Evaluation of Various Solvent Extracts of Tetrastigma leucostaphylum (Dennst.) Alston Leaves, a Bangladeshi Traditional Medicine Used for the Treatment of Diarrhea.

Tetrastigma leucostaphylum (TL) is an important ethnic medicine of Bangladesh used to treat diarrhea and dysentery. Hence, current study has been designed to characterize the antidiarrheal (in vivo) and cytotoxic (in vitro) effects of T. leucostaphylum. A crude extract was prepared with methanol (MTL) and further partitioned into n-hexane (NTL), dichloromethane (DTL), and n-butanol (BTL) fractions. Antidiarrheal activity was investigated using castor oil induced diarrhea, enteropooling, and gastrointestinal transit models, while cytotoxicity was evaluated using the brine shrimp lethality bioassay. In antidiarrheal experiments, all doses (100, 200, and 400 mg/kg) of the DTL extract significantly reduced diarrheal stool frequency, volume and weight of intestinal contents, and gastrointestinal motility in mice. Similarly, in the cytotoxicity assay, all extracts exhibited activity, with the DTL extract the most potent (LC50 67.23 µg/mL). GC-MS analysis of the DTL extract identified 10 compounds, which showed good binding affinity toward M3 muscarinic acetylcholine, 5-HT3, Gut inhibitory phosphodiesterase, DNA polymerase III subunit alpha, and UDP-N-acetylglucosamine-1 carboxyvinyltransferase enzyme targets upon molecular docking analysis. Although ADME/T analyses predicted the drug-likeness and likely safety upon consumption of these bioactive compounds, significant toxicity concerns are evident due to the presence of the known phytotoxin, 2,4-di-tert-butylphenol. In summary, T. leucostaphylum showed promising activity, helping to rationalize the ethnomedicinal use and importance of this plant, its safety profile following both acute and chronic exposure warrants further investigation.

The Distribution of Respiratory Viral Pathogens Among the Symptomatic Respiratory Tract Infection Patients From Dhaka City in the Pre-COVID-19 Pandemic Era.

Rapid and accurate diagnosis is crucial for determining the etiology and, perhaps, effectively treating and preventing viral respiratory infections. A multiplex quantitative reverse transcription polymerase chain reaction (qRT-PCR) assay⁠⁠⁠⁠⁠⁠⁠ was utilized to determine the prevalence of viral etiology in cases of acute respiratory tract infections (ARTIs). Outpatient department (OPD) and intensive care unit (ICU) patients with fever and respiratory symptoms were enrolled from December 2018 to April 2020. Nucleic acids were extracted from the respiratory tract samples using the SV Total RNA Isolation System (Promega Corporation, Madison, WI), and virus identification was performed using qRT-PCR assay (Fast Track Diagnostics {FTD} Respiratory Pathogens, Esch-sur-Alzette, Luxembourg). A total of 152 samples were collected from OPD and ICU. Among them, 32.23% (n = 49) of the patients were positive for at least one respiratory virus. From 49 infected cases, 42 had only a single viral pathogen, whereas seven had co-infections. Of the patients, 32.25% (30) in the OPD and 32.20% (19) in the ICU tested positive for the respiratory viral pathogen. Among the OPD patients, human coronaviruses (HCoVs) OC43, 229E, NL63, and HKU1 were detected as predominant viruses (10.75%), followed by influenza virus (IFV) (8.6%), human rhinoviruses (HRVs) (6.45%), human parainfluenza viruses (HPIVs) (6.45%), respiratory syncytial virus (RSV) (3.22%), and adenovirus (2.15%). In ICU cases, HPIV and HRV were detected as predominant viruses (8.47% each), followed by HCoV (5.08%), human metapneumovirus (HMPV) (5.08%), influenza A virus (IAV) (3.38%), adenovirus (3.38%), and RSV (1.69%). This study highlighted the prevalence of respiratory viruses in both the community and hospital settings during pre-COVID-19, indicating a significant presence among patients in these environments.

Assessing measures implemented by export-oriented RMG firms in an emerging economy during COVID-19.

