A retrospective analysis on seroprevalence of acute viral hepatitis observed among dengue patients attending a tertiary care centre in central India.

PURPOSE: The present study was conducted retrospectively to assess the frequency of acute viral hepatitis among the clinically suspected dengue cases presented at our tertiary care centre during 2021. METHODS: To determine the presence of acute viral hepatitis; Hepatitis A virus (HAV) and Hepatitis E virus (HEV) infections, 104 specimens were selected from the dengue-suspected clinical specimens received during 2021 on the basis of acute viral hepatitis symptoms. Following this, serological diagnosis was performed on those samples using anti-HAV IgM and anti-HEV IgM ELISA kits. RESULTS: Based on sero-positivity for IgM antibodies, 3 (5.3%) dengue virus (DENV) seropositive samples were positive for both HAV and HEV, while among DENV seronegative cases, 11 (22.91%) samples were positive for HEV and 1 (2.08%) sample was positive for HAV, pointing towards misdiagnosis due to overlapping symptoms. Additionally, co-infection of HAV & HEV in 1 sample was also observed in this study. CONCLUSIONS: This study revealed the presence of acute hepatitis infections among the dengue cases during monsoon and post-monsoon season. Overlapping of the clinical manifestations of these diseases can create misdiagnosis incidences raising risk for underreporting of the true cases of acute viral hepatitis infection. Dengue-suspected patients with selected symptoms during the monsoon and post-monsoon season should additionally be screened for acute hepatitis infections, as suggested in this study.

Comparison of Intraperitoneal Irrigation With Sodium Bicarbonate Versus Normal Saline in Reducing Pain After Operative Laparoscopy: A Randomized Controlled Trial.

Background It has been postulated that sodium bicarbonate can reduce postoperative pain by neutralizing the acidic peritoneal environment created by carbon dioxide. It also prevents phrenic nerve damage and peritoneal irritation. The present study is a randomized controlled trial aimed at studying the effects of sodium bicarbonate in reducing postoperative pain in laparoscopic gynecological surgeries. Materials and methods This was a single-center, prospective, two-arm, double-blinded randomized control trial in which intraperitoneal irrigation with sodium bicarbonate was compared with normal saline in operative laparoscopy. Group I (intervention group) consisted of 40 patients who received intraperitoneal sodium bicarbonate, and Group II (control group) consisted of 40 patients who received normal saline. All procedures were conducted under general anesthesia. Postoperative pain scores were compared between intervention and control groups.  Results The most common indication of laparoscopy was infertility. There was no difference in the duration of surgery between the two arms (p=0.27). The mean value of the visual analog scale (VAS) score at the shoulder tip was found to be significantly reduced in the intervention group at two hours (p=0.02), four hours (p=0.0009), and 12 hours (p=0.0002) after surgery. The mean VAS score at the abdomen and port sites was also found to be significantly reduced in the intervention group in the first 24 hours after surgery (p<0.05). With the increase in the time period from surgery, the mean VAS scores decreased in both intervention and control groups.  Conclusion Intraperitoneal irrigation with sodium bicarbonate is beneficial in reducing postoperative pain in operative laparoscopy. However, multicenter randomized trials with a greater number of participants will be helpful to confirm the findings.

Molecular surveillance of dengue virus in field-collected Aedes mosquitoes from Bhopal, central India: evidence of circulation of a new lineage of serotype 2.

