Selective Detection of Zn2+ Ions by Ratiometric Receptor (E)-N′-(1-(2, 5-Dihydroxy phenyl) Ethylidene) Isonicotinohydrazide: A DFT Study

The metal ion sensing characteristics of a novel Schiff-based ratiometric UV-visible chemosensor (E)-N’-(1-(2,5-dihydroxy phenyl)ethylidene) isonicotinohydrazide) (R1) has been explored. In EtOH:H2O (7:3, v/v), it has high sensitivity and selectivity for Zn2+ among a series of metal ions. With the addition of Zn2+ ions solution, R1 displayed discriminating spectral activity. The other metal ions did not affect R1 in any way. Furthermore, the addition of Zn2+ ions to R1 and LMCT action caused the shifting of the peak to a longer wavelength of 406 nm. The interaction of Zn2+ ions with R1 was further investigated using Density Functional Theory (DFT) investigations. Zn2+-R1 combination has a lower energy (2.2667 kcal.mol-1 to 0.9339 kcal.mol-1) than R1, indicating a strong connection with excellent stability. The Zn2+-R1 complex’s association constant (Ka) was discovered to be 6795M-1 and 6836M-1 using Benesi-Hildebrand and Scatchard plots respectively. The detection limit was determined to be 276 nM.

Attention Layer-Based Multidimensional Feature Extraction for Diagnosis of Lung Cancer

At present, early lung cancer screening is mainly based on radiologists' experience in diagnosing benign and malignant pulmonary nodules by lung CT images. On the other hand, intraoperative rapid freezing pathology needs to analyse the invasive adenocarcinoma nodules with the worst recovery in adenocarcinoma. Moreover, rapid freezing pathology has a low diagnostic accuracy for small-diameter nodules. Because of the above problems, an algorithm for diagnosing invasive adenocarcinoma nodules in ground-glass pulmonary nodules is based on CT images. According to the nodule space information and plane features, sample data of different dimensions are designed, namely, 3D space and 2D plane feature samples. The network structure is designed based on the attention mechanism and residual learning unit; 2D and 3D neural networks are along built. By fusing the feature vectors extracted from networks of different dimensions, the diagnosis results of invasive adenocarcinoma nodules are finally obtained. The algorithm was studied on 1760 ground-glass nodules with 5-20 mm diameter collected from a city chest hospital with surgical and pathological results. There were 340 nodules with invasive adenocarcinoma and 340 with noninvasive adenocarcinoma. A total of 1420 invasive nodule samples were cross-validated on this example dataset. The classification accuracy of the algorithm was 82.7%, the sensitivity was 82.9%, and the specificity was 82.6%.

Deep Learning-Based Real-Time Discriminate Correlation Analysis for Breast Cancer Detection

Breast cancer is the most common cancer in women, and the breast mass recognition model can effectively assist doctors in clinical diagnosis. However, the scarcity of medical image samples makes the recognition model prone to overfitting. A breast mass recognition model integrated with deep pathological information mining is proposed: constructing a sample selection strategy, screening high-quality samples across different mammography image datasets, and dealing with the scarcity of medical image samples from the perspective of data enhancement; mining the pathology contained in limited labeled models from shallow to deep information; and dealing with the shortage of medical image samples from the perspective of feature optimization. The multiview effective region gene optimization (MvERGS) algorithm is designed to refine the original image features, improve the feature discriminate and compress the feature dimension, better match the number of samples, and perform discriminate correlation analysis (DCA) on the advanced new features; in-depth cross-modal correlation between heterogeneous elements, that is, the deep pathological information, can be mined to describe the breast mass lesion area accurately. Based on deep pathological information and traditional classifiers, an efficient breast mass recognition model is trained to complete the classification of mammography images. Experiments show that the key technical indicators of the recognition model, including accuracy and AUC, are better than the mainstream baselines, and the overfitting problem caused by the scarcity of samples is alleviated.