Manufacturing firms that continued production activities during the COVID-19 have been taking necessary measures to cope with the risks imposed by the pandemic. This study assesses the measures implemented by the Ready-Made Garments (RMG) sector in Bangladesh. With the increase in COVID-19 cases in Bangladesh, following government order, along with firms in other manufacturing sectors, the RMG firms had to shut-down their production between March 26 and April 25, 2020. Soon after the factories reopened, they had to take necessary actions to ensure employee safety, supply of raw materials, and purchase orders from buyers. Using a semi-structured interview approach, we identify 16 measures that have been implemented in the RMG sector in Bangladesh for the employees, suppliers and buyers. Then, we assess the degree of implementation of these measures using the Bayesian Best-Worst method. We find that providing healthcare safety, bringing previously outsourced activities in-house, and ensuring smooth delivery of existing orders were the three most implemented measures for employees, suppliers and buyers, respectively. On a higher level, the RMG industry professionals prioritised buyer-related measures the most, followed by employee and supplier-related. The analysed measures provide a blueprint for supply chain risk management during future waves of COVID-19 transmission and for other potential large-scale natural disasters.

Ratio of Two Independent Lindley Random Variables.

The distribution of the ratio of two independently distributed Lindley random variables X and Y , with different parameters, is derived. The associated distributional properties are provided. Furthermore, the proposed ratio distribution is fitted to two applications data (COVID-19 and Bladder Cancer Data), and compared it with some well-known right-skewed variations of Lindley distribution, namely; Lindley distribution, new generalized Lindley distribution, new quasi Lindley distribution and a three parameter Lindley distribution. The numerical result of the study reveals that the proposed distribution of two independent Lindley random variables fits better to the above said data sets than the compared distribution.

COVID-19 and the environment: A critical review and research agenda.

The current Coronavirus infection (COVID-19) outbreak has had a substantial impact on many aspects of general life. Although a number of studies have been published on the topic already, there has not been a critical review of studies on the impacts of COVID-19 by and on environmental factors. The current study fills this gap by presenting a critical analysis of 57 studies on the nexus between COVID-19 and the environment, published in nine journals up to May 2020. Majority of the studies in our sample are published in Science of the Total Environment (74%), and studies used mostly descriptive statistics and regression as research methods. We identified four underlying research clusters based on a systematic content analysis of the studies. The clusters are: (1) COVID-19 and environmental degradation, (2) COVID-19 and air pollution, (3) COVID-19 and climate/metrological factors and (4) COVID-19 and temperature. Besides a critical analysis of the studies in each cluster, we propose research questions to guide future research on the relationship between COVID-19 and the environment.

A logistic model of the effects of roadway, environmental, vehicle, crash and driver characteristics on hit-and-run crashes.

Leaving the scene of a crash without reporting it is an offence in most countries and many studies have been devoted to improving ways to identify hit-and-run vehicles and the drivers involved. However, relatively few studies have been conducted on identifying factors that contribute to the decision to run after the crash. This study identifies the factors that are associated with the likelihood of hit-and-run crashes including driver characteristics, vehicle types, crash characteristics, roadway features and environmental characteristics. Using a logistic regression model to delineate hit-and-run crashes from nonhit-and-run crashes, this study found that drivers were more likely to run when crashes occurred at night, on a bridge and flyover, bend, straight road and near shop houses; involved two vehicles, two-wheel vehicles and vehicles from neighboring countries; and when the driver was a male, minority, and aged between 45 and 69. On the other hand, collisions involving right turn and U-turn maneuvers, and occurring on undivided roads were less likely to be hit-and-run crashes.

Total contact cast for neuropathic diabetic foot ulcers.