Introduction: Dengue fever is hyperendemic in several Southeast and South Asian countries, including India, with all four serotypes (DENV 1-4) circulating at different periods and in different locations. Sustainable and improved virological and entomological surveillance is the only tool to prevent dengue and other vector-borne diseases. Objectives: The present study has been carried out to detect and characterize the circulating dengue virus (DENV) in field-collected Aedes mosquitoes in Bhopal, Central India. Methods: Aedes mosquitoes were collected from 29 localities within Bhopal city during October 2020 to September 2022. DENV infection was assessed in the individual head and thorax regions of Aedes mosquitoes using reverse transcriptase PCR. Positive samples were sequenced, and the circulating serotypes and genotypes were determined using phylogenetic analysis. Results: DENV RNA was detected in 7 Aedes aegypti and 1 Aedes albopictus, with infection rates of 0.59 and 0.14%, respectively. Phylogenetic analysis revealed all the isolates belonged to DENV serotype 2 and distinctly clustered with the non-Indian lineage (cosmopolitan genotype 4a), which was not recorded from the study area earlier. The time to most common recent ancestor (TMRCA) of these sequences was 7.4 years old, with the highest posterior density (HPD) of 3.5-12.2 years, indicating that this new lineage emerged during the year 2014. This is the first report on the DENV incrimination in both Ae. aegypti and Ae. albopictus mosquitoes collected from Bhopal, Central India. Conclusion: The observed emergence of the non-Indian lineage of DENV-2 in Bhopal, which again is a first report from the area, coincides with the gradual increase in DENV cases in Bhopal since 2014. This study emphasizes the importance of DENV surveillance and risk assessment in this strategically important part of the country to decipher its outbreak and severe disease-causing potential.

How Electronic Medical Record Integration Can Support More Efficient Critical Care Clinical Trials.

Large volumes of data are collected on critically ill patients, and using data science to extract information from the electronic medical record (EMR) and to inform the design of clinical trials represents a new opportunity in critical care research. Using improved methods of phenotyping critical illnesses, subject identification and enrollment, and targeted treatment group assignment alongside newer trial designs such as adaptive platform trials can increase efficiency while lowering costs. Some tools such as the EMR to automate data collection are already in use. Refinement of data science approaches in critical illness research will allow for better clinical trials and, ultimately, improved patient outcomes.

Post-Transition State Direct Dynamics Simulations on the Ozonolysis of Catechol in an N2 Bath and Comparison with Gas-Phase Results.

Chemical dynamics simulations on the post-transition state dynamics of ozonolysis of catechol are performed in this article using a newly developed QM + MM simulation model. The reaction is performed in a bath of N2 molecules equilibrated at 300 K. Two bath densities, namely, 20 and 324 kg/m3, are considered for the simulation. The excitation temperatures of a catechol-O3 moiety are taken as 800, 1000, and 1500 K for each density. At these new excitation temperatures, the gas-phase results are also computed to compare the results and quantify the effect of surrounding molecules on this reaction. Like the previous findings, five reaction channels are observed in the present investigation, producing CO2, CO, O2, small carboxylic acid (SCA), and H2O. The probabilities of these products are discussed with the role of bath densities. Results from the gas-phase simulation and density of 20 kg/m3 are very similar, whereas results differ significantly at a higher bath density of 324 kg/m3. The rate constants for the unimolecular channel at each temperature and density are also calculated and reported. The QM + MM setup used here can also be used for other chemical reactions, where the solvent effect is important.

Continued dominance of dengue virus serotype 2 during the recent Central India outbreaks (2019-2021) with evidence of genetic divergence.

Central India faced major dengue outbreaks in 2019 and 2021. In the present study, we aimed to identify the dengue virus serotypes and genotypes circulating in Central India during the COVID pre-pandemic year (2019) and ongoing-pandemic year (2021). For this purpose, the suspected cases were first tested by serological assays. Sero-positive samples were then subjected to molecular diagnosis by RT-PCR and semi-nested PCR. The serotypes obtained were confirmed by nucleotide sequencing. A phylogenetic analysis of serotypes was performed to identify the circulating genotypes. All four DENV serotypes were detected during 2019 and 2021, with the predominance of DENV2. Cases with multiple DENV serotype infections were also identified, involving DENV-2 in all the coinfections. Genotyping revealed that DENV-1 (Genotype V, American/African), DENV-2 (Genotype IV, Cosmopolitan), DENV-3 (Genotype III, Cosmopolitan), and DENV-4 (Genotype I) were involved during both outbreaks. DENV-2 detected in 2019 and 2021 has diverged from the previous strains detected in Central India (2016 and 2018), which may account for the higher transmission of DENV-2 during these outbreaks. The detection of heterologous DENV serotypes with high transmission efficiency calls for continuous viral monitoring and surveillance, which will contribute to a better understanding of changing viral dynamics and transmission patterns.

