Machine-Learning-Based Predictions of Polymer and Postconsumer Recycled Polymer Properties: A Comprehensive Review

There has been a tremendous increase in demand for virgin and postconsumer recycled (PCR) polymers due to their wide range of chemical and physical characteristics. Despite the numerous potential benefits of using a data-driven approach to polymer design, major hurdles exist in the development of polymer informatics due to the complicated hierarchical polymer structures. In this review, a brief introduction on virgin polymer structure, PCR polymers, compatibilization of polymers to be recycled, and their characterization using sensor array technologies as well as factors affecting the polymer properties are provided. Machine-learning (ML) algorithms are gaining attention as cost-effective scalable solutions to exploit the physical and chemical structures of polymers. The basic steps for applying ML in polymer science such as fingerprinting, algorithms, open-source databases, representations, and polymer design are detailed in this review. Further, a state-of-the-art review of the prediction of various polymer material properties using ML is reviewed. Finally, we discuss open-ended research questions on ML application to PCR polymers as well as potential challenges in the prediction of their properties using artificial intelligence for more efficient and targeted PCR polymer discovery and development.

Soybean cyst nematode detection and management: a review

Soybeans play a key role in global food security. U.S. soybean yields, which comprise [Formula: see text] of the total soybeans planted in the world, continue to experience unprecedented grain loss due to the soybean cyst nematode (SCN) plant pathogen. SCN remains one of the primary disruptive pests despite the existence of advanced management techniques such as crop rotation and SCN-resistant varieties. SCN detection is a key step in managing this disease; however, early detection is challenging because soybeans do not show any above ground symptoms unless they  are significantly damaged. Direct soil sampling remains the most common method for SCN detection, however, this method has several problems. For example, the threshold damage methods-adopted by most of the laboratories to make recommendations-is not reliable as it does not consider soil pH, N, P, and K values and relies solely on the egg count instead of assessment of the root infection. To overcome the challenges of manual soil sampling methods, deep learning and hyperspectral imaging are important current topics in precision agriculture for plant disease detection and have been proposed as cost-effective and efficient detection methods that can work at scale. We have reviewed more than 150 research papers focusing on soybean cyst nematodes with an emphasis on deep learning techniques for detection and management. First: we describe soybean vegetation and reproduction stages, SCN life cycles, and factors influencing this disease. Second: we highlight the impact of SCN on soybean yield loss and the challenges associated with its detection. Third: we describe direct sampling methods in which the soil samples are procured and analyzed to evaluate SCN egg counts. Fourth: we highlight the advantages and limitations of these direct methods, then review computer vision- and remote sensing-based detection methods: data collection using ground, aerial, and satellite approaches followed by a review of machine learning methods for image analysis-based soybean cyst nematode detection. We highlight the evaluation approaches and the advantages of overall detection workflow in high-performance and big data environments. Lastly, we discuss various management approaches, such as crop rotation, fertilization, SCN resistant varieties such as PI 88788, and SCN's increasing resistance to these strategies. We review machine learning approaches for soybean crop yield forecasting as well as the influence of pesticides, herbicides, and fertilizers on SCN infestation reduction. We provide recommendations for soybean research using deep learning and hyperspectral imaging to accommodate the lack of the ground truth data and training and testing methodologies, such as data augmentation and transfer learning, to achieve a high level of detection accuracy while keeping costs as low as possible.

Virtual oncology research-different models and lessons learned

PURPOSE OF REVIEW

The COVID-19 pandemic posed several challenges to cancer research including halting of trials, reduced recruitment and protocol violations related to inflexible processes followed in clinical trials. Researchers adopted innovative measures to mitigate these problems and continue studies without compromising their quality. This review collates these adaptations that could well continue after the pandemic.

RECENT FINDINGS

The COVID-19 pandemic forced researchers globally to adopt innovative measures to overcome the challenges of the pandemic. These included protocol amendments to adjust to the pandemic and travel restrictions, and increased use of digital technologies. 'Virtual' clinical trials were conducted increasingly with adaptations in ethics and regulatory approvals, patient recruitment and consenting, study interventions and delivery of study medications, trial assessments, and monitoring. Many of these adaptations are safe and feasible, without compromising study quality and data integrity. Although these may not be universally applicable in all types of research, they bring many benefits including more diverse patient participation, less burden on patients for study procedures and reduced resources to conduct trials.

