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Despite intensive research in surface enhanced Raman spectroscopy (SERS), the influence mechanism of chemical effects on Raman signals remains elusive. Here, we investigate such chemical effects through tip-enhanced Raman spectroscopy (TERS) of a single planar ZnPc molecule with varying but controlled contact environments. TERS signals are found dramatically enhanced upon making a tip-molecule point contact. A combined physico-chemical mechanism is proposed to explain such an enhancement via the generation of a ground-state charge-transfer induced vertical Raman polarizability that is further enhanced by the strong vertical plasmonic field in the nanocavity. In contrast, TERS signals from ZnPc chemisorbed flatly on substrates are found strongly quenched, which is rationalized by the Raman polarizability screening effect induced by interfacial dynamic charge transfer. Our results provide deep insights into the understanding of the chemical effects in TERS/SERS enhancement and quenching.
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BACKGROUND: Hepatitis C virus (HCV) is the major cause of liver cirrhosis, chronic liver disease, and hepatocellular carcinoma. More than 10 million individuals are living with HCV infection in Pakistan. Due to unawareness, very little information is known about HCV genotype occurrence in Punjab, the largest province of Pakistan. Identification of HCV genotype is very important for HCV treatment because different genotypes of HCV respond differently to antiviral therapy. OBJECTIVE: The purpose of this research was to determine the distribution frequency of different HCV genotypes in the Punjab province and to demonstrate the distribution pattern of HCV genotypes in different age groups and sexes. MATERIALS AND METHODS: In this study, we performed HCV genotyping of 3692 samples collected from different sites of the Punjab province, Pakistan. Among 3692 samples, 1755 (47.5%) were males and 1937 (52.4%) were females. RESULTS: A total of 3692 samples were subjected to HCV genotyping and 2977 (81%) patients were genotyped successfully, whereas 715 (19%) patients were found to be HCV not detected. Our study demonstrated that among typeable genotypes, 3a constituted 2582 (69.9%) patients followed by 1a (n = 280) 7.5%, 1b (n = 64) 1.7%, 2a (n = 6) 0.16%, genotype 4 (n = 10) 0.27%, 3+4 (n = 2) 0.56%, 1a+2a (n = 11) 0.29%, 1b+2a (n = 1) 0.02%, 1a+1b (n = 1) 0.02%, and 1a+1b+3 (n = 1) 0.02% patients. HCV genotype distribution was evaluated gender wise and in different age groups like 0-12, 13-18, 19-59, and >60 years. All the HCV genotypes were equally distributed among men and women. The most affected age group was 19-59 years as compared to other age groups. CONCLUSION: The most frequently distributed HCV genotype in Punjab was found to be genotype 3a followed by genotype 1a, and only 0.94% of infected patients had a mixed genotype infection. Genotype 1a was found to be increasing significantly in the studied population. With these results, it can be assumed that genotype 3a may be replaced by genotype 1a with the passage of time. If this happens, this situation will be challenging in terms of antiviral therapy.
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Background/objective Coronavirus infectious disease (COVID-19) is a novel disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). Some studies have shown that disease severity according to clinical and biochemical parameters are in direct relation to viral load while others have found no direct correlation. In this study, the COVID-19 cycle threshold (Ct) value, which is taken as a direct indicator of the viral load, has been correlated with the biochemical and clinical parameters in COVID-19 patients. Methods In this cross-sectional, retrospective, and single-center study, 365 patients admitted with COVID 19 were divided into three groups according to their Ct values obtained from reverse transcription-polymerase chain reaction RT-PCR as 1 (9-20), 2 (21-30), and 3 (31-40). The correlation of the COVID-19 Ct value with biochemical parameters and clinical presentation (taken as mild, moderate, and severe) was done and analyzed. The chi-square test was used for the correlation and calculated by using SPSS V-24.0 (IBM Corp., Armonk, NY). p-value <0.05 was considered significant statistically. Results Disease severity levels (mild, moderate, and severe) correlated in group 1 (Ct value 9 to 20), 2 (Ct value 21 to 30), and 3 (Ct value 31 to 40) but no significance was found between disease severity levels and the Ct value groups' p-value (>0.05). All the biochemical parameters analyzed (alanine transaminase (ALT), aspartate aminotransferase (AST), albumin, bilirubin, c-reactive protein (CRP), lactate dehydrogenase (LDH), ferritin, D-dimer, and total leucocyte count (TLC)) showed a significant p-value (<0.05) in all the three groups studied. Procalcitonin (PCT), however, did not show any significant value in any of the groups studied. In the intergroup assessment, it was found that the values of ALT, AST, albumin, CRP, ferritin, bilirubin, and TLC are maximum in group 2 with a downward trend in groups 1 and 2. Neutrophils and lymphocytes did not show any variations. LDH did not follow the trend of increasing viral load. Conclusions The severity of the disease was not statistically significant in the Ct value groups (p> 0.05). However biochemical parameters, i.e. ALT, AST, ALP, CRP, and bilirubin were statistically significant (p<0.05). Patients with COVID-19 should be closely monitored for the assessment of disease progression according to the above-mentioned biochemical parameters.
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The strong spatial confinement of a nanocavity plasmonic field has made it possible to visualize the inner structure of a single molecule and even to distinguish its vibrational modes in real space. With such ever-improved spatial resolution, it is anticipated that full vibrational imaging of a molecule could be achieved to reveal molecular structural details. Here we demonstrate full Raman images of individual vibrational modes at the ångström level for a single Mg-porphine molecule, revealing distinct characteristics of each vibrational mode in real space. Furthermore, by exploiting the underlying interference effect and Raman fingerprint database, we propose a new methodology for structural determination, which we have called 'scanning Raman picoscopy', to show how such ultrahigh-resolution spectromicroscopic vibrational images can be used to visually assemble the chemical structure of a single molecule through a simple Lego-like building process.