What can GPT-4 do for Diagnosing Rare Eye Diseases? A Pilot Study

INTRODUCTION

Generative pretrained transformer-4 (GPT-4) has gained widespread attention from society, and its potential has been extensively evaluated in many areas. However, investigation of GPT-4's use in medicine, especially in the ophthalmology field, is still limited. This study aims to evaluate GPT-4's capability to identify rare ophthalmic diseases in three simulated scenarios for different end-users, including patients, family physicians, and junior ophthalmologists.

METHODS

We selected ten treatable rare ophthalmic disease cases from the publicly available EyeRounds service. We gradually increased the amount of information fed into GPT-4 to simulate the scenarios of patient, family physician, and junior ophthalmologist using GPT-4. GPT-4's responses were evaluated from two aspects: suitability (appropriate or inappropriate) and accuracy (right or wrong) by senior ophthalmologists (> 10 years' experiences).

RESULTS

Among the 30 responses, 83.3% were considered "appropriate" by senior ophthalmologists. In the scenarios of simulated patient, family physician, and junior ophthalmologist, seven (70%), ten (100%), and eight (80%) responses were graded as "appropriate" by senior ophthalmologists. However, compared to the ground truth, GPT-4 could only output several possible diseases generally without "right" responses in the simulated patient scenarios. In contrast, in the simulated family physician scenario, 50% of GPT-4's responses were "right," and in the simulated junior ophthalmologist scenario, the model achieved a higher "right" rate of 90%.

CONCLUSION

To our knowledge, this is the first proof-of-concept study that evaluates GPT-4's capacity to identify rare eye diseases in simulated scenarios involving patients, family physicians, and junior ophthalmologists. The results indicate that GPT-4 has the potential to serve as a consultation assisting tool for patients and family physicians to receive referral suggestions and an assisting tool for junior ophthalmologists to diagnose rare eye diseases. However, it is important to approach GPT-4 with caution and acknowledge the need for verification and careful referrals in clinical settings.

Pathogenesis of myopic choroidal neovascularization: A systematic review and meta-analysis

Myopic choroidal neovascularization (CNV) is a vision-threatening complication of high myopia. Here, we systematically review cohort, case-control, and cross-sectional studies in PubMed, Embase, and Web of Science, and summarize the associated factors of myopic CNV using meta-analysis where applicable. Among 1,333 records assessed, 50 were found eligible, all having a low-to-moderate risk of bias. Highly myopic eyes with CNV had a higher risk of lacquer cracks (odds ratio = 2.88) and patchy chorioretinal atrophy (odds ratio = 3.43) than those without. The mean posterior staphyloma height (µm) was greater in myopic CNV eyes than in highly myopic eyes without CNV (mean difference = 82.03). The thinning of choroidal thickness (µm) between myopic eyes with and without CNV differed significantly (mean difference = -47.76). The level of vascular endothelial growth factor (pg/ml) in the aqueous humor of myopic CNV eyes was significantly higher than in highly myopic eyes without CNV (mean difference = 24.98), the same as interleukin-8 (IL-8) (pg/ml, mean difference = 7.73). Single-nucleotide polymorphisms in the vascular endothelial growth factor, complement factor I, and collagen type VIII alpha 1 genes were associated with myopic CNV. We found that myopic CNV eyes have a higher ratio of lacquer cracks and patchy chorioretinal atrophy, thinner choroid, greater posterior staphyloma height, and a higher level of vascular endothelial growth factor and IL-8 in aqueous. Structural predisposing lesions, hemodynamic, genetic, and systemic factors are also associated with myopic CNV.

Assessment of Parafoveal Diabetic Macular Ischemia on Optical Coherence Tomography Angiography Images to Predict Diabetic Retinal Disease Progression and Visual Acuity Deterioration

Importance

The presence of diabetic macular ischemia (DMI) on optical coherence tomography angiography (OCTA) images predicts diabetic retinal disease progression and visual acuity (VA) deterioration, suggesting an OCTA-based DMI evaluation can further enhance diabetic retinopathy (DR) management.

Objective

To investigate whether an automated binary DMI algorithm using OCTA images provides prognostic value on DR progression, diabetic macular edema (DME) development, and VA deterioration in a cohort of patients with diabetes.