SUMMARY

The COVID-19 pandemic has affected cancer research adversely; however, learnings from the pandemic and adaptations from researchers are likely to improve the efficiency of clinical research beyond the pandemic.

Random Forest Regressor-Based Approach for Detecting Fault Location and Duration in Power Systems

Power system failures or outages due to short-circuits or "faults" can result in long service interruptions leading to significant socio-economic consequences. It is critical for electrical utilities to quickly ascertain fault characteristics, including location, type, and duration, to reduce the service time of an outage. Existing fault detection mechanisms (relays and digital fault recorders) are slow to communicate the fault characteristics upstream to the substations and control centers for action to be taken quickly. Fortunately, due to availability of high-resolution phasor measurement units (PMUs), more event-driven solutions can be captured in real time. In this paper, we propose a data-driven approach for determining fault characteristics using samples of fault trajectories. A random forest regressor (RFR)-based model is used to detect real-time fault location and its duration simultaneously. This model is based on combining multiple uncorrelated trees with state-of-the-art boosting and aggregating techniques in order to obtain robust generalizations and greater accuracy without overfitting or underfitting. Four cases were studied to evaluate the performance of RFR: 1. Detecting fault location (case 1), 2. Predicting fault duration (case 2), 3. Handling missing data (case 3), and 4. Identifying fault location and length in a real-time streaming environment (case 4). A comparative analysis was conducted between the RFR algorithm and state-of-the-art models, including deep neural network, Hoeffding tree, neural network, support vector machine, decision tree, naive Bayesian, and K-nearest neighborhood. Experiments revealed that RFR consistently outperformed the other models in detection accuracy, prediction error, and processing time.

An Instance Segmentation and Clustering Model for Energy Audit Assessments in Built Environments: A Multi-Stage Approach

Heat loss quantification (HLQ) is an essential step in improving a building's thermal performance and optimizing its energy usage. While this problem is well-studied in the literature, most of the existing studies are either qualitative or minimally driven quantitative studies that rely on localized building envelope points and are, thus, not suitable for automated solutions in energy audit applications. This research work is an attempt to fill this gap of knowledge by utilizing intensive thermal data (on the order of 100,000 plus images) and constitutes a relatively new area of analysis in energy audit applications. Specifically, we demonstrate a novel process using deep-learning methods to segment more than 100,000 thermal images collected from an unmanned aerial system (UAS). To quantify the heat loss for a building envelope, multiple stages of computations need to be performed: object detection (using Mask-RCNN/Faster R-CNN), estimating the surface temperature (using two clustering methods), and finally calculating the overall heat transfer coefficient (e.g., the U-value). The proposed model was applied to eleven academic campuses across the state of North Dakota. The preliminary findings indicate that Mask R-CNN outperformed other instance segmentation models with an mIOU of 73% for facades, 55% for windows, 67% for roofs, 24% for doors, and 11% for HVACs. Two clustering methods, namely K-means and threshold-based clustering (TBC), were deployed to estimate surface temperatures with TBC providing consistent estimates across all times of the day over K-means. Our analysis demonstrated that thermal efficiency not only depended on the accurate acquisition of thermal images but also relied on other factors, such as the building geometry and seasonal weather parameters, such as the outside/inside building temperatures, wind, time of day, and indoor heating/cooling conditions. Finally, the resultant U-values of various building envelopes were compared with recommendations from the American Society of Heating, Refrigerating, and Air-conditioning Engineers (ASHRAE) building standards.

AB0128 CONSTRUCTION OF THE VETERANS AFFAIRS NATIONAL RHEUMATOID ARTHRITIS DATABASE (VANRAD)

Background:

The Department of Veterans Affairs (DVA) provides comprehensive medical care at minimal or no cost to 9 million veterans annually through 170 medical centers and 1074 outpatient clinics across the United States. In 1999, the DVA established a national, fully integrated electronic health record (EHR), which now includes approximately 24 million veterans. However, few studies have used VA EHR data to examine the validity of diagnoses of rheumatoid arthritis (RA).