Supervised Computer-Aided Diagnosis (CAD) Methods for Classifying Alzheimer's Disease-Based Neurodegenerative Disorders

Alzheimer's disease is incurable at the moment. If it can be appropriately diagnosed, the correct treatment can postpone the patient's illness. To aid in the diagnosis of Alzheimer's disease and to minimize the time and expense associated with manual diagnosis, a machine learning technique is employed, and a transfer learning method based on 3D MRI data is proposed. Machine learning algorithms can dramatically reduce the time and effort required for human treatment of Alzheimer's disease. This approach extracts bottleneck features from the M-Net migration network and then adds a top layer to supervised training to further decrease the dimensionality and delete portions. As a consequence, the transfer network presented in this study has several advantages in terms of computational efficiency and training time savings when used as a machine learning approach for AD-assisted diagnosis. Finally, the properties of all subject slices are combined and trained in the classification layer, completing the categorization of Alzheimer's disease symptoms and standard control. The results show that this strategy has a 1.5 percentage point better classification accuracy than the one that relies exclusively on VGG16 to extract bottleneck features. This strategy could cut the time it takes for the network to learn and improve its ability to classify things. The experiment shows that the method works by using data from OASIS. A typical transfer learning network's classification accuracy is about 8% better with this method than with a typical network, and it takes about 1/60 of the time with this method.

Privacy Protection of Healthcare Data over Social Networks Using Machine Learning Algorithms

With the rapid development of mobile medical care, medical institutions also have the hidden danger of privacy leakage while sharing personal medical data. Based on the k-anonymity and l-diversity supervised models, it is proposed to use the classified personalized entropy l-diversity privacy protection model to protect user privacy in a fine-grained manner. By distinguishing solid and weak sensitive attribute values, the constraints on sensitive attributes are improved, and the sensitive information is reduced for the leakage probability of vital information to achieve the safety of medical data sharing. This research offers a customized information entropy l-diversity model and performs experiments to tackle the issues that the information entropy l-diversity model does not discriminate between strong and weak sensitive features. Data analysis and experimental results show that this method can minimize execution time while improving data accuracy and service quality, which is more effective than existing solutions. The limits of solid and weak on sensitive qualities are enhanced, sensitive data are reduced, and the chance of crucial data leakage is lowered, all of which contribute to the security of healthcare data exchange. This research offers a customized information entropy l-diversity model and performs experiments to tackle the issues that the information entropy l-diversity model does not discriminate between strong and weak sensitive features. The scope of this research is that this paper enhances data accuracy while minimizing the algorithm's execution time.

A Case of Idiopathic Retinitis Vasculitis Aneurysms and Neuroretinitis (IRVAN) Treated with Adalimumab

PURPOSE

To report a case of IRVAN in a 13-year-old girl responding well to Adalimumab and Azathioprine.

RESULTS

A 13-year-old girl presented to us with central scotoma for a duration of 10 months. She was treated earlier with oral steroids with poor response. Fundus examination revealed features of IRVAN. She was treated with intravitreal dexamethasone implant in both eyes with oral Mycophenolate Mofetil (MMF) with transient response to it. So she was switched over to subcutaneous Adalimumab 40 mg once in 2 weeks and oral Azathioprine 50 mg BD. The disease activity was well controlled with the current regime.

CONCLUSION

Though various treatment modalities have been described in literature for the treatment of IRVAN. This is the first case of IRVAN to be treated with Adalimumab along with Azathioprine to be reported.

Machine Learning and Cloud-Based Knowledge Graphs to Recognize Suicidal Mental Tendencies

To improve the quality of knowledge service selection in a cloud manufacturing environment, this paper proposes a cloud manufacturing knowledge service optimization decision method based on users' psychological behavior. Based on the characteristic analysis of cloud manufacturing knowledge service, establish the optimal evaluation index system of cloud manufacturing knowledge service, use the rough set theory to assign initial weights to each evaluation index, and adjust the initial weights according to the user's multiattribute preference to ensure that the consequences are allocated correctly. The system can help counselors acquire psychological knowledge in time and identify counselors with suicidal tendencies to prevent danger. This paper collected some psychological information data and built a knowledge graph by creating a dictionary and generating entities and relationships. The Han language processing word segmentation tool generates keywords, and CHI (Chi-square) feature selection is used to classify the problem. This feature selection is a statistical premise test that is acceptable when the chi-square test results are distributed with the null hypothesis. It includes the Pearson chi-square test and its variations. The Chi-square test has several benefits, including its distributed processing resilience, ease of computation, broad information gained from the test, usage in research when statistical assumptions are not satisfied, and adaptability in organizing information from multiple or many more group investigations. For improving question and answer efficiency, compared with other models, the BiLSTM (bidirectional long short-term memory) model is preferred to build suicidal tendencies. The Han language processing is a method that is used for word segmentation, and the advantage of this method is that it plays a key role in the word segmentation tool and generates keywords, and CHI (Chi-square) feature selection is used to classify the problem. Text classifier detects dangerous user utterances, question template matching, and answer generation by computing similarity scores. Finally, the system accuracy test is carried out, proving that the system can effectively answer the questions related to psychological counseling. The extensive experiments reveal that the method in this paper's accuracy rate, recall rate, and F1 value is much superior to other standard models in detecting psychological issues.

