In the course of studying the family Lythraceae of Bangladesh in 2023–2024, some specimens of the family were found to be different than those of any other species of this family reported so far from this country. After a critical examination, these specimens have been identified as Ammannia auriculata, Rotala ramosior, and Rotala malampuzhensis of the Lythraceae. These species are new to the flora of Bangladesh. A detailed taxonomic description, including data on ecology, distribution, and use, a list of representative specimens examined, and illustrations have been provided for each species. Bangladesh J. Plant Taxon. 31(1): 15-24, 2024 (June)

Stomatal traits of leaves are critical for regulating the exchange of gases between plant tissues and the atmosphere, and thus play a crucial role in the physiological activities of plants. The hypothesis of this study is that distinct stomatal features among different species grown in diverse habitats can serve as a potential marker for species identification. Leaf samples were collected from the mangrove forests of Sundarbans and the freshwater swamp forests of Ratargul in Bangladesh. In total, we examined 11 species from eight different families. We used deep convolutional neural network (DCNN) to automatically identify tree species from microscopic stomatal imprints, as there is currently no established protocol for this task. For model training, 80% (866 images) of the data was used for training the models. Our study observed significant variations in stomatal attributes such as length, width, and density among different species, families, and habitats. These variations could help in accurate species identification by machine learning approaches used in the present study. An empirical comparison was conducted among EfficientNetV2, Xception, VGG16, VGG19, MobileNetV2, ResNet50V2, Resnet152, DenseNet201, and NasNetLarge. We propose a novel approach called the “Normalized Leverage Factor” that utilizes accuracy, precision, recall, and f1-score to select the optimal model. This approach eliminates the non-uniformity of the scores. Although MobileNetV2 achieved an accuracy of 99.06%, our findings indicate that EfficientNetV2 is the optimal model for species identification. This is due to its higher normalized leverage factor (1.92) compared to MobileNetV2 (1.88). The findings demonstrate that plants of diverse habitats show a unique footprint of stomata that offers an innovative method of species identification using DCNN. The study would help to develop a stomatal image-based user interface to identify species even without expert taxonomic knowledge and could be particularly useful in fields such as pharmacology, conservation biology, forestry, and environmental science.

Thirty four arsenic resistant bacterial strains were isolated from the soil samples of Khulna Shipyard. They were isolated by growing them on nutrient broth medium containing 5 mgl-1 of arsenic. From them, five strains were finally selected, and studied their morphological, biochemical and ecological characters in details. They were identified as Bacillus lichenifomis, Bacillus polymyxa, Listeria murrayi, Moraxella urethralis and Planococcus citreus. All of these strains were able to tolerate upto100 ppm (mgl-1) of arsenic (III). It is possibly due to the presence of arsenic (III) resistance mechanism(s) in these bacterial strains. The optimum pH and temperature for the growth of these bacterial strains were 8.5 and 37 °C, respectively.

Background National forest inventory and forest monitoring systems are more important than ever considering continued global degradation of trees and forests. These systems are especially important in a country like Bangladesh, which is characterised by a large population density, climate change vulnerability and dependence on natural resources. With the aim of supporting the Government’s actions towards sustainable forest management through reliable information, the Bangladesh Forest Inventory (BFI) was designed and implemented through three components: biophysical inventory, socio-economic survey and remote sensing-based land cover mapping. This article documents the approach undertaken by the Forest Department under the Ministry of Environment, Forests and Climate Change to establish the BFI as a multipurpose, efficient, accurate and replicable national forest assessment. The design, operationalization and some key results of the process are presented. Methods The BFI takes advantage of the latest and most well-accepted technological and methodological approaches. Importantly, it was designed through a collaborative process which drew from the experience and knowledge of multiple national and international entities. Overall, 1781 field plots were visited, 6400 households were surveyed, and a national land cover map for the year 2015 was produced. Innovative technological enhancements include a semi-automated segmentation approach for developing the wall-to-wall land cover map, an object-based national land characterisation system, consistent estimates between sample-based and mapped land cover areas, use of mobile apps for tree species identification and data collection, and use of differential global positioning system for referencing plot centres. Results Seven criteria, and multiple associated indicators, were developed for monitoring progress towards sustainable forest management goals, informing management decisions, and national and international reporting needs. A wide range of biophysical and socioeconomic data were collected, and in some cases integrated, for estimating the indicators. Conclusions The BFI is a new information source tool for helping guide Bangladesh towards a sustainable future. Reliable information on the status of tree and forest resources, as well as land use, empowers evidence-based decision making across multiple stakeholders and at different levels for protecting natural resources. The integrated socio-economic data collected provides information about the interactions between people and their tree and forest resources, and the valuation of ecosystem services. The BFI is designed to be a permanent assessment of these resources, and future data collection will enable monitoring of trends against the current baseline. However, additional institutional support as well as continuation of collaboration among national partners is crucial for sustaining the BFI process in future.