Design, Setting, and Participants

In this cohort study, DMI assessment of superficial capillary plexus and deep capillary plexus OCTA images was performed by a previously developed deep learning algorithm. The presence of DMI was defined as images exhibiting disruption of fovea avascular zone with or without additional areas of capillary loss, while absence of DMI was defined as images presented with intact fovea avascular zone outline and normal distribution of vasculature. Patients with diabetes were recruited starting in July 2015 and were followed up for at least 4 years. Cox proportional hazards models were used to evaluate the association of the presence of DMI with DR progression, DME development, and VA deterioration. Analysis took place between June and December 2022.

Main Outcomes and Measures

DR progression, DME development, and VA deterioration.

Results

A total of 321 eyes from 178 patients were included for analysis (85 [47.75%] female; mean [SD] age, 63.39 [11.04] years). Over a median (IQR) follow-up of 50.41 (48.16-56.48) months, 105 eyes (32.71%) had DR progression, 33 eyes (10.28%) developed DME, and 68 eyes (21.18%) had VA deterioration. Presence of superficial capillary plexus-DMI (hazard ratio [HR], 2.69; 95% CI, 1.64-4.43; P < .001) and deep capillary plexus-DMI (HR, 3.21; 95% CI, 1.94-5.30; P < .001) at baseline were significantly associated with DR progression, whereas presence of deep capillary plexus-DMI was also associated with DME development (HR, 4.60; 95% CI, 1.15-8.20; P = .003) and VA deterioration (HR, 2.12; 95% CI, 1.01-5.22; P = .04) after adjusting for age, duration of diabetes, fasting glucose, glycated hemoglobin, mean arterial blood pressure, DR severity, ganglion cell-inner plexiform layer thickness, axial length, and smoking at baseline.

Conclusions and Relevance

In this study, the presence of DMI on OCTA images demonstrates prognostic value for DR progression, DME development, and VA deterioration.

A MULTITASK DEEP-LEARNING SYSTEM FOR ASSESSMENT OF DIABETIC MACULAR ISCHEMIA ON OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY IMAGES

PURPOSE

We aimed to develop and test a deep-learning system to perform image quality and diabetic macular ischemia (DMI) assessment on optical coherence tomography angiography (OCTA) images.

METHODS

This study included 7,194 OCTA images with diabetes mellitus for training and primary validation and 960 images from three independent data sets for external testing. A trinary classification for image quality assessment and the presence or absence of DMI for DMI assessment were labeled on all OCTA images. Two DenseNet-161 models were built for both tasks for OCTA images of superficial and deep capillary plexuses, respectively. External testing was performed on three unseen data sets in which one data set using the same model of OCTA device as of the primary data set and two data sets using another brand of OCTA device. We assessed the performance by using the area under the receiver operating characteristic curves with sensitivities, specificities, and accuracies and the area under the precision-recall curves with precision.

RESULTS

For the image quality assessment, analyses for gradability and measurability assessment were performed. Our deep-learning system achieved the area under the receiver operating characteristic curves >0.948 and area under the precision-recall curves >0.866 for the gradability assessment, area under the receiver operating characteristic curves >0.960 and area under the precision-recall curves >0.822 for the measurability assessment, and area under the receiver operating characteristic curves >0.939 and area under the precision-recall curves >0.899 for the DMI assessment across three external validation data sets. Grad-CAM demonstrated the capability of our deep-learning system paying attention to regions related to DMI identification.

CONCLUSION

Our proposed multitask deep-learning system might facilitate the development of a simplified assessment of DMI on OCTA images among individuals with diabetes mellitus at high risk for visual loss.

A Multitask Deep-Learning System to Classify Diabetic Macular Edema for Different Optical Coherence Tomography Devices: A Multicenter Analysis

OBJECTIVE

Diabetic macular edema (DME) is the primary cause of vision loss among individuals with diabetes mellitus (DM). We developed, validated, and tested a deep learning (DL) system for classifying DME using images from three common commercially available optical coherence tomography (OCT) devices.

RESEARCH DESIGN AND METHODS

We trained and validated two versions of a multitask convolution neural network (CNN) to classify DME (center-involved DME [CI-DME], non-CI-DME, or absence of DME) using three-dimensional (3D) volume scans and 2D B-scans, respectively. For both 3D and 2D CNNs, we used the residual network (ResNet) as the backbone. For the 3D CNN, we used a 3D version of ResNet-34 with the last fully connected layer removed as the feature extraction module. A total of 73,746 OCT images were used for training and primary validation. External testing was performed using 26,981 images across seven independent data sets from Singapore, Hong Kong, the U.S., China, and Australia.