Optimized Attribute Selection Using Artificial Plant (AP) Algorithm with ESVM Classifier (AP-ESVM) and Improved Singular Value Decomposition (ISVD)-Based Dimensionality Reduction for Large Micro-array Biological Data

In the tremendous field of the bioinformatics look into, enormous volume of genetic information has been produced. Higher throughput gadgets are made accessible at lower cost made the age of Big data. In a time of developing information multifaceted nature and volume and the approach of huge information, feature selection has a key task to carry out in decreasing high dimensionality in AI issues. Dealing with such huge data has turned out to be incredibly testing strategy for choosing the exact features in enormous medical databases. Large clinical data frequently comprise of an enormous number of identifiers of the disease. Data mining when applied to clinical data for identification of diseases, a few identifiers are will not be much useful and sometimes may even have negative impacts. Consequently, when the FS is applied, it is vital as it can expel those insignificant disease identifiers. It likewise builds the adequacy of decision by a physician emotionally supportive network by viably diminishing the time of learning of the framework. In this paper, a unique approach is presented for the feature selection utilizing the Artificial Plant algorithm which uses the Enhanced Support Vector Machine classifier. The features got are additionally dimensionally decreased by presenting the Improved Singular Value Decomposition strategy; finally, enhancement is done by the outstanding BAT streamlining method. The examinations are completed with real-time large cervical cancer data and it demonstrated to be more effective than the current methods.

Tuberculosis retreatment outcomes and associated factors: a mixed-methods study from Puducherry, India

Setting: Four Tuberculosis (TB) Units in the Union Territory of Puducherry in India. Objectives: To identify factors associated with unfavourable outcomes among retreatment TB cases in Puducherry. Design: The study had a mixed-methods design in which routinely reported TB data from retreatment TB cases registered during 2014 and 2015 were used for the quantitative part; the qualitative phase comprised interviews and focus group discussions with health care providers. Results: Among the 392 retreatment cases, 297 (75.8%) had favourable outcomes. Outcome for previous treatment such as loss to follow-up (LTFU) (adjusted relative risk [aRR] 1.6, 95%CI 1.1-2.4, P = 0.001), treatment failure (aRR 1.7, 95%CI 1.04-2.8, P = 0.03) and pre-treatment weight <40 kg (aRR 1.8, 95%CI 1.3-2.5, P = 0.001) had increased risk for unfavourable outcomes. Health care providers reported that alcoholism, lack of family support, job-related issues and lack of access to trained staff for injections were some of the reasons for unfavourable outcomes. Providing incentives, nutritional supplements and early retrieval of the LTFU cases were some of the suggestions to reduce unfavourable outcomes. Conclusion: Outcome of previous treatment and low pre-treatment weight of the patient affected retreatment outcomes. Health professionals and workers highlighted social and health system-related factors. Commitment at all levels on the part of health care providers and addressing their concerns can improve retreatment outcomes.