Objectives:

Develop a validated, national database (VANRAD) of patients with RA who received VA care since International Classification of Diseases, tenth revision (ICD-10) coding was introduced in 2015. The database will provide infrastructure for retrospective and prospective research to address the ‘real-world’ care of patients with RA.

Methods:

Patients with the following criteria were identified from the VA EHR as of October 2, 2020: (a) ≥1 ICD-10 diagnosis code of RA; (b) treatment with ≥1 disease-modifying anti-rheumatic drug (DMARD); (c) ≥2 VA rheumatology clinic visits; and (d) ≥1 rheumatoid factor (RF) or anti-cyclic citrullinated peptide (aCCP) antibody test result. From this group, 553 EHRs were randomly selected for review. The ‘gold standard’ for the diagnosis of RA was the treating rheumatologist’s diagnosis, documented in the EHR.

Results:

27,482 patients met eligibility criteria. Sociodemographic characteristics were: 85.6% male, mean age of 69.7 years (y) (SD=10.9 y; range=21.9 y to 100.5 y), 76.4% white, 17.0% African American; and mean VA care duration 14.1 y (SD=5.3 y, range=0.04 y to 20.0 y).

For patients with ≥1 RF or aCCP test, the positive predictive value (PPV) for RA ranged from 65.3% (aCCP-/RF-) to 95.8% (aCCP+/RF+); rheumatologists’ likelihood of a ‘possible’ diagnosis was higher if the aCCP test result was negative or not available (Table 1). Excluding patients with a second rheumatologic diagnosis did not improve PPV results (data not shown).

Table 1.

Proportion of patients with a valid RA diagnosis1 as a function of RF and aCCP laboratory results

Test ResultaCCPNot Available (0)2Negative (-)Positive (+)TotalRheumatoid FactorNot Available (0)(N = 1253)3N 427N 1,159N 1,586RA4 89.7%RA 98.2%RA 93.5%Poss5 RA 5.9%Poss RA 0.0%Poss RA 3.2%Negative (-)N 810N 5,308N 2,005N 8,123RA 86.3%RA 65.3%RA 94.5%RA 80.7%Poss RA 3.9%Poss RA 11.9%Poss RA 0.0%Poss RA 5.8%Positive (+)N 2,229N 2,566N 12,978N 17,773RA 94.6%RA 78.0%RA 95.8%RA 87.6%Poss RA 0.0%Poss RA 8.5%Poss RA 2.1%Poss RA 4.3%TotalN 3,039N 8.301N 16,142N 27,482RA 90.7%RA 76.1%RA 95.9%RA 85.9%Poss RA 1.9%Poss RA 9.2%Poss RA 0.5%Poss RA 4.7%

1Diagnosis given by the treating rheumatologist.

2No test results available or test results available but without normal range values.

31,253 patients without available or interpretable RF or aCCP excluded from initial cohort.

4Percent of 553 charts reviewed confirmed as RA.

5Poss RA = Possible RA. Patients met our inclusion criteria but the treating rheumatologist never made definitive diagnosis of RA or alternative diagnosis (from 553 charts reviewed).

The percentage of RA-confirmed patients with one test not available, whose complementary test was negative (RF0/aCCP- or RF-/aCCP0), was greater than of patients for whom both tests were negative (RF-/aCCP-). This suggests our data extraction methods may be incomplete or that unidentified bias may be present and warrants further study.

Conclusion:

Our methodology for constructing an RA database by selecting patients with ≥2 rheumatology clinic visits, ≥1 ICD-10 diagnosis of RA, and treatment with ≥1 DMARD, has high positive predictive value for RA. Positive RF and aCCP test results were strong predictors of rheumatologists’ diagnostic certainty for an RA diagnosis. Thus, the VANRAD database and the associated EHR provide opportunity for a wide range of retrospective observational and prospective longitudinal studies based on ‘real-world’ patient care.