Molecular crowding in highly concentrated monoclonal antibody (mAb) solutions results in significant increases in viscosity, which complicates fill-finish steps and patient administration by subcutaneous injection. As viscosity measurements for optimization of the mAb formulation require significant amounts of material not always available in early development, fluorescence correlation spectroscopy (FCS) is evaluated as a potential ultra-low volume technique for viscosity measurement of high concentration protein solutions assuming the Generalised Stokes Einstein relation (GSE) remains valid. Using like-charge fluorescent tracers of different sizes, FCS provided measurements of microviscosities which were compared to the macroviscosity. After parametrising the protein concentration dependence of the viscosity by the exponential coefficient (k) of a simple exponential model, FCS derived k-values of like-size tracer to the crowder followed the same ordering as the macroviscosity derived k-values with respect to solvent conditions. Furthermore, k and the diffusion-derived protein-protein interaction parameter, kD, are linked, and, attractive conditions for mAbs result in a stronger concentration dependence of the viscosity. For tracers and crowders of like-size, a key result is negative deviations from the GSE relation are observed in presence of strong attractive interactions between crowder molecules. These data demonstrate that FCS has application to the screening of high concentration mAb solutions for formulation selection.

Epileptic seizure is a neurological disorder characterized by abnormal synchronous discharge of the neuronal activities in the brain structures. These abnormal electrical activities can be recorded via multi-channel electroencephalography (EEG) signals placed on the scalp of the brain. Usually, these signals, recorded from this EEG device, are interpreted by the neurologist which require their availability and it is very time consuming especially for long duration signals. This study presents a fully automatic system for the detection of seizure from non-seizure signals. Firstly, it pre-processes the signal to remove noise and artefacts from the raw-EEG signals and then extracts features. Features are extracted from time-domain, spectral domain, wavelet domain. In addition, connectivity and entropy based feature have also been extracted. After that, prominent features have been selected from this large feature set by a multi-objective evolutionary algorithm and finally, Support Vector Machine (SVM) classifier has been used for classification. A Bayesian optimization algorithm has been used to optimize the hyper-parameters of SVM. Linear Discriminant Analysis (LDA) and Quadratic Linear Discriminant Analysis (QLDA) have also been used for comparison. The proposed system is tested on a publicly available CHB-MIT database and results show the significance of the proposed system. The distinguished accuracy of the classifier is 76.41%, 80.79% and 97.05% in LDA, QLDA and SVM, respectively.

In this research, A Conceptual Framework of the Intelligent Agent-Based Knowledge Profile designed to help people become aware of their skills. It will also analyze their skills, tools, and practices helping them to identify skill gaps if there is any. This is a web-based platform design. Where full mechanisms and functions controlled by automatic bots or intelligent agent through an algorithm specifically designed to meet the purpose. During this study, very few research has found so far related to dynamic Knowledge Profile. The number of research papers, information, and data regarding relevant research is difficult to find. We also have found a similarity between Knowledge profile and Graduate profile. A theoretical framework and structural design have proposed in this research. Also, an algorithm has proposed for comparing data. Basically, this framework raised on some specific components. The user, Intelligent Bot, and Algorithm, these three components are the main pillars of this framework. It is expected that this framework can be used to identify Knowledge Gap in a particular context. This dynamic knowledge profile has been designed in the presence of Intelligent agents. The Intelligent Agent will automatically collect data from a user and provide their Knowledge Status. This dynamic knowledge profile provides positive feedback after the Dataset and Algorithm Experiments on many occasions.