OBJECTIVE: To determine the outcome of diabetic neuropathic foot ulcers treated with Total Contact Cast (TCC) in terms of percentage of ulcers healed and time to heal. STUDY DESIGN: Analytical study. PLACE AND DURATION OF STUDY: Department of Orthopaedic Surgery, Abbasi Shaheed Hospital, Karachi Medical and Dental College, from April 2005 to March 2007. METHODOLOGY: The study included diabetic patients with non-ischemic neuropathic foot ulcers of upto grade 2 of Wagner's classification. Ulcers were debrided off necrotic tissues and Total Contact Cast (TCC) was applied. TCC was renewed every 2 weeks till healing. Cases were labeled as cast failure when there was no reduction in wound size in 4 consecutive weeks or worsening to a higher grade. Main outcome measures were the percentage of ulcers healed and time to heal in the cast. RESULTS: Thirty four (87.17%) patients were males and 5(12.82%) were females. The mean age was 62 +/- 13.05 years. All patients had NIDDM. Out of the 52 ulcers, 41(78.84%) healed with TCC in an average 2 casts duration (mean 32 days). There were 11(21.15%) cast failure. Majority (63.63%) of cast failure ulcers were located on pressure bearing area of heel. Most (90%) of the ulcers on forefoot and midsole region healed with TCC (p < 0.001). Longer ulcer duration (mean 57.45 +/- 29.64 days) significantly reduced ulcer healing (p < 0.001). CONCLUSION: Total contact cast was an effective treatment modality for neuropathic diabetic foot ulcers of Wagner's grade 2, located on forefoot and midsole region.

Molecular Simulation Studies of 3,3'-Diindolylmethane as a Potent MicroRNA-21 Antagonist.

OBJECTIVE: In recent decades, the overexpression of microRNA-21 (miR-21) is found to be progressively linked with many diseases such as different types of cancers, cardiovascular diseases, and inflammation. Thereby, it has become an attractive target for pharmacological and genetic modulation in various diseases, and also for overcoming the resistance to chemotherapy in several cancers. Here, in this study, the role of molecular therapeutics of 3,3'-diindolylmethane (DIM) has been investigated for its ability to bind with the precursor miRNA as a target of miR-21 (hsa-mir-21), which may alter the catalyzation process of dicer, a RNase III enzyme, involved in miRNA transcription. METHODS: In this context, the present study describes the potential binding and the structure alteration properties of DIM to precursor miR-21 (pre-miR-21) through Molecular Docking and Molecular Dynamics simulation techniques. RESULTS: As a corollary, DIM formed both non-bonded and covalent interactions with the bases of pre-miR, while covalent interaction with guanine in the 6th position was found to be consensus in molecular dynamics simulation. Furthermore, the stability of both DIM and pre-miR-21 was found to be inversely correlated to each other in binding condition. CONCLUSION: This result indicates that DIM can be used in target-based therapy and also as a lead for further development of potent small molecule miRNA antagonist.

Severity of motorcycle crashes in Calgary.

Motorcycle riders would be more vulnerable in the event of a crash because of their lack of protection which would often result in them suffering more severe injuries than car drivers. This paper estimated three crash severity models to identify factors that contributed to increasing the severity of motorcycle involved crashes in the Canadian City of Calgary. We found that results from the ordered logit model, heterogeneous choice model and partially constrained generalized ordered logit model produced estimates that were very similar which attested to their robustness. Injury severity tended to increase in neighborhoods with loops and lollipops types of streets or involved right-angle and left-turn-across-path crashes, a truck, unsafe speed or alcohol use but tended to decrease if the crash occurred in parking lots or during winter, involved a van or male rider, or a rider following-too-closely to the vehicle in front.

Effect of street pattern on the severity of crashes involving vulnerable road users.

Road crashes not only claim lives and inflict injuries but also create an economic burden to the society due to loss of productivity. Although numerous studies have been conducted to examine a multitude of factors contributing to the frequency and severity of crashes, very few studies have examined the influence of street pattern at a community level. This study examined the effect of different street patterns on crash severity using the City of Calgary as a case study. In this study, street pattern is classified into four categories: grid-iron, warped parallel, loops and lollipops, and mixed patterns. Their effects on injury risk are examined together with other factors including road features, drivers' characteristics, crash characteristics, environmental conditions and vehicle attributes. Pedestrian and bicycle crash data for the years 2003-2005 were utilized to develop a multinomial logit model of crash severity. Our results showed that compared to other street patterns, loops and lollipops design increases the probability of an injury but reduces the probability of fatality and property-damage-only in an event of a crash.