ChestCovidNet: An Effective DL-based Approach for COVID-19, Lung Opacity, and Pneumonia Detection Using Chest Radiographs Images.

Currently used lung disease screening tools are expensive in terms of money and time. Therefore, chest radiograph images (CRIs) are employed for prompt and accurate COVID-19 identification. Recently, many researchers have applied Deep learning (DL) based models to detect COVID-19 automatically. However, their model could have been more computationally expensive and less robust, i.e., its performance degrades when evaluated on other datasets. This study proposes a trustworthy, robust, and lightweight network (ChestCovidNet) that can detect COVID-19 by examining various CRIs datasets. The ChestCovidNet model has only 11 learned layers, eight convolutional (Conv) layers, and three fully connected (FC) layers. The framework employs both the Conv and group Conv layers, Leaky Relu activation function, shufflenet unit, Conv kernels of 3×3 and 1×1 to extract features at different scales, and two normalization procedures that are cross-channel normalization and batch normalization. We used 9013 CRIs for training whereas 3863 CRIs for testing the proposed ChestCovidNet approach. Furthermore, we compared the classification results of the proposed framework with hybrid methods in which we employed DL frameworks for feature extraction and support vector machines (SVM) for classification. The study's findings demonstrated that the embedded low-power ChestCovidNet model worked well and achieved a classification accuracy of 98.12% and recall, F1-score, and precision of 95.75%.

Enhanced As-COF nanochannels as a high-capacity anode for K and Ca-ion batteries.

Covalent organic frameworks can be used for next-generation rechargeable metal-ion batteries due to their controllable spatial and chemical architectures and plentiful elemental reserves. In this study, the arsenic-based covalent organic framework (As-COF) is designed by employing the geometrical symmetry of a semiconducting phosphazene-based covalent organic framework that uses p-phenylenediamine as a linker and hexachorocyclotriphosphazene as an As-containing monomer in a C3-like spatial configuration. The As-COF with engineered nanochannels demonstrates exceptional anodic behavior for potassium (K) and calcium (Ca) ion batteries. It exhibits a high storage capacity of about 914(2039) mA h g-1, low diffusion barriers of 0.12(0.26) eV, low open circuit voltage of 0.23(0.18) V, and a minimal volume expansion of 2.41(2.32)% for K (Ca) ions. These attributes collectively suggest that As-COF could significantly advance high-capacity rechargeable batteries.

Applications of different types of heat pipes in solar desalinations: A comprehensive review.

Desalination processes are energy consuming and it is required to apply clean energy sources for supplying them to prevent environmental issues. Solar energy is one of the attractive clean energy sources for desalination. In solar thermal desalination systems, different thermal components could be used for heat transfer purpose. In solar desalination technologies, heat pipe as efficient heat transfer mediums could be employed to transfer absorbed and/or stored thermal energy. The objective of this study is to review applications of heat pipes in solar energy desalination systems. Regarding the performance dependency of these thermal systems on the variety of factors, scholars have investigated these systems by consideration of the effect of different influential factors. Based on the results, it is concluded that use of heat pipes could lead to proper performance of solar desalination systems. Aside from direct transfer of absorbed heat from solar radiation, heat pipes can be applied in the storage units of solar desalination systems to keep the systems active in night-hours or low solar irradiation conditions. The overall performance of the solar desalinations systems with heat pipes can be influenced by some factors such as filling ratio and operating fluid that affect the performance of heat pipes.

Tunable metalensing based on plasmonic resonators embedded on thermosresponsive hydrogel.

Metalenses of adjustable power and ultrathin flat zoom lens system have emerged as a promising and key photonic device for integrated optics and advanced reconfigurable optical systems. Nevertheless, realizing an active metasurface retaining lensing functionality in the visible frequency regime has not been fully explored to design reconfigurable optical devices. Here, we present a focal tunable metalens and intensity tunable metalens in the visible frequency regime through the control of the hydrophilic and hydrophobic behavior of freestanding thermoresponsive hydrogel. The metasurface is comprised of plasmonic resonators embedded on the top of hydrogel which serves as dynamically reconfigurable metalens. It is shown that the focal length can be continuously tuned by adjusting the phase transition of hydrogel, the results reveal that the device is diffraction limited in different states of hydrogel. In addition, the versatility of hydrogel-based metasurfaces is further explored to design intensity tunable metalens, that can dynamically tailor the transmission intensity and confined it into the same focal spot under different states, i.e., swollen and collapsed. It is anticipated that the non-toxicity and biocompatibility make the hydrogel-based active metasurfaces suitable for active plasmonic devices with ubiquitous roles in biomedical imaging, sensing, and encryption systems.