Efficient mapping of RNA-binding residues in RNA-binding proteins using local sequence features of binding site residues in protein-RNA complexes.

Protein-RNA interactions play vital roles in plethora of biological processes such as regulation of gene expression, protein synthesis, mRNA processing and biogenesis. Identification of RNA-binding residues (RBRs) in proteins is essential to understand RNA-mediated protein functioning, to perform site-directed mutagenesis and to develop novel targeted drug therapies. Moreover, the extensive gap between sequence and structural data restricts the identification of binding sites in unsolved structures. However, efficient use of computational methods demanding only sequence to identify binding residues can bridge this huge sequence-structure gap. In this study, we have extensively studied protein-RNA interface in known RNA-binding proteins (RBPs). We find that the interface is highly enriched in basic and polar residues with Gly being the most common interface neighbor. We investigated several amino acid features and developed a method to predict putative RBRs from amino acid sequence. We have implemented balanced random forest (BRF) classifier with local residue features of protein sequences for prediction. With 5-fold cross-validations, the sequence pattern derived dipeptide composition based BRF model (DCP-BRF) resulted in an accuracy of 87.9%, specificity of 88.8%, sensitivity of 82.2%, Mathew's correlation coefficient of 0.60 and AUC of 0.93, performing better than few existing methods. We further validated our prediction model on known human RBPs through RBR prediction and could map ~54% of them. Further, knowledge of binding site preferences obtained from computational predictions combined with experimental validations of potential RNA binding sites can enhance our understanding of protein-RNA interactions. This may serve to accelerate investigations on functional roles of many novel RBPs.

Modular architecture and functional annotation of human RNA-binding proteins containing RNA recognition motif.

RNA-binding proteins (RBPs) are structurally and functionally diverse macromolecules with significant involvement in several post-transcriptional gene regulatory processes and human diseases. RNA recognition motif (RRM) is one of the most abundant RNA-binding domains in human RBPs. The unique modular architecture of each RBP containing RRM is crucial for its diverse target recognition and function. Genome-wide study of these structurally conserved and functionally diverse domains can enhance our understanding of their functional implications. In this study, modular architecture of RRM containing RBPs in human proteome is identified and systematically analysed. We observe that 30% of human RBPs with RNA-binding function contain RRM in single or multiple repeats or with other domains with maximum of six repeats. Zinc-fingers are the most frequently co-occurring domain partner of RRMs. Human RRM containing RBPs mostly belong to RNA metabolism class of proteins and are significantly enriched in two functional pathways including spliceosome and mRNA surveillance. Various human diseases are associated with 18% of the RRM containing RBPs. Single RRM containing RBPs are highly enriched in disorder regions. Gene ontology (GO) molecular functions including poly(A), poly(U) and miRNA binding are highly depleted in RBPs with single RRM, indicating the significance of modular nature of RRMs in specific function. The current study reports all the possible domain architectures of RRM containing human RBPs and their functional enrichment. The idea of domain architecture, and how they confer specificity and new functionalities to RBPs, can help in re-designing of modular RRM containing RBPs with re-engineered function.

Adsorptive removal of Cd2+ ions using dolochar at an industrial-scale process optimization by response surface methodology.

In this work, performance of laboratory-synthesized dolochar has been investigated for adsorption of Cd2+ ions in a large-scale process with the application of Aspen Adsorption. Moreover, the optimum values of the operating parameters (namely, flow rate, bed height, and inlet metal ion concentration) that would result into maximum amount of cadmium ion adsorption (high exhaustion capacity) in minimum time (less exhaustion time) for a fixed mass of dolochar have been calculated via the application of response surface methodology. It was found that, at optimum values of bed height (3.48 m), flow rate (76.31 m3/day), and inlet concentration (10 ppm), the optimized value of exhaustion capacity and exhaustion time for cadmium ion adsorption in dolochar packed bed is equal to 1.85 mg/g and 11.39 h, respectively. The validity of these simulation experiments can be proven by the fact that the obtained exhaustion capacity of dolochar packed bed always remained in close proximity of the experimentally obtained value of adsorption capacity of the dolochar in batch process mode (equal to 2.1 mg/g).