RESULTS

In classifying the presence or absence of DME, the DL system achieved area under the receiver operating characteristic curves (AUROCs) of 0.937 (95% CI 0.920-0.954), 0.958 (0.930-0.977), and 0.965 (0.948-0.977) for the primary data set obtained from CIRRUS, SPECTRALIS, and Triton OCTs, respectively, in addition to AUROCs >0.906 for the external data sets. For further classification of the CI-DME and non-CI-DME subgroups, the AUROCs were 0.968 (0.940-0.995), 0.951 (0.898-0.982), and 0.975 (0.947-0.991) for the primary data set and >0.894 for the external data sets.

CONCLUSIONS

We demonstrated excellent performance with a DL system for the automated classification of DME, highlighting its potential as a promising second-line screening tool for patients with DM, which may potentially create a more effective triaging mechanism to eye clinics.

Detection of Diabetic Retinopathy from Ultra-Widefield Scanning Laser Ophthalmoscope Images: A Multicenter Deep Learning Analysis

PURPOSE

To develop a deep learning (DL) system that can detect referable diabetic retinopathy (RDR) and vision-threatening diabetic retinopathy (VTDR) from images obtained on ultra-widefield scanning laser ophthalmoscope (UWF-SLO).

DESIGN

Observational, cross-sectional study.

PARTICIPANTS

A total of 9392 UWF-SLO images of 1903 eyes from 1022 subjects with diabetes from Hong Kong, the United Kingdom, India, and Argentina.

METHODS

All images were labeled according to the presence or absence of RDR and the presence or absence of VTDR. Labeling was performed by retina specialists from fundus examination, according to the International Clinical Diabetic Retinopathy Disease Severity Scale. Three convolutional neural networks (ResNet50) were trained with a transfer-learning procedure for assessing gradability and identifying VTDR and RDR. External validation was performed on 4 datasets spanning different geographical regions.

MAIN OUTCOME MEASURES

Area under the receiver operating characteristic curve (AUROC); area under the precision-recall curve (AUPRC); sensitivity, specificity, and accuracy of the DL system in gradability assessment; and detection of RDR and VTDR.

RESULTS

For gradability assessment, the system achieved an AUROC of 0.923 (95% confidence interval [CI], 0.892-0.947), sensitivity of 86.5% (95% CI, 77.6-92.8), and specificity of 82.1% (95% CI, 77.3-86.2) for the primary validation dataset, and >0.82 AUROCs, >79.6% sensitivity, and >70.4% specificity for the geographical external validation datasets. For detecting RDR and VTDR, the AUROCs were 0.981 (95% CI, 0.977-0.984) and 0.966 (95% CI, 0.961-0.971), with sensitivities of 94.9% (95% CI, 92.3-97.9) and 87.2% (95% CI, 81.5-91.6), specificities of 95.1% (95% CI, 90.6-97.9) and 95.8% (95% CI, 93.3-97.6), and positive predictive values (PPVs) of 98.0% (95% CI, 96.1-99.0) and 91.1% (95% CI, 86.3-94.3) for the primary validation dataset, respectively. The AUROCs and accuracies for detecting both RDR and VTDR were >0.9% and >80%, respectively, for the geographical external validation datasets. The AUPRCs were >0.9, and sensitivities, specificities, and PPVs were >80% for the geographical external validation datasets for RDR and VTDR detection.

CONCLUSIONS

The excellent performance achieved with this DL system for image quality assessment and detection of RDR and VTDR in UWF-SLO images highlights its potential as an efficient and effective diabetic retinopathy screening tool.

Assessment of retinal neurodegeneration with spectral-domain optical coherence tomography: a systematic review and meta-analysis

OBJECTIVES

To comprehensively assess diabetic retinopathy neurodegeneration (DRN) as quantified by retinal neuronal and axonal layers measured with spectral-domain optical coherence tomography (SD-OCT) in subjects with diabetes mellitus (DM).

METHODS

Articles on the topic of examining macular ganglion cell-inner plexiform layer (m-GCIPL), macular retinal nerve fibre layer (m-RNFL), macular ganglion cell complex (m-GCC), and peripapillary RNFL (p-RNFL) measured with SD-OCT in DM subjects without DR (NDR) or with non-proliferative DR (NPDR) were searched in PubMed and Embase up to November 31, 2019. Standardized mean difference (SMD) as effect size were pooled using random-effects model.