Mechanistic study to reveal steric and electronic aspects involved in the formation of microstructures during Pd-catalyzed olefin/divinyl formal copolymerization: reactivity to catalyst choice.

The advancement of metal-catalyzed copolymers is a formidable challenge for achieving distinct catalytic properties to compete with existing plastic polymers in industrial commodities. Herein, we reveal the roles of electronic and steric environments in the thermodynamic preference of microstructures in ethylene/divinyl formal (DVF) co-polymerization using a Pd catalyst under mild conditions to accommodate the respective industrial applicabilities. The insertion products of DVF result in the alteration of the steric crowding, ultimately favoring the efficient formation of cyclic units having potential applications in the manufacture of high-strength fibers. More specifically, to achieve an improved yield of the end copolymer, we tuned the catalytic activity and regioselectivity through a variety of catalysts during ethylene-DVF co-polymerization. The naphthalene-bridged (P^O)PdMe catalyst was found to be promising in terms of the least hindered (buried volume of 47.8%) environment with the thermodynamic preference of 2,1-insertion with an energy of 5.1 kcal mol-1 among all the Pd-metal based catalysts. The highest activity with moderate energy barriers of the proposed catalyst will open new avenues for achieving a variety of potential applications, which is typically not possible using existing polymerization techniques.

Healthcare workers safety in the COVID-19 era: the impact of pre-pandemic personal protective equipment (PPE) training in Pakistan.

BACKGROUND: The COVID-19 pandemic has revealed vulnerabilities in healthcare systems worldwide, emphasizing the importance of healthcare worker safety through adequate utilization of personal protective equipment (PPE). This study aims to assess the impact of pre-pandemic PPE training on the practices and other associated factors among frontline healthcare workers during the COVID-19 pandemic in Pakistan and provide insights into the implications of such training programs for future initiatives. METHODS: A cross-sectional study from May 9th to June 5th, 2020 was conducted among the frontline healthcare workers against COVID-19 in Pakistan, utilizing an online structured questionnaire shared via WhatsApp and Facebook by using purposive sampling. Statistical analyses, including chi-square tests for proportion and logistic regression for the association while multi-logistic regression for potential confounders, were performed using SPSS version 22. RESULTS: A total of 453 healthcare staff participated, with 68.9% (n = 312) reporting no prior PPE training and 31.1% (n = 141) having received training. Significant associations were found between prior training and healthcare group distribution (p = 0.006), with doctors exhibiting the highest proportion of training 82 (37.61%), followed by nurses 50 (27.32%) and paramedics 9 (17.31%). Those who didn't receive any prior training in PPEs showed a higher perceived professional risk of 216 (69.23%) compared to those who received prior PPE training 96 (30.77%, p-value 0.005). Similarly, a higher frequency 137 (63.72%) of Perceived Personal risk was observed in those who didn't receive training, labeled as "high risk" compared to those who were trained 78 (36.28%, P value 0.02). Multi-logistic regression analysis identified paramedics as 0.26 times less likely to have received prior PPE training (Adjusted OR 0.26, 95% CI 0.10-0.65, p = 0.01) compared to medical doctors. Healthcare workers in tertiary care hospitals were 0.46 times less likely to undergo PPE training (Adjusted OR 0.46, 95% CI 0.25-0.87,p = 0.01) compared to those working at COVID-19 facilities/hospitals/quarantine centers. Likewise, individuals who doffed disposable gowns [Adjusted OR 3.86, (95% CI, 1.23-12.08, p = 0.02] were 3.86 times more interested in getting prior training in PPE compared to those who don't have skills to wear them. CONCLUSION: Our findings highlight that healthcare levels, type of healthcare, and doffing skills are important predictors of whether healthcare workers have taken prior training in PPE. These findings imply developing effective training programs for healthcare workers to ensure safety while providing care during pandemics like COVID-19.

