Laccase Mimics: Probing the Electrocatalytic Potential for CO Reduction.

The intricate copper-based redox center in laccase serves as an exemplar for developing laccase mimics. The current need of the hour is exploring the application of these biogenic laccase mimics beyond their traditional roles in sustainable energy conversion. This study investigates the untapped potential of laccase and their biogenic copper-amino acid mimic in the context of electrochemical CO₂ reduction (ECR), leveraging the Cu/Cu redox system.

Hydroxy-substituted aromatic N-heterocycles as high-affinity CO adsorbents: a DFT study.

Hydroxy-substituted aromatic N-heterocycles, including hydroxy pyridine (py), dihydroxy naphthyridines (nt), and trihydroxy pyridonaphthyridines (pn), have been investigated for their potential as CO adsorbents using density functional theory (DFT) calculations. Building on the pioneering work of Luo , who demonstrated exceptional CO capture capacities in pyridine-containing anion-functionalized ionic liquids, this study extends the exploration to a broader range of N-heterocycles. These N-heterocycles exhibit exceptional CO capture capabilities, driven by cooperative interactions between nitrogen and oxygen centres with CO.

Substituent Effects on NMR Chemical Shifts and Cyclic Hydrogen Bonding in 2-Pyridone Dimers: An Accurate Approach to Hammett Constant Determination Linking Structure, Energetics, and Electron Distribution.

The Hammett substituent parameter () is fundamental to physical organic chemistry but often suffers from inconsistencies in experimental determination across diverse substituents. This study presents a quantum chemical approach for estimating values using H NMR chemical shift differences (Δ) in hydrogen-bonded 2-pyridone heterodimers. Using density functional theory (M06L/6-311++G(d,p)), we examined four dimer topologies─, , , and ─and found that the Δ values in the configuration, where the substituent is spatially remote from the hydrogen-bonding region, exhibit the strongest correlation with .

Artificial intelligence based malignant lymphoma type prediction using enhanced super resolution image and hybrid feature extraction algorithm.

In the medical field, the most common and frequent type of blood cancer is lymphoma. Accurately predicting and early response to lymphoma treatment will be useful for initiating treatment plans to achieve a greater rate of cure or reduced risk of treatment-related morbidity and death. Numerous research studies have revealed several pre-treatment predictive variables, including age, lactate dehydrogenase (LDH), Ann Arbor stage, and ECOG performance.

Efficacy and safety of 8-week regimens for the treatment of rifampicin-susceptible pulmonary tuberculosis (TRUNCATE-TB): a prespecified exploratory analysis of a multi-arm, multi-stage, open-label, randomised controlled trial.

Background: WHO recommends a 2-month optimal duration for new drug regimens for rifampicin-susceptible tuberculosis. We aimed to investigate the efficacy and safety of the 8-week regimens that were assessed as part of the TRUNCATE management strategy of the TRUNCATE-TB trial.

Methods: TRUNCATE-TB was a multi-arm, multi-stage, open-label, randomised controlled trial in which participants aged 18-65 years with rifampicin-susceptible pulmonary tuberculosis were randomly assigned via a web-based system, using permuted blocks, to 24-week standard treatment (rifampicin, isoniazid, pyrazinamide, and ethambutol) or the TRUNCATE management strategy comprising initial 8-week treatment, then post-treatment monitoring and re-treatment where needed.