Molecular insights into binding dynamics of tandem RNA recognition motifs (tRRMs) of human antigen R (HuR) with mRNA and the effect of point mutations in impaired HuR-mRNA recognition.

Human antigen R (HuR) is a key regulatory protein with prominent roles in RNA metabolism and post-transcriptional gene regulation. Many studies have shown the involvement of HuR in plethora of human diseases, which are often manifestations of impaired HuR-RNA interactions. However, the inherent complexities of highly flexible protein-RNA interactions have limited our understanding of the structural basis of HuR-RNA recognition. In this study, we dissect the underlying molecular mechanism of interaction between N-terminal tandem RNA-recognition motifs (tRRMs) of HuR and mRNA using molecular dynamics simulation. We have also explored the effect of point mutations (T90A, R97A and R136A) of three reported critical residues in HuR-mRNA binding specificity. Our findings show that N-terminal tRRMs exhibit conformational stability upon RNA binding. We further show that R136A and R97A mutants significantly lose their binding affinity owing to the loss of critical interactions with mRNA. This may be attributed to the larger domain rearrangements in the mutant complexes, especially the ß2ß3 loops in both the tRRMs, leading to unfavourable conformations and loss of binding affinity. We have identified critical binding residues in tRRMs of HuR, contributing favourable binding energy in mRNA recognition. This study contributes significantly to understand the molecular mechanism of RNA recognition by tandem RRMs and provides a platform to modulate binding affinities through mutations. This may further guide in future structure-based drug-therapies targeting impaired HuR-RNA interactions.Communicated by Ramaswamy H. Sarma.

SWEAT ICU-An Observational Study of Physician Workload and the Association of Physician Outcomes in Academic ICUs.

The optimal staffing model for physicians in the ICU is unknown. Patient-to-intensivist ratios may offer a simple measure of workload and be associated with patient mortality and physician burnout. To evaluate the association of physician workload, as measured by the patient-to-intensivist ratio, with physician burnout and patient mortality. DESIGN: Cross-sectional observational study. SETTING: Fourteen academic centers in the United States from August 2020 to July 2021. SUBJECTS: We enrolled ICU physicians and collected data on adult ICU patients under the physician's care on the single physician-selected study day for each physician. MEASUREMENTS and MAIN RESULTS: The primary exposure was workload (self-reported number of patients' physician was responsible for) modeled as high (>14 patients) and low (≤14 patients). The primary outcome was burnout, measured by the Well-Being Index. The secondary outcome measure was 28-day patient mortality. We calculated odds ratio for burnout and patient outcomes using a multivariable logistic regression model and a binomial mixed effects model, respectively. We enrolled 122 physicians from 62 ICUs. The median patient-to-intensivist ratio was 12 (interquartile range, 10-14), and the overall prevalence of burnout was 26.4% (n = 32). Intensivist workload was not independently associated with burnout (adjusted odds ratio, 0.74; 95% CI, 0.24-2.23). Of 1,322 patients, 679 (52%) were discharged alive from the hospital, 257 (19%) remained hospitalized, and 347 (26%) were deceased by day 28; 28-day outcomes were unknown for 39 of patients (3%). Intensivist workload was not independently associated with 28-day patient mortality (adjusted odds ratio, 1.33; 95% CI, 0.92-1.91). CONCLUSIONS: In our cohort, approximately one in four physicians experienced burnout on the study day. There was no relationship be- tween workload as measured by patient-to-intensivist ratio and burnout. Factors other than the number of patients may be important drivers of burnout among ICU physicians.

Determining the optimum cut-off IgM/ IgG ratio for predicting secondary dengue infections: An observational hospital based study from Central India.