Mechanistic Study on Steric Activity Interplay of Olefin/Polar Monomers for Industrially Selective Late Transition Metal Catalytic Reactions.

A significant issue in developing metal-catalyzed plastic polymer materials is obtaining distinctive catalytic characteristics to compete with current plastics in industrial commodities. We performed first-principle DFT calculations on the key insertion steps for industrially important monomers, vinyl fluoride (VF) and 3,3,3-trifluoropropene (TFP), to explain how the ligand substitution patterns affect the complex's polymerization behaviors. Our results indicate that the favorable 2,1-insertion of TFP is caused by less deformation in the catalyst moiety of the complexes in contrast to the 1,2-insertion mode. In contrast to the VF monomer, the additional interaction between the fluorine atoms of 3,3,3-trifluoropropene and the carbons of the catalyst ligands also contributed to favor the 2,1-insertion. It was found that the regioselectivity of the monomer was predominated by the progressive alteration of the catalytic geometry caused by small dihedral angles that were developed after the ligand-monomer interaction. Based on the distribution of the 1,2- and 2,1-insertion products, the activity and selectivity were influenced by the steric environment surrounding the palladium center; thus, an increased steric bulk visibly improved the selectivity of the bulkier polar monomer (TFP) during the copolymerization mechanism. In contrast, better activity was maintained through a sterically less hindered Pd metal center; the calculated moderate energy barriers showed that a catalyst with less steric hindrance might provide an opportunity for a wide range of prospective industrial applications.

Association and comparison of periodontal and oral hygiene status with serum HbA1c levels: a cross-sectional study.

BACKGROUND: Diabetes Mellitus and periodontitis are chronic diseases with known reciprocal association. Studies have shown that uncontrolled diabetes increases the risk of development and progression of periodontal disease. This study aimed to explore the association and severity of periodontal clinical parameters and oral hygiene with HbA1c levels in non-diabetics and T2DM patients. MATERIALS AND METHODS: In this cross-sectional study, the periodontal status of 144 participants, categorized into non-diabetics, controlled T2DM, and uncontrolled T2DM and were assessed via the Community Periodontal Index (CPI), Loss of Attachment Index (LOA index), and the number of missing teeth, while oral hygiene was measured by utilizing the Oral Hygiene Index Simplified (OHI-S). SPSS was used for data analysis. Chi-square test was used to find out the association of different independent variables with HbA1c groups, while ANOVA and post-hoc tests were run for inter-group and intra-group comparison respectively. RESULTS: Out of 144 participants, the missing dentition was prevalent in uncontrolled T2DM with mean 2.64 ± 1.97 (95% CI 2.07-3.21; p = 0.01) followed by controlled T2DM 1.70 ± 1.79 (95% CI 1.18-2.23; p = 0.01) and non-diabetics 1.35 ± 1.63 (95% CI 0.88-1.82; p = 0.01) respectively. Furthermore, non-diabetics had a higher proportion of CPI score 0 (Healthy) [30 (20.8%); p = 0.001] as compared to uncontrolled T2DM [6 (4.2%); p = 0.001], while CPI score 3 was more prevalent in uncontrolled T2DM in comparison to non-diabetics. Loss of attachment (codes-2,3 and 4) was also frequently observed in uncontrolled T2DM compared to non-diabetics (p = 0.001). Similarly, based on Oral Hygiene Index- Simplified (OHI-S), the result showed that poor oral hygiene was most commonly observed in uncontrolled T2DM 29 (20.1%) followed by controlled T2DM patients 22 (15.3%) and non-diabetic [14 (9.7%); p = 0.03]. CONCLUSION: This study showed that periodontal status and oral hygiene status were deteriorated in uncontrolled T2DM patients compared to non-diabetic participants and controlled T2DM.

Oral health behind the bars: oral health seeking behavior among jail prisoners at central jail of Peshawar, Pakistan: a cross-sectional study.