[BCIgEPRED-a Dual-Layer Approach for Predicting Linear IgE Epitopes]

Allergy is a common health problem worldwide, especially food allergy. Since B cell epitopes that are recognized by the IgE antibodies act as antigenic determinants for allergy, they play a vital role in diagnostics. Hence, knowledge of an IgE binding epitope in a protein is of particular interest for identifying aller-genic proteins. Though IgE epitopes maybe conformational or linear, identification of the later is useful especially in food allergens that undergo processing or digestion. Very few computational tools are available for the prediction of linear IgE epitopes. Here we report a prediction system that predicts the exact linear IgE epitope. Since our earlier study on linear B cell epitope prediction demonstrated the effectiveness of using an exact epitope dataset (in contrast to epitope containing region datasets), the dataset in this study uses only experimentally verified exact IgE, IgG, IgM and IgA epitopes. Models for Support Vector Machine (SVM) and Random Forest (RF) were constructed adopting Dipeptide Deviation from the Expected mean (DDE) feature vector. Extensive validation procedures including five-fold cross validation and two different independent dataset tests have been performed to validate the proposed method, which achieved a balanced accuracy ranging from 74 to 78% with area under receiver operator curve greater than 0.8. Performance of the proposed method was observed to be better (accuracy difference of 16-28%) in comparison to the existing available method. The proposed method is developed as a standalone tool that could be used for predicting IgE epitopes as well as to be incorporated into any allergen prediction toolhttps://github.com/brsaran/BCIgePred.

CTAB-Aided Synthesis of Stacked V2O5 Nanosheets: Morphology, Electrochemical Features and Asymmetric Device Performance

To accomplish superior performance in supercapacitors, a fresh class of electrode materials with advantageous structures is essential. Owing to its rich electrochemical activity, vanadium oxides are considered to be an attractive electrode material for energy storing devices. In this work, vanadium pentoxide (V2O[Formula: see text] nanostructures were prepared using surfactant (CTAB)-assisted hydrothermal route. Stacked V2O5 sheets enable additional channels for electrolyte ion intercalation. These stacked V2O5 nanosheets show highest specific capacitance of 466[Formula: see text]Fg[Formula: see text] at 0.5[Formula: see text]Ag[Formula: see text]. In addition, it exhibits good rate capacity, lower value of charge transfer resistance and good stability when used as an electrode material for supercapacitors. Further, an asymmetric supercapacitor device was assembled utilizing the stacked V2O5 sheets and activated carbon as electrodes. The electrochemical features of the device are also discussed.

A divergent and metal free synthesis of sulfoximine tethered imidazoles, imidazopyridines, imidazothiazoles, imidazobenzothiazines, thiazoles and selenazoles

A divergent and metal free approach has been successfully developed for the synthesis of sulfoximine tethered heterocycles from a α-bromoalkanone building block.

Kinetics studies on the removal of Methyl ethyl ketone using cornstack based biofilter

The performance of cornstack based biofilter inoculated with a mixed culture was evaluated for gas phase MEK removal under various operating conditions. Experiments were carried out at different flow rates (0.03-0.12m³h^-1) and various initial concentrations (0.2-1.2g^-3). A maximum elimination capacity (EC) of 35g^-3h^-1 was achieved at an inlet loading rate of 60g^-3h^-1 with a removal efficiency of 95%. High elimination capacity reached with this system could have been due to the dominant presence of filamentous fungi among others. The experimental results were compared with the values obtained from the Ottengraf-van den Oever model for zero-order diffusion-controlled region. The critical inlet concentration, critical inlet load and biofilm thickness were estimated using the model predictions.

Stereoselective synthesis of 4-aminobenzo[c][1,2]thiazine via modification of the Harmata benzothiazine synthesis

A stereoselective synthesis of 4-aminobenzothiazines was developed through a modified Harmata benzothiazine synthesis.

An in vitro comparative evaluation of fracture resistance of custom made, metal, glass fiber reinforced and carbon reinforced posts in endodontically treated teeth

BACKGROUND

Posts are used to enhance crown buildup in pulpless teeth with destructed crown portion. Different types of post are used in endodontically treated teeth. The aim of the present in vitro study was to evaluate fracture resistance of custom made, metal, glass fiber reinforced and carbon reinforced posts in endodontically treated teeth.

MATERIALS AND METHODS

An in vitro study was carried out on extracted 40 human maxillary central incisor teeth, which was divided into four groups with 10 samples in each group with custom made, metal post, glass fiber reinforced, and carbon reinforced posts. The samples were decoronated at cemento-enamel junction and endodontically treated. Post space was prepared and selected posts were cemented. The composite cores were prepared at the height of 5 mm and samples mounted on acrylic blocks. Later fracture resistance to the compressive force of samples was measured using Universal Testing Machine.

