Electrically controlled eight-spin-qubit entangled-state generation in a molecular break junction.

The generation of spin-based multi-qubit entangled states in the presence of an electric field is one of the most challenging tasks in current quantum-computing research. Such examples are still elusive. By using non-equilibrium Green's function-based quantum-transport calculations in combination with non-collinear spin density functional theory, we report that an eight-spin-qubit entangled state can be generated with the high-spin state of a dinuclear Fe(II) complex when the system is placed in a molecular break junction. The possible gate operation scheme, gating time, and decoherence issues have been carefully addressed. Furthermore, our calculations reveal that the preservation of the high spin state of this complex is possible if the experimentalists keep the electric-field strength below 0.78 V nm(-1). In brief, the present study offers a unique way to realize the first example of a multi-qubit entangled state by electrical means only.

Probing the bioethanol production potential of Scheffersomyces (Pichia) stipitis using validated genome-scale model.

A detailed in silico analysis of different strategies for enhancement of bioethanol production by Scheffersomyces stipitis, = Pichia stipitis, using validated genome-scale metabolic model is presented. Glucose inhibition on xylose uptake is dominant in S. stipitis which makes fed-batch fermentation more effective for higher sugar concentrations. Bioethanol production potential of S. stipitis can be improved by growth media modification by introducing certain amino acids in small quantities. Slower sugar uptake by S. stipitis can be overcome by community-culture with recombinant Escherichia coli strain ZSC113, which has a higher xylose uptake rate. Ethanol yield and productivity of community-culture can be further enhanced by genetic modification of E. coli strain ZSC113.

Dynamic flux balance analysis of batch fermentation: effect of genetic manipulations on ethanol production.

In silico optimization of bioethanol production from lignocellulosic biomasses is investigated by combining process systems engineering approach and systems biology approach. Lignocellulosic biomass is an attractive sustainable carbon source for fermentative production of bioethanol. For enhanced ethanol production, metabolic engineering of wild-type strains-that can metabolize both hexose and pentose sugars or microbial consortia consisting of substrate-selective microbes-may be advantageous. This study presents a detailed in silico analysis of bioethanol production from glucose-xylose mixtures of various compositions by batch mono-culture and co-culture fermentation of specialized microbes. Dynamic flux balance models based on available genome-scale reconstructions of the microorganisms have been used to analyze bioethanol production, and the maximization of ethanol productivity is addressed by computing optimal aerobic-anaerobic switching times. Effects of ten metabolic engineering strategies that have been suggested in the literature for ethanol overproduction, have been evaluated for their efficiency in enhancing the ethanol productivity in the context of batch mono-culture and co-culture processes.

Post COVID sequelae among COVID-19 survivors: insights from the Indian National Clinical Registry for COVID-19.

INTRODUCTION: The effects of COVID-19 infection persist beyond the active phase. Comprehensive description and analysis of the post COVID sequelae in various population groups are critical to minimise the long-term morbidity and mortality associated with COVID-19. This analysis was conducted with an objective to estimate the frequency of post COVID sequelae and subsequently, design a framework for holistic management of post COVID morbidities. METHODS: Follow-up data collected as part of a registry-based observational study in 31 hospitals across India since September 2020-October 2022 were used for analysis. All consenting hospitalised patients with COVID-19 are telephonically followed up for up to 1 year post-discharge, using a prestructured form focused on symptom reporting. RESULTS: Dyspnoea, fatigue and mental health issues were reported among 18.6%, 10.5% and 9.3% of the 8042 participants at first follow-up of 30-60 days post-discharge, respectively, which reduced to 11.9%, 6.6% and 9%, respectively, at 1-year follow-up in 2192 participants. Patients who died within 90 days post-discharge were significantly older (adjusted OR (aOR): 1.02, 95% CI: 1.01, 1.03), with at least one comorbidity (aOR: 1.76, 95% CI: 1.31, 2.35), and a higher proportion had required intensive care unit admission during the initial hospitalisation due to COVID-19 (aOR: 1.49, 95% CI: 1.08, 2.06) and were discharged at WHO ordinal scale 6-7 (aOR: 49.13 95% CI: 25.43, 94.92). Anti-SARS-CoV-2 vaccination (at least one dose) was protective against such post-discharge mortality (aOR: 0.19, 95% CI: 0.01, 0.03). CONCLUSION: Hospitalised patients with COVID-19 experience a variety of long-term sequelae after discharge from hospitals which persists although in reduced proportions until 12 months post-discharge. Developing a holistic management framework with engagement of care outreach workers as well as teleconsultation is a way forward in effective management of post COVID morbidities as well as reducing mortality.

Constructing regions of attainable sizes and achieving target size distribution in a batch cooling sonocrystallization process.

The application of ultrasound to a crystallization process has several interesting benefits. The temperature of the crystallizer increases during ultrasonication and this makes it difficult for the temperature controller of the crystallizer to track a set temperature trajectory precisely. It is thus necessary to model this temperature rise and the temperature-trajectory tracking ability of the crystallizer controller to perform model-based dynamic optimization for a given cooling sonocrystallization set-up. In our previous study, we reported a mathematical model based on population balance framework for a batch cooling sonocrystallization of l-asparagine monohydrate (LAM). Here we extend the previous model by including energy balance equations and a Generic Model Control algorithm to simulate the temperature controller of the crystallizer that tracks a cooling profile during crystallization. The improved model yields very good closed-loop prediction and is conveniently used for studies related to particle engineering by optimization. First, the model is used to determine the regions of attainable particle sizes for LAM batch cooling sonocrystallization process by solving appropriate dynamic optimization problems. Then the model is used to determine optimal operating conditions for achieving a target crystal size distribution. The experimental evidence clearly demonstrates the efficiency of the particle engineering approach by optimization.