BACKGROUND: The oral health care-seeking behavior among prison inmates is an overlooked area, often leading to deteriorating general health due to the prisoners' limited awareness of oral hygiene practices. It is crucial to address this issue and understand the factors associated with oral healthcare-seeking behavior in prisons. OBJECTIVE: To assess the oral healthcare-seeking behavior of prison inmates at Central Prisoner Jail, Peshawar Pakistan and to look the factors associated with their dental care utilization. MATERIAL AND METHODS: This cross-sectional study was conducted at Central Prisoner Jail, Peshawar Khyber Pakhtunkhwa, Pakistan from November 2021 to April 2022. A consecutive sampling technique was used to collect data from both convicted and under-trial prisoners by using a pre-tested WHO Basic Oral Health Survey 2013 tool. Our outcome variable was "Visit to a dentist in the last 12 months (Never/Once or more than one visit). Chi-square test was used to determine univariate association with other explanatory variables while multivariable logistic regression was performed to adjust for potential confounders. RESULT: A total of 225 participants were recruited to the study with a mean (SD) age of 32.9(11.4). More than two-thirds of 200(88.9%) of the participants were males. One-third of the sample never visited the dentist75(33.3). Participants who completed college/university education and never visited the dentist in the last 12 months constituted a smaller proportion (17.6%) compared to those who visited the dentist once or more than once n = 28(82.4%, p-value = 0.003). Individuals who were using toothbrushes were most frequently visiting the dentist n = 130(72.6%=p value = 0.001) as compared to never visitors. Multivariate logistic regression analysis revealed that Participants who experienced teeth pain or discomfort had 0.42 times lower odds of visiting the dentist compared to those who did not experience any pain or discomfort [AOR 0.42 (95% CI 0.17-0.80), p = 0.04]. Similarly, Participants who do not use any denture have 4.06 times higher odds[AOR 4.06(95% CI 1.76-9.36), p = 0.001] of visiting the dentist compared to those who use a denture. CONCLUSION: Our result demonstrates that those prisoners who were experiencing tooth pain or discomfort and not using dentures were the strong predictors with lower dental visit frequency to seek oral health care.

Structural and compositional segregation of the gut microbiota in HCV and liver cirrhotic patients: A clinical pilot study.

Gut microbial dysbiosis during the development of Hepatitis C virus and liver-related diseases is not well studied. Nowadays, HCV and liver cirrhosis are the major concerns that cause gut bacterial alteration, which leads to dysbiosis. For this purpose, the present study was aimed at correlating the gut bacterial community of the control group in comparison to HCV and liver cirrhotic patients. A total of 23 stool samples were collected, including control (9), liver cirrhotic (8), and HCV (6). The collected samples were subjected to 16 S rRNA Illumina gene sequencing. In comparison with control, a significant gut bacterial alteration was observed in the progression of HCV and liver cirrhosis. Overall, Firmicutes were significantly abundant in the whole study. No significant difference was observed in the alpha diversity of the control and patient studies. Additionally, the beta diversity based on non-metric multidimensional scaling (NMDS) has a significant difference (p = 0.005) (ANOSIM R2 = 0.14) in all groups. The discriminative results based on the LEfSe tool revealed that the HCV-infected patients had higher Enterobacteriaceae and Enterobacterial, as well as Lactobacillus and Bacilli in comparison than the liver-cirrhotic patients. These taxa were significantly different from the control group (p < 0.05). Regarding prospects, a detailed analysis of the function through metagenomics and transcriptomics is needed.

Lactobacillus plantarum strains attenuated DSS-induced colitis in mice by modulating the gut microbiota and immune response.

Gut microbiota has become a new therapeutic target in the treatment of inflammatory Bowel Disease (IBD). Probiotics are known for their beneficial effects and have shown good efficacy in the clinical treatment of IBD and animal models of colitis. However, how these probiotics contribute to the amelioration of IBD is largely unknown. In the current study, the DSS-induced mouse colitis model was treated with oral administration of Lactobacillus plantarum strains to investigate their effects on colitis. The results indicated that the L. plantarum strains improved dysbiosis and enhanced the abundance of beneficial bacteria related to short-chain fatty acids (SCFAs) production. Moreover, L. plantarum strains decreased the level of pro-inflammatory cytokines, i.e., IL-17A, IL-17F, IL-6, IL-22, and TNF-α and increased the level of anti-inflammatory cytokines, i.e., TGF-ß, IL-10. Our result suggests that L. plantarum strains possess probiotic effects and can ameliorate DSS colitis in mice by modulating the resident gut microbiota and immune response.