PURPOSE: The present study was conducted to determine an optimum cut-off IgM/IgG ratio for differentiating between primary and secondary Dengue. The calculated cut-off was used to estimate the relative prevalence of primary and secondary Dengue in central India during the 2021 outbreak. METHODS: To differentiate between primary and secondary Dengue, optimum cut-off IgM/IgG ratio was determined using ROC curve analysis and Area under the curve (AUC) was calculated. For this 84 IgM positive samples were selected during the study period and Dengue IgM and IgG testing was performed. RESULTS: Based on sero-positivity for IgG antibodies, we observed a prevalence of 77.4% for secondary Dengue during this outbreak. IgM/IgG ratio of 1.59 delivered a sensitivity of 100% and specificity of 90.8%. Comparison of clinical characteristics revealed significant differences in rigors (p â€‹= â€‹0.04) and haemorrhagic manifestations (p â€‹= â€‹0.01) between the two types of infection. CONCLUSIONS: This study revealed an overwhelming predominance of secondary Dengue during the reported outbreak, which hints at increasing endemicity in this region and raises the risk of severe clinical manifestations. An optimal IgM/IgG cut-off ratio, tailored according to the endemicity of this geographical region, is therefore suggested in this study.

Leveraging Natural Learning Processing to Uncover Themes in Clinical Notes of Patients Admitted for Heart Failure.

Heart failure occurs when the heart is not able to pump blood and oxygen to support other organs in the body as it should. Treatments include medications and sometimes hospitalization. Patients with heart failure can have both cardiovascular as well as non-cardiovascular comorbidities. Clinical notes of patients with heart failure can be analyzed to gain insight into the topics discussed in these notes and the major comorbidities in these patients. In this regard, we apply machine learning techniques, such as topic modeling, to identify the major themes found in the clinical notes specific to the procedures performed on 1,200 patients admitted for heart failure at the University of Illinois Hospital and Health Sciences System (UI Health). Topic modeling revealed five hidden themes in these clinical notes, including one related to heart disease comorbidities.

In COVID-19 acute hypoxemia, awake prone positioning vs. usual care did not reduce intubation at 30 d.

SOURCE CITATION: Alhazzani W, Parhar KK, Weatherald J, et al. Effect of awake prone positioning on endotracheal intubation in patients with COVID-19 and acute respiratory failure: a randomized clinical trial. JAMA. 2022;327:2104-13. 35569448.

Post-Transition-State Direct Dynamics Simulations on the Ozonolysis of Catechol.

On-the-fly dynamics simulations are performed for the reaction of catechol + O3. The post transition state (TS) dynamics is studied at temperatures of 400 and 500 K. The PM7 semiempirical method is employed for calculating the potential energy gradient needed for integrating Hamilton's equations of motion. This semiempirical method provides excellent agreement in terms of energy and geometry of the TSs as well as minimum energy states of the system with respect to B3LYP/6-311+G (2df, 2p) calculated results. In the dynamics, first, a peroxyacid is formed, which further dissociates to different fragments. Four major channels forming CO, CO2, H2O, and small carboxylic acid (SCA) fragments are seen in this reaction. Rates of each of the channels and the overall unimolecular reaction are calculated at both temperatures. Branching ratios of all these product channels are calculated and compared with experiment. The minimum energy profile of CO2, CO, and H2O channels are calculated. A qualitative estimate of activation energies for all the channels are obtained and compared with the explicit TS energies of three product channels, which ultimately correlate with the reaction probabilities.

The Impact of Individualized Complementary and Integrative Health Interventions Provided in Clinical Settings on Quality of Life: A Systematic Review of Practice-Based Research.