RESULTS

The maximum resistance to the compressive force was observed in carbon reinforced and glass fiber reinforced posts compared others which is statistically significant (P > 0.001) and least was seen in custom fabricated post.

CONCLUSION

It is concluded that carbon reinforced fiber post and glass fiber posts showed good fracture resistance compared to custom made and metal posts.

Crystal structure of (2-bromo-methyl-1-phenyl-sulfonyl-1H-indol-3-yl)(phen-yl)methanone

In the title compound, C₂₂H₁₆BrNO₃S, the phenyl rings make dihedral angles of 84.81 (16) and 61.67 (17)° with the indole ring system (r.m.s. deviation = 0.012 Å), while the phenyl rings are inclined to one another by 69.5 (2)°. The mol­ecular structure is stabilized by weak intra­molecular C—H⋯O hydrogen bonds. The sulfonyl S atom has a distorted tetra­hedral configuration. In the crystal, there are no significant inter­molecular inter­actions present.

Crystal structure of (2-methyl-1-phenyl-sulfon-yl-1H-indol-3-yl)(phen-yl)methanone

In the title compound, the indole ring system makes the dihedral angles of 84.89 (7) and 57.32 (5)° with the phenyl rings. In the crystal, mol­ecules are linked by C—H⋯O hydrogen bonds.

In the title compound, C₂₂H₁₇NO₃S, the sulfonyl-bound phenyl ring is almost orthogonal to the indole ring system, making a dihedral angle of 84.89 (7)°. The carbonyl-bound phenyl ring forms a dihedral angle of 57.32 (5)° with the indole ring system. The two phenyl rings are inclined at 52.68 (7)°. The S atom has a distorted tetra­hedral configuration. In the crystal, weak C—H⋯O inter­actions link the mol­ecules, forming a helical chain along the b-axis direction.

2-Bromo-1-(1-phenyl-sulfonyl-1H-indol-3-yl)propan-1-one

In the title compound, C₁₇H₁₄BrNO₃S, the phenyl ring makes a dihedral angle of 89.78 (16)° with the plane of the indole ring system. The terminal Br atom and the methyl group are disordered over two sets of sites, with site occupancies of 0.860 (2) and 0.140 (2). In the crystal, mol­ecules are linked into a chain along the b-axis direction by weak C—H⋯O hydrogen bonds. The chains are further linked by C—H⋯π inter­actions, forming layers parallel to the bc plane.

(E)-1-[2-(2-Nitro-styr-yl)-1-phenyl-sulfonyl-1H-indol-3-yl]propan-1-one

In the title compound, C₂₅H₂₀N₂O₅S, the phenyl ring makes dihedral angles of 89.88 (8) and 13.98 (8)°, respectively, with the indole ring system and the nitro­benzene ring. The dihedral angle between the indole ring system and the nitro­benzene ring is 88.48 (11)°. The mol­ecular structure is stabilized by a weak intra­molecular C—H⋯O inter­action. In the crystal, π–π inter­actions, with centroid–centroid distances of 3.6741 (18) and 3.8873 (17) Å, link the mol­ecules into layers parallel to the ab plane.

(E)-2-Bromo-1-[2-(2-nitro-styr-yl)-1-phenyl-sulfonyl-1H-indol-3-yl]ethanone

In the title compound C₂₄H₁₇BrN₂O₅S, the phenyl ring makes dihedral angles of 85.4 (2) and 8.8 (2)° with the indole ring system and the nitro­benzene ring, respectively, while the indole ring system and nitrobenzene ring make a dihedral angle of 80.1 (2)°. In the crystal, weak C—H⋯O inter­actions link the mol­ecules, forming a two-dimensional network parallel to the bc plane.

Successful aqueous processing of a lead free 0.5Ba(Zr0.2Ti0.8)O3–0.5(Ba0.7Ca0.3)TiO3 piezoelectric material composition

We report on successful aqueous processing of a lead free BZT–BCT composition with its dielectric properties unaffected by hydrolysis.