A Robust End-to-End Deep Learning-Based Approach for Effective and Reliable BTD Using MR Images.

Detection of a brain tumor in the early stages is critical for clinical practice and survival rate. Brain tumors arise in multiple shapes, sizes, and features with various treatment options. Tumor detection manually is challenging, time-consuming, and prone to error. Magnetic resonance imaging (MRI) scans are mostly used for tumor detection due to their non-invasive properties and also avoid painful biopsy. MRI scanning of one patient's brain generates many 3D images from multiple directions, making the manual detection of tumors very difficult, error-prone, and time-consuming. Therefore, there is a considerable need for autonomous diagnostics tools to detect brain tumors accurately. In this research, we have presented a novel TumorResnet deep learning (DL) model for brain detection, i.e., binary classification. The TumorResNet model employs 20 convolution layers with a leaky ReLU (LReLU) activation function for feature map activation to compute the most distinctive deep features. Finally, three fully connected classification layers are used to classify brain tumors MRI into normal and tumorous. The performance of the proposed TumorResNet architecture is evaluated on a standard Kaggle brain tumor MRI dataset for brain tumor detection (BTD), which contains brain tumor and normal MR images. The proposed model achieved a good accuracy of 99.33% for BTD. These experimental results, including the cross-dataset setting, validate the superiority of the TumorResNet model over the contemporary frameworks. This study offers an automated BTD method that aids in the early diagnosis of brain cancers. This procedure has a substantial impact on improving treatment options and patient survival.

Predicting Students' Academic Performance with Conditional Generative Adversarial Network and Deep SVM.

The availability of educational data obtained by technology-assisted learning platforms can potentially be used to mine student behavior in order to address their problems and enhance the learning process. Educational data mining provides insights for professionals to make appropriate decisions. Learning platforms complement traditional learning environments and provide an opportunity to analyze students' performance, thus mitigating the probability of student failures. Predicting students' academic performance has become an important research area to take timely corrective actions, thereby increasing the efficacy of education systems. This study proposes an improved conditional generative adversarial network (CGAN) in combination with a deep-layer-based support vector machine (SVM) to predict students' performance through school and home tutoring. Students' educational datasets are predominantly small in size; to handle this problem, synthetic data samples are generated by an improved CGAN. To prove its effectiveness, results are compared with and without applying CGAN. Results indicate that school and home tutoring combined have a positive impact on students' performance when the model is trained after applying CGAN. For an extensive evaluation of deep SVM, multiple kernel-based approaches are investigated, including radial, linear, sigmoid, and polynomial functions, and their performance is analyzed. The proposed improved CGAN coupled with deep SVM outperforms in terms of sensitivity, specificity, and area under the curve when compared with solutions from the existing literature.

Association between FADS1 rs174547 and levels of long-chain PUFA: a meta-analysis.

In the present study, we analysed the effects of SNP rs174547 (T/C) in the fatty acid desaturase 1 (FADS1) gene on long-chain PUFA levels. Four databases were searched to retrieve related literature with keywords such as fatty acid (FA), SNP, FADS1 and rs174547. A meta-analysis of the data was performed using Stata12.0 software, including summary statistics, test for heterogeneity, evaluation of publication bias, subgroup analysis and sensitivity analysis. The associations between rs174547 in FADS1 and seven types of FA, and Δ-5 (D5D) and Δ-6 fatty acid desaturase (D6D) activity were assessed based on the pooled results from eleven papers. A total of 3713 individuals (1529 TT and 2184 TC + CC) were included. The results demonstrated that minor C allele carriers of rs174547 had higher linoleic acid (LA; P < 0·001) and α-linolenic acid (P = 0·020) levels, lower γ-linolenic acid (GLA; P = 0·001) and arachidonic acid (P = 0·024) levels, and lower D5D (P = 0·005) and D6D (P = 0·004) activities than the TT genotype group. Stratification analysis showed that minor C allele carriers of rs174547 had higher LA and lower GLA levels and lower D6D activities in plasma (LA, P < 0·001; GLA, P < 0·001; D6D activity, P < 0·001) samples and in Asian populations (LA, P < 0·001; GLA, P = 0·001; D6D activity, P = 0·001) than the TT genotype group. In conclusion, minor C allele carriers of the SNP rs174547 were associated with decreased activity of D5D and D6D.