This study was carried out to provide the baseline data on the composition and distribution of the angiosperms and to assess their current status in Rajkandi Reserve Forest of Moulvibazar, Bangladesh. The study reports a total of 549 angiosperm species belonging to 123 families, 98 (79.67%) of which consisting of 418 species under 316 genera belong to Magnoliopsida (dicotyledons), and the remaining 25 (20.33%) comprising 132 species of 96 genera to Liliopsida (monocotyledons). Rubiaceae with 30 species is recognized as the largest family in Magnoliopsida followed by Euphorbiaceae with 24 and Fabaceae with 22 species; whereas, in Lilliopsida Poaceae with 32 species is found to be the largest family followed by Cyperaceae and Araceae with 17 and 15 species, respectively. Ficus is found to be the largest genus with 12 species followed by Ipomoea, Cyperus and Dioscorea with five species each. Rajkandi Reserve Forest is dominated by the herbs (284 species) followed by trees (130 species), shrubs (125species), and lianas (10 species). Woodlands are found to be the most common habitat of angiosperms. A total of 387 species growing in this area are found to be economically useful. 25 species listed in Red Data Book of Bangladesh under different threatened categories are found under Lower Risk (LR) category in this study area.

Abstract not available Jahangirnagar University J. Biol. Sci. 7(2): 115-119, 2018 (December)

This study has recognized the occurance of a total of 346 species of Angiosperms under 256 genera and 82 families and assessed their current status and distribution in Mirpur area of Dhaka district. Majority of these families, 68 (82.92%) consist of 255 species under 192 genera, belong to Magnoliopsida (dicotyledons), and the rest 14 (17.07%) comprise of 91 species under 64 genera to Liliopsida (monocotyledons). Asteraceae with 18 species is found to be the largest family in Magnoliopsida followed by Euphorbiaceae and Fabaceae consists of 17 species each; while Poaceae is recognized as the largest family with 41 species in Liliopsida followed by Cyperaceae with 19 species. Ficus of Moraceae and Cyperus of Cyperaceae, each consists of 6 species, are found to be the largest genera in Magnoliopsida and Liliopsida, respectively. Total 236 species have been recorded as herbs followed by 58 tree seedlings, 50 shrubs and 2 lianas. Scrub jungles harbouring a total of 90 species are found to be the most common habitat of Angiosperms in the area, which is followed by marginal lands, road sides, grasslands, lake banks, fallow lands, woodlands, river bank, and highland slope and wet lands. A total of 281 economically important species have been determined from the study area. The occurrence of two threatened species, viz. Andrographis paniculata (Burm.f.) Nees and Rauvolfia serpentina (L.) Benth. ex Kurz, listed in the Red Data Book of Bangladesh, is recognized to be Vulnerable (V) in the study area. Jahangirnagar University J. Biol. Sci. 7(2): 47-64, 2018 (December)

The aim of this study was to find out the environmental as well as genetic factors responsible for increasing the number of autism spectrum disorder (ASD) patients in Bangladesh. A questionnaire was developed based on 12 environmental factors and genetic aspects. Sixty six patients of ASD and 66 non-ASD control were selected randomly. Among the environmental factors, the age of the mother, premature birth, air pollution, age of the father, hypoxia during childbirth and oral contraceptive came out as significant (p<0.05) factors for ASD incidence compared to the control. Association of multiple factors on an individual was found to be crucial to enhance the risk and exposure to five and six factors was statistically significant (p<0.05) for ASD development. Prospective parents should try to keep the number of risk factors as low as possible before 1-2 months of pregnancy, during pregnancy and 1-2 years after the child birth (for child only).

Pteridophytes growing in the Rajkandi Reserve Forest of Moulvibazar district were indentified and a total of 52 species belonging to 30 genera of 20 families have been documented. The family Pteridaceae with nine species was found to be the largest, which was followed by Polypodiaceae with seven, Tectariaceae with six and Thelypteridaceae with five species. The genus Pteris with six species was found as the largest, which was followed by Tectaria with five and Bolbitis , Lygodium and Selaginella , each with 3 species, and the rest of the genera consisted of two or one species. Most of the species were recorded from the woodlands and three species, viz ., Tectaria chattagramica and Cyathea gigantea enlisted in Red Data Book of Bangladesh (Khan et al ., 2001), were found as common in this reserve forest. Jahangirnagar University J. Biol. Sci. 5 (2): 27-40, 2016 (December)