Background: The goal of this systematic review was to evaluate the impact of individualized complementary and integrative health (CIH) interventions on quality-of-life outcomes as collected in CIH outpatient clinics. Methods: A systematic review was conducted using PubMed, OVID, Cochrane, Web of Science, Scopus, and Embase through December 2020. Inclusion criteria were as follows: individualized CIH treatment, longitudinal effectiveness design, patient-reported outcomes, outpatient CIH clinic setting, participants aged ≥18 years, sample size of ≥25, and English full text. The study was listed in the PROSPERO database (CRD42020159193), and PRISMA guidelines were used. The variables extracted from articles focused on study details/demographics, CIH intervention characteristics, and outcome characteristics. Results: The literature search yielded 3316 records with 264 assessed for full-text review. Of these, 19 studies (including ∼14,002 patients) were specific to quality of life (or well-being) as a main outcome. Most studies included were multidisciplinary studies (n = 12), followed by acupuncture (n = 4), chiropractic (n = 3), and massage or reflexology (n = 1). The short-form group of questionnaires (SF-12, SF-36, SF-8) were the most used quality-of-life/well-being questionnaire, comprising 37% of studies (n = 7), and the Patient Reported Outcomes Measurement Information System (PROMIS) measures comprised 21% (n = 4). Both questionnaires are normed to U.S. population, allowing for comparison. The average improvement across the comparable SF and PROMIS measures for Physical Health was 6% (range 2%-20%) and for Mental Health was 5% (range 1%-11%), demonstrating clinical significance. Improvements in the observational studies are comparable to improvements reported from randomized controlled trials. Conclusions: Results from this systematic review indicate that CIH therapies largely have positive effects on health-related quality of life and well-being for various patient populations seen in CIH clinical settings. Direct comparisons across studies were limited due to the variability in study design and incomplete reporting in some of the publications. Suggestions for improving the design and reporting for future practice-based research are provided.

A comparative analysis of machine learning classifiers for predicting protein-binding nucleotides in RNA sequences.

RNA-protein interactions play vital roles in driving the cellular machineries. Despite significant involvement in several biological processes, the underlying molecular mechanism of RNA-protein interactions is still elusive. This may be due to the experimental difficulties in solving co-crystallized RNA-protein complexes. Inherent flexibility of RNA molecules to adopt different conformations makes them functionally diverse. Their interactions with protein have implications in RNA disease biology. Thus, study of binding interfaces can provide a mechanistic insight of the molecular functioning and aberrations caused due to altered interactions. Moreover, high-throughput sequencing technologies have generated huge sequence data compared to available structural data of RNA-protein complexes. In such a scenario, efficient computational algorithms are required for identification of protein-binding interfaces of RNA in the absence of known structures. We have investigated several machine learning classifiers and various features derived from nucleotide sequences to identify protein-binding nucleotides in RNA. We achieve best performance with nucleotide-triplet and nucleotide-quartet feature-based random forest models. An overall accuracy of 84.8%, sensitivity of 83.2%, specificity of 86.1%, MCC of 0.70 and AUC of 0.93 is achieved. We have further implemented the developed models in a user-friendly webserver "Nucpred", which is freely accessible at "http://www.csb.iitkgp.ac.in/applications/Nucpred/index".

Novel molecular approaches to combat vectors and vector-borne viruses: Special focus on RNA interference (RNAi) mechanisms.

Vector-borne diseases, such as dengue, chikungunya, zika, yellow fever etc pose significant burden among the infectious diseases globally, especially in tropical and sub-tropical regions. Globalization, deforestation, urbanization, climate change, uncontrolled population growth, inadequate waste management and poor vector-management infrastructure have all contributed to the expansion of vector habitats and subsequent increase in vector-borne diseases throughout the world. Conventional vector control methods, such as use of insecticides, have significant negative environmental repercussions in addition to developing resistance in vectors. Till date, a very few vaccines or antiviral therapies have been approved for the treatment of vector borne diseases. In this review, we have discussed emerging molecular approaches like CRISPR (clustered regularly interspaced short palindromic repeats)/Cas-9, sterile insect technique (SIT), release of insects carrying a dominant lethal (RIDL), Wolbachia (virus transmission blocking) and RNA interference (RNAi) to combat vector and vector-borne viruses. Due to the extensive advancements in RNAi research, a special focus has been given on its types, biogenesis, mechanism of action, delivery and experimental studies evaluating their application as anti-mosquito and anti-viral agent. These technologies appear to be highly promising in terms of contributing to vector control and antiviral drug development, and hence can be used to reduce global vector and vector-borne disease burden.