Adenine ultrafast photorelaxation via electron-driven proton transfer.

Photorelaxation of adenine in water was reported to be ultrafast (within 180 fs) primarily due to radiationless relaxation. However, in the last two decades, several experimental and theoretical investigations on photoexcitation of adenine have revealed diverse types of decay mechanisms. Using time-dependent density functional excited-state nonadiabatic dynamics simulations we show that it is the water to adenine electron-driven proton transfer (EDPT) barrierless reaction responsible for the ultrafast component of the adenine relaxation, which, however, occurred only in the case of the 7H isomer of adenine with five water molecules. This result reveals a known reaction pathway, however not found in previous simulations, with inference for the ultrafast relaxation mechanisms of adenine reported in experiments. The 9H isomer of adenine with six water molecules relaxing in a water cluster followed the previously known structural distortion (C2) decay pathway. The observations of the adenine EDPT reaction with water provide the origin of the experimental ultrafast adenine decay component and present a possible method to tackle future computational challenges in molecular-level biological processes.

Air pollution and associated self-reported effects on the exposed students at Malakand division, Pakistan.

Air pollution is associated with several severe physical, behavioral, and psychological health risks and glitches. Air pollution has been linked to 11 million premature deaths in Pakistan, out of the total 153 million premature deaths worldwide. Air pollution is continuously growing as a threatening challenge for Pakistan. Keeping this in view, the current study was designed to assess air pollution in terms of air quality index (AQI), particulate matters (PM2.5 and PM10), SO2, NO2, and O3 over six districts of Malakand division, Northern Pakistan. The second part of the study appraised the associated self-reported effects of air pollution on Pakistani students and the practices, perceptions, and awareness of the students regarding air pollution through a closed-ended questionnaire, administered to 4100 students. The first section of the questionnaire was focused on the physical effects associated with air pollution; the second section was focused on air pollution-linked behavior and psychology; the third portion was focused on perception and awareness of the subjects, whereas the final section was focused on practices and concerns of the subjects regarding air pollution. The students reported that exposure to air pollution significantly affected their physical health, behavior, and psychology. The subjects were aware of the different air pollutants and health complications associated with air pollution, and therefore had adopted preventive measures. It was concluded that air pollution had adverse impacts on the physical and psychological health of the respondents, which consequently altered their behavior. Mass awareness, proper mitigating plan, suitable management, and implementation of strict environmental laws are suggested before the air gets further polluted and becomes life-threatening.

Gate-controlled terahertz focusing based on graphene-loaded metasurface.

Metasurfaces have proven their great application potentials in terahertz (THz) wave modulations. However, realizing an active metasurface retaining lensing functionality in the THz frequency regime is still highly desired. Here a metalens, featuring electrically tunable focal length, based on propagation phase delay, is proposed and demonstrated experimentally. To have full control over the designed lens functionality, a gold thin film etched with a C-shaped aperture antenna array covered by monolayer graphene is used. By applying a bias voltage to the graphene, the phase control of the antenna array is changed, and thus the focus of the linearly polarized THz beam can be flexibly tuned from 7.13mm to 8.25mm. The proposed approach has a promising perspective for a variety of applications in communication, reconfigurable flat optics and real-time imaging in THz regime.

C-reactive protein exacerbates epithelial-mesenchymal transition through Wnt/ß-catenin and ERK signaling in streptozocin-induced diabetic nephropathy.