The study revealed the occurrence of 528 species of vascular plants belonging to 356 genera and 111 families in the Sundarban Mangrove Forest of Bangladesh. Among these species, 24 were pteridophytes and the rest were angiosperms, of which only 24 were true mangroves and 70 were mangrove associates. Magnoliopsida and Liliopsida were represented by 373 and 131 species, respectively. These species belonged to 345 herbs, 89 shrubs and 94 trees. Sixty-four species were climbers, 14 were epiphytes, 6 were parasites, and 7 were palms. The species number per family varied from 1 to 42. In pteridophytes, Pteridaceae with 4 genera and 5 species was the largest family. In angiosperms, Fabaceae with 24 genera and 42 species and Poaceae with 27 genera and 42 species were the largest families, respectively, in Magnoliopsida and Liliopsida. Most of the species included in this checklist were found in oligohaline zone, Sarankhola range and the forest margins, and recognized as economically important. Eleven species categorized as threatened in Bangladesh were found to occur in this mangrove forest.Bangladesh J. Plant Taxon. 22(1): 17–41, 2015 (June)

ABSTRACT Mikulicz disease (MD) is a disorder characterized by multiple lymphoepithelial lesions involving lacrimal and salivary glands. It is an uncommon condition, and very few cases are reported in the literature. It is a variant of Sjögren syndrome (SS) with patients presenting with clinical features over a wide range of spectrum. It is important to differentiate on which side of the disease spectrum the patient is presenting, i.e., either primary SS or secondary SS, because management can vary. The purpose of mentioning these two cases and its importance lie in the fact that the patients presented at two ends of the spectrum of SS – the first patient belonging to secondary SS and the second patient belonging to primary SS – which changes the line management for both patients, conservative and surgical respectively. The purpose of reporting these two cases is to emphasize the importance of identifying disease symptoms and signs early, which can help stratify the patient as a variant of primary SS or secondary SS and thus decide on the appropriate line of management, saving precious time and discomfort to the patient. Here we are mentioning two case reports of MD belonging to diagonally opposite spectrums of SS and their management with successful remission. How to cite this article Bhattacharjee A, Uddin S, Prakash R, Rathor A, Kalita S. Diagnostic and Management Challenges in Mikulicz Syndrome. Int J Head Neck Surg 2015;6(4): 139-145.

Clinically significant 18 Single Nucleotide Polymorphisms (SNPs) from exon regions of Retinoblastoma gene (RB1) were analyzed to find out the structural variations in mRNAs. Online bioinformatic tools i.e., Vienna RNA, RNAfold were used for secondary structure analysis of mRNAs. Predicted minimum Free Energy Change (MFE) was calculated for mRNAs structures. It has been observed that the average of predicted MFE value from 13 nonsense mutations was higher (0.76 kcal/mol) in comparison to 5 missense mutations. Presumably, 13 nonsense mutations are responsible for Nonsense Mediated mRNA Decay (NMD), therefore, excluded from haplotype analysis. From the statistical analysis all the thermodynamic data obtained from four SNP haplotypes are significant (p≤0.05), followed by three-SNP haplotype data except Ensemble diversity (p≤0.10). Interestingly, MEF of Centroid Secondary Structure is highly significant (p≤0.01) in all the cases (Two-SNP haplotypes, Three-SNP haplotypes and Four-SNP haplotypes).