References:

[1]Ng B, et al. Arthritis Care Res 2012;64:1490-6; Hanly JG, et al. Open Access Rheumatol 2015;7:69-75.

Acknowledgements:

This study was sponsored by Bristol Myers Squibb.

Disclosure of Interests:

Amy Joseph Speakers bureau: Speakers bureau in the distant past., Grant/research support from: Bristol Myers Squibb, Jodi Yanagida: None declared, Xinliang Huang: None declared, Prabha Ranganathan: None declared, Melissa Laurie Shareholder of: Bristol-Myers Squibb, Employee of: I am currently employed by Bristol Myers Squibb., Hong Xian Grant/research support from: Bristol Myers Squibb Co., Seth Eisen Grant/research support from: The effort presented in this Abstract was supported with funds provided by Bristol-Meyers Squibb.

Choroidal thickness in lupus nephritis

OBJECTIVE

This study aimed to compare choroidal thickness between patients with systemic lupus erythematosus (SLE) and lupus nephritis (LN) in complete renal remission to that of patients with SLE without LN.

METHODS

This was a retrospective case-control study of 23 SLE patients meeting either the American College of Rheumatology or Systemic Lupus International Collaborating Clinics classification criteria and followed at Washington University School of Medicine Rheumatology or Nephrology, and Ophthalmology outpatient clinics. The diagnosis of LN was based on renal pathology, and complete renal remission was defined as proteinuria <500 mg/daily and serum creatinine at baseline. Extra-renal flare status was determined using modified Fortin criteria. Choroidal thickness was measured using spectral-domain optical coherence tomography and read by blinded reviewers.

RESULTS

In SLE patients without extra-renal flare, choroidal thickness of LN patients was 281 ± 78 µm compared to 288 ± 70 µm in non-LN SLE patients (p = 0.766) at the fovea.

CONCLUSION

Choroidal thickness was not different in patients with LN in remission compared to non-LN SLE patients in remission. Additional studies are needed to examine choroidal thickness in patients with SLE with active LN.

Does a less intensive surveillance protocol affect the survival of patients after treatment of a sarcoma of the limb?

Aims

A single-centre prospective randomized trial was conducted to investigate whether a less intensive follow-up protocol would not be inferior to a conventional follow-up protocol, in terms of overall survival, in patients who have undergone surgery for sarcoma of the limb. Initial short-term results were published in 2014.

Patients and Methods

The primary objective was to show non-inferiority of a chest radiograph (CXR) group compared with a CT scan group, and of a less frequent (six-monthly) group than a more frequent (three-monthly) group, in two-by-two comparison. The primary outcome was overall survival and the secondary outcome was a recurrence-free survival. Five-year survival was compared between the CXR and CT scan groups and between the three-monthly and six-monthly groups. Of 500 patients who were enrolled, 476 were available for follow-up. Survival analyses were performed on a per-protocol basis (n = 412).

Results

The updated results recorded 12 (2.4%) local recurrences, 182 (36.8%) metastases, and 56 (11.3%) combined (local + metastases) recurrence at a median follow-up of 81 months (60 to 118). Of 68 local recurrences, 60 (88%) were identified by the patients themselves. The six-monthly regime (overall survival (OS) 54%, recurrence-free survival (RFS) 46%) did not lead to a worse survival and was not inferior to the three-monthly regime (OS 55%, RFS 47%) in terms of detecting recurrence. Although CT scans (OS 53%, RFS 54%) detected pulmonary metastasis earlier, it did not lead to a better survival compared with CXR (OS 56%, RFS 59%).

Conclusion

The overall survival of patients who are treated for a sarcoma of the limb is not inferior to those followed up with a less intensive regimen than a more intensive protocol, in terms of frequency of visits and mode of imaging. CXR at six-monthly intervals and patient education about examination of the site of the surgery will detect most recurrences without deleterious effects on the eventual outcome. Cite this article: Bone Joint J 2018;100-B:262–8.

Utilization of operating room time in a cancer hospital

BACKGROUND

Appropriate usage of operating room (OR) time can improve efficiency of utilization of resources and help to decrease surgical waiting lists.

AIMS

This study was conducted to evaluate the pattern of usage of OR time in a tertiary referral cancer hospital.