Nucleation kinetics from metastable zone widths for sonocrystallization of l-phenylalanine.

This study investigates the effect of ultrasound on metastable zone width (MSZW) during crystallization of l-phenylalanine from aqueous solution. The solubility of l-phenylalanine in water was measured gravimetrically in the temperature range of 293.15-333.15K. The MSZW was measured by conventional polythermal method for four different cooling rates at five different saturation temperatures in absence and presence of ultrasound. The MSZW increased with increase in cooling rates and decreased with increase in saturation temperature. The application of ultrasound considerably reduced the MSZW for all the experiments. The obtained MSZW data are analysed using four different approaches to calculate various nucleation parameters. In presence of ultrasound, the apparent nucleation order decreased and nucleation rate constant increased significantly.

In silico analysis of bioethanol overproduction by genetically modified microorganisms in coculture fermentation.

Lignocellulosic biomass is an attractive sustainable carbon source for fermentative production of bioethanol. In this context, use of microbial consortia consisting of substrate-selective microbes is advantageous as it eliminates the negative impacts of glucose catabolite repression. In this study, a detailed in silico analysis of bioethanol production from glucose-xylose mixtures of various compositions by coculture fermentation of xylose-selective Escherichia coli strain ZSC113 and glucose-selective wild-type Saccharomyces cerevisiae is presented. Dynamic flux balance models based on available genome-scale metabolic networks of the microorganisms have been used to analyze bioethanol production and the maximization of ethanol productivity is addressed by computing optimal aerobic-anaerobic switching times. A set of genetic engineering strategies for ethanol overproduction by E. coli strain ZSC113 have been evaluated for their efficiency in the context of batch coculture process. Finally, simulations are carried out to determine the pairs of genetically modified E. coli strain ZSC113 and S. cerevisiae that significantly enhance ethanol productivity in batch coculture fermentation.

Malignant large cell calcifying sertoli cell tumor of testis with skip metastasis to lung presented with peutz-jeghers syndrome.

Large cell calcifying Sertoli cell tumor of the testis (LCCSCT) is a rare tumor that is usually benign and multifocal. It may be associated with hereditary endocrine anomalies such as Carney's and Peutz-Jeghers syndromes. It is a rare histological variant of sex cord stromal tumors. It is exceptional in elderly men and the outcome is rarely fatal. We report a case of LCCSCT in a 44 year-old man with fatal outcome. The tumor involved the right testis and several areas of the tunica albuginea were grossly invaded. It composed of cords and trabeculae of large polygonal cells embedded in a myxoid and fibrous stroma with areas of calcification along with nuclear atypia, necrosis, and abundant mitoses. The Peutz-Jeghers syndrome (PJS) is known to be commonly associated with ovarian tumors. However, its association with testicular tumors is uncommon. To the best of our knowledge, this is the eight such case being reported in the literature. Our case, to our knowledge, is the only other reported case of malignant large cell calcifying Sertoli cell tumor with clinical and histopathological features related to aggressiveness, such as large tumor size, cellular pleomorphism, high mitotic rate, necrosis and aneuploid deoxyribonucleic acid. Such characteristics are not found in benign large cell calcifying Sertoli cell tumors.

Gastric adenocarcinoma associated with lymphangitis carcinomatosa, adrenal metastasis with ectopic ACTH syndrome and malignant common bile duct stricture.

Ectopic adrenocorticotrophic hormone (ACTH) syndrome (EAS) commonly occurs secondary to neuroendocrine tumours and small cell carcinoma of lung. EAS has also been reported in association with gastric carcinoids. But, the occurrence of EAS secondary to gastric adenocarcinoma has rarely been reported. A 45-year-old male patient from Bangladesh presented with abdominal pain, jaundice and hyperpigmentation. Extensive work-up revealed poorly differentiating mucin-secreting adenocarcinoma of stomach with lymphangitis carcinomatosa of lung, bilateral adrenal metastasis and malignant common bile duct (CBD) stricture. Laboratory reports were suggestive for ectopic ACTH production. Most of these features are very rare in adenocarcinoma of stomach, and all these rare events occurring in a single patient is probably the rarest.

Genetic algorithms with filters for optimal control problems in fed-batch bioreactors.

When using a genetic algorithm (GA) to solve optimal control problems that can arise in a fed-batch bioreactor, the most obvious direct approach is to rely on a finite dimensional discretization of the optimal control problem into a nonlinear programming problem. Usually only the control function is discretized, and the continuous control function is approximated by a series of piecewise constant functions. Even though the piecewise discretized controls that the GA produces for the optimal control problem may give good performances, the control policies often show very high activity and differ considerably from those obtained using a continuous optimization strategy. The present study introduces a few filters into a real-coded genetic algorithm as additional operators and investigates the smoothing capabilities of the filters employed. It is observed that inclusion of a filter significantly smoothens the optimal control profile and often encourages the convergence of the algorithm. The applicability of the technique is illustrated by solving two previously reported optimal control problems in fed-batch bioreactors that are known to have singular arcs.