BACKGROUNDHead neck cancer (HNCA) is a major health problem, accounting for 30-40% cancers at all sites with the incidence in North-East India, where this study has been conducted is highest in the country (54.48%). As various substances alter quantitatively in the serum during tumor development, we intended to explore the changes in the haematological profile in cases of head neck squamous cell carcinoma and epithelial precursor lesions. Moreover, such study will be the first on HNCA patients in this North East region of India.AIMSTo assess the variations of haematological and biochemical parameters in HNSCC and Epithelial precursor lesions of the head and neck.METHODS AND MATERIALBlood samples from the cases were collected to quantify Hb%, hematocrit, RBC count, MCV, MCH, MCHC, TLC, RDW-CV, blood urea, creatinine and glucose levels. Using ANOVA test, the difference in various groups were compared and the significance obtained.RESULTSOur study showed extremely significant difference in Hb% level in both the HNSCC and EPL group from the control population. There was no significant correlation between WBC count and the development of SCC or EPL. MCHC and MCV was found to be high in majority of cases and the difference of MCHC among the three groups was found to be extremely significant. We found elevated RDW-SD levels in majority of cases in both groups while mean ESR level was very high in EPL group only. However, blood biochemistry parameters did not reveal any significant results.CONCLUSIONSThe present study shows that among different hematological parameters, Hb%, MCHC, MCV, RDW, SD and ESR are significantly altered in HNCA and premalignant states. Present study also confirms that there is no significant correlation between WBC count and HNCA. The grossly raised MCHC, RDW-SD and ESR values in both cancerous and precancerous lesion of HNCA point out that these parameters should be considered collectively during evaluation of HNCA patients. The variations in these parameters may be useful in the prediction of malignant transformation, prognosis or in treatment progress.

Not availableDOI: http://dx.doi.org/10.3329/bjpt.v21i2.21362Bangladesh J. Plant Taxon. 21(2): 199-202, 2014 (December)

Better predictive ability of salt and buffer effects on protein-protein interactions requires separating out contributions due to ionic screening, protein charge neutralization by ion binding, and salting-in(out) behavior. We have carried out a systematic study by measuring protein-protein interactions for a monoclonal antibody over an ionic strength range of 25 to 525 mM at 4 pH values (5, 6.5, 8, and 9) in solutions containing sodium chloride, calcium chloride, sodium sulfate, or sodium thiocyante. The salt ions are chosen so as to represent a range of affinities for protein charged and noncharged groups. The results are compared to effects of various buffers including acetate, citrate, phosphate, histidine, succinate, or tris. In low ionic strength solutions, anion binding affinity is reflected by the ability to reduce protein-protein repulsion, which follows the order thiocyanate > sulfate > chloride. The sulfate specific effect is screened at the same ionic strength required to screen the pH dependence of protein-protein interactions indicating sulfate binding only neutralizes protein charged groups. Thiocyanate specific effects occur over a larger ionic strength range reflecting adsorption to charged and noncharged regions of the protein. The latter leads to salting-in behavior and, at low pH, a nonmonotonic interaction profile with respect to sodium thiocyanate concentration. The effects of thiocyanate can not be rationalized in terms of only neutralizing double layer forces indicating the presence of an additional short-ranged protein-protein attraction at moderate ionic strength. Conversely, buffer specific effects can be explained through a charge neutralization mechanism, where buffers with greater valency are more effective at reducing double layer forces at low pH. Citrate binding at pH 6.5 leads to protein charge inversion and the formation of attractive electrostatic interactions. Throughout the report, we highlight similarities in the measured protein-protein interaction profiles with previous studies of globular proteins and of antibodies providing evidence that the behavior will be common to other protein systems.

Understanding how protein-protein interactions depend on the choice of buffer, salt, ionic strength, and pH is needed to have better control over protein solution behavior. Here, we have characterized the pH and ionic strength dependence of protein-protein interactions in terms of an interaction parameter kD obtained from dynamic light scattering and the osmotic second virial coefficient B22 measured by static light scattering. A simplified protein-protein interaction model based on a Baxter adhesive potential and an electric double layer force is used to separate out the contributions of longer-ranged electrostatic interactions from short-ranged attractive forces. The ionic strength dependence of protein-protein interactions for solutions at pH 6.5 and below can be accurately captured using a Deryaguin-Landau-Verwey-Overbeek (DLVO) potential to describe the double layer forces. In solutions at pH 9, attractive electrostatics occur over the ionic strength range of 5-275 mM. At intermediate pH values (7.25 to 8.5), there is a crossover effect characterized by a nonmonotonic ionic strength dependence of protein-protein interactions, which can be rationalized by the competing effects of long-ranged repulsive double layer forces at low ionic strength and a shorter ranged electrostatic attraction, which dominates above a critical ionic strength. The change of interactions from repulsive to attractive indicates a concomitant change in the angular dependence of protein-protein interaction from isotropic to anisotropic. In the second part of the paper, we show how the Baxter adhesive potential can be used to predict values of kD from fitting to B22 measurements, thus providing a molecular basis for the linear correlation between the two protein-protein interaction parameters.