RESULTS

Thirty-six studies searched from online databases and the CUHK DM cohort were included in the meta-analysis. In the comparison between NDR and control, macular measures including mean m-GCIPL (SMD = -0.26, p = 0.003), m-RNFL (SMD = -0.26, p = 0.046), and m-GCC (SMD = -0.28; p = 0.009) were significantly thinner in the NDR group. In the comparison between NPDR and NDR, only mean p-RNFL was significantly thinner in the NPDR group (SMD = -0.27; p = 0.03), but not other macular measures.

CONCLUSIONS

Thinning of retinal neuronal and axonal layers at macula as measured by SD-OCT are presented in eyes with NDR, supporting DRN may be the early pathogenesis in the DM patients without the presence of clinical signs of DR. In the future, these SD-OCT measures may be used as surrogates of DRN to stratify DM patients with a high risk of DR, and may be used as a therapeutic target if neuroprotection treatment for DR is available.

Clinically relevant factors associated with quantitative optical coherence tomography angiography metrics in deep capillary plexus in patients with diabetes

Background

To test clinically relevant factors associated with quantitative artifact-free deep capillary plexus (DCP) metrics in patients with diabetes mellitus (DM).

Methods

563 eligible eyes (221 with no diabetic retinopathy [DR], 135 with mild DR, 130 with moderate DR, and 77 with severe DR) from 334 subjects underwent optical coherence tomography-angiography (OCT-A) with a swept-source OCT (Triton DRI-OCT, Topcon, Inc., Tokyo, Japan). Strict criteria were applied to exclude from analysis those DCP images with artifacts and of poor quality, including projection artifacts, motion artifacts, blurriness, signal loss, B-scan segmentation error, or low-quality score. A customized MATLAB program was then used to quantify DCP morphology from the artifact-free DCP images by calculating three metrics: foveal avascular zone (FAZ), vessel density (VD), and fractal dimension (FD).

Results

166 (29.5%) eyes were excluded after quality control, leaving in the analysis 397 eyes (170 with no DR, 101 with mild DR, 90 with moderate DR, 36 with severe DR) from 250 subjects. In the multiple regression models, larger FAZ area was associated with more severe DR (β = 0.687; p = 0.037), shorter axial length (AL) (β = − 0.171; p = 0.003), thinner subfoveal choroid thickness (β = − 0.122; p = 0.031), and lower body mass index (BMI) (β = − 0.090; p = 0.047). Lower VD was associated with more severe DR (β = − 0.842; p = 0.001), shorter AL (β = 0.107; p = 0.039), and poorer visual acuity (VA) (β = − 0.133; p = 0.021). Lower FD was associated with more severe DR (β = − 0.891; p < 0.001) and with older age (β = − 0.142; p = 0.004).

Conclusions

Quantitative artifact-free DCP metrics are associated with VA, DR severity, AL, subfoveal choroidal thickness, age, and BMI in diabetic patients. The effects of ocular and systemic factors should be considered for meaningful interpretations of DCP changes in DM patients.

Evaluation of migraineurs' preferences for naratriptan over conventional first-line agents

OBJECTIVE

To assess patient satisfaction with and preference for naratriptan hydrochloride therapy over previous "nontriptan" therapy for migraines.

DESIGN AND SETTING

Open-label study conducted at 15 primary care clinics.

PATIENTS

One hundred forty-three adults meeting International Headache Society diagnostic criteria for migraine who were not using triptans as first-line therapy for migraines were enrolled; 115 completed the study. INTERVENTION AND OUTCOME ASSESSMENTS: At baseline, satisfaction with current migraine therapy was assessed. Patients were provided with naratriptan hydrochloride, 2.5 mg, to treat 3 migraines and diaries to record headache symptoms and response to treatment. After treating 3 migraines, satisfaction with naratriptan therapy and preference for either previous or naratriptan therapy were assessed.