Previous studies have reported the pathogenic role of C-reactive protein (CRP) during diabetic kidney disease (DKD) in human CRP transgenic and Crp-/- mice. However, because humans and mice have inverse acute phase expression patterns of CRP and serum amyloid P component, this could lead to the inaccurate evaluation of CRP function with the above-mentioned CRP transgenic mouse. But different from mice, rats have the same acute phase protein expression pattern as human, which might avoid this problem and be a better choice for CRP function studies. To dispel this doubt and accurately define the role of CRP during diabetic nephropathy, we created the first Crp-/- rat model, which we treated with streptozocin to induce DKD for in vivo studies. Moreover, an established cell line (human kidney 2) was used to further investigate the pathologic mechanisms of CRP. We found that CRP promotes epithelial-mesenchymal transition (EMT) through Wnt/ß-catenin and ERK1/2 signaling, which are dependent on CRP binding to FcγRII on apoptotic cells. By promoting EMT, CRP was demonstrated to accelerate the development of DKD. We thus present convincing evidence demonstrating CRP as a therapeutic target for DKD treatment.-Zhang, L., Shen, Z.-Y., Wang, K., Li, W., Shi, J.-M., Osoro, E. K., Ullah, N., Zhou, Y., Ji, S.-R. C-reactive protein exacerbates epithelial-mesenchymal transition through Wnt/ß-catenin and ERK signaling in streptozocin-induced diabetic nephropathy.

Post-traumatic stress disorder and association with low birth weight in displaced population following conflict in Malakand division, Pakistan: a case control study.

BACKGROUND: The northern part of the province of Khyber Pakhtunkhwa in Pakistan experienced armed conflict since September 2007 till the autumn of 2011. Conflict involved widespread insurgency activity and military intervention including in 2009 internally displacing the 2.5 million people of the valley of Swat to live in camps, with relatives, or in rented accommodation across the region for approximately 4 months. It was during this period the current study was conducted to determine whether Post-Traumatic Stress Disorder in pregnant women was independently associated with Low Birth Weight (LBW) in an area affected by conflict and militancy. METHODS: A case control study was conducted in tertiary care hospitals of district Peshawar, Khyber Pakhtunkhwa. Two hundred twenty-five cases (neonates with birth weight <  2.5 kg) and 225 controls (neonates with birth weight of > 2.5 kg) were enrolled within 24 h of delivery. Post-Traumatic Stress Disorder was assessed through the MINI Neuropsychiatric Interview 5.0, a validated questionnaire along with the birth weight of the newborn. Maternal anthropometry, anemia and other sociodemographic details were also obtained during data collection. Data was analyzed using statistical package (STATA version 14). Logistic regression analysis of the association between LBW and all variables collected with a p-value of < 0.25 on uni-variate analysis were entered. RESULTS: A total of 450 newborn and mother pairs participated in the study with 225 cases and 225 controls. On univariate analysis factors significantly associated with LBW include: less than 5 years of paternal schooling and PTSD. On logistic regression, PTSD was independently associated with low birth weight in the presence of other factors like maternal/paternal schooling, gravida, history of preterm, BMI of the mother and maternal anemia. CONCLUSION: PTSD was found to be independently associated with LBW. In light of the current findings and other similar literature, intervention programs should be considered for pregnant women exposed to traumatic events.

Nonradiative Excited-State Decay via Conical Intersection in Graphene Nanostructures.

Chemical groups are known to tune the luminescent efficiencies of graphene-related nanomaterials, but some species, including the epoxide group (-COC-), are suspected to act as emission-quenching sites. Herein, by performing nonadiabatic excited-state dynamics simulations, we reveal a fast (within 300 fs) nonradiative excited-state decay of a graphene epoxide nanostructure from the lowest excited singlet (S1 ) state to the ground (S0 ) state via a conical intersection (CI), at which the energy difference between the S1 and S0 states is approximately zero. This CI is induced after breaking one C-O bond at the -COC- moiety during excited-state structural relaxation. This study ascertains the role of epoxide groups in inducing the nonradiative recombination of the excited electron-hole, providing important insights into the CI-promoted nonradiative de-excitations and the luminescence tuning of relevant materials. In addition, it shows the feasibility of utilizing nonadiabatic excited-state dynamics simulations to investigate the photophysical processes of the excited states of graphene nanomaterials.