SETTING AND DESIGN

This was a prospective audit carried out over 2 months in 11 major ORs in a cancer hospital.

MATERIALS AND METHODS

OR anesthesiologists filled a standard form for all patients undergoing elective surgery and documented the following times: entry into OR, start of anesthesia, handover to surgeon, incision, start of reversal, end of anesthesia, and shifting out of patient.

STATISTICAL ANALYSIS

Median time utilized for various OR processes was calculated.

RESULTS

An average of two surgeries were performed per OR session (828 surgeries in 407 OR sessions). Anesthesia and surgery-related processes contributed to 17% and 79%, respectively, of total OR time, with turnover time between cases accounting for the remaining 4%. Fifteen percent (60 out of 407) OR sessions started more than 10 min later than the planned start time, and 17% (70 of 407) of OR sessions ended more than 2 h after the scheduled finish time. An anesthesia procedure room was utilized in only 15% of cases where it could potentially have been used.

CONCLUSION

This audit identified patterns of OR usage in a cancer hospital and helped to detect areas of inefficient utilization. Anesthesia-related processes contributed to 17% of the total OR time.

Decontamination of laryngoscope blades: is our practice adequate?

BACKGROUND

The laryngoscope has been identified as a potential source of cross-infection, because of blood and bacterial contamination. In India, there are no guidelines for cleaning and disinfection of anesthesia-related equipment. Practices for decontamination of laryngoscopes vary widely and in most healthcare institutes, laryngoscope blades are re-used after cleaning with tap-water.

MATERIALS AND METHODS

We prospectively compared two techniques for decontamination of laryngoscope blades - a) washing with tap-water and b) washing with tap-water followed by disinfection by immersing in 5% v/v (volume/volume, 1:20 dilution) aldehyde-free biguanide agent for 10 min. We calculated the cost-effectiveness of using 5% v/v aldehyde-free biguanide agent for disinfection of laryngoscopes. We also conducted a survey to assess the decontamination practices in other Indian hospitals.

RESULTS

Overall bacterial growth was 58% (29 out of 50 blades) after tap-water cleaning (of which 60% were pathogenic organisms) versus 3.4% (one out of 29 blades) after tap-water cleaning followed by immersion in disinfectant (all of which were commensals). The cost of disinfection with biguanide was Indian Rupees 1.13 (20 US cents) per laryngoscope. Most hospitals in India do not have guidelines regarding laryngoscope decontamination between uses, and cleaning with tap water is a commonly used method.

CONCLUSION

Cleaning of laryngoscope blades with tap-water is a commonly used but inadequate method for decontamination. Washing with tap-water followed by disinfection with 5% v/v aldehyde-free biguanide for at least 10 min is an effective and inexpensive alternative. National guidelines for the decontamination of anesthesia equipment are necessary.

Genetics of bone loss in rheumatoid arthritis--role of vitamin D receptor polymorphisms

RA is a systemic inflammatory arthritis that leads to local and systemic bone loss. Osteoporosis or the systemic bone loss associated with RA increases the risk for fragility fractures, which can affect quality of life dramatically in RA patients. Although traditional and RA-related risk factors have been defined and studied for osteoporosis associated with RA, genetic factors such as polymorphic variants in the traditional candidate genes for osteoporosis, such as the vitamin D receptor (VDR), type 1 collagen A1 (COLIA1) and oestrogen receptor-alpha (ESR1), have not been well elucidated in RA patients. This review summarizes the currently available literature on the association of VDR polymorphisms with local and systemic bone loss in RA. It also discusses potential targets for genetic research in this area, such as polymorphisms in genes, such as IL-6 (IL6) and TNF receptor type 2 (TNFRSF1B), which control the inflammatory response in RA and may influence bone loss in RA. Defining such genetic factors, in addition to traditional and RA-related risk factors for osteoporosis in RA, may facilitate early identification of patients at high risk for fractures who can then be targeted for treatment.