RESULTS

Eighty-nine (62%) of 143 patients had previous exposure to triptans, with lack of prescribing (55%) as the primary reason for not continuing their use as first-line therapy. Medications used for first-line therapy included simple analgesics (59%), combination products (46%), and narcotics (13%). After treating 3 migraines with naratriptan, satisfaction with migraine therapy increased from 47% to 75%. Sixty-three percent of patients preferred naratriptan therapy over their previous nontriptan therapy, 27% preferred their previous therapy, and 10% had no preference. The main reasons for preference for naratriptan therapy were "relieves pain effectively" (86%) and "restores ability to function/perform task" (81%).

CONCLUSION

Naratriptan for first-line migraine therapy was preferred by most patients over previous nontriptan therapy.

Photocytotoxic and DNA damaging effect of temoporfin (mTHPC) and merocyanine 540 (MC540) on nasopharyngeal carcinoma cell

Photodynamic therapy (PDT) is a new approach to cancer treatment for a variety of malignant tumors. In this study, two clinical photosensitizers, Temoporfin (meta-tetra-hydroxyl-phenyl-chlorin; mTHPC) and merocyanine 540 (MC540), were selected to explore for their photocytotoxic and genotoxic effects on nasopharyngeal carcinoma cells (NPC/HK1 and CNE2). Results of tetrazolium reduction assay showed that 80% cell killing were achieved for both cell lines at 0.4 microg/ml mTHPC for 24 h incubation and then with 40 kJ/m2 light irradiation, whereas 40 microg/ml MC540 with 50 kJ/m2 light dosage was required to attain the same level of phototoxicity for NPC/HK1. On the contrary, NPC/CNE2 was quite resistant to MC540. Hence, mTHPC-mediated PDT exerted a more potent effect than MC540-mediated PDT, even though the molar extinction coefficient of the main absorption peak for MC540 is much higher than that of mTHPC. Dark cytotoxicity remained negligible for both sensitizers. Comet assay was used to evaluate the DNA strand break and potential genotoxic effect induced by mTHPC and MC540 on the NPC cells. No DNA strand break was detected in the absence of light, and under sublethal treatment (LD25) for either sensitizer-loaded cells. Confocal laser scanning microscopy showed that mTHPC and MC540 localized in the cytoplasm but not in the nucleus of the tumor cells, which provided evidence for undetectable DNA damage under dark and low photodynamic dose.

Tacrine for Alzheimer's disease

BACKGROUND

Tacrine is one of the first drugs to be widely marketed for the loss of memory and intellectual decline in Alzheimer's disease. The alleged success of tacrine in the treatment of these symptoms has been heralded as confirmation of the cholinergic theory of Alzheimer's disease. However, the efficacy of tacrine for symptoms of dementia remains controversial. This is reflected by the low rate of prescription of tacrine in countries where it is approved and the lack of approval by several regulatory authorities in Europe and elsewhere. The uncertainty about the efficacy of tacrine is due to the difficulties in interpretation of the results from the clinical trials. The reasons for this are the small effects of tacrine compared to placebo for all outcomes; the high incidence of adverse events; the lack of benefit observed in several trials; the use of cross-over designs and their associated methodological problems in a disease like dementia; the use of different measurement scales to assess outcome in different trials; and the problem of high dropout rates.

OBJECTIVES

To determine the clinical efficacy of tacrine for the symptoms of Alzheimer's disease.

SEARCH STRATEGY

The Cochrane Dementia Group Register of Clinical Trials was searched using the terms 'tacrine', 'tetrahydroaminoacridine' and 'THA' (see the Group's search strategy for full details).

SELECTION CRITERIA

All unconfounded, double-blind, randomized trials in which treatment with tacrine was administered for more than a day and compared to placebo in patients with dementia of the Alzheimer's type.

DATA COLLECTION AND ANALYSIS

Data were extracted independently by two reviewers, pooled if appropriate and possible, and the pooled odds ratios (95%CI) or the average differences (95%CI) were estimated. Where possible, intention-to-treat data were used.

