements in the pH, PaO2 levels and serum lactate levels after initiation of ECMO were associated with survival benefits. CONCLUSION: The early initiation of ECMO for paediatric cardiotomies could be a beacon of hope for families and medical teams confronting these challenging situations. Improvement in indicators of adequate perfusion and ventricular recoveries like pH and serum lactate and absence of arrhythmia and sepsis are associated with good outcomes.

Nutritional status of Zombi pea (Vigna vexillata) as influenced by plant density and deblossoming.

Feeding billions, a healthy and nutritious diet in the era of climate change is a major challenge before plant breeders, geneticists and agronomist. In this context, the continuous search for adaptive and nutritious crops could be a better alternative to combat the problems of hunger and malnutrition. The zombi pea, a nutritious and underutilized leguminous vegetable, is one of such better alternatives to feed billions a nutritious food besides being a potential gene source for breeding abiotic stress resistant varieties. To evaluate its potential as a wonder crop in the tropical and subtropical regions of India, the nutritional status of tubers, pods and pericarp were investigated under different treatments of plant spacings and deblossoming. The experiment was conducted in split plot design with three replications and eight treatments during 2021-2022 in the coastal regions of India. The nutrient profiling in tubers and pericarp of pods in zombi pea revealed higher accumulation of nutrients viz. potassium (K), magnesium (Mg), iron (Fe), manganese (Mn) and zinc (Zn) with blossom retention. The zombi pea tubers reflected significantly high protein accumulation with the increase in plant spacing. The results pertaining to nutrient profiling in the pods of zombi pea indicated that the plant spacing has no significant effect on the accumulation of majority of nutrients under study. The above-mentioned findings are conspicuously novel and valuable. The present study would pave the way for understanding nutritional importance and breeding potential of this orphan crop. The blossom retention renders higher nutrient accumulation in tubers, pods and pericarp of zombi pea. Deblossoming has no significant influence on nutritional profile of this wonder crop but, wider spacing is effective in producing tubers with high protein content.

A Spin-Frustrated Azide- and Alkoxide-Bridged Heterobimetallic Mixed-Valence MnIIMnIII2NiII4 Disc with S = 17/2 or 19/2.

Seven-membered homometallic FeIII7, MnIII3MnII4 coordination clusters were previously reported to be spin-frustrated molecular discs. Herein, a mixed bimetallic and mixed-valence dicationic [MnIIMnIII2NiII4(N3)4(hmp)10](NO3)2 (12+(NO3)2) was isolated in pure form without scrambling of Ni/Mn ions. It was structurally characterized by single-crystal X-ray single-crystal diffraction. The presence of MnII ions at the center of the disc has been confirmed by EPR measurements. The magnetic studies suggest that complex 12+(NO3)2 possesses spin frustration with spin ground states S = 17/2 and 19/2, which has been studied and supported by DFT calculation. The purity of 12+(NO3)2 was confirmed by powder XRD measurements, and the ratio of Ni:Mn = 4:3 was further determined by SEM-EDX analysis.