Possible link between glycated hemoglobin and lipid peroxidation in hyperthyroidism

BACKGROUND

Glycated hemoglobin (HbA1C) levels are enhanced by elevated glucose concentrations. Glycation of hemoglobin is also modulated by lipid peroxides, ascorbic acid and reduced glutathione (GSH). We determined the strength of the relationships among these variables in a group of hyperthyroid patients.

METHODS

Twenty-two untreated hyperthyroid patients and 17 healthy controls were recruited for the study. Whole blood GSH, HbA1C, plasma lipid peroxides, ascorbic acid and fasting glucose were analyzed in both the groups. Direct and partial correlation analysis was performed to explore the possible relationships between these variables.

RESULTS

In hyperthyroid patients, HbA1C and lipid peroxides levels were found to be significantly increased than the controls. Ascorbic acid and GSH were decreased significantly in the test group when compared with the healthy control group. With partial correlation analysis, fasting glucose and lipid peroxides were found to have a significant positive correlation with HbA1C. Ascorbic acid and GSH showed no significant association with HbA1C levels.

CONCLUSION

These data suggest that HbA1C levels are closely associated with fasting glucose and lipid peroxides in hyperthyroid patients. Therefore, serum lipid peroxides level should be kept in mind while interpreting HbA1C as a long-term glycemic index in hyperthyroid cases.

Will pharmacogenetics allow better prediction of methotrexate toxicity and efficacy in patients with rheumatoid arthritis?

Methotrexate (MTX) remains the most commonly used disease modifying antirheumatic drug in rheumatoid arthritis (RA) because of its cost and experience in its use, despite the availability of new treatments such as leflunomide and the biological agents. However, a significant number of patients with RA either do not benefit from the drug or are unable to tolerate it. Pharmacogenetic approaches may help optimise treatment with MTX, and also other agents, in RA.

Creatine kinase as an indicator of sperm quality and maturity in men with oligospermia

OBJECTIVES

To determine the differences among the creatine kinase (CK) levels in the spermatozoa of subfertile men with mild, moderate, or severe oligospermia and to examine the differences in CK activity between infertile patients with various clinical diagnoses and a group of normal healthy donors (control). CK is a marker of sperm maturity that correlates with the sperm fertilizing capacity. Elevated levels are associated with an increased rate of functional abnormalities and increased cytoplasmic retention.

METHODS

We compared the CK levels in 51 oligospermic men who could not initiate a pregnancy. Patients were categorized according to their degree of oligospermia as defined by the total sperm count: mild (greater than 10 to 40 x 10(6); n = 30), moderate (5 to 10 x 10(6); n = 11), and severe (less than 5 x 10(6); n = 10). These patients were further classified according to their diagnosis (ie, varicocele, n = 24; unexplained infertility, n = 17; vasectomy reversal, n = 9; and unknown diagnosis, n = 1). A separate group consisting of 25 healthy donors was included as a control group. A computer-assisted semen analyzer assessed the sperm characteristics, and the CK levels were measured using a CK test kit after the enzyme was extracted with Triton-X.

RESULTS

The CK levels were significantly higher in the sperm of the severely oligospermic group (8.8 +/- 6.5 IU/10(8) sperm) than in the moderate (0.50 +/- 0.19 IU/10(8) sperm) and mild (0.49 +/- 0.15 IU/10(8) sperm) groups (P <0.0001). The mean CK level in the severely oligospermic group was 18-fold higher than that in the moderate (P = 0.03) and mild (P <0.001) groups. The CK levels were significantly higher in all three infertile groups compared with the donor group (0.06 +/- 0.01 IU/10(8) sperm). Patients with varicocele had the highest CK level (3.42 +/- 2.56 IU/10(8) sperm) compared with patients in the vasectomy reversal group (1.73 +/- 0.98 IU/10(8) sperm) and the idiopathic infertility group (0.26 +/- 0.08 IU/10(8) sperm).

CONCLUSIONS

Elevated CK levels are associated with severe oligospermia, irrespective of the clinical diagnosis. CK may be a sensitive indicator of sperm quality and maturity in the follow-up of patients treated for male factor infertility.