MAIN RESULTS

This review produced no clear results. The results were compatible with tacrine producing improvement, no change or even harm for those with Alzheimer's disease. It was not possible to use many of the published results in a combined analysis. For measures of overall clinical improvement, the intention-to-treat analyses failed to detect any difference between tacrine and placebo (OR 0.87; 95%CI 0.61 - 1.23). Behavioural disturbance, as measured by the Alzheimer's Disease Assessment Scale-noncognitive, failed to detect any difference between tacrine and placebo (SMD -0.04; 95%CI -0.52 - 0.43). For cognition function, the effect of tacrine was not statistically significantly different from placebo for the MiniMental State Examination score (0-30; high =good) (SMD 0.14; 95%CI -0.02 - 0.30) and was barely statistically significantly in favour of treatment for the Alzheimer's Disease Assessment Scale-cognitive scale (SMD -0.22; 95%CI -0.32 - -0.13). Adverse events were not reported in a systematic way in the different trials, making formal comparison difficult. Raised serum liver enzymes was the major reason for withdrawal. The odds ratio for withdrawal due to an adverse event was significantly different from one, the control group experienced fewer events (OR 5.7; 95%CI 4.1-7.9). Gastrointestinal side effects (diarrhoea, anorexia, dyspepsia and abdominal pain) were the other major cause of adverse events and for withdrawal, and the odds ratio for withdrawal was also significantly different from one in favour of the control group (OR 3.8; 95%CI 2.8-5.1). No deaths were reported in any of the studies during the trial period, up to six months.

REVIEWER'S CONCLUSIONS

This review provides no convincing evidence that tacrine is a useful treatment for the symptoms of Alzheimer's disease. However, as so few trials presented data in a format suitable for pooling, the results of this review may be modified when further data from all relevant trials are included. There is an urgent need for the independent evaluation of the data already existing in the trials but not accessible through published or grouped data. A

Susceptibility testing of clinical isolates of Enterococcus faecium and Enterococcus faecalis

We collected 103 clinical Enterococcus faecium isolates from across Canada, performed standard broth microdilution susceptibility testing, and compared these results with results from the MicroScan Pos MIC Type 6 panel (Baxter Health Care Corp., West Sacramento, Calif.) and the AMS-Vitek Gram-Positive Susceptibility card (Vitek Inc., St. Louis, Mo.). High-level aminoglycoside resistance to gentamicin and streptomycin was detected by a single-concentration agar method with 1,000 micrograms of each aminoglycoside per ml. In addition, we tested the effect of the lower calcium content in broth media as recommended in National Committee for Clinical Laboratory Standards (NCCLS) guideline M7-A2 on the activity of the highly calcium-dependent agent daptomycin. Of the 103 E. faecium isolates, there were 4 and 30 isolates with high-level gentamicin resistance (HLGR) and high-level streptomycin resistance (HLSR), respectively. An additional 39 (37 with HLGR and 36 with HLSR) E. faecium isolates were tested by both the MicroScan and the AMS-Vitek systems. The AMS-Vitek card demonstrated sensitivities of 95 and 82% for detecting HLGR strains and HLSR strains, respectively. The MicroScan panel demonstrated improved sensitivities for detecting HLGR (42 to 97%) and HLSR (64 to 84%) when readings were performed manually instead of being generated automatically. Ampicillin resistance (MIC, greater than or equal to 16 micrograms/ml) was detected in 23 of the 103 E. faecium isolates. Only 14 and 20 of these were detected by the MicroScan panels and AMS-Vitek cards, respectively. beta-Lactamase activity was not detected in any isolates. The lower calcium content in broth media recommended by NCCLS guideline M7-A2 markedly reduced the in vitro activity of daptomycin against Enterococcus spp.

Comparison of the new MicroScan Pos MIC Type 6 panel and AMS-Vitek Gram Positive Susceptibility Card (GPS-TA) for detection of high-level aminoglycoside resistance in Enterococcus species

We compared the MicroScan Pos MIC Type 6 panel and AMS-Vitek Gram Positive Susceptibility Card (GPS-TA) to agar dilution screen plates for the detection of high-level aminoglycoside resistance in 182 enterococcal isolates. The specificity of the two commercial systems was 100%, with the exception of one susceptible isolate found to be streptomycin resistant by the Vitek system. The MicroScan and Vitek systems had comparable sensitivities for the detection of gentamicin resistance (90 and 95% respectively) and streptomycin resistance (85 and 78%, respectively). These results suggest that screening tests such as agar dilution screen plates, broth dilution, or disk diffusion should continue to be used to detect high-level gentamicin and streptomycin resistance.