(E)-1-[2-(4-Chloro-2-nitro-styr-yl)-1-phenyl-sulfonyl-1H-indol-3-yl]propan-1-one

In the title compound, C₂₅H₁₉ClN₂O₅S, the phenyl ring forms dihedral angles of 79.62 (12) and 80.02 (13)° with the indole ring system and the benzene ring, respectively. The nitro group is twisted at an angle of 22.39 (11)° with respect to the attached benzene ring. In the crystal, mol­ecules assemble into double layers in the ab plane via C—H⋯O inter­actions.

1-(2-Bromo-meth-yl-1-phenyl-sulfonyl-1H-indol-3-yl)propan-1-one

In the title compound, C₁₈H₁₆BrNO₃S, the dihedral angle between the phenyl ring and the indole ring system is 89.91 (11)°. The mol­ecular structure features weak C—H⋯O and C—H⋯Br hydrogen bonds. In the crystal, mol­ecules are linked by weak C—H⋯O hydrogen bonds, forming chains along the a-axis direction. The chains are further linked by C—H⋯π inter­actions, forming a layer parallel to the ab plane.

(E)-1-[2-(4-Fluoro-2-nitro-styr-yl)-1-phenyl-sulfonyl-1H-indol-3-yl]propan-1-one

In the title compound, C25H19FN2O5S, the substituted phenyl ring makes a dihedral angle of 12.26 (9)° with the indole ring system. The nitro group is twisted at an angle of 26.92 (8)° out of the plane of the ring to which it is attached. The mol-ecular structure is stabilized by weak C-H⋯O hydrogen bonds. In the crystal, weak C-H⋯O, C-H⋯F and π-π [centroid-centroid distance = 3.6645 (11) Å] inter-actions link the mol-ecules, forming a three-dimensional network.

(Z)-3-(1-Chloro-prop-1-en-yl)-2-methyl-1-phenyl-sulfonyl-1H-indole

In the title compound, C₁₈H₁₆ClNO₂S, the indole ring system forms a dihedral angle of 75.07 (8)° with the phenyl ring. The mol­ecular structure is stabilized by a weak intra­molecular C—H⋯O hydrogen bond. In the crystal, mol­ecules are linked by weak C—H⋯O hydrogen bonds, forming a chain along [10-1]. C—H⋯π inter­actions are also observed, leading to a three-dimensional network.

2-Methyl-1-phenylsulfonyl-1H-indole-3-carbaldehyde

In the title compound, C₁₆H₁₃NO₃S, the sulfonyl-bound phenyl ring forms a dihedral angle of 84.17 (6)° with the indole ring system. An intra­molecular C—H⋯O hydrogen bond generates an S(6) ring motif. The crystal structure exhibits weak inter­molecular C—H⋯O hydrogen bonds and π–π inter­actions between the five- and six-membered rings of the indole group [centroid–centroid distance = 3.6871 (9) Å].

Ethyl 1-phenylsulfonyl-1H-indole-2-carboxylate

In the title compound, C₁₇H₁₅NO₄S, the six-membered ring of the indole unit makes a dihedral angle of 72.40 (5)° with the phenyl ring. The mol­ecular structure features a short C—H⋯O contact.

2-(4-Methylphenyl)-1-phenylsulfonyl-3-nitro-1,2-dihydroquinoline

In the title compound, C₂₂H₁₈N₂O₄S, the dihedral angle between the phenyl­sulfonyl ring and the methyl­phenyl ring is 67.78 (7)°. In the crystal, mol­ecules are linked by weak inter­molecular C—H⋯O inter­actions into a zigzag chain along the [101] direction.

(Acetoxy)(2-methylphenyl)methyl acetate

In the title compound, C₁₂H₁₄O₄, the two acet­oxy groups are inclined by 57.92 (5)° and 62.71 (6)° to the benzene ring. An inter­molecular C—H⋯O inter­action involving the two acet­oxy groups generates a centrosymmetric dimer via an R²₂(16) ring motif.

Anaemia in rheumatoid arthritis: can we afford to ignore it?