Growth hormone levels in relation to birth weight and gestational age

Growth hormone levels were measured in 33 umbilical cord blood samples collected from babies born at JIPMER Hospital during April and May-1998. The study was done to evaluate the growth hormone profile in relation to birth weight and gestational age. There was statistically significant difference in the cord blood growth hormone levels between babies weighing > 2500 gms (28.1 +/- 12.83 ng/dl) and low birth weight babies (76.8 +/- 55.7 ng/dl). The difference in growth hormone levels between term babies weighing > 2500 gms and preterm babies (72.5 +/- 29.4 ng/dl) was also statistically significant. However, there was no significant difference in the cord blood growth hormone levels between term low birth weight and preterm babies. Growth hormone levels were higher in preterm babies and low birth weight babies as compared to term babies weighing > 2500 gms indicating that growth hormone has an important role to play in intrauterine growth along with other growth promoting factors.

Nuclear targeting peptide scaffolds for lipofection of nondividing mammalian cells

Lipofection of nondividing cells is inefficient because much of the transfected DNA is retained in endosomes, and that which escapes to the cytoplasm enters the nucleus at low rates. To improve the final rate-limiting step of nuclear import, we conjugated a nonclassical nuclear localization signal (NLS) containing the M9 sequence of heterogeneous nuclear ribonucleoprotein (hnRNP) A1, to a cationic peptide scaffold derived from a scrambled sequence of the SV40 T-antigen consensus NLS (ScT). The ScT was added to improve DNA binding of the M9 sequence. Lipofection of confluent endothelium with plasmid complexed with the M9-ScT conjugate resulted in 83% transfection and a 63-fold increase in marker gene expression. The M9-ScT conjugate localized fluorescent plasmid into the nucleus of permeabilized cells, and addition of the nuclear pore blocker wheat germ agglutinin prevented nuclear import. This method of gene transfer may lead to viral- and lipid-free transfection of nondividing cells.

Sexual abuse: giving support to nurses

Nurses dealing with people who have been sexually abused as children need strong support and supervision systems to enable them to cope with the feelings of helplessness and sadness that can arise. Such a system has been set up at a psychiatric day hospital in London to help nurses provide consistent, long-term and non-judgemental care.

Transfusion-associated AIDS: donor-recipient human immunodeficiency virus exhibits genetic heterogeneity

The genetic diversity of the human immunodeficiency virus (HIV) isolated from transfusion-associated AIDS patients has been examined. Restriction enzyme mapping studies of integrated proviral DNA of donor and recipient origin demonstrated genomic variation between isolates. Analysis of the molecularly cloned viral genomes of one donor-recipient pair showed that virus from the recipient had restriction enzyme site differences from the donor, noticeably clustered in the env and orf-2 regions, and also had a greater number of restriction sites in common with the donor as well. These results suggest that HIV may undergo genomic variation in vivo. Comparison of donor-recipient viruses may further the understanding of the molecular basis for AIDS pathogenesis.

Molecular characterization of human immunodeficiency virus from Zaire: nucleotide sequence analysis identifies conserved and variable domains in the envelope gene

To examine the genetic relatedness of human immunodeficiency viruses (HIV) from different geographic locations, we molecularly cloned the genome of HIV isolated from a Zairian AIDS patient. Restriction mapping of the recombinant clone, designated HIV-Zr6, revealed both common (as observed in other HIV isolates) and unique restriction sites. The DNA clone of HIV-Zr6, shown to give rise to infectious cytopathic virus after transfection of cultured lymphoid cells, was sequenced in several regions. The long terminal repeat (LTR), open reading frame 1 (ORF1), C-terminal envelope (env) gene domain, and ORF2 showed less than 6% difference in nucleotide sequence when compared to other HIV isolates including human T-lymphotropic virus-type III (HTLV-III) clone B10, lymphadenopathy-associated virus-1 (LAV-1), and AIDS-associated retrovirus-2 (ARV-2). About 15% difference in nucleotide sequences was noted in the N-terminal env gene domain. Alignments of env gene sequences revealed conserved, moderately variable, and hypervariable stretches in the predicted amino acid sequences. This model provides a basis for assessing the significance of sequence variation on properties controlled by the viral Env glycoproteins such as cell tropism and immunogenicity.