Three human alcohol dehydrogenase subunits: cDNA structure and molecular and evolutionary divergence

Class I human alcohol dehydrogenase (ADH; alcohol:NAD+ oxidoreductase, EC 1.1.1.1) consists of several homo- and heterodimers of alpha, beta, and gamma subunits that are governed by the ADH1, ADH2, and ADH3 loci. We previously cloned a full length of cDNA for the beta subunit, and the complete sequence of 374 amino acid residues was established. cDNAs for the alpha and gamma subunits were cloned and characterized. A human liver cDNA library, constructed in phage lambda gt11, was screened by using a synthetic oligonucleotide probe that was matched to the gamma but not to the beta sequence. Clone pUCADH gamma 21 and clone pUCADH alpha 15L differed from beta cDNA with respect to restriction sites and hybridization with the nucleotide probe. Clone pUCADH gamma 21 contained an insertion of 1.5 kilobase pairs (kbp) and encodes 374 amino acid residues compatible with the reported amino acid sequence of the gamma subunit. Clone pUCADH alpha 15L contained an insertion of 2.4 kbp and included nucleotide sequences that encode 374 amino acid residues for another subunit, the alpha subunit. In addition, this clone contained the sequences that encode the COOH-terminal part of the beta subunit at its extended 5' region. The amino acid sequences and coding regions of the cDNAs of the three subunits are very similar (approximately 93-95% identity). A high degree of resemblance is observed also in their 3' noncoding regions. However, distinctive differences exist in the vicinity of the Zn-binding cysteine residue at position 46--i.e., Cys-Gly-Thr in the alpha, Cys-Arg-Thr in the wild-type beta 1, Cys-His-Thr in the Oriental-type beta 2, and Cys-Arg-Ser in the gamma, reflecting the differences in their kinetic properties. Based on the cDNA sequences and the deduced amino acid sequences of the three subunits, their structural and evolutionary relationships are discussed.

Residues of chlorpyrifos-methyl in balsam fir foliage, forest litter, soil, stream water, sediment and fish tissue after double aerial applications of Reldan

Chlorpyrifos-methyl was applied twice at 70 g A.I./ha by means of a fixed-wing aircraft to a mixed coniferous forest near Allardville, New Brunswick. Residue in balsam fir foliage was highest (1 ppm wet wt) 1 hr after spraying and rapidly declined to about 30% within 1 day, but persisted at a very low level (0.03 ppm wet wt) for 125 days. Current year's foliage contained a higher level of residue than old foliage. Chlorpyrifos-methyl persisted longer in forest litter than in soil. After 125 days, trace amounts (less than 6 ppb wet wt) were still found in litter but were not detected in soil. In stream water the residue dissipated very rapidly; more than 90% disappeared 3 hours after the second application and were not detected after 4 days. Low-level residue (less than 0.1 ppm wet wt) was present in the sediment and persisted for 10 days. Although brook trout and slimy sculpin captured in the stream within 3 days of the second application contained residues (less than 0.05 ppm fresh wt) none were detected in any fish captured, 9 and 47 days later.

The dissipation of nonylphenol in stream and pond water under simulated field conditions

The dissipation of 1.0 ppm nonylphenol in stream and pond water, incubated in flasks at 16 degree C under simulated field conditions up to 44 days indicated that the half-life was 2.5 days if the flasks were open, and 16 days if they were closed. A transformed product was detected in the closed flasks. Translocation of nonylphenol in water occurred when treated water samples were incubated in the presence of sediment. After 10 days, nonylphenol was detected only in the sediment, but not in water (detection limit = 10 ppb). About 80% of the nonylphenol was degraded in 71 days, but no degradation occurred if the water and the sediment were autoclaved prior to incubation.

Residues of nonylphenol in spruce foliage, forest soil, stream water and sediment after its aerial application

Nonylphenol, a major component of the Matacil (aminocarb) formulation, was mixed with insecticide diluent 585 and applied at 0.47 l/ha by a fixed-wing aircraft to a mixed coniferous forest in Algoma District, Ontario. Residues in white spruce foliage were the highest 1 h after spraying (18.90 ppm) and declined to 60% in the next two hours. After 30 days only 3% of the highest concentration recorded was observed. No detectable levels (less than 0.20 ppm) of nonylphenol were found after 62 days. No residues were detected in any forest soil sample collected after spraying. Nonylphenol residues were about 9 ppb in the stream water 1 h after its application and declined to 50% in the next two hours. Only trace amounts (less than 2.0 ppb) were detected after 5 days and no residues were detected in any water sample taken beyond this time. Residues at trace level (less than 0.10 ppm) were detected in only one sediment sample taken 4 hours after spraying.