INTRODUCTION Anaemia is common in rheumatoid arthritis (RA). Clinicians may focus on rheumatological issues and assume anaemia of chronic disease (ACD). This study challenged this assumption and investigated the causes of anaemia in a large cohort of RA patients to assess its implications. METHODS The hospital where the study was conducted monitors regular full blood count and erythrocyte sedimentation rate (ESR) monthly in all RA patients on disease modifying drugs to assess efficacy and safety. A computerised system identifies and records abnormal results. The database for 2009 was interrogated to find all patients with two consecutive haemoglobin values <11&emsp14;g/dl. Using a proforma, patients were defined as having iron deficiency anaemia (IDA), ACD, macrocytic anaemia (MCA) or another cause. All results of further tests investigating the anaemia were recorded. RESULTS Among 2000 RA patients on the system, 199 (10%) were identified as having anaemia over a year. Of these, 90 had IDA, 78 had ACD, 25 had MCA, and 6 had postoperative anaemia. Among 90 patients with IDA, investigations were performed in 53, with 23 normal. An explanation for IDA was found in 30: gastrointestinal bleeding in 25, gynaecological blood loss in 3, and urinary bleeding in 2. Among 78 patients with ACD, response to intensification of RA treatment occurred in 45, but erythropoietin therapy was required in 9. Within the 25 patients with MCA, 12 had unrecognised vitamin B(12) deficiency, 4 drug induced changes, 3 myeloid malignancy, 2 hypothyroidism, and 2 alcoholism. CONCLUSIONS Anaemia in RA is common, multifactorial, and potentially both serious and correctable. Established malignancy was present in 10 patients and premalignancy in a further 10 (10% of total). Treatable causes were commonly identified. Clinicians need to investigate the nature and cause of persistent anaemia, and must not assume it to be simply ACD without evidence.

Ethyl 1-benzenesulfonyl-2-[(E)-2-(2-methylphenyl)ethenyl]indole-3-carboxylate

In the title compound, C₂₆H₂₃NO₄S, the phenyl, tolyl and ester groups make dihedral angles of 82.28 (5), 77.67 (6) and 8.52 (6)°, respectively, with the indole ring system. The S atom of the sulfonyl group is displaced by 0.1968 (4) Å from the indole mean plane. The mol­ecular structure is stabilized by weak intra­molecular C—H⋯O inter­actions. The crystal structure structure features short intramolecular C—H⋯O contacts and π–π stacking inter­actions between the phenyl and tolyl groups [centroid–centroid distance = 3.9448 (11) Å].

Tapered anaerobic hybrid reactor--a better option for treating low-strength wastewaters

Anaerobic biofilm reactors have limitations in treating wastewaters with low organic substrate concentrations (COD value below 1000 mg/L) because the substrate cannot reach the microorganisms present in the interior part of the biogranules. Hence, the performance of these reactors is mainly influenced by the size of the biogranules present within the reactor. An anaerobic hybrid reactor with a tapered configuration has been developed where the self-immobilized biogranules are kept under completely fluidized condition. The tapered configuration can retain smaller sized biogranules more effectively than a cylindrical configuration for the same hydraulic loading rate. A synthetic effluent containing glucose as the sole carbon source was used to study the performance of this reactor. The reactor could handle an organic loading rate up to 19.1 kgCOD/(m3 x d) with a hydraulic retention time (HRT) of 0.63 h, removing around 90% of inlet COD. Even though the strength of the wastewater is low, the resultant organic loading rate is also high because of the high hydraulic loading rate (low HRT). The specific substrate utilization rate study showed that the concentration of methanogenic bacteria within the biogranules increased along the reactor height, whereas the concentration of acidogens decreased. The morphology and hydrodynamic characteristics of the biogranules obtained from the reactor at different heights were also studied. The biogranules obtained from the upper port of the reactor had a lower diameter, lower terminal settling velocity and more cavities than those from the lower port. Biogranules up to the size of 5.2 mm were observed.

How to reduce morbidity and mortality from chest infections in rheumatoid arthritis

Morbidity and mortality from pneumonia is increased in patients with rheumatoid arthritis. Factors contributing to this have been recently identified and a number of recommendations have been implemented in an attempt to reverse this trend. The present paper shows that these measures have combined to produce a fourfold reduction in both admissions and case fatality rates. In the study population, immunisation rates against influenza and pneumococcus have improved to 86% and 65%, oral steroid consumption has halved and disease modifying drugs were usually appropriately suspended during acute infection. These measures may now merit more widespread adoption.